MétaCan
Menu
Back to cohort
Record W2069656494 · doi:10.1186/1471-2407-13-492

Selenized milk casein in the diet of BALB/c nude mice reduces growth of intramammary MCF-7 tumors

2013· article· en· W2069656494 on OpenAlexafffund
Jenny Warrington, Julie J.M. Kim, Priska Stahel, Scott Cieslar, Roger A. Moorehead, Brenda L. Coomber, Milena Corredig, J.P. Cant

Bibliographic record

VenueBMC Cancer · 2013
Typearticle
Languageen
FieldNursing
TopicSelenium in Biological Systems
Canadian institutionsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of CanadaDairy Farmers of OntarioUniversity of Guelph
KeywordsMammary tumorCaseinSeleniumSurgical oncologyApoptosisEndocrinologyMedicineInternal medicineAndrologyChemistryCancerBreast cancerFood scienceBiochemistry

Abstract

fetched live from OpenAlex

BACKGROUND: Dietary selenium has the potential to reduce growth of mammary tumors. Increasing the Se content of cows' milk proteins is a potentially effective means to increase Se intake in humans. We investigate the effects of selenized milk protein on human mammary tumor progression in immunodeficient BALB/c nude mice. METHODS: Four isonitrogenous diets with selenium levels of 0.16, 0.51, 0.85 and 1.15 ppm were formulated by mixing low- and high-selenium milk casein isolates with a rodent premix. MCF-7 cells were inoculated into the mammary fat pad of female BALB/c nude mice implanted with slow-release 17 β-estradiol pellets. Mice with palpable tumors were randomly assigned to one of the four diets for 10 weeks, during which time weekly tumor caliper measurements were conducted. Individual growth curves were fit with the Gompertz equation. Apoptotic cells and Bcl-2, Bax, and Cyclin D1 protein levels in tumors were determined. RESULTS: There was a linear decrease in mean tumor volume at 70 days with increasing Se intake (P < 0.05), where final tumor volume decreased 35% between 0.16 and 1.15 ppm Se. There was a linear decrease in mean predicted tumor volume at 56, 63 and 70 days, and the number of tumors with a final volume above 500 mm3, with increasing Se intake (P < 0.05). This tumor volume effect was associated with a decrease in the proportion of tumors with a maximum growth rate above 0.03 day-1. The predicted maximum volume of tumors (Vmax) and the number of tumors with a large Vmax, were not affected by Se-casein. Final tumor mass, Bcl-2, Bax, and Cyclin D1 protein levels in tumors were not significantly affected by Se-casein. There was a significantly higher number of apoptotic cells in high-Se tumors as compared to low-Se tumors. CONCLUSIONS: Taken together, these results suggest that turnover of cells in the tumor, but not its nutrient supply, were affected by dairy Se. We have shown that 1.1 ppm dietary Se from selenized casein can effectively reduce tumor progression in an MCF-7 xenograft breast cancer model. These results show promise for selenized milk protein as an effective supplement during chemotherapy.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.379
Threshold uncertainty score0.980

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.024
GPT teacher head0.273
Teacher spread0.249 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations13
Published2013
Admission routes2
Has abstractyes

Explore more

Same venueBMC CancerSame topicSelenium in Biological SystemsFrench-language works237,207