Retracted Article: A high-throughput metabolomics strategy for discovering the influence of differential metabolites and metabolic pathways of huaxian capsules on sepsis-associated Qi deficiency and blood stasis syndrome
Post-publication record
Source: Retraction Watch, joined by DOI. OpenAlex records retraction as is_retracted, a boolean over a state space with at least four values, so it cannot express an expression of concern, a correction or a reinstatement; it reports them as false, which reads as “fine”.
Bibliographic record
Abstract
High-throughput metabolomics can be used to investigate the therapeutic targets and metabolic mechanisms of traditional Chinese medicine (TCM) formulae, which have multiple targets in disease therapy, but it is a great challenge to explore their mechanism of action. Huaxian capsule (HXC) is a classical formula in TCM that has therapeutic effects on a sepsis-associated Qi deficiency and blood stasis syndrome (SQBS). However, its targets and metabolic mechanisms need more investigation. To investigate the therapeutic effects of HXC in the treatment of SQBS and elucidate the potential mechanism, we used a high-throughput metabolomics strategy based on the ultraperformance liquid chromatography/mass spectrometry combined with chemometrics to analyze and identify differential metabolites and pathways. The pathological examination of organs and biochemical indices was also performed to verify the successful establishment of the rat model and protective effects of HXC. Pathological symptoms and biochemical indicators of SQBS rats were reversed by the HXC treatment. A total of 24 potential biomarkers were identified to indicate the difference between the control and model groups; they were closely associated with ten metabolic pathways and regulated by the HXC administration. From the pathway analysis, we further understood the protective activity of HXC against SQBS, which affected amino acid metabolism, molecular transport, small molecule biochemistry and cell signaling as well as vitamin and mineral metabolism. In conclusion, HXC protects against SQBS by modulating the metabolic biomarkers and functional pathways.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.033 | 0.012 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".