Hepatoprotective plants role in human health: A cross-kingdom review
Bibliographic record
Abstract
Liver, being one of the most fundamental and vital organ existing in human body and performing significant role in regulation of enormous number of biological processes including metabolism of biomolecules, secretion, storage, detoxification and excretion of xenobiotics from body. Accomplishment of all these processes leads to acute or chronic hepatic injuries and liver dysfunctions, which sequentially contributes to global health care threat as well as it is a concern for pharmaceutical industry as despite all advancements in medicine there is still a lack of completely assured hepato-protective drugs which stimulate and enhance liver function. However, nature full fills these vacant spaces by providing a number of plant derived hepatoprotective phytochemicals, which are comparatively less toxic and this leads to introduction of an alternative phytotherapeutic approach i.e., the use of poly herbal formulations for treatment of liver diseases. Throughout the world, herbalists claim the use of a number of remedial plants for treatment of hepatic dysfunctions. Nevertheless, recent research also reveals that not only phytochemicals, but also regulatory microRNAs are being transferred from plant to animal kingdom. Thus, this leads to an alternative concept of cross-kingdom gene regulation by non-coding tiny molecules i.e. orally consumed plant derived xeno-MIRs play a chief role in human health regulation. The abilities of microRNAs to regulate cross-kingdom gene regulation have prompted the hopes to explore this novel concept in diagnosis, prognosis and treatment as potential therapeutic and dietary supplements. The present review is aimed to compile the available data of promising hepatoprotective plants and introduce the cross-kingdom gene regulation approach as potential therapy for human health care.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".