Bioinformatics analysis of proteomic profiles during the process of anti-Thy1 nephritis.

Anti-Thy1 nephritis is a well-established experimental mesangial proliferative nephritis model. Exploring the molecular mechanisms of pathophysiology in anti-Thy1 nephritis may elucidate the pathogeneses of mesangial proliferation. We examined the roles and acting mechanisms of differentially expressed proteins (DEPs) by bioinformatics analysis of glomeruli proteomic profiles during the course of anti-Thy1 nephritis. In total, 108 DEPs were found by two-dimensional fluorescence difference gel electrophoresis (2D-DIGE), and 40 DEPs were identified by matrix-assisted laser desorption ionization/time of flight and liquid chromatography-MS. DEPs were classified into five clusters (Clusters 1-5), according to their expression trends using Cluster 3.0 software, involved in regulating biological processes such as the stress response, cell proliferation, apoptosis, energy metabolism, transport, and the actin cytoskeleton. The expression patterns of ten DEPs, distributed across five clusters, including AKR1A1, AGAT, ATP6V1B2, HIBADH, MDH1, MPST, NIT2, PRDX6, PSMB7, and TPI1, were validated by Western blotting. Based on Western blotting and immunohistochemistry, we also found that the DEP FHL2, which was primarily expressed in the mesangial region, was down-regulated on days 3 and 5, and up-regulated on day 10. In vitro, we found that FHL2 overexpression induced mesangial cell proliferation by increasing the number of S-phase cells and decreasing G2/M-phase cells, whereas inhibiting FHL2 had the opposite effect. This study explored novel DEPs and their expression patterns during anti-Thy1 nephritis, and elucidated FHL2's effect on mesangial cell proliferation. These results will contribute to our understanding of the pathogenesis of mesangial proliferation.

[Effect of high glucose on NADPH oxidase expression and reactive oxygen species generation in human umbilical vein endothelial cells].

OBJECTIVE: To explore the effect of high glucose on NADPH oxidase (NOX) expression and intracellular reactive oxygen species (ROS) generation in human umbilical vein endothelial cells (HUVECs). METHODS: HUVECs were divided into a control group, a mannite group, a glucose group and a glucose plus diphenylene iodonium (DPI) group. Intracellular ROS was detected by flow cytometry. RNA and protein expression of NOX in HUVECs was analyzed by reverse transcriptase polymerase chain reaction (RT-PCR) and Western blot, respectively. RESULTS: 1) Compared with the control group, the intracellular ROS were significantly increased in the glucose group (P< 0.05, n=3), but there were no significant change in the glucose plus DPI group (P> 0.05, n=3); 2) Compared with the control group, the mRNA and protein expression of NOX4 in the glucose group were significantly increased (P< 0.05), but there were no significant change in the mRNA and protein expression of NOX2, p22phox, p67phox and rac (all P> 0.05); 3) there were no significant difference in the mRNA and protein expression of NOX2, NOX4, p22phox, p67phox and rac between the glucose plus DPI group and the control group (all P> 0.05). CONCLUSION: High glucose may increases intracellular ROS generation by increasing the expression of NOX4 in HUVECs, which might mediate the oxidative stress.

A cross-sectional study of the major risk factor at different levels of cognitive performance within Chinese-origin middle-aged and elderly individuals.

OBJECTIVE: Senior citizens suffering from cognitive impairment (CI) are on the East Asia rise. Multiple variables could lead to inter-/intra-individual cognition effectiveness variations, though previous research efforts did not consider weighting issues. METHODS: This study scrutinized 5639 participants meeting required inclusion criteria by the CHARLS. Cognitive capacity was evaluated through Mini-Mental State Examination (MMSE). Considering that MMSE scorings were not following normal distribution, a non-parametric test and multiple linear regression were performed to screen candidate variables linked to cognitive capacity. Such applicability of candidate factors in the cumulative effect and the weighting of the impact on cognitive performance were evaluated by random forest (RF) algorithm. RESULTS: Age, gender, education, marital status, residence, the type of residence, exercise, socialization level and drinking were correlated to MMSE scorings (p < 0.05). Among them, age, education, gender and sociality were correlated to individual MMSE items (p < 0.05). Regardless of MMSE scores and several MMSE items, age is always a prime factor. However, in the attention and computation item, education is better than age and ranks first. CONCLUSIONS: This preliminary study prompted age, education, gender, and sociality with varying weightings to be linked to cognitive capacity within a Chinese cohort by differing cognitive aspects. At different levels of cognitive performance, the main risk factors are basically similar, but there are still some differences.

