Sapna Kumari

Wood is an essential renewable raw material for industrial products and energy. However, knowledge of the genetic regulation of wood formation is limited. We developed a genome-wide high-throughput system for the discovery and validation of specific transcription factor (TF)-directed hierarchical gene regulatory networks (hGRNs) in wood formation. This system depends on a new robust procedure for isolation and transfection of Populus trichocarpa stem differentiating xylem protoplasts. We overexpressed Secondary Wall-Associated NAC Domain 1s (Ptr-SND1-B1), a TF gene affecting wood formation, in these protoplasts and identified differentially expressed genes by RNA sequencing. Direct Ptr-SND1-B1-DNA interactions were then inferred by integration of time-course RNA sequencing data and top-down Graphical Gaussian Modeling-based algorithms. These Ptr-SND1-B1-DNA interactions were verified to function in differentiating xylem by anti-PtrSND1-B1 antibody-based chromatin immunoprecipitation (97% accuracy) and in stable transgenic P. trichocarpa (90% accuracy). In this way, we established a Ptr-SND1-B1-directed quantitative hGRN involving 76 direct targets, including eight TF and 61 enzyme-coding genes previously unidentified as targets. The network can be extended to the third layer from the second-layer TFs by computation or by overexpression of a second-layer TF to identify a new group of direct targets (third layer). This approach would allow the sequential establishment, one two-layered hGRN at a time, of all layers involved in a more comprehensive hGRN. Our approach may be particularly useful to study hGRNs in complex processes in plant species resistant to stable genetic transformation and where mutants are unavailable.

Background Constructing coexpression networks and performing network analysis using large-scale gene expression data sets is an effective way to uncover new biological knowledge; however, the methods used for gene association in constructing these coexpression networks have not been thoroughly evaluated. Since different methods lead to structurally different coexpression networks and provide different information, selecting the optimal gene association method is critical. Methods and Results In this study, we compared eight gene association methods – Spearman rank correlation, Weighted Rank Correlation, Kendall, Hoeffding's D measure, Theil-Sen, Rank Theil-Sen, Distance Covariance, and Pearson – and focused on their true knowledge discovery rates in associating pathway genes and construction coordination networks of regulatory genes. We also examined the behaviors of different methods to microarray data with different properties, and whether the biological processes affect the efficiency of different methods. Conclusions We found that the Spearman, Hoeffding and Kendall methods are effective in identifying coexpressed pathway genes, whereas the Theil-sen, Rank Theil-Sen, Spearman, and Weighted Rank methods perform well in identifying coordinated transcription factors that control the same biological processes and traits. Surprisingly, the widely used Pearson method is generally less efficient, and so is the Distance Covariance method that can find gene pairs of multiple relationships. Some analyses we did clearly show Pearson and Distance Covariance methods have distinct behaviors as compared to all other six methods. The efficiencies of different methods vary with the data properties to some degree and are largely contingent upon the biological processes, which necessitates the pre-analysis to identify the best performing method for gene association and coexpression network construction.

Abstract Betula L. (birch) is a pioneer hardwood tree species with ecological, economic, and evolutionary importance in the Northern Hemisphere. We sequenced the Betula platyphylla genome and assembled the sequences into 14 chromosomes. The Betula genome lacks evidence of recent whole-genome duplication and has the same paleoploidy level as Vitis vinifera and Prunus mume. Phylogenetic analysis of lignin pathway genes coupled with tissue-specific expression patterns provided clues for understanding the formation of higher ratios of syringyl to guaiacyl lignin observed in Betula species. Our transcriptome analysis of leaf tissues under a time-series cold stress experiment revealed the presence of the MEKK1–MKK2–MPK4 cascade and six additional mitogen-activated protein kinases that can be linked to a gene regulatory network involving many transcription factors and cold tolerance genes. Our genomic and transcriptome analyses provide insight into the structures, features, and evolution of the B. platyphylla genome. The chromosome-level genome and gene resources of B. platyphylla obtained in this study will facilitate the identification of important and essential genes governing important traits of trees and genetic improvement of B. platyphylla.

Common effluent treatment plants (CETPs) are used to collectively treat the effluents generated from different types of manufacturing industries of an industrial cluster before discharge so as to prevent the environment from the harmful effects of the effluents. There are several failure modes (FMs) that may lead to the failure of the CETP which may result in discontinuation of its operation. Thus, it is imperative to identify and estimate the criticality of the various FMs using failure mode and effects analysis (FMEA) in order to minimize the risk of failure of the CETP. This study identifies 24 potential FMs of the CETP, installed in humid subtropical regions, with the help of consensus among 5 experts who are the managers of CETPs installed at five different industrial regions of Delhi, the capital town of India. Subsequently, it applies a combined fuzzy based multi criteria decision making (MCDM) methods i.e. fuzzy analytic hierarchy process (FAHP) and fuzzy technique for order of preference by similarity to ideal solution (FTOPSIS) to derive rank of FMs. FAHP is applied to calculate the weights of three risk factors (RFs) i.e. occurrence (O) which refers to the chance of a failure cause occurring; severity (S) which measures the extent of effect of a failure cause on the system and the detection (D) which represents the chance of detecting the failure cause before the failure actually occurs. Then FTOPSIS is employed to determine rank of the FMs which signifies their criticality. The data required to implement FAHP and FTOPSIS are gathered from the experts in linguistic terms which are subsequently converted into equivalent triangular fuzzy numbers. Finally, sensitivity analysis is carried to ensure robustness of the ranking results produced by the combined FAHP and FTOPSIS method.

Rheumatoid arthritis (RA) is a chronic inflammatory condition primarily affecting the musculoskeletal system but can often involve other organ systems as well. Rheumatoid meningitis is a rare central nervous system (CNS) manifestation of RA characterized by pachymeningeal and leptomeningeal enhancement. Herein, we present a case of a 64-year-old male who presented with left lower extremity weakness and witnessed seizures. The diagnostic work-up, including lumbar puncture, brain MRI and meningeal biopsy ruled out malignancy and were consistent with the diagnosis of rheumatoid meningitis. The patient was discharged on high-dose steroids along with anti-seizure medications. On subsequent follow-up visits, the patient remained seizure-free.

Abstract We report here the genome-wide changes resulting from low N (N-W+), low water (N+W-)) and dual stresses (N-W-) in root and shoot tissues of two rice genotypes, namely, IR 64 (IR64) and Nagina 22 (N22), and their association with the QTLs for nitrogen use efficiency. For all the root parameters, except for root length under N-W+, N22 performed better than IR64. Chlorophyll a, b and carotenoid content were higher in IR64 under N+W+ treatment and N-W+ and N+W- stresses; however, under dual stress, N22 had higher chlorophyll b content. While nitrite reductase, glutamate synthase (GS) and citrate synthase assays showed better specific activity in IR64, glutamate dehydrogenase showed better specific activity in N22 under dual stress (N-W-); the other N and C assimilating enzymes showed similar but low specific activities in both the genotypes. A total of 8926 differentially expressed genes (DEGs) were identified compared to optimal (N+W+) condition from across all treatments. While 1174, 698 and 903 DEGs in IR64 roots and 1197, 187 and 781 in N22 roots were identified, nearly double the number of DEGs were found in the shoot tissues; 3357, 1006 and 4005 in IR64 and 4004, 990 and 2143 in N22, under N-W+, N+W- and N-W- treatments, respectively. IR64 and N22 showed differential expression in 15 and 11 N-transporter genes respectively, under one or more stress treatments, out of which four showed differential expression also in N+W- condition. The negative regulators of N- stress, e.g., NIGT1 , OsACTPK1 and OsBT were downregulated in IR64 while in N22, OsBT was not downregulated. Overall, N22 performed better under dual stress conditions owing to its better root architecture, chlorophyll and porphyrin synthesis and oxidative stress management. We identified 12 QTLs for seed and straw N content using 253 recombinant inbred lines derived from IR64 and N22 and a 5K SNP array. The QTL hotspot region on chromosome 6 comprised of 61 genes, of which, five were DEGs encoding for UDP-glucuronosyltransferase, serine threonine kinase, anthocyanidin 3-O-glucosyltransferase, and nitrate induced proteins. The DEGs, QTLs and candidate genes reported in this study can serve as a major resource for both rice improvement and functional biology.

