Journal: Developmental Cell

Article Title: Mechanical regulation of substrate adhesion and de-adhesion drives a cell-contractile wave during Drosophila tissue morphogenesis

doi: 10.1016/j.devcel.2023.11.022

Figure Lengend Snippet:

Article Snippet: All image processing and data analysis were performed using ImageJ (1.53v), Matlab (2019b or 2014b) including Curve Fitting, Image Processing, Statistics and Machine Learning Toolboxes (Mathworks), Ilastik (v. 1.3.3) and IgorPro (v6.3 or 9, Wavemetrics).

Techniques: Recombinant, Cloning, Sequencing, Software

Journal: PLoS ONE

Article Title: Reconstruction of membrane current by deconvolution and its application to membrane capacitance measurements in cardiac myocytes

doi: 10.1371/journal.pone.0188452

Figure Lengend Snippet: A: Sampled voltage stimulus and current responses (the first 200 microseconds are shown). Upper panel : the single sample voltage impulse. Lower panel : the sampled current responses obtained by averaging 4096 records to suppress the noise. ●–the averaged current response recorded with the 4.7 MΩ resistor connected between the amplifier input and the ground (R+C response); ○—the averaged current response recorded with the 4.7 MΩ resistor connected to the amplifier input and disconnected from the ground (C-response);. ■—the impulse current response (R-response) obtained by subtracting the C-response from the R+C response. B: The characteristic of the signal path in the frequency domain, H S , obtained by FFT of the R-response. C: An example of the recorded low-pass filtered current response (grey line) and of the current response reconstructed by deconvolution procedure (black line) obtained with the hardware model cell ( C M = 10 pF, R M = 500 MΩ, R A = 4.7 MΩ) to V Stim = 80 mV. The parasitic capacitance was compensated by the amplifier compensation circuitry.

Article Snippet: The whole processing and analysis procedure for deconvolution of membrane current records was written into an interactive software package MAT-MECAS in MATLAB v. 2014b (see: http://mat-mecas.sourceforge.net ), which was used also in this study.

Techniques:

Journal: PLoS ONE

Article Title: Reconstruction of membrane current by deconvolution and its application to membrane capacitance measurements in cardiac myocytes

doi: 10.1371/journal.pone.0188452

Figure Lengend Snippet: A: Analysis of the simulated, filtered, and reconstructed current records by the deconvolution (■) and the standard procedures (○). The differences in estimates of C M , R M , and R A before and after increasing the R A value by 1 MΩ are plotted against the range of pertinent τ values . B: Analysis of current records obtained with the use of compensation settings of the recording amplifier. Upper panels : time series of C M estimates. Lower panels : time series of R A estimates. The R A value was changed manually by about 1 MΩ for 2–3 seconds using the R A compensation knob. The C M value was set to emulate either a small cell (left panels, τ = 136 μs) or a large cell (right panels, τ = 713μs). The deconvolution (Dec) and standard (Std) traces were obtained by the deconvolution and standard procedures, respectively. Square-wave ±40 mV, 10 ms periods, bandwidth 50 Hz. C: Contribution of the R A / C M crosstalk error to the overall C M resolution. A set of filtered current responses was simulated for a cell of C M = 50 pF, R M = 200 MΩ, and R A varying randomly with the same mean of 5 MΩ but different values of standard deviation (500 stimulation periods for each σ R A ). The standard deviation σ C M in the C M time series was estimated for 50 Hz bandwidth. Dashed line–the thermal noise level calculated by . The σ C M values in the time series of C M estimates obtained by the deconvolution (■) or standard (○) procedures. Solid line–the sum thermal noise and the standard procedure data. Notably, in the case of the deconvolution procedure (■), the fluctuations in C M caused by fluctuations of R A were by 3 orders of magnitude below the thermal noise level.

Article Snippet: The whole processing and analysis procedure for deconvolution of membrane current records was written into an interactive software package MAT-MECAS in MATLAB v. 2014b (see: http://mat-mecas.sourceforge.net ), which was used also in this study.

Techniques: Standard Deviation

Journal: PLoS ONE

Article Title: Reconstruction of membrane current by deconvolution and its application to membrane capacitance measurements in cardiac myocytes

doi: 10.1371/journal.pone.0188452

Figure Lengend Snippet: A: The onset of filtered current responses to step voltage changes with input of the measuring amplifier open and shielded. The compensation circuitry of the measuring amplifier was set to emulate cell circuit parameters. Upper panel : ●–the current response recorded with R A set to 5.5 MΩ, C M set to 109 pF, and the input capacitance well compensated. □ –the current response recorded with decompensated input capacitance and R A and C M controls set to zero. ■ –the combined current response recorded with decompensated input capacitance, R A set to 5.5 MΩ, and C M set to 109 pF. Lower panel : the current responses corresponding to records in the upper panel reconstructed by the deconvolution procedure. B: Effects of changes of parasitic capacitance (lower panel) on estimates of C M and R A of a cell emulated with the compensation circuitry of recording amplifier. Black traces–the time series of parameter estimates of current responses reconstructed by the deconvolution procedure. Grey traces–the time series of parameter estimates of current responses reconstructed with the deconvolution procedure applied to current responses with the first 60 μs blanked (note the absence of C P crosstalk in C M trace). The flickering artefacts are caused by handling of the fast capacitance compensation control. The change of parasitic capacitance Δ C P was evaluated from the integral of the onset of recorded current response .

Article Snippet: The whole processing and analysis procedure for deconvolution of membrane current records was written into an interactive software package MAT-MECAS in MATLAB v. 2014b (see: http://mat-mecas.sourceforge.net ), which was used also in this study.

Techniques: Control

Journal: PLoS ONE

Article Title: Reconstruction of membrane current by deconvolution and its application to membrane capacitance measurements in cardiac myocytes

doi: 10.1371/journal.pone.0188452

Figure Lengend Snippet: A: The simulated data. Left panel : Dependence of estimates of cell impedance parameters on R Seal value (estimated by Eqs and from simulated current responses of the equivalent circuit according , , C M = 140 fF, R M = 0.5 GΩ, R A = 4 MΩ). Right panel : Simulated experiment with two events. The first event contained a step decrease of R Seal from 100 to 10 GΩ while the second event contained a step change of C M from 98.7 fF to 99.0 fF. Note that in the first event an anti-correlated step change emerged in C M and R M but not in R A or Q C traces, while in the second event a correlated change was present in the C M and Q C but not in R M and R A traces. The same set of circuit parameters as in the left panel, square-wave ±30 mV, 20 ms period, analysed by the deconvolution procedure. B: Records of impedance parameters of ventricular myocytes obtained by the deconvolution procedure. Left panel : A segment of a record containing an anti-correlated step change in C M and R M but not in R A or Q C traces (square-wave ±30 mV, 20 ms period), indicating artefactual change in membrane capacitance arising from the change of R Seal . Right panel : A segment of a record containing a well-resolved step C M event without correlated changes in either R M or R A but mirrored in Q C (square-wave ±20 mV, 10 ms period), indicating a true change of membrane capacitance.

Article Snippet: The whole processing and analysis procedure for deconvolution of membrane current records was written into an interactive software package MAT-MECAS in MATLAB v. 2014b (see: http://mat-mecas.sourceforge.net ), which was used also in this study.

Techniques: Membrane