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Abstract In bread wheat, a literature search gave 228 QTLs for six traits, including resistance against spot blotch and the following five other related traits: (i) stay green; (ii) flag leaf senescence; (iii) green leaf area duration; (iv) green leaf area of the main stem; and (v) black point resistance. These QTLs were used for metaQTL (MQTL) analysis. For this purpose, a consensus map with 72,788 markers was prepared; 69 of the above 228 QTLs, which were suitable for MQTL analysis, were projected on the consensus map. This exercise resulted in the identification of 16 meta-QTLs (MQTLs) located on 11 chromosomes, with the PVE ranging from 5.4% (MQTL7) to 21.8% (MQTL5), and the confidence intervals ranging from 1.5 to 20.7 cM (except five MQTLs with a range of 36.1–57.8 cM). The number of QTLs associated with individual MQTLs ranged from a maximum of 17 in MQTL3 to 8 each in MQTL5 and MQTL8 and 5 each in MQTL7 and MQTL14. The 16 MQTLs, included 12 multi-trait MQTLs; one of the MQTL also overlapped a genomic region carrying the major spot blotch resistance gene Sb1. Of the total 16 MQTLs, 12 MQTLs were also validated through marker-trait associations that were available from earlier genome-wide association studies. The genomic regions associated with MQTLs were also used for the identification of candidate genes (CGs) and led to the identification of 516 CGs encoding 508 proteins; 411 of these proteins are known to be associated with resistance against several biotic stresses. In silico expression analysis of CGs using transcriptome data allowed the identification of 71 differentially expressed CGs, which were examined for further possible studies. The findings of the present study should facilitate fine-mapping and cloning of genes, enabling Marker Assisted Selection.

Abstract A novel collaborative and continual learning across a network of decentralised healthcare units, avoiding identifiable data-sharing capacity, is proposed. Currently available methodologies, such as federated learning and swarm learning, have demonstrated decentralised learning. However, the majority of them face shortcomings that affect their performance and accuracy. These shortcomings include a non-uniform rate of data accumulation, non-uniform patient demographics, biased human labelling, and erroneous or malicious training data. A novel method to reduce such shortcomings is proposed in the present work through selective grouping and displacing of actors in a network of many entities for intra-group sharing of learning with inter-group accessibility. The proposed system, known as Orbital Learning, incorporates various features from split learning and ensemble learning for a robust and secure performance of supervised models. A digital embodiment of the information quality and flow within a decentralised network, this platform also acts as a digital twin of healthcare network. An example of ECG classification for arrhythmia with 6 clients is used to analyse its performance and is compared against federated learning. In this example, four separate experiments are conducted with varied configurations, such as varied age demographics and clients with data tampering. The results obtained show an average area under receiver operating characteristic curve (AUROC) of 0.819 (95% CI 0.784–0.853) for orbital learning whereas 0.714 (95% CI 0.692–0.736) for federated learning. This result shows an increase in overall performance and establishes that the proposed system can address the majority of the issues faced by existing decentralised learning methodologies. Further, a scalability demo conducted establishes the versatility and scalability of this platform in handling state-of-the-art large language models.

Abstract Plasmonic coatings can absorb electromagnetic radiation from visible to far-infrared spectrum for the better performance of solar panels and energy saving smart windows. For these applications, it is important for these coatings to be as thin as possible and grown at lower temperatures on arbitrary substrates like glass, silicon, or flexible polymers. Here, we tune and investigate the plasmonic resonance of titanium nitride thin films in lower thicknesses regime varying from ~ 20 to 60 nm. High-quality crystalline thin films of route-mean-square roughness less than ~ 0.5 nm were grown on a glass substrate at temperature of ~ 200 °C with bias voltage of − 60 V using cathodic vacuum arc deposition. A local surface-enhanced-plasmonic-resonance was observed between 400 and 500 nm, which further shows a blueshift in plasmonic frequency in thicker films due to the increase in the carrier mobility. These results were combined with finite-difference-time-domain numerical analysis to understand the role of thicknesses and stoichiometry on the broadening of electromagnetic absorption.

Abstract The persistent challenges posed by pollution and climate change are significant factors disrupting ecosystems, particularly aquatic environments. Numerous contaminants found in aquatic systems, such as ammonia and metal toxicity, play a crucial role in adversely affecting aquaculture production. Against this backdrop, fish feed was developed using quinoa husk (the byproduct of quinoa) as a substitute for fish meal. Six isonitrogenous diets (30%) and isocaloric diets were formulated by replacing fish meal with quinoa husk at varying percentages: 0% quinoa (control), 15, 20, 25, 30 and 35%. An experiment was conducted to explore the potential of quinoa husk in replacing fish meal and assess its ability to mitigate ammonia and arsenic toxicity as well as high-temperature stress in Pangasianodon hypophthalmus. The formulated feed was also examined for gene regulation related to antioxidative status, immunity, stress proteins, growth regulation, and stress markers. The gene regulation of sod, cat, and gpx in the liver was notably upregulated under concurrent exposure to ammonia, arsenic, and high-temperature (NH3 + As + T) stress. However, quinoa husk at 25% downregulated sod, cat, and gpx expression compared to the control group. Furthermore, genes associated with stress proteins HSP70 and DNA damage-inducible protein (DDIP) were significantly upregulated in response to stressors (NH3 + As + T), but quinoa husk at 25% considerably downregulated HSP70 and DDIP to mitigate the impact of stressors. Growth-responsive genes such as myostatin (MYST) and somatostatin (SMT) were remarkably downregulated, whereas growth hormone receptor (GHR1 and GHRβ), insulin-like growth factors (IGF1X, IGF2X), and growth hormone gene were significantly upregulated with quinoa husk at 25%. The gene expression of apoptosis (Caspase 3a and Caspase 3b) and nitric oxide synthase (iNOS) were also noticeably downregulated with quinoa husk (25%) reared under stressful conditions. Immune-related gene expression, including immunoglobulin (Ig), toll-like receptor (TLR), tumor necrosis factor (TNFα), and interleukin (IL), strengthened fish immunity with quinoa husk feed. The results revealed that replacing 25% of fish meal with quinoa husk could improve the gene regulation of P. hypophthalmus involved in mitigating ammonia, arsenic, and high-temperature stress in fish.

