Depolarization of surface-attached hypothalamic mouse neurons studied by acoustic wave (thickness shear mode) detector
Bibliographic record
Abstract
Isolation of neurons from animal tissue is an important aspect of understanding basic biochemical processes such as the action of hormones and neurotransmitters. In the present work, the focus is on an effort to evaluate the utility of acoustic wave physics for the study of such cells. Immortalised hypothalamic neuronal cells from mouse embryos were cultured on the surface of the gold electrode of a 9.0 MHz thickness-shear mode acoustic wave sensor. These cells, which are clonal, are imposed on the surface of the device at a confluence in the range of 80-100%. The coated sensor is incorporated into a flow-injection configuration such that electrolytes can be introduced in order to examine their effects through measurement by network analysis. Both series resonance frequency, fs, and motional resistance, R(m), were measured in a number of experiments involving the injection of KCl and NaCl into the sensor-neuron system. The various responses to these electrolytes were interpreted in terms of changes in cellular structure associated with the depolarization process. The sensor-neuron system was found to elicit different responses to the addition of KCl and NaCl. Preliminary findings indicate that the TSM sensor does not purely measure changes in the membrane potential upon KCl addition. Typical changes in fs for 15 mM, 30 mM and 60 mM KCl additions were 54 +/- 15, 80 +/- 26 and 142 +/- 58 Hz (mean +/- standard deviation) respectively. Typical changes in R(m) for these KCl additions were 7 +/- 3, 13 +/- 4 and 23 +/- 6 Omega, respectively. These results were concluded after 17 runs at each concentration. Despite the large relative standard deviations, the dependence of f(s) and R(m) with respect to concentration was apparent. Controls performed by coating the TSM sensor with laminin or a cell attachment matrix showed no significant changes in either f(s) or R(m) for the same solutions tested on the sensor-neuron system.
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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 | 0.000 | 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) | 0.000 | 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 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".