Microbes for lung cancer detection: feasibility and limitations.

As the second most common cancer in the world, the development of lung cancer is closely related to factors such as heredity, environmental exposure, and lung microenvironment, etc. Early screening and diagnosis of lung cancer can be helpful for the treatment of patients. Currently, CT screening and histopathologic biopsy are widely used in the clinical detection of lung cancer, but they have many disadvantages such as false positives and invasive operations. Microbes are another genome of the human body, which has recently been shown to be closely related to chronic inflammatory, metabolic processes in the host. At the same time, they are important players in cancer development, progression, treatment, and prognosis. The use of microbes for cancer therapy has been extensively studied, however, the diagnostic role of microbes is still unclear. This review aims to summarize recent research on using microbes for lung cancer detection and present the current shortcomings of microbes in collection and detection. Finally, it also looks ahead to the clinical benefits that may accrue to patients in the future about screening and early detection.

Machine learning-based integration develops an immunogenic cell death-derived lncRNA signature for predicting prognosis and immunotherapy response in lung adenocarcinoma.

Accumulating evidence demonstrates that lncRNAs are involved in the regulation of the immune microenvironment and early tumor development. Immunogenic cell death occurs mainly through the release or increase of tumor-associated antigen and tumor-specific antigen, exposing "danger signals" to stimulate the body's immune response. Given the recent development of immunotherapy in lung adenocarcinoma, we explored the role of tumor immunogenic cell death-related lncRNAs in lung adenocarcinoma for prognosis and immunotherapy benefit, which has never been uncovered yet. Based on the lung adenocarcinoma cohorts from the TCGA database and GEO database, the study developed the immunogenic cell death index signature by several machine learning algorithms and then validated the signature for prognosis and immunotherapy benefit of lung adenocarcinoma patients, which had a more stable performance compared with published signatures in predicting the prognosis, and demonstrated predictive value for benefiting from immunotherapy in multiple cohorts of multiple cancers, and also guided the utilization of chemotherapy drugs.

Effect-directed analysis of androgenic compounds from sewage sludges in China.

The safety of municipal sewage sludge has raised great concerns because of the accumulation of large-scale endocrine disrupting chemicals in the sludge during wastewater treatment. The presence of contaminants in sludge can cause secondary pollution owing to inappropriate disposal mechanisms, posing potential risks to the environment and human health. Effect-directed analysis (EDA), involving an androgen receptor (AR) reporter gene bioassay, fractionation, and suspect and nontarget chemical analysis, were applied to identify causal AR agonists in sludge; 20 of the 30 sludge extracts exhibited significant androgenic activity. Among these, the extracts from Yinchuan, Kunming, and Shijiazhuang, which held the most polluted AR agonistic activities were prepared for extensive EDA, with the dihydrotestosterone (DHT)-equivalency of 2.5 - 4.5 ng DHT/g of sludge. Seven androgens, namely boldione, androstenedione, testosterone, megestrol, progesterone, and testosterone isocaproate, were identified in these strongest sludges together, along with testosterone cypionate, first reported in sludge media. These identified androgens together accounted for 55 %, 87 %, and 52 % of the effects on the sludge from Yinchuan, Shijiazhuang, and Kunming, respectively. This study elucidates the causative androgenic compounds in sewage sludge and provides a valuable reference for monitoring and managing androgens in wastewater treatment.

Deciphering the heterogeneity dominated by tumor-associated macrophages for survival prognostication and prediction of immunotherapy response in lung adenocarcinoma.

