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• Explore the relationship between industrial solid waste and socioeconomic. • Analyze the flow relationships among different sectors of industrial solid waste. • Determine the industrial solid waste discharge responsibility for each sector. • Identify the key sectors for industrial solid waste discharge. • Simulate industrial solid waste reduction measures. Rapid economic development inevitably leads to the discharge of a large amount of common industrial solid waste (CISW), which not only pollutes the environment but also restricts economic development in turn. In this study, a dynamic common industrial solid waste (DCISW) model is developed to analyze the retrospectively CISW development in Shanghai from 2000 to 2017 and simulate prospectively multi-perspective emission reduction measures. Specifically, the dynamic linkages between CISW and socio-economics are established at both the systematic and sectoral levels through input–output analysis, ecological network analysis, and related socio-economic indicators. Abatement measure simulations are conducted using RAS and other methods. The findings reveal that the growth of CISW in Shanghai is closely related to its fast-growing economy. The Others sector (OS) receives the most CISW from other sectors, while the Mining industry (MI) sends the most CISW to others. From production-based, consumption-based, and income-based perspectives, Chemical Products (CP) consistently remain the largest contributors. For the proposed waste generation intensity (WGI) indicator, the Mining industry (MI) is regarded as the main sector in all three perspectives. Moreover, the MI consistently emerges as the key sector of the system. CISW simulations indicate that improving the MI emission technology and increasing the MI output value will be top priorities for CISW emission reduction in Shanghai. This study is expected to provide scientific support to address the CISW problem in Shanghai and other similar fast-growing metropolises. [ABSTRACT FROM AUTHOR]

Amid China's rapid economic expansion, the country's industrial solid waste (ISW) problem is escalating. As each sector generates distinct types of ISW, a multi-indicator assessment of each sector is essential to address China's New Solid Waste Policy. To investigate the ISW situation of each sector and perform a comprehensive assessment, we formulate an industrial solid waste ecological analysis framework based on ISW generation and ISW flow in the sector. Various indicators (i.e., solid waste utilization coefficient, solid waste threat coefficient, and solid waste threat intensity) are employed to assess the utilization of solid waste generated for each sector, as well as the threat of solid waste originating in each sector to society. Ecological network analysis probes the interrelationships between diverse sectors. Taking Shanghai in 2017 as an example, the study indicates that some sectors (e.g., production and supply of electric power and heat power (EH) and metal smelting and rolling processing sector (MS)) exhibit higher direct ISW generation and the direct industrial solid waste value-added coefficient (SVAC) for common industrial solid waste (CISW). Specifically, the direct CISW generation of EH and MS is 539.21Mt and 277.00Mt respectively. The direct SVAC of EH and MS is 157.06kg/103RMB and 126.27kg/103RMB respectively. These sectors should prioritize reducing emissions at the source. Additionally, the threats to society from various sectors are relatively insignificant for the CISW, while for the hazardous waste (HW), all sectors pose a considerable threat to Shanghai's society. Moreover, some sectors (e.g., mining industry) exhibit the highest mutualism relationships in the CISW and the HW. Enhancing mining sector technologies is a vital strategy for mitigating ISW sources. Specifically, MI has 9 pairs of mutualism relationships in the CISW and 8 pairs in the HW. These insights will provide empirical evidence for tackling the ISW problem in Shanghai. [ABSTRACT FROM AUTHOR]

This study focuses on the equity of spatial layout for public service facilities targeting different age groups and proposes a systematic analytical approach. The method mainly includes the following steps: (1) collecting spatial distribution data of population and various types of public service facilities for each age group; (2) establishing demand matrices for different groups regarding different types of public service facilities and calculating supply-demand density; (3) calculating the level of public service accessibility for different population groups at any spatial location; (4) introducing the Gini coefficient to assess the spatial equity of public service accessibility for different age groups; (5) evaluating whether the Gini coefficient meets the planning objectives and identifying areas with inadequate public service accessibility for optimization of facility layout. Choosing Hongkou District in Shanghai as a case study, the analysis process and results indicate the technical feasibility of the proposed method and its supportive role in public service facility planning. Furthermore, the article discusses the importance of a systematic analysis perspective, the applicability of the methodology in planning decisions, and the enhancement of facility supply levels in weak areas. [ABSTRACT FROM AUTHOR]

