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Record W4392712712 · doi:10.1111/cns.14666

Hyperforin ameliorates neuroinflammation and white matter lesions by regulating microglial <scp>VEGFR<sub>2</sub></scp>/<scp>SRC</scp> pathway in vascular cognitive impairment mice

2024· article· en· W4392712712 on OpenAlexaff
Xin Gao, Jingjing Chen, Ge Yin, Yan Liu, Zhengsheng Gu, Rui Sun, Xu Sun, Xuehao Jiao, Ling Wang, Nuo Wang, Yanbo Zhang, Yuting Kan, Xiaoying Bi, Bingying Du

Bibliographic record

VenueCNS Neuroscience & Therapeutics · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicNatural Compound Pharmacology Studies
Canadian institutionsUniversity of Alberta
FundersNational Natural Science Foundation of China
KeywordsHyperforinNeuroinflammationPharmacologyHypericum perforatumNeuroprotectionMorris water navigation taskLuxol fast blue stainMicrogliaMedicineChemistryImmunologyHippocampusInternal medicineInflammation

Abstract

fetched live from OpenAlex

Abstract Aim To explore the neuroprotective potential of hyperforin and elucidate its underlying molecular mechanisms involved in its therapeutic effects against vascular cognitive impairment (VCI). Methods The active compounds and possible targets of Hypericum perforatum L. that may be effective against VCI were found by network pharmacology in this research. We utilized bilateral common carotid artery occlusion (BCCAO) surgery to induce a VCI mouse model. Morris water maze (MWM) and Y‐maze tests were used to assess VCI mice's cognitive abilities following treatment with hyperforin. To evaluate white matter lesions (WMLs), we utilized Luxol fast blue (LFB) stain and immunofluorescence (IF). Neuroinflammation was assessed using IF, western blot (WB), and enzyme‐linked immunosorbent assay (ELISA). The effects of hyperforin on microglia were investigated by subjecting the BV2 microglial cell line to oxygen–glucose deprivation/reperfusion (OGD/R) stimulation. The expressions of VEGFR 2 , p‐SRC, SRC, VEGFA, and inflammatory markers including IL‐10, IL‐1β, TNF‐α, and IL‐6 were subsequently assessed. Results The VEGFR 2 /SRC signaling pathway is essential for mediating the protective properties of hyperforin against VCI according to network pharmacology analysis. In vivo findings demonstrated that hyperforin effectively improved BCCAO‐induced cognitive impairment. Furthermore, staining results showed that hyperforin attenuated WMLs and reduced microglial activation in VCI mice. The hyperforin treatment group's ELISA results revealed a substantial decrease in IL‐1β, IL‐6, and TNF‐α levels. According to the results of in vitro experiments, hyperforin decreased the release of pro‐inflammatory mediators (TNF‐α, IL‐6, and IL‐1β) and blocked microglial M1‐polarization by modulating the VEGFR 2 /SRC signaling pathway. Conclusion Hyperforin effectively modulated microglial M1 polarization and neuroinflammation by inhibiting the VEGFR 2 /SRC signaling pathways, thereby ameliorating WMLs and cognitive impairment in VCI mice.

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 score0.286
Threshold uncertainty score0.776

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.023
GPT teacher head0.248
Teacher spread0.225 · 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

Citations9
Published2024
Admission routes1
Has abstractyes

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