SARS-CoV-2-encoded ORF8 protein possesses complement inhibitory properties.

Hyperactivation of the complement system, a major component of innate immunity, has been recognized as one of the core clinical features in severe covid-19 patients. However, how the virus escapes the targeted elimination by the network of activated complement pathways still remains an enigma. Here, we identified SARS-CoV-2-encoded ORF8 protein as one of the major binding partners of human complement C3/C3b components and their metabolites. Our results demonstrated that preincubation of ORF8 with C3/C3b in the fluid phase has two immediate functional consequences in the alternative pathway; this preincubation inhibits factor I-mediated proteolysis and blocks factor B zymogen activation into active Bb. ORF8 binding results in the occlusion of both factor H and factor B from C3b, rendering the complexes resistant to factor I-mediated proteolysis and inhibition of pro-C3-convertase (C3bB) formation, respectively. We also confirmed the complement inhibitory activity of ORF8 in our hemolysis-based assay, where ORF8 prevented human serum-induced lysis of rabbit erythrocytes with an IC50 value of about 2.3 µM. This inhibitory characteristic of ORF8 was also supported by in-silico protein-protein docking analysis, as it appeared to establish primary interactions with the ß-chain of C3b, orienting itself near the C3b CUB (C1r/C1s, Uegf, Bmp1) domain like a peptidomimetic compound, sterically hindering the binding of essential cofactors required for complement amplification. Thus, ORF8 has characteristics to act as an inhibitor of critical regulatory steps in the alternative pathway, converging to hasten the decay of C3-convertase and thereby, attenuating the complement amplification loop.

Biofortification of Triticum species: a stepping stone to combat malnutrition.

BACKGROUND: Biofortification represents a promising and sustainable strategy for mitigating global nutrient deficiencies. However, its successful implementation poses significant challenges. Among staple crops, wheat emerges as a prime candidate to address these nutritional gaps. Wheat biofortification offers a robust approach to enhance wheat cultivars by elevating the micronutrient levels in grains, addressing one of the most crucial global concerns in the present era. MAIN TEXT: Biofortification is a promising, but complex avenue, with numerous limitations and challenges to face. Notably, micronutrients such as iron (Fe), zinc (Zn), selenium (Se), and copper (Cu) can significantly impact human health. Improving Fe, Zn, Se, and Cu contents in wheat could be therefore relevant to combat malnutrition. In this review, particular emphasis has been placed on understanding the extent of genetic variability of micronutrients in diverse Triticum species, along with their associated mechanisms of uptake, translocation, accumulation and different classical to advanced approaches for wheat biofortification. CONCLUSIONS: By delving into micronutrient variability in Triticum species and their associated mechanisms, this review underscores the potential for targeted wheat biofortification. By integrating various approaches, from conventional breeding to modern biotechnological interventions, the path is paved towards enhancing the nutritional value of this vital crop, promising a brighter and healthier future for global food security and human well-being.

Targeted HBx gene editing by CRISPR/Cas9 system effectively reduces epithelial to mesenchymal transition and HBV replication in hepatoma cells.

BACKGROUND AND AIMS: Hepatitis B virus X protein (HBx) play a key role in pathogenesis of HBV-induced hepatocellular carcinoma (HCC) by promoting epithelial to mesenchymal transition (EMT). In this study, we hypothesized that inhibition of HBx is an effective strategy to combat HCC. METHODOLOGY AND RESULTS: We designed and synthesized novel HBx gene specific single guide RNA (sgRNA) with CRISPR/Cas9 system and studied its in vitro effects on tumour properties of HepG2-2.15. Full length HBx gene was excised using HBx-CRISPR that resulted in significant knockdown of HBx expression in hepatoma cells. HBx-CRISPR also decreased levels of HBsAg and HBV cccDNA expression. A decreased expression of mesenchymal markers, proliferation and tumorigenic properties was observed in HBx-CRISPR treated cells as compared to controls in both two- and three- dimensional (2D and 3D) tumour models. Transcriptomics data showed that out of 1159 differentially expressed genes in HBx-CRISPR transfected cells as compared to controls, 70 genes were upregulated while 1089 genes associated with cell proliferation and EMT pathways were downregulated. CONCLUSION: Thus, targeting of HBx by CRISPR/Cas9 gene editing system reduces covalently closed circular DNA (cccDNA) levels, HBsAg production and mesenchymal characteristics of HBV-HCC cells. We envision inhibition of HBx by CRISPR as a novel therapeutic approach for HBV-induced HCC.

