Current update and future directions on gut microbiome and nephrolithiasis
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
<br>The incidence of nephrolithiasis is increasing worldwide. Understanding how gut microbiome influences oxalate homeostasis has the potential to offer new strategies to prevent nephrolithiasis. The literature was reviewed to gather the evidence on the association between gut microbiome, hyperoxaluria and nephrolithiasis, and to identify the therapeutic interventions focused on the gut microbiome that could decrease hyperoxaluria and prevent nephrolithiasis. Gut microbiome is constituted by a plethora of microbiota including<i> Oxalobacter formigenes </i>(Oxf) and lactobacilli. Oxf can degrade dietary oxalate and induce enteral oxalate secretion. Animal studies suggested an association between oral <i>Oxf</i> supplementation and a decrease in hyperoxaluria. However, human studies have showed inconsistent results. Oral supplementation of lactobacilli did not show benefit in decreasing the hyperoxaluria. Antibiotic exposure, by affecting the gut microbiome, has been associated with an increase in nephrolithiasis. <i>In vivo</i> studies suggest fecal transplantation as a potential treatment option for reducing nephrolithiasis, but needs further evaluation in clinical studies. The current evidence suggests an association between gut microbiome and nephrolithiasis. However, the strategies focused on modulating gut microbiome for decreasing hyperoxaluria and preventing nephrolithiasis need further research. Judicious use of antibiotics in those predisposed to nephrolithiasis offers a preventative strategy for decreasing nephrolithiasis.<br>
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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