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Abstract Background The emergence of Multidrug-Resistant Tuberculosis (MDR-TB) poses a significant threat to global tuberculosis control efforts. This study aimed to examine the influence of mutations in Toxin-Antitoxin system genes on the global transmission of MDR-TB caused by Mycobacterium tuberculosis (M. tuberculosis). Methods Whole-genome sequencing was conducted on 13,518 M. tuberculosis isolates. Genes of the Toxin-Antitoxin system were obtained from the National Center for Biotechnology Information (NCBI) Gene database. Techniques such as Random Forest, Gradient Boosting Decision Tree, and Generalized Linear Mixed Models were employed to identify mutation sites in Toxin-Antitoxin system-related genes that facilitated the transmission of MDR-TB. Results 4,066 (30.08%) were identified as MDR-TB strains of all analyzed isolates. We found significant associations between specific gene mutations and MDR-TB transmission clusters including mutations in Rv0298 (G213A), Rv1959c (parE1, C88T), Rv1960c (parD1, C134T), Rv1991A (maze, G156A), Rv2547 (vapB, C54G), Rv2862A (vapB23, T2C), and Rv3385c (vapB46, G70A). Additionally, several gene mutations associated with MDR-TB transmission clades such as Rv1956 (higA, G445T), Rv1960c (parD1, C134T), and Rv1962A (vapB35, G99A) were noted. Certain gene mutations including vapB35 (G99A), higA (G445T), and parD1 (C134T) correlated with cross-regional transmission clades. Conclusion This study highlights the significant association between specific gene mutations in the Toxin-Antitoxin system and the global transmission of MDR-TB, providing valuable insights for developing targeted interventions to control MDR-TB.

Abstract Background The respiratory chain plays a key role in the growth of Mycobacterium tuberculosis complex (MTBC). However, the exact regulatory mechanisms of this system still need to be elucidated, and only a few studies have investigated the impact of genetic mutations within the respiratory chain on MTBC transmission. This study aims to explore the impact of respiratory chain gene mutations on the global spread of MTBC. Results A total of 13,402 isolates of MTBC were included in this study. The majority of the isolates (n = 6,382, 47.62%) belonged to lineage 4, followed by lineage 2 (n = 5,123, 38.23%). Our findings revealed significant associations between Single Nucleotide Polymorphisms (SNPs) of specific genes and transmission clusters. These SNPs include Rv0087 (hycE, G178T), Rv1307 (atpH, C650T), Rv2195 (qcrA, G181C), Rv2196 (qcrB, G1250T), Rv3145 (nuoA, C35T), Rv3149 (nuoE, G121C), Rv3150 (nuoF, G700A), Rv3151 (nuoG, A1810G), Rv3152 (nuoH, G493A), and Rv3157 (nuoM, A1243G). Furthermore, our results showed that the SNPs of atpH C73G, atpA G271C, qcrA G181C, nuoJ G115A, nuoM G772A, and nuoN G1084T were positively correlated with cross-country transmission clades and cross-regional transmission clades. Conclusions Our study uncovered an association between mutations in respiratory chain genes and the transmission of MTBC. This important finding provides new insights for future research and will help to further explore new mechanisms of MTBC pathogenicity. By uncovering this association, we gain a more complete understanding of the processes by which MTBC increases virulence and spread, providing potential targets and strategies for preventing and treating tuberculosis.

