Development and validation of a machine learning-based model to predict isolated post-challenge hyperglycemia in middle-aged and elder adults: Analysis from a multicentric study.

INTRODUCTION: Due to the high cost and complexity, the oral glucose tolerance test is not adopted as the screening method for identifying diabetes patients, which leads to the misdiagnosis of patients with isolated post-challenge hyperglycemia (IPH), that is., patients with normal fasting plasma glucose (<7.0 mmoL/L) and abnormal 2-h postprandial blood glucose (≥11.1 mmoL/L). We aimed to develop a model to differentiate individuals with IPH from the normal population. METHODS: Data from 54301 eligible participants were obtained from the Risk Evaluation of Cancers in Chinese Diabetic Individuals: a longitudinal (REACTION) study in China. Data from 37740 participants were used to develop the diagnostic system. External validation was performed among 16561 participants. Three machine learning algorithms were used to create the predictive models, which were further evaluated by various classification algorithms to establish the best predictive model. RESULTS: Ten features were selected to develop an IPH diagnosis system (IPHDS) based on an artificial neural network. In external validation, the AUC of the IPHDS was 0.823 (95% CI 0.811-0.836), which was significantly higher than the AUC of the Taiwan model [0.799 (0.786-0.813)] and that of the Chinese Diabetes Risk Score model [0.648 (0.635-0.662)]. The IPHDS model had a sensitivity of 75.6% and a specificity of 74.6%. This model outperformed the Taiwan and CDRS models in subgroup analyses. An online site with instant predictions was deployed at https://app-iphds-e1fc405c8a69.herokuapp.com/. CONCLUSIONS: The proposed IPHDS could be a convenient and user-friendly screening tool for diabetes during health examinations in a large general population.

Genetic association of glycemic traits and antihyperglycemic agent target genes with the risk of lung cancer: A Mendelian randomization study.

AIMS: To evaluate the potential causal effect of glycemic traits on lung cancer and investigate the impact of antihyperglycemic agent-target genes on lung cancer risk. METHODS: Genetic variants associated with glycemic traits, antihyperglycemic agent-target genes, and lung cancer were extracted from the Meta-Analyses of Glucose and Insulin-related traits Consortium (MAGIC), expression quantitative trait loci (eQTLs), protein quantitative trait loci (pQTLs), and the International Lung Cancer Consortium (ILCCO), respectively. Mendelian randomization (MR) analyses were performed to examine the associations of glycemic traits and antihyperglycemic agent-target genes with lung cancer. Mediation analysis was conducted to explore whether overweight operated as a mediator between antihyperglycemic agents and lung cancer outcomes. RESULTS: Genetically determined glycated hemoglobin A1c levels were associated with squamous cell lung cancer (OR = 1.78; 95 % CI, 1.08-2.92; p = 0.023). The PRKAB1 gene (the target of metformin) was associated with a lower risk of developing lung adenocarcinoma (OR = 0.85; 95 % CI, 0.76-0.96; p = 0.006). Further mediation analyses did not support overweight as a mediator between PRKAB1 activation and lung adenocarcinoma. CONCLUSION: Our analyses suggest an association of genetically determined abnormal glycemic traits with squamous cell lung cancer. The potential association between PRKAB1 activation and a reduced risk of developing lung adenocarcinoma appears to be independent of the anti-obesity effects of metformin, suggesting that PRKAB1 activation may have a direct protective effect on lung adenocarcinoma development.

Assessment of prolonged proteasome inhibition through ixazomib-based oral regimen on newly diagnosed and first-relapsed multiple myeloma: A real-world Chinese cohort study.

