Osteoporosis is a systemic disease characterized by imbalanced bone metabolism and destruction of bone microstructure, with reduced bone density, decreased bone quality, and significantly increased risk of fracture as its hallmarks. At present, osteoporosis is primarily diagnosed through bone density measurement. However, this method has low sensitivity and is challenging for the early diagnosis of osteoporosis. We analyzed osteoporosis-related metabolomics studies based on blood, urine, and fecal samples, as well as the application of multi-omics approaches in elucidating its pathogenesis. Evidence suggests that metabolomics can detect metabolic alterations prior to measurable changes in bone mineral density, offering promising avenues for early osteoporosis detection. Blood-based metabolomics studies indicate that amino acid metabolism dysregulation is a key feature of osteoporosis. Specifically, glycine, glutamine, lysine, and hydroxyproline exhibit negative correlations with bone mineral density, whereas tryptophan, branched-chain amino acids, and arginine show positive associations. Lipid metabolism disturbances are characterized by increased levels of phosphatidylcholine, phosphatidylethanolamine, and triglycerides, alongside decreased levels of sphingomyelin and carnitine. Fecal metabolomics studies highlight the significance of the "gut-bone axis" in osteoporosis, where gut microbiota dysbiosis influences bone metabolism through modulation of arginine and proline metabolism and aminoacyl-tRNA biosynthesis pathways. Multi-omics approaches integrate metabolomics, genomics, proteomics, and other omics data to provide a more comprehensive understanding of osteoporosis' molecular mechanisms, enabling the identification of key biomarkers and therapeutic targets. Metabolomics holds considerable potential for early diagnosis, while multi-omics integration offers novel insights into the complex pathophysiological mechanisms underlying osteoporosis. As detection technologies and analytical methods continue to advance, omics-based strategies are expected to play a pivotal role in the development of precision medicine for osteoporosis.

The Janus kinase/signal transducers and activators of transcription (JAK-STAT) control natural killer (NK) cells development and cytotoxic functions, however, whether long non-coding RNAs (lncRNAs) are involved in this pathway remains unknown. We found that miR155HG was elevated in activated NK cells and promoted their proliferation and effector functions in both NK92 and induced-pluripotent stem cells (iPSCs)-derived NK (iPSC-NK) cells, without reliance on its derived miR-155 and micropeptide P155. Mechanistically, miR155HG bound to miR-6756 and relieved its repression of JAK3 expression, thereby promoting the JAK-STAT pathway and enhancing NK cell proliferation and function. Further investigations disclosed that upon cytokine stimulation, STAT3 directly interacts with miR155HG promoter and induces miR155HG transcription. Collectively, we identify a miR155HG-mediated positive feedback loop of the JAK-STAT signaling. Our study will also provide a power target regarding miR155HG for improving NK cell generation and effector function in the field of NK cell adoptive transfer therapy against cancer, especially iPSC-derived NK cells.

Objective To analyze the epidemiological characteristics and prognostic factors of acute cardiovascular and cerebrovascular events in Jianyang City from 2020 to 2023. Methods Medical records of acute cardiovascular and cerebrovascular disease patients treated in three hospitals in Jianyang City from January 2020 to December 2023 were selected, and their epidemiological characteristics were analyzed. Multivariate logistic regression was used to analyze the risk factors for mortality. Results From 2020 to 2023, 23000 cases of acute cardiovascular and cerebrovascular events were reported in Jianyang City, with a standardized incidence rate of 508.76/100 000 and a gender ratio of 1.33:1. All diseases and the total standardized incidence rate of men are higher than those of women; ≥ The total incidence rate and all incidence rate of the 85 year old group are the highest; The incidence rate is the highest in 2021, and the incidence rate is the highest in spring and winter. The standardized mortality rate of acute cardiovascular and cerebrovascular events was 108.08/100 000, with significant differences among different ages, disease types, and onset seasons (P<0.05). Multivariate analysis showed that age, onset season, and disease type were independent risk factors for patient mortality (P<0.05). Conclusion From 2020 to 2023, the standardized incidence rate of acute cardiovascular and cerebrovascular events in Jianyang City is higher, which is more common in the elderly population. The risk of men is higher than that of women, and the risk is higher in spring and winter. Age, disease type, and onset season are all directly related to the risk of death. In the future, it is necessary to strengthen the monitoring and prevention of cardiovascular and cerebrovascular diseases, and optimize emergency treatment work in order to improve patient prognosis.

