Establishment of a machine learning predictive model for non-alcoholic fatty liver disease: A longitudinal cohort study.

BACKGROUND AND AIMS: Non-alcoholic fatty liver disease (NAFLD) is a common chronic liver disease, which lacks effective drug treatments. This study aimed to construct an eXtreme Gradient Boosting (XGBoost) prediction model to identify or evaluate potential NAFLD patients. METHODS AND RESULTS: We conducted a longitudinal study of 22,140 individuals from the Beijing Health Management Cohort. Variable filtering was performed using the least absolute shrinkage and selection operator. Random Over Sampling Examples was used to address imbalanced data. Next, the XGBoost model and the other three machine learning (ML) models were built using balanced data. Finally, the variable importance of the XGBoost model was ranked. Among four ML algorithms, we got that the XGBoost model outperformed the other models with the following results: accuracy of 0.835, sensitivity of 0.835, specificity of 0.834, Youden index of 0.669, precision of 0.831, recall of 0.835, F-1 score of 0.833, and an area under the curve of 0.914. The top five variables with the greatest impact on the onset of NAFLD were aspartate aminotransferase, cardiometabolic index, body mass index, alanine aminotransferase, and triglyceride-glucose index. CONCLUSION: The predictive model based on the XGBoost algorithm enables early prediction of the onset of NAFLD. Additionally, assessing variable importance provides valuable insights into the prevention and treatment of NAFLD.

Association of sex-specific body mass index and waist circumference trajectories with non-alcoholic fatty liver disease incidence based on growth mixture modeling.

BACKGROUND AND AIMS: Non-alcoholic fatty liver disease (NAFLD) is a common chronic liver disease. The relationship between the trajectories of obesity indicators and incident NAFLD is unknown. Therefore, this study aims to explore the sex-specific association between the trajectories of obesity indicators and the incidence of NAFLD. METHODS AND RESULTS: In total, 9067 participants were recruited for this longitudinal study. Obesity indicators use body mass index (BMI) and waist circumference (WC). The trajectory of obesity indicators was analyzed using the growth mixture modeling. The multivariate logistic regression model was used to analyze the association between obesity indicators' trajectories and incident NAFLD. Over a median follow-up of 1.82 years, 1013 (11.74%) participants developed NAFLD. We identified BMI and WC change trajectories as the stable group, increasing group, and decreasing group. After adjusting for baseline level and other confounders, multivariate logistic regression analysis showed that compared with stable group of BMI, the increasing group, and decreasing group odds ratio and 95% confidence interval of NAFLD were 2.10 (1.06-4.15), and 0.25 (0.09-0.67) in men, and 1.82 (1.08-3.04) and 0.32 (0.16-0.64) in women. Compared with stable group of WC, the increasing group was 2.57 (1.39-4.74) in men, the increasing group, and decreasing group were 2.29 (1.70-3.10) and 0.28 (0.12-0.64) in women. Sensitivity analysis showed that the results were stable. CONCLUSION: The BMI and WC changing trajectories are significantly associated with the incidence of NAFLD in men and women. Populations of real-world health examinations can be categorized based on obesity indicator changes to prevent NAFLD.

Effects of Xiaoyao San on exercise capacity and liver mitochondrial metabolomics in rat depression model.

