Widefield-microscopy Based Detection of Calcium Oscillations in Precision Cut Lung Slices
Bibliographic record
Abstract
Abstract Rationale In the lung, changes in calcium oscillation frequencies drive airways smooth muscle contraction, making these oscillations relevant to airway hyperresponsiveness. These oscillations can be studies using fluorescent calcium probes. As cellular calcium levels change, calcium ions bind and unbind to the probe, resulting in brightness oscillations. Precision cut lung slices (PCLS) are increasingly relevant for studying airway disease, but their thickness presents challenges in the form of signals from out-of-focus cells, obscuring calcium oscillations. To date, this issue has only been overcome with confocal microscopy. A widefield imaging approach would lower the barrier to studying oscillations. Methods The ability to detect calcium oscillations using widefield microscopy was accomplished by staining live PCLS, then comparing the fluctuations in fluorescence emissions before and after a methacholine dose. Slices were stained with a solution of Calbryte-520 (5 uM), Pluronic™ F-127 (0.04%), in HBSS (includes 10mM HEPES, pH 7.3) at 37C and 5% CO2 for 1.5 hours. Stained slices were mounted to coverslip bottom 6 well plates using a transparent slice holder (physioMesh, SCIREQ, Canada) then imaged on a widefield automated epifluorescence microscope (physioLens, SCIREQ, Canada) equipped with a 20X 0.5NA Plan Fluorite objective (Evident Scientific, Japan). Airways were imaged before and after dosing with the following conditions: 6 frames per second for 30 seconds, with both brightfield and fluorescence imaging (ex/em: 480 nm/520 nm). The time course of intensity of each pixel is analyzed by Fast Fourier Transform (FFT) to obtain the oscillation frequency. Results We detect calcium oscillation in mouse PCLS using widefield imaging and Calbryte-520AM, as shown in Figure 1. At baseline, a region of interest is shown to be constant in brightness, in comparison to the dosed case which has eight percent increases in brightness occurring regularly. The baseline heat map shows either undetectable or slow oscillations in contrast to the dosed case, which shows multiple locations of increased oscillation frequencies at a value of 0.5hz, consistent with literature. Conclusion A widefield microscope, with the correct objective and a proper dye can be used to detect calcium oscillations in PCLS, something to date that has only done using confocal. Figure 1: Overview of calcium oscillations between baseline and dosed slices. Brightfield images of the airway, a heat map of oscillation frequency and the intensity trace of a region of interest (∼10 micron diameter) corresponding to the red arrow are shown for both the baseline and dosed cases. Scale 0.1mm.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".