Abstract In the present study, an attempt has been made to assess the impact of vehicular noise upon the 3-wheeler tempo drivers and to know whether there is any relationship between hearing loss and cumulative noise exposure. For this purpose, 3-wheeler tempo drivers (Exposed group) and non-commercial light motor vehicle car drivers (Unexposed group) were chosen as study subjects. Three traffic routes were selected to assess the noise level during waiting and running time in the exposed and unexposed groups. Among all three routes, the highest mean noise level (Leq) was observed on the Chowk to Dubagga route for waiting and en-route noise measurement. It was measured as 84.13 dB(A) and 86.36 dB(A) for waiting and en-route periods of 7.68 ± 3.46 and 31.05 ± 6.6 min, respectively. Cumulative noise exposure was found to be significantly different (p

Abstract It is an urgent needs to address climate change and pollution in aquatic systems using suitable mitigation measures to avoid the aquatic animals' extinction. The vulnerability and extinction of the aquatic animals in the current scenario must be addressed to enhance safe fish food production. Taking into consideration of such issues in fisheries and aquaculture, an experiment was designed to mitigate high temperature (T) and low pH stress, as well as arsenic (As) pollution in fish using copper (Cu) containing diets. In the present investigation, the Cu-containing diets graded with 0, 4, 8, and 12 mg kg-1 were prepared and fed to Pangasianodon hypophthalmus reared under As, low pH, and high-temperature stress. The gene expression was highly affected in terms of the primary, secondary, and tertiary stress response, whereas supplementation of Cu-containing diet mitigates the stress response. Oxidative stress genes such as catalase (CAT), superoxide dismutase (SOD), and glutathione peroxidase (GPx) were significantly upregulated by stressors (As, As + T, and As + pH + T). Whereas, heat shock protein (HSP 70), inducible nitric oxide synthase (iNOS), metallothionine (MT), caspase 3a (Cas 3a), and cytochrome P450 (CYP 450) were highly upregulated by stressors, while dietary Cu at 8 mg kg-1 diet significantly downregulated these gene expressions. Indeed, the immunity-related genes viz. TNFα, Ig, TLR, and immune-related attributes viz. albumin, globulin, total protein, A:G ratio, blood glucose, NBT, and myeloperoxidase (MPO) were also improved with Cu-containing diets. Cu containing diets substantially improved neurotransmitter enzyme (AChE) and vitamin C (Vit C). DNA damage was also reduced with supplementation of Cu at 8 mg kg-1 diet. The growth index viz. final body weight gain (%), specific growth rate, protein efficiency ratio, food conversion ratio, relative feed intake, and daily growth index were noticeably enhanced by Cu diets (4 and 8 mg kg-1 diet). The growth-related genes expressions viz. growth hormone (GH), growth hormone regulator 1 (Ghr1), growth hormone regulator β (Ghrβ,) myostatin (MYST), and somatostatin (SMT) supported the growth enhancement with Cu at 8 mg kg-1 diet. The bioaccumulation of As was reduced with Cu-containing diets. The fish were infected with Aeromonas hydrophila at the end of the 105 days experimental trial. Cu at 8 mg kg-1 diet improved immunity, reduced the cumulative mortality, and enhanced the relative percentage survival of the fish. The results revealed that the innovative Cu diets could reduce the extinction of the fish against climate change and pollution era and produce the safest production that is safe to humans for consumption.

Abstract The ongoing challenges of climate change and pollution are major factors disturbing ecosystems, including aquatic systems. They also have an impact on gene regulation and biochemical changes in aquatic animals, including fish. Understanding the mechanisms of gene regulation and biochemical changes due to climate change and pollution in aquatic animals is a challenging task. However, with this backdrop, the present investigation was conducted to explore the effects of arsenic (As) and ammonia (NH3) toxicity and high-temperature (T) stress on gene regulation and biochemical profiles, mitigated by dietary manganese (Mn) in Pangasianodon hypophthalmus. The fish were exposed to different combinations of As, NH3, and T, and fed with dietary Mn at 4, 8, and 12 mg kg−1 to evaluate the gene expression of immunity, antioxidative status, cytokine, and NfKB signaling pathway genes. HSP 70, cytochrome P450 (CYP 450), metallothionein (MT), DNA damage-inducible protein (DDIP), caspase (CAS), tumor necrosis factor (TNFα), toll-like receptor (TLR), interleukin (IL), inducible nitric oxide synthase (iNOS), catalase (CAT), superoxide dismutase (SOD), and glutathione peroxidase (GPx) were noticeably highly upregulated by As + NH3 + T stress, whereas Mn diet at 8 mg kg−1 downregulated these genes. Further, total immunoglobulin (Ig), myostatin (MYST), somatostatin (SMT), growth hormone (GH), growth hormone regulator 1 and β, insulin-like growth factors (IGF1X1 and IGF1X2) were significantly upregulated by Mn diets. The biochemical profiles were highly affected by stressors (As + NH3 + T). The bioaccumulation of arsenic in different tissues was also notably reduced by Mn diets. Furthermore, the infectivity of the fish was reduced, and survival against pathogenic bacteria was enhanced by Mn diet at 8 mg kg−1. The results of the present investigation revealed that dietary Mn at 8 mg kg−1 controls gene regulation against multiple stressors (As, NH3, As + NH3, NH3 + T, As + NH3 + T) in fish.

