Search

Aim: This study aims to explore the duration and influencing factors of care-seeking delay among patients with heart failure (HF) in China., Methods and Results: A convergent mixed method containing a cross-sectional study and two parts of qualitative studies was designed, following the STROBE and COREQ guidelines. Convenience sampling was applied to recruit patients with HF from two general hospitals from December 2021 to December 2022. Purposive sampling was used to enrol healthcare professionals from two general hospitals and two community hospitals from June to November 2022. Among the 258 patients with HF in the cross-sectional study, the median duration of care-seeking delay was 7.5 days. The result integration indicated that the delay duration was influenced by the dyspnoea symptom burden, the oedema symptom burden, and the depression status. The lower dyspnoea symptom burden, the higher oedema symptom burden, and the higher depression score were related to the prolonged care-seeking delay duration. The duration was also affected by the COVID-19 pandemic, level of support from medical system, and the symptom management abilities of the caregivers. The COVID-19 pandemic, low level of support from medical system, and limited symptom management abilities of caregivers were related to the prolonged care-seeking delay duration., Conclusions: Care-seeking delay among patients with HF needs attention in China. The duration of care-seeking delay of patients with HF was influenced by the dyspnoea symptom burden, the oedema symptom burden, and depression status, as well as the COVID-19 pandemic, level of support from medical system, and the symptom management abilities of the caregivers., (© 2024 The Authors. ESC Heart Failure published by John Wiley & Sons Ltd on behalf of European Society of Cardiology.)

Antimicrobial resistance (AMR) undermines the United Nations Sustainable Development Goals of good health and well-being. Antibiotics are known to exacerbate AMR, but nonantibiotic antimicrobials, such as quaternary ammonium compounds (QACs), are now emerging as another significant driver of AMR. However, assessing the AMR risks of QACs in complex environmental matrices remains challenging due to the ambiguity in their chemical structures and antibacterial activity. By machine learning prediction and high-resolution mass spectrometric analysis, a list of antibacterial QACs ( n = 856) from industrial chemical inventories is compiled, and it leads to the identification of 50 structurally diverse antibacterial QACs in sediments, including traditional hydrocarbon-based compounds and new subclasses that bear additional functional groups, such as choline, ester, betaine, aryl ether, and pyridine. Urban wastewater, aquaculture, and hospital discharges are the main factors influencing QAC distribution patterns in estuarine sediments. Toxic unit calculations and metagenomic analysis revealed that these QACs can influence antibiotic resistance genes (particularly sulfonamide resistance genes) through cross- and coresistances. The potential to influence the AMR is related to their environmental persistence. These results suggest that controlling the source, preventing the co-use of QACs and sulfonamides, and prioritizing control of highly persistent molecules will lead to global stewardship and sustainable use of QACs.

Identifying persistent, mobile, and toxic (PMT) substances from synthetic chemicals is critical for chemical management and ecological risk assessment. Inspired by the triazine analogues (e.g., atrazine and melamine) in the original European Union's list of PMT substances, the occurrence and compositions of alkylamine triazines (AATs) in the estuarine sediments of main rivers along the eastern coast of China were comprehensively explored by an integrated strategy of target, suspect, and nontarget screening analysis. A total of 44 AATs were identified, of which 23 were confirmed by comparison with authentic standards. Among the remaining tentatively identified analogues, 18 were emerging pollutants not previously reported in the environment. Tri- and di-AATs were the dominant analogues, and varied geographic distributions of AATs were apparent in the investigated regions. Toxic unit calculations indicated that there were acute and chronic risks to algae from AATs on a large geographical scale, with the antifouling biocide cybutryne as a key driver. The assessment of physicochemical properties further revealed that more than half of the AATs could be categorized as potential PMT and very persistent and very mobile substances at the screening level. These results highlight that AATs are a class of PMT substances posing high ecological impacts on the aquatic environment and therefore require more attention.

The limited information in existing mass spectral libraries hinders an accurate understanding of the composition, behavior, and toxicity of organic pollutants. In this study, a total of 350 polycyclic aromatic compounds (PACs) in 9 categories were successfully identified in fine particulate matter by gas chromatography high resolution mass spectrometry. Using mass spectra and retention indexes predicted by in silico tools as complementary information, the scope of chemical identification was efficiently expanded by 27%. In addition, quantitative structure-activity relationship models provided toxicity data for over 70% of PACs, facilitating a comprehensive health risk assessment. On the basis of extensive identification, the cumulative noncarcinogenic risk of PACs warranted attention. Meanwhile, the carcinogenic risk of 53 individual analogues was noteworthy. These findings suggest that there is a pressing need for an updated list of priority PACs for routine monitoring and toxicological research since legacy polycyclic aromatic hydrocarbons (PAHs) contributed modestly to the overall abundance (18%) and carcinogenic risk (8%). A toxicological priority index approach was applied for relative chemical ranking considering the environmental occurrence, fate, toxicity, and analytical availability. A list of 39 priority analogues was compiled, which predominantly consisted of high-molecular-weight PAHs and alkyl derivatives. These priority PACs further enhanced source interpretation, and the highest carcinogenic risk was attributed to coal combustion.

