Search

BackgroundProgressive supranuclear palsy (PSP) is a rare neurodegenerative disease characterized by the accumulation of aggregated tau proteins in astrocytes, neurons, and oligodendrocytes. Previous genome-wide association studies for PSP were based on genotype array, therefore, were inadequate for the analysis of rare variants as well as larger mutations, such as small insertions/deletions (indels) and structural variants (SVs).MethodIn this study, we performed whole genome sequencing (WGS) and conducted association analysis for single nucleotide variants (SNVs), indels, and SVs, in a cohort of 1,718 cases and 2,944 controls of European ancestry. Of the 1,718 PSP individuals, 1,441 were autopsy-confirmed and 277 were clinically diagnosed.ResultsOur analysis of common SNVs and indels confirmed known genetic loci at MAPT, MOBP, STX6, SLCO1A2, DUSP10, and SP1, and further uncovered novel signals in APOE, FCHO1/MAP1S, KIF13A, TRIM24, TNXB, and ELOVL1. Notably, in contrast to Alzheimer's disease (AD), we observed the APOE ε2 allele to be the risk allele in PSP. Analysis of rare SNVs and indels identified significant association in ZNF592 and further gene network analysis identified a module of neuronal genes dysregulated in PSP. Moreover, seven common SVs associated with PSP were observed in the H1/H2 haplotype region (17q21.31) and other loci, including IGH, PCMT1, CYP2A13, and SMCP. In the H1/H2 haplotype region, there is a burden of rare deletions and duplications (P = 6.73 × 10-3) in PSP.ConclusionsThrough WGS, we significantly enhanced our understanding of the genetic basis of PSP, providing new targets for exploring disease mechanisms and therapeutic interventions.

Abstract Brainstem cerebral cavernous malformations (CCM) are clinically more aggressive compared to superficial CCMs. Due to their location, resection can be challenging, making stereotactic radiosurgery (SRS) an attractive alternative for symptomatic patient. Brainstem CCM patients (n = 170) were treated with Gamma Knife SRS at 11 radiosurgical centers. Hemorrhagic risk reduction, risk factors of post-SRS hemorrhage, and clinical outcomes were retrospectively analyzed. Most patients had a single (165/170 patients) brainstem CCMs treated; the majority of CCMs (165/181) presented with bleeding. Single-session SRS decreased the risk of repeat hemorrhage in patients with hemorrhagic brainstem CCM (HR: 0.17, p 13 Gy (HR = 2.57, p = 0.044). Adverse radiation effect (ARE) occurred in 9 patients (5.3%) and was symptomatic in four (2.4%). At a median follow-up of 3.4 years (Inter-quartile range: 5.4), 13 patients (8.0%) had a worsened clinical status, with the treated CCM being the cause in 5.6% (10) of the patients. Single-session SRS decreased the risk of repeat hemorrhage in patients with hemorrhagic brainstem CCM and conveyed this benefit with a low risk of advrse radiation effects (ARE) and worsening clinical status.

Abstract It is tough and complex to forecast wind speed due to its intermittent and stochastic nature as well as sudden and abrupt variations in the wind speed. Further, it is required to handle the variety of scenarios e.g. cyber‐attacks, unexpected power device malfunction, communication/sensor outages etc. that can cause the missing data.This paper proposes and employs a de‐noising autoencoder algorithm for wind speed forecasting to ensure the handling of missing data information. At the next step, the data is processed via variational mode decomposition technique to mitigate the noise and improves the model's prediction accuracy. Furthermore, the bi‐directional long‐short term memory deep learning approach is tied with convolution neural network to increase prediction accuracy and anticipating the sudden/abrupt changes in wind speed accurately. Finally, actual wind speed related data is examined to scrutinize meticulousness of projected forecast methodology particularly during sudden/abrupt changes in the wind speed. The parameter indicators of the wind speed forecasting technique exhibit the capability of improved predictions under the diversified conditions.

