Results of Proton MRS Studies in PVS and MCS Patients
Bibliographic record
Abstract
Proton magnetic resonance spectroscopy ( 1 H-MRS) is useful in monitoring biochemical changes in metabolic, traumatic, infectious, and oncologic disorders of the brain.N-acetyl aspartate (NAA) content is a measure of neuronal integrity, choline (Cho) content mirrors membrane turnover, and creatine (Cre) relates to energy dependent systems.A decrement of NAA concentration has been interpreted as a sign of neuronal loss or dysfunction.To reduce intra and inter-subject variability in MRS measurements, peak area ratios are also computed for, NAA/Cre and NAA/Cho.MRS may thus improve the efficiency and sensitivity of MRI, especially for the detection of functional lesions that are not visible in conventional imaging sequences.[1][2][3] The persistent vegetative state (PVS) is one of the least understood and most ethically upsetting conditions because even modern high-technology does not restore function after brain damage.This term describes a unique condition in which patients who emerge from coma appear to be awake but show no signs of awareness.The diagnosis of PVS has been made more difficult by recognition of the minimally conscious state (MCS) as a transitional phase in the partial recovery of self-awareness or environmental awareness while a patient emerges from PVS, leading to a relative high proportion of errors.[4][5][6] In this paper, we will describe metabolic changes assessed by MRS comparing two patients who evolved from PVS to MCS and two others who remained in PVS.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".