Peng Wang

Excessive cadmium (Cd) accumulation in rice poses a risk to food safety. OsHMA3 plays an important role in restricting Cd translocation from roots to shoots. A non-functional allele of OsHMA3 has been reported in some Indica rice cultivars with high Cd accumulation, but it is not known if OsHMA3 allelic variation is associated with Cd accumulation in Japonica cultivars. In this study, we identified a Japonica cultivar with consistently high Cd accumulation in shoots and grain in both field and greenhouse experiments. The cultivar possesses an OsHMA3 allele with a predicted amino acid mutation at the 380(th) position from Ser to Arg. The haplotype had no Cd transport activity when the gene was expressed in yeast, and the allele did not complement a known nonfunctional allele of OsHMA3 in F1 test. The allele is present only in temperate Japonica cultivars among diversity panels of 1483 rice cultivars. Different cultivars possessing this allele showed greatly increased root-to-shoot Cd translocation and a shift in root Cd speciation from Cd-S to Cd-O bonding determined by synchrotron X-ray absorption spectroscopy. Our study has identified a new loss-of-function allele of OsHMA3 in Japonica rice cultivars leading to high Cd accumulation in shoots and grain.

H19, a maternally expressed imprinted gene transcribing a long noncoding RNA, has previously been reported to be involved in tumorigenesis and cancer progression. However, the association between the H19 polymorphisms and breast cancer (BC) susceptibility has remained elusive. The aim of this study was to evaluate the associations between 2 H19 haplotype tagging SNPs (rs3741219 T>C, rs217727 C>T) and the risk of breast cancer. Our study comprised 464 BC patients and 467 cancer-free controls in China. rs3741219 and rs217727 were genotyped with polymerase chain reaction-restriction fragment-length polymorphism (PCR-RFLP) and created restriction site PCR (CRS-RFLP) assays, respectively. False-positive report probability (FPRP) was calculated to test the false-positive association. On performing univariate analysis, no significant association between H19 polymorphisms (rs3741219 and rs217727) and BC was observed. However, in further stratified analyses, CT+TT genotypes of rs217727 had a significantly lower risk of breast cancer among women with number of pregnancy >2 (OR = 0.79; 95% CI = 0.55–0.97). CT genotype of rs217727 was associated with ER positivity (OR = 2.19; 95 % CI = 1.07–4.45) and HER-2 positivity (OR = 1.34; 95 % CI = 1.05–2.12). It was proved that our results were less likely to be false positives according to false-positive report probability calculation. Our findings extend available data on the association of H19 polymorphisms and BC susceptibility. Further validation in large population or cohort studies is needed.

Microplastic exposure leads to various toxic effects in Daphnia magna; however, the effects of microplastics on the metabolic processes in D. magna and the corresponding molecular toxicity mechanisms remain unclear. In the present study, the effects of acute exposure to polyethylene microplastics with different particle sizes (20 μm [MPs-20] and 30 μm [MPs-30]) on metabolites in D. magna and the mechanisms of toxicity were investigated by combining metabolomics and traditional toxicology techniques. Exposure to both MPs-20 and MPs-30 resulted in significant accumulation of microplastics in the gut of D. magna and significantly reduced D. magna survival and heart rate. Metabolomics analysis revealed that MPs-20 and MPs-30 induced significant changes in up to 88 and 91 differential metabolites, respectively, and collectively induced significant changes in 75 metabolites in D. magna. Among lipid metabolites, MPs-20 specifically downregulated phosphatidylcholine and upregulated phosphatidylethanolamine, which mainly affected phospholipid metabolism, whereas MPs-30 specifically downregulated amino acid metabolites l-glutamine, l-glutamate and malic acid, which mainly interfered with energy metabolism. The results of this study provide novel insights into the mechanism of effects of microplastics on metabolic processes in D. magna.

The identification of the high‐efficiency and non‐invasive biomarkers for hepatocellular carcinoma (HCC) detection is urgently needed. This study aims to screen out potential autoantibodies to tumor‐associated antigens (TAAbs) and to assess their diagnostic value for HCC. Fifteen potential TAAbs were screened out from the Human Proteome Microarray by 30 HCC sera and 22 normal control sera, of which eight passed multiple‐stage validations by ELISA with a total of 1625 human serum samples from normal controls (NCs) and patients with HCC, liver cirrhosis, chronic hepatitis B, gastric cancer, esophageal cancer, and colorectal cancer. Finally, an immunodiagnostic model including six TAAbs (RAD23A, CAST, RUNX1T1, PAIP1, SARS, PRKCZ) was constructed by logistic regression, and yielded the area under curve (AUC) of 0.835 and 0.788 in training and validation sets, respectively. The serial serum samples from HCC model mice were tested to explore the change in TAAbs during HCC formation, and an increasing level of autoantibodies was observed. In conclusion, the panel of six TAAbs can provide potential value for HCC detection, and the strategy to identify novel serological biomarkers can also provide new clues in understanding immunodiagnostic biomarkers.

The purpose of this study is to discover novel tumor-associated antigens (TAAs) to improve the diagnosis of lung cancer (LC). Oncomine database was used to discover potential TAAs from LC tissues, enzyme-linked immunosorbent assay (ELISA) was used to detect the levels of autoantibodies against TAAs in two independent sets (identification set, n = 368; validation set, n = 1011). Analyses of sera from identification set showed that the sensitivity of autoantibodies against five TAAs (HMGB3, ZWINT, GREM1, NUSAP1 and MMP12) reached 57.1%, 42.4%, 38.0%, 36.4% and 20.7%, with area under ROC curve (AUC) of 0.85, 0.75, 0.71, 0.73 and 0.70, respectively. It also validated the diagnostic performances of these autoantibodies with AUC of 0.72, 0.65, 0.61, 0.64 and 0.64, respectively. Autoantibody against HMGB3 exhibited significantly increased frequency in early LC (53.3%) compared to advanced LC (29.3%) (P < .05). The positive rates of autoantibody against HMGB3 and NUSAP1 in serum of LC patients without distant metastasis were significantly higher than that of distant metastatic LC (P < .05). When each of the three protein biomarkers (CEA, CA125 and CYFRA21-1) was combined with anti-HMGB3 autoantibody, the sensitivity of early LC increased to 72.7%, 63.3% and 75.9% from 36.4%, 13.3% and 27.6%, respectively. Autoantibodies against 5 TAAs (HMGB3, ZWINT, GREM1, NUSAP1 and MMP12) might have favorable diagnostic values in LC detection, and autoantibody against HMGB3 has the potential to serve as a serological biomarker in early-stage LC. The combination of protein biomarkers and anti-HMGB3 might contribute to detection of early-stage LC.

Abstract The aim of this study was to develop a noninvasive serological diagnostic approach in identifying and evaluating a panel of candidate autoantibodies to tumor‐associated antigens (TAAs) based on protein microarray technology for early detection of ovarian cancer (OC). Protein microarray based on 154 proteins encoded by 138 cancer driver genes was used to screen candidate anti‐TAA autoantibodies in a discovery cohort containing 17 OC and 27 normal controls (NC). Indirect enzyme‐linked immunosorbent assay (ELISA) was used to detect the content of candidate anti‐TAA autoantibodies in sera from 140 subjects in the training cohort. Differential anti‐TAA autoantibodies were further validated in the validation cohort with 328 subjects. Subsequently, 112 sera from the patients with ovarian benign diseases with 104 OC sera and 104 NC sera together were recruited to identify the specificity of representative autoantibodies to OC among ovarian diseases. Five TAAs (GNAS, NPM1, FUBP1, p53, and KRAS) were screened out in the discovery phase, in which four of them presented higher levels in OC than controls ( P &lt; .05) in the training cohort, which was consistent with the result in the subsequent validation cohort. An optimized panel of three anti‐TAA (GNAS, p53, and NPM1) autoantibodies was identified to have relatively high sensitivity (51.2%), specificity (86.0%), and accuracy (68.6%), respectively. This panel can identify 51% of OC patients with CA125 negative. This study supports our assumption that anti‐TAA autoantibodies can be considered as potential diagnostic biomarkers for detection of OC; especially a panel of three anti‐TAA autoantibodies could be a good tool in immunodiagnosis of OC.

Slowing hot carrier (HC) cooling in lead halide perovskites is important to further improve the efficiency of perovskite solar cells (PSCs). Herein, we found that HC cooling can be efficiently prolonged by incorporating an organic small molecule (TDGA) into the perovskite film as an additive through transient absorption spectroscopy measurements, which is conducive to the extraction of the HC energies by the carrier transport layers and reduces charge carrier recombination, consequently improving the efficiency of the TDGA-doped device.

MicroRNAs (miRNAs), a class of small non-coding RNAs, mediate gene expression by either cleaving target mRNAs or inhibiting their translation. They have key roles in the tumorigenesis of several cancers, including non-small cell lung cancer (NSCLC). The aim of this study was to investigate the clinical significance of miR-638 in the evaluation of NSCLC patient prognosis in response to chemotherapy. First, we detected miR-638 expression levels in vitro in the culture supernatants of the NSCLC cell line SPC-A1 treated with cisplatin, as well as the apoptosis rates of SPC-A1. Second, serum miR-638 expression levels were detected in vivo by using nude mice xenograft models bearing SPC-A1 with and without cisplatin treatment. In the clinic, the serum miR-638 levels of 200 cases of NSCLC patients before and after chemotherapy were determined by quantitative real-time PCR, and the associations of clinicopathological features with miR-638 expression patterns after chemotherapy were analyzed. Our data helped in demonstrating that cisplatin induced apoptosis of the SPC-A1 cells in a dose- and time-dependent manner accompanied by increased miR-638 expression levels in the culture supernatants. In vivo data further revealed that cisplatin induced miR-638 upregulation in the serum derived from mice xenograft models, and in NSCLC patient sera, miR-638 expression patterns after chemotherapy significantly correlated with lymph node metastasis. Moreover, survival analyses revealed that patients who had increased miR-638 levels after chemotherapy showed significantly longer survival time than those who had decreased miR-638 levels. Our findings suggest that serum miR-638 levels are associated with the survival of NSCLC patients and may be considered a potential independent predictor for NSCLC prognosis.

Lung cancer (LC) is the leading cause of cancer-related deaths for both male and female worldwide. Early detection of LC could improve five-year survival rate up to 48.8% compared to 3.3% of late/distant stage. Autoantibodies to tumor-associated antigens (TAAs) have been described as being present before clinical symptoms in lung and other cancers. We aimed to identify more TAAs to improve the performance for discovering non-small cell lung cancer (NSCLC) patients from healthy individuals.Two independent sets were included in this study. Serological proteome analysis (SERPA) was used to identify TAAs from NSCLC cell line H1299 in a discovery set. In validation study, anti-ENO1 autoantibody was examined by immunoassay in sera from 242 patients with NSCLC and 270 normal individuals.A 47 KDa protein was identified to be alpha-enolase (ENO1) by using SERPA. Analysis of sera from 512 participants by ELISA showed significantly higher frequency of anti-ENO1 autoantibodies in NSCLC sera compared with the sera from normal individuals, with AUC (95%CI) of 0.589 (0.539-0.638, P=0.001). There was no significant difference in frequency of anti-ENO1 in different stages, histological or metastasis status of NSCLC. When anti-ENO1 detection was combined with other two tumor protein biomarkers (CEA and CYFRA 21-1), the sensitivity of NSCLC increased to 84%.ENO1 can elicit humoral immune response in NSCLC and its autoantibody has association with the tumorigenesis of NSCLC. Furthermore, these intriguing results suggest the possibility of autoantibody against ENO1 serving as a potential diagnostic biomarker in NSCLC and have implications for defining novel histological determinants of NSCLC.

This systematic review aims to outline and summarize known tumor-associated antigens (TAAs) or anti-TAA autoantibodies and their diagnostic values in ovarian cancer (OC).A systematic literature search was conducted in two databases. Data were independently extracted and reviewed by two junior investigators and the disagreement was further resolved by consulting one of the senior investigators.Sixty publications reporting 113 different TAAs or anti-TAA autoantibodies were included. The majority of the studies were conducted in western countries. CA125, p53 and HE4 were the most frequently tested TAAs in OC. Meta-analysis showed that there was a significant association between serum anti-p53 autoantibody and increased risk of OC.Serum TAAs or anti-TAA autoantibodies are promising diagnostic biomarkers in the detection of OC. A customized mini-array of multiple TAAs may enhance the detection of anti-TAA autoantibodies in OC. Additional studies with sufficient number of OC patients and carefully selected controls are needed to further verify the results.

Non-small cell lung cancer (NSCLC) is the major cause of lung cancer-related deaths. Erlotinib is an effective drug for NSCLC patients, but its effect in advanced NSCLC is compromised because of the drug resistance. The mechanism of erlotinib resistance in NSCLC is largely unknown. In the current study, we found that erlotinib treatment down-regulated miR-17-5p level in A549 cells and miR-17-5p was lower in acquired erlotinib-resistant A549 cells (A549-ER) compared with erlotinib-sensitive A549 cells. Consistently, miR-17-5p was down-regulated in the tumor tissues and the plasma of erlotinib-resistant NSCLC patients in comparison to those who are sensitive to erlotinib. Moreover, miR-17-5p mimic increased the sensitivity of A549 and A549-ER to erlotinib. In contrast, miR-17-5p inhibitor decreased the cell death of A549 and A549-ER induced by erlotinib. In addition, we also demonstrated that miR-17-5p could inhibit the mRNA and protein levels of enhancer of zeste homolog (EZH) 1, a member of the EZH family that contributes to drug resistance in several types of cancer. The luciferase assay of 3'-untranslated region (UTR) demonstrates that EZH1 is a direct target of miR-17-5p and EZH1 RNAi recapitulates the effect of miR-17-5p overexpression on erlotinib resistance. Further, mutation in seed sequence of miR-17-5p could totally abolish the sensitization of A549-ER to erlotinib induced by miR-17-5p overexpression. Our results indicate that miR-17-5p down-regulation contributes to erlotinib resistance of NSCLC by modulating its target genes such as EZH1 and plasma miR-17-5p might be a potential biomarker of erlotinib response in NSCLC patients.

