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Felty syndrome is a rare and serious complication of Rheumatoid Arthritis (RA), characterised by a triad of RA, splenomegaly (enlarged spleen), and neutropenia (low neutrophil count). RA, a systemic autoimmune inflammatory disease marked by synovitis, commonly occurs in the fifth or sixth decade of life and often affects patients with a history of RA exceeding ten years. It is more prevalent in the Caucasian population due to the underexpression of the Human Leukocyte Antigen (HLA)-DR4 gene in African Americans. Felty syndrome requires the presence of neutropenia, defined as an Absolute Neutrophil Count (ANC) below 2000 cells/mm³, alongside splenomegaly and long-standing RA. Hereby, the authors present a case report of a 44-year-old female with a three-year history of RA, who presented with ascites for nine months and was found to have portal hypertension. Her diagnosis of Felty syndrome was confirmed based on the triad of RA, neutropenia, and splenomegaly, highlighting the importance of early recognition and management to prevent severe complications such as infections and systemic issues like portal hypertension.

Abstract The Asian green mussel, Perna viridis is an important aquaculture species in the family Mytilidae contributing substantially to molluscan aquaculture. We generated a high-quality chromosome level assembly of this species by combining PacBio single molecule sequencing technique (SMRT), Illumina paired-end sequencing, high-throughput chromosome conformation capture technique (Hi-C) and Bionano mapping. The final assembly resulted in a genome of 723.49 Mb in size with a scaffold N50 of 49.74 Mb with 99% anchored into 15 chromosomes. A total of 49654 protein-coding genes were predicted from the genome. The presence of 634 genes associated with the cancer pathway and 408 genes associated with viral carcinogenesis indicates the potential of this species to be used as a model for cancer studies. The chromosome-level assembly of this species is also a valuable resource for further genomic selection and selective breeding for improving economically important aquaculture traits and augmenting aquaculture productivity.

Musculoskeletal pathologies affecting shoulder girdle joints, other than gleno-humeral joint such as acromioclavicular joint arthritis, tendonitis, subacromial bursitis, subdeltoid bursitis, and osteochondritis dissecans, are relatively rare. In Middle East and Asian countries, public health services are generally availed by a large number of patients in primary health centres, rural hospitals, and district hospitals, but the scarcity of specialist orthopaedic surgeons in such hospitals usually leads to misdiagnosis of rare musculoskeletal pathologies, which may result in complications and morbidity. The study aims to determine the presentation, progression, diagnostic evaluation, and treatment of musculoskeletal pathologies affecting the shoulder girdle and develop an algorithm to screen such pathologies. A systematic literature search of four medical databases (PubMed, Scopus, Web of Science and Google Scholar) was conducted, from 1st January 1950 to 31st December 2022. Studies (case reports, prospective studies, review articles) reporting pathological conditions affecting shoulder girdles, with a focus on clinical presentation, physical examination tests required for diagnostic evaluation, and management, were included. The relevant data was extracted from the selected studies and tabulated for analysis. Seventeen studies were included in the final analysis. Several case reports, case series and review articles showed that very few musculoskeletal conditions can be correctly diagnosed based on only physical examination tests. Radiological and anatomical basis of each of the cases were discussed. An algorithm was prepared to help diagnose shoulder girdle pathologies based on clinical presentation and examination findings.

Background The role of dual-modality drainage of walled-off necrosis (WON) in patients with acute pancreatitis (AP) is established. However, there are no data on the association of clinical outcomes with the timing of percutaneous catheter drainage (PCD). We investigated the impact of the timing of PCD following endoscopic drainage of WON on clinical outcomes in AP.

Background: Physical inactivity leads to stress-related unconstructive repetitive thought, negatively affecting student’s cognitive health. The present study tried to find a way to enhance students’ cognition through yoga. The study assessed the effect of “Om” Chanting, Bhramari Pranayama, and Nadi Shodhana Pranayama on cognition of medical students. Methods: One hundred and fifty participants (75 in each group aged 18­27 years) were selected from SGRR Medical College, Dehradun, in the northern region of India. They were randomized into the yoga group (n = 75) and control group (n = 75). Cognitive functions were assessed using psychological tools. Attention was assessed for six letter cancelation tasks. Reaction time was assessed with reaction time apparatus. Metacognition was evaluated with the metacognitive inventory. Working memory was assessed with the digit span (forward and backward) test. Results: A total of 73 (49%) male and 77 (51%) female participants were included in the study. Participants’ mean age was 20.10 (standard deviation ­ 0.89102). There was a statistically significant mean difference between both the groups at postintervention concerning digit span forward (0.000), digit span backward (0.000), letter cancellation test (total attempted ­ 0.000, wrongly attempted ­ 0.009, and net attempted ­ 0.000), and metacognition test (0.002) variables were

Abstract Objectives Sabkhas represent polyextreme environments characterized by elevated salinity levels, intense ultraviolet (UV) radiation exposure, and extreme temperature fluctuations. In this study, we present the complete genomes of five bacterial isolates isolated from the sabkha-shore region and investigate their genomic organization and gene annotations. A better understanding of the bacterial genomic organization and genetic adaptations of these bacteria holds promise for engineering microbes with tailored functionalities for diverse industrial and agricultural applications, including bioremediation and promotion of plant growth under salinity stress conditions. Data description We present a comprehensive genome sequencing and annotation of five bacteria (kcgeb_sa, kcgeb_sc, kcgeb_sd, kcgeb_S4, and kcgeb_S11) obtained from the shores of the Abu Dhabi Sabkha region. Initial bacterial identification was conducted through 16 S rDNA amplification and sequencing. Employing a hybrid genome assembly technique combining Illumina short reads (NovaSeq 6000) and Oxford Nanopore long reads (MinION), we obtained complete annotated high-quality gap-free genome sequences. The genome sizes of the kcgeb_sa, kcgeb_sc, kcgeb_sd, kcgeb_S4, and kcgeb_S11 isolates were determined to be 2.4 Mb, 4.1 Mb, 2.9 Mb, 5.05 Mb, and 4.1 Mb, respectively. Our analysis conclusively assigned the bacterial isolates as Staphylococcus capitis (kcgeb_sa), Bacillus spizizenii (kcgeb_sc and kcgeb_S11), Pelagerythrobacter marensis (kcgeb_sd), and Priestia aryabhattai (kcgeb_S4).

Pseudomonas aeruginosa is capable of producing biofilms on various surfaces, medical implants and burn wounds which inhibit the action of antimicrobial agents. This study was undertaken for the screening, identification and purification of a natural antimicrobial compound from the hospital waste sites against P. aeruginosa. The partial purification of the antimicrobial agent was performed with ethyl acetate from the culture supernatant of the isolate and further purified by HPLC. For the characterization of the active compound, we have used Fourier Transform Infrared Spectroscopy (FT-IR) and Electrospray Ionization mass spectrometry (ESI-MS) analysis. The purified compound was tested for anti-biofilm activity in vitro against P. aeruginosa and on various surfaces such as plastic, glass, and steel. The potent isolate was confirmed as Bacillus licheniformis strain RG1002. The HPLC purified compound was characterized as lichenysin using FTIR and ESI-MS analysis. This study identifies and characterize the potent antimicrobial agent against other important human pathogens such as Staphylococcus aureus, Salmonella typhi, Shigella flexneri and Escherichia coli. Purified lichenysin showed strong inhibitory effect against P. aeruginosa and other important pathogens and inhibits the biofilm formation of P. aeruginosa in vitro on various types of surfaces. The current study suggests the application of lichenysin as a protective coating on various indwelling medical devices and catheters to prevent the biofilm formation by P. aeruginosa.

