Spatial-temporal distribution of human brucellosis in mainland China from 2004 to 2017 and an analysis of social and environmental factors.

BACKGROUND: This study aimed to describe the changing distribution of human brucellosis between 2004 and 2017 in mainland China and seek scientific evidence of the relationship between socio-economic, environmental, and ecological factors and human brucellosis incidence. METHODS: The annual numbers of brucellosis cases and incidence rates from 31 provinces in mainland China between 2004 and 2017 were obtained from the Data-Center for China Public Health Science. The number of monthly brucellosis cases in 2018 was obtained from the Chinese Center for Disease Control and Prevention. The electronic map of the People's Republic of China was downloaded from the National Earth System Science Data Sharing Platform. Human population density, gross domestic product (GDP), and an inventory of cattle and sheep at the end of each year from 2004 to 2017 were obtained from the National Bureau of Statistics of China. Annual rainfall data from 31 provinces in the People's Republic of China from 2004 to 2017 were collected from the China Meteorological Data Service Center. The risk distribution and changing trends of human brucellosis were mapped with ArcGIS. A cluster analysis was employed to identify geographical areas and periods with statistically significant incidence rates. Multivariate linear regression was used to determine possible factors that were significantly correlated with the presence of human brucellosis cases. RESULTS: Human brucellosis cases have spread throughout the whole country. Human brucellosis cases occurred mostly from March to August and were concentrated from April to July. The inventory of sheep, GDP, and climate were significantly correlated with the presence of brucellosis cases in mainland China. CONCLUSIONS: The geographical expansion of human brucellosis in mainland China was observed, so did the high-incidence clusters between 2004 and 2017. Most of the cases were reported during the early spring to early summer (February-August). Results from the multivariate linear regression suggested that the inventory of sheep, GDP, and climate were significantly associated with the incidence of human brucellosis in mainland China.

Time series analysis of human brucellosis in mainland China by using Elman and Jordan recurrent neural networks.

BACKGROUND: Establishing epidemiological models and conducting predictions seems to be useful for the prevention and control of human brucellosis. Autoregressive integrated moving average (ARIMA) models can capture the long-term trends and the periodic variations in time series. However, these models cannot handle the nonlinear trends correctly. Recurrent neural networks can address problems that involve nonlinear time series data. In this study, we intended to build prediction models for human brucellosis in mainland China with Elman and Jordan neural networks. The fitting and forecasting accuracy of the neural networks were compared with a traditional seasonal ARIMA model. METHODS: The reported human brucellosis cases were obtained from the website of the National Health and Family Planning Commission of China. The human brucellosis cases from January 2004 to December 2017 were assembled as monthly counts. The training set observed from January 2004 to December 2016 was used to build the seasonal ARIMA model, Elman and Jordan neural networks. The test set from January 2017 to December 2017 was used to test the forecast results. The root mean squared error (RMSE), mean absolute error (MAE) and mean absolute percentage error (MAPE) were used to assess the fitting and forecasting accuracy of the three models. RESULTS: There were 52,868 cases of human brucellosis in Mainland China from January 2004 to December 2017. We observed a long-term upward trend and seasonal variance in the original time series. In the training set, the RMSE and MAE of Elman and Jordan neural networks were lower than those in the ARIMA model, whereas the MAPE of Elman and Jordan neural networks was slightly higher than that in the ARIMA model. In the test set, the RMSE, MAE and MAPE of Elman and Jordan neural networks were far lower than those in the ARIMA model. CONCLUSIONS: The Elman and Jordan recurrent neural networks achieved much higher forecasting accuracy. These models are more suitable for forecasting nonlinear time series data, such as human brucellosis than the traditional ARIMA model.

Mycoplasma Genitalium and Mycoplasma Hominis are prevalent and correlated with HIV risk in MSM: a cross-sectional study in Shenyang, China.

