Differences in oral microbiota associated with type 2 diabetes mellitus between the Dai and Han populations.

Background: Type 2 diabetes mellitus (T2DM) development is closely linked to microbiota, influenced by geography, ethnicity, gender, and age. While the relationship between oral microbiota and T2DM has been explored, specific microbiota associated with T2DM in the Dai and Han populations remains unclear. This study aims to compare oral microbiota differences and identify keystone species between these populations, both with and without T2DM.

Value of Glycemic Dispersion Index in Predicting Major Adverse Cardiovascular Events in Diabetic Patients with Concomitant Acute Coronary Syndrome.

Aim: This investigation aims to assess the predictive value of the glycemic dispersion index (GDI), calculated by incorporating glycated hemoglobin, fasting plasma glucose, and 2-hour postprandial plasma glucose, in predicting major adverse cardiovascular events (MACE) within a 12-month timeframe for diabetic patients with concomitant acute coronary syndrome (ACS).

Methods: A retrospective study was conducted on 3261 diabetic patients with ACS who were hospitalized in the Department of Cardiology, the Sixth Affiliated Hospital of Kunming Medical University, from January 2016 to July 2022. Based on the inclusion and exclusion criteria, 512 patients were ultimately enrolled in the study.

Comparative study of type 2 diabetes mellitus-associated gut microbiota between the Dai and Han populations.

Background: The global prevalence of type 2 diabetes mellitus (T2DM) is increasing. T2DM is associated with alterations of the gut microbiota, which can be affected by age, illness, and genetics. Previous studies revealed that there are discriminating microbiota compositions between the Dai and the Han populations.

Glycemic dispersion: a new index for screening high glycemic variability.

Objective: For patients with diabetes, high-frequency and -amplitude glycemic variability may be more harmful than continuous hyperglycemia; however, there is still a lack of screening indicators that can quickly and easily assess the level of glycemic variability. The aim of this study was to investigate whether the glycemic dispersion index is effective for screening high glycemic variability.

Methods: A total of 170 diabetes patients hospitalized in the Sixth Affiliated Hospital of Kunming Medical University were included in this study.

Application of robot-assisted radical prostatectomy in men over 75 years: an analysis of comparative outcomes.

Objective: This study aimed to summarize the current evidence regarding the feasibility of robot-assisted radical prostatectomy (RARP) in men aged over 75 years.

Method: A comprehensive search of four electronic databases (China National Knowledge Infrastructure, PubMed, Web of Science, and Cochrane Library) was performed to identify eligible comparative studies as of April 2022. Parameters, including perioperative results and oncological and functional outcomes, were evaluated.

Serum albumin to globulin ratio prior to treatment as a potential non-invasive prognostic indicator for urological cancers.

Background: Numerous clinical studies have reported an association between the pretreatment albumin to globulin ratio (AGR) and survival outcomes of urological cancers. However, these conclusions remain controversial. Therefore, we performed a meta-analysis to explore the prognostic value of the AGR in urinary system tumors.

Prognostic value of pretreatment serum albumin-globulin ratio in urothelial carcinoma: A systematic review and meta-analysis.

Objective: To evaluate whether pretreatment albumin-globulin ratio (AGR) can be used as a biomarker for predicting the prognosis of patients with urothelial carcinoma (UC).

Methods: We systematically searched PubMed, Web of Science, China National Knowledge Infrastructure (CNKI), Google Scholar and Cochrane Library; the search time was up to May 2022. Stata 16.

Co-Occurrence of the and Gene in SCAc2001 Isolated from Patients with Diarrheal Disease.

Purpose: To characterize the genetic feature of a multi-drug-resistant strain isolated from the diarrhea sample of a 45-year-old male patient with acute diarrhea.

Materials And Methods: Whole-genome of the strain SCAc2001 was sequenced via the Illumina system, followed by a series of bioinformatic analyses to describe the genetic feature.

Results: The genome sequence of SCAc2001 was assembled into 340 scaffolds (305 of them were > 1000 bp in length and 4,487,370 bp in total) with an average G+C content of 61.

Whole-Genome Analysis of Two Copies of Gene Carrying Strain Acsw19 Isolated from Sichuan, China.

Purpose: To characterize the genetic feature of the carbapenems resistant strain Acsw19 isolated from municipal sludge. This strain was found to carry two copies of -like gene, and -like gene along with other 8 antimicrobial resistance genes, 3 plasmids, 15 genomic islands and 8 prophages.

Methods: A carbapenem-resistant strain Acsw19 isolated from municipal sludge was subjected to whole-genome sequencing (WGS) via the PacBio and Illumina MiSeq platforms.

Study on the prediction of the contamination symptoms in the fermentation process of Chlortetracycline based on soft sensor modeling method.

Background: How to accurately predict the occurrence of contamination in the fermentation process of Chlortetracycline? How to prompt field operators to take effective measures in time? This is a difficult problem that the fermentation process of Chlortetracycline has not been solved well.

Objective: The aim of this paper is to effectively predict whether the fermentation process of Chlortetracycline is contaminated or not.

Methods: A Gaussian process regression soft sensor modeling method with real time integration learning is studied in depth by combining two local learning strategies, namely just-in-time learning (JITL) method and integrated learning method, and a multi-model weighted Gaussian process regression (MWGPR) soft sensor modeling method based on real-time integration learning is proposed in the paper.