Evidence map›Paper›PMID 42625659›Full record

ArticleFrontiers in cellular and infection microbiology2026

Machine learning-based feature selection suggests circulating proteins as best at predicting and diagnosing tuberculosis in

Taylor A L Woodard, Smriti Mehra, Deepak Kaushal, Vitaly V Ganusov

Abstract read
In one paragraph

Article in Frontiers in cellular and infection microbiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Taylor A L WoodardHost-Pathogen Interactions program, Texas Biomedical Research Institute, San Antonio, TX, United States.
Smriti MehraDisease Intervention and Prevention program, Texas Biomedical Research Institute, San Antonio, TX, United States.
Deepak KaushalHost-Pathogen Interactions program, Texas Biomedical Research Institute, San Antonio, TX, United States.
Vitaly V GanusovHost-Pathogen Interactions program, Texas Biomedical Research Institute, San Antonio, TX, United States.

Funding

ROLE OF INDUCIBLE BRONCHUS ASSOCIATED LYMPHOID TISSUE IN LATENT TUBERCULOSISR01AI111914 · NIAID · WASHINGTON UNIVERSITY · PI KAUSHAL, DEEPAK, KHADER, SHABAANA A. · 2015 to 2025
$11.1M
Myeloid and lymphoid immunity-specific mechanisms of IDO mediated immunosuppression and its reversal, during TBR01AI134245 · NIAID · TULANE UNIVERSITY OF LOUISIANA · PI Smriti Mehra · 2018 to 2026
$6.2M
Immune Correlates of Protection from TBR01AI134240 · NIAID · TULANE UNIVERSITY OF LOUISIANA · PI KAUSHAL, DEEPAK · 2017 to 2022
$4.8M
SigH based attenuated, efficacious Mtb vaccines to protect against lethal TBR01AI138587 · NIAID · TULANE UNIVERSITY OF LOUISIANA · PI JAGANNATH, CHINNASWAMY, KAUSHAL, DEEPAK · 2018 to 2022
$4.4M
Mathematical modeling of Mycobacterium tuberculosis disseminationR01AI158963 · NIAID · UNIVERSITY OF TENNESSEE KNOXVILLE · PI Vitaly V. Ganusov · 2022 to 2026
$3.2M
Modulating Indoleamines to Optimize Immunity in the Setting of Mtb/HIV Co-infectionR01AI181701 · NIAID · TEXAS BIOMEDICAL RESEARCH INSTITUTE · PI Smriti Mehra · 2024 to 2026
$2.8M
NIAID NIH HHS R01 AI111914NIAID NIH HHS R01 AI134240NIAID NIH HHS R01 AI134245NIAID NIH HHS R01 AI138587NIAID NIH HHS R01 AI158963NIAID NIH HHS R01 AI181701
6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

Blood ProteinsMachine LearningMycobacterium tuberculosisTuberculosisAnimalsBiomarkersC-Reactive ProteinDisease Models, AnimalMacaca mulattaBiomarkersBlood ProteinsC-Reactive Proteinbiomakersmachine learningMycobacterium tuberculosisnon-human primatestuberculosis

Identifiers

PMID42625659
PMCPMC13489891

What Socratic holds

Textmetadata
LicenceCC BY
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.