Objective: This study aimed to investigate the therapeutic effects of Xiaoyao San (XYS), a herbal medicine formula, on exercise capacity and liver mitochondrial metabolomics in a rat model of depression induced by chronic unpredictable mild stress (CUMS). Methods: A total of 24 male SD rats were randomly divided into four groups: control group (C), CUMS control group (M), Venlafaxine positive treatment group (V), and XYS treatment group (X). Depressive behaviour and exercise capacity of rats were assessed by body weight, sugar-water preference test, open field test, pole test, and rotarod test. The liver mitochondria metabolomics were analyzed by using liquid chromatography-mass spectrometry (LC-MS) method. TCMSP database and GeneCards database were used to screen XYS for potential targets for depression, and GO and KEGG enrichment analyses were performed. Results: Compared with C group, rats in M group showed significantly lower body weight, sugar water preference rate, number of crossing and rearing in the open field test, climbing down time in the pole test, and retention time on the rotarod test (P < 0.01). The above behaviors and exercise capacity indices were significantly modulated in rats in V and X groups compared with M group (P < 0.05, 0.01). Compared with C group, a total of 18 different metabolites were changed in the liver mitochondria of rats in M group. Nine different metabolites and six metabolic pathways were regulated in the liver mitochondria of rats in X group compared with M group. The results of network pharmacology showed that 88 intersecting targets for depression and XYS were obtained, among which 15 key targets such as IL-1ß, IL-6, and TNF were predicted to be the main differential targets for the treatment of depression. Additionally, a total of 1 553 GO signaling pathways and 181 KEGG signaling pathways were identified, and the main biological pathways were AGE-RAGE signaling pathway, HIF-1 signaling pathway, and calcium signaling pathway. Conclusion: XYS treatment could improve depressive symptoms, enhance exercise capacity, positively regulate the changes of mitochondrial metabolites and improve energy metabolism in the liver of depressed rats. These findings suggest that XYS exerts antidepressant effects through multi-target and multi-pathway.

Temporal relationship between elevated serum uric acid levels and dyslipidemia: A 5-year cohort study using cross-lagged panel analysis.

BACKGROUND AND AIM: Previous studies have demonstrated an association between SUA and dyslipidemia. This study aims to explore the temporal relationship between SUA and dyslipidemia. METHODS AND RESULTS: Based on the Beijing Health Management Cohort conducted from 2013 to 2018, the data of a physical examination population was collected, including a total of 6630 study subjects. Cross-lagged panel analysis was employed to examine the temporal relationship between elevated SUA levels and dyslipidemia, indicated by either elevated TG or decreased HDL-C. The path coefficient and the 95 % CI from baseline TG to follow-up SUA were as follows: in the general population, men, women, and people with BMI ≥25 kg/m2were 0.027 (0.008-0.045), 0.024 (0.001-0.048), 0.032 (0.001-0.063) and 0.033 (0.006-0.059) (P < 0.05); however, the path coefficient from baseline SUA to follow-up TG and the 95 % CI were not statistically significant. Furthermore, the path coefficients and 95 % CIs between elevated SUA and decreased HDL-C were not statistically significant, both in the general population and in populations stratified by gender and BMI. CONCLUSIONS: We found a temporal relationship from elevated TG to elevated SUA in the general population and the populations stratified by gender and BMI (≥25 kg/m2). However, we did not observe a reverse relationship from elevated SUA to elevated TG. Additionally, we did not find a temporal relationship between decreased HDL-C and elevated SUA in both the general population and the stratified populations.

DDX60 Promotes Migration and Invasion of Head and Neck Squamous Cell Carcinoma Cell through the NF-κB/IFI27 Signaling Pathway.

BACKGROUND: Despite its significance in multiple cancer types. the function and mechanism of DEXD/H box helicase 60 (DDX60) in head and neck squamous cell carcinoma (HNSCC) remain unreported. METHODS: Thirty paired HNSCC tissues and adjoining normal tissues and human normal oral epithelial keratinocytes (HOK) and four HNSCC cells (CAL27, SAS, CAL33, and SCC25) were analyzed for DDX60 expression by Semi-quantitative real-time PCR (SQ RT-PCR) and western blot. To investigate how DDX60 affects HNSCC cell migration and invasion, transwell experiments were performed. The western blot was implemented to understand the interaction among DDX60, Interferon Alpha Inducible Protein 27 (IFI27), and the NF-κB pathway. RESULTS: Results revealed the upregulation of DDX60 in HNSCC cell lines and tissues. Additionally, patients with upregulated DDX60 expression exhibited a dismal prognosis relative to those with downregulated expression. DDX60 enhanced the migration, invasion, and epithelial to mesenchymal transition (EMT) in HNSCC cells. The results from mechanistic studies revealed that DDX60 could promote the IFI27 expression following the activation of NF-κB pathway. CONCLUSION: DDX60 promoted the migratory and invasive capacities of HNSCC cells via the NF-κB/IFI27 axis.