In Populus, low nitrogen (LN) elicits rapid and vigorous lateral root (LR) proliferation, which is closely mirrored by corresponding transcriptomic changes. Using transcriptomic data, we built a genetic network encompassing a large proportion of the differentially regulated transcriptome. The network is organized in a hierarchical fashion, centered on 11 genes. Transgenic manipulations of only three of the 11 genes had a strong impact on root development under LN. These three genes encoded an F-box protein similar to Hawaiian Skirt (PtaHWS) and two transcription factors (PtaRAP2.11 and PtaNAC1). Up- and downregulation of the three genes caused increased and decreased root proliferation under LN conditions, respectively. The transgenic manipulations had a strong positive effect on growth under greenhouse conditions including increased shoot and root biomass. The three genes appeared to encompass a putative yet-unknown mechanism that underlies root development under LN. Specifically, the genes are predominantly expressed in roots and have a similar temporal response to LN. More importantly, transgenic manipulation for each of the three genes had a highly significant impact on the expression of the other two. The transgenic manipulations appear to also affect the expression of the regulatory miRNA (PtamiRNA164e) of one of the transcription factors (PtaNAC1), albeit in an opposite fashion. Consistent with a putative function of PtaHWS in proteasome degradation, treatment with proteasome inhibitor reversed the expression changes in the transgenic plants. The insights from this study will allow genetic modifications of root architecture for more efficient and dynamic nitrogen foraging in biofuel crops like poplar.

Abstract Background Multilayered hierarchical gene regulatory networks (ML-hGRNs) are very important for understanding genetics regulation of biological pathways. However, there are currently no computational algorithms available for directly building ML-hGRNs that regulate biological pathways. Results A bottom-up graphic Gaussian model (GGM) algorithm was developed for constructing ML-hGRN operating above a biological pathway using small- to medium-sized microarray or RNA-seq data sets. The algorithm first placed genes of a pathway at the bottom layer and began to construct a ML-hGRN by evaluating all combined triple genes: two pathway genes and one regulatory gene. The algorithm retained all triple genes where a regulatory gene significantly interfered two paired pathway genes. The regulatory genes with highest interference frequency were kept as the second layer and the number kept is based on an optimization function. Thereafter, the algorithm was used recursively to build a ML-hGRN in layer-by-layer fashion until the defined number of layers was obtained or terminated automatically. Conclusions We validated the algorithm and demonstrated its high efficiency in constructing ML-hGRNs governing biological pathways. The algorithm is instrumental for biologists to learn the hierarchical regulators associated with a given biological pathway from even small-sized microarray or RNA-seq data sets.

Background: Healthcare is a professional area bound to the ethical foundation of “do no harm.”, But in the current scenario, a rush to promote the curative scenario has led to the total downplay of the preventive aspect of care. The aim of this study was to assess the knowledge regarding nursing care bundle for the prevention of VAP among nursing officers before and after clinical teaching and to evaluate the effectiveness of clinical teaching. Methods: This pretest-post-test study was conducted on nursing officers working in the ICU of the All-India Institute of Medical Sciences, Bhopal, Madhya Pradesh. 100 nursing officers were enrolled in the study via convenience sampling technique. The self-structured tool was validated by 10 experts with a mean CVI value of 0.94. The reliability of the self-structured knowledge questionnaire was determined by the test-retest method and found to be 0.87. The collected data was analysed for frequency, mean, standard deviation, t-test, and association. Results: Findings showed that the mean knowledge score was 18.46±3.543 before intervention. After the intervention of video-assisted clinical teaching, a post-test was conducted, and the mean post-test knowledge scores was 25.07±2.801 at the p value <0.01. Knowledge of subjects about nursing care bundle for prevention of VAP was found to have a significant association with only educational qualification. Conclusions: This study's findings concluded that educational interventions are necessary for the enhancement of knowledge and better compliance of nursing officers with guidelines regarding the bundle of care for the prevention of ventilator-associated pneumonia.

The burden of Coronavirus Disease 2019 (COVID-19) has been identified as causing multiorgan damage. Respiratory compromise remains one of the most common presentations, but cardiac injuries, including myocardial injury, ischemia, and conduction abnormalities, are also becoming prevalent. We present a case of an 87-year-old male with a history of dementia, type 2 diabetes mellitus, hypertension, chronic kidney disease, and a left kidney transplant. He was hospitalized for respiratory distress and generalized tonic-clonic seizures. Upon admission, he was found to be bradycardic, with a heart rate of 27 beats per minute, and hypotensive, with a mean arterial pressure below 60 mmHg. An electrocardiogram (EKG) depicted high-grade atrioventricular block (AV block). A transvenous pacemaker was placed via femoral access, and he tested positive for COVID-19. A workup was conducted to rule out possible causes of bradycardia, such as hypothyroidism, ischemia, AV nodal blocking agents, and drug-induced bradycardia, but results were negative. His hospital stay was complicated by methicillin-resistant Staphylococcus aureus (MRSA) pneumonia, leading to empyema and bacteremia. Unfortunately, due to his critical condition, the family opted for comfort measures, and he died. Our clinical vignette highlights that cardiovascular complications in COVID-19 patients are associated with poor outcomes if not addressed. Conduction abnormalities in patients with normal cardiac structure and function are becoming more common in the setting of COVID infection. Assessment with serial EKGs and cardiac monitoring might be essential, as patients can develop AV blocks at any point in the course of the disease.

Perception of environmental cues and adaptation to changing environmental conditions are crucial for survival of sessile organisms like plants. This is even more important for woody perennial species like trees that can occupy a site for thousands of years. We have previously shown that under low nitrogen (LN), poplar trees display a vigorous and long-lasting root growth associated with global transcriptomic reprogramming and an activation of hierarchical genetic networks. Here we use computational analysis to better understand the network among the genes showing distinct chronological patterns of expression during the response. Our analyses confirm the previous findings, define new potential signaling pathways and the possible downstream targets of these signaling events.

Cognitive behavior therapy is probably the most well-known and the most practiced form of modern psychotherapy and has been integrated into highly structured package for the treatment of patients suffering from social phobia. The present case study is an attempt to provide therapeutic intervention program to a 27-year-old, unmarried Christian man suffering from social phobia. The patient was treated by using cognitive behavioral techniques. After 17 sessions of therapeutic intervention program, significant improvement was found. He was under follow-up for a period of 6 months and recovered to the premorbid level of functioning.

