Applications of scanning probe microscopy in neuroscience research
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
Abstract Scanning probe microscopy techniques allow for label-free high-resolution imaging of cells, tissues, and biomolecules in physiologically relevant conditions. These techniques include atomic force microscopy (AFM), atomic force spectroscopy, and Kelvin probe force microscopy, which enable high resolution imaging, nanomanipulation and measurement of the mechanoelastic properties of neuronal cells, as well as scanning ion conductance microscopy, which combines electrophysiology and imaging in living cells. The combination of scanning probe techniques with optical spectroscopy, such as with AFM-IR and tip-enhanced Raman spectroscopy, allows for the measurement of topographical maps along with chemical identity, enabled by spectroscopy. In this work, we review applications of these techniques to neuroscience research, where they have been used to study the morphology and mechanoelastic properties of neuronal cells and brain tissues, and to study changes in these as a result of chemical or physical stimuli. Cellular membrane models are widely used to investigate the interaction of the neuronal cell membrane with proteins associated with various neurological disorders, where scanning probe microscopy and associated techniques provide significant improvement in the understanding of these processes on a cellular and molecular level.
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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 | 0.001 | 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