Predicting coronary heart disease in Chinese diabetics using machine learning.

Diabetes, a common chronic disease worldwide, can induce vascular complications, such as coronary heart disease (CHD), which is also one of the main causes of human death. It is of great significance to study the factors of diabetic patients complicated with CHD for understanding the occurrence of diabetes/CHD comorbidity. In this study, by analyzing the risk of CHD in more than 300,000 diabetes patients in southwest China, an artificial intelligence (AI) model was proposed to predict the risk of diabetes/CHD comorbidity. Firstly, we statistically analyzed the distribution of four types of features (basic demographic information, laboratory indicators, medical examination, and questionnaire) in comorbidities, and evaluated the predictive performance of three traditional machine learning methods (eXtreme Gradient Boosting, Random Forest, and Logistic regression). In addition, we have identified nine important features, including age, WHtR, BMI, stroke, smoking, chronic lung disease, drinking and MSP. Finally, the model produced an area under the receiver operating characteristic curve (AUC) of 0.701 on the test samples. These findings can provide personalized guidance for early CHD warning for diabetic populations.

Dangui Huoxue Preparation (DHP) Ameliorates Skin Fibrosis, Inflammation, and Vasculopathy in the Bleomycin-Induced Murine Model of Systemic Sclerosis.

Systemic sclerosis (SSc) is an immune-mediated rheumatic disease that is characterized by fibrosis of the skin and internal organs and vasculopathy with poor prognosis. Dangui Huoxue Preparation (DHP) is a clinically effective traditional Chinese herbal formula for the treatment of SSc in the hospital. This study aims to investigate the therapeutic effects and underlying molecular mechanisms of DHP in the treatment of SSc. SSc mice models are induced by bleomycin (BLM). Tissues of DHP group, normal control group, and positive control drug Sanqi Tongshu Capsule (STC) group are collected for inflammation, fibrosis, and vasculopathy. Also, the human dermal fibroblasts (HDF) stimulated with TGF-ß1 are analyzed for in vitro study. The expression levels of MCP-1, IFN-γ, IL-1ß, IL-10, Fizz1, iNOS, and IL12p40, and the mRNA levels of Col1a1, Col1a2, Col3a1, and Col5a1 are significantly decreased in all DHP groups and STC group compare with those in the BLM group. The main drug of DHP inhibits the proliferation and migration of HDF, reduces Ctgf, Itgb3, Itgb5 expression, and also inhibits the Smad3 pathway. In conclusion, DHP can ameliorate SSc skin inflammation, fibrosis, and vasculopathy, possibly suppressing the TGF-ß1/Smad3 signaling pathway through extracellular and intracellular mechanisms.

Plasma metabolomics reveals the intervention mechanism of different types of exercise on chronic unpredictable mild stress-induced depression rat model.

OBJECTIVE: To study the effects of different types of exercise on the plasma metabolomics of chronic unpredictable mild stress (CUMS)-induced depressed rats based on 1H-NMR metabolomics techniques, and to explore the potential mechanisms of exercise for the treatment of depression. Rats were randomly divided into blank control group (C), CUMS control group (D), pre-exercise with CUMS group (P), CUMS with aerobic exercise group, CUMS with resistance exercise group (R), and CUMS with aerobic + resistance exercise group (E). The corresponding protocol intervention was applied to each group of rats. Body weight, sucrose preference and open field tests were performed weekly during the experiment to evaluate the extent of depression in rats. Plasma samples from each group of rats were collected at the end of the experiment, and then the plasma was analyzed by 1H-NMR metabolomics combined with multivariate statistical analysis methods to identify differential metabolites and perform metabolic pathway analysis. (1) Compared with the group D, the body weight, sucrose preference rate, and the number of crossings and standings in the different types of exercise groups were significantly improved (p < 0.05 or p < 0.01). (2) Compared to group C, a total of 15 differential metabolites associated with depression were screened in the plasma of rats in group D, involving 6 metabolic pathways. Group P can regulate the levels of 6 metabolites: valine, lactate, inositol, glucose, phosphocreatine, acetoacetic acid. Group A can regulate the levels of 6 metabolites: N-acetylglycoprotein, leucine, lactate, low density lipoprotein, glucose and acetoacetic acid. Group R can regulate the levels of 6 metabolites: choline, lactate, inositol, glucose, phosphocreatine and acetoacetic acid. Group E can regulate the levels of 5 metabolites: choline, citric acid, glucose, acetone and acetoacetic acid. The different types of exercise groups can improve the depressive symptoms in CUMS rats, and there are common metabolites and metabolic pathways for their mechanism of effects. This study provides a powerful analytical tool to study the mechanism of the antidepressant effect of exercise, and provides an important method and basis for the early diagnosis, prevention and treatment of depression.

