Lyme disease (LD) is a common arthropod-borne inflammatory disorder prevalent in the northern hemisphere. LD is caused by a spirochete named Borrelia burgdorferi s.l., which is transmitted to humans by ticks. Climate, environment, and other factors affect land use; recreational-behavior changes affect human contact with infected ticks. Studies in Europe and North America have looked at these aspects, but studies in Asia have not. We searched databases to identify all relevant abstracts published until March 2021. A meta-analysis was undertaken using the standard methods and procedures established by the Cochrane Collaboration. Ninety-one articles were included in our meta-analysis. The literature search identified data from nine countries (China, Japan, Malaysia, Mongolia, Pakistan, Russia Siberia region, South Korea, Thailand and Turkey). Furthermore, 53,003 ticks from six genera (Amblyomma, Dermacentor, Haemaphysalis, Hyalomma, Ixodes and Rhipicephalus) were inspected for infection with B. burgdorferi. The pooled prevalence was 11.1% (95% CI = 8.3–14.2%). Among the nine countries, China had the most studies (56) and Malaysia had the highest infection rate (46.2%). Most infected ticks were from the genera Ixodes and Haemaphysalis. Ticks of the genus Ixodes had the highest infection rate (16.9%). Obvious heterogeneity was noted in our meta-analysis. We analyzed the heterogeneity with regard to countries, genera, time points, and detection methods. This study suggests that Ixodes, Haemaphysalis and Dermacentor may be the most common tike of B. burgdorferi-positive in Asia. The highest proportion of ticks infected by B. burgdorferi were from the genus Ixodes. This meta-analysis is the first attempt to explain the B. burgdorferi infection of hard-body ticks in Asia. The infection rate for each country and infection rate of different tick genera were analyzed: there were large differences between them. The literature is concentrates mainly on East Asia, and data are limited. Our study can provide a reference for a more comprehensive and in-depth investigation of ticks in Asia infected by B. burgdorferi spirochetes.

Coronavirus disease-2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has become a global pandemic and has severely affected socio-economic conditions and people’s life. The lung is the major target organ infected and (seriously) damaged by SARS-CoV-2, so a comprehensive understanding of the virus and the mechanism of infection are the first choices to overcome COVID-19. Recent studies have demonstrated the enormous value of human organoids as platforms for virological research, making them an ideal tool for researching host–pathogen interactions. In this study, the various existing lung organoids and their identification biomarkers and applications are summarized. At the same time, the seven coronaviruses currently capable of infecting humans are outlined. Finally, a detailed summary of existing studies on SARS-CoV-2 using lung organoids is provided and includes pathogenesis, drug development, and precision treatment. This review highlights the value of lung organoids in studying SARS-CoV-2 infection, bringing hope that research will alleviate COVID-19-associated lung infections.

The aim of this study was to evaluate the diagnostic accuracy of the IGRA, TST, and TBST by combining diagnostic test accuracy (DTA) analysis and network meta-analysis (NMA) to increase the reliability and accuracy of diagnostic methods and promote the eradication of TB. An electronic search of the PubMed, Embase, and Cochrane databases was conducted, from the date of establishment to September 30, 2024. Data were synthesized with frequentist random-effects network meta-analyses, a single-group rate meta-analysis algorithm, and a bivariate mixed-effects logistic regression model. Summarized receiver operating characteristic curves and Fagan nomograms were used to assess diagnostic accuracy and clinical utility. Deeks’ funnel plots and the Quality Assessment of Diagnostic Accuracy Studies 2 tools were used to assess publication bias and risk of bias. Sources of heterogeneity were investigated using subgroup analyses. Forty-nine studies were identified. The diagnostic performance of the three diagnostic methods for TB infection is summarized as follows: the pooled sensitivity was 77.9% (95% confidence interval [CI], 0.69–0.856), and the pooled specificity was 80.3% (95% CI, 0.75–0.86). The sensitivity and specificity of the IGRA were 82.1% (95% CI, 0.78–0.86) and 81.1% (95% CI, 0.75–0.86), respectively, both higher than the TST. However, the TBST exhibited the highest specificity, at 98.5% (95% CI, 0.96–1.00), with a sensitivity of 78.7% (95% CI, 0.68–0.88), which was between that of the IGRA and TST. Subgroup analysis found that population categories and reference standards, among other factors, may be attributed to heterogeneity. In addition, the TST and IGRA add-on TBST can significantly improve diagnostic accuracy. In our study, the IGRA showed higher sensitivity, whereas the TBST showed higher specificity. Interestingly, under certain conditions, TST add-on TBST and IGRA add-on TBST showed better accuracy than TST and IGRA alone and could provide more effective guidance for clinical practice (PROSPERO CRD42023420136).

