TLT-1 Promotes Platelet-Monocyte Aggregate Formation to Induce IL-10-Producing B Cells in Tuberculosis.

The immunoregulation of platelets and platelet-monocyte aggregates (PMAs) is increasingly recognized, but it roles in tuberculosis (TB) remain to be elucidated. In this study, we found that CD14+CD41+ PMAs were increased in peripheral blood of patients with active TB. CD14+CD41+ PMAs highly expressed triggering receptors expressed on myeloid cells (TREMs)-like transcript-1 (TLT-1), P-selectin (CD62P), and CD40L. Our in vitro study found that platelets from patients with active TB aggregate with monocytes to induce IL-1ß and IL-6 production by monocytes. Importantly, we identified that TLT-1 was required for formation of PMAs. The potential TLT-1 ligand was expressed and increased on CD14+ monocytes of patients with TB determined by using TLT-1 fusion protein (TLT-1 Fc). Blocking of ligand-TLT-1 interaction with TLT-1 Fc reduced PMA formation and IL-1ß and IL-6 production by monocytes. Further results demonstrated that PMAs induced IL-10 production by B cells (B10) dependent on IL-1ß, IL-6, and CD40L signals in a coculture system. Moreover, TLT-1 Fc treatment suppressed B10 polarization via blocking PMA formation. Taking all of these data together, we elucidated that TLT-1 promoted PMA-mediated B10 polarization through enhancing IL-1ß, IL-6, and CD40L origin from PMAs, which may provide potential targeting strategies for TB disease treatment.

TARM-1 Is Critical for Macrophage Activation and Th1 Response in Mycobacterium tuberculosis Infection.

T cell-interacting activating receptor on myeloid cells 1 (TARM-1) is a novel leukocyte receptor expressed in neutrophils and macrophages. It plays an important role in proinflammatory response in acute bacterial infection, but its immunomodulatory effects on chronic Mycobacterium tuberculosis infections remain unclear. TARM-1 expression was significantly upregulated on CD14high monocytes from patients with active pulmonary tuberculosis (TB) as compared that on cells from patients with latent TB or from healthy control subjects. Small interfering RNA knockdown of TARM-1 reduced expression levels of proinflammatory cytokines IL-12, IL-18, IL-1ß, and IL-8 in M. tuberculosis-infected macrophages, as well as that of HLA-DR and costimulatory molecules CD83, CD86, and CD40. Moreover, TARM-1 enhanced phagocytosis and intracellular killing of M. tuberculosis through upregulating reactive oxygen species. In an in vitro monocyte and T cell coculture system, blockade of TARM-1 activity by TARM-1 blocking peptide suppressed CD4+ T cell activation and proliferation. Finally, administration of TARM-1 blocking peptide in a mouse model of M. tuberculosis infection increased bacterial load and lung pathology, which was associated with decreased macrophage activation and IFN-γ production by T cell. Taken together, these results, to our knowledge, demonstrate a novel immune protective role of TARM-1 in M. tuberculosis infection and provide a potential therapeutic target for TB disease.

Epidemiology and genetic diversity of group A rotavirus in acute diarrhea patients in pre-vaccination era in southwest China.

Group A rotavirus (RVA) is one of the leading cause of acute diarrhea worldwide, the RVA-related disease burden and the genotypes of RVA is important reference to introduce RVA variance to national immunisation programmes, 1,121 diarrhea cases and 319 healthy controls were recruited from four sentinel hospital outpatient from July 2014 to June 2015. The prevalence of RVA was 244 (21.8%) in gastroenteritis cases and in 12 (3.8%) in healthy controls across all age group (OR = 7.12, 95%CI = 3.93-12.89); the detection rate of RVA in diarrhea patients under 5 years was more higher than in diarrhea cases over 5 years (26.1%, 222/850; 8.1%, 22/271, respectively, P = 0.000). Of 244 RVA strains isolated from acute diarrhea cases, G9 (66.4%) was predominant G genotype, followed by G3 (18.7%), G1 (8.9%), and G1G3 (3.8%); P[8] was the overwhelming prevalence P genotype, followed by P[4] (4.7%); G9P[8] (54.9%) was most common G and P Combination, followed by G3P[8] (17.6%) and G1[8] (8.6%). The conclusion of the study was important to provide reference for introducing the RVA vaccine to prevent and control RVA-associated disease burden. J. Med. Virol. 89:71-78, 2017. © 2016 Wiley Periodicals, Inc.

