Shubham Pandey

Follicular lymphoma (FL) is the most frequent indolent lymphoma and is characterized by the accumulation of germinal center-derived malignant B cells engaged in a bidirectional crosstalk with their supportive microenvironment in invaded lymph nodes (LNs) and bone marrow (BM). T follicular helper (TFH) cells and infiltrating stromal cells have been shown to favor FL B-cell growth, but the mechanisms of their protumoral effect and how the LN/BM microenvironment is converted into a lymphoma-permissive cell niche remain poorly understood. We demonstrated here that FL-infiltrating LN and BM stromal cells overexpressed CXCL12 in situ. Interleukin-4 high (IL-4hi) FL-TFH cells, unlike FL B cells themselves, triggered CXCL12 upregulation in human stromal cell precursors. In agreement, expression of CXCL12 was associated with IL-4 expression and signaling within the FL BM and LN niches. This IL-4/CXCL12 axis was amplified in activated lymphoid stromal cells as shown in our in vitro model of human lymphoid stroma differentiation and in an inducible mouse model of ectopic lymphoid organ formation. Finally, CXCL12 triggered primary FL B-cell activation, migration, and adhesion, a process antagonized by BTK and PI3K inhibitors. These data identified the IL-4/CXCL12 loop as a previously unrecognized pathway involved in lymphoid stroma polarization and as a potential therapeutic target in FL patients.

Genome engineered natural killer (NK) cell therapies are emerging as a promising cancer immunotherapy platform with potential advantages and remaining uncertainties. Feeder cells induce activation and proliferation of NK cells via cell surface receptor-ligand interactions, supported by cytokines. Feeder cell expanded NK cell products have supported several NK cell adoptive transfer clinical trials over the past decade. Genome engineered NK cell therapies, including CAR-NK cells, seek to combine innate and alloreactive NK cell anti-tumor activity with antigen specific targeting or additional modifications aimed at improving NK cell persistence, homing or effector function. The profound activating and expansion stimulus provided by feeder cells is integral to current applications of clinical-scale genome engineering approaches in donor-derived, primary NK cells. Herein we explore the complex interactions that exist between feeder cells and both viral and emerging non-viral genome editing technologies in NK cell engineering. We focus on two established clinical-grade feeder systems; Epstein-Barr virus transformed lymphoblastoid cell lines and genetically engineered K562.mbIL21.4-1BBL feeder cells.

Matrix detachment triggers anoikis, a form of apoptosis, in most normal epithelial cells, while acquisition of anoikis resistance is a prime requisite for solid tumor growth. Of note, recent studies have revealed that a small population of normal human mammary epithelial cells (HMECs) survive in suspension and generate multicellular spheroids termed ‘mammospheres’. Therefore, understanding how normal HMECs overcome anoikis may provide insights into breast cancer initiation and progression. Primary breast tissue-derived normal HMECs were grown as adherent monolayers or mammospheres. The status of AMP-activated protein kinase (AMPK) and PEA15 signaling was investigated by immunoblotting. Pharmacological agents and an RNA interference (RNAi) approach were employed to gauge their roles in mammosphere formation. Immunoprecipitation and in vitro kinase assays were undertaken to evaluate interactions between AMPK and PEA15. In vitro sphere formation and tumor xenograft assays were performed to understand their roles in tumorigenicity. In this study, we show that mammosphere formation by normal HMECs is accompanied with an increase in AMPK activity. Inhibition or knockdown of AMPK impaired mammosphere formation. Concomitant with AMPK activation, we detected increased Ser116 phosphorylation of PEA15, which promotes its anti-apoptotic functions. Inhibition or knockdown of AMPK impaired PEA15 Ser116 phosphorylation and increased apoptosis. Knockdown of PEA15, or overexpression of the nonphosphorylatable S116A mutant of PEA15, also abrogated mammosphere formation. We further demonstrate that AMPK directly interacts with and phosphorylates PEA15 at Ser116 residue, thus identifying PEA15 as a novel AMPK substrate. Together, these data revealed that AMPK activation facilitates mammosphere formation by inhibition of apoptosis, at least in part, through Ser116 phosphorylation of PEA15. Since anoikis resistance plays a critical role in solid tumor growth, we investigated the relevance of these findings in the context of breast cancer. Significantly, we show that the AMPK-PEA15 axis plays an important role in the anchorage-independent growth of breast cancer cells both in vitro and in vivo. Our study identifies a novel AMPK-PEA15 signaling axis in the anchorage-independent growth of both normal and cancerous mammary epithelial cells, suggesting that breast cancer cells may employ mechanisms of anoikis resistance already inherent within a subset of normal HMECs. Thus, targeting the AMPK-PEA15 axis might prevent breast cancer dissemination and metastasis.

