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Abstract With the increasing demand for antimicrobial agents and the spread of antibiotic resistance in pathogens, the exploitation of plant oils to partly replace antibiotic emerges as an important source of fine chemicals, functional food utility and pharmaceutical industries. This work introduces a novel catalytic method of plant oils hydroxylation by Fe(III) citrate monohydrate (Fe3+-cit.)/Na2S2O8 catalyst. Methyl (9Z,12Z)-octadecadienoate (ML) was selected as an example of vegetable oils hydroxylation to its hydroxy-conjugated derivatives (CHML) in the presence of a new complex of Fe(II)-species. Methyl 9,12-di-hydroxyoctadecanoate 1, methyl-9-hydroxyoctadecanoate 2 and methyl (10E,12E)-octadecanoate 3 mixtures is produced under optimized condition with oxygen balloon. The specific hydroxylation activity was lower in the case of using Na2S2O8 alone as a catalyst. A chemical reaction has shown the main process converted of plantoils hydroxylation and (+ 16 Da) of OH- attached at the methyl linoleate (ML-OH). HPLC and MALDI-ToF-mass spectrometry were employed for determining the obtained products. It was found that adding oxidizing agents (Na2S2O8) to Fe3+ in the MeCN mixture with H2O would generate the new complex of Fe(II)-species, which improves the C-H activation. Hence, the present study demonstrated a new functional method for better usage of vegetable oils.Producing conjugated hydroxy-fatty acids/esters with better antipathogenic properties. CHML used in food industry, It has a potential pathway to food safety and packaging process with good advantages, fundamental to microbial resistance. Lastly, our findings showed that biological monitoring of CHML-minimum inhibitory concentration (MIC) inhibited growth of various gram-positive and gram-negative bacteria in vitro study. The produced CHML profiles were comparable to the corresponding to previousstudies and showed improved the inhibition efficiency over the respective kanamycin derivatives.

Whether or not hydrogen gas (H2) can reduce cadmium (Cd) toxicity in Ganoderma lucidum has remained largely unknown. Here, we report that Cd-induced growth inhibition in G. lucidum was significantly alleviated by H2 fumigation or hydrogen-rich water (HRW), evaluated by lower oxidative damage and Cd accumulation. Moreover, the amelioration effects of H2 fumigation were better than of HRW in an optimum concentration of H2 under our experimental conditions. Further results showed that H2-alleviated growth inhibition in G. lucidum was accompanied by increased nitric oxide (NO) level and nitrate reductase (NR) activity under Cd stress. On the other hand, the mitigation effects were reversed after removing endogenous NO with its scavenger cPTIO or inhibiting H2-induced NR activity with sodium tungstate. The role of NO in H2-alleviated growth inhibition under Cd stress was proved to be achieved through a restoration of redox balance, an increase in cysteine and proline contents, and a reduction in Cd accumulation. In summary, these results clearly revealed that NR-dependent NO might be involved in the H2-alleviated Cd toxicity in G. lucidum through rebuilding redox homeostasis, increasing cysteine and proline levels, and reducing Cd accumulation. These findings may open a new window for H2 application in Cd-stressed economically important fungi.

Brassica juncea (Indian mustard) is a commercially important oil seed crop, which is highly affected by many biotic stresses. Among them, Alternaria leaf blight and powdery mildew are the most devastating diseases leading to huge yield losses in B. juncea around the world. In this regard, genetic engineering is a promising tool that may possibly allow us to enhance the B. juncea disease resistance against these pathogens. NPR1 (non-expressor of pathogen-related gene 1) is a bonafide receptor of salicylic acid (SA) which modulates multiple immune responses in plants especially activation of induced and systemic acquired resistance (SAR). Here, we report the isolation and characterization of new NPR1 homolog (BjNPR1) from B. juncea. The phylogenetic tree constructed based on the deduced sequence of BjNPR1 with homologs from other species revealed that BjNPR1 grouped together with other known NPR1 proteins of Cruciferae family, and was nearest to B. napus. Furthermore, expression analysis showed that BjNPR1 was upregulated after SA treatment and fungal infection but not by jasmonic acid or abscisic acid. To understand the defensive role of this gene, we generated B. juncea transgenic lines overexpressing BjNPR1, and further confirmed by PCR and Southern blotting. The transgenic lines showed no phenotypic abnormalities, and constitutive expression of BjNPR1 activates defense signaling pathways by priming the expression of antifungal PR genes. Moreover, BjNPR1 transgenic lines showed enhanced resistance to Alternaria brassicae and Erysiphe cruciferarum as there was delay in symptoms and reduced disease severity than non-transgenic plants. In addition, the rate of disease spreading to uninfected or distal parts was also delayed in transgenic plants thus suggesting the activation of SAR. Altogether, the present study suggests that BjNPR1 is involved in broad spectrum of disease resistance against fungal pathogens.

