LIST: A Newly Developed Laser-assisted Cell Bioprinting Technology.

Cell bioprinting technologies aim to fabricate tissue-like constructs by delivering biomaterials layer-by-layer. Bioprinted constructs can reduce the use of animals in drug development and hold promise for addressing the shortage of organs for transplants. We recently introduced a laser-assisted drop-on-demand bioprinting technology termed Laser Induced Side Transfer (LIST). This technology can print delicate cell types, including primary neurons. This bioprinting protocol includes the following key steps: cell harvesting, bio-ink preparation, laser setup priming, printing, and post-printing analysis. This protocol includes a detailed description of the laser setup, which is a rather unusual setup for a biology lab. This should allow easy reproduction by readers with basic knowledge of optics. Although we have focused on neuron bioprinting, interested readers will be able to adapt the protocol to bioprint virtually any cell type.

Estimation of the tissue damage after MI through time-frequency analysis of the electromechanical signals.

Abstract Coronary congestion is a heart disease that puts many lives at risk each year. The task of coronary arteries is to distribute blood to the heart tissue and any blockage in them can cause the tissue to absorb less oxygen and nutrients than needed (ischaemia disease). This imbalance will continue until the first cell is destroyed (myocardial infarction). Simulating the myocardial infarction in the laboratory rats, this study tries to determine the extent of tissue damage through the electrocardiogram (ECG) and atrial blood pressure (ABP) synchronic signals. The signals of 50 wistar rats with a weight range of 200-300 g were recorded at 30 min in the normal case and 30 min in the ischaemia and myocardial infarction (MI) case (the artificial complete blockage was in the left anterior descending coronary artery (LAD)). For a different injury in the rats' heart, the vasopressin (AVP) with different doses was injected to 40 rats. After that the images of the heart sections and the data were extracted, the 50-dimensional feature vector was generated by using the wavelet packet transform (WPT) on the ECG and ABP signals and also by obtaining the entropy of the wavelet coefficients. The extent of tissue damage on the images of the heart tissue was extracted by using the image processing method. Finally, the amount of the damaged tissue was estimated by four artificial neural networks (ANN) (with different structures) with an averaging criterion. The intelligent machine estimated the ischaemia and normal tissues with the average error of 2.91% for all the AVP doses and control cases.