Network Meta-analysis of Chinese patent medicine containing Hirudo in treatment of atherosclerosis / 中国中药杂志

This study aimed to evaluate the efficacy and safety of Chinese patent medicines containing Hirudo in the treatment of atherosclerosis(AS) by network Meta-analysis, and to provide evidence-based reference for clinical treatment of AS. The clinical randomized controlled trial(RCT) on the treatment of atherosclerosis with Chinese patent medicines containing Hirudo were searched in CNKI, Wanfang, VIP, SinoMed, PubMed and EMbase from the establishment of the databases to July 1, 2022. And data extraction and quality assessment of the included RCT was performed according to the Cochrane standards. Stata 17 and ADDIS 1.16.5 were then used for Bayesian model network Meta-analysis. Finally, 67 RCTs with a total sample size of 6 826 cases were included, 3 569 cases in the experimental group and 3 257 cases in the control group, involving three oral Chinese patent medicines. Network Meta-analysis showed that in terms of reducing intima-media thickness(IMT), the top three Chinese patent medicines were Tongxinluo Capsules+sta-tins>Maixuekang Capsules+statins>Maixuekang Capsules. In terms of reducing plaque area, the top one was Maixuekang Capsules+sta-tins, and the other Chinese patent medicines had similar efficacy. For lowering AS Crouse scores, the top three were Maixuekang Capsules>Tongxinluo Capsules+statins>Naoxintong Capsules. For decreasing plaque number, the top three were Naoxintong Capsules+sta-tins>Tongxinluo Capsules+statins>Tongxinluo Capsules. With regard to adverse reactions/events, Naoxintong Capsules+statins had the lo-west incidence. In conclusion, in Chinese patent medicines containing Hirudo for the treatment of AS, Tongxinluo Capsules+statins, Maixuekang Capsules, Maixuekang Capsules+statins, and Naoxintong Capsules+statins were the primary choices to reduce IMT, AS Crouse scores, plaque area, and plaque number, respectively. The efficacy of Chinese patent medicines containing Hirudo with or without statins was more significant than that of statins alone in the four outcome indexes. Additionally, the treatment of AS should be evaluated comprehensively, and attention should be paid to Chinese patent medicines or their combination with western medicine, to optimize the treatment effect and minimize adverse reactions as the benchmark.

Benchmark dose estimation based on Bayesian model averaging and its application to evaluation of cadmium exposure of population in Baiyin / 环境与职业医学

Background The optimal model method for estimation of benchmark dose (BMD) does not consider the uncertainty of model selection. There is a lack of studies on using Bayesian model averaging (BMA) to estimate BMD. Objective To apply BMA to the exposure assessment of cadmium pollution in China, discuss the role of BMA in estimating BMD based on dose-response models, and to provide methodological support for health risk assessment of hazardous substances. Methods The parameters of five dose-response models (Gamma, Log-logistic, Log-probit, Two-stage, and Weibull models) estimated from the data from a cadmium-contaminated area in Baiyin City of Gansu Province and the urinary cadmium ranges in five cadmium-contaminated areas in China were used to simulate the data of varied correct models with different numbers of dosage groups (5 and 8) and different sample sizes (50, 100, and 200), then the performance of BMA and traditional optimal model were compared. The case analysis used the cadmium exposure data in Baiyin, Gansu Province. All analyses set urinary cadmium as the indicator of cadmium exposure, the abnormal rate of β2-microglobulin as the effect indicator, and the benchmark response to 10%. The correct model (the model used when simulating data), optimal model [the model with smallest Akaike information criterion (AIC)], and BMA were used to estimate BMD and lower confidence limit of benchmark dose (BMDL); the BMDs, BMDLs, and relative deviations from different methods were compared. Results In the simulation study, with increasing sample size or the number of dosage groups, the intervals of the 5th percentile and the 90th percentile of BMD tended to be narrower; when the correct model was a single model, the relative deviation of BMD estimation by BMA was greater than that of the traditional optimal model; when the correct model was an equal weight mixed model, the relative deviation of BMD estimation by BMA was less than that by the traditional optimal model. For the data of cadmium-contaminated areas, the optimal model was a Log-probit model (AIC=1814.46), followed by a Log-logistic model (AIC=1814.57); the BMDs (BMDLs) estimated by the Log-probit model, the Log-logistic model, and BMA were 3.46 (2.68), 3.16 (2.33), and 2.92 (2.07) μg·g−1, respectively. Conclusion The traditional optimal model is still recommended when the correct model is known. However, when the dose-response relationship of a hazardous substance is uncertain or with different sources or exposure grouping, compared with the traditional optimal model, BMA theoretically provides more stable estimation of BMD and BMDL by considering multiple possible alternative models.