Aquaporins (AQPs) are a class of integral membrane proteins involved in the transport of water and many other small solutes. The AQPs have been extensively studied in many land species obtaining water and nutrients from the soil, but their distribution and evolution have never been investigated in aquatic plant species, where solute assimilation is mostly through the leaves. In this regard, identification of AQPs in the genome of Zostera marina L. (eelgrass), an aquatic ecological model species could reveal important differences underlying solute uptake between land and aquatic species. In the present study, genome-wide analysis led to the identification of 25 AQPs belonging to four subfamilies, plasma membrane intrinsic proteins (PIPs), tonoplast intrinsic proteins (TIPs), nodulin 26-like intrinsic proteins (NIPs), small basic intrinsic proteins (SIPs) in eelgrass. As in other monocots, the XIP subfamily was found to be absent from the eelgrass genome. Further classification of subfamilies revealed a unique distribution pattern, namely the loss of the NIP2 (NIP-III) subgroup, which is known for silicon (Si) transport activity and ubiquitously present in monocot species. This finding has great importance, since the eelgrass population stability in natural niche is reported to be associated with Si concentrations in water. In addition, analysis of available RNA-seq data showed evidence of expression in 24 out of the 25 AQPs across four different tissues such as root, vegetative tissue, male flower and female flower. In contrast to land plants, higher expression of PIPs was observed in shoot compared to root tissues. This is likely explained by the unique plant architecture of eelgrass where most of the nutrients and water are absorbed by shoot rather than root tissues. Similarly, higher expression of the TIP1 and TIP5 families was observed specifically in male flowers suggesting a role in pollen maturation. This genome-wide analysis of AQP distribution, evolution and expression dynamics can find relevance in understanding the adaptation of aquatic and land species to their respective environments.

Plasmodium falciparum, the causative agent of the fatal form of malaria, synthesizes GMP primarily from IMP and, hence, needs active GMPS (GMP synthetase) for its survival. GMPS, a G-type amidotransferase, catalyses the amination of XMP to GMP with the reaction occurring in two domains, the GAT (glutamine amidotransferase) and ATPPase (ATP pyrophosphatase). The GAT domain hydrolyses glutamine to glutamate and ammonia, while the ATPPase domain catalyses the formation of the intermediate AMP-XMP from ATP and XMP. Co-ordination of activity across the two domains, achieved through channelling of ammonia from GAT to the effector domain, is the hallmark of amidotransferases. Our studies aimed at understanding the kinetic mechanism of PfGMPS (Plasmodium falciparum GMPS) indicated steady-state ordered binding of ATP followed by XMP to the ATPPase domain with glutamine binding in a random manner to the GAT domain. We attribute the irreversible, Ping Pong step seen in initial velocity kinetics to the release of glutamate before the attack of the adenyl-XMP intermediate by ammonia. Specific aspects of the overall kinetic mechanism of PfGMPS are different from that reported for the human and Escherichia coli enzymes. Unlike human GMPS, absence of tight co-ordination of activity across the two domains was evident in the parasite enzyme. Variations seen in the inhibition by nucleosides and nucleotide analogues between human GMPS and PfGMPS highlighted differences in ligand specificity that could serve as a basis for the design of specific inhibitors. The present study represents the first report on recombinant His-tagged GMPS from parasitic protozoa. [ABSTRACT FROM AUTHOR]

Abstract Background Magnesium (Mg) is essential for plant growth and development and plays critical roles in physiological and biochemical processes. Mg deficiency adversely affects growth of plants by limiting shoot and root development, disturbing the structure and membranes of the grana, reducing photosynthesis efficiency, and lowering net CO2 assimilation. The MGT (Magnesium transporter) family is responsible for the absorption and transportation of magnesium in plants. Although the MGT family has been identified in different plant species, research regarding the soybean MGT genes is limited. Results In the current study, a total of 39 MGT genes distributed on 17 different chromosomes were identified in soybean. Phylogenetic analysis classified GmMGTs into three subgroups, NIPA, MRS2/MGT, and CorA, which showed little homology with MGTs of Arabidopsis thaliana and Oryza sativa members and clustered tightly with GmMGTs. Gene structure and conserved motif analysis also confirmed similar grouping in GmMGTs. The expansion of the GmMGT members in NIPA and MRS2/MGT was predicted, while CorA was identified as the most conserved group in G. max. Segmental duplication under purifying selection pressure was identified as the major driving force in the expansion of MGTs in soybean. GmMGTs showed diverse tissue-specific and stress-response expression patterns due to the presence of stress-related cis-regulatory elements in their promoter regions. Under Mg-deficiency and surplus stress conditions, a decrease in root length, shoot length, and root and shoot fresh as well dry weight in susceptible genotypes showed the variegated expression of MGTs in soybean genotypes. Furthermore, the upregulation of GmMGT2 and GmMGT29 in tolerant genotypes in response to Mg-deficiency as well as surplus stress conditions in leaves suggested the essential role of GmMGT genes in the absorption and transportation of Mg in soybean leaves. Conclusion This study presents a comprehensive analysis of the MGT gene family in soybean, providing insights into their evolutionary relationships, gene classification, protein structures, and expression patterns under both Mg deficiency and Mg surplus conditions.