Tumor-associated macrophages (TAMs) are a specific subset of macrophages that reside inside the tumor microenvironment. The dynamic interplay between TAMs and tumor cells plays a crucial role in the treatment response and prognosis of lung adenocarcinoma (LUAD). The study aimed to examine the association between TAMs and LUAD to advance the development of targeted strategies and immunotherapeutic approaches for treating this type of lung cancer. The study employed single-cell mRNA sequencing data to characterize the immune cell composition of LUAD and delineate distinct subpopulations of TAMs. The "BayesPrism" and "Seurat" R packages were employed to examine the association between these subgroups and immunotherapy and clinical features to identify novel immunotherapy biomarkers. Furthermore, a predictive signature was generated to forecast patient prognosis by examining the gene expression profile of immunotherapy-associated TAMs subsets and using 104 machine-learning techniques. A comprehensive investigation has shown the existence of a hitherto unidentified subgroup of TAMs known as RGS1 + TAMs, which has been found to have a strong correlation with the efficacy of immunotherapy and the occurrence of tumor metastasis in LUAD patients. CD83 was identified CD83 as a distinct biomarker for the expression of RGS1 + TAMs, showcasing its potential utility as an indicator for immunotherapeutic interventions. Furthermore, the prognostic capacity of the RTMscore signature, encompassing three specific mRNA (NR4A2, MMP14, and NPC2), demonstrated enhanced robustness when contrasted against the comprehensive collection of 104 features outlined in the published study. CD83 has potential as an immunotherapeutic biomarker. Meanwhile, The RTMscore signature established in the present study might be beneficial for survival prognostication.

Design and Study of Machine Tools for the Fly-Cutting of Ceramic-Copper Substrates.

Ceramic-copper substrates, as high-power, load-bearing components, are widely used in new energy vehicles, electric locomotives, high-energy lasers, integrated circuits, and other fields. The service length will depend on the substrate's copper-coated surface quality, which frequently achieved by utilising an abrasive strip polishing procedure on the substrate's copper-coated surface. Precision diamond fly-cutting processing machine tools were made because of the low processing accuracy and inability to match the production line's efficiency. An analysis of the fly-cutting machining principle and the structural makeup of the ceramic-copper substrate is the first step in creating a roughness prediction model based on a tool tip trajectory. This model demonstrates that a shift in the tool tip trajectory due to spindle runout error directly impacts the machined surface's roughness. The device's structural optimisation design is derived from the above analyses and implemented using finite element software. Modal and harmonic response analysis validated the machine's gantry symmetrical structural layout, a parametric variable optimisation design optimised the machine tool's overall dimensions, and simulation validated the fly-cutterring's constituent parts. Enhancing the machine tool's stability and motion accuracy requires using the LK-G5000 laser sensor to measure the guideway's straightness. The result verified the machine tool's design index, with the Z- and Y-axes' straightness being better than 2.42 µm/800 mm and 2.32 µm/200 mm, respectively. Ultimately, the device's machining accuracy was confirmed. Experiments with flying-cut machining on a 190 × 140 mm ceramic-copper substrate yielded a roughness of Sa9.058 nm. According to the experimental results, the developed machine tool can fulfil the design specifications.

Aldehyde dehydrogenase 2-mediated aldehyde metabolism promotes tumor immune evasion by regulating the NOD/VISTA axis.