We present measurements of the reduction of light output by plastic scintillators irradiated in the CMS detector during the 8 TeV run of the Large Hadron Collider and show that they indicate a strong dose rate effect. The damage for a given dose is larger for lower dose rate exposures. The results agree with previous measurements of dose rate effects, but are stronger due to the very low dose rates probed. We show that the scaling with dose rate is consistent with that expected from diffusion effects.

During the Rabi season respective years 2021-22 and 2022-23, a field experiment was conducted at the student instructional farm of CSAUA&T, Kanpur. Experimental soil had a texture of sandy loam. There are 15 treatment combination involved varying combinations of micronutrients and biofertilizers with three replications of randomized block design. The cultivation of lentil variety Lentil- KLS9-3 (Krish) was carried out in accordance with the suggested agronomic practices. It can be concluded from these findings that the two-year results are consistent with the T14 (RDF + ZnSO4 (0.5%) +FeSO4 (0.5%) foliar spray at pre flowering + pod development stage + Rhizobium) showed the highest values economics parameters i.e., maximum cost of cultivation ₹ 38507 & ₹ 39444, gross returns of ₹105799 & ₹ 116068, net return of ₹ 67292 & ₹ 75884 of respective both of years followed by T15.

This study investigated the impact of solid biofertilizers and organic ameliorants on soil biological properties and chickpea yield. The experiment was conducted at the Instructional Farm of ANDUA&T Ayodhya India during the Rabi season of 2020-2021. The experiment was comprised of eleven treatments, control (T1); (T2); chemical fertilizers 100% RDF; (T3)chemical fertilizers 50% RDF (T4); FYM +Jeevamrit (T5); Agro residue Mulch + FYM + Jeevamrit (T6); Rhizobium +PSB (T7); FYM + Jeevamrit + Rhizobium +PSB (T8); T3 + FYM + Jeevamrit T9; T3 + T5, T10; T3 + T6, T11; T3 + T4 + T6, were replicated thrice in RBD. Chickpea variety KPG-59 was taken as test crop. The results showed that the application of solid biofertilizers and organic ameliorants with chemical fertilizer significantly improved some soil biological properties. The treatments that included FYM and Rhizobium + PSB showed the greatest improvements in soil health as well as chickpea yield. Soil properties as EC, OC and OM were found to be significant while physical property were non-significant.

This article provides an in-depth analysis of the use of Artificial Intelligence (AI) in various aspects of biology, including healthcare, agriculture, and environmental monitoring. It highlights AI's ability to mimic human intelligence and analyze large datasets for predictions and tasks. The article also discusses its integration into Chinese medicine, where AI-guided diagnostic and therapeutic systems optimize clinical treatments and health management. AI is also used in disease management, analyzing data on diseases and pests, predicting their impact on ecosystems, and implementing preventative measures. The article also highlights the role of integrated information systems in environmental monitoring. Artificial intelligence (AI) has significant potential in healthcare research and chemical discoveries. Pharmaceutical companies are using AI to improve drug development by utilizing computational biology and machine learning systems to predict molecular behavior and the likelihood of finding a useful drug. This saves time and money on unnecessary tests. Clinical studies, electronic medical records, high-resolution medical images, and genomic profiles can be used as resources for drug development. Strong AI systems can analyze extensive data sets in pharmaceutical and medical research. This review focuses on integrating knowledge of cancer drugs, drug resistance, next-generation sequencing, genetic variants, and structural biology in cancer precision drug discovery.