Exploring the Role of Non-synonymous and Deleterious Variants Identified in Colorectal Cancer: A Multi-dimensional Computational Scrutiny of Exomes.

Introduction: Colorectal cancers are the world's third most commonly diagnosed type of cancer. Currently, there are several diagnostic and treatment options to combat it. However, a delay in detection of the disease is life-threatening. Additionally, a thorough analysis of the exomes of cancers reveals potential variation data that can be used for early disease prognosis. Methods: By utilizing a comprehensive computational investigation, the present study aimed to reveal mutations that could potentially predispose to colorectal cancer. Ten colorectal cancer exomes were retrieved. Quality control assessments were performed using FastQC and MultiQC, gapped alignment to the human reference genome (hg19) using Bowtie2 and calling the germline variants using Haplotype caller in the GATK pipeline. The variants were filtered and annotated using SIFT and PolyPhen2 successfully categorized the mutations into synonymous, non-synonymous, start loss and stop gain mutations as well as marked them as possibly damaging, probably damaging and benign. This mutational profile helped in shortlisting frequently occurring mutations and associated genes, for which the downstream multi-dimensional expression analyses were carried out. Results: Our work involved prioritizing the non-synonymous, deleterious SNPs since these polymorphisms bring about a functional alteration to the phenotype. The top variations associated with their genes with the highest frequency of occurrence included LGALS8, CTSB, RAD17, CPNE1, OPRM1, SEMA4D, MUC4, PDE4DIP, ELN and ADRA1A. An in-depth multi-dimensional downstream analysis of all these genes in terms of gene expression profiling and analysis and differential gene expression with regard to various cancer types revealed CTSB and CPNE1 as highly expressed and overregulated genes in colorectal cancer. Conclusion: Our work provides insights into the various alterations that might possibly lead to colorectal cancer and suggests the possibility of utilizing the most important genes identified for wet-lab experimentation.

Multi-location evaluation of field pea in Indian climates: eco-phenological dynamics, crop-environment relationships, and identification of mega-environments.

Characterization of crop-growing environments in relation to crop's genotypic performance is crucial to harness positive genotype-by-environment interactions (GEI) in systematic breeding programs. Given that, the study aimed to delineate the impact of diverse environments on crop phenology and yield traits of dwarf-statured field pea, pinpointing location(s) favoring higher yield and distinctiveness within breeding lines. We tested twelve field pea breeding lines across twenty locations in India, covering Central Zone (CZ), North Western Plain Zone (NWPZ), North Eastern Plain Zone (NEPZ), and Northern Hill Zone (NHZ). Across these locations, maximum and minimum temperatures during flowering (TMAXF, TMINF) and reproductive period (TMAXRP, TMINRP) ranged 18.9-28.3, 3.3-18.0, 15.0-30.8, and 7.9-22.1oC, respectively. Meanwhile, notable variations in phenological and agronomic traits (coefficient of variation) were observed: flowering (31%), days to maturity (21%), reproductive period (18%), grain yield (48%), and 100-seed weight (18%). Combined ANOVA demonstrated an oversized impact of environment (81%) on yield, while genotype and GEI effects were 2% and 14%, respectively. The variables TMINF, TMINRP, and cumulative growing degree-day showed positive correlations with yield, while extended vegetative and maturity durations negatively influenced yield (p < 0.05). Additionally, linear mixed-models and PCA results explained that instability in crop phenology had significant influence on field pea yield. Seed weight was markedly varied within the locations (9.9-20.8 g) and both higher and lower seed weights were associated with lower yields (Optimal = 17.1 g). HA-GGE biplot-based on environment focus-scaling demonstrated three mega-environments and specific locations viz. Kota (CZ), SK Nagar (CZ), Raipur (CZ), Sehore (CZ), and Pantnagar (NWPZ) as the ideal testing-environments with high efficiency in selecting new genotypes with wider adaptability. The study findings highlight distinct impact of environments on crop phenology and agronomic traits of field pea (dwarf-type), hold substantial value in designing efficient field pea (dwarf-type) breeding program at mega-environment scale.

