Transmission is a Noticeable Cause of Resistance Among Treated Tuberculosis Patients in Shanghai, China
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB21577 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| ERR2020050.fastq.gz | Fastqsanger.gz | |||
| ERR2020060.fastq.gz | Fastqsanger.gz | |||
| ERR2020060_1.fastq.gz | Fastqsanger.gz | |||
| ERR2020060_2.fastq.gz | Fastqsanger.gz | |||
| ERR2020070.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 126 |
Similar Datasets
Project description:Background:
- Early detection of colon cancer can improve the chances of successful treatment for most people. This approach is especially important if blood is detected in the stool. However, much better stool sample tests are needed to find this cancer early. To improve the tests, researchers want to collect samples from people who are already being screened for colon cancer. This study will collect information and samples from older adults in Shanghai, China. These adults will be participating in screening tests for colon cancer.
Objectives:
- To collect samples and medical information for colon cancer screening from older adults in Shanghai, China.
Eligibility:
* Adults between 50 and 74 years of age who are being screened for colon cancer.
* Participants will be recruited from two community health centers in Shanghai, China.
Design:
* Participants will provide information on their medical history and factors related to colon cancer. They will respond to questions on use of medications, diet choices (such as eating red meat), bowel habits, and other factors.
* Participants will collect samples for study. These samples will be collected within 3 days of the screening visit. Particpants will provide a urine sample and four stool samples. They will also use cotton swabs to collect samples from just inside the anus. The samples will be returned to the study doctors for research tests that may indicate who has colon cancer.
* Treatment will not be provided as part of this study.
| 2139076 | ecrin-mdr-crc
Project description:It is generally believed that drug resistance among treated tuberculosis (TB) patients is as a result of acquired drug resistance due to inappropriate treatment. Previous studies have shown that primary drug resistance caused by transmission also plays a role among treated cases. Differentiating the two types of drug resistance will help in developing appropriate strategies for control of drug resistant tuberculosis. In this study, we tested the hypothesis that drug resistance among treated TB patients is mainly caused by primary resistance rather than acquired resistance. Defining resistance profiles by molecular drug susceptibility test, we used Unit Variable Number Tandem Repeats (VNTR) to genotype and Whole Genome Sequencing (WGS) to confirm the accordance of the first and last Mycobacterium tuberculosis isolates from treated pulmonary TB patients in Shanghai from 2009-2015. Among 81 patients with increasing drug resistance, out of 390 patients enrolled, paired isolates from 59.3% (48/81) had different VNTR patterns indicating primary drug resistance. Our results have demonstrated that primary resistance due to exogenous reinfection is the major cause of drug resistance among treated TB patients in Shanghai; thus, strategies aimed at preventing and interrupting transmission are urgently needed to effectively reduce the epidemic of drug resistant tuberculosis.
| S-EPMC5550506 | biostudies-literature
Project description:Transcriptional profiling of mycobacterium tuberculosis clinical isolates in China comparing extensively drug-resistant tuberculosis with drug sensitive one.
2009-04-04 | GSE15540 | GEO
Project description:Shigui Ruan. Modeling the transmission dynamics and control of rabies in China. Mathematical Biosciences 286 (2017).
Human rabies was first recorded in ancient China in about 556 BC and is still one of the major public-health problems in China. From 1950 to 2015, 130,494 human rabies cases were reported in Mainland China with an average of 1977 cases per year. It is estimated that 95% of these human rabies cases are due to dog bites. The purpose of this article is to provide a review about the models, results, and simulations that we have obtained recently on studying the transmission of rabies in China. We first construct a basic susceptible, exposed, infectious, and recovered (SEIR) type model for the spread of rabies virus among dogs and from dogs to humans and use the model to simulate the human rabies data in China from 1996 to 2010. Then we modify the basic model by including both domestic and stray dogs and apply the model to simulate the human rabies data from Guangdong Province, China. To study the seasonality of rabies, in Section 4 we further propose a SEIR model with periodic transmission rates and employ the model to simulate the monthly data of human rabies cases reported by the Chinese Ministry of Health from January 2004 to December 2010. To understand the spatial spread of rabies, in Section 5 we add diffusion to the dog population in the basic SEIR model to obtain a reaction-diffusion equation model and determine the minimum wave speed connecting the disease-free equilibrium to the endemic equilibrium. Finally, in order to investigate how the movement of dogs affects the geographically inter-provincial spread of rabies in Mainland China, in Section 6 we propose a multi-patch model to describe the transmission dynamics of rabies between dogs and humans and use the two-patch submodel to investigate the rabies virus clades lineages and to simulate the human rabies data from Guizhou and Guangxi, Hebei and Fujian, and Sichuan and Shaanxi, respectively. Some discussions are provided in Section 7.
2024-09-02 | BIOMD0000000726 | BioModels
Project description:Transcriptional profiling of mycobacterium tuberculosis clinical isolates in China comparing extensively drug-resistant tuberculosis with drug sensitive one. The same condition experiment. The samples were from the different drug-resistant strains. Only one replicate.
2009-04-04 | E-GEOD-15540 | biostudies-arrayexpress
Project description:Background: In December 2019, an outbreak of coronavirus disease (later named as COVID-19) was identified in Wuhan, China and, later on, detected in other parts of China. Our aim is to evaluate the effectiveness of the evolution of interventions and self-protection measures, estimate the risk of partial lifting control measures and predict the epidemic trend of the virus in the mainland of China excluding Hubei province based on the published data and a novel mathematical model.
Methods: A novel COVID-19 transmission dynamic model incorporating the intervention measures implemented in China is proposed. COVID-19 daily data of the mainland of China excluding Hubei province, including the cumulative confirmed cases, the cumulative deaths, newly confirmed cases and the cumulative recovered cases between 20 January and 3 March 2020, were archived from the National Health Commission of China (NHCC). We parameterize the model by using the Markov Chain Monte Carlo (MCMC) method and estimate the control reproduction number (Rc), as well as the effective daily reproduction ratio- Re(t), of the disease transmission in the mainland of China excluding Hubei province.
Results: The estimation outcomes indicate that Rc is 3.36 (95% CI: 3.20-3.64) and Re(t) has dropped below 1 since 31 January 2020, which implies that the containment strategies implemented by the Chinese government in the mainland of China are indeed effective and magnificently suppressed COVID-19 transmission. Moreover, our results show that relieving personal protection too early may lead to a prolonged disease transmission period and more people would be infected, and may even cause a second wave of epidemic or outbreaks. By calculating the effective reproduction ratio, we prove that the contact rate should be kept at least less than 30% of the normal level by April, 2020.
Conclusions: To ensure the pandemic ending rapidly, it is necessary to maintain the current integrated restrict interventions and self-protection measures, including travel restriction, quarantine of entry, contact tracing followed by quarantine and isolation and reduction of contact, like wearing masks, keeping social distance, etc. People should be fully aware of the real-time epidemic situation and keep sufficient personal protection until April. If all the above conditions are met, the outbreak is expected to be ended by April in the mainland of China apart from Hubei province.
2024-09-02 | BIOMD0000000981 | BioModels
Project description:Klebsiella pneumoniae isolate:Shanghai Genome sequencing
| PRJNA1044916 | ENA
Project description:Transmission of Mycobacterium Tuberculosis in Switzerland over 25 Years
| PRJEB5925 | ENA