Mitochondrial VOLTAGE-DEPENDENT ANION CHANNEL 3 regulates stomatal closure by abscisic acid signaling.

In Arabidopsis (Arabidopsis thaliana), stomatal closure mediated by abscisic acid (ABA) is redundantly controlled by ABA receptor family proteins (PYRABACTIN RESISTANCE 1 [PYR1]/PYR1-LIKE [PYLs]) and subclass III SUCROSE NONFERMENTING 1 (SNF1)-RELATED PROTEIN KINASES 2 (SnRK2s). Among these proteins, the roles of PYR1, PYL2, and SnRK2.6 are more dominant. A recent discovery showed that ABA-induced accumulation of reactive oxygen species (ROS) in mitochondria promotes stomatal closure. By analyzing stomatal movements in an array of single and higher order mutants, we revealed that the mitochondrial protein VOLTAGE-DEPENDENT ANION CHANNEL 3 (VDAC3) jointly regulates ABA-mediated stomatal closure with a specialized set of PYLs and SnRK2s by affecting cellular and mitochondrial ROS accumulation. VDAC3 interacted with 9 PYLs and all 3 subclass III SnRK2s. Single mutation in VDAC3, PYLs (except PYR1 and PYL2), or SnRK2.2/2.3 had little effect on ABA-mediated stomatal closure. However, knocking out PYR1, PYL1/2/4/8, or SnRK2.2/2.3 in vdac3 mutants resulted in significantly delayed or attenuated ABA-mediated stomatal closure, despite the presence of other PYLs or SnRK2s conferring redundant functions. We found that cellular and mitochondrial accumulation of ROS induced by ABA was altered in vdac3pyl1 mutants. Moreover, H2O2 treatment restored ABA-induced stomatal closure in mutants with decreased stomatal sensitivity to ABA. Our work reveals that VDAC3 ensures redundant control of ABA-mediated stomatal closure by canonical ABA signaling components.

Quantitative proteomics and multi-omics analysis identifies potential biomarkers and the underlying pathological molecular networks in Chinese patients with multiple sclerosis.

Multiple sclerosis (MS) is an autoimmune disorder caused by chronic inflammatory reactions in the central nervous system. Currently, little is known about the changes of plasma proteomic profiles in Chinese patients with MS (CpwMS) and its relationship with the altered profiles of multi-omics such as metabolomics and gut microbiome, as well as potential molecular networks that underlie the etiology of MS. To uncover the characteristics of proteomics landscape and potential multi-omics interaction networks in CpwMS, Plasma samples were collected from 22 CpwMS and 22 healthy controls (HCs) and analyzed using a Tandem Mass Tag (TMT)-based quantitative proteomics approach. Our results showed that the plasma proteomics pattern was significantly different in CpwMS compared to HCs. A total of 90 differentially expressed proteins (DEPs), such as LAMP1 and FCG2A, were identified in CpwMS plasma comparing to HCs. Furthermore, we also observed extensive and significant correlations between the altered proteomic profiles and the changes of metabolome, gut microbiome, as well as altered immunoinflammatory responses in MS-affected patients. For instance, the level of LAMP1 and ERN1 were significantly and positively correlated with the concentrations of metabolite L-glutamic acid and pro-inflammatory factor IL-17 (Padj < 0.05). However, they were negatively correlated with the amounts of other metabolites such as L-tyrosine and sphingosine 1-phosphate, as well as the concentrations of IL-8 and MIP-1α. This study outlined the underlying multi-omics integrated mechanisms that might regulate peripheral immunoinflammatory responses and MS progression. These findings are potentially helpful for developing new assisting diagnostic biomarker and therapeutic strategies for MS.

Stacking-dependent interlayer magnetic interactions in CrSe2.

Recently, CrSe2, a new ferromagnetic van der Waals two-dimensional material, was discovered to be highly stable under ambient conditions, making it an attractive candidate for fundamental research and potential device applications. Here, we study the interlayer interactions of bilayer CrSe2using first-principles calculations. We demonstrate that the interlayer interaction depends on the stacking structure. The AA and AB stackings exhibit antiferromagnetic (AFM) interlayer interactions, while the AC stacking exhibits ferromagnetic (FM) interlayer interaction. Furthermore, the interlayer interaction can be further tuned by tensile strain and charge doping. Specifically, under large tensile strain, most stacking structures exhibit FM interlayer interactions. Conversely, under heavy electron doping, all stacking structures exhibit AFM interlayer interactions. These findings are useful for designing spintronic devices based on CrSe2.

