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Record W2058727950 · doi:10.1159/000366281

Psychobiotics and Their Involvement in Mental Health

2014· editorial· en· W2058727950 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueMicrobial Physiology · 2014
Typeeditorial
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsnot available
Fundersnot available
KeywordsMicrobiomeGut bacteriaBacteriaProbioticBiologyChemistryBioinformaticsGenetics

Abstract

fetched live from OpenAlex

Editorial J Mol Microbiol Biotechnol 2014;24:211–214 DOI: 10.1159/000366281 Published online: August 30, 2014 Psychobiotics and Their Involvement in Mental Health Fengyi Tang a Bhaskara L. Reddy a, b Milton H. Saier Jr. a a Ingested prebiotic organic compounds stimulate the growth of intestinal probiotic bacteria [Saier and Man- sour, 2005]. Pre- and probiotics represent important components in chains of complex biosynthetic and cata- bolic reactions that provide tremendous health benefits to the human or animal host organism [Singh et al., 2013; Vitetta et al., 2014]. These bacteria, which in part com- prise the intestinal microbiome, do so by supplying nu- trients such as short-chain fatty acids [Ohashi and Ush- ida, 2009] and precursors of enzyme cofactors including vitamin B 12 [Capozzi et al., 2012]. They also successfully compete with potential pathogens [Corr et al., 2009] and stimulate host immune responses [Jirillo et al., 2012; Vi- taliti et al., 2014]. They strongly influence either posi- tively or negatively, depending on the bacterial types present, symptoms of numerous metabolic disorders in- cluding those responsible, in part, for the current obesity epidemic [Kotzampassi et al., 2014; Vitetta et al., 2014]. Therefore, not surprisingly, malnutrition in children has been shown to be associated with a lack of certain crucial gut bacteria [Subramanian et al., 2014]. It is now clear that the intestinal microbiome influences innumerable processes essential for the physical fitness of animals and humans. © 2014 S. Karger AG, Basel E-Mail karger@karger.com www.karger.com/mmb The contribution of beneficial gut bacteria to human health is now scientifically well established [Shanahan et al., 2012]. The predominant well-studied probiotic bacte- ria are Firmicutes such as Lactobacillus species, Actino- bacteria such as Bifidobacterium species and Bacteroide- tes such as Bacteroides species. Several others, including Proteobacteria such as certain Escherichia coli strains, have also been shown to exhibit probiotic qualities. In fact, all of these microbes have beneficial consequences to the host organism. In only a few cases have the probiotic bacterial mechanisms of action been elucidated [Butel, Since these bacteria influence so many aspects of hu- man physiology, it should not be considered surprising that recent studies have revealed that they also have pro- nounced effects on brain function. Indeed, these bacteria produce tryptophan, a precursor of serotonin (5-hy- droxytryptamine), tyrosine, a precursor of L-3,4-dihy- droxyphenylalanine (DOPA) and dopamine, and other amino acids such as γ-amino butyric acid (GABA) and glycine, both of which serve as neurotransmitters in ani- mals [Clarke et al., 2014b]. In fact, recent research has shown that the microbiota strongly influences brain ac- tivity and consequently behavior. It exerts effects on our moods, cognition and sensitivities to pain [Borre et al., Milton H. Saier Jr. Department of Molecular Biology Division of Biological Sciences, University of California at San Diego La Jolla, CA 92093-0116 (USA) E-Mail msaier @ ucsd.edu Downloaded by: Univ. of California San Diego 132.239.144.87 - 2/15/2017 1:46:22 AM Department of Molecular Biology, Division of Biological Sciences, University of California at San Diego, La Jolla, Calif. , and b Department of Mathematics and Natural Sciences, College of Letters and Sciences, National University, Ontario, Calif. , USA

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.461
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.006
GPT teacher head0.258
Teacher spread0.253 · 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