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BackgroundThe Xiangjiang River is an important drinking water resource for the Hunan Province of China. It is crucial to ascertain the pollution status, influencing factors, ecological risks, and possible sources of heavy metals in the sediments of the Xiangjiang River. Sediment is both a source and a sink of heavy metals in aquatic ecosystems. In this study, surface sediment was collected from the Zhuzhou Reach of the Xiangjiang River and eight heavy metals were investigated.ResultsIn all sediment samples, all eight heavy metals were detected and their average concentration fell in the order of Zn > Pb > As > Cu > Cr > Ni > Cd > Co. Assessment shows extremely serious Cd pollution and a very high potential ecological risk from Cd. According to correlation analysis and principal component analysis (PCA), As, Cu, Ni, Pb, and Zn originate from industrial wastewater and mineral smelting activities, whereas Co, Cr, and Ni come from natural sources. Redundancy analysis (RDA) reveals that the organic matter content and the particle size of the sediment have a certain influence on the enrichment of heavy metals.ConclusionAmong all eight examined heavy metals in the surveyed area, the content of Zn, Pb, and As is the highest, and that of Cd and Co is the lowest. Despite a low level of absolute content, the Cd in sediment already renders a high ecological risk and thus calls for urgent attention. Anthropogenic activities are the main source of heavy metals in the sediment. The distribution of heavy metals may also be influenced by sediment properties. The results provide guidance for controlling heavy metal pollution and protecting drinking water sources in the Xiangjiang River.

Metal pollution in drinking water source has been under scrutiny as it seriously affects human health. This work examined 12 dissolved metals in the surface and overlying water of the Xiangjiang River, an important drinking water source in southern China, and characterized their distribution, identified their possible sources, assessed their toxicity load, and determined their potential ecological and health risk. No significant difference was found in the metal concentration between surface and overlying water. The average metal concentration fell in the order of Mg > Mn > Ba > Fe > Zn > As > Sb > Ni > Cd > V > Cr > Co, and all was lower than the safety threshold in the drinking water guideline of China. Anthropogenic activities were found to be the main source of metals from correlation analysis, principal component analysis (PCA), and cluster analysis (CA). According to the total heavy metal toxicity load (HMTL), 98.20%, 71.54%, 68.88%, and 7.97% of As, Cd, Sb, and Mn should be removed from the surface water to ensure safety. Most water samples from the surveyed area were found to have high ecological risk as was measured by the ecological risk index (RI). Health risk assessment showed that children are more susceptible than adults to the non-carcinogenic risk of dissolved metals, and the potential carcinogenic risk (CR) of As and Cd should be addressed. The results provide guidance for controlling the metal pollution of the Xiangjiang River and improving its quality as a drinking water source.

This work examined the contamination of poly- and perfluorinated compounds (PFASs) in the water and sediment of the Baiyangdian Lake. The total concentration of PFASs in the surface water varied from 140.5 to 1828.5 ng/L, and the highest concentration of PFASs were observed near the entrance of Fuhe river. The topmost contaminant was sodium perfluorohexanesulfonate (PFHxS) and perfluorooctanoic acid (PFOA) in the north and south of the Baiyangdian Lake respectively, which indicated different contamination sources. The total concentration of PFASs in the sediment varied from 0.48 to 30 ng/g, and the distribution of PFASs in the sediment was similar with that in the surface water. The concentrations of polyfluoroalkyl phosphoric diesters (diPAPs) were three to four orders of magnitude lower than those of perfluorocarboxylates (PFCAs) and PFSAs. Although the pore water and the surface water had similar ΣPFASs, the concentration of perfluorodecanoic acid (PFDA) in pore water was 1.4 to 4.4 times higher than that in surface water, and the concentration of perfluoropentanoic acid (PFPeA) in pore water was 20–70% that in surface water. The results of ecological risk assessment showed that the PFASs were currently of no immediate risk to the aquatic life.