Use of plastics in the modern world has significantly increased and its persistent nature in an environment is still a major area of concern. Polystyrene (PS) is a synthetic derivative of plastic which is composed of styrene monomer units, and the presence of phenol group in the styrene monomer contributes to its stability. PS is used in large quantities as it is used for various packaging purposes in industry, but the major area of concern is its persistent nature in an environment. In addition to various physical and chemical techniques, the biodegradation method using microorganisms has also been employed. Numerous bacterial and fungal groups have been reported to possess potential to biodegrade PS. Microorganism-mediated PS degradation involves destruction of the core styrene structure which results in lowering molecular mass. Microorganism-mediated enzymatic degradation of PS is also one of the popular methods of biodegradation. Different techniques like scanning electron microscopy, transmission electron microscopy, biogas production, and determination of molar mass have been used to detect the biodegradation of PS.

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Targeting a vaccine to the mucosal surface has recently been recognized as a promising approach to efficiently induce mucosal immune responses against enteric pathogens. However, poor uptake and inefficient transport of orally delivered subunit vaccines across the intestinal epithelium combined with weak immune responses still present important bottlenecks for mucosal vaccination. A possible strategy suggested to surmount these hurdles is to target the selected antigen to transcytotic receptors, such as aminopeptidase N (APN) present on enterocytes and antigen-presenting cells (APCs). Therefore, we aimed to identify potent and selective VHHs against porcine aminopeptidase N (pAPN), that were fused to the fragment crystallizable (Fc) domain of the murine IgG2a, resulting in dimeric VHH-MG fusions. Out of a library of 30 VHH-MG fusion candidates, two fusions displaying the best binding on pAPN-expressing cells were selected and showed in vivo internalization across the porcine gut epithelium. One of these fusions triggered systemic and intestinal IgA responses upon oral administration. Our results demonstrate the potential of bivalent VHH-MG fusions as delivery vehicles for vaccine antigens. VHH-mediated targeting of antigens to APN to generate protective immunity at the mucosal surface remains to be further validated.

Long-Range networks are increasingly used in smart spaces due to their ability to provide longer communication range while consuming low energy. To facilitate communication among different Long-Range nodes, a gateway is used. For instance, in smart buildings such as airports, railway stations, indoor stadiums, and auditoriums, sensory data from multiple sites are transferred to a base station through a Long-Range gateway. However, when multiple nodes transmit data simultaneously to the gateway, it generates network interference, especially in high-ceiling smart buildings where Long-Range nodes with sensors are attached to monitor the building’s health. In this paper, we present a new method for identifying interfering Long-Range Nodes (LNs) in high-ceiling smart buildings using a classification model. Our approach involves gathering and analyzing network parameters, such as signal-to-noise ratio and received signal strength indicator, from the signals to extract features that the classifier uses for interference classification. The approach categorizes interference based on the number of interfering LNs, with each class representing a distinct number of interfering LNs. We also introduce a push-based mechanism to detect and adjust the power levels of faulty LNs, reducing interference. Our method is cost-effective as it is hardware-independent, making it feasible to implement on the LG platform. Finally, we present a dataset of network interference generated by varying the number of nodes, obstacles, and other parameters. We train the model on the generated dataset and evaluate its effectiveness using a test bed. The experimental results demonstrate that the approach can successfully identify interference nodes in a complex network.

In the frame of nationwide radon/thoron monitoring program, indoor radon/thoron and their progeny concentrations have been estimated for 210 dwellings situated in 8 towns (urban) and 9 villages (rural) of Chhattisgarh state of India. The measurement has been made on quarterly integrating cycle for one full year in each dwelling. Twin chamber dosimeter cup with LR-115 Type-II Solid State Nuclear Track Detector was used for the measurement of indoor radon/thoron concentration. The results show that the geometric mean of indoor thoron concentration in urban dwellings varies from 11.57 to 25.88Bqm-3 with an overall geometric mean value of 16.65Bqm-3, while in rural dwellings it varies from 12.50 to 30.08Bqm-3 with an overall geometric mean value of 19.00Bqm-3. The potential alpha energy concentration (PAEC) levels of thoron in the urban and rural dwellings are found to be 2.58 and 4.57 mWL, respectively. Similarly, the geometric mean of indoor radon concentrations in urban dwellings is found to vary from 20.20 to 30.13Bqm-3 with an overall geometric mean value of 25.28Bqm-3, while in rural dwellings it varies from 15.50 to 36.05Bqm-3 with an overall geometric mean value of 27.32Bqm-3. The PAEC levels of radon in the urban and rural dwellings are found to be 1.50 and 1.87 mWL, respectively. The dose contribution of thoron and progeny in total inhalation dose has been found to be more than 20% in all the surveyed places that show the necessity to pay attention to the presence of thoron and progeny from public health point of view.