OBJECTIVE: To evaluate the effectiveness, safety, and convenience of in-class transition (iCT) from intravenous bortezomib-based induction to ixazomib-based oral regimens. METHODS: This retrospective real-world study was conducted in 16 Chinese hospitals between October 2017 and April 2023 and analyzed newly diagnosed (NDMM) and first-line relapsed multiple myeloma (FRMM) patients who attained at least a partial response from bortezomib-based induction therapy, followed by an ixazomib-based oral regimen for 2 year or until disease progression or intolerable toxicity. RESULTS: The study enrolled 199 patients, median age: 63 years old, male 55.4%, 53% as high risk (HR), and 47% as standard risk. Cytogenetic risk stratification by metaphase fluorescence in situ hybridization (M-FISH), based on the Mayo Clinic risk stratification system. The median duration of total PI therapy was 11 months, with ixazomib-based treatment spanning 6 months. At the 20-month median follow-up, 53% of patients remained on therapy. The 24-month PFS rate was 84.3% from the initiation of bortezomib-based induction and 83.4% from the start of ixazomib-based treatment. Overall response rate (ORR) was 100% post-bortezomib induction and 90% following 6 cycles of the ixazomib-based regimen. Based on the Sankey diagrams, 89.51% of patients maintained or improved their disease response after 2 cycles of iCT, 6 cycles (90.14%), and 12 cycles (80%). The HR level of Mayo was found to be a significant independent factor in a worse remission (hazard ratio (HR) 2.55; p = 0.033). Ixazomib's safety profile aligned with previous clinical trial data, with 49% of patients experiencing at least one AE of any grade. The most common AEs included peripheral neuropathy, nausea and vomiting, diarrhea, thrombocytopenia, and granulocytopenia. CONCLUSION: In the real-world Chinese MM population, NDMM and FRMM patients responded favorably to PI-based continuous therapy, demonstrating substantial response rates. The ixazomib-based iCT allows for sustained PI-based treatment, offering promising efficacy and tolerable AEs.

Frailty mediating the causality between leucocyte telomere length and mortality: a cohort study of 440,551 UK Biobank participants.

Introduction: Previous studies reported leucocyte telomere length (LTL) and frailty were associated with mortality, but it remains unclear whether frailty serves as a mediator in the relationship between leucocyte telomere length and mortality risk. This study aimed to evaluate how measuring LTL and frailty can support early monitoring and prevention of risk of mortality from the prospective of predictive, preventive, and personalized medicine (PPPM/3PM). Methods: We included 440,551 participants from the UK Biobank between the baseline visit (2006-2010) and November 30, 2022. The time-dependent Cox proportional hazards model was conducted to assess the association between LTL and frailty index with the risk of mortality. Furthermore, we conducted causal mediation analyses to examine the extent to which frailty mediated the association between LTL and mortality. Results: During a median follow-up of 13.74 years, each SD increase in LTL significantly decreased the risk of all-cause [hazard ratio (HR): 0.94, 95% confidence interval (CI): 0.93-0.95] and CVD-specific mortality (HR: 0.92, 95% CI: 0.90-0.95). The SD increase in FI elevated the risk of all-cause (HR: 1.35, 95% CI: 1.34-1.36), CVD-specific (HR: 1.47, 95% CI: 1.44-1.50), and cancer-specific mortality (HR: 1.22, 95% CI: 1.20-1.24). Frailty mediated approximately 10% of the association between LTL and all-cause and CVD-specific mortality. Conclusions: Our results indicate that frailty mediates the effect of LTL on all-cause and CVD-specific mortality. There findings might be valuable to predict, prevent, and reduce mortality through primary prevention and healthcare in context of PPPM. Supplementary Information: The online version contains supplementary material available at 10.1007/s13167-024-00355-7.

Revealing genes associated with cervical cancer in distinct immune cells: A comprehensive Mendelian randomization analysis.

Human papillomavirus can be contracted by sexually active women. However, only a small proportion of these infections persist and have the potential to progress into cervical cancers, indicating a significant involvement of the immune system in cervical cancer development. Despite this, our understanding of the precise contributions of genes from different immune cell types in cervical cancers remains limited. Therefore, the primary objective of our study was to investigate the potential causal relationships between specific immune cell genes and the development of cervical cancers. By accessing expression quantitative trait loci datasets of 14 distinct immune cell types and genome wide association study of cervical cancers, we employed the summary data-based Mendelian randomization (SMR) along with multi-single nucleotide polymorphism (SNP)-based SMR to identify significant genes associated with cervical cancers. Colocalization analysis was further conducted to explore the shared genetic causality. A total of 10 genes across 11 immune cell types (26 significant gene-trait associations) were found to be associated with cervical cancers after false discovery rate correction. Notably, the ORMDL3, BRK1 and HMGN1 gene expression levels showed significant association with cervical cancer in specific immune cell types, respectively. These associations were supported by strong evidence of colocalization analyses. Our study has identified several genes in different immune cells that were associated with cervical cancer. However, further research is necessary to confirm these findings and provide more comprehensive insights into the association between these gene expressions and cervical cancer risk.

