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Metagenomics is a novel genomic tool employed to accurately study the composition of microbial communities in their ecological environments, including mass transport systems. Despite the potential significance of these sites as sources of exposure, the pathogenic microbiomes in these constructed settings remain unexplored. In this study, high-throughput sequencing was utilized to identify the microbiota obtained from the Metropolitan Transport of Shanghai (MTS) during the spring and summer. A diverse range of microbiota, especially pathogens, and models for mapping diversity and environmental variables were analyzed using the metagenomic techniques. The results indicate that bacteria accounted for 95.26% of the categorized genes in the 108 aerosol samples analyzed during the spring and summer, with the remaining 4.73% attributed to eukaryotes, viruses, and archaea. We successfully identified 86 microorganisms that align with the National Microbiology Data Center's List of Pathogenic Microorganisms, uncovering unique characteristics of various species with potential health implications throughout across seasons. Additionally, the distribution and diversity of the microbiota were significantly influenced by temperature, humidity, season, and time of day. The study's findings establish a framework for investigating and evaluating potential public health risks, offering early warning of biosecurity concerns related to these built environments. They also provide a comprehensive and unbiased perspective on the characteristics of microbial communities and potential pathogens in urban metros. Environmental and public health experts will find this investigation into the pathogenic microbiomes found in aerosol samples compelling. [ABSTRACT FROM AUTHOR]

Background: Organophosphate flame retardants (OPFRs) are compounds with a wide range of industrial and commercial applications and are mainly used as flame retardants and plasticizers. The global consumption of OPFRs has risen rapidly in recent decades, and they have been widely detected in environmental media. Unfortunately, OPFRs have been associated with many adverse health outcomes. The issue of the health risks of OPFRs is attracting increasing attention. Therefore, there is a need to review the current state of research and trends in this field to help researchers and policymakers quickly understand the field, identify new research directions, and allocate appropriate resources for further development of the OPFR health risk research field. Methods: This study statistically analyzed 1162 relevant publications included in the Web of Science Core Collection from 2003–2023. The internal and external features of the literature, such as publication trends, countries, authors, journals, and keywords, were quantitatively analyzed and visually presented to identify the research hotspots, compositions, and paradigms of the field and to horizontally and vertically analyze the development trends and structural evolution of the field. Results: The development of the field can be divided into three stages, and the field entered a period of rapid development in 2016. China (649 papers) is the most prolific country, followed by the United States (188 papers). The authors STAPLETON HM and WANG Y have the highest combined impact. International collaboration between countries and researchers still needs to be strengthened. Science of The Total Environment is the most frequently published journal (162 papers), and Environmental Science and Technology is the most frequently cited journal (5285 citations). Endocrine disruption, developmental toxicity, and neurotoxicity are the health effects of greatest interest. Conclusions: Future research is expected to be multidisciplinary, and research hotspots may involve a comprehensive assessment of OPFR exposure in the population, exploration of the mechanisms of endocrine-disrupting effects and in vivo metabolic processes, and examination of the health effects of OPFR metabolites. [ABSTRACT FROM AUTHOR]

Background: The establishment of sister chromatid cohesion N-acetyltransferase 2 (ESCO2) is involved in the development of multiple malignancies. However, its role in hypopharyngeal carcinoma (HPC) progression remains uncharacterized. Methods: This study employed bioinformatics to determine the ESCO2 expression in head and neck squamous cell carcinoma (HNSC) and normal tissues. In vitro cell proliferation, migration, apoptosis, and/or cell cycle distribution assays were used to determine the function of ESCO2 and its relationship with STAT1. Xenograft models were established in nude mice to determine ESCO2 in HPC growth in vivo. Co-immunoprecipitation/mass spectrometry (Co-IP/MS) was conducted to identify the potential ESCO2 binding partners. Results: We found that ESCO2 expression was elevated in HNSC tissues, and ESCO2 depletion suppressed tumor cell migration in vitro and inhibited tumor growth in vitro and in vivo. Co-IP/MS and immunoblotting assays revealed the interaction between ESCO2 and STAT1 in HPC cells. STAT1-overexpression compromised ESCO2-mediated suppressive effects on HPC cell proliferation, viability, and migration. Conclusions: These findings suggest that ESCO2 is crucial in promoting HPC malignant progression through the STAT1 pathway and provides novel therapeutic targets for HPC treatment. [ABSTRACT FROM AUTHOR]

