Background Exposure to polycyclic aromatic hydrocarbons (PAHs) is associated with the development of metabolic syndrome (MS). However, the role of amino acids in PAH-induced MS remains unclear. Objective To explore the impact of PAHs exposure on the incidence of MS among coking workers, and to determine potential modifying effect of amino acid on this relationship. Methods Unmatched nested case-control design was adopted and the baseline surveys of coking workers were conducted in two plants in Taiyuan in 2017 and 2019, followed by a 4-year follow-up. The cohort comprised 667 coking workers. A total of 362 participants were included in the study, with 84 newly diagnosed cases of MS identified as the case group and 278 as the control group. Urinary levels of 11 PAH metabolites and plasma levels of 17 amino acids were measured by ultrasensitive performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). Logistic regression was used to estimate the association between individual PAH metabolites and MS. Stratified by the median concentration of amino acids, Bayesian kernel machine regression (BKMR) model was employed to assess the mixed effects of PAHs on MS. Due to the skewed data distribution, all PAH metabolites and amino acids in the analysis were converted by natural logarithm ln (expressed as lnv). Results The median age of the 362 participants was 37 years, and 83.2% were male. Compared to the control group, the case group exhibited higher concentrations of urinary 2-hydroxyphenanthrene (2-OHPhe), 9-hydroxyphenanthrene (9-OHPhe), and hydroxyphenanthrene (OHPhe) (P=0.005, P=0.049, and P=0.004, respectively), as well as elevated levels of plasma branched chain amino acid (BCAA) and aromatic amino acid (AAA) (P<0.05). After being adjusted for confounding factors, for every unit increase in lnv_2-OHPhe in urine, the OR (95%CI) of MS was 1.57 (1.11, 2.26), and for every unit increase in lnv_OHPhe, the OR (95%CI) of MS was 1.82 (1.16, 2.90). Tyrosine, leucine, and AAA all presented a significant nonlinear correlation with MS. At low levels, tyrosine, leucine, and AAA did not significantly increase the risk of MS, but at high levels, they increased the risk of MS. In the low amino acid concentration group, as well as in the low BCAA and low AAA concentration groups, it was found that compared to the PAH metabolite levels at the 50th percentile (P₅₀), the log-odds of MS when the PAH metabolite levels was at the 75th percentile (P₇₅) were 0.158 (95%CI: 0.150, 0.166), 0.218 (95%CI: 0.209, 0.227), and 0.262 (95% CI: 0.241, 0.282), respectively, However, no correlation between PAHs and MS was found in the high amino acid concentration group. Conclusion Amino acids modify the effect of PAHs exposure on the incidence of MS. In individuals with low plasma amino acid levels, the risk of developing MS increases with higher concentrations of mixed PAH exposure. This effect is partly due to the low concentrations of BCAA and AAA.

BACKGROUND: It is inaccurate to reflect the level of dust exposure through working years. Furthermore, identifying a predictive indicator for lung function decline is significant for coal miners. The study aimed to explored whether club cell secretory protein (CC16) levels can reflect early lung function changes. METHODS: The cumulative respiratory dust exposure (CDE) levels of 1,461 coal miners were retrospectively assessed by constructed a job-exposure matrix to replace working years. Important factors affecting lung function and CC16 were selected by establishing random forest models. Subsequently, the potential of CC16 to reflect lung injury was explored from multiple perspectives. First, restricted cubic spline (RCS) models were used to compare the trends of changes in lung function indicators and plasma CC16 levels after dust exposure. Then mediating analysis was performed to investigate the role of CC16 in the association between dust exposure and lung function decline. Finally, the association between baseline CC16 levels and follow-up lung function was explored. RESULTS: The median CDE were 35.13 mg/m³-years. RCS models revealed a rapid decline in forced vital capacity (FVC), forced expiratory volume in the first second (FEV₁), and their percentages of predicted values when CDE exceeded 25 mg/m³-years. The dust exposure level (<5 mg/m³-years) causing significant changes in CC16 was much lower than the level (25 mg/m³-years) that caused changes in lung function indicators. CC16 mediated 11.1% to 26.0% of dust-related lung function decline. Additionally, workers with low baseline CC16 levels experienced greater reductions in lung function in the future. CONCLUSIONS CC16 levels are more sensitive than lung indicators in reflecting early lung function injury and plays mediating role in lung function decline induced by dust exposure. Low baseline CC16 levels predict poor future lung function.
Uteroglobin/blood* ; Humans ; Dust/analysis* ; Occupational Exposure/analysis* ; Male ; Middle Aged ; Adult ; Retrospective Studies ; Lung Injury/chemically induced* ; Coal Mining ; Biomarkers/blood* ; China/epidemiology* ; Air Pollutants, Occupational ; Female

Natural products, and especially the active ingredients found in traditional Chinese medicine (TCM), have a thousand-year-long history of clinical use and a strong theoretical basis in TCM. As such, traditional remedies provide shortcuts for the development of original new drugs in China, and increasing numbers of natural products are showing great therapeutic potential in various diseases. This paper reviews the molecular mechanisms of action of natural products from different sources used in the treatment of inflammatory diseases and cancer, introduces the methods and newly emerging technologies used to identify and validate the targets of natural active ingredients, enumerates the expansive list of TCM used to treat inflammatory diseases and cancer, and summarizes the patterns of action of emerging technologies such as single-cell multiomics, network pharmacology, and artificial intelligence in the pharmacological studies of natural products to provide insights for the development of innovative natural product-based drugs. Our hope is that we can make use of advances in target identification and single-cell multiomics to obtain a deeper understanding of actions of mechanisms of natural products that will allow innovation and revitalization of TCM and its swift industrialization and internationalization.

Background: The dietary agent sulforaphane (SFN) has been reported to reduce diabetes-induced renal fibrosis, as well as inhibit histone deacetylase (HDAC) activity. Bone morphologic protein 7 (BMP-7) has been shown to reduce renal fibrosis induced by transforming growth factor-beta1. The aim of this study was to investigate the epigenetic effect of SFN on BMP-7 expression in diabetes-induced renal fibrosis. Methods: Streptozotocin (STZ)-induced diabetic mice and age-matched controls were subcutaneously injected with SFN or vehicle for 4 months to measure the in vivo effects of SFN on the kidneys. The human renal proximal tubular (HK11) cell line was used to mimic diabetic conditions in vitro. HK11 cells were transfected to over-express HDAC2 and treated with high glucose/palmitate (HG/Pal) to explore the epigenetic modulation of BMP-7 in SFN-mediated protection against HG/Pal-induced renal fibrosis. Results: SFN significantly attenuated diabetes-induced renal fibrosis in vivo. Among all of the HDACs we detected, HDAC2 activity was markedly elevated in the STZ-induced diabetic kidneys and HG/Pal-treated HK11 cells. SFN inhibited the diabetes-induced increase in HDAC2 activity which was associated with histone acetylation and transcriptional activation of the BMP-7 promoter. HDAC2 over-expression reduced BMP-7 expression and abolished the SFN-mediated protection against HG/Pal-induced fibrosis in vitro. Conclusion Our study demonstrates that the HDAC inhibitor SFN protects against diabetes-induced renal fibrosis through epigenetic up-regulation of BMP-7.