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Record W4381243118 · doi:10.3390/life13061411

Recent Reports on Bioactive Compounds from Marine Cyanobacteria in Relation to Human Health Applications

2023· review· en· W4381243118 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

VenueLife · 2023
Typereview
Languageen
FieldEnergy
TopicAlgal biology and biofuel production
Canadian institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsCyanobacteriaHuman healthBiologyBacteriaMedicine

Abstract

fetched live from OpenAlex

The ocean is a valuable natural resource that contains numerous biologically active compounds with various bioactivities. The marine environment comprises unexplored sources that can be utilized to isolate novel compounds with bioactive properties. Marine cyanobacteria are an excellent source of bioactive compounds that have applications in human health, biofuel, cosmetics, and bioremediation. These cyanobacteria exhibit bioactive properties such as anti-inflammatory, anti-cancer, anti-bacterial, anti-parasitic, anti-diabetic, anti-viral, antioxidant, anti-aging, and anti-obesity effects, making them promising candidates for drug development. In recent decades, researchers have focused on isolating novel bioactive compounds from different marine cyanobacteria species for the development of therapeutics for various diseases that affect human health. This review provides an update on recent studies that explore the bioactive properties of marine cyanobacteria, with a particular focus on their potential use in human health applications.

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 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 score0.994
Threshold uncertainty score0.954

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.001

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 head0.086
GPT teacher head0.360
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