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Detrimental effect of excessive collagenase class II on human islet isolation outcome

2008· article· en· W2010661668 on OpenAlexaff
Tatsuya Kin, Xiaojun Zhai, Doug O’Gorman, A. M. James Shapiro

Bibliographic record

VenueTransplant International · 2008
Typearticle
Languageen
FieldMedicine
TopicPancreatic function and diabetes
Canadian institutionsUniversity of AlbertaCapital District Health Authority
FundersNational Institute of Diabetes and Digestive and Kidney Diseases
KeywordsCollagenaseIsletMedicineThermolysinPancreasInternal medicineEndocrinologyAndrologyEnzymeDiabetes mellitusTrypsinBiochemistryBiology

Abstract

fetched live from OpenAlex

Commercially available purified collagenases, derived from Clostridium histolyticum, contain two different classes of collagenase: class I collagenase (CI) and class II collagenase (CII) at a predetermined ratio. In this study, using purified CI and CII in separate vials, we had a unique opportunity to investigate the effect of the proportion between two collagenase classes on clinical human islet isolation. Pancreas organs derived from deceased donors were prospectively assigned to one of three different enzyme protocols: group A--CII:CI = 1:1 vial; group B--1:2; group C--1.5:1. As a result, their total collagenase activities were 2116, 2230, and 3117 Wunsch units/pancreas in groups A, B, and C, respectively but thermolysin dosage was adjusted to 624-988 Units/g pancreas. The pancreas was not efficiently digested in group C in spite of a relatively longer digestion time and significantly higher Wunsch activity, resulting in the poorest islet isolation outcome among the three groups. Additional retrospective analysis revealed that this suboptimal outcome in group C was not because of the absolute excessive amount of collagenase activity but as a result of the relatively high proportion of CII (i.e., unbalanced CII/CI ratio). Our study suggests that an excessive CII is ineffective in releasing islets from human pancreas, and rather a balanced CII/CI ratio is of paramount importance.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.351
Threshold uncertainty score0.928

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.034
GPT teacher head0.318
Teacher spread0.284 · 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 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

Citations23
Published2008
Admission routes1
Has abstractyes

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