Extended Data Fig. 5: Further in vivo ischaemic rat heart pacing with 10-ms light pulse duration. | Nature

Extended Data Fig. 5: Further in vivo ischaemic rat heart pacing with 10-ms light pulse duration.

From: Monolithic silicon for high spatiotemporal translational photostimulation

Extended Data Fig. 5

a, Plot of ECG waveforms before and after LAD ligation. Acute heart ischaemia results in increased heart rate and stronger breathing cycles, indicated by periodic fluctuations of the baseline. b, Optoelectronic pacing on LAD-ligated heart with varying light intensities. Pacing frequency was 360 bpm and pulse duration was 10 ms. Plotted are representative data from N > 3 individual rat hearts. c, Photostimulation success rate at different intensities. 100% reliability was achieved for intensities above 0.84 mW mm−2. Data are expressed as mean ± s.d. measured from N = 3 independent rats and devices. For six the plotted intensities from 0.64 to 1.65 mW mm−2, the total number of QRS evaluated are as follows, respectively: 78, 90, 94, 89, 95 and 95. d, Stable and consistent synchronization was demonstrated at 0.73 mW mm−2 with 10-ms light duration. Plotted are representative data from N = 4 individual rat hearts. e, Photograph of biventricular photostimulation on a single monolithic Si device using two spatially separated laser sources with wavelengths of 635 nm and 473 nm. ECG traces show biventricular pacing following simultaneous optoelectronic pacing on the left and right ventricles. f, Comparison of QRS durations among sinus rhythm and various pacing conditions. N = 10 QRS durations were evaluated for each condition. Boxes bind the IQR divided by the median; whiskers extend 1.5 times the IQR. Statistics are calculated using one-way analysis of variance followed by post hoc Tukey’s honestly significant difference test. n.s. > 0.05. **P < 0.01, ****P < 0.0001. g, Rat heart optoelectronic pacing at 1.22 mW mm−2 for 5 min (approximately 1,800 paced QRS complexes) demonstrated a 100% success rate. Surface ECG data were recorded using an Arduino Uno board and the ECG sensor AD8232.

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