Association between nonalcoholic fatty liver disease and type 2 diabetes: A bidirectional two-sample mendelian randomization study.

OBJECTIVE: The aim of this study was to explore the mutually causal relationship between NAFLD and type 2 diabetes. METHODS: Based on the data obtained from GWAS, this study employed bidirectional two-sample MR analysis to investigate the causal relationship between NAFLD and type 2 diabetes, and also examined the causal relationship between liver fat accumulation and type 2 diabetes as well as the relationship between NAFLD and FPG, IR. RESULTS: In MR analysis of NAFLD and type 2 diabetes, when NAFLD as an exposure and type 2 diabetes as a result, the OR (95 % CI) was 1.10890 (1.00135-1.22801); in the reverse analysis, the OR value was not statistically significant. In MR analysis of NAFLD, FPG and IR, there was no statistical significance in both directions. In MR analysis of liver fat accumulation and type 2 diabetes, when liver fat as an exposure and type 2 diabetes as a result, the OR (95 % CI) was 1.17516 (1.02054-1.35321); in the reverse analysis, the OR value (95 % CI) was 1.06283 (1.02879-1.09799). CONCLUSION: There is a unidirectional causal relationship between NAFLD and type 2 diabetes. Furthermore, a bidirectional causal relationship exists between liver fat accumulation and type 2 diabetes.

Clinical Manifestations and Risk Factors Associated with 14 Deaths following Swarm Wasp Stings in a Chinese Tertiary Grade A General Hospital: A Retrospective Database Analysis Study.

INTRODUCTION: The objective was to evaluate the poisoning severity score (PSS) as an early prognostic predictor in patients with wasp stings and identify associated clinical characteristics and risk factors for mortality. METHODS: A total of 363 patients with wasp stings at Suining Central Hospital between January 2016 and December 2018 were enrolled. Within the first 24 h of admission, the poisoning severity score (PSS) and the Chinese expert consensus on standardized diagnosis and treatment of wasp stings (CECC) were utilized for severity classification, and their correlation was examined. Patients were then divided into survival and death groups based on discharge status. Logistic regression analysis was employed to analyze factors influencing patients' outcomes. RESULTS: The mortality of wasp sting patients was 3.9%. The PSS and CECC were found to correlate for severity classification. Additionally, female gender, age, number of stings, and PSS were identified as independent risk factors for mortality in wasp sting patients. Combining these four factors yielded an AUC of 0.962 for predicting death. CONCLUSIONS: PSS aids in early severity classification of wasp stings. Female gender, age, number of stings, and PSS were independent mortality risk factors in these patients.

Bidirectional relationship between nonalcoholic fatty liver disease and serum creatinine-to-body weight ratio as a proxy for skeletal muscle mass index.

