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Record W4400040402 · doi:10.3389/fnut.2024.1409381

New alternatives to holder pasteurization in processing donor milk in human milk banks

2024· article· en· W4400040402 on OpenAlexaff
Guido E. Moro, M Girard, Chiara Peila, Nadia Garcia, Diana Escuder‐Vieco, Kristin Keller, Tanya Cassidy, Enrico Bertino, Clair‐Yves Boquien, Rachel Buffin, Javier Calvo, Antoni Gayà, Corinna Gebauer, Delphine Lamireau, David Lembo, Jean‐Charles Picaud, Aleksandra Wesołowska, Sertaç Arslanoğlu, Laura Cavallarin, Marzia Giribaldi

Bibliographic record

VenueFrontiers in Nutrition · 2024
Typearticle
Languageen
FieldNursing
TopicInfant Nutrition and Health
Canadian institutionsHéma-Québec
Fundersnot available
KeywordsPasteurizationFood scienceSterilization (economics)Hop (telecommunications)PascalizationChemistryBusinessEnvironmental scienceHigh pressureComputer scienceEngineeringTelecommunications

Abstract

fetched live from OpenAlex

Infectious and toxicological risks are the main potential hazards that operators of Human Milk Banks (HMBs) encounter and must eliminate. HMBs are trying to implement procedures that allow to manage and sanitize human milk without altering significantly its nutritional and biologically protective components, obtaining a product characterized by a valid balance between safety and biological quality. The history of human milk processing is linked to the origins of HMBs themselves. And although other forms of sterilization were used originally, pasteurization soon became the recognized most effective means for sanitizing milk: all the milk that arrives at the HMB must be pasteurized. Holder pasteurization (HoP) is the most used methodology, and it is performed using low temperature and long time (+62.5°C for 30 min). With HoP some bioactive milk components are lost to varying degrees, but many other precious bioactive compounds are completely or partially preserved. To improve the quality of human milk processed by HMBs, maintaining in the meantime the same microbiological safety offered by HoP, new technologies are under evaluation. At present, High-Temperature Short-Time pasteurization (HTST) and High-Pressure Processing are the most studied methodologies. HTST is already utilized in some HMBs for daily practical activity and for research purposes. They seem to be superior to HoP for a better preservation of some nutritional and biologically protective components. Freeze-drying or lyophilization may have advantages for room temperature storage and transportation. The aim of this study is to evaluate the advancement regarding the processing of DHM with a literature search from 2019 to 2022. The effects of the new technologies on safety and quality of human milk are presented and discussed. The new technologies should assure microbiological safety of the final product at least at the same level as optimized HoP, with an improved preservation of the nutritional and bioactive components of raw human milk.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.016
GPT teacher head0.306
Teacher spread0.290 · 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 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

Citations14
Published2024
Admission routes1
Has abstractyes

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