RETRACTED: Wheat extracts as an efficient cryoprotective agent for primary cultures of rat hepatocytes
Post-publication record
OpenAlex flags this work as retracted, but it carries no matching Retraction Watch record in this frame.
Bibliographic record
Abstract
Hepatocytes are an important physiological model for evaluation of metabolic and biological effects of xenobiotics. They do not proliferate in culture and are extremely sensitive to damage during freezing and thawing, even after the addition of classical cryoprotectants. Thus improved cryopreservation techniques are needed to reduce cell injury and functional impairment. Here, we describe a new and efficient cryopreservation method, which permits long-term storage and recovery of large quantities of healthy cells that maintain high hepatospecific functions. In culture, the morphology of hepatocytes cryopreserved with wheat protein extracts (WPE) was similar to that of fresh cells. Furthermore, hepatospecific functions such as albumin secretion and biotransformation of ammonium to urea were well maintained during 4 days in culture. Inductions of CYP1A1 and CYP2B in hepatocytes cryopreserved with WPEs were similar to those in fresh hepatocytes. These findings clearly show that WPEs are an excellent cryopreservant for primary hepatocytes. The extract was also found to cryopreserve other human and animal cell types such as lung carcinoma, colorectal adenocarcinoma, Chinese hamster ovary transfected with TGF-b1 cDNA, cervical cancer taken from Henrietta Lacks, intestinal epithelium, and T cell leukemia. WPEs have potential as a universal cryopreservant agent of mammalian cells. It is an economic, efficient and non-toxic agent.
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) | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".