Effects of Succinate on Growth Performance, Meat Quality and Lipid Synthesis in Bama Miniature Pigs.

Succinate, one of the intermediates of the tricarboxylic acid cycle, is now recognized to play a role in a broad range of physiological and pathophysiological settings, but its role in adipogenesis is unclear. Our study used Bama miniature pigs as a model to explore the effects of succinate on performance, meat quality, and fat formation. The results showed that adding 1% succinate significantly increased the average daily gain, feed/gain ratio, eye muscle area, and body fat content (p < 0.05), but had no effect on feed intake. Further meat quality analysis showed that succinate increased the marbling score and intramuscular fat content of longissimus dorsi muscle (LM), while decreasing the shear force and the cross-sectional area of LM (p < 0.05). Metabolomics analysis of LM revealed that succinate reshaped levels of fatty acids, triglycerides, glycerophospholipids, and sphingolipids in LM. Succinate promotes adipogenic differentiation in porcine primary preadipocytes. Finally, dietary succinate supplementation increased succinylation modification rather than acetylation modification in the adipose tissue pool. This study elucidated the effects of succinate on the growth and meat quality of pigs and its mechanism of action and provided a reference for the role of succinate in the nutrition and metabolism of pigs.

Development and application of a deep learning-based comprehensive early diagnostic model for chronic obstructive pulmonary disease.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a frequently diagnosed yet treatable condition, provided it is identified early and managed effectively. This study aims to develop an advanced COPD diagnostic model by integrating deep learning and radiomics features. METHODS: We utilized a dataset comprising CT images from 2,983 participants, of which 2,317 participants also provided epidemiological data through questionnaires. Deep learning features were extracted using a Variational Autoencoder, and radiomics features were obtained using the PyRadiomics package. Multi-Layer Perceptrons were used to construct models based on deep learning and radiomics features independently, as well as a fusion model integrating both. Subsequently, epidemiological questionnaire data were incorporated to establish a more comprehensive model. The diagnostic performance of standalone models, the fusion model and the comprehensive model was evaluated and compared using metrics including accuracy, precision, recall, F1-score, Brier score, receiver operating characteristic curves, and area under the curve (AUC). RESULTS: The fusion model exhibited outstanding performance with an AUC of 0.952, surpassing the standalone models based solely on deep learning features (AUC = 0.844) or radiomics features (AUC = 0.944). Notably, the comprehensive model, incorporating deep learning features, radiomics features, and questionnaire variables demonstrated the highest diagnostic performance among all models, yielding an AUC of 0.971. CONCLUSION: We developed and implemented a data fusion strategy to construct a state-of-the-art COPD diagnostic model integrating deep learning features, radiomics features, and questionnaire variables. Our data fusion strategy proved effective, and the model can be easily deployed in clinical settings. TRIAL REGISTRATION: Not applicable. This study is NOT a clinical trial, it does not report the results of a health care intervention on human participants.

Evaluation of G3BP1 in the prognosis of acute and acute-on-chronic liver failure after the treatment of artificial liver support system.

BACKGROUND: The increased expression of G3BP1 was positively correlated with the prognosis of liver failure. AIM: To investigate the effect of G3BP1 on the prognosis of acute liver failure (ALF) and acute-on-chronic liver failure (ACLF) after the treatment of artificial liver support system (ALSS). METHODS: A total of 244 patients with ALF and ACLF were enrolled in this study. The levels of G3BP1 on admission and at discharge were detected. The validation set of 514 patients was collected to verify the predicted effect of G3BP1 and the viability of prognosis. RESULTS: This study was shown that lactate dehydrogenase (LDH), alpha-fetoprotein (AFP) and prothrombin time were closely related to the prognosis of patients. After the ALSS treatment, the patient' amount of decreased G3BP1 index in difference of G3BP1 between the value of discharge and admission (difG3BP1) < 0 group had a nearly 10-fold increased risk of progression compared with the amount of increased G3BP1 index. The subgroup analysis showed that the difG3BP1 < 0 group had a higher risk of progression, regardless of model for end-stage liver disease high-risk or low-risk group. At the same time, compared with the inflammatory marks [tumor necrosis factor-α, interleukin (IL)-1ß and IL-18], G3BP1 had higher discrimination and was more stable in the model analysis and validation set. When combined with AFP and LDH, concordance index was respectively 0.84 and 0.8 in training and validation cohorts. CONCLUSION: This study indicated that G3BP1 could predict the prognosis of ALF or ACLF patients treated with ALSS. The combination of G3BP1, AFP and LDH could accurately evaluate the disease condition and predict the clinical endpoint of patients.

