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Record W2265094363 · doi:10.1007/978-1-59745-182-6_9

In Vitro Human T Cell Development Directed by Notch–Ligand Interactions

2008· article· en· W2265094363 on OpenAlexaff
Génève Awong, Ross N. La Motte-Mohs, Juan Carlos Zúñiga‐Pflücker

Bibliographic record

VenueMethods in molecular biology · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDevelopmental Biology and Gene Regulation
Canadian institutionsSunnybrook HospitalUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsStromal cellHaematopoiesisCell biologyBone marrowBiologyStem cellLymphopoiesisImmunologyCancer research

Abstract

fetched live from OpenAlex

Traditionally, the study of human T cell development has relied on the availability of human and mouse thymic tissue. In this chapter, we outline a simple in vitro protocol for generating large numbers of human T-lineage cells from umbilical cord blood (CB)- derived hematopoietic stem cells (HSCs) using a bone marrow stromal cell line. This protocol is broken into three major steps: (1) the maintenance of a working stock of OP9 bone marrow stromal cells expressing the Notch receptor ligand Delta-like 1 (OP9- DL1), (2) the purification of human HSCs from umbilical CB, and (3) the initiation and maintenance/expansion of OP9-DL1 cocultures over time (see Fig. 1). The use of this system opens avenues for basic research as it equips us with a simple in vitro method for studying human T cell development.

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 score0.005
Threshold uncertainty score0.016

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.003

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 head0.015
GPT teacher head0.354
Teacher spread0.339 · 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

Citations29
Published2008
Admission routes1
Has abstractyes

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