Progress of researches on the application of risk assessment models in assessment of the schistosomiasis transmission risk / 中国血吸虫病防治杂志

With the deepening of the schistosomiasis research, risk assessment models have been widely used in schistosomiasis research and control. This paper reviews the theoretical basis and applications of common schistosomiasis risk assessment models and the Bayesian model, so as to provide insights into national schistosomiasis elimination program in China.

The classification model of type 2 diabetic peripheral neuropathy was studied based on GA-BP neural network model / 解放军医学杂志

Objective: To establish the genetic algorithm optimizing back-propagation (GA-BP) neural network model based on the clinical examination index for diagnosing type 2 diabetic peripheral neuropathy (DPN), and evaluate its diagnostic performance. Methods: A total of 2240 DPN patients and 2632 non-DPN patients were collected from the Hospital affiliated to Chongqing Medical University from January to December 2016, and univariate analysis was performed for 41 clinical test indicators of the two groups of patients with SPSS 21.0. Thirty-seven items of statistically significant variables were selected to establish the decision tree and Bayesian model with R software, MATLAB 2014a software was employed to establish the BP neural network and GA-BP neural network model, the advantages and disadvantages of these four models were compared with various evaluation parameters. Results: Using decision tree, the Bayesian, BP neural network and GA-BP neural network for 4872 cases of observation object model, the decision tree of The test sample accuracy with decision tree model was 93.4%, with Bayesian model was 70.0%, with BP neural network model was 98.9%, and with GA-BP neural network model was 99.5%. The areas under the ROC curve were 0.93, 0.72, 0.99 and 0.99, respectively. The Youden Indexes were 0.87, 0.59, 0.98 and 0.98, respectively. Conclusion: The GA-BP neural network established in present paper has a good computer-aided diagnosis function for type 2 diabetic peripheral neuropathy, but further clinical trials are still needed.

GPA: A Microbial Genetic Polymorphisms Assignments Tool in Metagenomic Analysis by Bayesian Estimation / 基因组蛋白质组与生物信息学报·英文版

Identifying antimicrobial resistant (AMR) bacteria in metagenomics samples is essential for public health and food safety. Next-generation sequencing (NGS) technology has provided a powerful tool in identifying the genetic variation and constructing the correlations between genotype and phenotype in humans and other species. However, for complex bacterial samples, there lacks a powerful bioinformatic tool to identify genetic polymorphisms or copy number variations (CNVs) for given genes. Here we provide a Bayesian framework for genotype estimation for mixtures of multiple bacteria, named as Genetic Polymorphisms Assignments (GPA). Simulation results showed that GPA has reduced the false discovery rate (FDR) and mean absolute error (MAE) in CNV and single nucleotide variant (SNV) identification. This framework was validated by whole-genome sequencing and Pool-seq data from Klebsiella pneumoniae with multiple bacteria mixture models, and showed the high accuracy in the allele fraction detections of CNVs and SNVs in AMR genes between two populations. The quantitative study on the changes of AMR genes fraction between two samples showed a good consistency with the AMR pattern observed in the individual strains. Also, the framework together with the genome annotation and population comparison tools has been integrated into an application, which could provide a complete solution for AMR gene identification and quantification in unculturable clinical samples. The GPA package is available at https://github.com/IID-DTH/GPA-package.