BACKGROUND AND AIM: Although an association between skeletal muscle mass index and nonalcoholic fatty liver disease (NAFLD) has previously been demonstrated, the causal direction remains unclear. Herein, we investigated the directional association between NAFLD and the serum creatinine-to-body weight ratio (sCr/bw), a surrogate marker of the muscle mass index, using longitudinal data. METHODS: We recruited 9662 participants in 2017 and performed follow-up over 4 years. We evaluated whether sCr/bw was related to NAFLD development (Analysis I) and whether NAFLD was associated with a low sCr/bw incidence (Analysis II) using logistic regression models. Furthermore, a random intercept cross-lagged panel model was applied to evaluate the bidirectional association between sCr/bw ratio and NAFLD (Analysis III). RESULTS: Analysis I demonstrated an association between sCr/bw and incident NAFLD (odds ratio [OR] = 0.160, 95% confidence interval [CI]:0.107-0.232). Analysis II indicated a relationship between NAFLD and subsequent low sCr/bw ratio (OR = 1.524, 95% CI: 1.258-1.846). Analysis III indicated that the standard regression coefficient from sCr/bw to subsequent hepatic steatosis (HS) was -0.053 for ßsCr/bw2017 â†’ HS2019 and -0.060 for ßsCr/bw2019 â†’ HS2021 and the coefficient from HS to subsequent sCr/bw was -0.093 for ßHS2017 â†’ sCr/bw2019 and -0.112 for ßHS2019 â†’ sCr/bw2021 (all P < 0.05). CONCLUSIONS: This study indicated mutual causality between sCr/bw and NAFLD. Considering that sCr/bw is a surrogate marker of muscle mass index, the findings emphasize that NAFLD and low muscle mass form a vicious cycle, which should be taken seriously in clinical practice.

Effect of Artificial Intelligence-based Health Education Accurately Linking System (AI-HEALS) for Type 2 diabetes self-management: protocol for a mixed-methods study.

BACKGROUND: Patients with type 2 diabetes (T2DM) have an increasing need for personalized and Precise management as medical technology advances. Artificial intelligence (AI) technologies on mobile devices are being developed gradually in a variety of healthcare fields. As an AI field, knowledge graph (KG) is being developed to extract and store structured knowledge from massive data sets. It has great prospects for T2DM medical information retrieval, clinical decision-making, and individual intelligent question and answering (QA), but has yet to be thoroughly researched in T2DM intervention. Therefore, we designed an artificial intelligence-based health education accurately linking system (AI-HEALS) to evaluate if the AI-HEALS-based intervention could help patients with T2DM improve their self-management abilities and blood glucose control in primary healthcare. METHODS: This is a nested mixed-method study that includes a community-based cluster-randomized control trial and personal in-depth interviews. Individuals with T2DM between the ages of 18 and 75 will be recruited from 40-45 community health centers in Beijing, China. Participants will either receive standard diabetes primary care (SDPC) (control, 3 months) or SDPC plus AI-HEALS online health education program (intervention, 3 months). The AI-HEALS runs in the WeChat service platform, which includes a KBQA, a system of physiological indicators and lifestyle recording and monitoring, medication and blood glucose monitoring reminders, and automated, personalized message sending. Data on sociodemography, medical examination, blood glucose, and self-management behavior will be collected at baseline, as well as 1,3,6,12, and 18 months later. The primary outcome is to reduce HbA1c levels. Secondary outcomes include changes in self-management behavior, social cognition, psychology, T2DM skills, and health literacy. Furthermore, the cost-effectiveness of the AI-HEALS-based intervention will be evaluated. DISCUSSION: KBQA system is an innovative and cost-effective technology for health education and promotion for T2DM patients, but it is not yet widely used in the T2DM interventions. This trial will provide evidence on the efficacy of AI and mHealth-based personalized interventions in primary care for improving T2DM outcomes and self-management behaviors. TRIAL REGISTRATION: Biomedical Ethics Committee of Peking University: IRB00001052-22,058, 2022/06/06; Clinical Trials: ChiCTR2300068952, 02/03/2023.

A novel insight for high-rate and low-efficiency glucose metabolism in depression through stable isotope-resolved metabolomics in CUMS-induced rats.