Abstract Amyotrophic Lateral Sclerosis (ALS) is a rapidly progressive neurodegenerative disease. Accurately predicting the survival time for ALS patients can help patients and clinicians to plan for future treatment and care. We describe the application of a machine-learned tool that incorporates clinical features and cortical thickness from brain magnetic resonance (MR) images to estimate the time until a composite respiratory failure event for ALS patients, and presents the prediction as individual survival distributions (ISDs). These ISDs provide the probability of survival (none of the respiratory failures) at multiple future time points, for each individual patient. Our learner considers several survival prediction models, and selects the best model to provide predictions. We evaluate our learned model using the mean absolute error margin (MAE-margin), a modified version of mean absolute error that handles data with censored outcomes. We show that our tool can provide helpful information for patients and clinicians in planning future treatment.

Abstract Obesity is a complex disease caused by various factors, and synthetic drugs used to treat it can have side effects. Natural compounds, such as olivetol, could be a promising alternative. Olivetol is a substance found in certain lichen species and has anti-inflammatory and anti-cancer properties. In this study, researchers conducted in-silico molecular docking studies and found that olivetol had significant binding affinity with receptors involved in obesity. They also investigated the effects of olivetol on a diet-induced obese zebrafish model and found that high doses of olivetol reduced excessive fat accumulation and triglyceride and lipid accumulation. The low dose of olivetol showed a significant reduction in liver enzymes' levels. However, the high dose of olivetol resulted in a significant increase in HMG-CoA levels. These results suggest that olivetol may be a promising anti-obesity agent for the treatment of hyperlipidemia-related disorders, but further research is necessary to understand its full effects on the body.

Abstract Ammonia and arsenic pollution, along with the impact of climate change, represent critical factors influencing both the quantity and quality of aquaculture production. Recent developments have underscored the significance of these issues, as they not only disrupt aquatic ecosystems but also have far reaching consequences for human health. To addressed above challenges, an experiment was conducted to delineate the potential of manganese nanoparticles (Mn-NPs) to mitigate arsenic and ammonia pollution as well as high temperature stress in Pangasianodon hypophthalmus. The fish were exposed to different combination of arsenic and ammonia pollution as well as high temperature stress, while simultaneously incorporating diets enriched with Mn-NPs. The inclusion of Mn-NPs at 3 mg kg−1 in the diet led to a noteworthy downregulation of cortisol and HSP 70 gene expression, indicating their potential in mitigating stress responses. Furthermore, immune related gene expressions were markedly altered in response to the stressors but demonstrated improvement with the Mn-NPs diet. Interestingly, the expression of inducible nitric oxide synthase (iNOS), caspase (CAS), metallothionine (MT) and cytochrome P450 (CYP450) genes expression were prominently upregulated, signifying a stress response. Whereas, Mn-NPs at 3 mg kg−1 diet was significantly downregulated theses gene expression and reduces the stress. In addition to stress-related genes, we evaluated the growth-related gene expressions such as growth hormone (GH), growth hormone regulator 1 (GHR1 and GHRβ), Insulin like growth factor (IGF1 and IGF2) were significantly upregulated whereas, myostatin and somatostatin were downregulated upon the supplementation of dietary Mn-NPs with or without stressors in fish. The gene expression of DNA damage inducible protein and DNA damage in response to head DNA % and tail DNA % was protected by Mn-NPs diets. Furthermore, Mn-NPs demonstrated a capacity to enhance the detoxification of arsenic in different fish tissues, resulting in reduced bioaccumulation of arsenic in muscle and other tissues. This finding highlights Mn-NPs as a potential solution for addressing bioaccumulation associated risks. Our study aimed to comprehensively examined the role of dietary Mn-NPs in mitigating the multiple stressors using gene regulation mechanisms, with enhancing the productive performance of P. hypophthalmus.

Abstract More than six and half million people have died as a result of the COVID-19 pandemic till Dec 2022. Vaccination is the most effective means to prevent mortality and infection attributed to COVID-19. Identifying public attitudes and perceptions on COVID-19 vaccination is essential to strengthening the vaccination programmes. This study aims to identify attitudes and perceptions of twitter users towards COVID-19 vaccinations in four different countries. A sentiment analysis of 663,377 tweets from October 2020 to September 2022 from four different countries (i.e., India, South Africa, UK, and Australia) was conducted. Text mining using roBERTA (Robustly Optimized Bert Pretraining approach) python library was used to identify the polarity of people’s attitude as "negative", "positive" or "neutral" based on tweets. A sample of 2000 tweets (500 from each country) were thematically analysed to explore the people’s perception concerning COVID-19 vaccines across the countries. The attitudes towards COVID-19 vaccines varied by countries. Negative attitudes were observed to be highest in India (58.48%), followed by United Kingdom (33.22%), Australia (31.42%) and South Africa (28.88%). Positive attitudes towards vaccines were highest in the United Kingdom (21.09%). The qualitative analysis yielded eight themes namely (i) vaccine shortages, (ii) vaccine side-effects, (iii) distrust on COVID-19 vaccines, (iv) voices for vaccine equity, (v) awareness about vaccines, (vi) myth busters, (vii) vaccines work and (viii) vaccines are safe. The twitter discourse reflected the evolving situation of COVID-19 pandemic and vaccination strategies, lacunae and positives in the respective countries studied.

