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Limited research has explored the effectiveness of insulin resistance (IR) in forecasting metabolic syndrome (MetS) risk, especially within the Iranian population afflicted with type 2 diabetes mellitus (T2DM). The present investigation aimed to assess the efficacy of IR indices in predicting the risk of MetS among T2DM patients. Convenient sampling was utilized to select four hundred subjects with T2DM. Metabolic factors and IR indices, including the Waist Circumference-Triglyceride Index (WTI), Triglyceride and Glucose Index (TyG index), the product of TyG index and abdominal obesity indices, and the Metabolic Score for Insulin Resistance (METS-IR), were evaluated. Logistic regression, coupled with modeling, was employed to explore the risk of MetS. The predictive performance of the indices for MetS stratified by sex was evaluated via receiver operating characteristic (ROC) curve analysis and estimation of the area under the curve (AUC) values. The TyG-Waist Circumference (TyG-WC) index exhibited the largest AUCs in both males (0.91) and females (0.93), while the TyG-Body Mass Index (TyG-BMI) demonstrated the smallest AUCs (0.77 in males and 0.74 in females). All indices significantly predicted the risk of MetS in all subjects before and after adjustment (p < 0.001 for all). The TyG-WC index demonstrated the highest odds ratios for MetS (8.06, 95% CI 5.41–12.00). In conclusion, all IR indices assessed in this study effectively predicted the risk of MetS among Iranian patients with T2DM, with the TyG-WC index emerging as the most robust predictor across both genders. [ABSTRACT FROM AUTHOR]

Background:Some recommendations and health protocols were presented to control COVID-19 after the outbreak, such as the use of face masks, observing social distancing, closure of schools, etc. Despite these protocols, we witnessed different peaks and variants of COVID-19 for more than two years. This study investigated some risky behaviors, such as not wearing face masks, violating social distancing, and attendance at crowded places. Methods: We used a checklist containing some demographic, caring behaviors, and survey questions. Data were collected from four universities in Iran. Patients with positive PCR results for COVID-19 were included in the study. The minimum sample size required for this study was estimated to be 407, which were selected from the universities by proportional allocation. Results: The use of face mask proportion was different between the upper and lower age groups of 50 years (P=0.005). Also, this proportion was different in the subgroups of educational level, job status, income, and living area. Conclusion: The space of most crowded places was confined and many patients did not use face masks and did not observe social distancing in these places. Hence, social distancing and face mask use can be considered the most important caring behaviors to deal with COVID-19. [ABSTRACT FROM AUTHOR]

In the present study, the magnetic NH2-MIL-101(Al)/chitosan nanocomposite (MIL/Cs@Fe3O4 NCs) was synthesized and used in the removal of azithromycin (AZT) from an aqueous solution for the first time. The as-synthesized MIL/Cs@Fe3O4 NCs was characterized by SEM, TEM, XRD, FTIR, BET, and VSM techniques. The effect of various key factors in the AZT adsorption process was modeled and optimized using response surface methodology based on central composite design (RSM-CCD). The low value of p-value (1.3101e−06) and RSD (1.873) parameters, along with the coefficient of determination > 0.997 implied that the developed model was well fitted with experimental data. Under the optimized conditions, including pH: 7.992, adsorbent dose: 0.279 g/L, time: 64.256 min and AZT concentration: 10.107 mg/L, removal efficiency and AZT adsorption capacity were obtained as 98.362 ± 3.24% and 238.553 mg/g, respectively. The fitting of data with the Langmuir isotherm (R2: 0.998, X2: 0.011) and Pseudo-second-order kinetics (R2: 0.999, X2: 0.013) showed that the adsorption process is monolayer and chemical in nature. ΔH° > 0, ΔS° > 0, and ∆G° < 0 indicated that AZT removal was spontaneous and endothermic in nature. The effect of Magnesium on AZT adsorption was more complicated than other background ions. Reuse of the adsorbent in 10 consecutive experiments showed that removal efficiency was reduced by about 30.24%. The performance of MIL/Cs@Fe3O4 NCs under real conditions was also tested and promising results were achieved, except in the treatment of AZT from raw wastewater. [ABSTRACT FROM AUTHOR]

Correction to: I Scientific Reports i https://doi.org/10.1038/s41598-022-21551-3, published online 08 November 2022 The Acknowledgements section in the original version of this Article was incomplete. "This work was supported by the Zahedan University of Medical Sciences, Zahedan, Iran [Grant No. 10588]." now reads: "The authors would like to thank Zahedan University of Medical Sciences for funding this research. [Extracted from the article]

A novel ultrasound-assisted magnetic solid-phase extraction coupled with gas chromatography-mass spectrometry (US-MSPE-GC/MS) was developed to detect trace amounts of polycyclic aromatic hydrocarbons (PAHs) in tomato paste, using a magnetic biochar adsorbent derived from nectarine cores. The highest extraction recovery was attained under 10 mg adsorbent mass, 30 min extraction time, 9 % ( w / v ) sodium chloride, and elution with 200 μL of dichloromethane. Under optimum conditions, the method demonstrated excellent linearity (R 2  > 0.992) across a wide concentration range (0.01-100 ng g -1 ) with high sensitivity (LODs: 0.028-0.053 ng g -1 , LOQs: 0.094-0.176 ng g -1 ) and good repeatability (RSDs <5.96 %). The application of the US-MSPE-GC/MS method was tested on four brands of real tomato paste and no PAHs were detected in unspiked samples, indicating no background contamination. This method showed high relative recoveries 88.03-98.52 %) and good reproducibility (<9.19 %.) at two concentration levels, confirming its effectiveness for PAH analysis in real samples., Competing Interests: The authors have declared no conflict of interest., (© 2024 The Authors. Published by Elsevier Ltd.)