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Record W3185159821 · doi:10.3390/nu13082492

Lactoferrin and Its Detection Methods: A Review

2021· review· en· W3185159821 on OpenAlexafffund
Yingqi Zhang, Chao Lu, Jin Zhang

Bibliographic record

VenueNutrients · 2021
Typereview
Languageen
FieldNursing
TopicInfant Nutrition and Health
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsLactoferrinBiomarkerDiseaseInflammatory bowel diseaseHuman diseaseMedicineComputational biologyBiologyBioinformaticsBiochemistryPathology

Abstract

fetched live from OpenAlex

Lactoferrin (LF) is one of the major functional proteins in maintaining human health due to its antioxidant, antibacterial, antiviral, and anti-inflammatory activities. Abnormal levels of LF in the human body are related to some serious diseases, such as inflammatory bowel disease, Alzheimer's disease and dry eye disease. Recent studies indicate that LF can be used as a biomarker for diagnosis of these diseases. Many methods have been developed to detect the level of LF. In this review, the biofunctions of LF and its potential to work as a biomarker are introduced. In addition, the current methods of detecting lactoferrin have been presented and discussed. We hope that this review will inspire efforts in the development of new sensing systems for LF detection.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.862
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.132
GPT teacher head0.489
Teacher spread0.357 · 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.

Study designOther design
Domainnot available
GenreReview

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

Citations85
Published2021
Admission routes2
Has abstractyes

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