Function and mechanism of exosomes derived from different cells as communication mediators in colorectal cancer metastasis.

Colorectal cancer (CRC) ranks as the second leading cause of cancer-related mortality, with metastasis being the primary determinant of poor prognosis in patients. Investigating the molecular mechanisms underlying CRC metastasis is currently a prominent and challenging area of research. Exosomes, as crucial intercellular communication mediators, facilitate the transfer of metabolic and genetic information from cells of origin to recipient cells. Their roles in mediating information exchange between CRC cells and immune cells, fibroblasts, and other cell types are pivotal in reshaping the tumor microenvironment, regulating key biological processes such as invasion, migration, and formation of pre-metastatic niche. This article comprehensively examines the communication function and mechanism of exosomes derived from different cells in cancer metastasis, while also presenting an outlook on current research advancements and future application prospects. The aim is to offer a distinctive perspective that contributes to accurate diagnosis and rational treatment strategies for CRC.

Blood urea nitrogen to serum albumin ratio: a novel mortality indicator in intensive care unit patients with coronary heart disease.

The blood urea nitrogen to albumin ratio (BAR) has been demonstrated as a prognostic factor in sepsis and respiratory diseases, yet its role in severe coronary heart disease (CHD) remains unexplored. This retrospective study, utilizing data from the Medical Information Mart for Intensive Care-IV database, included 4254 CHD patients, predominantly male (63.54%), with a median age of 74 years (IQR 64-83). Primary outcomes included in-hospital, 28-day and 1-year all-cause mortality after ICU admission. The Kaplan-Meier curves, Cox regression analysis, multivariable restricted cubic spline regression were employed to assess association between BAR index and mortality. In-hospital, within 28-day and 1-year mortality rates were 16.93%, 20.76% and 38.11%, respectively. Multivariable Cox proportional hazards analysis revealed associations between the increased BAR index and higher in-hospital mortality (HR 1.11, 95% CI 1.02-1.21), 28-day mortality (HR 1.17, 95% CI 1.08-1.27) and 1-year mortality (HR 1.23, 95% CI 1.16-1.31). Non-linear relationships were observed for 28-day and 1-year mortality with increasing BAR index (both P for non-linearity < 0.05). Elevated BAR index was a predictor for mortality in ICU patients with CHD, offering potential value for early high-risk patient identification and proactive management by clinicians.

Constructing a Nomogram Model to Estimate the Risk of Ventilator-Associated Pneumonia for Elderly Patients in the Intensive Care Unit.

BACKGROUND: Ventilator-associated pneumonia (VAP) causes heavy losses in terms of finances, hospitalization, and death for elderly patients in the intensive care unit (ICU); however, the risk is difficult to evaluate due to a lack of reliable assessment tools. We aimed to create and validate a nomogram to estimate VAP risk to provide early intervention for high-risk patients. METHODS: Between January 2016 and March 2021, 293 patients from a tertiary hospital in China were retrospectively reviewed as a training set. Another 84 patients were enrolled for model validation from April 2021 to February 2022. Least absolute shrinkage and selection operator (LASSO) regression and multivariable logistic regression analysis were employed to select predictors, and a nomogram model was constructed. The calibration, discrimination, and clinical utility of the nomogram were verified. Finally, a web-based online scoring system was created to make the model more practical. RESULTS: The predictors were hypoproteinemia, long-term combined antibiotic use, intubation time, length of mechanical ventilation, and tracheotomy/intubation. The area under the curve (AUC) was 0.937 and 0.925 in the training and validation dataset, respectively, suggesting the model exhibited effective discrimination. The calibration curve demonstrated high consistency with the observed result and the estimated values. Decision curve analysis (DCA) demonstrated that the nomogram was clinically applicable. CONCLUSIONS: We have created a novel nomogram model that can be utilized to anticipate VAP risk in elderly ICU patients, which is helpful for healthcare professionals to detect patients at high risk early and adopt protective interventions.

