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Record W4323041084 · doi:10.1097/gox.0000000000004831

Immunohistochemical Analysis of Lymphocyte Populations in Acute Skin Rejection: The University Health Network Addition to the Banff Classification

2023· article· en· W4323041084 on OpenAlexaff
Siba Haykal, Natasha Barone, Sara Rostami, Sajad Moshkelgosha, S. Juvet, Shaf Keshavjee, Danny Ghazarian

Bibliographic record

VenuePlastic & Reconstructive Surgery Global Open · 2023
Typearticle
Languageen
FieldMedicine
TopicOrgan and Tissue Transplantation Research
Canadian institutionsToronto General HospitalMcGill University Health CentreUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsDermisPathologyImmunohistochemistrySubcutaneous tissueHistologyMedicineAllotransplantationEpidermis (zoology)TransplantationAnatomyInternal medicine

Abstract

fetched live from OpenAlex

Acute rejection in vascularized composite allotransplantation has been identified using the Banff 2007 working classification. We propose an addition to this classification based on histological and immunological assessment within the skin and subcutaneous tissue. Methods: Biopsies from vascularized composite transplant patients were obtained at scheduled visits and whenever skin changes occurred. Histology and immunohistochemistry were performed on all samples, looking at infiltrating cells. Results: Observations were made specifically related to each component of the skin, including the epidermis, dermis, vessels, and subcutaneous tissue. Our findings led to the establishment of the University Health Network addition of skin rejection. Conclusions: The high rate of rejection where the skin is involved requires novel techniques for early detection. The University Health Network skin rejection addition can serve as an adjunct to the Banff classification.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.186
Threshold uncertainty score0.293

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.006
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 head0.070
GPT teacher head0.355
Teacher spread0.285 · 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.

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

Citations3
Published2023
Admission routes1
Has abstractyes

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