RETRACTED: Targeting epithelial-mesenchymal transition signaling pathways with Dietary Phytocompounds and repurposed drug combinations for overcoming drug resistance in various cancers
Post-publication record
OpenAlex flags this work as retracted, but it carries no matching Retraction Watch record in this frame.
Bibliographic record
Abstract
The epithelial-to-mesenchymal transition (EMT) is a crucial step in metastasis formation. It enhances the ability of cancer cells' to self-renew and initiate tumors, while also increasing resistance to apoptosis and chemotherapy. Among the signaling pathways a few signaling pathways such as Notch, TGF-beta, and Wnt-beta catenin are critically involved in the epithelial-to-mesenchymal transition (EMT) acquisition. Therefore, regulating EMT is a key strategy for controlling malignant cell behavior. This is done by interconnecting other signaling pathways in many cancer types. Although there is extensive preclinical evidence regarding EMT's function in the development of cancer, there is still a deficiency in clinical translation at the therapeutic level. Thus, there is a need for medications that are both highly effective and with low cytotoxic for modulating EMT transitions at ground level. Thus, this led to the study of the evaluation and efficiency of phytochemicals found in dietary sources of fruits and vegetables and also the combination of small molecular repurposed drugs that can enhance the effectiveness of traditional cancer treatments. This review summarises major EMT-associated pathways and their cross talks with their mechanistic insights and the role of different dietary phytochemicals (curcumin, ginger, fennel, black pepper, and clove) and their natural analogs and also repurposed drugs (metformin, statin, chloroquine, and vitamin D) which are commonly used in regulating EMT in various preclinical studies. This review also investigates the concept of low-toxicity and broad spectrum ("The Halifax Project") approach which can help for site targeting of several key pathways and their mechanism. We also discuss the mechanisms of action, models for our dietary phytochemicals, and repurposed drugs and their combinations used to identify potential anti-EMT activities. Additionally, we also analyzed existing literature and proposed new directions for accelerating the discovery of novel drug candidates that are safe to administer.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.025 | 0.011 |
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".