A Fully Automated Mini-Mental State Examination Assessment Model Using Computer Algorithms for Cognitive Screening.

Background: Rapidly growing healthcare demand associated with global population aging has spurred the development of new digital tools for the assessment of cognitive performance in older adults. Objective: To develop a fully automated Mini-Mental State Examination (MMSE) assessment model and validate the model's rating consistency. Methods: The Automated Assessment Model for MMSE (AAM-MMSE) was an about 10-min computerized cognitive screening tool containing the same questions as the traditional paper-based Chinese MMSE. The validity of the AAM-MMSE was assessed in term of the consistency between the AAM-MMSE rating and physician rating. Results: A total of 427 participants were recruited for this study. The average age of these participants was 60.6 years old (ranging from 19 to 104 years old). According to the intraclass correlation coefficient (ICC), the interrater reliability between physicians and the AAM-MMSE for the full MMSE scale AAM-MMSE was high [ICC (2,1)=0.952; with its 95% CI of (0.883,0.974)]. According to the weighted kappa coefficients results the interrater agreement level for audio-related items showed high, but for items "Reading and obey", "Three-stage command", and "Writing complete sentence" were slight to fair. The AAM-MMSE rating accuracy was 87%. A Bland-Altman plot showed that the bias between the two total scores was 1.48 points with the upper and lower limits of agreement equal to 6.23 points and -3.26 points. Conclusions: Our work offers a promising fully automated MMSE assessment system for cognitive screening with pretty good accuracy.

Design of pH-responsive antimicrobial peptide melittin analog-camptothecin conjugates for tumor therapy.

Melittin, a classical antimicrobial peptide, is a highly potent antitumor agent. However, its significant toxicity seriously hampers its application in tumor therapy. In this study, we developed novel melittin analogs with pH-responsive, cell-penetrating and membrane-lytic activities by replacing arginine and lysine with histidine. After conjugation with camptothecin (CPT), CPT-AAM-1 and CPT-AAM-2 were capable of killing tumor cells by releasing CPT at low concentrations and disrupting cell membranes at high concentrations under acidic conditions. Notably, we found that the C-terminus of the melittin analogs was more suitable for drug conjugation than the N-terminus. CPT-AAM-1 significantly suppressed melanoma growth in vivo with relatively low toxicity. Collectively, the present study demonstrates that the development of antitumor drugs based on pH-responsive antimicrobial peptide-drug conjugates is a promising strategy.

Effect of lipopolysaccharide on TAK1-mediated hepatocyte PANoptosis through Toll-like receptor 4 during acute liver failure.

BACKGROUND: Intestinal endotoxemia (IETM) is an important pathogenic mechanism of acute liver failure (ALF), and TAK1-mediated PANoptosis is a novel cell death mode. This study investigated whether IETM can induce hepatocyte PANoptosis during ALF. METHOD: PANoptosis cell and mouse models were generated, and lentiviruses (LVs), adeno-associated viral vectors (AVVs), and small interfering RNAs (siRNAs) were subsequently used to overexpress or knock down TLR and TAK1. Then, the levels of hepatocyte injury, TLR4, TAK1 and PANoptosis were detected via an enzyme-labeling instrument, tissue staining, RT-PCR, western blotting, immunofluorescence, and flow cytometry. RESULTS: The BioGRID database search revealed that TAK1 might interact with TLR4. According to the in vivo experiments, compared with those in ALF mice, liver tissue damage, hepatocyte mortality and PANoptosis in mice in the AAV-TAK1 group were significantly lower, and liver function was significantly improved. According to the in vitro experiments, after promoting the expression of TLR4 in the model group, the degree of cell damage, TLR4 expression and PANoptosis further increased, while the level of TAK1 further decreased. The opposite result was obtained when TLR4 expression was inhibited. The increase in TAK1 expression in the model group reduced the degree of cell damage and PANoptosis, but the level of TLR4 was not significantly changed. In the model group of cells that exhibited TAK1 expression, further promotion of TLR4 expression inhibited the protective effect of TAK1 on cells. In the model group of cells after TAK1 expression was promoted, if the expression of TLR4 was further promoted, the protective effect of TAK1 on cells was inhibited. CONCLUSION: IETM inhibited the expression of TAK1 by binding to TLR4 molecules and promoting hepatocyte PANoptosis during ALF. Promoting TAK1 expression effectively relieved lipopolysaccharide-induced hepatocyte PANoptosis.

