Antioxidative effect of astragalosides on acute pancreatitis in mice.

Introduction: The research examined the antioxidative impact of astragalosides (AST) on experimental acute pancreatitis (AP) in mice. This study aims to assess the correlation between varying doses of astragalosides and superoxide dismutase (SOD) activity in an acute pancreatitis mouse model. By examining the interplay between astragaloside's protective effects and its antioxidant properties, we aim to deepen our understanding of its therapeutic potential in acute pancreatitis. Methods: The AP model in mice was induced by retrograde injection of sodium deoxycholate into the biliary and pancreatic ducts. Serum amylase activity was monitored at various time points following induction. Furthermore, 24 hours post-induction, levels of serum nitric oxide (NO), superoxide dismutase (SOD) activity, and malondialdehyde (MDA) content in pancreatic tissue were assessed. Results: The findings of this study illustrated that AST, while exhibiting a protective effect in experimental AP, could effectively lower the elevated serum NO levels, reduce MDA production, and enhance SOD activity in model mice. AST notably reduced MDA levels in the pancreatic tissue of AP mice, underscoring its ability to inhibit membrane peroxidation induced by oxygen free radicals. Furthermore, AST was observed to elevate SOD activity in scavenging oxygen free radicals in pancreatic tissue. Conclusion: These findings suggest that AST enhances recovery in an experimental acute pancreatitis mouse model by exerting antioxidative effects.

Identification of QTLs associated with yield-related traits and superior genotype prediction using recombinant inbred line population in tobacco.

Tobacco is an economically significant industrial crop and model plant for genetic research, yet little is known about its genetic architecture. Quantitative trait loci (QTL) analysis was performed for six agronomic traits on an F_7 population of 341 genotypes, parents, and F1 plants using 1974 SSR markers across two environments. 31 QTLs contributing single-locus additive effects on 13 linkage groups (LGs) and 6 QTL pairs contributing epistatic effects on 6 LGs, were detected by the QTLNetwork 2.0 which was developed for the mixed-linear-model-based composite interval mapping (MCIM). Notably, 5 QTLs and 1 epistatic QTL pair were found to have pleiotropic effects on some genetically related traits. Moreover, the Broad sense heritability of the detected QTLs ranged from 1.05% to 43.33%, while genotype-by-environment interaction heritability spanned from 27.09% to 56.25%. Based on the results of QTL mapping, the potential superior lines for all or specific environments were designed and evaluated. Five major QTLs were finely dissected based on the tobacco reference genome of K326, and 31 candidate genes were predicted. This study offered new insights into the complicated genetic architecture and QTL resources for efficient breeding design for genetic improvement of agronomic traits in tobacco.

Dissection of genetic architecture of nine hazardous component traits of mainstream smoke in tobacco (Nicotiana tabacum L.).

Tobacco (Nicotiana tabacum L.) use is the leading cause of preventable death, due to deleterious chemical components and smoke from tobacco products, and therefore reducing harmful chemical components in tobacco is one of the crucial tobacco breeding targets. However, due to complexity of tobacco smoke and unavailability of high-density genetic maps, the genetic architecture of representative hazardous smoke has not been fully dissected. The present study aimed to explore the genetic architecture of nine hazardous component traits of mainstream smoke through QTL mapping using 271 recombinant inbred lines (RILs) derived from K326 and Y3 in multiple environments. The analysis of genotype and genotype by environment interaction (GE) revealed substantially greater heritability over 95% contributed mostly by GE interaction effects. We also observed strong genetic correlations among most studied hazardous smoke traits, with the highest correlation coefficient of 0.84 between carbon monoxide and crotonaldehyde. Based on a published high-density genetic map, a total of 19 novel QTLs were detected for eight traits using a full QTL model, of which 17 QTLs showed significant additive effects, six showed significant additive-by-environment interaction effects, and one pair showed significant epistasis-by-environment interaction effect. Bioinformatics analysis of sequence in QTL region predicted six genes as candidates for four traits, of which Nt21g04598.1, Nt21g04600.1, and Nt21g04601.1 had pleiotropic effects on PHE and TAR.

Ultrasmall Polyphenol-NAD+ Nanoparticle-Mediated Renal Delivery for Mitochondrial Repair and Anti-Inflammatory Treatment of AKI-to-CKD Progression.

As a central metabolic molecule, nicotinamide adenine dinucleotide (NAD+) can potentially treat acute kidney injury (AKI) and chronic kidney disease (CKD); however, its bioavailability is poor due to short half-life, instability, the deficiency of targeting, and difficulties in transmembrane transport. Here a physiologically adaptive gallic acid-NAD+ nanoparticle is designed, which has ultrasmall size and pH-responsiveness, passes through the glomerular filtration membrane to reach injured renal tubules, and efficiently delivers NAD+ into the kidneys. With an effective accumulation in the kidneys, it restores renal function, immune microenvironment homeostasis, and mitochondrial homeostasis of AKI mice via the NAD+-Sirtuin-1 axis, and exerts strong antifibrotic effects on the AKI-to-CKD transition by inhibiting TGF-ß signaling. It also exhibits excellent stability, biodegradable, and biocompatible properties, ensuring its long-term safety, practicality, and clinical translational feasibility. The present study shows a potential modality of mitochondrial repair and immunomodulation through nanoagents for the efficient and safe treatment of AKI and CKD.

Searching across-cohort relatives in 54,092 GWAS samples via encrypted genotype regression.

Explicitly sharing individual level data in genomics studies has many merits comparing to sharing summary statistics, including more strict QCs, common statistical analyses, relative identification and improved statistical power in GWAS, but it is hampered by privacy or ethical constraints. In this study, we developed encG-reg, a regression approach that can detect relatives of various degrees based on encrypted genomic data, which is immune of ethical constraints. The encryption properties of encG-reg are based on the random matrix theory by masking the original genotypic matrix without sacrificing precision of individual-level genotype data. We established a connection between the dimension of a random matrix, which masked genotype matrices, and the required precision of a study for encrypted genotype data. encG-reg has false positive and false negative rates equivalent to sharing original individual level data, and is computationally efficient when searching relatives. We split the UK Biobank into their respective centers, and then encrypted the genotype data. We observed that the relatives estimated using encG-reg was equivalently accurate with the estimation by KING, which is a widely used software but requires original genotype data. In a more complex application, we launched a finely devised multi-center collaboration across 5 research institutes in China, covering 9 cohorts of 54,092 GWAS samples. encG-reg again identified true relatives existing across the cohorts with even different ethnic backgrounds and genotypic qualities. Our study clearly demonstrates that encrypted genomic data can be used for data sharing without loss of information or data sharing barrier.