Autoantibodies against tumor-associated antigens (TAAs) are attractive non-invasive biomarkers for detection of cancer due to their inherently stable in serum. Serum autoantibodies against 9 TAAs from gastric cancer (GC) patients and healthy controls were measured by enzyme-linked immunosorbent assay (ELISA). A logistic regression model predicting the risk of being diagnosed with GC in the training cohort (n = 558) was generated and then validated in an independent cohort (n = 372). Area under the receiver operating characteristic curve (AUC) was used to assess the diagnostic performance. Finally, an optimal prediction model with 6 TAAs (p62, c-Myc, NPM1, 14-3-3ξ, MDM2 and p16) showed a great diagnostic performance of GC with AUC of 0.841 in the training cohort and 0.856 in the validation cohort. The proportion of subjects being correctly defined were 78.49% in the training cohort and 81.99% in the validation cohort. This prediction model could also differentiate early-stage (stage I-II) GC patients from healthy controls with sensitivity/specificity of 76.60%/72.34% and 80.56%/79.17% in the training and validation cohort, respectively, and the overall sensitivity/specificity for early-stage GC were 78.92%/74.70% when being combined with two cohorts. This prediction model presented no significant difference for the diagnostic accuracy between early-stage and late-stage (stage III – IV) GC patients. The model with 6 TAAs showed a high diagnostic performance for GC detection, particularly for early-stage GC. This study further supported the hypothesis that a customized array of multiple TAAs was able to enhance autoantibody detection in the immunodiagnosis of GC.

Lung cancer (LC) is one of the most common malignant tumors worldwide with low five-year survival rate due to lack of effective diagnosis. This study aims to find an optimal combination of autoantibodies for detecting of early-stage LC. Nine relatively novel autoantibodies against tumor-associated (TAAs) (PSIP1, TOP2A, ACTR3, RPS6KA5, HMGB3, MMP12, GREM1, ZWINT and NUSAP1) were detected by using ELISA. Diagnostic models were developed by using the training set (n = 644) and further validated in another independent set (n = 248). We also evaluated the diagnostic accuracy of the model to detect benign lung diseases (BLD) from the early-stage lung cancer. The areas under the receiver operating characteristic curve (AUC) for the model with three TAAs panel (GREM1, HMGB3 and PSIP1) was 0.711(95% CI 0.674–0.746) in the training set and 0.858 (95% CI 0.808–0.899) in the validation set, which demonstrated a higher diagnostic capability. The AUC of this three TAAs model was 0.833 (95%CI 0.780–0.878) in discriminating LC from BLD. This model could identify early-stage LC patients from normal control (NC) individuals, with AUC of 0.687(95% CI 0.634–0.736) in training set and AUC of 0.920(95% CI 0.860–0.960) in validation set, and the overall AUC for early-stage LC was 0.779(95% CI 0.739–0.816) when the training set and validation set were combined. The model with three TAAs panel would detect LC with higher effectiveness, and might be potential screening method for the early LC.

Blood-brain barrier (BBB) damage is considered an important part of Alzheimer's disease (AD) progression, and cerebral small-vessel disease (CSVD) is commonly associated with AD. However, the relationship between BBB damage, small cerebrovascular lesions, especially cerebral microbleeds (CMBs), and amyloid and tau biomarkers remains controversial. Therefore, our study aimed to further investigate their association in our cohort of patients with AD.A total of 139 individuals were divided into probable AD (18F-florbetapir PET positive, n = 101) and control group (cognitively normal, n = 38). The levels of cerebrospinal fluid (CSF) and plasma t-tau, p-tau181, Aβ40, Aβ42, and albumin were measured using corresponding commercial assay kits, and the CSF/plasma albumin ratio (Qalb), an indicator of BBB dysfunction, was calculated. CSVD burden and the number of CMBs were defined using magnetic resonance imaging.Patients with AD had higher Qalb (p = 0.0024), higher numbers of CMBs (p = 0.03), and greater CSVD burden (p < 0.0001). In the AD group, CMBs and CSVD correlated with a higher Qalb (p = 0.03), and the numbers of CMBs negatively correlated with CSF Aβ42 (p = 0.02).Blood-brain barrier damage was accompanied by a more severe burden of CSVD, including CMB, in patients with AD.

Advanced colorectal cancer (CRC) has a bad prognosis and is challenging to cure. Therefore, there is an urgent need for an effective early diagnosis marker. MicroRNA-21 (miR-21) regulates the expression of multiple cancer target genes. The objective of this study was to assess the diagnostic role of miR-21 in CRC.A meta-analysis of PubMed, Cochrane Library, EMBASE, and Web of Science databases was performed with a carefully designed search strategy to identify records related to the diagnostic role of miR-21 in CRC. TCGA data was used to search for different microRNAs in colorectal cancer samples and surrounding tissues. In addition, potential target genes for miR-21 were predicted and evaluated by functional analysis. We conducted a meta-analysis for 10 studies, including 728 blood samples of patients with CRC and 472 healthy controls. The combined sensitivity and specificity of miR-21 to diagnose colorectal cancer were 0.79 (95% CI: 0.67-0.87) and 0.92 (95% CI: 0.85-0.96), respectively. The combined positive likelihood ratio (PLR) was 10.20 (95% CI: 4.8-21.5), the combined negative likelihood ratio (NLR) was 0.23 (95% CI: 0.14-0.37), the diagnostic odds ratio (DOR) was 45.00 (95% CI:15-132), the area under the summary receiver operating characteristic curve (SROC) for the included studies was 0.93(95%CI: 0.91-0.95). Simultaneously, TCGA data showed that miR-21 was a differential microRNA in colorectal cancer tissues and adjacent tissues, and it was an up-regulated gene. After verification by three databases, 48 target genes of miR-21 were obtained. Through GO enrichment analysis, it was found that the target genes were mainly distributed in the fiber center, the molecular function was mainly focused on cytokine receptor binding, and the biological process was mainly focused on ubiquitin-dependent protein catabolism mediated by the proteasome. KEGG pathway analysis showed that the target genes were mainly distributed in tumor pathways.

To identify biomarkers for diagnosis and prognosis of hepatocellular carcinoma (HCC).Screening the HCC cDNA library with HCC patients sera. Isolated proteins were used as antigens to detect antibodies from patients with HCC and control sera.Eighty-one positive clones were identified. The frequencies of autoantibody against five HCC-associated antigens were higher in HCC than that in chronic hepatitis and normal human sera. The sensitivity and specificity of KRT23, AHSG and FTL antigens combination tests up to 98.2% in joint test and 90.0% in series test separately.HCC associate antigens identified from this study supply candidate markers of diagnosis, combined detection and immunotherapy of HCC.

Very low density lipoprotein receptor (VLDLR) has been considered as a multiple function receptor due to binding numerous ligands, causing endocytosis and regulating cellular signaling. Our group previously reported that enhanced activity of type II VLDLR (VLDLR II), one subtype of VLDLR, promotes adenocarcinoma SGC7901 cells proliferation and migration. The aim of this study is to explore the expression levels of VLDLR II in human gastric, breast and lung cancer tissues, and to investigate its relationship with clinical characteristics and β-catenin expression status.VLDLR II expression was examined using immunohistochemistry (IHC) and Western blot in tumor tissues from 213 gastric, breast and lung cancer patients, tumor adjacent noncancerous tissues by same methods. Correlations between VLDLR II and clinical features, as well as β-catenin expression status were evaluated by statistical analysis.The immunohistochemical staining of VLDLR II showed statistical difference between tumor tissues and tumor adjacent noncancerous tissues in gastric, breast and lung cancers (P = 0.034, 0.018 and 0.043, respectively). Moreover, using Western, we found higher VLDLR II expression levels were associated with lymph node and distant metastasis in gastric and breast cancer (P < 0.05). Furthermore, highly significant positive correlations were found between VLDLR II and β-catenin in gastric cancer (r = 0.689; P < 0.001)breast cancer (r = 0.594; P < 0.001).According to the results of the current study, high VLDLR II expression is correlated with lymph node and distant metastasis in gastric and breast cancer patients, the data suggest that VLDLR II may be a clinical marker in cancers, and has a potential link with β-catenin signaling pathway. This is the first to reveal the closer relationship of VLDLR II with clinical information.

Esophageal squamous cell carcinoma (ESCC) develops in a background of chronic inflammation; therefore, it is a promising candidate for treatment by immunotherapy. Although tumor immunity is critically involved in tumor growth and metastasis in ESCC, important gaps exist in our understanding of its immune microenvironment. This study aimed to investigate the expression and prognostic significance of immune checkpoint proteins in ESCC and the associated T-cell densities.We investigated the infiltration of CD8+ T cells and the expressions of immune checkpoint proteins (PD-1, TIGIT, PD-L1, and PD-L2) in 154 primary ESCC patients by immunohistochemistry. The correlation of immune checkpoint proteins' expression and clinical outcomes was determined by Kaplan-Meier test and multivariate Cox regression analysis.PD-L1 and PD-L2 expression were detected in 45.5 and 59.7% of the ESCC samples, respectively. The high densities of PD-1+ and TIGIT+ tumor-infiltrating lymphocytes (TILs) were expressed in 47.4 and 49.4% of the ESCC patients, respectively. The number of PD-1+ TILs was significantly positively correlated with CD8+ TILs (P<0.001). Cases displaying high PD-L1 expression exhibited consistently high CD8+ T-cell infiltration (P=0.0157). Increased numbers of PD-1+ and TIGIT+ TILs alone or both, as well as PD-L1 and PD-L2 expression alone or both, were significantly and associated with a shorter overall survival among these patients. The combined analysis of the expression of PD-1, TIGIT, PD-L1, and PD-L2 found that a group of patients with PD-1+/TIGIT+ TILs and PD-L1- and/or PD-L2-positive tumor cells had the worst prognosis in primary ESCC.These immune profiles of checkpoint proteins expression should guide the selection of ESCC patients to receive suitable immunotherapies.

The present study aimed to select anti‐tumor‐associated antigen ( TAA ) autoantibodies as biomarkers in the immunodiagnosis of gastric adenocarcinoma ( GAC ) by the recursive partitioning approach ( RPA ) and further construct and evaluate a predictive model. A case‐control study was designed including 407 GAC patients as the case group and 407 normal controls. In addition, 67 serial serum samples from 25 GAC patients were collected at different time points before and after gastrectomy treatment. Autoantibodies against 14 TAA were measured in sera from all subjects by enzyme immunoassay. Finally, RPA resulted in the selection of nine‐panel TAA (c‐Myc, p16, HSPD 1, PTEN , p53, NPM 1, ENO 1, p62, HCC 1.4) from all detected TAA in the case‐control study; the classification tree based on this nine‐ TAA panel had area under curve ( AUC ) of 0.857, sensitivity of 71.5% and specificity of 71.3%; The optimal panel also can identify GAC patients at an early stage from normal individuals, with AUC of 0.737, sensitivity of 64.9% and specificity of 70.5%. However, frequencies of the nine autoantibodies showed no correlation with GAC stage, tumor size, lymphatic metastasis or differentiation. GAC patients positive for more than two autoantibodies in the nine‐ TAA panel had a worse prognosis than that of the GAC patients positive for no or one antibody. Titers of 10 autoantibodies in serial serum samples were significantly higher in GAC patients after surgical resection than before. In conclusion, this study showed that the panel of nine multiple TAAs could enhance the detection of anti‐ TAA antibodies in GAC , and may be potential prognostic biomarkers in GAC .

The identification of tumor-associated antigens (TAAs) and their corresponding autoantibodies in lung cancer (LC) may expand our vision of cancer immunity. This study aims to screen novel TAAs to distinguish LC from the healthy population. In our previous study, 35 genes encoding LC-associated TAAs were identified from the serological analysis of recombinant cDNA expression libraries (SEREX), and Oncomine database was further used to identify potential genes in cancer progression. Autoantibody to TAAs were tested by enzyme-linked immunosorbent assay (ELISA) in sera from 1379 participants in validation set and verification set. Based on analysis of three independent microarrays in Oncomine, ten genes were consistently dysregulated in LC. The sera level and positive frequency of the anti-TOP2A, anti-ACTR3, anti-RPS6KA5 and anti-PSIP1 from LC patients were higher than normal control in validation set. The area under curve (AUC) of anti-TOP2A, anti-ACTR3, anti-RPS6KA5 and anti-PSIP1 was respectively 0.758, 0.787, 0.707, 0.668. The sensitivity of these four autoantibodies for LC detection ranged from 26.63 % to 32.07 % with the specificity over 90 %. Data from the verification set confirmed the results. Except that, the frequency of serum autoantibody against TOP2A (43.3 %) and ACTR3 (50.0 %) was significantly higher in early stage LC than late stage (23.6 % and 22.3 %, respectively). TOP2A, ACTR3, RPS6KA5 and PSIP1 can elicit humoral immune response in LC and their autoantibodies have relationship with the tumorigenesis of LC. Anti-TOP2A and anti-ACTR3 have the potential to serve as a serological biomarkers in early stage LC.