Machine learning-based algorithm identifies key mitochondria-related genes in non-alcoholic steatohepatitis.

BACKGROUND: Evidence suggests that hepatocyte mitochondrial dysfunction leads to abnormal lipid metabolism, redox imbalance, and programmed cell death, driving the onset and progression of non-alcoholic steatohepatitis (NASH). Identifying hub mitochondrial genes linked to NASH may unveil potential therapeutic targets. METHODS: Mitochondrial hub genes implicated in NASH were identified via analysis using 134 algorithms. RESULTS: The Random Forest algorithm (RF), the most effective among the 134 algorithms, identified three genes: Aldo-keto reductase family 1 member B10 (AKR1B10), thymidylate synthase (TYMS), and triggering receptor expressed in myeloid cell 2 (TREM2). They were upregulated and positively associated with genes promoting inflammation, genes involved in lipid synthesis, fibrosis, and nonalcoholic steatohepatitis activity scores in patients with NASH. Moreover, using these three genes, patients with NASH were accurately categorized into cluster 1, exhibiting heightened disease severity, and cluster 2, distinguished by milder disease activity. CONCLUSION: These three genes are pivotal mitochondrial genes implicated in NASH progression.

Machine learning-based integration identifies the ferroptosis hub genes in nonalcoholic steatohepatitis.

BACKGROUND: Ferroptosis, is characterized by lipid peroxidation of fatty acids in the presence of iron ions, which leads to cell apoptosis. This leads to the disruption of metabolic pathways, ultimately resulting in liver dysfunction. Although ferroptosis is linked to nonalcoholic steatohepatitis (NASH), understanding the key ferroptosis-related genes (FRGs) involved in NASH remains incomplete. NASH may be targeted therapeutically by identifying the genes responsible for ferroptosis. METHODS: To identify ferroptosis-related genes and develop a ferroptosis-related signature (FeRS), 113 machine-learning algorithm combinations were used. RESULTS: The FeRS constructed using the Generalized Linear Model Boosting algorithm and Gradient Boosting Machine algorithms exhibited the best prediction performance for NASH. Eight FRGs, with ZFP36 identified by the algorithms as the most crucial, were incorporated into in FeRS. ZFP36 is significantly enriched in various immune cell types and exhibits significant positive correlations with most immune signatures. CONCLUSION: ZFP36 is a key FRG involved in NASH pathogenesis.

A New Potent Inhibitor against α-Glucosidase Based on an In Vitro Enzymatic Synthesis Approach.

Inhibiting the activity of intestinal α-glucosidase is considered an effective approach for treating type II diabetes mellitus (T2DM). In this study, we employed an in vitro enzymatic synthesis approach to synthesize four derivatives of natural products (NPs) for the discovery of therapeutic drugs for T2DM. Network pharmacology analysis revealed that the betulinic acid derivative P3 exerted its effects in the treatment of T2DM through multiple targets. Neuroactive ligand-receptor interaction and the calcium signaling pathway were identified as key signaling pathways involved in the therapeutic action of compound P3 in T2DM. The results of molecular docking, molecular dynamics (MD) simulations, and binding free energy calculations indicate that compound P3 exhibits a more stable binding interaction and lower binding energy (-41.237 kcal/mol) with α-glucosidase compared to acarbose. In addition, compound P3 demonstrates excellent characteristics in various pharmacokinetic prediction models. Therefore, P3 holds promise as a lead compound for the development of drugs for T2DM and warrants further exploration. Finally, we performed site-directed mutagenesis to achieve targeted synthesis of betulinic acid derivative. This work demonstrates a practical strategy of discovering novel anti-hyperglycemic drugs from derivatives of NPs synthesized through in vitro enzymatic synthesis technology, providing potential insights into compound P3 as a lead compound for anti-hyperglycemic drug development.

MetMiner: A user-friendly pipeline for large-scale plant metabolomics data analysis.

