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Abstract Identifying faces requires configural processing of visual information. We previously proposed that the poor visual acuity experienced by newborns in their first year of life lays the groundwork for such configural processing by forcing integration over larger spatial fields. This hypothesis predicts that children treated for congenital cataracts late in life will exhibit persistent impairments in face- but not object-identification, because they begin their visual journey with higher than newborn acuity. This would not be the case for patients whose pretreatment condition has allowed for initial low acuity vision, like that of a newborn. Here, we test this prediction by assessing the development of facial identification skill in three groups: patients treated for congenital cataracts whose pretreatment visual acuity was worse than that of a newborn, patients whose pretreatment acuity was better than that of a newborn, and age-matched controls. We find that while both patient groups show significant gains in object-identification, the emergence of face identification is determined by pretreatment acuity: patients with pre-operative acuity worse than a newborn did not show any improvements on face-identification tasks despite years of visual experience, whereas those with pretreatment acuity comparable to a newborn improved on both the object- and face-identification tasks. These findings not only answer our research question but also provide new insights into the role of early visual acuity in facial identification development. We discuss these results in the context of both typical and atypical visual development.

Okra bast fiber (OBF) is one of the underutilized natural bast fibers, extracted from the bark of the okra plant’s (Abelmoschus esculentus) stem. Globally, the okra crop is cultivated for its green immature fruit consumed as a vegetable. After fruit harvesting, the okra plants are treated as agro-waste. Worldwide, 62.11 lakh MT of green okra plant agro-waste is estimated annually. This agro-waste can be utilized to extract the technical bast fibers. The estimated production potential per hectare is 162 kg OBF and nearly 186 lakh kg OBF in the world. Extracted OBF has the potential to be utilized as commercial fiber-like jute fiber (JF). Therefore, the properties of extracted OBF were compared with those of JF in terms of linear density (tex), optical, tensile, and structural properties. OBF was extracted from the 120 ± 10 days old okra plant harvest waste through the water retting process (both flowing and stagnant water) in two different time intervals (17 and 25 days). Overall OBF showed better optical properties and similar or better tensile properties, while coarseness in its fineness than JF.

Abstract To meet the unprecedented requirement of diagnostic testing for SARS-CoV-2, a large number of diagnostic kits were authorized by concerned authorities for diagnostic use within a short period of time during the initial phases of the ongoing pandemic. We undertook this study to evaluate the inter-test agreement and other key operational features of 5 such commercial kits that have been extensively used in India for routine diagnostic testing for COVID-19. The five commercial kits were evaluated, using a panel of positive and negative respiratory samples, considering the kit provided by National Institute of Virology, Indian Council of Medical Research (2019-nCoV Kit) as the reference. The positive panel comprised of individuals who fulfilled the 3 criteria of being clinically symptomatic, having history of contact with diagnosed cases and testing positive in the reference kit. The negative panel included both healthy and disease controls, the latter being drawn from individuals diagnosed with other respiratory viral infections. The same protocol of sample collection, same RNA extraction kit and same RT-PCR instrument were used for all the kits. Clinical samples were collected from a panel of 92 cases and 60 control patients, who fulfilled our inclusion criteria. The control group included equal number of healthy individuals and patients infected with other respiratory viruses (n = 30, in each group). We observed varying sensitivity and specificity among the evaluated kits, with LabGun COVID-19 RT-PCR kit showing the highest sensitivity and specificity (94% and 100% respectively), followed by TaqPath COVID-19 Combo and Allplex 2019-nCoV assays. The extent of inter-test agreement was not associated with viral loads of the samples. Poor correlation was observed between Ct values of the same genes amplified using different kits. Our findings reveal the presence of wide heterogeneity and sub-optimal inter-test agreement in the diagnostic performance of the evaluated kits and hint at the need of adopting stringent standards for fulfilling the quality assurance requirements of the COVID-19 diagnostic process.

Complete avulsion of the ureter is one of the most serious complications of ureteroscopy. It requires open or laparoscopic intervention for repair. This case report emphasizes its management and presents recommendations for prevention in current urological practice.

The study examines China’s performance in science and technology (S&T) during 1997–2007, based on several parameters including the country’s annual average growth rate, global publication share and rank, strong and weak subject areas (in terms of national priority, international collaborative share and global share), institutional profiles of select top institutions, the overall international collaboration profile and major collaborative partners, patterns of communication in national and international journals and characteristics of its top highly cited papers. The study also compares similarities of China’s research profile with nineteen other top productive countries. [ABSTRACT FROM PUBLISHER]

Gender relations in organisations are a function of the socio-cultural and institutional context. This study analyses the perceptions of men and women scientists in India with respect to their work environment. It indicates that the twin aspects of Indian culture, patriarchy and hierarchy, contribute to a masculine environment at the workplace. Idealisation of women’s family roles as part of ‘Indian culture’ depresses women’s position as scientists. The hierarchical culture affects junior women scientists particularly through structural inefficiencies and gendered methods to subvert hierarchy. Since the Indian social milieu is in transition, changes are slowly taking place within organisations, offering hope for a change in gendered work environments. In exploring solutions to gender problems and understanding gender relations, the specific national context needs to be highlighted. [ABSTRACT FROM AUTHOR]

This study analyses the research output of Bangladesh in S&T during 2001-10 on several parameters including its growth and country publications share in the world's research output, country publications share in various subjects in the national and global context, pattern of research communication in core domestic and international journals, geographical distribution of publications, share of international collaborative publications at the national-level as well as across subjects and characteristics of high productivity institutions, authors, and cited papers. The Scopus Citation Database has been used to retrieve the publication data for 10 years. It concludes that Bangladesh needs to increase its output and bring about improvement in the quality of its research efforts further. [ABSTRACT FROM AUTHOR]

