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Lactic Acid Bacteria in Pharmaceutical Formulations: Presence and Viability of “Healthy Microorganisms”

2014· article· en· W2100503421 on OpenAlexvenueno aff
Mariantonietta Succi, Elena Sorrentino, Tiziana Di Renzo, Patrizio Tremonte, Anna Reale, Luca Tipaldi, Gianfranco Pannella, A Russo, Raffaele Coppola

Bibliographic record

VenueJournal of Pharmacy and Nutrition Sciences · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicProbiotics and Fermented Foods
Canadian institutionsnot available
Fundersnot available
KeywordsLactic acidProbioticBacteriaMicroorganismBiologyFood scienceMicrobiology

Abstract

fetched live from OpenAlex

Many probiotic formulations are available in the market and are advertised for several preventive or curative roles. The aim of this study was the identification of microorganisms composing different lactic acid bacteria based pharmaceutical formulations and the ascertainment of their ability to survive gastro-intestinal (GI) stresses, the main requisite to produce beneficial effects. For this purpose, viable bacteria were enumerated by plate counts in different media. Denaturing Gradient Gel Electrophoresis-Polymerase Chain Reaction (PCR-DGGE) analysis was applied on pure isolates and on crude formulations to confirm the composition in species. Also, crude formulations were subjected to stresses characteristic of the GI tract (GIT) to assess cell survival. Results highlighted concentrations lower than those reported in the labels in almost all the formulations. Moreover, some discrepancies were observed between reported species and those ascertained through the identification, and the use of an erroneous nomenclature was highlighted. The GI stress test revealed that bacteria are strongly injured, and this fact was evidenced by a marked reduction in viable counts after the stress. In conclusion, a widespread number of lactic acid bacteria based formulations are sold as probiotics, but their probiotic requisites are not adequately observed.

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 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 score0.420
Threshold uncertainty score0.100

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.049
GPT teacher head0.335
Teacher spread0.286 · 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

Citations10
Published2014
Admission routes1
Has abstractyes

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