BACKGROUND: Aldehyde dehydrogenase 2 (ALDH2) is a crucial enzyme involved in endogenous aldehyde detoxification and has been implicated in tumor progression. However, its role in tumor immune evasion remains unclear. METHODS: Here, we analyzed the relationship between ALDH2 expression and antitumor immune features in multiple cancers. ALDH2 knockout tumor cells were then established using CRISPR/Cas9 system. In immunocompetent breast cancer EMT6 and melanoma B16-F10 mouse models, we investigated the impact of ALDH2 blockade on cytotoxic T lymphocyte function and tumor immune microenvironment by flow cytometry, mass cytometry, Luminex liquid suspension chip detection, and immunohistochemistry. Furthermore, RNA sequencing, flow cytometry, western blot, chromatin immunoprecipitation assay, and luciferase reporter assays were employed to explore the detailed mechanism of ALDH2 involved in tumor immune evasion. Lastly, the synergistic therapeutic efficacy of blocking ALDH2 by genetic depletion or its inhibitor disulfiram in combination with immune checkpoint blockade (ICB) was investigated in mouse models. RESULTS: In our study, we uncovered a positive correlation between the expression level of ALDH2 and T-cell dysfunction in multiple cancers. Furthermore, blocking ALDH2 significantly suppressed tumor growth by enhancing cytotoxic activity of CD8+ T cells and reshaping the immune landscape and cytokine milieu of tumors in vivo. Mechanistically, inhibiting ALDH2-mediated metabolism of aldehyde downregulated the expression of V-domain Ig suppressor of T-cell activation (VISTA) via inactivating the nucleotide oligomerization domain (NOD)/nuclear factor kappa-B (NF-κB) signaling pathway. As a result, the cytotoxic function of CD8+ T cells was revitalized. Importantly, ALDH2 blockade markedly reinforced the efficacy of ICB treatment. CONCLUSIONS: Our data delineate that ALDH2-mediated aldehyde metabolism drives tumor immune evasion by activating the NOD/NF-κB/VISTA axis. Targeting ALDH2 provides an effective combinatorial therapeutic strategy for immunotherapy.

Organic ultraviolet absorbents in soils and typical plants from an industrial metropolis in China: Concentrations, profiles and environmental implications.

There is accumulating evidence of the toxicity of organic ultraviolet absorbers (OUVAs); however, limited information is available regarding the presence of OUVAs in terrestrial environments and organisms. Therefore, this study was conducted to investigate the occurrence of 11 OUVAs in soils and typical plant species from an industrial metropolis in China. Total OUVA concentrations in soils ranged from 1.30 to 80.3 ng g-1 DW. Based on comparison with previously reported data, OUVA contamination in soil was not severe. Benzophenone and octocrylene were the dominant OUVAs in soils, with median contributions to total concentrations of 25% and 15%, respectively. Source assessment revealed that the observed OUVA contamination primarily originated from industrial activities and the use of personal care products. The concentration of 11 OUVAs in plants ranged from 159 to 4470 ng g-1 DW, at high levels. Our findings imply that great attention should be given to the presence of these chemicals in plants because of the risk they could pose as well as the potential for biomagnification as plants are eaten by insects and birds. Our results also indicate the necessity to further study the geochemical behavior of these chemicals in urban ecosystems in order to better manage the harmfulness to terrestrial ecological health caused by their exposure through the food chains.

Progress in understanding and treating idiopathic pulmonary fibrosis: recent insights and emerging therapies.

Idiopathic pulmonary fibrosis (IPF) is a long-lasting, continuously advancing, and irrevocable interstitial lung disorder with an obscure origin and inadequately comprehended pathological mechanisms. Despite the intricate and uncharted causes and pathways of IPF, the scholarly consensus upholds that the transformation of fibroblasts into myofibroblasts-instigated by injury to the alveolar epithelial cells-and the disproportionate accumulation of extracellular matrix (ECM) components, such as collagen, are integral to IPF's progression. The introduction of two novel anti-fibrotic medications, pirfenidone and nintedanib, have exhibited efficacy in decelerating the ongoing degradation of lung function, lessening hospitalization risk, and postponing exacerbations among IPF patients. Nonetheless, these pharmacological interventions do not present a definitive solution to IPF, positioning lung transplantation as the solitary potential curative measure in contemporary medical practice. A host of innovative therapeutic strategies are presently under rigorous scrutiny. This comprehensive review encapsulates the recent advancements in IPF research, spanning from diagnosis and etiology to pathological mechanisms, and introduces a discussion on nascent therapeutic methodologies currently in the pipeline.

Understanding bacterial biofilms: From definition to treatment strategies.