Neonatal seizure is an important clinical symptom of brain dysfunction, which is more common in infancy than in childhood. At present, video electroencephalogram (VEEG) technology is widely used in clinical practice. However, video electroencephalogram technology has several disadvantages. For example, the wires connecting the medical instruments may interfere with the infant's movement and the gel patch electrode or disk electrode commonly used to monitor EEG may cause skin allergies or even tears. For the above reasons, we developed a wearable multi-sensor platform for newborns to collect physiological and movement signals. In this study, we designed a second-generation multi-sensor platform and developed an automatic detection algorithm for neonatal seizures based on ECG, respiration and acceleration. Data for 38 neonates were recorded at the Children's Hospital of Fudan University in Shanghai. The total recording time was approximately 300 h. Four of the patients had seizures during data collection. The total recording time for the four patients was approximately 34 h, with 30 seizure episodes recorded. These data were evaluated by the algorithm. To evaluate the effectiveness of combining ECG, respiration and movement, we compared the performance of three types of seizure detectors. The first detector included features from ECG, respiration and acceleration records; the second detector incorporated features based on respiratory movement from respiration and acceleration records; and the third detector used only ECG-based features from ECG records. Our study illustrated that, compared with the detector utilizing individual modal features, multi-modal feature detectors could achieve favorable overall performance, reduce false alarm rates and give higher F-measures. [ABSTRACT FROM AUTHOR]

Sleep staging is the essential step in sleep quality assessment and sleep disorders diagnosis. However, most current automatic sleep staging approaches use recurrent neural networks (RNN), resulting in a relatively large training burden. Moreover, these methods only extract information of the whole epoch or adjacent epochs, ignoring the local signal variations within epoch. To address these issues, a novel deep learning architecture named segmented attention network (SAN) is proposed in this paper. The architecture can be divided into feature extraction (FE) and time sequence encoder (TSE). The FE module consists of multiple multiscale CNN (MMCNN) and residual squeeze and excitation block (SE block). The former extracts features from multiple equal-length EEG segments and the latter reinforced the features. The TSE module based on a multi-head attention mechanism could capture the temporal information in the features extracted by FE module. Noteworthy, in SAN, we replaced the RNN module with a TSE module for temporal learning and made the network faster. The evaluation of the model was performed on two widely used public datasets, Montreal Archive of Sleep Studies (MASS) and Sleep-EDFX, and one clinical dataset from Huashan Hospital of Fudan University, Shanghai, China (HSFU). The proposed model achieved the accuracy of 85.5%, 86.4%, 82.5% on Sleep-EDFX, MASS and HSFU, respectively. The experimental results exhibited favorable performance and consistent improvements of SAN on different datasets in comparison with the state-of-the-art studies. It also proved the necessity of sleep staging by integrating the local characteristics within epochs and adjacent informative features among epochs. [ABSTRACT FROM AUTHOR]

Electrical status epilepticus during sleep (ESES) is an epileptic encephalopathy in children with complex clinical manifestations. It is accompanied by specific electroencephalography (EEG) patterns of continuous spike and slow-waves. Quantifying such EEG patterns is critical to the diagnosis of ESES. While most of the existing automatic ESES quantification systems ignore the morphological variations of the signal as well as the individual variability among subjects. To address these issues, this paper presents a hybrid expert system that dedicates to mimicking the decision-making process of clinicians in ESES quantification by taking the morphological variations, individual variability, and medical knowledge into consideration. The proposed hybrid system not only offers a general scheme that could propel a semi-auto morphology analysis-based expert decision model to a fully automated ESES quantification with biogeography-based optimization (BBO), but also proposes a more precise individualized quantification system to involve the personalized characteristics by adopting an individualized parameters-selection framework. The feasibility and reliability of the proposed method are evaluated on a clinical dataset collected from twenty subjects at Children’s Hospital of Fudan University, Shanghai, China. The estimation error for the individualized quantitative descriptor ESES is 0-4.32% and the average estimation error is 0.95% for all subjects. Experimental results show the presented system outperforms existing works and the individualized system significantly improves the performance of ESES quantification. The favorable results indicate that the proposed hybrid expert system for automatic ESES quantification is promising to support the diagnosis of ESES. [ABSTRACT FROM AUTHOR]

