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Record W2922184234 · doi:10.1093/jbcr/irz013.274

366 Humanized Skin Model in Severe Combined Immune Deficient Pigs

2019· article· en· W2922184234 on OpenAlexaff
Alexandra Singer, Christopher K. Tuggle, Annette Ahrens, Mariana M. Sauer, Scott McClain, E. E. Tredget, Louis Rosenberg

Bibliographic record

VenueJournal of Burn Care & Research · 2019
Typearticle
Languageen
FieldMedicine
TopicTissue Engineering and Regenerative Medicine
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineImmune systemInflammationTransplantationWound healingPathologyHuman skinAntibodyDermatomeImmunologySurgeryBiology

Abstract

fetched live from OpenAlex

Hypertrophic scarring after burns is common resulting in significant disfigurement and dysfunction. Further advances in understanding the pathobiology of scarring and the development of novel therapies aimed at reducing scarring are hindered by the lack of appropriate large animal models. Transplantation of human xenografts onto immune compromised mice is a powerful research tool for studying wound healing. However, differences in healing between humans and mice and their small size limits this model. Recently, a severe combined immune deficiency (SCID) pig was accidentally discovered. We determined whether human cadaver skin xenografts transplanted onto SCID pigs would survive and not be rejected. Split thickness, meshed (1:1.5), cryopreserved human cadaver skin obtained from a skin bank was transplanted onto 10 partial thickness dermatome wounds in each of two normal domestic pigs and two SCID pigs. Autografts (n=2/animal) from the 4 animals were used as controls. Animals were followed for 4 weeks and periodic digital images and full thickness biopsies were obtained to monitor healing using H&E stains as well as T-cell specific CD3-antibodies. Human specific HLA antibodies were used to determine the origin of the transplanted skin in SCID pigs. In normal pigs, all autografts were engrafted and healed with minimal if any inflammation and scarring. All human xenografts were rejected by the normal pigs within 5-11 days and associated with an intense T-cell inflammatory response. In contrast, both autografts and xenografts were engrafted and survived the 28-day study in the SCID pigs with minimal inflammation in only 1/20 xenografts and no gross scarring in any wounds. Human specific antibodies (HLA-ABC) confirmed the human source of the healed xenografts. This study serves as proof-of-concept that human cadaver skin survives on SCID pigs for at least 28 days. Further development of this model is ongoing to determine if human hypertrophic scars or keloids can be transplanted onto SCID pigs. We believe that a humanized scar model in pigs will be helpful in the development of novel therapies aimed at preventing or reducing hypertrophic scarring after burns.

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)0.001
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 score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.040
GPT teacher head0.360
Teacher spread0.320 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

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