The utilization of metabolomics approaches to explore the metabolic mechanisms underlying plant fitness and adaptation to dynamic environments is growing, highlighting the need for an efficient and user-friendly toolkit tailored for analyzing the extensive datasets generated by metabolomics studies. Current protocols for metabolome data analysis often struggle with handling large-scale datasets or require programming skills. To address this, we present MetMiner (https://github.com/ShawnWx2019/MetMiner), a user-friendly, full-functionality pipeline specifically designed for plant metabolomics data analysis. Built on R shiny, MetMiner can be deployed on servers to utilize additional computational resources for processing large-scale datasets. MetMiner ensures transparency, traceability, and reproducibility throughout the analytical process. Its intuitive interface provides robust data interaction and graphical capabilities, enabling users without prior programming skills to engage deeply in data analysis. Additionally, we constructed and integrated a plant-specific mass spectrometry database into the MetMiner pipeline to optimize metabolite annotation. We have also developed MDAtoolkits, which include a complete set of tools for statistical analysis, metabolite classification, and enrichment analysis, to facilitate the mining of biological meaning from the datasets. Moreover, we propose an iterative weighted gene co-expression network analysis strategy for efficient biomarker metabolite screening in large-scale metabolomics data mining. In two case studies, we validated MetMiner's efficiency in data mining and robustness in metabolite annotation. Together, the MetMiner pipeline represents a promising solution for plant metabolomics analysis, providing a valuable tool for the scientific community to use with ease.

Hosts engineering and in vitro enzymatic synthesis for the discovery of novel natural products and their derivatives.

Novel natural products (NPs) and their derivatives are important sources for drug discovery, which have been broadly applied in the fields of agriculture, livestock, and medicine, making the synthesis of NPs and their derivatives necessarily important. In recent years, biosynthesis technology has received increasing attention due to its high efficiency in the synthesis of high value-added novel products and its advantages of green, environmental protection, and controllability. In this review, the technological advances of biosynthesis strategies in the discovery of novel NPs and their derivatives are outlined, with an emphasis on two areas of host engineering and in vitro enzymatic synthesis. In terms of hosts engineering, multiple microorganisms, including Streptomyces, Aspergillus, and Penicillium, have been used as the biosynthetic gene clusters (BGCs) provider and host strain for the expression of BGCs to discover new compounds over the past years. In addition, the use of in vitro enzymatic synthesis strategy to generate novel compounds such as triterpenoid saponins and flavonoids is also hereby described.

Value of conventional ultrasound and contrast-enhanced ultrasound for the assessment of renal allograft dysfunction and prognosis.

BACKGROUND: Ultrasound (US) is the primary imaging modality for the assessment of transplanted kidneys. This study aims to investigate the ability of conventional US and contrast-enhanced US (CEUS) in assessing renal allograft function and prognosis. METHODS: A total of 78 consecutive renal allograft recipients were enrolled. Patients were classified as normal allograft function (n = 41) and allograft dysfunction (n = 37) groups. All patients underwent US and parameters were measured. The independent-samples t-test or Mann-Whitney U test, logistic regression analysis, Kaplan-Meier survival plots, and Cox regression analysis were used. RESULTS: In multivariable analysis, cortical echo intensity (EI) and cortical peak intensity (PI) were determinant US parameters for renal allograft dysfunction (p = .024 and p = .003, respectively). The combination of cortical EI and PI showed an area under the receiver operating characteristic curve (AUROC) of .785 (p < .001). Of 78 patients (median follow-up: 20mo), 16 (20.5%) exhibited composite end points. Cortical PI had a general prediction accuracy with an AUROC of .691, sensitivity of 87.5%, and specificity of 46.8% at the threshold of 22.08 dB in predicting prognosis (p = .019). The combination of estimated-glomerular filtration rate (e-GFR) and PI in predicting prognosis showed an AUROC of .845 with a cut-off value of .836, sensitivity of 84.0%, and specificity of 67.3% (p < .001). CONCLUSION: This study indicates that cortical EI and PI are useful US parameters for evaluating renal allograft function and e-GFR combined with PI may provide a more accurate predictor of survival.

Shear wave elastography parameters adds prognostic value to adverse outcome in kidney transplantation recipients.