Early diagnosis of breast cancer has always been a difficult clinical challenge. We developed a deep-learning model EDL-BC to discriminate early breast cancer with ultrasound (US) benign findings. This study aimed to investigate how the EDL-BC model could help radiologists improve the detection rate of early breast cancer while reducing misdiagnosis.In this retrospective, multicentre cohort study, we developed an ensemble deep learning model called EDL-BC based on deep convolutional neural networks. The EDL-BC model was trained and internally validated on B-mode and color Doppler US image of 7955 lesions from 6795 patients between January 1, 2015 and December 31, 2021 in the First Affiliated Hospital of Army Medical University (SW), Chongqing, China. The model was assessed by internal and external validations, and outperformed radiologists. The model performance was validated in two independent external validation cohorts included 448 lesions from 391 patients between January 1 to December 31, 2021 in the Tangshan People's Hospital (TS), Chongqing, China, and 245 lesions from 235 patients between January 1 to December 31, 2021 in the Dazu People's Hospital (DZ), Chongqing, China. All lesions in the training and total validation cohort were US benign findings during screening and biopsy-confirmed malignant, benign, and benign with 3-year follow-up records. Six radiologists performed the clinical diagnostic performance of EDL-BC, and six radiologists independently reviewed the retrospective datasets on a web-based rating platform.The area under the receiver operating characteristic curve (AUC) of the internal validation cohort and two independent external validation cohorts for EDL-BC was 0.950 (95% confidence interval [CI]: 0.909-0.969), 0.956 (95% [CI]: 0.939-0.971), and 0.907 (95% [CI]: 0.877-0.938), respectively. The sensitivity values were 94.4% (95% [CI]: 72.7%-99.9%), 100% (95% [CI]: 69.2%-100%), and 80% (95% [CI]: 28.4%-99.5%), respectively, at 0.76. The AUC for accurate diagnosis of EDL-BC (0.945 [95% [CI]: 0.933-0.965]) and radiologists with artificial intelligence (AI) assistance (0.899 [95% [CI]: 0.883-0.913]) was significantly higher than that of the radiologists without AI assistance (0.716 [95% [CI]: 0.693-0.738]; p < 0.0001). Furthermore, there were no significant differences between the EDL-BC model and radiologists with AI assistance (p = 0.099).EDL-BC can identify subtle but informative elements on US images of breast lesions and can significantly improve radiologists' diagnostic performance for identifying patients with early breast cancer and benefiting the clinical practice.The National Key R&D Program of China.

Impaired facial expressions of emotions have been described as characteristic symptoms of schizophrenia. Previous investigations of dynamic facial expressions have reported on global assessment of positive and negative emotion expressions. In this study, we examined facial expression differences based on duration and frequencies of emotion expressions.12 persons with stable schizophrenia and matched healthy controls underwent a standardized procedure for evoked facial expressions of five universal emotions, including happy, sad, anger, fear, and disgust expressions. Subjects completed self-ratings of their emotion experience. Reliable raters coded evoked facial expressions according to the Facial Expression Coding System. For each emotion, facial expressions were coded as target, non-target or neutral expressions. Logistic regression analyses examined group differences in duration and frequencies of facial expressions.Comparing overall duration of and frequencies of emotion expressions revealed affective flattening and inappropriate affect in patients, as evidenced by neutral and non-target expressions. Separated by emotion, impaired emotion expression was found in happy, sad and anger expression, but not for fear and disgust in which expressions were not well recognized.In matched groups of participants, we found evidence for altered expressions in schizophrenia but equal subjective experience. Both affective flattening and inappropriate affect comprise abnormal facial expressions but may differ with respect to interpersonal communication and engagement. Future directions may include automated measurement, remediation of expressions and early detection of schizophrenia.

In the present work we genotyped three single-nucleotide polymorphisms (SNPs) (rs7301328, rs1805247, and rs1805502) of the GRIN2B gene in a set of 480 unrelated bipolar disorder patients and 480 unrelated genetically matched normal controls in Chinese Han population by either allelic-specific multiplex ligation-detection reaction (AMLR) technology or direct sequencing. Rs1805247 and the haplotype consisting of rs1805502 and rs1805247 were significantly associated, suggesting GRIN2B as having a role in the etiology of bipolar disorder.

The galactose-based polymer is a promising drug delivery material. Herein, a new galactose-based block copolymer, termed as 6-O-vinyl sebacic acid-D-galactopyranosyl ester block 3-acrylamide phenylboric acid p(OVNG-b-AAPBA) was successfully synthesized by 'block copolymer' method. The structure of p(OVNG-b-AAPBA) was proved by nuclear magnetic hydrogen spectrum (1 HNMR) and infrared (IR), the thermal stability was observed by thermogravimetric analyzer, and the molecular weights (Mw and Mn) were demonstrated by Gel permeation chromatography (GPC). The above test results suggested that the polymer of p(OVNG-b-AAPBA) was successfully synthesized, and it had optimal molecular weight and thermal stability, which could be used for investigating the drug delivery system. Then, this block copolymer was prepared to the nanoparticle (NP), these NPs had a satisfactory morphology, and their safety was verified by MTT and chronic animal toxicology test. In addition, insulin was encapsulated by the p(OVNG-b-AAPBA) NPs, the drug loading rate and encapsulation efficiency increased with that of AAPBA in the polymer. Finally, this study confirmed that these NPs can effectively maintain the blood sugar of diabetic mice at 96 h. In conclusion, the current study suggested that the insulin-loaded galactose-based polymer-block-3-acrylamide phenylboric acid NPs had slow-release/glucose-responsive drug release performance, which might play an active role in the diabetes therapy.

Substantial evidence manifests the occurrence of autoantibodies to tumor-associated antigens (TAAs) in the early stage of hepatocellular carcinoma (HCC), and previous studies have mainly focused on known TAAs. In the present study, protein microarrays based on cancer driver genes were customized to screen TAAs. Subsequently, autoantibodies against selected TAAs in sera were tested by enzyme-linked immunosorbent assays (ELISA) in 1175 subjects of three independent datasets (verification dataset, training dataset, and validation dataset). The verification dataset was used to verify the results from the microarrays. A logistic regression model was constructed within the training dataset; seven TAAs were included in the model and yielded an area under the receiver operating characteristic curve (AUC) of 0.831. The validation dataset further evaluated the model, exhibiting an AUC of 0.789. Remarkably, as the aggravation of HCC increased, the prediction probability (PP) of the model tended to decrease, the trend of which was contrary to alpha-fetoprotein (AFP). For AFP-negative HCC patients, the positive rate of this model reached 67.3% in the training dataset and 50.9% in the validation dataset. Screening TAAs with protein microarrays based on cancer driver genes is the latest, fast, and effective method for finding indicators of HCC. The identified anti-TAA autoantibodies can be potential biomarkers in the early detection of HCC.

Objectives: To retrospectively assess the efficacy of combined ablation-chemotherapy in comparison to that of chemotherapy alone in patients with liver metastasized pancreatic ductal adenocarcinoma (lmPDAC).Methods: In total 104 patients with hepatic oligo metastasized PDAC were identified; among them, 74 patients underwent combined thermal ablation-chemotherapy, and 30 patients underwent chemotherapy alone. Through propensity score matching, 1:1 matching of the combined ablation-chemotherapy group and chemotherapy group was achieved. The primary endpoint of this study was overall survival (OS). Clinical and tumor-related factors affecting OS were also analyzed through univariate and multivariate analyses using the Cox risk model.Results: For patients treated with combined ablation-chemotherapy, the median OS was 10.77 months, while it was 5.77 months for patients treated with chemotherapy alone (P = 0.011). The survival benefit for patients treated with combined ablation-chemotherapy was still preserved in the matched cohort, with a median OS of 8.17 months compared to 5.77 months in the chemotherapy group. Univariate and multivariate analyses in the matched population also showed treatment with combined ablation-chemotherapy was an independent prognostic factor (P < 0.05).Conclusions: For patients with liver metastases from pancreatic cancer, the combined use of thermal ablation and systemic chemotherapy offers a chance for a better survival outcome.

A novel functional single nucleotide polymorphism (SNP) rs2274223 located in the phospholipase C epsilon 1 (PLCE1) gene was found to be associated with the risk of esophageal squamous cell carcinoma (ESCC) by three large-scale genome-wide association studies (GWAS) in Chinese populations. In the present study, we validated this finding and also explored the risk of ESCC associated with other two unreported potentially functional SNPs (rs17417407 G > T and rs2274224 C > G) of PLCE1 in a population-based case–control study to investigate the association between these three potentially functional SNPs in PLCE1 and susceptibility to ESCC. A total of 381 ESCC cases and 420 controls matched by age and sex were recruited and successfully genotyped for three SNPs (rs17417407, rs2274223 and rs2274224) of the PLCE1 in a central Chinese population. SNP rs2274223 was independently associated with increased risk of ESCC (adjusted odds ratio [OR], 2.80; 95% confidence interval [95% CI], 1.45–5.39 for GG vs. AA), and SNP rs2274224 was found to be associated with decreased risk of ESCC (adjusted OR, 0.65; 95% CI, 0.46–0.91 for CG vs. CC). The combined effects of risk alleles for three SNPs (rs17417407T, rs2274223G and rs2274224G) were found to be associated with elevated risk of ESCC in a dose-dependent effect manner (Ptrend = 0.005). The Grs17417407Ars2274223Crs2274224 haplotype decreased the risk of ESCC (adjusted OR, 0.76; 95% CI, 0.62–0.93), meanwhile the Grs17417407Grs2274223Crs2274224 and Trs17417407Grs2274223Crs2274224 haplotypes could increase the risk of ESCC (adjusted OR, 1.75; 95% CI, 1.33–2.18 and OR, 2.51; 95% CI, 1.15–2.49). Gene–environment interaction analysis presented a best model consisted of four factors (rs2274223, rs2274224, family history, and smoking) with testing balance accuracy (TBA): 0.66 and cross validation consistency (CVC): 7/10, which could increase the esophageal cancer risk in the “high risk group” with 3.67-fold (OR: 3.67, 95% CI: 2.74–4.92), compared to the “low risk group”. Our results further confirmed that genetic variations in PLCE1 may contribute to ESCC risk associated with tobacco exposure in a central Chinese population. Further functional studies are needed to validate our results.

Ovarian cancer (OC) is a major malignancy affecting a large population over the world, and a biomarker that holds diagnostic potential is of critical importance. Recently, autoantibodies have been indicated as biomarkers in multiple cancer research. The current study was designed to explore the practice of using autoantibodies in diagnostic settings by the enzyme-linked immunosorbent assay of sera with a panel of tumor-associated antigens (TAAs).A panel of 12 TAAs was selected to detect the corresponding autoantibodies in sera sampled from 132 OC patients as case group and 147 normal healthy individuals as the control group. The diagnostic potential of this panel was evaluated by conventional evaluation, receiver operating characteristic (ROC) curve analyses, and classification tree analysis.When the cutoff values were set as mean ± 2 SD for normal healthy individuals, the positive rates of antibodies to any single TAA were less than 20% both in OC and in normal healthy individuals. In a parallel screening approach, a panel of nine TAAs (p53, C-myc, p90, p62, AHSG, 14-3-3zeta, RalA, Koc, and p16), obtained optimal diagnostic performance in OC with the sensitivity of 61.4% at the 85.0% specificity. In addition, when the nine TAAs were combined with CA125, the sensitivity and specificity were improved to 94.7% and 78.2%, respectively. The ROC curve analyses showed that only the area under the receiver operating characteristic curves (AUCs) of antibodies against C-myc, Koc, and RalA was beyond 0.6, which were 0.732, 0.668, and 0.665, respectively. The AUC of the combination was up to 0.914 (P < 0.05). Decision tree analysis showed that C-myc, HCC1.3, RalA, and CA125 held high potential in the detection of OC. The panel of nine TAAs also identified 78.8% of OC patients who had normal CA125 levels in their serum samples, indicating that elevated CA125 and anti-TAA antibodies appeared to be independent but supplementary biomarkers for diagnosing OC.In summary, the current study further supports that a customized TAA panel can serve as a promising and powerful tool for immunodiagnosis of OC and may be particularly useful in patients with normal CA125 levels.

Purpose. This study is aimed at evaluating serum autoantibodies against four tumor-associated antigens, including LRDD, STC1, FOXA1, and EDNRB, as biomarkers in the immunodiagnosis of ovarian cancer (OC). Methods. The autoantibodies against LRDD, STC1, FOXA1, and EDNRB were measured using an enzyme-linked immunosorbent assay (ELISA) in 94 OC patients and 94 normal healthy controls (NHC) in the research group. In addition, the diagnostic values of different autoantibodies were validated in another independent validation group, which comprised 136 OC patients, 136 NHC, and 181 patients with benign ovarian diseases (BOD). Results. In the research group, autoantibodies against LRDD, STC1, and FOXA1 had higher serum titer in OC patients than NHC ( <math xmlns="http://www.w3.org/1998/Math/MathML" id="M1"> <mi>P</mi> <mo>&lt;</mo> <mn>0.001</mn> </math> ). The area under receiver operating characteristic curves (AUCs) of these three autoantibodies were 0.910, 0.879, and 0.817, respectively. In the validation group, they showed AUCs of 0.759, 0.762, and 0.817 and sensitivities of 49.3%, 42.7%, and 48.5%, respectively, at specificity over 90% for discriminating OC patients from NHC. For discriminating OC patients from BOD, they showed AUCs of 0.718, 0.729, and 0.814 and sensitivities of 47.1%, 39.0%, and 51.5%, respectively, at specificity over 90%. The parallel analyses demonstrated that the combination of anti-LRDD and anti-FOXA1 autoantibodies achieved the optimal diagnostic performance with the sensitivity of 58.1% at 87.5% specificity and accuracy of 72.8%. The positive rate of the optimal autoantibody panel improved from 62.4% to 87.1% when combined with CA125 in detecting OC patients. Conclusion. Serum autoantibodies against LRDD, STC1, and FOXA1 have potential diagnostic values in detecting OC.

Abstract Spiro‐OMeTAD is a commonly used material in perovskite solar cells (PSCs). It requires chemical doping with a lithium compound and 4‐ tert ‐butylpyridine to enhance its conductivity and hole extraction efficiency. However, this conventional doping process has limitations in terms of efficiency and stability. In this study, an innovative approach using an in situ combined dual‐hole transport layer with 6,13‐bis(triisopropylsilylethynyl)pentacene (TIPS‐Pn) is introduced to improve PSC performance. These results show that this in situ combined hole transport layer with TIPS‐Pn channels effectively extracts and transports hole carriers, reducing non‐radiative recombination. Additionally, it allows for the absorption of excess photo energy from hot hole carriers, resulting in a significant increase in the average power conversion efficiency of PSCs from 22.42% to 24.13%. Furthermore, the device retains 90% of its initial efficiency after 1900 h of exposure to air, indicating improved stability. Notably, a 44% improvement in thermal stability is observed after 500 h due to the robust morphology and hydrophobic surface. This work presents a novel strategy for enhancing the performance of Spiro‐OMeTAD in PSCs and provides valuable insights into hole carrier dynamics in perovskite‐based optoelectronic devices.