Emergence of human caliciviruses among diarrhea cases in southwest China.

BACKGROUND: Acute diarrhea is one of the most serious problems in global public health that causes considerable morbidity and mortality worldwide. Human caliciviruses (HuCV) including norovirus (NoV, genogroup GI and GII) and sapovirus (SaV), is a leading cause of acute sporadic diarrhea in individuals across all age groups. However, few studies had been conducted clarifying the characteristics of HuCV in diarrhea cases across all age groups in China. Our study was aimed at assessing the HuCV-related diarrhea burden and NoV genotypes distribution in southwest China. METHODS: The study was conducted in four hospitals in Kunming city, Yunnan province, from June 2014 to July 2015. Stool specimens were collected from 1,121 diarrhea cases and 319 healthy controls in outpatient departments. Reverse transcription polymerase chain reaction (RT-PCR) was used to detect NoV (GI, GII) and SaV. Sequencing was applied to confirm the three viral infections and phylogenetic analysis was performed to determine their genotypes. A structured questionnaire was used to record the demographic information and clinical symptoms of subjects. RESULTS: HuCV was detected at an 11.0 % infection rate in 1,121 diarrhea cases and at 3.4 % rate in 319 non-diarrhea subjects (p < 0.0001, OR = 3.5, 95 % CI 1.8-6.5). The prevalence of the NoV genogroup GII and genotype GII.4 in diarrhea cases was significantly higher than that found in healthy controls (p < 0.0001, p = 0.018, respectively). NoV GII (n = 118, 10.5 %) was the most common HuCV subtype in diarrhea cases, followed by SaV (n = 3, 0.3 %) and NoV GI (n = 2, 0.2 %). Of 118 NoV GII strains isolated from diarrhea patients. GII.4 (n = 55, 46.6 %) was the predominant strain, followed by GII.3 (n = 28, 23.7 %), GII.12 (n = 25, 21.2 %), GII.17 (n = 8, 6.8 %), and GII.5 (n = 2, 1.7 %). Of the 55 GII.4 strains, the GII.4 Sydney 2012 variant had absolutely predominant prevalence (n = 52, 94.5 %), followed by the NoV GII.4-2006b variant (n = 3, 5.5 %). The GII.4 Orleans 2009 variant was not found in diarrhea cases of the study. CONCLUSIONS: NoV GII was the major genogroup and GII.4 was the most predominant strain detected in diarrhea patients. The GII.17 is an emergent variant in sporadic diarrhea and might become the predominant strain in diarrhea cases in the near future. Rapid, accurate detection kits need to be developed to help us find and treat NoV-associated diarrhea in clinical settings in a timely manner.

Advancing Construction 3D Printing with Predictive Interlayer Bonding Strength: A Stacking Model Paradigm.

To enhance the quality stability of 3D printing concrete, this study introduces a novel machine learning (ML) model based on a stacking strategy for the first time. The model aims to predict the interlayer bonding strength (IBS) of 3D printing concrete. The base models incorporate SVR, KNN, and GPR, and subsequently, these models are stacked to create a robust stacking model. Results from 10-fold cross-validation and statistical performance evaluations reveal that, compared to the base models, the stacking model exhibits superior performance in predicting the IBS of 3D printing concrete, with the R2 value increasing from 0.91 to 0.96. This underscores the efficacy of the developed stacking model in significantly improving prediction accuracy, thereby facilitating the advancement of scaled-up production in 3D printing concrete.

Interpretable machine learning for predicting chronic kidney disease progression risk.