Introduction: Acute hemorrhagic conjunctivitis (AHC) outbreaks are caused mostly by viruses. During July-August 2023, there was a sudden spike in acute hemorrhage conjunctivitis cases in Eastern Uttar Pradesh, India. To identify the etiological and gain molecular epidemiology of the agent, the study was conducted. Methodology: Conjunctival swabs were collected from patients (n = 128) with presumed acute hemorrhage conjunctivitis visiting two tertiary care hospitals. Results: Enteroviruses infection was identified in 96 (75%) patients. In these patients, coxsackievirus A24 (CV-A24) infection was further confirmed by targeting the genetic regions of 3C protease and VP1. Furthermore, the study established the outbreak was caused by the genotype IV of CV-A24 with the highest genetic similarity with CV-A24 reported from Northeast India, China, and Pakistan circulating during the same period. The comparison of our study sequences with earlier Indian outbreak strains (2007) revealed four amino acid substitutions at the 3C region (“S21N,” “V30I,” “S66I,” and “V75I”) and three non-synonymous mutations at the VP1 region (“L16I,” “P21S,” and “N301D”). Conclusion: The study findings revealed that the AHC outbreak was caused by genotype IV of CV-A24 in this region. Molecular identification accompanied by phylogenetic analysis will be useful in studying the enterovirus epidemiology associated with AHC outbreaks.

Cameras are typically used at road intersections to collect data to perform object detection but struggle in low-light and harsh weather. On the other hand, Light Detection and Ranging (LiDAR) is used as a key technology in 3D vision systems. It gives the 3D point cloud, which includes accurate depth information, but its resolution is cost-dependent, with higher resolutions being more expensive. Deep learning-based method requires large, labelled dataset which increases the cost, time and accuracy depending on the model trained on labelled dataset. To perform object detection in point cloud data is a challenging task due to the incomplete representations, data sparsity and unavailability of training data. To overcome this by using an unsupervised approach, it is important to identify the static scene and then detect the moving object. This work incorporated a novel approach to construct static scene using azimuth angle and laser channel information using an unsupervised clustering approach. This work incorporates two modules I) data collection using VLP-16 LiDAR, and II) static scene construction using DBSCAN (density-based spatial clustering and noise) clustering-based approach. Data is collected at a 4-legged intersection and pre-processed to extract aggregated distances corresponding to the unique pair of azimuth angle and laser channel. DBSCAN is used to perform clustering on the aggregated distances, based on the highest silhouette score and lowest intra distance between points in cluster, static points are identified, and static scene constructed. The qualitative evaluation of method demonstrates that the algorithm effectively and accurately filters out background points.

Abstract Sustainable agriculture is crucial for meeting the growing global food demand. With the pressure of climate change, resource depletion, and the need for increased agricultural productivity, innovative approaches are essential. Nanotechnology is an emerging technology in achieving sustainable development goals (SDGs). Despite its promising benefits, the safe implementation of nanotechnology in agriculture requires careful consideration of potential health and environmental risks. However, there is a lack of comprehensive documentation on the application, potential and limitations of nanotechnology in the field of agriculture. To address this gap, a desk research approach was used by utilizing peer-reviewed electronic databases like PubMed, Scopus, Google Scholar, Web of Science, and Science Direct for relevant articles. Out of 157 initially identified articles, 85 were deemed pertinent, focusing primarily on potential nanotechnology in smart agricultural systems. Taking into account research findings worldwide, we found significant improvements with nanotechnology over traditional methods which underscores the practical benefits of nanotechnology, including increased crop yields, efficient resource use, and reduced environmental footprint. The objective of this systematic review is to explore the nexus between nanotechnology and agricultural systems, highlighting its potential to enhance productivity, sustainability, and resilience and to inform researchers, practitioners, and policymakers about the transformative impact of nanotechnology on sustainable agriculture and underscores the need for further research to address safety concerns and maximize its potential for agricultural advancement.

