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Objective·To investigate the current situation and distribution characteristics of chronic comorbidities, and to provide reference for further improving the self-management of comorbidities and implementing the whole course and all-round management of comorbidity.Methods·Two thousand and forty-five inpatients in the Department of Geriatrics,Renji Hospital, Shanghai Jiao Tong University School of Medicine were enrolled in this study from December 2020 to February 2023. The general vital signs, routine laboratory examination and disease status were collected. The epidemiological distribution characteristics of chronic diseases and comorbidities were analyzed.Results·The incidence of chronic diseases in the surveyed population was 99.6%, and the incidence of comorbidities was 94.2%. The top 5 chronic diseases were hypertension (43.68%), diabetes mellitus (24.81%), malignant tumor (21.48%), hyperlipidemia (18.38%) and coronary heart disease (11.99%). The detection rates of hypertension, diabetes mellitus, coronary heart disease, chronic obstructive pulmonary disease, stoke and chronic kidney disease in males were significantly higher than those in females (P

Objective·To explore the correlation between comorbidities of chronic non-communicable diseases (chronic diseases), phase angle (PhA), and muscle mass decline associated with sarcopenia in the elderly, and the predictive value of chronic disease comorbidities and PhA in muscle mass decline in the elderly.Methods·By retrospectively screening inpatients aged ≥60 years who were admitted to the Department of Geriatrics, Renji Hospital, Shanghai Jiao Tong University School of Medicine from August 1, 2018 to July 31, 2019, basic information and medical history of the patients (gender, age, number of medications used, number of comorbidities, presence of osteoporosis, smoking history, etc.) were collected, as well as laboratory examination indicators (hemoglobin, albumin, serum creatinine, serum uric acid, ferritin, vitamin D, triacylglycerol, total cholesterol, high-density lipoprotein, low-density lipoprotein, etc.). The age-adjusted Charlson comorbidity index (aCCI) was calculated. The InBody S10 bioelectrical impedance body composition detector was used to test the body composition. Body mass index (BMI), skeletal muscle mass index (SMI), and PhA were collected. Some patients underwent measurement of grip strength. Muscle mass decline was diagnosed by using the SMI values recommended by the 2019 Asian Working Group for Sarcopenia (AWGS) (≤7.0 kg/m2 for males and ≤5.7 kg/m2 for females). According to the measured SMI values, patients were divided into a group with normal muscle mass and a group with muscle mass decline. Univariate and multivariate Logistic analyses were employed to investigate the risk factors associated with muscle mass decline related to sarcopenia in the elderly. Additionally, the receiver operator characteristic (ROC) curve and the area under the curve were utilized to predict the significance of these factors in muscle mass decline.Results·A total of 359 chronic disease patients were enrolled, including 226 males and 133 females. There were 241 cases in the normal muscle mass group and 118 cases in the muscle mass decline group. The incidence of muscle mass decline related to sarcopenia in the elderly was 32.9%. The univariate Logistic regression analysis showed that age (OR=1.036, 95%CI 1.013‒1.060), comorbidities (OR=1.117, 95%CI 1.025‒1.217), aCCI (OR=1.123, 95%CI 1.031‒1.222), and high-density lipoprotein (OR=3.688, 95%CI 2.065‒6.622) were positively correlated with the risk of muscle mass decline in the elderly. BMI (OR=0.514, 95%CI 0.443‒0.597), PhA (OR=0.195, 95%CI 0.126‒0.303), hemoglobin (OR=0.984, 95%CI 0.972‒0.996) and triacylglycerol (OR=0.606, 95%CI 0.424‒0.866) were negatively correlated with the risk of muscle mass decline in the elderly. Multivariate Logistic regression model indicated that PhA (OR=0.338, 95%CI 0.119‒0.959) and BMI (OR=0.634, 95%CI 0.476‒0.844) were negatively correlated with the risk of muscle mass decline in elderly. The area under the ROC curve for predicting muscle mass decline related to sarcopenia in elderly by using BMI and PhA was 0.893 (95%CI 0.855‒0.931) and 0.786 (95%CI 0.736‒0.837), respectively. The sensitivity was 0.724 and 0.676, respectively. The specificity was 0.916 and 0.762, respectively. When BMI combined with PhA predicted muscle mass decline in the elderly, the area under the ROC curve was 0.917 (95%CI 0.883‒0.951). The sensitivity was 0.867, and the specificity was 0.860.Conclusion·aCCI is correlated with muscle mass decline associated with sarcopenia in the elderly. As BMI and PhA decrease, the risk of muscle mass decline in the elderly increases. The combination of BMI and PhA has a high predictive value in muscle mass decline in the elderly.No predictive value of chronic diseases comorbidities in muscle mass decline related to sarcopenia in the elderly is found.

