Evidence map›Paper›PMID 41207945›Full record

ReviewAdvances in experimental medicine and biology2026

Future Research Directions on Mycobacterium tuberculosis Proteins.

Parissa Farnia, Ali Akbar Velayati, Jalaledin Ghanavi, Poopak Farnia

Abstract readReview
PubMed Publisher
In one paragraph

Review in Advances in experimental medicine and biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Parissa FarniaShahid Beheshti University of Medical Sciences, Mycobacteriology Research Centre (MRC), National Research Institute of Tuberculosis and Lung Diseases (NRITLD), Tehran, Iran. pfarnia@theaasm.org.
Ali Akbar VelayatiShahid Beheshti University of Medical Sciences, Mycobacteriology Research Centre (MRC), National Research Institute of Tuberculosis and Lung Diseases (NRITLD), Tehran, Iran.
Jalaledin GhanaviShahid Beheshti University of Medical Sciences, Mycobacteriology Research Centre (MRC), National Research Institute of Tuberculosis and Lung Diseases (NRITLD), Tehran, Iran.
Poopak FarniaShahid Beheshti University of Medical Sciences, Mycobacteriology Research Centre (MRC), National Research Institute of Tuberculosis and Lung Diseases (NRITLD), Tehran, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Future research on Mycobacterium tuberculosis (Mtb) proteins is essential for advancing tuberculosis (TB) diagnosis, treatment, and control amid rising drug resistance and global health challenges. Recent studies focus on elucidating protein structures and interactions critical to bacterial survival, virulence, and drug resistance, enabling the identification of novel therapeutic targets. Cutting-edge technologies such as single-cell proteomics, cryo-electron microscopy, and spatial proteomics provide unprecedented resolution of protein localization, dynamics, and host-pathogen interactions. Posttranslational modifications and dynamic proteomic profiling reveal bacterial adaptive mechanisms, while integrative multi-omics combined with artificial intelligence (AI) and machine learning accelerate functional annotation and predictive modeling. Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-based functional genomics complements these approaches by enabling precise gene regulation studies. Advances in AI-powered diagnostics and genomic surveillance are transforming TB detection and drug resistance profiling, improving patient outcomes, especially in resource-limited settings. Overall, integrating experimental and computational innovations promises to deepen understanding of Mtb biology, accelerate drug discovery, enhance diagnostics, and ultimately contribute to global efforts in combating tuberculosis.

Indexed as

Bacterial ProteinsMycobacterium tuberculosisTuberculosisAntitubercular AgentsHost-Pathogen InteractionsHumansProteomicsAntitubercular AgentsBacterial ProteinsArtificial intelligence (AI)Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)Mycobacterium tuberculosisPosttranslational modification (PTM)Single-cell proteomicsSpatial proteomics

Identifiers

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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 Socratic graph.