Abstract Background During the last decade, leadless pacemakers (LPMs) have turned into a prevalent alternative to traditional transvenous (TV) pacemakers; however, there is no consolidated data on LPM implantation in emergencies. Methods Digital databases were searched for this review and four relevant studies, including 1276 patients were included in this review with procedure duration, fluoroscopic time, major complications, and mortality as primary outcomes and pacing threshold, impedance, sensing of LPM, and hospital stay as secondary outcomes. Results Gonzales et al. and Marschall et al. showed the duration of the procedure to be 180 ± 45 versus 324.6 ± 92 and 39.9 ± 8.7 versus 54.9 ± 9.8, respectively. Zhang et al. demonstrated the duration of the procedure and fluoroscopy time to be 36 ± 13.4 and 11.1 ± 3.1, respectively. Similarly, Schiavone et al. exhibited intermediate times of implantation at 60 (45–80) versus 50 (40–65) and fluoroscopic times at 6.5 (5–9.7) versus 5.1 (3.1–9). Hospital stay was more with a temp‐perm pacemaker as compared to LPM and pacing parameters were not significantly different in all the studies. Conclusion For underlying arrhythmias, whenever appropriate, our review shows that LPMs may be a better option than temporary pacemakers, even as an urgent treatment.

Despite the fact that violence against women is a significant public health problem, there is a paucity of research into this area, and little is known about the extent to which women with psychiatric disorders are affected.The aim of the study was to assess and compare the severity of violence and quality of life of women with psychiatric disorders and normal controls.Based on purposive sampling technique, a sample consisting of 120 participants was selected from in-patient (female section) and outpatient services of the Ranchi Institute of Neuro-Psychiatry and Allied Sciences and Kanke Area. Both groups were matched on sociodemographic details. Normal controls were screened using General Health Questionnaire-12. The severity of violence against women scale and the revised Conflict Tactics Scale were used to assess the severity of violence, and World Health Organization Quality of Life (WHOQOL)-BREF scale was used for the assessment of the quality of life. Scales were scored as per their test manuals. Results were tabulated and compared using appropriate statistical tests.Women with psychiatric illness as well as normal controls faced various forms of symbolic violence equally. Women with psychiatric disorders faced significantly higher severity of physical assault, sexual coercion, and injury as compared to normal controls. Women with psychiatric disorders had significantly lower scores on WHOQOL BREF compared to normal participants.Women with psychiatric disorders suffered significantly higher severity of both physical and sexual violence and had significantly worse quality of life compared to normal controls.

It is well established that sovereign bond spreads vary with changes in financial conditions and political risk factors. What is less evident is the differential impact of political risk factors relative to the financial conditions of emerging market (EM) countries. This paper fills this gap by analyzing how changes in political risk overall and political risk components impact EM bond spreads and credit ratings. We find that improving political risk factors lowers sovereign bond spreads and improves credit rating outlooks. However, the effect varies by type of political risk. Also, the impact varies by type of EM country, with more of the impact of political risk components affecting higher financial risk countries.

Acute Encephalitis Syndrome (AES) is a serious, life-threatening disease, which is endemic in India and South-East Asia, where it adds to the strain on healthcare systems. It is a communicable disease that is caused by a virus attacking the brain tissues. The main objective of this study is to present a system that allows for monitoring, controlling, and preventing the spread of Encephalitis. The system is based on Hybrid-Fog-Computing (HFC) for real-time alert generation and notifies medical caregivers in case of abnormal geospatial distribution of infections. Deep learning, incorporating Multi-scaled Long Short Term Memory (MLSTM) and Convolutional Neural Network (CNN), is used to identify the health risk in terms of the Outbreak Severity Index (OSI). Our deep-learning model is integrated with Geographical Information System (GIS) tools to analyze the spatial distribution of disease-ridden areas and a Self-Organized Mapping (SOM) technique is used to visualize AES hotspots using spatial cluster analysis techniques including Getis-Ord Gi*. To determine the category of a patient's health state, a Bayesian classifier is used. A Spatio-temporal prediction model is used to coordinate medical resources toward successful health-oriented decision-making and effective knowledge delivery. The system is validated using real datasets, and the results are compared to various state-of-the-art prediction models. The proposed model outperforms other decision models for accuracy, precision, f-measure, and overall system stability.

The aim of this experiment was to investigate the effect of sodium fluoride (NaF) on the red blood cells (RBC) present in spleen. Twelve weeks old albino rats (Rattus norvegicus) of average weight 110g were randomly distributed into three groups of eight animals each. One group was given gavages of NaF with a single dose of 25mg/kg- bw/day and the other group was fed the same but with a higher dose of 50mg/kg-bw daily and the third group were kept as control. After 30 days of treatment with sodium fluoride, the animals were sacrificed by cervical dislocation. The abdominal cavity was opened and spleens were cut into pieces and fixed in carnoy's fixative for 3 hours for light microscopy. The heart was punctured to obtain blood for the analysis of hemoglobin percentage and blood count. It was found that in the sodium fluoride treated groups, rats showed a significant decrease in the hemoglobin percentage as compared to the control group. Also the red blood cell count was significantly decreased in the fluoride treated group in comparison to the controlled ones. These findings were also observed in the tissues of spleen. In comparison to the controlled ones the fluoride treated spleens of animals showed large number of dead cells of red blood cells. This decrease in hemoglobin percentage and reduced red blood cell count were more pronounced in the animals treated with higher dose of NaF. Although the spleen is graveyard of erythrocytes but the large destruction of RBC in fluoride treated rats as compared to the controlled ones as revealed by the light microscopy suggested the increased phagocytic activity of macrophages in spleen due to the fluoride toxicity. Thus from the above finding it may be concluded that the sodium fluoride toxicity may increase the phagocytic activity of macrophages to engulf more RBC in spleen and develop anemia. : Sodium Fluoride, Spleen, Hemoglobin, Erythrocytes, Anemia.

Deployment of the root system is highly sensitive to the levels and spatial distribution of nutrients like nitrogen. However, the genetic determinants of these sensing and deployment mechanisms are still poorly understood. Previously, using system approaches based on temporal changes in root transcriptome in relation to low nitrogen (LN), we have been able to identify a module that activates root production in poplar in response to LN conditions. Here, using comparative, gene ontology and expression analyses, we provide further evidence that the genes in this module are indeed involved in regulation of root development under LN. Better understanding of these modules will enable approaches for breeding for better nitrogen use efficiency through development of a more sensitive and plastic root system.

We present a new method, called the pixel array method, for approximating all solutions in a bounding box for an arbitrary nonlinear system of relations. In contrast with other solvers, our approach requires that the user must specify which variables are to be exposed, and which are to be left latent. The entire solution set is then obtained---in terms of these exposed variables---by performing a series of array multiplications on the $n_i$-dimensional plots of the individual relations $R_i$. This procedure introduces no false negatives and is much faster than Newton-based solvers. The key is the unexposed variables, which Newton methods can make no use of. In fact, we found that with even a single unexposed variable our method was more than 10x faster than Julia's NLsolve. Due to its relative simplicity, the pixel array method is also applicable to a broader class of systems than Newton-based solvers are. The purpose of this article is to give an account of this new method.

