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Record W2906405458 · doi:10.1039/c8cs00304a

Hypoxia-targeted drug delivery

2018· review· en· W2906405458 on OpenAlexaff
Amit Sharma, Jonathan F. Arambula, Seyoung Koo, Rajesh Kumar, H.B. Singh, Jonathan L. Sessler, Jong Seung Kim

Bibliographic record

VenueChemical Society Reviews · 2018
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Hypoxia, and Metabolism
Canadian institutionsUniversity of Manitoba
FundersNational Cancer InstituteNational Research Foundation of KoreaWelch Foundation
KeywordsHypoxia (environmental)DrugOxygen deliveryOxygen tensionPharmacologyChemistryOxygenDrug deliveryMedicineOrganic chemistry

Abstract

fetched live from OpenAlex

Hypoxia is a state of low oxygen tension found in numerous solid tumours. It is typically associated with abnormal vasculature, which results in a reduced supply of oxygen and nutrients, as well as impaired delivery of drugs. The hypoxic nature of tumours often leads to the development of localized heterogeneous environments characterized by variable oxygen concentrations, relatively low pH, and increased levels of reactive oxygen species (ROS). The hypoxic heterogeneity promotes tumour invasiveness, metastasis, angiogenesis, and an increase in multidrug-resistant proteins. These factors decrease the therapeutic efficacy of anticancer drugs and can provide a barrier to advancing drug leads beyond the early stages of preclinical development. This review highlights various hypoxia-targeted and activated design strategies for the formulation of drugs or prodrugs and their mechanism of action for tumour diagnosis and treatment.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.003

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 head0.032
GPT teacher head0.302
Teacher spread0.270 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations538
Published2018
Admission routes1
Has abstractyes

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