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Record W3014007372 · doi:10.3390/cells9040813

Single-Cell Protein and RNA Expression Analysis of Mononuclear Phagocytes in Intestinal Mucosa and Mesenteric Lymph Nodes of Ulcerative Colitis and Crohn’s Disease Patients

2020· review· en· W3014007372 on OpenAlexfundno aff
Laurence Chapuy, Marika Sarfati

Bibliographic record

VenueCells · 2020
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsnot available
FundersCanadian Institutes of Health Research
KeywordsUlcerative colitisMesenteric lymph nodesMedicineCrohn's diseaseIntestinal mucosaPathologyLymphCrohn diseaseCellPeripheral blood mononuclear cellDiseaseImmunologyBiologyInternal medicineImmune system

Abstract

fetched live from OpenAlex

Inflammatory bowel diseases (IBDs), which include Crohn's disease (CD) and ulcerative colitis (UC), are driven by an abnormal immune response to commensal microbiota in genetically susceptible hosts. In addition to epithelial and stromal cells, innate and adaptive immune systems are both involved in IBD immunopathogenesis. Given the advances driven by single-cell technologies, we here reviewed the immune landscape and function of mononuclear phagocytes in inflamed non-lymphoid and lymphoid tissues of CD and UC patients. Immune cell profiling of IBD tissues using scRNA sequencing combined with multi-color cytometry analysis identifies unique clusters of monocyte-like cells, macrophages, and dendritic cells. These clusters reflect either distinct cell lineages (nature), or distinct or intermediate cell types with identical ontogeny, adapting their phenotype and function to the surrounding milieu (nurture and tissue imprinting). These advanced technologies will provide an unprecedented view of immune cell networks in health and disease, and thus may offer a personalized medicine approach to patients with IBD.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.673
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.012
GPT teacher head0.244
Teacher spread0.231 · 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 teacher head, not a consensus.

Study designOther design
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

Citations19
Published2020
Admission routes1
Has abstractyes

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