BACKGROUND: A high proportion of men who have sex with men (MSM) use geosocial networking apps (Apps) to seek partners. However, the relationship of app use with HIV risk is unknown. Further, the risks of some sexually transmitted infection (STIs), including Mycoplasma genitalium, have seldom been studied among MSM. METHODS: MSM were enrolled at a community-based HIV testing site in Shenyang, China. After completing a questionnaire survey, we collected rectal swabs and venous blood specimens. We then simultaneously tested for ten STIs (Chlamydia trachomatis [CT], Neisseria gonorrhea [NG], Ureaplasma urealyticum [Uu], Ureaplasma parvum species [Up1, Up3, Up6, Up14), Mycoplasma hominis [Mh], Mycoplasma genitalium [Mg], and Herpes Simplex Virus Type 2 (HSV-2) using multiple PCR. We also performed blood tests for HIV, Syphilis, Hepatitis C antibody (HCV-Ab), Hepatitis B Surface Antigen (HBsAg), and Hepatitis A-IgM (HAV-IgM), etc. RESULTS: One hundred and eighty-three MSM participated in this study, of which 51.4% reported seeking partners through apps in the past year. The prevalence of HIV was 19.7%, Syphilis 12.0%, HAV 1.1%, rectal Mg 15.3% and Mh 7.1%. Multivariable logistic regression showed that HIV infection was independently correlated with app-using behavior (adjusted odds ratio[aOR] = 2.6), Mg infection (aOR = 3.2), Mh infection (aOR = 4.1) and Syphilis infection (aOR = 3.1) (each P < 0.05). CONCLUSIONS: App use, Mg, Mh and Syphilis infection were correlated with higher HIV Risk in MSM. Geosocial networking apps should be utilized for HIV interventions targeting MSM. There is a need for more expansive STIs screening, particularly for Mg, Mh and Syphilis in MSM.

Prevalence of perinatal depression among HIV-positive women: a systematic review and meta-analysis.

BACKGROUND: Increasing attention has been paid to differences in the prevalence of perinatal depression by HIV status, although inconsistent results have been reported. The aim of this systematic review and meta-analysis was to assess the relationship between perinatal depression and HIV infection. A comprehensive meta-analysis of comparative studies comparing the prevalence of antenatal or postnatal depression between HIV-infected women and HIV-negative controls was conducted. METHODS: Studies were identified through PubMed/Medline, Scopus, Web of Science, Cochrane Library, Embase and PsycINFO, and the reading of complementary references in August 2019. Subgroup analyses were performed for anticipated explanation of heterogeneity using methodological quality and pre-defined study characteristics, including study design, geographical location and depression screening tools for depression. The overall odds ratio (OR) and mean prevalence of each group were calculated. RESULTS: Twenty-three studies (from 21 publications), thirteen regarding antenatal depression and ten regarding postnatal depression were included, comprising 3165 subjects with HIV infection and 6518 controls. The mean prevalence of antenatal depressive symptoms in thirteen included studies was 36% (95% CI: 27, 45%) in the HIV-positive group and 26% (95% CI: 20, 32%) in the control group. The mean prevalence of postnatal depressive symptoms in ten included studies was 21% (95% CI: 14, 27%) in the HIV-positive group and 16% (95% CI: 10, 22%) in the control group. Women living with HIV have higher odds of antenatal (OR: 1.42; 95% CI: 1.12, 1.80) and postnatal depressive symptoms (OR: 1.58; 95% CI: 1.08, 2.32) compared with controls. Publication bias and moderate heterogeneity existed in the overall meta-analysis, and heterogeneity was partly explained by the subgroup analyses. CONCLUSIONS: Women with HIV infection exhibit a significantly higher OR of antenatal and postnatal depressive symptoms compared with controls. For the health of both mother and child, clinicians should be aware of the significance of depression screening before and after delivery in this particular population and take effective measures to address depression among these women.

A review of documents prepared by international organizations about influenza pandemics, including the 2009 pandemic: a bibliometric analysis.

BACKGROUND: World Health Organization (WHO), the World Bank, UN System Influenza Coordination (UNSIC) and other international organizations released a series of documents to fight against the influenza pandemic. Those documents have great significance on guiding influenza pandemic preparedness and responses and providing a multilevel, multi-directional influenza pandemic prevention and control network for their member countries. This study focuses on the above-mentioned influenza pandemic preparedness guidelines with the aim of exploring the roles of the society, defining the relationship of different interventions and evaluating the planning on influenza pandemic preparedness. METHODS: Documents about pandemic influenza preparedness were retrieved from the official websites of the following three international organizations, World Health Organization (WHO), the World Bank, UN System Influenza Coordination (UNSIC) with the key words 'pandemic', 'influenza' and the Boolean combinations of these words as the retrieval strategy. Guidelines, research study and meeting reports were included in the study. The categories of the ministries/departments involved and their roles/responsibilities in pandemic influenza preparedness were summarized. Word frequency of selected vocabularies about pandemic influenza preventive measures were collected from the documents and the correlations between the word frequency of these measures were analyzed. Ochiai coefficient was employed to show the correlation between the word vocabularies. RESULTS: A total of 38 records on the topic of pandemic influenza preparedness were included. The responsibilities of the whole-of-society mentioned in the international organizations' documents varied across the 2009 influenza pandemic period. Meanwhile, it had been emphasized that a comprehensive influenza prevention and control plan in every sector should be developed and evaluated. Because various measures were emphasized in the guidelines after 2009 pandemic influenza, the correlations between the word frequencies of the various influenza preventive measures became stronger after the pandemic influenza. CONCLUSIONS: Responsibilities of ministries of education, ministries of energy, ministries of agriculture and animal health, ministries of communication and the business sector in the pandemic influenza preparedness were described more comprehensively in the international organizations' documents in 2017. Better understanding the variations of the guidelines delivered by international organizations would be useful for the member countries to strengthen their influenza control network.