Environmental factors affecting the risk of generalization for ocular-onset myasthenia gravis: a nationwide cohort study.

BACKGROUND: The environmental effects on the prognosis of ocular myasthenia gravis (OMG) remain largely unexplored. AIM: To investigate the association between specific environmental factors and the generalization of OMG. DESIGN: The cohort study was conducted in China based on a nationwide multicenter database. METHODS: Adult patients with OMG at onset, who were followed up for at least 2 years until May 2022, were included. We collected data on demographic and clinical factors, as well as environmental factors, including latitude, socioeconomic status (per capita disposable income [PDI] at provincial level and education) and smoking. The study outcome was the time to the development of generalized myasthenia gravis (GMG). Cox models were employed to examine the association between environmental exposures and generalization. Restricted cubic spline was used to model the association of latitude with generalization risk. RESULTS: A total of 1396 participants were included. During a median follow-up of 5.15 (interquartile range [IQR] 3.37-9.03) years, 735 patients developed GMG within a median of 5.69 (IQR 1.10-15.66) years. Latitude of 20-50°N showed a U-shaped relation with generalization risk, with the lowest risk at around 30°N; both higher and lower latitudes were associated with the increased risk (P for non-linearity <0.001). Living in areas with lower PDI had 1.28-2.11 times higher risk of generalization. No significant association was observed with education or smoking. CONCLUSIONS: Latitude and provincial-level PDI were associated with the generalization of OMG in China. Further studies are warranted to validate our findings and investigate their potential applications in clinical practice and health policy.

Mental health outcomes in parents of children with a cancer diagnosis in Sweden: A nationwide cohort study.

Background: The diagnosis of paediatric cancer is a crisis for the parents who are the primary caregivers of the affected child. A comprehensive assessment of the longitudinal impact of childhood cancer on parental mental health and the potential sex differences between the parents is lacking. Thus, we aimed to explore the subsequent short- and long-term mental health outcomes among the parents of children with cancer and examine whether the outcomes vary between the mother and father. Methods: By combining several Swedish registers, parents of a child (ages 0-14 years) with a cancer diagnosis between Jan 1, 2006, and Dec 31, 2016 were identified. For each parent of children with cancer, up to five mothers or fathers of cancer-free children were randomly selected and matched, respectively. Hospital contacts for any mental health disorders between 5 years before and 7 years after the diagnosis of childhood cancer were retrieved. An interrupted time series negative binomial regression was performed to assess the short- and long-term impact of a childhood cancer diagnosis on the parents' subsequent mental health outcomes. Findings: 16,199 mothers (2852 with a child with cancer and 13,347 without) and 15,708 fathers (2769 with a child with cancer and 12,939 without) were included in this study. Compared with mothers of children without cancer, mothers of children with cancer had higher risks of mental health disorders in the first year after diagnosis (rate ratio [RR] and 95% Confidence Interval [CI], 1.17 (1.03-1.32)), and notably, the adverse impact became more severe over time (RR and 95% CI, 1.36 (1.07-1.74), in the seventh year). For fathers of children with cancer, the risk of mental health disorders was continuously higher compared to matched comparisons (RR and 95% CI, 1.31 (1.01-1.71)). Interpretation: Our findings suggested that parental mental health was affected continuously by a diagnosis of childhood cancer in their children. In particular, the mother's mental health was affected more severely. Customised psychological services or interventions are highly needed for the parents of children with cancer. Funding: Swedish Research Council, Allmänna Sjukhusets i Malmö Stiftelsen för bekämpande av cancer, Swedish Heart-Lung Foundation, ALF funding from Region Skåne and China Scholarship Council.