Abstract Seasonal epidemics of influenza viruses are responsible for a significant global public health burden. Vaccination remains the most effective way to prevent infection; however, due to the persistence of antigenic drift, vaccines must be updated annually. The selection of vaccine strains occurs months in advance of the influenza season to allow adequate time for production in eggs. RNA vaccines offer the potential to accelerate production and improve efficacy of influenza vaccines. We leveraged the nucleoside-modified RNA (modRNA) platform technology and lipid nanoparticle formulation process of the COVID-19 mRNA vaccine (BNT162b2; Comirnaty®) to create modRNA vaccines encoding hemagglutinin (HA) (modRNA-HA) for seasonal human influenza strains and evaluated their preclinical immunogenicity and toxicity. In mice, a monovalent modRNA vaccine encoding an H1 HA demonstrated robust antibody responses, HA-specific Th1-type CD4+ T cell responses, and HA-specific CD8+ T cell responses. In rhesus and cynomolgus macaques, the vaccine exhibited durable functional antibody responses and HA-specific IFN-γ+ CD4+ T cell responses. Immunization of mice with monovalent, trivalent, and quadrivalent modRNA-HA vaccines generated functional antibody responses targeting the seasonal influenza virus(es) encoded in the vaccines that were greater than, or similar to, those of a licensed quadrivalent influenza vaccine. Monovalent and quadrivalent modRNA-HA vaccines were well-tolerated by Wistar Han rats, with no evidence of systemic toxicity. These nonclinical immunogenicity and safety data support further evaluation of the modRNA-HA vaccines in clinical studies.

Abstract Introduction Primary health care has regained its importance in global policy making. In 2018, the Government of India initiated the Ayushman Bharat - Comprehensive Primary Health Care (AB-CPHC) programme. It was based on upgrading the existing primary health facilities into Health and Wellness Centers (HWCs). The current study aimed to assess the readiness and performance of HWCs in providing comprehensive primary health care services in India’s Chhattisgarh state. Methods We conducted a cross-sectional health facility assessment with a state-representative sample of 404 HWCs. A standardized health facility survey tool was used to collect information on essential inputs and service outputs of HWCs. The expected population healthcare needs were estimated using secondary sources. The performance of HWCs was assessed by comparing the volume of services provided against the expected population need for outpatient care. Results On an average, 358 outpatients including 128 non-communicable disease (NCD) patients were treated monthly at an HWC. HWCs were able to cover 31% of the total population’s health need for outpatient care, 26% for hypertension, and 21% for diabetes care. In addition to services for reproductive and child health, HWCs provided services for common acute ailments (cold, cough, fever, aches and pains); infections of skin, eye, ear, and reproductive tract, and minor injuries. HWCs were also contributing significantly to national disease control programmes. Acute ailments followed by NCDs and communicable diseases had the largest share among services provided. The key gaps were in coverage of mental illnesses and chronic respiratory diseases. Most of the HWCs showed adequate readiness for the availability of required human resources, supplies, and infrastructure. Conclusion HWCs were able to provide a comprehensive range of primary care services and able to cater to a sizable portion of the rural population’s acute and chronic health care needs. The performance was made possible by the adequate availability of medicines, staff, training programmes and tele-consultation linkages. If HWCs in other states are able to reach a similar level of performance, the initiative will prove to be a game changer for equitable primary care in India.

Abstract This paper comprehensively analyses the specific absorption rate (SAR) for an ultra-wideband (UWB) wearable antenna designed for body-centric communication applications. The study is motivated by the extent of electromagnetic radiation in our surroundings, raising worries about health for wireless device users and wearable devices that utilize UWB technology. The proposed antenna is made of a foam substrate having a dielectric constant of 1.07, a thickness of 2 mm with a dimension of $$36\times 48\times 2 {\text{mm}}^{3}$$ 36 × 48 × 2 mm 3 . The designed structure optimizes UWB (3.1–10.6 GHz) in connotation with the ISM band of 2.4 GHz. The proposed antenna works well over the wide frequency range resulting in a bandwidth of 11.53 GHz and a total gain of 8.05 dBi. An excellent impedance matching is obtained by creating a stub at the feed point which gives the maximum value of S11 as − 44.88 dB. The analysis focuses on the SAR values to measure the rate of electromagnetic energy absorption by human tissues over 1 and 10 g by constructing an equivalent three-layer body phantom model. The results indicate that the proposed antenna exhibits SAR values well within the limits set by international standards of 1.6 W/kg averaged over 1 g of tissue and 2 W/kg for 10 g of tissue, while maintaining efficient radiation characteristics across the UWB spectrum.

