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Three‐yr follow‐up of a type 1 diabetes mellitus patient with an islet xenotransplant

2007· article· en· W2109397744 on OpenAlexaff
R Valdés-González, David J. White, L Dorantes, Luis M. Terán, Guadalupe N. Garibay-Nieto, Eduardo Bracho‐Blanchet, Roberto Dávila-Pérez, Lola Evia-Viscarra, Christopher E. Ormsby, Jorge‐Tonatiuh Ayala‐Sumuano, María L. Silva‐Torres, B Ramírez-González

Bibliographic record

VenueClinical Transplantation · 2007
Typearticle
Languageen
FieldMedicine
TopicPancreatic function and diabetes
Canadian institutionsWestern University
FundersUniversity of Miami
KeywordsXenotransplantationMedicineIsletInsulinTransplantationType 1 diabetesEconomic shortageDiabetes mellitusInternal medicineType 2 Diabetes MellitusHemoglobinEndocrinologySurgeryAndrology

Abstract

fetched live from OpenAlex

In order to alleviate the shortage of human donors, the use of porcine islets of Langerhans for xenotransplantation in diabetic patients has been proposed as a solution. To overcome rejection, we have developed a procedure for protecting the islets by combining them with Sertoli cells and placing them in a novel subcutaneous device, that generates an autologous collagen covering. A type 1 diabetic woman was closely monitored for 10 months, and then transplanted in two devices with two months of difference and a third time after 22 months. Here we present a three-yr follow-up. The close monitoring induced a rapid decrease in exogenous insulin requirements, which stabilized between 19 and 28 IU/d for nine months. After transplantation, the requirements reduced further to below 6 IU/d and for some weeks she was insulin free. Glycosylated hemoglobin levels decreased concomitantly. Porcine insulin could be detected in the serum after a glucose challenge and insulin positive cells inside a removed device after two yr. No complications have arisen and no porcine endogenous retrovirus infection has been detected through PCR and RT-PCR. This case demonstrates the feasibility of using the xenotransplantation of porcine cells to alleviate metabolic complications and insulin requirements in type 1 diabetic patients.

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 score0.120
Threshold uncertainty score0.466

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.047
GPT teacher head0.326
Teacher spread0.279 · 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

Citations38
Published2007
Admission routes1
Has abstractyes

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