Association of mental disorders with sepsis: a bidirectional Mendelian randomization study.

Background: Substantial research evidence supports the correlation between mental disorders and sepsis. Nevertheless, the causal connection between a particular psychological disorder and sepsis remains unclear. Methods: For investigating the causal relationships between mental disorders and sepsis, genetic variants correlated with mental disorders, including anorexia nervosa (AN), attention-deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), major depressive disorder (MDD), obsessive-compulsive disorder (OCD), panic disorder (PD), posttraumatic stress disorder (PTSD), schizophrenia (SCZ), and tourette syndrome (TS), were all extracted from the Psychiatric Genomics Consortium (PGC). The causal estimates and direction between these mental disorders and sepsis were evaluated employing a two-sample bidirectional MR strategy. The inverse variance weighted (IVW) method was the primary approach utilized. Various sensitivity analyses were performed to confirm the validity of the causal effect. Meta-analysis, multivariable MR, and mediation MR were conducted to ensure the credibility and depth of this research. Results: The presence of AN was in relation to a greater likelihood of sepsis (OR 1.08, 95% CI 1.02-1.14; p = 0.013). A meta-analysis including validation cohorts supported this observation (OR 1.06, 95% CI 1.02-1.09). None of the investigated mental disorders appeared to be impacted when sepsis was set as the exposure factor. Even after adjusting for confounding factors, AN remained statistically significant (OR 1.08, 95% CI 1.02-1.15; p = 0.013). Mediation analysis indicated N-formylmethionine levels (with a mediated proportion of 7.47%), cystatin D levels (2.97%), ketogluconate Metabolism (17.41%) and N10-formyl-tetrahydrofolate biosynthesis (20.06%) might serve as mediators in the pathogenesis of AN-sepsis. Conclusion: At the gene prediction level, two-sample bidirectional MR analysis revealed that mental disorder AN had a causal association with an increased likelihood of sepsis. In addition, N-formylmethionine levels, cystatin D levels, ketogluconate metabolism and N10-formyl-tetrahydrofolate biosynthesis may function as potential mediators in the pathophysiology of AN-sepsis. Our research may contribute to the investigation of novel therapeutic strategies for mental illness and sepsis.

Formaldehyde-Mediated Hydride Liberation of Alkylamines for Intermolecular Reactions in Hexafluoroisopropanol.

The ability of alkylamines to spontaneously liberate hydride ions is typically restrained, except under specific intramolecular reaction settings. Herein, we demonstrate that this reactivity can be unlocked through simple treatment with formaldehyde in hexafluoroisopropanol (HFIP) solvent, thereby enabling various intermolecular hydride transfer reactions of alkylamines under mild conditions. Besides transformations of small molecules, these reactions enable unique late-stage modification of complex peptides. Mechanistic investigations uncover that the key to these intermolecular hydride transfer processes lies in the accommodating conformation of solvent-mediated macrocyclic transition states, where the aggregates of HFIP molecules act as dexterous proton shuttles. Importantly, negative hyperconjugation between the lone electron pair of nitrogen and the antibonding orbital of amine's α C-H bond plays a critical role in the C-H activation, promoting its hydride liberation.

Novel Autophagy-Related Blood Biomarkers Associated with Immune Cell Infiltration in Ankylosing Spondylitis.

Background: This study aims to identify new therapeutic targets and explore the molecular mechanism of ankylosing spondylitis (AS), a rheumatic immune disease that mainly affects the sacroiliac and spinal joints. Despite extensive research, the exact cause of AS is still unknown. The research team utilized a bioinformatics approach to achieve their objectives. Methods: The GSE73754 dataset was downloaded from GEO database. Autophagy-related genes (ARGs) were collected from the Human Autophagy-dedicated Database. The limma package was used to screen for differentially expressed genes (DEGs), which were then intersected with the autophagy-related genes (ARGs) to identify differentially expressed autophagy-related genes (DEARGs). Subsequently, the DEARGs associated with AS were subjected to GO-BP and KEGG enrichment analyses using the clusterProfiler package. Core genes were identified using the cytoHubba plug-in of Cytoscape and were validated by clinical blood samples. Additionally, the Cell algorithm was utilized to evaluate the proportion of immune cell infiltration. Results: A total of 29 DEARGs were identified, which were found to be mainly enriched in autophagy, apoptosis, and necroptosis through functional enrichment analysis. Two core genes, HSPA5 and SQSTM1, were confirmed to have diagnostic value in AS. Immune cell infiltration analysis revealed CD8+ T cells, CD8+ T effector memory (Tem), natural killer (NK) cells, T gamma delta (Tgd) cells, and T-helper 1 (Th1) cells as major participants in AS development. Furthermore, HSPA5 expression was significantly correlated with Th1 cells, CD8+ T cells, CD4+ memory cells, and macrophages. Conclusion: This study suggested that HSPA5 and SQSTM1 can serve as useful diagnostic biomarkers for AS. These findings lay the foundation for identifying crucial mRNAs in the whole blood of AS patients, which may aid in the development of novel markers for AS.

Elucidation of the Key Therapeutic Targets and Potential Mechanisms of Marmesine against Knee Osteoarthritis via Network Pharmacological Analysis and Molecular Docking.