Bacterial biofilms are complex microbial communities encased in extracellular polymeric substances. Their formation is a multi-step process. Biofilms are a significant problem in treating bacterial infections and are one of the main reasons for the persistence of infections. They can exhibit increased resistance to classical antibiotics and cause disease through device-related and non-device (tissue) -associated infections, posing a severe threat to global health issues. Therefore, early detection and search for new and alternative treatments are essential for treating and suppressing biofilm-associated infections. In this paper, we systematically reviewed the formation of bacterial biofilms, associated infections, detection methods, and potential treatment strategies, aiming to provide researchers with the latest progress in the detection and treatment of bacterial biofilms.

Disposable Polypropylene Face Masks: A Potential Source of Micro/Nanoparticles and Organic Contaminates in Humans.

We have been effectively protected by disposable propylene face masks during the COVID-19 pandemic; however, they may pose health risks due to the release of fine particles and chemicals. We measured micro/nanoparticles and organic chemicals in disposable medical masks, surgical masks, and (K)N95 respirators. In the breathing-simulation experiment, no notable differences were found in the total number of particles among mask types or between breathing intensities. However, when considering subranges, <2.5 µm particles accounted for ∼90% of the total number of micro/nanoparticles. GC-HRMS-based suspect screening tentatively revealed 79 (semi)volatile organic compounds in masks, with 18 being detected in ≥80% of samples and 44 in ≤20% of samples. Three synthetic phenolic antioxidants were quantified, and AO168 reached a median concentration of 2968 ng/g. By screening particles collected from bulk mask fabrics, we detected 18 chemicals, including four commonly detected in masks, suggesting chemical partition between the particles and the fabric fibers and chemical exposure via particle inhalation. These particles and chemicals are believed to originate from raw materials, intentionally and nonintentionally added substances in mask production, and their transformation products. This study highlights the need to study the long-term health risks associated with mask wearing and raises concerns over mask quality control.

Robustness of Multi-Project Knowledge Collaboration Network in Open Source Community.

Multi-project parallelism is an important feature of open source communities (OSCs), and multi-project collaboration among users is a favorable condition for an OSC's development. This paper studies the robustness of this type of community. Based on the characteristics of knowledge collaboration behavior and the large amount of semantic content generated from user collaboration in open source projects, we construct a directed, weighted, semantic-based multi-project knowledge collaboration network. Using analysis of the KCN's structure and user attributes, nodes are divided into knowledge collaboration nodes and knowledge dissemination nodes that participate in either multi- or single-project collaboration. From the perspectives of user churn and behavior degradation, two types of failure modes are constructed: node failure and edge failure. Based on empirical data from the Local Motors open source vehicle design community, we then carry out a dynamic robustness analysis experiment. Our results show that the robustness of our constructed network varies for different failure modes and different node types: the network has (1) a high robustness to random failure and a low robustness to deliberate failure, (2) a high robustness to edge failure and a low robustness to node failure, and (3) a high robustness to the failure of single-project nodes (or their edges) and a low robustness to the failure of multi-project nodes (or their edges). These findings can be used to provide a more comprehensive and targeted management reference, promoting the efficient development of OSCs.

Rapid identification of salmonella serovars by using Raman spectroscopy and machine learning algorithm.

A widespread and escalating public health problem worldwide is foodborne illness, and foodborne Salmonella infection is one of the most common causes of human illness.For the three most pathogenic Salmonella serotypes, Raman spectroscopy was employed to acquire spectral data.As machine learning offers high efficiency and accuracy, we have chosen the convolutional neural network(CNN), which is suitable for solving multi-classification problems, to do in-depth mining and analysis of Raman spectral data.To optimize the instrument parameters, we compared three laser wavelengths: 532, 638, and 785 nm.Ultimately, the 532 nm wavelength was chosen as the most effective for detecting Salmonella.A pre-processing step is necessary to remove interference from the background noise of the Raman spectrum.Our study compared the effects of five spectral preprocessing methods, Savitzky-Golay smoothing (SG), Multivariate Scatter Correction (MSC), Standard Normal Variate (SNV), and Hilbert Transform (HT), on the predictive power of CNN models.Accuracy(ACC), Precision, Recall, and F1-score 4 machine learning evaluation indicators are used to evaluate the model performance under different preprocessing methods.In the results, SG combined with SNV was found to be the most accurate spectral pre-processing method for predicting Salmonella serotypes using Raman spectroscopy, achieving an accuracy of 98.7% for the training set and over 98.5% for the test set in CNN model.Pre-processing spectral data using this method yields higher accuracy than other methods.As a conclusion, the results of this study demonstrate that Raman spectroscopy when used in conjunction with a convolutional neural network model enables the rapid identification of three Salmonella serotypes at the single-cell level, and that the model has a great deal of potential for distinguishing between different serotypes of pathogenic bacteria and closely related bacterial species.This is vital to preventing outbreaks of foodborne illness and the spread of foodborne pathogens.

