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Record W2975456987 · doi:10.2147/dddt.s217211

<p>Hydrogels For Peptide Hormones Delivery: Therapeutic And Tissue Engineering Applications</p>

2019· review· en· W2975456987 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueDrug Design Development and Therapy · 2019
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHydrogels: synthesis, properties, applications
Canadian institutionsUniversity of Toronto
FundersKerman University of Medical Sciences
KeywordsSelf-healing hydrogelsPeptideHormoneTissue engineeringChemistryBiomedical engineeringInternal medicineMedicineBiochemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Peptides are the most abundant biological compounds in the cells that act as enzymes, hormones, structural element, and antibodies. Mostly, peptides have problems to move across the cells because of their size and poor cellular penetration. Therefore, a carrier that could transfer peptides into cells is ideal and would be effective for disease treatment. Until now, plenty of polymers, e.g., polysaccharides, polypeptides, and lipids were used in drug delivery. Hydrogels made from polysaccharides showed significant development in targeted delivery of peptide hormones because of their natural characteristics such as networks, pore sizes, sustainability, and response to external stimuli. The main aim of the present review was therefore, to gather the important usages of the hydrogels as a carrier in peptide hormone delivery and their application in tissue engineering and regenerative medicine.

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.973
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
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 head0.039
GPT teacher head0.265
Teacher spread0.226 · 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