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In order to reveal the influence of carnosic acid on the quality characteristics of thermal processed rapeseed oil, the changes of color, acid value, peroxide value, tocopherol, viscosity, fatty acid composition and total polar compound were investigated during thermal processing (180 ℃, 0, 8, 16, 24, 32 h) by adding different concentrations of carnosic acid (0, 200, 400, 700 mg/kg) and 200 mg/kg tert-butylhydroquinone as antioxidants. The results indicated that the addition of 700 mg/kg carnosic acid showed a better performance in the thermal processed rapeseed oil: The color deterioration was delayed and the increase of viscosity was inhibited; the increased value of acid value was the smallest which was from 0.280±0.030 mg/g to 0.757±0.020 mg/g, as well as the minimum peroxide value (0.138 g/100 g) was obtained at 32 h; the loss rate of α-tocopherol and γ-tocopherol were 95.51%±0.96% and 83.37%±0.39%, respectively; the content of polar components was 26.62%±0.03%, prolonging the thermal processing life of rapeseed oil by delaying the increase of total polar compound. It was found that the use of carnosic acid could better control the risk factors in rapeseed oil during thermal processing and reduce the waste of oils.

BackgroundAntiretroviral therapy (ART) has been shown to reduce human immunodeficiency virus (HIV) viral replication and ultimately achieve viral suppression and eliminate HIV transmission. However, little is known about the impact of viral suppression on high-risk behaviors and sexually transmitted infections (STIs).ObjectiveThis study aimed to assess the rates of current syphilis infection in virally suppressed people living with HIV (PLWH) and whether with the duration of ART can reduce the current syphilis infection in eastern China.MethodWe conducted a cross-sectional survey of PLWH in Zhejiang Province, China, in 2022. PLWH who were on ART >6 months and were virally suppressed (viral load

BackgroundMen who have sex with men (MSM) constitute a significant population of patients infected with HIV. In recent years, several efforts have been made to promote HIV testing among MSM in China. ObjectiveThis study aimed to assess HIV testing coverage and factors associated with first-time HIV testing among MSM to provide a scientific basis for achieving the goal of diagnosing 95% of patients infected with HIV by 2030. MethodsThis cross-sectional study was conducted between July 2023 and December 2023. MSM were recruited from the “Sunshine Test,” an internet platform that uses location-based services to offer free HIV testing services to MSM by visiting the WeChat official account in Zhejiang Province, China. Participants were required to complete a questionnaire on their demographic characteristics, sexual behaviors, substance use, and HIV testing history. A logistic regression model was used to analyze first-time HIV testing and its associated factors. ResultsA total of 7629 MSM participated in the study, with 87.1% (6647) having undergone HIV testing before and 12.9% (982) undergoing HIV testing for the first time. Multivariate logistic regression analysis revealed that first-time HIV testing was associated with younger age (adjusted odds ratio [aOR] 2.55, 95% CI 1.91-3.42), lower education (aOR 1.39, 95% CI 1.03-1.88), student status (aOR 1.35, 95% CI 1.04-1.75), low income (aOR 1.55, 95% CI 1.16-2.08), insertive anal sex role (aOR 1.28, 95% CI 1.05-1.56), bisexuality (aOR 1.69, 95% CI 1.40-2.03), fewer sex partners (aOR 1.44, 95% CI 1.13-1.83), use of rush poppers (aOR 2.06, 95% CI 1.70-2.49), unknown HIV status of sex partners (aOR 1.40, 95% CI 1.17-1.69), lack of awareness of HIV pre-exposure prophylaxis (aOR 1.39, 95% CI 1.03-1.88), and offline HIV testing uptake (aOR 2.08, 95% CI 1.80-2.41). ConclusionsA notable 12.9% (982/7629) of MSM had never undergone HIV testing before this large internet survey. We recommend enhancing HIV intervention and testing through internet-based platforms and gay apps to promote testing among MSM and achieve the target of diagnosing 95% of patients infected with HIV by 2030.