Background aims Myelodysplastic syndromes (MDS) are a group of clonal stem cell disorders affecting the normal hematopoietic differentiation process and leading to abnormal maturation and differentiation of all blood cell lineages. Treatment options are limited, and there is an unmet medical need for effective therapies for patients with severe cytopenias. Methods We demonstrate that multipotent adult progenitor cells (MAPC) improve the function of hematopoietic progenitors derived from human MDS bone marrow (BM) by significantly increasing the frequency of primitive progenitors as well as the number of myeloid colonies. Results This effect was more pronounced in a non-contact culture, indicating the importance of soluble factors produced by the MAPC cells. Moreover, the cells did not stimulate the growth of the abnormal MDS clone, as shown by fluorescent in situ hybridization analysis on BM cells from patients with a known genetic abnormality. We also demonstrate that MAPC cells can provide stromal support for patient-derived hematopoietic cells. When MAPC cells were intravenously injected into a mouse model of MDS, they migrated to the site of injury and increased the hematopoietic function in diseased mice. Discussion The preclinical studies undertaken here indicate an initial proof of concept for the use of MAPC cell therapy in patients with MDS-related severe and symptomatic cytopenias and should pave the way for further investigation in clinical trials.

We investigate hide-and-seek games on complex networks using a random walk framework. Specifically, we investigate the efficiency of various degree-biased random walk search strategies to locate items that are randomly hidden on a subset of vertices of a random graph. Vertices at which items are hidden in the network are chosen at random as well, though with probabilities that may depend on degree. We pitch various hide and seek strategies against each other, and determine the efficiency of search strategies by computing the average number of hidden items that a searcher will uncover in a random walk of n steps. Our analysis is based on the cavity method for finite single instances of the problem, and generalises previous work of De Bacco et al (2015 J. Phys. A: Math. Theor. 48 205004) so as to cover degree-biased random walks. We also extend the analysis to deal with the thermodynamic limit of infinite system size. We study a broad spectrum of functional forms for the degree bias of both the hiding and the search strategy and investigate the efficiency of families of search strategies for cases where their functional form is either matched or unmatched to that of the hiding strategy. Our results are in excellent agreement with those of numerical simulations. We propose two simple approximations for predicting efficient search strategies. One is based on an equilibrium analysis of the random walk search strategy. While not exact, it produces correct orders of magnitude for parameters characterising optimal search strategies. The second exploits the existence of an effective drift in random walks on networks, and is expected to be efficient in systems with low concentration of small degree nodes.

Field trials were undertaken to investigate the impact of integrated nutrient management on wheat yield and economic aspects during the Rabi season of 2021-22 and 2022-23. The experimentation took place at the student's instructional farm of Chandra Shekhar Azad University of Agriculture & Technology in Kanpur. The study encompassed 11 treatment combinations, organized in a randomized block design with three replications. These treatments involved varying combinations of inorganic fertilizers, organic manure, and biofertilizers. The cultivation of wheat variety HD-2967 was carried out in accordance with the suggested agronomic practices. Based on the outcomes derived from the investigation, it can be deduced that among the various productivity parameters, the treatment labeled as T10 [100 % NPK + S40 + Zn5 + Fe10 + Azotobacter + PSB + 5 ton FYM] exhibited the highest grain yield of 48.60 and 49.93 quintals per hectare, straw yield of 63.15 and 67.53 quintals per hectare, and biological yield of 111.75 and 117.46 quintals per hectare across both years of experimentation. For economic factors, the treatment T10 also yielded the highest gross returns of ₹ 1,40,190 and ₹154,632 during the first year (2021-22) and second year (2022-23) of the experiment, respectively. Moreover, the treatment T7 [100 % NPK + Zn5] showcased the maximum benefit-cost ratio (B:C ratio) of 2.26 and 2.39. It is noteworthy that the highest costs of cultivation were observed in the treatment T10, amounting to ₹ 53,805 in the first year and ₹ 55,561 in the second year. This treatment encompassed a combination of 100 % NPK, S40, Zn5, Fe10, Azotobacter, PSB, and 5 tons of FYM.