Background: Obstructive sleep apnea (OSA) is a globally prevalent disease with a complex diagnostic method. Severe OSA is associated with multi-system dysfunction. We aimed to develop an interpretable machine learning (ML) model for predicting the risk of severe OSA and analyzing the risk factors based on clinical characteristics and questionnaires. Methods: This was a retrospective study comprising 1656 subjects who presented and underwent polysomnography (PSG) between 2018 and 2021. A total of 23 variables were included, and after univariate analysis, 15 variables were selected for further preprocessing. Six types of classification models were used to evaluate the ability to predict severe OSA, namely logistic regression (LR), gradient boosting machine (GBM), extreme gradient boosting (XGBoost), adaptive boosting (AdaBoost), bootstrapped aggregating (Bagging), and multilayer perceptron (MLP). All models used the area under the receiver operating characteristic curve (AUC) was calculated as the performance metric. We also drew SHapley Additive exPlanations (SHAP) plots to interpret predictive results and to analyze the relative importance of risk factors. An online calculator was developed to estimate the risk of severe OSA in individuals. Results: Among the enrolled subjects, 61.47% (1018/1656) were diagnosed with severe OSA. Multivariate LR analysis showed that 10 of 23 variables were independent risk factors for severe OSA. The GBM model showed the best performance (AUC = 0.857, accuracy = 0.766, sensitivity = 0.798, specificity = 0.734). An online calculator was developed to estimate the risk of severe OSA based on the GBM model. Finally, waist circumference, neck circumference, the Epworth Sleepiness Scale, age, and the Berlin questionnaire were revealed by the SHAP plot as the top five critical variables contributing to the diagnosis of severe OSA. Additionally, two typical cases were analyzed to interpret the contribution of each variable to the outcome prediction in a single patient. Conclusions: We established six risk prediction models for severe OSA using ML algorithms. Among them, the GBM model performed best. The model facilitates individualized assessment and further clinical strategies for patients with suspected severe OSA. This will help to identify patients with severe OSA as early as possible and ensure their timely treatment. Trial registration: Retrospectively registered. [ABSTRACT FROM AUTHOR]

Background: To investigate the relationship between tongue fat content and severity of obstructive sleep apnea (OSA) and its effects on the efficacy of uvulopalatopharyngoplasty (UPPP) in the Chinese group. Method: Fifty-two participants concluded to this study were diagnosed as OSA by performing polysomnography (PSG) then they were divided into moderate group and severe group according to apnea hypopnea index (AHI). All of them were also collected a series of data including age, BMI, height, weight, neck circumference, abdominal circumference, magnetic resonance imaging (MRI) of upper airway and the score of Epworth Sleepiness Scale (ESS) on the morning after they completed PSG. The relationship between tongue fat content and severity of OSA as well as the association between tongue fat content in pre-operation and surgical efficacy were analyzed.Participants underwent UPPP and followed up at 3rd month after surgery, and they were divided into two groups according to the surgical efficacy. Results: There were 7 patients in the moderate OSA group and 45 patients in the severe OSA group. The tongue volume was significantly larger in the severe OSA group than that in the moderate OSA group. There was no difference in tongue fat volume and tongue fat rate between the two groups. There was no association among tongue fat content, AHI, obstructive apnea hypopnea index, obstructive apnea index and Epworth sleepiness scale (all P > 0.05), but tongue fat content was related to the lowest oxygen saturation (r=-0.335, P < 0.05). There was no significantly difference in pre-operative tongue fat content in two different surgical efficacy groups. Conclusions: This study didn't show an association between tongue fat content and the severity of OSA in the Chinese group, but it suggested a negative correlation between tongue fat content and the lowest oxygen saturation (LSaO2). Tongue fat content didn't influence surgical efficacy of UPPP in Chinese OSA patients. Trial registration: This study didn't report on a clinical trial, it was retrospectively registered. [ABSTRACT FROM AUTHOR]

Air pollution is a global public health concern, and numerous studies have attempted to identify the health effects of air pollutants, including nitrogen dioxide (NO2). In China, there are few studies investigating the relationship between NO2 exposure and symptoms among children at an individual level. The aim of the study was to evaluate the acute effects of NO2 on prevalence of symptoms of primary students. An environmental and health questionnaire survey was administered to 4240 primary students in seven districts of Shanghai. Daily symptoms, as well as the daily air pollution and meteorological data from each community, were recorded during the corresponding period. A multivariable logistic regression model was utilized to analyze the relationship between the prevalence of symptoms and NO2 exposure in school-age children. A model with interaction items was adopted to estimate the interactive effects of NO2 and confounding factors on symptoms. The average NO2 level in central urban, industrial and rural areas were 62.07 ± 21.66, 54.86 ± 18.32 and 36.62 ± 21.23 μg m−3, respectively. Our findings demonstrate that the occurrence of symptoms was significantly affected by NO2 exposure in the short-term. The largest associations were observed for a 10 μg m−3 increase in 5-day moving average (lag04) NO2 concentration with prevalence of general symptoms (odds ratio [OR] = 1.15, 95% confidence interval [95% CI]: 1.07–1.22), throat symptoms (OR = 1.23, 95% CI: 1.13–1.35) and nasal symptoms (OR = 1.142, 95% CI: 1.02–1.27). Subgroup analysis showed that non-rural areas, boys, nearby environmental pollution source and history of present illness were all susceptible factors to the effects of NO2 exposure. Furthermore, there were interactive effects between NO2 exposure and area types on reported symptoms. NO2 can increase the risk of symptoms in primary students in the short-term, which could be significantly enhanced in central urban and industrial areas. [ABSTRACT FROM AUTHOR]

