Evidence map›Paper›PMID 38071144›Full record

ReviewTrends in biotechnology2024

3D human tissue models and microphysiological systems for HIV and related comorbidities.

3D Human Tissue Models for HIV Working Group. Electronic address: dwight.yin@nih.gov, 3D Human Tissue Models for HIV Working Group

Open access · greenAbstract readReview
In one paragraph

Review in Trends in biotechnology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.7field-weighted citation impact, top 30% of its field
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

5 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Review
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

2 authors.

3D Human Tissue Models for HIV Working Group. Electronic address: dwight.yin@nih.gov
3D Human Tissue Models for HIV Working Group

Funding

REACH: Research Enterprise to Advance a Cure for HIVUM1AI164565 · NIAID · WEILL MEDICAL COLL OF CORNELL UNIV · PI Marina Caskey, R. Brad Jones · 2021 to 2026
$32.9M
HOPE - HIV Obstruction by Programmed EpigeneticsUM1AI164559 · NIAID · J. DAVID GLADSTONE INSTITUTES · PI Lishomwa C Ndhlovu, Melanie Maria Ott · 2021 to 2026
$32.2M
Tissue Engineering Resource Center: TTDP41EB027062 · NIBIB · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI Gordana Vunjak-Novakovic · 2019 to 2026
$12.6M
Intramural NIH HHS Z99 AI999999NIAID NIH HHS UM1 AI164559NIAID NIH HHS UM1 AI164565NIBIB NIH HHS P41 EB027062
6 · The paper itself

Abstract

Three-dimensional (3D) human tissue models/microphysiological systems (e.g., organs-on-chips, organoids, and tissue explants) model HIV and related comorbidities and have potential to address critical questions, including characterization of viral reservoirs, insufficient innate and adaptive immune responses, biomarker discovery and evaluation, medical complexity with comorbidities (e.g., tuberculosis and SARS-CoV-2), and protection and transmission during pregnancy and birth. Composed of multiple primary or stem cell-derived cell types organized in a dedicated 3D space, these systems hold unique promise for better reproducing human physiology, advancing therapeutic development, and bridging the human-animal model translational gap. Here, we discuss the promises and achievements with 3D human tissue models in HIV and comorbidity research, along with remaining barriers with respect to cell biology, virology, immunology, and regulatory issues.

Indexed as

HIV InfectionsMicrophysiological SystemsAnimalsComorbidityCOVID-19HumansModels, BiologicalTuberculosisexplantHIV/AIDSmicrophysiological systemorgan-chiporganoidtuberculosis

Identifiers

PMID38071144
PMCPMC11065605
OpenAlexW4389488587

What OpenQuestion holds

Textmetadata
LicenceTDM
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 OpenQuestion graph.