Mendelian randomization analyses in ocular disease: a powerful approach to causal inference with human genetic data.

Ophthalmic epidemiology is concerned with the prevalence, distribution and other factors relating to human eye disease. While observational studies cannot avoid confounding factors from interventions, human eye composition and structure are unique, thus, eye disease pathogenesis, which greatly impairs quality of life and visual health, remains to be fully explored. Notwithstanding, inheritance has had a vital role in ophthalmic disease. Mendelian randomization (MR) is an emerging method that uses genetic variations as instrumental variables (IVs) to avoid confounders and reverse causality issues; it reveals causal relationships between exposure and a range of eyes disorders. Thus far, many MR studies have identified potentially causal associations between lifestyles or biological exposures and eye diseases, thus providing opportunities for further mechanistic research, and interventional development. However, MR results/data must be interpreted based on comprehensive evidence, whereas MR applications in ophthalmic epidemiology have some limitations worth exploring. Here, we review key principles, assumptions and MR methods, summarise contemporary evidence from MR studies on eye disease and provide new ideas uncovering aetiology in ophthalmology.

A probabilistic model for co-occurrence analysis in bibliometrics.

The co-occurrence analysis of Medical Subject Heading (MeSH) terms extracted from the PubMed database is popularly used in bibliometrics. Practically for making the result interpretable, it is necessary to apply a certain filter procedure of co-occurrence matrix for removing the low-frequency items due to their low representativeness. Unfortunately, there is rare research referring to determine a critical threshold to remove the noise of co-occurrence matrix. Here, we proposed a probabilistic model for co-occurrence analysis that can provide statistical inferences about whether the paired items co-occur randomly. With help of this model, the dimensionality of co-occurrence matrix could be reduced according to the selected threshold. The conceptual model framework, simulation and practical applications are illustrated in the manuscript. Further details (including all reproducible codes) can be downloaded from the project website: https://github.com/xizhou/co-occurrence-analysis.git.

Defining matrix Gla protein expression in the Dunkin-Hartley guinea pig model of spontaneous osteoarthritis.

BACKGROUND: Matrix Gla (γ-carboxyglutamate) protein (MGP) is considered a strong inhibitor of ectopic calcification, and it has been associated with OA severity, although not conclusively. We utilized male Dunkin-Hartley (DH) guinea pigs to investigate the expression of MGP throughout aging and disease pathogenesis in a spontaneous model. METHOD: Twenty-five male DH guinea pigs were obtained and nurtured to several timepoints, and then randomly and equally divided by age into five subgroups (1-, 3-, 6-, 9-, and 12-months, with the 1-month group as the reference group). DH guinea pigs in each group were euthanized at the designated month-age and the left or right medial tibial plateaus cartilages were randomly excised. OA severity was described by modified Mankin Score (MMS) at microscopy (Safranin O/Fast Green stain). Proteomic evaluation using isobaric tags for relative and absolute quantification (iTRAQ) was performed to validate the age-related changes in the MGP profiles, and immunohistochemistry (IHC) methods were applied for semi-quantitative determination of MGP expression in articular cartilage. RESULTS: The histopathologic findings validated the increasing severity of cartilage degeneration with age in the DH guinea pigs. The MMS showed significant, stepwise (every adjacent comparison P < 0.05) disease progression with month-age. The iTRAQ indicated that MGP levels increased significantly with advancing age (P < 0.05), as supported by the IHC result (P < 0.05). CONCLUSION: Increased expression of MGP in male DH guinea pigs was present throughout aging and disease progression and may be link to increased OA severity. Further studies are needed to investigate and confirm the association between MGP levels and OA severity.

The effects of dehiscence and fenestration before orthodontic treatment on external apical root resorption in maxillary incisors.

