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Record W2289583429 · doi:10.1016/j.celrep.2016.03.039

Common-Lymphoid-Progenitor-Independent Pathways of Innate and T Lymphocyte Development

2016· article· en· W2289583429 on OpenAlexaff
Maryam Ghaedi, Catherine A. Steer, Itziar Martínez-González, Timotheus Y.F. Halim, N. B. Abraham, Fumio Takei

Bibliographic record

VenueCell Reports · 2016
Typearticle
Languageen
FieldImmunology and Microbiology
TopicIL-33, ST2, and ILC Pathways
Canadian institutionsUniversity of British ColumbiaBC Cancer Agency
FundersCancer Research UK
KeywordsInnate lymphoid cellInterleukin-7 receptorBiologyProgenitor cellImmunologyLymphopoiesisProgenitorTransplantationLymphocyteImmune systemInnate immune systemCell biologyStem cellT cellMedicineInternal medicineIL-2 receptor

Abstract

fetched live from OpenAlex

All lymphocytes are thought to develop from common lymphoid progenitors (CLPs). However, lymphoid-primed multipotent progenitors (LMPPs) are more efficient than CLPs in differentiating into T cells and group 2 innate lymphoid cells (ILC2s). Here, we have divided LMPPs into CD127(-) (LMPP-s) and CD127(+) (LMPP+s) subsets and compared them with Ly6D(-) and Ly6D(+) CLPs. Adult LMPP+s differentiated into T cells and ILCs more rapidly and efficiently than other progenitors in transplantation assays. The development of T cells and ILC2s is highly active in the neonatal period. Neonatal CLPs are rare and, unlike prominent neonatal LMPP+s, do not efficiently differentiate into T cells and ILC2s. ILC2s generated in the neonatal period are long lived and persist in adult tissues. These results suggest that some ILCs and T cells may develop from LMPP+s via CLP-independent pathways.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

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 science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.013
GPT teacher head0.204
Teacher spread0.191 · 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 designBench or experimental
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

Citations79
Published2016
Admission routes1
Has abstractyes

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