Crochetage Sign on ECG in ASDSweta Singh1, Abhishek Thakur2, Saurav Jha31B.P Koirala Institute of Health Sciences, Dharan, Nepal, 2National Cardiac Centre, Kathmandu, Nepal,3Manipal College Of Medical Sciences, Pokhara, NepalCorrespondence: Dr. Abhishek Thakur, National Cardiac Centre, Kathmandu, Nepal, Email: abhishekthakur1039@gmail.com

ABSTRACT Background The emergence of novel reassortant influenza A virus strains and zoonotic transmission to the human population is a critical factor in the development of a global pandemic, as exemplified by the 2009 swine flu pandemic, and the ongoing threat of an H5N1 avian flu pandemic. Small, unconjugated synthetic peptide vaccines comprising multiple, highly conserved epitopes may provide an important strategy towards a cost-effective, easily scalable, supra-seasonal universal influenza vaccine that can target across human, swine and avian strains, advancing pandemic preparedness. Objective The aim of this study was to evaluate the immunogenicity of a synthetic, single, unconjugated, multi-epitope composite peptide vaccine targeting human, swine, and avian zoonotic viruses. Methods Outbred mice were immunized with different doses of the single peptide vaccine LHNVD-110, and immunogenicity was evaluated using ELISA, Hemagglutinin Inhibition Assay, Microneutralization Assay, and Enzyme-linked Lectin Assay. Results Strong IgG1 (Th2) and IgG2a (Th1) responses were generated against HA, NA and Matrix epitopes, and multiple strains of influenza A/H1N1pdm09, A/H3N2, A/H5N1 (HPAI) and B/Victoria viruses. Cross-reactive, neutralizing antibodies also showed inhibition of multiple viral HA and NA subtypes, demonstrating the breadth of humoral responses. Conclusion This single, unconjugated, multi-epitope, composite peptide vaccine, generated a robust and balanced immune response inhibiting multiple HA and NA subtypes across human, swine and avian viruses. This approach provides a cost-effective, easily scalable, seasonal, and pandemic vaccine option with the potential of a universal influenza vaccine and efficient pandemic readiness.

Artificial intelligence (AI) in maternal healthcare presents both opportunities and risks. While AI can enhance risk detection, personalized care, and maternal health education, it also risks reinforcing disparities through biased algorithms, misinformation, and data colonialism. AI models, often developed in high-income settings, may misdiagnose conditions, and exacerbate inequities in resource-limited regions. Ethical deployment, diverse datasets, and robust governance are essential to ensure AI bridges—rather than widens—maternal health gaps. This commentary underscores the need for equitable AI integration to maximize benefits while mitigating harm.

Giant asymptomatic intermuscular lipoma of right thigh- Case report and review of literature.Letho Letho1 Nishal Chhetri21 Department of Orthopedics, Jigme Dorji Wangchuck National Referral Hospital, Thimphu, Bhutan2 Department of Pathology and Laboratory Services, Jigme Dorji Wangchuck National Referral Hospital, Thimphu BhutanCorrespondence: Letho Letho (letho@jdwnrh.gov.bt)Keywords: Giant lipoma, asymptomatic, intermuscular, Case Report

Pulmonary hypertension (PH) is a fatal cardiovascular disorder characterized by the remodeling of pulmonary vasculature, which serves as a key pathological feature. Treatment options remain constrained, and significant gaps persist in our foundational, clinical, and translational knowledge, thereby necessitating further investigation. Extensive evidence suggests that dysfunction in diverse types of vascular cells plays a critical role in the pathogenesis of PH, with metabolic reprogramming profoundly influencing this process. Nevertheless, the precise molecular mechanisms involved remain poorly understood. Recent studies indicate that epigenetic abnormalities modulate cellular metabolism by altering the gene expression of essential metabolic enzymes, either directly or indirectly. As the role of epigenetics in PH becomes progressively elucidated, it offers promise for establishing a coherent framework for understanding metabolic reprogramming in cells affected by PH. This review concentrates on the alterations in glucose, lipid, and amino acid metabolism of vascular cells within the framework of pulmonary hypertension and delineates the advancements in research concerning epigenetic modifications linked to metabolic regulation in this condition. The reversibility of epigenetic modifications provides the opportunity to rectify their aberrant states. Consequently, targeting epigenetic modifications is considered an appealing therapeutic target for pulmonary hypertension. Finally, we provide a comprehensive summary of the prospects and challenges associated with potential therapeutic strategies for pulmonary hypertension, which are predicated on the reprogramming of vascular cell metabolism via epigenetic modifications.