Abstract Background Iron plays a crucial role in the growth of Mycobacterium tuberculosis (M. tuberculosis). However, the precise regulatory mechanism governing this system requires further elucidation. Additionally, limited studies have examined the impact of gene mutations related to iron on the transmission of M. tuberculosis globally. This research aims to investigate the correlation between mutations in iron-related genes and the worldwide transmission of M. tuberculosis. Results A total of 13,532 isolates of M. tuberculosis were included in this study. Among them, 6,104 (45.11%) were identified as genomic clustered isolates, while 8,395 (62.04%) were classified as genomic clade isolates. Our results showed that a total of 12 single nucleotide polymorphisms (SNPs) showed a positive correlation with clustering, such as Rv1469 (ctpD, C758T), Rv3703c (etgB, G1122T), and Rv3743c (ctpJ, G676C). Additionally, seven SNPs, including Rv0104 (T167G, T478G), Rv0211 (pckA, A302C), Rv0283 (eccB3, C423T), Rv1436 (gap, G654T), ctpD C758T, and etgB C578A, demonstrated a positive correlation with transmission clades across different countries. Notably, our findings highlighted the positive association of Rv0104 T167G, pckA A302C, eccB3 C423T, ctpD C758T, and etgB C578A with transmission clades across diverse regions. Furthermore, our analysis identified 78 SNPs that exhibited significant associations with clade size. Conclusions Our study reveals the link between iron-related gene SNPs and M. tuberculosis transmission, offering insights into crucial factors influencing the pathogenicity of the disease. This research holds promise for targeted strategies in prevention and treatment, advancing research and interventions in this field.

BackgroundThe toxin-antitoxin (TA) system plays a vital role in the virulence and pathogenicity of Mycobacterium tuberculosis (M. tuberculosis). However, the regulatory mechanisms and the impact of gene mutations on M. tuberculosis transmission remain poorly understood.ObjectiveTo investigate the influence of gene mutations in the toxin-antitoxin system on M. tuberculosis transmission dynamics.MethodWe performed whole-genome sequencing on the analyzed strains of M. tuberculosis. The genes associated with the toxin-antitoxin system were obtained from the National Center for Biotechnology Information (NCBI) Gene database. Mutations correlating with enhanced transmission within the genes were identified by using random forest, gradient boosting decision tree, and generalized linear mixed models.ResultsA total of 13,518 M. tuberculosis isolates were analyzed, with 42.29% (n = 5,717) found to be part of genomic clusters. Lineage 4 accounted for the majority of isolates (n = 6488, 48%), followed by lineage 2 (n = 5133, 37.97%). 23 single nucleotide polymorphisms (SNPs) showed a positive correlation with clustering, including vapB1 G34A, vapB24 A76C, vapB2 T171C, mazF2 C85T, mazE2 G104A, vapB31 T112C, relB T226A, vapB11 C54T, mazE5 T344C, vapB14 A29G, parE1 (C103T, C88T), and parD1 C134T. Six SNPs, including vapB6 A29C, vapB31 T112C, parD1 C134T, vapB37 G205C, Rv2653c A80C, and vapB22 C167T, were associated with transmission clades across different countries. Notably, our findings highlighted the positive association of vapB6 A29C, vapB31 T112C, parD1 C134T, vapB37 G205C, vapB19 C188T, and Rv2653c A80C with transmission clades across diverse regions. Furthermore, our analysis identified 32 SNPs that exhibited significant associations with clade size.ConclusionOur study presents potential associations between mutations in genes related to the toxin-antitoxin system and the transmission dynamics of M. tuberculosis. However, it is important to acknowledge the presence of confounding factors and limitations in our study. Further research is required to establish causation and assess the functional significance of these mutations. These findings provide a foundation for future investigations and the formulation of strategies aimed at controlling TB transmission.

Abstract Background Fatty acid metabolism greatly promotes the virulence and pathogenicity of Mycobacterium tuberculosis (M.tb). However, the regulatory mechanism of fatty acid metabolism in M.tb remains to be elucidated, and limited evidence about the effects of gene mutations in fatty acid metabolism on the transmission of M.tb was reported. Results Overall, a total of 3193 M.tb isolates were included in the study, of which 1596 (50%) were genomic clustered isolates. Most of the tuberculosis isolates belonged to lineage2(n = 2744,85.93%), followed by lineage4(n = 439,13.75%) and lineage3(n = 10,0.31%).Regression results showed that the mutations of gca (136,605, 317G > C, Arg106Pro; OR, 22.144; 95% CI, 2.591-189.272), ogt(1,477,346, 286G > C ,Gly96Arg; OR, 3.893; 95%CI, 1.432–10.583), and rpsA (1,834,776, 1235 C > T, Ala412Val; OR, 3.674; 95% CI, 1.217–11.091) were significantly associated with clustering; mutations in gca and rpsA were also significantly associated with clustering of lineage2. Mutation in arsA(3,001,498, 885 C > G, Thr295Thr; OR, 6.278; 95% CI, 2.508–15.711) was significantly associated with cross-regional clusters. We also found that 20 mutation sites were positively correlated with cluster size, while 11 fatty acid mutation sites were negatively correlated with cluster size. Conclusion Our research results suggested that mutations in genes related to fatty acid metabolism were related to the transmission of M.tb. This research could help in the future control of the transmission of M.tb.

