OBJECTIVE Aimd to investigate the prevalence of olfactory dysfunction among healthy elderly individuals in China using a large sample size and to explore its correlations with demographic and other factors.METHODS A total of 5 258 participants who aged 60 and above underwent the T&T olfactometer test and completed questionnaires.The prevalence of olfactory dysfunction was reported,and logistic regression analyses were performed to assess the associations between olfactory dysfunction and other factors.RESULTS The overall prevalence of olfactory dysfunction in the study was 26.5%.Independent risk factors for olfactory dysfunction included advanced age,rural residence(OR=1.88,95%CI:1.60-2.22,P<0.01),current smoking(OR=1.45,95%CI:1.15-1.83,P<0.01),and self-reported olfactory dysfunction(OR=10.12,95%CI:8.44-12.14,P<0.01).In contrast,female gender(OR=0.70,95%CI:0.58-0.85,P<0.01)and high educational attainment were independently associated with a lower prevalence of olfactory dysfunction.CONCLUSION The prevalence of olfactory dysfunction among individuals aged 60 and above increased with age.Male gender,rural residence,low educational attainment,current smoking,and self-reported decline in olfactory function were independently associated with olfactory dysfunction.

OBJECTIVES: To explore the mechanism of Circ-MYOCD back-splicing and its regulatory role in myocardial hypertrophy. METHODS: Sanger sequencing and RNase R assays were performed to verify the circularity and stability of Circ-MYOCD, whose subcellular distribution was determined by nuclear-cytoplasmic fractionation. Bioinformatics analysis and mass spectrometry from pull-down assays were conducted to predict the RNA-binding proteins (RBPs) interacting with Circ-MYOCD. In rat cardiomyocytes H9C2 cells, the effects of HNRNPH1 and HNRNPL knockdown and overexpression on Circ-MYOCD back-splicing were evaluated. In a H9C2 cell model of angiotensin II (Ang II)-induced myocardial hypertrophy, the expression of HNRNPH1 was detected, the effects of HNRNPH1 knockdown and overexpression on progression of myocardial hypertrophy were assessed, and the regulatory effect of HNRNPH1 on Circ-MYOCD back-splicing was analyzed. RESULTS: Sanger sequencing confirmed that the junction primers could amplify the correct Circ-MYOCD sequence. RNase R and nuclear-cytoplasmic fractionation assays showed that Circ-MYOCD was stable and predominantly localized in the cytoplasm. Bioinformatics analysis and mass spectrometry from the Circ-MYOCD pull-down assay identified HNRNPH1 and HNRNPL as the RBPs interacting with Circ-MYOCD. In H9C2 cells, HNRNPH1 knockdown significantly enhanced while its overexpression inhibited Circ-MYOCD back-splicing; HNRNPH1 overexpression obviously increased the expressions of myocardial hypertrophy markers ANP and BNP, while its knockdown produced the opposite effect. In Ang II-induced H9C2 cells, which exhibited a significant increase of HNRNPH1 expression and increased expressions of ANP and BNP, HNRNPH1 knockdown obviously increased Circ-MYOCD expression, decreased MYOCD expression and lowered both ANP and BNP expressions. CONCLUSIONS HNRNPH1 regulates Circ-MYOCD back-splicing to influence the progression of myocardial hypertrophy.
Animals ; Rats ; RNA, Circular/genetics* ; Cardiomegaly/metabolism* ; Myocytes, Cardiac/metabolism* ; Heterogeneous-Nuclear Ribonucleoprotein Group F-H/metabolism* ; Cell Line ; RNA Splicing ; Angiotensin II ; RNA-Binding Proteins

Gallbladder cancer has an insidious onset,and most of the cases are in advanced stage at the time of diagnosis,with unfavorable prognosis. Radical surgery is the only potential curative method for gallbladder cancer at present,but radical surgery of advanced gallbladder cancer is difficult and the postoperative recurrence rate is high. Neoadjuvant therapy and conversion therapeutic modalities are of great significance to improve the rate of radical resection of advanced gallbladder cancer and reducing the risk of postoperative recurrence. The application and research of minimally invasive approach surgery in gallbladder cancer are increasing; organoid technology provides a new platform for precise and individualized treatment and new drug development, and the application of artificial intelligence combined with big data shows great potential in tumor diagnosis, surgical assistance and prognosis evaluation. Although these techniques provide more means to improve the therapeutic effect of advanced gallbladder cancer, there are still challenges in clinical practice and more high-quality clinical studies.

