Review in ImmunoHorizons, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
0numbers the graph read from it
0cells of the map it votes in
1citing 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.
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
1 author.
Brandon J DeKoskyThe Ragon Institute of Mass General, MIT, and Harvard, Cambridge, MA, United States.ORCID 0000-0001-6406-0836
Funding
Dissecting the mechanisms of HIV resistance in vivo to broadly neutralizing antibodiesU01AI169587 · NIAID · UNIVERSITY OF MINNESOTA · PI Priyamvada Acharya, Brandon James DeKosky · 2022 to 2026
$7.8M
Potent broadly neutralizing antibody development against the HIV-1 fusion peptide epitopeR01AI181684 · NIAID · MASSACHUSETTS GENERAL HOSPITAL · PI Brandon James DeKosky · 2023 to 2026
$3.0M
Comprehensive analysis of human adaptive immune receptors to elucidate correlates of Epstein-Barr virus disease suppressionDP5OD023118 · OD · UNIVERSITY OF KANSAS LAWRENCE · PI DEKOSKY, BRANDON JAMES · 2016 to 2022
$2.2M
Potent Antibody Protection Against P. falciparum and P. vivax MalariaR01AI192975 · NIAID · MASSACHUSETTS GENERAL HOSPITAL · PI Brandon James DeKosky · 2025 to 2026
$1.6M
MATCHMAKERS - Solving T-cell receptor recognition and design via integrated high-throughput screening and structural, functional and computational approachesOT2CA297514 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI Brandon James DeKosky · 2024 to 2026
$964k
Rapid antibody screening systems to identify and engineer antiviral protectionR21AI166396 · NIAID · MASSACHUSETTS GENERAL HOSPITAL · PI DEKOSKY, BRANDON JAMES · 2022 to 2023
$850k
High-throughput identification and transcriptional analysis of autoreactive T cells in individuals with membranous nephropathy.R21AI178021 · NIAID · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI CRAVEDI, PAOLO · 2023 to 2024
$479k
Comprehensive molecular and functional analyses of anti-HIV-1 broadly neutralizing antibody repertoiresR21AI143407 · NIAID · UNIVERSITY OF KANSAS LAWRENCE · PI DEKOSKY, BRANDON JAMES, FORREST, MARCUS LAIRD · 2019 to 2020
$435k
Probing antigen specificity and response of autoimmune B cells in Neuromyelitis OpticaR21AI144408 · NIAID · UNIVERSITY OF KANSAS LAWRENCE · PI DEKOSKY, BRANDON JAMES · 2019 to 2020
Antibodies and T cell receptors are the molecular basis of immune memory, and have become the foundation for generations of clinically successful biologics. Decades of research have established diverse systems to observe, identify, discover, and optimize the adaptive immune receptors, both from natural and synthetic sources. Recent advances in high-throughput display, next-generation sequencing analysis, and machine learning data mining are accelerating our capabilities to characterize immune receptor repertoires, including based on functional properties. This commentary discusses common principles in modern immune receptor studies, with an eye toward the near-term horizon in large functional dataset collection and analysis.
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.
The adaptive immune receptors in a big data world. · full record | OpenQuestion