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Record W2969093075 · doi:10.1093/glycob/cwz062

9-O-acetyl sialic acid levels identify committed progenitors of plasmacytoid dendritic cells

2019· article· en· W2969093075 on OpenAlexaff
Ilka Arun Netravali, Annaiah Cariappa, Kathleen B. Yates, W. Nicholas Haining, Alice Bertocchi, Hugues Allard‐Chamard, Ian M. Rosenberg, Shiv Pillai

Bibliographic record

VenueGlycobiology · 2019
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmunotherapy and Immune Responses
Canadian institutionsUniversité de Sherbrooke
FundersNational Institute of Arthritis and Musculoskeletal and Skin DiseasesNational Institute of Diabetes and Digestive and Kidney DiseasesNational Institute of Allergy and Infectious DiseasesNational Institutes of HealthBoston Area Diabetes Endocrinology Research Center
KeywordsSialic acidLineage (genetic)HaematopoiesisProgenitor cellMyeloidCell biologyBiologyProgenitorPlasmacytoid dendritic cellCell lineageStem cellChemistryCellular differentiationDendritic cellImmunologyBiochemistryGeneAntigen

Abstract

fetched live from OpenAlex

The origins of plasmacytoid dendritic cells (pDCs) have long been controversial and progenitors exclusively committed to this lineage have not been described. We show here that the fate of hematopoietic progenitors is determined in part by their surface levels of 9-O-acetyl sialic acid. Pro-pDCs were identified as lineage negative 9-O-acetyl sialic acid low progenitors that lack myeloid and lymphoid potential but differentiate into pre-pDCs. The latter cells are also lineage negative, 9-O-acetyl sialic acid low cells but are exclusively committed to the pDC lineage. Levels of 9-O-acetyl sialic acid provide a distinct way to define progenitors and thus facilitate the study of hematopoietic differentiation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.014
GPT teacher head0.255
Teacher spread0.241 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2019
Admission routes1
Has abstractyes

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