Objective To explore the function of electroacupuncture(EA)on body mass,fasting blood glucose,heat pain threshold,and transient receptor potential vanilloid 4(TRPV4)in the dorsal root ganglia(DRG)of rats with diabetic neuropathic pain(DNP).Methods A DNP rat model was formed by intraperitoneally injecting the animals with STZ.From days 15 to 21,bilateral Zusanli and Kunlun points of the DNP rat model were treated with electroacupuncture once daily for 30 min.We then measured their body mass,fasting blood glucose,and heat pain threshold.The co-expression of TRPV4 and NeuN in the rat L4～L6 DRG was detected by immunofluorescence.The effects of the TRPV4 agonist GSK1016790A on body mass,fasting blood glucose,and the heat pain threshold of DNP rats treated with electroacupuncture were detected.Results After the 7th day,body mass was significantly decreased(P<0.01)and fasting glucose was significantly increased(P<0.01)in the model group compared with the normal group.After the 21st day,compared with the model group,heat pain threshold of the model+electroacupuncture group was significantly higher(P<0.01);the results of co-expression of TRPV4 and NeuN immunofluorescence on rat L4～L6 DRG showed that:the expression of positive cells in the model group was significantly higher(P<0.01)than that in the normal group,the co-expression of TRPV4 and NeuN positive cells in L4～L6 DRG of rats in the model+electroacupuncture group was significantly lower(P<0.01)than that in the model group.The TRPV4 agonist GSK1016790A can reverse the downregulation of thermal pain threshold induced by electroacupuncture in DNP rats(P<0.01).Conclusion Electroacupuncture alleviated the DNP induced by STZ,and its mechanism may involve the inhibition of TRPV4 protein expression in the DRG.

Objective:A predictive model for cirrhosis-associated hepatic encephalopathy (HE) was constructed and validated using a machine learning algorithm to evaluate the predictive efficacy of the model.Methods:Clinical data of patients with liver cirrhosis (4 537 cases) in the medical record system and laboratory information system of the First Hospital of Jilin University from January 2018 to December 2019 were collected and analyzed retrospectively. Based on the inclusion and exclusion criteria, 474 patients were finally included in the study. Cohort 1 included patients with cirrhosis without HE (113 cases) and patients with cirrhosis complicated with HE (108 cases) from January to December 2018, and was used for feature screening, model building, optimal algorithm selection, and internal validation of the cirrhosis complicated with HE risk prediction model. Cohort 2 included patients with cirrhosis without HE (133 patients) and patients with cirrhosis complicated with HE (120 patients) from January 2019 to December 2019 for external validation. Lasso regression was utilized to identify key predictive variables, and various models such as extreme gradient boosting (XGBoost), light gradient boosting machine (LightGBM), random forest (RF), and support vector machine (SVM) were employed for model building and internal validation. The DeLong test was used to compare the predictive efficacy of the four models for HE, and the optimal algorithm was selected by combining the specificity or sensitivity. The area under the ROC curve, calibration curve and decision curve were applied to evaluate the predictive efficacy, accuracy of predicted probabilities and clinical utility of the model.Results:The 46 tests with<30% missing data in Cohort 1 were extracted as variables to be selected for modeling. Seven characteristic variables were obtained using Lasso regression screening, including hemoglobin (Hb), total bile acid (TBA), cholinesterase, total bilirubin, creatinine, prothrombin activity, and circulating platelets. The prediction model built by the LightGBM algorithm (HE-Lab7 model) predicted HE with an area under the curve (AUC) of 0.880, which was higher than that of XGBoost, RF, and SVM (all P<0.05), with a sensitivity of 0.825 and a specificity of 0.836. The Brier score of the calibration curve was 0.147, indicating that the predicted probability of the model is in good agreement with the actual probability of occurrence. Decision curves indicate that the model has a high clinical benefit. In Cohort 2, the HE-Lab7 model predicted HE with an AUC of 0.775, a sensitivity of 0.927, and a specificity of 0.758. Conclusion:The predictive efficacy of the cirrhosis-associated HE risk prediction model developed based on the optimal LightGBM algorithm using the large-scale test data based on four machine learning algorithms is good, which provides a reference basis for early prediction and identification of cirrhosis-associated HE.

