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Record W4407700003 · doi:10.1021/acs.jnatprod.4c01359

Secondary Metabolites of the Lichen <i>Lethariella cladonioides</i> and Their Neuroprotective Potential

2025· article· en· W4407700003 on OpenAlexaff
Lei Zhang, Wen-Hua Chao, Cui-Cui Tan, Zhiying Dou, Feng Qiu, Yu‐Ming Liu, Li‐Ning Wang

Bibliographic record

VenueJournal of Natural Products · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLichen and fungal ecology
Canadian institutionsOptech (Canada)
FundersTianjin Research Program of Application Foundation and Advanced Technology of ChinaNational Key Research and Development Program of China
KeywordsLichenNeuroprotectionPharmacognosyChemistryStereochemistryBotanyBiologyPharmacologyBiological activityBiochemistryIn vitro

Abstract

fetched live from OpenAlex

In the pathogenesis of neurodegenerative diseases, particularly Alzheimer’s disease, cholinergic neuron dysfunction and neuroinflammation are integral components. Against this backdrop, within the vast array of potential sources under exploration, Lethariella cladonioides, a remarkable lichen with profound ethnopharmacological significance among various Chinese ethnic minorities, has recently emerged as a promising candidate. Through our comprehensive phytochemical investigation, five undescribed diphenylmethanes ( 1 – 5 ), three unreported depsides ( 6 – 8 ), and one novel diphenylether ( 9 ), along with 16 known compounds, were successfully isolated and identified. Their structures were elucidated by spectroscopic analysis and X-ray crystallography. Specifically, compounds 3 – 7 and 9 exhibited acetylcholinesterase inhibitory activity, while compounds 1, 2, and 4 significantly inhibited NO production by LPS in RAW264.7 cells. Collectively, these findings suggest that L. cladonioides has potential value in preventing and treating neurodegenerative diseases. This potential lies in its ability to potentially retard disease progression or alleviate symptoms by enhancing cholinergic transmission and mitigating neuroinflammation.

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 score0.380
Threshold uncertainty score0.229

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 integrity0.0000.001
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 head0.004
GPT teacher head0.179
Teacher spread0.175 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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