Increased expression of SLC25A18 is associated with Alzheimer's disease and is involved in Aß42-induced mitochondrial dysfunction and apoptosis in neuronal cells.

Alzheimer's disease (AD) is currently one of the most serious public health concerns in the world. However, the best approach to treat AD has yet to be discovered, implying that we must continue to work hard to find new AD target genes. In this study, we further analysed Gene Expression Omnibus (GEO) data and discovered that the expression of the Mitochondria glutamate carrier SLC25A18 is associated with AD by screening the differentially expressed genes in different regions of the brains of Alzheimer's disease patients. To verify the expression of SLC25A18 during Alzheimer's disease development, we analysed animal models (5×FAD transgenic AD animal model, chemically induced AD animal model, natural ageing animal model), and the results showed that the expression of SLC25A18 was increased in animal models of AD. Further investigation of the different regions found that SLC25A18 expression was elevated in the EC, TeA, and CA3, and expressed in neurons. Next, We found that Aß42 treatment elevated SLC25A18 expression in Neuro 2A cells. Reducing SLC25A18 expression attenuated mitochondrial dysfunction and neuronal apoptosis caused by Aß42. Overexpression of SLC25A18 increased ATP and intracellular superoxide anions but decreased mitochondrial membrane potential. The results indicate that SLC25A18 affects mitochondrial function and neuronal apoptosis, and is related to AD, which makes it a potential target for treating brain dysfunction.

[Exploring the mechanisms of ferroptosis in non-obstructive azoospermia based on bioinformatics and machine learning].

OBJECTIVE: To explor the potential mechanisms of ferroptosis involvement in non-obstructive azoospermia based on bioinformatics and machine learning methods. METHODS: To obtain disease-related datasets and ferroptosis-related genes, we utilized the GEO database and FerrDb database, respectively. Using the R software, the disease dataset was subjected to normalization, differential analysis, and GO and KEGG enrichment analysis. The differentially expressed genes from the disease dataset were then intersected with the ferroptosis-related genes to identify common genes. Core genes were selected using three machine learning algorithms, namely LASSO, SVM-RFE, and random forest. Further analysis included exploring immune infiltration correlation, predicting target drugs, and conducting molecular docking simulations. RESULTS: The differential analysis of the GSE45885 dataset yielded 1751 differentially expressed genes, while the GSE145467 dataset yielded 4358 differentially expressed genes. The intersection of these two gene sets resulted in a disease-related gene set consisting of 508 genes. Taking the intersection of the disease-related gene set and the ferroptosis-related gene set, we obtained 17 disease-related ferroptosis genes. After machine learning-based screening, three core genes were identified: GPX4, HSF1, and KLHDC3. CONCLUSION: The mechanism underlying the involvement of ferroptosis in non-obstructive azoospermia may be linked to the downregulation of GPX4, HSF1, and KLHDC3 expression. This finding provides a basis for subsequent in-depth mechanistic and therapeutic studies.

[Retrospective analysis on pregnancy outcomes and fat-related factors of treatment of endomorph PCOS infertility patients by acupuncture of 8 acupoints around umbilicus].

OBJECTIVE: To assess the therapeutic effect of acupuncture of eight acupoints around the umbilicus in improving the metabolic level and reproductive function in endomorph polycystic ovary syndrome (PCOS) infertile patients. METHODS: Retrospective analysis was performed on 96 cases of endomorph type PCOS infertility patients who were admitted to the clinic of the Reproductive Center of the First Affiliated Hospital of Tianjin University of Traditional Chinese Medicine from October 2015 to June 2018. Among them, fifty-six cases of the acupuncture group received treatment with acupuncture stimulation of eight acupoints (Shuifen ï¼»CV9ï¼½, Yinjiao ï¼»CV7ï¼½, Tianshu ï¼»ST25ï¼½, Wailing ï¼»ST26ï¼½, Huaroumen ï¼»ST24ï¼½, etc.) around the umbilicus, and 40 cases of the control group were treated by oral administration of Letrozole. Acupuncture was performed once every other day, and Letrozole (2.5 mg/day) given once daily for 5 days, if no pregnancy got, the treatment procedure was repeated once again next menstruation cycle, continuously for 3 months. The pregnancy outcomes including the pregnancy rate, persistent pregnancy rate, ovulation rate and the first trimester abortion rate, and the levels of fat-related factors including body mass index (BMI), waist-to-hip ratio (WHR), homeostasis model of insulin resistance (HOMA-IR=fasting insulin x fasting blood glucose /22.5), leptin(LEP) and adiponectin(APN) of the two groups were compared. The ovulation rate (number of effective ovulation cycles/ number of observation cycles) x 100%, the first trimester abortion rate (number of spontaneous abortion within 12 weeks÷pregnancy cases) X100% were calculated. The fasting blood samples were taken for assaying serum LEP and APN contents using ELISA, blood glucose level using hexokinase assay, and serum insulin by using chemiluminescent microparticle immunoassay, separately. RESULTS: After the treatment, the pregnancy rate and the level of APN were significantly higher (P<0.05), and the BMI, WHR, HOMA-IR and LEP levels were all obviously lower in the acupuncture group than in the control group (P<0.05). There were no significant differences between the two groups in the persistent pregnancy rate, abortion rate and ovulation rate (P>0.05). CONCLUSION: Acupuncture at the eight points around the umbilicus can raise the pregnancy rate in obese type PCOS patients, which may be related to its effects in up-regulating serum APN and lowering BMI, WHR, HOMA-IR, and serum LEP levels.

A fourteen-lncRNA risk score system for prognostic prediction of patients with non-small cell lung cancer.

Growing evidence has underscored long non-coding RNAs (lncRNAs) serving as potential biomarkers for cancer prognosis. However, systematic tracking of a lncRNA signature for prognosis prediction in non-small cell lung cancer (NSCLC) has not been accomplished yet. Here, comprehensive analysis with differential gene expression analysis, univariate and multivariate Cox regression analysis based on The Cancer Genome Atlas (TCGA) database was performed to identify the lncRNA signature for prediction of the overall survival of NSCLC patients. A risk-score model based on a 14-lncRNA signature was identified, which could classify patients into high-risk and low-risk groups and show poor and improved outcomes, respectively. The receiver operating characteristic (ROC) curve revealed that the risk-score model has good performance with high AUC value. Multivariate Cox's regression model and stratified analysis indicated that the risk-score was independent of other clinicopathological prognostic factors. Furthermore, the risk-score model was competent for the prediction of metastasis-free survival in NSCLC patients. Moreover, the risk-score model was applicable for prediction of the overall survival in the other 30 caner types of TCGA. Our study highlighted the significant implications of lncRNAs as prognostic predictors in NSCLC. We hope the lncRNA signature could contribute to personalized therapy decisions in the future.