Background: Family caregivers play crucial roles in the self-management of patients with heart failure (HF). However, little is known about caregiving experiences of Chinese family caregivers during acute HF., Objective: The aim of this study was to describe Chinese family caregivers' experiences in symptom management and care-seeking during acute HF., Methods: This is an exploratory, qualitative study using the Consolidated Criteria for Reporting Qualitative Research guidelines. Data were collected through semistructured interviews and analyzed with thematic analysis., Findings: A total of 21 family caregivers of patients with acute HF were enrolled in this study. "Empowered but isolated" was identified as the overarching theme during data analysis, including 3 themes and 6 subthemes: (1) "Responsible symptom managers: leading the home-based symptom management," including 2 subthemes, "Proxy in symptom management" and "Only knowing the surface, instead of the truth"; (2) "Powerless anchors: care-seeking is a torturous journey," including 2 subthemes, "Facing discrepancies in care-seeking" and "Seeing a doctor is the last choice"; (3) "Carrying the weight forward: responsibility combing with emotional burnout," including 2 subthemes, "Living on tenterhooks" and "Submitting to fate.", Conclusions: In this study, we described Chinese family caregivers' experiences in symptom management and care-seeking during acute HF. Although empowered as proxy, they were also isolated bearing a great burden, receiving insufficient support from patients, family, and the medical system., Competing Interests: The authors have no funding or conflicts of interest to disclose., (Copyright © 2023 Wolters Kluwer Health, Inc. All rights reserved.)

Objective: During the Omicron wave of the COVID-19 pandemic in Shanghai, Fangcang Shelter Hospital (FSH) served as the major way in patient quarantine. Many COVID patients served as volunteers in FSH providing a lot of assistance for the medical workers and other COVID patients. The aim of this study was to explore the experiences of patient volunteers in FSH. It helps health professionals better understand their motivational incentives and barriers in their volunteer work, and improves recruiting and managing volunteers in subsequent public health emergencies., Methods: This is a qualitative study using semi-structured interviews. Thirteen patient volunteers working in an FSH in Shanghai were included. Thematic analysis was applied to data analysis., Results: Four themes and nine subthemes were identified. The wishes to give back to society and the responsibility of politics and religion were the main reasons for the patients to serve as volunteers in FSH. The patient volunteers served as the bridge to reduce the communication barriers between other patients and healthcare professionals. They also provided support in supply distribution and psychological counseling. They viewed voluntary work as a usual task and tried to solve the barriers in their work. In turn, the voluntary work brought them benefits in mental and physical health, as well as another chance for growth., Conclusion: Working as volunteers in FSHs not only brought personal benefits to the COVID patients but also fulfilled the needs of the healthcare system during public health emergencies. The mode of mutual help between patients could be taken as an example in other public health emergencies., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Zhu, Xu, Ruan, Huang and Cen.)

Benzotriazole ultraviolet stabilizers (BZT-UVs), substituted diphenylamine antioxidants (S-DPAs), and synthetic phenolic antioxidants (SPAs) are three types of synthetic additive pollutants that are received increasing attention in the recent decade. In this study, a total of twenty-seven target analytes were measured in sediment cores and surface sediments collected from a lake with long sedimentary history. All target analytes were detected in the sediment samples, and mean values of the total ∑BZT-UVs, ∑S-DPAs and ∑SPAs concentrations were 220 ± 552 ng/g dry weight (d.w.), 20.8 ± 27.9 ng/g d. w., and 95.8 ± 146 ng/g d. w., respectively. Based on the dating results of two sediment cores, the total concentrations of BZT-UVs, S-DPA, and SPAs showed a fluctuating but overall increasing trend over time, which intuitively reflects the change of historical emissions. Meanwhile, fecal and sewage markers (i.e., sterols and pharmaceuticals, respectively) were jointly used to trace the probable sources of these pollutants. Results from the correlation and clustering analyses suggest that unregular fecal discharges and point-source domestic sewage need to be considered if pollution in the investigated area is to be controlled. To our knowledge, this study is the initial attempt to reveal the temporal variations of these synthetic additive pollutants in an aquatic environment in China and to demonstrate the feasibility of using markers to trace the sources of emerging pollutant analogues., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

In recent years, relation extraction on unstructured texts has become an important task in medical research. However, relation extraction requires a large amount of labeled corpus, manually annotating sequences is time consuming and expensive. Therefore, efficient and economical methods for annotating sequences are required to ensure the performance of relational extraction. This paper proposes a method of subsequence and distant supervision based active learning. The method is annotated by selecting information-rich subsequences as a sampling unit instead of the full sentences in traditional active learning. Additionally, the method saves the labeled subsequence texts and their corresponding labels in a dictionary which is continuously updated and maintained, and pre-labels the unlabeled set through text matching based on the idea of distant supervision. Finally, the method combines a Chinese-RoBERTa-CRF model for relation extraction in Chinese medical texts. Experimental results test on the CMeIE dataset achieves the best performance compared to existing methods. And the best F1 value obtained between different sampling strategies is 55.96%., (© 2023. The Author(s).)