Objective: Chronic kidney disease (CKD) poses a major global health burden. Early CKD risk prediction enables timely interventions, but conventional models have limited accuracy. Machine learning (ML) enhances prediction, but interpretability is needed to support clinical usage with both in diagnostic and decision-making. Methods: A cohort of 491 patients with clinical data was collected for this study. The dataset was randomly split into an 80% training set and a 20% testing set. To achieve the first objective, we developed four ML algorithms (logistic regression, random forests, neural networks, and eXtreme Gradient Boosting (XGBoost)) to classify patients into two classes-those who progressed to CKD stages 3-5 during follow-up (positive class) and those who did not (negative class). For the classification task, the area under the receiver operating characteristic curve (AUC-ROC) was used to evaluate model performance in discriminating between the two classes. For survival analysis, Cox proportional hazards regression (COX) and random survival forests (RSFs) were employed to predict CKD progression, and the concordance index (C-index) and integrated Brier score were used for model evaluation. Furthermore, variable importance, partial dependence plots, and restrict cubic splines were used to interpret the models' results. Results: XGBOOST demonstrated the best predictive performance for CKD progression in the classification task, with an AUC-ROC of 0.867 (95% confidence interval (CI): 0.728-0.100), outperforming the other ML algorithms. In survival analysis, RSF showed slightly better discrimination and calibration on the test set compared to COX, indicating better generalization to new data. Variable importance analysis identified estimated glomerular filtration rate, age, and creatinine as the most important predictors for CKD survival analysis. Further analysis revealed non-linear associations between age and CKD progression, suggesting higher risks in patients aged 52-55 and 65-66 years. The association between cholesterol levels and CKD progression was also non-linear, with lower risks observed when cholesterol levels were in the range of 5.8-6.4 mmol/L. Conclusions: Our study demonstrated the effectiveness of interpretable ML models for predicting CKD progression. The comparison between COX and RSF highlighted the advantages of ML in survival analysis, particularly in handling non-linearity and high-dimensional data. By leveraging interpretable ML for unraveling risk factor relationships, contrasting predictive techniques, and exposing non-linear associations, this study significantly advances CKD risk prediction to enable enhanced clinical decision-making.

Efficacy of acupuncture treatment for breast cancer-related insomnia: study protocol for a multicenter randomized controlled trial.

Background: Insomnia is one of the most common symptoms among breast cancer patients, which can be present throughout all stages of breast cancer. As a non-pharmacological alternative treatment, acupuncture has been suggested to improve sleep situations in patients with cancer suffering from insomnia. However, there is a lack of well-designed, high-quality clinical evidence regarding the efficacy of acupuncture in the treatment of breast cancer-related insomnia. This study is conducted to evaluate the efficacy and safety of acupuncture treatment for breast cancer-related insomnia. Methods: This study was designed as a multicenter, randomized, sham-controlled clinical trial. A total of 264 eligible patients with breast cancer-related insomnia will be randomized into an acupuncture group and a sham acupuncture group in a 1:1 ratio. In the trial, patients in the acupuncture and sham acupuncture groups will receive 12 sessions over a consecutive 4-week period. The primary outcome will be the treatment response rate of Insomnia Severity Index (ISI) at week 4; secondary outcomes include treatment remission rate of ISI, Sleep Efficiency (SE) obtained by the use of Sleep diary, treatment response rate of ISI at 8th and 16th weeks of follow-up, the mean changes of ISI, Generalized Anxiety Disorder Scale (GAD-7), Patient Health Questionnaire-9 (PHQ-9), Quality of Life Questionnaire - Core 30 (QLQ-C30), sleep parameters recorded in Actigraphy and weekly usage of remedial drugs. Adverse events will be recorded throughout the study. All analyses will be based on the ITT principle and performed with SAS 9.4 statistical software. Discussion: This trial will evaluate the clinical efficacy and safety of acupuncture for breast cancer-related insomnia. If proven effective, acupuncture will provide an effective option for patients with breast cancer-related insomnia, which will play a positive role in helping patients reduce their use of sleeping medications. Clinical trial registration: ClinicalTrials.gov, identifier NCT05510700.

Efficacy and Safety of Bufei Jiedu Granules in Treating Multidrug-Resistant Pulmonary Tuberculosis: A Multi-center, Double-Blinded and Randomized Controlled Trial.