Time to implement tailored interventions in Chhattisgarh, east-central India to reach malaria elimination.

BACKGROUND OBJECTIVES: Despite significant progress in malaria control throughout India, Chhattisgarh state continues to be a significant contributor to both malaria morbidity and mortality. This study aims to identify key factors associated with malaria endemicity, with a goal of focusing on these factors for malaria elimination by 2030. METHODS: We employed an analysis and narrative review methodology to summarize the existing evidence on malaria epidemiology in Chhattisgarh. Data encompassing environmental conditions, dominant malaria vectors and their distribution, and the impact of previous interventions on malaria control, were extracted from published literature using PubMed and Google Scholar. This information was subsequently correlated with malaria incidence data using appropriate statistical and geographical methods. RESULTS: Much of the malaria burden in Chhattisgarh state is concentrated in a few specific districts. The primary malaria vectors in these regions are Anopheles culicifacies and An. fluviatilis. High transmission areas are found in tribal belts which are challenging to access and are characterized by densely forested areas that provide a conducive habitat for malaria vectors. INTERPRETATION CONCLUSION: Conducive environmental conditions characterized by high forest cover, community behavior, and insurgency, contribute to high malaria endemicity in the area. Challenges include insecticide resistance in malaria vectors and asymptomatic malaria. Allocating additional resources to high-endemic districts is crucial. Innovative and focused malaria control programs of the country, such as DAMAN and Malaria Mukt Abhiyan, hold immense importance.

Diurnal rail noise measurement, analysis, and evaluation of associated health impacts on residents living in the proximity of rail track area.

In India, railway is the major transportation mode for carrying goods and people. The tracks for the movement of the rail were initially constructed in the city for the pre-eminence and expediency of the vantage of the people. Rapid modernization and increasing population in the city crammed the area around the railway tracks. Moving rail on the tracks passing through the city is not compatible, which is creating problems for the nearby residents. In the urban and suburban regions, the railway noise has become a major problem. This study was conducted to examine the perception of the physiological and psychological effects of railway noise in the nearby areas of railway stations in Delhi, India. For this purpose, 10 sites near the railway station were selected for the study. To assess the impact of railway noise pollution on the health of humans, a questionnaire survey was conducted. The data of 344 individuals were collected through the questionnaire survey and analyzed to get the perception towards railway noise. Noise level was monitored by a Sound Level Meter (SLM) and the equivalent noise level (Leq) in dB(A) was used to compute the noise pollution in three shifts, i.e., morning, noon, and evening time. Results showed that 57.65% of female and 86.11% of male respondents in the survey reported the disturbance due to railway noise. The level of noise pollution was found higher in the evening time as compared to the noon and morning period, which exceeds the limit set by the Central Pollution Control Board (CPCB) at all the monitored locations. Findings of the study show that the primary cause of the health problems is railroad noise, which is negatively impacting the health of the residents, who are living in the proximity of the rail track region. The perception survey reported that headache, sleep disturbance, irritation, and stress are common health issues among the locals residing around the railway track proximity in Delhi.

De Novo Design of Anti-COVID Drugs Using Machine Learning-Based Equivariant Diffusion Model Targeting the Spike Protein.

The drug discovery and research for an anti-COVID-19 drug has been ongoing despite repurposed drugs in the market. Over time, these drugs were discontinued due to side effects. The search for effective drugs is still under process. The role of Machine Learning (ML) is critical in the search for novel drug compounds. In the current work, using the equivariant diffusion model, we built novel compounds targeting the spike protein of SARS-CoV-2. Using the ML models, 196 de novo compounds were generated which had no hits on any major chemical databases. These novel compounds fulfilled all the criteria of ADMET properties to be lead-like and drug-like compounds. Of the 196 compounds, 15 were docked with high confidence in the target. These compounds were further subjected to molecular docking, the best compound having an IUPAC name of (4aS,4bR,8aS,8bS)-4a,8a-dimethylbiphenylene-1,4,5,8(4aH,4bH,8aH,8bH)-tetraone and a binding score of -6.930 kcal/mol. The principal compound is labeled as CoECG-M1. Density Function Theory (DFT) and Quantum optimization was carried out along with the study of ADMET properties. This suggests that the compound has potential drug-like properties. The docked complex was further subjected to MD simulations, GBSA, and metadynamics simulations to gain insights into the stability of binding. The model can be in the future modified to improve the positive docking rate.