Benzotriazole UV stabilizers (BZT-UVs), including 2-(3,5-di- tert -amyl-2-hydroxyphenyl)benzotriazole (UV-328) that is currently under consideration for listing under the Stockholm Convention, are applied in many commodities and industrial products. However, limited information is available on the interannual variation of their environmental occurrence. In this study, an all-in-one strategy combining target, suspect, and nontarget screening analysis was established to comprehensively explore the temporal trends of BZT-UVs in mollusks collected from the Chinese Bohai Sea between 2010 and 2018. Significant residue levels of the target analytes were determined with a maximum total concentration of 6.4 × 10 3 ng/g dry weight. 2-(2-Hydroxy-3- tert -butyl-5-methyl-phenyl)-5-chloro-benzotriazole (UV-326), 5-chloro-2-(3,5-di- tert -butyl-2-hydroxyphenyl)benzotriazole (UV-327), and 2-(2-hydroxy-5-methylphenyl) benzotriazole (UV-P) were the predominant analogues, and UV-328 was the most frequently detected BZT-UV with a detection frequency (DF) of 87%. Whereas five biotransformation products and six impurity-like BZT-UVs were tentatively identified, their low DFs and semi-quantified concentrations suggest that the targeted analytes were the predominant BZT-UVs in the investigated area. A gradual decrease in the total concentrations of BZT-UVs was observed, accompanied by downward trends of the abundant compounds (e.g., UV-326 and UV-P). Consequently, the relative abundance of UV-327 increased because of its consistent environmental presence. These results suggest that continuous monitoring and risk assessment of BZT-UVs other than UV-328 are of importance in China.

Chemical mixtures in surface waters could have significant impacts on exposure risks to human beings and pollution stress to aquatic system. By suspect screening analysis of high-resolution mass spectrometry data, occurrence, and compositions of ToxCast chemicals were investigated in grab estuarine water samples from a combination of 20 rivers that represents approximately 70% of the total river flow discharge along the east coast of China. In total, 59 ToxCast chemicals in seven use categories were identified, in which pesticides, intermediates, and pharmaceuticals were the abundant analogues. Significant differences in pollutant composition profiles were noticed, which possibly reflected singular release pattern and geographical-relevant usage preference (especially for herbicides and fungicides in the pesticide category). With the aid of tentative quantitative/semiquantitative measurement, essential contributors to the cumulative pollutant mass discharges and aquatic acute toxicity potentials were focused onto few particular chemicals. Existence of transformation products was further explored, which indicated that the fates of the selected parent ToxCast chemicals could be influenced by dominating transformation reactions (e.g., N -dealkylation and hydroxylation) and possible environmental factors (i.e., microbial activity). The results emphasize the necessity of suspect screening analysis for assessing the influence of terrestrial emissions of pollutants to the surrounding environment.

Three full-length monopartite begomovirus sequences were obtained from two field-collected pepper plants exhibiting severe leaf yellowing disease symptoms in Yunnan province of China. The three full-length viral sequences contain 2,748 nucleotides (nt) and share the highest nt sequence similarity (88.2% identity) with that of malvastrum yellow vein Yunnan virus (MYVYNV). The betasatellite molecules of the two viruses share the highest sequence similarity (99.3% identity) with that of malvastrum yellow vein Yunnan betasatellite (MYVYNB). Based on the current species demarcation criteria for the genus Begomovirus, these three newly identified isolates can be considered members of a novel monopartite Begomovirus species, and we have named this virus "pepper yellow leaf curl virus" (PepYLCV). Phylogenetic analysis showed that PepYLCV clustered with pepper leaf curl Yunnan virus (PepLCYNV). Recombination analysis revealed that PepYLCV is likely to have originated through a recombination event between MYVYNV and tomato leaf curl Yunnan virus (TLCYnV).

