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Lactoferrin in Malignant Human Tumours: New Insights from an Immunohistochemical Meta-Analysis

2013· article· en· W2149566079 on OpenAlexvenueno aff
Antonio Ieni, Valeria Barresi, Giuseppe Giuffrè, Giovanni Tuccari

Bibliographic record

VenueJournal of Analytical Oncology · 2013
Typearticle
Languageen
FieldNursing
TopicInfant Nutrition and Health
Canadian institutionsnot available
Fundersnot available
KeywordsLactoferrinImmunohistochemistryGlycoproteinReceptorPathologyIntracellularBiologyCancer researchCell biologyMedicineMolecular biologyBiochemistry

Abstract

fetched live from OpenAlex

Lactoferrin (LF), an iron-binding glycoprotein, is well known to have different physiological activities in humans; in normal conditions, it has been found in milk, blood, urine as well as in many external and mucosal secretions. Herein we have performed a meta-analysis regarding LF immunohistochemical expression as well as its localization pattern in human malignant tumours obtained from personal observations and literature suggestions. The observed heterogeneity in LF immunoexpression between different malignancies as well as inside the same tumour was also discussed in order to acquire a possible explanation for its presence and function. We suggest that neoplastic elements should be able to produce LF in order to make a greater amount of iron available for their turnover; alternatively, the localization of LF in malignant cells may not reflect an intracellular synthesis, reflecting instead the degree of trans-membranous iron transfer as the consequence of defective or functionally impaired LF-receptors, already documented elsewhere on the surface of target cells as well as in human neoplastic cell lines.

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.084
GPT teacher head0.400
Teacher spread0.316 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
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

Citations0
Published2013
Admission routes1
Has abstractyes

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