Drought stress poses a serious threat to agricultural growth and productivity worldwide as climate change worsens. bHLH transcription factors play a significant and diverse role in plant stress response, yet the regulatory network of bHLH transcription factors in eggplant ( Solanum melongena L.) under drought stress remains unclear. Here, we cloned SmMYC2 gene from “March eggplant” leaves, which belongs to the bHLH transcription factor (TF) family and located in the nucleus. Through quantitative real-time PCR (qRT-PCR), we demonstrated that SmMYC2 expression was substantially higher in leaves, with tender leaves expressing the most and fruits expressing the least. Compared with the wild type (WT), the SmMYC2 overexpression eggplants plants ( SmMYC2-OE) showed enhanced drought resilience, lower MDA conten, higher SOD content in the leaves, but no significant difference in POD enzyme activity after drought treatment. Meanwhile, SmMYC2-OE plants exhibited a considerable increase in stem thickness and we found that the SmMYC2 gene can bind to the SmNST1 promoter to participate in the regulation of secondary cell wall (SCW) thickening. Furthermore, double molecule fluorescence (BiFC) assay and luciferase complementation (LCI) analysis showed that SmMYC2 can interacts with SmJAZ1, SmJAZ3, and SmMYB21 in vivo. Through the yeast one-hybrid (Y1H) assay and the luciferase reporter system (LUC) assay, we revealed that SmMYC2 engaged in negative feedback regulation by binding to its own promoter and inhibited its transcription in eggplant. Additionally, we found that SmMYC2 can also bind to SmMYB108 promoters and decrease its expression but act as an activator and interact with SmNST1 promoter in vivo. Together, the results of this study may reveal that SCW thickening is related to enhanced drought resistance in eggplants, and further provide insights into its regulatory network, which may greatly improve agricultural productivity.

Using high- and low-flatness fruits of Ziziphus jujuba Mill. cv. ’Lingwuchangzao’ at different developmental stages as test materials, this study examined the mechanisms underlying variations in fruit appearance and internal quality. The findings revealed significant differences between S and R fruits throughout development. S fruits were glossy, smaller, and predominantly seedless, with lower single-fruit weight and thinner pericarp and pulp, while R fruits exhibited reduced glossiness, larger size, and deeper coloration. Transcriptome analysis identified key genes, including CER1 and FAR, involved in wax synthesis, influencing cuticular wax production on the fruit surface. Additionally, genes such as AUX/IAA affected epidermal cell development, leading to smaller and denser cells in R fruits, thereby impacting surface flatness. Collectively, genes regulating cell development and wax biosynthesis determined the glossiness of Lingwu jujube fruits. Metabolomic analysis identified 779 metabolites, with flavonoids constituting the most abundant class. Protein interaction network analysis highlighted the hub gene ABCG31, closely linked to wax synthesis, as a critical factor in fruit flatness and glossiness. This study elucidates the quality differences and molecular regulatory mechanisms between high- and low-flatness Lingwu jujube fruits, offering valuable insights for genetic improvement to enhance visual appeal and commercial value.

ABSTRACT Background: The plantar fascia develops a degenerative disease called plantar fasciitis. The most prevalent cause of inflammation in the inferior heel is plantar fasciitis. Excessive stretching can develop plantar fasciitis, an inflammatory disorder of the plantar fascia that can cause ripping and inflammation of the fascia. Plantar fasciitis is considered the etiology of 11% to 15% of foot complaints that need medical attention. Plantar fasciitis affects two million people, resulting in one million outpatient visits per year. The aim of this study is to find out the effect of Muscle Energy Technique versus Conventional exercise on pain and functional outcome in subjects with Plantar Fasciitis. Methods: Subjects with plantar fasciitis were included based on the selection criteria. The plantar fasciitis pain/disability scale was used to calculate pre and post-test results. The subjects were randomly assigned into, Muscle Energy Technique group (n=30) followed by post isometric relaxation and reciprocal inhibition and received muscle energy technique and to Conventional exercise group(n=30) received stretching of calf muscle and plantar fascia and strengthening the intrinsic foot muscles followed by ultrasound for 15 minutes. Result: According to the statistical analysis, both groups had a statistically significant improvement between their pre and post values (p<0.0001). There was significant variation in postexercise results between the two groups (p<0.0001), indicating that muscle energy technique is more effective than conventional exercise. Conclusion: Muscle energy technique has been shown to be more effective than Conventional exercise at relieving pain and improving functional outcome. Keywords: Conventional; Muscle energy technique; Plantar fasciitis; Ultrasound. Abbreviations: MET – Muscle Energy Technique, PF- Plantar fasciitis, PFPS-Plantar Fasciitis Pain/Disability Scale, PIR- Post Isometric Relaxation, RI- Reciprocal Inhibition.