BACKGROUND: Existing research has suggested that depression results in disorders of glucose metabolism in the organism which causing insufficient energy supply. However, the overall changes in glucose metabolism that arise from depression have not been clarified. METHODS: In this study, the depression-like behavior in chronically unpredictable mild stressed rats was investigated, and the fate of glucose was tracked through isotope tracing and mass spectrometry, with a focus on metabolite changes in cecal contents. RESULTS: As indicated by the results, the isotopic results of cecal contents can indicate the metabolic end of the organism. Moreover, the TCA cycle activity was notably reduced, and the gluconeogenesis pathway was abnormally up-regulated in the CUMS-induced rats. The organism expedited other glucose metabolism pathways to make up for the insufficiency of energy. As a result, the activity of the inefficient glycolysis pathway was increased. LIMITATIONS: Existing research has only investigated the metabolism of 13C-glucose, and lipids and proteins have been rarely explored. CONCLUSIONS: The chronic unpredictable mild stress can inhibit the entry of pyruvate into mitochondria in SD rats, such that the activity of TCA is reduced, and insufficient energy supply is caused. The organism is capable of expediting other glucose metabolism rate pathways to make up for the insufficiency of energy, whereas it still cannot compensate for the loss of energy. As a result, CUMS-induced rats exhibited high-rate and low-efficiency glucose metabolism.

Establishment of dynamic nomogram and risk score models for T2DM: a retrospective cohort study in Beijing.

BACKGROUND: Health interventions can delay or prevent the occurrence and development of diabetes. Dynamic nomogram and risk score (RS) models were developed to predict the probability of developing type 2 diabetes mellitus (T2DM) and identify high-risk groups. METHODS: Participants (n = 44,852) from the Beijing Physical Examination Center were followed up for 11 years (2006-2017); the mean follow-up time was 4.06 ± 2.09 years. Multivariable Cox regression was conducted in the training cohort to identify risk factors associated with T2DM and develop dynamic nomogram and RS models using weighted estimators corresponding to each covariate derived from the fitted Cox regression coefficients and variance estimates, and then undergone internal validation and sensitivity analysis. The concordance index (C-index) was used to assess the accuracy and reliability of the model. RESULTS: Of the 44,852 individuals at baseline, 2,912 were diagnosed with T2DM during the follow-up period, and the incidence density rate per 1,000 person-years was 16.00. Multivariate analysis indicated that male sex (P < 0.001), older age (P < 0.001), high body mass index (BMI, P < 0.05), high fasting plasma glucose (FPG, P < 0.001), hypertension (P = 0.015), dyslipidaemia (P < 0.001), and low serum creatinine (sCr, P < 0.05) at presentation were risk factors for T2DM. The dynamic nomogram achieved a high C-index of 0.909 in the training set and 0.905 in the validation set. A tenfold cross-validation estimated the area under the curve of the nomogram at 0.909 (95% confidence interval 0.897-0.920). Moreover, the dynamic nomogram and RS model exhibited acceptable discrimination and clinical usefulness in subgroup and sensitivity analyses. CONCLUSIONS: The T2DM dynamic nomogram and RS models offer clinicians and others who conduct physical examinations, respectively, simple-to-use tools to assess the risk of developing T2DM in the urban Chinese current or retired employees.

Risk prediction of diabetes and pre-diabetes based on physical examination data.

Diabetes is a metabolic disorder caused by insufficient insulin secretion and insulin secretion disorders. From health to diabetes, there are generally three stages: health, pre-diabetes and type 2 diabetes. Early diagnosis of diabetes is the most effective way to prevent and control diabetes and its complications. In this work, we collected the physical examination data from Beijing Physical Examination Center from January 2006 to December 2017, and divided the population into three groups according to the WHO (1999) Diabetes Diagnostic Standards: normal fasting plasma glucose (NFG) (FPG < 6.1 mmol/L), mildly impaired fasting plasma glucose (IFG) (6.1 mmol/L ≤ FPG < 7.0 mmol/L) and type 2 diabetes (T2DM) (FPG > 7.0 mmol/L). Finally, we obtained1,221,598 NFG samples, 285,965 IFG samples and 387,076 T2DM samples, with a total of 15 physical examination indexes. Furthermore, taking eXtreme Gradient Boosting (XGBoost), random forest (RF), Logistic Regression (LR), and Fully connected neural network (FCN) as classifiers, four models were constructed to distinguish NFG, IFG and T2DM. The comparison results show that XGBoost has the best performance, with AUC (macro) of 0.7874 and AUC (micro) of 0.8633. In addition, based on the XGBoost classifier, three binary classification models were also established to discriminate NFG from IFG, NFG from T2DM, IFG from T2DM. On the independent dataset, the AUCs were 0.7808, 0.8687, 0.7067, respectively. Finally, we analyzed the importance of the features and identified the risk factors associated with diabetes.