BackgroundAs the longest river in Asia, the Yangtze River flows through the most industrialized cities in China and provides critical ecological services for agriculture, industry, and transportation. Polychlorinated biphenyls (PCBs) have been banned for many years, but trace amounts of PCBs still exist as persistent organic pollutant in drinking water and are an ecotoxicological problem. In this work, we collected water, sediment, and suspended particulate matter (SPM) samples along the Yangtze River, to study the distribution and transport of PCBs for the risk assessment of the Yangtze River as a drinking water source.ResultsThe ΣPCBs concentrations in water, sediment, and SPM ranged in 0.04–11 ng/L, 0.33–69 ng/g, and 0.72–153 ng/L, respectively. The main pollutants were PCB17, 18, 28, 47, and 118 in the Yangtze River. The ffSW value of PCB18 and PCB28 all exceeded 0.50, whereas the ffSW value of PCB47 and PCB118 (except for PCB118 at Y-4) was less than 0.50. The toxic equivalent quantity (TEQ) range of PCBs in water and in sediment was ND–5.55 pg-TEQ/L and ND–2.51 pg-TEQ/g, respectively.ConclusionsIn both water and sediment, lower chlorinated PCBs are dominant in the middle reaches and higher chlorinated PCBs are dominant at downstream. In contrast, SPM is dominated by tetra-CBs. The ffSW values reveal a net redissolution of lower PCBs from sediments to water but a net sorption of higher PCBs from water to sediment. The PCBs in water and sediment at downstream pose potential ecological risk, but the drinking water does not have a non-carcinogenic risk for humans.

Volatile organic compounds (VOCs) typically exist in the aqueous environment due to global anthropogenic activities. The distribution and contaminated profile (or characteristics) of VOCs in the groundwater of Lanzhou, China, were investigated in this study. Groundwater samples were collected from 30 sampling points in December 2015, and a total of 17 VOCs were analyzed by purge and trap gas chromatography–mass spectrometry. Thirteen types of VOCs were detected at 29 sampling points in the study area. Of these, dichloromethane and toluene, which were found at 22 sampling points, had the highest detection frequency (73.3%), followed by benzene (66.7%), 1,2-dichloroethane (50%), and xylenes (50%). The highest average concentration among the detected VOCs was found for chloroform (5151.5 μg/L). The spatial distribution of VOC contamination in four major urban areas of Lanzhou and the variation in VOC concentration caused by land use transitions were also analyzed. The results showed that Xigu district was the most polluted area in Lanzhou, mainly due to land use for industrial proposes. On the contrary, the samples for Anning district showed lower VOC concentrations because of better groundwater quality, which is associated with the absence of manufacturing industries in this region. The health risk assessment model developed by the United States Environmental Protection Agency was employed in this study to evaluate safety for drinking water use. This study found that despite considering the volatilization of VOCs from water due to heating, six sampling points (G05 in Qilihe district; G07 and G09 in Xigu district; G16, G17, and G15 in Chengguan district) showed non-carcinogenic risks, ranging from 1.63 to 14.2, while three points (G16 in Chengguan district, and G10 and G07 in Xigu district) exhibited high carcinogenic risks for human health, ranging from 2.94 × 10−4 to 6.85 × 10−4. Trichloroethylene, tetrachloroethylene, and 1,2-dichloroethylene were identified as the dominant VOCs, presenting high non-carcinogenic risk. 1,2-dichloroethane and vinyl chloride were the primary factors for high carcinogenic risk. The high-risk areas were concentrated in Xigu and Chengguan districts, suggesting the need to alert the relevant local government departments.

