Application of Singh-Jha Equation in the Evaluation of b* Parameter of Laidler-Landskroener Equation in the Hydrolysis of Vinyl Acetate

Singh-Jha method is applied to calculate b* of Laidler-Landskroener equation, the distance of closed approach of solvent molecules to the activated complexes in alkaline hydrolysis of vinyl acetate. This method is applied to alkaline hydrolysis of vinyl acetate in water enriched ethanol between 30 °C and 35 °C. The rate of hydrolysis decreases with the increase of content of organic solvent at both temperatures. The size of transition state was found to be large as compared to the initial state. The b* was found to be 3.7693Å which is in agreement with the values obtained earlier

De Novo Sequencing and Hybrid Assembly of the Biofuel Crop <i>Jatropha curcas</i> L.: Identification of Quantitative Trait Loci for Geminivirus Resistance

Jatropha curcas is an important perennial, drought tolerant plant that has been identified as a potential biodiesel crop. We report here the hybrid de novo genome assembly of J. curcas generated using Illumina and PacBio sequencing technologies, and identification of quantitative loci for Jatropha Mosaic Virus (JMV) resistance. In this study, we generated scaffolds of 265.7 Mbp in length, which correspond to 84.8% of the gene space, using Benchmarking Universal Single-Copy Orthologs (BUSCO) analysis. Additionally, 96.4% of predicted protein-coding genes were captured in RNA sequencing data, which reconfirms the accuracy of the assembled genome. The genome was utilized to identify 12,103 dinucleotide simple sequence repeat (SSR) markers, which were exploited in genetic diversity analysis to identify genetically distinct lines. A total of 207 polymorphic SSR markers were employed to construct a genetic linkage map for JMV resistance, using an interspecific F2 mapping population involving susceptible J. curcas and resistant Jatropha integerrima as parents. Quantitative trait locus (QTL) analysis led to the identification of three minor QTLs for JMV resistance, and the same has been validated in an alternate F2 mapping population. These validated QTLs were utilized in marker-assisted breeding for JMV resistance. Comparative genomics of oil-producing genes across selected oil producing species revealed 27 conserved genes and 2986 orthologous protein clusters in Jatropha. This reference genome assembly gives an insight into the understanding of the complex genetic structure of Jatropha, and serves as source for the development of agronomically improved virus-resistant and oil-producing lines

Obesity, inflammatory and thrombotic markers, and major clinical outcomes in critically ill patients with COVID‐19 in the US

Objective This study aimed to determine whether obesity is independently associated with major adverse clinical outcomes and inflammatory and thrombotic markers in critically ill patients with COVID‐19. Methods The primary outcome was in‐hospital mortality in adults with COVID‐19 admitted to intensive care units across the US. Secondary outcomes were acute respiratory distress syndrome (ARDS), acute kidney injury requiring renal replacement therapy (AKI‐RRT), thrombotic events, and seven blood markers of inflammation and thrombosis. Unadjusted and multivariable‐adjusted models were used. Results Among the 4,908 study patients, mean (SD) age was 60.9 (14.7) years, 3,095 (62.8%) were male, and 2,552 (52.0%) had obesity. In multivariable models, BMI was not associated with mortality. Higher BMI beginning at 25 kg/m2 was associated with a greater risk of ARDS and AKI‐RRT but not thrombosis. There was no clinically significant association between BMI and inflammatory or thrombotic markers. Conclusions In critically ill patients with COVID‐19, higher BMI was not associated with death or thrombotic events but was associated with a greater risk of ARDS and AKI‐RRT. The lack of an association between BMI and circulating biomarkers calls into question the paradigm that obesity contributes to poor outcomes in critically ill patients with COVID‐19 by upregulating systemic inflammatory and prothrombotic pathways