Hepatopulmonary syndrome is associated with low sphingosine-1-phosphate levels and can be ameliorated by the functional agonist fingolimod.

BACKGROUND & AIMS: Hepatopulmonary syndrome (HPS) is characterised by a defect in arterial oxygenation induced by pulmonary vascular dilatation in patients with liver disease. Fingolimod, a sphingosine-1-phosphate (S1P) receptor modulator, suppresses vasodilation by reducing nitric oxide (NO) production. We investigated the role of S1P in patients with HPS and the role of fingolimod as a therapeutic option in an experimental model of HPS. METHODS: Patients with cirrhosis with HPS (n = 44) and without HPS (n = 89) and 25 healthy controls were studied. Plasma levels of S1P, NO, and markers of systemic inflammation were studied. In a murine model of common bile duct ligation (CBDL), variations in pulmonary vasculature, arterial oxygenation, liver fibrosis, and inflammation were estimated before and after administration of S1P and fingolimod. RESULTS: Log of plasma S1P levels was significantly lower in patients with HPS than in those without HPS (3.1 ± 1.4 vs. 4.6 ± 0.2; p <0.001) and more so in severe intrapulmonary shunting than in mild and moderate intrapulmonary shunting (p <0.001). Plasma tumour necrosis factor-α (76.5 [30.3-91.6] vs. 52.9 [25.2-82.8]; p = 0.02) and NO (152.9 ± 41.2 vs. 79.2 ± 29.2; p = 0.001) levels were higher in patients with HPS than in those without HPS. An increase in Th17 (p <0.001) and T regulatory cells (p <0.001) was observed; the latter inversely correlated with plasma S1P levels. In the CBDL HPS model, fingolimod restored pulmonary vascular injury by increasing the arterial blood gas exchange and reducing systemic and pulmonary inflammation, resulting in improved survival (p = 0.02). Compared with vehicle treatment, fingolimod reduced portal pressure (p <0.05) and hepatic fibrosis and improved hepatocyte proliferation. It also induced apoptotic death in hepatic stellate cells and reduced collagen formation. CONCLUSIONS: Plasma S1P levels are low in patients with HPS and even more so in severe cases. Fingolimod, by improving pulmonary vascular tone and oxygenation, improves survival in a murine CBDL HPS model. IMPACT AND IMPLICATIONS: A low level of plasma sphingosine-1-phosphate (S1P) is associated with severe pulmonary vascular shunting, and hence, it can serve as a marker of disease severity in patients with hepatopulmonary syndrome (HPS). Fingolimod, a functional agonist of S1P, reduces hepatic inflammation, improves vascular tone, and thus retards the progression of fibrosis in a preclinical animal model of HPS. Fingolimod is being proposed as a potential novel therapy for management of patients with HPS.

Lower-Dose Zinc for Childhood Diarrhea - A Randomized, Multicenter Trial.

BACKGROUND: The World Health Organization recommends 20 mg of zinc per day for 10 to 14 days for children with acute diarrhea; in previous trials, this dosage decreased diarrhea but increased vomiting. METHODS: We randomly assigned 4500 children in India and Tanzania who were 6 to 59 months of age and had acute diarrhea to receive 5 mg, 10 mg, or 20 mg of zinc sulfate for 14 days. The three primary outcomes were a diarrhea duration of more than 5 days and the number of stools (assessed in a noninferiority analysis) and the occurrence of vomiting (assessed in a superiority analysis) within 30 minutes after zinc administration. RESULTS: The percentage of children with diarrhea for more than 5 days was 6.5% in the 20-mg group, 7.7% in the 10-mg group, and 7.2% in the 5-mg group. The difference between the 20-mg and 10-mg groups was 1.2 percentage points (upper boundary of the 98.75% confidence interval [CI], 3.3), and that between the 20-mg and 5-mg groups was 0.7 percentage points (upper boundary of the 98.75% CI, 2.8), both of which were below the noninferiority margin of 4 percentage points. The mean number of diarrheal stools was 10.7 in the 20-mg group, 10.9 in the 10-mg group, and 10.8 in 5-mg group. The difference between the 20-mg and 10-mg groups was 0.3 stools (upper boundary of the 98.75% CI, 1.0), and that between the 20-mg and 5-mg groups was 0.1 stools (upper boundary of the 98.75% CI, 0.8), both of which were below the noninferiority margin (2 stools). Vomiting within 30 minutes after administration occurred in 19.3%, 15.6%, and 13.7% of the patients in the 20-mg, 10-mg, and 5-mg groups, respectively; the risk was significantly lower in the 10-mg group than in the 20-mg group (relative risk, 0.81; 97.5% CI, 0.67 to 0.96) and in the 5-mg group than in the 20-mg group (relative risk, 0.71; 97.5% CI, 0.59 to 0.86). Lower doses were also associated with less vomiting beyond 30 minutes after administration. CONCLUSIONS: Lower doses of zinc had noninferior efficacy for the treatment of diarrhea in children and were associated with less vomiting than the standard 20-mg dose. (Funded by the Bill and Melinda Gates Foundation; ZTDT ClinicalTrials.gov number, NCT03078842.).