China has implemented the “tiered medical services” policy since 2015, while there is a paucity of data evaluating the the current status of chronic obstructive pulmonary disease (COPD) management under the system. Characteristics and treatments from 11,905 COPD patients in 88 hospitals across different tiers in China were included and analyzed. We assessed the statistical significance of differences by one way analysis of variance (ANOVA) for continuous variables and with the chi-squared test for categorical variables. Patients in primary hospitals (Tier1) exhibited heightened exposure to risk factors including smoking, household biofuel, and family history of respiratory diseases, and displayed elevated COPD assessment test (CAT) and modified Medical Research Council (mMRC) dyspnea scale scores, and worse lung function, in comparison to tertiary (Tier3) hospitals ( P  < 0.001). However, the utilization of inhaled maintenance treatments in Tier1 hospitals is markedly lower than that in Tier3 hospitals (54.8% vs. 81.3%, P  < 0.001). At odds with the patients with more severer symptoms (as indicated by CAT ≥ 10 or mMRC ≥ 2), a higher proportion relied exclusively on single bronchodilators in Tier1 hospitals was observed compared to secondary (Tier2) and Tier3 hospitals (37.7% vs. 32.1% vs. 26.3%, 40.0% vs. 29.8% vs. 25.6%, P <0.001). Dual bronchodilators (long-acting β2-agonists /long-acting muscarinic antagonist, LABA/LAMA) represented the least common medication regimen across all tiers of hospitals, albeit their usage rates increased in tandem with hospital tier (0.7% vs. 7.2% vs. 10.4%, P  < 0.001). In addition, the use of inhalation therapies containing inhaled corticosteroids (ICS) in China’s primary care is notably lower (16.9%) than the United States, the United Kingdom, and other middle-to-high-income countries (29.5-57.0%). There was compelling evidence pointing to greater disease severity in Tier1 hospitals, attributable to the lower and inappropriate utilization of inhaled maintenance treatments. This underscores the necessity for enhanced availability of medications and educational initiatives aimed at both physicians and patients within Tier1 hospitals.

[...]despite having a higher diagnostic accuracy, TTNA has been associated with a high rate of pneumothorax. [...]conventional bronchoscopy with a low rate of pneumothorax has exhibited a low diagnostic yield for peripheral pulmonary nodules, particularly for nodules <2 cm in size or those without a bronchus leading directly to them. [...]Herth et al[1] developed a novel bronchoscopy technique called bronchoscopic transparenchymal nodule access (BTPNA) under the guidance of Archimedes Virtual Bronchoscopic Navigation (VBN) System for the purpose of accessing pulmonary nodules using a transparenchymal approach without relying on the airway to approach the lesion. Biopsy yield and sampling yield of the tunnel length created: A prospective study conducted by Sun et al[6] found no significant difference in the biopsy yield between a tunnel length of <30 and ≥30 mm (78.9% vs. 90.6%, P = 0.40). [...]BTPNA significantly improved the diagnostic yield of pulmonary nodules in certain anatomical locations of the lung and may play a complementary role for TTNA. Limitations of this novel approach: [...]it is more difficult to adjust the angulation and orientation of the sheath and dissection tip to the desired direction.

Background The relationship between periodontitis and cardiovascular disease (CVD) has been extensively studied, but the role of biological aging in this relationship remains poorly understood. This study is dedicated to investigating the effect of periodontitis on the incidence of CVD and to elucidating the potential mediating role of biological aging. Furthermore, this study will seek to elucidate the causal association between periodontitis, CVD, and biological aging. Methods We included 3269 participants from the National Health and Nutrition Examination Survey (2009–2014) with diagnostic information on periodontitis and composite CVD events. Biological aging was evaluated by utilizing both the Klemera–Doubal method’s calculated biological age (KDMAge) and phenotypic age (PhenoAge). Logistic regression, restricted cubic spline (RCS) analysis, and subgroup analysis were used for data analysis. Mediation analysis was employed to explore the mediating role of biological aging. Subsequently, Mendelian randomization (MR) analyses were performed using genome-wide association study databases to explore potential causal relationships between periodontitis, CVD, and biological aging. Results Periodontitis was associated with a higher risk of CVD. Participants with periodontitis were found to have increased levels of biological aging, and elevated levels of biological aging were associated with increased CVD risk. Mediation analyses showed a partial mediating effect of biological aging (PhenoAge: 44.6%; KDMAge: 22.9%) between periodontitis and CVD risk. MR analysis showed that periodontitis played a causal role in increasing the risk of small vessel stroke, while myocardial infarction was found to increase the risk of periodontitis. In addition, reverse MR analysis showed that phenotypic aging can increase the risk of periodontitis, and there is a two-way causal relationship between CVD and biological aging. Conclusions Periodontitis is associated with an increased CVD risk, partially mediated by biological aging, with a complex causal interrelationship. Targeted interventions for periodontal health may slow the biological aging processes and reduce CVD risk.