INTRODUCTION: The tissue stiffness of donor kidneys in transplantation may increase due to pathological changes such as glomerulosclerosis and interstitial fibrosis, and those changes associate worse outcomes in kidney transplantation recipients. Ultrasound elastography is a noninvasive imaging examination with the ability to quantitatively reflect tissue stiffness. Aim of this study was to evaluate the prognostic value of ultrasound elastography for adverse kidney outcome in kidney transplantation recipients. METHODS: Shear wave elastography (SWE) examinations were performed by two independent operators in kidney transplantation recipients. The primary outcome was a composite of kidney graft deterioration, all-cause re-hospitalization, and all-cause mortality. Survival analysis was calculated by Kaplan-Meier curves with the log-rank test and Cox regression analysis. RESULTS: A total of 161 patients (mean age 46 years, 63.4% men) were followed for a median of 20.1 months. 27 patients (16.77%) reached the primary endpoint. The mean and median tissue stiffness at the medulla (hazard ratio: 1.265 and 1.229, respectively), estimated glomerular filtration rate (eGFR), and serum albumin level were associated with the primary outcome in univariate Cox regression. Adding mean or median medulla SWE to a baseline model containing eGFR and albumin significantly improved its discrimination (C-statistics: 0.736 for the baseline, 0.766 and 0.772 for the model added mean and median medulla SWE, respectively). CONCLUSION: The medullary tissue stiffness of kidney allograft measured by shear wave elastography may provide incremental prognostic value to adverse outcomes in kidney transplantation recipients. Including SWE parameters in kidney transplantation recipients management could be considered to improve risk stratification.

The effects of metals and mixture exposure on lung function and the potential mediating effects of oxidative stress.

Exposure to metals is associated with lung function decline. However, limited data are available about effects of co-exposure of metals on lung function. Additionally, the mechanism of the association between metals and lung function remains unclear. We conducted a longitudinal panel study in 2017-2018 among 45 healthy college students. Urinary 15 metals, lung function, biomarkers of oxidative stress and inflammation of participants were measured. Linear mixed effect (LME) and Bayesian kernel machine regression (BKMR) models were applied to explore the associations of urinary metals and mixture with lung function. Furthermore, we analyzed the mediating effect of biomarkers in the association between urinary metals and lung function. LME models showed the negative associations of aluminum (Al), vanadium (V), manganese (Mn), cobalt (Co), nickel (Ni), cadmium (Cd) or antimony (Sb) with Forced vital capacity (FVC), and V, Co, Ni, and Sb with Forced expiratory volume in one second (FEV1). BKMR models indicated the overall effect of metals mixture was negatively associated with FEV1 and FVC; urinary Sb was identified as the major contributor to decreased FVC and FEV1. Urinary 8-hydroxydeoxyguanosine mediated the association of Al, Mn, or Sb with FVC and the relationship of V with FEV1. The results revealed the longitudinal dose-response relationships of urinary metals with pulmonary function among healthy adults. Oxidative stress may be the underlying mechanisms of metals exposure associated with decreased lung function. Due to the small sample size, the interpretation of the results of this study should be cautious, and more studies are needed to verify the findings of this study.

Long-term exercise training down-regulates m6A RNA demethylase FTO expression in the hippocampus and hypothalamus: an effective intervention for epigenetic modification.

BACKGROUND: Exercise boosts the health of some brain parts, such as the hippocampus and hypothalamus. Several studies show that long-term exercise improves spatial learning and memory, enhances hypothalamic leptin sensitivity, and regulates energy balance. However, the effect of exercise on the hippocampus and hypothalamus is not fully understood. The study aimed to find epigenetic modifications or changes in gene expression of the hippocampus and hypothalamus due to exercise. METHODS: Male C57BL/6 mice were randomly divided into sedentary and exercise groups. All mice in the exercise group were subjected to treadmill exercise 5 days per week for 1 h each day. After the 12-week exercise intervention, the hippocampus and hypothalamus tissue were used for RNA-sequencing or molecular biology experiments. RESULTS: In both groups, numerous differentially expressed genes of the hippocampus (up-regulated: 53, down-regulated: 49) and hypothalamus (up-regulated: 24, down-regulated: 40) were observed. In the exercise group, increased level of N6-methyladenosine (m6A) was observed in the hippocampus and hypothalamus (p < 0.05). Furthermore, the fat mass and obesity-associated gene (FTO) of the hippocampus and hypothalamus were down-regulated in the exercise group (p < 0.001). In addition, the Fto co-expression genes of the mouse brain were studied and analyzed using database to determine the potential roles of exercise-downregulated FTO in the brain. CONCLUSION: The findings demonstrate that long-term exercise might elevates the levels of m6A-tagged transcripts in the hippocampus and hypothalamus via down-regulation of FTO. Hence, exercise might be an effective intervention for epigenetic modification.