Objective: To investigate the association between three-dimensional (3-D) left ventricular ejection fraction (LVEF) and various speckle tracking echocardiographic (STE) strain parameters in non-ischemic left bundle branch block (LBBB) patients with major adverse cardiovascular events (MACE) during a one-year follow-up phase. Method: A total of 50 patients with non-ischemic LBBB were assessed using various parameters of 3-D echocardiography. They were compared with their same-age and sex control group and then followed up with repeat 3-D echocardiography for MACE for one year. Results: Composite outcomes were seen in (n = 11 [22 %], including cardiovascular mortality (n = 2 [4.0 %]) and hospitalization for heart failure (n = 9 [18.0 %]). Mean values of the left ventricle (LV) global longitudinal (GLS), circumferential (GCS), and radial (GRS) strains were −14.4 ± 5.6, −14.3 ± 5.8, and 15.3 ± 5.9 respectively in the study cases. Initial GLS values were significantly impaired among those who had clinical events (−9.2 vs −15.9). Also, significant worsening of GLS (p value

Transition-metal-mediated “borrowing hydrogen" also known as hydrogen auto-transfer reactions allow the sustainable construction of C–C and C–N bonds using alcohols as hydrogen donors. In recent years, manganese complexes have been explored as efficient catalysts in these reactions. This review highlights the significant progress made in manganese-catalyzed C–C and C–N bond-formation reactions via hydrogen auto-transfer, emphasizing the importance of this methodology and manganese catalysts in sustainable synthesis strategies.

Airgun injuries are prevalent in the pediatric population. The present study described a case of air gun pelletinjury to the left carotid artery and its successful management. A 25-year-old man presented to the emergencydepartment complaining that his son had accidentally injured him with an air gun pellet while playing. TheX-ray cervical spine revealed a single foreign body (pellet) located directly anterior to the C5-C6 vertebra. ACT angiography of the neck showed a spherical hyperdense object just anterior to the C6 vertebral body onthe left side, 3 mm posteromedial to the left common carotid artery, which was most likely a pellet foreignbody. The patient was sent to operation theatre (OT) for exploration. There was a rent in the internal carotidartery with active bleeding. After exerting both proximal and distal control, the rent was closed. Close air guninjury could result in gunshot wounds, as in the present case. Plain X-rays in AP and lateral view are required.Nonoperative management could be employed in a restricted group of patients with satisfactory outcomes.Those who have vascular involvement will require surgical intervention.

Plasminogen activator inhibitor-1 (PAI-1/Serpin E1) is classically known for its antifibrinolytic activity via inhibiting uPA and tPA of the fibrinolytic pathway. PAI-1 has a paradoxical role in tumor progression, and its molecular functions are poorly understood. PAI-1 is a widely accepted secretory protease inhibitor, however, a study suggested the localization of PAI-1 in the cytoplasm and the nucleus. Besides the plethora of its biological functions as a secretory protein, intracellular localization, and functions of PAI-1 remain unexplored at the molecular level. In this study, using various in silico approaches, we showed that PAI-1 possesses a nuclear export signal. Using the CRM1-specific inhibitor leptomycin B, we demonstrated that PAI-1 has a functional CRM1-dependent NES, indicating the possibility of its nuclear localization. Further, we confirm that PAI-1 is localized in the nucleus of endothelial cells using fluorescence microscopy and immunoprecipitation. Notably, we identified an unconventional distribution of PAI-1 in the PML bodies of the nucleus of normal endothelial cells, while the protein was restricted in the cytoplasm of slow-growing cells. The data showed that the localization of PAI-1 in PML bodies is highly correlated with the growth potential of endothelial cells. This conditional nucleocytoplasmic shuttling of PAI-1 during the aging of cells could impart a strong link to its age-related functions and tumor progression. Together, this study identifies the novel behavior of PAI-1 that might be linked with cell aging and may be able to unveil the elusive role of PAI-1 in tumor progression.

In this research, aligned with global policies aimed at reducing CO2 emissions from traditional power plants, we developed a holistic energy system utilizing solar, wind, and ocean thermal energy sources, tailored to regions optimal for ocean thermal energy conversion (OTEC). The selected site, characterized by favorable wind and solar conditions close to areas with high OTEC potential, is designed to meet the electricity needs of a coastal community. The system's core components include an Organic Rankine Cycle, turbines, thermoelectric elements, pumps, a heat exchanger, a wind turbine, and a solar collector. A detailed system analysis and thermodynamic evaluation based on thermodynamic principles were carried out using the Engineering Equation Solver (EES) software. Key factors such as wind speed, solar radiation, and collector area were critical in determining system performance. To enhance the system's effectiveness, we conducted a comprehensive comparison of optimization algorithms, incorporating the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) and utilizing a Pareto front for value optimization. This approach significantly outperformed other algorithms such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Simulated Annealing (SA) in terms of system efficiency and cost-effectiveness. The developed system achieved an exergy efficiency of 14.46 % and a cost rate of $74.98 per hour, demonstrating its suitability for its intended functions. Moreover, exergoenvironmental evaluation was conducted for the proposed plant. The findings revealed that key component HEX has a high exergoenvironmental factor due to their use of hot water, which has zero unit exergoenvironmental impact. Additionally, pumps demonstrated a zero exergoenvironmental impact factor, indicating negligible component-related environmental impacts. Sensitivity analysis further evaluated critical performance parameters, revealing that increases in solar irradiation lead to decreased total system cost rates, while higher turbine temperatures resulted in a remarkable 14.08 % reduction in the system's cost rate. These results underscore the economic viability of operating the system at higher temperatures and strengthen the argument for its adoption from a financial perspective.

ABSTRACT Purpose: Amid rising health awareness, natural products which has milder effects than medical drugs are becoming popular. However, only few systems can quantitatively assess their impact on living organisms. Therefore, we developed a deep-learning system to automate the counting of cells in a gerbil model, aiming to assess a natural product’s effectiveness against ischemia. Methods: The image acquired from paraffin blocks containing gerbil brains was analyzed by a deep-learning model (fine-tuned Detectron2). Results: The counting system achieved a 79%-positive predictive value and 85%-sensitivity when visual judgment by an expert was used as ground truth. Conclusions: Our system evaluated hydrogen water’s potential against ischemia and found it potentially useful, which is consistent with expert assessment. Due to natural product’s milder effects, large data sets are needed for evaluation, making manual measurement labor-intensive. Hence, our system offers a promising new approach for evaluating natural products.