Specific differences and novel key regulatory genes of sex in influencing exceptional longevity phenotypes.

BACKGROUND AND AIMS: Although the life expectancy of women systematically and robustly exceeds that of men, specific differences and molecular mechanisms of sex in influencing longevity phenotypes remain largely unknown. Therefore, we performed transcriptome sequencing of peripheral blood samples to explore regulatory mechanisms of healthy longevity by incorporating sex data. METHODS: We selected 34 exceptional longevity (age: 98.26 ± 2.45 years) and 16 controls (age: 52.81 ± 9.78) without advanced outcomes from 1363 longevity and 692 controls recruited from Nanning of Guangxi for RNA sequencing 1. The transcriptome sequencing 1 data of 50 samples were compared by longevity and sex to screen differentially expressed genes (DEGs). Then, 121 aging samples (40-110 years old) without advanced outcomes from 355 longevity and 294 controls recruited from Dongxing of Guangxi were selected for RNA sequencing 2. The genes associated with aging from the transcriptome sequencing 2 of 121 aging samples were filtered out. Finally, the gender-related longevity candidate genes and their possible metabolic pathways were verified by cell model of aging and a real-time polymerase chain reaction (RT-PCR). RESULTS: Metabolism differs between male and female and plays a key role in longevity. Moreover, the principal findings of this study revealed a novel key gene, UGT2B11, that plays an important role in regulating lipid metabolism through the peroxisome proliferator activated receptor gamma (PPARG) signalling pathway and ultimately improving lifespan, particularly in females. CONCLUSION: The findings suggest specific differences in metabolism affecting exceptional longevity phenotypes between the sexes and offer novel therapeutic targets to extend lifespan by regulating lipid homeostasis.

Plasma metabolites and risk of myocardial infarction: a bidirectional Mendelian randomization study.

BACKGROUND: Myocardial infarction (MI) is a critical cardiovascular event with multifaceted etiology, involving several genetic and environmental factors. It is essential to understand the function of plasma metabolites in the development of MI and unravel its complex pathogenesis. METHODS: This study employed a bidirectional Mendelian randomization (MR) approach to investigate the causal relationships between plasma metabolites and MI risk. We used genetic instruments as proxies for plasma metabolites and MI and conducted MR analyses in both directions to assess the impact of metabolites on MI risk and vice versa. In addition, the large-scale genome-wide association studies datasets was used to identify genetic variants associated with plasma metabolite (1400 metabolites) and MI (20,917 individuals with MI and 440,906 individuals without MI) susceptibility. Inverse variance weighted was the primary method for estimating causal effects. MR estimates are expressed as beta coefficients or odds ratio (OR) with 95% CI. RESULTS: We identified 14 plasma metabolites associated with the occurrence of MI (P < 0.05), among which 8 plasma metabolites [propionylglycine levels (OR = 0.922, 95% CI: 0.881-0.965, P < 0.001), gamma-glutamylglycine levels (OR = 0.903, 95% CI: 0.861-0.948, P < 0.001), hexadecanedioate (C16-DC) levels (OR = 0.941, 95% CI: 0.911-0.973, P < 0.001), pentose acid levels (OR = 0.923, 95% CI: 0.877-0.972, P = 0.002), X-24546 levels (OR = 0.936, 95% CI: 0.902-0.971, P < 0.001), glycine levels (OR = 0.936, 95% CI: 0.909-0.964, P < 0.001), glycine to serine ratio (OR = 0.930, 95% CI: 0.888-0.974, P = 0.002), and mannose to trans-4-hydroxyproline ratio (OR = 0.912, 95% CI: 0.869-0.958, P < 0.001)] were correlated with a decreased risk of MI, whereas the remaining 6 plasma metabolites [1-palmitoyl-2-arachidonoyl-GPE (16:0/20:4) levels (OR = 1.051, 95% CI: 1.018-1.084, P = 0.002), behenoyl dihydrosphingomyelin (d18:0/22:0) levels (OR = 1.076, 95% CI: 1.027-1.128, P = 0.002), 1-stearoyl-2-docosahexaenoyl-GPE (18:0/22:6) levels (OR = 1.067, 95% CI: 1.027-1.109, P = 0.001), alpha-ketobutyrate levels (OR = 1.108, 95% CI: 1.041-1.180, P = 0.001), 5-acetylamino-6-formylamino-3-methyluracil levels (OR = 1.047, 95% CI: 1.019-1.076, P < 0.001), and N-acetylputrescine to (N (1) + N (8))-acetylspermidine ratio (OR = 1.045, 95% CI: 1.018-1.073, P < 0.001)] were associated with an increased risk of MI. Furthermore, we also observed that the mentioned relationships were unaffected by horizontal pleiotropy (P > 0.05). On the contrary, MI did not lead to significant alterations in the levels of the aforementioned 14 plasma metabolites (P > 0.05 for each comparison). CONCLUSIONS: Our bidirectional MR study identified 14 plasma metabolites associated with the occurrence of MI, among which 13 plasma metabolites have not been reported previously. These findings provide valuable insights for the early diagnosis of MI and potential therapeutic targets.