Human metapneumovirus (hMPV) is an important respiratory pathogen for which no licensed antivirals or vaccines exist. Single-domain antibodies represent promising antiviral biologics that can be easily produced and formatted. We describe the isolation and detailed characterization of two hMPV-neutralizing single-domain antibodies that are directed against the fusion protein F. One of these single-domain antibodies broadly neutralizes hMPV A and B strains, can prevent proteolytic maturation of F, and binds to an epitope in the F trimer interface. This suggests that hMPV pre-F undergoes trimer opening or "breathing" on infectious virions, exposing a vulnerable site for neutralizing antibodies. Finally, we show that this single-domain antibody, fused to a human IgG1 Fc, can protect cotton rats against hMPV replication, an important finding for potential future clinical applications.

The dataset consists of simulations of calibrated reconstructed hits produced by a pion passing through the HGCAL test beam prototype. For the simulations, Monte Carlo method is used to produce the pions with energy ranging from 10 to as high as 500 GeV. The dataset contains the coordinates of the calibrated reconstructed hits in the prototype along with the calibrated energy in units of MIP. The HDF5 files can be extracted from the gzip files.

Electroactive polymers (EAPS) are polymeric materials that might undergo changes in shape and dimension as a response to an applied suitable electrical stimulus. They are a subclass of electroresponsive polymers, especially in electromechanical systems. EAPs are a subject of interest in engineering, science, and technology due their useful properties in numerous bioinspired, sensing, innovative generators, and technological applications. EAPs consist of a broad class of promising sensing materials; however, they are still a new concept for scientists that work in sensor-related research. Currenlty, no material can cover all sensory requirements, and the choice of material should be carefully chosen to fit the individual requirements.

Catalysis is important in today’s world, particularly in industries where chemical reactions are used to turn raw materials into useful products. It serves as the foundation for many industrial processes, and advances in catalytic reactions not only enhance the efficacy of chemical reactions but also reduce waste and environmental impact. Heterogeneous catalysts have many advantages over homogeneous catalysts, including fast separation and recycling, high thermal and chemical stability, and so on. Porous organic polymers (POPs) have a high chemical and thermal stability. Functional groups can also be inserted into POPs during the synthesis procedure by polymerization of the functionalized monomers, where both the functional groups and the polymer matrix can be precisely modified. In polymerization reactions, it is possible to change the porosity of the polymer and insert hierarchical porosity in the polymer. Ionic liquids exist in various structures with negligible volatility, stability, and solubility.

We study the light output, light collection efficiency and signal timing of a variety of organic scintillators that are being considered for the upgrade of the hadronic calorimeter of the CMS detector. The experimental data are collected at the H2 test-beam area at CERN, using a 150 GeV muon beam. In particular, we investigate the usage of over-doped and green-emitting plastic scintillators, two solutions that have not been extensively considered. We present a study of the energy distribution in plastic-scintillator tiles, the hit efficiency as a function of the hit position, and a study of the signal timing for blue and green scintillators.

Road accidents are one of the causes of disability, injury and death. As per the latest road accident data released by the Ministry of Road Transport & Highways (MoRTH), the total number of accidents increased by 2.5 percent from 4,89,400 in 2014 to 5,01,423 in 2015. The analysis reveals that about 1,374 accidents and 400 deaths take place every day. Every single year, it has been estimated that over three lakh persons die and 10-15 million persons are injured in road accidents throughout the world. According to the analyses, statistics of global accident indicate that in developing countries, the rate of fatality per licensed vehicle is very high as compared to that of industrialized countries. A road stretch of about 500 metres in length in which either ten fatalities or five road accidents (involving grievous injuries/fatalities) took place during last three calendar years, on National Highways is considered as a road accident black spot according to MoRTH, Government of India. In the present study the identified black spots of Haridwar and Dehradun city were included comprising of a total of 81 black spots out of which there were 49 black spots which were identified in Dehradun followed by 32 black spots in Haridwar. The present study was an attempt to carry out the prioritization of these identified blackspots with respect to the factors that were considered to evaluate accident prone locations on the road. The identified black spots were then prioritized using the classification scheme (ranking from low to high).The study reveals that the advantage of using this approach for prioritizing accident black spots on roads is that it requires very less additional data other than the road network maps.

