Twist: a new player in the epithelial-mesenchymal transition of the peritoneal mesothelial cells
Bibliographic record
Abstract
BACKGROUND: The peritoneal membrane is a vital structure for peritoneal dialysis (PD) patients. It has been increasingly recognized that the transition of the peritoneal lining mesothelial cells into a more fibroblastic phenotype is a key step in peritoneal membrane injury. METHODS: Relevant literature was reviewed and summarized. RESULTS: Epithelial-to-mesenchymal transition (EMT) is a basic cellular process that occurs in a variety of physiologic and pathologic processes. The hallmark of this process is a loss of epithelial markers, and E-cadherin is a prototypical epithelial transmembrane protein. E-cadherin expression is suppressed at many levels and the gene is regulated by a family of transcription factors. Twist is one of the lesser studied E-cadherin regulatory factors, which belongs to a larger family of basic helix-loop-helix DNA-binding proteins. In this issue of Nephrology Dialysis Transplantation, Cuixiang Li reports on in vitro experiments where the expression of Twist led to a decreased expression of E-cadherin and the evidence of EMT. In an in vivo model of dialysate exposure, Li demonstrates that Twist expression is increased in the injured peritoneal tissues. CONCLUSIONS: These important observations are the first to link Twist to mesothelial cell EMT and peritoneal membrane injury. Like most novel observations, this paper leaves many questions unanswered. Twist is only one of several transcription factors involved in EMT and how these factors interact will require further investigations. Furthermore, the question of whether Twist interacts at multiple levels in the EMT process, or simply gives an initial push to the process, is left unanswered. Finally, to bring these early significant findings to the bedside as potential therapies for PD patients will require further innovation.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".