Measurements of peri-prostatic adipose tissue by MRI predict bone metastasis in patients with newly diagnosed prostate cancer.

Objectives: To investigate the role of MRI measurements of peri-prostatic adipose tissue (PPAT) in predicting bone metastasis (BM) in patients with newly diagnosed prostate cancer (PCa). Methods: We performed a retrospective study on 156 patients newly diagnosed with PCa by prostate biopsy between October 2010 and November 2022. Clinicopathologic characteristics were collected. Measurements including PPAT volume and prostate volume were calculated by MRI, and the normalized PPAT (PPAT volume/prostate volume) was computed. Independent predictors of BM were determined by univariate and multivariate logistic regression analysis, and a new nomogram was developed based on the predictors. Receiver operating characteristic (ROC) curves were used to estimate predictive performance. Results: PPAT and normalized PPAT were associated with BM (P<0.001). Normalized PPAT positively correlated with clinical T stage(cT), clinical N stage(cN), and Grading Groups(P<0.05). The results of ROC curves indicated that PPAT and normalized PPAT had promising predictive value for BM with the AUC of 0.684 and 0.775 respectively. Univariate and multivariate analysis revealed that high normalized PPAT, cN, and alkaline phosphatase(ALP) were independently predictors of BM. The nomogram was developed and the concordance index(C-index) was 0.856. Conclusions: Normalized PPAT is an independent predictor for BM among with cN, and ALP. Normalized PPAT may help predict BM in patients with newly diagnosed prostate cancer, thus providing adjunctive information for BM risk stratification and bone scan selection.

Modifiable pathways for longevity: A Mendelian randomization analysis.