Bone mineral density in patients with primary ovarian insufficiency: A systematic review and Meta-Analysis.

INTRODUCTION: Premature menopause is a major complication of primary ovarian insufficiency (POI), and this loss is closely relates to bone mineral density (BMD). Previous research has indicated potential associations between BMD and POI. This study set out to provide the first systematic literature review and meta-analysison account of BMD content among women with POI. METHODS: Studies including women with POI and controls were eligible from PubMed, Embase, Cochrane Library and Web of Science databases (from their inception to April 2022). Two reviewers independently evaluated study eligibility. The meta-analysis was performed using the DerSimonian and Laird random effects model. RESULTS: Ten studies featuring 578 women with POI and 480 controls were selected. BMD content of femur neck (SMD:-0.76; 95 % CI: -1.20 to -0.31; P = 0.0008), the BMD content of nondominating forearm (SMD:-0.67; 95 % CI: -1.15 to -0.18; P = 0.007) were significantly decreased in women with POI. However, no differences were seen in other regions (lumbar spine, total hip, hipneck). DISCUSSION: The results of this study indicate that BMD content altered in patients with primary ovarian insufficiency. An implication of this is the possibility that hormone replacement therapy to minimize the prevalence of fracture morbidity and mortality associated with osteopenia in patients with POI.

Development and validation of a stacking ensemble model for death prediction in the Chinese Longitudinal Healthy Longevity Survey (CLHLS).

OBJECTIVE: This study aimed to develop and validate a mortality risk prediction model for older people based on the Chinese Longitudinal Healthy Longevity Survey using the stacking ensemble strategy. MATERIAL AND METHODS: A total of 12,769 participants aged 65 or more at baseline were included. Ensemble machine learning models were applied to develop a mortality prediction model. We selected three base learners, including logistic regression, eXtreme Gradient Boosting, and Categorical + Boosting, and used logistic regression as the meta-learner. The primary outcome was five-year survival. Variable importance was evaluated by the SHapley Additive exPlanations method. RESULTS: The mean age at baseline was 88, and 57.8 % of participants were women. The CatBoost model performed the best among the three base learners, the area under the receiver operating characteristics curve (AUC) reached 0.8469 (95%CI: 0.8345-0.8593), and the stacking ensemble model further improved the discrimination ability (AUC = 0.8486, 95%CI: 0.8367-0.8612, P = 0.046). Conventional logistic regression had comparable performance (AUC = 0.8470, 95 % CI: 0.8346-0.8595). Older age, higher scores for self-care activities of daily living, being male, higher objective physical performance capacity scores, not undertaking housework, and lower scores on the Mini-Mental State Examination contributed to higher risk. CONCLUSIONS: We successfully constructed and validated a few death risk prediction models for a Chinese population of older adults. While the stacking ensemble approach had the best prediction performance, the improvement over conventional logistic regression was insubstantial.

Transcriptome-wide N6-methyladenosine (m6A) methylation profiling of long non-coding RNAs in ovarian endometriosis.