Abiotic and biotic stress alleviating effects of the medicinal and aromatic plant-derived product on striped catfish Pangasianodonhypophthalmus.

Intensification of aquaculture production leads to abiotic and biotic stresses, which are further induced by the impact of climate change. Thus, it is important to explore a combined strategy to alleviate multiple stresses in fish. In the present investigation, the removal of nitrogenous metabolites from aquaponics water was studied using products derived from five different locally available medicinal and aromatic plants (MAPs) namely banana stem (Musa Accuminata), Aloe vera, Mint (Minata sepicata), Indian beech/Pongameoil-tree/Karanj (Pongamia pinnatum), and Coat Button/Mexican daisy/Dagadipala (Tridax procrumbens) in the batch experiment for 24 h. A reduction of 91-94% in the ammonia level and 75-80% removal of nitrite-N in the treatments with products derived from mint, banana stem, and aloe vera has been observed. Mint product was also found to be bactericidal against fish pathogenic bacteria. Based on this dual function of mint, further study was conducted under wet-lab conditions to evaluate the possible protective role of the mint-based product in dry powder form against abiotic stresses caused by nitrogenous toxicants for 24 h and 45 days multiple stresses caused by nitrogenous toxicants in freshwater stocked with eight fingerlings of Pangasianodon hypophthalmus of the initial weight of 8 ± 0.5g for 24 h and 8.82 ± 0.75g for 45 days. The results revealed that mint-derived plant product has better anti-stress properties in terms of their bioremediation effectiveness in lowering ammonia and nitrite. Mint also improved the fish growth performance with better physiological responses and anti-oxidative status and reduced the cellular metabolic stress in fish reared under ammonia, as further indicated by reduced oxidative stress parameters, and tissue biochemical indices. Overall, mint showed its main properties as a growth promoter, and immune enhancer, where this medicinal plant product acts as a bioremediation and antibacterial agent to the host immune system. This has potential applications in the environmental and health management of aquaculture.

Genetic analysis of iron, zinc and grain yield in wheat-Aegilops derivatives using multi-locus GWAS.

BACKGROUND: Wheat is a major staple crop and helps to reduce worldwide micronutrient deficiency. Investigating the genetics that control the concentrations of iron (Fe) and zinc (Zn) in wheat is crucial. Hence, we undertook a comprehensive study aimed at elucidating the genomic regions linked to the contents of Fe and Zn in the grain. METHODS AND RESULTS: We performed the multi-locus genome-wide association (ML-GWAS) using a panel of 161 wheat-Aegilops substitution and addition lines to dissect the genomic regions controlling grain iron (GFeC), and grain zinc (GZnC) contents. The wheat panel was genotyped using 10,825 high-quality SNPs and phenotyped in three different environments (E1-E3) during 2017-2019. A total of 111 marker-trait associations (MTAs) (at p-value < 0.001) were detected that belong to all three sub-genomes of wheat. The highest number of MTAs were identified for GFeC (58), followed by GZnC (44) and yield (9). Further, six stable MTAs were identified for these three traits and also two pleiotropic MTAs were identified for GFeC and GZnC. A total of 1291 putative candidate genes (CGs) were also identified for all three traits. These CGs encode a diverse set of proteins, including heavy metal-associated (HMA), bZIP family protein, AP2/ERF, and protein previously associated with GFeC, GZnC, and grain yield. CONCLUSIONS: The significant MTAs and CGs pinpointed in this current study are poised to play a pivotal role in enhancing both the nutritional quality and yield of wheat, utilizing marker-assisted selection (MAS) techniques.

