Association between alcohol consumption and latent fasting blood glucose trajectories among midlife women

BackgroundThis investigation sought to elucidate the correlations between alcohol intake and trajectories of fasting blood glucose (FBG) among American women in midlife.MethodsOur analysis was rooted in the foundational data from the Study of Women’s Health Across the Nation (SWAN), a comprehensive longitudinal study centered on US women during their midlife transition. We employed group-based trajectory modeling to chart the FBG trajectories spanning from 1996 to 2005. Employing logistic regression, we gauged the odds ratios (ORs) and 95% confidence intervals (CIs) to draw connections between initial alcohol consumption and FBG trajectory patterns, whilst controlling for predominant potential confounders.ResultsOur cohort comprised 2,578 women in midlife, ranging in age from 42 to 52, each having a minimum of three subsequent FPG assessments. We discerned two distinct FBG trajectories: a low-stable pattern (n = 2,467) and a high-decreasing pattern (n = 111). Contrasted with the low-stable group, our data showcased an inverse relationship between alcohol intake and the high-decreasing FBG trajectory in the fully adjusted model 3. The most pronounced reduction was evident in the highest tertile of daily servings of alcoholic beverages (OR: 0.23, 95% CI: 0.10–0.52, p < 0.001), percentage of kilocalories sourced from alcoholic beverages (OR: 0.30, 95% CI: 0.16–0.58, p < 0.001), and daily caloric intake from alcoholic beverages (OR: 0.31, 95% CI: 0.16–0.62, p < 0.001).ConclusionModerate alcohol consumption may protect against high FPG trajectories in middle-aged women in a dose–response manner. Further researches are needed to investigate this causality in midlife women

Live bacteria found in gastric cancer tumor tissue

BackgroundMost research on gastric cancer and microorganisms has focused on Helicobacter pylori as a causative agent and on the relationship between the microbiota and gastric cancer. There is no direct evidence of bacteria in gastric cancer tissues or their relationship with gastric cancer.MethodsGastric cancer tissue samples were collected, and the bacteria within tumor tissues were observed by transmission electron microscopy. The bacteria cultured were stained by Gram Staining and then subjected to High-throughput third-generation full-length 16S rRNA amplicon sequencing. Pure cultures were used to infect AGS gastric cancer cells, followed by protein extraction and Western blotting to detect POF1B protein expression.ResultsThe bacteria were observed in tumor tissues through transmission electron microscopy and had been cultivated under microaerophilic and anaerobic conditions, specifically, then were identified as Propionibacterium acnes (P. acnes), Klebsiella pneumoniae (K. pneumoniae), and Lactobacillus salivarius (L. salivarius). The vacuolation and mortality of AGS cell infected with P. acnes increased (p < 0.05) and the POF1B protein expression upregulated (p < 0.05).ConclusionThe live bacteria, including L. salivarius, P. acnes, and K. pneumoniae, have been found in gastric cancer tumor tissue. P. acnes specifically upregulate the oncogenic protein POF1B expression. The pathway through which this bacterium enters tumor tissue and its role in the tumor microenvironment require further investigation

Research on the Stability of a Rabbit Dry Eye Model Induced by Topical Application of the Preservative Benzalkonium Chloride

Dry eye is a common disease worldwide, and animal models are critical for the study of it. At present, there is no research about the stability of the extant animal models, which may have negative implications for previous dry eye studies. In this study, we observed the stability of a rabbit dry eye model induced by the topical benzalkonium chloride (BAC) and determined the valid time of this model.). Decreased levels of mucin-5 subtype AC (MUC5AC), along with histopathological and ultrastructural disorders of the cornea and conjunctiva could be observed in Group BAC-W4 and particularly in Group BAC-W5 until day 21.A stable rabbit dry eye model was induced by topical 0.1% BAC for 5 weeks, and after BAC removal, the signs of dry eye were sustained for 2 weeks (for the mixed type of dry eye) or for at least 3 weeks (for mucin-deficient dry eye)

Treatment of Cancer Gene Changes in Chronic Myeloid Leukemia by Big Data Analysis Platform-Based Dasatinib

Based on data mining, an innovative big data analysis platform was utilized to discuss the treatment of cancer in chronic myeloid leukemia (CML) by dasatinib, aiming to offer help to the diagnosis and treatment of cancer. An integrated gene expression analysis system (IEAS) was firstly constructed to automatically classify data in the online human Mendelian genetic database using clustering algorithms. At the same time, the gene expression profile was analyzed by principal component analysis (PCA) in the analysis system. In addition, the efficacy of dasatinib in the treatment of patients with advanced CML was then retrospectively analyzed. The results showed that the IEAS system could incorporate the gene expression analysis vectors it contained by JAVA-related technologies, and the generated clustering genes showed similar functions. The clustering algorithm could homogenize data and generate visual clustering heat maps. The analysis results of major elements were diverse under different experimental conditions. The characteristic value of the first major element was the largest. Messenger ribonucleic acid (mRNA) datasets of CML patients were selected from cancer genomic map, including 120 samples and 20,614 mRNA in total. In micro-RNA (miRNA) datasets, there were 202 samples including 1,406 miRNAs. Data were screened by miRNA–mRNA regulation template, and 20 differentially expressed mRNAs were obtained. In conclusion, the proposed IEAS system could mine and analyze the gene expression data. Dasatinib showed good efficacy in the treatment of patients with advanced CML. Besides, it could improve visual queries, and data mining had a broad application prospect in clinical application. Dasatinib was considered to be a good option for patients with advanced CML