Abstract The use of hydrogen as an energy carrier will require low‐cost, low‐power hydrogen sensors. Toward this goal, penta‐twinned palladium nanowires (Pd NWs) are synthesized and fabricated sensors from them by drop‐casting. Pd NWs drop‐cast onto an interdigitated electrode (IDE) gave a response of 0.3% to 1 vol.% H2, with response and recovery times of 12 and 20 s, respectively. However, they exhibited a negative response (decreased resistance) at low H2 concentrations. Pd NWs on a paper substrate provided a tenfold higher response to 1 vol.% H2, with response and recovery times of 10 s each, but still exhibited negative response at low H2 concentration. Exposing the Pd NW‐on‐paper sensor to ozone‐generating UV light degraded the PVP used in Pd NW synthesis, eliminating the reverse sensing response, and providing a response of 5% to 1 vol.% H2, with response and recovery times of 15 s. This allowed reliable H2 detection down to 100 ppm H2. Finally, coating the Pd NWs with a small amount of Pt (

Abstract The adoption of green hydrogen economy is an indispensable necessity in the current global scenario of environment and energy security. In this endeavor, ammonia is poised to play a key vector of hydrogen to mitigate the challenges arising from transportation, storage and safety. Besides containing a high volumetric and gravimetric hydrogen density, NH3 decomposition into H2 for onsite utilization as a distributed energy source is devoid of greenhouse gases production. In this endeavor, significant technological advancements have been made for in situ production of H2 from NH3 decomposition and the use of NH3 in fuel cell devices to produce electricity. The ammonia decomposition methods to produce H2 mainly involve thermocatalytic, oxidative, electrocatalytic and photocatalytic, among which the catalyst assisted thermal cracking of NH3 has been widely investigated. The research progress in electrolysis of NH3 has been notable in the last couple of years and provides a low‐cost alternative to produce H2 at room temperature. In the area of device development, solid oxide fuel cells (SOFC) have witnessed rapid development in the performances and stability, as ammonia is completely decomposed into H2 and N2 at high operating temperature above ~700 °C.

Shrinking of the thickness of silicon on insulator (SOI) has been proposed as a potential solution for scaling down the physical base length of symmetric lateral electrostatically doped bipolar transistors. An ultra-thin body device that utilizes the full SOI thickness has been presented and the performance of the same is investigated in detail. The device features two distinct doping techniques: work function-induced electrostatic doping (WED) and bias-induced electrostatic doping (BED). The proposed design approach leads to significant improvements in gain and cut-off frequency compared to previously reported designs. The resulting devices exhibit peak current gain β values >1100, ft>500 GHz, fmax>1300 GHz. Moreover, these improved device performance matrices get translated into better performance of universal gates with low rise and fall time of ∼1.3 ns, and improved noise margin performance in static random access memory (SRAM) device of 0.43 and 0.41 for WED and BED based devices respectively. Furthermore, the study investigates the reliability of the device concerning breakdown voltage and its response to different temperature conditions. The findings reveal a decline in the β value for WED-based devices when subjected to temperatures exceeding 340 K. In contrast, BED-based devices demonstrate a comparatively smaller variation in β at temperatures above 340 K. These results show the potential of the proposed device for mixed-signal and digital circuit applications.

This research descibes a pioneering approach aimed at preparing zinc oxide nanoparticles (ZnO-NPs) with colchicine as the reducing and capping agent. Colchicine-loaded ZnO-NPs (CHZnO-NPs) were prepared by adding colchicine to the zinc sulfate heptahydrate solution. The CHZnO-NPs formulation was then characterized to determine the morphology, size, crystallinity, elemental composition and vibrational properties. Upon characterization, CHZnO-NPs were studied for their cytotoxic effect against the breast cancer cell line (MDA-MB-231). The successful biosynthesis of CHZnO-NPs was initially confirmed visually by the changes in the mixture color, from light-yellow to white cloudy. The best CHZnO-NPs formulation selected was F3, which possessed 10 mg/mL of colchicine. Formulation (F3) had the smallest mean particle diameter of 43.77 nm and the lowest zeta potential of −19.60 mV. It also had 92.21 ± 0.012 % encapsulation efficiency and 20.86 ± 0.005 % drug loading. Formulation (F3) displayed a hexagonal wurtzite structure with irregular morphology. The observation of colchicine peaks on the FTIR spectra of F3 proved the role of colchicine as a reducing and capping agent during the synthesis of ZnO-NPs. Besides, the in-vitro cell cytotoxicity study on the MDA-MB-231 cell line revealed a significant reduction in cell proliferation at the concentration of 25 μg of colchicine and F3. Further, studies on the cellular migration potential also demonstrated concentration-dependent activity. Overall, CHZnO-NPs were shown to be successfully synthesized via an environmental-friendly procedure and colchicine acted as a capping agent to regulate the particle size, and aggregation, in addition to its anticancer properties.

Solar photovoltaic (PV) panels play a crucial role in sustainable energy generation, yet their power output often faces uncertainties due to dynamic weather conditions. In this study, a comparative machine learning approach is introduced, utilizing multivariate regression (MR), support vector machine regression (SVMR), and Gaussian regression (GR) techniques for precise solar PV panel power prediction. The investigation into the impact of environmental factors—solar radiation, ambient temperature, and relative humidity—on PV panel output reveals the superior predictive capabilities of SVMR models. With a mean squared error (MSE) of 0.038, a mean absolute error (MAE) of 0.17, and an R2 value of 0.99, SVMR outperforms GR and MR models. Conversely, Gaussian regression demonstrates comparatively weaker performance, yielding an R2 of 0.88, an MSE of 0.49, and an MAE of 0.63.This research underscores the reliability and enhanced accuracy of the proposed SVMR model in forecasting solar PV panel output. The outcomes presented herein carry significant implications for promoting the widespread adoption of PV panels in electricity generation, particularly in challenging environmental conditions. The findings offer valuable insights into optimizing solar PV deployment, ultimately contributing to the expansion of solar power generation in the national energy landscape. Moreover, the comparative analysis provides insights into how anticipated PV power generation can adapt to varying weather conditions, encompassing factors such as temperature, humidity, and solar radiation.

A new and simple articulator classification has been proposed which includes both mechanical and virtual articulators to meet with the modern day dental practice that has shown a gradual shift toward digital technology and workflow.

Renal transplant recipients are prone to urological complications, the most common of which is stricture of the transplant ureter. We present a rare case of complete ureteric stricture in a 37-year-old man who had undergone spousal living donor kidney transplantation with ABO incompatibility. Initially, treatment involved creating an anastomosis between the native right ureter and the renal pelvis of the transplanted kidney. However, the stricture recurred. Subsequently, the patient was successfully treated with inferior polar nephrectomy and vesicocalicostomy, which entailed anastomosing the lower calyx of the transplanted kidney to the bladder. After 7 months of follow-up, the patient continued to exhibit stable renal function without stricture recurrence.

