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Abstract Arachis hypogaea is an allotetraploid crop widely grown in the world. Wild relatives of genus Arachis are the rich source of genetic diversity and high levels of resistance to combat pathogens and climate change. The accurate identification and characterization of plant resistance gene, nucleotide binding site leucine rich repeat receptor (NLRs) substantially contribute to the repertoire of resistances and improve production. In the current study, we have studied the evolution of NLR genes in genus Arachis and performed their comparative genomics among four diploids (A. duranensis, A. ipaensis, A. cardenasii, A. stenosperma) and two tetraploid (wild: A. monticola and domesticated: A. hypogaea) species. In total 521, 354, 284, 794, 654, 290 NLR genes were identified from A. cardenasii, A. stenosperma and A. duranensis, A. hypogaea, A. monticola and A. ipaensis respectively. Phylogenetic analysis and classification of NLRs revealed that they belong to 7 subgroups and specific subgroups have expanded in each genome leading towards divergent evolution. Gene gain and loss, duplication assay reveals that wild and domesticated tetraploids species have shown asymmetric expansion of NLRome in both sub-genome (AA and BB). A-subgenome of A. monticola exhibited significant contraction of NLRome while B-subgenome shows expansion and vice versa in case of A. hypogaea probably due to distinct natural and artificial selection pressure. In addition, diploid species A. cardenasii revealed the largest repertoire of NLR genes due to higher frequency of gene duplication and selection pressure. A. cardenasii and A. monticola can be regarded as putative resistance resources for peanut breeding program for introgression of novel resistance genes. Findings of this study also emphasize the application neo-diploids and polyploids due to higher quantitative expression of NLR genes. To the best of our knowledge, this is the first study that studied the effect of domestication and polyploidy on the evolution of NLR genes in genus Arachis to identify genomic resources for improving resistance of polyploid crop with global importance on economy and food security.

Abstract Maize is the world's most produced cereal crop, and the selection of maize cultivars with a high stem elastic modulus is an effective method to prevent cereal crop lodging. We developed an ultra-compact sensor array inspired by earthquake engineering and proposed a method for the high-throughput evaluation of the elastic modulus of maize cultivars. A natural vibration analysis based on the obtained Young’s modulus using finite element analysis (FEA) was performed and compared with the experimental results, which showed that the estimated Young’s modulus is representative of the individual Young’s modulus. FEA also showed the hotspot where the stalk was most deformed when the corn was vibrated by wind. The six tested cultivars were divided into two phenotypic groups based on the position and number of hotspots. In this study, we proposed a non-destructive high-throughput phenotyping technique for estimating the modulus of elasticity of maize stalks and successfully visualized which parts of the stalks should be improved for specific cultivars to prevent lodging.

Abstract Actinobacteria represent one of the largest bacterial phyla harboring many species of high medical, biotechnological and ecological relevance. Prophage elements are major contributors to bacterial genome diversity and were shown to significantly shape bacterial fitness and host-microbe interactions. In this study, we performed a systematic analysis of prophage elements in 2406 complete actinobacterial genomes. Overall, 2106 prophage elements were predicted to be present in about 50% (1172/2406) of the analyzed datasets. Interestingly, these identified sequences compose a high prevalence of cryptic prophage elements, indicating genetic decay and domestication. Analysis of the sequence relationship of predicted prophages with known actinobacteriophage genomes revealed an exceptional high phylogenetic diversity of prophage elements. As a trend, we observed a higher prevalence of prophage elements in vicinity to the terminus. Analysis of the prophage-encoded gene functions revealed that prophage sequences significantly contribute to the bacterial antiviral immune system, but no biosynthetic gene clusters involved in the synthesis of known antiphage molecules were identified in prophage genomes. Overall, the current study highlights the remarkable diversity of prophages in actinobacterial genomes, with highly divergent prophages in actinobacterial genomes and thus provides an important basis for further investigation of phage-host interactions in this important bacterial phylum.

Abstract Accurately predicting red blood cell (RBC) transfusion requirements in cardiothoracic (CT) surgery could improve blood inventory management and be used as a surrogate marker for assessing hemorrhage risk preoperatively. We developed a machine learning (ML) method to predict intraoperative RBC transfusions in CT surgery. A detailed database containing time-stamped clinical variables for all CT surgeries from 5/2014–6/2019 at a single center (n = 2410) was used for model development. After random forest feature selection, surviving features were inputs for ML algorithms using five-fold cross-validation. The dataset was updated with 437 additional cases from 8/2019–8/2020 for validation. We developed and validated a hybrid ML method given the skewed nature of the dataset. Our Gaussian Process (GP) regression ML algorithm accurately predicted RBC transfusion amounts of 0 and 1–3 units (root mean square error, RMSE 0.117 and 1.705, respectively) and our GP classification ML algorithm accurately predicted 4 + RBC units transfused (area under the curve, AUC = 0.826). The final prediction is the regression result if classification predicted

Abstract Hollow nanostructures of copper oxides help to stabilize appreciably higher electrochemical characteristics than their solid counter parts of various morphologies. The specific capacitance values, calculated using cyclic voltammetry (CV) and charge-discharge (CD) studies, are found to be much higher than the values reported in literature for copper oxide particles showing intriguing morphologies or even composites with trendy systems like CNTs, rGO, graphene, etc. The proposed cost-effective synthesis route makes these materials industrially viable for application in alternative energy storage devices. The improved electrochemical response can be attributed to effective access to the higher number of redox sites that become available on the surface, as well as in the cavity of the hollow particles. The ion transport channels also facilitate efficient de-intercalation, which results in the enhancement of cyclability and Coulombic efficiency. The charge storage mechanism in copper oxide structures is also proposed in the paper.