Prevalence, awareness, treatment and control of type 2 diabetes and its determinants among Mongolians in China: a cross-sectional analysis of IMAGINS 2015-2020.

OBJECTIVES: This study aims to estimate the prevalence, awareness, treatment and control rates of type 2 diabetes (T2D) and pre-diabetes as well as to identify its associated factors among Mongolians living in the Inner Mongolia Autonomous Region, China. DESIGN: Cross-sectional study. SETTING AND PARTICIPANTS: This sample included 11 361 Mongolian participants from the Inner Mongolian Healthy Aging Intervention Study, a population-based screening project consisting of 141 255 adults aged above 35 years in Inner Mongolia from 2015 to 31 December 2020. OUTCOME MEASURES: The prevalence and 95% CIs of T2D and pre-diabetes were calculated. Factors associated with the prevalence, awareness, treatment and control of T2D were explored by a binomial logistic regression. RESULTS: A total of 17.2% (95% CI 16.5% to 17.9%) of the sample had T2D, of whom 34.0% (95% CI 31.9% to 36.1%) were aware of their diagnosis, 24.7% (95% CI 22.8% to 26.6%) were taking prescribed antidiabetic medications, 6.7% (95% CI 5.6% to 7.8%) had achieved control and 27.5% (95 % CI 26.7% to 28.3%) had pre-diabetes. The prevalence of T2D increased with increasing age, male, lower education level, smoking, obesity and a history of hypertension or dyslipidaemia (all p<0.05). CONCLUSIONS: T2D is highly prevalent, with suboptimal awareness, treatment and control rates, and an escalating health challenge among the Mongolian population. Broad-based strategies, including diabetes prevention education, better screening and affordable treatment, should be implemented to raise awareness, treatment and control rates of T2D in Inner Mongolia.

Sex differences in the non-linear association between BMI and LDL cholesterol in middle-aged and older adults: findings from two nationally representative surveys in China.

BACKGROUND: The relationship between body mass index (BMI) and low-density lipoprotein cholesterol (LDL-C) has not been clearly elucidated in middle-aged and older adults. This study aimed to evaluate the non-linear dose-response relationship between BMI and LDL-C in males and females. METHODS: Data was obtained from two nationally representative surveys in China-the China Health and Nutrition Survey (CHNS, 2009) and China Health and Retirement Longitudinal Study (CHARLS, 2011-2012). To evaluate the sex differences in the association between BMI and LDL-C, the generalized additive models with a smooth function for continuous BMI and smooth-factor interaction for sexes with BMI were used. Segmented regressions were fitted to calculate the slopes with different estimated breakpoints among females and males. RESULTS: A total of 12,273 participants (47.1% male) aged 45 to 75 years were included. The generalized additive models revealed that a non-linear relationship between BMI and LDL-C level in both sexes after adjustment for age, residence, education levels, marital status, drinking, smoking status, and cohort (CHNS or CHARLS). Slopes of the association between BMI and LDL-C association changed at BMI 20.3 kg/m2 (95% CI: 18.8 to 21.8) in females and 27.1 kg/m2 (95% CI: 25. 8 to 28.4) in males. Below these BMI breakpoints, LDL-C levels increased 1.84 (95% CI: 1.45 to 2.31) in males and 3.49 (95% CI: 1.54 to 5.45) mg/dL per kg/m2 in females. However, LDL-C levels declined - 1.50 (95% CI: - 2.92 to - 0.09) mg/dL per kg/m2 above BMI of 27.1 kg/m2 in males. The non-linear association BMI and LDL-C in males and females was varied by cohort source, age groups, and the number of metabolic syndrome criteria. CONCLUSIONS: In the Chinese middle aged and older adults, the BMI and LDL-C relationship was inverted U-shaped with a high level of LDL-C at a BMI of 27.1 kg/m2 in males, and an approximately linear association was observed in females.

CYP3A5*3 polymorphism and age affect tacrolimus blood trough concentration in myasthenia gravis patients.

