Hemodynamic effects of a soluble guanylate cyclase stimulator, Riociguat, and an activator, Cinaciguat, during NO-modulation in healthy pigs

Cardiovascular diseases are often characterized by dysfunctional endothelium. To compensate for the related lack of nitric oxide (NO), a class of soluble guanylate cyclase (sGC) stimulators and activators have been developed with the purpose of acting downstream of NO in the NO-sGC-cGMP cascade. These drugs have been discovered using photoaffinity labeling of sGC and high-throughput screening of a vast number of chemical compounds. Therefore, an understanding of the integrated physiological effects of these drugs in vivo is necessary on the path to clinical application. We have characterized the integrated hemodynamic impact of the sGC stimulator riociguat and the activator cinaciguat in different NO-states in healthy juvenile pigs (n = 30). We assessed the vascular effects in both systemic and pulmonary circulation, the contractile effects in the right and left ventricles, and the effects on diastolic cardiac functions. Nitric oxide-tone in these pigs were set by using the NO-blocker l-NAME and by infusion of nitroglycerine. The studies show a more pronounced vasodilatory effect in the systemic than pulmonary circulation for both drugs. Riociguat acts integrated with NO in an additive manner, while cinaciguat, in principle, completely blocks the endogenous NO effect on vascular control. Neither compound demonstrated pronounced cardiac effects but had unloading effect on both systolic and diastolic function. Thus, riociguat can potentially act in various disease states as a mean to increase NO-tone if systemic vasodilation can be balanced. Cinaciguat is a complicated drug to apply clinically due to its almost complete lack of integration in the NO-tone and balance

Mitochondrial dynamics and quantification of mitochondria-derived vesicles in cardiomyoblasts using structured illumination microscopy

Mitochondria are essential energy-providing organelles of particular importance in energy-demanding tissue such as the heart. The production of mitochondria-derived vesicles (MDVs) is a cellular mechanism by which cells ensure a healthy pool of mitochondria. These vesicles are small and fast-moving objects not easily captured by imaging. In this work, we have tested the ability of the optical super-resolution technique 3DSIM to capture high-resolution images of MDVs. We optimized the imaging conditions both for high-speed video microscopy and fixed-cell imaging and analysis. From the 3DSIM videos, we observed an abundance of MDVs and many dynamic mitochondrial tubules. The density of MDVs in cells was compared for cells under normal growth conditions and cells during metabolic perturbation. Our results indicate a higher abundance of MDVs in H9c2 cells during glucose deprivation compared with cells under normal growth conditions. Furthermore, the results reveal a large untapped potential of 3DSIM in MDV research

Vasopressin impairs brain, heart and kidney perfusion: an experimental study in pigs after transient myocardial ischemia

Introduction: Arginine vasopressin (AVP) is increasingly used to restore mean arterial pressure (MAP) in low-pressure shock states unresponsive to conventional inotropes. This is potentially deleterious since AVP is also known to reduce cardiac output by increasing vascular resistance. The effects of AVP on blood flow to vital organs and cardiac performance in a circulation altered by cardiac ischemia are still not sufficiently clarified. We hypothesised that restoring MAP by low dose, therapeutic level AVP would reduce vital organ blood flow in a setting of experimental acute left ventricular dysfunction. Methods: Cardiac output (CO) and arterial blood flow to the brain, heart, kidney and liver were measured in nine pigs using transit-time flow probes. Left ventricular pressure-volume catheter and central arterial and venous catheters were used for haemodynamic recordings and blood sampling. Transient left ventricular ischemia was induced by intermittent left coronary occlusions resulting in a 17% reduction in cardiac output and a drop in MAP from 87 ± 3 to 67 ± 4 mmHg (p < 0.001). A low-dose therapeutic level of AVP (0.005 U/kg/min) was used to restore MAP to pre-ischemic values (93 ± 4 mmHg). Results: AVP further impaired systemic perfusion (CO and brain, heart and kidney blood flow reduced by 29, 18, 23 and 34%, respectively) due to a 2.0-, 2.2-, 1.9- and 2.1-fold increase in systemic, brain, heart and kidney specific vascular resistances. The hypoperfusion induced by AVP was associated with an increased systemic oxygen extraction. Oxygen saturation in blood drawn from the great cardiac vein fell from 29 ± 1 to 21 ± 3% (p = 0.01). Finally, these effects were reversed 40 min after AVP was withdrawn. Conclusion: Low dose AVP induced a pronounced reduction in vital organ blood flow in pigs after transient cardiac ischemia. This indicates a potentially deleterious effect of AVP in patients with heart failure or cardiogenic shock due to impaired coronary perfusion

Learning Nanoscale Motion Patterns of Vesicles in Living Cells

Detecting and analyzing nanoscale motion patterns of vesicles, smaller than the microscope resolution (~250 nm), inside living biological cells is a challenging problem. State-of-the-art CV approaches based on detection, tracking, optical flow or deep learning perform poorly for this problem. We propose an integrative approach, built upon physics based simulations, nanoscopy algorithms, and shallow residual attention network to make it possible for the first time to analysis sub-resolution motion patterns in vesicles that may also be of sub-resolution diameter. Our results show state-of-the-art performance, 89% validation accuracy on simulated dataset and 82% testing accuracy on an experimental dataset of living heart muscle cells imaged under three different pathological conditions. We demonstrate automated analysis of the motion states and changed in them for over 9000 vesicles. Such analysis will enable large scale biological studies of vesicle transport and interaction in living cells in the future

Virtual labeling of mitochondria in living cells using correlative imaging and physics-guided deep learning

Mitochondria play a crucial role in cellular metabolism. This paper presents a novel method to visualize mitochondria in living cells without the use of fluorescent markers. We propose a physics-guided deep learning approach for obtaining virtually labeled micrographs of mitochondria from bright-field images. We integrate a microscope’s point spread function in the learning of an adversarial neural network for improving virtual labeling. We show results (average Pearson correlation 0.86) significantly better than what was achieved by state-of-the-art (0.71) for virtual labeling of mitochondria. We also provide new insights into the virtual labeling problem and suggest additional metrics for quality assessment. The results show that our virtual labeling approach is a powerful way of segmenting and tracking individual mitochondria in bright-field images, results previously achievable only for fluorescently labeled mitochondria

Risk ranking and source attribution of food- and waterborne pathogens for surveillance purposes. Opinion of the Panel on Biological Hazards of the Norwegian Scientific Committee for Food and Environment

publishedVersio

Risk ranking and source attribution of food- and waterborne pathogens for surveillance purposes

publishedVersio

Risk ranking and source attribution of food- and waterborne pathogens for surveillance purposes

publishedVersio

Risk ranking and source attribution of food- and waterborne pathogens for surveillance purposes. Opinion of the Panel on Biological Hazards of the Norwegian Scientific Committee for Food and Environment

publishedVersio