Development and Validation of a Multiplex Real-Time Qpcr Assay Using GMP-grade Reagents for Leprosy Diagnosis.
Biochimica et biophysica acta(2022)
Fiocruz MS
Abstract
Leprosy is a chronic dermato-neurological disease caused by Mycobacterium leprae, an obligate intracellular bacterium. Timely detection is a challenge in leprosy diagnosis, relying on clinical examination and trained health professionals. Furthermore, adequate care and transmission control depend on early and reliable pathogen detection. Here, we describe a qPCR test for routine diagnosis of leprosy-suspected patients. The reaction simultaneously amplifies two specific Mycobacterium leprae targets (16S rRNA and RLEP), and the human 18S rRNA gene as internal control. The limit of detection was estimated to be 2.29 copies of the M. leprae genome. Analytical specificity was evaluated using a panel of 20 other skin pathogenic microorganisms and Mycobacteria, showing no cross-reactivity. Intra- and inter-operator Cp variation was evaluated using dilution curves of M. leprae DNA or a synthetic gene, and no significant difference was observed between three operators in two different laboratories. The multiplex assay was evaluated using 97 patient samples with clinical and histopathological leprosy confirmation, displaying high diagnostic sensitivity (91%) and specificity (100%). Validation tests in an independent panel of 50 samples confirmed sensitivity and specificity of 97% and 98%, respectively. Importantly, assay performance remained stable for at least five months. Our results show that the newly developed multiplex qPCR effectively and specifically detects M. leprae DNA in skin samples, contributing to an efficient diagnosis that expedites the appropriate treatment.
MoreTranslated text
Key words
Leprosy,Mycobacterium leprae,Diagnosis
PDF
View via Publisher
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
- Pretraining has recently greatly promoted the development of natural language processing (NLP)
- We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
- We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
- The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
- Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Try using models to generate summary,it takes about 60s
Must-Reading Tree
Example

Generate MRT to find the research sequence of this paper
Related Papers
Frontiers in Tropical Diseases 2022
被引用4
LEPROSY REVIEW 2023
被引用3
ACS INFECTIOUS DISEASES 2023
被引用2
BMC MICROBIOLOGY 2023
被引用1
Challenges and Advances in Serological and Molecular Tests to Aid Leprosy Diagnosis.
EXPERIMENTAL BIOLOGY AND MEDICINE 2023
被引用1
Hansen’s Disease 2023
被引用0
PLOS NEGLECTED TROPICAL DISEASES 2024
被引用0
AMERICAN JOURNAL OF TROPICAL MEDICINE AND HYGIENE 2024
被引用0
Frontiers in Molecular Biosciences 2024
被引用0
DIAGNOSTIC MICROBIOLOGY AND INFECTIOUS DISEASE 2024
被引用1
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
去 AI 文献库 对话