The Kelch-F-box protein SMALL AND GLOSSY LEAVES 1 (SAGL1) negatively influences salicylic acid biosynthesis in Arabidopsis thaliana by promoting the turn-over of transcription factor SYSTEMIC ACQUIRED RESISTANCE DEFICIENT 1 (SARD1).

Salicylic acid (SA) is a key phytohormone regulating plant immunity. Although the transcriptional regulation of SA biosynthesis has been well-studied, its post-translational regulation is largely unknown. We report that a Kelch repeats-containing F-box (KFB) protein, SMALL AND GLOSSY LEAVES 1 (SAGL1), negatively influences SA biosynthesis in Arabidopsis thaliana by mediating the proteolytic turnover of SYSTEMIC ACQUIRED RESISTANCE DEFICIENT 1 (SARD1), a master transcription factor that directly drives SA biosynthesis during immunity. Loss of SAGL1 resulted in characteristic growth inhibition. Combining metabolomic, transcriptional and phenotypic analyses, we found that SAGL1 represses SA biosynthesis and SA-mediated immune activation. Genetic crosses to mutants that are deficient in SA biosynthesis blocked the SA overaccumulation in sagl1 and rescued its growth. Biochemical and proteomic analysis identified that SAGL1 interacts with SARD1 and promotes the degradation of SARD1 in a proteasome-dependent manner. These results unravelled a critical role of KFB protein SAGL1 in maintaining SA homeostasis via controlling SARD1 stability.

HSF-1 mediated combined ginsenosides ameliorating Alzheimer's disease like symptoms in Caernorhabditis elegans.

There are few effective medications to treat Alzheimer's disease (AD). It has been suggested that several ginsenosides possess mild or moderate anti-AD activity. In our present work, a preferred combined ginsenosides was shown to have a more significant benefit effect on AD-like symptoms of worm paralysis and hypersensitivity to exogenous 5-HT in C. elegans. The combined ginsenosides can suppress Aß deposits and Aß oligomers, alleviating the toxicity induced by Aß overexpression more effectively than used alone. Its anti-AD effect was partially abolished by hsf-1 RNAi knocked down or hsf-1 inactivation by point mutation, but not by daf-16 or skn-1 RNAi knocked down. Furthermore, it markedly activated hsp-16.2 gene expression downstream of HSF-1. Our results demonstrated that HSF-1 signaling pathway exerts an important role in mediating the therapeutic effect of combined ginsenosides on AD worms. These results provided powerful evidences and theoretical foundation for reshaping medicinal products of ginsenosides and ginseng on prevention of neurodegenerative diseases.

Combined effects of exposure to polycyclic aromatic hydrocarbons and metals on oxidative stress among healthy adults in Caofeidian, China.

Exposure to polycyclic aromatic hydrocarbons (PAHs) and metals is associated with many adverse effects on human health, accompanied by oxidative stress. This study aimed to investigate the effects of co-exposure to PAHs and metals on oxidative stress in healthy adults. A preliminary longitudinal panel study was conducted between 2017 and 2018 in 45 healthy college students in Caofeidian, China. Six urinary monohydroxylated-PAHs (OH-PAHs), ten metals, 8-hydroxydeoxyguanosine (8-OHdG), and 8-iso-prostaglandin-F2α (8-iso-PGF2α) were measured. Linear mixed effects (LME) models and Bayesian kernel machine regression (BKMR) models were used to explore the associations of urinary OH-PAHs and metals with 8-OHdG and 8-iso-PGF2α. LME models showed that most urinary OH-PAHs and metals were positively associated with 8-OHdG and 8-iso-PGF2α. For example, a one-unit increase in the ln-transformed level of 1-hydroxypyrene (1-OHPyr) and vanadium (V) was associated with an increase of 143.8% (95% CI: 105.7 - 188.9%) and 105.8% (95% CI: 79.2-136.4%) in 8-OHdG; 8-iso-PGF2α increased by 118.9% (95% CI: 99.2-140.5%) and 83.9% (95% CI: 67.2-102.2%) with a one-unit increase in the ln-transformed level of 3-hydroxyphenanthrene (3-OHPhe) and aluminum (Al). BKMR models indicated the overall positive associations of the mixture of six OH-PAHs, ten metals, or six OH-PAHs and ten metals with 8-OHdG and 8-iso-PGF2α. Urinary 1-OHPyr and V were identified as the major contributors to the increased urinary 8-OHdG levels, while urinary 3-OHPhe and Al were the most vital contributors to the increased urinary 8-iso-PGF2α levels. The results revealed the longitudinal dose-response relationships of urinary OH-PAHs and metals with oxidative stress among healthy adults in Caofeidian; this finding serves as an evidence regarding the early health hazard caused by exposure to PAHs and metals and has implications for the environmental management of PAH and metal emissions in this area.

