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Hyperforin promotes mitochondrial function and development of oligodendrocytes

2011· article· en· W2145243511 on OpenAlexafffund
Yanlin Wang, Yanbo Zhang, Jue He, Handi Zhang, Lan Xiao, Adil J. Nazarali, Zhijun Zhang, Dai Zhang, Jiming Kong, Xin‐Min Li

Bibliographic record

VenueJournal of Neurochemistry · 2011
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicNatural Compound Pharmacology Studies
Canadian institutionsUniversity of ManitobaUniversity of Saskatchewan
FundersCanadian Institutes of Health Research
KeywordsHyperforinOligodendrocyteProgenitor cellNeural stem cellAntidepressantNeuroscienceMitochondrionPharmacologyBiologyCell biologyHypericum perforatumChemistryStem cellCentral nervous systemHippocampusMyelin

Abstract

fetched live from OpenAlex

St. John's wort has been found to be an effective and safe herbal treatment for depression in several clinical trials. However, the underlying mechanism of its therapeutic effects is unclear. Recent studies show that the loss and malfunction of oligodendrocytes are closely related to the neuropathological changes in depression, which can be reversed by antidepressant treatment. In this study, we evaluated the effects of hyperforin, a major active component of St. John's wort, on the proliferation, development and mitochondrial function of oligodendrocytes. The study results revealed that hyperforin promotes maturation of oligodendrocytes and increases mitochondrial function without affecting proliferation of an oligodendrocyte progenitor cell line and neural stem/progenitor cells. Hyperforin also prevented mitochondrial toxin-induced cytotoxicity in an oligodendrocyte progenitor cell line. These findings suggest that hyperforin may stimulate the development and function of oligodendrocytes, which could be a mechanism of its effect in depression. Future in vitro and in vivo studies are required to further characterize the mechanisms of hyperforin.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.233
Threshold uncertainty score0.113

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.046
GPT teacher head0.228
Teacher spread0.182 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations25
Published2011
Admission routes2
Has abstractyes

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