Preprint Version 

Another groundbreaking discovery after graphene is goldene (Kashiwaya et al.,2024). It joins the list of novel 2D materials. It is the first stable monolayer metal sheet and expected to bring in new physics like graphene. We have designed, for the first time, goldene and its bilayer. The bandstructure of goldene has new features forecasting multiple applications. As a first step the interaction of H 2 with goldene is investigated. The H 2 undergoes non-dissociative adsorption on the surface of goldene which is unusual for a metallic surface. Unlike graphene bilayer goldene bilayer turns out to be a quasi 2D material harbouring many interesting properties.

IntroductionThere are few reports on arrhythmia treatment in patients with the later-onset phenotype of Fabry disease (FD). Case reportAblation was performed for recurrent atrial fibrillation (AF) in a patient with FD. Even after the re-isolation of the left inferior pulmonary vein (LIPV), AF was easily induced. After fractionated signal area ablation,

Copper (Cu) is a recyclable, abundant, and promising catalyst for energy transition reactions like electrochemical conversion of nitrate (NO₃RR) and CO2 electroreduction. However, conventional Cu-based electrocatalysts struggle with activity, selectivity, and durability, especially under harsh electrochemical conditions. Exsolution—the in-situ generation of metallic nanoparticles on oxide supports in a single step—enables tightly anchored, size-controlled particles, enhancing stability and performance. Incorporating Cu into Sr1-α(Ti, Fe)O₃-γ perovskites, an earth-abundant system with mixed ionic-electronic conductivity and adequate oxygen vacancies, overcomes the limitations of traditional Sr(Ti, Fe)O₃ in facilitating nanoparticle exsolution. In this work, we demonstrate that incorporating Cu-doping into strontium-titanite-ferrite (STF) (Sr0.95Ti0.3Fe0.7-xCuxO3-γ) perovskites promotes the in-situ exsolution of well-dispersed Cu-nanoparticles with tunable properties. The designed material enables nanoparticle formation at temperatures as low as 400 °C within one hour, representing relatively mild temperature conditions and relatively fast exsolution compared to the literature. By varying the exsolution conditions, such as temperature and time, we demonstrate substantial control over nanoparticle characteristics, for example, particle size between ~13 and ~38 nm and population density between ~118 and 650 particles/μm2, allowing the tuning of catalytic activity for NO₃RR. These findings highlight the potential of Cu-doped perovskites as a versatile and sustainable platform for advanced catalytic applications.

This research examines the evolving landscape of LGBT rights and sexual politics in India, focusing on the interplay of homophobia, traditional cultural values, government action, and international human rights frameworks. India's LGBT rights struggle is uniquely shaped by its complex political, religious, and legal environment. The study explores clashes between traditional values and LGBT advocacy, emphasizing the decriminalization of Section 377 and the influence of the Yogyakarta Principles on policy. Analyzing governmental actions, religious discourse, and international human rights law, it highlights India's nuanced LGBT rights movement, distinguishing it from global counterparts. Despite legal progress, societal acceptance remains a significant barrier. By integrating historical and contemporary perspectives, the paper identifies persistent obstacles and critiques gaps in implementing global human rights standards. It concludes with actionable recommendations for advancing LGBT rights in India, underscoring the ongoing tension between legal reforms and societal resistance.