Elimination of intra-artifacts in EEG has been overlooked in most of the existing sleep staging systems, especially in deep learning-based approaches. Whether intra-artifacts, originated from the eye movement, chin muscle firing, or heart beating, etc., in EEG signals would lead to a positive or a negative masking effect on deep learning-based sleep staging systems was investigated in this paper. We systematically analyzed several traditional pre-processing methods involving fast Independent Component Analysis (FastICA), Information Maximization (Infomax), and Second-order Blind Source Separation (SOBI). On top of these methods, a SOBI-WT method based on the joint use of the SOBI and Wavelet Transform (WT) is proposed. It offered an effective solution for suppressing artifact components while retaining residual informative data. To provide a comprehensive comparative analysis, these pre-processing methods were applied to eliminate the intra-artifacts and the processed signals were fed to two ready-to-use deep learning models, namely two-step hierarchical neural network (THNN) and SimpleSleepNet for automatic sleep staging. The evaluation was performed on two widely used public datasets, Montreal Archive of Sleep Studies (MASS) and Sleep-EDF Expanded, and a clinical dataset that was collected in Huashan Hospital of Fudan University, Shanghai, China (HSFU). The proposed SOBI-WT method increased the accuracy from 79.0% to 81.3% on MASS, 83.3% to 85.7% on Sleep-EDF Expanded, and 75.5% to 77.1% on HSFU compared with the raw EEG signal, respectively. Experimental results demonstrate that the intra-artifacts bring out a masking negative impact on the deep learning-based sleep staging systems and the proposed SOBI-WT method has the best performance in diminishing this negative impact compared with other artifact elimination methods. [ABSTRACT FROM AUTHOR]

To delineate the clinical characteristics of intestinal fistula patients with Bloodstream infection (BSI). Retrospective case series in Surgical Intensive Care Unit (SICU), Shanghai Ninth People's Hospital, Shanghai JiaoTong University School of Medicine, Shanghai, China. Among a cohort of 204 patients with a diagnosis of intestinal fistula, 46 who were complicated with BSI were analysed retrospectively. Data was collected from January 1, 2018 to February 1, 2020. Among the 204 patients with intestinal fistula, 46 patients showed positive blood cultures, which clearly had BSIs. Parenteral nutrition (PN) time (OR 1.08, 95% CI 1.04∼1.12, P < 0.01), transferred from external ICU (OR 3.68, 95% CI 1.48∼9.17, P = 0.01), septic shock (OR 4.61, 95% CI 1.77∼11.97, P < 0.01), APACHE II (OR 1.11, 95% CI 1.01∼1.22, P = 0.04) were significantly associated with BSI in patients with intestinal fistula. When APACHE II score exceeds 12.0 points or PN time exceeds 18.0 D, the chance of BSI in patients with intestinal fistula increases significantly. In addition, compared with the non-BSI group, BSI group had a higher mortality and expenses in ICU, longer stay in ICU and total hospital stay, and worse quality of life (all P < 0.05). A total of 105 isolates from samples (including sputum, pus and blood) of 46 patients in the BSI group, among which were mainly gram negative rods and fungi, as well as blood isolates. Importantly, in patients with intestinal fistula, BSIs caused by fungi accounted for 23.4%. Long-term PN, transfer from external ICU, septic shock, and higher APACHE II scores are often associated with an increased probability of BSIs in patients with intestinal fistula and a higher mortality. Gram-negative bacteria are the main pathogenic bacteria in intestinal fistula patients with BSI, and patients with intestinal fistula are more likely to develop fungal BSIs. [ABSTRACT FROM AUTHOR]