Effective utilization of discarded reverse osmosis post-carbon for adsorption of dyes from wastewater.

In this study, the deployment of post Reverse Osmosis (RO)-carbon as a adsorbent for dye removal from water has been investigated. The post RO-carbon was thermally activated (RO900), and the material thus obtained exhibited high surface area viz. 753 m2/g. In the batch system, the efficient Methylene Blue (MB) and Methyl Orange (MO) removal was obtained by using 0.08 g and 0.13 g/50 mL adsorbent dosage respectively. Moreover, 420 min was the optimized equilibration time for both the dyes. The maximum adsorption capacities of RO900 for MB and MO dyes were 223.29 and 158.14 mg/g, respectively. The comparatively higher MB adsorption was attributed to the electrostatic attraction between adsorbent and MB. The thermodynamic findings revealed the process as spontaneous, endothermic, and accompanied by entropy increment. Additionally, simulated effluent was treated, and >99% dye removal efficiency was achieved. To mimic an industrial perspective, MB adsorption onto RO900 was also carried out in continuous mode. The initial dye concentration and effluent flow rate were among the process parameters that were optimized using the continuous mode of operation. Further, the experimental data of continuous mode was fitted with Clark, Yan, and Yoon-Nelson models. Py-GC/MS investigation revealed that dye-loaded adsorbents could be pyrolyzed to produce valuable chemicals. The cost and low toxicity associated benefits of discarded RO-carbon over other adsorbents reveal the significance of the present study.

Extraction, isolation, synthesis, and biological evaluation of novel piperic acid derivatives for the treatment of Alzheimer's disease.

In this paper, we developed a series of piperic acid (PA) analogs with the aim of overcoming the limitations associated with the natural products for the management of Alzheimer's disease (AD). A comprehensive SAR study was performed to enhance cholinesterase inhibition of PA. The acetylcholinesterase inhibition and its kinetic data suggested 6j as the lead molecule (AChE IC50 = 2.13 ± 0.015 µM, BChE = 28.19 ± 0.20%), in comparison to PA (AChE = 7.14 ± 0.98%) which was further selected for various biological studies in AD models. 6j, exhibited interaction with the peripheral anionic site of AChE, BBB permeability (Pe = 7.98), and antioxidant property (% radical scavenging activity = 35.41 ± 1.09, 2.43 ± 1.65, for 6j and PA at 20 M[Formula: see text], respectively). The result from the metal chelation study suggests that 6j did not effectively chelate iron. The molecular modeling studies suggested that 6j could effectively interact with Ser293, Phe295, Arg296, and Tyr34 of AChE. In the cell-based cytotoxicity studies, 6j exhibited cytocompatibility at the different tested concentrations. The acute toxicity data on mice suggested that compound 6j had no renal and hepatotoxicity at 500 mg/kg. Moreover, 6j could effectively reverse scopolamine-induced amnesia by improving spatial and cognitive memory in mice. The above results strongly suggest that compound 6j may act as a novel multi-targeted lead for AD therapy.

Delineating Marker-Trait Associations for Fusarium Wilt in Chickpea Using the Axiom® CicerSNP Array.

Fusarium wilt (FW) caused by Fusarium oxysporum f. sp. ciceri is a devastating disease of chickpea (Cicer arietinum). To identify promising resistant genotypes and genomic loci for FW resistance, a core set of 179 genotypes of chickpea was tested for FW reactions at the seedling and reproductive stages under field conditions and controlled conditions in the greenhouse. Our results revealed that at the seedling stage, most of the genotypes were resistant, whereas at the reproductive stage, most of the genotypes were susceptible. Genotyping using a 50K Axiom® CicerSNP Array and trait data of FW together led to the identification of 26 significant (P ≤ E-05) marker-trait associations (MTAs) for FW resistance. Among the 26 MTAs, 12 were identified using trait data recorded in the field (three at the seedling and nine at the reproductive stage), and 14 were identified using trait data recorded under controlled conditions in the greenhouse (six at the seedling and eight at the reproductive stage). The phenotypic variation explained by these MTAs varied from 11.75 to 15.86%, with an average of 13.77%. Five MTAs were classified as major, explaining more than 15% of the phenotypic variation for FW, and two were declared stable, being identified in two environments. One of the promising stable and major MTAs (Affx_123280060) detected in field conditions at the reproductive stage was also detected in greenhouse conditions at the seedling and reproductive stages. The stable and major (>15% PVE) MTAs can be used in chickpea breeding programs.