Pharmaceutical targeting Th2-mediated immunity enhances immunotherapy response in breast cancer.

BACKGROUND: Breast cancer is a complex disease with a highly immunosuppressive tumor microenvironment, and has limited clinical response to immune checkpoint blockade (ICB) therapy. T-helper 2 (Th2) cells, an important component of the tumor microenvironment (TME), play an essential role in regulation of tumor immunity. However, the deep relationship between Th2-mediated immunity and immune evasion in breast cancer remains enigmatic. METHODS: Here, we first used bioinformatics analysis to explore the correlation between Th2 infiltration and immune landscape in breast cancer. Suplatast tosilate (IPD-1151 T, IPD), an inhibitor of Th2 function, was then employed to investigate the biological effects of Th2 blockade on tumor growth and immune microenvironment in immunocompetent murine breast cancer models. The tumor microenvironment was analyzed by flow cytometry, mass cytometry, and immunofluorescence staining. Furthermore, we examined the efficacy of IPD combination with ICB treatment by evaluating TME, tumor growth and mice survival. RESULTS: Our bioinformatics analysis suggested that higher infiltration of Th2 cells indicates a tumor immunosuppressive microenvironment in breast cancer. In three murine breast cancer models (EO771, 4T1 and EMT6), IPD significantly inhibited the IL-4 secretion by Th2 cells, promoted Th2 to Th1 switching, remodeled the immune landscape and inhibited tumor growth. Remarkably, CD8+ T cell infiltration and the cytotoxic activity of cytotoxic T lymphocyte (CTL) in tumor tissues were evidently enhanced after IPD treatment. Furthermore, increased effector CD4+ T cells and decreased myeloid-derived suppressor cells and M2-like macrophages were also demonstrated in IPD-treated tumors. Importantly, we found IPD reinforced the therapeutic response of ICB without increasing potential adverse effects. CONCLUSIONS: Our findings demonstrate that pharmaceutical inhibition of Th2 cell function improves ICB response via remodeling immune landscape of TME, which illustrates a promising combinatorial immunotherapy.

Tracing Foodborne Botulism Events Caused by Clostridium botulinum in Xinjiang Province, China, Using a Core Genome Sequence Typing Scheme.

Foodborne botulism is a rare but life-threatening illness resulting from the action of a potent toxin mainly produced by Clostridium botulinum. It grows in an oxygen-deficient environment and is extremely viable in meat and soy products, making it one of the most virulent bacteria. How to track foodborne botulism events quickly and accurately has become a key issue. Here, we investigated two foodborne botulism events that occurred in Xinjiang in 2019 based on whole-genome sequencing and also successfully traced the relationship between clinical and food C. botulinum isolates using whole-genome core gene markers. All 59 isolates were classified as group I strains. Of the strains isolated in this study, 44 were found to be botulinum toxin A(B), and 15 isolates contained only the toxin B locus. Both the toxin A and B gene segments were located on the chromosome and organized in an ha cluster. Antibiotic resistance and virulence factors were also investigated. A set of 329 universal core gene markers were established using C. botulinum strains from a public database. These core gene markers were applied to the published C. botulinum genomes, and three outbreaks were identified. This work demonstrates that universal core gene markers can be used to trace foodborne botulism events, and we hope that our work will facilitate this effort in future. IMPORTANCE In this study, we analyzed 59 foodborne botulism (FB)-related strains isolated in Xinjiang Province, China. Our findings not only reveal the group classification, neurotoxin locus organization, antibiotic resistance and virulence factors of these strains but also establish a set of core gene markers for tracing foodborne botulism events, which was verified using published genomes. These findings indicate that these gene markers might be used as a potential tracing tool for FB events caused by C. botulinum group I strains, which have relatively stable genomic components.

