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Record W1872184414 · doi:10.1111/nyas.12823

Age‐related aspects of human IgM<sup>+</sup> B cell heterogeneity

2015· article· en· W1872184414 on OpenAlexaff
Victoria Martin, Bryan Wu, David Kipling, Deborah K. Dunn‐Walters

Bibliographic record

VenueAnnals of the New York Academy of Sciences · 2015
Typearticle
Languageen
FieldImmunology and Microbiology
TopicT-cell and B-cell Immunology
Canadian institutionsInstitute of Infection and Immunity
FundersBiotechnology and Biological Sciences Research CouncilRosetrees TrustKing's College LondonMedical Research CouncilNational Institute for Health and Care Research
KeywordsImmunoglobulin DImmunologyRepertoireBiologyAntibodyImmune systemMemory B cellPopulationImmunoglobulin MNaive B cellB cellB-1 cellImmunoglobulin GT cellMedicine

Abstract

fetched live from OpenAlex

The CD27(+) IgD(+) B cell population, known as IgM memory, reduces with age. It is thought that this population is responsible for pneumococcal polysaccharide T-independent responses, and that the age-related reduction might be partially responsible for the increased susceptibility of older people to bacterial pathogens. There are other IgM(+) B cell populations that do not express IgD. We compared the different IgM populations using high-throughput sequencing of the immunoglobulin (Ig) gene repertoire and multidimensional cell phenotyping and found that the different populations of IgM cells, defined by CD27 and IgD expression, have repertoire differences. Some of these differences are likely indicative of different selection pressures in an immune response, although the older individuals were found to have a changed repertoire in naive B cells, which may contribute to some of the changes seen in memory cells. In addition, even within the CD27(+) IgD(+) IgM memory population there are multiple cell types. We show that the level of IgM expression varies substantially and hypothesize that this distinguishes between T-dependent and T-independent types of IgM memory cells. Significant age-related changes in the relative proportions of these populations may exacerbate the reduction in T-independent responders in old age.

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 score0.002
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 science0.0000.000
Research integrity0.0000.000
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 head0.085
GPT teacher head0.313
Teacher spread0.228 · 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

Citations38
Published2015
Admission routes1
Has abstractyes

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