The effects of psychological interventions on depression and anxiety among Chinese adults with cancer: a meta-analysis of randomized controlled studies.

BACKGROUND: Our previous studies found the high prevalence of depression and anxiety among Chinese cancer patients, and many empirical studies have been conducted to evaluate the effects of psychological interventions on depression and anxiety among Chinese cancer patients. This study aimed to conduct a meta-analysis in order to assess the effects of psychological interventions on depression and anxiety in Chinese adults with cancer. METHODS: The four most comprehensive Chinese academic database- CNKI, Wanfang, Vip and CBM databases-were searched from their inception until January 2014. PubMed and Web of Science (SCIE) were also searched from their inception until January 2014 without language restrictions, and an internet search was used. Randomized controlled studies assessing the effects of psychological interventions on depression and anxiety among Chinese adults with cancer were analyzed. Study selection and appraisal were conducted independently by three authors. The pooled random-effects estimates of standardized mean difference (SMD) and 95% confidence intervals (CI) were calculated. Moderator analysis (meta-regression and subgroup analysis) was used to explore reasons for heterogeneity. RESULTS: We retrieved 147 studies (covering 14,039 patients) that reported 253 experimental-control comparisons. The random effects model showed a significant large effect size for depression (SMD = 1.199, p < 0.001; 95% CI = 1.095-1.303) and anxiety (SMD = 1.298, p < 0.001; 95% CI = 1.187-1.408). Cumulative meta-analysis indicated that sufficient evidence had accumulated since 2000-2001 to confirm the statistically significant effectiveness of psychological interventions on depression and anxiety in Chinese cancer patients. Moderating effects were found for caner type, patients' selection, intervention format and questionnaires used. In studies that included lung cancer, preselected patients with clear signs of depression/anxiety, adopted individual intervention and used State-Trait Anxiety Inventory (STAI), the effect sizes were larger. CONCLUSIONS: We concluded that psychological interventions in Chinese cancer patients have large effects on depression and anxiety. The findings support that an adequate system should be set up to provide routine psychological interventions for cancer patients in Chinese medical settings. However, because of some clear limitations (heterogeneity and publication bias), these results should be interpreted with caution.

A data-driven interpretable ensemble framework based on tree models for forecasting the occurrence of COVID-19 in the USA.

This prevalence of coronavirus disease 2019 (COVID-19) has become one of the most serious public health crises. Tree-based machine learning methods, with the advantages of high efficiency, and strong interpretability, have been widely used in predicting diseases. A data-driven interpretable ensemble framework based on tree models was designed to forecast daily new cases of COVID-19 in the USA and to determine the important factors related to COVID-19. Based on a hyperparametric optimization technique, we developed three machine learning algorithms based on decision trees, including random forest (RF), eXtreme Gradient Boosting (XGBoost), and Light Gradient Boosting Machine (LightGBM), and three linear ensemble models were used to integrate these outcomes for better prediction accuracy. Finally, the SHapley Additive explanation (SHAP) value was used to obtain the feature importance ranking. Our outcomes demonstrated that, among the three basic machine learners, the prediction accuracy was the following in descending order: LightGBM, XGBoost, and RF. The optimized LAD ensemble was the most precise prediction model that reduced the prediction error of the best base learner (LightGBM) by approximately 3.111%, while vaccination, wearing masks, less mobility, and government interventions had positive effects on the control and prevention of COVID-19.

Effects of doxofylline as an adjuvant on severe exacerbation and long-term prognosis for COPD with different clinical subtypes.