OBJECTIVE: To assess the efficacy and safety of Bufei Jiedu (BFJD) ranules as adjuvant therapy for patients with multidrug-resistant pulmonary tuberculosis (MDR-PTB). METHODS: A large-scale, multi-center, double-blinded, and randomized controlled trial was conducted in 18 sentinel hospitals in China from December 2012 to December 2016. A total of 312 MDR-PTB patients were randomly assigned to BFJD Granules or placebo groups (1:1) using a stratified randomization method, which both received the long-course chemotherapy regimen for 18 months (6 Am-Lfx-P-Z-Pto, 12 Lfx-P-Z-Pto). Meanwhile, patients in both groups also received BFJD Granules or placebo twice a day for a total of 18 months, respectively. The primary outcome was cure rate. The secondary outcomes included time to sputum-culture conversion, changes in lung cavities and quality of life (QoL) of patients. Adverse reactions were monitored during and after the trial. RESULTS: A total of 216 cases completed the trial, 111 in the BFJD Granules group and 105 in the placebo group. BFJD Granules, as an adjuvant treatment, increased the cure rate by 13.6% at the end of treatment, compared with the placebo (58.4% vs. 44.8%, P=0.02), and accelerated the median time to sputum-culture conversion (5 months vs. 11 months). The cavity closure rate of the BFJD Granules group (50.6%, 43/85) was higher than that of the placebo group (32.1%, 26/81; P=0.02) in patients who completed the treatment. At the end of the intensive treatment, according to the 36-item Short Form, the BFJD Granules significantly improved physical functioning, general health, and vitality of patients relative to the placebo group (all P<0.01). Overall, the death rates in the two groups were not significantly different; 5.1% (8/156) in the BFJD Granules group and 2.6% (4/156) in the placebo group. CONCLUSIONS: Supplementing BFJD Granules with the long-course chemotherapy regimen significantly increased the cure rate and cavity closure rates, and rapidly improved QoL of patients with MDR-PTB (Registration No. ChiCTR-TRC-12002850).

Genetically predicted circulating levels of cytokines and the risk of depression: a bidirectional Mendelian-randomization study.

Objective: Inflammatory cytokines disturbance is the main result of immune dysregulation, which is widely described in major depressive disorder (MDD). However, the potential causal relationship between these two factors has not been discovered. Therefore, the purpose of this study was to investigate the causal relationship between inflammatory cytokines and MDD risk by using the two-sample Mendelian randomization (MR) analysis. Method: Two genetic instruments obtained from publicly available gene profile data were utilized for the analysis. We obtained the genetic variation data of 41 inflammatory cytokines from genome-wide association studies (GWAS) meta-analysis of 8293 individuals of Finnish descent. The MDD data, including 135,458 MDD cases and 344,901 controls, were obtained from the Psychiatric Genomics Consortium Database. For the Mendelian randomization (MR) estimation, several methods were employed, namely, MR-Egger regression, inverse-variance weighted (IVW), weighted median, and MR-Pleiotropy RESidual Sum and Outlier (MR-PRESSO) methods. Result: A causal relationship was identified between the genetically proxied levels of Interleukin (IL) -18, IL-1ß, and Regulated upon activation normal T cell expressed and secreted (RANTES) and the risk of MDD (OR = 0.968, 95%CI = 0.938, 0.998, p = 0.036; OR = 0.875, 95%CI = 0.787, 0.971, p = 0.012; OR = 0.947, 95%CI = 0.902, 0.995, p = 0.03; respectively). However, our Mendelian randomization (MR) estimates provided no causality of MDD on inflammatory cytokines. Conclusion: Our study elucidates the connection between inflammatory cytokines and MDD by using MR analysis, thereby enhancing our comprehension of the potential mechanisms. By identifying these associations, our findings hold substantial implications for the development of more effective treatments aimed at improving patient outcomes. However, further investigation is required to fully comprehend the exact biological mechanisms involved.

Elucidation of the underlying mechanism of Hua-ban decoction in alleviating acute lung injury by an integrative approach of network pharmacology and experimental verification.

The pathogenic hyper-inflammatory response has been regarded as the major cause of the severity and death related to acute lung injury (ALI). Hua-ban decoction (HBD) is a classical prescription in traditional Chinese medicine (TCM). It has been extensively used to treat inflammatory diseases; however, its bioactive components and therapeutic mechanisms remain unclear. Here, we established a lipopolysaccharide (LPS)-induced ALI model that presents a hyperinflammatory process to explore the pharmaco-dynamic effect and underlying molecular mechanism of HBD on ALI. In vivo, we confirmed that in LPS-induced ALI mice, HBD improved pulmonary injury by via down-regulating the expression of proinflammatory cytokines, including IL-6, TNF-α, and macrophage infiltration, as well as macrophage M1 polarization. Moreover, in vitro experiments in LPS-stimulated macrophages demonstrated that the potential bioactive compounds of HBD inhibited the secretion of IL-6 and TNF-α. Mechanically, the data revealed that HBD treatment of LPS-induced ALI acted via NF-κB pathway, which regulated macrophage M1 polarization. Additionally, two major HBD compounds, i.e., quercetin and kaempferol, showed a high binding affinity with p65 and IkBα. In conclusion, the data obtained in this study demonstrated the therapeutic effects of HBD, which indicates the possibility for the development of HBD as a potential treatment for ALI.

