Evidence map›Paper›PMID 42523221›Full record

ArticlebioRxiv : the preprint server for biology2026

Sirui Ding, Sanchita Bhattacharya, Minnie M Sarwal, Marina Sirota, Atul J Butte

Abstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in bioRxiv : the preprint server for biology, 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

5 authors.

Sirui DingBakar Computational Health Sciences Institute, University of California, San Francisco, CA, USA.
Sanchita BhattacharyaBakar Computational Health Sciences Institute, University of California, San Francisco, CA, USA.
Minnie M SarwalDivision of Transplant Surgery, Department of Surgery, University of California San Francisco, San Francisco, California, USA.
Marina SirotaBakar Computational Health Sciences Institute, University of California, San Francisco, CA, USA.
Atul J ButteBakar Computational Health Sciences Institute, University of California, San Francisco, CA, USA.

Funding

Computational Drug Repositioning for Antibody Mediated Renal Allograft RejectionR01AI180118 · NIAID · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI MARINA SIROTA, Minnie M Sarwal · 2024 to 2026
$2.4M
NIAID NIH HHS R01 AI180118NIH HHS HHSN316201200036W
6 · The paper itself

Abstract

Reproducible biomarker identification and transplant rejection risk prediction remain fundamental yet unsolved challenges in transplantation medicine. Traditional approaches rely on hypothesis-driven analyses and domain expertise, limiting scalability and generalizability across diverse populations. We introduce

Identifiers

PMID42523221
PMCPMC13404656

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.