BackgroundLimited studies have explored the impact of the Omicron variant on SARS-CoV-2 infection, hospitalization, and associated factors among people living with HIV, particularly in China. The adjustment of preventive policies since December 2022 in China presents an opportunity to evaluate the real-world factors influencing SARS-CoV-2 infection and related hospitalization among people living with HIV. ObjectiveThis study aimed to investigate SARS-CoV-2 infection, hospitalization rates, and associated factors among people living with HIV following the adjustment of preventive policies from December 2022 to February 2023 in southeastern China. MethodsA cross-sectional telephone or web-based survey was conducted among people living with HIV in 5 cities in southeastern China from December 2022 to February 2023. Demographic information, SARS-CoV-2 infection and related hospitalization, and HIV-specific characteristics were collected from existing databases and special investigations. Multivariate logistic regression analyses were conducted to determine the associated factors for infection and hospitalization rates of SARS-CoV-2. Additionally, subgroup analyses were conducted for the association between vaccination and infection across different vaccination statuses and time since the last vaccination. ResultsAmong people living with HIV with a COVID-19 testing history, the SARS-CoV-2 infection rate was 67.13% (95% CI 65.81%-68.13%), whereas the hospitalization rate was 0.71% (95% CI 0.46%-0.97%). Factors such as age, latest CD4 cell count, latest HIV viral load, and transmission route were found to be associated with SARS-CoV-2 infection, while age, cancer, latest CD4 cell count, and latest HIV viral load were associated with SARS-CoV-2 hospitalization. In terms of SARS-CoV-2 vaccination, compared to unvaccinated people living with HIV, there was a lower infection rate among those who had been vaccinated for

Abstract Background/objective People living with HIV (PLWH) are prone to mental health problems and evidence indicates that HIV-related stigma can negatively impact mental health-related quality of life. This study explored potential mechanisms between HIV-related stigma and mental health-related quality of life, specifically whether anxiety or depression mediates, and whether social support moderates, the relationship. Method A total of 1197 Chinese PLWH participated in the study. The Berger HIV Stigma Scale, the Hospital Anxiety and Depression Scale (HADS), the 12-item Brief Health Survey (SF-12), and the Multidimensional Scale of Perceived Social Support (MSPSS) were employed. Results HIV-related stigma was negatively associated with mental health-related quality of life. Anxiety and depression partially mediated the relationship between HIV-related stigma and mental health-related quality of life; social support played a moderating role. Conclusions The mental health-related quality of life in PLWH was shown to be indirectly affected by HIV-related stigma through anxiety and depression in China. The negative impact of HIV-related stigma decreased with increased social support.

HIV drug resistance compromises the ability of anti-retroviral therapy (ART) to suppress viral replication, resulting in treatment failure. This study investigates the prevalence of pre-treatment drug resistance (PDR) in newly diagnosed individuals in a prosperous city (Wenzhou) in Southeastern China. A cross-sectional investigation was carried out among 473 newly diagnosed ART-naive HIV-1-infected individuals between January and December 2022. The protease–reverse transcriptase (PR-RT) region and integrase (IN) region of HIV-1 were amplified by two separately nested PCRs, followed by sequencing. Drug resistance mutations (DRMs) and drug resistance to nucleoside reverse transcriptase inhibitors (NRTIs), non-nucleoside reverse transcriptase inhibitors (NNRTIs), protease inhibitors (PIs) and integrase strand transfer inhibitors (INSTIs) were analyzed. The PDR prevalence was 6.5% [95% CI: 4.4–9.1] for any anti-retroviral drug, 0.9% [95% CI: 0.3–2.3] for NRTIs, 4.1% [95% CI: 2.5–6.5] for NNRTIs, 1.8% [95% CI: 0.8–3.6] for PIs and 0.5% [95% CI: 0.1–1.8] for INSTIs. According to the subtyping results of the PR-RT region, 11 different subtypes and 31 unique recombinant forms (URFs) were found. CRF07_BC was the dominant subtype (53.7%, 233/434), followed by CRF01_AE (25.3%, 110/434). V179D (1.6%) and K103N (1.4%) were the most predominant types of NNRTI DRMs. Q58E (1.2%) and M184V (0.7%) were the most frequent PI DRMs and NRTI DRMs, respectively. The INSTI-related DRMs Y143S (causes high-level resistance to RAL) and G163K (causes low-level resistance to EVG and RAL) were found in one patient each. Given the relatively high PDR prevalence of NNRTI (4.1%), non-NNRTI-based ART may be preferred in the future. It is recommended to include genotypic resistance testing before starting ART in regions where feasible.