Quantitative Representativeness and Constituency of the Long-Term Agroecosystem Research Network and Analysis of Complementarity with Existing Ecological Networks.

Studies conducted at sites across ecological research networks usually strive to scale their results to larger areas, trying to reach conclusions that are valid throughout larger enclosing regions. Network representativeness and constituency can show how well conditions at sampling locations represent conditions also found elsewhere and can be used to help scale-up results over larger regions. Multivariate statistical methods have been used to design networks and select sites that optimize regional representation, thereby maximizing the value of datasets and research. However, in networks created from already established sites, an immediate challenge is to understand how well existing sites represent the range of environments in the whole area of interest. We performed an analysis to show how well sites in the USDA Long-Term Agroecosystem Research (LTAR) Network represent all agricultural working lands within the conterminous United States (CONUS). Our analysis of 18 LTAR sites, based on 15 climatic and edaphic characteristics, produced maps of representativeness and constituency. Representativeness of the LTAR sites was quantified through an exhaustive pairwise Euclidean distance calculation in multivariate space, between the locations of experiments within each LTAR site and every 1 km cell across the CONUS. Network representativeness is from the perspective of all CONUS locations, but we also considered the perspective from each LTAR site. For every LTAR site, we identified the region that is best represented by that particular site-its constituency-as the set of 1 km grid locations best represented by the environmental drivers at that particular LTAR site. Representativeness shows how well the combination of characteristics at each CONUS location was represented by the LTAR sites' environments, while constituency shows which LTAR site was the closest match for each location. LTAR representativeness was good across most of the CONUS. Representativeness for croplands was higher than for grazinglands, probably because croplands have more specific environmental criteria. Constituencies resemble ecoregions but have their environmental conditions "centered" on those at particular existing LTAR sites. Constituency of LTAR sites can be used to prioritize the locations of experimental research at or even within particular sites, or to identify the extents that can likely be included when generalizing knowledge across larger regions of the CONUS. Sites with a large constituency have generalist environments, while those with smaller constituency areas have more specialized environmental combinations. These "specialist" sites are the best representatives for smaller, more unusual areas. The potential of sharing complementary sites from the Long-Term Ecological Research (LTER) Network and the National Ecological Observatory Network (NEON) to boost representativeness was also explored. LTAR network representativeness would benefit from borrowing several NEON sites and the Sevilleta LTER site. Later network additions must include such specialist sites that are targeted to represent unique missing environments. While this analysis exhaustively considered principal environmental characteristics related to production on working lands, we did not consider the focal agronomic systems under study, or their socio-economic context.

Implementation of ensemble machine learning algorithms on exome datasets for predicting early diagnosis of cancers.

Classification of different cancer types is an essential step in designing a decision support model for early cancer predictions. Using various machine learning (ML) techniques with ensemble learning is one such method used for classifications. In the present study, various ML algorithms were explored on twenty exome datasets, belonging to 5 cancer types. Initially, a data clean-up was carried out on 4181 variants of cancer with 88 features, and a derivative dataset was obtained using natural language processing and probabilistic distribution. An exploratory dataset analysis using principal component analysis was then performed in 1 and 2D axes to reduce the high-dimensionality of the data. To significantly reduce the imbalance in the derivative dataset, oversampling was carried out using SMOTE. Further, classification algorithms such as K-nearest neighbour and support vector machine were used initially on the oversampled dataset. A 4-layer artificial neural network model with 1D batch normalization was also designed to improve the model accuracy. Ensemble ML techniques such as bagging along with using KNN, SVM and MLPs as base classifiers to improve the weighted average performance metrics of the model. However, due to small sample size, model improvement was challenging. Therefore, a novel method to augment the sample size using generative adversarial network (GAN) and triplet based variational auto encoder (TVAE) was employed that reconstructed the features and labels generating the data. The results showed that from initial scrutiny, KNN showed a weighted average of 0.74 and SVM 0.76. Oversampling ensured that the accuracy of the derivative dataset improved significantly and the ensemble classifier augmented the accuracy to 82.91%, when the data was divided into 70:15:15 ratio (training, test and holdout datasets). The overall evaluation metric value when GAN and TVAE increased the sample size was found to be 0.92 with an overall comparison model of 0.66. Therefore, the present study designed an effective model for classifying cancers which when implemented to real world samples, will play a major role in early cancer diagnosis.