BACKGROUND: A variety of factors, including diet and lifestyle, obesity, physiology, metabolism, hormone levels, psychology, and inflammation, have been associated with longevity. The specific influences of these factors, however, are poorly understood. Here, possible causal relationships between putative modifiable risk factors and longevity are investigated. METHODS: A random effects model was used to investigate the association between 25 putative risk factors and longevity. The study population comprised 11,262 long-lived subjects (≥90 years old, including 3484 individuals ≥99 years old) and 25,483 controls (≤60 years old), all of European ancestry. The data were obtained from the UK Biobank database. Genetic variations were used as instruments in two-sample Mendelian randomization to reduce bias. The odds ratios for genetically predicted SD unit increases were calculated for each putative risk factor. Egger regression was used to determine possible violations of the Mendelian randomization model. RESULTS: Thirteen potential risk factors showed significant associations with longevity (≥90th) after correction for multiple testing. These included smoking initiation (OR:1.606; CI: 1.112-2.319) and educational attainment (OR:2.538, CI: 1.685-3.823) in the diet and lifestyle category, systolic and diastolic blood pressure (OR per SD increase: 0.518; CI: 0.438-0.614 for SBP and 0.620; CI 0.514-0.748 for DBP) and venous thromboembolism (OR:0.002; CI: 0.000-0.047) in the physiology category, obesity (OR: 0.874; CI: 0.796-0.960), BMI (OR per 1-SD increase: 0.691; CI: 0.628-0.760), and body size at age 10 (OR per 1-SD increase:0.728; CI: 0.595-0.890) in the obesity category, type 2 diabetes (T2D) (OR:0.854; CI: 0.816-0.894), LDL cholesterol (OR per 1-SD increase: 0.743; CI: 0.668-0.826), HDL cholesterol (OR per 1-SD increase: 1.243; CI: 1.112-1.390), total cholesterol (TC) (OR per 1-SD increase: 0.786; CI: 0.702-0.881), and triglycerides (TG) (OR per 1-SD increase: 0.865; CI: 0.749-0.998) in the metabolism category. Both longevity (≥90th) and super-longevity (≥99th), smoking initiation, body size at age 10, BMI, obesity, DBP, SBP, T2D, HDL, LDL, and TC were consistently associated with outcomes. The examination of underlying pathways found that BMI indirectly affected longevity through three pathways, namely, SBP, plasma lipids (HDL/TC/LDL), and T2D (p < 0.05). CONCLUSION: BMI was found to significantly affect longevity through SBP, plasma lipid (HDL/TC/LDL), and T2D. Future strategies should focus on modifying BMI to improve health and longevity.

Development of a model for the prediction of biological age.

BACKGROUND AND OBJECTIVE: Rates of aging vary markedly among individuals, and biological age serves as a more reliable predictor of current health status than does chronological age. As such, the ability to predict biological age can support appropriate and timely active interventions aimed at improving coping with the aging process. However, the aging process is highly complex and multifactorial. Therefore, it is more scientific to construct a prediction model for biological age from multiple dimensions systematically. METHODS: Physiological and biochemical parameters were evaluated to gage individual health status. Then, age-related indices were screened for inclusion in a model capable of predicting biological age. For subsequent modeling analyses, samples were divided into training and validation sets for subsequent deep learning model-based analyses (e.g. linear regression, lasso model, ridge regression, bayesian ridge regression, elasticity network, k-nearest neighbor, linear support vector machine, support vector machine, and decision tree models, and so on), with the model exhibiting the best ability to predict biological age thereby being identified. RESULTS: First, we defined the individual biological age according to the individual health status. Then, after 22 candidate indices (DNA methylation, leukocyte telomere length, and specific physiological and biochemical indicators) were screened for inclusion in a model capable of predicting biological age, 14 age-related indices and gender were used to construct a model via the Bagged Trees method, which was found to be the most reliable qualitative prediction model for biological age (accuracy=75.6%, AUC=0.84) by comparing 30 different classification algorithm models. The most reliable quantitative predictive model for biological age was found to be the model developed using the Rational Quadratic method (R2=0.85, RMSE=8.731 years) by comparing 24 regression algorithm models. CONCLUSIONS: Both qualitative model and quantitative model of biological age were successfully constructed from a multi-dimensional and systematic perspective. The predictive performance of our models was similar in both smaller and larger datasets, making it well-suited to predicting a given individual's biological age.

The relationship between sleep duration and activities of daily living (ADL) disability in the Chinese oldest-old: A cross-sectional study.

Objective: To investigate the relationship between sleep duration and activities of daily living (ADL) disability, and to explore the optimal sleep duration among oldest-old Chinese individuals. Methods: In this cross-sectional study, 1,798 participants (73.2% female) were recruited from Dongxing and Shanglin in Guangxi Zhuang Autonomous Region, China in 2019. The restricted cubic spline function was used to assess the dose-response relationship between sleep duration and ADL disability, and the odds ratios (ORs) of the associations were estimated by logistic regression models. Results: The overall prevalence of ADL disability was 63% (64% in females and 58% in males). The prevalence was 71% in the Han population (72% in females and 68% in males), 60% in the Zhuang population (62% in females and 54% in males) and 53% in other ethnic population (53% in females and 53% in males). A nonlinear relationship between sleep duration and ADL disability was observed. Sleep duration of 8-10 hours was associated with the lowest risk of ADL disability. Sleep duration (≥12 hours) was associated with the risk of ADL disability among the oldest-old individuals after adjusting for confounding factors (OR = 1.47, 95% CI [1.02, 2.10], p < 0.05). Conclusion: Sleep duration more than 12 hours may be associated with an increased risk of ADL disability in the oldest-old individuals, and the optimal sleep duration among this population could be 8-10 h.