Abstract The mining industry confronts significant challenges in mitigating airborne particulate matter (PM) pollution, necessitating innovative approaches for effective monitoring and prediction. This research focuses on the design and development of an Internet of Things (IoT)-based real-time monitoring system tailored for PM pollutants in surface mines, specifically PM 1.0, PM 2.5, PM 4.0, and PM 10.0. The novelty of this work lies in the integration of IoT technology for real-time measurement and the application of machine learning (ML) techniques for accurate prediction based on recorded dust pollutants data. The study's findings indicate that PM 1.0 pollutants exhibited the highest concentration in the atmosphere of the ball clay surface mine sites, with the stockyard site registering the maximum levels of PM pollutants (28.45 µg/m3, 27.89 µg/m3, 26.17 µg/m3, and 27.24 µg/m3, respectively) due to the dry nature of clay materials. Additionally, the research establishes four ML models—Decision Tree (DT), Gradient Boosting Regression (GBR), Random Forest (RF), and Linear Regression (LR)—for predicting PM pollutant concentrations. Notably, Random Forest demonstrates superior performance with the lowest Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE) at 1.079 and 1.497, respectively. This comprehensive solution, combining IoT-based monitoring and ML-based prediction, contributes to sustainable mining practices, safeguarding worker well-being, and preserving the environment.

The growth of eggplant (Pusa Safed Baingan-1) was studied during the semi-arid (March to June) and humid sub-tropical (July to September) seasons of New Delhi, India. The individual effects of wheat straw biomass (WSBM), wheat straw biochar (WSBC) and compost versus the combined effect of WSBM plus compost and WSBC plus compost were determined under field conditions. The amendments were made at two different application rates: 1 wt% and 2 wt%. WSBC was successfully prepared in a proprietary kachcha reactor (Indian patent no. 380921), designed using locally sourced clay. Amendments were characterized using elemental analyzer, scanning electron microscopy (SEM), transmission electron (TEM) microscopy, Fourier transform infrared (FTIR) spectroscopy and X-Ray diffraction (XRD). The field study was conducted in 11 (1x1-meter) plots with two replicates. Basic soil health parameters including pH, electrical conductivity (EC), water holding capacity (WHC), bulk density (BD), cation exchange capacity (CEC), soil total nitrogen (STN), soil available nitrogen (SAN), soil organic carbon (SOC), soil available phosphorus (SAP), microbial biomass carbon (MBC) and mineral contents are analyzed. Observable plant growth characteristics (germination percentage, height, number of leaves, fruits, and plant biomass) were also recorded. Biochar amendment was most beneficial for enhancing the majority of these parameters. With respect to the control, a 20% decrease in bulk density, a 30% increase in water holding capacity, a 122% increase in organic carbon, a 175% increase in total nitrogen, a 23% increase in available nitrogen, and a 473% increase in available phosphorus were recorded. Furthermore, with respect to the control, a 115% increase in CEC was recorded using the compost amendment vs 84% with WSBC. Synergism between biochar and compost was reflected by high germination percentage (44%), number of fruits (600%), plant biomass weight (243%) and soil microbial biomass carbon (286%). Biomass amendment failed to show any positive influence. In summary, biochar emerges as a superior choice compared to both biomass and compost when it comes to soil amendments.

Groundwater is the primary source of water for domestic and irrigation purposes in the peninsular region of the Bhagalpur and Khagaria districts of Bihar. Though this region is bounded by perennial rivers on three sides, the groundwater level is decreasing gradually because of over exploitation and misuse. In this study, spatial and temporal analyses of rainfall and groundwater levels for pre- and post-monsoon seasons from 1996 to 2020 have been carried out using GIS tools, graphical plots, and statistical methods of pattern recognition. The spatial analysis of rainfall shows less rainfall in the western region of the study area, whereas it shows heavy rainfall in the region near the Vikramshila Bridge. The temporal analysis of rainfall shows decreasing trend in the whole study area and the rate of decrease was 25.05 mm/year during 1996–2020. The results of the pre-monsoon groundwater levels analysis show decreasing trend in the majority of wells, and the rate of decrease varies from 0.005 to 0.102 m/year. By contrast, the post-monsoon groundwater levels showed an increasing trend varying from 0.005 to 0.083 m/year at wells located near the River Ganga, except at Maheshkhunt. Thus, there is a need for proper groundwater management for a sustainable future. HIGHLIGHTS The study investigated the change in the patterns of rainfall and groundwater levels in a peninsular region formed by four rivers.; The study used GIS tools and graphical and statistical methods for spatio-temporal analysis.; The results showed a declining trend in rainfall and groundwater levels and their variation in space.; Based on this study, the authorities can initiate steps for groundwater management.;

Generative AI (GenAI) and Natural Language Processing (NLP) are transforming the landscape of question-answering systems, shifting from traditional methods to more advanced, automated solutions. This study explores into applying these technologies using a unique dataset derived from the ancient Hindu scriptures, specifically the Atharv Ved. Employing a combination of vector embedding transformations and a novel question-answering model integrating BERT embeddings, attention mechanisms, and Gated Recurrent Unit (GRU) layers, we have developed a system capable of understanding and generating semantically rich questions and answers. Our model was rigorously evaluated against the Atharv Ved and SQuAD datasets, demonstrating high accuracy rates of 94% and 95%, respectively. These results underscore the model’s capability to handle complex, context-heavy textual data effectively. The study concludes with the model’s potential applications in digital humanities, preserving cultural heritage, and enhancing the accessibility of ancient texts through modern technology.

The accurate collection of operational data at airports is essential for ensuring the fair distribution of national funds. However, many U.S. airports lack control towers, which forces planners to rely on sound, radio, and transponder-based systems for detecting aircraft operations. While these methods are useful, they have limitations, such as low accuracy and an inability to identify specific aircraft. In our previous work, we developed a computer vision-based system capable of accurately counting and identifying aircraft. However, implementing this system requires powerful computing devices that are not typically found at non-towered airports. Additionally, cloud computing is not a viable option due to data transfer limitations and associated costs. To address these challenges, we propose an affordable solution utilizing edge computing. This paper describes the necessary software and hardware modules, including optimized machine learning methods and edge devices, for deploying the system at airports. We tested the system’s performance using two independent standalone setups, created with NVIDIA edge kits, at three non-towered airports. The first setup aimed to obtain an accurate count of operations without detailed aircraft information, while the second setup was designed to extract an operations count with comprehensive aircraft information, including aircraft type recognition and identification. The accurate retrieval of aircraft information in the edge computing system is achieved through the introduction of a tailored CNN-based recognition model and the execution of a 3-step tail number identification algorithm. The results demonstrate the practical value of the proposed system, indicating that an accurate count of operations with detailed aircraft information can be obtained at a reasonable cost.

