A broadband continuous-wave multichannel near-infrared system for measuring regional cerebral blood flow and oxygen consumption in newborn piglets
Bibliographic record
Abstract
Near-infrared spectroscopy (NIRS) is a promising technique for assessing brain function in newborns, particularly due to its portability and sensitivity to cerebral hemodynamics and oxygenation. Methods for measuring cerebral blood flow (CBF) and cerebral metabolic rate of oxygen (CMRO(2)) have been developed based on broadband continuous-wave NIRS. However, broadband NIRS apparatus typically have only one detection channel, which limits their applicability to measuring regional CBF and CMRO(2). In this study, a relatively simple multiplexing approach based on electronically controlled mechanical shutters is proposed to expand the detection capabilities from one to eight channels. The tradeoff is an increase in the sampling interval; however, this has negligible effects on CBF measurements for intervals less than or equal to 1 s. The ability of the system to detect focal brain injury was demonstrated in piglets by injecting endothelin-1 (ET-1) into the cerebral cortex. For validation, CBF was independently measured by computed tomography (CT) perfusion. The average reduction in CBF from the source-detector pair that interrogated the injured region was 51%+/-9%, which was in good agreement with the CBF reduction measured by CT perfusion (55%+/-5%). No significant changes in regional CMRO(2) were observed. The average regional differential pathlength prior to ET-1 injection was 8.4+/-0.2 cm (range of 7.1-9.6 cm) and did not significantly change after the injury.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".