Bibliographic record
Abstract
Probiotics are live nonpathogenic organisms that promote beneficial health effects when ingested. Increasing numbers of reports indicate that probiotics may have therapeutic potential in disorders ranging from atopic dermatitis to arthritis, highlighting the systemic impact of these organisms. While probiotics have been proposed as adjuvant therapy for depression, to date little is known of the ability of probiotic treatment to modulate brain function. The brain and the gut are engaged in constant bidirectional communication. Such communication becomes apparent when alterations in gastrointestinal (GI) function are communicated to the brain, bringing about the perception of visceral events such as nausea, satiety, and pain or when, in turn, stressful experiences lead to altered GI secretions and motility. This communication system involves neural pathways as well as immune and endocrine mechanisms. Consistent observations have suggested that patients with major depression who are otherwise healthy have activated inflammatory pathways, as indicated by increased proinflammatory cytokines, increased acute-phase proteins, and greater expression of chemokines and adhesion molecules. In addition to direct neural pathways, the gut also communicates to the brain utilizing hormonal signaling pathways that involve the release of gut peptides from enteroendocrine cells which can act directly on the brain at the area postrema, one of the circumventricular organs that lie outside the blood-brain barrier. Future research should be aimed at determining specific mechanisms involved in linking the human microbiota in general with central nervous system (CNS) homeostasis and function.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.021 | 0.009 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".