Informing Nature-based Climate Solutions for the United States with the best-available science.

Nature-based Climate Solutions (NbCS) are managed alterations to ecosystems designed to increase carbon sequestration or reduce greenhouse gas emissions. While they have growing public and private support, the realizable benefits and unintended consequences of NbCS are not well understood. At regional scales where policy decisions are often made, NbCS benefits are estimated from soil and tree survey data that can miss important carbon sources and sinks within an ecosystem, and do not reveal the biophysical impacts of NbCS for local water and energy cycles. The only direct observations of ecosystem-scale carbon fluxes, for example, by eddy covariance flux towers, have not yet been systematically assessed for what they can tell us about NbCS potentials, and state-of-the-art remote sensing products and land-surface models are not yet being widely used to inform NbCS policymaking or implementation. As a result, there is a critical mismatch between the point- and tree-scale data most often used to assess NbCS benefits and impacts, the ecosystem and landscape scales where NbCS projects are implemented, and the regional to continental scales most relevant to policymaking. Here, we propose a research agenda to confront these gaps using data and tools that have long been used to understand the mechanisms driving ecosystem carbon and energy cycling, but have not yet been widely applied to NbCS. We outline steps for creating robust NbCS assessments at both local to regional scales that are informed by ecosystem-scale observations, and which consider concurrent biophysical impacts, future climate feedbacks, and the need for equitable and inclusive NbCS implementation strategies. We contend that these research goals can largely be accomplished by shifting the scales at which pre-existing tools are applied and blended together, although we also highlight some opportunities for more radical shifts in approach.

Phenolic and flavonoid contents and antioxidant activity of an endophytic fungus Nigrospora sphaerica (EHL2), inhabiting the medicinal plant Euphorbia hirta (dudhi) L.

Since endophytic fungi are pivotal sources of various bioactive natural compounds, the present study is aimed to investigate the antioxidant compounds of the endophytic fungus Nigrospora sphaerica isolated from a pantropical weed, Euphorbia hirta L. The fungus was fermented in four different media and each filtered broth was sequentially extracted in various solvents. Crude extracts collected from different solvents were subjected to phytochemical analysis and antioxidant activity. The total phenolic content (TPC) and total flavonoid content (TFC) were maximal in ethyl acetate crude extract (EtOAcE) of endophyte fermented in potato dextrose broth (PDB) medium (77.74 ± 0.046mgGAE/g and 230.59 ± 2.0 mgRE/g) with the highest 96.80% antioxidant activity. However, TPC and TFC were absent in hexane extract of Czapek Dox broth (CDB) medium exhibiting the lowest 4.63 ± 2.75% activity. The EtOAcE (PDB) showed a positive correlation between TFC and antiradical activity (R2 = 0.762; P < 0.05), whereas a high positive correlation was noticed between TPC and antioxidant activity (R2 = 0.989; P < 0.05). Furthermore, to determine the antioxidant activity, EtOAcE (PDB) was subjected to TLC bioautography-based partial purification, while GC/MS analysis of the partial purified extract was done to confirm the presence of phenolics along with antioxidant compounds that resulted in the detection of 2,4-Di-tert-butylphenol (13.83%), a phenolic compound accountable for the antioxidant potential. Conclusively, N. sphaerica is a potential candidate for natural antioxidant.

Reverse genetic approaches for breeding nutrient-rich and climate-resilient cereal and food legume crops.

In the last decade, advancements in genomics tools and techniques have led to the discovery of many genes. Most of these genes still need to be characterized for their associated function and therefore, such genes remain underutilized for breeding the next generation of improved crop varieties. The recent developments in different reverse genetic approaches have made it possible to identify the function of genes controlling nutritional, biochemical, and metabolic traits imparting drought, heat, cold, salinity tolerance as well as diseases and insect-pests. This article focuses on reviewing the current status and prospects of using reverse genetic approaches to breed nutrient-rich and climate resilient cereal and food legume crops.