Millions of packages are delivered successfully by online and local retail stores across the world every day. The proper delivery of packages is needed to ensure high customer satisfaction and repeat purchases. These deliveries suffer various problems despite the best efforts from the stores. These issues happen not only due to the large volume and high demand for low turnaround time but also due to mechanical operations and natural factors. These issues range from receiving wrong items in the package to delayed shipment to damaged packages because of mishandling during transportation. Finding solutions to various delivery issues faced by both sending and receiving parties plays a vital role in increasing the efficiency of the entire process. This paper shows how to find these issues using customer feedback from the text comments and uploaded images. We used transfer learning for both Text and Image models to minimize the demand for thousands of labeled examples. The results show that the model can find different issues. Furthermore, it can also be used for tasks like bottleneck identification, process improvement, automating refunds, etc. Compared with the existing process, the ensemble of text and image models proposed in this paper ensures the identification of several types of delivery issues, which is more suitable for the real-life scenarios of delivery of items in retail businesses. This method can supply a new idea of issue detection for the delivery of packages in similar industries.

The discovery of new inorganic materials in unexplored chemical spaces necessitates calculating total energy quickly and with sufficient accuracy. Machine learning models that provide such a capability for both ground-state (GS) and higher-energy structures would be instrumental in accelerating the screening for new materials over vast chemical spaces. Here, we develop a unique graph neural network model to accurately predict the total energy of both GS and higher-energy hypothetical structures. We use ~16,500 density functional theory calculated total energy from the NREL Materials Database and ~11,000 in-house generated hypothetical structures to train our model, thus making sure that the model is not biased towards either GS or higher-energy structures. We also demonstrate that our model satisfactorily ranks the structures in the correct order of their energies for a given composition. Furthermore, we present a thorough error analysis to explain several failure modes of the model, which highlights both prediction outliers and occasional inconsistencies in the training data. By peeling back layers of the neural network model, we are able to derive chemical trends by analyzing how the model represents learned structures and properties.

Audio call transcripts are one of the valuable sources of information for multiple downstream use cases such as understanding the voice of the customer and analyzing agent performance. However, these transcripts are noisy in nature and in an industry setting, getting tagged ground truth data is a challenge. In this paper, we present a solution implemented in the industry using BERT Language Models as part of our pipeline to extract key topics and multiple open intents discussed in the call. Another problem statement we looked at was the automatic tagging of transcripts into predefined categories, which traditionally is solved using supervised approach. To overcome the lack of tagged data, all our proposed approaches use unsupervised methods to solve the outlined problems. We evaluate the results by quantitatively comparing the automatically extracted topics, intents and tagged categories with human tagged ground truth and by qualitatively measuring the valuable concepts and intents that are not present in the ground truth. We achieved near human accuracy in extraction of these topics and intents using our novel approach

Le lymphome folliculaire (FL) est le lymphome B indolent le plus frequent. Outre des alterations geniques recurrentes, le micro-environnement tumoral, et notamment les cellules stromales lymphoides,joue un role majeur dans le developpement de ce cancer. Cependant, la caracterisation in-situ des cellules stromales lymphoides chez l'homme tout comme les facteurs menant a la polarisation du stroma en un stroma protumoral ont ete peu etudies. Dans cette these, nous avons montre, que les cellules stromales presentes dans les ganglions et la moelle osseuse envahis des patients atteints de FL surexpriment fortement la chimiokine CXCL12. Nous avons ensuite tente de comprendre les mecanismes responsables de cette induction. Alors que les cellules B tumorales induisent une surexpression de la chimiokine CCL2 dans les cellules stromales de facon dependante de leur synthese de TNF, elles ne contribuent pas a l'induction de CXCL12. A l'inverse, le principal compartiment TCD4 implique dans la croissance tumorale du FL, les cellules T follicular helper (TFH), augmentent l'expression de CXCL12 dans les cellules stromales. Le taux d'IL-4, la principale cytokine produite par les TFH de FL, est d'ailleurs correle a celui de CXCL12 au sein de ma niche tumorale du FL. De plus, a l’aide d'un modele de differenciation en stroma lymphoide, nous avons demontre que l’IL4 induit l’expression de CXCL12 par les cellules stromale in vitro. Cette production est augmentee quand les cellules stromales sont deja engagees vers la voie de differentiation lymphoide par un traitement TNF/LT qui favorise l'activation de STAT6 par l'IL-4. Nous avons valide ces resultats dans un modele de formation d'organe lymphoide ectopique chez la souris. Enfin, CXCL12 induit la migration et l'adhesion au stroma des B de FL via l'activation de cascades de signalisations qui peuvent etre abrogees par l'utilisation d'un inhibiteur de Btk utilise en clinique, l'Ibrutinib. Ces resultats sont en faveur de l'interet de considerer la boucle IL-4/CXCL12 pour developper de nouvelles strategies therapeutiques dans cette pathologie constamment fatale.