Abstract Hydrogels are used extensively as cell-culture scaffolds for both 2D and 3D cell cultures due to their biocompatibility and the ease in which their mechanical and biological properties can be tailored to mimic natural tissue. The challenge when working with hydrogel-based scaffolds is in their handling, as hydrogels that mimic e.g. brain tissue, are both fragile and brittle when prepared as thin (sub-mm) membranes. Here, we describe a method for facile handling of thin hydrogel cell culture scaffolds by molding them onto a polycaprolactone (PCL) mesh support attached to a commonly used Transwell set-up in which the original membrane has been removed. In addition to demonstrating the assembly of this set-up, we also show some applications for this type of biological membrane. A polyethylene glycol (PEG)-gelatin hydrogel supports cell adhesion, and the structures can be used for biological barrier models comprising either one or multiple hydrogel layers. Here, we demonstrate the formation of a tight layer of an epithelial cell model comprising MDCK cells cultured over 9 days by following the build-up of the transepithelial electrical resistances. Second, by integrating a pure PEG hydrogel into the PCL mesh, significant swelling is induced, which leads to the formation of a non-adherent biological scaffold with a large curvature that is useful for spheroid formation. In conclusion, we demonstrate the development of a handling platform for hydrogel cell culture scaffolds for easy integration with conventional measurement techniques and miniaturized organs-on-chip systems.

Abstract Manganese (Mn) is an essential element for humans and animals including, fish. It is a still poorly studied in aquatic organisms, where it can be noticeably useful for dietary components and also found pollutant in aquatic environment at high concentrations. On the above information, an experiment was delineated to determine the lethal concentration of manganese (Mn) and manganese nanoparticles (Mn-NPs) alone and with high temperature (34 °C) and its effect on various biochemical markers in Pangasianodon hypophthalmus. The median lethal concentration (96-LC50) of Mn alone (111.75 mg L−1) and along with high temperature (110.76 mg L−1), Mn-NPs alone (93.81 mg L−1) and with high temperature (34 °C) (92.39 mg L−1) was determined in P. hypophthalmus. The length and weight of the fish were 6.32 ± 0.23 cm and 7.57 ± 1.35 g. The present investigation used five hundred forty-six fish, including range finding (216 fish) and definitive test (330 fish). The acute definitive doses were applied to assess the effect of oxidative stress, glycolytic biomarkers, protein biomarkers, fish immunity, neurotransmitter, energy level, stress hormone and histopathology. Oxidative stress (catalase, superoxide dismutase, glutathione-s-transferase and glutathione peroxidase), stress biomarkers (lipid peroxidation, cortisol, heat shock protein, and blood glucose), lactate and malate dehydrogenase, alanine and aspartate aminotransferase, a neurotransmitter, glucose-6-phosphate dehydrogenase (G6PDH), ATPase, immune system biomarkers (NBT, total protein, albumin, globulin and A:G ratio) were altered with exposure to Mn and Mn-NPs. The histopathology of the liver and gill were also changed due to exposure to Mn and Mn-NPs. The bioaccumulation of Mn in the liver, gill, kidney, brain and muscle tissues, and experimental water at different intervals of 24, 48, 72 and 96 h were determined. Based on the present results, it is strongly suggested that Mn and Mn-NPs exposure alone and with high temperature (34 °C) enhanced toxicity and altered biochemical and morphological attributes. This study also suggested that essential elements in both forms (inorganic and nano) at higher concentrations of Mn and Mn-NPs lead to pronounced deleterious alteration in cellular and metabolic activities and histopathology of P. hypophthalmus.

Abstract The toxicity of ammonia surged with arsenic pollution and high temperature (34 °C). As climate change enhances the pollution in water bodies, however, the aquatic animals are drastically affected and extinct from nature. The present investigation aims to mitigate arsenic and ammonia toxicity and high-temperature stress (As + NH3 + T) using zinc nanoparticles (Zn-NPs) in Pangasianodon hypophthalmus. Zn-NPs were synthesized using fisheries waste to developing Zn-NPs diets. The four isonitrogenous and isocaloric diets were formulated and prepared. The diets containing Zn-NPs at 0 (control), 2, 4 and 6 mg kg−1 diets were included. Superoxide dismutase (SOD), catalase (CAT), glutathione peroxidase (GPx) and glutathione-s-transferase (GST) were noticeably improved using Zn-NPs diets in fish reared under with or without stressors. Interestingly, lipid peroxidation was significantly reduced, whereas vitamin C and acetylcholine esterase were enhanced with supplementation of Zn-NPs diets. Immune-related attributes such as total protein, globulin, albumin, myeloperoxidase (MPO), A:G ratio, and NBT were also improved with Zn-NPs at 4 mg kg−1 diet. The immune-related genes such as immunoglobulin (Ig), tumor necrosis factor (TNFα), and interleukin (IL1b) were strengthening in the fish using Zn-NPs diets. Indeed, the gene regulations of growth hormone (GH), growth hormone regulator (GHR1), myostatin (MYST) and somatostatin (SMT) were significantly improved with Zn-NPs diets. Blood glucose, cortisol and HSP 70 gene expressions were significantly upregulated by stressors, whereas the dietary Zn-NPs downregulated the gene expression. Blood profiling (RBC, WBC and Hb) was reduced considerably with stressors (As + NH3 + T), whereas Zn-NPs enhanced the RBC, WBC, and Hb count in fish reread in control or stress conditions. DNA damage-inducible protein gene and DNA damage were significantly reduced using Zn-NPs at 4 mg kg−1 diet. Moreover, the Zn-NPs also enhanced the arsenic detoxification in different fish tissues. The present investigation revealed that Zn-NPs diets mitigate ammonia and arsenic toxicity, and high-temperature stress in P. hypophthalmus.