The application of advanced omics technologies in plant science has generated an enormous dataset of sequences, expression profiles, and phenotypic traits, collectively termed “big data” for their significant volume, diversity, and rapid pace of accumulation. Despite extensive data generation, the process of analyzing and interpreting big data remains complex and challenging. Big data analyses will help identify genes and uncover different mechanisms controlling various agronomic traits in crop plants. The insights gained from big data will assist scientists in developing strategies for crop improvement. Although the big data generated from crop plants opens a world of possibilities, realizing its full potential requires enhancement in computational capacity and advances in machine learning (ML) or deep learning (DL) approaches. The present review discuss the applications of genomics, transcriptomics, proteomics, metabolomics, epigenetics, and phenomics “big data” in crop improvement. Furthermore, we discuss the potential application of artificial intelligence to genomic selection. Additionally, the article outlines the crucial role of big data in precise genetic engineering and understanding plant stress tolerance. Also we highlight the challenges associated with big data storage, analyses, visualization and sharing, and emphasize the need for robust solutions to harness these invaluable resources for crop improvement.

Alkaline stress is one of the major abiotic constraints that limits plant growth and development. However, the genetic basis underlying alkaline tolerance in soybean [Glycine max (L.) Merr.] remains largely unexplored. In this study, an integrated genomic analysis approach was employed to elucidate the genetic architecture of alkaline tolerance in a diverse panel of 326 soybean cultivars. Through association mapping, we detected 28 single nucleotide polymorphisms (SNPs) significantly associated with alkaline tolerance. By examining the genomic distances around these significant SNPs, five genomic regions were characterized as stable quantitative trait loci (QTLs), which were designated as qAT1, qAT4, qAT14, qAT18, and qAT20. These QTLs are reported here for the first time in soybean. Seventeen putative candidate genes were identified within the physical intervals of these QTLs. Haplotype analysis indicated that four of these candidate genes exhibited significant allele variation associated with alkaline tolerance-related traits, and the haplotype alleles for these four genes varied in number from two to four. The findings of this study may have important implications for soybean breeding programs aimed at enhancing alkaline tolerance.

In the original publication [...]

Accurate segmentation of brain tumors from MRI (Magnetic Resonance Imaging) sequences is essential across diverse clinical scenarios, facilitating precise delineation of anatomical structures and disease-affected areas. This study presents an innovative deep-learning method for segmenting glioma brain tumors, utilizing a hybrid architecture that combines ResNet U-Net with Transformer blocks. The proposed model adeptly encompasses both the local and global contextual details present in MRI scans. The architecture includes an encoder based on ResNet for extracting hierarchical features, followed by residual blocks to enhance feature representation while maintaining spatial information. Additionally, a central transformer block, incorporating multi-head attention mechanisms, enables the modeling of long-range dependencies and contextual comprehension, progressively refining feature interactions. To handle structural scale variations within MRI images, skip connections are utilized during the decoding phase. Transposed convolutional layers in the decoder upsample feature maps, retaining details and incorporating contextual information from earlier layers. A rigorous assessment of the model’s functionality was carried out with the BraTS2019 dataset, employing a comprehensive set of evaluation metrics including accuracy, IOU score, specificity, sensitivity, dice score, and precision. The evaluation focused on individual tumor classes, namely the whole, core, and enhancing tumor regions. During validation, the suggested model demonstrated remarkable dice scores of 0.91, 0.89, and 0.84 for the whole tumor, core tumor, and enhancing tumor, respectively, yielding an impressive overall accuracy rate of 98%.

Recent advancements in deep learning, particularly convolutional networks, have rapidly become the preferred methodology for analyzing medical images, facilitating tasks like disease segmentation, classification, and pattern quantification. Central to these advancements is the capacity to leverage hierarchical feature representations acquired solely from data. This comprehensive review meticulously examines a variety of deep learning techniques applied across diverse healthcare domains, delving into the intricate realm of medical imaging to unveil concealed patterns through strategic deep learning methodologies. Encompassing a range of diseases, including Alzheimer’s, breast cancer, brain tumors, glaucoma, heart murmurs, retinal microaneurysms, colorectal liver metastases, and more, the analysis emphasizes contributions succinctly summarized in a tabular form.The table provides an overview of various deep learning approaches applied to different diseases, incorporating methodologies, datasets, and outcomes for each condition.Notably, performance metrics such as accuracy, specificity, sensitivity, and other crucial measures underscore the achieved results. Specifically, an in-depth discussion is conducted on the Convolutional Neural Network (CNN) owing to its widespread adoption as a paramount tool in computer vision tasks. Moreover, an exhaustive exploration encompasses deep learning classification approaches, procedural aspects of medical image processing, as well as a thorough examination of key features and characteristics. At the end, we delve into a range of research challenges and put forth potential avenues for future improvements in the field.