Efficacy of traditional Chinese medicine on shortening the negative conversion time of SARS-CoV-2 ribonucleic acid in patients with mild COVID-19: a retrospective cohort study.

Background: The holistic view of the 'The unity of man and nature' promotes the development and application of traditional Chinese medicine (TCM). Despite the absence of modern pharmacological therapies with robust efficacy against coronavirus disease 2019 (COVID-19), TCM has exhibited potential utility for treating the disease in clinical practice. Methods: A retrospective cohort study was conducted to investigate the therapeutic effect of TCM treatment intensity (TCMTI) in patients with mild COVID-19. A total of 6120 laboratory-confirmed patients with mild COVID-19 were recruited from temporary isolation facilities. The primary outcome measure was severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) ribonucleic acid conversion time. In addition, restricted cubic spline models were employed to elucidate nonlinear relationships. Results: The median age (range) of the study participants was 43.0 (2.0-75.0) years, with a median hospitalization duration of 9.7 (4.1-22.5) days. The median time for achieving SARS-CoV-2 ribonucleic acid negativity was 6.67 days. The restricted cubic spline models revealed a remarkable nonlinear association between TCMTI and the time-to-ribonucleic acid negativity. After adjusting for potential confounders, the high TCMTI group exhibited a markedly shorter median time to SARS-CoV-2 ribonucleic acid negativity and reduced hospitalization duration (P < 0.001) than the low TCMTI group. Moreover, the mean time to achieve SARS-CoV-2 ribonucleic acid negativity was shortened by 1.909 days (P < 0.001) in the high-TCMTI group compared to the low-TCMTI group. Conclusion: This study suggests that early initiation and intensified use of TCM may accelerate the time required to achieve SARS-CoV-2 ribonucleic acid negativity in patients with COVID-19, bearing considerable implications for public health.

Reduced SARS-CoV-2 infection risk is associated with the use of Seven-Flavor Herb Tea: A multi-center observational study in Shanghai, China.

OBJECTIVE: Omicron, a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variant, is responsible for numerous infections in China. This study investigates the association between the use of Seven-Flavor Herb Tea (SFHT) and the risk of SARS-CoV-2 infection to develop precise and differentiated strategies for control of the coronavirus disease 2019 (COVID-19). METHODS: This case-control study was conducted at shelter hospitals and quarantine hotels in China. A total of 5348 laboratory-confirmed COVID-19 patients were enrolled between April 1 and May 31, 2022, while 2190 uninfected individuals served as healthy controls. Structured questionnaires were used to collect data on demographics, underlying diseases, vaccination status, and use of SFHT. Patients were propensity-score-matched using 1:1 nearest-neighbor matching of the logit of the propensity score. Subsequently, a conditional logistic regression model was used for data analysis. RESULTS: Overall, 7538 eligible subjects were recruited, with an average age of [45.54 ± 16.94] years. The age of COVID-19 patients was significantly higher than that of uninfected individuals ([48.25 ± 17.48] years vs [38.92 ± 13.41] years; t = 22.437, P < 0.001). A total of 2190 COVID-19 cases were matched with uninfected individuals at a 1:1 ratio. The use of SFHT (odds ratio = 0.753, 95% confidence interval: 0.692, 0.820) was associated with a lower risk of SARS-CoV-2 infection compared to untreated individuals. CONCLUSION: Our findings suggest that taking SFHT reduces the risk of SARS-CoV-2 infection. This is a useful study in the larger picture of COVID-19 management, but data from large-sample multi-center, randomized clinical trial are warranted to confirm the finding. Please cite this article as: Zhang SX, Chen XX, Zheng Y, Cai BH, Shi W, Ru M, Li H, Zhang DD, Tian Y, Chen YL. Reduced SARS-CoV-2 infection risk is associated with the use of Seven-Flavor Herb Tea: A multi-center observational study in Shanghai, China. J Integr Med. 2023; 21(4):369-376.

Public health implications of Yersinia enterocolitica investigation: an ecological modeling and molecular epidemiology study.

