Investigation of Early Death-Induced Changes in Rat Brain by Solid Phase Microextraction via Untargeted High Resolution Mass Spectrometry: <i>In Vivo</i> versus Postmortem Comparative Study
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
Analysis of brain samples obtained postmortem remains a standard approach in neuroscience, despite often being suboptimal for inferring roles of small molecules in the pathophysiology of brain diseases. Sample collection and preservation further hinders conclusive interpretation of biomarker analysis in autopsy samples. We investigate purely death-induced changes affecting rat hippocampus in the first hour of postmortem interval (PMI) by means of untargeted liquid chromatography–mass spectrometry-based metabolomics. The unique possibility of sampling the same brain area of each animal both in vivo and postmortem was enabled by employing solid phase microextraction (SPME) probes. Four millimeter probes coated with mixed mode extraction phase were used to sample awake, freely roaming animals, with 2 more sampling events performed after death. Significant changes in brain neurochemistry were found to occur as soon as 30 min after death, further progressing with increasing PMI, evidenced by relative changes in levels of metabolites and lipids. These included species from several distinct groups, which can be classified as engaged in energy metabolism-related processes, signal transduction, neurotransmission, or inflammatory response. Additionally, we perform thorough analysis of interindividual variability in response to death, which provides insights into how this aspect can obscure conclusions drawn from an untargeted study at single metabolite and pathway level. The results suggest high demand for systematic studies examining the PMI time course with in vivo sampling as a starting point to eliminate artifacts in the form of neurochemical changes assumed to occur in vivo.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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