N6-methyladenosine (m6A) methylation is the most prevalent internal epigenetic posttranscriptional mechanism for regulating mammalian RNA. Despite recent advances in determining the biological functions of m6A methylation, its association with the pathology of ovarian endometriosis remains uncertain. Herein, we performed m6A transcriptome-wide profiling to identify key lncRNAs with m6A modification involved in ovarian endometriosis development by bioinformatics analysis. We found the total m6A level was lower in ovarian endometriosis than in normal endometrium samples, with 9663 m6A peaks associated with 8989 lncRNAs detected in ovarian endometriosis and 9902 m6A peaks associated with 9210 lncRNAs detected in normal endometrium samples. These m6A peaks were primarily enriched within AAACU motifs. Functional enrichment analysis indicated that pathways involving the regulation of adhesion and development were significantly enriched in these differentially methylated lncRNAs. The regulatory relationships among lncRNAs, microRNAs (miRNAs), and mRNAs were identified by competing endogenous RNA (ceRNA) analysis and determination of the network regulating lncRNA-mRNA expression. Several specific lncRNA, including LINC00665, LINC00937, FZD10-AS1, DIO3OS and GATA2-AS1 which were differently expressed and modified by m6A, were validated using qRT-PCR and its interaction with infiltrating immune cells was explored. Furthermore, we found LncRNA DIO3OS promotes the invasion and migration of Human endometrial stromal cells (THESCs) and ALKBH5 regulates the expression of the lncRNA DIO3OS through m6A modification in vitro. Our study firstly revealed the transcriptome-wide map of m6A modification in lncRNAs of ovarian endometriosis. These findings may enable the determination of the underlying mechanism governing the pathogenesis of ovarian endometriosis and provide theoretical basis for further deeper research on the role of m6A in the development of ovarian endometriosis.

The antioxidant strain Lactiplantibacillus plantarum AS21 and Clostridium butyricum ameliorate DSS-induced colitis in mice by remodeling the assembly of intestinal microbiota and improving gut functions.

Probiotics are known for their beneficial effects on improving intestinal function by alleviating the gut microbial diversity. However, the influences of antioxidant lactic acid bacteria (LAB) and anti-inflammatory Clostridium butyricum (CB) on ameliorating enteritis remain unclear. In this study, we investigated the effects of the antioxidant strain Lactiplantibacillus plantarum AS21 and CB alone, or in combination on intestinal microbiota, barrier function, oxidative stress and inflammation in mice with DSS-induced colitis. All probiotic treatments relieved the pathological development of colitis by improving the integrity of the intestinal mucosal barrier and the length of the colon. The probiotics also suppressed inflammation and oxidative stress by improving gut short-chain fatty acids and inhibiting the p38-MAPK/NF-κB pathway in colon tissues. According to the meta-network analysis, three distinct modules containing sensitive OTUs of the gut bacterial community specific to the control, DSS and DSS + probiotics groups were observed, and unlike the other two modules, Lachnospiraceae and Clostridia dominated the sensitive OTUs in the DSS + probiotics group. In addition, administration of the present probiotics particularly increased antioxidant and anti-inflammatory microbes Muribaculaceae, Bifidobacterium, Prevotellaceae and Alloprevotella. Furthermore, combined probiotic strain treatment showed a more stable anti-colitis effect than a single probiotic strain. Collectively, the present probiotics exhibited protective effects against colitis by suppressing the inflammation and oxidative damage in the colon, improving the gut microbiota and their functions, and consequently preventing the gut leak. The results indicate that the combination of the antioxidant properties of LAB and the anti-inflammatory properties of CB as nutritional intervention and adjuvant therapy could be an effective strategy to prevent and alleviate colitis.

Efficacy and safety of traditional plant-based medicines for preventing chronic oxaliplatin-induced peripheral neurotoxicity in patients with colorectal cancer: A systematic review and meta-analysis with core herb contribution.