Clinicopathological Features of Breast Cancer in Relation to Exposure of Cycling Reproductive Hormones: A Multicenter Retrospective Study of 14,731 Patients Diagnosed with Invasive Breast Cancer.

BACKGROUND Reproductive period for women, begins at menarche and ends at menopause, which represented the total time period of exposure to cycling reproductive hormones. The potential associations between clinicopathological features and the exposure of cycling reproductive hormones has not been extensively studied. The retrospective study enrolled 14,731 patients diagnosed with invasive breast cancer was designed to evaluate factors associated with the reproductive period on breast cancer type and patient outcomes. MATERIAL AND METHODS 14, 731 female breast cancer (BC) patients from Western China Clinical Cooperation Group (WCCCG) between January 1, 2008 to December 31, 2017 were identified. Unconditional logistic regression was performed to assess the associations between clinicopathological features and menarche age, menopause age, and reproductive years. The differences in risk factors between lower and higher number of reproductive years (<35 and ³35 yrs) were examined with the chi-square test. RESULTS First, patients with late menarche age were more likely to present with tumors of higher histological grade and larger sizes. Second, the findings suggested a higher likelihood of smaller tumor sizes in postmenopausal patients with a greater length of reproductive years. Conversely, higher histological grade was associated with this group of patients, compared to their counterparts with shorter reproductive years. Third, in luminal breast cancer, patients with a greater length of reproductive years were more probably present larger tumor. CONCLUSIONS Our findings indicated that several clinicopathologic factors including tumor size and histological grade were associated with the length of reproductive years in patients diagnosed with breast cancer.

FGFR blockade boosts T cell infiltration into triple-negative breast cancer by regulating cancer-associated fibroblasts.

Background: Since T cell exclusion contributes to tumor immune evasion and immunotherapy resistance, how to improve T cell infiltration into solid tumors becomes an urgent challenge. Methods: We employed deep learning to profile the tumor immune microenvironment (TIME) in triple negative breast cancer (TNBC) samples from TCGA datasets and noticed that fibroblast growth factor receptor (FGFR) signaling pathways were enriched in the immune-excluded phenotype of TNBC. Erdafitinib, a selective FGFR inhibitor, was then used to investigate the effect of FGFR blockade on TIME landscape of TNBC syngeneic mouse models by flow cytometry, mass cytometry (CyTOF) and RNA sequencing. Cell Counting Kit-8 (CCK-8) assay and transwell migration assay were carried out to detect the effect of FGFR blockade on cell proliferation and migration, respectively. Cytokine array, western blot, enzyme-linked immunosorbent assay (ELISA) and immunofluorescence (IF) were employed to investigate the potential mechanism by which FGFR inhibition enhanced T cell infiltration. Results: Blocking FGFR pathway by Erdafitinib markedly suppressed tumor growth with increased T cell infiltration in immunocompetent mouse models of TNBC. Mechanistically, FGFR blockade inhibited cancer-associated fibroblasts (CAFs) proliferation, migration and secretion of vascular cell adhesion molecule 1 (VCAM-1) by down-regulating MAPK/ERK pathway in CAFs, thus promoting T cell infiltration by breaking physical and chemical barriers built by CAFs in TIME. Furthermore, we observed that FGFR inhibition combined with immune checkpoint blockade therapy (ICT) greatly improved the therapeutic response of TNBC tumor models. Conclusions: FGFR blockade enhanced ICT response by turning immune "cold" tumor into "hot" tumor, providing remarkable implications of FGFR inhibitors as adjuvant agents for combinatorial immunotherapy.