The pod and seed counts are important yield-related traits in soybean. High-precision soybean breeders face the major challenge of accurately phenotyping the number of pods and seeds in a high-throughput manner. Recent advances in artificial intelligence, especially deep learning (DL) models, have provided new avenues for high-throughput phenotyping of crop traits with increased precision. However, the available DL models are less effective for phenotyping pods that are densely packed and overlap in in situ soybean plants; thus, accurate phenotyping of the number of pods and seeds in soybean plant is an important challenge. To address this challenge, the present study proposed a bottom-up model, DEKR-SPrior (disentangled keypoint regression with structural prior), for in situ soybean pod phenotyping, which considers soybean pods and seeds analogous to human people and joints, respectively. In particular, we designed a novel structural prior (SPrior) module that utilizes cosine similarity to improve feature discrimination, which is important for differentiating closely located seeds from highly similar seeds. To further enhance the accuracy of pod location, we cropped full-sized images into smaller and high-resolution subimages for analysis. The results on our image datasets revealed that DEKR-SPrior outperformed multiple bottom-up models, viz., Lightweight-OpenPose, OpenPose, HigherHRNet, and DEKR, reducing the mean absolute error from 25.81 (in the original DEKR) to 21.11 (in the DEKR-SPrior) in pod phenotyping. This paper demonstrated the great potential of DEKR-SPrior for plant phenotyping, and we hope that DEKR-SPrior will help future plant phenotyping.

Abstract Global climate change has threatened world crop production and food security. Decoding the adaptive genetic basis of wild relatives provides an invaluable genomic resource for climate‐smart crop breedinG. Here, we performed whole‐genome sequencing of 185 diverse wild soybean (Glycine soja) accessions collected from three major agro‐ecological zones in China to parse the genomic basis of local adaptation in wild soybean. The population genomic diversity pattern exhibited clear agro‐ecological zone‐based population structure, and multiple environmental factors were observed to contribute to the genetic divergence. Demographic analysis shows that wild soybeans from the three ecological zones diverged about 1 × 105 years ago, and then the effective population sizes have undergone different degrees of expansions. Genome‐environment association identified multiple genes involved in the local adaptation, such as flowering time and temperature‐related genes. A locus containing two adjacent MADS‐box transcription factors on chromosome 19 was identified for multiple environmental factors, and it experienced positive selection that enables the adaptation to high‐latitude environment. This study provides insights into the genetic mechanism of ecological adaptation in wild soybean that may facilitate climate‐resilient soybean breeding.

Salinity threatens soybean germination, growth and production. The germination stage is a key period in the life of soybean. Wild soybean contains many genes related to stress resistance that are valuable resources for the genetic improvement of soybean. To identify the genetic loci of wild soybean that are active during seed germination under salt stress, two populations, a soybean interspecific hybrid population comprising 142 lines and a natural population comprising 121 wild soybean accessions, were screened for three germination-related traits in this study. By using single-nucleotide polymorphism (SNP) markers with three salt tolerance indices, 25 quantitative trait loci (QTLs), 21 significant SNPs (–log10(P)≥4.0) and 24 potential SNPs (3.5

Objective: Leptin has drawn the attention of experts for its role in a myriad of conditions including stroke. However, in the absence of credible evidence linking leptin to stroke, its role as a risk factor is still debatable. We aimed to determine the leptin levels and its relationship with other cardiometabolic risk factors in patients with ischemic stroke in our region. Materials and Methods: It was a hospital based case-control observational study involving 100 patients and 100 age- and sex- matched healthy controls. Leptin levels were measured in both patients and controls in addition to estimation of lipid profile, insulin level and fasting blood glucose. Insulin resistance was calculated using the homeostasis model assessment for insulin resistance model. Carotid intima-media thickness (CIMT) was determined by high-resolution echocolour Doppler system (GE LOGIQ S8). Neuroimaging was also performed. Student’s t-test for continuous variables, chi-square test for categorical variables and Pearson correlation coefficient to determine the correlation of leptin levels with various parameters were used. Results: The mean leptin levels were significantly higher in patients compared to control group (15.36±5.76 vs. 5.72±1.19 ng/ml; p

Background: Maturity onset diabetes of young (MODY) is considered to be the most underdiagnosed condition. The correct diagnosis of MODY has a definite bearing on the outcome and clinical course of the disease. We aim to determine the prevalence and clinical profile of MODY among young diabetic patients attending at Department of Endocrinology, a tertiary care institute in North India. Methods: It was a cross-sectional study involving all consecutive consenting patients with diabetes and age of onset ≤35 years. A total of 1,094 patients were included in this study, of whom 858 were having age of onset of diabetes 0.6 ng/mL were subjected to the Ala98 Val polymorphism (SNP) in hepatocyte nuclear factor (HNF) 1α gene. Results: The prevalence of MODY among the study cohort as per clinical criteria was found to be 7.7%. Males constituted the majority of patients (male vs female, 56% vs. 44%; P < 0.001). The patients with MODY were younger (p < 0.001), leaner (p < 0.001), had younger age at onset of diabetes mellitus (p < 0.001), and lower frequency of features of insulin resistance in the form of skin tags and acanthosis nigricans. Among the 40 patients who were subjected to Ala98Val polymorphism of HNF1α gene (MODY 3), the mutant genotype was seen in 20 (50%) patients. Conclusion: We report a higher prevalence of MODY in our young diabetic patients. A high index of suspicion is required to diagnose MODY as misdiagnosis and inappropriate treatment may have a significant impact on quality-of-life (QOL) with increased cost and unnecessary treatment with insulin.

