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Record W1968044944 · doi:10.4236/mc.2014.31001

Intraperitoneal distribution of alginate microcapsules in mice

2014· article· en· W1968044944 on OpenAlexaff
François Dagbert, Yarrow J. McConnell, E. Carmona, Lucas Sidéris, Jean‐Pierre Hallé, Pierre‐André Dubé

Bibliographic record

VenueModern Chemotherapy · 2014
Typearticle
Languageen
FieldMedicine
TopicIntraperitoneal and Appendiceal Malignancies
Canadian institutionsUniversity of CalgaryUniversité de MontréalHôpital Maisonneuve-Rosemont
Fundersnot available
KeywordsPeritoneumPeritoneal cavityMedicineLaparotomyDistribution (mathematics)Drug deliveryAbdominal cavityIntraperitoneal injectionMicrosphereSurgeryPharmacologyChemistry

Abstract

fetched live from OpenAlex

Introduction: Improved drug delivery mechanisms for the treatment of residual peritoneal cancer cells following cytoreduction surgery are needed. Alginate microcapsules are a potentially useful mechanism for delivery of bioengineered cells, but when injected into the peritoneum, their distribution and properties are not well described. Methods: Aliquots of 300, 600 or 1200 microcapsules were injected into the peritoneum of 81 mice. Mice were sacrificed at 6, 12, 18, and 48 days and laparotomy was performed to quantify the distribution of microspheres. Results: The injections were well tolerated for up to 48 days. No peritoneal adherence or inflammatory reaction was noted to the microcapsules. Injection of 1200 microcapsules resulted in a better overall persistence and widespread peritoneal distribution at up to 48 days. The volume of fluid used for injection of the microcapsules did not affect their distribution or persistence. Conclusion: The intraperitoneal injection of alginate microspheres allows wide and persistent distribution throughout the abdominal cavity. The next step is to test the distribution of microcapsules when delivered following surgery in a rodent model.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.053
Threshold uncertainty score0.501

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)0.0000.000

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 head0.007
GPT teacher head0.237
Teacher spread0.230 · 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

Citations5
Published2014
Admission routes1
Has abstractyes

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