Abstract Chronic obstructive pulmonary disease (COPD) is the 3rd leading cause of death worldwide. Cigarette smoke which has approximately 2–3 µg of Cadmium (Cd) per cigarette contributes to the environmental exposure and development and severity of COPD. With the lack of a cadmium elimination mechanism in humans, the contribution of cadmium induced stress to lung epithelial cells remains unclear. Studies on cadmium responsive miRNAs suggest regulation of target genes with an emphasis on the critical role of miRNA–mRNA interaction for cellular homeostasis. Mir-381, the target miRNA in this study is negatively regulated by cadmium in airway epithelial cells. miR-381 is reported to also regulate ANO1 (Anoctamin 1) expression negatively and in this study low dose cadmium exposure to airway epithelial cells was observed to upregulate ANO1 mRNA expression via mir-381 inhibition. ANO1 which is a Ca2+-activated chloride channel has multiple effects on cellular functions such as proliferation, mucus hypersecretion and fibroblast differentiation in inflamed airways in chronic respiratory diseases. In vitro studies with cadmium at a high concentration range of 100–500 µM is reported to activate chloride channel, ANO1. The secretory epithelial cells are regulated by chloride channels like CFTR, ANO1 and SLC26A9. We examined “ever” smokers with COPD (n = 13) lung tissue sections compared to “never” smoker without COPD (n = 9). We found that “ever” smokers with COPD had higher ANO1 expression. Using mir-381 mimic to inhibit ANO1, we demonstrate here that ANO1 expression is significantly (p

Abstract The insular region of Wallacea has become a focal point for studying Pleistocene human ecological and cultural adaptations in island environments, however, little is understood about early burial traditions during the Pleistocene. Here we investigate maritime interactions and burial practices at Ratu Mali 2, an elevated coastal cave site on the small island of Kisar in the Lesser Sunda Islands of eastern Indonesia dated to 15,500–3700 cal. BP. This multidisciplinary study demonstrates extreme marine dietary adaptations, engagement with an extensive exchange network across open seas, and early mortuary practices. A flexed male and a female, interred in a single grave with abundant shellfish and obsidian at Ratu Mali 2 by 14.7 ka are the oldest known human burials in Wallacea with established funerary rites. These findings highlight the impressive flexibility of our species in marginal environments and provide insight into the earliest known ritualised treatment of the dead in Wallacea.

Abstract Invasive plant species are considered one of the significant drivers of habitat loss, leading to biodiversity loss. They have also been observed to alter the local ecology, resulting in a decline of native flora. The management of invasive species is widely recognised as one of the most severe challenges to biodiversity conservation. The International Union for Conservation of Nature (IUCN) considers Lantana camara, as one of the ten worst weeds. Over time, native and indigenous species may evolve to co-exist or compete with invasive species, reducing invader fitness. It is observed that species competition fluctuates throughout environmental gradients, life phases, and abundances. Hence, competition outcome is very context-dependent. To address this challenge, we conducted a comprehensive study in three phases: we identified native species coexisting with Lantana in their natural habitats in the Doon Valley (Phase I) and documented the phenotypic traits of selected coexisting species using the Landmark BBCH (Biologische Bun-desantalt, Bundessortenamt und Chemische Industrie) scale, revealing the phenological growth patterns of selected co-existing species (Phase II). This was followed by conducting pot (Phase IIIa) and field (Phase IIIb) experiments to study the interactions between them. Notably, Justicia adhatoda, Broussonetia papyrifera, Pongamia pinnata, Urtica dioica and Bauhinia variegata demonstrated promising results in both pot and field conditions. Furthermore, after the mechanical removal of Lantana and prior to the plantation in the field experiments, four native grass species were introduced using the seed ball method. Among these, Pennisetum pedicellatum and Sorghum halpense exhibited prompt regeneration and effectively colonised the field, densely covering the cleared area. The study provides a comprehensive management plan for the restoration of Lantana affected areas through competition using native species. This study utilizes phenological assessment for native plant selection using reclamation from native grasses and proposes a management plan for combating invasive Lantana.

Background: Patients with chronic heart failure (CHF) frequently have associated iron deficiency, which may or may not be associated with anemia. Studies to ascertain the impact of repleting iron in patients with CHF and various other prognostic markers are lacking in Indian patients and the Indian context. Objectives: The objective is to study the prevalence of iron deficiency anemia in patients with CHF and its prognostic significance in predicting major adverse cardiovascular events (MACEs) during 6 months of follow-up along with the role of other clinical and demographic variables. Methodology: A prospective, observational, hospital-based study conducted in a government tertiary medical center in south India on patients admitted with the diagnosis of CHF. Full demographic and clinical characterization and all relevant laboratory investigations including iron profile were done per protocol. The incidence of a MACE (rehospitalization for heart failure or death) and its association with iron deficiency was studied at the end of a 6-month follow-up. Results: A total of 388 patients were followed for 6 months. Out of those, 211 patients (54%) developed composite outcomes. Old age, coronary artery disease, atrial fibrillation, previous heart failure history, chronic kidney disease, and reduced left ventricular ejection fraction were independent predictors of composite outcome. The prevalence of anemia in the study population was 71%, and iron deficiency was 63% (20% absolute and 43% relative). Iron deficiency without anemia was also an independent predictor of the composite outcome. Conclusions: This study highlights the underestimated and neglected burden of iron deficiency in CHF patients in India. It also suggests further large-scale studies to characterize this easily treatable condition better and consider routine testing of iron profiles in future Indian guidelines.

Background: Basic sanitation and waste management have always remained a central issue in India. The country launched its flagship sanitation program – Swachh Bharat Abhiyan (SBA) (Clean India Mission) in 2014 to abolish open defecation and achieve universal sanitation coverage. Objective: This study aimed to examine barriers to toilet use and women's menstrual hygiene practices in relation to the availability of toilets among rural residents. Materials and Methods: Using a cross-sectional design and multi-stage sampling method, 120 households were selected from rural villages of the Mayurbhanj district of Odisha. Structured questionnaires and direct observation methods were used for data collection. Results: All the houses had SBA latrines, yet 25% population defecated outside. About 40% households reportedly never cleaned their toilets. Most menstruating women (86.2%) preferred to change their menstrual pads/cloths in their bedroom instead of bathrooms. Incomplete construction was reported as the major reason for not using toilets. Large family size and low caste were found to be other predictors of non-use of toilets. Rural women did not use toilets for menstrual purposes as they do not consider these places as clean and safe. Conclusion: This study clearly suggests that constructing toilets without adequate behaviour change interventions would not solve the problem of hygiene and sanitation in India, particularly in rural areas. There must be adequate monitoring of SBA scheme and utilization of funds for toilet usage. Development and implementation of suitable behaviour change strategies for toilet use in rural areas are essential to achieve the goal of open defaecation-free India.

This research aims to provide an efficient and cost-effective renewable energy supply. It assesses the potential for photovoltaic (PV) and hydro energy in Pirthala, Haryana, India, using HOMER Pro® v3.14.2. A Hybrid renewable energy system (HRES) can continuously power 855 homes. The optimal HRES configuration comprises well-optimized PV modules, hydro turbines, converters, and batteries. The top four configurations were selected based on criteria such as net present cost (NPC) and cost of energy production (COE). The most effective HRES configuration involves a 3461-kW solar array, a 98.1 kW hydro turbine, 304 lithium-ion batteries of 100 kWh, and a 2785-kW converter, achieving a 100 % integration of renewable energy. This ideal HRES was thoroughly assessed regarding economic, technical, and renewable energy considerations. The results and the optimized HRES configuration can serve as a valuable reference for similar initiatives in rural areas, contributing to adopting renewable energy sources and enhancing energy access and reliability.