Most plant traits are governed by polygenes including both major and minor genes. Linkage mapping and positional cloning have contributed greatly to mapping genomic loci controlling important traits in crop species. However, they are low-throughput, time-consuming, and have low resolution due to which their efficiency in crop breeding is reduced. In this regard, the bulk segregant analysis sequencing (BSA-seq) and its related approaches, viz., quantitative trait locus (QTL)-seq, bulk segregant RNA-Seq (BSR)-seq, and MutMap, have emerged as efficient methods to identify the genomic loci/QTLs controlling specific traits at high resolution, accuracy, reduced time span, and in a high-throughput manner. These approaches combine BSA with next-generation sequencing (NGS) and enable the rapid identification of genetic loci for qualitative and quantitative assessments. Many previous studies have shown the successful identification of the genetic loci for different plant traits using BSA-seq and its related approaches, as discussed in the text with details. However, the efficiency and accuracy of the BSA-seq depend upon factors like sequencing depth and coverage, which enhance the sequencing cost. Recently, the rapid reduction in the cost of NGS together with the expected cost reduction of third-generation sequencing in the future has further increased the accuracy and commercial applicability of these approaches in crop improvement programs. This review article provides an overview of BSA-seq and its related approaches in crop breeding together with their merits and challenges in trait mapping.

Identifying the genetic components underlying yield-related traits in soybean is crucial for improving its production and productivity. Here, 211 soybean genotypes were evaluated across six environments for four yield-related traits, including seed yield per plant (SYP), number of pods per plant number of seeds per plant and 100-seed weight (HSW). Genome-wide association study (GWAS) and genomic prediction (GP) analyses were performed using 12,617 single nucleotide polymorphism markers from NJAU 355K SoySNP Array. A total of 57 SNPs were significantly associated with four traits across six environments and a combined environment using five Genome-wide association study models. Out of these, six significant SNPs were consistently identified in more than three environments using multiple GWAS models. The genomic regions (±670 kb) flanking these six consistent SNPs were considered stable QTL regions. Gene annotation and in silico expression analysis revealed 15 putative genes underlying the stable QTLs that might regulate soybean yield. Haplotype analysis using six significant SNPs revealed various allelic combinations regulating diverse phenotypes for the studied traits. Furthermore, the GP analysis revealed that accurate breeding values for the studied soybean traits is attainable at an earlier generation. Our study paved the way for increasing soybean yield performance within a short breeding cycle.

Purpose: The lactate level is being increasingly used as a marker of severity of illness and prognosis in multitude of critical conditions. However, its role in diabetic ketoacidosis (DKA) is not well defined. Aim: To determine the prevalence and clinical importance along with the underlying role of metformin in lactic acidosis (LA) in patients admitted with DKA. Methods: A 2-year prospective and observational study involving 62 consenting in hospital DKA patients. Plasma lactate level on arrival, its clinical significance and relationship with morbidity and mortality in patients with DKA was evaluated. Results: The prevalence of LA (lactate ≥2.5 mmol/l) among the study cohort was found to be 55% with significant LA (≥5 mmol/l) documented in 16%. The median lactate level was 2.55 mmol/l (interquartile range, 1.70–3.20). No significant difference in the severity of LA was seen with metformin use. Lactate correlated positively with initial plasma glucose (IPG) (P = 0.001) and APACHE-II Score (P = 0.002); correlated negatively with systolic blood pressure (P = 0.003), pH (P = 0.002) and severity of DKA (P = 0.001). After controlling for AKI, APACHE II score and blood pressure, lactate continued to correlate positively with IPG (P = 0.002). No mortality or significant morbidity was documented in the entire cohort. Conclusions: LA has a significant presence in patients with DKA; however, it is not associated with mortality or significant morbidity. Moreover, there was no significant difference in severity of LA with metformin use. Elevated lactate levels may be an adaptation to provide alternate substrate for metabolism in the presence of hypoinsulinemic state. The study results provide rationale for large well-designed studies evaluating in-depth clinical relationship of lactate in DKA.

The novel coronavirus pandemic has led to morbidity and mortality throughout the world. Until now, it is a highly virulent contagion attacking the respiratory system in humans, especially people with chronic diseases and the elderly who are most vulnerable. A majority of afflicted are those suffering from cardiovascular and coronary diseases. In this review article, an attempt has been made to discuss and thoroughly review the mode of therapies that alleviate cardiac complications and complications due to hypercoagulation in patients infected with the SARS-CoV-2 virus. Presently a host of thrombolytic drugs are in use like Prourokinase, Retelapse, RhTNK-tPA and Urokinase. However, thrombolytic therapy, especially if given intravenously, is associated with a serious risk of intracranial haemorrhage, systemic haemorrhage, immunologic complications, hypotension and myocardial rupture. The effects of the SARS-CoV-2 virus upon the cardiovascular system and coagulation state of the body are being closely studied. In connection to the same, clinical prognosis and complications of thrombolytic therapy are being scrutinized. It is noteworthy to mention that myocardial oxygen supply/demand mismatch, direct myocardial cells injury and acute plaque rupture are the multiple mechanisms responsible for acute coronary syndrome and cardiac complications in Covid-19 infection. However, this review has limitations as data available in this context is limited, scattered and heterogenous that questions the reliability of the same. So, more multi-centric studies involving representative populations, carried out meticulously, could further assist in responding better to cardiac complications among Covid-19 patients.