BackgroundIn recent years, the number and proportion of newly reported HIV/AIDS cases among older adults have increased dramatically. However, research on the pattern of temporal and spatial changes in newly reported HIV/AIDS among older adults remains limited. ObjectiveThis study analyzed the spatial and temporal distribution of HIV/AIDS cases and its influencing factors among older adults in Eastern China from 2004 to 2021, with the goal of improving HIV/AIDS prevention and intervention. MethodsWe extracted data on newly reported HIV/AIDS cases between 2004 and 2021 from a case-reporting system and used a Joinpoint regression model and an age-period-cohort model to analyze the temporal trends in HIV/AIDS prevalence. Spatial autocorrelation and geographically weighted regression models were used for spatial aggregation and influence factor analysis. ResultsA total of 12,376 participants with HIV/AIDS were included in the study. The newly reported HIV infections among older adults increased from 0.13 cases per 100,000 people in 2004 to 7.00 cases per 100,000 people in 2021. The average annual percent change in newly reported HIV infections was 28.0% (95% CI –21.6% to 34.8%). The results of the age-period-cohort model showed that age, period, and cohort factors affected the newly reported HIV infections among older adults. The newly reported HIV/AIDS cases among men who have sex with men (MSM) had spatial clustering, and the hotspots were mainly concentrated in Hangzhou. The disposable income of urban residents, illiteracy rate among people aged 15 years or older, and number of hospital beds per 1000 residents showed a positive association with the newly reported HIV infections among older MSM in the Zhejiang province. ConclusionsHIV/AIDS among older adults showed an increasing trend and was influenced by age, period, and cohort effects. Older MSM with HIV/AIDS showed regional clustering and was associated with factors such as the disposable income of urban residents, the illiteracy rate among people aged 15 years or older, and the number of hospital beds per 1000 people. Targeted prevention and control measures are needed to reduce HIV infection among those at higher risk.

Abstract Introduction People living with HIV (PLHIV) are a high-risk group for depression. In particular, the prevalence and burden of depression is higher and more severe among PLHIV in developing and less-developed countries. There is evidence that perceived social support has a positive impact on reducing the occurrence of depression, and high stigma and low adherence self-efficacy are barriers to the effectiveness of social support for depressed PLHIV. However, how these risks affect the effect of social support on depression still needs further identification. Methods Between 2017 and 2018, a total of 1139 Chinese PLHIV (74.36% male, mean age = 43.91 years) from three provinces (Shanghai, Zhejiang and Henan) in China were enrolled in the study. Data were analyzed by multiple regression, mediation model, and moderation model. Results A total of 43.99% of PLHIV had mild to severe depression. There was a significant negative association between perceived social support and depression (B = -0.049, P

Abstract Background Men who have sex with men and women (MSMW) are the most important bridge population for HIV transmission. Condom use plays an important role for HIV infection. However the predictors for condom ues with females are not well characterized. Methods This was a cross-sectional study. Participants were enrolled by four community-based organizations (CBOs) by offline (bathrooms, bars), and online (gay applications, chat room) from April to December 2019. Electronic questionnare was fulfilled after a face-to-face training led by CBOs. We identified predictors of inconsistent condom use with females by creating a risk score based on regression coefficients. We externally validated this score via an independent cross-sectional survey conducted in Zhejiang Province in 2021. A total of 917, 615 MSMW were included in analysis in 2019 and 2021, seperately. Results Among 917 MSMW, 73.2% reported heterosexual behavior in the prior 6 months and 38.3% reported inconsistent condom use with females (ICUF) over that time. Compared with heterosexual/unsure MSMW, bisexual MSMW reported more male and female sex partners, higher proportion of inconsistent condom use with males, less commercial sex with males (p