Observational studies indicate that variations in peripheral blood mononuclear cell (PBMC) subsets are associated with an increased risk of pulmonary tuberculosis (PTB) and coronavirus disease 2019 (COVID-19), but causal validation is lacking. Here, we combined single-cell expression quantitative trait locus (sc-eQTL) and two-sample mendelian randomization (MR) analyses to elucidate the causal relationship between PBMC subsets and the occurrence of PTB and COVID-19 and verified by RT-qPCR. We observed an increase in the CD4⁺ Effective Memory T Cell (CD4⁺ T_EM) cluster in both PTB and COVID-19 patients according to the single-cell transcriptional landscape of PBMC. Through MR analysis using an inverse variance weighted (IVW) method, we found strong evidence of positive correlations between CD4⁺ T_EM cell markers (GBP2, TRAV1-2, and ODF2L) and PTB, and between markers (LAG3 and SLFN5) and COVID-19, especially highlighted by lead eQTL-SNPs of GBP2 (rs2256752, p = 4.76321 × 10⁻¹⁵) and LAG3 (rs67706382, p = 6.16× 10⁻¹⁶). Similar results were observed in validation sets, and no pleiotropy was detected in sensitivity analyses including weighted median (WM), MR-Egger, MR-pleiotropy residual sum and outlier, and leave-one-out analyses (all p > 0.05). We visualized the colocalization of marker-eQTLs and markers of PTB and COVID-19 genome-wide association study (GWAS) associations. Based on CellChat analyses, monocytes communicated predominantly with CD4⁺ T_EM cells positively expressing PTB markers (GBP2, TRAV1-2, and ODF2L) and COVID-19 markers (LAG3 and SLFN5) in both PTB and COVID-19. Our data suggest a causal effect between two key CD4⁺ T_EM cell markers (GBP2 and LAG3) and the risk for PTB and COVID-19 infection. Our findings provide novel insights into the biological mechanism for PTB and COVID-19 infection, but future single-cell studies are necessary to further enhance understanding of this find.

Background Both Borrelia burgdorferi ( Bb ) and Anaplasma phagocytophilum (Ap) can infect humans and animals through tick-borne transmission, resulting in zoonosis. Under certain conditions, human infection can lead to Lyme disease (LD) and human granulocytosis (HGA), whereas infection in animals can cause various acute and non-specific symptoms. The combination of Bb and Ap has been reported to increase the disease severity in infected animals. In this systematic review and meta-analysis, we investigated the global diversity of Bb and Ap coinfection in animals and their prevalence and distribution regarding spatial and species ecoepidemiology. Methods We queried PubMed, Web of Science, Embase, and the Cochrane Library for original studies on Bb and Ap coinfection. We assessed the rate of Bb and Ap in all included articles by single-group meta-analysis and subgroup analyses. We evaluated publication bias using a combination of funnel plots, Egger's tests, and Begg's tests, and conducted risk of bias assessment using the SYRCLE tool. Results Our search retrieved 40 articles, with eight involving 8419 infected animals meeting our inclusion criteria. The SYRCLE bias risk assessment indicated that most of the included studies were of high quality. Forest maps showed that the combined Bb and Ap infection rate in animals worldwide was 5.5% (95% confidence interval (CI) = 2.4-9.6). Subgroup analysis of forest maps showed that the coinfection rates were 8.2% (95% CI = 2.2-17.2) in North American, 0.2% (95% CI = 0.1-0.7) in European, and 1.2% (95% CI = 0.8-1.8) in Asian animals. Coinfection rates were 6.7% (95% CI = 2.7- 12.2) in domestic and 0.0% (95% CI = 0.0-0.4) in wild animals. The coinfection rates were 9% (95% CI = 5.7-12.8) in domestic horses and 6% (95% CI = 1.9-12.2) in domestic dogs, whereas 7.5% (95% CI = 3-17.9) in wild squirrels and 0.2% (95% CI = 0.1-0.7) in wild mice. Funnel diagrams, Egger's tests, and Begg's tests showed no significant publication bias in the included studies. Conclusions Spatial epidemiology showed that coinfection with Bb and Ap in animals worldwide was most prevalent in the southwestern region of North America, whereas species epidemiology showed that coinfection was most prevalent in domesticated horses, followed by wild squirrels and domesticated dogs, but was less common in wild mice. These data on the epidemiological status of Bb and Ap coinfection in animals may help guide the prevention and treatment of zoonosis.