Abstract Industrial Internet of Things (IIoT) is the new paradigm to perform different healthcare applications with different services in daily life. Healthcare applications based on IIoT paradigm are widely used to track patients health status using remote healthcare technologies. Complex biomedical sensors exploit wireless technologies, and remote services in terms of industrial workflow applications to perform different healthcare tasks, such as like heartbeat, blood pressure and others. However, existing industrial healthcare technoloiges still has to deal with many problems, such as security, task scheduling, and the cost of processing tasks in IIoT based healthcare paradigms. This paper proposes a new solution to the above-mentioned issues and presents the deep reinforcement learning-aware blockchain-based task scheduling (DRLBTS) algorithm framework with different goals. DRLBTS provides security and makespan efficient scheduling for the healthcare applications. Then, it shares secure and valid data between connected network nodes after the initial assignment and data validation. Statistical results show that DRLBTS is adaptive and meets the security, privacy, and makespan requirements of healthcare applications in the distributed network.

Abstract East Kolkata Wetlands (EKW) is an important site for fish culture in sewage-fed areas, which are major receivers of pollutants and wastages from Kolkata. EKW is internationally important as the Ramsar site was declared on Aug 2002 with an area of 125 km2. EKW is a natural water body where wastewater-fed natural aquaculture has been practiced for more than 70 years. It is ecologically vulnerable due to the discharge of toxic waste through sewage canals from cities. Assessing the EKW to understand the inflow and load of the toxic metal (s) in fish, water, and sediments samples is essential. The field (samples collection from 13 sites) and lab (determination of toxic level of metals) based research were carried out to assess metal toxicity and health risk assessment in EKW. The levels of eighteen metals (18), namely Chromium, Vanadium, Cobalt, Manganese, Copper, Nickel, Zinc, Silver, Molybdenum, Arsenic, Selenium, Tin, Gallium, Germanium, Strontium, Cadmium, Mercury, and Lead, were determined using Inductively coupled plasma mass spectrometry (ICP-MS) in five fish tissues viz. muscle, liver, kidney, gill and brain, along with the water samples and soil sediments in 13 sampling sites. The bioaccumulation and concentration of metals in fish tissues, soil sediments, and water samples were well within the safe level concerning the recommendation of different national and international agencies except for a few metals in a few sampling sites like Cd, As, and Pb. The geoaccumulation index (Igeo) was also determined in the soil sediments, indicating moderate arsenic, selenium, and mercury contamination in a few sites. The contamination index in water was also determined in 13 sampling sites. The estimated daily intake (EDI), reference dose (RfD), target hazard quotient (THQ), slope factor and cancer risk of Cr, Mn, Co, Ni, Cu, Zn, As, Se, Cd, Pb and Hg from fish muscle were determined. Based on the results of the present investigation, it is concluded that fish consumption in the East Kolkata Wetland (EKW) is safe. The effects of bioaccumulation of metals in muscle tissue were well within the safe level for consumption as recommended by WHO/FAO.

Abstract Targeted covalent inhibition represents one possible strategy to block the function of SARS-CoV-2 Main Protease (MPRO), an enzyme that plays a critical role in the replication of the novel SARS-CoV-2. Toward the design of covalent inhibitors, we built a covalent inhibitor dataset using deep learning models followed by high throughput virtual screening of these candidates against MPRO. Two top-ranking inhibitors were selected for mechanistic investigations—one with an activated ester warhead that has a piperazine core and the other with an acrylamide warhead. Specifically, we performed a detailed analysis of the free energetics of covalent inhibition by hybrid quantum mechanics/molecular mechanics simulations. Cleavage of a fragment of the non-structured protein (NSP) from the SARS-CoV-2 genome was also simulated for reference. Simulations show that both candidates form more stable enzyme-inhibitor (E-I) complexes than the chosen NSP. It was found that both the NSP fragment and the activated ester inhibitor react with CYS145 of MPRO in a concerted manner, whereas the acrylamide inhibitor follows a stepwise mechanism. Most importantly, the reversible reaction and the subsequent hydrolysis reaction from E-I complexes are less probable when compared to the reactions with an NSP fragment, showing promise for these candidates to be the base for efficient MPRO inhibitors.

Abstract Brassica juncea is an important oilseed crop, widely grown as a source of edible oil. Seed size is a pivotal agricultural trait in oilseed Brassicas. However, the regulatory mechanisms underlying seed size determination are poorly understood. To elucidate the transcriptional dynamics involved in the determination of seed size in B. juncea, we performed a comparative transcriptomic analysis using developing seeds of two varieties, small-seeded Early Heera2 (EH2) and bold-seeded Pusajaikisan (PJK), at three distinct stages (15, 30 and 45 days after pollination). We detected 112,550 transcripts, of which 27,186 and 19,522 were differentially expressed in the intra-variety comparisons and inter-variety comparisons, respectively. Functional analysis using pathway, gene ontology, and transcription factor enrichment revealed that cell cycle- and cell division-related transcripts stay upregulated during later stages of seed development in the bold-seeded variety but are downregulated at the same stage in the small-seeded variety, indicating that an extended period of cell proliferation in the later stages increased seed weight in PJK as compared to EH2. Further, k-means clustering and candidate genes-based analyses unravelled candidates for employing in seed size improvement of B. juncea. In addition, candidates involved in determining seed coat color, oil content, and other seed traits were also identified.