Abstract Two-dimensional transition metal dichalcogenides (TMDs)-based memristors are promising candidates for realizing artificial synapses in next-generation computing. However, practical implementation faces several challenges, such as high non-linearity and asymmetry in synaptic weight updates, limited dynamic range, and cycle-to-cycle variability. Here, utilizing optimal-power argon plasma treatment, we significantly enhance the performance matrix of memristors fabricated from monolayer MoS2. Our approach not only improves linearity and symmetry in synaptic weight updates but also increases the number of available synaptic weight updates and enhances Spike-Time Dependent Plasticity. Notably, it broadens the switching ratio by two orders, minimizes cycle-to-cycle variability, reduces non-linear factors, and achieves an energy consumption of ~30 fJ per synaptic event. Implementation of these enhancements is demonstrated through Artificial Neural Network simulations, yielding a learning accuracy of ~97% on the MNIST hand-written digits dataset. Our findings underscore the significance of defect engineering as a powerful tool in advancing the synaptic functionality of memristors.

Abstract Background The variational method, a quantum mechanical approach, estimates effective charge distributions and ground-state energy by minimizing the Hamiltonian's expectation value using trial wave functions with adjustable parameters. This method provides valuable insights into system behavior and is widely used in theoretical chemistry and physics. This paper aims to investigate ground-state energies and isoelectronic sequences using the variational method, introducing a novel approach for analyzing multi-electron systems. This technique allows for determining effective charge values and ground-state energies for 2–5 electrons sequence up to Z ≤ 20. Hydrogenic wave functions are used as a trial wave function to calculate effective charge in 1 s, 2 s, and 2p states. Two varying parameters were used to calculate an approximate wave function for the system. These values are then used in non-relativistic Hamiltonian with electron–electron interaction terms to calculate the ground-state energy of an atom. Result The results align with the reported experimental values, showing a marginal 1% error. Conclusion A Python algorithm is established based on the variational principle. It was found that, based on a few selected parameters in scripting the program, a very promising result was obtained. Furthermore, adding more variational parameters can minimize the difference between experimental and theoretical values, and this technique can be extended to elements with higher atomic numbers.

Background: Undergraduate students from all fields of study are under constant perceived stress due to workload, and their perceptions about academic success. Determining the difference in the perception of Academic stress to cope with it. Objective: To determine the differences in perceptions of academic stress among medical and non-medical undergraduates. Materials and Methods: In this comparative cross-sectional study, data was collected through a stratified sampling technique from undergraduate medical (n=200) and non-medical (n=200) students. This research included male and female undergraduate students with a minimum of 50% attendance. Data was collected through the Perception of Academic Stress Scale (PASS) to measure the perception of academic stress. An online structured questionnaire was shared through a communication media platform and data analysis was made through SPSS version 27. Results: There were n=179 male undergraduates and n=221 female undergraduate students. The overall PASS score showed no significant difference (p≥0.05) in Perceived Academic stress in Medical and Non-Medical Undergraduate students and between male and female students. Conclusions: This study found moderate level of Perceived academic stress to be the most prevalent with no significant difference in the perception of academic stress between medical and non-medical students. Additionally, it showed that male and female students experienced similar levels of academic stress.

This study presents a novel integration of bibliometric and content analysis to comprehensively examine the research trends and scientific landscape of paver blocks. The investigation of 379 articles and reviews published across 174 journals reveals a steady growth in research output, with a notable surge in publications and citations from 2016 to 2024, underlining the increasing importance of this field. India, Malaysia, and the United States emerge as major contributors, with India leading in publication count (143) and the United States demonstrating high research impact through total citations (1,312) and citations per paper (48.59). Keyword examination highlights the prominence of sustainable materials, waste utilization, and innovative design strategies, while an in-depth review of highly cited papers unveils the potential for incorporating various waste streams to produce high-quality, eco-friendly paver blocks. Over the years, the research focus has expanded from conventional materials to recycled aggregates, permeable designs, and photocatalytic applications. This study identifies research gaps, such as the need for long-term performance assessment and life cycle analysis, and recommends future directions, including integrating paver blocks into urban planning and design strategies. The findings guide researchers and policymakers in the development of sustainable, resilient, and multifunctional paver block solutions.