The Phase I upgrade of the CMS Hadron Endcap Calorimeters consists of new photodetectors (Silicon Photomultipliers in place of Hybrid Photo-Diodes) and front-end electronics. The upgrade will eliminate the noise and the calibration drift of the Hybrid Photo-Diodes and enable the mitigation of the radiation damage of the scintillators and the wavelength shifting fibers with a larger spectral acceptance of the Silicon Photomultipliers. The upgrade also includes increased longitudinal segmentation of the calorimeter readout, which allows pile-up mitigation and recalibration due to depth-dependent radiation damage. As a realistic operational test, the responses of the Hadron Endcap Calorimeter wedges were calibrated with a 60Co radioactive source with upgrade electronics. The test successfully established the procedure for future source calibrations of the Hadron Endcap Calorimeters. Here we describe the instrumentation details and the operational experiences related to the sourcing test.

The growing interest in reliable multi-party applications has fostered widespread adoption of Byzantine Fault-Tolerant (BFT) consensus protocols. Existing BFT protocols need f more replicas than Paxos-style protocols to prevent equivocation attacks. Trust-BFT protocols instead seek to minimize this cost by making use of trusted components at replicas. This paper makes two contributions. First, we analyze the design of existing Trust-BFT protocols and uncover three fundamental limitations that preclude most practical deployments. Some of these limitations are fundamental, while others are linked to the state of trusted components today. Second, we introduce a novel suite of consensus protocols, FlexiTrust, that attempts to sidestep these issues. We show that our FlexiTrust protocols achieve up to 185% more throughput than their Trust-BFT counterparts.

The Internet of Things is a system of interrelated computing devices supported by cloud platforms. Objects, people, etc., which are assigned a sensor tag, are provided with unique identifiers and the ability to transfer sensed data over a wireless network without requiring human-to-human/−computer interaction. The IoT-based smart health monitoring system has a very important role in the telemedicine concept for mankind. The basic function of IoT for health is to store, display, and communicate the patient’s health data. So e-health monitoring system with IoT support is used for distant patient’s health monitoring on a regular basis and instant decision-making for the treatment. It is very useful in the field of e-smart health management for rural or urban patients.

Every year, 1.2 million people die as a result of road traffic accidents (RTA). Following ischemic heart disease and depression as the leading causes of death, RTA will become the third leading cause of death worldwide. The first RTA instance was documented in 1896 [1]. The term "black spot location" refers to an area where the number of traffic accidents is higher. The most prevalent assumption for a black spot site is that there should be any environmental or physical concerns on the road that are causing accidents to occur repeatedly. Our study was conducted in two districts of the Northern Region of India (Uttarakhand). The data were collected on various factors such as weather, accident type, severity levels, road geometry such as the number of curves, segment length, Annual Average Daily Traffic etc. The present study was an attempt to find out the risk factor for road traffic accident in the identified blackspots in the areas of Dehradun and Haridwar. Roadside features were found to significantly affect the severity of run-off-roadway accidents including the presence of bridges, cut-type slopes, ditches and culverts, fences, tree groups, sign supports, utility poles, and isolated trees, and guardrails.

Children of time is a story that undertakes a herculean endeavor: a fascinating attempt at worldbuilding, creating a snapshot as it were of the evolution of a particular species from simple biological creatures to wise and sentient beings. Aside from being a cogent account of a new world order in which intelligent spiders are at the top of the food chain and humans are the belligerent outsiders and colonizers seeking to seize control from the intelligent arthropods, Adrian Tchaikovsky’s novel also highlights the pertinent issue of ecological damage caused by anthropogenic activities which is rapidly taking the planet toward a cataclysmic event, the Sixth Extinction.