Background: To investigate the value of metagenomic next-generation sequencing (mNGS) in the diagnosis of focal pulmonary infections by using radial ultrasound bronchoscopic "cocktail" specimens., Methods: From March 2019 to May 2020, 90 patients with focal pulmonary infections [locatable by a radial probe endobronchial ultrasound (RP-EBUS)] treated by the Department of Respiratory and Critical Care Medicine at the Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital (Suzhou, China) were randomly allocated to the "cocktail" group, transbronchial brushing (TBBr) group or bronchoalveolar lavage fluid (BALF) group; 30 patients were assigned to each group. Using the extracted material, the diagnostic efficacy of the mNGS test for pathogen detection was compared across the three groups, and the effect of an antibiotic treatment on detection rate was assessed., Results: The sensitivity of mNGS analysis in cocktail group, TBBr group and BALF group was 90% (27/30), 66.7 (20/30) and 50% (15/30), respectively. The analysis of the sensitivity of the positive test, the detection rate of multiple pathogens, and the effect of antibiotics on the detection rate by mMGS indicated that the "cocktail" group was significantly higher number of samples positive for pathogens than the TBBr group (P<0.05), and the TBBr group was significantly higher number of samples positive for pathogens than the BALF group (P<0.05)., Conclusions: "Cocktail" specimens had high sensitivity in the identification of focal pathogens, and the use of antibiotics had little effect on the results of the mNGS analysis. These clinically valuable results can be used in the diagnosis and treatment of patients with focal pulmonary infections.

We used statistical approach by coupling redundancy analysis with linear regression analysis, which is useful to understand potential sources of antibiotics in the tide rising and ebbing of surface water in the Yongjiang Estuary, China. This study aimed to investigate the relationship between 29 antibiotics at five sites over four seasons and 13 environmental parameters during the tide rising and ebbing durations. The results found that dissolved organic carbon (DOC), salinity, temperature and chlorophyll a (Chla) were the main factors to impact antibiotics. The concentrations of macrolides were increasing with DOC, suggesting DOC may influence the adsorption capacity of antibiotics. The concentrations of tetracyclines had significant correlation with temperature and Chla during the tide rising period. This study demonstrated a method of exploring the relationship between the concentrations of antibiotics and environmental parameters, which is beneficial to future antibiotics research in estuaries., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Background: Laboratory indicator test results in electronic health records have been applied to many clinical big data analysis. However, it is quite common that the same laboratory examination item (i.e., lab indicator) is presented using different names in Chinese due to the translation problem and the habit problem of various hospitals, which results in distortion of analysis results., Methods: A framework with a recall model and a binary classification model is proposed, which could reduce the alignment scale and improve the accuracy of lab indicator normalization. To reduce alignment scale, tf-idf is used for candidate selection. To assure the accuracy of output, we utilize enhanced sequential inference model for binary classification. And active learning is applied with a selection strategy which is proposed for reducing annotation cost., Results: Since our indicator standardization method mainly focuses on Chinese indicator inconsistency, we perform our experiment on Shanghai Hospital Development Center and select clinical data from 8 hospitals. The method achieves a F1-score 92.08[Formula: see text] in our final binary classification. As for active learning, the new strategy proposed performs better than random baseline and could outperform the result trained on full data with only 43[Formula: see text] training data. A case study on heart failure clinic analysis conducted on the sub-dataset collected from SHDC shows that our proposed method is practical in the application with good performance., Conclusion: This work demonstrates that the structure we proposed can be effectively applied to lab indicator normalization. And active learning is also suitable for this task for cost reduction. Such a method is also valuable in data cleaning, data mining, text extracting and entity alignment.

Objectives: This study explored the relationship between skipping breakfast and physical fitness in a group of school-aged adolescents in China., Methods: This cross-sectional study from the Chinese National Surveillance on Students' Constitution and Health (CNSSCH) survey in Ningbo, China, used a standardized questionnaire to assess the frequency of breakfast consumption. Physical fitness was measured through standing long jump, 50-m sprint, 1,000 (or 800)-m run, and vital capacity tests. Multiple linear regression analysis was used to investigate the relationship between the frequency of breakfast consumption and physical fitness., Results: Our study included a total of 1,849 school-aged adolescents (aged 15.53±1.80 years). Among boys, non-breakfast-skippers had good scores for 50-m sprints, 1,000-m run, and vital capacity tests when compared with breakfast skippers (all p<0.05). Among girls, non-breakfast-skippers had a good scores for the standing long jump test compared with breakfast skippers (p=0.003). The multiple linear regression model showed that not skipping breakfast was positively associated with vital capacity (β=-173.78, p=0.004) and inversely associated with 50-m sprint (β=-0.12, p=0.018) and 1,000-m run times (β=-8.08, p=0.001) in boys., Conclusion: The results of this cross-sectional study revealed that skipping breakfast might be associated with lower physical fitness in Chinese adolescents aged 13-18 years, especially boys. Breakfast consumption should be promoted among Chinese school-aged boys.

