[Study on revision of standard limits for benzene in"Standards for indoor air quality（GB/T 18883-2022）"in China]

Benzene, as a major indoor pollutant, has received widespread attention. In order to better control indoor benzene pollution and protect people's health, the limit value of benzene in the"Standards for indoor air quality (GB/T 18883-2022)'' was reduced from 0.11 mg/m3 to 0.03 mg/m3. This study reviewed and discussed the relevant technical contents of the determination of benzene limit value, including the exposure status of benzene, health effects, and derivation of the limit value. It also proposed prospects for the future direction of formulating indoor air benzene standards.

Quantitative PCR of string-test collected gastric material: A feasible approach to detect Helicobacter pylori and its resistance against clarithromycin and levofloxacin for susceptibility-guided therapy

BACKGROUND

As the reduced eradication rate of Helicobacter pylori (H. pylori), we introduced string-test and quantitative PCR (qPCR) for susceptibility-guided therapy innovatively. The practicality of the string test was evaluated.

METHODS

It was an open-label, non-randomized, parallel, single-center study, in which subjects tested by ¹³ C- urea breath test (UBT) and string-qPCR were enrolled. Based on the results of string-qPCR, we calculated clarithromycin and levofloxacin resistance rates and gave ¹³ C-UBT positive patients 14 days susceptibility-guided bismuth quadruple therapy. In the empirical therapy group, we retrospectively analyzed the treatment results of ¹³ C-UBT positive patients also treated with bismuth quadruple at Shenzhen Luohu People's Hospital from January 2021 to May 2022. The eradication rate was compared between susceptibility-guided therapy and empirical therapy groups.

RESULTS

The diagnosis of H. pylori infection using the string-qPCR had an overall concordance rate of 95.9% with the ¹³ C-UBT results. Based on the results of string-qPCR, the clarithromycin and levofloxacin resistance rates were 26.1% and 31.8%, respectively. The patients who were given 14 days susceptibility-guided bismuth-based quadruple therapy achieved a high H. pylori eradication rate of 91.8%. Retrospective analysis of patient treatment data from January 2021 to May 2022 available in the hospital database revealed an overall success rate of 82.3% for those who received empirical bismuth-based quadruple therapies, which is marginally significantly lower than that of the string-qPCR susceptibility-guided group (p = 0.084).

CONCLUSION

The high treatment success rate of 91.8% indicates that the string-qPCR test is a valuable and feasible approach for clinical practice to help improve H. pylori treatment success rate.

Blood Biomarkers Panels for Screening of Colorectal Cancer and Adenoma on a Machine Learning-Assisted Detection Platform

OBJECTIVE

A mini-invasive and good-compliance program is critical to broaden colorectal cancer (CRC) screening and reduce CRC-related mortality. Blood testing combined with imaging examination has been proved to be feasible on screen for multicancer and guide intervention. The study aims to construct a machine learning-assisted detection platform with available multi-targets for CRC and colorectal adenoma (CRA) screening.

METHODS

This was a retrospective study that the blood test data from 204 CRCs, 384 CRAs, and 229 healthy controls was extracted. The classified models were constructed with 4 machine learning (ML) algorithms including support vector machine (SVM), random forest (RF), decision tree (DT), and eXtreme Gradient Boosting (XGB) based on the candidate biomarkers. The importance index was used by SHapely Adaptive exPlanations (SHAP) analysis to identify the dominant characteristics. The performance of classified models was evaluated. The most dominating features from the proposed panel were developed by logistic regression (LR) for identification CRC from control.

RESULTS

The candidate biomarkers consisted of 26 multi-targets panel including CEA, AFP, and so on. Among the 4 models, the SVM classifier for CRA yields the best predictive performance (the area under the receiver operating curve, AUC: .925, sensitivity: .904, and specificity: .771). As for CRC classification, the RF model with 26 candidate biomarkers provided the best predictive parameters (AUC: .941, sensitivity: .902, and specificity: .912). Compared with CEA and CA199, the predictive performance was significantly improved. The streamlined model with 6 biomarkers for CRC also obtained a good performance (AUC: .946, sensitivity: .885, and specificity: .913).