ABSTRACT: Objectives: This study aimed to establish a collaborative approach to quantify local HIV transmission, which is an issue of great concern to public health. Methods: We linked HIV-1 pol gene sequences to demographic information and epidemiological investigations in Hangzhou (a central city in East China). We estimated local acquisition rates from a collaboration of molecular network analysis (with a distance-based approach) and epidemiological investigations. Results: Among 1064 newly diagnosed patients with HIV, 857 pol sequences were acquired and subsequently analyzed. Multiple subtypes were identified, with circulating recombinant form (CRF)07_BC (42.5%) and CRF01_AE (39.2%) predominating, followed by 13 other subtypes and 26 unique recombinant forms. By integrating the molecular network analysis and epidemiological investigations, we estimated that the proportion of local infection was 63.2%. The multivariable analyses revealed that individuals in clusters were more likely to be local residents, be aged 50 years or older, work as farmers, and have a higher first cluster of differentiation 4 count level (P

In this study, we conducted a detailed molecular epidemiological analysis of HIV-1 epidemic strains in various sexual risk behaviour groups in a developed area in eastern China based on phylogenetic inference, molecular transmission networks, and Bayesian analyses. A total of 1083 pol sequences (91.23%, 1083/1187) from newly diagnosed HIV-1-positive patients from 2017 to 2020 were successfully obtained and involved thirteen HIV-1 subtypes, in which the major HIV-1 subtypes were CRF07_BC (36.10%, 391/1083) and CRF01_AE (34.63%, 375/1083). 485 individuals (44.78%,485/1083) formed 146 clusters in the network. Of which CRF07_BC showed extensive clustering driven by men who have sex with men (MSM) within larger networks, CRF01_AE and other subtypes were generally driven by small clusters (SCs) and medium clusters (MCs) among various risk groups. Through Sankey diagrams, the MSM group infected with CRF07_BC had a greater impact on the non-commercial heterosexual group among all cross-risk groups. In addition, a higher number of key individuals infected with CRF07_BC (40.22%, 74/127), suggests the crucial role of CRF07_BC-infected individuals as a local epidemic driver in the context of a mixed HIV-1 epidemic. Further Bayesian analysis confirmed that CRF07_BC was introduced into Jiaxing city from other provinces multiple times and spread rapidly among MSM and heterosexual individuals. Overall, our study provided some insights and information to explore the local transmission dynamics of HIV-1 epidemic strains involving various sexual risk groups, and emphasize that it is necessary to conduct in-depth research and precise intervention targeting key clusters/ individuals to effectively block the continued transmission of AIDS.

The quality and stability of oil during thermal processing reflect the reactions in vegetable oil. The deterioration of the oil is close to the viscosity, fatty acid composition (FA), total polar compounds (TPC), etc. Carnosic acid (CA) is the main antioxidant component of rosemary extract; it is a natural and clean-label antioxidant that is allowed to be added to prolong oil processing and storage. To achieve a clear correlation of this situation, a novel stability evaluation model was used to predict the thermal degradation of rapeseed oil (RSO) with CA. The RSO with CA (200 mg/kg, 400 mg/kg, and 700 mg/kg), the tert-Butylhydroquinone (TBHQ, 200 mg/kg), and the fresh RSO (without additives) during thermal processing (180 ± 5 °C) were studied. The temperature dependency of viscosity fits well with the Lioumbas model (R2 ≥ 0.999). The parameter b value in the Lioumbas model showed a decrease linearly with the processing time (tP, R2 ≥ 0.965). The multiple linear regression analysis showed that the accuracy of the model in predicting viscosity was less than ±2 mPa·s−1, and the deviation% was less than ±10% in all the samples. After 32 h of thermal degradation, the addition of 700 mg/kg CA showed the lowest degradation rate (13.84%) of polyunsaturated fatty acids (PUFAs), and the TPC content was 26.00 ± 0.50%. The TPC showed a positive relationship with viscosity (r = 0.99, p < 0.01), tP (r = 0.97, p < 0.01), and effective carbon numbers (ECN, r = 0.84, p < 0.05). In conclusion, this study can make a potential prediction for the stability of RSO.

