ArticleInfection and drug resistance2022
A Peptidomic Approach to Identify Novel Antigen Biomarkers for the Diagnosis of Tuberculosis.
Article in Infection and drug resistance, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed, 8 citations in OpenAlex.
- Quantum Dot-Based Nanosensors for In Vitro Detection ofNanomaterials (Basel, Switzerland) · 2024Review
- Evolution of tuberculosis diagnostics: From molecular strategies to nanodiagnostics.Tuberculosis (Edinburgh, Scotland) · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
15 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Here, we conducted a peptidomic study in murine model to identify novel antigen biomarkers for the diagnosis of tuberculosis (TB) with improved performance. Methods: Four recombinant proteins, including Results: A total of 65 peptides from 4 MTB precursor recombinant proteins were identified in mouse serum by LC-MS/MS, of which 5 peptides were selected as candidates for serological analysis. The concentrations of peptides MPT64-2, CFP10-2 and PstS1-2 in TB patients were significantly higher than those in non-TB patients. MPT64-2 exhibited the most promising sensitivity (81.4%), followed by PstS1-2 and CFP10-2. In addition, PstS1-2 had the highest specificity (93.3%), followed by CFP10-2 and MPT64-2. According to the area under the curve (AUC), MPT64-2 (AUC = 0.863), PstS1-2 (AUC = 0.812) and CFP10-2 (AUC = 0.809) exhibited better diagnostic validity. Conclusion: We develop an effective approach to identify new antigen biomarkers via LC-MS/MS-based peptidomics. Multiple peptides exhibit promising efficacy in diagnosis of active TB patients.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.