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Record W4409359879 · doi:10.1139/cjb-2024-0139

Liverworts as a hidden secret for soothing inflammation and alleviating pain

2025· article· en· W4409359879 on OpenAlexvenueno aff
Najla Meireles-Medeiros, Mateus Fernandes Oliveira, Andrea de Castro Perez, Adaíses Simone Maciel‐Silva

Bibliographic record

VenueBotany · 2025
Typearticle
Languageen
FieldHealth Professions
TopicInfant Health and Development
Canadian institutionsnot available
FundersCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsBiologyBotanyTraditional medicineMedicine

Abstract

fetched live from OpenAlex

Bryophytes, particularly liverworts, are known for producing bioactive compounds with therapeutic potential. In this review, we highlight the anti-inflammatory activities of liverworts, focusing on their ability to synthesize cannabinoids, compounds previously identified in only two genera. We explore the pharmacological parallels between liverwort cannabinoids and those from Cannabis sativa, emphasizing molecular similarities and interactions with the endocannabinoid system. Despite the promising nature of these compounds, there is a marked scarcity of studies exploring the pharmacological applications of liverwort-derived cannabinoids. This gap in research underscores the need for further investigation into their therapeutic potential. Additionally, we propose that cannabinoids or similar compounds may be more widespread in liverwort taxa than currently recognized, hypothesizing that other orders could also harbor these bioactive molecules. The potential discovery of new cannabinoids in liverworts could offer novel avenues for pharmacological exploitation. We conclude by calling for expanded chemical analyses to uncover more liverwort species with medicinally relevant compounds, which may reveal broader anti-inflammatory applications and therapeutic benefits.

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)0.002
metaresearch head score (Gemma)0.001
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.714
Threshold uncertainty score0.688

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.027
GPT teacher head0.382
Teacher spread0.355 · 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 designNot applicable
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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