BACKGROUND: Yersinia enterocolitica has been sporadically recovered from animals, foods, and human clinical samples in various regions of Ningxia, China. However, the ecological and molecular characteristics of Y. enterocolitica, as well as public health concerns about infection in the Ningxia Hui Autonomous Region, remain unclear. This study aims to analyze the ecological and molecular epidemiological characteristics of Y. enterocolitis in order to inform the public health intervention strategies for the contains of related diseases. METHODS: A total of 270 samples were collected for isolation [animals (n = 208), food (n = 49), and patients (n = 13)], then suspect colonies were isolated and identified by the API20E biochemical identification system, serological tests, biotyping tests, and 16S rRNA-PCR. Then, we used an ecological epidemiological approach combined with machine learning algorithms (general linear model, random forest model, and eXtreme Gradient Boosting) to explore the associations between ecological factors and the pathogenicity of Y. enterocolitis. Furthermore, average nucleotide identity (ANI) estimation, single nucleotide polymorphism (SNP), and core gene multilocus sequence typing (cgMLST) were applied to characterize the molecular profile of isolates based on whole genome sequencing. The statistical test used single-factor analysis, Chi-square tests, t-tests/ANOVA-tests, Wilcoxon rank-sum tests, and Kruskal-Wallis tests. RESULTS: A total of 270 isolates of Yersinia were identified from poultry and livestock (n = 191), food (n = 49), diarrhoea patients (n = 13), rats (n = 15), and hamsters (n = 2). The detection rates of samples from different hosts were statistically different (χ2 = 22.636, P < 0.001). According to the relatedness clustering results, 270 isolates were divided into 12 species, and Y. enterocolitica (n = 187) is a predominated species. Pathogenic isolates made up 52.4% (98/187), while non-pathogenic isolates made up 47.6% (89/187). Temperature and precipitation were strongly associated with the pathogenicity of the isolates (P < 0.001). The random forest (RF) prediction model showed the best performance. The prediction result shows a high risk of pathogenicity Y. enterocolitica was located in the northern, northwestern, and southern of the Ningxia Hui Autonomous Region. The Y. enterocolitica isolates were classified into 54 sequence types (STs) and 125 cgMLST types (CTs), with 4/O:3 being the dominant bioserotype in Ningxia. The dominant STs and dominant CTs of pathogenic isolates in Ningxia were ST429 and HC100_2571, respectively. CONCLUSIONS: The data indicated geographical variations in the distribution of STs and CTs of Y. enterocolitica isolates in Ningxia. Our work offered the first evidence that the pathogenicity of isolates was directly related to fluctuations in temperature and precipitation of the environment. CgMLST typing strategies showed that the isolates were transmitted to the population via pigs and food. Therefore, strengthening health surveillance on pig farms in high-risk areas and focusing on testing food of pig origin are optional strategies to prevent disease outbreaks.

Synergistic Effects of Rotavirus and Co-Infecting Viral Enteric Pathogens on Diarrheal Disease - Guangzhou City, Guangdong Province, China, 2019.

What is already known about this topic?: Diarrhea represents a substantial public health issue, contributing globally to a high number of pediatric medical consultations, hospital admissions, and mortality rates. What is added by this report?: An increase in diarrheal frequency serves as a critical benchmark for evaluating severity. The predominant pathogens associated with pediatric diarrhea are rotavirus and norovirus, with co-infections exerting a notable compounding effect that leads to more severe diarrhea. What are the implications for public health practice?: Implementing sensitive diagnostic techniques and comprehensive monitoring is paramount in identifying co-infections. Such strategies can provide physicians with critical insights into disease progression, thus considerably reducing the burden of diarrhea.

Assessing the association between the circulating levels of inflammatory cytokines and the risk of tuberculosis: A bidirectional two-sample mendelian randomization study.

BACKGROUND: Numerous observational studies have previously reported an association between inflammatory cytokines and tuberculosis (TB). However, the causal relationship between these factors remains unclear. Consequently, we conducted two-sample Mendelian randomization (MR) analyses to ascertain the causal link between levels of inflammatory cytokines and the risk of TB. METHODS: Single nucleotide polymorphisms (SNPs) robustly associated with the cytokines, located in or close to their coding gene. SNP was obtained from genome-wide association studies (GWAS) of 8293 individuals of Finnish. TB data was obtained from the UK Biobank, which included 46,293 individuals of European ancestry (comprising 2277 TB cases and 46,056 controls). Two-sample, bi-directional MR analyses using inverse-variance weighted (IVW) method as the primary analysis. Followed by comprehensive sensitivity analyses to validate the robustness of results. RESULT: The study showed that the causal relationship between circulating levels of interleukin (IL)-7 and risk of TB (odds ratio [OR] = 1.001, 95% confidence intervals [CIs]: 1.000, 1.003. p = 0.047). No causal associations were observed between other influencing factors and the occurrence of TB. Furthermore, the analysis revealed that TB infection exhibited negative causal associations with macrophage inflammatory protein 1 alpha ([MIP-1α], OR = 0.007, 95% CI: 0.000, 0.192. p = 0.004), IL-2 (OR = 0.014, 95% CI: 0.010, 0.427. p = 0.014), interleukin-2 receptor alpha chain([IL-2rα], OR = 0.019, 95% CI: 0.001, 0.525. p = 0.019) and basic fibroblast growth factor ([bFGF], OR = 0.066, 95% CI: 0.006, 0.700. p = 0.024). CONCLUSION: The study has illuminated the causal link between inflammatory cytokines and TB, thereby enhancing our comprehension of the potential mechanisms underlying TB pathogenesis. This discovery offers promising avenues for the identification of novel therapeutic targets in TB treatment. These insights may ultimately pave the way for more effective treatment approaches, thereby improving patient outcomes.