This study analyses the research output of Sri Lanka in S&T during 2001-2010 on several parameters including its growth and global publications share, citation impact, share of international collaborative papers, contribution of major collaborative partner countries, contribution to various subject fields, geographical distribution of its papers, evaluation of the characteristics on its high productive institutions, authors and papers and the journals publishing the research output. The Scopus Citation Database has been used to retrieve the publication data for 10 years. The study concludes that Sri Lanka needs to increase its output and bring about improvement in the quality of its research efforts. This can be done by investing much more in research and development (R&D) expenditure, increase in the deployment of more qualified manpower and international collaboration; and by modernizing and strengthening its research infrastructure. [ABSTRACT FROM AUTHOR]

The paper analyses India's publications output in three major international multidisciplinary databases, as indexed during 1981-2005. It reports on India's comparative strength in world science and technology (S&T) output, its growth and decline, its strong and weak subject areas of research, media of communication, its collaborative profile and quality of S&T output, institutional productivity and quality, and dynamics of Indian research at institutional and sectoral levels. The study also provides suggestions for improving the quantity and quality of research S&T in India. [ABSTRACT FROM AUTHOR]

This paper attempts to highlight the role of bibliometrics in studying the dynamics of science and technology. Tools and techniques available in bibliometrics to address and understand the complexities of scientific fields are explored. The paper concludes that for wider acceptance among academicians and policy makers, bibliometric approach should ingrain itself within sociology and philosophy of science in studying the different facets of science and technology. [ABSTRACT FROM AUTHOR]

Abstract Coagulation factor XII (FXII) conveys various functions as an active protease that promotes thrombosis and inflammation, and as a zymogen via surface receptors like urokinase-type plasminogen activator receptor (uPAR). While plasma levels of FXII are increased in diabetes mellitus and diabetic kidney disease (DKD), a pathogenic role of FXII in DKD remains unknown. Here we show that FXII is locally expressed in kidney tubular cells and that urinary FXII correlates with kidney dysfunction in DKD patients. F12-deficient mice (F12 -/- ) are protected from hyperglycemia-induced kidney injury. Mechanistically, FXII interacts with uPAR on tubular cells promoting integrin β1-dependent signaling. This signaling axis induces oxidative stress, persistent DNA damage and senescence. Blocking uPAR or integrin β1 ameliorates FXII-induced tubular cell injury. Our findings demonstrate that FXII-uPAR-integrin β1 signaling on tubular cells drives senescence. These findings imply previously undescribed diagnostic and therapeutic approaches to detect or treat DKD and possibly other senescence-associated diseases.

Abstract The escalating threat of climate change has placed global coastal communities at risk, with rising sea levels and intensified storm events presenting unprecedented challenges. Coastal vulnerability assessments, conducted every 3–5 years, are crucial. This empirical study assesses the Coastal Vulnerability Index (CVI) for the distinct coastal contexts of Dawlish, Happisburgh (England), and Aberystwyth (Wales). The CVI method consists of the Physical Coastal Vulnerability Index (PCVI) and the Economic Coastal Vulnerability Index (ECVI), which provide a multidimensional assessment of vulnerability for coastal zones. This integrated index allows for a nuanced evaluation of vulnerability, distinguishing between sites based on various factors. Additionally, this study conducted a correlation analysis to understand the associations between the parameters. The findings demonstrate that physical features like beach and dune widths significantly impact a location’s natural defences, and economic factors such as property values and population density are equally crucial in determining societal risks and potential financial repercussions. The Combined Coastal Vulnerability Index (CCVI) results confirm the effectiveness of incorporating a diverse range of variables. Despite its substantial economic value, it reveals that Dawlish requires targeted protective measures, whereas Happisburgh needs an increased focus on its most vulnerable sectors. Aberystwyth emerges as the area with the highest overall vulnerability, underscoring the need for comprehensive coastal management practices. The study’s conclusions emphasize the essential role of adaptive, integrated management strategies in enhancing coastal resilience against the complex threats posed by climate dynamics. Moving forward, the indices established herein advocate for their use in strategic planning and policymaking to strengthen coastal regions in the face of sea-level rise and climatic variability. This investigation lays the groundwork for future research, aimed at refining and expanding these methodologies, aspiring to develop a detailed national coastal vulnerability atlas, a critical tool for informed decision-making and safeguarding at-risk communities.

Abstract Heterochromatin organization is critical to many genome-related programs including transcriptional silencing and DNA repair. While super-resolution imaging, electron microscopy, and multiomics methods have provided indirect insights into the heterochromatin organization, a direct measurement of mesoscale heterochromatin ultrastructure is still missing. We use a combination of correlative light microscopy and cryo-soft X-ray tomography (CLXT) to analyze heterochromatin organization in the intact hydrated state of human mammary fibroblast cells. Our analysis reveals that the heterochromatin ultra-structure has a typical mean domain size of approximately 80 nm and a mean separation of approximately 120 nm between domains. Functional perturbations yield further insights into the molecular density and alterations in the mesoscale organization of the heterochromatin regions. Furthermore, our polymer simulations provide a mechanistic basis for the experimentally observed size and separation distributions of the mesoscale chromatin domains. Collectively, our results provide direct, label-free observation of heterochromatin organization in the intact hydrated state of cells.

Abstract Insecticidal potential of seven commonly available alkaloids against melon thrips (Thrips palmi Karny) was investigated through in vivo experiments and the bioactivity was explained via in silico approaches. In vivo screening showed highest mortality of T. plami larvae for reserpine (43%), closely followed by tropinone (41%) after 24 h of incubation. After 48 h, tropinone surpassed reserpine with 83% mortality, indicating its prolonged insecticidal activity. A detailed bioassay of tropinone revealed its LC50 values as 1187.9 and 686.9 µg mL−1 after 24 and 48 h, respectively. While studying the molecular interactions between the alkaloids and four physiologically important target proteins of T. palmi, tropinone demonstrated the highest ligand efficiency and lowest predicted inhibitory constant, particularly when forming complexes with CathB protein. However, binding energy calculations of the docked complexes showed most favorable binding of reserpine with CathB. To clear the ambiguity, considering both binding energy and ligand efficiency as the evaluation parameters, a molecular dynamics study was carried out, which predicted higher stability of CathB-tropinone complex than CathB-reserpine complex in terms of the total energy of the system. These in silico findings aligned well with the in vivo results, confirming tropinone as a promising candidate for effective thrips management programs.