OBJECTIVE: This study aimed to investigate the effectiveness of doxofylline as an adjuvant in reducing severe exacerbation for different clinical subtypes of chronic obstructive pulmonary disease (COPD). METHODS: The clinical trial was an open-label non-randomized clinical trial that enrolled patients with COPD. The patients were divided into two groups (doxofylline group[DG] and non-doxofylline group[NDG]) according to whether the adjuvant was used. Based on the proportion of inflammatory cells present, the patients were divided into neutrophilic, eosinophilic, and mixed granulocytic subtypes. The rates of severe acute exacerbation, use of glucocorticoids, and clinical symptoms were followed up in the first month, the third month, and the sixth month after discharge. RESULTS: A total of 155 participants were included in the study. The average age of the participants was 71.2 ± 10.1 years, 52.3% of the patients were male, and 29.7% of the participants had extremely severe cases of COPD. In the third month after discharge the numbers of patients exhibiting severe exacerbation among the neutrophilic subtype were 5 (6.6%) in the DG versus 17 (22.4%) in the NDG (incidence rate ratio[IRR] = 0.4 [95% CI: 0.2-0.9] P = 0.024). In the sixth month after discharge, the numbers were 3 (3.9%) versus 13 (17.1%; IRR = 0.3 [95%; CI: 0.1-0.9], P = 0.045), and those for the eosinophilic subtype were 0 (0.0%) versus 4 (14.8%), P = 0.02. In the eosinophilic subtype, the results for forced expiratory volume in the first second and maximal mid-expiratory flow were significantly higher in the DG. The mean neutrophil and eosinophil levels were significantly lower than in the NDG among the neutrophilic subtype, and the neutrophil percentage was lower than in the NDG among the eosinophilic subtype. At the six-month follow-up, the dose adjustment rates of the neutrophilic and eosinophilic subtypes showed a significant difference (P< 0.05). CONCLUSIONS: As an adjuvant drug, doxofylline has a good therapeutic effect on patients with the neutrophilic and eosinophilic clinical subtypes of COPD. It can reduce the incidence of severe exacerbation, the use of glucocorticoids, and inflammatory reactions in the long term (when used for a minimum of 3 months).

Socioeconomic, meteorological factors and spatiotemporal distribution of human brucellosis in China between 2004 and 2019-A study based on spatial panel model.

BACKGROUND: Human brucellosis continues to be a great threat to human health in China. The present study aimed to investigate the spatiotemporal distribution of human brucellosis in China from 2004 to 2019, to analyze the socioeconomic factors, meteorological factors and seasonal effect affecting human brucellosis incidence in different geographical regions with the help of spatial panel model, and to provide a scientific basis for local health authorities to improve the prevention of human brucellosis. METHODS: The monthly reported number and incidence of human brucellosis in China from January 2004 to December 2019 were obtained from the Data Center for China Public Health Science. Monthly average air temperature and monthly average relative humidity of 31 provincial-level administrative units (22 provinces, 5 autonomous regions and 4 municipalities directly under the central government) in China from October 2003 to December 2019 were obtained from the National Meteorological Science Data Centre. The inventory of cattle, the inventory of sheep, beef yield, mutton yield, wool yield, milk yield and gross pastoral product of 31 provincial-level administrative units in China from 2004 to 2019 were obtained from the National Bureau of Statistics of China. The temporal and geographical distribution of human brucellosis was displayed with Microsoft Excel and ArcMap software. The spatial autocorrelation and hotspot analysis was used to describe the association among different areas. Spatial panel model was constructed to explore the combined effects on the incidence of human brucellosis in China. RESULTS: A total of 569,016 cases of human brucellosis were reported in the 31 provincial-level administrative units in China from January 2004 to December 2019. Human brucellosis cases were concentrated between March and July, with a peak in May, showing a clear seasonal increase. The incidence of human brucellosis in China from 2004 to 2019 showed significant spatial correlations, and hotspot analysis indicated that the high incidence of human brucellosis was mainly in the northern China, particularly in Inner Mongolia, Shanxi, and Heilongjiang. The results from spatial panel model suggested that the inventory of cattle, the inventory of sheep, beef yield, mutton yield, wool yield, milk yield, gross pastoral product, average air temperature (the same month, 2-month lagged and 3-month lagged), average relative humidity (the same month) and season variability were significantly associated with human brucellosis incidence in China. CONCLUSIONS: The epidemic area of human brucellosis in China has been expanding and the spatial clustering has been observed. Inner Mongolia and adjacent provinces or autonomous regions are the high-risk areas of human brucellosis. The inventory of cattle and sheep, beef yield, mutton yield, wool yield, milk yield, gross pastoral product, average air temperature, average relative humidity and season variability played a significant role in the progression of human brucellosis. The present study strengthens the understanding of the relationship between socioeconomic, meteorological factors and the spatial heterogeneity of human brucellosis in China, through which 'One Health'-based strategies and countermeasures can be provided for the government to tackle the brucellosis menace.

Mapping Research Trends of Medications for Multidrug-Resistant Pulmonary Tuberculosis Based on the Co-Occurrence of Specific Semantic Types in the MeSH Tree: A Bibliometric and Visualization-Based Analysis of PubMed Literature (1966-2020).