Sensitivity of diagnostic methods for Mansonella ozzardi microfilariae detection in the Brazilian Amazon Region

BACKGROUND The human filarial worm Mansonella ozzardi is highly endemic in the large tributaries of the Amazon River. This infection is still highly neglected and can be falsely negative when microfilariae levels are low. OBJECTIVES This study investigated the frequency of individuals with M. ozzardi in riverine communities in Coari municipality, Brazilian Amazon. METHODS Different diagnostic methods including polymerase chain reaction (PCR), blood polycarbonate membrane filtration (PCMF), Knott's method (Knott), digital thick blood smears (DTBS) and venous thick blood smears (VTBS) were used to compare sensitivity and specificity among the methods. Data were analysed using PCMF and Bayesian latent class models (BLCM) as the gold standard. We used BLCM to calculate the prevalence of mansonelliasis based on the results of five diagnostic methods. FINDINGS The prevalence of mansonelliasis was 35.4% by PCMF and 30.1% by BLCM. PCR and Knott methods both possessed high sensitivity. Sensitivity relative to PCMF was 98.5% [95% confidence interval (CI): 92.0 - 99.7] for PCR and 83.5% (95% CI: 72.9 - 90.5) for Knott. Sensitivity derived by BLCM was 100% (95% CI 93.7 - 100) for PCMF, 100% (95% CI: 93.7 - 100) for PCR and 98.3% (95% CI: 90.6 - 99.9) for Knott. The odds ratio of being diagnosed as microfilaremic increased with age but did not differ between genders. Microfilariae loads were higher in subjects aged 30 - 45 and 45 - 60 years. MAIN CONCLUSIONS PCMF and PCR were the best methods to assess the prevalence of mansonelliasis in our samples. As such, using these methods could lead to higher prevalence of mansonelliasis in this region than the most commonly used method (i.e., thick blood smears).

Prognostic factors of colorectal cancer and establishment of colorectal cancer prognosis model / 中华医学图书情报杂志

The factors influencing the prognosis of colorectal cancer were studied after its characteristic variables were screened by stepwise logistic regression analysis, Bayesian model averaging analysis, and LASSO regression a-nalysis respectively. A model of colorectal cancer prognosis was established according to the artificial neural net-work classification algorithm for the assessment of colorectal cancer. The highest accuracy was detected in the model of colorectal cancer prognosis established by Bayesian model averaging analysis combined with artificial neural net-work classification algorithm.

Análise espaço-temporal da leishmaniose visceral no estado do Maranhão, Brasil / Space-time analysis of visceral leishmaniasis in the State of Maranhão, Brazil

Resumo Este estudo analisou a distribuição espaço-temporal dos casos de leishmaniose visceral (LV) no estado do Maranhão, no período de 2000 a 2009. A partir do número de casos notificados, foram elaborados mapas temáticos para demonstrar a evolução da distribuição geográfica da doença no estado. Utilizou-se o método MCMC para estimação dos parâmetros do modelo bayesiano espaço-temporal para a identificação das áreas de risco. De 2000 a 2009, foram notificados 5.389 casos de leishmaniose visceral, distribuídos em todas as 18 Unidades Regionais de Saúde do estado, com as maiores incidências em: Caxias, Imperatriz, Presidente Dutra e Chapadinha. As Unidades Regionais de Saúde com maiores riscos relativos por biênio foram: Caxias e Barra do Corda (2000-2001), Imperatriz e Presidente Dutra (2002-2003), Imperatriz e Caxias (2004-2005), Presidente Dutra e Codó (2006-2007), e Imperatriz e Caxias (2008-2009). Houve uma considerável expansão geográfica da LV no Maranhão, sendo necessária a adoção de medidas mais eficazes de prevenção e controle da doença no estado.