Impact factors of Blastocystis hominis infection in persons living with human immunodeficiency virus: a large-scale, multi-center observational study from China.

BACKGROUND: Blastocystis hominis (Bh) is zoonotic parasitic pathogen with a high prevalent globally, causing opportunistic infections and diarrhea disease. Human immunodeficiency virus (HIV) infection disrupts the immune system by depleting CD4+ T lymphocyte (CD4+ T) cell counts, thereby increasing Bh infection risk among persons living with HIV (PLWH). However, the precise association between Bh infection risk and HIV-related biological markers and treatment processes remains poorly understood. Hence, the purpose of the study was to explore the association between Bh infection risk and CD4+ T cell counts, HIV viral load (VL), and duration of interruption in antiviral therapy among PLWH. METHODS: A large-scale multi-center cross-sectional study was conducted in China from June 2020 to December 2022. The genetic presence of Bh in fecal samples was detected by real-time fluorescence quantitative polymerase chain reaction, the CD4+ T cell counts in venous blood was measured using flowcytometry, and the HIV VL in serum was quantified using fluorescence-based instruments. Restricted cubic spline (RCS) was applied to assess the non-linear association between Bh infection risk and CD4+ T cell counts, HIV VL, and duration of interruption in highly active antiretroviral therapy (HARRT). RESULTS: A total of 1245 PLWH were enrolled in the study, the average age of PLWH was 43 years [interquartile range (IQR): 33, 52], with 452 (36.3%) being female, 50.4% (n = 628) had no immunosuppression (CD4+ T cell counts > 500 cells/µl), and 78.1% (n = 972) achieved full virological suppression (HIV VL < 50 copies/ml). Approximately 10.5% (n = 131) of PLWH had interruption. The prevalence of Bh was found to be 4.9% [95% confidence interval (CI): 3.8-6.4%] among PLWH. Significant nonlinear associations were observed between the Bh infection risk and CD4+ T cell counts (Pfor nonlinearity < 0.001, L-shaped), HIV VL (Pfor nonlinearity < 0.001, inverted U-shaped), and duration of interruption in HARRT (Pfor nonlinearity < 0.001, inverted U-shaped). CONCLUSIONS: The study revealed that VL was a better predictor of Bh infection than CD4+ T cell counts. It is crucial to consider the simultaneous surveillance of HIV VL and CD4+ T cell counts in PLWH in the regions with high level of socioeconomic development. The integrated approach can offer more comprehensive and accurate understanding in the aspects of Bh infection and other opportunistic infections, the efficacy of therapeutic drugs, and the assessment of preventive and control strategies.

Multi-modal deep learning based on multi-dimensional and multi-level temporal data can enhance the prognostic prediction for multi-drug resistant pulmonary tuberculosis patients.

Despite the advent of new diagnostics, drugs and regimens, multi-drug resistant pulmonary tuberculosis (MDR-PTB) remains a global health threat. It has a long treatment cycle, low cure rate and heavy disease burden. Factors such as demographics, disease characteristics, lung imaging, biomarkers, therapeutic schedule and adherence to medications are associated with MDR-PTB prognosis. However, thus far, the majority of existing studies have focused on predicting treatment outcomes through static single-scale or low dimensional information. Hence, multi-modal deep learning based on dynamic data for multiple dimensions can provide a deeper understanding of personalized treatment plans to aid in the clinical management of patients.

