BioParity.UFO / UAP research

7 papers for “Medical research”

Results

PaperS7678

Annotation-free discovery of disease-relevant cells in single-cell datasets

Erin Craig, Timothy J Keyes, Jolanda Sarno, Jeremy P D’Silva, Pablo Domizi, Maxim Zaslavsky, Albert Tsai, David Glass, Garry P Nolan, Trevor Hastie, Robert Tibshirani, Kara L Davis. ebi.ac.uk. August 27, 2025.

This Nolan-coauthored computational study estimates disease-associated cells using patient disease labels and a healthy baseline, without requiring expert cell annotations. Reported leukemia examples support a research method, with stronger expert-label benchmarks, small patient cohorts and assumptions that limit interpretation. Millions of measured cells do not imply millions of independent patients. Disclosed NIH support does not establish a classified programme or UAP access.

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PaperS7676

The commitment of the human cell atlas to humanity

Ido Amit and coauthors (including Garry Nolan). ebi.ac.uk. November 20, 2024.

This HCA perspective, coauthored by Garry Nolan, describes equitable participation, local research leadership, informed consent, privacy and open versus managed data access. Its claims concern consortium aims and reported activities, rather than a clinical trial or proof of universal benefits. Public scientific collaboration and institutional affiliations do not demonstrate a secret government approach or UAP programme.

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PaperS7570

MAPS: pathologist-level cell type annotation from tissue images through machine learning

Muhammad Shaban, Yunhao Bai, Huaying Qiu, Shulin Mao, Jason Yeung, Yao Yu Yeo, Vignesh Shanmugam, Han Chen, Bokai Zhu, Jason L Weirather, Garry P Nolan, Margaret A Shipp, Scott J Rodig, Sizun Jiang, Faisal Mahmood. ebi.ac.uk. January 2, 2024.

MAPS uses expert-labelled protein-expression data to classify cells. The authors report strong results within datasets, while acknowledging leakage risk from splitting one patient’s CODEX image by cells. Performance falls across cohorts and competing methods sometimes do better. Nolan is a coauthor and supervisor; disclosed commercial interests, reporting differences and missing original materials accompany the findings.

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PaperS7571

Neurological, Cognitive, and Psychological Findings Among Survivors of Ebola Virus Disease From the 1995 Ebola Outbreak in Kikwit, Democratic Republic of Congo: A Cross-sectional Study

J Daniel Kelly, Nicole A Hoff, D’Andre Spencer, Kamy Musene, Matthew S Bramble, David McIlwain, Daniel Okitundu, Travis C Porco, George W Rutherford, M Maria Glymour, Zach Bjornson, Patrick Mukadi, Emile Okitolonda-Wemakoy, Garry P Nolan, Jean Jacques Muyembe-Tamfum, Anne W Rimoin. ebi.ac.uk. August 10, 2018.

A selected 2017 cross-sectional study compared 20 Ebola survivors with 187 contacts from the Kikwit outbreak community. Cognitive and psychological score associations do not establish persistent causal brain injury, clinical diagnoses or 22 years of longitudinal follow-up. Small samples, instrument limitations and inconsistent source values remain explicit. Nolan is a coauthor; no UAP programme is discussed.

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PaperS7482

The extra-islet pancreas supports autoimmunity in human type 1 diabetes

Graham L Barlow, Christian M Schürch, Salil S Bhate, Darci J Phillips, Arabella Young, Shen Dong, Hunter A Martinez, Gernot Kaber, Nadine Nagy, Sasvath Ramachandran, Janet Meng, Eva Korpos, Jeffrey A Bluestone, Garry P Nolan, Paul L Bollyky. ebi.ac.uk. April 15, 2025.

Barlow, Nolan and colleagues examine spatial immune patterns in a small diabetes donor study. The paper and its public reviews retain limits on selection, marker interpretation and causal inference; this is background biomedical research with no UAP-exposure cohort.

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PaperS7695

Quantitative characterization of tissue states using multiomics and ecological spatial analysis

Daisy Yi Ding, Zeyu Tang, Bokai Zhu, Hongyu Ren, Alex K. Shalek, Robert Tibshirani, Garry P. Nolan. pmc.ncbi.nlm.nih.gov. April 1, 2025.

This computational study reanalyses existing tissue datasets to describe spatial cell diversity and infer molecular relationships. Its liver comparison has one tissue per condition, subdivided into ten regions; these are not ten patients. Colorectal-cancer survival models use internal validation. Nolan is explicitly acknowledged for NIH support and two FDA Medical Countermeasures Initiative contracts. Those public acknowledgements establish reported research support, without verifying contract scope or a classified UAP approach.

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PaperS7679

Integration of spatial and single-cell data across modalities with weakly linked features

Shuxiao Chen, Bokai Zhu, Sijia Huang, John W Hickey, Kevin Z Lin, Michael Snyder, William J Greenleaf, Garry P Nolan, Nancy R Zhang, Zongming Ma. ebi.ac.uk. September 7, 2023.

This Nolan-coauthored study introduces MaxFuse, a computational method for aligning cell measurements across weakly linked data types. Benchmarks report gains on selected datasets; inferred spatial gene activity is distinguished from measurements actually made in each cell. Reused cell batches and tuned comparisons limit broader conclusions. The article explicitly attributes FDA Medical Countermeasures Initiative contracts and NIH support to Nolan, without reporting a secret approach or classified UAP programme.

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