The Human Epidermal Growth Factor Receptor 2 (HER2) is one of the aggressive subtypes of breast cancer. The HER2 status decides the requirement of breast cancer patients to receive HER2-targeted therapy. The HER2 testing involves combining Immunohistochemistry (IHC) screening, followed by fluorescence in situ hybridization (FISH) for cases where IHC results are equivocal. These tests may involve multiple trials, are time intensive, and tend to be more expensive for certain classes of people. Hematoxylin and Eosin (HE) staining is employed for visualizing general tissue morphology and is a routine, cost-effective method. In this study, we introduce a novel automated class-wise weighted average ensemble deep learning algorithm at the decision level. The proposed algorithm fuses three pre-trained deep-learning models at the decision level by assigning a weight to each class based on their performance of the model to classify the HE-stained breast histopathology images into multi-class HER2 statuses as HER2-0+, HER2-1+, HER2-2+, and HER2-3+. The class-wise weight allocation to the base classifiers is one of the key features of the proposed algorithm. The presented framework surpasses all the existing methods currently employed on the Breast Cancer Immunohistochemistry (BCI) dataset, establishing itself as a dependable approach for detecting HER2 status from HE-stained images. This study highlights the robustness of the proposed algorithm as well as the sufficient information encapsulated within HE-stained images for the effective detection of the HER2 protein present in breast cancer. Therefore, the proposed method possesses the potential to sideline the need for IHC laboratory tests, which hoard time and money.

Abstract Topological slow light exhibits potential to achieve stopped light by virtue of its widely known robust and non-reciprocal behaviours. Conventional approach for achieving topological slow light often involves flat-band engineering without disentangling the underlying physical mechanism. Here, we unveil the presence of counter-propagating waves within valley kink states as the distinctive hallmark of the slow light topological photonic waveguides. These counter-propagating waves, supported by topological vortices along glide-symmetric interface, provide significant flexibility for controlling the slowness of light. We tune the group velocity of light by changing the spatial separation between vortices adjacent to the glide-symmetric interface. We also dynamically control the group delay by introducing a non-Hermitian defect using photoexcitation to adjust the relative strength of the counter-propagating waves. This study introduces active slow light topological photonic device on a silicon chip, opening new horizons for topological photon transport through defects, topological light-matter interactions, nonlinear topological photonics, and topological quantum photonics.

Background: Lack of interest has been cited by many studies as the predominant cause for students undervaluing the subject of Community Medicine. However, there are few valid and reliable tools that could measure this interest. To develop and validate a questionnaire to measure a medical student's interest in the subject of Community Medicine. Material and Methods: Cross-sectional study conducted at MTMC Jamshedpur. The Community Medicine Interest Questionnaire (CMIQ) was developed in two phases: item generation and item reduction. Items were generated through a review of the literature, focused group discussions, and in-depth interviews. In the item reduction phase, the content and construct validity of the questionnaire were ascertained. Content validity was carried out by a group of experts based on three parameters: the interrater agreement on the representativeness of the item, the interrater agreement on the clarity of the items, and the content validity index. The construct validity was ascertained through pilot testing of 480 responses from undergraduate medical students. Exploratory factor analysis through principal axis factoring and Promax rotation. Results: Twenty-five items were generated. Three of these items were removed following expert validation. Furthermore, three items were removed after pilot testing. The resulting CMIQ consisted of 19 items distributed over three dimensions: feeling, value, and predisposition to reengage toward the subject. The internal consistency of each of the subscales was ascertained. Conclusions: CMIQ is a valid and reliable tool that can be used to measure such interest for providing educational interventions.

Introduction: Family adoption program (FAP) incorporated into the undergraduate medical education curriculum is beneficial to all stakeholders involved. Many medical colleges have started FAP at different times and various levels based on resources availability, feasibility, and accessibility. This article is intended to cover the process of FAP implementation, the strength, weakness, opportunities, and challenges at various levels, and its scope in future. Methodology: FAP was launched by adopting a hamlet 17 km away from the college. During the foundation course, orientation lessons and logbook discussions were conducted online before the actual field visit. During the initial visit, families were assigned, which was followed by collecting sociodemographic information, a plantation drive, and organizing medical camp/ door to door screening in the last visits for phase one students. Observations: The strengths perceived were early community exposure of students and leadership skills, and the weaknesses were allocating adequate number of slots in the curriculum, adopting families far away, etc., Similarly, FAP has an opportunity to achieve the larger goal of Heath for All in terms of identifying, following up, and managing various socio clinical cases in the adopted families. However, few challenges can pose as it progresses across other phases, such as language problem, allotment of problem families, existing social pathology in family, cultural taboos, etc., Conclusion: The article suggests that once a student leaves, another student should continue the cycle of adoption and provide continuum care of services to prevent the family from being orphaned.

In this article, the comparison of nanosheet (NS) FET, CombFET, and TreeFETs at advanced technology nodes is performed. Initially, the DC metrics like $I_{\mathrm {ON}}$ , $I_{\mathrm {ON}}/I_{\mathrm {OFF}}$ and $I_{\mathrm {D}} - V_{\mathrm {DS}}$ are dominated by TreeFET compared to Comb and NSFET. The TreeFET exhibits higher $I_{\mathrm {ON}}$ and ensures high-performance (HP) applications at advanced nodes. However, the NSFET continues as a better performer towards low power (LP) applications. The TreeFET dominates the performance and switching performance for temperature variation. At lower temperatures, the NS, Comb, and TreeFETs have a marginal impact on $I_{\mathrm {OFF}}$ . The analog performance is dominated by TreeFET due to higher $I_{\mathrm {ON}}$ . The NSFET exhibits lower $C$ gd and $C$ gs due to the absence of interbridges (IB) between channels. The RF performance is also dominated by Comb and TreeFETs due to the presence of IBs. Further, TreeFET based CMOS inverter outperforms in terms of switching current ( $I_{\mathrm {SC}}$ ) compared to the NSFET and CombFET counterparts. The 27-stage ring oscillator (RO) performance of TreeFET dominates Comb and NSFET with 11.56 GHz ensuring driving radio frequency applications. Thus, the paper will give deep insights into the performance of emerging FETs at both device as well as circuit levels.

Private Fifth Generation (5G) Networks can quickly scale coverage and capacity for diverse industry verticals by using the standardized 3rd Generation Partnership Project (3GPP) and Open Radio Access Network (O-RAN) interfaces that enable disaggregation, network function virtualization, and hardware accelerators. These private network architectures often rely on multi-cell deployments to meet the stringent reliability and latency requirements of industrial applications. One of the main challenges in these dense multi-cell deployments is the interference to/from adjacent cells, which causes packet errors due to the rapid variations from air-interface transmissions. One approach towards this problem would be to use conservative modulation and coding schemes (MCS) for enhanced reliability, but it would reduce spectral efficiency and network capacity. To unlock the utilization of higher efficiency schemes, in this paper, we present our proposed machine-learning (ML) based interference prediction technique that exploits channel state information (CSI) reported by 5G User Equipments (UEs). This method is integrated into an in-house developed Next Generation RAN (NG-RAN) research platform, enabling it to schedule transmissions over the dynamic air-interface in an intelligent way. By achieving higher spectral efficiency and reducing latency with fewer retransmissions, this allows the network to serve more devices efficiently for demanding use cases such as mission critical Internet-of-Things (IoT) and extended reality applications. In this work, we also demonstrate our over-the-air (OTA) testbed with 8 cells and 16 5G UEs in an Industrial IoT (IIoT) Factory Automation layout, where 5G UEs are connected to various industrial components like automatic guided vehicles (AGVs), supply units, robotics arms, cameras, etc. Our experimental results show that our proposed Interference-aware Intelligent Scheduling (IAIS) method can achieve up to 39% and 70% throughput gains in low and high interference scenarios, respectively, compared to a widely adopted link-adaptation scheduling approach.

