Fine particulate matter (PM2.5) induces the stem cell-like properties of hepatocellular carcinoma by activating ROS/Nrf2/Keap1-mediated autophagy.

Exposure to fine particulate matter (PM2.5) has been linked to an increased incidence and mortality of hepatocellular carcinoma (HCC). However, the impact of PM2.5 exposure on HCC progression and the underlying mechanisms remain largely unknown. This study aimed to investigate the effects of PM2.5 exposure on the stem cell-like properties of HCC cells. Our findings indicate that PM2.5 exposure significantly enhances the stemness of HCC cells (p < 0.01). Subsequently, male nude mice were divided into two groups (n = 8/group for tumor-bearing assay, n = 5/group for metastasis assay) for control and PM2.5 exposure. In vivo assays revealed that exposure to PM2.5 promoted the growth, metastasis, and epithelial-mesenchymal transition (EMT) of HCC cells (p < 0.01). Further exploration demonstrated that PM2.5 enhances the stemness of HCC cells by inducing cellular reactive oxygen species (ROS) generation (p < 0.05). Mechanistic investigation indicated that elevated intracellular ROS inhibited kelch-like ECH-associated protein 1 (Keap1) levels, promoting the upregulation and nucleus translocation of NFE2-like bZIP transcription factor 2 (Nrf2). This, in turn, induced autophagy activation, thereby promoting the stemness of HCC cells (p < 0.01). Our present study demonstrates the adverse effects of PM2.5 exposure on HCC development and highlights the mechanism of ROS/Nrf2/Keap1-mediated autophagy. For the first time, we reveal the impact of PM2.5 exposure on the poor prognosis-associated cellular phenotype of HCC and its underlying mechanism, which is expected to provide new theoretical basis for the improvement of public health.

Adequate Intake of Dietary Fiber May Relieve the Detrimental Impact of Blood Lead on Dyslipidemia among US Adults: A Study of Data from the National Health and Nutrition Examination Survey Database.

Lead (Pb) exposure is a well-established risk factor for dyslipidemia, and people are exposed to it in multiple ways daily. Dietary fiber is presumed to improve lipid metabolism disorders, but it is still unknown whether it can relieve the detrimental impact of Pb on dyslipidemia. We used publicly accessible data from the 2011-2016 cycles of the National Health and Nutrition Examination Survey (NHANES). A total of 2128 US adults were enrolled for the subsequent analysis. Heavy metal concentrations in blood were measured using inductively coupled plasma mass spectrometry (ICP-MS). A weighted logistic regression was conducted to calculate odds ratios (ORs) and 95% confidence intervals (CIs). The dose-response relationship between blood heavy metals and dyslipidemia was explored using a weighted restricted cubic spline (RCS) analysis. After fully adjusting for potential confounding factors (age, gender, race, education level, ratio of family income to poverty, marital status, body mass index, physical activity, waist circumference, smoke, alcohol drinking and history of metabolic syndrome, hypertension, and diabetes), a positive association between blood Pb levels and dyslipidemia risk was revealed (OR = 1.20, 95% CI: 1.03-1.40). Dietary fiber intake may significantly modify the association between blood Pb levels and dyslipidemia (p-interaction = 0.049), with a stronger association (OR = 1.26, 95% CI: 1.05-1.52) being revealed in individuals with an inadequate intake of dietary fiber (<14 g/1000 kcal/day), but a null association (OR = 1.01, 95% CI: 0.72-1.42) being observed in those with an adequate intake of dietary fiber (≥14 g/1000 kcal/day). Moreover, the weighted RCS analysis showed that compared with the average blood Pb exposure level (4.24 µg/dL), a lower blood Pb exposure level (3.08 µg/dL) may contribute to the risk of dyslipidemia in the group with an inadequate dietary fiber intake. Our findings suggest that Pb exposure in blood may be a risk factor for dyslipidemia. However, an adequate dietary fiber intake may offset the risk of dyslipidemia caused by blood Pb exposure. Since avoiding Pb exposure in daily life is difficult, increasing dietary fiber intake in the future might be a promising approach to alleviate dyslipidemia caused by Pb exposure.