Wheat is an important cereal crop species consumed globally. The growing global population demands a rapid and sustainable growth of agricultural systems. The development of genetically efficient wheat varieties has solved the global demand for wheat to a greater extent. The use of chemical substances for pathogen control and chemical fertilizers for enhanced agronomic traits also proved advantageous but at the cost of environmental health. An efficient alternative environment-friendly strategy would be the use of beneficial microorganisms growing on plants, which have the potential of controlling plant pathogens as well as enhancing the host plant’s water and mineral availability and absorption along with conferring tolerance to different stresses. Therefore, a thorough understanding of plant-microbe interaction, identification of beneficial microbes and their roles, and finally harnessing their beneficial functions to enhance sustainable agriculture without altering the environmental quality is appealing. The wheat microbiome shows prominent variations with the developmental stage, tissue type, environmental conditions, genotype, and age of the plant. A diverse array of bacterial and fungal classes, genera, and species was found to be associated with stems, leaves, roots, seeds, spikes, and rhizospheres, etc., which play a beneficial role in wheat. Harnessing the beneficial aspect of these microbes is a promising method for enhancing the performance of wheat under different environmental stresses. This review focuses on the microbiomes associated with wheat, their spatio-temporal dynamics, and their involvement in mitigating biotic and abiotic stresses.

Abstract Soybean is an important food crop that provides edible protein and oil for human and animal nutrition. Conventional phenotypic‐based breeding approaches have made significant contribution in the last century by developing many improved soybean varieties. However, due to the longer time taken to develop a variety, low genetic gain per unit time, and adverse environmental influence of phenotypic‐based selection, conventional approaches are not sufficient to maintain pace with growing population and climate change. In this context, the recent method of genotypic selection, that is, genomics‐assisted breeding (GAB) is considered a promising approach to address the challenges in soybean breeding. However, to harness the true potential of GAB in soybean improvement, the great coverage and precision in the genotyping and phenotyping are required. Previously, a huge gap was observed between the discovery and practical use of quantitative trait loci (QTLs) in soybean improvement. It has been suggested that low marker density and manually collected phenotypes are the major reasons for this failure. Hence, high‐throughput genotyping (HTG) providing higher genome‐wide marker density, as well as accurate and precise phenotyping using high‐throughput digital phenotyping (HTP) platforms, can significantly increase the success of QTL and candidate gene identification in soybean. These approaches can greatly increase the practical utility of GAB in soybean and also offer a faster characterization of germplasm and breeding materials. This review provides the detailed information on how the recent innovations in genomics and phenomics can assists in improving the efficiency and potential of GAB in soybean improvement.

Cadmium (Cd) is a trace element causing severe toxicity symptoms in plants, besides posing hazardous fitness issue due to its buildup in the human body through food chain. Nanoparticles (NPs) are recently employed as a novel strategy to directly ameliorate the Cd stress and acted as nano-fertilizers. The intend of the current study was to explore the effects of zinc oxide nanoparticles (ZnO-NPs; 50 mg/L) on plant growth, photosynthetic activity, elemental status and antioxidant activity in Oryza sativa (rice) under Cd (0.8 mM) stress. To this end, the rice plants are treated by Cd stress at 15 days after sowing (DAS), and the treatment was given directly into the soil. Supply of ZnO-NPs as foliar spray was given for five consecutive days from 30 to 35 DAS, and sampling was done at 45 DAS. However, rice plants supplemented with ZnO-NPs under the Cd toxicity revealed significantly increased shoot length (SL; 34.0%), root fresh weight (RFW; 30.0%), shoot dry weight (SDW; 23.07%), and root dry weight (RDW; 12.24%). Moreover, the ZnO-NPs supplement has also positive effects on photosynthesis related parameters, SPAD value (40%), chloroplast structure, and qualitatively high fluorescence observed by confocal microscopy even under Cd stress. ZnO-NPs also substantially prevented the increases of hydrogen peroxide (H2O2) and malondialdehyde (MDA) triggered by Cd. Physiological and biochemical analysis showed that ZnO-NPs increased enzymatic activities of superoxide dismutase (SOD; 59%), catalase (CAT; 52%), and proline (17%) that metabolize reactive oxygen species (ROS); these increases coincided with the changes observed in the H2O2 and MDA accumulation after ZnO-NPs application. In conclusion, ZnO-NPs application to foliage has great efficiency to improve biomass, photosynthesis, protein, antioxidant enzymes activity, mineral nutrient contents and reducing Cd levels in rice. This can be attributed mainly from reduced oxidative damage resulted due to the ZnO-NPs application.