Abstract Direct oxidation of methane to valuable oxygenates like alcohols and acetic acid under mild conditions poses a significant challenge due to high C‒H bond dissociation energy, facile overoxidation to CO and CO2 and the intricacy of C−H activation/C−C coupling. In this work, we develop a multifunctional iron(III) dihydroxyl catalytic species immobilized within a metal-organic framework (MOF) for selective methane oxidation into methanol or acetic acid at different reaction conditions using O2. The active-site isolation of monomeric FeIII(OH)2 species at the MOF nodes, their confinement within the porous framework, and their electron-deficient nature facilitate chemoselective C‒H oxidation, yielding methanol or acetic acid with high productivities of $$38,592\,\upmu {{{\rm{mol}}}}_{{{{\rm{CH}}}}_{3}{{\rm{OH}}}}{{{{\rm{g}}}}_{{{\rm{Fe}}}}}^{-1}{{{\rm{h}}}}^{-1}$$ 38 , 592 μ mol CH 3 OH g Fe − 1 h − 1 and $$81,043\,\upmu {{{\rm{mol}}}}_{{{{\rm{CH}}}}_{3}{{{\rm{CO}}}}_{2}{{\rm{H}}}}{{{{\rm{g}}}}_{{{\rm{Fe}}}}}^{-1}{{{\rm{h}}}}^{-1}$$ 81 , 043 μ mol CH 3 CO 2 H g Fe − 1 h − 1 , respectively. Experiments and theoretical calculations suggest that methanol formation occurs via a FeIII-FeI-FeIII catalytic cycle, whereas CH3CO2H is produced via hydrocarboxylation of in-situ generated CH3OH with CO2 and H2, and direct CH4 carboxylation with CO2.

Abstract Facial expressions are essential in animal communication, and facial expression-based pain scales have been developed for different species. Automated pain recognition offers a valid alternative to manual annotation with growing evidence across species. This study applied machine learning (ML) methods, using a pre-trained VGG-16 base and a Support Vector Machine classifier to automate pain recognition in caprine patients in hospital settings, evaluating different frame extraction rates and validation techniques. The study included goats of different breed, age, sex, and varying medical conditions presented to the University of Florida’s Large Animal Hospital. Painful status was determined using the UNESP-Botucatu Goat Acute Pain Scale. The final dataset comprised images from 40 goats (20 painful, 20 non-painful), with 2,253 ‘non-painful’ and 3,154 ‘painful’ images at 1 frame per second (FPS) extraction rate and 7,630 ‘non-painful’ and 9,071 ‘painful’ images at 3 FPS. Images were used to train deep learning-based models with different approaches. The model input was raw images, and pain presence was the target attribute (model output). For the single train-test split and 5-fold cross-validation, the models achieved approximately 80% accuracy, while the subject-wise 10-fold cross-validation showed mean accuracies above 60%. These findings suggest ML’s potential in goat pain assessment.

Abstract In case-control single-cell RNA-seq studies, sample-level labels are transferred onto individual cells, labeling all case cells as affected, when in reality only a small fraction of them may actually be perturbed. Here, using simulations, we demonstrate that the standard approach to single cell analysis fails to isolate the subset of affected case cells and their markers when either the affected subset is small, or when the strength of the perturbation is mild. To address this fundamental limitation, we introduce HiDDEN, a computational method that refines the case-control labels to accurately reflect the perturbation status of each cell. We show HiDDEN’s superior ability to recover biological signals missed by the standard analysis workflow in simulated ground truth datasets of cell type mixtures. When applied to a dataset of human multiple myeloma precursor conditions, HiDDEN recapitulates the expert manual annotation and discovers malignancy in early stage samples missed in the original analysis. When applied to a mouse model of demyelination, HiDDEN identifies an endothelial subpopulation playing a role in early stage blood-brain barrier dysfunction. We anticipate that HiDDEN should find wide usage in contexts that require the detection of subtle transcriptional changes in cell types across conditions.

Abstract Halide perovskites are an intriguing renewable energy materials that may assist in addressing the world’s energy scarcity. The Goldsmith tolerance factor (0.99 and 1.00) and negative formation energy guarantee the examined materials’ structural and thermodynamic stabilities. The Poisson’s and Pugh’s ratio proves the reviewed materials’ ductile nature. K/RbOsCl3 has electronic band gaps of 1.37 eV/1.39 eV and the highest light absorption in the ultraviolet and visible areas, enhancing its efficacy for solar cells and other optoelectronics technologies. The highest Seebeck coefficient and electrical conductivity render these materials feasible for thermoelectric properties. KOsCl3 and RbOsCl3 exemplify figures of merit of 0.89 and 0.88, respectively, at the ambient temperature. Additionally, the Debye model was implemented to figure out thermodynamic parameters such as heat capacity, thermal expansion, Debye temperature, and Grüneisen parameter.