ETHNOPHARMACOLOGICAL RELEVANCE: Traditional plant-based medicines (TMs) have been widely used to prevent chronic oxaliplatin-induced peripheral neurotoxicity (OIPN). However, the prevention and safety of TMs for chronic OIPN remain ambiguous. Furthermore, diverse TM prescriptions and complicated components limit in-depth research on the mechanisms of TMs. AIM OF THIS STUDY: To determine core TMs and potential pharmacological pathways on the basis of a thorough investigation into the preventive benefits and safety of oral TMs for chronic OIPN in colorectal cancer (CRC). METHODS: A search of the PubMed, Cochrane, Embase, CNKI, VIP, and Wanfang databases for RCTs reporting on TMs for chronic OIPN was conducted through December 1, 2022. Subgroup analysis, sensitivity analysis and meta-regression were applied to assess the impacts of influencing variables. The assessment of Risk of Bias was relied on Cochrane Risk of Bias tool. The funnel plot, Egger's test, and the Trim and Fill method were applied to identify potential publication bias. Trial sequential analyses (TSA) were carried out by the TSA tool to increase the robustness. The assessment of the quality of evidence was according to the GRADE system. System pharmacology analysis was employed to screen core herbal combinations to elucidate possible mechanisms for preventing chronic OIPN in CRC. RESULTS: The pooled effect estimate with robustness increased by TSA analysis demonstrated that oral TMs appeared to significantly decrease the incidence of chronic OIPN (RR = 0.66, 95% CI (0.56, 0.78); P＜0.00001), leukocytopenia (RR = 0.65, 95% CI (0.54,0.79); P＜0.00001), and nausea and vomiting (RR = 0.72, 95% CI (0.61,0.84); P＜0.0001) as well as improve the Objective Response Rate (ORR) (RR = 1.31, 95% CI (1.09,1.56); P = 0.003). The incidence of severe chronic OIPN was revealed a significant reduction, particularly when chemotherapy was administered for periods of time shorter than six months (RR = 0.33, 95% CI (0.15,0.71); P = 0.005; actuation duration＜3 months; RR = 0.33, 95% CI (0.17,0.62); P = 0.0007; actuation duration≥3 months, ＜6 months). The considerable heterogeneity among studies may be attributable to the severity of dysfunction categorized by grade and accumulated dosage. Using core TMs consisting of Astragalus membranaceus (Fisch.) Bunge, Atractylodes Macrocephala Koidz., Poria cocos (Schw.) Wolf, and Codonopsis pilosula (Franch.) Nannf. To regulate nuclear factor-kappa B against inflammation caused by activation of microglia might be an approach to preventing chronic OIPN. CONCLUSIONS: TMs appear to be effective and safe in the prevention of chronic OIPN, especially severe chronic OIPN. Additionally, core TMs consisting of Astragalus membranaceus (Fisch.) Bunge, Atractylodes Macrocephala Koidz., Poria cocos (Schw.) Wolf, and Codonopsis pilosula (Franch.) Nannf were presumably responsible for reducing the incidence of chronic OIPN, and the mechanism may be related to relieving inflammation. However, quality-assured trials with long-term follow-up for exploring inflammatory factors and preliminary research on core TMs and pharmacological pathways are needed.

Big data and artificial intelligence in cancer research.

The field of oncology has witnessed an extraordinary surge in the application of big data and artificial intelligence (AI). AI development has made multiscale and multimodal data fusion and analysis possible. A new era of extracting information from complex big data is rapidly evolving. However, challenges related to efficient data curation, in-depth analysis, and utilization remain. We provide a comprehensive overview of the current state of the art in big data and computational analysis, highlighting key applications, challenges, and future opportunities in cancer research. By sketching the current landscape, we seek to foster a deeper understanding and facilitate the advancement of big data utilization in oncology, call for interdisciplinary collaborations, ultimately contributing to improved patient outcomes and a profound understanding of cancer.

Low-dose Rivaroxaban: is it a safe alternative in Chinese older patients?

PURPOSE: 10 mg rivaroxaban is widely used in the Chinese mainland. This study aims to explore the association between 10 mg once daily rivaroxaban and all-cause mortality in patients with nonvalvular atrial fibrillation (NVAF). METHODS: This observational study enrolled 1131 NVAF patients at the cardiovascular department of the First Affiliated Hospital of Xi'an Jiaotong University. One-year outcomes included all-cause mortality and bleeding were recorded. Cox proportional hazards models and Kaplan-Meier analysis were utilized in the study. RESULTS: In total, 1131 patients (402 no anticoagulants, and 729 rivaroxaban) were included. Cox proportional hazard analysis demonstrated that low-dose rivaroxaban (10 mg, HR: 0.14, 95% CI:(0.07-0.28), P<0.001; 15 mg, HR: 0.20, 95% CI:(0.09-0.43), P<0.001; 20 mg, HR: 0.22, 95% CI:(0.05-0.96), P = 0.044) exhibited lower mortality risk compared to untreated patients. CONCLUSIONS: 10 mg once daily rivaroxaban may provide survival benefits for elderly patients with NVAF.