The genetic correlation and causal association between key factors that influence vascular calcification and cardiovascular disease incidence.

Background: Serum calcium (Ca), vitamin D (VD), and vitamin K (VK) levels are key determinants of vascular calcification, which itself impacts cardiovascular disease (CVD) risk. The specific relationships between the levels of these different compounds and particular forms of CVD, however, remain to be fully defined. Objective: This study was designed to explore the associations between these serum levels and CVDs with the goal of identifying natural interventions capable of controlling vascular calcification and thereby protecting against CVD pathogenesis, extending the healthy lifespan of at-risk individuals. Methods: Linkage disequilibrium score (LDSC) regression and a two-sample Mendelian randomization (MR) framework were leveraged to systematically examine the causal interplay between these serum levels and nine forms of CVD, as well as longevity through the use of large publically accessible Genome-Wide Association Studies (GWAS) datasets. The optimal concentrations of serum Ca and VD to lower CVD risk were examined through a restrictive cubic spline (RCS) approach. Results: After Bonferroni correction, the positive genetic correlations were observed between serum Ca levels and myocardial infarction (MI) (p = 1.356E-04), as well as coronary artery disease (CAD) (p = 3.601E-04). Negative genetic correlations were detected between levels of VD and CAD (p = 0.035), while elevated VK1 concentrations were causally associated with heart failure (HF) [odds ratios (OR) per 1-standard deviation (SD) increase: 1.044], large artery stroke (LAS) (OR per 1-SD increase: 1.172), and all stroke (AS) (OR per 1-SD increase: 1.041). Higher serum Ca concentrations (OR per 1-SD increase: 0.865) and VD levels (OR per 1-SD increase: 0.777) were causally associated with reduced odds of longevity. These findings remained consistent in sensitivity analyses, and serum Ca and VD concentrations of 2.376 mmol/L and 46.8 nmol/L, respectively, were associated with a lower CVD risk (p < 0.001). Conclusion: Our findings support a genetic correlation between serum Ca and VD and CVD risk, and a causal relationship between VK1 levels and CVD risk. The optimal serum Ca (2.376 mmol/L) and VD levels (46.8 nmol/L) can reduce cardiovascular risk.

Exploration for the reference interval of C-reactive protein in the Chinese longevity people over 90 years of age.

BACKGROUND: Older individuals tend to develop chronic inflammation. As a commonly used nonspecific inflammatory marker, C-reactive protein (CRP) can predict metabolic syndrome, cardiovascular diseases, etc. However, little is known about CRP levels in longevity people. OBJECTIVES: Investigate the distribution and correlates of CRP and provide a reference for the establishment of normal interval values in Chinese longevity people over 90 years of age. METHODS: We performed a correlation analysis to evaluate the correlation between CRP levels and longevity based on the basic demographic characteristics, anthropometric measurements and blood data of 4,418 participants in the 2015 China Health and Retirement Longitudinal Study and 636 participants in an ongoing longitudinal study of natural longevity people in Guangxi. On this basis, the CRP reference interval for longevity was explored. RESULTS: The CRP concentration was significantly different among the three age groups, with a median of 3.80 mg/L for those older than 90 years, which was significantly higher than that for those aged 45-64 years (median 1.20 mg/L, p < 0.001) and 65-89 years (median 1.30 mg/L, p < 0.001). Body mass index, waist circumference, the waist-to-height ratio, systolic blood pressure, diastolic blood pressure, and fasting and postprandial blood glucose, triglyceride, total cholesterol and low-density lipoprotein cholesterol levels were positively correlated with CRP levels, while fasting high-density lipoprotein cholesterol was negatively correlated with CRP levels. The CRP reference interval (RI) value in longevity people was 0.25-9.22 mg/L. CONCLUSION: The concentrations of CRP increased with advancing age, and the CRP reference interval was different between older and younger adults.