Cardiac resynchronization therapy (CRT) improves outcomes in heart failure patients with left bundle branch block (LBBB), but its efficacy in patients with nonspecific intraventricular conduction delay (NICD) and prolonged PR interval remains uncertain. We present a 69-year-old male with NICD who was successfully treated with individualized atrioventricular (AV) delay optimization using SyncAV™ Plus. This approach resulted in QRS narrowing, echocardiographic improvement, and catecholamine withdrawal. The patient remained stable for two years. This case underscores the role of advanced AV delay programming in optimizing CRT outcomes for NICD patients with PR prolongation.

A key challenge in climate model validation is the limited availability of observationally-based datasets on a global scale. This research addresses this gap by developing global land-atmosphere (LA) coupling metrics derived from gridded observational data while accounting for stochastic errors in soil moisture satellite measurements. These metrics are then validated against global LA coupling metrics derived from the Community Earth System Model (CESM). This dual approach bridges the gap between observational data and model performance.Global observationally-gridded LA coupling metrics are constructed using soil moisture time series from Soil Moisture Active Passive (SMAP L3) satellite, the Climate Change Initiative (ESA CCI v08.1), and soil moisture time series derived through machine learning trained with in-situ measurements (SoMo.ml). Observation-based surface heat fluxes are sourced from the Global Land Evaporation Amsterdam Model (GLEAM). For validation, simulations from the Atmospheric Model Intercomparison Project (AMIP), the Community Land Model (CLM), and the coupled CESM are utilized, ensuring a comprehensive comparison framework.Since soil moisture variability typically resembles a first-order Markov process, it enables the estimation of random errors in soil moisture time series. This characteristic enables the correction of global observationally-gridded LA coupling metrics, making them more robust when accounting for stochastic errors in satellite-based soil moisture data. Two categories of metrics are employed in this study: Soil Moisture Metrics and Bivariate Metrics.Soil Moisture Metrics focus on corrected soil moisture memory and the identification of key breakpoints, such as the wilting point and critical soil moisture, which help delineate regime distributions. On the other hand, Bivariate Metrics examine the corrected Pearson correlation coefficient between soil moisture and surface fluxes—latent heat flux (LE), sensible heat flux (H), and evaporative fraction (EF). This enables the derivation of the Coupling Index, which quantifies the strength of land-atmosphere interaction.To conduct a comprehensive comparison between observational LA coupling metrics and model-based estimates, we apply Soil Moisture Metrics (memory, breakpoints, regime distribution) and Bivariate Metrics (correlations, Coupling Index) to the CESM model, AMIP simulations, and the CLM model. This comparison identifies global regimes and hotspots for LA interactions, highlights regions where model biases are most pronounced, and interprets spatial patterns and seasonal variations in coupling metrics. Ultimately, our findings provide a framework for assessing model performance and can potentially improve parameterizations and climate model predictions.

Plant proteins are increasingly recognized for their role in sustainable diets, with functional properties being critical for food applications. However, the influence of extraction methods on legume proteins remains underexplored. This study compared dry, wet, and mild fractionation for producing protein-rich lentil fractions and assessing their nutritional and functional properties. Red lentils were tempered to 12% moisture, roller-milled, and then pin milled to create a fine parent flour (d90 < 40 μm) suitable for air classification and wet extraction. Air classification at 10,000, 7,000, 6,000, and 4,000 rpm speeds yielded protein-rich fractions, with the 6,000 rpm setting (cut point 22 μm, d90) offering an optimal balance of purity and yield. In wet fractionation, lentil protein isolate (89.2% protein) was produced through alkaline extraction and isoelectric precipitation, while mild extraction produced protein concentrate by just alkaline extraction (64.2% protein). Functional analysis showed wet extracted isolates performed better in emulsification, water, and oil absorption, while dry fractionated proteins performed better in foaming, solubility, and gelling. Mild wet extracted concentrates demonstrated good emulsification and oil absorption but poor foaming stability. Amino acid analysis showed that lentil protein isolate had higher concentrations of hydrophobic amino acids, particularly isoleucine, leucine, and phenylalanine compared to dry fractionated samples, which may contribute to its enhanced emulsifying properties. The dry fractionated samples maintained a similar amino acid profile as that of lentil flour contributing to its native functionality. In conclusion, dry fractionation offers a sustainable, eco-friendly alternative to wet extraction, preserving native protein integrity while delivering comparable functionality.