Beneficial associations between outdoor visible greenness at the workplace and metabolic syndrome in Chinese adults.

BACKGROUND: Greenness surrounding residential places has been found to significantly reduce the risk of diseases such as hypertension, obesity, and metabolic syndrome (MetS). However, it is unclear whether visible greenness exposure at the workplace has any impact on the risk of MetS. METHODS: Visible greenness exposure was assessed using a Green View Index (GVI) based on street view images through a convolutional neural network model. We utilized logistic regression to examine the cross-sectional association between GVI and MetS as well as its components among 51,552 adults aged 18-60 in the city of Hangzhou, China, from January 2018 to December 2021. Stratified analyses were conducted by age and sex groups. Furthermore, a scenario analysis was conducted to investigate the risks of having MetS among adults in different GVI scenarios. RESULTS: The mean age of the participants was 40.1, and 38.5% were women. We found a statistically significant association between GVI and having MetS. Compared to the lowest quartile of GVI, participants in the highest quartile of GVI had a 17% (95% CI: 11-23%) lower odds of having MetS. The protective association was stronger in the males, but we did not observe such differences in different age groups. Furthermore, we found inverse associations between GVI and the odds of hypertension, low high-density lipoprotein cholesterol, obesity, and high levels of FPG. CONCLUSIONS: Higher exposure to outdoor visible greenness in the workplace environment might have a protective effect against MetS.

Inhibition of cGAS-STING pathway by stress granules after activation of M2 macrophages by human mesenchymal stem cells against drug induced liver injury.

OBJECTIVE: Cells can produce stress granules (SGs) to protect itself from damage under stress. The cGAS-STING pathway is one of the important pattern recognition pathways in the natural immune system. This study was investigated whether human mesenchymal stem cells (hMSCs) could protect the liver by inducing M2 macrophages to produce SGs during acute drug induced liver injury (DILI) induced by acetaminophen (APAP). METHODS: After intragastric administration of APAP in vivo to induce DILI mice model, hMSCs were injected into the tail vein. The co-culture system of hMSCs and M2 macrophages was established in vitro. It was further use SGs inhibitor anisomicin to intervene M2 macrophages. The liver histopathology, liver function, reactive oxygen species (ROS) level, apoptosis pathway, endoplasmic reticulum stress (ERS) level, SGs markers (G3BP1/TIA-1), cGAS-STING pathway, TNF-α, IL-6, IL-1ß mRNA levels in liver tissue and M2 macrophages were observed. RESULTS: In vivo experiments, it showed that hMSCs could alleviate liver injury, inhibite the level of ROS, apoptosis and ERS, protect liver function in DILI mice. The mount of M2 was increased in the liver. hMSCs could also induce the production of SGs, inhibit the cGAS-STING pathway and reduce TNF-α, IL-6, IL-1ß mRNA expression. The results in vitro showed that hMSCs could induce the production of SGs in macrophages, inhibit the cGAS-STING pathway, promote the secretion of IL-4 and IL-13, and reduce TNF-α, IL-6, IL-1ß mRNA level in cells. In the process of IL-4 inducing M2 macrophage activation, anisomycin could inhibit the production of SGs, activate the cGAS-STING pathway, and promote the inflammatory factor TNF-α, IL-6, IL-1ß mRNA expression in cells. CONCLUSIONS: HMSCs had a protective effect on acute DILI in mice induced by APAP. Its mechanism might involve in activating M2 type macrophages, promoting the production of SGs, inhibiting the cGAS-STING pathway, and reducing the expression of pro-inflammatory factors in macrophages, to reduce hepatocytes damage.