Abstract Robust verification protocols are crucial for maintaining the security and reliability of sensitive information due to the increasing complexity of cyber-attacks. This paper introduces a novel 5G Secure Handover Protocol aimed at addressing security and effectiveness issues encountered in existing systems. The proposed protocol is robust against various attacks, including de-synchronization, replay, man-in-the-middle (MITM), denial of services (DoS), and jamming, ensures perfect forward key secrecy, safeguarding communication confidentiality. The proposed protocol utilizes a combination of spiking neural network and fuzzy logic (SNN-FL) techniques that must choose the goal cell as carefully as possible before initiating the transfer process. By combining fuzzy logic and spiking neural networks to reduce handover latency and thwart several types of cyberattacks, the proposed 5G Secure Handover Protocol improves security. Extensive simulations show its efficacy and emphasize its potential for safe communication in large-scale cybersecurity applications. The paper presents a novel secure authentication protocol that significantly reduces handover delays and improves efficiency. Simulations show its resilience against common security threats, protecting sensitive information and maintaining secure communication channels. The protocol, with low communication expenses, complex spatial, and latency for changeover verification, is ideal for large-scale cybersecurity applications, contributing to the development of secure digital authentication mechanisms.

Abstract Recent progress in deep learning has significantly impacted materials science, leading to accelerated material discovery and innovation. ElemNet, a deep neural network model that predicts formation energy from elemental compositions, exemplifies the application of deep learning techniques in this field. However, the “black-box” nature of deep learning models often raises concerns about their interpretability and reliability. In this study, we propose XElemNet to explore the interpretability of ElemNet by applying a series of explainable artificial intelligence (XAI) techniques, focusing on post-hoc analysis and model transparency. The experiments with artificial binary datasets reveal ElemNet’s effectiveness in predicting convex hulls of element-pair systems across periodic table groups, indicating its capability to effectively discern elemental interactions in most cases. Additionally, feature importance analysis within ElemNet highlights alignment with chemical properties of elements such as reactivity and electronegativity. XElemNet provides insights into the strengths and limitations of ElemNet and offers a potential pathway for explaining other deep learning models in materials science.

Abstract This research study evaluates the impact of low-density polyethylene (LDPE) modified asphalt binder on the mechanical performance and economical feasibility of asphalt concrete (AC) mixtures. LDPE-modified mixtures were compared with conventional mixes prepared with various binders commonly used in India, i.e., VG 30, VG 40, Polymer-Modified Binder (PMB), and Crumb Rubber Modified Binder (CRMB). LDPE-modified mixtures exhibit superior mechanical performance, increasing the stiffness of AC mixtures by 171% and 125% at 25 °C and 35 °C, respectively, compared to VG 30 base binder. Additionally, the indirect tensile strength (ITS) improved by 51% over VG 30. LDPE-modified mixtures also showed improved resistance to permanent deformation, with RT Index values up to 133.46% higher than VG 30, and higher fatigue resistance, as indicated by increased CT Index values compared to VG 30 and CRMB. However, the CT Index values for LDPE-modified mixtures were 26.32% and 56% lower than those for VG 40 and PMB, respectively. Pavement analysis using 3D-Move showed lesser deflections at pavement layer interfaces, resulting in higher rutting and fatigue life for LDPE-modified pavements. Furthermore, LDPE-modified pavements showed up to 57% higher fatigue life (Nf) and up to 42.33% higher rutting life (Nr) than other pavements. The economic analysis showed that the cost of LDPE-modified pavements is comparable to VG 40 and around 10% more economical than pavements containing PMB. Using LDPE also offers environmental benefits by repurposing up to 750 kg for every kilometer of single-lane pavement section having 50mm thick surface course. Overall, LDPE-modified asphalt mixtures present a sustainable and high-performance solution for asphalt pavement construction.

Abstract Diabetes is a metabolic condition defined by abnormal blood sugar levels. Targeting starch-hydrolyzing enzymes and Dipeptidyl Peptidase 4 (DPP-4) expressed on the surface of numerous cells is one of the key strategies to lower the risk of Type-2 diabetes mellitus (T2DM). Dalbergia sissoo Roxb. bark (DSB) extracts have been reported to have anti-diabetic properties. This study intended to scientifically validate use of alcoholic and hydro-alcoholic extracts of DSB for T2DM by conducting preliminary phytochemical investigations, characterising potential phytochemicals using Fourier transform infrared (FT-IR) spectroscopy and Gas chromatography-mass spectrometry (GC–MS) analysis followed by comprehensive in-silico analysis. A qualitative phytochemical evaluation indicated the presence of alkaloids, phenolics, glycosides, conjugated acids and flavonoids. Ethanolic extracts showed highest total phenolic content (TPC) (127.072 ± 14.08031 μg GAE/g dry extract) and total flavonoid content (106.911 ± 5.84516 μg QE /g dry extract). Further FT-IR spectroscopy also revealed typical band values associated with phenol, alcohol, alkene, alkane and conjugated acid functional groups. The GC–MS analysis identified 139 compounds, 18 of which had anti-diabetic potential. In-silico ADMET analysis of potential compounds revealed 15 compounds that followed Lipinski’s rule and demonstrated drug-like properties, as well as good oral bioavailability. Molecular docking was utilised to analyse their potential to interact with three targets: α-amylase, α-glucosidase, and DPP-4, which are crucial in managing diabetes-related problems. Molecular Docking analysis and membrane permeability test utilising the PerMM platform revealed that compounds in the extracts, such as Soyasapogenol B and Corydine, had better interactions and permeability across the plasma membrane than standard drugs in use. Molecular dynamics simulations also showed that selected compounds remained stable upon interaction with α-amylase. Overall, using the in-silico approaches it was predicted that DSB extracts contain potential phytochemicals with diverse anti-diabetic properties. It further needs to be investigated for possible development as formulation or drug of choice for treating T2DM.