Plasma metabolome identifies potential biomarkers of gastric precancerous lesions and gastric cancer risk.

OBJECTIVES: Currently, metabolic biomarkers with great practicability of gastric cancer (GC) and gastric precancerous lesions (GPL) are scarce. Thus, we are devoted to determining the plasma metabolic profiles of patients with GPL or GC and validate candidate biomarkers for disease diagnosis. METHODS: In this hospital-based case-control study, 68 plasma samples from 27 non-atrophic gastritis (NAG, control), 31 GPL, and 10 GC patients were collected for targeted metabolomics analysis. Univariate and multivariate analyses were used for selecting the differential metabolites. A receiver operating characteristic curve combined with binary logistic regression analysis was performed to test the diagnostic performance of the differential metabolites. Dietary data were obtained using a semiquantitative food frequency questionnaire. RESULTS: Distinct metabolomic profiles were noted for NAG, GPL, and GC. Compared to the NAG patients, the levels of 5 metabolites in the GPL group and 4 metabolites in the GC group were found to significantly elevate. Compared with the model involving 9 traditional risk factors (AUC: 0.89, 95%CI: 0.78-1.00), Trimethylamine N-oxide, the most significant metabolite (P = 2.00 × 10-5, FDR = 0.003, FC > 2, VIP > 2), showed a good diagnostic performance for the patients with GC (AUC: 0.90, 95%CI: 0.78-1.00), and its diagnostic performance has been further improved with the integration of Rhamnose (AUC: 0.96, 95%CI: 0.89-1.00). CONCLUSION: In our study, 9 defined metabolites might serve as meaningful biomarkers for identifying the high-risk population of GPL and GC, possibly enhancing the prevention and control of GPL and GC.

[Effects of whole grains on insulin resistance in overweight and obese adults: a Meta-analysis].

OBJECTIVE: To conduct a Meta-analysis of the effects of whole grains on insulin resistance in overweight and obese adults in randomize controlled trials. METHODS: Data were retrieved from PubMed, EMBASE, MEDLINE, Cochrane Library, CBM, CNKI and other databases from the database establishment to August 9, 2021. Randomize controlled trials of the effects of whole grains on insulin resistance in overweight and obese adults were screened out. Data extraction and quality evaluation were conducted for the literatures meeting the inclusion criteria. The Meta-analysis was conducted using R4.1.2 software. RESULTS: A total of 10 randomized controlled trials were included. Among the overweight and obese adults, the whole grains intake decreased their fasting plasma glucose(FPG)(MD=-0.08, 95%CI-0.12, -0.04), homeostasis model assessment of insulin resistance(HOMA-IR)(MD=-0.37, 95%CI-0.60, -0.14) and quantitative insulin sensitivity index(QUICKI)(MD=0.006, 95%CI 0.005, 0.007). However, there were no statistically significant among fasting insulin(FINS), postprandial blood glucose(PG), postprandial insulin(PI), and triglycerides(TG) in overweight and obese adults. In subgroup analysis, FPG was statistically significant in German, quality score 4, 150-200 g intake of whole grain, and health subgroups of each population. There was no statistical significance of the QUICKI group. In sensitivity analysis and publication bias, FINS, PG, PI and TG became significant after one article was removed. However, HOMA-IR result were not statistically significant after the removal of one article. Meanwhile, the publication bias of each index was analyzed by Egger regression. Based on the results of subgroup analysis, a further dose-response analysis was conducted on the whole grains intake. The result showed that the FPG effects scale was better when the daily intake of whole grains was between 140 g and 160 g. CONCLUSION: Daily intake of 140 g to 160 g of whole grains improves FPG levels in overweight and obese adults.