Elastography ultrasound with machine learning improves the diagnostic performance of traditional ultrasound in predicting kidney fibrosis.

BACKGROUND: Noninvasively predicting kidney tubulointerstitial fibrosis is important because it's closely correlated with the development and prognosis of chronic kidney disease (CKD). Most studies of shear wave elastography (SWE) in CKD were limited to non-linear statistical dependencies and didn't fully consider variables' interactions. Therefore, support vector machine (SVM) of machine learning was used to assess the prediction value of SWE and traditional ultrasound techniques in kidney fibrosis. METHODS: We consecutively recruited 117 CKD patients with kidney biopsy. SWE, B-mode, color Doppler flow imaging ultrasound and hematological exams were performed on the day of kidney biopsy. Kidney tubulointerstitial fibrosis was graded by semi-quantification of Masson staining. The diagnostic performances were accessed by ROC analysis. RESULTS: Tubulointerstitial fibrosis area was significantly correlated with eGFR among CKD patients (R = 0.450, P < 0.001). AUC of SWE, combined with B-mode and blood flow ultrasound by SVM, was 0.8303 (sensitivity, 77.19%; specificity, 71.67%) for diagnosing tubulointerstitial fibrosis (>10%), higher than either traditional ultrasound, or SWE (AUC, 0.6735 [sensitivity, 67.74%; specificity, 65.45%]; 0.5391 [sensitivity, 55.56%; specificity, 53.33%] respectively. Delong test, p < 0.05); For diagnosing different grades of tubulointerstitial fibrosis, SWE combined with traditional ultrasound by SVM, had AUCs of 0.6429 for mild tubulointerstitial fibrosis (11%-25%), and 0.9431 for moderate to severe tubulointerstitial fibrosis (>50%), higher than other methods (Delong test, p < 0.05). CONCLUSION: SWE with SVM modeling could improve the diagnostic performance of traditional kidney ultrasound in predicting different kidney tubulointerstitial fibrosis grades among CKD patients.

Exercise suppresses NLRP3 inflammasome activation in mice with diet-induced NASH: a plausible role of adropin.

NLRP3 inflammasome activation, which can be triggered by reactive oxygen species (ROS), contributes to nonalcoholic steatohepatitis (NASH) progression. Exercise is an effective therapeutic strategy for NASH. However, whether exercise prevents NLRP3 activation in NASH has not been investigated. Here, we investigated the effect of exercise on NLRP3 inflammasome in mice with high-fat diet (HFD)-induced or methionine and choine-deficient (MCD) diet-induced NASH and explored whether adropin, a metabolic peptide hormone shown to inhibit inflammation, mediates an exercise-induced benefit against NLRP3 inflammasome activation. Exercise alleviated diet-induced hepatic steatosis, inflammation, and fibrosis. Importantly, exercise significantly reduced the expression of NLRP3 inflammasome components, decreased Caspase-1 enzymatic activity, normalized IL-1ß production, and suppressed ROS overproduction in HFD-fed and MCD diet-fed mice. The exercise-elicited NLRP3 inflammasome inhibition was accompanied by increased adropin levels. Moreover, serum adropin levels were negatively correlated with serum IL-1ß levels. We further explored the effect of adropin on the NLRP3 inflammasome in palmitic acid (PA)-treated hepatocytes and Kupffer cells. Although adropin treatment did not significantly decrease the levels of all inflammasome components, it reduced the active Caspase-1 level, decreased Caspase-1 activity and downregulated IL-1ß expression in hepatocytes and Kupffer cells (KCs) treated with PA. Moreover, ROS levels in PA-stimulated hepatocytes and Kupffer cells were reduced upon adropin treatment. In summary, we demonstrated that the inhibitory effect of exercise on NLRP3 inflammasome activation was associated with adropin induction, resulting in NASH improvement.