Genome-Wide Association Study of Root System Architecture in Maize.

Roots are important plant organs for the absorption of water and nutrients. To date, there have been few genome-wide association studies of maize root system architecture (RSA) in the field. The genetic basis of maize RSA is poorly understood, and the maize RSA-related genes that have been cloned are very limited. Here, 421 maize inbred lines of an association panel were planted to measure the root systems at the maturity stage, and a genome-wide association study was performed. There was a strong correlation among eight RSA traits, and the RSA traits were highly correlated with the aboveground plant architecture traits (e.g., plant height and ear leaf length, r = 0.13-0.25, p < 0.05). The RSA traits of the stiff stalk subgroup (SS) showed lower values than those of the non-stiff stalk subgroup (NSS) and tropical/subtropical subgroup (TST). Using the RSA traits, the genome-wide association study identified 63 SNPs and 189 candidate genes. Among them, nine candidate genes co-localized between RSA and aboveground architecture traits. A further co-expression analysis identified 88 candidate genes having high confidence levels. Furthermore, we identified four highly reliable RSA candidate genes, GRMZM2G099797, GRMZM2G354338, GRMZM2G085042, and GRMZM5G812926. This research provides theoretical support for the genetic improvement of maize root systems, and it identified candidate genes that may act as genetic resources for breeding.

Occurrence and distribution of organic ultraviolet absorbents in sediments from small urban rivers, Tianjin, China: Implications for risk management.

Organic ultraviolet absorbents (OUVAs) in the environment have been of increasing concern because of their potential hazards. However, the OUVAs in waters is far from being well studied and little is known about their occurrence in small urban rivers. This study investigated the concentrations and distribution of eleven OUVAs in the sediments from five small urban rivers of Tianjin, China, and found total concentrations in the range of 11.6-189 ng/g dry weight. Relative to other rivers and lakes, no high concentrations of sediment OUVAs were observed in the small rivers. Benzophenone, homosalate and octocrylene were the dominant OUVAs, representing medians of 13.3%, 12.4% and 12.3% of the total concentrations, respectively. Our observed composition profiles of these chemicals were different from those found in most of other waters. The sediment OUVAs may originate more from industrial activities than the use of cosmetics and personal care products in this area. The risk to aquatic organisms from exposure to the sediment OUVAs in these small urban rivers was considered low, except for benzophenone. However, more researches are needed to investigate the pollution and associated risks of these chemicals in urban rivers due to the complexity of their toxicity to aquatic organisms.

Concentrations, distribution and potential health risks of organic ultraviolet absorbents in street dust from Tianjin, a megacity in northern China.

The distribution of organic ultraviolet absorbers (OUVAs) in outdoor dust remains poorly understood, especially in megacities. We measured the concentrations of 11 OUVAs in street dust from Tianjin, China, by a gas chromatography-mass spectrometry, and found total concentrations in the range of 10.3-129 ng/g. These OUVAs were prevalent in the study street dust, but their concentrations were much lower than those in indoor dust reported in other areas previously. Benzophenone and octocrylene were the dominant OUVAs, representing medians of 15.5% and 13.1% of total OUVA concentrations, respectively. Total concentrations of dust OUVAs in the industrial area were higher than the residential, cultural and new urban areas. Source assessment indicated that the OUVAs likely originated mainly from the manufacture and consumption of cosmetics and personal care products, and some may have been from the production and use of OUVA-containing consumer products. The calculated non-carcinogenic risks of OUVAs in street dust were low. Our results further confirmed that the OUVAs were prevalent in the environment, provide useful information for understanding potential risks of these chemicals and developing risk management strategies. Further studies are needed to investigate the occurrence, environmental behaviors and potential risks of these emerging contaminants in outdoor environment.