BackgroundContinuously growing of HIV incidence among men who have sex with men (MSM), as well as the low rate of HIV testing of MSM in China, demonstrates a need for innovative strategies to improve the implementation of HIV prevention. The use of machine learning algorithms is an increasing tendency in disease diagnosis prediction. We aimed to develop and validate machine learning models in predicting HIV infection among MSM that can identify individuals at increased risk of HIV acquisition for transmission-reduction interventions.MethodsWe extracted data from MSM sentinel surveillance in Zhejiang province from 2018 to 2020. Univariate logistic regression was used to select significant variables in 2018–2019 data (P < 0.05). After data processing and feature selection, we divided the model development data into two groups by stratified random sampling: training data (70%) and testing data (30%). The Synthetic Minority Oversampling Technique (SMOTE) was applied to solve the problem of unbalanced data. The evaluation metrics of model performance were comprised of accuracy, precision, recall, F-measure, and the area under the receiver operating characteristic curve (AUC). Then, we explored three commonly-used machine learning algorithms to compare with logistic regression (LR), including decision tree (DT), support vector machines (SVM), and random forest (RF). Finally, the four models were validated prospectively with 2020 data from Zhejiang province.ResultsA total of 6,346 MSM were included in model development data, 372 of whom were diagnosed with HIV. In feature selection, 12 variables were selected as model predicting indicators. Compared with LR, the algorithms of DT, SVM, and RF improved the classification prediction performance in SMOTE-processed data, with the AUC of 0.778, 0.856, 0.887, and 0.942, respectively. RF was the best-performing algorithm (accuracy = 0.871, precision = 0.960, recall = 0.775, F-measure = 0.858, and AUC = 0.942). And the RF model still performed well on prospective validation (AUC = 0.846).ConclusionMachine learning models are substantially better than conventional LR model and RF should be considered in prediction tools of HIV infection in Chinese MSM. Further studies are needed to optimize and promote these algorithms and evaluate their impact on HIV prevention of MSM.

Textual information is ubiquitous in our lives and is becoming an important component of our cognitive society. In the age of big data, we consistently need to traverse substantial amounts of data even to find a little information. To quickly acquire effective information, it is necessary to implement a textual similarity search based on an appropriate index structure to efficiently find results. In this article, we study top-k textual similarity search and develop a tree-based indexing approach that can construct indices to support various similarity functions. Our indexing approach clusters similar records in the same branch offline to improve the performance of online search. Based on the index tree, we present a top-k search algorithm with efficient pruning techniques. The experimental results demonstrate that our algorithm can achieve higher performance and better scalability than the baseline method.

Background: Tuberculosis (TB) is a critical global public threat, and limited epidemiology studies have been performed to explore the efficacy of active TB screening. Methods: Three sites located in eastern China were chosen in 2013, and three rounds of systematic screenings were performed in permanent residents aged older than 15 years. Results: The TB incidence showed a downtrend after several rounds of active screening at the three sites, and a significant change was observed at site A in the overall population. In the target population at sites A and B, both the elderly and people with a history of TB had a remarkable decline through the first or second round of screening. The implementation of active case-finding identified 2.36 [1.47,3.81] (2013 vs. 2012) and 1.49 [1.1,2.03] (2013–2015 vs. 2010–2012) more potential cases than the passive case-finding by the surveillance system at site A. Conclusions: Active case-finding of tuberculosis might be effective in high prevalence area with a low economic level, particularly among the elderly and people with a history of TB. Additionally, new rapid diagnosis technology should be considered to decrease the prevalence among people with a history of TB. Ultimately, active screening identified more active TB cases than passive case-finding, particularly in high prevalence area with underdeveloped economics. Keywords: Tuberculosis, Active screening, High prevalence, Target population

