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Record W4401890089 · doi:10.1002/adhm.202401713

Enzymes in Addressing Hypoxia for Biomaterials Engineering

2024· review· en· W4401890089 on OpenAlexaff
Pejman Ghaffari‐Bohlouli, Hafez Jafari, Lei Nie, Ashok Kakkar, Amin Shavandi

Bibliographic record

VenueAdvanced Healthcare Materials · 2024
Typereview
Languageen
FieldMaterials Science
TopicAdvanced Nanomaterials in Catalysis
Canadian institutionsMcGill University
FundersWallonie-Bruxelles InternationalNatural Science Foundation of Henan ProvinceFonds De La Recherche Scientifique - FNRS
KeywordsHypoxia (environmental)Tissue engineeringEnzymeMaterials scienceNanotechnologyChemistryBiomedical engineeringBiochemistryMedicineOxygenOrganic chemistry

Abstract

fetched live from OpenAlex

Oxygen is essential for normal cellular functions. Hypoxia impacts various cellular processes, such as metabolism, growth, proliferation, angiogenesis, metastasis, tumorigenesis, microbial infection, and immune response, mediated by hypoxia-inducible factors (HIFs). Hypoxia contributes to the progression and development of cancer, cardiovascular diseases, metabolic disorders, kidney diseases, and infections. The potential alleviation of hypoxia has been explored through the enzymatic in situ decomposition of hydrogen peroxide, leading to the generation of oxygen. However, challenges such as limited stability restrict the effectiveness of enzymes such as catalase in biomedical and in vivo applications. To overcome these limitations, targeted delivery of the enzymes has been proposed. This review offers a critical comparison of i) current approaches to enhance the in vivo stability of catalase; and ii) the structure, mechanism of action, and kinetics of catalase and catalase-like nanozymes.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.647
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0060.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.099
GPT teacher head0.417
Teacher spread0.319 · 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; both teacher heads agree on what is shown here.

Study designBench or experimental
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

Citations7
Published2024
Admission routes1
Has abstractyes

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