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Record W4394542359 · doi:10.6084/m9.figshare.24037842

The pharmacological actions of Danzhi-xiaoyao-San on depression involve lysophosphatidic acid and microbiota-gut-brain axis: novel insights from a systems pharmacology analysis of a double-blind, randomized, placebo-controlled clinical trial

2023· dataset· en· W4394542359 on OpenAlexaff
Xiuqing Zhu, Shengwei Wu, Yufang Zhou, Tao Xiao, Liang Xia, Youtian Wang, Aixiang Xiao, Jianxiong Guo, Ming Zhang, Dewei Shang, Lin Yu

Bibliographic record

VenueFigshare · 2023
Typedataset
Languageen
FieldNeuroscience
TopicTryptophan and brain disorders
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsGut–brain axisLysophosphatidic acidPharmacologyMedicinePlaceboNeuroscienceClinical trialGut floraPsychologyInternal medicineReceptorAlternative medicine

Abstract

fetched live from OpenAlex

Danzhi-xiaoyao-San (DZXYS), a Traditional Chinese Medicine, plays an essential role in the clinical treatment of depression, but its mechanisms in humans remain unclear. To investigate its pharmacological effects and mechanisms as an add-on therapy for depression, we conducted a double-blind, placebo-controlled trial with depressed patients receiving selective serotonin reuptake inhibitors (SSRIs). Serum and fecal samples were collected for metabolomic and microbiome analysis using UHPLC-QTRAP-MS/MS and 16S rRNA gene sequencing technologies, respectively. Depression symptoms were assessed using the 24-item Hamilton Depression Scale. We employed network pharmacology, metabolomics, and molecular docking to identify potential targets associated with DZXYS. We also examined the correlation between gut microbes and metabolites to understand how DZXYS affects the microbiota-gut-brain axis. The results showed that DZXYS combined with SSRIs was more effective than SSRIs alone in improving depression. We identified 39 differential metabolites associated with DZXYS treatment and found seven upregulated metabolic pathways. The active ingredients quercetin and luteolin were docked to targets (AVPR2, EGFR, F2, and CDK6) associated with the enriched pathways ‘pancreatic cancer’ and ‘phospholipase D signaling pathway’, which included the metabolite lysophosphatidic acid [LPA(0:0/16:0)]. Additionally, we identified 32 differential gut microbiota species related to DZXYS treatment, with Bacteroides coprophilus and Ruminococcus gnavus showing negative correlations with specific metabolites such as L-2-aminobutyric acid and LPA(0:0/16:0). Our findings indicate that DZXYS's antidepressant mechanisms involve multiple targets, pathways, and the regulation of LPA and the microbiota-gut-brain axis. These insights from our systems pharmacology analysis contribute to a better understanding of DZXYS's potential pharmacological mechanisms in depression treatment. Communicated by Ramaswamy H. Sarma This study presents a double-blind, randomized, placebo-controlled clinical trial comparing the clinical effects of Danzhi-xiaoyao-San (DZXYS) plus selective serotonin reuptake inhibitors (SSRIs) and SSRIs alone. This study is the first system pharmacology approach to integrate multi-omics and network pharmacology and examine the clinical pharmacological mechanisms of DZXYS as an add-on therapy for depression. This study highlights that regulation of lysophosphatidic acid (LPA) and the microbiota-gut-brain axis by DZXYS plays an essential role in its antidepressant mechanisms.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.150
GPT teacher head0.389
Teacher spread0.238 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreDataset

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

Citations0
Published2023
Admission routes1
Has abstractyes

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