INTRODUCTION: The objective of this study was to investigate the effects of dehiscence and fenestration on external apical root resorption (EARR) in maxillary incisors. METHODS: Seventy-eight patients were selected for this study. We set dehiscence, fenestration, sex, extraction, or nonextraction, tooth position, initial age, and duration of treatment as independent variables and EARR as the dependent variable. General statistical descriptions for these variables were made by mean, standard deviation and occurrence rates, etc. To make the data visualization and find more information, 2 heat maps were made. Generalized estimation equation analysis was performed to determine associations between EARR and independent variables. RESULTS: The occurrence rates of dehiscence and fenestration in maxillary incisors were 14.77% and 10.74%, respectively. The average value of EARR was 1.09 ± 0.87 mm in this study. Dehiscence, tooth position, extraction, initial age, and duration had significant correlations with EARR. The ratio of exponent B was 1:1.643 for dehiscence and nondehiscence, whereas fenestration and sex had no significant association with EARR. CONCLUSIONS: The amount of EARR at maxillary incisors in patients with dehiscence before orthodontic treatment might be less than that in patients without it, and different incisors might have different contributions to it. However, the low value of exponent B for dehiscence meant that there might be other unknown factors that were involved in this study.

Thymoquinone ameliorates the PM2.5-induced lung injury in rats.

BACKGROUND: This study aims to explore the effect of thymoquinone (TQ) on particulate matter 2.5 (PM2.5)-induced lung injury. METHODS: The PM2.5 sample was provided by Shenyang Environment Monitor Central Station. Lung injury was established by intratracheal instillation PM2.5 (7.5 mg/kg) followed by TQ treatment (20 and 40 mg/kg) for 14 d in rats. Hematoxylin and eosin (HE) and Evans blue dye (EBD) staining were detected on lung tissues. ELISA, real-time PCR, western blotting and TUNEL assays were also performed. RESULTS: The data showed that TQ diminished lung injury and EBD accumulation. The number of macrophages, neutrophils, eosinophils, and lymphocytes was ameliorated after TQ treatment. In addition, TQ suppressed the inflammation reaction parameters (interleukin-1ß and -6, IL-1ß and IL-6; tumor necrosis factor-α, TNF-α) and oxidative stress in PM2.5-induced lung injury. The levels of nuclear factor erythroid 2-related factor 2 (Nrf2) and heme oxygenase (HO-1) were increased due to the treatment of TQ. The number of TUNEL-positive cells was prominently reduced in TQ-treated rats compared with that in PM2.5 group. Intratracheal instillation PM2.5 activated autophagy, whilst TQ blocked it in lung. CONCLUSIONS: Taken together, this study provides the first in vivo evidence that TQ suppresses inflammation, oxidative stress, apoptosis, and autophagy in PM2.5-induced lung injury.

Evaluation of palatal support tissues for placement of orthodontic mini-implants in mouth breathers with high-narrow palates versus nose breathers with normal palates: a retrospective study.

OBJECTIVES: The aim of this study was to compare the palatal total support tissues (TSTs) and bone support tissues (BSTs) at 5-mm paramedian section to the midsagittal suture between mouth breathers with high-narrow palates and nose breathers with normal palates and confirm the practicability and limitation on superimposition of lateral cephalograms and plaster models for orthodontic mini-implant (OMI) implantation in these patients. MATERIAL AND METHODS: The sample consisted of 27 mouth breathers with high-narrow palates (study group (SG)) and 27 nose breathers with normal palates (control group (CG)). Upper digital dental models were superimposed with corresponding cone beam computed tomography (CBCT) images; then, TSTs and BSTs vertical to the curvature of the palatal mucosa were measured on the 5-mm paramedian section to the midsagittal suture. The measuring sites were the third ruga (R) and the sites anterior and posterior to R at 2-mm interval (A2, A4, A6, and A8; P2, P4, P6, and P8) along the palatal mucosa outline. TSTs and BSTs were also measured on the superimposition of lateral cephalograms and plaster models, and the site with the largest TST value in each patient was recorded. Descriptive statistics, independent-samples t test, and hierarchical clustering heat map were used for statistical analysis. RESULTS: The greatest average values of TSTs and BSTs in SG were 12.24 ± 2.63 mm and 9.59 ± 2.36 mm at P2 site, and those in CG were 12.96 ± 2.39 mm and 10.56 ± 2.38 mm at R site, respectively. The average values of both TSTs and BSTs in SG were less than those in CG at all insertion sites. Significant differences (P < 0.05) were found at A4, A6, and R for TSTs and at R and P4 for BSTs. P2 and R were clustered together for both TSTs and BSTs by the cluster analysis on heat map in both SG and CG. In both groups, only one patient from SG was found to have the insertion site with the largest TST value on 2D superimposition located in the blue area on the heat map, where the measurement values of TSTs were less than 8.5 mm and those of BSTs were less than 5 mm. CONCLUSIONS: Mouth breathers with high-narrow palates may have less palatal support tissues than nose breathers with normal palates at 5-mm paramedian section to the midsagittal suture of palate. The site a little posterior to R is more suitable for OMI implantation in mouth breathers. Two-dimensional superimposition of lateral cephalograms and plaster models can provide relatively effective assessment for the site choice of OMI implantation in both mouth breathers with high-narrow palates and nose breathers with normal palates. CLINICAL RELEVANCE: Three-dimensional superimposition of CBCT data and digital dental model can provide accurate information for palatal OMI implantation. Meanwhile, 2D superimposition of lateral cephalograms and plaster models can be used for assessing the implantation sites at 5-mm paramedian section to the midsagittal suture of palates in mouth breathers under most conditions even those who have less palatal support tissues.