Background: Electronic health records (EHRs) provide possibilities to improve patient care and facilitate clinical research. However, there are many challenges faced by the applications of EHRs, such as temporality, high dimensionality, sparseness, noise, random error and systematic bias. In particular, temporal information is difficult to effectively use by traditional machine learning methods while the sequential information of EHRs is very useful., Method: In this paper, we propose a general-purpose patient representation learning approach to summarize sequential EHRs. Specifically, a recurrent neural network based denoising autoencoder (RNN-DAE) is employed to encode inhospital records of each patient into a low dimensional dense vector., Results: Based on EHR data collected from Shuguang Hospital affiliated to Shanghai University of Traditional Chinese Medicine, we experimentally evaluate our proposed RNN-DAE method on both mortality prediction task and comorbidity prediction task. Extensive experimental results show that our proposed RNN-DAE method outperforms existing methods. In addition, we apply the "Deep Feature" represented by our proposed RNN-DAE method to track similar patients with t-SNE, which also achieves some interesting observations., Conclusion: We propose an effective unsupervised RNN-DAE method to summarize patient sequential information in EHR data. Our proposed RNN-DAE method is useful on both mortality prediction task and comorbidity prediction task.

Background: Health literacy is defined as the cognitive and social skills that determine the motivation and ability of individuals to gain access to, understand and use information in ways that promote and maintain good health. A Health Literacy Questionnaire (HLQ) is a toolkit with good reliability and validity. Accordingly, this study administered HLQ among older adults in China to examine its factor structure, reliability, homogeneity, and discriminant validity for use in understanding better the health literacy of older adults and determining corresponding measures., Methods: Psychometric properties were examined based on the data collected via face-to-face interviews (N = 343). Tests included the difficulty level, composite scale reliability, confirmatory factor analysis (CFA), and Bayesian structural equation modeling (BSEM)., Results: The easiest scale to obtain a high score was "Social support for health" and the hardest, "Navigating the health care system" and "Appraisal of health information." Two one-factor models fitted well with no correlated residuals allowed. After model modification, the CFA fit statistics of the other seven scales were good. All HLQ scales were found to be homogenous, with a composite reliability ranging from 0.74 to 0.85. The nine-factor Bayesian structural equation model fitted the data well (Posterior-Predictive-P value = 0.670; 95% Confidence Interval for the difference between the observed and replicated Chi-square values = - 163.320, 102.750)., Conclusions: The Chinese version of the HLQ has strong construct and content validity and high composite reliability when applied to older adults in Changsha City, China. Therefore, the nine-scale HLQ can now be administered to Chinese older adults, thereby providing a powerful approach to understanding the multidimensional area of health literacy.

Clinical named entity recognition (CNER) is a fundamental and crucial task for clinical and translation research. In recent years, deep learning methods have achieved significant success in CNER tasks. However, these methods depend greatly on recurrent neural networks (RNNs), which maintain a vector of hidden activations that are propagated through time, thus causing too much time to train models. In this paper, we propose a residual dilated convolutional neural network with the conditional random field (RD-CNN-CRF) for the Chinese CNER, which makes the model asynchronous in computation and thus speeding up the training period dramatically. To be more specific, Chinese characters and dictionary features are first projected into dense vector representations, then they are fed into the residual dilated convolutional neural network to capture contextual features. Finally, a conditional random field is employed to capture dependencies between neighboring tags and obtain the optimal tag sequence for the entire sequence. Computational results on the CCKS-2017 Task 2 benchmark dataset show that our proposed RD-CNN-CRF method competes favorably with state-of-the-art RNN-based methods both in terms of computational performance and training time.

Aromatic secondary amines (Ar-SAs), constituted of several analogues with varied substitutions in molecular structure, are among the most frequently used anthropogenic antioxidants. Despite the reported toxicity effects, little information is available on their environmental contamination, except for few particular congeners such as diphenylamine. In this study, the occurrence of two kinds of Ar-SAs, substituted diphenylamines (S-DPAs) and novel substituted p-phenylenediamines (S-PPDs), was investigated in dust samples collected from outdoor rubber playgrounds and residential houses. Seven S-DPAs (GM: 102 ng/g) and two S-PPDs (GM: 20.9 ng/g) were detected in indoor dust. Significantly higher concentrations of S-DPAs (GM: 422 ng/g) and S-PPDs (GM: 31.6 ng/g) were observed in playground dust (p < 0.05). Different dominant Ar-SA congeners were found for indoor dust (low molecular weight Ar-SAs) and playground dust (high molecular weight Ar-SAs), indicating varied sources of Ar-SAs for different dust matrices. Apart from these parent chemicals, three diphenylamine derivatives, including N-nitrosodiphenylamine, 2-nitrodiphenylamine, and 4-nitrodiphenylamine, were also confirmed in indoor dust (GM: 35.7 ng/g) and playground dust (GM: 7.88 ng/g). A preliminary estimated daily intake calculation via dust ingestion indicated no immediate health risk to Chinese population. To our knowledge, this is the first report on the occurrence of a wide range of Ar-SAs and related derivates in dust matrices., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Background: While doctors should analyze a large amount of electronic medical record (EMR) data to conduct clinical research, the analyzing process requires information technology (IT) skills, which is difficult for most doctors in China., Methods: In this paper, we build a novel tool QAnalysis, where doctors enter their analytic requirements in their natural language and then the tool returns charts and tables to the doctors. For a given question from a user, we first segment the sentence, and then we use grammar parser to analyze the structure of the sentence. After linking the segmentations to concepts and predicates in knowledge graphs, we convert the question into a set of triples connected with different kinds of operators. These triples are converted to queries in Cypher, the query language for Neo4j. Finally, the query is executed on Neo4j, and the results shown in terms of tables and charts are returned to the user., Results: The tool supports top 50 questions we gathered from two hospital departments with the Delphi method. We also gathered 161 questions from clinical research papers with statistical requirements on EMR data. Experimental results show that our tool can directly cover 78.20% of these statistical questions and the precision is as high as 96.36%. Such extension is easy to achieve with the help of knowledge-graph technology we have adopted. The recorded demo can be accessed from https://github.com/NLP-BigDataLab/QAnalysis-project ., Conclusion: Our tool shows great flexibility in processing different kinds of statistic questions, which provides a convenient way for doctors to get statistical results directly in natural language.

