Gut microbiota changes in airway diseases: a systematic review
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.
Bibliographic record
Abstract
<p><strong>Introduction</strong>: studies have highlighted the importance of gut microbiota (GM) to the host immune defenses, influencing the host<br />development and physiology. Changes in the composition and diversity of GM have been detected in some disease and could be<br />implicated in the pathophysiological mechanisms of them. <strong>Objective</strong>: the purpose of this study was to show an overview of the<br />current knowledge about the GM of patients with airway diseases (AD). Methodology: the literature search was performed in four<br />databases, using a combination of the descriptors: “Gastrointestinal Microbiome”, “Gut Microbiome”, “Gut Microbiota”, “Cystic Fibrosis”<br />(CF), “Asthma”, “Pulmonary Hypertension” (HP) and/or “Chronic Obstructive Pulmonary Disease” (COPD). <strong>Results</strong>: fifteen studies<br />were herein included: ten of CF and five of asthma. No study about other AD matched the inclusion criteria. In all studies about CF,<br />changes were detected in GM, particularly quantitative and qualitative microbial changes. For asthma, data showed changes in GM<br />also including a reduction of microbial richness, evenness and diversity and in the Bacteroidetes/Firmicutes ratio. Conclusions: the<br />current data indicate the existence of GM changes in AD. However, due to the few studies for asthma and the lack of investigations<br />on HP and COPD, it was not possible to confirm whether these GM changes are observed in other AD. Furthermore, this review shows<br />the necessity of more studies in this area to characterize dysbiosis and which alterations are more frequent observed in AD patients.</p>
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it