Background: Marmesine, a major active ingredient isolated from Radix Angelicae biseratae (Duhuo), has been reported to have multiple pharmacological activities. However, its therapeutic effects against knee osteoarthritis (OA) remain poorly investigated. The present study is aimed at uncovering the core targets and signaling pathways of marmesine against osteoarthritis using a combined method of bioinformatics and network pharmacology. Methods: We utilized SwissTargetPrediction and PharmMapper to collect the potential targets of marmesine. OA-related differentially expressed genes (DEGs) were identified from GSE98918 dataset. Then, the intersection genes between DEGs and candidate genes of marmesine were subjected to protein-protein interaction (PPI) network construction and functional enrichment analysis. The core targets were verified using the molecular docking technology. Results: A total of 320 marmesine-related genes and 5649 DEGs and 60 ingredient-disease targets between them were identified. The results of functional enrichment analyses revealed that response to oxygen levels, neuroinflammatory response, PI3K-Akt signaling pathway, MAPK signaling pathway, FoxO signaling pathway, and osteoclast differentiation was identified as the potential mechanisms of marmesine against OA. EGFR, CASP3, MMP9, PPARG, and MAPK1 served as hub genes regulated by marmesine in the treatment of OA, and the molecular docking further verified the results. Conclusion: Marmesine exerts the therapeutic effects against OA through multitarget and multipathways, in which EGFR, CASP3, MMP9, PPARG, and MAPK1 might be hub genes. Our research indicated that the combination of bioinformatics and network pharmacology could serve as an effective approach for investigating the potential mechanisms of natural product.

Non-Destructive Testing of Carbon Fibre Reinforced Plastics (CFRP) Using a Dual Transmitter-Receiver Differential Eddy Current Test Probe.

Transmitter-receiver (T-R) probes are widely used in the eddy-current testing of carbon fibre reinforced plastics (CFRP). However, T-R probes have the disadvantage of being highly sensitive to lift-off. On this basis, lift-off interference can be eliminated by differential structure. However, due to the electrical anisotropy of CFRP, the detection sensitivity of the side-by-side T-R probe and traditional R-T-R differential probe are greatly affected by the scanning angle, and the probe often needs to scan the sample along a specific path to achieve the ideal required detection effect. To solve these problems, a symmetrical dual-transmit-dual-receive (TR-TR) differential probe is designed in this paper. The detection performance of the TR-TR probe was verified by simulation and experiments. Results show that the TR-TR probe is less affected by the scanning angle and lift-off when used in CFRP defect detection, and has high detection sensitivity. However, the imaging results of the TR-TR probe do not show the defect characteristics straightforwardly. To solve this problem, a defect feature extraction algorithm is proposed in this paper. The results show that the defect feature extraction algorithm can locate and size the defect more accurately and improve the signal-to-noise ratio.

Harnessing Natural Products by a Pharmacophore-Oriented Semisynthesis Approach for the Discovery of Potential Anti-SARS-CoV-2 Agents.

Natural products possessing unique scaffolds may have antiviral activity but their complex structures hinder facile synthesis. A pharmacophore-oriented semisynthesis approach was applied to (-)-maoelactone A (1) and oridonin (2) for the discovery of anti-SARS-CoV-2 agents. The Wolff rearrangement/lactonization cascade (WRLC) reaction was developed to construct the unprecedented maoelactone-type scaffold during semisynthesis of 1. Further mechanistic study suggested a concerted mechanism for Wolff rearrangement and a water-assisted stepwise process for lactonization. The WRLC reaction then enabled the creation of a novel family by assembly of the maoelactone-type scaffold and the pharmacophore of 2, whereby one derivative inhibited SARS-CoV-2 replication in HPA EpiC cells with a low EC50 value (19±1 nM) and a high TI value (>1000), both values better than those of remdesivir.

Complementary and Alternative Medicine for Dysmenorrhea Caused by Endometriosis: A Review of Utilization and Mechanism.

Endometriosis (EM) is a common and benign estrogen-dependent gynecological disorder among women of reproductive age, and secondary dysmenorrhea is one of the more severe symptoms. However, the mechanism behind the development of dysmenorrhea is poorly understood, and there is a lack of effective methods for diagnosing and treating EM dysmenorrhea. In this regard, complementary and alternative medicine (CAM) has recently come into widespread use due to its limited adverse reactions and high efficiency. This review updates the progress of CAM in the treatment of EM dysmenorrhea and seeks to identify the therapeutic efficacy as well as the mechanisms behind these effects based on the available clinical and experimental studies. According to the literature, CAM therapy for EM dysmenorrhea, including herbs (herbal prescriptions, extracts, and patents), acupuncture, and Chinese herbal medicine enema (CHM enema), is effective for relieving dysmenorrhea with fewer unpleasant side effects when compared to hormonal and surgical treatments. In addition, we discuss and analyze the existing gaps in the literature. We hope to provide some instructive suggestions for clinical treatment and experimental research in the future.

Centuries of monthly and 3-hourly global ocean wave data for past, present, and future climate research.

Ocean surface waves are essential to navigation safety, coastal activities, and climate systems. Numerical simulations are still the primary methods used in wave climate research, especially in future climate change scenarios. Recently, First Institute of Oceanography-Earth System Model version 2.0 (FIO-ESM v2.0), a global climate model coupled with an ocean wave model, was carried out the Coupled Model Intercomparison Project phase 6 (CMIP6) experiments. Here, we present the global monthly-mean and 3-hourly instantaneous wave parameter dataset from the FIO-ESM v2.0 CMIP6 experiments, including 700-year piControl, 165-year historical, three 86-year future scenarios (ssp125, ssp245, and ssp585, respectively), and two 150-year climate sensitive experiments (1pctCO2 and abrupt-4xCO2) simulations. Historical results show that the model can capture the basic wave climate features under climate change. These unique centuries of global wave data are from a fully coupled system and can provide the community with a vital long-term data source for scientific and engineering applications, such as wave climate research, wave-related process studies and parameterizations, as well as coastal and near-shore industry designs.