Bibliographic record
Abstract
Introduction and Objective: Cryoablation has emerged as a primary therapy to treat prostate cancer.While effective, the assumption that freezing serves as a ubiquitous lethal stress is challenged by clinical experience and experimental evidence demonstrating time-temperature related cell death dependence.The age-related transformation from an androgen-sensitive (AS) to an androgen-insensitive (AI) phenotype is a major challenge in the management of prostate cancer.AI cells exhibit morphological changes and treatment resistance to many therapies.This resistance has been linked with α6 4 integrin overexpression as a result of androgen receptor (AR) loss.As such, we investigated the influence of increased α6 4 integrin expression as a result of AR loss, on the reported increased freeze tolerance of AI prostate cancer.Further, we evaluated the targeted modulation of integrin expression in combination with cryoablation on human prostate cancer cell death.Methods: A series of studies using AS (LNCaP LP and PC-3 AR) and AI (LNCaP HP and PC-3) cell lines were designed to investigate the cellular mechanisms contributing to variations in freezing response.Samples were frozen, thawed, and temporally assessed using fluorescence microscopy, flow cytometry and immunoblotting.Results: Investigation into α6 4 integrin expression revealed that AI cell lines overexpressed this protein, thereby altering morphology and increasing adhesion characteristics.For instance, following freezing to -15°C, AI cells were found to exhibit increased resistance to freezing injury compared to AS cells (55% vs. 18%, respectively).Molecular investigations revealed a significant decrease in caspase 8, 9, and 3 levels in AI cells following freezing.Inhibition of α6 4 integrin in AI samples resulted in increased caspase activity and enhanced cell death.Conclusions: These studies demonstrate that integrin expression significantly influences cell tolerance to cryoablation.The data demonstrate that the inhibition of α6 4 integrin function results in a significant increase in freeze sensitivity of AI prostate cancer cells.The results show that understanding the role of androgen-receptor related integrin expression in cell response to freezing may lead to novel options for neo-adjunctive approaches to treat prostate cancer.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.451 | 0.206 |
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".