Cell Adhesion and Spreading Affect Adipogenesis from Embryonic Stem Cells: The Role of Calreticulin
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
Calreticulin is an endoplasmic reticulum-resident multifunctional protein, which has been shown to influence numerous cellular processes, including cell adhesion. In this study, we characterized the adhesive properties of embryonic stem cells (ESCs) lacking calreticulin and showed that adipogenesis from ESCs is directly and reciprocally controlled by the adhesive status of a cell, which in turn is modulated by calreticulin. Calreticulin-deficient ESCs are not only highly adipogenic but also show elevated calmodulin/CaMKII signaling and poor adhesiveness compared with the wild-type ESCs. Calreticulin deficiency leads to a disorganized cytoskeleton and low levels of focal adhesion-related proteins, such as vinculin, paxillin, and phosphorylated focal adhesion kinase, which cause limited focal adhesion formation and limited fibronectin deposition. Moreover, differentiation on nonadhesive substrata, which hinder cell spreading, promoted adipogenesis in the wild-type ESCs that normally have low adipogenic potential, causing a decrease in focal adhesion protein expression and an increase in calmodulin/CaMKII signaling. In contrast, inhibition of CaMKII effectively increased focal adhesion protein levels and inhibited adipogenesis in calreticulin-deficient ESCs, causing them to behave like the low adipogenic, wild-type ESCs. Thus, the adipogenic potential of ESCs is proportional to their calmodulin/CaMKII activity but is inversely related to their focal adhesion protein levels and degree of adhesiveness/spreading.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".