The present study was carried out to explore the possible role of kinetin and gibberellic acid (GA3) on faba bean under chromium (Cr) stress. Cr treatment negatively affected growth and biomass production, reduced photosynthetic pigments, and inhibited photosynthesis, gas exchange parameters, antioxidant enzymes, and the glyoxylase cycle. Moreover, Cr stress enhanced the production of malondialdehyde (MDA, 216.11%) and hydrogen peroxide (H2O2, 230.16%), electrolyte leakage (EL, 293.30%), and the accumulation of proline and glycine betaine. Exogenous application of kinetin and GA3 increased growth and biomass, improved pigment contents and photosynthesis, as well as up-regulated the antioxidant system by improving the antioxidant enzyme activities and the content of nonenzymatic components, and the glyoxylase cycle. Additionally, kinetin and GA3 application displayed a considerable enhancement in proline (602.61%) and glycine betaine (423.72), which help the plants to maintain water balance under stress. Furthermore, a decline in Cr uptake was also observed due to kinetin and GA3 application. Exogenous application of kinetin and GA3 ameliorated the toxic effects of Cr in faba bean plants, up-shooting the tolerance mechanisms, including osmolyte metabolism and the antioxidant system.

The consequences of climate change, and the increased accumulation of metalloids, like arsenic (As), in the environment, are significantly affecting crop performance and yield. Arsenic interferes with various plant biochemical and physiological processes, which result in diminished plant growth and development. Magnesium oxide nanoparticles (MgO-NPs) can improve plant growth and contribute to plant tolerance of heavy metal/metalloid toxicity. During current research, the efficacy of MgO-NPs was assessed for lessening arsenic (As) toxicity in soybean plants. In our experiment As uptake, plant growth, antioxidant enzyme activity, nutrient content, photochemical efficiency and photosynthetic performance were evaluated with/without exogenous application of 500 mg L−1 MgO-NPs in the presence/absence of 150 µM As in soybean plants. Foliar application of MgO-NPs, in the presence of As, enhanced plant height and dry weight by 17% and 15% respectively, and improved net photosynthetic rate by 12.9%, stomatal conductance by 13.4%, intercellular CO2 concentration by 15.3% and transpiration rate by 14.7%, as well as nutrient uptake and photosystem II (PSII) efficiency. In contrast, it decreased As uptake and oxidative stress as evaluated with hydrogen peroxide (H2O2) and lipid peroxidation (MDA). Hence, field tests may be implemented to formulate MgO-NPs use in agriculture, in order to obtain sustainable crop production in arsenic-contaminated soils.

Nanoparticles (NPs) have recently emerged as potential agents for plants to ameliorate abiotic stresses by acting as nano-fertilizers. In this regard, the influence of the zinc oxide nanoparticles (ZnO-NPs) on plant responses to copper (Cu) stress has been poorly understood. Hence, the present study was executed to explore the role of ZnO-NPs (foliar) and 24-epibrassinolide (EBL; root dipping) individually or in combined form in the resilience of tomato (Solanum lycopersicum) plant to Cu stress. Tomato seeds were sown to make the nursery; and at 20 days after sowing (DAS) the plantlets were submerged in 10−8 M of EBL solution for 2 h, and subsequently transplanted in the soil-filled earthen pots. Cu concentration (100 mg kg−1) was applied to the soil at 30 DAS, whereas at 35 DAS plants were sprinkled with double distilled water (DDW; control), 50 mg/L of Zinc (Zn) and 50 mg/L of ZnO-NPs; and plant performance were evaluated at 45 DAS. It was evident that Cu-stress reduced photosynthesis (17.3%), stomatal conductance (18.1%), plant height (19.7%), and nitrate reductase (NR) activity (19.2%), but increased malondialdehyde (MDA; 29.4%), superoxide radical (O2-; 22.3%) and hydrogen peroxide (H2O2; 26.2%) content in S. lycopersicum. Moreover, ZnO-NPs and/or EBL implemented via different modes improved photosynthetic activity, stomatal aperture, growth, cell viability and activity of antioxidant enzymes and proline that augmented resilience of tomato plants to Cu stress. These observations depicted that application of ZnO-NPs and EBL could be a useful approach to assist Cu confiscation and stress tolerance against Cu in tomato plants grown in Cu contaminated sites.