Objective To analyze the changes in myocardial injury markers and cardiac function in patients with hypertrophic obstructive cardiomyopathy (HOCM) after Liwen surgery. Methods A retrospective analysis was conducted on the clinical data of HOCM patients who underwent Liwen surgery at the Department of Cardiac Surgery, Wuhan Asia Heart Hospital from December 2019 to April 2023, mainly including preoperative and postoperative dynamic follow-up laboratory test results and echocardiograms. Results A total of 42 patients were included, with 25 males and 17 females, aged (44.76±17.72) years, and a postoperative follow-up time of (15.02±6.97) months. The myocardial troponin level of the patients decreased from preoperative 0.03 (0.02, 0.06) ng/mL to postoperative 0.02 (0.01, 0.05) ng/mL (P=0.006), and the N-terminal pro-brain natriuretic peptide level decreased from preoperative 748.95 (337.40, 1600.75) ng/L to postoperative 367.15 (126.93, 1030.25) ng/L (P<0.001). After surgery, the left atrial diameter of the patients decreased from preoperative (4.18±0.57) cm to postoperative (3.93±0.55) cm (P=0.004), the end-diastolic interventricular septum thickness decreased from preoperative 2.25 (1.90, 2.75) cm to postoperative 1.70 (1.50, 1.90) cm (P<0.001), the left ventricular mass index decreased from preoperative 211.73 (172.28, 261.54) g/m2 to postoperative 156.78 (132.34, 191.36) g/m2 (P<0.001), the left ventricular weight decreased from preoperative 368.89 (292.34, 477.72) g to postoperative 266.62 (224.57, 326.04) g (P<0.001), the end-diastolic posterior wall thickness of the left ventricle decreased from preoperative 1.30 (1.20, 1.60) cm to postoperative 1.20 (1.18, 1.40) cm (P<0.001), the relative wall thickness decreased from preoperative 0.78 (0.78, 1.02) to postoperative 0.63 (0.56, 0.72) (P<0.001), the end-systolic inner diameter of the left ventricle increased from preoperative (2.91±0.50) cm to postoperative (3.19±0.53) cm (P=0.001), and the end-diastolic inner diameter of the left ventricle increased from preoperative (4.41±0.48) cm to postoperative (4.66±0.52) cm (P=0.005). The left ventricular outflow diameter increased from preoperative (1.28±0.46) cm to postoperative (1.57±0.32) cm (P=0.001), the left ventricular outflow pressure gradient decreased from preoperative 58.50 (40.75, 92.50) mm Hg to postoperative 11.50 (7.75, 20.50) mm Hg (P<0.001), the left ventricular ejection fraction increased from preoperative 60.00% (56.75%, 65.00%) to postoperative 63.00% (62.00%, 66.00%) (P=0.024), and the degree of systolic anterior motion of the mitral valve leaflets decreased (P＜0.001). Conclusion The cardiac function of patients with HOCM is improved after Liwen surgery, myocardial injury marker levels are decreased, cardiac reverse remodeling occurres, and the surgical outcome is good.

