Measurement of the membrane potential in small cells using patch clamp methods
Bibliographic record
Abstract
The resting membrane potential, E(m), of mammalian cells is a fundamental physiological parameter. Even small changes in E(m) can modulate excitability, contractility and rates of cell migration. At present accurate, reproducible measurements of E(m) and determination of its ionic basis remain significant challenges when patch clamp methods are applied to small cells. In this study, a mathematical model has been developed which incorporates many of the main biophysical principles which govern recordings of the resting potential of 'small cells'. Such a prototypical cell (approx. capacitance, 6 pF; input resistance 5 GΩ) is representative of neonatal cardiac myocytes, and other cells in the cardiovascular system (endothelium, fibroblasts) and small cells in other tissues, e.g. bone (osteoclasts) articular joints (chondrocytes) and the pancreas (β cells). Two common experimental conditions have been examined: (1) when the background K(+) conductance is linear; and (2) when this K(+) conductance is highly nonlinear and shows pronounced inward rectification. In the case of a linear K(+) conductance, the presence of a "leakage" current through the seal resistance between the cell membrane and the patch pipette always depolarizes E(m). Our calculations confirm that accurate characterization of E(m) is possible when the seal resistance is at least 5 times larger than the input resistance of the targeted cell. Measurement of E(m) under conditions in which the main background current includes a markedly nonlinear K(+) conductance (due to inward rectification) yields complex and somewhat counter-intuitive findings. In fact, there are at least two possible stable values of resting membrane potential for a cell when the nonlinear, inwardly rectifying K(+) conductance interacts with the seal current. This type of bistable behavior has been reported in a variety of small mammalian cells, including those from the heart, endothelium, smooth muscle and bone. Our theoretical treatment of these two common experimental situations provides useful mechanistic insights, and suggests practical methods by which these significant limitations, and their impact, can be minimized.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".