Abstract This study analyzed the spatial and temporal distribution of cases of visceral leishmaniasis in the State of Maranhão in the period from 2000 to 2009. Based on the number of reported cases, thematic maps were prepared to show the evolution of the geographical distribution of the disease in the state. The MCMC method was used for estimating the parameters of the Bayesian model for space-time identification of risk areas. From 2000 to 2009 there were 5389 reported cases of visceral leishmaniasis, distributed in all 18 Regional Health Units in the state, with the highest indices in the cities of Caxias, Imperatriz, Presidente Dutra and Chapadinha. The Regional Health Units with the highest relative risks per biennium were: Caxias and Barra do Corda (2000-2001), Imperatriz and President Dutra (2002-2003), Imperatriz and Caxias (2004-2005), Presidente Dutra and Codó (2006-2007) and Imperatriz and Caxias (2008-2009). There was considerable geographic expansion of visceral leishmaniasis in Maranhão, thus highlighting the need to adopt more effective measures for prevention and control of the disease in the state.

An analysis of the spatiotemporal distribution of American cutaneous leishmaniasis in counties located along road and railway corridors in the State of Maranhao, Brazil

Introduction The incidence of American cutaneous leishmaniasis (ACL) is increasing in Latin America, especially in Brazil, where 256,587 cases were confirmed in the last decade. Methods This study used a Bayesian model to examine the spatial and temporal distribution of ACL cases between 2000 and 2009 in 61 counties of State of Maranhão located along the three main road and railway corridors. Results During the study period, 13,818 cases of ACL were recorded. There was a significant decrease in the incidence of ACL in the ten study years. The recorded incidence rate ranged from 7.36 to 241.45 per 100,000 inhabitants. The relative risk increased in 77% of the counties, decreased in 18% and was maintained in only five counties. Conclusions Although there was a decreased incidence of the disease, ACL was present in all of the examined municipalities, thus maintaining the risk of contracting this illness. .

Effective connectivity between superior temporal gyrus and Heschl’s gyrus during white noise listening: linear versus non-linear models

Purpose: This fMRI study is about modelling the effective connectivity between Heschl’s gyrus (HG) and the superior temporal gyrus (STG) in human primary auditory cortices. Materials & methods: Ten healthy male participants were required to listen to white noise stimuli during functional magnetic resonance imaging (fMRI) scans. Statistical parametric mapping (SPM) was used to generate individual and group brain activation maps. For input region determination, two intrinsic connectivity models comprising bilateral HG and STG were constructed using dynamic causal modelling (DCM). The models were estimated and inferred using DCM while Bayesian Model Selection (BMS) for group studies was used for model comparison and selection. Based on the winning model, six linear and six non-linear causal models were derived and were again estimated, inferred, and compared to obtain a model that best represents the effective connectivity between HG and the STG, balancing accuracy and complexity. Results: Group results indicated significant asymmetrical activation (puncorr < 0.001) in bilateral HG and STG. Model comparison results showed strong evidence of STG as the input centre. The winning model is preferred by 6 out of 10 participants. The results were supported by BMS results for group studies with the expected posterior probability,r = 0.7830 and exceedance probability, φ = 0.9823. One-sample t-tests performed on connection values obtained from the winning model indicated that the valid connections for the winning model are the unidirectional parallel connections from STG to bilateral HG (p < 0.05). Subsequent model comparison between linear and non-linear models using BMS prefers non-linear connection (r = 0.9160, φ = 1.000) from which the connectivity between STG and the ipsi- and contralateral HG is gated by the activity in STG itself. Conclusion: We are able to demonstrate that the effective connectivity between HG and STG while listening to white noise for the respective participants can be explained by a non-linear dynamic causal model with the activity in STG influencing the STG-HG connectivity non-linearly.