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.

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.

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.

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.

Tracheal sounds accurately detect apnea in patients recovering from anesthesia.

Apnea should be monitored continuously in the post anesthesia care unit (PACU) to avoid serious complications. It has been confirmed that tracheal sounds can be used to detect apnea during sedation in healthy subjects, but the performance of this acoustic method has not been evaluated in patients with frequent apnea events in the PACU. Tracheal sounds were acquired from the patients in the PACU using a microphone encased in a plastic bell. Concurrently, a processed nasal pressure signal was used as a reference standard to identify real respiratory events. The logarithm of the tracheal sound variance (log-var) was used to detect apnea, and the results were compared to the reference method. Sensitivity, specificity, positive likelihood ratios (PLR), and negative likelihood ratios (NLR) were calculated. One hundred and twenty-one patients aged 55.5 ± 13.2 years (mean ± SD) with a body mass index of 24.6 ± 3.7 kg/m2 were included in data analysis. The total monitoring time was 52.6 h. Thirty-four patients experienced 236 events of apnea lasting for a total of 122.2 min. The log-var apnea detection algorithm detected apnea with 92% sensitivity, 98% specificity, 46 PLR and 0.08 NLR. The performance of apnea detection in the PACU using the log-var tracheal sounds method proved to be reliable and accurate. Tracheal sounds could be used to minimize the potential risks from apnea in PACU patients.

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.

Trends of reported human brucellosis cases in mainland China from 2007 to 2017: an exponential smoothing time series analysis.

BACKGROUND: The main objective of this study was to describe the temporal distribution of monthly reported human brucellosis cases in mainland China and develop an appropriate time series model for short-term extrapolation forecast. METHODS: Surveillance data of the monthly reported human brucellosis cases occurring from April 1, 2007, to March 31, 2017, in mainland China were obtained. The spectrum analysis was first adopted to find the cyclic and seasonal features, the existence of the seasonality and trend was determined by exponential smoothing method and the seasonal-trend decomposition. The candidate models of exponential smoothing included the additive model and multiplicative model; R2 was selected as the indicator for the selection of candidate model, and the stability of the model was verified by adjusting the training data and test data set. Finally, the extrapolations of monthly incident human brucellosis cases in 2017 were made. RESULTS: From April 1, 2007, to March 31, 2017, a total of 435,108 cases of Brucellosis occurred in mainland China were reported, with an average of 3626 cases per month and a standard deviation of 1834 cases. The R2 of the exponential smoothing method that based on additive model increased steadily from 0.927 to 0.949 with the increase of the data volume. Ten of 12 actual values fell in the confidence interval of predicted value. CONCLUSIONS: Human brucellosis cases peaked during the months from March to August in mainland China, with clear seasonality. The exponential smoothing based on the additive model method could be effectively used in the time series analysis of human brucellosis in China. Control methods, such as vaccination, quarantine, elimination of infected animals, and good hygiene within the production cycle, should be strengthened with paying more attention to the seasonality. Further research is warranted to explore the drivers behind the seasonality.