Objective: To explore the prognostic value of combined detection of serum prostate specific antigen (PSA), lung cancer metastasis-associated transcript 1 (<i>MALAT1</i>), transmembrane serine protease 2 (<i>TMPRSS2</i>), and erythropoietin-specific transforming gene variant 1 (<i>ETV1</i>) in prostate cancer. Methods: Ninety patients with prostate cancer who were treated in hospital were divided into two groups according to tumor node metastasis stage: Stage I−II group (n = 34) and stage III−IV group (n = 56). The serum levels of PSA, <i>MALAT1</i>, and <i>TMPRSS2</i>-<i>ETV1</i> were detected in both groups and correlated with prostate cancer status to determine their value as indicators of disease progression and prognosis. Results: Age, body mass index (BMI), and Gleason score differed significantly between the study group and the control group (<i>p</i> < 0.05). The expression levels of serum PSA and <i>MALAT1</i> were higher in group III–IV than in group I–II, and the positive expression rate of <i>TMPRSS2</i>-<i>ETV1</i> was significantly higher in group III–IV than in the control group (<i>p</i> < 0.05). Pearson’s correlation analysis showed that serum PSA, <i>MALAT1</i>, and <i>TMPRSS2</i>-<i>ETV1</i> were significantly correlated with prostate cancer (<i>p</i> < 0.05). Differences in PSA levels correlated with differences in age, BMI, type of pathology, and Gleason score, whereas differences in serum <i>MALAT1</i> levels correlated with differences in age, BMI, and type of pathology. Gleason scores differed significantly between patients with positive and negative <i>TMPRSS2</i>-<i>ETV1</i> indicators (<i>p</i> < 0.05). Multivariate logistic regression analysis showed that serum PSA, <i>MALAT1</i>, and <i>TMPRSS2</i>-<i>ETV1</i> were independent risk factors affecting the prognosis of prostate cancer (<i>p</i> < 0.05). The areas under the curve (AUCs) of serum PSA, <i>MALAT1</i>, and <i>TMPRSS2</i>-<i>ETV1</i> as prognostic predictors in prostate cancer were 0.692, 0.731, and 0.709, respectively, whereas the AUC of the combination was 0.819. Assessment of disease progression using the combination of indicators had a significantly higher prognostic value than single indicators (<i>p</i> < 0.05). Conclusions: Serum levels of PSA, <i>MALAT1</i>, and <i>TMPRSS2</i>-<i>ETV1</i> were abnormal in patients with prostate cancer, and the combined detection of these factors provided a reference for assessing disease progression and predicting the prognosis of prostate cancer.

This study was based on hepatocellular carcinoma (HCC) patients of early-stage to explore the diagnostic capability and possible production causes of anti-GNAS autoantibody.We evaluated the frequency of anti-GNAS autoantibody in sera from patients with early-stage HCC by enzyme-linked immunosorbent assay (ELISA) and the expression of GNAS protein in early-stage HCC tissues by immunohistochemistry. Western blotting (WB) and real-time polymerase chain reaction (RT-PCR) were utilized to examine the expressions of GNAS protein and mRNA in cell lines. GEO and International Cancer Genome Consortium (ICGC) databases were inquired to explore mRNA expression and mutation of GNAS in HCC tissues.The positive rates of anti-GNAS autoantibody in HCC patients at clinical stage I (78.1 %) and clinical stage II (57.1 %) were all significantly higher than that in healthy control (20 %). There was also a significant difference in GNAS protein expression between HCC and its adjacent normal liver tissues. The results from WB and RT-PCR showed a significant difference at the mRNA level but no statistical difference at the protein level between HCC and normal liver cell lines. The difference in mRNA level between HCC and adjacent normal liver tissues was verified to be significant. Furthermore, the ICGC database demonstrated a 10.6 % mutation frequency for GNAS in HCC patients.The coordination of elevated anti-GNAS autoantibody, high expression of GNAS in the mRNA and protein levels in HCC, and high frequency of GNAS mutation indicates that anti-GNAS autoantibody may be used as an early indicator of HCC.

Next-generation genome sequencing has revolutionized genetic testing, identifying numerous rare disease-associated gene variants. However, to impute pathogenicity, computational approaches remain inadequate and functional testing of gene variant is required to provide the highest level of evidence. The emergence of AlphaFold2 has transformed the field of protein structure determination, and here we outline a strategy that leverages predicted protein structure to enhance genetic variant classification. We used the gene IRF6 as a case study due to its clinical relevance, its critical role in cleft lip/palate malformation, and the availability of experimental data on the pathogenicity of IRF6 gene variants through phenotype rescue experiments in irf6-/- zebrafish. We compared results from over 30 pathogenicity prediction tools on 37 IRF6 missense variants. IRF6 lacks an experimentally derived structure, so we used predicted structures to explore associations between mutational clustering and pathogenicity. We found that among these variants, 19 of 37 were unanimously predicted as deleterious by computational tools. Comparing in silico predictions with experimental findings, 12 variants predicted as pathogenic were experimentally determined as benign. Even with the recently published AlphaMissense model, 15/18 (83%) of the predicted pathogenic variants were misclassified as benign. In comparison, mapping variants to the protein revealed deleterious mutation clusters around the protein binding domain, whereas N-terminal variants tend to be benign, suggesting the importance of structural information in determining pathogenicity of mutations in this gene. In conclusion, incorporating gene-specific structural features of known pathogenic/benign mutations may provide meaningful insights into pathogenicity predictions in a gene-specific manner and facilitate the interpretation of variant pathogenicity.

‘‘Learned” admission policies have shown promise in improving Content Delivery Network (CDN) cache performance and lowering operational costs. Unfortunately, existing learned policies are optimized with a few fixed cache sizes while in reality, cache sizes often vary over time in an unpredictable manner. As a result, existing solutions cannot provide consistent benefits in production settings. We present SLAP , a learned CDN cache admission approach based on segmented object reuse time prediction. SLAP predicts an object’s reuse time range using the Long-Short-Term-Memory model and admits objects that will be reused (before eviction) given the current cache size. SLAP decouples model training from cache size, allowing it to adapt to arbitrary sizes. The key to our solution is a novel segmented labeling scheme that makes SLAP without requiring precise prediction on object reuse time. To further make SLAP a practical and efficient solution, we propose aggressive reusing of computation and training on sampled traces to optimize model training, and a specialized predictor architecture that overlaps prediction computation with miss object fetching to optimize model inference. Our experiments using production CDN traces show that SLAP achieves significantly lower write traffic (38%-59%), longer SSDs lifetime (104%-178%), a consistently higher hit rate (3.2%-11.7%), and requires no effort to adapt to changing cache sizes, outperforming existing policies.

To establish nomograms integrating serum lactate levels and traditional risk factors for predicting diabetic kidney disease (DKD) in type 2 diabetes mellitus (T2DM) patients.A total of 570 T2DM patients and 100 healthy subjects were enrolled. T2DM patients were categorized into normal and high lactate groups. Univariate and multivariate logistic regression analyses were employed to identify independent predictors for DKD. Then, nomograms for predicting DKD were established, and the model performance was evaluated using the area under the receiver operating characteristic curve (AUC), calibration, and decision curve analysis (DCA).T2DM patients exhibited higher lactate levels compared to those in healthy subjects. Glucose, platelet, uric acid, creatinine, and hypertension were independent factors for DKD in T2DM patients with normal lactate levels, while diabetes duration, creatinine, total cholesterol, and hypertension were indicators in high lactate levels group (P<0.05). The AUC values were 0.834 (95% CI, 0.776 to 0.891) and 0.741 (95% CI, 0.688 to 0.795) for nomograms in both normal lactate and high lactate groups, respectively. The calibration curve demonstrated excellent agreement of fit. Furthermore, the DCA revealed that the threshold probability and highest Net Yield were 17-99% and 0.36, and 24-99% and 0.24 for the models in normal lactate and high lactate groups, respectively.The serum lactate level-based nomogram models, combined with traditional risk factors, offer an effective tool for predicting DKD probability in T2DM patients. This approach holds promise for early risk assessment and tailored intervention strategies.

The purpose of this study was to identify biomarkers associated with hepatitis B virus-associated hepatocellular carcinoma (HBV-HCC) and to develop a new combination with good diagnostic performance. This study was divided into four phases: discovery, verification, validation, and modeling. A total of four candidate tumor-associated autoantibodies (TAAb; anti-ZIC2, anti-PCNA, anti-CDC37L1, and anti-DUSP6) were identified by human proteome microarray (52 samples) and bioinformatics analysis. Subsequently, these candidate TAAbs were further confirmed by indirect ELISA with two testing cohorts (120 samples for verification and 663 samples for validation). The AUC for these four TAAbs to identify patients with HBV-HCC from chronic hepatitis B (CHB) patients ranged from 0.693 to 0.739. Finally, a diagnostic panel with three TAAbs (anti-ZIC2, anti-CDC37L1, and anti-DUSP6) was developed. This panel showed superior diagnostic efficiency in identifying early HBV-HCC compared with alpha-fetoprotein (AFP), with an AUC of 0.834 [95% confidence interval (CI), 0.772-0.897] for this panel and 0.727 (95% CI, 0.642-0.812) for AFP (P = 0.0359). In addition, the AUC for this panel to identify AFP-negative patients with HBV-HCC was 0.796 (95% CI, 0.734-0.858), with a sensitivity of 52.4% and a specificity of 89.0%. Importantly, the panel in combination with AFP significantly increased the positive rate for early HBV-HCC to 84.1% (P = 0.005) and for late HBV-HCC to 96.3% (P < 0.001). Our findings suggest that AFP and the autoantibody panel may be independent but complementary serologic biomarkers for HBV-HCC detection.

Enhancing the efficiency and stability is very critical for perovskite solar cells (PSCs) commercialization. Herein, we report an effective approach to enable highly efficient and stable PSCs by incorporating a polymer material, poly[N, N′-bis(2-octyldodecyl)-naphthalene-1,4,5,8-bis(dicarboximide)-2,6-diyl]-alt-5,5′-(2,2′-bithiophene) (named P(NDI2OD-T2)), into hole transport layer (HTL). Our research results exhibit that the addition of P(NDI2OD-T2) not only effectively improves the hole mobility and conductivity of HTL, but also makes its energy level more alignment with perovskite. More importantly, ultrafast carrier results demonstrate that the introduction of P(NDI2OD-T2) into Spiro-OMeTAD HTL can effectively improve the extraction and transfer of hot carriers from perovskite layer to HTL, and consequently reduce the recombination of charge carriers in the device. As a result, PSCs based on Spiro + P(NDI2OD-T2) as a HTL shows an enhanced power conversion efficiency (PCE) of 24.20 %, which is much higher than that of control device without P(NDI2OD-T2) (21.94 %). Furthermore, the un-encapsulated P(NDI2OD-T2)-treated PSCs exhibit excellent humidity, thermal and light stabilities, with the devices maintaining 94 % of its initial efficiency after 3000 h at ≈40 % humidity, 95 % of its initial efficiency after storage at 65 °C and 85 °C for 600 h, and 90 % of its initial efficiency after 600 h under one sun light irradiation, respectively. This work provides an effective strategy for improving the device efficiency and long-term stability of PSCs.

Abstract Modulating perovskite crystallization and understanding hot carriers (HCs) dynamics in perovskite films are very critical to achieving high‐performance perovskite solar cells (PSCs). Herein, a small organic molecule (6BAS) with multisite anchors (C═O) as an efficient additive is introduced into PbI 2 precursors to modulate perovskite crystallization during two‐step sequential deposition. The chemical interaction between 6BAS and PbI 2 enables more preferential PbI 2 crystal with enlarged interplanar spacing of PbI 2 lattice, which is beneficial to the penetration of organic ammonium salts into PbI 2 layer and the complete conversion to perovskite, consequently promoting the preferential crystallization of perovskite to realize high‐quality perovskite films with larger grain size and reduced defect state. By ultrafast spectroscopy, it is found that the incorporation of 6BAS can efficiently prolong HCs cooling, which helps to enhance HCs transfer and retard the charge carrier recombination in device. As a result, 6BAS doped‐PSCs efficiency significantly enhances to 25.32% from 22.91%. The target device achieves the enhanced long‐term stability. Only a 6% efficiency degradation is realized for un‐encapsulated device with 6BAS after 70 days under N 2 . Meanwhile, the 6BAS‐treated device retains 95% of its initial PCE after 1160 h of operation at the maximum power point under continuous AM 1.5 G illumination.