Abstract Background In recent years, tuberculosis outbreaks in schools have occurred more frequently in China than in other parts of the world, and have posed a public health threat to students and their families. This systematic review aimed to understand the epidemiological characteristics of tuberculosis (TB) outbreaks and analyze the factors associated with TB outbreaks in schools in China. Methods We conducted this systematic review following the standard procedures of the Cochrane Collaboration and the Preferred Reporting Items for Systematic Review and Meta-Analysis statement. The meta-analysis was performed with STATA using a random effects model. Results We included 107 studies involving 1795 student patients with TB in mainland China. The results of the systematic analysis indicated that TB outbreaks were more frequently reported in senior middle schools and in Eastern China. The outbreaks mainly occurred during the winter and spring, and the median outbreak duration was 4 months. The meta-analysis showed that the total attack rate and the class attack rate of tuberculosis outbreaks among students were 4.60% (95% CI 3.80 to 5.70%) and 22.70% (95% CI 19.20 to 27.00%), respectively. Subgroup analysis showed that outbreaks that occurred at universities or colleges had a relatively higher attack rate than those occurred in senior middle schools. The prevalence of latent tuberculosis infection (LTBI) among close contacts was 23.70% (95% CI 19.50 to 28.90%). The median case-finding interval was 2 months, and 47.40% of the index cases had a case-finding delay. Conclusion The results of our review indicated that school TB outbreaks were reported most frequently in senior middle schools in China. The attack rates of outbreaks at universities or colleges were higher than those in senior middle schools. The TB outbreaks in schools usually occurred over prolonged periods. The case-finding delay in the index cases must be reduced to prevent transmission in classes and schools. Effective surveillance and screening of presumptive TB cases in schools should be strengthened to reduce outbreaks in schools.

Abstract Knowledge graphs are widely applied in many applications. Automatically solving mathematical exercises is also an interesting task which can be enhanced by knowledge reasoning. In this paper, we design MathGraph, a knowledge graph aiming to solve high school mathematical exercises. Since it requires fine-grained mathematical derivation and calculation of different mathematical objects, we design a crowdsourcing-based method to help build MathGraph. MathGraph supports massive kinds of mathematical objects, operations and constraints which may be involved in exercises. Furthermore, we propose an algorithm to align a semantically parsed exercise to MathGraph and figure out the answer automatically. Extensive experiments on real-world datasets verify the effectiveness of MathGraph.

Educational theory claims that integrating learning style into learning-related activities can improve academic performance. Traditional methods to recognize learning styles are mostly based on questionnaires and online behavior analyses. These methods are highly subjective and inaccurate in terms of recognition. Electroencephalography (EEG) signals have significant potential for use in the measurement of learning style. This study uses EEG signals to design a deep-learning-based model of recognition to recognize people’s learning styles with EEG features by using a non-overlapping sliding window, one-dimensional spatio-temporal convolutions, multi-scale feature extraction, global average pooling, and the group voting mechanism; this model is named the TSMG model (Temporal-Spatial-Multiscale-Global model). It solves the problem of processing EEG data of variable length, and improves the accuracy of recognition of the learning style by nearly 5% compared with prevalent methods, while reducing the cost of calculation by 41.93%. The proposed TSMG model can also recognize variable-length data in other fields. The authors also formulated a dataset of EEG signals (called the LSEEG dataset) containing features of the learning style processing dimension that can be used to test and compare models of recognition. This dataset is also conducive to the application and further development of EEG technology to recognize people’s learning styles.

Existing methods for learning-style recognition are highly subjective and difficult to implement. Therefore, the present study aimed to develop a learning-style recognition mechanism based on EEG features. The process for the mechanism included labeling learners’ actual learning styles, designing a method to effectively stimulate different learners’ internal state differences regarding learning styles, designing the data-collection method, designing the preprocessing procedure, and constructing the recognition model. In this way, we designed and verified an experimental method that can effectively stimulate learning-style differences in the information-processing dimension. In addition, we verified the effectiveness of using EEG signals to recognize learning style. The recognition accuracy of the learning-style processing dimension was 71.2%. This result is highly significant for the further exploration of using EEG signals for effective learning-style recognition.