BACKGROUND: Chronic kidney disease (CKD)-associated anemia (CKD-anemia) is associated with poor survival, and hemoglobin targets are often not achieved with current therapies. Phase 3 trials have demonstrated the treatment efficacy of roxadustat for CKD-anemia. This phase 4 study aims to evaluate the long-term (52-week) safety and effectiveness of roxadustat in a broad real-world patient population with CKD-anemia with and without dialysis in China. METHODS: This Phase 4 multicenter, open-label, prospective study, conducted from 24 November 2020 to 11 November 2022, evaluated the long-term safety and effectiveness of roxadustat for CKD-anemia in China. Patients aged ≥18 years with CKD-anemia with or without dialysis were included. The initial oral dose was 70-120 mg (weight-based followed by dose adjustment) over 52 weeks. The primary endpoint was safety based on adverse events (AEs). The secondary endpoints were hemoglobin changes from baseline and the proportion of patients who achieved mean hemoglobin ≥100 g/L. Effectiveness evaluable populations 1 (EE1) and EE2 included roxadustat-naïve and previously roxadustat-treated patients, respectively. The safety analysis set (SAF) included all patients who received ≥1 occasion. RESULTS: The EE1, EE2, and SAF populations included 1804, 193, and 2021 patients, respectively. In the SAF, the mean age was 50 ± 14 years, and 1087 patients (53.8%) were male. Mean baseline hemoglobin was 96.9 ± 14.0 g/L in EE1 and 100.3 ± 12.9 g/L in EE2. In EE1, the mean (95% confidence interval) hemoglobin changes from baseline over weeks 24-36 and 36-52 were 14.2 (13.5-14.9) g/L and 14.3 (13.5-15.0) g/L, respectively. Over weeks 24-36 and 36-52, 83.3% and 86.1% of patients in EE1 and 82.7% and 84.7% in EE2 achieved mean hemoglobin ≥100 g/L, respectively. In the SAF, 1643 (81.3%) patients experienced treatment-emergent AEs (TEAEs). Overall, 219 (10.8%) patients experienced drug-related TEAEs. Thirty-eight (1.9%) patients died of TEAEs (unrelated to the study drug). Vascular access thrombosis was uncommon. CONCLUSIONS: Roxadustat (52 weeks) increased hemoglobin and maintained the treatment target in Chinese patients with CKD-anemia with acceptable safety, supporting its use in real-world settings. REGISTRATION Chinese Clinical Trial Registry ( www.chictr.org.cn ) ChiCTR2100046322; CDE ( www.chinadrugtrials.org.cn ) CTR20201568.
Humans ; Male ; Female ; Anemia/etiology* ; Middle Aged ; Renal Insufficiency, Chronic/complications* ; Glycine/adverse effects* ; Isoquinolines/adverse effects* ; Aged ; Prospective Studies ; Adult ; Hemoglobins/metabolism* ; Treatment Outcome ; China ; Registries ; East Asian People

Objective To explore the function of electroacupuncture(EA)on body mass,fasting blood glucose,heat pain threshold,and transient receptor potential vanilloid 4(TRPV4)in the dorsal root ganglia(DRG)of rats with diabetic neuropathic pain(DNP).Methods A DNP rat model was formed by intraperitoneally injecting the animals with STZ.From days 15 to 21,bilateral Zusanli and Kunlun points of the DNP rat model were treated with electroacupuncture once daily for 30 min.We then measured their body mass,fasting blood glucose,and heat pain threshold.The co-expression of TRPV4 and NeuN in the rat L4～L6 DRG was detected by immunofluorescence.The effects of the TRPV4 agonist GSK1016790A on body mass,fasting blood glucose,and the heat pain threshold of DNP rats treated with electroacupuncture were detected.Results After the 7th day,body mass was significantly decreased(P<0.01)and fasting glucose was significantly increased(P<0.01)in the model group compared with the normal group.After the 21st day,compared with the model group,heat pain threshold of the model+electroacupuncture group was significantly higher(P<0.01);the results of co-expression of TRPV4 and NeuN immunofluorescence on rat L4～L6 DRG showed that:the expression of positive cells in the model group was significantly higher(P<0.01)than that in the normal group,the co-expression of TRPV4 and NeuN positive cells in L4～L6 DRG of rats in the model+electroacupuncture group was significantly lower(P<0.01)than that in the model group.The TRPV4 agonist GSK1016790A can reverse the downregulation of thermal pain threshold induced by electroacupuncture in DNP rats(P<0.01).Conclusion Electroacupuncture alleviated the DNP induced by STZ,and its mechanism may involve the inhibition of TRPV4 protein expression in the DRG.