Background: With the increasing risk of infectious disease outbreaks around the world, the role of community health centres (CHCs) in the prevention and control of epidemics has become increasingly prominent. This study aimed to examine the capacities, vulnerabilities, and obstacles related to coping with infectious disease epidemics in Chinese CHCs. Methods: A cross-sectional study was conducted in Shanghai CHCs. Stratified random sampling was used to select 48 CHCs, and 2460 medical staff members responded to questionnaire surveys. ANOVA and multivariate analysis were used to evaluate the current situation and main obstacles regarding CHC medical staff members' perceptions of their capacity to cope with infectious disease epidemics. Results: The scores for regulation awareness (mean= 3.64, SD= 0.02) and detection/reporting ability (mean= 3.66, SD= 0.02) were lower than the score for the ability to handle an epidemic (mean= 3.79, SD= 0.02). After controlling for covariates, working in a traditional Chinese medicine (β= − 0.63, P= 0.002) or medical technology department (β= − 0.60, P= 0.002), not having participated in emergency exercises (β= − 0.78, P< 0.001), and not having participated in emergency training (β= − 0.59, P= 0.01) were associated with lower scores on all three domains. Those with senior professional titles reported relatively high levels of ability to handle an epidemic (β= 0.21, P= 0.01). Female workers reported relatively low regulation awareness (β= − 0.11, P= 0.02) and detection/reporting ability (β= − 0.11, P= 0.01). Conclusion: The three emergency response abilities of CHC medical workers differed based on the medical worker's sex, department, and title, indicating the need for targeted scientific emergency exercises and training for infectious disease outbreaks. Moreover, there is a need to improve the relevant policies and equipment. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study was to use the hospital information system to analyze the cancer profile and compare demographics, hospitalization, status of surgery and treatment cost of various cancer categories based on the electronic health record (EHR) of outpatient children with tumors in Shanghai, China. Patients and Methods: Information was collected from 3834 inpatients aged 0– 18 who were diagnosed with malignant tumors in all 17 hospitals with pediatric wards in the Pudong New District of Shanghai from 2011 to 2016. All patients were classified according to the International Classification of Childhood Cancer-3 (ICCC-3). The chi-squared test was used to compare demographics, hospitalization information, status of surgery and treatment cost according to inpatients' cancer category. Results: In both the malignant non-solid tumor and solid tumor groups, males and those aged 0– 4 years were the dominant groups. Lymphocytic leukemia was the most common cancer in all inpatients (n=994, 25.93%), and the acute myeloid leukemia had the longest length of stay of inpatients (median=26.00 days). In both the non-solid and solid tumor groups, patients who received only one type of surgery had an advantage. The highest proportion of patients who had undergone surgery was found in non-Hodgkin lymphoma patients. In terms of total cost, surgical cost and medicine cost, the expenditure of central nervous system tumor patients was the highest. Astrocytoma had the highest total cost. Conclusion: Leukemia is common in children with cancer in Pudong and should be given attention. Because the highest financial burden falls on patients with central nervous system tumors and acute myeloid leukemias, the government should take immediate and targeted measures for these cancers in particular. [ABSTRACT FROM AUTHOR]

Chinese ink animation has won worldwide respect for its ethereal and refined approach to ink painting. From the 1950s to 1980s, the Shanghai Animation Film Studio produced a number of award-winning ink animations. These animations share a unique traditional Chinese aesthetic based on Chinese literature and philosophy. However, the complex and long hand-made production process is one of the factors that caused the decline of Chinese ink animation following the 1980s. Since the millennium, three-dimensional ink modelling and digital painting technology have contributed to the revival of Chinese ink animation. This article summarizes the development of the production process of Chinese ink animation, together with its artistic features in both the analogue and digital age. Theoretically, this article focuses on a Chinese poetic framework, 'the Xiang system', as both a creative strategy for producing Chinese ink animation and an analytical lens to critique it. [ABSTRACT FROM AUTHOR]

Rheumatic heart disease (RHD) remains a serious public health burden in developing countries. We conducted a time-series study to explore the association between ambient temperature and daily hospital admissions for RHD in Shanghai, China. We collected data on daily hospital admissions for RHD from 2013 to 2015 from the database of Shanghai Health Insurance System. We applied the generalized additive models together with the distributed lag nonlinear model to estimate the association between temperature and RHD hospital admissions after controlling for relative humidity, time trend, day of the week, and holidays. Stratification analyses by age and gender were performed to evaluate their potential effect modification. A total of 4178 cases of RHD hospitalizations were identified over the study period. There were almost linear, positive, and significant associations between daily mean temperature and RHD hospital admissions with higher risks at hotter days. Compared to reference temperature (0 °C), the cumulative risks of moderate heat (the 90th percentile of temperature, 28.0 °C) and extreme heat (the 99th percentile of temperature, 33.5 °C) over lags 0-5 days were 2.55 (95% confidence interval 1.14, 5.73) and 3.22 (95% confidence interval 1.36, 7.61), respectively. These associations were significantly stronger in older people than in younger people. This study indicated larger risks of RHD hospital admissions associated with higher temperature, especially in older people. Our findings provided first-hand epidemiological evidence regarding the effects of ambient temperature on RHD incidence. [ABSTRACT FROM AUTHOR]