A Prognostic Model of Bladder Cancer Based on Metabolism-Related Long Non-Coding RNAs.

Background: Some studies have revealed a close relationship between metabolism-related genes and the prognosis of bladder cancer. However, the relationship between metabolism-related long non-coding RNAs (lncRNA) regulating the expression of genetic material and bladder cancer is still blank. From this, we developed and validated a prognostic model based on metabolism-associated lncRNA to analyze the prognosis of bladder cancer. Methods: Gene expression, lncRNA sequencing data, and related clinical information were extracted from The Cancer Genome Atlas (TCGA). And we downloaded metabolism-related gene sets from the human metabolism database. Differential expression analysis is used to screen differentially expressed metabolism-related genes and lncRNAs between tumors and paracancer tissues. We then obtained metabolism-related lncRNAs associated with prognosis by correlational analyses, univariate Cox analysis, and logistic least absolute shrinkage and selection operator (LASSO) regression. A risk scoring model is constructed based on the regression coefficient corresponding to lncRNA calculated by multivariate Cox analysis. According to the median risk score, patients were divided into a high-risk group and a low-risk group. Then, we developed and evaluated a nomogram including risk scores and Clinical baseline data to predict the prognosis. Furthermore, we performed gene-set enrichment analysis (GSEA) to explore the role of these metabolism-related lncRNAs in the prognosis of bladder cancer. Results: By analyzing the extracted data, our research screened out 12 metabolism-related lncRNAs. There are significant differences in survival between high and low-risk groups divided by the median risk scoring model, and the low-risk group has a more favorable prognosis than the high-risk group. Univariate and multivariate Cox regression analysis showed that the risk score was closely related to the prognosis of bladder cancer. Then we established a nomogram based on multivariate analysis. After evaluation, the modified model has good predictive efficiency and clinical application value. Furthermore, the GSEA showed that these lncRNAs affected bladder cancer prognosis through multiple links. Conclusions: A predictive model was established and validated based on 12 metabolism-related lncRNAs and clinical information, and we found these lncRNA affected bladder cancer prognosis through multiple links.

The major risk factor for depression in the Chinese middle-aged and elderly population: A cross-sectional study.

Background: The number of patients suffering from depression is continuously increasing in China. Demographic characteristics, physical health levels, and individual lifestyles/healthy behaviors are associated with the severity of depression. However, the major risk factor for depression remains unclear. Materials and methods: In this investigation, 16,512 patients were screened using the CHARLS (China Health and Retirement Longitudinal Study) database after being determined to be eligible based on the inclusion criteria. Depressive symptoms were evaluated through the CESD-10 (10-item Center for Epidemiological Studies Depression Scale). Consequently, various models were developed based on potential predictive factors, employing stepwise LR (Logistic Regression)/RF (Random Forests) models to examine the influence and weighting of candidate factors that affect depression. Results: Gender, residential address location, changes in health status following last interview, physical disabilities, chronic pain, childhood health status, ADL (activity of daily living), and social activity were all revealed to be independent risk factors for depression (p < 0.05) in this study. Depression has a synergic effect (across chronic pain and age groups). In comparison to other factors, RF results showed that chronic pain had a stronger impact on depression. Conclusion: This preliminary study reveals that chronic pain is a major risk factor for depression.

A Model for Identifying Optimal Patients for Primary Tumor Resection in Patients With Metastatic Bladder Cancer.