Background: Obstructive sleep apnea (OSA) is mainly characterized by sleep fragmentation and chronic intermittent hypoxia (CIH), the latter one being associated with multiple organ injury. Recently, OSA-induced cognition dysfunction has received extensive attention from scholars. Astrocytes are essential in neurocognitive deficits via A1/A2 phenotypic changes. Nucleotide oligomerization domain (NOD)-like receptor protein 3 (NLRP3) inflammasome is considered the most important factor inducing and maintaining neuroinflammation. However, whether the NLRP3 regulates the A1/A2 transformation of astrocytes in CIH-related brain injury remains unclear.Methods: We constructed an OSA-related CIH animal model and assessed the rats' learning ability in the Morris water maze; the histopathological assessment was performed by HE and Nissl staining. The expression of GFAP (astrocyte marker), C3d (A1-type astrocyte marker), and S100a10 (A2-type astrocyte marker) were detected by immunohistochemistry and immunofluorescence. Western blotting and RT-qPCR were used to evaluate the changes of A1/A2 astrocyte-related protein and NLRP3/Caspase-1/ASC/IL-1β.Results: The learning ability of rats decreased under CIH. Further pathological examination revealed that the neurocyte in the hippocampus were damaged. The cell nuclei were fragmented and dissolved, and Nissl bodies were reduced. Immunohistochemistry showed that astrocytes were activated, and morphology and number of astrocytes changed. Immunofluorescence, Western blotting and RT-qPCR showed that the expression of C3d was increased while S100a10 was decreased. Also, the expression of the inflammasome (NLRP3/Caspase-1/ASC/IL-1β) was increased. After treatment of MCC950 (a small molecule inhibitor of NLRP3), the damage of nerve cells was alleviated, the Nissl bodies increased, the activation of astrocytes was reduced, and the expression of A2-type astrocytes was increased. In contrast, A1-type astrocytes decreased, and the expression of inflammasome NLRP3/Caspase-1/ASC/IL-1β pathway-related proteins decreased.Conclusion: The NLRP3 inflammasome could regulate the A1/A2 transformation of astrocytes in brain injury induced by CIH. [ABSTRACT FROM AUTHOR]

The critical role of the tumor immune microenvironment (TIME) in determining response to immune checkpoint inhibitor (ICI) therapy underscores the importance of understanding cancer cell–intrinsic mechanisms driving immune-excluded ("cold") TIMEs. One such cold tumor is oral cavity squamous cell carcinoma (OSCC), a tobacco-associated cancer with mutations in the TP53 gene which responds poorly to ICI therapy. Because altered TP53 function promotes tumor progression and plays a potential role in TIME modulation, here we developed a syngeneic OSCC models with defined Trp53 (p53) mutations and characterized their TIMEs and degree of ICI responsiveness. We observed that a carcinogen-induced p53 mutation promoted a cold TIME enriched with immunosuppressive M2 macrophages highly resistant to ICI therapy. p53-mutated cold tumors failed to respond to combination ICI treatment; however, the combination of a programmed cell death protein 1 (PD-1) inhibitor and stimulator of interferon genes (STING) agonist restored responsiveness. These syngeneic OSCC models can be used to gain insights into tumor cell–intrinsic drivers of immune resistance and to develop effective immunotherapeutic approaches for OSCC and other ICI-resistant solid tumors. Oral squamous cell carcinoma models are presented with defined Trp53 mutations associated with immune checkpoint inhibitor responsiveness, e.g. T122N amino acid change of Tp53 promotes a cold TME enriched with immunosuppressive M2 macrophages resistant to ICI therapy. [ABSTRACT FROM AUTHOR]