Objective:A predictive model for cirrhosis-associated hepatic encephalopathy (HE) was constructed and validated using a machine learning algorithm to evaluate the predictive efficacy of the model.Methods:Clinical data of patients with liver cirrhosis (4 537 cases) in the medical record system and laboratory information system of the First Hospital of Jilin University from January 2018 to December 2019 were collected and analyzed retrospectively. Based on the inclusion and exclusion criteria, 474 patients were finally included in the study. Cohort 1 included patients with cirrhosis without HE (113 cases) and patients with cirrhosis complicated with HE (108 cases) from January to December 2018, and was used for feature screening, model building, optimal algorithm selection, and internal validation of the cirrhosis complicated with HE risk prediction model. Cohort 2 included patients with cirrhosis without HE (133 patients) and patients with cirrhosis complicated with HE (120 patients) from January 2019 to December 2019 for external validation. Lasso regression was utilized to identify key predictive variables, and various models such as extreme gradient boosting (XGBoost), light gradient boosting machine (LightGBM), random forest (RF), and support vector machine (SVM) were employed for model building and internal validation. The DeLong test was used to compare the predictive efficacy of the four models for HE, and the optimal algorithm was selected by combining the specificity or sensitivity. The area under the ROC curve, calibration curve and decision curve were applied to evaluate the predictive efficacy, accuracy of predicted probabilities and clinical utility of the model.Results:The 46 tests with<30% missing data in Cohort 1 were extracted as variables to be selected for modeling. Seven characteristic variables were obtained using Lasso regression screening, including hemoglobin (Hb), total bile acid (TBA), cholinesterase, total bilirubin, creatinine, prothrombin activity, and circulating platelets. The prediction model built by the LightGBM algorithm (HE-Lab7 model) predicted HE with an area under the curve (AUC) of 0.880, which was higher than that of XGBoost, RF, and SVM (all P<0.05), with a sensitivity of 0.825 and a specificity of 0.836. The Brier score of the calibration curve was 0.147, indicating that the predicted probability of the model is in good agreement with the actual probability of occurrence. Decision curves indicate that the model has a high clinical benefit. In Cohort 2, the HE-Lab7 model predicted HE with an AUC of 0.775, a sensitivity of 0.927, and a specificity of 0.758. Conclusion:The predictive efficacy of the cirrhosis-associated HE risk prediction model developed based on the optimal LightGBM algorithm using the large-scale test data based on four machine learning algorithms is good, which provides a reference basis for early prediction and identification of cirrhosis-associated HE.

Gallbladder cancer has an insidious onset,and most of the cases are in advanced stage at the time of diagnosis,with unfavorable prognosis. Radical surgery is the only potential curative method for gallbladder cancer at present,but radical surgery of advanced gallbladder cancer is difficult and the postoperative recurrence rate is high. Neoadjuvant therapy and conversion therapeutic modalities are of great significance to improve the rate of radical resection of advanced gallbladder cancer and reducing the risk of postoperative recurrence. The application and research of minimally invasive approach surgery in gallbladder cancer are increasing; organoid technology provides a new platform for precise and individualized treatment and new drug development, and the application of artificial intelligence combined with big data shows great potential in tumor diagnosis, surgical assistance and prognosis evaluation. Although these techniques provide more means to improve the therapeutic effect of advanced gallbladder cancer, there are still challenges in clinical practice and more high-quality clinical studies.