Abstract Protein–ligand interactions (PLIs) are essential for biochemical functionality and their identification is crucial for estimating biophysical properties for rational therapeutic design. Currently, experimental characterization of these properties is the most accurate method, however, this is very time-consuming and labor-intensive. A number of computational methods have been developed in this context but most of the existing PLI prediction heavily depends on 2D protein sequence data. Here, we present a novel parallel graph neural network (GNN) to integrate knowledge representation and reasoning for PLI prediction to perform deep learning guided by expert knowledge and informed by 3D structural data. We develop two distinct GNN architectures: $$\hbox {GNN}_{\mathrm{F}}$$ GNN F is the base implementation that employs distinct featurization to enhance domain-awareness, while $$\hbox {GNN}_{\mathrm{P}}$$ GNN P is a novel implementation that can predict with no prior knowledge of the intermolecular interactions. The comprehensive evaluation demonstrated that GNN can successfully capture the binary interactions between ligand and protein’s 3D structure with 0.979 test accuracy for $$\hbox {GNN}_{\mathrm{F}}$$ GNN F and 0.958 for $$\hbox {GNN}_{\mathrm{P}}$$ GNN P for predicting activity of a protein–ligand complex. These models are further adapted for regression tasks to predict experimental binding affinities and $$\hbox {pIC}_{\mathrm{50}}$$ pIC 50 crucial for compound’s potency and efficacy. We achieve a Pearson correlation coefficient of 0.66 and 0.65 on experimental affinity and 0.50 and 0.51 on $$\hbox {pIC}_{\mathrm{50}}$$ pIC 50 with $$\hbox {GNN}_{\mathrm{F}}$$ GNN F and $$\hbox {GNN}_{\mathrm{P}}$$ GNN P , respectively, outperforming similar 2D sequence based models. Our method can serve as an interpretable and explainable artificial intelligence (AI) tool for predicted activity, potency, and biophysical properties of lead candidates. To this end, we show the utility of $$\hbox {GNN}_{\mathrm{P}}$$ GNN P on SARS-Cov-2 protein targets by screening a large compound library and comparing the prediction with the experimentally measured data.

Abstract Since it emerged in December of 2019, COVID-19 has placed a huge burden on medical care in countries throughout the world, as it led to a huge number of hospitalizations and mortalities. Many medical centers were overloaded, as their intensive care units and auxiliary protection resources proved insufficient, which made the effective allocation of medical resources an urgent matter. This study describes learned survival prediction models that could help medical professionals make effective decisions regarding patient triage and resource allocation. We created multiple data subsets from a publicly available COVID-19 epidemiological dataset to evaluate the effectiveness of various combinations of covariates—age, sex, geographic location, and chronic disease status—in learning survival models (here, “Individual Survival Distributions”; ISDs) for hospital discharge and also for death events. We then supplemented our datasets with demographic and economic information to obtain potentially more accurate survival models. Our extensive experiments compared several ISD models, using various measures. These results show that the “gradient boosting Cox machine” algorithm outperformed the competing techniques, in terms of these performance evaluation metrics, for predicting both an individual’s likelihood of hospital discharge and COVID-19 mortality. Our curated datasets and code base are available at our Github repository for reproducing the results reported in this paper and for supporting future research.

Abstract Effects of a novel dietary mixture of selenium nanoparticles (Se-NPs) and omega-3-fatty acids i.e., Eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) on mitigating arsenic pollution, high-temperature stress and bacterial infection were investigated in Pangasianodon hypophthalmus. To aim this, four isocaloric and iso-nitrogenous diets were prepared: control feed (no supplementation), Se-NPs at 0.2 mg kg−1 diet with EPA + DHA at 0.2, 0.4 and 0.6% as supplemented diets. Fish were reared under normal condition or concurrent exposure to arsenic (2.65 mg L−1), and temperature (34 °C) (As + T) stress for 105 days. The experiment was conducted with eight treatments in triplicates. Response to various stresses i.e., primary (cortisol), secondary (oxidative stress, immunity, and stress biomarkers) and tertiary stress response (growth performance, bioaccumulation and mortality due to bacterial infection) were determined. Supplementation of dietary Se-NPs at 0.2 mg kg−1 diet and EPA + DHA at 0.2 and 0.4% reduced the primary stress level. Exposure to arsenic and temperature (As + T) and fed with control diet and EPA + DHA at 0.6% aggravated the cortisol level. Anti-oxidative enzymes (Catalase, superoxide dismutase, glutathione peroxidase and glutathione-s-transferase) and immunity (Nitroblue tetrazolium, total protein, albumin, globulin, A:G ratio, total immunoglobulin and myeloperoxidase) of the fish were augmented by supplementation of Se-NPs and EPA + DHA at 0.2 and 0.4%. Neurotransmitter enzyme, HSP 70, Vitamin C were significantly enhanced (p