Serum metabolomic responses to aerobic exercise in rats under chronic unpredictable mild stress.

This study analyzed the effects of aerobic exercise on endogenous serum metabolites in response to chronic unpredictable mild stress (CUMS) using a rat model, aiming to identify the metabolic regulatory pathways involved in the antidepressant effect resulted from a 28-day treadmill aerobic exercise intervention. The animals were randomly divided into four groups (n = 8): normal control, normal with aerobic exercise, CUMS control, and CUMS with aerobic exercise. Body weight, sucrose preference and open field tests were performed weekly during the intervention period for changes in depressant symptoms. Serum metabolic profiles obtained by using the LC-MS/MS metabolomics were analyzed to explore the regulatory mechanism for the effect of the aerobic exercise on depression. Behavior tests showed that the aerobic exercise resulted in a significant improvement in depression-like behavior in the CUMS rats. A total of 21 differential metabolites were identified as being associated with depression in serum metabolic profile, of which the aerobic exercise significantly modulated 15, mainly related to amino acid metabolism and energy metabolism. Collectively, this is the first study that LC-MS/MS techniques were used to reveal the modulatory effects of aerobic exercise on the serum metabolic profile of depressed rats and the findings further enriched our understanding of potential mechanisms of aerobic exercise interventions on depression.

First report of Colletotrichum fioriniae causing leaf spot on Schima superba in the world.

Schima superba Gardn. et Champ. is a subtropical evergreen tree species naturally distributed mainly in China, Japan, and Vietnam. It is primarily planted for its timber and urban landscaping in China (Ni, 1996). In September 2018, leaves necrotic spots were observed on S. superba in Jiangxi Forest Breeding Center (28°57'19.52" N, 115°39'21.32" E), Jiangxi Province, China. The disease incidence was about 30%. Initially, spots were circular to semicircular, grayish-brown in the center with dark brown margin, then expanded and eventually collapsed into sunken necrotic lesions. To identify the agent, diseased leaves were collected randomly. Pieces (5 × 5 mm) from the lesion borders were surfaced sterilized in 70% ethanol (30 s), 3% NaOCl (60 s), and rinsed 3 times in sterile water. These pieces were put on potato dextrose agar (PDA) and cultured at 25 °C. Pure cultures were obtained by monosporic isolation, and 3 isolates (MH-1, MH-2, MH-3) were used for morphological studies and phylogenetic analyses. On PDA, colonies were initially white, cottony, then became pinkish to deep-pink at the center and pink on the reverse. Conidia were fusiform with acute ends, smooth-walled, hyaline, 13.7-18.5 × 4.6-6.1 µm (16.4 ± 1.3× 5.3 ± 0.6 µm, n = 100). Conidiophores were colorless to pale brown, smooth, septate. Conidiogenous cells were colorless to pale brown, smooth, cylindrical to ampulliform. The morphological characteristics fit the descriptions of Colletotrichum acutatum J. H. Simmonds sensu lato (Damm et al., 2012). For accurate identification, genomic DNA of 3 isolates was extracted, and the internal transcribed spacer (ITS), actin (ACT), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), beta-tubulin 2 (TUB2), and chitin synthase (CHS-1) were amplified and sequenced using the corresponding primers (Weir et al., 2012). The sequences were deposited in GenBank (ITS: MZ325946, MZ325947, MW584318; ACT: MZ399375, MZ419566, MW661171; CHS-1: MZ399376, MZ419567, MW661172; MZ399377, GAPDH: MZ419568, MW661173; TUB2: MZ399378, MZ419569, MW661174). Five loci were concatenated, and the aligned sequences (1528bp) were 99.89% homologous to ex-type C. fioriniae (Marcelino & Gouli) R. G. Shivas & Y. P. Tan CBS128517. Phylogenetic analysis using the maximum likelihood showed that 3 isolates were clustered in C. fioriniae clade with 100% bootstrap support. Based on the multi-locus phylogeny and morphology, 3 isolates were identified as C. fioriniae. Pathogenicity tests were performed on 36 seedlings of S. superba (2-year-old). The leaves were wounded slightly and inoculated with a drop of spore suspension (106 conidia/mL). The sterile water was used as controls. All the tested leaves were covered with black plastic bags to keep them moist for 2 days. All seedlings were placed in the greenhouse (25 °C, 12 h light/dark) for 10 days, and all inoculated leaves had typical symptoms. The controls were asymptomatic. The same fungus was reisolated from the lesions, fulfilling Koch's postulates. Colletotrichum fioriniae was described as a new species from the C. acutatum s. l. (Shivas et al., 2009), and it was an important plant pathogen, such as Pyrus spp. (Pavlovic et al., 2019), Morus alba L. (Xue et al., 2019), and so on. This is the first report of the newly emerging disease of S. superba caused by C. fioriniae in the world, and its potential threat should be evaluated in the future. This study provided crucial information for epidemiologic studies and appropriate control strategies.