PD‐1 monoclonal antibodies (mAb) have demonstrated remarkable efficacy in a variety of cancers, including Hepatocellular carcinoma (HCC). However, the patient response rates remain suboptimal, and a significant proportion of initial responders may develop resistance to this therapeutic approach. Akkermansia muciniphila (AKK), a microorganism implicated in multiple human diseases, has been reported to be more abundant in patients who exhibit favorable responses to PD‐1mAb. However, the underlying mechanism has yet to be elucidated. In our study, we found that AKK could enhance the efficacy of PD‐1mAb against HCC in a tumor‐bearing mouse model. It promotes HCC tumor cells apoptosis and raise the CD8+T proportion in the tumor microenvironment. Additionally, AKK downregulates PD‐L1 expression in tumor cells. Furthermore, the analysis of metabonomics demonstrates that AKK induces alterations in the host's bile acid metabolism, leading to a significant increase in serum TUDCA levels. Considering the immunosuppresive roles of TUDCA in HCC development, it is plausible to speculate that AKK may reinforce the immunotherapy of PD‐1mAb against HCC through its impact on bile acid metabolism. [ABSTRACT FROM AUTHOR]

Abstract Background Hyperglycaemia in diabetes mellitus (DM) alters gene expression regulation in various organs and contributes to long term vascular and renal complications. We aimed to generate novel renal genome-wide gene transcription data in rat models of diabetes in order to test the responsiveness to hyperglycaemia and renal structural changes of positional candidate genes at selected diabetic nephropathy (DN) susceptibility loci. Methods Both Affymetrix and Illumina technologies were used to identify significant quantitative changes in the abundance of over 15,000 transcripts in kidney of models of spontaneous (genetically determined) mild hyperglycaemia and insulin resistance (Goto-Kakizaki-GK) and experimentally induced severe hyperglycaemia (Wistar-Kyoto-WKY rats injected with streptozotocin [STZ]). Results Different patterns of transcription regulation in the two rat models of diabetes likely underlie the roles of genetic variants and hyperglycaemia severity. The impact of prolonged hyperglycaemia on gene expression changes was more profound in STZ-WKY rats than in GK rats and involved largely different sets of genes. These included genes already tested in genetic studies of DN and a large number of protein coding sequences of unknown function which can be considered as functional and, when they map to DN loci, positional candidates for DN. Further expression analysis of rat orthologs of human DN positional candidate genes provided functional annotations of known and novel genes that are responsive to hyperglycaemia and may contribute to renal functional and/or structural alterations. Conclusion Combining transcriptomics in animal models and comparative genomics provides important information to improve functional annotations of disease susceptibility loci in humans and experimental support for testing candidate genes in human genetics.

Background: Isocitrate dehydrogenase wild-type (WT) glioblastoma (GBM) accounts for 90% of all GBMs, yet only 27% of isocitrate dehydrogenase WT-GBMs have p53 mutations. However, the tumor surveillance function of WT-p53 in GBM is subverted by mechanisms that are not fully understood.Methods: We investigated the proteolytic inactivation of WT-p53 by asparaginyl endopeptidase (AEP) and its effects on GBM progression in cancer cells, murine models, and patients' specimens using biochemical and functional assays. The sera of healthy donors (n = 48) and GBM patients (n = 20) were examined by enzyme-linked immunosorbent assay. Furthermore, effects of AEP inhibitors on GBM progression were evaluated in murine models (n = 6-8 per group). The statistical significance between groups was determined using two-tailed Student t tests.Results: We demonstrate that AEP binds to and directly cleaves WT-p53, resulting in the inhibition of WT-p53-mediated tumor suppressor function in both tumor cells and stromal cells via extracellular vesicle communication. High expression of uncleavable p53-N311A-mutant rescue AEP-induced tumorigenesis, proliferation, and anti-apoptotic abilities. Knock down or pharmacological inhibition of AEP reduced tumorigenesis and prolonged survival in murine models. However, overexpression of AEP promoted tumorigenesis and shortened the survival time. Moreover, high AEP levels in GBM tissues were associated with a poor prognosis of GBM patients (n = 83; hazard ratio = 3.94, 95% confidence interval = 1.87 to 8.28; P < .001). A correlation was found between high plasma AEP levels and a larger tumor size in GBM patients (r = 0.6, P = .03), which decreased dramatically after surgery.Conclusions: Our results indicate that AEP promotes GBM progression via inactivation of WT-p53 and may serve as a prognostic and therapeutic target for GBM. [ABSTRACT FROM AUTHOR]

Background: Body mass index (BMI), waist circumference (WC), visceral adiposity index (VAI), triglyceride glucose index (TyG), TyG-BMI, and TyG-WC have been reported as markers of insulin resistance or type 2 diabetes mellitus (T2DM). However, little is known about the associations between the aforementioned markers and the risk of prediabetes and diabetes in first-degree relatives (FDRs) of T2DM patients.Methods: 1544 FDRs of T2DM patients (635 men and 909 women) were enrolled in the initial cross-sectional study and all of them finished corresponding examinations. Logistic regression analysis and receiver operating characteristic (ROC) curve were used to compare and identify the associations of the six parameters (BMI, WC, VAI, TyG, TyG-BMI and TyG-WC) with the prevalence of prediabetes and diabetes. Subsequently, 452 of them were followed-up for an average of 5 years. Cox proportional hazard regression model was applied to confirm the predictive value of the optimal marker.Results: Among the indices, TyG-WC was more strongly associated with the prevalence of prediabetes and diabetes. Compared with participants in the lowest quartile of TyG-WC, the adjusted odds ratio and 95 % CIs for prediabetes and diabetes was 11.19 (7.62-16.42) for those in the top quartile of TyG-WC. Moreover, the largest AUC was also observed in TyG-WC (0.765, 95 % CIs 0.741-0.789, P < 0.001). The robust predictive value of TyG-WC was further confirmed in the follow-up study (HR: 7.13, 95 % CIs 3.41-14.90, P < 0.001).Conclusions: TyG-WC is a novel and clinically effective marker for early identifying the risks of prediabetes and diabetes in FDRs of T2DM patients. [ABSTRACT FROM AUTHOR]