Background: Before the COVID-19 pandemic, tuberculosis is the leading cause of death from a single infectious agent worldwide for the past 30 years. Progress in the control of tuberculosis has been undermined by the emergence of multidrug-resistant tuberculosis. The aim of the study is to reveal the trends of research on medications for multidrug-resistant pulmonary tuberculosis (MDR-PTB) through a novel method of bibliometrics that co-occurs specific semantic Medical Subject Headings (MeSH). Methods: PubMed was used to identify the original publications related to medications for MDR-PTB. An R package for text mining of PubMed, pubMR, was adopted to extract data and construct the co-occurrence matrix-specific semantic types. Biclustering analysis of high-frequency MeSH term co-occurrence matrix was performed by gCLUTO. Scientific knowledge maps were constructed by VOSviewer to create overlay visualization and density visualization. Burst detection was performed by CiteSpace to identify the future research hotspots. Results: Two hundred and eight substances (chemical, drug, protein) and 147 diseases related to MDR-PTB were extracted to form a specific semantic co-occurrence matrix. MeSH terms with frequency greater than or equal to six were selected to construct high-frequency co-occurrence matrix (42 × 20) of specific semantic types contains 42 substances and 20 diseases. Biclustering analysis divided the medications for MDR-PTB into five clusters and reflected the characteristics of drug composition. The overlay map indicated the average age gradients of 42 high-frequency drugs. Fifteen top keywords and 37 top terms with the strongest citation bursts were detected. Conclusion: This study evaluated the literatures related to MDR-PTB drug therapy, providing a co-occurrence matrix model based on the specific semantic types and a new attempt for text knowledge mining. Compared with the macro knowledge structure or hot spot analysis, this method may have a wider scope of application and a more in-depth degree of analysis.

Efficacy of endoluminal interventional therapy in diabetic peripheral arterial occlusive disease: a retrospective trial.

BACKGROUND: The purpose of this study was to assess the efficacy of interventional therapy for peripheral arterial occlusive disease and the difference between diabetic patients and non-diabetic patients. METHODS: 139 consecutive patients between September 2006 and September 2010 who underwent percutaneous lower extremity revascularization for arterial lesions were divided into diabetes group (n = 62) and non-diabetes group (n = 77). Before intervention, rest ankle brachial indexes and three dimensional computed tomography angiography from abdominal aorta to tiptoe were performed. The interventional treatments included angioplasty with or without stenting. The clinical outcomes included rest ankle-brachial indexes, primary patency rates, secondary patency rates and limb-salvage rates for 6-month, 12-month, 24-month and 36-month after treatment. The primary and secondary patency rates of all interventions and the limb-salvage rates of the patients are illustrated by Kaplan-Meier curves and compared by log-rank analysis. RESULTS: The interventional operation success rates were 98.4% (61/62) in diabetes group and 100% (77/77) in non-diabetes group. The re-interventional operation success rates were 85.7% (18/21) in diabetes group and 76.9% (20/26) in non-diabetes group. The mean value of ankle brachial indexes was significantly increased after intervention (0.397 ± 0.125 versus 0.779 ± 0.137, t = -25.780, P < 0.001) in diabetes group and (0.406 ± 0.101 versus 0.786 ± 0.121, t = -37.221, P < 0.001) in non-diabetes group. Perioperative 30-day mortality was 0%. Major complications included groin hematoma in 7.2%, and pseudoaneurysm formation 2.2%. In diabetes group, 6, 12, 24, and 36-month primary patency rates were 88.7% ± 4.0%, 62.3% ± 6.6%, 55.3% ± 7.0%, and 46.5% ± 7.5%; secondary patency rates were 93.5% ± 3.1%, 82.3% ± 5.1%, 70.8% ± 6.5%, and 65.7% ± 7%; limb-salvage rates were 95.2% ± 2.7%, 87.7% ± 4.4%, 85.5% ± 4.8%, and 81.9% ± 5.8%. In non-diabetes group, 6, 12, 24, and 36-month primary patency rates were 90.9% ± 3.3%, 71.8% ± 5.4%, 71.8% ± 5.4%, and 60.9% ± 6.2%; secondary patency rates were 96.1% ± 2.2%, 91.6% ± 3.3%, 82.7% ± 4.8%, and 71.8% ± 6.2%; limb-salvage rates were 97.4% ± 1.8%, 94.4% ± 2.7%, 90.6% ± 3.7%, and 83.1% ± 5.4%. The differences between two groups were not significant (P > 0.05). CONCLUSION: With a low risk of morbidity and mortality, the percutaneous revascularization accepted by patients does not affect ultimate necessary surgical revascularization and consequently should be considered as the preferred therapy for chronic lower extremity ischemia. The efficacy and prognosis of interventional therapy in diabetic patients is similar that in non-diabetic patients.

Infection rate of Eperythrozoon spp. in Chinese population: a systematic review and meta-analysis since the first Chinese case reported in 1991.