BackgroundThe residual chemical pollutants in drinking water may cause adverse effects on human health. Chemical compounds potentially affecting human health have been widely explored, while the multiphasic evaluation of chemical compounds by process control and human health risk is still rarely reported. In the present study, we used multiphasic criteria to assess the health risk including effluent concentration, accumulation index, purification index for the removal efficiency during the drinking water treatment processes, carcinogen classification based on the International Agency for Research on Cancer standards, non-carcinogenic health hazards and carcinogenic risk.ResultsAmong the monitored chemicals, 47 and 44 chemical compounds were detected in raw water and treated water, respectively. The generation and removal of chemical compounds implied that the migration and transformation of chemicals during the purification processes affected the effluent concentration, posing a direct potential health risk. Of these compounds, 41 contaminants’ profiles were screened as priority chemical compounds (PCCs).ConclusionsThe top eight PCCs with high carcinogenic risk were highlighted. Some effective steps, such as protecting the raw water sources, improving the removal performance and reducing the disinfection by-products during the purification process by introducing advanced treatment technologies, were suggested to maintain drinking water security. Collectively, our findings provided novel scientific supports for the sustainable management of drinking water to promote human health.

The Bronchial Provocation Test (BPT) is the gold standard for diagnosing airway hyperresponsiveness (AHR) in suspected asthma patients but is time-consuming and resource-intensive. This study explores the potential of baseline pulmonary function parameters, particularly small airway indices, in predicting AHR and develops a machine learning-based model to improve screening efficiency and reduce unnecessary BPT referrals. This retrospective study analyzed baseline pulmonary function data and BPT results from Henan Provincial People's Hospital (May to September 2024). Data were randomly split into training (69.8%,  = 289) and validation (30.2%,  = 125) groups using R software (Version 4.4.1). The Least Absolute Shrinkage and Selection Operator (LASSO) was applied to identify the most predictive variables, and 10-fold cross-validation was used to determine the optimal penalty parameter (  = 0.023) to prevent overfitting. Model fit was evaluated using the Akaike Information Criterion (AIC), and a logistic regression model was constructed along with a nomogram. The optimal model (Model C, AIC = 310.44) included FEV1/FVC%, MEF75%, PEF%, and MMEF75-25%, which demonstrated superior discriminative capacity in both the training (AUC = 0.790, cut-off = 0.354, 95% CI: 0.724-0.760) and validation cohorts (AUC = 0.756, cut-off = 0.404, 95% CI: 0.600-0.814). In the validation cohort, multidimensional validation through calibration plots showed a slope of 0.883. The Net Reclassification Improvement (NRI) for Model C compared to other models was 0.169 (vs. Model A), 0.144 (vs. Model B), and 0.158 (vs. Model D). The Integrated Discrimination Improvement (IDI) and Decision Curve Analysis (DCA) indicated that Model C provided superior predictive performance and a significantly higher net benefit compared to the extreme curves. For instance, the 10th randomly selected patient in the validation cohort showed an 89.80% probability of AHR diagnosis, with a well-fitting model. This study identifies MEF75%, MMEF75-25%, FEV1/FVC%, and PEF% as effective predictors of early airway hyperresponsiveness in suspected asthma patients. The machine learning-based predictive model demonstrates strong performance and clinical utility, offering potential as a visual tool for early detection and standardized treatment, thereby reducing the risk of symptom exacerbation, lung function decline, and airway remodeling.