A nosocomial cluster induced by co-infections with avian influenza A(H7N9) and A(H1N1)pdm09 (pH1N1) viruses occurred in 2 patients at a hospital in Zhejiang Province, China, in January 2014. The index case-patient was a 57-year-old man with chronic lymphocytic leukemia who had been occupationally exposed to poultry. He had co-infection with H7N9 and pH1N1 viruses. A 71-year-old man with polycythemia vera who was in the same ward as the index case-patient for 6 days acquired infection with H7N9 and pH1N1 viruses. The incubation period for the second case-patient was estimated to be

Closure of live poultry markets was implemented in areas affected by the influenza virus A(H7N9) outbreak in China during winter, 2013–14. Our analysis showed that closing live poultry markets in the most affected cities of Guangdong and Zhejiang provinces was highly effective in reducing the risk for H7N9 infection in humans.

OBJECTIVES:More than 900 students and teachers at many schools in Jiaxing city developed acute gastroenteritis in February 2014. An immediate epidemiological investigation was conducted to identify the pathogen, infection sources and route of transmission. METHODS:The probable cases and confirmed cases were defined as students or teachers with diarrhoea or vomiting present since the term began in February 2014. An active search was conducted for undiagnosed cases among students and teachers. Details such as demographic characteristics, gastrointestinal symptoms, and drinking water preference and frequency were collected via a uniform epidemiological questionnaire. A case-control study was implemented, and odds ratios (ORs) and 95% confidence intervals were calculated. Rectal swabs from several patients, food handlers and barrelled water factory workers, as well as water and food samples, were collected to test for potential bacteria and viruses. RESULTS:A total of 924 cases fit the definition of the probable case, including 8 cases of laboratory-confirmed norovirus infection at 13 schools in Jiaxing city between February 12 and February 21, 2014. The case-control study demonstrated that barrelled water was a risk factor (OR: 20.15, 95% CI: 2.59-156.76) and that bottled water and boiled barrelled water were protective factors (OR: 0.31, 95% CI: 0.13-0.70, and OR: 0.36, 95% CI: 0.16-0.77). A total of 11 rectal samples and 8 barrelled water samples were detected as norovirus-positive, and the genotypes of viral strains were the same (GII). The norovirus that contaminated the barrelled water largely came from the asymptomatic workers. CONCLUSIONS:This acute gastroenteritis outbreak was caused by barrelled water contaminated by norovirus. The outbreak was controlled after stopping the supply of barrelled water. The barrelled water supply in China represents a potential source of acute gastroenteritis outbreaks due to the lack of surveillance and supervision. Therefore, more attention should be paid to this area.

In June 2013, a subclinical infection with severe fever with thrombocytopenia syndrome virus (SFTSV) was detected in Zhejiang Province, China, prompting seroprevalence studies in 6 districts within the province. Of 986 healthy persons tested, 71 had IgG antibodies against SFTSV. This finding suggests that most natural infections with SFTSV are mild or subclinical.

To date, there have been a total of 637 laboratory-confirmed cases of human infection with avian influenza A (H7N9) virus across mainland China, with 28% (179/637) of these reported in Zhejiang Province. Surveillance of avian H7N9 virus was conducted to investigate environmental contamination during H7N9 outbreaks. We sought to evaluate the prevalence of H7N9 in the environment, and the effects of poultry market closures on the incidence of human H7N9 cases.We collected 6740 environmental samples from 751 sampling sites across 11 cities of Zhejiang Province (China) between January 2013 and March 2014. The presence of H7N9 was determined by reverse transcription polymerase chain reaction, with prevalence compared between sites and over time. The relationship between environmental contamination and human cases of H7N9 infection were analyzed using Spearman's ranked correlation coefficient.Of the 6740 samples, 10.09% (680/6740) were H7N9-positive. The virus was found to circulate seasonally, and peaked during the spring and winter of 2013-2014. The prevalence of the virus decreased from the north to the southeast of the province, coinciding with the geographical distribution of human H7N9 cases. Compared with other sampling sites, live poultry markets (LPMs) had the highest prevalence of H7N9 virus at 13.94% (667/4784). Of the various sample types analyzed, virus prevalence was highest for chopping board swabs at 15.49% (110/710). The prevalence of the virus in the environment positively correlated with the incidence of human H7N9 cases (r2 = 0.498; P < 0.01). Cities with a higher incidence of human H7N9 cases also had a higher prevalence of H7N9 among samples and at sampling sites. Following the closure of LPMs at the end of January 2014, the prevalence of H7N9 decreased from 19.18% (487/2539) to 6.92% (79/1141). This corresponded with a decrease in the number of human H7N9 cases reported.The prevalence of H7N9 virus in environmental samples oscillated seasonally, regardless of whether LPMs were open. The presence of H7N9 in environmental samples positively correlated with the number of human H7N9 cases, indicating that eradication of the virus from the environment is essential in reducing the numbers of H7N9 cases and halting the spread of the virus.