&lt;p&gt;Supplementary Figure S5: In the training set, the AUC for identifying HBV-HCC patients from CHB patients 0.788 (95% CI: 0.733-0.843) (Supplementary Figure S5A). Similarly, the AUC of the panel was 0.764 (95% CI: 0.695-0.833) in the test-set (Supplementary Figure S5B). In the training set, the AUC for identifying HBV-HCC patients from HBV-LC patients was 0.646 (95% CI: 0.576-0.716) (Supplementary Figure S5C). In the test set, the AUC for identifying HBV-HCC patients from HBV-LC patients was 0.595 (95% CI: 0.507-0.684) (Supplementary Figure S5D).&lt;/p&gt;

&lt;p&gt;Supplementary Table S4: The AUC of these four TAAbs for identifying HBV-HCC patients from CHB patients ranged from 0.693-0.739. Among them, anti-DUSP6 showed the highest diagnostic ability, with an AUC of 0.739 (95% CI [confidence interval]: 0.694-0.785). The diagnostic capability of anti-PCNA was the poorest, with an AUC of 0.693 (95% CI: 0.645-0.741). The AUC of four candidate TAAbs in differentiating between HBV-HCC and HBV-LC patients ranged from 0.589 to 0.624. Among them, anti-PCNA had the most diagnostic capacity, with an AUC of 0.624 (95% CI: 0.569-0.679). Anti-CDC37L1 had the least diagnostic capability, with an AUC of 0.589 (95% CI: 0.533-0.645).&lt;/p&gt;

&lt;p&gt;Supplementary Table S3: Samples from the training set (116 HBV-HCC samples, 124 HBV-LC samples, and 157 CHB samples) were used to construct a predictive model and samples from the test set (78 HBV-HCC samples, 82 HBV-LC samples, and 106 CHB samples) were used to verify the stability of the model. The characteristics of samples in the training and test sets are shown in Supplementary Table S3.&lt;/p&gt;

&lt;p&gt;Supplementary Table S3: Samples from the training set (116 HBV-HCC samples, 124 HBV-LC samples, and 157 CHB samples) were used to construct a predictive model and samples from the test set (78 HBV-HCC samples, 82 HBV-LC samples, and 106 CHB samples) were used to verify the stability of the model. The characteristics of samples in the training and test sets are shown in Supplementary Table S3.&lt;/p&gt;

&lt;p&gt;Supplementary Table S2: RNA sequencing data (GSE22058, GSE121248, and GSE55092) from the Gene Expression Omnibus (GEO) database were downloaded for analyses. These three datasets derived from two microarray platforms (Rosetta/Merck Human RSTA Custom Affymetrix 1.0 microarray and Affymetrix Human Genome U133 Plus 2.0 Array). The GEO query software package was used to download datasets and to collect clinical information. The sample sizes for these three datasets are shown in Supplementary Table S2.&lt;/p&gt;

&lt;p&gt;Supplementary Table S1: We applied 52 serum samples to the HuProt™ microarray and detected autoantibody signals in 10 pooled HCC samples and 10 pooled normal control (NC) samples, including 30 HCC patients and 22 NCs. Samples were merged based on age and gender to ensure consistency. For the HCC group, ten pooled samples were created by mixing every three sera. As for the NC group, six pooled samples were generated by mixing every three sera, while the remaining four samples were used separately (Supplementary Table S1).&lt;/p&gt;

&lt;p&gt;Supplementary Figure S4: These four candidate TAAbs were further confirmed by indirect ELISA with two testing cohorts. In the initial verification of candidate TAAbs in 120 sera, the expression of all four TAAbs was significantly different between the HBV-HCC and CHB groups (P&lt;0.001) (Supplementary Figure S4A). These four TAAbs were further validated in a large dataset (663 sera). The results showed that the expression of four TAAbs was significantly different in the pairwise comparisons between the three groups (P&lt;0.01), and the expression was highest in the HBV-HCC group and lowest in the CHB group (Supplementary Figure S4B).&lt;/p&gt;

&lt;p&gt;Supplementary Table S1: We applied 52 serum samples to the HuProt™ microarray and detected autoantibody signals in 10 pooled HCC samples and 10 pooled normal control (NC) samples, including 30 HCC patients and 22 NCs. Samples were merged based on age and gender to ensure consistency. For the HCC group, ten pooled samples were created by mixing every three sera. As for the NC group, six pooled samples were generated by mixing every three sera, while the remaining four samples were used separately (Supplementary Table S1).&lt;/p&gt;

&lt;p&gt;Supplementary Table S5: All data are derived from the training set. The performance evaluation of this panel in an AUC of 0.788 (95% CI: 0.733-0.843), with a sensitivity of 62.9% and a specificity of 80.9%. The AUC for identifying HBV-HCC patients from HBV-LC patients was 0.646 (95% CI: 0.576-0.716), with a sensitivity of 31.0% and a specificity of 83.9%. This panel showed superior diagnostic efficiency in identifying early HBV-HCC compared with AFP, with an AUC of 0.856 (95% CI: 0.761-0.924) for this panel and 0.652 (0.536-0.757) for AFP (P=0.0026).&lt;/p&gt;

&lt;div&gt;Abstract&lt;p&gt;The purpose of this study was to identify biomarkers associated with hepatitis B virus-associated hepatocellular carcinoma (HBV-HCC) and to develop a new combination with good diagnostic performance. This study was divided into four phases: discovery, verification, validation, and modeling. A total of four candidate tumor-associated autoantibodies (TAAb; anti-ZIC2, anti-PCNA, anti-CDC37L1, and anti-DUSP6) were identified by human proteome microarray (52 samples) and bioinformatics analysis. Subsequently, these candidate TAAbs were further confirmed by indirect ELISA with two testing cohorts (120 samples for verification and 663 samples for validation). The AUC for these four TAAbs to identify patients with HBV-HCC from chronic hepatitis B (CHB) patients ranged from 0.693 to 0.739. Finally, a diagnostic panel with three TAAbs (anti-ZIC2, anti-CDC37L1, and anti-DUSP6) was developed. This panel showed superior diagnostic efficiency in identifying early HBV-HCC compared with alpha-fetoprotein (AFP), with an AUC of 0.834 [95% confidence interval (CI), 0.772–0.897] for this panel and 0.727 (95% CI, 0.642–0.812) for AFP (&lt;i&gt;P&lt;/i&gt; = 0.0359). In addition, the AUC for this panel to identify AFP-negative patients with HBV-HCC was 0.796 (95% CI, 0.734–0.858), with a sensitivity of 52.4% and a specificity of 89.0%. Importantly, the panel in combination with AFP significantly increased the positive rate for early HBV-HCC to 84.1% (&lt;i&gt;P&lt;/i&gt; = 0.005) and for late HBV-HCC to 96.3% (&lt;i&gt;P&lt;/i&gt; &lt; 0.001). Our findings suggest that AFP and the autoantibody panel may be independent but complementary serologic biomarkers for HBV-HCC detection.&lt;/p&gt;Prevention Relevance:&lt;p&gt;We developed a robust diagnostic panel for identifying patients with HBV-HCC from patients with CHB. This autoantibody panel provided superior diagnostic performance for HBV-HCC at an early stage and/or with negative AFP results. Our findings suggest that AFP and the autoantibody panel may be independent but complementary biomarkers for HBV-HCC detection.&lt;/p&gt;&lt;/div&gt;

&lt;p&gt;Supplementary Table S2: RNA sequencing data (GSE22058, GSE121248, and GSE55092) from the Gene Expression Omnibus (GEO) database were downloaded for analyses. These three datasets derived from two microarray platforms (Rosetta/Merck Human RSTA Custom Affymetrix 1.0 microarray and Affymetrix Human Genome U133 Plus 2.0 Array). The GEO query software package was used to download datasets and to collect clinical information. The sample sizes for these three datasets are shown in Supplementary Table S2.&lt;/p&gt;

&lt;p&gt;Supplementary Figure S5: In the training set, the AUC for identifying HBV-HCC patients from CHB patients 0.788 (95% CI: 0.733-0.843) (Supplementary Figure S5A). Similarly, the AUC of the panel was 0.764 (95% CI: 0.695-0.833) in the test-set (Supplementary Figure S5B). In the training set, the AUC for identifying HBV-HCC patients from HBV-LC patients was 0.646 (95% CI: 0.576-0.716) (Supplementary Figure S5C). In the test set, the AUC for identifying HBV-HCC patients from HBV-LC patients was 0.595 (95% CI: 0.507-0.684) (Supplementary Figure S5D).&lt;/p&gt;

&lt;p&gt;Supplementary Table S5: All data are derived from the training set. The performance evaluation of this panel in an AUC of 0.788 (95% CI: 0.733-0.843), with a sensitivity of 62.9% and a specificity of 80.9%. The AUC for identifying HBV-HCC patients from HBV-LC patients was 0.646 (95% CI: 0.576-0.716), with a sensitivity of 31.0% and a specificity of 83.9%. This panel showed superior diagnostic efficiency in identifying early HBV-HCC compared with AFP, with an AUC of 0.856 (95% CI: 0.761-0.924) for this panel and 0.652 (0.536-0.757) for AFP (P=0.0026).&lt;/p&gt;

&lt;p&gt;Supplementary Figure S2: Samples (n=192) from GSE22058 were clustered and analyzed to detect the presence of outliers. Sample clustering demonstrated that two outliers (GSM548410 and GSM548460) need to be removed and the remaining samples (n=190) were applied for subsequent analyses (Supplementary Figure S2A). The scale-free modules were constructed by the optimal threshold of β=4 (Supplementary Figure S2B). Genes were divided into 16 modules by the thresholding power (Supplementary Figure S2C). The blue module had the highest correlation with the sample traits (r=0.93, P&lt;0.001) (Supplementary Figure S2D) and the genes in this module were highly correlated with clinical information (cor=0.98, P&lt;0.001) (Supplementary Figure S2E).&lt;/p&gt;

&lt;p&gt;Supplementary Table S4: The AUC of these four TAAbs for identifying HBV-HCC patients from CHB patients ranged from 0.693-0.739. Among them, anti-DUSP6 showed the highest diagnostic ability, with an AUC of 0.739 (95% CI [confidence interval]: 0.694-0.785). The diagnostic capability of anti-PCNA was the poorest, with an AUC of 0.693 (95% CI: 0.645-0.741). The AUC of four candidate TAAbs in differentiating between HBV-HCC and HBV-LC patients ranged from 0.589 to 0.624. Among them, anti-PCNA had the most diagnostic capacity, with an AUC of 0.624 (95% CI: 0.569-0.679). Anti-CDC37L1 had the least diagnostic capability, with an AUC of 0.589 (95% CI: 0.533-0.645).&lt;/p&gt;

&lt;p&gt;Supplementary Figure S1: In the discovery phase, a total of 71 differentially expressed TAAbs between the HCC and NC groups were identified using HuProt™ microarray (Supplementary Figure S1). These proteins could clearly distinguish the HCC group from the NC group.&lt;/p&gt;

&lt;p&gt;Supplementary Figure S2: Samples (n=192) from GSE22058 were clustered and analyzed to detect the presence of outliers. Sample clustering demonstrated that two outliers (GSM548410 and GSM548460) need to be removed and the remaining samples (n=190) were applied for subsequent analyses (Supplementary Figure S2A). The scale-free modules were constructed by the optimal threshold of β=4 (Supplementary Figure S2B). Genes were divided into 16 modules by the thresholding power (Supplementary Figure S2C). The blue module had the highest correlation with the sample traits (r=0.93, P&lt;0.001) (Supplementary Figure S2D) and the genes in this module were highly correlated with clinical information (cor=0.98, P&lt;0.001) (Supplementary Figure S2E).&lt;/p&gt;

&lt;p&gt;Supplementary Figure S4: These four candidate TAAbs were further confirmed by indirect ELISA with two testing cohorts. In the initial verification of candidate TAAbs in 120 sera, the expression of all four TAAbs was significantly different between the HBV-HCC and CHB groups (P&lt;0.001) (Supplementary Figure S4A). These four TAAbs were further validated in a large dataset (663 sera). The results showed that the expression of four TAAbs was significantly different in the pairwise comparisons between the three groups (P&lt;0.01), and the expression was highest in the HBV-HCC group and lowest in the CHB group (Supplementary Figure S4B).&lt;/p&gt;

&lt;p&gt;Supplementary Figure S3: A total of 964 genes were identified by weighted gene co-expression network analysis (WGCNA) and difference analysis (GSE22058, GSE55092 and GSE121248). And four TAAs (ZIC2, PCNA, CDC37L1 and DUSP6) were identified by an intersection of the human proteome microarray and bioinformatics analysis.&lt;/p&gt;

&lt;div&gt;Abstract&lt;p&gt;The purpose of this study was to identify biomarkers associated with hepatitis B virus-associated hepatocellular carcinoma (HBV-HCC) and to develop a new combination with good diagnostic performance. This study was divided into four phases: discovery, verification, validation, and modeling. A total of four candidate tumor-associated autoantibodies (TAAb; anti-ZIC2, anti-PCNA, anti-CDC37L1, and anti-DUSP6) were identified by human proteome microarray (52 samples) and bioinformatics analysis. Subsequently, these candidate TAAbs were further confirmed by indirect ELISA with two testing cohorts (120 samples for verification and 663 samples for validation). The AUC for these four TAAbs to identify patients with HBV-HCC from chronic hepatitis B (CHB) patients ranged from 0.693 to 0.739. Finally, a diagnostic panel with three TAAbs (anti-ZIC2, anti-CDC37L1, and anti-DUSP6) was developed. This panel showed superior diagnostic efficiency in identifying early HBV-HCC compared with alpha-fetoprotein (AFP), with an AUC of 0.834 [95% confidence interval (CI), 0.772–0.897] for this panel and 0.727 (95% CI, 0.642–0.812) for AFP (&lt;i&gt;P&lt;/i&gt; = 0.0359). In addition, the AUC for this panel to identify AFP-negative patients with HBV-HCC was 0.796 (95% CI, 0.734–0.858), with a sensitivity of 52.4% and a specificity of 89.0%. Importantly, the panel in combination with AFP significantly increased the positive rate for early HBV-HCC to 84.1% (&lt;i&gt;P&lt;/i&gt; = 0.005) and for late HBV-HCC to 96.3% (&lt;i&gt;P&lt;/i&gt; &lt; 0.001). Our findings suggest that AFP and the autoantibody panel may be independent but complementary serologic biomarkers for HBV-HCC detection.&lt;/p&gt;Prevention Relevance:&lt;p&gt;We developed a robust diagnostic panel for identifying patients with HBV-HCC from patients with CHB. This autoantibody panel provided superior diagnostic performance for HBV-HCC at an early stage and/or with negative AFP results. Our findings suggest that AFP and the autoantibody panel may be independent but complementary biomarkers for HBV-HCC detection.&lt;/p&gt;&lt;/div&gt;

&lt;p&gt;Supplementary Figure S3: A total of 964 genes were identified by weighted gene co-expression network analysis (WGCNA) and difference analysis (GSE22058, GSE55092 and GSE121248). And four TAAs (ZIC2, PCNA, CDC37L1 and DUSP6) were identified by an intersection of the human proteome microarray and bioinformatics analysis.&lt;/p&gt;

&lt;p&gt;Supplementary Figure S1: In the discovery phase, a total of 71 differentially expressed TAAbs between the HCC and NC groups were identified using HuProt™ microarray (Supplementary Figure S1). These proteins could clearly distinguish the HCC group from the NC group.&lt;/p&gt;

Abstract Aims This study aimed to investigate environmental factors and genetic variant loci associated with hepatocellular carcinoma (HCC) in Chinese population and construct a weighted genetic risk score (wGRS) and polygenic risk score (PRS). Methods A case–control study was applied to confirm the single nucleotide polymorphisms (SNPs) and environmental variables linked to HCC in the Chinese population, which had been screened by meta‐analyses. wGRS and PRS were built in training sets and validation sets. Area under the curve (AUC), net reclassification improvement (NRI), integrated discrimination improvement (IDI), Akaike information criterion (AIC), and Bayesian information criterion (BIC) were applied to evaluate the performance of the models. Results A total of 13 SNPs were included in both risk prediction models. Compared with wGRS, PRS had better accuracy and discrimination ability in predicting HCC risk. The AUC for PRS in combination with drinking history, cirrhosis, HBV infection, and family history of HCC in training sets and validation sets (AUC: 0.86, 95% CI: 0.84–0.89; AUC: 0.85, 95% CI: 0.81–0.89) increased at least 20% than the AUC for PRS alone (AUC: 0.63, 95% CI: 0.60–0.67; AUC: 0.65, 95% CI: 0.60–0.71). Conclusions A novel model combining PRS with alcohol history, HBV infection, cirrhosis, and family history of HCC could be applied as an effective tool for risk prediction of HCC, which could discriminate at‐risk individuals for precise prevention.

