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Record W112085085 · doi:10.1177/229255030501300305

Patterns of Reinnervation and Blood Flow in Split-Skin Grafts

2005· article· en· W112085085 on OpenAlexvenueno aff
D. Oudit, Mohamed A. Ellabban

Bibliographic record

VenueCanadian Journal of Plastic Surgery · 2005
Typearticle
Languageen
FieldMedicine
TopicDermatologic Treatments and Research
Canadian institutionsnot available
Fundersnot available
KeywordsLaser Doppler velocimetryReinnervationMedicineBlood flowCalcitonin gene-related peptideCD31Skin biopsySkin graftingPathologyAnatomyImmunohistochemistrySurgeryNeuropeptideBiopsyInternal medicine

Abstract

fetched live from OpenAlex

One of the most important functions of skin is thermoregulation. The alterations in the patterns of blood flow in skin is one of the main physiological processes responsible for thermoregulatory control. The mechanisms governing the thermoregulatory control of cutaneous blood flow are mainly neural and chemical in nature. At present, there is a lack of studies in the literature looking at the relationship between reinnervation and the blood flow pattern of skin grafts. The present study uses Laser Doppler flowmetry and the immunohistochemical stains protein gene product 9.5, calcitonin gene-related peptide and substance P to identify nerve fibres, and antibodies to CD31 and von Willebrand factor to identify endothelial tissues. The aim of the present study was to investigate the patterns of blood flow and nerve tissue regeneration in split-skin grafts up to 15 years following the original procedure. Thirty-two split-skin grafts were studied and these were placed into two groups based on the nature of the bed of excision: group I consisted of patients who underwent tangential excision and split-skin grafting (n=17), and group II consisted of patients with split-skin grafts placed onto fascial beds (n=15). Each subpopulation of patients was further divided into three groups based on the length of time following grafting: one to three years, four to six years and seven to 15 years. These divisions were arbitrarily chosen and called A1, A2 and A3, respectively. In the Laser Doppler flowmetry arm of the study, the grafts were assessed at various stages after heating, cooling and further reheating. The Laser Doppler flowmetry studies showed that, on subjecting the skin grafts in both groups I and II to heating and cooling followed by reheating, the overall response of the blood flow to changes in the temperature was slower. The immunohistochemical analysis showed that in all graft types and graft ages, protein gene product 9.5, calcitonin gene-related peptide and substance P stains demonstrated a relative lack of the presence of nerve fibres in the split-skin grafts compared with the control ('normal' skin). However, von Willebrand factor and CD31 immunological staining demonstrated that vessels were present in the split-skin grafts, with no significant difference in size or quantity from the control samples. It was found that the blood flow in the split-skin graft in response to thermal challenge, although present, was slower than that of normal skin, a finding which was independent of the age of the skin graft. It is thought that this was related to a lack of regeneration of nerve fibres and, hence, a deficiency in the neurally mediated reflexes of the blood vessels within the split-skin grafts.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.024
GPT teacher head0.249
Teacher spread0.225 · 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

Citations0
Published2005
Admission routes1
Has abstractyes

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