No abstract

Objective. We herein aim to explore the relationship between the triglyceride-glucose (TyG) index and metabolic syndrome (MS). Methods. We enrolled 298,652 individuals with an average age of 47.08 ± 12.94 years and who underwent health check-ups at the First Affiliated Hospital of Wuhu Wannan Medical College in this cross-sectional study from 2014 to 2016. We enlisted 125,025 women (41.86%) and 173,627 men (58.14%). The survey information included a questionnaire survey, a physical examination, and a laboratory examination. Results. The prevalence of MS increased gradually in the TyG-index subgroups (Q1, TyG <8.30; Q2, 8.30≤ TyG <8.83; and Q3, TyG ≥8.83). We noted significant differences in hypertension, hyperlipidemia, hyperglycemia, sex, age, body mass index (BMI), smoking and drinking habits, and estimated glomerular filtration rate between the TyG-index subgroups. Multiclass logistic regression analysis showed that the group with TyG <8.30 was the reference group, and the 8.30≤ TyG <8.83 and the TyG ≥8.83 groups exhibited a higher TyG index with MS, and a lower TyG index without MS disease. In the linear curve analysis of the TyG index and MS components, BMI, systolic blood pressure, and diastolic blood pressure showed upward trends, while high-density lipoprotein cholesterol showed no obvious trend in the TyG index at a range of 7.8–11.0. Receiver operating characteristic analysis was used to evaluate the predictive value of the TyG index, triglycerides, and fasting blood glucose for MS, and we found that the area under the TyG index curve was the largest (AUC = 0.89). Conclusion. There were associations between the TyG index and MS and its components, and the TyG index is therefore of great value in the early diagnosis of MS.

The aim of this study is to evaluate the value of the triglyceride-glucose (TyG) index and the risk of large artery atherosclerotic (LAA) stroke. Information on general demographic and clinical characteristics, magnetic resonance angiography (MRA) examination, and blood biochemical index determination were obtained. Based on age stratification, three models to evaluate the odds ratio (OR) and the 95% confidence interval (95% CI) were employed to determine the correlation between the TyG index and the risk of LAA stroke. The most effective TyG index threshold in predicting a high risk of LAA stroke was identified using receiver operating characteristic (ROC) curve analysis. Logistic regression verified the association between the risk of LAA stroke and the TyG index. Both with and without age stratification, logistic regression analysis showed that the TyG index was a significant predictor of the occurrence of LAA stroke ( P < 0.05 ). The maximum Youden index for determining a high risk of LAA stroke was found at a TyG index of 4.60. The area under the ROC curve was 0.69 (95% CI: 0.646–0.742, P < 0.05 ), sensitivity was 78.0%, and specificity was 63.4%. An elevated TyG index was remarkably associated with a high risk of LAA stroke.

Background The clinical symptoms of invasive fungal infections (IFI) are nonspecific, and early clinical diagnosis is challenging, resulting in high mortality rates. This study reports the development of a novel aptamer-G-quadruplex/hemin self-assembling color system (AGSCS) based on (1 → 3)-β-D-glucans’ detection for rapid, specific and visual diagnosis of IFI. Methods We screened high affinity and specificity ssDNA aptamers binding to (1 → 3)-β-D-glucans, the main components of cell wall from Candida albicans via Systematic Evolution of Ligands by EXponential enrichment. Next, a comparison of diagnostic efficiency of AGSCS and the (1 → 3)-β-D-glucans assay (“G test”) with regard to predicting IFI in 198 clinical serum samples was done. Results Water-soluble (1 → 3)-β-D-glucans were successfully isolated from C. albicans ATCC 10,231 strain, and these low degree of polymerization glucans (< 1.7 kD) were targeted for aptamer screening with the complementary sequences of G-quadruplex. Six high affinity single stranded DNA aptamers (A1, A2, A3, A4, A5 and A6) were found. The linear detection range for (1 → 3)-β-D-glucans stretched from 1.6 pg/mL to 400 pg/mL on a microplate reader, and the detection limit was 3.125 pg/mL using naked eye observation. Using a microplate reader, the sensitivity and specificity of AGSCS for the diagnosis of IFI were 92.68% and 89.65%, respectively, which was higher than that of the G test. Conclusion This newly developed visual diagnostic method for detecting IFI showed promising results and is expected to be developed as a point-of-care testing kit to enable quick and cost effective diagnosis of IFI in the future.

Background Mycobacterial interspersed repetitive unit-variable number tandem repeat (MIRU-VNTR) is a frequently used typing method for identifying the Beijing genotype of Mycobacterium tuberculosis (Mtb), which is easily transformed into rifampicin (RIF) resistance. The RIF resistance of Mtb is considered to be highly related with the mutation of rpoB gene. Therefore, this study aimed to analyze the relationship between the repetitive number of MIRU loci and the mutation of rpoB gene. Methods An open-source whole-genome sequencing data of Mtb was used to detect the mutation of rpoB gene and the repetitive number of MIRU loci by bioinformatics methods. Cochran-Armitage analysis was performed to analyze the trend of the rpoB gene mutation rate and the repetitive number of MIRU loci. Results Among 357 rifampicin-resistant tuberculosis (RR-TB), 304 strains with mutated rpoB genes were detected, and 6 of 67 rifampicin susceptible strains were detected mutations. The rpoB gene mutational rate showed an upward trend with the increase of MIRU10, MIRU39, QUB4156 and MIRU16 repetitive number, but only the repetitive number of MIRU10, MRIU39 and QUB4156 were risk factors for rpoB gene mutation. The Hunter-Gaston discriminatory index (HGDI) of MIRU10 (0.65) and QUB4156 (0.62) was high in the overall sample, while MIRU39 (0.39) and MIRU16 (0.43) showed a moderate discriminatory Power. Conclusion The mutation rate of rpoB gene increases with the addition of repetitive numbers of MIRU10, QUB4156 and MIRU39 loci.