Abstract Background Results regarding whether it is essential to incorporate genetic variants into risk prediction models for esophageal cancer (EC) are inconsistent due to the different genetic backgrounds of the populations studied. We aimed to identify single-nucleotide polymorphisms (SNPs) associated with EC among the Chinese population and to evaluate the performance of genetic and non-genetic factors in a risk model for developing EC. Methods A meta-analysis was performed to systematically identify potential SNPs, which were further verified by a case-control study. Three risk models were developed: a genetic model with weighted genetic risk score (wGRS) based on promising SNPs, a non-genetic model with environmental risk factors, and a combined model including both genetic and non-genetic factors. The discrimination ability of the models was compared using the area under the receiver operating characteristic curve (AUC) and the net reclassification index (NRI). The Akaike information criterion (AIC) and Bayesian information criterion (BIC) were used to assess the goodness-of-fit of the models. Results Five promising SNPs were ultimately utilized to calculate the wGRS. Individuals in the highest quartile of the wGRS had a 4.93-fold (95% confidence interval [CI]: 2.59 to 9.38) increased risk of EC compared with those in the lowest quartile. The genetic or non-genetic model identified EC patients with AUCs ranging from 0.618 to 0.650. The combined model had an AUC of 0.707 (95% CI: 0.669 to 0.743) and was the best-fitting model (AIC = 750.55, BIC = 759.34). The NRI improved when the wGRS was added to the risk model with non-genetic factors only (NRI = 0.082, P = 0.037). Conclusions Among the three risk models for EC, the combined model showed optimal predictive performance and can help to identify individuals at risk of EC for tailored preventive measures.

Introduction: We aimed to modify the LR-5 strategy to improve the diagnostic sensitivity for hepatocellular carcinoma (HCC) in high-risk patients while maintaining specificity. Methods: This study retrospectively analyzed 412 patients with 445 liver observations who underwent preoperative gadolinium ethoxybenzyl DTPA (GD-EOB-DTPA)-enhanced MRI followed by surgical procedures or biopsies. All observations were classified according to LI-RADS v2018, and the classifications were adjusted by modifying major features (MF)(substituting threshold growth with a more HCC-specific ancillary features (AF): presence of blood products within the mass, arterial phase hyperenhancement (APHE) was interpreted with hypointensity on precontrast imaging- isointensity in arterial phase (AP) and extending washout to transitional phase (TP)(2 min)). The specificity, sensitivity, and positive predictive value (PPV) were assessed to compare LR-5 (definitely HCC) diagnostic efficacy between LI-RADS version 2018 and modified LI-RADS. Results: Apart from nonenhancing “capsule”, the interreader agreement of MFs and HCC-specific AFs between the two readers reached substantial or excellent ranges (κ values ranging from 0.631 to 0.911). According to LI-5 v2018, the specificity, sensitivity and PPV of HCC were 90.74%, 82.35%, and 98.17%, respectively. Based on a more HCC-specific AF, signal intensity in AP and TP (2 min), the sensitivity of the three modified strategies were 86.19%, 93.09%, 96.67% (P &lt; .05)), while maintaining high specificity and PPV rates at 88.89% and 98.25% (P &gt; .05) Conclusion: Further investigation into the efficacy of threshold growth as a MF is warranted. By utilizing GD-EOB-DTPA-enhanced MRI, enhancing the sensitivity of the modified LR-5 category may be achieved without compromising specificity and PPV in diagnosing HCC among high-risk patients.

In our previous whole-genome sequencing study of 30 unrelated northern Chinese Han patients, we identified six single nucleotide polymorphisms (SNPs) in the interleukin 17 receptor C (IL17RC) and collagen type VI α1 chain (COL6A1) genes that were potentially associated with thoracic ossification of the posterior longitudinal ligament (T-OPLL). To determine whether these six SNPs are associated with susceptibility to T-OPLL in the northern Chinese Han population, we performed a case-control association study to confirm specific susceptible loci in the expanded samples.The six SNPs in the IL17RC and COL6A1 genes were analyzed in 200 northern Chinese individuals (100 patients and 100 control subjects) using the Sequenom system.The genotype distributions and allele frequencies of each SNP in the control and patient groups were compared. rs201153092, rs13051496, rs199772854, rs76999397, and rs189013166 showed potential pathogenic loci for T-OPLL in the northern Chinese Han population, whereas rs151158105 did not. At the genotype level, the differences in the genotype frequencies of rs201153092, rs13051496, rs199772854, rs76999397, and rs189013166 between T-OPLL cases and controls reached statistical significance.To the best of our knowledge, this is the first association study of susceptibility genes in Han Chinese patients with T-OPLL. The results revealed five SNPs in the IL17RC and COL6A1 genes that represented potentially pathogenic mutations in patients with T-OPLL.

This study aims to evaluate the clinical performance of the HPV E6/E7 mRNA test in cervical cancer screening in China. A hospital-based study was conducted with mRNA, DNA, and liquid-based cytology (LBC) as primary screening tests. Each woman with a positive result received colposcopy with lesion-targeted-biopsy. Histopathological diagnosis was used as the gold standard. The total agreement of HPV DNA and mRNA was 90.7% (95%CI: 87.9, 92.9) with a kappa value of 0.81. The positive rates of HPV DNA, mRNA, and LBC increased with the severity of histopathology diagnosis, from 25.5, 19.1, and 11.4% in normal to 100.0% in SCC, respectively. The sensitivities for mRNA to detect CIN2+ and CIN3+ were 93.8% (95%CI: 89.7-96.4) and 95.7% (95%CI: 91.3-97.9), respectively, which were not different from HPV DNA testing (95.7% [95%CI: 92.0-97.7], 96.3% [95%CI: 92.1-98.3]), but higher than LBC (80.4% [95%CI: 74.5-85.2] and 88.8% [95%CI: 83.0-92.8]). The specificities for mRNA to detect CIN2+ (79.0% [95%CI: 74.2-83.0]) and CIN3+ (70.5% [95%CI: 65.7-74.9]) were higher than HPV DNA testing (71.0% [95%CI: 65.9-75.7], 62.8% [95%CI: 57.8-67.5]), but lower than LBC (84.5% [95%CI: 80.1-88.0] 79.8% [95%CI: 75.4-83.6]). All tests were more effective in women older than 30 years. HPV mRNA test showed excellent agreement with the DNA test, with similar sensitivity and a higher specificity in detecting high-grade cervical lesions. It is promising that mRNA test could be used for the national cervical cancer screening to reduce false positive without losing sensitivity.

To determine whether a panel of multiple tumor-associated antigens (TAAs) would enhance antibody detection, the diagnostic value of autoantibodies to a panel of multiple TAAs in cancer has been evaluated. The TAAs used in this study was composed of eight TAAs including Imp1, p62, Koc, p53, C-myc, Cyclin B1, Survivin, and p16 full-length recombinant proteins. Enzyme-linked immunosorbent assay and immunoblotting were used to detect antibodies in 304 cancer sera and also 58 sera from normal individuals. The antibody frequency to any individual TAA in cancer was variable but rarely exceeded 20%. With the successive addition of TAAs to a final combination of total of eight antigens, there was a stepwise increase of positive antibody reactions reaching a sensitivity of 63.5% and a specificity of 86.2% in the combined cancer group. In different types of cancer, the ranges of positive and negative likelihood ratio were 4.07-4.76 and 0.39-0.51, respectively, and the ranges of positive and negative predictive values were 74.2-88.7% and 58.8-75.8%, respectively. Agreement rate and Kappa value were 67.1% and 0.51, respectively. These results further support our previous hypothesis that detection of anti-TAAs autoantibodies for diagnosis of certain type of cancer can be enhanced by using a miniarray of several TAAs.

To identify proteomic biomarkers in cerebrospinal fluid (CSF) and develop a diagnostic proteomic model for neuropsychiatric systemic lupus erythematosus (NPSLE).CSF proteomic spectra were generated by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) combined with weak cation exchange (WCX) magnetic beads. The spectra were taken from 27 patients with NPSLE before and after treatment, and 27 controls including 17 patients with scoliosis and 10 patients with SLE but without neuropsychiatric manifestation. Discriminating peaks were processed by Biomarker Patterns Software to build a decision tree model for NPSLE classification. In addition, CSF samples of 12 patients with NPSLE, 12 patients with lumbar disc herniation, and 9 patients with other neurological conditions were used as a blind test group to verify the accuracy of the model.Twelve discriminating mass-to-charge (m/z) peaks were identified between NPSLE and controls: m/z peaks 7740, 11962, 8065, 7661, 6637, 5978, 11384, 11744, 8595, 10848, 7170, and 5806. The diagnostic decision tree model, built with a panel of m/z peaks 8595, 7170, 7661, 7740, and 5806, recognized NPSLE with both sensitivity and specificity of 92.6%, based on training group samples, and sensitivity and specificity of 91.7% and 85.7%, respectively, based on the blind test group. In addition, the root node m/z peak 8595 protein, which was downregulated in the CSF of patients with NPSLE after treatment, was identified and confirmed as ubiquitin by immunoprecipitation and ELISA.Potential CSF biomarkers for NPSLE are identified by MALDI-TOF-MS combined with WCX magnetic beads. The novel diagnostic proteomic model with m/z peaks 8595, 7170, 7661, 7740, and 5806 is highly sensitive and relatively specific for NPSLE diagnosis. The level of ubiquitin in CSF is a promising biomarker for active NPSLE.

Human leukocyte antigen-G (HLA-G) is a tumor-associated molecule, whose expression may help the cancer cells to escape the immune response.The aim of this study was to evaluate the diagnostic value of HLA-G level in oral squamous cell carcinoma (OSCC).A total of 52 patients who had definite pathological diagnosis and 20 cases of healthy controls were enrolled in this clinical trial. Immunohistochemisty (IHC) and quantitative real-time reverse transcription-polymerase chain reaction (RT-PCR) analysis were considered for HLA-G identification and multilevel validations. Statistical analysis was performed using SPSS and statistical significance was determined at P < 0.05.IHC results demonstrated that the expression of HLA-G in OSCC was strongly positive and the rate of positive expression was 55.77% (29/52), but the expression of HLA-G in healthy controls was negative (0/20). Furthermore, RT-PCR results showed that the positive expression rate of HLA-G messenger RNA was weak in healthy controls, but strong in OSCC. Besides, HLA-G expression in the tumors was significantly correlated with histological grade.Our results suggested that HLA-G is associated with the prognosis of OSCC and may serve as a novel therapeutic target.

Abstract Granitoid rocks are universal in continental crust and are of special significance in understanding tectonic settings. This paper presents detailed zircon U-Pb dating, Hf isotope, whole-rock geochemistry, and Sr-Nd-Pb isotope analyses, and mineralogy of two Ordovician granitoid intrusions and one quartz diorite intrusion in Western Kunlun, NW Tibetan Plateau. The Yutian Complex is composed of diverse rock suites, including monzogabbros, quartz monzodiorites, monzogranites, and monzodioritic enclaves. These suites have similar rock formation ages (447–440 Ma) and minerals, e.g., amphibole grains from different suites belonging to pargasite. Moreover, they exhibit geochemical similarities, such as broadly parallel trace-element patterns characterized by enrichments in light rare earth elements and large ion lithophile elements, and depletions in high field strength elements, which are typical features of arc rocks. Furthermore, the studied samples display homogeneous zircon Hf values, e.g., εHf(t) = −1 to −3, and whole-rock isotopic compositions, e.g., εNd(t) = −4 to −6. Thus, they were most likely derived from a mantle wedge enriched by subducted sediments and fluids, which then evolved into different suites through fractional crystallization of hornblende and plagioclase. The ca. 440 Ma North Yutian quartz diorite intrusion, with an average of εHf(t) value of −6, was a product of the partial melting of mafic lower crust through slightly fractional crystallization of hornblende. In contrast, the ca. 470 Ma Aqiang granodiorite intrusion has εHf(t) values varying from −5 and −2, but it has heterogeneous petrological and geochemical features. It is considered to be a product of the partial melting of the overriding mantle wedge modified by fluids derived from the subducted Proto-Tethys slab and some mixed crustal materials. The Aqiang samples belong to the slightly fractionated I-type series, but they have variable alumina saturation index (ASI = molar Al2O3/[CaO – 3.33 × P2O5 + Na2O + K2O]) values (0.74–1.03) due to variable peraluminous biotite contents. The different suites in the Yutian Complex display low ASI values (&amp;lt;1) controlled by sources and fractional crystallization. The Yutian Complex and the North Yutian intrusion were emplaced during the southward subduction of the Proto-Tethys oceanic lithosphere, and the Aqiang intrusion was emplaced in response to the northward subduction.