BACKGROUND: Eperythrozoonosis is an important animal health problem worldwide, it not only has a major impact on the economic viability, but also makes a significant impact on public health issues. The present systemic review intends to collate all relevant published data to assess the burden of Eperythrozoon infection in Chinese population and discuss the implications of these findings for public health policy. METHODS: A meta-analysis was conducted to review the published studies that reported Eperythrozoon spp. in Chinese population. Inclusion criteria comprised of the use of microscopic venous blood smear examination for Eperythrozoon detection and a detailed description of sampling techniques. RESULTS: Twenty-four cross-sectional studies with 52,433 participants and 14,951 positive cases, within the range of China mainland, were included in the present analysis. The infection rate of Eperythrozoon varied from 0 to 97.29% with geographical and seasonal variations, people with mild infection intensity contributed the major part (68.93%). The infection rates were highest in the children and adolescents group, significantly increased risk of Eperythrozoon infection was found among herdsmen. CONCLUSIONS: The current study raises awareness about the human eperythrozoonosis in China, which is a newly emerging zoonosis. The majority of Eperythrozoon infection intensity was asymptomatic mild infection. The infection rate of Eperythrozoon in Chinese population varied by geographical region, season, age and occupation. These factors need to be considered when conducting health education campaigns and comparing the surveillance results from different studies.

Introducer curving technique to reduce tilting of transfemoral Gunther Tulip IVC filter: in vitro study.

BACKGROUND: Severe tilting of Günther Tulip filter (GTF) may be associated with difficulty in retrieval. PURPOSE: To determine if an introducer curving technique of GTF can decrease the tilting degree of GTF in a caval model. MATERIAL AND METHODS: The model was constructed by placing Dacron grafts in bifurcated glass tubes. The study included three groups: Right Straight Group (G(1)), Left Straight Group (G(2)), and Left Curved Group (G(3)). In G(3), a 10-20° angle was curved on the metal introducer before insertion to decrease the angle between inferior vena cava axes and metal introducer (A(CM)). Before GTF was released, the distance between the caval right wall and the apical hook (D(CH1)), and A(CM) were measured. The tilt angle of GTF (A(CF)) was also measured. RESULTS: In G(1), GTF apex tended to center compared to G(2) (59% vs. 36%, P < 0.01). In G(3), GTF apex tended to center compared to G(2) (71% vs. 36%, P < 0.01). The differences of A(CF) between G(1) and G(2) (2.66 ± 1.80 vs. 4.13 ± 2.07, P < 0.01) and between G(2) and G(3) (4.13 ± 2.07 vs. 2.39 ± 1.79, P < 0.01) were statistically significant. There were significant positive correlations between A(CM) and A(CF), whereas significant negative correlations were detected between D(CH1) and A(CF) in each group. CONCLUSION: The oblique course of GTF delivery system relative to the axis of the cava causes filter tilt, and thus, curving the introducer prior to its introduction helps to reduce the filter tilt. We recommend a clinical study to determine whether the introducer curving technique improves filter centering and its retrievability.

The correlation between temperature and the incidence of COVID-19 in four first-tier cities of China: a time series study.

The COVID-19 outbreak emerged in Wuhan, China, and was declared a global pandemic in March 2020. This study aimed to explore the association of daily mean temperature with the daily counts of COVID-19 cases in Beijing, Shanghai, Guangzhou, and Shenzhen, China. Data on daily confirmed cases of COVID-19 and daily mean temperatures were retrieved from the 4 first-tier cities in China. Distributed lag nonlinear models (DLNMs) were used to assess the association between daily mean temperature and the daily cases of COVID-19 during the study period. After controlling for the imported risk index and long-term trends, the distributed lag nonlinear model showed that there were nonlinear and lag relationships. The daily cumulative relative risk decreased for every 1.0 °C change in temperature in Shanghai, Guangzhou, and Shenzhen. However, the cumulative relative risk increased with a daily mean temperature below - 3 °C in Beijing and then decreased. Moreover, the delayed effects of lower temperatures mostly occurred within 6-7 days of exposure. There was a negative correlation between the cumulative relative risk of COVID-19 incidence and temperature, especially when the temperature was higher than - 3 °C. The conclusions from this paper will help government and health regulators in these cities take prevention and protection measures to address the COVID-19 crisis and the possible collapse of the health system in the future.

Spatiotemporal cluster analysis of COVID-19 and its relationship with environmental factors at the city level in mainland China.