[Primary study of respiratory monitoring based on breath sounds].

It is nonlinear relationship between breath sounds and respiratory flow rate, thus breath sounds might be a new solution for respiratory monitoring. The envelope of the breath sounds was created firstly. And the linear relationship between the logarithm of envelope and the respiratory flow rate was proved. Then model parameters were derived from every subject using regression analysis. Finally, using these parameters estimated respiratory flow rate was achieved by the logarithm of envelope with 14.9% error. Therefore, respiratory flow rate estimation and respiration monitoring based on breath sounds are feasible.

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.

Assessing the impact of COVID-19 non-pharmaceutical interventions and relaxation policies on Class B respiratory infectious diseases transmission in China.

This study investigates the incidence of Class B respiratory infectious diseases (RIDs) in China under the Coronavirus disease 2019 (COVID-19) epidemic and examines variations post-epidemic, following the relaxation of non-pharmaceutical interventions (NPIs). Two-stage evaluation was used in our study. In the first stage evaluation, we established counterfactual models for the pre-COVID-19 period to estimate expected incidences of Class B RIDs without the onset of the epidemic. In the second stage evaluation, we constructed seasonal autoregressive integrated moving average intervention (SARIMA-Intervention) models to evaluate the impact on the Class B RIDs after NPIs aimed at COVID-19 pandemic were relaxed. The counterfactual model in the first stage evaluation suggested average annual increases of 10.015%, 78.019%, 70.439%, and 67.799% for tuberculosis, scarlet fever, measles, and pertussis respectively, had the epidemic not occurred. In the second stage evaluation, the total relative reduction in 2023 of tuberculosis, scarlet fever, measles and pertussis were - 35.209%, - 59.184%, - 4.481%, and - 9.943% respectively. The actual incidence declined significantly in the first stage evaluation. However, the results of the second stage evaluation indicated that a rebound occurred in four Class B RIDs after the relaxation of NPIs; all of these showed a negative total relative reduction rate.

Exploring the influence of COVID-19 on the spread of hand, foot, and mouth disease with an automatic machine learning prediction model.

Hand, foot, and mouth disease (HFMD) is an important public health problem and has received concern worldwide. Moreover, the coronavirus disease 2019 (COVID-19) epidemic also increases the difficulty of understanding and predicting the prevalence of HFMD. The purpose is to prove the usability and applicability of the automatic machine learning (Auto-ML) algorithm in predicting the epidemic trend of HFMD and to explore the influence of COVID-19 on the spread of HFMD. The AutoML algorithm and the autoregressive integrated moving average (ARIMA) model were applied to construct and validate models, based on the monthly incidence numbers of HFMD and meteorological factors from May 2008 to December 2019 in Henan province, China. A total of four models were established, among which the Auto-ML model with meteorological factors had minimum RMSE and MAE in both the model constructing phase and forecasting phase (training set: RMSE = 1424.40 and MAE = 812.55; test set: RMSE = 2107.83, MAE = 1494.41), so this model has the best performance. The optimal model was used to further predict the incidence numbers of HFMD in 2020 and then compared with the reported cases. And, for analysis, 2020 was divided into two periods. The predicted incidence numbers followed the same trend as the reported cases of HFMD before the COVID-19 outbreak; while after the COVID-19 outbreak, the reported cases have been greatly reduced than expected, with an average of only about 103 cases per month, and the incidence peak has also been delayed, which has led to significant changes in the seasonality of HFMD. Overall, the AutoML algorithm is an applicable and ideal method to predict the epidemic trend of the HFMD. Furthermore, it was found that the countermeasures of COVID-19 have a certain influence on suppressing the spread of HFMD during the period of COVID-19. The findings are helpful to health administrative departments.

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).

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.