Abstract Background Two-component systems (TCSs) play a crucial role in the growth of Mycobacterium tuberculosis (M. tuberculosis). However, the precise regulatory mechanism of their contribution remain to be elucidated, and only a limited number of studies have investigated the impact of gene mutations within TCSs on the transmission of M. tuberculosis. Therefore, this study aims to explore the relationship between TCSs gene mutation and the global transmission of M. tuberculosis. Results A total of 13531 M.tuberculosis strains were enrolled in the study. Most of the M.tuberculosis strains belonged to lineage4 (n=6497,48.0%), followed by lineage2 (n=5136,38.0%). Our results showed that a total of 36 single nucleotide polymorphisms (SNPs) were positively correlated with clustering of lineage2, such as Rv0758 (phoR, C820G), Rv1747(T1102C), and Rv1057(C1168T). A total of 30 SNPs showed positive correlation with clustering of lineage4, such as phoR(C182A, C1184G, C662T, T758G), Rv3764c (tcrY, G1151T), and Rv1747 C20T. A total of 19 SNPs were positively correlated with cross-country transmission of lineage2, such as phoR A575C, Rv1028c (kdpD, G383T, G1246C), and Rv1057 G817T. A total of 41 SNPs were positively correlated with cross-country transmission of lineage4, such as phoR(T758G, T327G, C284G), kdpD(G1755A, G625C), Rv1057 C980T, and Rv1747 T373G. Conclusions Our study identified that SNPs in genes of two-component systems were related to the transmission of M. tuberculosis. This finding adds another layer of complexity to M. tuberculosis virulence and provides insight into future research that will help to elucidate a novel mechanism of M. tuberculosis pathogenicity.

Abstract Background The ongoing coronavirus 2019 (COVID-19) pandemic has emerged and caused multiple pandemic waves in the following six countries: India, Indonesia, Nepal, Malaysia, Bangladesh and Myanmar. Some of the countries have been much less studied in this devastating pandemic. This study aims to assess the impact of the Omicron variant in these six countries and estimate the infection fatality rate (IFR) and the reproduction number $${R}_{0}$$ R 0 in these six South Asia, Southeast Asia and Oceania countries. Methods We propose a Susceptible-Vaccinated-Exposed-Infectious-Hospitalized-Death-Recovered model with a time-varying transmission rate $$\beta (t)$$ β ( t ) to fit the multiple waves of the COVID-19 pandemic and to estimate the IFR and $${R}_{0}(t)$$ R 0 ( t ) in the aforementioned six countries. The level of immune evasion and the intrinsic transmissibility advantage of the Omicron variant are also considered in this model. Results We fit our model to the reported deaths well. We estimate the IFR (in the range of 0.016 to 0.136%) and the reproduction number $${R}_{0}(t)$$ R 0 ( t ) (in the range of 0 to 9) in the six countries. Multiple pandemic waves in each country were observed in our simulation results. Conclusions The invasion of the Omicron variant caused the new pandemic waves in the six countries. The higher $${R}_{0}(t)$$ R 0 ( t ) suggests the intrinsic transmissibility advantage of the Omicron variant. Our model simulation forecast implies that the Omicron pandemic wave may be mitigated due to the increasing immunized population and vaccine coverage.