This study sought to identify the spatial, temporal, and spatiotemporal clusters of COVID-19 cases in 366 cities in mainland China with the highest risks and to explore the possible influencing factors of imported risks and environmental factors on the spatiotemporal aggregation, which would be useful to the design and implementation of critical preventative measures. The retrospective analysis of temporal, spatial, and spatiotemporal clustering of COVID-19 during the period (January 15 to February 25, 2020) was based on Kulldorff's time-space scanning statistics using the discrete Poisson probability model, and then the logistic regression model was used to evaluate the impact of imported risk and environmental factors on spatiotemporal aggregation. We found that the spatial distribution of COVID-19 cases was nonrandom; the Moran's I value ranged from 0.017 to 0.453 (P < 0.001). One most likely cluster and three secondary likely clusters were discovered in spatial cluster analysis. The period from February 2 to February 9, 2020, was identified as the most likely cluster in the temporal cluster analysis. One most likely cluster and seven secondary likely clusters were discovered in spatiotemporal cluster analysis. Imported risk, humidity, and inhalable particulate matter PM2.5 had a significant impact on temporal and spatial accumulation, and temperature and PM10 had a low correlation with the spatiotemporal aggregation of COVID-19. The information is useful for health departments to develop a better prevention strategy and potentially increase the effectiveness of public health interventions.

Nursing Scheduling Mode and Experience from the Medical Teams in Aiding Hubei Province During the COVID-19 Outbreak: A Systematic Scoping Review of 17 Studies.

INTRODUCTION: Due to COVID-19 outbreak, since January 24, 2020, national medical teams from across the country and the armed forces have been dispatched to aid Hubei. The present review was designed to timely summarize the existing frontline information about nursing scheduling mode with special focus on the length of shifts with the aim to contribute to improve the nurses' job satisfaction and the quality of nursing services. METHODS: Articles from Jan 2020 to October 2020 were retrieved from China National Knowledge Infrastructure, Wanfang Data and Weipu Information, with the terms "COVID-19", "designated hospital", "Hubei-assisted", "makeshift hospital", "nursing", "nursing shift", "whole-system takeover" and variations of these, in the title and abstract fields and the Boolean combinations of these words as the retrieval strategy. RESULTS: Seventeen journal articles have been included in the target field, from the nurses in aiding Hubei Province, four kinds of shift length, 2-hour (h), 3-h, 4-h and 6-h shift have been considered, the main nursing scheduling mode adopted in designated hospitals for COVID-19 patients was dynamic scheduling based on workload, flexible scheduling based on working hours, workload and the number of critically ill patients admitted, humanized scheduling based on the daily reported health status of the nurses, and professional-integrated scheduling according to the professional distribution of nurses on the basis of four-hour shift length, and in makeshift hospitals for mild patients, the scheduling mode was 6-h based correspondingly. CONCLUSION: The descriptive results of the present systematic review shed light on the challenges and practical solutions of nursing scheduling mode in the context of cross-regional medical assistance. Additionally, the present systematic review could provide the academic community of nurses, nurse managers and administrators with baseline information and scientific productions from the content's points of view in the target field.

Improving the precision of modeling the incidence of hemorrhagic fever with renal syndrome in mainland China with an ensemble machine learning approach.

OBJECTIVE: Hemorrhagic fever with renal syndrome (HFRS), one of the main public health concerns in mainland China, is a group of clinically similar diseases caused by hantaviruses. Statistical approaches have always been leveraged to forecast the future incidence rates of certain infectious diseases to effectively control their prevalence and outbreak potential. Compared to the use of one base model, model stacking can often produce better forecasting results. In this study, we fitted the monthly reported cases of HFRS in mainland China with a model stacking approach and compared its forecasting performance with those of five base models. METHOD: We fitted the monthly reported cases of HFRS ranging from January 2004 to June 2019 in mainland China with an autoregressive integrated moving average (ARIMA) model; the Holt-Winter (HW) method, seasonal decomposition of the time series by LOESS (STL); a neural network autoregressive (NNAR) model; and an exponential smoothing state space model with a Box-Cox transformation; ARMA errors; and trend and seasonal components (TBATS), and we combined the forecasting results with the inverse rank approach. The forecasting performance was estimated based on several accuracy criteria for model prediction, including the mean absolute percentage error (MAPE), root-mean-squared error (RMSE) and mean absolute error (MAE). RESULT: There was a slight downward trend and obvious seasonal periodicity inherent in the time series data for HFRS in mainland China. The model stacking method was selected as the best approach with the best performance in terms of both fitting (RMSE 128.19, MAE 85.63, MAPE 8.18) and prediction (RMSE 151.86, MAE 118.28, MAPE 13.16). CONCLUSION: The results showed that model stacking by using the optimal mean forecasting weight of the five abovementioned models achieved the best performance in terms of predicting HFRS one year into the future. This study has corroborated the conclusion that model stacking is an easy way to enhance prediction accuracy when modeling HFRS.

[The effect of simvastatin on alveolar epithelial cells in cigarette smoking-induced emphysema].