Introduction: Road traffic accidents (RTA) will become the third-largest contributor to the global burden of diseases after the ischemic heart diseases and depression. The place where the traffic accident percentages are higher is called as black spot location. The most common assumption for a black spot location is that, there should be any road environmental or geometric issues resulting in the repetition of accidents. Methodology: Our study was conducted in two districts of the Northern Region of India (Uttarakhand). The data were collected on various factors such as weather, accident type, severity levels, and road geometry such as number of curves, segment length, Annual Average Daily Traffic. Results: The present study was an attempt to find out the black spots and to measure the accident severity index (ASI) of the identified black spots in the areas of Dehradun and Haridwar. For each location the ASI was calculated and the Rankings were allotted to the black spots so as to find the severity of the black spots. Conclusion: The present study also suggests that the RTA should be taken under consideration as per the accident severity rather than the frequency of the accidents.

The present electromagnetic and hadronic calorimeters of the CMS experiment will be upgraded to cope with the harsh radiation environment and pileup conditions posed by the high luminosity operations of the LHC (HL-LHC) expected to start in 2027. The CMS collaboration has opted for a sampling calorimeter in the endcap sections of the detector, based on silicon and scintillator technologies, with unprecedented transverse and longitudinal segmentation to facilitate particle identification, particle-flow reconstruction and pileup rejection. As part of the ongoing development and testing phase of this High Granularity Calorimeter (HGCAL), prototypes of both the silicon and scintillator based calorimeter sections have been tested in 2018 in beams at CERN. We report on the performance of the prototype detectors in terms of stability of noise and pedestals, calibration with minimum-ionizing-particles (MIPs), and energy linearity and resolution for electrons and pions. We compare the measurements with a detailed GEANT4-based simulation.

The Constitution of India mandates citizen’s ‘right of access to justice’ and it is the onerous duty of the State to take positive steps in the fulfilment of the right. The ‘right of access to justice’ encompasses within itself two aspects: the right to access courts and tribunals of the country and the right to reasonable speedy and effective justice in any court or tribunal of the country. However, due to huge arrears and pendency of cases in the Indian courts, the State is miserably failing in its constitutional duty to provide right of access to justice. The situation is aggravated due to the spread of pandemic COVID-19 in the year 2020-21, which led to closure of physical court complexes leading to denial of access to justice. With basic infrastructural upgrades, like integration of Information and Communication Technologies in courts, it was seen that India was successfully able to shift its courts on the virtual medium with much ease and success. In the long run, implementing AI-based technologies, like machine learning and natural language processing, to restructure the judicial system will help in reducing the arrears and pendency in the court system. But integration of technology in the judiciary raises some fundamental issues, which needs to be addressed beforehand. At the foremost lies the issue of ‘digital-divide’, which is the disparate distribution of affordable technology among the rural and urban populations of the country. Secondly, the issue of language and the rights of the disabled people. And thirdly, the issue of data privacy with regards to the litigants which is perplexing the dynamics of constitutionalism. It is therefore argued that the policy makers should adopt a principled approach to address the perplexing issues of technology-based solution, for long term integration of technology in the Justice Delivery System.

Projects that do not meet the original time, cost 8 quality requirements are said to be failed Projects. Four Pillars of Project: Man, machine, money 8 managements; if any of the four pillars get disturbed the building of projects fails. Research reveals that project management in many firms 8 companies currently ranges from undisciplined to confusion. Most of the project failure is related to the time, cost 8 quality paradigm is the motivation of research on this topic. This paper examines some of the issues 8 casual factors of projects failure.

This paper describes the procedures used and the results obtained in calibrating the Nuclear Research Corporation (NRC) model MD55E bismuth-germanium-oxygen (BGO) {sup 16}N monitor. Because it is difficult to find a certified radioactive source with gamma-ray energies as high as 6.13 and 7.12 MeV of 16 N, the method in this work involved the determination of the fast neutron flux at the in-core terminal of the pneumatic transfer system (rabbit) of the Pennsylvania State University TRIGA Mark III nuclear reactor. The {sup 16}O(n, p){sup 16}N fast neutron reaction was used, and its best available cross section was employed to determine the {sup 16}N production rate in the terminal with a 750-kW power level. Using reactor-produced {sup 16}N, measures were conducted to determine both the intrinsic detection efficiency of a 5.08- x 5.08-cm BGO detector for {sup 16}N gamma rays and the attenuation of these photons in steel. The experimental data were used to verify a Monte Carlo simulation system established at NRC that is used to determine {sup 16}N activity under various in-plant conditions.