The study aims to identify clinical factors affecting tacrolimus blood trough concentration (C0) in myasthenia gravis (MG) patients and to optimize the initial dose of tacrolimus in MG treatment. A total of 103 MG patients participated in this study, and their clinical factors, medication regimens, C0 values and CYP3A5*3 polymorphisms were collected in detail. We used a linear mixed model to analyze the effect of multiple factors on the dosage-weighted C0 (C0:D) and performed subgroup analyses to investigate the consistency of correlations between influencing factors and the C0:D ratios. Among all factors, CYP3A5*3 polymorphism and age showed a strong positive correlation with C0:D ratios. The C0:D ratios (ng/ml·mg-1) were higher for CYP3A5*3/*3 than for CYP3A5*1 (mean difference: 1.038, 95% confidence interval [CI]: 0.820-1.256, P-value <0.001), and for age in the range of 45-64 and ≥ 65 years than for age < 45 years (mean difference [95% CI] and P-value: 0.531[0.257-0.805] and P-value <0.001, 0.703 [0.377-1.029] and P-value <0.001, respectively). The C0:D ratios were not related to corticosteroid dosage, body weight, sex, hematocrit or the concomitant use of calcium channel blockers. The consistencies of the correlations between C0:D ratios and CYP3A5*3 polymorphism or age were confirmed by subgroup analyses. Thus, CYP3A5*3 polymorphism and age should be considered in optimizing the initial dose of tacrolimus for MG treatment.

Histologic subtype classification of non-small cell lung cancer using PET/CT images.

PURPOSES: To evaluate the capability of PET/CT images for differentiating the histologic subtypes of non-small cell lung cancer (NSCLC) and to identify the optimal model from radiomics-based machine learning/deep learning algorithms. METHODS: In this study, 867 patients with adenocarcinoma (ADC) and 552 patients with squamous cell carcinoma (SCC) were retrospectively analysed. A stratified random sample of 283 patients (20%) was used as the testing set (173 ADC and 110 SCC); the remaining data were used as the training set. A total of 688 features were extracted from each outlined tumour region. Ten feature selection techniques, ten machine learning (ML) models and the VGG16 deep learning (DL) algorithm were evaluated to construct an optimal classification model for the differential diagnosis of ADC and SCC. Tenfold cross-validation and grid search technique were employed to evaluate and optimize the model hyperparameters on the training dataset. The area under the receiver operating characteristic curve (AUROC), accuracy, precision, sensitivity and specificity was used to evaluate the performance of the models on the test dataset. RESULTS: Fifty top-ranked subset features were selected by each feature selection technique for classification. The linear discriminant analysis (LDA) (AUROC, 0.863; accuracy, 0.794) and support vector machine (SVM) (AUROC, 0.863; accuracy, 0.792) classifiers, both of which coupled with the ℓ2,1NR feature selection method, achieved optimal performance. The random forest (RF) classifier (AUROC, 0.824; accuracy, 0.775) and ℓ2,1NR feature selection method (AUROC, 0.815; accuracy, 0.764) showed excellent average performance among the classifiers and feature selection methods employed in our study, respectively. Furthermore, the VGG16 DL algorithm (AUROC, 0.903; accuracy, 0.841) outperformed all conventional machine learning methods in combination with radiomics. CONCLUSION: Employing radiomic machine learning/deep learning algorithms could help radiologists to differentiate the histologic subtypes of NSCLC via PET/CT images.

Modelling biological age based on plasma peptides in Han Chinese adults.

Age-related disease burdens increased over time, and whether plasma peptides can be used to accurately predict age in order to explain the variation in biological indicators remains inadequately understood. Here we first developed a biological age model based on plasma peptides in 1890 Chinese Han adults. Based on mass spectrometry, 84 peptides were detected with masses in the range of 0.6-10.0 kDa, and 13 of these peptides were identified as known amino acid sequences. Five of these thirteen plasma peptides, including fragments of apolipoprotein A-I (m/z 2883.99), fibrinogen alpha chain (m/z 3060.13), complement C3 (m/z 2190.59), complement C4-A (m/z 1898.21), and breast cancer type 2 susceptibility protein (m/z 1607.84) were finally included in the final model by performing a multivariate linear regression with stepwise selection. This biological age model accounted for 72.3% of the variation in chronological age. Furthermore, the linear correlation between the actual age and biological age was 0.851 (95% confidence interval: 0.836-0.864) and 0.842 (95% confidence interval: 0.810-0.869) in the training and validation sets, respectively. The biological age based on plasma peptides has potential positive effects on primary prevention, and its biological meaning warrants further investigation.