Background and Objectives: At present, the association between the long non-coding RNA (lncRNA) metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) polymorphism rs3200401 C > T and cancer risk remain controversial. The aim of this meta-analysis was to assess the association between rs3200401 C > T and cancer susceptibility. Materials and Methods: The databases of PubMed, EMBASE and Web of Science were searched for literature published in English until 1 September 2021. The odd ratios (ORs) and 95% confidence intervals (CIs) were applied to evaluate the strength of association in five genetic models. Heterogeneity was assessed using the Q-test and I2 test. Begg's funnel plot and Egger's linear regression test were conducted to assess publication bias. Meta-regression analysis was used to explore potential sources of heterogeneity. Trial sequential analysis (TSA) was performed to validate the reliability of the results. Results: A total of 10 case-control studies involving 6630 cases and 7457 controls were included in this study. The pooled ORs showed no significant association between MALAT1 rs3200401 C > T and cancer risk in five genetic models. Similarly, the association was not found in the subgroups of control source, ethnicity and study quality. In the cancer type subgroup, the results demonstrated that the T allele increased the risk of colorectal cancer (CRC) compared with the C allele. (C vs. T: OR, 1.16; 95% CI, 1.01-1.33). Conclusion: In the current meta-analysis, we found no significant association between MALAT1 polymorphism rs3200401 C > T and overall cancer risk. However, the rs3200401 C > T may be linked to a higher risk of CRC, which needs more studies to be further confirmed.

Abstract Granitoids with diverse composition and tectonic settings provide important tools for exploring crustal evolution and regional geodynamic history. Here we present an integrated study using petrological, mineralogical, zircon U-Pb geochronological, whole-rock geochemical, and isotopic data on the Late Triassic Daocheng batholith in the Yidun Terrane with a view to understanding the petrogenesis of a compositionally diverse batholith and its implications for the evolution of the Paleo-Tethys Ocean in the eastern Tibetan Plateau. The different lithological units of the batholith, including granodiorite, monzogranite, and quartz diorite, with abundant mafic microgranular enclaves in the granodiorite (MME I) and monzogranite (MME II), show identical crystallization ages of 218–215 Ma. The mineral assemblage and chemical composition of the granodiorite are identical to those of tonalitic-granodioritic melts generated under water-unsaturated conditions. The insignificant Eu anomalies and low magmatic temperatures indicate hydrous melting in the source. The relatively narrow range of whole-rock chemical and Sr-Nd isotopes, as well as the zircon trace element and Hf isotopic compositions of the granodiorite, suggest a homogeneous crustal source for the magma. Our modeling suggests that the rock was produced by 20–50% of lower crustal melting. The Daocheng monzogranites display more evolved compositions and larger variations in Sr-Nd-Hf isotopes than the granodiorite, which are attributed to assimilation and the fractional crystallization process. This is evidenced by the presence of metasedimentary enclave and inherited zircon grains with Neoproterozoic and Paleozoic ages, a non-cotectic trend in composition, and the trend shown by the modeling of initial 87Sr/86Sr ratios and Sr. The quartz diorites and MMEs showing composition similar to that of andesitic primary magma have high zircon εHf(t) values and are characterized by enrichment in LILEs and depletion of HFSEs. They were derived from the partial melting of lithospheric mantle that had been metasomatized by slab melts and fluids. The MMEs in both rocks display typical igneous texture and higher rare earth element (REE) and incompatible element concentrations than their host granites. The presence of fine-grained margins, acicular apatite, and plagioclase megacrysts suggests a magma mingling process. The overgrowth of amphibole around the pyroxene, quartz ocelli rimmed by biotite, and oscillatory zones of plagioclase are all indicative of chemical diffusion. Their enriched Sr-Nd isotopes imply isotopic equilibrium with the host granites. Based on a comparison with the coeval subduction-related magmatism, we propose that subduction and subsequent rollback of the Paleo-Tethys (Garzê-Litang Ocean) oceanic slab was the possible mechanism that triggered the diverse Triassic magmatism within the eastern Tibetan Plateau.

The purpose of this study was to test the associations about Helicobacter pylori infection and polymorphisms of IL-1B-31/-511 and IL-1RN VNTR polymorphism with gastric cancer in cases' and controls' family members from the areas of high cancer prevalence in China. IL-1B-511T and IL-1RN *2 were associated with risks of gastric cancer. The association strength reduced with the relative degree decreasing. Such association was not found in the polymorphisms of IL-1B-31. But the haplotype analysis of IL-1B-511 and IL-1B-31 genotype could enhance the risks of gastric cancer. The positive H. pylori status could increase the risks of IL-1B to gastric cancer.

The main objective of this study was to compare the application value of indocyanine green fluorescence imaging (ICGFI) and its combined tracing method with the blue dye method in guiding sentinel lymph node biopsy for breast cancer. A computerized search of the Pubmed, Embase, Web of Science, and Cochrane Library databases was conducted to identify all relevant literature on ICGFI compared to the sole methylene blue (MB) tracing method in guiding sentinel lymph node biopsy for breast cancer. The search was performed up until May 2023. After assessing the quality of the included studies, a meta-analysis was conducted using STATA 12.0 software. A total of 11 relevant studies were included in this research. The analysis results showed that, in terms of the detection rate, the ICGFI group had a higher detection rate to the MB group [odds ratio (OR) = 8.64, 95% CI: 5.46–13.66, P = 0.000], and had a higher quantity compared to the MB group [weighted mean difference (WMD) = 0.72, 95% CI 0.31–1.13, P = 0.001], and it also had a lower false-negative rate [OR = 0.10, 95% CI 0.02–0.43, P = 0.002]. However, there was no statistically significant difference in the positive detection rate, and sensitivity comparison. The indocyanine green fluorescence imaging and tracing method for sentinel lymph node biopsy for breast cancer are simple and effective, and they are well suited for clinical use. A multicenter randomized controlled trial with a large sample size should be conducted in the future for further validation of the method.

In recent years, metabolomics research has become a hot spot in the screening and treatment of cancer. It is a popular technique for the quantitative characterization of small molecular compounds in biological cells, tissues, organs or organisms. Further study of the tumor revealed that amino acid changes may occur early in the tumor. The rapid growth and metabolism required for survival result in tumors exhibiting an increased demand for amino acids. An abundant supply of amino acids is important for cancer to maintain its proliferative driving force. Changes in amino acid metabolism can be used to screen malignant tumors and improve therapeutic outcomes. Therefore, it is particularly important to study the characteristics of amino acid metabolism in colorectal cancer. This article reviews several specific amino acid metabolism characteristics in colorectal cancer.

Abstract To evaluate the potential of zinc finger protein 1 (ZPR1) as a diagnostic biomarker and explore the underlying role for esophageal squamous cell carcinoma (ESCC). A human proteome microarray was customized to identify anti‐ZPR1 autoantibody, and enzyme‐linked immunosorbent assay (ELISA) was adopted to assess the diagnostic performance of anti‐ZPR1 autoantibody in 294 patients with ESCC and 294 normal controls. The expression of ZPR1 protein was measured by immunohistochemistry. The effect of ZPR1 on the proliferation, migration, and invasion of ESCC cells was investigated through CCK‐8, wound healing, and Transwell assays. The expression level of anti‐ZPR1 autoantibody (fold change = 2.77) in ESCC patients was higher than that in normal controls. The receiver operating characteristic (ROC) analysis manifested anti‐ZPR1 autoantibody achieved area under the ROC curve (AUC) of 0.726 and 0.734 to distinguish ESCC from normal controls with sensitivity of 50.0% and 42.3%, and specificity of 91.0% and 92.0% in the test group and validation group, respectively. The positive rate of ZPR1 protein was significantly higher in ESCC tissues (75.5%, 80/106) than paracancerous tissues (9.4%, 5/53). Compared with the human normal esophageal cell line, the expression level of ZPR1 mRNA and protein in ESCC lines (KYSE150, Eca109, and TE1) had an increased trend. The knockdown or overexpression of ZPR1 reduced and enhanced the proliferation, migration, and invasion of ESCC cell, respectively. ZPR1 was a potential immunodiagnostic biomarker for noninvasive detection and could be a promotional factor in tumor progression of ESCC.

Understanding the role of perovskite surface passivators in hot carriers transfer dynamics is important to develop highly efficient perovskite solar cells (PSCs). In this work, we have designed and synthesized a naphthalimide-based organic small molecule (NCN) for perovskite surface defect passivator. We reveal that the introduction of NCN not only reduces the density of perovskite defect-state, but also promotes hot carriers (HCs) cooling in perovskite through the transient absorption spectroscopy measurements. Fast HCs cooling permits HCs transfer from perovskite layer into NCN layer, thus resulting in the decreased charge-carrier recombination in NCN-treated device. As expected, the power conversion efficiency (PCE) of PSCs with NCN is enhanced to 22.02% from 19.95% for the control device. The findings are relevant for developing highly efficient PSCs.

Major depressive disorder (MDD) is one of the most severe psychiatric disorders. The objective of this study was to explore the effects of CREB1 gene polymorphisms on risk of developing MDD and the joint effects of gene-environment interactions. Genotyping was performed by Taqman allelic discrimination assay among 586 patients and 586 healthy controls. A significant impact on rs6740584 genotype distribution was found for childhood trauma (P = 0.015). We did not find an association of CREB1 polymorphisms with MDD susceptibility. However, we found a significantly increased risk associated with the interactions of CREB1 polymorphisms and drinking (OR = 11.67, 95% CI = 2.52-54.18; OR = 11.52, 95% CI = 2.55-51.95 for rs11904814; OR = 4.18, 95% CI = 1.87-9.38; OR = 5.02, 95% CI = 2.27-11.14 for rs6740584; OR = 7.58, 95% CI = 2.05-27.98; OR = 7.59, 95% CI = 2.12-27.14 for rs2553206; OR = 8.37, 95% CI = 3.02-23.23; OR = 7.84, 95% CI = 2.93-20.98 for rs2551941). We also noted that CREB polymorphisms combined with family harmony and childhood trauma conferred increased susceptibility for MDD. In conclusion, polymorphisms in the CREB gene may not be independently associated with MDD risk, but they are likely to confer increased susceptibility by interacting with environmental risk factors in the Chinese population.

Dysregulation of miR-675 has been found in a variety of solid tumors. MiR-675 has been suggested as having both oncogenic and tumor suppression properties in cancer. However, there is no evidence whether miR-675 is involved in breast cancer. The objective of this study was to evaluate the expression status of miR-675 and its clinical relevance in breast cancer patients.The expression level of miR-675 was detected in 100 breast cancer patients and 38 cancer-free controls using real-time quantitative PCR. The clinicopathological characteristics of miR-675 in breast cancer were also investigated. All statistical analyses were performed using SPSS 20.0.The study showed that miR-675 was significantly up-regulated in breast cancer patients compared with controls (P < 0.01). There was no significant difference in age, lymph nodes stage, ER status and PR status between patients with and without miR-675 over-expression (P > 0.05). The frequency of miR-675 over-expression was higher in the patients of histological grade I-II than in others (50% versus 9%, P = 0.011). The expression level of miR-675 had a high correlation with miR-24/93/98/378 in breast cancer patients.Taken together, our study demonstrated that miR-675 in formalin-fixed paraffin-embedded (FFPE) tissues might serve as a good source for biomarker discovery and breast cancer validation.

Qingyihuaji formula (QYHJ), confirmed efficacious in a series of clinical trials, has been applied to human pancreatic carcinoma treatment in Shanghai Cancer Center for years. Recent evidence highlighted that pluripotent stem cells transcription factor Nanog plays a pivotal role in carcinogenesis. However, there is little published information regarding the underlying clinical significance and mechanisms of transcription factor Nanog in pancreatic cancer. In this study, our results indicated that Nanog is overexpressed in human pancreatic cancer stem cells and downregulated by QYHJ, which may contribute to explain the clinical effectiveness of QYHJ and provide advanced pancreatic cancer patients with a new therapeutic option, supporting our hypothesis that the degradation pathway is another mechanism by which QYHJ affects Nanog expression.

Abstract Lung adenocarcinoma (LUAD) is a lethal malignancy worldwide and a major public health concern. We explored the potential clinical significance for LUAD of ATP-binding cassette (ABC), sub-family C, consisting of ABCC1–6, 8–12, and cystic fibrosis transmembrane conductance regulator (CFTR). Five hundred LUAD patients from The Cancer Genome Atlas database were used for analysis, including differential expression and diagnostic and prognostic significance. Oncomine and MERAV databases were used to validate differential expression and diagnostic significance. A risk score model was constructed using prognosis-related ABCC members. Prognosis-related genes were further explored to correlate their expression with tumor stage progression. Interaction networks, including biological processes and metabolic pathways, were constructed using Cytoscape software and STRING website. ABCC1–3 consistently showed high expression in tumor tissues (all P ≤ 0.05). Most datasets indicated that ABCC5, 10, and 11 were highly expressed in tumor tissues whereas ABCC6, 9, and CFTR were highly expressed in nontumor tissues (all P ≤ 0.05). Diagnostic significance of ABCC3 and ABCC5 was consistently assessed and validated in three datasets (all area under the curve &gt; 0.700) whereas ABCC6, 8, 10, 11, and CFTR were assessed in The Cancer Genome Atlas dataset and validated in one dataset (all area under the curve &gt; 0.700). Prognostic analysis indicated that ABCC2, 6, and 8 mRNA expression was associated with survival of LUAD (all adjusted P ≤ .037). The risk score model constructed using ABCC2, 6, and 8 suggested prognostic significance for survival predictions. ABCC2 expression was associated with tumor stage, whereas ABCC6 and 8 were not. Interaction networks indicated that they were involved in establishment of localization, ion transport, plasma membrane, apical plasma membrane, adenylyl nucleotide binding, ABC transporters, ABC transporter disorders, ABC-family-protein-mediated transport, and bile secretion. Differentially expressed ABCC2 and ABCC5 might be diagnostic whereas ABCC2, 6, and 8 may be prognostic biomarkers for LUAD, possibly through ABC-family-mediated transporter disorders.