Nanoindentation technique is generally used for measuring thinfilm mechanical properties such as hardness, modulus and stiffness. Nanoindentation of ceramic thinfilms of SiO2, Si3N4 and Al2O3 was deposited by radio-frequency (RF) magnetron sputtering on the stainless steel (SS304) substrates using a nanoindenter. Under varied sputtering conditions, the “as-deposited” film was amorphous. The as-deposited thin film had a thickness of 200 nm. The amorphous film was loaded/unloaded only once while operating in load control mode. Hardness and Young's modulus, two mechanical properties of the ceramic thinfilms, were also measured. When SiO2, Si3N4, and Al2O3 thinfilms are deposited onto stainless steel substrates using an RF magnetron sputtering, the roughness of the ceramic thinfilms is in the range of 8 to 12 nm. The nanoindentation results were compared, the hardness of the coatings is in the range of 6 to 9 GPa, and these ceramic coatings can be used as an adhesive layer for multilayer thin film coating.

The coating materials, thickness and number of layers directly influence the reflectance and absorptance properties of the thin films. However, while selecting the materials for single and coatings, the substrate’s refractive index; bond layer, functional layer and protective layer have to be carefully chosen to obtain the desired reflectance and absorptance values. Hence, modelling and simulating the thin film coatings is essential before conducting the experiments to get meaningful results. The simulation results of single coatings have been discussed. Generally, glass is one of the widely used substrate materials for solar reflectors, aluminum is the optimal functional material, with a reflection of 93 % of light. Nickel would be a preferable functional layer with a reflection of 64 % and absorptance of 36 %, Si3N4 being the acceptable bond layers and protective layers with a reflection of 68 % some solar thermal receiver tube applications however research effort is being made to find alternate lightweight materials for this application. Polycarbonate has been chosen as an alternate material for the substrate because it is light in weight with a reflection of 93 %, which is durable and not fragile.

Melanoma is a type of skin cancer that poses significant health risks and requires early detection for effective treatment. This study proposing a novel approach that integrates a transformer-based model with hand-crafted texture features and Gray Wolf Optimization, aiming to enhance efficiency of melanoma classification. Preprocessing involves standardizing image dimensions and enhancing image quality through median filtering techniques. Texture features, including GLCM and LBP, are extracted to capture spatial patterns indicative of melanoma. The GWO algorithm is applied to select the most discriminative features. A transformer-based decoder is then employed for classification, leveraging attention mechanisms to capture contextual dependencies. The experimental validation on the HAM10000 dataset and ISIC2019 dataset showcases the effectiveness of the proposed methodology. The transformer-based model, integrated with hand-crafted texture features and guided by Gray Wolf Optimization, achieves outstanding results. The results showed that the proposed method performed well in melanoma detection tasks, achieving an accuracy and F1-score of 99.54% and 99.11% on the HAM10000 dataset, and an accuracy of 99.47%, and F1-score of 99.25% on the ISIC2019 dataset.• We use the concepts of LBP and GLCM to extract features from the skin lesion images.• The Gray Wolf Optimization (GWO) algorithm is employed for feature selection.• A decoder based on Transformers is utilized for melanoma classification.

The Raniganj coalfield, which is the oldest coal mine in India, is susceptible to ground subsidence. For the purpose of detecting surface deformation, this work makes use of field surveys, interferometric synthetic aperture radar (InSAR), and Differential GPS (DGPS). The study utilised Sentinel-1 InSAR data spanning from 2017 to 2023. PS-InSAR was used for both ascending and descending datasets, while SBAS-InSAR was used for descending datasets alone. Records show a maximum subsidence rate of −21.18 mm/year. Three surface deformation maps were generated from time-series assessments of individual locations, revealing regions undergoing significant changes. Known mining collapse locations and continuing deformation zones were designated with four differential GPS stations. By analysing the DGPS data with the GAMIT/GLOBK software, we were able to measure surfaces that were undergoing rapid deformation. Using Google Earth Engine (GEE), we generated thermal maps to delve deeper into the coal fire activity. We found coal bed methane (CBM) mining causing substantial subsidence in Kataberia and the surrounding areas. Shyamsundarpur and New Kenda are impacted by mining voids and coal fire-induced subsidence, respectively. The results of this study give the Raniganj region’s decision-making procedures more credibility in terms of minimising and controlling geological dangers.

Digital payments in India are rising with a high share of mobile payments; still, it faces a digital divide. Concerning digital financial services, India has the lowest number of women who owe debit and credit cards, and less than one-third of women receive and make digital payments among the G-20 nations. Hence, the present study investigates female users' risk perception and its effect on trust and satisfaction and, ultimately, continuance usage intention towards mobile payment services. Furthermore, the impact of self-efficacy is examined on continuance usage intentions. This study tested empirical data from 444 existing female mobile payment users. The result indicates that financial and performance risks negatively impact users' satisfaction and trust, but privacy risk has no role among female users. Surprisingly, psychological risk is positively associated with female users' trust and satisfaction, and self-efficacy strengthens continuance usage intention. Trust and satisfaction mitigate risk perception and foster continuance usage.

Objectives: Monitoring of Leishmania transmission is considered a strategic priority for sustaining elimination of visceral leishmaniasis as a public health problem in the Indian subcontinent. The objective of this study was to evaluate whether serological surveys can distinguish between communities with and without Leishmania transmission, and to assess which serological marker performs best. Methods: Seven villages were selected from Bihar and Uttar Pradesh state, India, and categorized as either currently endemic (CE), previously endemic (PE) or nonendemic (NE). Blood samples were analyzed with the rK39 RDT, direct agglutination test (DAT), and rK39 ELISA. Results: Contrary to the rK39 RDT and DAT, the rK39 ELISA showed a significant difference between all three categories of endemicity, with a seroprevalence of 5.21% in CE villages, 1.55% in PE villages, and 0.13% in NE villages. Even when only looking at the seroprevalence among children aged

Background: In the past, microsurgical resection was considered the gold standard treatment for colloid cysts. The endoscopic approach is gaining popularity and has been recognized as a safe and effective alternative to open surgery. Aims: To evaluate our results, safety and efficacy of the endoscopic approach Materials and methods: This retrospective study included seven patients with colloid cysts who underwent endoscopic resection between May 2020 and April 2022. Patient records, radiological images, and surgical notes were assessed. Follow-up data, including clinical and radiological details, were retrieved. Postoperative Computed tomography (CT) was performed, and magnetic resonance imaging (MRI) was performed in all patients. Result: Seven patients aged range 27-56 years 4 males and 3 females underwent endoscopic resection of the tumor during the study period. All patients presented with headaches. The mean diameter of the cyst was 10.6(range 8 -14mm), and the mean operating time was 126(range 100 -180 min). All patients underwent the single burr hole and single port technique. Six patients underwent transforaminal surgery and one patient underwent trans-septal corridor. GTR was achieved in six patients. One patient underwent near-total resection with coagulation of the capsule. None of the endoscopic procedures was converted to open resection. No patient had a recurrence, and the mean follow-up period was 24.3 (range 16 to 36 months). There were no deaths during the follow-up period. No residual cysts were observed on postoperative MRI in any patient. Conclusion: Endoscopic excision of colloid cysts is an effective and safe alternative method. Although the follow-up time was short, the residual cyst wall remained asymptomatic without any evidence of growth after near excision and coagulation of the wall.