Neuroprotective mechanism involved in spinal cord stimulation postconditioning.

OBJECTIVES: Delayed paraplegia developed postoperatively after thoracoabdominal aneurysm surgery is primarily associated with spinal cord ischemia/reperfusion injury. Our previous study suggested that spinal cord stimulation postconditioning protected the spinal cord from ischemia/reperfusion injury through microglia inhibition. In this study, we further investigated whether α7 nicotinic acetylcholine receptors were involved in the neuroprotective mechanism of spinal cord stimulation. METHODS: Rabbits were randomly assigned to sham, control, 2 Hz, α-bungarotoxin, and 2 Hz-α-bungarotoxin groups (n = 24/group). Transient spinal cord ischemia was performed on all rabbits except rabbits in the sham group. Rabbits in the control group received no further intervention, rabbits in the 2 Hz group were given 2 Hz spinal cord stimulation, rabbits in the α-bungarotoxin group received prescribed intrathecal α-bungarotoxin (α-bungarotoxin, a specific α7 nicotinic acetylcholine receptor antagonist) injections, and rabbits in the 2 Hz-α-bungarotoxin group received both α-bungarotoxin injections and 2 Hz spinal cord stimulation. Hind-limb neurologic function was assessed, and spinal cord histologic examination, terminal deoxynucleotidyl transferase-mediated dUTP nick end labeling staining, and microglia staining were performed at 8 hours, 1 day, 3 days, and 7 days of reperfusion. RESULTS: Rabbits in the 2 Hz group had significantly better neurologic functions, more α-motor neurons, and lower terminal deoxynucleotidyl transferase-mediated dUTP nick end labeling-positive neuron rates and microglia area/anterior horn area ratios (microglia area ratios) than the control group. The neurologic functions of the α-bungarotoxin group were significantly worse than those of the control group, whereas other results were not significantly different from the control group. The results of the 2 Hz-α-bungarotoxin group were insignificant to the control group except for the terminal deoxynucleotidyl transferase-mediated dUTP nick end labeling-positive neuron rates, which were significantly lower than in the control group. CONCLUSIONS: The neuroprotective effects of spinal cord stimulation postconditioning against spinal cord ischemia/reperfusion injury were partially mediated by activating α7 nicotinic acetylcholine receptors.

Association of Depressive Symptoms With Incident Cardiovascular Diseases in Middle-Aged and Older Chinese Adults.

Importance: The prevalence of depressive symptoms among older adults has become an increasingly important public health priority. Elevated depressive symptoms are well documented among elderly people with cardiovascular disease (CVD), but studies conducted among Chinese adults are scarce. Objective: To estimate the association between depressive symptoms and incident CVD among middle-aged and older Chinese adults. Design, Setting, and Participants: The China Health and Retirement Longitudinal Study is an ongoing nationally representative prospective cohort study that was initiated in 2011. This cohort study included 12 417 middle-aged and older Chinese adults without heart disease and stroke at baseline. Statistical analysis was conducted from April 25, 2018, to December 13, 2018. Exposure: Depressive symptoms were assessed using the validated 10-item of Center for Epidemiologic Studies Depression Scale. Main Outcomes and Measures: Incident CVD (ie, self-reported physician-diagnosed heart disease and stroke combined) was followed-up from June 1, 2011, to June 31, 2015. The Center for Epidemiologic Studies Depression Scale total score ranges from 0 to 30, with a score of 12 or more indicating elevated depressive symptoms. Results: Of the 12 417 participants (mean [SD] age at baseline, 58.40 [9.51] years), 6113 (49.2%) were men. During the 4 years of follow-up, 1088 incident CVD cases were identified. Elevated depressive symptoms were independently associated with an increased CVD risk (adjusted hazard ratio, 1.39; 95% CI, 1.22-1.58) after adjusting for age, sex, residence, marital status, educational level, smoking status, drinking status, systolic blood pressure, and body mass index; history of diabetes, hypertension, dyslipidemia, and chronic kidney disease; and use of hypertension medications, diabetes medications, and lipid-lowering therapy. Of the 10 individual depressive symptoms measured by the Center for Epidemiologic Studies Depression Scale, only 2 symptoms, restless sleep (adjusted hazard ratio, 1.21; 95% CI, 1.06-1.39) and loneliness (adjusted hazard ratio, 1.21; 95% CI, 1.02-1.44), were significantly associated with incident CVD. Conclusions and Relevance: Elevated depressive symptoms overall and 2 individual symptoms (restless sleep and loneliness) were significantly associated with incident CVD among middle-aged and older Chinese adults.

