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Use of Donkey Milk in Cases of Cow’s Milk Protein Allergies

2015· article· en· W1261164543 on OpenAlexvenueno aff
Paolo Polidori, Ambra Ariani, Silvia Vincenzetti

Bibliographic record

VenueInternational Journal of Child Health and Nutrition · 2015
Typearticle
Languageen
FieldMedicine
TopicFood Allergy and Anaphylaxis Research
Canadian institutionsnot available
Fundersnot available
KeywordsDonkeyMedicineAllergyFood scienceCow milkImmunologyBiology

Abstract

fetched live from OpenAlex

Human breast milk is the best nutritional support that insure the right development and influence immune status of the newborn infant. However, when it is not possible to breast feeding may be necessary to use commercial infant formulas that mimic, where possible, the levels and types of vitamins, minerals and other nutrients present in human milk. Despite this, some formula-fed infant develops allergy, atopic disease and differences in response to infection with respect to breast-fed infants. Donkey milk may be considered a good substitute for dairy cow’s milk derivatives in feeding children with severe Cow’s Milk Protein Allergy (CMPA) since its composition is closer to human milk compared to other species commonly bred. It has been proposed as an alternative to cow’s milk for children affected by CMPA when it is not possible breast feeding. Donkey milk is characterized by a low casein content, with values very close to human milk, and also total whey protein content in donkey milk is very close to that found in human milk but higher compared to bovine milk. Donkey milk has been used in several clinical trials involving children affected by CMPA because of the low allergenicity of this milk. The results shown in this review confirmed the nutritional characteristics of the protein fractions of donkey milk and the possibility of using donkey milk in feeding children with CMPA, particularly after an adequate lipid integration, including children with multiple food allergies.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.294
Threshold uncertainty score0.199

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 head0.072
GPT teacher head0.363
Teacher spread0.291 · 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 designNot applicable
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

Citations29
Published2015
Admission routes1
Has abstractyes

Explore more

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