Objective: This paper constructs a mortality prediction system based on a real-world dataset. This mortality prediction system aims to predict mortality in heart failure (HF) patients. Effective mortality prediction can improve resources allocation and clinical outcomes, avoiding inappropriate overtreatment of low-mortality patients and discharging of high-mortality patients. This system covers three mortality prediction targets: prediction of in-hospital mortality, prediction of 30-day mortality and prediction of 1-year mortality., Materials and Methods: HF data are collected from the Shanghai Shuguang hospital. 10,203 in-patients records are extracted from encounters occurring between March 2009 and April 2016. The records involve 4682 patients, including 539 death cases. A feature selection method called Orthogonal Relief (OR) algorithm is first used to reduce the dimensionality. Then, a classification algorithm named Dynamic Radius Means (DRM) is proposed to predict the mortality in HF patients., Results and Discussions: The comparative experimental results demonstrate that mortality prediction system achieves high performance in all targets by DRM. It is noteworthy that the performance of in-hospital mortality prediction achieves 87.3% in AUC (35.07% improvement). Moreover, the AUC of 30-day and 1-year mortality prediction reach to 88.45% and 84.84%, respectively. Especially, the system could keep itself effective and not deteriorate when the dimension of samples is sharply reduced., Conclusions: The proposed system with its own method DRM can predict mortality in HF patients and achieve high performance in all three mortality targets. Furthermore, effective feature selection strategy can boost the system. This system shows its importance in real-world applications, assisting clinicians in HF treatment by providing crucial decision information., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Chlorinated polyfluorinated ether sulfonates (Cl-PFAESs) are the alternative products of perfluorooctanesulfonate (PFOS) in the metal plating industry in China. The similarity in chemical structures between Cl-PFAESs and PFOS makes it reasonable to assume they possess similar biological activities. In the present study, we investigated whether Cl-PFAESs could induce cellular effects through peroxisome proliferator-activated receptors (PPARs) signaling pathways like PFOS. By using fluorescence competitive binding assay, we found two dominant Cl-PFAESs (6:2 Cl-PFAES and 8:2 Cl-PFAES) bound to PPARs with affinity higher than PFOS. Based on the luciferase reporter gene transcription assay, the two Cl-PFAESs also showed agonistic activity toward PPARs signaling pathways with potency similar to (6:2 Cl-PFAES) or higher than (8:2 Cl-PFAES) PFOS. Molecular docking simulation showed the two Cl-PFAESs fitted into the ligand binding pockets of PPARs with very similar binding mode as PFOS. The cell function results showed Cl-PFAESs promoted the process of adipogenesis in 3T3-L1 cells with potency higher than PFOS. Taken together, we found for the first time that Cl-PFAESs have the ability to interfere with PPARs signaling pathways, and current exposure level of 6:2 Cl-PFAES in occupational workers has exceeded the margin of safety. Our study highlights the potential health risks of Cl-PFAESs as PFOS alternatives.

There is a potential risk to the environment from persistent estrogenic compounds in sewage sludge. In this study, eight bisphenols (BPs) were identified in sewage sludge collected from wastewater treatment plants in 15 cities in China. The estrogenic potencies of the eight BPs and the estrogenic activities of sludge samples were evaluated using a bioluminescence yeast estrogen screen (BLYES) assay. All sludge samples elicited considerable estrogenic activity at a range of 2.8-4.7 ng E2 g(-1) dry weight (dw). All BPs exhibited estrogenic activity in the BLYES assay, but there were significant differences between the potency of individual chemicals. Bisphenol AF had the highest activity, followed by tetrachlorobisphenol A, bisphenol F, bisphenol A, bisphenol E, bisphenol S and 2,4-dihydroxybenzophenone. Tetrabromobisphenol A showed weak estrogenic activity at 1×10(4)nM, but significant cytotoxicity above this concentration. The total estradiol equivalency quantities (EEQs) of BPs were in the range of 2.16-49.13 pg E2 g(-1) dw, accounting for 0.05-1.47% of the total EEQs in sewage sludge samples. The results indicate that BPs made a minor contribution to the estrogenic activity of the investigated sewage sludge. Nevertheless, our results suggest that considerable attention should be directed to the estrogenic potentials of emerging organic pollutants because of their widespread use and their potential to persist in the environment., (Copyright © 2014 Elsevier Ltd. All rights reserved.)

