1657: Laboratory Investigation of Urinary Stone Composition and Structure by X-Ray Coherent Scatter: New Insights for Prevention?
Bibliographic record
Abstract
INTRODUCTION AND OBJECTIVE: Accurate stone analysis is important to determine which preventative strategy will benefit stone patients.Current laboratory techniques like infrared spectroscopy (IRS) and x-ray diffractometry (XRD) require small powdered samples for analysis.Since many stones are of mixed composition, an accurate analysis may only be achieved if several zones are sampled.We investigate the application of x-ray coherent scatter (CS) analysis to identify topographic urinary stone composition ex vivo.This transmissionbased XRD method depends on molecular structure and can therefore distinguish different compounds without destroying the stone.Diagnostic xray equipment facilitates examination of structural arrangements of minerals within intact calculi.METHODS: Tomographic CS images of various calculi were acquired with a purpose-built scanner.CS patterns were acquired in 0.25 mm increments as the intact stone was translated through the x-ray beam (70 kVp, 200 mA) for each of the 90 angular views.CS images were reconstructed and composition was extracted by fitting a library of pure stone component CS signatures to each image pixel signature.Two zones from each stone were powdered for IRS analysis and compared with CS RESULTS:.Each stone was also analyzed for bulk composition independently by IRS analysis.Results: CS composition maps revealed the spatial arrangement of minerals in intact calculi (see figure).IRS correlated with CS within 10% for selected regions-of-interest.Bulk composition performed by IRS, however, did not accurately identify all stone components.CONCLUSIONS: The examination of intact calculi by CS analysis revealed the presence of minerals and their spatial arrangement in composition image maps.These maps demonstrate that misrepresentations or oversights can occur due to inadequate sampling in IRS characterizations.Knowledge of the interrelationship between stone features and other important mechanistic properties can impact clinical decisions aimed at preventative therapies.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".