Background Epidemiologic studies of PM 2.5 (particulate matter with aerodynamic diameter ≤2.5 μm) and black carbon (BC) typically use ambient measurements as exposure proxies given that individual measurement is infeasible among large populations. Failure to account for variation in exposure will bias epidemiologic study results. The ability of ambient measurement as a proxy of exposure in regions with heavy pollution is untested. Objective We aimed to investigate effects of potential determinants and to estimate PM 2.5 and BC exposure by a modeling approach. Methods We collected 417 24 h personal PM 2.5 and 130 72 h personal BC measurements from a panel of 36 nonsmoking college students in Shanghai, China. Each participant underwent 4 rounds of three consecutive 24-h sampling sessions through December 2014 to July 2015. We applied backwards regression to construct mixed effect models incorporating all accessible variables of ambient pollution, climate and time-location information for exposure prediction. All models were evaluated by marginal R 2 and root mean square error (RMSE) from a leave-one-out-cross-validation (LOOCV) and a 10-fold cross-validation (10-fold CV). Results Personal PM 2.5 was 47.6% lower than ambient level, with mean (±Standard Deviation, SD) level of 39.9 (±32.1) μg/m 3 ; whereas personal BC (6.1 (±2.8) μg/m 3 ) was about one-fold higher than the corresponding ambient concentrations. Ambient levels were the most significant determinants of PM 2.5 and BC exposure. Meteorological and season indicators were also important predictors. Our final models predicted 75% of the variance in 24 h personal PM 2.5 and 72 h personal BC. LOOCV analysis showed an R 2 (RMSE) of 0.73 (0.40) for PM 2.5 and 0.66 (0.27) for BC. Ten-fold CV analysis showed a R 2 (RMSE) of 0.73 (0.41) for PM 2.5 and 0.68 (0.26) for BC. Conclusion We used readily accessible data and established intuitive models that can predict PM 2.5 and BC exposure. This modeling approach can be a feasible solution for PM exposure estimation in epidemiological studies. [ABSTRACT FROM AUTHOR]

This research examined the applicability of a widely used instrument-Parenting Style Index (PSI), which was developed in the Western context, to Chinese secondary school students. Seven hundred and seventy-five students in Nanjing and 176 students in Shanghai participated in this research. Confirmatory factor analysis and cross-validation procedure showed that the three-factor model, representing the three dimensions (acceptance/involvement, strictness/supervision, and psychological autonomy granting) of the PSI fit the data according to multiple model fit indices. The internal consistencies of the three dimensions of the PSI ranged from 0.75 to 0.78 for the Nanjing sample and from 0.67 to 0.72 for the Shanghai sample. Taken together, the revised Chinese version of the PSI had acceptable reliability and validity, indicating that the PSI can be used to measure Chinese adolescents' perceived parenting styles. Further empirical studies among diverse Chinese adolescents are needed to improve the psychometric properties of the PSI. [ABSTRACT FROM AUTHOR]

Non-invasive bio-samples, such as saliva and urine, are promising tools for assessment of inflammation and oxidative stress biomarkers. Few studies have investigated potential responses of those biomarkers towards short-term PM 2.5 exposure. We conducted a longitudinal study with 4 repeated examinations among 40 healthy, nonsmoking adults in Shanghai, China. Personal samplings were performed for PM 2.5 exposure assessment. Then, five biomarkers, including C-reactive protein (CRP), tumor necrosis factor-α (TNF-α), alpha-1 antitrypsin (A1AT) in saliva and 8-Iso-Prostaglanding F 2α (8-iso-PGF 2α), total antioxidant capacity (TAC) in urine, were measured. We fitted linear mixed-effect models to evaluate short-term effect of personal PM 2.5 exposure on salivary and urinary biomarkers, adjusting for potential confounders of meteorology, sociodemographic characteristics and biomarker detection. We also explored sensitive time windows of exposure for different biomarkers. We found robust associations of salivary CRP, TNF-α, and urinary 8-iso-PGF 2α with PM 2.5 exposure, and responses of salivary inflammatory markers occurred more acutely than urinary oxidative stress markers. For instance, a 10 μg/m3 increase in PM 2.5 was associated with an elevation of 5.49% (95% CI: 1.17%, 9.99%) in CRP and 7.05% (95% CI: 1.29%, 13.13%) in TNF-α both at lag 12 h, and 6.97% (95% CI: 1.33%, 12.92%) in 8-iso-PGF 2α at lag 01 d. Based on non-invasive samples, this study provided evidence on effect of PM 2.5 exposure on responses of systematic inflammation and oxidative stress. Sub-daily (6–12 h) and daily (≥24 h) period after PM 2.5 exposure might be sensitive time window to detect the responses of salivary (i.e. CRP, TNF) and urinary biomarkers (i.e. 8-iso-PGF 2α), respectively. • PM 2.5 was associated with elevated inflammatory saliva markers (CRP&TNF-α). • Sub-daily period (6–12 h) is critical window to detect salivary CRP&TNF-α response. • PM 2.5 was associated with elevated urine oxidative stress marker (8-iso-PGF 2α). • Daily period (≥24 h) is critical window to detect urinary 8-iso-PGF 2α response. [ABSTRACT FROM AUTHOR]