Sustainability is one of the grand challenges of humanity. This urgency has driven alternatives such as using microalgae to capture and transform carbon dioxide (CO 2) into valuable products. Although all biotechnological processes face several challenges such as scaling up, on-line monitoring, and control of critical biological variables (pH, temperature). For photobioreactors other variables such as light intensity which commonly affects growth phenotypes, are critical to have more efficient bioreactor operations while decreasing shading effects. This work describes the design and development of a low-cost monitoring and control system designed to automate the measuring process of meaningful variables in a photobioreactor. The proposed system is based on Raspberry Pi 4 microcomputer programming with the open-source programming language Python. The performance of the system was evaluated in a bubble column over a ten-day course of growth of the algae Haematococcus lacustris. As expected, the cost of this monitoring system was only the 6% of the average potential cost found in the commercial market. The system has other advantages for example that it is portable and can be installed in different types of photobioreactors (airlift, stirred tank, raceway). Moreover, all collected data was visualized in the display and stored for external analysis in compatible formats. When the algae H. lacustris was inoculated and the variables such as pH and volume started to change we found that our system achieved comparable performance to external sensors (with a measurement error of less than 1%) while attaining final biomass densities of up to 1, which is remarkably higher than the obtained in flasks cultures (0.1). Development of reliable low-cost monitoring systems facilitates the expansion of operation to precision and parallel culturing of light-driven biotechnology processes.

DNA Barcoding using Sanger sequencing is a popular technique for identifying species on a per specimen basis. However for larger projects, sequencing individual voucher specimens can be time and resource intensive and moreover is associated with high levels of sequencing failure and contamination. Oxford Nanopore Sequencing Technology (ONT) has emerged as a scalable alternative, capable of generating hundreds of DNA barcodes simultaneously using the portable, benchtop MinION sequencing device. In this study we aim to compare and contrast the sequencing outcomes of Oxford Nanopore R10 Flongle flowcells verses Sanger sequencing for DNA barcoding and produce a DNA barcode reference library. We demonstrate that DNA barcodes generated using ONT outperform those produced by Sanger sequencing in terms of recovery and sequence quality with lower rates of contamination. We then produced DNA barcodes for 146 seagrass associated marine invertebrate OTUs collected from four seagrass beds in Scotland, targeting COI and 18S V4 regions. Using both markers, we show the number of recovered OTUs was higher than if each marker was used in isolation and make use of degenerate and group-specific primer pairs to improve recovery. Furthermore we demonstrate how mapping ONT reads to pre-existing DNA barcodes can be used to reduce ambiguous basecalls and improve recovery of sequences from contaminated specimens. Overall this study informs prospective users intending to carry out multimarker DNA barcode projects using Oxford Nanopore Sequencing. Furthermore, we generated the first DNA barcode reference library for seagrass beds in Scotland to support future biomonitoring of these priority habitats.

Stable isotope analysis (SIA) provides essential information step toward a better understanding of trophic ecology. However, the interpretation of SIA results relies on assumptions about the trophic discrimination factor (TDF) that aims to improve the accuracy but may lead to bias. In aquatic ecosystems, most biota are poikilothermic organisms, thus temperature is one of the most important parameters affecting all biological processes, including trophic discrimination of stable isotopes. Therefore, we conducted an experiment to establish TDF for freshwater fish under different temperature regimes (15, 25 °C, and natural ambient pond temperatures from July to September). We used common carp ( Cyprinus carpio, L., 1758) as a model organism. In the first phase of the experiment (weeks 1-6), all fish were fed by a defined fish feed to establish a baseline isotopic signal for all individuals. In the second phase (weeks 7-18), fish were randomly divided into three temperature groups and were all fed by different fish feed. Results indicated temperature dependent TDF, whereby nitrogen showed higher temperature dependency, where highest TDF were observed in 15 °C group and lowest in 25 °C group. In than carbon, where equilibrium of muscle isotopic value of was reached only in the natural, ambient temperature regime. Presumably, discrimination of nitrogen isotopes was related to metabolic turnover rates, where all values were significant, while in carbon only significant values was found in natural, ambient temperature regime These findings highlight the importance of considering environmental thermal conditions in evaluating stable isotope signatures in trophic studies.