Contrast-enhanced MRI can be used to identify patients with hepatocellular carcinoma (HCC). However, studies around the world have found differing diagnostic accuracies for the technique. Hence, we designed this meta-analysis to assess the accuracy of contrast-enhanced MRI for HCC diagnosis.We conducted a systematic search for all studies reporting the diagnostic accuracy of contrast-enhanced MRI for HCC in the databases of MEDLINE, EMBASE, Cochrane Library, Web of Science, SCOPUS, ScienceDirect, and Google Scholar from inception until January 2021. We used the "Midas" package from the STATA software to perform the meta-analysis.Our study was based on 21 publications with 5,361 patients. The pooled HCC diagnosis sensitivity and specificity were 75% (95% CI, 70%-80%) and 90% (95% CI, 88%-92%), respectively, for gadoxetic acid-enhanced MRI; and they were 70% (95% CI, 57%-81%) and 94% (95% CI, 85%-97%), respectively, for MRI with extracellular contrast agents (ECA-MRI). We found significant heterogeneity with a significant chi-square test and an I2 statistic >75%. We also found significant publication bias as per Deeks' test results and funnel plot.We found that both types of contrast-enhanced MRI are accurate diagnostic and surveillance tools for HCC and offer high sensitivity and specificity. Further studies on different ethnic populations are required to strengthen our findings.

Ovarian cancer is one of the most common cancers in women. Its early stages may be asymptomatic, and as a result diagnosis frequently occurrs at an advanced, often incurable, stage. The high mortality and low survival rates associated with ovarian cancer can in part be attributed to the lack of diagnostic methods allowing for early detection, yet a methodology to identify patients with early-stage ovarian cancer remains to be established. In order to investigate the frequency of antibodies against a panel of multiple carefully-selected tumor-associated antigens (TAAs) in sera from patients with ovarian cancer, and to determine the possibility and usefulness of such a panel of TAAs in the immunodiagnosis of ovarian cancer, sera from 32 ovarian cancer patients and 82 normal individuals were tested using an enzyme-linked immunosorbent assay (ELISA) for the presence of autoantibodies to a panel of 13 TAAs. ELISA results were also confirmed by immunoblotting analysis. The sensitivity and specificity of the multiple anti-TAA antibodies in the detection of ovarian cancer was 62.5 and 85.4%, respectively. With the successive addition of TAAs to a total of 7 antigens (survivin, p53, p16, cyclin B1, cyclin D1, cyclin A and cyclin E), there was a stepwise increase in sensitivity of up to 62.5%, and in specificity of 90.2%. With the addition of more antigens to the panel, no further increase in sensitivity was detected. This study further supports our previous hypothesis that a combination of antibodies might acquire higher sensitivity for the diagnosis of cancer, and also indicates that, in the selection of ovarian cancer-associated TAAs, some may be specific to ovarian cancer while others may not be. This emphasizes the importance of a comprehensive analysis of antibody response to selected TAAs in various disease conditions, such as ovarian cancer, in benign ovarian diseases, and in normal individuals, before conclusions can be drawn regarding their contribution to ovarian cancer.

The serological biomarkers as noninvasive tests are the most promising way for diagnosing gastric cancer (GC). Serological proteome analysis (SERPA) has been used to identify tumor-associated antigens (TAAs) and the corresponding autoantibodies in many studies. To explore the relationship between gastric cancer development and serum autoantibody anti-GRP78 response found by the method of SERPA with the GC cell line AGS, we included two cohorts (133 GC and 133 normal individuals in test group; 300 GC and 300 normal individuals in validation group) of patients with newly diagnosed GC for verification. All GC and normal controls were matched by age and gender. The autoantibody levels of the sera in two cohorts were measured by immunoassay. Finally, the results showed that 78-kDa glucose-regulated protein (GRP78) was identified in GC by SERPA and the level of anti-GRP78 antibody in GC was higher than that in normal individuals in the two cohorts. Receiver operating characteristic (ROC) curve analysis showed similar diagnostic value of anti-GRP78 antibody in test group (AUC: 0.718) and validation group (AUC: 0.666) to identify GC patients from normal individuals. The AUCs of anti-GRP78 autoantibody in the diagnosis of GC patients with different clinical characteristic ranged from 0.676 to 0.773 in test group and ranged from 0.645 to 0.707 in validation group. In conclusion, autoantibody against GRP78 might be a potential diagnostic biomarker. Further large-scale studies will be needed to validate and improve its performance of the sensitivity, specificity, and AUC value in distinguishing GC from other diseases.

Reappraisal of the role of postoperative radiotherapy in pN2 non-small cell lung cancer (NSCLC) patients according to N1 lymph node involvement.A total of 218 pIIIa-N2 NSCLC patients who underwent complete surgical resection with systematic nodal dissections were enrolled. Propensity scores were used for matching N1 involvement. Overall survival (OS) and disease-free survival (DFS) were analyzed retrospectively.After matching, pN2b patients without N1 involvement (pN0N2b) exhibited better prognoses than those with N1 involvement (pN1N2b) (5-year OS: 37.5% vs. 7.1%, P = 0.008; 5-year DFS: 31.8% vs. 4.6%, P = 0.004). Similar results were not detected in pN2a disease (5-year OS: 37.8% vs. 31.0%, P = 0.517; 5-year DFS: 27.1% vs. 20.2%, P = 0.788). The five-year OS of patients who received no adjuvant therapy (22 pN2a cases, 7 pN0N2b, 5 pN1N2b), adjuvant chemotherapy alone (74 pN2a cases, 11 pN0N2b, 17 pN1N2b) or chemoradiotherapy (25 pN2a cases, 7 pN0N2b, 6 pN1N2b) were compared (pN2a: 31.3%, 37.0%, and 32.0%, P = 0.808; pN0N2b: 0.0%, 18.2%, and 71.4%, P = 0.108; pN1N2b: 0.0%, 0.0%, and 33.3%, P < 0.0001). The five-year DFS was also analyzed (pN2a: 31.6%, 24.0%, and 18.3%, P = 0.410; pN0N2b: 0.0%, 11.1%, and 57.1%, P = 0.192; pN1N2b: 0.0%, 0.0%, and 16.7%, P < 0.0001). Multivariate analysis revealed that the novel classification based on N1 involvement and pN2a/pN2b staging was an independent prognostic factor of OS and DFS.N1 involvement significantly impacted the prognosis of pN2b NSCLC patients. The benefit of adjuvant therapy in pN2a and pN0N2b patients requires confirmation by further study.

Methylenetetrahydrofolate reductase (MTHFR) plays a central role in folate metabolism. This study with 381 esophageal cancer patients and 432 healthy controls was conducted to examine the association of MTHFR C677T and A1298C polymorphisms with susceptibility to esophageal cancer (EC) in a Chinese population. Compared with the CC genotype of MTHFR C677T, subjects carrying homozygote TT and variant genotypes (CT+TT) demonstrated reduced risk of EC with adjusted ORs (95% CI) of 0.44 (0.28-0.71) and 0.57 (0.37-0.88), respectively. However, no association was found between the MTHFR A1298C polymorphism and the risk of EC. Comparing to haplotype CA, haplotypes TA and TC could reduce the susceptibility to EC with adjusted ORs (95% CI) of 0.61(0.47-0.79) and 0.06 (0.01-0.43), respectively. In conclusion, the present study suggested that the MTHFR C677T polymorphism can markedly influence the risk of EC in Chinese.

BACKGROUND: Rap1GAP, a member of the family of GTPase-activating proteins, is reported to be involved in cancer development and progression. OBJECTIVE: The study aimed to investigate the expression and prognostic value of Rap1GAP in gastric cancer patients. METHODS: Real-time quantitative polymeras e chain reaction and western blotting were performed to examine Rap1GAP expression in tumorous and matched adjacent non-tumorous gastric tissues. Immunohistochemical staining was used to analyze Rap1GAP expression in 456 gastric cancer tissues. The correlation between Rap1GAP expression level and clinicopathological features as well as gastric cancer prognosis was analyzed. RESULTS: Rap1GAP expression was remarkably decreased in tumor tissues at mRNA (p= 0.012) and protein (p= 0.034) level. Clinicopathological analysis revealed that low Rap1GAP expression was significantly correlated with tumor size (p= 0.033), histological grade (p= 0.034), T classification (p= 0.012), N classification (p= 0.006) and clinical stage (p= 0.005). Kaplan-Meier survival analysis revealed the association between low Rap1GAP expression and poor survival in gastric cancer patients. Furthermore, multivariate Cox regression analysis showed that Rap1GAP expression was an independent prognostic factor (p= 0.02). CONCLUSION: Rap1GAP may play a significant role in gastric cancer progression and act as a valuable prognostic marker for gastric cancer.

This study was to investigate the association of melatonin (MTN) pathway gene's single-nucleotide polymorphisms (SNPs) with susceptibility to systemic lupus erythematosus (SLE).We recruited 495 SLE patients and 493 healthy controls, 11 tag SNPs in MTN receptor 1a (MTNR1a), MTNR1b, and arylalkylamine N-acetyltransferase (AANAT) genes were genotyped and analyzed. Serum MTN concentration was determined by enzyme-linked immunosorbent assay (ELISA) kits.Two SNPs of AANAT gene (rs8150 and rs3760138) associated with the risk of SLE; CC carriers of rs8150 had a lower risk as compared to GG (OR = 0.537, 95% CI: 0.361, 0.799), whereas GG carrier in rs3760138 had an increased risk (OR = 1.823, 95% CI: 1.154, 2.880) compared to TT. However, we did not find any genetic association between the other nine SNPs with SLE risk. Case-only analysis showed associations of rs2165667 and rs1562444 with arthritis, rs10830962 with malar rash, rs3760138 with immunological abnormality, and rs8150 with hematological abnormality. Furthermore, a significant difference between plasma MTN levels with different genotypes of rs1562444 was observed. Haplotype analyses revealed that haplotype of CCTAT, CTAGT, and GGG was significantly associated with the increased risk in SLE susceptibility, but TCTAT and CTG appeared to be a protective haplotype.The present study supported the genetic association of MTN pathway genes with SLE susceptibility and specific clinical manifestations, suggesting the potential role of MTN pathway genes in the pathogenesis and development of SLE.

Abstract Purpose To assess the value of adjuvant radiotherapy for treatment of gastric adenocarcinoma and to investigate subgroups of patients suitable for adjuvant radiotherapy. Methods and materials Data from 785 patients with gastric adenocarcinoma who had undergone D1/D2 radical resection and adjuvant chemotherapy were collected, the site of first progression was determined, and the relationship between the rate of local recurrence and clinicopathologic features was analyzed. Results By the end of the follow-up period, progression was observed in 405 patients. Local recurrence was observed as the first progression in 161 cases. The local recurrence rate was significantly lower than the non-local progression rate (20.5% vs 31.5%, p=0.007). Multivariate Cox regression analysis showed a significant relationship among degree of differentiation, T stage, N stage, and rate of local recurrence. Conclusions Not all patients with gastric carcinoma required adjuvant radiotherapy. However, patients with poorly differentiated cancer cells, advanced T stage (T3/T4), and positive lymph nodes, which included patients in the T4N1-2M0 subgroup, were recommended for adjuvant radiotherapy.

In previous study, we have reported an increased plasma midkine (MK) and pleiotrophin (PTN) concentrations in patients with systemic lupus erythematosus (SLE), and the increase of MK and PTN associated with inflammatory cytokines IL-17 level and some clinical manifestations, suggesting the underlying association of MK and PTN with SLE. This study was conducted to investigate the association between common single-nucleotide polymorphisms (SNPs) in the MK and PTN gene and SLE susceptibility. A total of 989 subjects (496 SLE patients and 493 healthy controls) were included and genotyped for three MK SNPs and seven PTN SNPs in using improved multiple ligase detection reaction (iMLDR). Results have demonstrated no significant differences for genotype and allele frequencies in all 10 SNPs between SLE patients and healthy controls. Case-only analysis in SLE revealed that, in MK gene, the genotype frequency of AA/AG (rs35324223) was significantly lower in patients with photosensitivity than those without; the allele frequency of A/G (rs20542) was significantly higher in patients without serositis. In PTN gene, the A/G allele frequency (rs322236), C/T allele frequency and TT/CT genotype frequency (rs6970141) appeared significantly increased results in patients with immunological disorder compared to those without. Furthermore, no significant differences in plasma MK and PTN concentrations with its SNPs genotypes were found. MK and PTN SNPs showed no associations with SLE genetic susceptibility, but it may be associated with the course of this disease; further studies are needed to focus on the mechanism of MK and PTN genes in the pathogenesis of SLE.

The study aims to explore the diagnostic value of anti-GNA11 autoantibody in esophageal squamous cell carcinoma (ESCC) from multiple levels. Autoantibody against GNA11 with the highest diagnostic performance was screened out from the customized protein microarray. A total of 486 subjects including ESCC patients and matched normal controls were recruited in the verification and validation phases by using enzyme-linked immunosorbent assay (ELISA). Western blotting analysis was used to verify the ELISA results. Immunohistochemistry (IHC) was used to evaluate GNA11 expression in ESCC tissues and para-tumor tissues. In addition, a bioinformatics approach was adopted to investigate the mRNA expression of GNA11 in ESCC. Results indicated that the level of anti-GNA11 autoantibody in ESCC patients was significantly higher than that in the normal controls, and it can be used to distinguish ESCC patients from normal individuals in clinical subgroups ( p &amp;lt; 0.05), as revealed by both ELISA and Western blotting. The receiver operating characteristic (ROC) curve analysis showed that anti-GNA11 autoantibody could distinguish ESCC patients from normal controls with an area under the ROC curve (AUC) of 0.653, sensitivity of 10.96%, and specificity of 98.63% in the verification cohort and with an AUC of 0.751, sensitivity of 38.24%, and specificity of 88.82% in the validation cohort. IHC manifested that the expression of GNA11 can differentiate ESCC tissues with para-tumor tissues ( p &amp;lt; 0.05), but it cannot be used to differentiate different pathological grades and clinical stages ( p &amp;gt; 0.05). The mRNA expression of GNA11 in ESCC patients and normal controls was different with a bioinformatics mining with The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) data in Gene Expression Profiling Interactive Analysis (GEPIA). In summary, anti-GNA11 autoantibody has the potential to be a new serological marker in the diagnosis of ESCC.