Since December 2019, the pandemic of coronavirus (CorV) is spreading all over the world. CorV is a viral disease that results in ill effects on humans and is recognized as public health concern globally. The objective of the paper is to diagnose and prevent the spread of CorV. Spatio-temporal based fine-tuned deep learning model is used for detecting Corv disease so that the prevention measures could be taken on time. Deep learning is an emerging technique that has an extensive approach to prediction. The proposed system presents a hybrid model using chest X-ray images to early identify the CorV suspected people so that necessary action can be taken timely. The proposed work consists of various deep learning neural network algorithms for the identification of CorV patients. A decision model with enhanced accuracy has been presented for early identification of the suspected CorV patients and time-sensitive decision-making. A SQueezeNet model is used for the classification of the CorV patient. An experiment has been conducted for validation purposes to register an average accuracy of 97.8%. Moreover, the outcomes of statistical parameters are compared with numerous state-of-the-art decision-making models in the current domain for performance assessment.

Women, the fair sex, are considered to be the weaker sex and one of the most powerless and marginalized sections of our society. Violence against women and girls continues to be a global epidemic. It is present in every country, cutting across boundaries of culture, class, education, income, ethnicity and age. A growing body of research studies indicates that 20% to 50% (varying from country to country) of women have experienced domestic violence. A multilayered strategy that addresses the structural causes of violence against women is needed. Strategies and interventions attempting to address violence against women should be guided by 5 underlying principles: Prevention, protection, early intervention, rebuilding the lives of victims/survivors and accountability. When planning interventions, there are a variety of stakeholders who should be borne in mind. Key areas for intervention include encouraging women empowerment; advocacy and awareness raising; education for building a culture of nonviolence; encouraging active participation of women in political system; resource development; direct service provision to victims, survivors and perpetrators; networking and community mobilization; direct intervention to help victims/survivors rebuild their lives; legal reform; monitoring interventions and measures; early identification of 'at risk' families, communities, groups and individuals; and data collection and analysis.

Multi-view ensemble learning (MEL) is new and fast growing area of machine learning. Here, the subsets of multiple features of same dataset are used for the learning and their prediction is finally ensembled. Vertical partition of dataset corresponds to the subset of the feature set is considered as view in a single-sourced dataset. View construction is an important task in MEL because the quantity of views and their quality leads to better performance of MEL. There is a well known graph partitioning technique, called graph coloring that assign the vertices with different color so that no two adjacent vertices have same color. This technique has various applications in different fields. The one of the applications of coloring is in clustering. In this paper, graph coloring is used for the creation of views in multiview ensemble learning. Here uncorrelated (dissimilar) feature clustering is done with the help of coloring. This paper presents a Graph coloring based views creation (GC-VC) method for automatic views creation in multi-view ensemble learning(MEL). To illustrate the performance of the framework, the five different classifiers have been employed namely Support Vector Machine (SVM), K-nearest neighbors (KNN), Naïve Baysian (NB), Neural Network (NN), Decision Tree (DT). The experiments have been performed on ten different datasets from the UCI repository. The results and their non-parametric statistical analysis of MEL have been done. A good enhanced classification accuracy has been achieved by the purposed MEL framework.

In the last few decades, tremendous change is observed in rainfall patterns which are majorly influenced by two major factors 1) climate change and 2) CO2 emission. Erratic rainfall patterns caused catastrophic effects on agriculture and human life in developing countries like Pakistan, where major economic growth is largely dependent on agriculture. The main objective of this study is to evaluate a performance different Machine learning algorithms for forecasting rainfall patterns using dimensionality reduction techniques on climate change indicators. For this purpose rainfall data was collected for Pakistan. Principle component analysis (PCA), Pearson correlation, and Greedy search algorithms were used for feature selection and the evolution of models was performed using Root Mean Square error (RMSE), Root Absolute Error (RAE), and Coefficient of determination metrics. Results show that features obtained using the Pearson correlation produced the least error and Bayesian linear regression performed with the highest accuracy followed by Neural Network regression.

With the exponential growth and intensification of the process of global integration, an individual health is gaining attention day by day. As the number of human mobility is growing, the threat of the outbreak of epidemic Airborne Infectious virus diseases (AIVD) is the main problem all over the world. As the AIVD has affected countries not only economically but also affected socially. Although much less fatal than Ebola and SARS Virus epidemics, the current coronavirus (COVID-19) and its variant has spread more quickly in people within a few days. So, the current study proposed a deep learning which is a subset of machine learning based framework for combating the AIVD such as COVID-19 in the field of global public health. This article represents systematically and comprehensively evaluates the study of AIVD from the perspective of healthcare research areas. It provides insights into the citation patterns, highly cited literature, core keywords, and network visualization of the analysis for the AIVD research.

Coronavirus disease 2019 (COVID-19) burden has been identified to cause multiorgan damage. Respiratory compromise is still one of the most common presentations, but cardiac injuries like myocardial injury, ischemia, and conduction abnormalities are also becoming prevalent. We present a case of an 87-year-old male with a history of dementia, type 2 diabetes mellitus, hypertension, chronic kidney disease, and a left kidney transplant hospitalized for respiratory distress and generalized tonic-clonic seizures. He was bradycardic to 27 beats per minute, hypotensive with mean arterial pressure(EKG) depicted a high-grade atrioventricular block (AV-block). The transvenous pacemaker was placed via femoral access and tested positive for COVID-19. Work-up was done to rule out possible causes of bradycardia, like hypothyroidism, ischemia, AV nodal blocking agents, and drug-induced bradycardia was negative. His hospital stay got complicated by methicillin-resistant staphylococcus aureus (MRSA) pneumonia leading to empyema and bacteremia. Unfortunately, being critically ill, the family opted for comfort measures, and he passed away. Our clinical vignette signifies cardiovascular complications in COVID-19 patients are associated with poor outcomes if not addressed. The conduction abnormalities in patients with intact cardiac structure and function are becoming more common in the setting of COVID infection. Assessment with serial EKGs and cardiac monitoring might be essential as patients can develop AV blocks at any point of the disease.

The study was done to look into the physicochemical properties of tamarind candy developed from blending different spices. The proximate analysis and the analysis of the antioxidants reveal that the candy contains reasonable amounts, which is beneficial for health. The sample was produced and stored at ambient temperature (43 0C) for 20 days. The colour of the sample was visually observed, and it was found that there was no difference in colour during accelerated storage conditions. The reading for the water activity of fresh candy was 0.344, and the result indicates that water activity was decreased as per the prolonged storage of the sample. The overall acceptability of tamarind candy after 20 days of accelerated storage was good. As per the study, the accelerated ageing test calculation indicates that a product shelf life of more than three months at ambient temperature is acceptable.

Nowadays many tall structures and high rise buildings are being built all around the world. Wind load is found to be dominant load in analysis of tall structures. The IS 875 (Part-3): 2015 deals with wind loads on different types of structures. Effect of wind is predominant on tall structures depending on location of the structure and height of the structure. Tubular structures, when subjected to lateral load such as wind load, the corner columns experience much higher axial load due to the shear lag phenomenon. Several studies investigated tall tubular structures for its shear lag responses. In this study, both tubular and realistic framed buildings have been studied for the understanding of relative shear lag effect subjected to wind loading. This study presents the shear lag effects on buildings with different terrain categories as per IS 875 (Part3), with varying plan aspect ratio using STAAD.Pro. Both tubular and framed models are analyzed with aspect ratio 0.5, 0.75, 1 and 1.167. Also the effect of height variation on amplified axial forces is studied by varying height from 16 to 40 storeys.