Treatment of Cancer Gene Changes in Chronic Myeloid Leukemia by Big Data Analysis Platform-Based Dasatinib

Based on data mining, an innovative big data analysis platform was utilized to discuss the treatment of cancer in chronic myeloid leukemia (CML) by dasatinib, aiming to offer help to the diagnosis and treatment of cancer. An integrated gene expression analysis system (IEAS) was firstly constructed to automatically classify data in the online human Mendelian genetic database using clustering algorithms. At the same time, the gene expression profile was analyzed by principal component analysis (PCA) in the analysis system. In addition, the efficacy of dasatinib in the treatment of patients with advanced CML was then retrospectively analyzed. The results showed that the IEAS system could incorporate the gene expression analysis vectors it contained by JAVA-related technologies, and the generated clustering genes showed similar functions. The clustering algorithm could homogenize data and generate visual clustering heat maps. The analysis results of major elements were diverse under different experimental conditions. The characteristic value of the first major element was the largest. Messenger ribonucleic acid (mRNA) datasets of CML patients were selected from cancer genomic map, including 120 samples and 20,614 mRNA in total. In micro-RNA (miRNA) datasets, there were 202 samples including 1,406 miRNAs. Data were screened by miRNA–mRNA regulation template, and 20 differentially expressed mRNAs were obtained. In conclusion, the proposed IEAS system could mine and analyze the gene expression data. Dasatinib showed good efficacy in the treatment of patients with advanced CML. Besides, it could improve visual queries, and data mining had a broad application prospect in clinical application. Dasatinib was considered to be a good option for patients with advanced CML.</jats:p

Lower dietary magnesium is associated with a higher hemoglobin glycation index in the National Health and Nutrition Examination Survey

Abstract Background and Aims: The data for the effect of dietary magnesium (Mg) on hemoglobin glycation index (HGI) is limited. Thus, this study aimed to examine the relationship between dietary Mg and HGI in the general population. Methods and Results Our research used data from the National Health and Nutrition Examination Survey from 2001 to 2002. The dietary intake of Mg was assessed by two 24-h dietary recalls. The predicted HbA1c was calculated based on fasting plasma glucose. Logistic regression and restricted cubic spline models were applied to assess the relationship between dietary Mg intake and HGI. We found a significant inverse association between dietary Mg intake and HGI (β = -0.00016, 95%CI: -0.0003, -0.00003, P = 0.019). Dose-response analyses revealed that HGI decreased with increasing intakes of Mg when reached the point above 412 mg/d. There was a linear dose-response relationship between dietary Mg intake and HGI in diabetic subjects, and there was an L-shape dose-response relationship in non-diabetic individuals. Conclusion Increasing the intake of Mg might help lower the risk associated with high HGI. Further prospective studies are requested before dietary recommendations.</jats:p

Down-regulation of HPGD by miR-146b-3p promotes cervical cancer cell proliferation, migration and anchorage-independent growth through activation of STAT3 and AKT pathways

Abstract While the application of early screening and HPV vaccines has reduced the incidence and mortality rates of cervical cancer, it remains the third most common carcinoma and fourth leading cause of cancer-associated death among women worldwide. The precise mechanisms underlying progression of cervical cancer are not fully understood at present. Here, we detected significant down-regulation of 15-hydroxyprostaglandin dehydrogenase (HPGD) in cervical cancer tissues. Overexpression of HPGD inhibited cervical cancer cell proliferation, migration and anchorage-independent growth to a significant extent. To clarify the mechanisms underlying HPGD down-regulation in cervical cancer, miRNA microarray, bioinformatics and luciferase reporter analyses were performed. HPGD was identified as a direct target of miR-146b-3p displaying up-regulation in cervical cancer tissues. Similar to the effects of HPGD overexpression, down-regulation of miR-146b-3p strongly suppressed proliferation, migration and anchorage-independent growth of cervical cancer cells. Furthermore, HPGD negatively regulated activities of STAT3 and AKT that promote cervical cancer cell proliferation. Notably, HPV oncogenes E6 and E7 were determined as potential contributory factors to these alterations. Our results collectively suggest that the HPGD/miR-146b-3p axis plays a significant role in cervical cancer and may serve as a potentially effective therapeutic target