Abstract Myotonic Dystrophy type 1 (DM1), a highly prevalent form of muscular dystrophy, is caused by (CTG)n repeat expansion in the DMPK gene. Much of DM1 research has focused on the effects within the muscle and neurological tissues; however, DM1 patients also suffer from various metabolic and liver dysfunctions such as increased susceptibility to metabolic dysfunction-associated fatty liver disease (MAFLD) and heightened sensitivity to certain drugs. Here, we generated a liver-specific DM1 mouse model that reproduces molecular and pathological features of the disease, including susceptibility to MAFLD and reduced capacity to metabolize specific analgesics and muscle relaxants. Expression of CUG-expanded (CUG)exp repeat RNA within hepatocytes sequestered muscleblind-like proteins and triggered widespread gene expression and RNA processing defects. Mechanistically, we demonstrate that increased expression and alternative splicing of acetyl-CoA carboxylase 1 drives excessive lipid accumulation in DM1 livers, which is exacerbated by high-fat, high-sugar diets. Together, these findings reveal that (CUG)exp RNA toxicity disrupts normal hepatic functions, predisposing DM1 livers to injury, MAFLD, and drug clearance pathologies that may jeopardize the health of affected individuals and complicate their treatment.

Abstract Active acoustic metamaterials (AAMM) have garnered special attention because of their potential as multi-function devices. In this direction, the present article demonstrates a novel AAMM that can be programmed as a multi-functional Active Acoustic Meta-device (AAMD) that can switch functionalities between Acoustic Switch (AS), Acoustic Lens (AL), and Acoustic Barrier (AB). Functionality: AL corresponds to the wave vector space, and AS and AB correspond to the frequency space of the proposed AAMM. Additional functionality, such as acoustic logic gates in phase space, is also envisaged. The proposed design is found to change the dispersion diagram by acquiring different configurations while keeping the basic design parameters constant. These design parameters include constituent elements, lattice constants, and filling fractions. Further, for the said functionalities, the proposed AAMM does not rely on the deformation characteristics of the constituents. It rather capitalises on the possible relative displacements of the scatterers. As an AL, AAMM demonstrates zero angle refraction, i.e., collimation, and negative refraction of the transmitted beam at a given angle of incidence over a frequency range of 200 kHz (22.22% of the applied frequency sweep, a.f.s.). AB is shown to attenuate acoustic energy over a frequency range of 700 kHz (77.78% of a.f.s.) compared to its reference and foundation design, a statically designed Phononic Crystal (PnC). Furthermore, as AS, it operates over the entire range of applied frequency sweep (100 kHz to 1000 kHz), i.e., over the frequency range of 900 kHz (100% of a.f.s.).

Abstract Calcium is involved in vision processes in the retina and implicated in various pathologies, including glaucoma. Rod cells rely on store-operated calcium entry (SOCE) to safeguard against the prolonged lowering of intracellular calcium ion concentrations. Zebrafish that lacked the endoplasmic reticulum Ca2+ sensor Stim2 (stim2 knockout [KO]) exhibited impaired vision and lower light perception-related gene expression. We sought to understand mechanisms that are responsible for vision impairment in stim2 KO zebrafish. The single-cell RNA (scRNA) sequencing of neuronal cells from brains of 5 days postfertilization larvae distinguished 27 cell clusters, 10 of which exhibited distinct gene expression patterns, including amacrine and γ-aminobutyric acid (GABA)ergic retinal interneurons and GABAergic optic tectum cells. Five clusters exhibited significant changes in cell proportions between stim2 KO and controls, including GABAergic diencephalon and optic tectum cells. Transmission electron microscopy of stim2 KO zebrafish revealed decreases in width of the inner plexiform layer, ganglion cells, and their dendrites numbers (a hallmark of glaucoma). GABAergic neuron densities in the inner nuclear layer, including amacrine cells, as well as photoreceptors significantly decreased in stim2 KO zebrafish. Our study suggests a novel role for Stim2 in the regulation of neuronal insulin expression and GABAergic-dependent vision causing glaucoma-like retinal pathology.

Abstract Duckweeds (Spirodela polyrrhiza) are free-floating macrophytes that grow profusely in nutrient-rich waters. Under ideal conditions, they exhibit a rapid growth rate and can absorb a substantial amount of nutrients, macromolecules, and pollutants from bodies of water. Zinc oxide nanoparticles (ZnO NPs) synthesized from plant extracts, particularly under stress conditions, have opened new research avenues in the field of nanotechnology. Under salinity stress, the accumulation of flavonoids in duckweeds can affect the structure of ZnO NPs, helping researchers ascertain their antimicrobial role. In our study, we exposed mid-log phase duckweed monocultures to 75 mM NaCl in a full-strength Murashige and Skoog medium for 7 days, followed by a 15-day recovery period. We observed significant overexpression of superoxide and hydrogen peroxide as reactive oxygen species. As a result, chlorophyll and certain metabolites were produced in lesser amounts, while flavonoid and phenol content increased by 12% and 8%, respectively. This overproduction persisted up to 10 days into the recovery treatment period but dropped by 8% and 5%, respectively, by the 15th day. The flavonoid coating transformed the NPs into rosette clusters, which exhibited reduced antimicrobial activity against Aeromonas hydrophila, a Gram-negative, fish-pathogenic bacterium. Herein, we discuss potential mechanisms for the conformational transformation of ZnO NPs into finer dimensions in response to NaCl-induced oxidative stress in duckweed. In this study, the azo dye degradation capacity of salinity-treated plants increased as the flavonoid profile became enriched. Zinc oxide nanoparticles, both prior to and after salinity treatment, were found to be efficient in scavenging azo dye and mitigating its toxicity, as evidenced by improved germination, growth, and overall plant morphometry.

Abstract In the domain of natural language processing, the rise of Large Language Models and Generative AI represents a noteworthy transition, enabling machines to understand and generate text resembling that produced by humans. This research conducts a thorough examination of this transformative technology, with a focus on its influence on machine translation. The study explores the translation landscape between English and Indic languages, which include Hindi, Kannada, Malayalam, Tamil, and Telugu. To address this, the Large Language Model, BLOOMZ-3b, is utilized, which has been primarily developed for a text generation task. Multiple prompting engineering techniques for machine translation are prominently explored. The study further traverse fine-tuning the BLOOMZ-3b model using a Parameter Efficient Fine-Tuning technique called Low Rank Adaptation, aiming to reduce computational complexity. Hence, by combining innovative prompting approaches using BLOOMZ-3b model and fine-tuning the model, it contributes to continuous development of machine translation technologies beyond traditional borders of what can be done with respect to language processing. In this regard, not only does this research shed light on the intricacy of translation problems but it also sets a precedence for optimizing or adapting big language models to various languages which end up advancing Artificial Intelligence and Natural Language Processing at large.