Abstract Development of effective counteragents against the novel coronavirus disease (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) strains, requires clear insights and information for understanding the immune responses associated with it. This global pandemic has pushed the healthcare system and restricted the movement of people and succumbing of the available therapeutics utterly warrants the development of a potential vaccine to contest the deadly situation. In the present study, highly efficacious, immunodominant cytotoxic T-lymphocyte (CTL) epitopes were predicted by advanced immunoinformatics assays using the spike glycoprotein of SARS-CoV2, generating a robust and specific immune response with convincing immunological parameters (Antigenicity, TAP affinity, MHC binder) engendering an efficient viral vaccine. The molecular docking studies show strong binding of the CTL construct with MHC-1 and host membrane specific TLR2 receptors. The molecular dynamics simulation in an explicit system confirmed the stable and robust binding of CTL epitope with TLR2. Steep magnitude RMSD variation and compelling residual fluctuations existed in terminal residues and various loops of the β linker segments of TLR2-epitope (residues 105-156 and 239-254) to about 0.4 nm. The reduced Rg value (3.3 nm) and stagnant SASA analysis (275 nm/S2/N after 8 ns and 5 ns) for protein surface and its orientation in the exposed and buried regions suggests more compactness due to the strong binding interaction of the epitope. The CTL vaccine candidate establishes a high capability to elicit the critical immune regulators, like T-cells and memory cells as proven by the in silico immunization assays and can be further corroborated through in vitro and in vivo assays.

Abstract The highly successful PBE functional and the modified Becke–Johnson exchange potential were used to calculate the structural, electronic, and optical properties of the vacancy-ordered double perovskites A2BX6 (A = Rb, Cs; B = Sn, Pd, Pt; X = Cl, Br, and I) using the density functional theory, a first principles approach. The convex hull approach was used to check the thermodynamic stability of the compounds. The calculated parameters (lattice constants, band gap, and bond lengths) are in tune with the available experimental and theoretical results. The compounds, Rb2PdBr6 and Cs2PtI6, exhibit band gaps within the optimal range of 0.9–1.6 eV, required for the single-junction photovoltaic applications. The photovoltaic efficiency of the studied materials was assessed using the spectroscopic-limited-maximum-efficiency (SLME) metric as well as the optical properties. The ideal band gap, high dielectric constants, and optimum light absorption of these perovskites make them suitable for high performance single and multi-junction perovskite solar cells.

Abstract Antigen-adjuvant conjugation is known to enhance antigen-specific T-cell production in vaccine models, but scalable methods are required to generate site-specific conjugation for clinical translation of this technique. We report the use of the cell-free protein synthesis (CFPS) platform as a rapid method to produce large quantities (> 100 mg/L) of a model antigen, ovalbumin (OVA), with site-specific incorporation of p-azidomethyl-l-phenylalanine (pAMF) at two solvent-exposed sites away from immunodominant epitopes. Using copper-free click chemistry, we conjugated CpG oligodeoxynucleotide toll-like receptor 9 (TLR9) agonists to the pAMF sites on the mutant OVA protein. The OVA-CpG conjugates demonstrate enhanced antigen presentation in vitro and increased antigen-specific CD8+ T-cell production in vivo. Moreover, OVA-CpG conjugation reduced the dose of CpG needed to invoke antigen-specific T-cell production tenfold. These results highlight how site-specific conjugation and CFPS technology can be implemented to produce large quantities of covalently-linked antigen-adjuvant conjugates for use in clinical vaccines.

Abstract Exposure to Ionizing radiation (IR) poses a severe threat to human health. Therefore, there is an urgent need to develop potent and safe radioprotective agents for radio-nuclear emergencies. Phosphatidylinositol-3-kinase (PI3K) mediates its cytoprotective signaling against IR by phosphorylating membrane phospholipids to phosphatidylinositol 3,4,5 triphosphate, PIP3, that serve as a docking site for AKT. Phosphatase and Tensin Homolog on chromosome 10 (PTEN) antagonizes PI3K activity by dephosphorylating PIP3, thus suppressing PI3K/AKT signaling that could prevent IR induced cytotoxicity. The current study was undertaken to investigate the radioprotective potential of PTEN inhibitor (PTENi), bpV(HOpic). The cell cytotoxicity, proliferation index, and clonogenic survival assays were performed for assessing the radioprotective potential of bpV(HOpic). A safe dose of bpV(HOpic) was shown to be radioprotective in three radiosensitive tissue origin cells. Further, bpV(HOpic) significantly reduced the IR-induced apoptosis and associated pro-death signaling. A faster and better DNA repair kinetics was also observed in bpV(HOpic) pretreated cells exposed to IR. Additionally, bpV(HOpic) decreased the IR-induced oxidative stress and significantly enhanced the antioxidant defense mechanism in cells. The radioprotective effect of bpV(HOpic) was found to be AKT dependant and primarily regulated by the enhanced glycolysis and associated signaling. Furthermore, this in-vitro observation was verified in-vivo, where administration of bpV(HOpic) in C57BL/6 mice resulted in AKT activation and conferred survival advantage against IR-induced mortality. These results imply that bpV(HOpic) ameliorates IR-induced oxidative stress and cell death by inducing AKT signaling mediated antioxidant defense system and DNA repair pathways, thus strengthening its potential to be used as a radiation countermeasure.

Abstract Accessing the peripheral nervous system (PNS) by topically applied nanoparticles is a simple and novel approach with clinical applications in several PNS disorders. Skin is richly innervated by long peripheral axons that arise from cell bodies located distally within ganglia. In this study we attempt to target dorsal root ganglia (DRG) neurons, via their axons by topical application of lectin-functionalized gold nanoparticles (IB4-AuNP). In vitro, 140.2 ± 1.9 nm IB4-AuNP were found to bind both axons and cell bodies of DRG neurons, and AuNP applied at the axonal terminals were found to translocate to the cell bodies. Topical application of IB4-AuNP on rat hind-paw resulted in accumulation of three to fourfold higher AuNP in lumbar DRG than in contralateral control DRGs. Results from this study clearly suggest that topically applied nanoparticles with neurotropic targeting ligands can be utilized for delivering nanoparticles to neuronal cell bodies via axonal transport mechanisms.