Multi-omic dissection of the drought resistance traits of soybean landrace LX.

With diverse genetic backgrounds, soybean landraces are valuable resource for breeding programs. Herein, we apply multi-omic approaches to extensively characterize the molecular basis of drought tolerance in the soybean landrace LX. Initial screens established that LX performed better with PEG6000 treatment than control cultivars. LX germinated better than William 82 under drought conditions and accumulated more anthocyanin and flavonoids. Untargeted mass spectrometry in combination with transcriptomic analyses revealed the chemical diversity and genetic basis underlying the overall performance of LX landrace. Under control and drought conditions, significant differences in the expression of a suite of secondary metabolism genes, particularly those involved in the general phenylpropanoid pathway and flavonoid but not lignin biosynthesis, were seen in LX and William 82. The expression of these genes correlated with the corresponding metabolites in LX plants. Further correlation analysis between metabolites and transcripts identified pathway structural genes and transcription factors likely are responsible for the LX agronomic traits. The activities of some key biosynthetic genes or regulators were confirmed through heterologous expression in transgenic Arabidopsis and hairy root transformation in soybean. We propose a regulatory mechanism based on flavonoid secondary metabolism and adaptive traits of this landrace which could be of relevance to cultivated soybean.

Multiband Superconductivity with Sign-Preserving Order Parameter in Kagome Superconductor CsV_{3}Sb_{5}.

The superconductivity of a kagome superconductor CsV_{3}Sb_{5} is studied by scanning tunneling microscopy and spectroscopy at ultralow temperature with high resolution. Two kinds of superconducting gaps with multiple sets of coherent peaks and residual zero-energy density of states (DOS) are observed on both half-Cs and Sb surfaces, implying multiband superconductivity. In addition, in-gap states can be induced by magnetic impurities but not by nonmagnetic impurities, suggesting a sign-preserving or s-wave superconducting order parameter. Moreover, the interplay between charge density waves (CDW) and superconductivity differs on various bands, resulting in different density-of-states distributions. Our results suggest that the superconducting gap is likely isotropic on the sections of Fermi surface that play little roles in CDW, and the superconducting gaps on the sections of Fermi surface with anisotropic CDW gaps are likely anisotropic as well. The residual spectral weights at zero energy are attributed to the extremely small superconducting gap on the tiny oval Fermi pockets. Our study provides critical clues for further understanding the superconductivity and its relation to CDW in CsV_{3}Sb_{5}.

Adropin regulates hepatic glucose production via PP2A/AMPK pathway in insulin-resistant hepatocytes.

Adropin as a secretory peptide has shown a protective role on the disorders of glucose and lipid metabolism. However, the role and mechanism of this peptide on the hepatic glucose production has remained unclear. Adropin knockout (KO) mice were generated to explore its effects on the enhanced hepatic glucose production in obesity. We found that compared to wild-type (WT) mice, adropin-KO mice developed the unbalanced enhanced hepatic glucose production in advance of the whole-body insulin resistance (IR) by high-fat diet (HFD). Mechanistically, adropin dissociated CREB-CRTC2 and FoxO1-PGC1α complex and reduced their binding to the promoters of G6Pase and PEPCK to decrease glucose production in IR. However, these effects were not observed in insulin-sensitive hepatocytes. Furthermore, in IR hepatocytes, dampened AMPK signaling was re-activated by adropin treatment via inhibition of PP2A. To further authenticate AMPK role in vivo, we administrated HFD-fed mice with AAV8-CA AMPKα and found that AMPK activation functionally restored the aberrant glucose production and IR induced by adropin-deficiency. This study provides evidence that adropin activates the AMPK pathway via inhibition of PP2A and decreases the liver glucose production in IR context. Therefore, adropin may represent a novel target for the prevention and treatment of diabetes.