Effects of temperature and aldehyde fixation on tissue water diffusion properties, studied in an erythrocyte ghost tissue model
Bibliographic record
Abstract
Ex vivo biological sample imaging can complement in vivo MRI studies. Since ex vivo studies are typically performed at room temperature, and samples are frequently preserved by fixation, it is important to understand how environmental and chemical changes dictated by ex vivo studies alter the physical and MR properties of a sample. Diffusion and relaxation time measurements were used to assess the effects of temperature change and aldehyde fixation on the biophysical and MR properties of a model biological tissue comprised of erythrocyte ghosts suspended in buffer or agarose gel. Sample temperature was varied between 10 degrees C and 37 degrees C. Diffusion MRI data were analyzed with a biophysically appropriate two-compartment exchange model. Temperature change resulted in a complex alteration of water diffusion properties due to the compartmental nature of tissues and alteration in membrane permeability. Formaldehyde, Karnovsky's solution, and glutaraldehyde all caused statistically significant changes to the biophysical and MR properties of the samples. Fixation caused large decreases in water proton T2, which was restored to near prefixation values by washing free fixative from the samples. Water membrane permeability was also significantly altered by fixation. This study demonstrates that relating in vivo MR data to chemically fixed ex vivo data requires an understanding of the effects of sample preparation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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".