Disability Transitions and Health Expectancies among Elderly People Aged 65 Years and Over in China: A Nationwide Longitudinal Study.

Disability has become a critical issue among elderly populations, yet limited large-scale research related to this issue has been conducted in China, an aging society. This study explored sex and urban-rural differences in disability transitions and life expectancies among older adults in China. Data were collected from the Chinese Longitudinal Health Longevity Survey (CLHLS), which enrolled people aged 65 and older and was conducted in randomly selected counties and cities across 22 provinces in China. Disability was diagnosed based on basic activities of daily living (BADLs) and instrumental activities of daily living (IADLs). Several individual characteristics were assessed, including sociodemographic factors (age, sex and region, etc.) and health behaviors (currently smoking, currently drinking, etc.). Multistate models were applied to analyze the transition rates among 4 states: no disability, mild disability, severe disability and death. The transition rates from disabled states to the no-disability state were found to decrease markedly with age. The rates of recovery from mild disability in rural areas were higher than those in urban areas. Rural elderly individuals lived shorter lives than their urban counterparts, but they tended to live with better functional status, spending a larger fraction of their remaining life with less severe disability. Based on these findings, devoting more attention and resources to rural areas may help less severely disabled people recuperate and prevent severe disability. The study provides insights into health plan strategies to help guide the allocation of limited resources.

Bioinformatics analysis of the regulatory lncRNA­miRNA­mRNA network and drug prediction in patients with hypertrophic cardiomyopathy.

Hypertrophic cardiomyopathy (HCM) is a complex inherited cardiovascular disease. The present study investigated the long noncoding (lnc)RNA/microRNA (mi)RNA/mRNA expression pattern of patients with HCM and aimed to identify key molecules involved in the development of this condition. An integrated strategy was conducted to identify differentially expressed miRNAs (DEmiRs), differentially expressed lncRNAs (DElncs) and differentially expressed genes (DEGs) based on the GSE36961 (mRNA), GSE36946 (miRNA), GSE68316 (lncRNA/mRNA) and GSE32453 (mRNA) expression profiles downloaded from the Gene Expression Omnibus datasets. Bioinformatics tools were employed to perform function and pathway enrichment analysis, protein­protein interaction, lncRNA­miRNA­mRNA and hub gene networks. Subsequently, DEGs were used as targets to predict drugs. The results indicated that a total of 2,234 DElncs (1,120 upregulated and 1,114 downregulated), 5 DEmiRs (2 upregulated and 3 downregulated) and 42 DEGs (35 upregulated and 7 downregulated) were identified in 4 microarray profiles. Gene ontology analysis revealed that DEGs were mainly involved in actin filament and stress fiber formation and in calcium ion binding, whereas Kyoto Encyclopedia of Genes and Genomes pathway analysis identified the hypoxia inducible factor­1, transforming growth factor­ß and tumor necrosis factor signaling pathways as the main pathways involved in these processes. The hub genes were screened using cytoHubba. A total of 1,086 lncRNA­miRNA­mRNA interactions including 67 lncRNAs, 5 miRNAs and 25 mRNAs were mined in the present study based on prediction websites. Drug prediction indicated that the targeted drugs mainly included angiotensin converting enzyme inhibitors or ß­blockers. A comprehensive bioinformatics analysis of the molecular regulatory lncRNA­miRNA­mRNA network was performed and potential therapeutic applications of drugs were predicted in HCM patients. The data may unravel the future molecular mechanism of HCM.