Fresh-cut 'Fuji' apples were immersed for 5 min in plasma-activated water (PAW) generated, by plasma generated with sinusoidal voltages at 7.0 kHz with amplitudes of 6 kV, 8 kV, and 10 kV, designated PAW-6, PAW-8, and PAW-10, respectively. The control group was soaked in distilled water for 5 min instead of PAW. The results indicated that the growth of bacteria, molds, and yeasts was inhibited by PAW treatments during storage at 4 ± 1 °C, especially the microbial inactivation with PAW-8, which was the most efficient. PAW-8 reduced the microbial counts by 1.05 log 10 CFU g−1, 0.64 log 10 CFU g−1, 1.04 log 10 CFU g−1 and 0.86 log 10 CFU g−1 for aerobic bacteria (aerobic plate counts), molds, yeasts and coliforms on day 12, respectively. In addition, the bacterial counts of fresh-cut apples treated with PAW were <5 log 10 CFU g−1, which did not exceed to the existing China Shanghai local standard (DB 31/2012–2013) during 12 days of storage. PAW treatments reduced superficial browning of fresh-cut apples without affecting their firmness and titratable acidity. In addition, no significant change was observed in antioxidant content and radical scavenging activity between the PAW-treated and control groups. It is suggested that PAW is a promising method for preservation of fresh-cut fruits and vegetables, which is usually beneficial to the quality maintenance of fresh-cut fruits and vegetables during storage. • PAW treatment inhibited the growth of bacteria, molds and yeasts in fresh-cut apple. • PAW generated at 8 kV reduced the aerobic bacteria count by 1.05 log10CFU g−1 on day 12 of refrigerated storage. • PAW treatment has a beneficial effect on reducing the browning of fresh-cut apple. • PAW is a promising method for preservation of fresh-cut fruits and vegetables. [ABSTRACT FROM AUTHOR]

Combined atmospheric oxidant capacity (O x), represented by the sum of nitrogen dioxide (NO 2) and ozone (O 3), is an important hazardous property of outdoor air pollution mixture. It remains unknown whether its adverse effects can be ameliorated by dietary fish-oil supplementation. To assess the effects of fish-oil supplementation against oxidative stress induced by acute O x exposure. We conducted a randomized, double-blinded and placebo-controlled study among 65 young adults in Shanghai, China between September 2017 and January 2018. We randomly assigned participants to receive either 2.5 g/day of fish oil or placebo, and conducted four repeated physical examinations during the last two months of treatments. O x concentrations were calculated as the sum of hourly measurements of NO 2 and O 3. We measured six biomarkers on systemic oxidative stress and antioxidant activity. Linear mixed-effect models were used to assess the short-term effects of O x on biomarkers in each group. During our study period, the 72-h average O x concentration was 93.6 μg/m3. Short-term exposure to O x led to weaker changes in all biomarkers in the fish oil group than in the placebo group. Compared with the placebo group, for a 10-μg/m3 increase in O x , there were smaller decrements in myeloperoxidase (MPO, difference = 5.92%, lag = 0–2 d, p = 0.03) and malondialdehyde (MDA, difference = 5.00%, lag = 1 d, p = 0.04) in the fish-oil group; there were also larger increments in total antioxidant capacity (TAC, difference = 16.33%, lag = 2 d, p = 0.02) and in glutathione peroxidase (GSH-Px, difference = 8.89%, lag = 0–2 d, p = 0.03) in the fish-oil group. The estimated differences for MPO were robust to adjustment for all co-pollutants and the differences for other biomarkers remained for some co-pollutants. This trial provides first-hand evidence that dietary fish-oil supplementation may alleviate the systemic oxidative stress induced by O x. • Combined atmospheric oxidant capacity (O x) exposure induced oxidative stress. • We provided the first-hand evidence on the effects of fish-oil against O x exposure. • Fish-oil supplementation could mitigate systemic oxidative stress response to O x. [ABSTRACT FROM AUTHOR]