CONCLUSIONS

The predictive models consisting of 26 multi-targets panel would be used as a non-invasive, economical, and effective risk stratification platform, which was expected to be applied for auxiliary screening of CRA and CRC in clinical practice.

Sodium-Glucose Cotransporter 2 Inhibitors and the Risk of Pneumonia and Septic Shock

CONTEXT

Individuals with type 2 diabetes mellitus (DM) have an increased risk of pneumonia and septic shock. Traditional glucose-lowering drugs have recently been found to be associated with a higher risk of infections. It remains unclear whether sodium-glucose cotransporter 2 inhibitors (SGLT2is), which have pleiotropic/anti-inflammatory effects, may reduce the risk of pneumonia and septic shock in DM.

METHODS

MEDLINE, Embase, and ClinicalTrials.gov were searched from inception up to May 19, 2022, for randomized, placebo-controlled trials of SGLT2i that included patients with DM and reported outcomes of interest (pneumonia and/or septic shock). Study selection, data extraction, and quality assessment (using the Cochrane Risk of Bias Assessment Tool) were conducted by independent authors. A fixed-effects model was used to pool the relative risk (RRs) and 95% CI across trials.

RESULTS

Out of 4568 citations, 26 trials with a total of 59 264 patients (1.9% developed pneumonia and 0.2% developed septic shock) were included. Compared with placebo, SGLT2is significantly reduced the risk of pneumonia (pooled RR 0.87, 95% CI 0.78-0.98) and septic shock (pooled RR 0.65, 95% CI 0.44-0.95). There was no significant heterogeneity of effect size among trials. Subgroup analyses according to the type of SGLT2i used, baseline comorbidities, glycemic control, duration of DM, and trial follow-up showed consistent results without evidence of significant treatment-by-subgroup heterogeneity (all Pheterogeneity > .10).

CONCLUSION

Among DM patients, SGLT2is reduced the risk of pneumonia and septic shock compared with placebo. Our findings should be viewed as hypothesis generating, with concepts requiring validation in future studies.

Associations of multiple plasma metals with the risk of metabolic syndrome: A cross-sectional study in the mid-aged and older population of China

BACKGROUND

Metal exposures have been reported to be related to the progress of metabolic syndrome (MetS), however, the currents results were still controversial, and the evidence about the effect of multi-metal exposure on MetS were limited. In this study, we intended to evaluate the relationships between metal mixture exposure and the prevalence of MetS in a mid-aged and older population of China.

METHODS

The plasma levels of 13 metals (aluminum, magnesium, calcium, iron, manganese, cobalt, copper, arsenic, zinc, selenium, cadmium, molybdenum and thallium) were detected by inductively coupled plasma mass spectrometry (ICP-MS) in 1277 adults recruited from the Eighth Affiliated Hospital of Sun Yat-Sen University (Shenzhen, China). Logistic regression, the adaptive least absolute shrinkage and selectionator operator (LASSO) penalized regression analysis and restricted cubic spline (RCS) analysis were used to explore the associations and dose-response relationships of plasma metals with MetS. To evaluate the cumulative effect of metals, the Bayesian Kernel Machine Regression (BKMR) model was applied.

RESULTS

The concentrations of magnesium and molybdenum were lower in the MetS group (p < 0.05). In the single-metal model, the adjusted ORs (95%CI) in the highest quartiles were 0.44 (0.35, 0.76) for magnesium and 0.30 (0.17, 0.51) for molybdenum compared with the lowest quartile. The negative associations and dose-dependent relationships of magnesium and molybdenum with MetS were further validated by the stepwise model, adaptive LASSO penalized regression and RCS analysis. The BKMR models showed that the metal mixture were associated with decreased MetS when the chemical mixtures were≥ 25th percentile compared to their medians, and Mg, Mo were the major contributors to the combined effect. Moreover, concentrations of magnesium were significantly related to blood glucose, and molybdenum was related with BMI, blood glucose and blood pressure.

CONCLUSIONS

Elevated levels of plasma magnesium and molybdenum were associated with decreased prevalence of MetS. Further investigations in larger perspective cohorts are needed to confirm our findings.