Abstract Protein aggregation plays key roles in age-related degenerative diseases, but how different proteins coalesce to form inclusions that vary in composition, morphology, molecular dynamics and confer physiological consequences is poorly understood. Here we employ a general reporter based on mutant Hsp104 to identify proteins forming aggregates in human cells under common proteotoxic stress. We identify over 300 proteins that form different inclusions containing subsets of aggregating proteins. In particular, TDP43, implicated in Amyotrophic Lateral Sclerosis (ALS), partitions dynamically between two distinct types of aggregates: stress granule and a previously unknown non-dynamic (solid-like) inclusion at the ER exit sites (ERES). TDP43-ERES co-aggregation is induced by diverse proteotoxic stresses and observed in the motor neurons of ALS patients. Such aggregation causes retention of secretory cargos at ERES and therefore delays ER-to-Golgi transport, providing a link between TDP43 aggregation and compromised cellular function in ALS patients.

Abstract Breast Cancer (BC) is the most common cause of cancer-associated deaths in females worldwide. Despite advancements in BC treatment driven by extensive characterization of its molecular hallmarks, challenges such as drug resistance, tumor relapse, and metastasis persist. Therefore, there is an urgent need for alternative treatment approaches with multi-modal efficacy to overcome these hurdles. In this context, natural bioactives are increasingly recognized for their pivotal role as anti-cancer compounds. This study focuses on predicting molecular targets for key herbal phytoconstituents—gallic acid, piperine, quercetin, resveratrol, and beta-sitosterol—present in the polyherbal formulation, Krishnadi Churna. Using an in-silico network pharmacology model, key genes were identified and docked against these marker compounds and controls. Mammary carcinoma emerged as the most significant phenotype of the putative targets. Analysis of an online database revealed that out of 135 predicted targets, 134 were mutated in breast cancer patients. Notably, ESR1, CYP19A1, and EGFR were identified as key genes which are known to regulate the BC progression. Docking studies demonstrated that the herbal phytoconstituents had similar or better docking scores than positive controls for these key genes, with convincing protein-ligand interactions confirmed by molecular dynamics simulations, MM/GBSA and free energy landscape (FEL) analysis. Overall, this study highlights the predictive potential of herbal phytoconstituents in targeting BC genes, suggesting their promise as a basis for developing new therapeutic formulations for BC.

Abstract The 3D printing technique has recently become more prevalent among researchers for the fabrication of nanocomposites. The low crystallinity of polylactic acid (PLA) leads to the poor mechanical and thermal properties of its 3D-printed products, which restrict their applications in many fields. To overcome the limitations of PLA, the present work aims to develop PLA-based bionanocomposite filaments with varying percentages (1, 3, and 5 wt%) of crystalline nanocellulose (CNC) through a single screw extruder. The filaments will be further utilized for the development of bionanocomposite samples to evaluate their properties. The effect of CNC reinforcement on the chemical structure of the filaments was analyzed by FTIR analysis. XRD analysis revealed that the crystallinity of the filaments was significantly improved due to the nucleating effect of CNC. The maximum crystallinity was observed in the filament containing 1 wt% CNC, which was 26% higher than the pure PLA filament. The thermal and mechanical performance of the filaments was also considerably improved after CNC reinforcement, which was confirmed by DSC-TGA and tensile test analysis. The maximum tensile strength and tensile modulus were observed to be 48.9 MPa and 1700 MPa, respectively, in the filament reinforced with 1 wt% CNC, which was 35.5% and 21.89%, respectively, higher than those of the pure PLA filament. Rheological analysis showed that the complex viscosity, storage modulus, and loss modulus of the filaments were significantly affected by the reinforcement of CNC.

Abstract Salmonella enterica subspecies enterica serovar Abortusequi (S. Abortusequi) is a leading cause of abortion in equines that hinders the rapid growth of equine industry. S. Abortusequi infection in equids has re-emerged over last ten years. In the present study, S. Abortusequi was isolated and characterized from donkeys during an abortion storm in the southern peninsular region of India. Further, whole genome sequencing and phylogenomic analysis revealed that the present isolate was clustered among S. Abortusequi clade. The core genome MLST (cgMLST) analysis based on hierarchical clustering and single nucleotide polymorphism (SNP) core-genome dendrogram of the present isolate against 10 S. Abortusequi isolates revealed that the present isolate established a distinct clade compared to all previously reported isolates. A comparison of cgMLST and SNP analyses revealed the same clustering concordance between isolates. In addition, comparative genomics and phylogenetic analysis was carried out with six S. Abortusequi serovars showed a higher number of core genes than accessory genes. Further, comparative analysis of phenotype and genotype antimicrobial resistance revealed a concordance of 32% and discordance of 68% respectively.