Metabolomics is a novel tool to explore the biological mechanisms of the health effects of fine particulate matter (PM 2.5) air pollution. Very few studies have examined the urinary metabolomic changes associated with PM 2.5 exposure. To assess the alternation in urine metabolomics in response to short-term PM 2.5 exposure. We conducted a randomized, double-blind, crossover trial of 9-day real or sham indoor air purification among 45 healthy college students in Shanghai, China. Urine samples were collected immediately at the end of each intervention stage and were analyzed for metabolomics using ultrahigh performance liquid chromatography-mass spectrometry. Orthogonal partial least square-discriminant analysis and linear mixed effect models were used to examine metabolomic changes between interventional scenarios and their associations with continuous PM 2.5 exposure. The time-weighted average personal PM 2.5 exposure in the real-purified scenario was 50% lower than in the sham-purified air scenario (28.3 μg/m3 VS 56.9 μg/m3). A total of 40 differentiated urinary metabolites at a false discovery rate <0.05 were identified for the effects of both intervention and continuous PM 2.5 exposure, including 16 lipids, 5 purine metabolites, 2 neurotransmitters, and 3 coenzymes. This real-world randomized crossover trial demonstrated that short-term PM 2.5 exposure could result in significant changes in urinary metabolomic profile, which may further lead to perturbation in energy metabolism, oxidative stress and inflammation. • Limited evidence on exploration of PM 2.5 effects with urine metabolomics approach • We designed a randomized, double-blind, crossover trial of air purifiers. • We identified 16 lipids, 5 purines, 2 neurotransmitters, and 3 coenzymes. • PM 2.5 results in energy metabolism perturbation, oxidative stress and inflammation. [ABSTRACT FROM AUTHOR]

Background: The emergence and wide global spread of carbapenem-resistant Klebsiella pneumoniae (CRKP) isolates are of great concern, and the aim of this study was to investigate drug resistance, molecular epidemiology, and genetic relationship of CRKP isolates from patients in Shanghai, China. Methods: A retrospective study was conducted from April 2018 to July 2019, and a total of 133 CRKP isolates were collected. Antimicrobial susceptibility was determined by VITEK-2 automated microbiology analyzer platform (bioMérieux, France) and the broth microdilution method. Polymerase chain reaction assays were used to investigate the presence of drug resistance genes. A modified carbapenem inactivation method was performed to detect carbapenemases. Multilocus sequence typing and pulsed-field gel electrophoresis (PFGE) were conducted for genetic relatedness of 50 CRKP isolates selected. Results: Among 670 isolates of K. pneumoniae, 133 (19.9%) strains were identified as CRKP, of which, 76.7% (102/133) strains were isolated from intensive care units (ICUs). All the 133 CRKP isolates were found to be carbapenemase-producers and harbor blaKPC-2 gene. No other carbapenemase genes of blaNDM, blaOXA-48, blaVIM, and blaIMP were detected. Furthermore, β-lactamase genes of blaSHV, blaCTX, and blaTEM were the most common resistance-associated genes among these KPC-2 producing isolates. All the 133 CRKP strains displayed >95% of resistance to cephalosporins and carbapenems, except for gentamicin, trimethoprim-sulfamethoxazole, amikacin, tigecycline and colistin, and ceftazidime-avibactam. The most common sequence type was ST11, accounting for 90.0% of the 50 CRKP selected, followed by ST15 (10.0%). PFGE analysis clustered the 50 KPC-2-producing isolates into seven (A–G) distinct clonal clusters at 85% cutoff. Of which, A and G were the two major clusters, accounting for the majority of the strains collected in emergency ICU and neurosurgical ICU. And all the strains of clusters D and E were collected in cardiothoracic surgery ICU, except for one strain collected in one outpatient. Conclusion: The KPC-2-producing K. pneumoniae belonged to ST11 was widely disseminated in ICUs, and active and effective surveillance of infection control strategies was initiated to limit the spread of CRKP strains. [ABSTRACT FROM AUTHOR]

Epidemiological studies have shown that fine particulate matter (PM 2.5) has adverse impacts on human health. However, limited studies have investigated the effects of short-term exposure to PM 2.5 and its constituents on mortality in China. This study used the generalized linear model (GLM) to investigate the effects of PM 2.5 and its constituents, including organic carbon (OC), element carbon (EC), ammonium (NH 4 +), nitrate (NO 3 −), sulfate (SO 4 2−), on different causes of mortality in Shanghai from January 1, 2013 to December 31, 2015. The single-day lagged model and the moving average lagged model were used to examine the lagging effects of pollutants on mortality. At lag0 day, PM 2.5 had a significant effect on all-cause mortality, and a 10 μg/m3 increase leads to 0.68% increase in all-cause mortality (RR 1.0068, 95%CI 1.0013–1.0123). Among the five constituents, EC had the greatest impact on all-cause mortality in Shanghai, with 10.48% increase of mortality (RR 1.1048, 95%CI 1.0266–1.1891) per 10 μg/m3 increase of concentrations, followed by OC (RR 1.0577, 95%CI 1.0277–1.0886), NH 4 + (RR 1.0272, 95%CI 1.0028–1.0522) and SO 4 2− (RR 1.0104, 95%CI 1.0003–1.0206). For respiratory diseases mortality, EC, OC, NO 3 − and NH 4 + had significant impacts and caused an increase of mortality by 44.99% (RR 1.4499, 95%CI 1.1813–1.7794), 10.40% (RR 1.1040, 95%CI 1.0260–1.1880), 5.338% (RR 1.0533, 95%CI 1.0097–1.0989) and 7.34% (RR 1.0734, 95%CI 1.0015–1.1505) per 10 μg/m3 increase of concentrations, respectively. The cumulative effect of PM 2.5 on mortality was significant in Shanghai. Except for SO 4 2−, the RR value of the single-day lagged model was smaller than the moving average lagged model. • PM2.5 was associated with all-cause mortality and respiratory disease mortality in Shanghai. • EC had the highest relative risk for all-cause mortality among the constituents. • The risk of PM2.5 constituents on respiratory mortality was higher than that of circulatory mortality. • The relative risk value of the single-day lagged model was smaller than the moving average lagged model. [ABSTRACT FROM AUTHOR]

