Evaluation of miRNA-146a, miRNA-34a, and pro-inflammatory cytokines as a potential early indicators for type 1 diabetes mellitus.

Background: Type I diabetes mellitus (T1DM) is one of the most common chronic autoimmune diseases worldwide. miRNAs are a class of small non-coding RNA molecules that have been linked to immune system functions, ß-cell metabolism, proliferation, and death, all of which contribute to pathogenesis of TIDM. Dysregulated miRNAs have been identified in Egyptian TIDM patients. Aim: Several miRNAs were profiled in Egyptian TIDM patients to determine whether they can be used as molecular biomarkers for T1DM. The relationship between the investigated miRNAs and pro-inflammatory cytokines (TNF-α and IL-6) has also been evaluated in the development of TIDM, in addition to the creation of a proposed model for TIDM prediction. Patients & methods: Case-control study included 177 Egyptian patients with confirmed type I diabetes mellitus and 177 healthy individuals. MiRNA-34 and miRNA-146 were detected in serum samples using real-time PCR, whereas TNF-α and IL-6 levels were assessed using ELIZA. Results: Patients with TIDM showed a significant decrease in the expression of miRNA-146, with a cut-off value ≤ 3.3, 48 % specificity, and 92.1 % sensitivity, whereas miRNA-34 had the highest sensitivity (95.5 %) and specificity (97.2 %) for differentiating diabetic patients from controls. Furthermore, other diagnostic proinflammatory markers showed lower sensitivity and specificity. Conclusion: Serum levels of miRNA-34a, miRNA-146, IL-6, and TNF-α provide new insights into T1DM pathogenesis and could be used for screening and diagnosis purposes. They can be also a potential therapeutic target, as well as allowing for more strategies to improve T1DM disease outcomes.

Triglyceride-Glucose Index as Predictor for Hypertension, CHD and STROKE Risk among Non-Diabetic Patients: A NHANES Cross-Sectional Study 2001-2020.

BACKGROUND: Cardiovascular disease (CVD) is a leading cause of global mortality. Early intervention and prevention of CVD depend on accurately predicting the risk of CVD. This study aimed to investigate the association between the TyG index and the risk of coronary heart disease (CHD), congestive heart failure (CHF), heart attack (HA), stroke, and hypertension (HTN) among patients without diabetes in the United States. METHODS: In this retrospective, cross-sectional study, we used data from the National Health and Nutrition Examination Survey (NHANES) from 2001 to 2020. We conducted several regression analysis models and calculated the sensitivity and specificity of (TyG) index for predicting the onset of CHD, CHF, HA, stroke, and HTN. RESULTS: A total of 10,937 individuals without diabetes participated in our study. Individuals with a TyG index greater than 8.96 displayed significant increasing in various parameters, including BMI, systolic/diastolic blood pressure, total cholesterol, LDL, and Apo-B levels (p < 0.001). Almost all regression models ensured that a higher TyGI value was associated with higher odds of having CHD, CHF, HA, stroke, and HTN, which patients with a TyGI value higher than 8.96 have odds ratios of 2.24-5.58 for CHD, 1.68-4.42 for stroke, 2.45-3.77 for HA and 1.75-3.93 for HTN comparing than patients with a TyGI value lower than 8.11 (p-value < 0.05).We evaluated the predictive value of the TyG index for each endpoint, obtaining the following area under the curve (AUC) values: 54.75% for CHF (95% CI: 0.542-0.614), 52.32% for stroke (95% CI: 0.529-0.584), 55.67% for HA (95% CI: 0.595-0.646), 55.59% for HTN (95% CI: 0.574-0.597), and 50.31% for CHD (95% CI: 0.592-0.646). CONCLUSION: The TyG index showed a strong correlation with cardiovascular risk factors in individuals without diabetes, however it was a poor predictor of almost studied cardiovascular diseases.

Quantification of malachite green in fish feed utilising liquid chromatography-tandem mass spectrometry with a monolithic column.

The purpose of this study was to develop a rapid and sensitive method for the quantification of malachite green (MG) in fish feed using LC-ESI-MS/MS with a monolithic column as stationary phase. Fish feed was cleaned using ultrasonic assisted liquid-liquid extraction. The separation was achieved on a Chromolith® Performance RP-18e column (100 × 4.6 mm) using gradient mobile phase composition of methanol and 0.1% formic acid at the flow rate of 1.0 ml min⁻¹. The analyte was ionised using electrospray ionisation in positive mode. Mass spectral transitions were recorded in selected reaction monitoring (SRM) mode at m/z 329.78 → m/z 314.75 with a collision energy (CE) of 52% for MG. The system suitability responses were calculated for reproducibility tests of the retention time, number of theoretical plates and capacity factor. System validation was evaluated for precision, specificity and linearity of MG. The linearity and calibration graph was plotted in the range of 15.0-250 ng ml⁻¹ with the regression coefficient of >0.997. The lower limits of detection and quantification for MG were 0.55 and 1.44 ng ml⁻¹, respectively, allowing easy determination in fish feed with accuracy evaluated as a percentage recovery of 92.1% and precision determined as % CV of < 5. The method was also extended to the determination of MG in an actual fish feed. The sensitivity and selectivity of LC-ESI-MS/MS using monolithic column offers a valuable alternative to the methodologies currently employed for the quantification of MG in fish feeds.