Abstract Cancer, being the most formidable ailment, has had a profound impact on the human health. The disease is primarily associated with genetic mutations that impact oncogenes and tumor suppressor genes (TSGs). Recently, growing evidence have shown that X‐linked TSGs have specific role in cancer progression and metastasis as well. Interestingly, our genome harbors around substantial portion of genes that function as tumor suppressors, and the X chromosome alone harbors a considerable number of TSGs. The scenario becomes even more compelling as X‐linked TSGs are adaptive to key epigenetic processes such as X chromosome inactivation. Therefore, delineating the new paradigm related to X‐linked TSGs, for instance, their crosstalk with autosome and involvement in cancer initiation, progression, and metastasis becomes utmost importance. Considering this, herein, we present a comprehensive discussion of X‐linked TSG dysregulation in various cancers as a consequence of genetic variations and epigenetic alterations. In addition, the dynamic role of X‐linked TSGs in sex chromosome–autosome crosstalk in cancer genome remodeling is being explored thoroughly. Besides, the functional roles of ncRNAs, role of X‐linked TSG in immunomodulation and in gender‐based cancer disparities has also been highlighted. Overall, the focal idea of the present article is to recapitulate the findings on X‐linked TSG regulation in the cancer landscape and to redefine their role toward improving cancer treatment strategies.

The current study, deals with the GC-Mass analysis of soil and antibiosis activity of soil bacteria, isolated from district hospital at Kabir Chaura, Varanasi, India. Standard serial dilution plate procedures were used to isolate the bacteria. Gram staining was used to identify the isolates morphologically. Strain KC14 was Gram-negative and all other isolates were Gram-positive. Isolated bacteria were tested against six human pathogens viz., Escherichia coli, Pseudomonas aeruginosa, Salmonella typhi, Staphylococcus aureus, Shigella flexneri and Bacillus subtilis. Primary and secondary screening were done by perpendicular streaking and seed overlay techniques. Based on the results most potential isolates were selected for tertiary screening. The GC-MS of soil samples revealed some major medical pollutants such as para-hydroxy acetanilide, 2-methyl-5-nitro-imidazole and 2-acetoxybenzoic acid. The KC14 isolate was chosen for further studies after demonstrating positive results against S. aureus with a maximum antagonistic activity of 17.3 ± 0.5 zone of inhibition. The molecular identification of KC14 isolate was determined by using 16S rRNA sequencing. The obtained nucleotide sequences were subjected to BLASTN in NCBI, and found similar to the available sequence of Acinetobacter junii. The nucleotide sequences have been deposited in GenBank with accession no. OP265396. The active compound was partially purified by ethyl acetate and tested its activity against S. aureus. This study defines the composition of hospital waste soil and identified a Gram-negative bacterium producing antibacterial activity against important human pathogens.

PurposeThe present study aims to identify the crucial determinants of the adoption of zero-tillage (ZT) technology in maize production in peninsular India. The study also measures the impact of ZT adoption on maize yield, income generation, and the expenses associated with different agricultural operations.MethodologyThe study used multi-stage stratified random sampling and conducted a face-to-face questionnaire survey to collect primary data from 1,189 maize farmers. Initially, the study employed probit regression analysis to identify the ZT adoption determinants. Subsequently, using the Propensity Score Matching (PSM) approach, the study measures the impact of ZT adoption over conventional tillage in terms of yield, income, and cost management. Finally, the Endogenous Switch Regression (ESR) method was implemented to mitigate unobserved heterogeneity and sample selection bias. Additionally, ESR assessed the robustness of PSM results.FindingsThe probit model identifies that variables like education, institutional credit adoption, crop insurance, visit of extension agent, landholding size, and prior experience of new technology adoption positively influence ZT adoption. The PSM and ESR approach results suggest that ZT adoption positively impacts farmers’ yield and net income while reducing cultivation costs and labor use. Results show that ZT adoption decreases the cost of land preparation, weed, pest management, and harvesting by INR 2708 acre−1, INR 167 acre−1, and INR 649 acre−1, respectively, thereby decreasing the overall cultivation cost by INR 8376 acre−1. However, seed and seed treatment costs and irrigation costs improve by INR 108 acre−1 and 176 acre−1 due to the adoption of ZT in maize cultivation. Moreover, ZT improves maize yield by 2.53 quintal acre−1 and minimises 9.56 person-days acre−1. ESR results suggest that the net return from maize cultivation is 26.1% higher for ZT adopters than conventional farmers. Additionally, ZT adopters can save 8.23 man-days acre−1, providing additional monetary benefits of INR 3259 acre−1 compared to ZT non-adopters.Practical implicationsThe study findings may support policymakers in designing suitable agricultural policies to improve technology adoption and motivate small and marginal maize farmers for sustainable production.

The intricate network of glands and organs that makes up the endocrine system. Hormones are used to regulate and synchronize the nervous and physiological systems. The agents which perturbate an endocrine system are called endocrine disruptors and they can eventually affect cellular proliferation and differentiation in target tissues. A subclass of endocrine disruptors known as thyroid disruptors (TDs) or thyroid disrupting chemicals (TDCs) influence the hypothalamo-pituitary-thyroid axis or directly interfere with thyroid function by binding to thyroid hormone receptors. Thyroid hormone levels in circulation are now included in more test guidelines (OECD TG 441, 407, 408, 414, 421/422, 443/416). Although these might be adequate to recognize thyroid adversity, they are unable to explain the underlying mechanism of action. Thyroid peroxidase (TPO) and sodium iodide symporter (NIS), two proteins essential in the biosynthesis of thyroid hormones, are well-accepted molecular targets for inhibition. The screening of a large number of molecules using high throughput screening (HTS) requires a minimum quantity of sample, cost, and time consuming. Whereas 3-dimensional quantitative structure-activity relationship (3D-QSAR) analysis can screen the TDCs before synthesizing a compound. In the present study, the human TPO (hTPO) and NIS (hNIS) structures were modelled using homology modeling and the quality of the structures was validated satisfactorily using MD simulation for 100ns. Further, 190 human TPO inhibitors with IC50 were curated from Comptox and docked with the modelled structure of TPO using D238, H239 and D240 centric grid. The binding conformation of a molecule with low binding energy was used as a reference and the rest other molecules were aligned after generating the possible conformers. The activity-stratified partition was performed for aligned molecules and training set (139), test set (51) were defined. The machine learning models such as k Nearest Neighbor (kNN) and Random Forest (RF) models were built and validated using external experimental dataset containing 10 molecules. Among the 10 molecules, all 10 molecules were identified as TPO inhibitors and demonstrated 100 % accuracy qualitatively. To confirm the selective TPO inhibition all 10 molecules were docked with the modelled structure of hNIS and the results have demonstrated the selective TPO inhibition.