Respiratory viruses like 2019 - nCoV, influenza viruses, respiratory syncytial virus, adenoviruses, and Mycoplasma Pneumonia are highly epidemic. Detecting these six is crucial for disease control. We designed specific primers and probes and developed an extraction - free method based on fluorescence PCR melting curve for sensitive detection. It has high sensitivity (single - copy detection limit), can detect six viruses simultaneously by one - step amplification for multiplex detection.

Article type: letterTitle: Effectiveness of Tofacitinib Plus Dupilumab Compared with Dupilumab Monotherapy in Adolescents with Moderate-to-Severe Atopic Dermatitis: A Real-World Study

Urban intersections, critical hotspots for severe traffic crashes, demand advanced analytical approaches, particularly in developing nations where such methods remain underexplored. This study introduces a novel data mining framework integrating deep learning to analyze collision patterns at urban intersections in Qazvin, Iran. Utilizing 245 crash records (2021–2023), the research applied k-means clustering to categorize variables, regression trees for classification, and a deep convolutional neural network (DCNN) to evaluate data clusters. Three primary crash-influencing factors emerged: vehicle type, human factors, and lighting conditions. Training the DCNN on 2021–2022 data and testing it on 2023 data yielded 97% accuracy in predicting crash determinants. Findings highlighted unique crash characteristics across intersections, emphasizing context-specific risk factors. The model enables precise identification of variable importance, offering actionable insights for targeted safety interventions. This approach bridges methodological gaps in crash analysis for developing regions, demonstrating the efficacy of hybrid data mining and deep learning in enhancing intersection safety planning. By prioritizing key risk variables and enabling predictive analytics, the framework supports data-driven policymaking to mitigate crash severity and frequency in urban settings.

Organisms living in arid biomes are predicted to be at threat of extinction associated with ongoing climatic and anthropogenic change. Our understanding of species responses to Pleistocene climatic changes within these environments is still limited, particularly in Australia. Here we evaluate the demographic and evolutionary history of a widespread Australian marsupial, the black-footed rock-wallaby (Petrogale lateralis) whose contemporary distribution is highly fragmented across the arid biome and offshore islands. Combining genomic data from historical and modern samples we evaluate the divergence history of the five P. lateralis sub-species. The species has experienced a Pleistocene demographic expansion across the vast Australian arid biome, with subsequent fragmentation of populations and sub-species. Populations of the widespread sub-species P. lateralis lateralis are as divergent as sub-species within P. lateralis and there is negligible recent gene flow between most populations/sub-species. Individuals on islands have extremely low genetic diversity and high inbreeding coefficients, in contrast to the naturally fragmented mainland populations. Our results indicate historical connectivity of populations ~160-640 kya, and indications of bottlenecks for both island and some isolated mainland populations, providing important context for conservation management and potential genetic rescue. However, given the large ecological gradient and chromosomal variation within this widespread species, assessment of ecological differences will be important before decisions to mix across geographically distant populations and/or sub-species.

This study focused on the effects of biochar and hydrothermally modified biochar on the physicochemical properties and other aspects of saline-alkaline soil in the Yellow River Delta. In order to improve the saline-alkaline soils in the Yellow River Delta, hydrothermal peanut hull biochar (FBC1), hydrothermal wheat straw biochar (FBC2), hydrothermal corn stover biochar (FBC3), hydrothermal rice hull biochar (FBC4) and phosphoric acid-modified biochar were prepared to remediate the saline-alkaline soils. It was found that the addition of biochar significantly increased soil porosity, water content, cation exchange capacity (CEC), and organic matter content, while soil bulk weight, total water-soluble salts, exchangeable Na + content (EX-Na +), and exchangeable sodium percentage (ESP) significantly decreased. Modified biochar showed significantly higher effect in reducing total soil water-soluble salts, EX-Na + and ESP compared to unmodified biochar. Unmodified biochar reduced total water-soluble salts by 18% while modified biochar reduced them by 30.7%; for EX-Na +, unmodified biochar reduced it by 43.49% while modified biochar reduced it by 49.67%; and for ESP, unmodified biochar reduced it by 51.29% while modified biochar reduced it by 59.38%. However, modified and unmodified biochar did not show significant differences in improving other properties of saline soils. The addition of modified biochar increased soil nutrient content while altering the diversity and relative abundance of soil bacterial communities, enhancing the bacteria’s ability to synthesize and utilize soil nutrients. These results provide a basic scientific basis for the application of biochar in soil improvement in the Delta.