Palbociclib induces cell senescence and apoptosis of gastric cancer cells by inhibiting the Notch pathway.

Palbociclib (PD0332991), a selective cyclin-dependent kinase 4/6 (CDK4/6) inhibitor, has been reported to exert anticancer activity in some cancers, including gastric cancer (GC). However, the role of palbociclib in GC remains largely unknown. The present study aimed to investigate the effects of palbociclib on the progression of GC and the potential mechanisms underlying its effects. The colony formation, proliferation, senescence, as well as apoptosis and cell cycle progression of AGS and HGC-27 cells following treatment with palbociclib were analyzed using colony formation assays, MTT assays, senescence-associated ß-galactosidase (SA-ß-gal) staining and flow cytometry, respectively. The protein expression levels of Bax, Caspase-3, Bcl-2, p16, p21, p53, Notch1, Notch2 and hairy and enhancer of split 1 (Hes1) were measured in AGS and HGC-27 cells using western blotting. Moreover, the mRNA expression levels of Notch1, Notch2 and Hes1 in AGS and HGC-27 cells were determined by reverse transcription-quantitative PCR. In the present study, palbociclib significantly inhibited cell proliferation and induced cell senescence, cell cycle arrest and apoptosis in both cell lines in a dose-dependent manner. Additionally, palbociclib significantly increased the expression levels of Bax, Caspase-3, p16, p21 and p53, whilst decreasing the expression of Bcl-2, Notch1, Notch2 and Hes1 in AGS and HGC-27 cells. Furthermore, the Notch pathway activator Jagged-1/FC reversed the effects of palbociclib on cell proliferation, apoptosis, senescence and cell cycle progression. These findings demonstrated that palbociclib could inhibit proliferation and induce senescence, cell cycle arrest and apoptosis in GC cells by inhibiting the Notch pathway.

Stable Isotope-Resolved Metabolomics Reveals the Abnormal Brain Glucose Catabolism in Depression Based on Chronic Unpredictable Mild Stress Rats.

The severe harm of depression to human life has attracted great attention to neurologists, but its pathogenesis is extremely complicated and has not yet been fully elaborated. Here, we provided a new strategy for revealing the specific pathways of abnormal brain glucose catabolism in depression, based on the supply of energy substrates and the evaluation of the mitochondrial structure and function. By using stable isotope-resolved metabolomics, we discovered that the tricarboxylic acid cycle (TCA cycle) is blocked and gluconeogenesis is abnormally activated in chronic unpredictable mild stress (CUMS) rats. In addition, our results showed an interesting phenomenon that the brain attempted to activate all possible metabolic enzymes in energy-producing pathways, but CUMS rats still exhibited a low TCA cycle activity due to impaired mitochondria. Depression caused the mitochondrial structure and function to be impaired and then led to abnormal brain glucose catabolism. The combination of the stable isotope-resolved metabolomics and mitochondrial structure and function analysis can accurately clarify the mechanism of depression. The mitochondrial pyruvate carrier and acetyl-CoA may be the key targets for depression treatment. The strategy provides a unique insight for exploring the mechanism of depression, the discovery of new targets, and the development of ideal novel antidepressants. Data are available via ProteomeXchange with identifier PXD025548.