Abstract The Electronic and optical properties of InGeX3(X = Cl, Br) were examined by adopting the density functional theory (DFT) approach. We applied the GGA + Trans-Blaha modified Becke–Johnson (TB-mBJ) technique to acquire the precise bandgap of 1.52 and 0.98 eV of the compounds InGeX3(X = Cl, Br) respectively which suggests the direct bandgap at (M-M). The stability of the material is confirmed by the formation energy (– 2.83 = Cl; – 2.35 = Br) and Mechanical stability. Primarily elastic constants were extracted for each of the materials under scrutiny, and these values then served to gauge all of the materials’ mechanical properties. The assessed Poisson’s and Pugh’s ratios for the materials InGeCl3 and InGeBr3 were verified to identify the degree of ductility. The quasi-harmonic Debye model additionally covers the temperature and pressure dependence on thermodynamic parameters, particularly volume, specific heat capacity (Cv) at constant volume, and the Gruneisen parameter (γ) in the range of 0–800 K and 0–5 GPa. It is anticipated that InGeCl3 and InGeBr3 will have static dielectric constants of 4.01 and 5.74, respectively. InGeX3(X = Cl, Br) also reveals significant absorption in the high UV spectrum. The thermoelectric properties have also been calculated vdata-element-id="9QNfR3VHbcMHX_W0fJCYp" data-element-type="html" style="display: initial; visibility: initial; opacity: initial; clip-path: initial; position: relative; float: left; top: 0px; left: 0px; z-index: 1 !important; pointer-events: none;" />ia boltztrap2 code using a k mesh of around 1,50,000 points.

Abstract Proliferative vitreoretinopathy is a vision-threatening response to penetrating ocular injury, for which there is no satisfactory treatment. In this disorder, retinal pigment epithelial cells, abandon their attachment to Bruch’s membrane on the scleral side of the retina, transform into motile fibroblast-like cells, and migrate through the retinal wound to the vitreal surface of the retina, where they secrete membrane-forming proteins. Annexin A2 is a calcium-regulated protein that, in complex with S100A10, assembles plasmin-forming proteins at cell surfaces. Here, we show that, in proliferative vitreoretinopathy, recruitment of macrophages and directed migration of retinal pigment epithelial cells are annexin A2-dependent, and stimulated by macrophage inflammatory protein-1α/β. These factors induce translocation of annexin A2 to the cell surface, thus enabling retinal pigment epithelial cell migration following injury; our studies reveal further that treatment of mice with intraocular antibody to either annexin A2 or macrophage inflammatory protein dampens the development of proliferative vitreoretinopathy in mice.

Abstract Mental health issues have increased substantially since the onset of the COVID-19 pandemic. However, health policymakers do not have adequate data and tools to predict mental health demand, especially amid a crisis. Using time-series data collected in Singapore, this study examines if and how algorithmically measured emotion indicators from Twitter posts can help forecast emergency mental health needs. We measured the mental health needs during 549 days from 1 July 2020 to 31 December 2021 using the public’s daily visits to the emergency room of the country’s largest psychiatric hospital and the number of users with “crisis” state assessed through a government-initiated online mental health self-help portal. Pairwise Granger-causality tests covering lag length from 1 day to 5 days indicated that forecast models using Twitter joy, anger and sadness emotions as predictors perform significantly better than baseline models using past mental health needs data alone (e.g., Joy Intensity on IMH Visits, χ2 = 14·9, P < ·001***; Sadness Count on Mindline Crisis, χ2 = 4·6, P = ·031*, with a one-day lag length). The findings highlight the potential of new early indicators for tracking emerging public mental health needs.

Abstract Our study from an ongoing research experiment initiated in Rabi 1967 at the Research Farm of CCS Haryana Agricultural University, Haryana, India, reports that during the 51st wheat cycle in pearl millet-wheat sequence, adding FYM in both seasons significantly impacted various soil parameters at different wheat growth stages compared to the rabi season. The application of 15 t of FYM ha−1 resulted in a considerable increase in dissolved organic carbon content (9.1–11.2%), available P (9.7–12.1%), and available S (12.6–17.1%), DHA levels by 7.3–22.0%, urease activity (10.1 and 17.0%), β-Glucosidase activity (6.2–8.4%), and APA activity (5.2–10.6%), compared to 10 t FYM ha−1. Application of N120 exhibited a considerable improvement in DHA (11.0–23.2%), β-Glucosidase (9.4–19.2%), urease (13.3–28.3%), and APA (3.3–6.2%) activity compared to control (N0). At stage 3, the box plot revealed that 50% of the available N, P, and S values varied from 223.1 to 287.9 kg ha−1, 53.0 to 98.2 kg ha−1, and 50.0 to 97.6 kg ha−1, respectively. Principal component analysis, with PC1 explaining 94.7% and PC2 explaining 3.15% of the overall variability, and SOC had a polynomial relationship with soil characteristics (R2 = 0.89 to 0.99). Applying FYM15 × N120 treatment during both seasons proved beneficial in sustaining the health of sandy loam soil in North-West India.

Abstract The present paper introduces the development of dynamic stiffness method for analyzing small-scale sandwich functionally graded nanoplates resting on elastic foundation in thermal environments. The mathematical formulation is based on classical plate theory in conjunction with nonlocal elasticity theory. The governing equation is derived using Hamilton’s principle. The dynamic stiffness matrix is obtained through the application of the Levy displacement approach and assembled to form the global stiffness matrix. The final matrix is solved for natural frequency of the plates using the Wittrick–Williams algorithm. The proposed methodology is validated against existing literature, demonstrating a strong agreement. Various parametric studies explore the effects of thermal environments, volume fraction index, sandwich configurations, elastic foundation characteristics, nonlocal parameter and boundary conditions. The results show the versatility of the proposed approach in addressing small scaled complex engineering structures. This research significantly contributes to the understanding and analysis of sandwich functionally graded nanoplates, providing valuable insights for applications in aerospace, structural systems, sensors, actuators, and energy harvesting devices.