The rapid and efficient strategy for SARS-CoV-2 Omicron transmission control: analysis of outbreaks at the city level.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron (B.1.1.529) variant is highly transmissible with potential immune escape. Hence, control measures are continuously being optimized to guard against large-scale coronavirus disease 2019 (COVID-19) outbreaks. This study aimed to explore the relationship between the intensity of control measures in response to different SARS-CoV-2 variants and the degree of outbreak control at city level. METHODS: A retrospective study was conducted in 49 cities with COVID-19 outbreaks between January 2020 and June 2022. Epidemiological data on COVID-19 were extracted from the National Health Commission, People's Republic of China, and the population flow data were sourced from the Baidu migration data provided by the Baidu platform. Outbreak control was quantified by calculating the degree of infection growth and the time-varying reproduction number ([Formula: see text]). The intensity of the outbreak response was quantified by calculating the reduction in population mobility during the outbreak period. Correlation and regression analyses of the intensity of the control measures and the degree of outbreak control for the Omicron variant and non-Omicron mutants were conducted, respectively. RESULTS: Overall, 65 outbreaks occurred in 49 cities in China from January 2020 to June 2022. Of them, 66.2% were Omicron outbreaks and 33.8% were non-Omicron outbreaks. The intensity of the control measures was positively correlated with the degree of outbreak control (r = 0.351, P = 0.03). The degree of reduction in population mobility was negatively correlated with the Rt value (r = - 0.612, P < 0.01). Therefore, under the same control measure intensity, the number of new daily Omicron infections was 6.04 times higher than those attributed to non-Omicron variants, and the Rt value of Omicron outbreaks was 2.6 times higher than that of non-Omicron variants. In addition, the duration of non-Omicron variant outbreaks was shorter than that of the outbreaks caused by the Omicron variant (23.0 ± 10.7, 32.9 ± 16.3, t = 2.243, P = 0.031). CONCLUSIONS: Greater intensity of control measures was associated with more effective outbreak control. Thus, in response to the Omicron variant, the management to restrict population movement should be used to control its spread quickly, especially in the case of community transmission occurs widely. Faster than is needed for non-Omicron variants, and decisive control measures should be imposed and dynamically adjusted in accordance with the evolving epidemic situation.

Predictors for Treatment Outcomes in Patients with Multi-drug Resistant Tuberculosis - China, 2018-2020.

What is already known about this topic?: Multi-drug resistant tuberculosis (MDR-TB) is a critical global public health problem. What is added by this report?: Sputum cultures and lung images show a strong association with treatment outcomes, serving as a multi-dimensional approach to identify MDR-TB patients with poor outcomes. What are the implications for public health practice?: The results imply that funds and policy investments should be increased by early monitoring of MDR-TB patients, especially regarding imaging and sputum bacterium. By informing physicians on changes to the therapeutic schedule, treatment outcomes can be improved.

Soaring Asymptomatic Infected Individuals Bring About Barriers and Difficulties for Interruption of COVID-19 Prevalence in China.

Background: Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become a global pandemic, which has caused unprecedented damage to human health and life. The present study aimed to carry out and discover asymptomatic infected individuals in Shenzhen, China. The data will provide the control measures to stop COVID-19 prevalence. Methods: The study was a retrospective review of medical records from 462 confirmed patients with COVID-19 and 45 asymptomatic infected individuals in Shenzhen from January 19 to April 30, 2020; this is a retrospective, observational multicenter study. Results: A total of 462 confirmed cases were diagnosed in Shenzhen from January 19 to April 30, 2020. The cohort included 423 domestic cases (91.56%, 95% confidence interval [CI]: 88.67-93.76) and 39 (8.44%, 95% CI: 6.24-11.33) imported cases from other countries. Moreover, a total of 45 asymptomatic infections were found, encompassing 31 (68.89%, 95% CI: 54.34-80.47) local infections and 14 (31.11%, 95% CI: 19.53-45.66) individuals imported from other countries. The proportion of asymptomatic infected persons in Shenzhen is continuously increasing (Z = 13.19, p < 0.0001). The total number of local asymptomatic infections was more than that in other provinces (χ2 = 118.83, p < 0.0001). The proportion of asymptomatic infected individuals among cases imported from other countries was higher than the domestic cases (χ2 = 22.51, p < 0.0001, odds ratio = 4.90, 95% CI: 2.40-9.98). Conclusions: The proportion of asymptomatic infection is increasing. Hence, development and application of the diagnosis method with high sensitivity and specificity play a critical role in reducing COVID-19 global epidemics.