BACKGROUND: A survival benefit was observed in metastatic bladder cancer patients who underwent primary tumor resection, but it was still confusing which patients are suitable for the surgery. For this purpose, we developed a model to screen stage M1 patients who would benefit from primary tumor resection. METHODS: Patients with metastatic bladder cancer were screened from the Surveillance, Epidemiology, and End Results database (2004-2016) and then were divided into surgery (partial or complete cystectomy) group and non-surgery group. To balance the characteristics between them, a 1:1 propensity score matching analysis was applied. A hypothesis was proposed that the received primary tumor resection group has a more optimistic prognosis than the other group. The multivariable Cox model was used to explore the independent factors of survival time in two groups (beneficial and non-beneficial groups). Logistic regression was used to build a nomogram based on the significant predictive factors. Finally, a variety of methods are used to evaluate our model. RESULTS: A total of 7,965 patients with metastatic bladder cancer were included. And 3,314 patients met filtering standards, of which 545 (16.4%) received partial or complete cystectomy. Plots of the Kaplan-Meier and subgroup analyses confirmed our hypothesis. After propensity score matching analysis, a survival benefit was still observed that the surgery group has a longer median overall survival time (11.0 vs. 6.0 months, p < 0.001). Among the surgery cohort, 303 (65.8%) patients lived longer than 6 months (beneficial group). Differentiated characteristics included age, gender, TNM stage, histologic type, differentiation grade, and therapy, which were integrated as predictors to build a nomogram. The nomogram showed good discrimination in both training and validation cohorts (area under the receiver operating characteristic curve (AUC): 0.806 and 0.742, respectively), and the calibration curves demonstrated good consistency. Decision curve analysis showed that the nomogram was clinically useful. Compared with TNM staging, our model shows a better predictive value in identifying optimal patients for primary tumor resection. CONCLUSIONS: A practical predictive model was created and verified, which might be used to identify the optimal candidates for the partial or complete cystectomy group of the primary tumor among metastatic bladder cancer.

Autophagy can repair endoplasmic reticulum stress damage of the passive Heymann nephritis model as revealed by proteomics analysis.

Membranous nephropathy is a common cause of nephrotic syndrome in adults. Although many mechanisms have been proposed, whole proteomic research is still lacking. We analyzed the passive Heymann nephritis animal model using label-free quantitative proteome technology. Results showed 160 differential proteins between control and PHN model groups at days 14 and 21. The expression level of endoplasmic reticulum stress (ERS)-associated protein GRP78 and GRP94 protein was up-regulated on day 14 or 21, which was confirmed by Western blotting. The results also showed that the autophagy marker LC3 was up-regulated in the models. Furthermore, we used tunicamycin to induce ERS of podocytes in vitro to investigate the mechanism. Results of Western blotting revealed that the expression of GRP78, GRP94, and LC3 was up-regulated, while that of the cytoskeletal protein tubulin-ß was down-regulated, and immunofluorescence displayed disordered distribution of tubulin-ß. These suggest that ERS plays an important role in podocyte damage. Autophagy can repair the cytoskeleton damage caused by ERS as a protective mechanism. This provides an important basis for a thorough understanding of the mechanism of podocyte damage and the pathogenesis of membranous nephropathy.

Tissue inhibitor of metalloproteinase-1 promotes NIH3T3 fibroblast proliferation by activating p-Akt and cell cycle progression.

Tissue inhibitor of metalloproteinase-1 (TIMP-1) plays various roles in cell growth in different cell types. However, few studies have focused on TIMP-1's effect on fibroblast cells. In this study, we investigated the effects of TIMP-1 overexpression on NIH3T3 fibroblast proliferation and potential transduction signaling pathways involved. Overexpression of TIMP-1, by transfection of the pLenti6/V5-DESTTIMP-1 plasmid, significantly promoted NIH3T3 proliferation as determined by the BrdU array. Neither 5 nor 15 nM GM6001 (matrix metalloproteinase system inhibitor) affected NIH3T3 proliferation, but 45 nM GM6001 inhibited proliferation. TIMP-1 overexpression activated the p-Akt pathway, but not the p-ERK or p-p38 pathway. In TIMP-1-transfected cells, cyclinD1 was upregulated and p21CIP1 and p27(KIP1) were downregulated, which promoted cell entry into the S and G2/M phases. The PI3-K inhibitor LY294002 abolished the TIMP-1-induced effects. Overexpression of intracellular TIMP-1 stimulated NIH3T3 fibroblast proliferation in a matrix metalloproteinase (MMP)-independent manner by activating the p-Akt pathway and related cell cycle progression.