The classification performance of multi-view learning is better than the traditional machine learning algorithms as stated in state-of-art. In this research, using the graph coloring technique, clustering of dissimilar features has been done for view construction in multiview ensemble learning. Ten similarity measures (correlation, cosine, Euclidean, Minkowski, Manhattan, Seuclidean, Sqeuclidean, Chebyshev, Canberra, and Bray Curtis) have been applied for the graph coloring-based view-construction approach and their impact is analyzed using the k-Nearest Neighbors (KNN), Support Vector Machine (SVM), and Naive Bayesian (NB) classifier over the eight different datasets. Based on overall performance, the research recommends the correlation distance for the view-construction method. The proposed method Graph Coloring based View-Construction methods (GC-VC) has been compared with state-of-art methods. The analysis of results and their statistical analysis show that the GC-VC method has performed significantly better than other methods.

Water is indispensable and one of the precious natural resource of this planet. Ground water is an important source of water supply throughout the world. Fluoride poisoning arises from drinking fluoride rich ground water. Our present experiment was designed to study the efficacy of NaF on the splenocytes and its role in immunogenic response. The albino rats were taken for the experiment and randomly assigned into three groups of each of eight animals. First group and the second group were fed with lower (25mg/kg-bw/day) and higher (50mg/kg-bw/day) doses of NaF for 60 days and the third group rats were kept as control. Later on the animals were killed by cervical dislocation and spleens were dissected out and processed for light microscopy and scanning electron microscopy. In the light microscope it was observed that fluoride causes shrinkage in the white pulp nodule and degeneration of red pulp. Scanning electron microscope also revealed the degeneration of many splenocytes in the fluoride treated group. The changes were more prominent in the rats treated with the higher dose of NaF. The finding suggests that NaF may play a key role in the activity of Ca 2+ ATPase and adversely affect the cell-cell and cell-matrix adhesion of splenocytes. It was concluded that NaF may adversely affect the structure and function of the spleen particularly due to the apoptosis of splenocytes and degeneration of red pulp in the rat leading to the reduced immunogenic response.

Cross-border tunnel detection has been the common and the most important concern for the nation because of its usage by terrorists, illegal immigrants, smugglers, prisoners. For this there is a need to locate, map, monitor and detect the tunnel. Various techniques used in this process from electromagnetic methods to RADAR to sensors. The first method which was used in 1990s as a subject of tunnel detection and was successful in detecting it at the experimental tunnel site in Otay Mesa, San Diego. From the various researches it has been seen that electromagnetic methods and seismic methods are mostly used methods. In this paper, there is discussion as well as review of various researchers and technology which was used and is still in used. It is divided into sections such as introduction, technology description, comparison table along with discussion and conclusion.

Handwritten Identification is an ability of the computer to receive and translate the intelligible handwritten text into machine-editable text.It is classified into two types based on the way input is given namely: off-line and online.In Off-line handwritten recognition, the input is given in the form of the image while in online input is entered on a touch screen device.The research on off-line and online handwritten Sindhi character identification is on its very initial stage in comparison to other languages.Sindhi is one of the subcontinent's oldest languages with extensive literature and rich culture.Therefore, this paper aims to identify off-line Sindhi handwritten characters.In the proposed work, major steps involve in characters identification are training and testing of the system.Training is performed using a feed-forward neural network based on the efficient accelerative technique, the Back Propagation (BP) learning algorithm with momentum term and adaptive learning rate.The dataset of 304 Sindhi handwritten characters is collected from 16 different Sindhi writers, each with 19 characters.The novelty of proposed work is the comparison of the recognition rate for the single character, two characters and three characters at a time.Results showed that the recognition rate achieved for a single character is more than the recognition rate of multiple characters at a time.

Abstract We report here the genome-wide changes resulting from low N (N-W+), low water (N+W-) and dual stresses (N-W-) in root and shoot tissues of two rice genotypes, namely, IR 64 (IR64) and Nagina 22 (N22), and their association with the QTLs for nitrogen use efficiency. For all the root parameters, except for root length under N-W+, N22 performed better than IR64. Chlorophyll a, b and carotenoid content were higher in IR64 under N+W+ treatment and N- and W- stresses; however, under dual stress, N22 had higher chlorophyll b content. While nitrite reductase, glutamate synthase (GS) and citrate synthase assays showed better specific activity in IR64, glutamate dehydrogenase showed better specific activity in N22 under dual stress; the other N and C assimilating enzymes showed similar but low specific activities in both the genotypes. A total of 8926 differentially expressed genes (DEGs) were identified compared to optimal (N+W+) condition from across all treatments. While 1174, 698 and 903 DEGs in IR64 roots and 1197, 187 and 781 in N22 roots were identified, nearly double the number of DEGs were found in the shoot tissues; 3357, 1006 and 4005 in IR64 and 4004, 990 and 2143 in N22, under N-W+, N+W- and N-W- treatments, respectively. IR64 and N22 showed differential expression in 15 and 11 N-transporter genes respectively, under one or more stress treatments, out of which four showed differential expression also in N+W- condition. The negative regulators of N- stress, e.g., NIGT1 , OsACTPK1 and OsBT were downregulated in IR64 while in N22, OsBT was not downregulated. Overall, N22 performed better under dual stress conditions owing to its better root architecture, chlorophyll and porphyrin synthesis and oxidative stress management. We identified 12 QTLs for seed and straw N content using 253 recombinant inbred lines derived from IR64 and N22 and a 5K SNP array. Three QTLs co-localized on chromosome 6 spanning 417 Kbp and comprising of 31 genes, of which, five were DEGs including two UDP-glucuronosyl/UDP-glucosyltransferase family proteins. The DEGs, QTLs and candidate genes reported in this study can serve as a major resource for both rice improvement and functional biology.

In current cellular networks base stations (BSs) usually perform independent scheduling without coordinating the resource allocation among different cells.This, however, often leads to high interference levels in cellular networks operating with universal frequency reuse, such as the 3GPP UTRAN Long Term Evolution (LTE).Coordinated scheduling between different BSs may mitigate this problem by taking interference from and to nearby BSs into account in order to avoid high interference situations.For uplink in multiuser major issue to maintain throughput of the system.To solve this problem, a channel estimation method for SC-OFDM under the framework of compressive sensing (CS) is proposed in this paper.Firstly, by exploiting the signal.(SP)algorithm to utilize a very small amount of frequency domain pilots embedded in the SC-OFDM block for the exact channel estimation.Moreover, the obtained auxiliary channel information is adopted to reduce the complexity of the classical SP algorithm..

Three-way stopcocks (3WSCs) are open systems used on intravenous tubing. Split septums (SSs) are closed systems with prepierced septums. Single-use prefilled flushing devices (SUFs) carry a lower risk of contamination than standard intravenous flushing. 3WSC and standard flushing are widely used in developing countries. This is the first randomized clinical trial (RCT) to compare rates of central line–associated bloodstream infection (CLABSI) between patients using an SS + SUF and those using a 3WSC.An RCT with 1096 patients in 5 adult intensive care units was conducted between April 2012 and August 2014 to evaluate their impact on CLABSI rates. Centers for Disease Control and Prevention/National Healthcare Safety Network definitions were applied and International Nosocomial Infection Control Consortium methodology were followed.The study cohort included 547 patients and 3619 central line (CL)-days for the SS + SUF group, and 549 patients and 4061 CL-days for the 3WSC group. CLABSI rates were 2.21 per 1000 CL-days for SS + SUF and 6.40 per 1000 CL-days for 3WSC (relative risk, 0.35; 95% confidence interval [CI], 0.16-0.76; P = .006). The SS + SUF group had significantly better cumulative infection-free catheter survival compared with the 3WSC group (hazard ration, 0.33; 95% CI, 0.15-0.73; P = .006). Using an SS + SUF represents savings of $402.88 and an increase in quality-adjusted life years of 0.0008 per patient. For each extra dollar invested in an SS + SUF, $124 was saved.The use of SS + SUF is cost-effective and associated with a significantly lower CLABSI rate compared with the use of 3WSC.

