Identification of the shared hub gene signatures and molecular mechanisms between HIV-1 and pulmonary arterial hypertension.

The close link between HIV-1 infection and the occurrence of pulmonary arterial hypertension (PAH). However, the underlying molecular mechanisms of their interrelation remain unclear. The microarray data of HIV-1 and PAH were downloaded from GEO database. We utilized WGCNA to identify shared genes between HIV-1 and PAH, followed by conducting GO and pathway enrichment analyses. Subsequently, differentially genes analysis was performed using external validation datasets to further filter hub genes. Immunoinfiltration analysis was performed using CIBERSORT. Finally, hub gene expression was validated using scRNA-seq data. We identified 109 shared genes through WGCNA, primarily enriched in type I interferon (IFN) pathways. By taking the intersection of WGCNA important module genes and DEGs, ISG15 and IFI27 were identified as pivotal hub genes. Immunoinfiltration analysis and scRNA-seq results indicated the significant role of monocytes in the shared molecular mechanisms of HIV-1 and PAH. In summary, our study illustrated the possible mechanism of PAH secondary to HIV-1 and showed that the heightened IFN response in HIV-1 might be a crucial susceptibility factor for PAH, with monocytes being pivotal cells involved in the type I IFN response pathway. This provides potential new insights for further investigating the molecular mechanisms connecting HIV-1 and PAH.

Predicting pulmonary tuberculosis incidence in China using Baidu search index: an ARIMAX model approach.

BACKGROUND: Existing researches have established a correlation between internet search data and the epidemics of numerous infectious diseases. This study aims to develop a prediction model to explore the relationship between the Pulmonary Tuberculosis (PTB) epidemic trend in China and the Baidu search index. METHODS: Collect the number of new cases of PTB in China from January 2011 to August 2022. Use Spearman rank correlation and interaction analysis to identify Baidu keywords related to PTB and construct a PTB comprehensive search index. Evaluate the predictive performance of autoregressive integrated moving average (ARIMA) and ARIMA with explanatory variable (ARIMAX) models for the number of PTB cases. RESULTS: Incidence of PTB had shown a fluctuating downward trend. The Spearman rank correlation coefficient between the PTB comprehensive search index and its incidence was 0.834 (P < 0.001). The ARIMA model had an AIC value of 2804.41, and the MAPE value was 13.19%. The ARIMAX model incorporating the Baidu index demonstrated an AIC value of 2761.58 and a MAPE value of 5.33%. CONCLUSIONS: The ARIMAX model is superior to ARIMA in terms of fitting and predicting accuracy. Additionally, the use of Baidu Index has proven to be effective in predicting cases of PTB.

Early Warning and Prediction of Scarlet Fever in China Using the Baidu Search Index and Autoregressive Integrated Moving Average With Explanatory Variable (ARIMAX) Model: Time Series Analysis.

BACKGROUND: Internet-derived data and the autoregressive integrated moving average (ARIMA) and ARIMA with explanatory variable (ARIMAX) models are extensively used for infectious disease surveillance. However, the effectiveness of the Baidu search index (BSI) in predicting the incidence of scarlet fever remains uncertain. OBJECTIVE: Our objective was to investigate whether a low-cost BSI monitoring system could potentially function as a valuable complement to traditional scarlet fever surveillance in China. METHODS: ARIMA and ARIMAX models were developed to predict the incidence of scarlet fever in China using data from the National Health Commission of the People's Republic of China between January 2011 and August 2022. The procedures included establishing a keyword database, keyword selection and filtering through Spearman rank correlation and cross-correlation analyses, construction of the scarlet fever comprehensive search index (CSI), modeling with the training sets, predicting with the testing sets, and comparing the prediction performances. RESULTS: The average monthly incidence of scarlet fever was 4462.17 (SD 3011.75) cases, and annual incidence exhibited an upward trend until 2019. The keyword database contained 52 keywords, but only 6 highly relevant ones were selected for modeling. A high Spearman rank correlation was observed between the scarlet fever reported cases and the scarlet fever CSI (rs=0.881). We developed the ARIMA(4,0,0)(0,1,2)(12) model, and the ARIMA(4,0,0)(0,1,2)(12) + CSI (Lag=0) and ARIMAX(1,0,2)(2,0,0)(12) models were combined with the BSI. The 3 models had a good fit and passed the residuals Ljung-Box test. The ARIMA(4,0,0)(0,1,2)(12), ARIMA(4,0,0)(0,1,2)(12) + CSI (Lag=0), and ARIMAX(1,0,2)(2,0,0)(12) models demonstrated favorable predictive capabilities, with mean absolute errors of 1692.16 (95% CI 584.88-2799.44), 1067.89 (95% CI 402.02-1733.76), and 639.75 (95% CI 188.12-1091.38), respectively; root mean squared errors of 2036.92 (95% CI 929.64-3144.20), 1224.92 (95% CI 559.04-1890.79), and 830.80 (95% CI 379.17-1282.43), respectively; and mean absolute percentage errors of 4.33% (95% CI 0.54%-8.13%), 3.36% (95% CI -0.24% to 6.96%), and 2.16% (95% CI -0.69% to 5.00%), respectively. The ARIMAX models outperformed the ARIMA models and had better prediction performances with smaller values. CONCLUSIONS: This study demonstrated that the BSI can be used for the early warning and prediction of scarlet fever, serving as a valuable supplement to traditional surveillance systems.