Background: Few studies have evaluated the health benefits of omega-3 fatty acid supplementation against fine particulate matter (aerodynamic diameter <2.5 μm [PM2.5]) exposure in highly polluted areas.Objectives: The authors sought to evaluate whether dietary fish-oil supplementation protects cardiovascular health against PM2.5 exposure in China.Methods: This is a randomized, double-blinded, and placebo-controlled trial among 65 healthy college students in Shanghai, China. Participants were randomly assigned to either the placebo group or the intervention group with dietary fish-oil supplementation of 2.5 g/day from September 2017 to January 2018, and received 4 rounds of health examinations in the last 2 months of treatments. Fixed-site PM2.5 concentrations on campus were measured in real time. The authors measured blood pressure and 18 biomarkers of systematic inflammation, coagulation, endothelial function, oxidative stress, antioxidant activity, cardiometabolism, and neuroendocrine stress response. Acute effects of PM2.5 on these outcomes were evaluated within each group using linear mixed-effect models.Results: The average PM2.5 level was 38 μg/m3 during the study period. Compared with the placebo group, the fish-oil group showed relatively stable levels of most biomarkers in response to changes in PM2.5 exposure. Between-group differences associated with PM2.5 exposure varied by biomarkers and by lags of exposure. The authors observed beneficial effects of fish-oil supplementation on 5 biomarkers of blood inflammation, coagulation, endothelial function, oxidative stress, and neuroendocrine stress response in the fish-oil group at a false discovery rate of <0.05.Conclusions: This trial shows that omega-3 fatty acid supplementation is associated with short-term subclinical cardiovascular benefits against PM2.5 exposure among healthy young adults in China. (Effect of Dietary Supplemental Fish Oil in Alleviating Health Hazards Associated With Air Pollution; NCT03255187). [ABSTRACT FROM AUTHOR]

It remains unclear whether carbon content in airway macrophages (AM) can predict personal short-term exposure to fine particulate matter (PM 2.5) air pollution and its respiratory health effects. We aimed to evaluate the pathway from personal PM 2.5 exposure to adverse respiratory outcomes through AM carbon content. We designed a longitudinal panel study with 3 scheduled follow-ups among 113 non-smoking patients of chronic obstructive pulmonary disease in Shanghai, China, from April 2017 to January 2019. We quantified AM carbon content from induced sputum by image analysis, tested lung function and measured sputum levels of 4 pro-inflammatory cytokines and 2 anti-inflammatory cytokines. We applied the "meet in the middle" approach incorporating linear mixed-effect models to evaluate the associations from external PM 2.5 exposure to respiratory outcomes through AM carbon content. Our results indicated that personal exposure to PM 2.5 within 24 h was significantly associated with decreased forced expiratory volume in 1s and anti-inflammatory cytokines, as well as increased macrophages and pro-inflammatory cytokines. These changes were accompanied by increased areas of AM carbon and higher percentage of AM area occupied by carbon, both of which were associated with increased levels of pro-inflammatory cytokines and decreased levels of anti-inflammatory cytokines. Exposure to ambient black carbon and organic carbon in PM 2.5 within 2 days was significantly associated with increased AM carbon area and percentage of AM area occupied by carbon. Our findings reinforced the causality in respiratory health effects of PM 2.5 in which increased AM carbon content might serve as a valid exposure biomarker. • Acute PM 2.5 exposure increases AM carbon content and leads to respiratory effects. • The percentage of carbon area in AM may be a better exposure biomarker of PM 2.5. • This study reinforces the causality for the acute respiratory effects of PM 2.5. [ABSTRACT FROM AUTHOR]