Evaluation of Milk Colostrum Derived Lactoferrin of Sahiwal (Bos indicus) and Karan Fries (Cross-Bred) Cows for Its Anti-Cancerous Potential
Bibliographic record
Abstract
Lactoferrin (Lf) is an iron-binding glycoprotein protein known to have immune-modulatory role and recently, its anticancerous effect against different cancer cell types was emphasized. In the present investigation, a comparative evaluation of anticancer potential of colostrum-derived lactoferrin from Indian native zebu cow (Sahiwal, SAC), crossbred (Karan Fries, KFC) and commercially available (C-Lf) lactoferrin from exotic cow using cellular models was made. A protocol was standardized successfully to purify Lf protein from colostrum of both breeds using HPLC and purity was confirmed by LC–MS. A standardized dose of 750 µg/mL Lf was used to treat two cell types MDA-MB-231 and MCF-7 with Lf from three different sources; SAC-Lf, KFC-Lf and C-Lf for 48 h and 72 h. Different cellular parameters including cytotoxicity, viability, apoptosis and cell proliferation were determined. Comparatively, Lf from commercial source (C-Lf) had maximum effect in both cell types followed by SAC-Lf and KFC-Lf. Further, transcriptional changes in genes associated with apoptosis (Bax and Bcl-2), tumor progression (p53, p21, CD44 and NF-κβ) and survival (survivin) were evaluated in Lf treatment. The overall results strongly emphasized to the fact that Lf purified from cow colostrum has the capacity to inhibit the in vitro growth of cancerous cell lines albeit to a varied extent.
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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".