Abstract In Virtual Reality (VR), a higher level of presence positively influences the experience and engagement of a user. There are several parameters that are responsible for generating different levels of presence in VR, including but not limited to, graphical fidelity, multi-sensory stimuli, and embodiment. However, standard methods of measuring presence, including self-reported questionnaires, are biased. This research focuses on developing a robust model, via machine learning, to detect different levels of presence in VR using multimodal neurological and physiological signals, including electroencephalography and electrodermal activity. An experiment has been undertaken whereby participants (N = 22) were each exposed to three different levels of presence (high, medium, and low) in a random order in VR. Four parameters within each level, including graphics fidelity, audio cues, latency, and embodiment with haptic feedback, were systematically manipulated to differentiate the levels. A number of multi-class classifiers were evaluated within a three-class classification problem, using a One-vs-Rest approach, including Support Vector Machine, k-Nearest Neighbour, Extra Gradient Boosting, Random Forest, Logistic Regression, and Multiple Layer Perceptron. Results demonstrated that the Multiple Layer Perceptron model obtained the highest macro average accuracy of $$93\pm 0.03\%$$ 93 ± 0.03 % . Posthoc analysis revealed that relative band power, which is expressed as the ratio of power in a specific frequency band to the total baseline power, in both the frontal and parietal regions, including beta over theta and alpha ratio, and differential entropy were most significant in detecting different levels of presence.

Abstract We present a novel system that leverages curators in the loop to develop a dataset and model for detecting structure features and functional annotations at residue-level from standard publication text. Our approach involves the integration of data from multiple resources, including PDBe, EuropePMC, PubMedCentral, and PubMed, combined with annotation guidelines from UniProt, and LitSuggest and HuggingFace models as tools in the annotation process. A team of seven annotators manually curated ten articles for named entities, which we utilized to train a starting PubmedBert model from HuggingFace. Using a human-in-the-loop annotation system, we iteratively developed the best model with commendable performance metrics of 0.90 for precision, 0.92 for recall, and 0.91 for F1-measure. Our proposed system showcases a successful synergy of machine learning techniques and human expertise in curating a dataset for residue-level functional annotations and protein structure features. The results demonstrate the potential for broader applications in protein research, bridging the gap between advanced machine learning models and the indispensable insights of domain experts.

Abstract This study conducts a comprehensive analysis and comparison of Bombyx mori cuticles across different developmental stages, ranging from larval to adult, utilizing advanced solid-state NMR techniques. The primary objective is to elucidate the underlying reasons for the contrasting hardness of adult cuticles and softness of larval cuticles. Notably, PXRD analysis reveals a prominent broad peak at 19.34°, indicating the predominantly amorphous nature of both larval and adult cuticles. Analysis of 13C CP-MAS SSNMR spectra highlights an elevated proportion of phenoxy carbon in adult cuticles (6.77%) compared to larval cuticles (1.24%). Furthermore, a distinctive resonance line at 144 ppm is exclusively observed in adult cuticles, due to catechols, suggesting potential biochemical pathway variations during development. Significant variations in the primary components of 13C chemical shift anisotropy (CSA) tensors for aliphatic carbons of amino acids, catechols, and lipids between adult and larval cuticles indicate alterations in electronic environments. Additionally, the shorter spin–lattice relaxation time of carbon nuclei in larval cuticles compared to adult cuticles implies slower motional dynamics with enhanced degree of sclerotization in adults. By investigating the internal structure and dynamics of cuticles, this research not only contributes to biomimetic material development but also enhances our understanding of structural changes across different developmental stages of B. mori.

Abstract Symbiosis between insects and bacteria has been established countless times. While it is well known that the symbionts originated from a variety of different bacterial taxa, it is usually difficult to determine their environmental source and a route of their acquisition by the host. In this study, we address this question using a model of Neisseriaceae symbionts in rodent lice. These bacteria established their symbiosis independently with different louse taxa (Polyplax, Hoplopleura, Neohaematopinus), most likely from the same environmental source. We first applied amplicon analysis to screen for candidate source bacterium in the louse environment. Since lice are permanent ectoparasites, often specific to the particular host, we screened various microbiomes associated with three rodent species (Microtus arvalis, Clethrionomys glareolus, and Apodemus flavicollis). The analyzed samples included fur, skin, spleen, and other ectoparasites sampled from these rodents. The fur microbiome data revealed a Neisseriaceae bacterium, closely related to the known louse symbionts. The draft genomes of the environmental Neisseriaceae, assembled from all three rodent hosts, converged to a remarkably small size of approximately 1.4 Mbp, being even smaller than the genomes of the related symbionts. Our results suggest that the rodent fur microbiome can serve as a source for independent establishment of bacterial symbiosis in associated louse species. We further propose a hypothetical scenario of the genome evolution during the transition of a free-living bacterium to the member of the rodent fur-associated microbiome and subsequently to the facultative and obligate louse symbionts.

Abstract Multimodal therapy for peritoneal metastasis (PM) including cytoreductive surgery (CRS) and hyperthermic intraperitoneal chemotherapy (HIPEC) provides long-term survival in highly selected colorectal cancer patients. Mechanisms behind HIPEC are unknown and may include induction of adaptive immunity. We therefore analyzed human PM samples and explored the impact of HIPEC in experimental models. Human samples from colorectal primary tumors (n = 19) and PM lesions (n = 37) were examined for the presence of CD8 + T-cells and their association with disease free (DFS) and overall survival (OS). CD8 + T cell response after HIPEC was assessed using an in-vivo PM mouse model, tumor cell lines and patient-derived tumor organoids. Patients with high intraepithelial CD8 + T cell counts showed longer DFS and OS. In the mouse model, HIPEC controlled growth of PM and increased numbers of functional granzyme positive CD8 + T cells within tumors. Cell lines and human organoids that were treated with heated chemotherapies showed immunogenic changes, reflected by significantly higher levels of MHC-class I molecules and expression of Cancer Testis Antigens Cyclin A1 and SSX-4. Using in-vitro co-culture assays, we noticed that cancer cells treated with heated chemotherapy primed dendritic cells, which subsequently enhanced effector functions of CD8 + T cells. The presence of CD8 + T-cells within PM lesions is associated with prolonged survival of patients with PM. Data from PM mouse model and in-vitro assay show that heated chemotherapies induce immunogenic changes on cancer cells leading to induction of CD8 + T-cells mediated immunity, which seems to control growth of PM lesions in mice after HIPEC.