Evidence map›Paper›PMID 42395438›Full record

ArticlebioRxiv : the preprint server for biology2026

Fault-tolerant 3D reconstruction from 2D spatial proteomics sections.

Zhaojun Zhang, Yuqi Tan, Michael Snyder, Garry P Nolan, Zongming Ma

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.

Zhaojun ZhangDepartment of Statistics and Data Science, The Wharton School, University of Pennsylvania, PA, United States.
Yuqi TanDepartment of Microbiology and Immunology, Stanford University, CA, United States.ORCID 0000-0002-7200-3222
Michael SnyderDepartment of Genetics, Stanford University, CA, United States.
Garry P NolanDepartment of Pathology, Stanford University, CA, United States.
Zongming MaDepartment of Statistics and Data Science, Yale University, CT, United States.ORCID 0000-0003-2401-0177

Funding

Stanford Tissue Mapping Center - STELLARU54HG012723 · NHGRI · STANFORD UNIVERSITY · PI SNYDER, MICHAEL P. · 2022 to 2025
$7.8M
Center for Human Lymphoma Spatiotemporal Atlas (HuLymSTA)U01CA294514 · NCI · YALE UNIVERSITY · PI FAN, RONG, HALENE, STEPHANIE · 2024 to 2025
$5.1M
NCI NIH HHS U01 CA294514NHGRI NIH HHS U54 HG012723
6 · The paper itself

Abstract

Reconstructing 3D molecular volumes from sparsely sampled 2D tissue sections is limited by per-section marker dropout and tissue loss. We present 3D-Omics-Flow, a generative pipeline that jointly repairs damaged sections and interpolates between them at single-cell resolution. Across datasets spanning health and disease, 3D-Omics-Flow expands 3D spatial proteomics to practical sampling regimes, enabling atlas construction and downstream analysis from imperfect 2D section stacks.

Indexed as

3D inferenceDiffusion modelGenerative AIMultiplexed imagingSpatial proteomics

Identifiers

PMID42395438
PMCPMC13320739

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.