Background: In children, obstructive sleep apnea (OSA) can cause cognitive dysfunctions. Amyloid-beta and tau are elevated in OSA. Neurofilament light (NfL) is a marker of neuro-axonal damage, but there are no reports of NfL for OSA. The objective was to investigate the serum levels of NfL and tau in children with or without OSA and explore their relationship with cognitive dysfunctions caused by OSA.Methods: This retrospective case-control study included children diagnosed with adenoid tonsil hypertrophy from July 2017 to September 2019 at the Second Affiliated Hospital of Xi'an Jiaotong University. Correlations between cognitive scores and tau and NfL were examined.Results: Fifty-six OSA and 49 non-OSA children were included. The serum NfL levels were higher in the OSA group (31.68 (27.29-36.07) pg/ml) than in the non-OSA group (19.13 (17.32-20.95) pg/ml) (P < 0.001). Moreover, NfL was correlated with the course of the disease, apnea-hypopnea index (AHI), obstructive apnea index (OAI), obstructive apnea-hypopnea index (OAHI), average oxygen saturation (SaO2), respiratory arousal index (RAI), and cognitive dysfunctions evaluated by the Chinese Wechsler Intelligence Scale for Children (C-WISC) (all P < 0.05). The area under the receiver operating characteristics curve (AUC) of NfL was 0.816 (95%CI: 0.736-0.897). Multiple regression analysis revealed that NfL was significantly associated with verbal intelligence quotient (VIQ), performance intelligence quotient (PIQ) and full-scale intelligence quotient (FIQ) (P < 0.001, respectively).Conclusions: Serum NfL levels are associated with the severity of cognitive dysfunctions in children diagnosed with adenoid tonsil hypertrophy and might be a candidate noninvasive, objective marker to identify cognitive dysfunctions in children with OSA. [ABSTRACT FROM AUTHOR]

Objective: Polysomnography is typically used to evaluate the severity of obstructive sleep apnea (OSA) but the inconvenience of application and high cost considerably affect the diagnostics. In this study, sleep sound signals are used to detect OSA in patients. Approach: A deep feature transfer-based OSA detection approach is proposed. First, a deep convolutional neural network is trained on large-scale labeled audio data sets to distinguish respiration sounds from environmental noise. Second, the trained model is transferred to recognize respiration sounds in sleep sound signals. Third, the deep features of the detected respiration sounds are used to train a logistic regression classifier to identify OSA patients from potential patients. Polysomnography-based diagnosis is used as a reference. Main results: A self-collected data set of 132 potential OSA patients is applied in OSA detection experiments. The OSA detection performances are tested on four models for different apnea–hypopnea index thresholds and sexes resulting in accuracies of 80.17%, 80.21%, 81.63% and 77.22%. The corresponding areas under the receiver operating characteristic curves are 0.82, 0.80, 0.81 and 0.79. In addition, the proposed method presented a significant performance improvement compared with the state-of-the-art methods. Significance: Big data, deep learning and transfer learning can be successfully applied to improve diagnostic accuracy in OSA detection. The performance of the proposed approach is superior to that of traditional audio analysis technology. The proposed method significantly reduces difficulties in OSA detection and diagnosis, such that potential OSA patients can perform initial inspections by themselves at home. [ABSTRACT FROM AUTHOR]

Objective: The aim of this study was to perform an exposure assessment of PM2.5 (particulate matter less than 2.5μm in aerodynamic diameter) among children and to explore the potential sources of exposure from both indoor and outdoor environments. Methods: In terms of real-time exposure measurements of PM2.5, we collected data from 57 children aged 8–12 years (9.64 ± 0.93 years) in two schools in Shanghai, China. Simultaneously, questionnaire surveys and time-activity diaries were used to estimate the environment at home and daily time-activity patterns in order to estimate the exposure dose of PM2.5 in these children. Principle component regression analysis was used to explore the influence of potential sources of PM2.5 exposure. Results: All the median personal exposure and microenvironment PM2.5 concentrations greatly exceeded the daily 24-h PM2.5 Ambient Air Quality Standards of China, the USA, and the World Health Organization (WHO). The median Etotal (the sum of the PM2.5 exposure levels in different microenvironment and fractional time) of all students was 3014.13 (μg.h)/m3. The concentration of time-weighted average (TWA) exposure of all students was 137.01 μg/m3. The median TWA exposure level during the on-campus period (135.81 μg/m3) was significantly higher than the off-campus period (115.50 μg/m3, P = 0.013 < 0.05). Besides ambient air pollution and meteorological conditions, storey height of the classroom and mode of transportation to school were significantly correlated with children’s daily PM2.5 exposure. Conclusions: Children in the two selected schools were exposed to high concentrations of PM2.5 in winter of 2013 in Shanghai. Their personal PM2.5 exposure was mainly associated with ambient air conditions, storey height of the classroom, and children’s transportation mode to school. [ABSTRACT FROM AUTHOR]