BackgroundImmune checkpoint inhibitors (ICIs) have changed the treatment pattern of advanced and metastatic NSCLC. A series of ICI based therapies have emerged in the first-line treatment field, but the comparative efficacy was unclear.MethodWe searched multiple databases and abstracts of major conference proceedings up to Apri1, 2022 for phase III randomised trials of advanced driver-gene wild type NSCLC patients receiving first-line therapy. Outcomes analyzed included progression free survival (PFS), overall survival (OS), and et al.ResultsThirty-two double-blind RCTs were included, involving 18,656 patients assigned to 22 ICI-based first-line regimens. A series of ICI regiments (including ICI plus chemotherapy), ICI monotherapy, doublet ICIs, doublet ICIs plus chemotherapy) emerged, and showed significant PFS and OS benefit than chemotherapy and chemotherapy + bevacizumab (BEV) for advanced wild-type NSCLC. In comprehensive terms of PFS, chemoimmunotherapy (CIT) were significantly more effective than ICI monotherapy and doublet ICIs. In terms of OS for patients with non-squamous NSCLC, pembrolizumab containing CIT was associated with a median rank of the best regimens, and followed by Atezolizumab+BEV based CIT; while for OS in patients with squamous NSCLC, Cemiplimab and sintilimab based CIT were the most effective regimens. For more than 2 years follow-up, the atezolizumab, pembrolizumab, nivolumab and durvalumab containing ICI therapy all provide a durable long-term OS benefit over chemotherapy and BEV + chemotherapy.ConclusionsThe findings of the present NMA represent the most comprehensive evidence, which might suggest or provide basis for first-line ICI therapy decision for advanced NSCLC patients without oncogenic driver mutations.

By February 2021, the overall impact of the COVID-19 pandemic in India had been relatively mild in terms of total reported cases and deaths. Surprisingly, the second wave in early April becomes devastating and attracts worldwide attention. Multiple factors (e.g., Delta variants with increased transmissibility) could have driven the rapid growth of the epidemic in India and led to a large number of deaths within a short period. We aim to reconstruct the transmission rate, estimate the infection fatality rate and forecast the epidemic size. We download the reported COVID-19 mortality data in India and formulate a simple mathematical model with a flexible transmission rate. We use iterated filtering to fit our model to deaths data. We forecast the infection attack rate in a month ahead. Our model simulation matched the reported deaths well and is reasonably close to the results of the serological study. We forecast that the infection attack rate (IAR) could have reached 43% by July 24, 2021, under the current trend. Our estimated infection fatality rate is about 0.07%. Under the current trend, the IAR will likely reach a level of 43% by July 24, 2021. Our estimated infection fatality rate appears unusually low, which could be due to a low case to infection ratio reported in previous study. Our approach is readily applicable in other countries and with other types of data (e.g., excess deaths).

Tuberculosis (TB) incidence has been in steady decline in China over the last few decades. However, ongoing demographic transition, fueled by aging, and massive internal migration could have important implications for TB control in the future. We collated data on TB notification, demography, and drug resistance between 2004 and 2017 across seven cities in Shandong, the second most populous province in China. Using these data, and age-period-cohort models, we (i) quantified heterogeneities in TB incidence across cities, by age, sex, resident status, and occupation and (ii) projected future trends in TB incidence, including drug-resistant TB (DR-TB). Between 2006 and 2017, we observed (i) substantial variability in the rates of annual change in TB incidence across cities, from -4.84 to 1.52%; (ii) heterogeneities in the increments in the proportion of patients over 60 among reported TB cases differs from 2 to 13%, and from 0 to 17% for women; (iii) huge differences across cities in the annual growths in TB notification rates among migrant population between 2007 and 2017, from 2.81 cases per 100K migrants per year in Jinan to 22.11 cases per 100K migrants per year in Liaocheng, with drastically increasing burden of TB cases from farmers; and (iv) moderate and stable increase in the notification rates of DR-TB in the province. All of these trends were projected to continue over the next decade, increasing heterogeneities in TB incidence across cities and between populations. To sustain declines in TB incidence and to prevent an increase in Multiple DR-TB (MDR-TB) in the future in China, future TB control strategies may (i) need to be tailored to local demography, (ii) prioritize key populations, such as elderly and internal migrants, and (iii) enhance DR-TB surveillance.