OBJECTIVE: to explore the effect of simvastatin on alveolar epithelial cells and the expression of vascular endothelial growth factor (VEGF) in cigarette smoking-induced emphysema in rats. METHODS: twenty-four, 12-week-old healthy male and female Wistar rats were randomly divided into 4 groups of 6 each: a control (W) group, a smoking (Sm) group, a simvastatin (St) group, and a smoking-simvastatin (SmSt) group. The rats were simultaneously fed, and kept in individual cages for 16 weeks. The VEGF level in lung tissue and bronchoalveolar lavage fluid (BALF) of each group was measured by ELISA. The expression of VEGF mRNA was determined by RT-PCR. The expressions of VEGF and proliferating cell nuclear antigen (PCNA) were determined by two-step immunohistochemistry assay. One-way ANOVA and LSD-t test were used for statistical analysis. RESULTS: the percentage of PCNA-positively stained alveolar epithelial cells was significantly higher in the SmSt group [(10.3 ± 2.0)%] than in the Sm group [(4.8 ± 0.8)%]. The levels of VEGF in BALF and lung tissue homogenate of the SmSt group [(187 ± 15) ng/L and (6782 ± 50) ng/L] were similar to the W group [(200 ± 20) ng/L and (7558 ± 330) ng/L], but were significantly higher than that in the Sm group [(71 ± 16) ng/L and (4149 ± 110) ng/L]. VEGF expression in alveolar and bronchial epithelial cells of rats in the SmSt group [(67.7 ± 5.0)% and (49.0 ± 3.0)%], was similar to the W group [(68.3 ± 3.3)% and (51.3 ± 2.9)%]. But the level of VEGF expression was significantly increased as compared to that in the Sm group [(27.0 ± 5.9)% and (16.3 ± 2.7)%]. SmSt group vs Sm group t = 1.117 - 12.001, all P < 0.01. CONCLUSIONS: simvastatin ameliorated the development of cigarette smoke-induced COPD in rats, partly by promoting alveolar epithelial cell proliferation and up-regulating the expression of VEGF.

A prognostic gene model of immune cell infiltration in diffuse large B-cell lymphoma.

BACKGROUND: Immune cells in the tumor microenvironment are an important prognostic indicator in diffuse large B-cell lymphoma (DLBCL). However, information on the heterogeneity and risk stratification of these cells is limited. We sought to develop a novel immune model to evaluate the prognostic intra-tumoral immune landscape of patients with DLBCL. METHODS: The ESTIMATE and CIBERSORT algorithms were used to estimate the numbers of 22 infiltrating immune cells based on the gene expression profiles of 229 patients with DLBCL who were recruited from a public database. The least absolute shrinkage and selection operator (Lasso) penalized regression analyses and nomogram model were used to construct and evaluate the prognostic immunoscore (PIS) model for overall survival prediction. An immune gene prognostic score (IGPS) was generated by Gene Set Enrichment Analysis (GSEA) and Cox regression analysis was and validated in an independent NCBI GEO dataset (GSE10846). RESULTS: A higher proportion of activated natural killer cells was associated with a poor outcome. A total of five immune cells were selected in the Lasso model and DLBCL patients with high PIS showed a poor prognosis (hazard ratio (HR) 2.16; 95% CI [1.33-3.50]; P = 0.002). Differences in immunoscores and their related outcomes were attributed to eight specific immune genes involved in the cytokine-cytokine receptor interaction and chemokine signaling pathways. The IGPS based on a weighted formula of eight genes is an independent prognostic factor (HR: 2.14, 95% CI [1.40-3.28]), with high specificity and sensitivity in the validation dataset. CONCLUSIONS: Our findings showed that a PIS model based on immune cells is associated with the prognosis of DLBCL. We developed a novel immune-related gene-signature model associated with the PIS model and enhanced the prognostic functionality for the prediction of overall survival in patients with DLBCL.

Global Research Output and Theme Trends on Climate Change and Infectious Diseases: A Restrospective Bibliometric and Co-Word Biclustering Investigation of Papers Indexed in PubMed (1999-2018).

Climate change is a challenge for the sustainable development of an international economy and society. The impact of climate change on infectious diseases has been regarded as one of the most urgent research topics. In this paper, an analysis of the bibliometrics, co-word biclustering, and strategic diagram was performed to evaluate global scientific production, hotspots, and developing trends regarding climate change and infectious diseases, based on the data of two decades (1999-2008 and 2009-2018) from PubMed. According to the search strategy and inclusion criteria, a total of 1443 publications were found on the topic of climate change and infectious diseases. There has been increasing research productivity in this field, which has been supported by a wide range of subject categories. The top highly-frequent major MeSH (medical subject headings)/subheading combination terms could be divided into four clusters for the first decade and five for the second decade using a biclustering analysis. At present, some significant public health challenges (global health, and travel and tropical climate, etc.) are at the center of the whole target research network. In the last ten years, "Statistical model", "Diarrhea", "Dengue", "Ecosystem and biodiversity", and "Zoonoses" have been considered as emerging hotspots, but they still need more attention for further development.