In one paragraphArticle 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
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 registryThe 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 literatureWho cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
4 · The recordCorrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
5 · Who and what moneyAuthors and funding
11 authors.
Zhen MiaoGraduate Group in Genomics and Computational Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.ORCID 0000-0002-3255-9517 Yilong QuGraduate Group in Genomics and Computational Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Sijia HuangPenn Institute of Biomedical Informatics, University of Pennsylvania, Philadelphia, PA, USA.ORCID 0000-0002-4680-9484 Linshan LauxMasonic Institute on the Biology of Aging and Metabolism, Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota, Minneapolis, MN, USA.
Samuel PetersMasonic Institute on the Biology of Aging and Metabolism, Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota, Minneapolis, MN, USA.
Alisha AristelDepartment of Statistics and Data Science, The Wharton School, University of Pennsylvania, Philadelphia, PA, USA.
Zhaojun ZhangDepartment of Statistics and Data Science, The Wharton School, University of Pennsylvania, Philadelphia, PA, USA.
Laura NiedernhoferMasonic Institute on the Biology of Aging and Metabolism, Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota, Minneapolis, MN, USA.ORCID 0000-0002-1074-1385 Andrew McMahonDepartment of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA.ORCID 0000-0002-3779-1729 Junhyong KimGraduate Group in Genomics and Computational Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.ORCID 0000-0002-7726-8246 Nancy R ZhangGraduate Group in Genomics and Computational Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.ORCID 0000-0002-0880-5749 Funding
Multiomic single cell and spatial interrogation of mechanisms in cellular adaptation to stressR01GM149671 · NIGMS · UNIVERSITY OF PENNSYLVANIA · PI Sydney Shaffer, Nancy R Zhang · 2024 to 2026
$1.6MMultiomic methods for the characterization of cellular agingR56AG081351 · NIA · UNIVERSITY OF PENNSYLVANIA · PI JOHNSON, F. BRAD, ZHANG, NANCY R · 2024 to 2024
$400kNIA NIH HHS R56 AG081351NIGMS NIH HHS R01 GM149671
6 · The paper itselfAbstract
Spatial transcriptomics enables the study of how cells coordinate their molecular states within tissue, providing insight into both normal function and disease processes. A key challenge is to identify gene expression programs that vary continuously across space and are coordinated between cell types. We present
Identifiers
PMID42079111
PMCPMC13131544
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