IntroductionTuberculosis is one of the main infectious diseases threatening global health, which is also the main cause of death from a single source of infection (above HIV/AIDS). China is a country with a high burden of tuberculosis in the world, ranking only behind India and Indonesia. However, there are few ecological studies on the burden of tuberculosis in China. This study aims to provide more research basis for the government to formulate tuberculosis policies by exploring the ecological factors associated with the incidence of tuberculosis, so as to achieve the goal of eliminating tuberculosis by 2030.MethodsWe collected data on the incidence of tuberculosis and ecological factors of 31 provinces, autonomous regions, and municipalities in Mainland China (excluding Taiwan, Hong Kong, and Macau) from 2002 to 2018. We constructed a framework of ecological factors affecting the incidence, which consists of 5 secondary indicators and 35 tertiary indicators. And we construct a dynamic panel data model based on the Lasso Regression to select variables to test the effect of each ecological factor on the incidence.ResultsAmong the 35 tertiary indicators, economy 3,4,6,7, environment 1, recourses 1,3, demography 3, and lifecare 2,4,8,9,13 passed the significance test at the 1% level, economy 1,2,5, environment 2,9, lifecare 6,12 passed the significance test at the 5% level, lifecare 10 passed the significance test at the 10% level. Only economy 5 and economy 6 have a positive impact on the incidence, other statistically significant ecological indicators are negatively correlated with the incidence.ConclusionsOur study indicated that many ecological factors, including residents' income, unemployment rate, educational level, medical resources, population density, sunshine duration and dietary structure, are closely related to the incidence of tuberculosis. These findings contribute the government to taking targeted measures for tuberculosis prevention and control, including improving the level of economic development, increasing employment, expanding the scale of enrollment in colleges and universities, and ensuring that the prices of sources of animal protein are reasonable to meet the residents' intake of protein.

Abstract Background Few studies have investigated the associations between outdoor air pollution and outpatient visits for respiratory diseases (RDs) in general population. Methods We collected daily outpatient data of primary RDs from five hospitals in Jinan during January 2012 and December 2016, as well as daily measurements of air pollutants from the Jinan Environmental Monitoring Center and daily meteorological variables from the China Meteorological Data Sharing Service System. A generalized additive model (GAM) with quasi-Poisson regression was constructed to estimate the associations between daily average concentrations of outdoor air pollutants (PM2.5,PM10, SO2, NO2, CO and O3) and daily outpatient visits of RDs after adjusting for long-time trends, seasonality, the “day of the week” effect, and weather conditions. Subgroup analysis stratified by gender, age group and the type of RDs was conducted. Results A total of 1,373,658 outpatient visits for RDs were identified. Increases of 10 μg/m3 in PM2.5, PM10, NO2, CO and O3 were associated with0.168% (95% CI, 0.072–0.265%), 0.149% (95% CI, 0.082–0.215%), 0.527% (95% CI, 0.211–0.843%), 0.013% (95% CI, 0.003–0.023%), and 0.189% (95% CI, 0.032–0.347%) increases in daily outpatient visits for RDs, respectively. PM2.5 and PM10 showed instant and continuous effects, while NO2, CO and O3 showed delayed effects on outpatient visits for RDs. In stratification analysis, PM2.5 and PM10 were associated with acute RDs only. Conclusions Exposure to outdoor air pollutants including PM2.5, PM10, NO2, CO and O3 associated with increased risk of outpatient visits for RDs.

In this analysis, we observed that human development index (an integrated index of life expectation, education and living standard) correlates with infection rate (proportion of confirmed cases among the population) and the fatality rate of COVID-19 in Italy based on data as of May 15, 2020. Further analysis showed that HDI is negatively correlated with cigarette consumption, whereas it is positively correlated with chronic disease and average annual gross salary. These factors may partially explain why unexpected positive correlation is observed between human development index and risk of infections and deaths of COVID-19 in Italy.