Camel whey protein hydrolysates induced G2/M cellcycle arrest in human colorectal carcinoma
Bibliographic record
Abstract
Abstract Camel milk has been gaining immmense importance due to high nutritious value and medicinal properties. Peptides from milk proteins is gaining popularity in various therapeutics including human cancer. The study was aimed to investigate the anti-cancerous and anti-inflammatory properties of camel whey protein hydrolysates (CWPHs). CWPHs were generated at three temperatures (30 ℃, 37 ℃, and 45 ℃), two hydrolysis timepoints (120 and 360 min) and with three different enzyme concentrations (0.5, 1 and 2 %). CWPHs demonstrated an increase in anti-inflammatory effect between 732.50 (P-6.1) and 3779.16 (P-2.1) µg Dicolfenac Sodium Equivalent (DSE)/mg protein. CWPHs (P-4.3 & 5.2) inhibited growth of human colon carcinoma cells (HCT116) with an IC 50 value of 231 and 221 μg/ml, respectively. P-4.3 induced G2/M cell cycle arrest and modulated the expression of Cdk1, p-Cdk1, Cyclin B1, p-histone H3, p21 and p53. Docking of two peptides (AHLEQVLLR and ALPNIDPPTVER) from CWPHs (P-4.3) identified Polo like kinase 1 as a potential target, which strongly supports our in vitro data and provides an encouraging insight into developing a novel peptide-based anticancer formulation. These results suggest that the active component, CWPHs (P-4.3), can be further studied and modeled to form a small molecule anti-cancerous therapy.
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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) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".