E-Commerce is fastest growing sector over the last decade. Firms across the globe adopted E-commerce in their operations for sure profit. E-Commerce stands for electronic commerce, buying and selling through electronic channels like internet, mobiles, tablets, etc. E Commerce just not includes buying and selling via networks but it also includes pre and post sale activities. The success of E-Commerce is totally depends upon strategies made by sellers. This paper gives an overview of future prospects of E-Commerce in India and builds a vision of future. It also deals with the Future challenges and opportunities prevailing in India and how rapidly e commerce sector is growing.

The output of ML-hGRN operating over lignocellulosic pathway built with the bottom-up GGM algorithm. Table S2. The output of regulatory layer over lignocellulosic pathway identified by ARACNE algorithm. Table S3. The ML-hGRN operating over human pluripotency renewal pathway built with the bottom-up GGM algorithm. Table S4. The output of regulatory layer over human stem cell renewal pathway identified by ARACNE algorithm. Table S5. Comparison of bottom-up GGM algorithm with ARANCE using yeast synthetic data. (XLSX 232 kb)

Drinking water is one of the largest sources of fluoride. Excessive intake of fluoride results in all the three forms of fluorosis viz. Dental fluorosis, skeletal fluorosis and Non-skeletal fluorosis. Our present experiment was designed to study the non-skeletal fluorosis. The experimental animal Rattus norvegicus were randomly distributed into two groups of eight animals each. One group was given gavages of NaF at 50mg/kg-bw/day for 60 days along with the diet and the other group was paired fed which served as control. After 60 days the animals of both the group were sacrificed by cervical dislocation, the abdominal cavity was opened and spleens were dissected out. The tissue was further processed for light microscopy, transmission electron microscopy and scanning electron microscopy and analysed. Both light microscopic and electron microscopic observations showed damage to the reticular cells and reticular fibers of the spleen in the fluoride treated group. This may adversely affect the structure and function of the spleen grossly inhibiting the antigenic reactions resulting into the declination of the immune power.

Fluoride, a strong electronegative anion has a disruptive effect on various tissues in the body. The rats (Rattus norvegicus) were fed with Sodium fluoride (NaF) at 25mg/kg‐bw and 50mg/kg‐bw daily for 60 days. The abdominal cavity was opened after cervical dislocation of rats and spleen was dissected out. The organs were cut into pieces and processed for light and transmission electron microscopy. Animals treated with fluoride showed the degenerative changes in the morphology of spleen. The photomicrographs showed that the capsule and trabeculae were broken at many places, many large spaces occured in between the concentric array of cells in follicles of white pulp and the cells of PALS infiltered in the red pulp area. The electron micrographs revealed the abnormal shaped nucleus with swollen and enlarged mitochondria and degenerated cristae in the cytosol. The above results suggests that the spleen treated with fluoride might loss or reduce the ability of contraction and adversely affect the immuogenicity by not synthesizing the ATP required during the clonal expression of B‐cells.

Environmentally friendly Friedel-Craft diacylation of aromatic ring as well as sydnone ring has been used for a rapid, efficient, clean and environmentally benign exclusive synthesis of a series of 4-acyl-3-(3,5-disubstituted) phenyl sydnones with excellent yields under microwaves irradiation. The results are compared with conventional method. Structural assignments are based on physical, analytical and spectroscopic data (IR, 1 H-NMR & 13 C-NMR).

Lipases are very important industrial enzymes. They are used in number of industries including paper, detergent, food, dairy, pharmaceutical, diagnostic centre, cosmetic etc.  By considering immense applications of lipases, an attempt was made to optimize lipase production in submerged fermentation (SmF) from a fungal isolate. In the present study, various parameters such as carbon source, nitrogen source, pH, temperature and incubation time were optimized for a lipolytic fungal strain named as S2St1, previously isolated from mustard field soil sample, for lipase production in SmF. Maximum activity of lipase (157.28±4.26 U/ml/min) was obtained at 28 oC, after 7 days of incubation in the medium containing mixture of fructose (0.5% w/v) + coconut oil (1% v/v) as carbon source and peptone (4% w/v) + (NH 4 ) 2 SO 4 (0.1% w/v) as nitrogen source. The present study reveals that coconut oil was found to be best among other lipid carbon source for lipase production, which indicates that presence of inducer (oil) is required for maximum lipase activity. Lipase activity was also found better at 50 oC (65.77±5.39 U/ml/min), indicating superior thermo-stability of fungal strain for lipase production.

An important role of management is to help make work more satisfying and rewarding for employees and to make employees' motivation consistent with organizational objectives.With the diversity of contemporary workplaces, this is a complex task.Many factors, including the influences of different cultures, affect what people value and what is rewarding to them.From a manager's perspective, this study tries to understand what prompts people, what influences them, and why they persist in particular actions.This study also intends to evaluate motivation of employees in the organization.A good motivational program procedure is essential to achieve goal of the organization.If efficient motivational programmers of employees are made not only in this particular organization but also in any other organization, the organizations can achieve the efficiency also to develop a good organizational culture and the attainment of organizational goals at large.

<div>Redox titrations are the titrimetric method developed to know the</div><div>concentration of the analyte by creating redox reaction among titrant and analyte. The</div><div>basic principle involved in the redox titration is the oxidation-reduction reaction, in</div><div>which electron transfer from one reactant to another reactant takes place. Oxidation</div><div>means loss of electron and reduction means gain of electron. These must happen at the</div><div>same time, when a substance loses electrons, there must be some other substance to</div><div>accept those electrons. The main applications associated with redox titrations are</div><div>determining the reduction potential of sHdrA flavin from Hyphomicrobium</div><div>denitrificans, water in non-aqueous solutions, dissolved oxygen in water and</div><div>determination of alcohol content in the whiskey bottles, etc.</div>

<div>Analytical chemistry, a branch of chemistry, deals with the analysis of</div><div>substances. Identification of the constituents from the mixture or substance is called</div><div>qualitative analysis while Quantitative Analysis deals with determining the purity of</div><div>the constituents present in the mixture. This is also known as assay method. Various</div><div>methods like volumetric analysis, gravimetric analysis, polarimetry, refractometry,</div><div>photometry, fluorimetry, electrochemical methods, chromatographic methods and</div><div>biological methods comes under the category of quantitative analysis. Volumetric</div><div>titrations are the elementary procedures applied in the life sciences, pharmaceutics,</div><div>industrial analysis, water pollution and clinical chemistry and are used to determine the</div><div>amount of analyte with the standard solution. Main advantages of these methods are</div><div>cost-effective, rapid and simple, while disadvantages include pH, temperature, and</div><div>humidity sensitivity, indicator requirement, occurrence of human error, etc.</div>

This paper analyses the contribution of Pakistani female researchers in the field of ICT using the bibliometric analysis method. It helps to observe a female researcher’s productivity and assists in identifying problems, such as the need to empower female researchers in ICT. No such work has been conducted yet on gender-based bibliometric analysis in Pakistan. In this paper, bibliometric data of 300 female researchers were extracted from Google Scholar profiles. With the help of this study, the most prestigious female researcher in the field of ICT from Pakistan was analysed based on the h-index. Also, the most active ICT institute in terms of female research productivity (the number of publications) was observed. Furthermore, the annual growth rate of 15 years (2006–2021) of female-led research is calculated and is analysed that the maximum annual growth rate of research productivity (140.965) was in 2010. Additionally, the active contribution of female researchers in most trending research areas of ICT was found by generating the co-occurrence network diagram using 3,640 research paper titles. According to the co-occurrence network diagram, the most popular research areas are image classification and prediction, Internet of Things (IoT), wireless sensor network and smart grid, fuzzy logic and deep learning.