Chromium (Cr) is an important environmental constraint effecting crop productivity. Spermine (SPM) is a polyamine compound regulating plant responses to abiotic stresses. However, SPM-mediated tolerance mechanisms against Cr stress are less commonly explored in plants. Thus, current research was conducted to explore the protective mechanisms of SPM (0.01 mM) against Cr (100 µM) toxicity in two rice cultivars, CY927 (sensitive) and YLY689 (tolerant) at the seedling stage. Our results revealed that, alone, Cr exposure significantly reduced seed germination, biomass and photosynthetic related parameters, caused nutrient and hormonal imbalance, desynchronized antioxidant enzymes, and triggered oxidative damage by over-accretion of reactive oxygen species (ROS), malondialdehyde (MDA) and electrolyte leakage in both rice varieties, with greater impairments in CY927 than YLY689. However, seed priming with SPM notably improved or reversed the above-mentioned parameters, especially in YLY689. Besides, SPM stimulated the stress-responsive genes of endogenous phytohormones, especially salicylic acid (SA), as confirmed by the pronounced transcript levels of SA-related genes (OsPR1, OsPR2 and OsNPR1). Our findings specified that SPM enhanced rice tolerance against Cr toxicity via decreasing accumulation of Cr and markers of oxidative damage (H2O2, O2•− and MDA), improving antioxidant defense enzymes, photosynthetic apparatus, nutrients and phytohormone balance.

Chitinases are enzymes catalyzing the hydrolysis of chitin that are present on the cell wall of fungal pathogens. Here, we identified and characterized the chitinase gene family in cultivated soybean (Glycine max L.) across the whole genome. A total of 38 chitinase genes were identified in the whole genome of soybean. Phylogenetic analysis of these chitinases classified them into five separate clusters, I–V. From a broader view, the I–V classes of chitinases are basically divided into two mega-groups (X and Y), and these two big groups have evolved independently. In addition, the chitinases were unevenly and randomly distributed in 17 of the total 20 chromosomes of soybean, and the majority of these chitinase genes contained few introns (≤2). Synteny and duplication analysis showed the major role of tandem duplication in the expansion of the chitinase gene family in soybean. Promoter analysis identified multiple cis-regulatory elements involved in the biotic and abiotic stress response in the upstream regions (1.5 kb) of chitinase genes. Furthermore, qRT-PCR analysis showed that pathogenic and drought stress treatment significantly induces the up-regulation of chitinase genes belonging to specific classes at different time intervals, which further verifies their function in the plant stress response. Hence, both in silico and qRT-PCR analysis revealed the important role of the chitinases in multiple plant defense responses. However, there is a need for extensive research efforts to elucidate the detailed function of chitinase in various plant stresses. In conclusion, our investigation is a detailed and systematic report of whole genome characterization of the chitinase family in soybean.

Plants coevolved with their antioxidant defense systems, which detoxify and adjust levels of reactive oxygen species (ROS) under multiple plant stresses. We performed whole-genome identification of ascorbate peroxidase (APX) and catalase (CAT) families in cultivated and wild soybeans. In cultivated and wild soybean genomes, we identified 11 and 10 APX genes, respectively, whereas the numbers of identified CAT genes were four in each species. Comparative phylogenetic analysis revealed more homology among cultivated and wild soybeans relative to other legumes. Exon/intron structure, motif and synteny blocks are conserved in cultivated and wild species. According to the Ka/Ks value, purifying selection is a major force for evolution of these gene families in wild soybean; however, the APX gene family was evolved by both positive and purifying selection in cultivated soybean. Segmental duplication was a major factor involved in the expansion of APX and CAT genes. Expression patterns revealed that APX and CAT genes are differentially expressed across fourteen different soybean tissues under water deficit (WD), heat stress (HS) and combined drought plus heat stress (WD + HS). Altogether, the current study provides broad insights into these gene families in soybeans. Our results indicate that APX and CAT gene families modulate multiple stress response in soybeans.

Background: Fibrocalculous pancreatic diabetes (FCPD) is a secondary form of diabetes, described from several tropical countries, including India. We described the existence of this entity in the subtropical region-the Kashmir valley of the Indian subcontinent and compared the clinical characteristics of these patients with type 2 diabetes mellitus (T2DM) patients. Aim: The present study aimed to compare the clinical characteristics of patients with FCPD and those with T2DM to identify the characteristics distinctive of FCPD. Materials and Methods: A total of 124 patients with FCPD were compared with 124 patients with T2DM matched for age and duration of diabetes. Biochemical parameters and microvascular and macrovascular complications were assessed in all patients. Multivariate regression analyses were performed to study the determinants of microvascular complications in both groups. Results: FCPD patients had significantly lower serum cholesterol, serum triglyceride, and serum calcium levels but higher glycosylated hemoglobin levels compared to T2DM patients. FCPD participants were significantly leaner. The prevalence of retinopathy, neuropathy, and nephropathy was similar between the two. Five T2DM patients had documented cardiovascular disease compared to one in FCPD patients (P < 0.05). Multiple logistic regression analysis revealed glycosylated hemoglobin and duration of diabetes to be significantly associated with retinopathy and nephropathy in T2DM. Among FCPD patients, glycosylated hemoglobin showed a strong association with retinopathy as well as nephropathy. BMI showed a significant negative association with nephropathy in FCPD patients. Age and age at onset showed a strong association with neuropathy in FCPD patients while the duration of diabetes showed the association with neuropathy (P = 0.015) in T2DM. Conclusion: There are several differences in the phenotype, biochemical parameters, and prevalence of diabetic complications between patients with FCPD and T2DM.