Benzotriazole ultraviolet stabilizers (BZT-UVs) have previously been found in sludge from wastewater treatment plants (WWTPs), which might be potential sources of BZT-UVs to the surrounding environment. In this work, the occurrence and fate of seven emerging 2-hydroxyphenyl substituted BZT-UVs were investigated in a Chinese WWTP. This group of hydrophobic BZT-UVs possess log Kow values ranging from 4.31 to 7.67 which could be associated with their fate in WWTPs. Field samples including 24 h flow composites of influent, effluent and grab sludge samples from different treatment processes were collected and analyzed. Concentrations of BZT-UVs dissolved in aqueous-phases were in the range of 4.88±1.35 (UV-234) to 34.5±12.4 ng L(-1) (UV-P) in the primary influent, while only UV-P and UV-328 were detected in the final effluent at concentrations of 10.5±6.59 and 2.74±1.73 ng L(-1), respectively. Considering the amount of target BZT-UVs adsorbed to total suspended solids (TSS), the daily mass flux in the primary influent of the WWTP ranged from 22.3 g day(-1) (UV-P, 7.99%) to 74.0 g day(-1) (UV-234, 26.5%). Total removal efficiency of the integrated treatment process ranged from 89.7% for UV-P to 99.7% for UV-234 suggesting nearly complete removal. Organic solid sedimentation in primary and secondary clarifiers was the dominant elimination route for BZT-UV analogues, which constituted 96.3% of the total removal efficiency. Advanced treatment (using ultraviolet disinfection) in this plant might further contribute to the high removal efficiencies (ranging from 19.6% to 77.3%).

Quaternary ammonium compounds (QACs) have raised considerable attention due to their wide commercial applications and recent discovery of unknown persistent analogues in aqueous environment. In this work, the occurrence and distribution of alkyltrimethylammonium (ATMAC), benzylakyldimethylethylammonium (BAC) and dialkyldimethylammonium (DADMAC) homologues were investigated in fifty-two municipal sewage sludge samples. ATMAC C10-18, BAC C8-18 and paired DADMAC C8:8-C18:18 as well as emerging homologues such as ATMAC-20, 22 and mixed DADMAC-16:18 and 14:16 were present. Furthermore, paired DADMAC-20:20 and mixed DADMAC-14:18, 18:20 were identified for the first time by nontarget qualitative strategies. A triple quadruple mass spectrometer quantification method was also initially verified with the aid of laboratory synthesized standards for the analysis of the mixed DADMACs with no certificated commercial standards currently available. The total concentrations of ATMACs, BACs and DADMACs were in the range of 0.38-293, 0.09-191 and 0.64-344 μg/g dry weight, respectively, and particularly, mixed DADMACs constituted 39 ± 7% of total DADMAC concentrations. The concentrations and profiles of individual homologues further suggested different QAC applications and fate in China. Significant correlations were also found among the concentrations of various QAC homologues as well as wastewater treatment plant (WWTP) characteristics (total organic carbon contents and daily treatment volumes).

Constructing ontology manually is a time-consuming, error-prone, and tedious task. We present SSCO, a self-supervised learning based chinese ontology, which contains about 255 thousand concepts, 5 million entities, and 40 million facts. We explore the three largest online Chinese encyclopedias for ontology learning and describe how to transfer the structured knowledge in encyclopedias, including article titles, category labels, redirection pages, taxonomy systems, and InfoBox modules, into ontological form. In order to avoid the errors in encyclopedias and enrich the learnt ontology, we also apply some machine learning based methods. First, we proof that the self-supervised machine learning method is practicable in Chinese relation extraction (at least for synonymy and hyponymy) statistically and experimentally and train some self-supervised models (SVMs and CRFs) for synonymy extraction, concept-subconcept relation extraction, and concept-instance relation extraction; the advantages of our methods are that all training examples are automatically generated from the structural information of encyclopedias and a few general heuristic rules. Finally, we evaluate SSCO in two aspects, scale and precision; manual evaluation results show that the ontology has excellent precision, and high coverage is concluded by comparing SSCO with other famous ontologies and knowledge bases; the experiment results also indicate that the self-supervised models obviously enrich SSCO.