Identification of Novel Circulating miRNA Biomarkers for the Diagnosis of Esophageal Squamous Cell Carcinoma and Squamous Dysplasia.

BACKGROUND: Circulating miRNAs have been identified as diagnostic biomarkers for esophageal squamous cell carcinoma (ESCC), but their efficacy in discovering early-stage ESCC is still unsatisfying. Esophageal squamous dysplasia (ESD) is the precursor lesion of ESCC. Notably, little is known about the role(s) of circulating miRNAs in identifying ESD. In this study, we, therefore, aimed to identify serum miRNAs as novel diagnostic markers for detecting ESD and ESCC. METHODS: The genome-wide miRNA expression was profiled in 104 (52 ESCC and 52 controls) serum samples using microarray. Seven candidate miRNAs from the microarray assay were evaluated for their diagnostic performance in another cohort of 266 participants (96 ESCC, 92 ESD, and 78 healthy controls). RESULTS: The serum levels of miR-16-5p, miR-197-5p, miR-451a, and miR-92a-3p were associated with ESCC; the biomarker based on the panel of these four miRNAs could efficiently distinguish patients with ESCC from the controls [AUC = 0.856; 95% confidence interval (CI), 0.794-0.905; P < 0.001]. The serum levels of miR-16-5p, miR-320c, miR-638, and miR-92a-3p were significantly higher in patients with ESD than in controls, and this four-miRNA signature could efficiently differentiate patients with ESD from the controls (AUC = 0.842; 95% CI, 0.778-0.893; P < 0.001). In addition, compared with serum carcinoembryonic antigen and carbohydrate antigen 199, miRNA-based panels had a better diagnostic performance in distinguishing patients with ESCC and ESD from healthy controls. CONCLUSIONS: Our study identified two novel panels of circulating miRNAs with high efficiency in detecting ESCC and ESD, suggesting that circulating miRNAs, in particular the combination of them, might serve as noninvasive biomarkers for the early detection of ESCC. IMPACT: This study suggests the feasibility of using circular miRNA-based blood tests to aid in the detection of ESD and ESCC.

Identification of Serum MicroRNAs as Novel Biomarkers in Esophageal Squamous Cell Carcinoma Using Feature Selection Algorithms.

Introduction: Circulating microRNAs (miRNAs) are promising molecular biomarkers for the early detection of esophageal squamous cell carcinoma (ESCC). We investigated the serum miRNA expression profiles from microarray-based technologies and evaluated the diagnostic value of serum miRNAs as potential biomarkers for ESCC by using feature selection algorithms. Methods: Serum miRNA expression profiles were obtained from 52 ESCC patients and 52 age- and sex-matched controls via performing a high-throughput microarray assay. Five representative feature selection algorithms including the false discovery rate procedure, family-wise error rate procedure, Lasso logistic regression, hybrid huberized support vector machine (SVM), and SVM using the squared-error loss with the elastic-net penalty were jointly carried out to select the significantly differentially expressed miRNAs based on the miRNA profiles. Results: Three miRNAs including miR-16-5p, miR-451a, and miR-574-5p were identified as the powerful biomarkers for the diagnosis of ESCC. The diagnostic accuracy of the combination of these three miRNAs was evaluated by using logistic regression and the SVM. The averages of the area under the receiver operating curve and classification accuracies based on different classifiers were more than 0.80 and 0.79, respectively. The cross-validation results suggested that the three-miRNA-based classifiers could clearly distinguish ESCC patients from healthy controls. Moreover, the classifying performance of the miRNA panel persisted in discriminating the healthy group from patients with ESCC stage I-II (AUC > 0.76) and patients with ESCC stage III-IV (AUC > 0.80). Conclusions: These results in this study have moved forward the identification of novel biomarkers for the diagnosis of ESCC.