Subcellular Biochemical Investigation of Purkinje Neurons Using Synchrotron Radiation Fourier Transform Infrared Spectroscopic Imaging with a Focal Plane Array Detector
Bibliographic record
Abstract
Coupling Fourier transform infrared spectroscopy with focal plane array detectors at synchrotron radiation sources (SR-FTIR-FPA) has provided a rapid method to simultaneously image numerous biochemical markers in situ at diffraction limited resolution. Since cells and nuclei are well resolved at this spatial resolution, a direct comparison can be made between FTIR functional group images and the histology of the same section. To allow histological analysis of the same section analyzed with infrared imaging, unfixed air-dried tissue sections are typically fixed (after infrared spectroscopic analysis is completed) via immersion fixation. This post fixation process is essential to allow histological staining of the tissue section. Although immersion fixation is a common practice in this filed, the initial rehydration of the dehydrated unfixed tissue can result in distortion of subcellular morphology and confound correlation between infrared images and histology. In this study, vapor fixation, a common choice in other research fields where postfixation of unfixed tissue sections is required, was employed in place of immersion fixation post spectroscopic analysis. This method provided more accurate histology with reduced distortions as the dehydrated tissue section is fixed in vapor rather than during rehydration in an aqueous fixation medium. With this approach, accurate correlation between infrared images and histology of the same section revealed that Purkinje neurons in the cerebellum are rich in cytosolic proteins and not depleted as once thought. In addition, we provide the first direct evidence of intracellular lactate within Purkinje neurons. This highlights the significant potential for future applications of SR-FTIR-FPA imaging to investigate cellular lactate under conditions of altered metabolic demand such as increased brain activity and hypoxia or ischemia.
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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 | 0.000 |
| 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 | 0.001 |
| 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".