Analysis of retrieved stroke thrombi from mechanical thrombectomy using X-ray fluorescence imaging and Fourier-transform infrared spectroscopy.
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
RATIONALE: With the recent technological advances in mechanical thrombectomy, and evidence that clearly demonstrates the need for fast and effective thrombus retrieval, it remains unclear as to which device and technique combination is most effective. Defining characteristics of stroke related thrombus with advanced synchrotron based imaging techniques, may help us better understand the biochemical composition of clots.METHODS: Freshly retrieved thrombi were characterized using advanced synchrotron based imaging techniques including, X-ray fluorescence (XRF) and Fourier-transform infrared spectroscopy (FTIR) to map the distribution of biological elements (Fe, Ca) and macromolecules (proteins, amides, glutamate), respectively. Clinical data and stroke outcome is acquired for those patients included in the study.RESULTS: XRF analysis exhibited increased distribution of P and Fe in fibrin-rich white clots. FTIR analysis demonstrated an increased distribution of amide I, amide II, proteins and glutamate in white clots.CONCLUSION: Thrombus characterization, while correlating patient clinical information as well as outcomes, will improve understanding of stroke treatment outcomes.ACKNOWLEDGMENTS: I would like to thank Sharleen Maley, Lilian Urroz, Ruth Whelan, Aaron Gardner and Aaron Huber for administrative and clinical support, and all the funding agencies including, Heart & Stroke Foundation, Saskatchewan, the Saskatchewan Health Research Foundation, and the University Of Saskatchewan College Of Medicine, the College of Medicine Research and Development (CoMRAD). I would like to thank the Canadian Light Source (CLS), and Stanford Synchrotron Radiation Laboratory (SSRL) for aiding in data collection.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.030 | 0.029 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.007 | 0.016 |
| Open science | 0.012 | 0.010 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.019 | 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