Osteoporosis is a systemic disease characterized by imbalanced bone metabolism and destruction of bone microstructure, with reduced bone density, decreased bone quality, and significantly increased risk of fracture as its hallmarks. At present, osteoporosis is primarily diagnosed through bone density measurement. However, this method has low sensitivity and is challenging for the early diagnosis of osteoporosis. We analyzed osteoporosis-related metabolomics studies based on blood, urine, and fecal samples, as well as the application of multi-omics approaches in elucidating its pathogenesis. Evidence suggests that metabolomics can detect metabolic alterations prior to measurable changes in bone mineral density, offering promising avenues for early osteoporosis detection. Blood-based metabolomics studies indicate that amino acid metabolism dysregulation is a key feature of osteoporosis. Specifically, glycine, glutamine, lysine, and hydroxyproline exhibit negative correlations with bone mineral density, whereas tryptophan, branched-chain amino acids, and arginine show positive associations. Lipid metabolism disturbances are characterized by increased levels of phosphatidylcholine, phosphatidylethanolamine, and triglycerides, alongside decreased levels of sphingomyelin and carnitine. Fecal metabolomics studies highlight the significance of the "gut-bone axis" in osteoporosis, where gut microbiota dysbiosis influences bone metabolism through modulation of arginine and proline metabolism and aminoacyl-tRNA biosynthesis pathways. Multi-omics approaches integrate metabolomics, genomics, proteomics, and other omics data to provide a more comprehensive understanding of osteoporosis' molecular mechanisms, enabling the identification of key biomarkers and therapeutic targets. Metabolomics holds considerable potential for early diagnosis, while multi-omics integration offers novel insights into the complex pathophysiological mechanisms underlying osteoporosis. As detection technologies and analytical methods continue to advance, omics-based strategies are expected to play a pivotal role in the development of precision medicine for osteoporosis.

Objective:To explore the clinical efficacy of endoscopic sleeve gastrectomy (ESG) in the treatment of obesity.Method:A 26 year old female patient was admitted on October 20, 2022 due to a progressive increase in weight for 2 years. Her body mass index (BMI) was 30.04 kg/m 2, body fat percentage was 39.2%, and visceral fat grade was 15. ESG was performed using the OverStitch SX endoscopic suture system. Result:The surgery was successful, with approximately 5 ml of intraoperative bleeding.The patient discharged on the first day after surgery. Two weeks after surgery, small bowel follow-through showed a tubular shape of the stomach. At 6 months after surgery, the BMI was 25.2 kg/m 2, body fat percentage was 32%, visceral fat grade was 10. The total body weight loss rate (%TBWL) at 6 months after surgery was 16%, and the excess weight loss rate (%EWL) was 54.5%. Conclusion:ESG is effective for the treatment of obesity.

Objective:To explore the clinical efficacy of endoscopic sleeve gastrectomy (ESG) in the treatment of obesity.Method:A 26 year old female patient was admitted on October 20, 2022 due to a progressive increase in weight for 2 years. Her body mass index (BMI) was 30.04 kg/m 2, body fat percentage was 39.2%, and visceral fat grade was 15. ESG was performed using the OverStitch SX endoscopic suture system. Result:The surgery was successful, with approximately 5 ml of intraoperative bleeding.The patient discharged on the first day after surgery. Two weeks after surgery, small bowel follow-through showed a tubular shape of the stomach. At 6 months after surgery, the BMI was 25.2 kg/m 2, body fat percentage was 32%, visceral fat grade was 10. The total body weight loss rate (%TBWL) at 6 months after surgery was 16%, and the excess weight loss rate (%EWL) was 54.5%. Conclusion:ESG is effective for the treatment of obesity.

OBJECTIVE To provide reference for improving the rational use of antimicrobial drugs in primary township medical institutions. METHODS Based on the county prescription pre-review center， a team led by anti-infective clinical pharmacists constructed the management mode for the use of antimicrobial drugs in county-level medical communities with clinical pharmacists as the main team by finding out the main problems in the use of antimicrobial drugs in primary township medical institutions， providing feedback on the problems， organizing relevant training for the problems， improving the customization rules of the prescription pre-review software， implementing the automatic interception and pharmacist online prescription review and other measures. Data on the use of antimicrobial drugs were collected and compared in the 15 primary township medical institutions between January-June in 2022 （before the implementation of the mode） and January-June in 2023 （after the implementation of the mode）. RESULTS Compared with before the implementation of the mode， the utilization rate of antimicrobial drugs in outpatients of primary township medical institutions decreased from 24.97% before the implementation of the mode to 19.39% after the implementation of the mode； the utilization rate of antimicrobial injection in outpatients decreased from 66.10% to 46.80%； the utilization rate of intravenous drip of antimicrobial drugs in outpatients decreased from 52.33% to 40.35%； the rates of combined use of antimicrobial drugs in outpatients decreased from 12.70% to 8.19%； the reasonable rate of antimicrobial prescribing in outpatients increased from 55.28% to 73.93%. After the implementation of the mode， the proportion of antimicrobial prescriptions for each diagnosis was basically the same as before； the defined daily dose system （DDDs） and proportion of a few antimicrobial drugs changed compared with before according to the anatomical therapeutic chemical classification of drugs， among which DDDs of lincomycin， gentamicin and other drugs declined significantly； DDDs of antimicrobial drugs for each classification was basically the same as before according to AWaRe classification. CONCLUSIONS The management mode of the use of antimicrobial drugs led by anti-infective clinical pharmacists is constructed in the prescription pre-reviewing center of county-level medical communities， which can effectively improve the rational use of antimicrobial drugs in the primary township medical institutions.

