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Record W4386443572 · doi:10.3390/pharmaceutics15092284

Autophagy and Biomaterials: A Brief Overview of the Impact of Autophagy in Biomaterial Applications

2023· review· en· W4386443572 on OpenAlexafffund
Leila Pirmoradi, Shahla Shojaei, Saeid Ghavami, Atefeh Zarepour, Ali Zarrabi

Bibliographic record

VenuePharmaceutics · 2023
Typereview
Languageen
FieldMedicine
TopicAutophagy in Disease and Therapy
Canadian institutionsCancerCare ManitobaResearch Institute in Oncology and HematologyChildren's Hospital Research Institute of ManitobaUniversity of Manitoba
FundersTürkiye Bilimsel ve Teknolojik Araştırma KurumuUniversity of Manitoba
KeywordsAutophagyBiomaterialNanotechnologyComputational biologyCell biologyMedicineBiologyMaterials scienceBiochemistry

Abstract

fetched live from OpenAlex

Macroautophagy (hereafter autophagy), a tightly regulated physiological process that obliterates dysfunctional and damaged organelles and proteins, has a crucial role when biomaterials are applied for various purposes, including diagnosis, treatment, tissue engineering, and targeted drug delivery. The unparalleled physiochemical properties of nanomaterials make them a key component of medical strategies in different areas, such as osteogenesis, angiogenesis, neurodegenerative disease treatment, and cancer therapy. The application of implants and their modulatory effects on autophagy have been known in recent years. However, more studies are necessary to clarify the interactions and all the involved mechanisms. The advantages and disadvantages of nanomaterial-mediated autophagy need serious attention in both the biological and bioengineering fields. In this mini-review, the role of autophagy after biomaterial exploitation and the possible related mechanisms are explored.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.923
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
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 head0.249
GPT teacher head0.522
Teacher spread0.274 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations10
Published2023
Admission routes2
Has abstractyes

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