Rising CO2 concentration in the atmosphere is a matter of global concern and poses apprehension about how plants will adapt to the changing environment. Various studies have proved that under high CO2 levels, plant physiology alters and affects plant functioning. However, under elevated CO2, the stomatal characters and their relation with physiological responses are still not yet clear. To find out these changes in the stomatal parameters at ambient and two elevated CO2 (550 ppm and 700 ppm) levels, four genotypes of maize (Zea mays L.) viz. DHM-117, Harsha, Varun and M-24 were grown in open-top chambers. In the study, it was observed that the stomatal density increased, stomatal size altered, stomatal conductance (gs) and transpiration rate (Tr) decreased under elevated CO2 (eCO2) while photosynthetic rate (Pn), water use efficiency (WUE), yield and biomass, of which especially the reproductive biomass increased. Under eCO2, stomatal and physiological changes were genotypic and CO2 concentration specific. Increased stomatal density at eCO2 was mainly due to increased abaxial stomatal density. The improved Pn and reduced Tr at 550 ppm improved the WUE in the plants, while this response was not observed at 700 ppm. These results elucidate that this C4 crop responded positively to up to 550 ppm of CO2 concentrations, and beyond this, the impact was minimal.

Abstract Ficus auriculata (Timla) is an underutilized wild fruit compared to the more commonly consumed fruit of the same genus, Ficus carica (Anjeer). This review focuses on the industrial and pharmaceutical benefits of F. auriculata while highlighting its potential as a valuable alternative to F. carica. Based on the vast literature found in Scopus database, both fruits have significant nutritional and medicinal value; however, due to the rarity and lack of widespread knowledge, F. auriculata still remains underutilized, unlike F. carica, which is well known and more popular in the human diet. In terms of nutrition, F. auriculata is superior in various aspects like protein (3–5.32%), magnesium (68.0 mg/100 g), potassium (329.0 mg/100 g), and iron (5.0 mg/100 g). As a result, it plays a pivotal role for addressing nutrient deficiencies. Besides, it has rich history of many noteworthy applications in traditional remedies which are also recognized in modern pharmaceutical research. This could be attributed to the presence of phytocompounds. Ficus auriculata needs to be promoted, not only as a nutritional addition to the plate but also as an economically viable fruit. Based on its considerable potential, it is possible that F. auriculata can also be used as an alternative to F. carica; however, further research and promotion of the benefits of F. auriculata could help to increase its utilization and provide additional health and economic benefits to communities. Moreover, omics technologies based comprehensive study of fruits can assist in the identification of bioactive metabolites, nutritional content, and possible health benefits. It offers insights into the genetic composition, gene expression patterns, protein activities, and metabolic pathways of fruits thereby revealing the mechanisms driving flavor, color, and disease resistance.

Abstract Sugarcane smut is the most damaging disease that is present almost across the globe, causing mild to severe yield losses depending upon the cultivar types, pathogen races and climatic conditions. Cultivation of smut-resistant cultivars is the most feasible and economical option to mitigate its damages. Previous investigations revealed that there is a scarcity of information on early detection and effective strategies to suppress etiological agents of smut disease due to the characteristics overlapping within species complexes. In this study, 104 sugarcane cultivars were screened by artificial inoculation with homogenate of all possible pathogen races of Sporisorium scitamineum during two consecutive growing seasons. The logistic smut growth pattern and the disease intrinsic rate were recorded by disease growth curve. Variable levels of disease incidence i.e., ranging from 0 to 54.10% were observed among these sugarcane cultivars. Besides, pathogen DNA in plant shoots of all the cultivars was successfully amplified by PCR method using smut-specific primers except 26 cultivars which showed an immune reaction in the field trial. Furthermore, the plant germination and tillering of susceptible sugarcane cultivars were greatly influenced by pathogen inoculation. In susceptible cultivars, S. scitamineum caused a significant reduction in setts germination, coupled with profuse tillering, resulting in fewer millable canes. Correlation analysis demonstrated that there was a positive relationship between reduction in setts germination and increase in the number of tillers. The present study would be helpful for the evaluation of smut resistance in a wide range of sugarcane germplasm, especially from the aspects of setts germination and tillers formation, and it also screened out several excellent germplasm for potential application in sugarcane breeding.