Autism spectrum disorder (ASD) is a range of neurodevelopmental diseases characterized by social dysfunction and stereotypic behaviors. The etiology of ASD remains largely unexplored, resulting in a diverse array of described clinical manifestations and varying degrees of severity. Currently, there are no drugs approved by a supervisory organization that can effectively treat the core symptoms of ASD. Childhood and adolescence are crucial stages for making significant achievements in ASD treatment, necessitating the development of drugs specifically for these periods. Based on the drug targets and mechanisms of action, it can be found that atypical psychotropic medications, anti-inflammatory and antioxidant medications, hormonal medications, ion channel medications, and gastrointestinal medications have shown significant improvement in treating the core symptoms of ASD in both children and adolescents. In addition, comparisons of drugs within the same category regarding efficacy and safety have been made to identify better alternatives and promote drug development. While further evaluation of the effectiveness and safety of these medications is needed, they hold great potential for widespread application in the clinical treatment of the principal symptoms of ASD.
Humans ; Autism Spectrum Disorder/drug therapy* ; Child ; Adolescent ; Psychotropic Drugs/therapeutic use* ; Antioxidants/therapeutic use* ; Anti-Inflammatory Agents/therapeutic use* ; Gastrointestinal Agents/therapeutic use*

Aim To explore the feasibility of using machine learning algorithms combined with coronary computed tomography(CT)derived perivascular fat attenuation index(FAI)and plaque information to evaluate myocardial ischemia in stable coronary heart disease patients.Methods A retrospective analysis was conducted on the clinical and imaging data of patients who underwent preoperative coronary CT angiography(CCTA),invasive coronary angiography(ICA),and flow reserve fraction(FFR)measurements at Zhongshan Hospital Affiliated to Fudan University from April 2019 to October 2021.206 patients with stable coronary heart disease were selected.The semi-automatic plaque analysis software was used for quantification of plaque and lumen parameters and perivascular FAI measurement,with man-ual delineation of a 40 mm segment of the coronary artery starting 10 mm from the ostium for perivascular FAI measure-ment.Differences in plaque characteristics,perivascular FAI,and coronary perivascular FAI between stable coronary heart disease patients with FFR≤0.8 and FFR＞0.8 were compared.The diagnostic performance of combining perivascu-lar FAI,coronary perivascular FAI,and plaque features using machine learning algorithms for myocardial ischemia in stable coronary heart disease patients was evaluated through ROC curves.Results 206 stable coronary heart disease patients were divided into FFR≤0.8 group(50 cases)and FFR＞0.8 group(156 cases).The mean periplaque FAI of patients with FFR≤0.8 was-69.28±5.65 HU,significantly higher than that of patients with FFR＞0.8 at-80.10±7.75 HU(P＜0.001).Further analysis was conducted using machine learning models,including XGBoost,random forest,and Logistic regression models,all of which had an accuracy rate of over 0.8 in diagnosing myocardial ischemia.Among them,the XGBoost model performed the best with an accuracy of 0.903,an F1 value of 0.774,and an AUC of 0.931,in-dicating its high effectiveness in diagnosing myocardial ischemia.Conclusion The combination of FAI and machine learning algorithm XGBoost model is a new method for diagnosing myocardial ischemia,which has better diagnostic value in evaluating myocardial ischemia in stable coronary heart disease patients.