Universal Precise Growth of 2D Transition-Metal Dichalcogenides in Vertical Direction.

Two-dimensional transition-metal dichalcogenides (TMDs) have been one of the hottest focus of materials due to the most beneficial electronic and optoelectronic properties. Up to now, one of the big challenges is the synthesis of large-area layer-number-controlled single-crystal films. However, the poor understanding of the growth mechanism seriously hampers the progress of the scalable production of TMDs with precisely tunable thickness at an atomic scale. Here, the growth mechanisms in the vertical direction were systemically studied based on the density functional theory (DFT) calculation and an advanced chemical vapor deposition (CVD) growth. As a result, the U-type relation of the TMD layer number to the ratio of metal/chalcogenide is confirmed by the capability of ultrafine tuning of the experimental conditions in the CVD growth. In addition, high-quality uniform monolayer, bilayer, trilayer, and multilayer TMDs in a large area (8 cm2) were efficiently synthesized by applying this modified CVD. Although bilayer TMDs can be obtained at both high and low ratios of metal/chalcogenide based on the suggested mechanism, they demonstrate significantly different optical and electronic transport properties. The modified CVD strategy and the proposed mechanism should be helpful for synthesizing and large-area thickness-controlled TMDs and understanding their growth mechanism and could be used in integrated electronics and optoelectronics.

Barriers to community-based drug dependence treatment: implications for police roles, collaborations and performance indicators.

INTRODUCTION: Worldwide, people who use drugs (PWUD) are among the populations at highest risk for HIV infection. In China, PWUD are primarily sentenced to compulsory detainment centres, in which access to healthcare, including HIV treatment and prevention services, is limited or non-existent. In 2008, China's 2008 Anti-Drug Law encouraged the development and use of community-based drug dependence rehabilitation, yet there is limited evidence evaluating the efficacy and challenges of this model in China. In this study, we explore these challenges and describe how cooperation between law enforcement and health departments can meet the needs of PWUD. METHODS: In 2015, we conducted semi-structured, in-depth interviews with all four staff members and 16 clients of the Ping An Centre No. 1 for community-based drug treatment, three local police officers and three officials from the local Centre for Disease Control. Interviews explored obstacles in implementing community-based drug dependence treatment and efforts to resolve these difficulties. Transcripts were coded and analyzed with qualitative data analysis software (MAXQDA 11). RESULTS: We identified three challenges to community-based drug treatment at the Ping An Centre No. 1: (1) suboptimal coordination among parties involved, (2) a divergence in attitudes towards PWUD and harm reduction between law enforcement and health officials and (3) conflicting performance targets for police and health officials that undermine the shared goal of treatment. We also identified the take-home methadone maintenance treatment model at the Ping An Centre No. 1 as an example of an early successful collaboration between the police, the health department and PWUD. CONCLUSIONS: To overcome barriers to effective community-based drug treatment, we recommend aligning the goals of law enforcement and public health agencies towards health-based performance indicators. Furthermore, tensions between PWUD and police need to be addressed and trust between them fostered, using community-based treatment centres as mediators. The preliminary success of the take-home methadone maintenance treatment pilot can serve as an example of how collaboration with the police and other government agencies can meet the needs of PWUD and contribute to the success of community-based treatment.