Abstract Sugarcane-derived biomass is a promising source of renewable energy to meet the growing demands for biofuel. Currently, modern sugarcane cultivars are unable to provide enough biomass due to their narrow genetic base and susceptibility to abiotic and biotic stresses. We have evaluated total of 23 hybrids derived from diverse genetic backgrounds of different Saccharum spp. and allied genera, one inbred and compared with commercial checks. Intergeneric hybrids (IGHs) KGS 99-100 and GU 04-432, produced significantly higher biomass (43.37 t ha−1 and 35.24 t ha−1, respectively) than commercial sugarcane have genes derived from Erianthus arundinaceus. Interspecific hybrids (ISHs) GU 07-3704 and 99-489, also produced significantly higher amounts of biomass (37.24 t ha−1 and 33.25 t ha−1, respectively) than commercial checks have genes from S. officinarum and S. spontaneum backgrounds. ISHs recorded significantly higher biomass yield, number of stalks and total dry matter percentage whereas, IGH group recorded significantly higher fibre percent. Furthermore, the clones resistant to red rot and sugarcane borers were identified. The estimated energy value for seven hybrid clones was found to be very high. Cluster analysis of genetic traits revealed two major clusters in traits improving biomass. Our study has revealed that the genetic diversity present in these hybrids could be used for improving biomass production and tolerance to abiotic and biotic stresses in cultivated sugarcanes.

Abstract Here, we report that minimal functional gelsolin i.e. fragment 28–161 can display F-actin depolymerizing property even after heating the protein to 80 °C. Small angle X-ray scattering (SAXS) data analysis confirmed that under Ca2+-free conditions, 28–161 associates into monomer to dimer and tetramer, which later forms β-amyloids, but in presence of Ca2+, it forms dimers which proceed to non-characterizable aggregates. The dimeric association also explained the observed decrease in ellipticity in circular dichroism experiments with increase in temperature. Importantly, SAXS data based models correlated well with our crystal structure of dimeric state of 28–161. Characterization of higher order association by electron microscopy, Congo red and ThioflavinT staining assays further confirmed that only in absence of Ca2+ ions, heating transforms 28–161 into β-amyloids. Gel filtration and other experiments showed that β-amyloids keep leaching out the monomer, and the release rates could be enhanced by addition of L-Arg to the amyloids. F-actin depolymerization showed that addition of Ca2+ ions to released monomer initiated the depolymerization activity. Overall, we propose a way to compose a supramolecular assembly which releases functional protein in sustained manner which can be applied for varied potentially therapeutic interventions.

Abstract Efficient solar to hydrogen conversion using photoelectrochemical (PEC) process requires semiconducting photoelectrodes with advanced functionalities, while exhibiting high optical absorption and charge transport properties. Herein, we demonstrate magneto-tunable photocurrent in CoFe2O4 nanostructure film under low applied magnetic fields for efficient PEC properties. Photocurrent is enhanced from ~1.55 mA/cm2 to ~3.47 mA/cm2 upon the application of external magnetic field of 600 Oe leading to ~123% enhancement. This enhancement in the photocurrent is attributed to the reduction of optical bandgap and increase in the depletion width at CoFe2O4/electrolyte interface resulting in an enhanced generation and separation of the photoexcited charge carriers. The reduction of optical bandgap in the presence of magnetic field is correlated to the shifting of Co2+ ions from octahedral to tetrahedral sites which is supported by the Raman spectroscopy results. Electrochemical impedance spectroscopy results confirm a decrease in the charge transfer resistance at the CoFe2O4/electrolyte interface in the presence of magnetic field. This work evidences a coupling of photoexcitation properties with magnetic properties of a ferromagnetic-semiconductor and the effect can be termed as magnetophototronic effect.

Abstract We report the occurrence of an explosive death transition for the first time in an ensemble of identical limit cycle and chaotic oscillators coupled via mean–field diffusion. In both systems, the variation of the normalized amplitude with the coupling strength exhibits an abrupt and irreversible transition to death state from an oscillatory state and this first order phase transition to death state is independent of the size of the system. This transition is quite general and has been found in all the coupled systems where in–phase oscillations co–exist with a coupling dependent homogeneous steady state. The backward transition point for this phase transition has been calculated using linear stability analysis which is in complete agreement with the numerics.

Abstract Groundnut (Arachis hypogaea L.) is an important oil seed crop having major biotic constraint in production due to stem rot disease caused by fungus, Athelia rolfsii causing 25–80% loss in productivity. As chemical and biological combating strategies of this fungus are not very effective, thus genome sequencing can reveal virulence and pathogenicity related genes for better understanding of the host-parasite interaction. We report draft assembly of Athelia rolfsii genome of ~73 Mb having 8919 contigs. Annotation analysis revealed 16830 genes which are involved in fungicide resistance, virulence and pathogenicity along with putative effector and lethal genes. Secretome analysis revealed CAZY genes representing 1085 enzymatic genes, glycoside hydrolases, carbohydrate esterases, carbohydrate-binding modules, auxillary activities, glycosyl transferases and polysaccharide lyases. Repeat analysis revealed 11171 SSRs, LTR, GYPSY and COPIA elements. Comparative analysis with other existing ascomycotina genome predicted conserved domain family of WD40, CYP450, Pkinase and ABC transporter revealing insight of evolution of pathogenicity and virulence. This study would help in understanding pathogenicity and virulence at molecular level and development of new combating strategies. Such approach is imperative in endeavour of genome based solution in stem rot disease management leading to better productivity of groundnut crop in tropical region of world.