Nonsyndromic cleft lip & palate is a congenital deformity of multifactorial origin.Various etiologic candidate genes have been reported with conflicting results, according to the race and population studied.Numerous efforts have been made to understand the etiology of cleft/palate so as to predict its occurrence and thus enable its prevention.The FGF regulation pathway also plays a major role in craniofacial development.FGFR1, FGFR2, FGFR3, FGF10 and FGF18 are expressed during the various stages of secondary palate development.Thus their inactivation leads to cleft palate.This study was done to evaluate the association of FGFR1 and FGF10 gene variants with nonsyndromic cleft lip and palate.DNA samples of 25 subjects with nonsyndromic cleft lip and palate and 25 unrelated controls, collected from the department were used for the study.The extracted DNA samples were subjected to Polymerase chain reaction later subjected to DNA sequencing.The results were documented in the form of electropherogram.The results indicated that for FGFR1 gene (rs13317), genotype CC (P=0.02) was statistically significant and FGF 10 gene (rs1448037), genotype AA (P< 0.001) was highly statistically significant.Thus suggesting a strong association between FGFR1 and FGF10 with NSCLP.

Objectives: Atherosclerosis, the key pathology for cardiovascular disease, is thought to be a disease of affluent people. This study was designed to estimate risk factor prevalence of atherosclerosis in different socioeconomic classes. Methodology: Questionnaire-based data was obtained from 395 subjects, divided into three socioeconomic classes according to monthly income (high income, HI: &gt; 100,000 PKR; Middle income, MI: 50,000 – 100,000 PKR; Low income, LI: &lt; 20,000 PKR). Data was collected with regard to hypertension, diabetes, hypercholesterolemia, obesity, smoking, tobacco use, physical inactivity, and dietary habits. Results: Number of participants was: HI – 115; MI – 119; LI – 161. Mean age of cohort was 35.81 ± 14.29. The three classes showed no significant difference with regard to age and body mass index, BMI (p = 0.055, 0.222 respectively). A statistically significant difference was present with regard to lack of exercise, hypercholesterolemia, hypertension (HTN) and tobacco use (p&lt;0.001, p=0.025, p=0.005, p&lt;0.001 respectively). No significant difference was observed with regard to smoking and diabetes (p = 0.326, .424 respectively). Prevalence of ≥ 3 risk factors was: HI – 12.17%; MI – 14.28%; LI – 11.17%. Conclusion: Low, middle and high socioeconomic classes showed HTN, lack of exercise and hypercholesterolemia as the most prevalent risk factors respectively. Middle class showed most clustering of risk factors followed by high and low classes. Lack of exercise was the most prevalent risk factor overall, most pronounced in middle class.

Objective: To determine the frequency of correct fetal weight estimation by clinical and ultrasound methods in pregnant women. Study Design: A cross-sectional study. Place and Duration: Department of Obstetrics and Gynaecology, Nishtar Hospital Multan, From February 2021 to July 2022. Methodology: A total of 383 women with singleton pregnancy, gestational age between 37 to 40 weeks and who underwent labor induction or elective cesarean section were included. Fetal weight estimation was done by clinical and ultrasound methods in pregnant women. Following delivery, “actual birth weight” of neonate was measured and data recorded in the shape of correct fetal weight estimation by both studied methods. Results: In a total of 383 women, the mean age was 29.50±2.22 years ranging between 18-35 years while the mean gestational age was 38.09±0.91 weeks. The mean mother’s weight was 70.19±10.56 kg, mean clinical weight estimation 3127.03±561.38 grams, mean ultrasound weight estimation 3137.25±658.05 grams and mean actual weight was 3157.63±648.33 grams. Correct clinical weight estimation was reported in 49.6% cases while correct ultrasound weight estimation was noted in 80.9%. Practical Implications: Accuracy in fetal weight estimation can be achieved by applying Dare’s method in the clinical setting. Conclusion: Fetal weight estimation adopting Dare's formula was found to be comparable to ultrasound estimation for the prediction of actual birth weight within 10%. Keywords: Fetal weight, gestational age, singleton, ultrasound.

Technology development plays a vital role in every aspect of life, whether it is in the medical domain or any other era. In the present scenario, scientists, researchers, and healthcare experts are still looking for a new technology against Air-Borne Disease(ABD) over the world. The use of Artificial Intelligence (AI) has encouraged researchers by providing a modern approach for combating Air-Borne diseases. The current study reviews approximately 145 papers for the literature review that insights AI-based application technology to prevent ABD. For this purpose, the current study discusses ideal epidemiology study, early disease diagnosis, and its progression concerning ABD. Although the reviewed AI application-based methods for ABD control are promising, this review suggests research that integrates ML advances should be done. ML techniques may lead to success in controlling the ABD if these suggestions are implemented. Finally, this study addresses the obstacles and opportunities for future research.

During this Covid-19-time number of patients in hospital are increased. The covid-19 patients are mainly of two types one who has a serious condition and the other who has a mild covid-19 symptom. On the other way, the patients who have very serious conditions generally have all facilities, they have doctors around them and other medical staff also there to take care of the situation, but the patients who have not very serious conditions are generally isolated in their home, a problem with this home isolated patients are they do not consult with doctor day to day and what happens if patients condition become serious basically this paper is going to solve this two problem and also monitoring the patients while getting different data like a heartbeat, SpO2, body temperature, etc. along with that we used a location sharing and nearest hospitals identification. Here we design IoT, GSM/GPS-based system through which we send the patients' health data directly to the hospital and if the patients' conduction becomes serious then it sends an alert to the hospital along with the patient's location and it also sends the hospital location to the patients.

Nutrition has an important role in anemia and of all the nutrients involved, iron is the most crucial and regarding dietary causes of anemia, the most common kind of anemia includes iron deficiency anemia and one of the most common is an inadequate intake of iron in the diet. The deficiency may be latent or patent. It may be responsible for repeated infections and interfere with the child's psychomotor development. The disease is most often due to a low intake of dietary iron, and it can be prevented by supplementing the mothers during pregnancy and by an adequate diet. Aim & Objectives: To assess knowledge and practices regarding prevention of nutritional anemia among mothers of under-five children. Methods: The study adopted descriptive research design and was conducted at selected villages of Sirmour District, H.P. A total of 100 mothers were selected by convenient sampling technique. A structured knowledge questionnaire was used to assess knowledge and the structured questionnaire on self-reported practices was used to assess the practices regarding prevention of nutritional anemia. Results: Data analysis was done by descriptive and inferential statistics. The study results showed that 71% respondents had the moderately adequate knowledge, 22% of respondents had inadequate knowledge and remaining 7% respondents had the adequate level of knowledge and 98% of mothers had good practices and remaining 2% were had poor practices. Correlation coefficient indicates that weak positive linear correlation between knowledge and practice score as the value of p= 0.097 and r= .336. Chi-square test indicates that there is the significant association between age of mother, dietary habits, sources of information and knowledge score, the highly significant association between education of mother, an occupation of mother, education of father and knowledge score. Chi-square test indicates that no significant association between practice score and selected demographic variables. Conclusion: The results of the study suggest that there was the adequate level of knowledge and good practices regarding prevention of nutritional anemia help to reduce the chances of nutritional anemia among under-five children.