A total of 134 cases of H7N9 influenza infection were identified in 12 provinces of China between March 25 and September 31, 2013. Of these, 46 cases occurred in Zhejiang Province. We carried out a preliminary comparison of characteristics between rural and urban H7N9 cases from Zhejiang Province, China. Field investigations were conducted for each confirmed H7N9 case. A standardized questionnaire was used to collect information about demographics, exposure history, clinical signs and symptoms, timelines of medical visits and care after onset of illness. Of the 46 H7N9 cases in Zhejiang Province identified between March 25 and September 31, 2013, there were 16 rural cases and 30 urban cases. Compared to urban cases, there was a higher proportion of females among the rural cases [11/16 (69%) vs. 6/30 (20%), P = 0.001]. Among the rural cases, 14/15 (93%) with available data had a history of recent poultry exposure, which was significantly higher than that among urban cases (64%, P = 0.038). More patients from the rural group had a history of breeding poultry compared with those from the urban group [38% (6/16) vs. 10% (3/30), respectively; P = 0.025]. Interestingly, the median number of medical visits of patients from rural areas was higher than that of patients from urban areas (P = 0.046). There was no difference between the two groups in terms of age distribution, fatality rate, incubation period, symptoms, and underlying medical conditions. In conclusion, compared to patients from urban areas, more patients from rural areas were female, had an exposure history, had a history of breeding poultry, and had a higher number of medical visits. These findings indicate that there are different exposure patterns between patients living in rural and urban areas and that more rural cases were infected through backyard poultry breeding.

The adaptive learning environment provides learning support that suits individual characteristics of students, and the student model of the adaptive learning environment is the key element to promote individualized learning. This paper provides a systematic overview of the existing student models, consequently showing that the Elo rating system has greater potential as compared to the other models regarding application in the online learning environment. Based on the Elo model, this study proposes the EELO, an enhanced Elo rating system, in consideration of the application scenarios of polychotomously scored items and multi-dimensional granularity evaluations not covered by the basic Elo rating system. The EELO model estimating students' cognitive abilities and predicting their future performances on unknown questions is evaluated based on one public set (Assigment2) and one proprietary dataset (HSK), and achieved an AUC of 0.92 for Assigment2 and 0.84 for HSK, which shows that the EELO model has the best performance regarding the above-mentioned objectives as compared with the latest extensions of the IRT and BKT models. Subsequently, the EELO model was tested and applied successfully in a real large-scale online learning environment to demonstrate the potential of the EELO model in adaptive learning applications.

Few case control studies were conducted to explore risk factors for severe cases of 2009 influenza A (H1N1) with the mild cases as controls. Mild and severe cases of 2009 influenza A (H1N1), 230 cases each, were randomly selected from nine cities in Zhejiang Province, China, and unmatched case control study was conducted. This study found that it averagely took 5 days for the severe cases of 2009 influenza A (H1N1) to start antiviral therapy away from onset, 2 days later than mild cases. Having chronic underlying diseases and bad psychological health combined with chronic underlying diseases were two important risk factors for severe cases, and their OR values were 2.39 and 5.85 respectively. Timely anti-viral therapy was a protective factor for severe cases (OR = 0.35, 95% CI: [0.18-0.67]). In conclusion, psychological health education and intervention, as well as timely anti-viral therapy, could not be ignored in the prevention, control and treatment of 2009 influenza A (H1N1).