A new method using ultrasonic extraction and solid phase extraction (SPE) clean-up pretreatments was developed for the analysis of mono-, di- and tri-substituted polyfluoroalkyl phosphates (abbreviated as mono-PAPs, di-PAPs and tri-PAPs) and perfluorinated phosphonic acids (PFPAs) in sludge from wastewater treatment plants (WWTPs). For the ultrasonic extraction of three mono-PAPs, three di-PAPs and three PFPAs in sludge samples, a mixture of tetrahydrofuran/acetic acid (1:1, v/v) was found to be the most suitable extraction solvent. The subsequently optimized clean-up and enrichment procedures were carried out with weak anion exchange (WAX) cartridges in-line coupled with graphitized carbon black (ENVI-Carb) tubes. Two tri-PAPs were ultrasonically extracted by acetonitrile/tetrahydrofuran (1:1, v/v) and cleaned by mixed-mode anion exchange (MAX) in-line coupled with ENVI-Carb cartridges. The analytes were analyzed by optimized high performance liquid chromatography tandem mass spectrometry (HPLC-MS/MS) method either in negative or positive ionization mode. The method quantification limits (MQLs) of the 11 analytes in sludge ranged from 0.6 to 5.1 ng/g, meanwhile the total recoveries of the pretreatment varied from 24% (6:2 mono-PAP) to 107% (PFDPA). The method was successfully applied to analyze 16 sewage sludge samples collected from seven provinces in China, and two mono-PAPs were identified with concentrations ranging from

Increasing attention has been paid to bisphenol A and bisphenol (BP) analogues due to high production volumes, wide usage and potential adverse effects. Bisphenol AF (BPAF) is considered a new bisphenol analogue which is used as raw material in plastic industry, but little is known about its occurrence in the environment and the potential associated risk. In this work, BPAF levels and environmental distribution were reported in samples collected around a manufacturing plant and a preliminary exposure risk assessment to local residents was conducted. BPAF was detected in most of the samples, with levels in river ranging between

The environmental contamination and fate of benzotriazole UV stabilizers (BZTs) have received increasing attention due to their large production volume and wide usage in various consumer and industrial products. In the present work, 60 municipal sewage sludge samples from wastewater treatment plants (WWTPs) in 33 cities in China were collected to investigate the occurrence and distribution of 9 frequently used BZTs. The most dominant analogue was 2-[3,5-bis(1-methyl-1-phenylethyl)-2-hydroxyphenyl]benzotriazole (UV-234) at a median concentration of 116 ng/g (dry weight) and accounted on average for 27.2% of total BZTs. The abundance was successively followed by 2-(2-hydroxy-5-tert-octylphenyl)benzotriazole (UV-329, average 24.3%), 2-(2-hydroxy-3-tert-butyl-5-methylphenyl)-5-chlorobenzotriazole (UV-326, average 22.2%), 2-(3,5-di-tert-amyl-2-hydroxyphenyl)benzotriazole (UV-328, average 17.7%), and 2-(2-hydroxy-5-methylphenyl)benzotriazole (UV-P, average 6.6%), with median concentrations of 66.8, 67.8, 57.3, and 20.6 ng/g, respectively. 5-Chloro-2-(3,5-di-tert-butyl-2-hydroxyphenyl)benzotriazole (UV-327) and 2-(3-sec-butyl-5-tert-butyl-2-hydroxyphenyl)benzotriazole (UV-350) had low detection frequency, while 2-(3,5-di-tert-butyl-2-hydroxyphenyl)benzotriazole (UV-320) and 2-(5-tert-butyl-2-hydroxyphenyl)benzotriazole (UV-PS) were not detectable in any sample. To our knowledge, this is the first study reporting the occurrence of UV-234, UV-329, and UV-350 in sewage sludge in China. Significant correlations were found among the BZT concentrations and also with a WWTP characteristic (daily treatment volume). Furthermore, results from degradation prediction and multimedia fate simulation based on a quantitative structure-property relationship (QSPR) model at screening level also implied that the commercial BZT chemicals and their plausible transformation products might be persistent in the environment.

Short chain chlorinated paraffins (SCCPs) are listed as persistent organic pollutant candidates in the Stockholm Convention and are receiving more and more attentions worldwide. In general, concentrations of contaminants in sewage sludge can give an important indication on their pollution levels at a local/regional basis. In this study, SCCPs were investigated in sewage sludge samples collected from 52 wastewater treatment plants in China. Concentrations of total SCCPs (ΣSCCPs) in sludge were in the range of 0.80-52.7 μg/g dry weight (dw), with a mean value of 10.7 μg/g dw. Most of SCCPs in the sludge samples showed a similar congener distribution patterns, and C(11) and Cl(7,8) were identified as the dominant carbon and chlorine congener groups. Significant linear relationships were found among different SCCP congener groups (r(2) ≥ 0.9). High concentrations of SCCPs in sewage sludge imply that SCCPs are widely present in China., (Copyright © 2011 Elsevier Ltd. All rights reserved.)