Background: Zinc (Zn), a heavy metal present in aquatic environment, has toxic effect on fishes. Present study was to assess toxicity of Zinc salt (ZnSO4) on total erythrocyte count (TEC), haemoglobin (Hb) content (g/dl) and haematocrit value (PCV%) of blood of freshwater mud eel Amphipnous cuchia. Methods: Live fishes collected from ponds were acclimatized in laboratory. TEC, Hb content and PCV% of blood samples collected after 15, 30, 60 and 90 days, of control fishes and fishes exposed to low (0.5mg/l) and high (1mg/l) concentrations of ZnSO4, were determined by standard methods. Result: TEC, Hb content and PCV% varied respectively from 2.48 x 106/mm3 to 2.70 x 106/mm3, 12.02 g/dl to 12.30 g/dl and 28.50 % to 33.60 % in fishes in low and from 2.36 x 106/mm3 to 2.60 x 106/mm3, 11.82 g/dl to 12.20 g/dl and 26.20 % to 31.50 % in fishes in high concentration of ZnSO4 solution, showing decreasing trend in all three blood parameters vis-a-vis their control values viz. TEC (2.74 x 106/mm3), Hb content (12.60 g/dl) and PCV% (34.50 %), decrease being more prominent in fishes exposed to high than those to low concentration. The depletion in these blood parameters may be attributed to the haemotoxic characteristics of Zinc (Zn).

The developmental processes and functions of an organism are controlled by the genes and the proteins that are derived from these genes. The identification of key genes and the reconstruction of gene networks can provide a model to help us understand the regulatory mechanisms for the initiation and progression of biological processes or functional abnormalities (e.g. diseases) in living organisms. In this dissertation, I have developed statistical methods to identify the genes and transcription factors (TFs) involved in biological processes, constructed their regulatory networks, and also evaluated some existing association methods to find robust methods for coexpression analyses. Two kinds of data sets were used for this work: genotype data and gene expression microarray data. On the basis of these data sets, this dissertation has two major parts, together forming six chapters. The first part deals with developing association methods for rare variants using genotype data (chapter 4 and 5). The second part deals with developing and/or evaluating statistical methods to identify genes and TFs involved in biological processes, and construction of their regulatory networks using gene expression data (chapter 2, 3, and 6).

Particulate matter is the pollutant generally viewed as most unsafe to human wellbeing. PM comprises a combination of liquid and solid particles suspended in the atmosphere. Its minuscule size permits the particles to enter the circulation system by means of respiration, causing asthma and heart disease. COVID-19 has been declared as a Public Health Emergency of International Concern by WHO on 30 th January 2020. The objectives of the present study include air quality (with respect to PM2.5 and PM10) monitoring at pre-selected locations during and post COVID- 19 phase, comparative assessment of air quality parameters PM2.5 and PM10 concentrations in Delhi during and post COVID-19. To conduct this study the station for air quality monitoring selected is near Hauz Khas metro station, Delhi. Total 4 locations are selected around CPCB Air pollution monitoring station, Hauz Khas. PM sampling has been done for 12 continuous days. The dataset of the time frame (March and April of 2020) of the lockdown phase is collected from CPCB and compared with the dataset of the same time frame (March and April 2021) using excel software. The pollution level drastically increases after the lockdown phase according to present observation and improvement in air quality could not last long after the reopening of industries and vehicular activities according to this investigation.

Additional file 1: Supplementary Table 1: All differentially expressed genes identified under N-W+, N + W- and N_W- treatments compared to optimal input supply (N + W+) in root and shoot tissues of IR64 and N22. Supplementary Table 2: Comparison of the expression of N transporters, sensors and regulators under various stress treatments in IR64 and N22. Supplementary Table 3: Comparison of the expression of known transcription factors (TFs) under various stress treatments in IR64 and N22. Supplementary Table 4: Comparison of the expression of novel (not annotated) genes under various stress treatments in IR64 and N22. Supplementary Table 5: Comparison of plant hormone metabolism genes and their receptors under various stress treatments in IR64 and N22. Supplementary Table 6: Comparison of the expression profile of the genes and QTLs known for Nitrogen use efficiency. Supplementary Table 7: Details of primers designed for validation of the DEGs identified from transcriptome analysis by qPCR assay. Supplementary Table 8: SNPs in the two major QTL hotspot regions identified on chromosomes 1 and 6. Supplementary Table 9: Relative water content (%) under optimal and all the three stress conditions measured in an independent experiment. Supplementary Table 10: DEGS identified in genes encoding for major enzymes involved in C and N skeleton. Supplementary Table 11: Details of variations in cis elements between IR64 and N22 genotypes for 20 N transporter, N regulator, TOND1, Dof genes and candidate genes identified from the major QTLs mapped in the present study. Supplementary Table 12: miRNAs in the candidate genes present in interval of the QTL hotspot region identified on chromosome 6. Supplementary Table 13: Comparison of expression of DE ABA related genes under different stress treatments in two rice genotypes N22 and IR64.

Fifty strains in E. coliwere isolated from the liverand intestinal samples of fifty healthy Japanese quails in Poultry Fanns of Patna. Altogether 18 serotypes of E. coli such as 06, 08, 09, 012, 018, 020, 032, 036, 033, 054, 0103, 0106, 0109, 0111, 0132, 0153, 0157 and 0171 from 48 strains were obtained whereas three were Wltypable and one was rough strain. Interspecies transfer of several serotypes of E. coli may occur between poultry and quail. The public health significance of isolated E. coli serotypes have been discussed.

Altogether 80 samples, 40 gills and 40 intestines from 40 Rohu fishes were collected from different fish markets of Patna for isolation of staphylococci. The samples were inoculated first in nutrient broth and subculture was made on blood agar and Baired & Parker agar plates and incubated at 37°C for 24 hrs. Typical shiny black colonies with narrow white margin surrounded by a zone of clearing were procured and subjected to coagulase test. Gills and intestines revealed Staphylococci spp. in the percentage of 62.50 and 50.00 with an overall prevalence of 56.25 per cent. Out of these, Staph. aureus (coagulase positive) was obtained from gills (27.50%) and intestines (20.00%). Public health significance of this organism has been discussed.

A total of 52 E. coli were isolated from, liver and intestinal sample of 50 Japanese quails of patna. In vitro drug sensltlvlty test of E. call showed highest senstivity to amikacin, ceftriaxone, cephotaxine, cephalexin, ciprotloxacin, pefloxacin and norfloxacin. Most E. coli were resistant to ampicillin, chloramphenicol and tetracycline. Multiple drug resistance was common. 21.15% E. coli were resistant to one drug, followed by 28.84% to two drugs, 36.53% to three drugs, 9.61% is! four drugs and 3.84% were resistant against five drugs.