Nerve growth factor (NGF) is a key mediator of nociception, acting during the development and differentiation of dorsal root ganglion (DRG) neurons, and on adult DRG neuron sensitization to painful stimuli. NGF also has central actions in the brain, where it regulates the phenotypic maintenance of cholinergic neurons. The physiological function of NGF as a pain mediator is altered in patients with Hereditary Sensory and Autonomic Neuropathy type V (HSAN V), caused by the 661CϾT transition in the Ngf gene, resulting in the R100W missense mutation in mature NGF. Homozygous HSAN V patients present with congenital pain insensitivity, but are cognitively normal. This led us to hypothesize that the R100W mutation may differentially affect the central and peripheral actions of NGF. To test this hypothesis and provide a mechanistic basis to the HSAN V phenotype, we generated transgenic mice harboring the human 661CϾT mutation in the Ngf gene and studied both males and females. We demonstrate that heterozygous NGF R100W/wt mice display impaired nociception. DRG neurons of NGF R100W/wt mice are morphologically normal, with no alteration in the different DRG subpopulations, whereas skin innervation is reduced. The NGF R100W protein has reduced capability to activate pain-specific signaling, paralleling its reduced ability to induce mechanical allodynia. Surprisingly, however, NGF R100W/wt mice, unlike heterozygous mNGF ϩ/Ϫ mice, show no learning or memory deficits, despite a reduction in secretion and brain levels of NGF. The results exclude haploinsufficiency of NGF as a mechanistic cause for heterozygous HSAN V mice and demonstrate a specific effect of the R100W mutation on nociception.
The vasculature is innervated by a network of peripheral afferents that sense and regulate blood flow. Here, we describe a system of non-peptidergic sensory neurons with cell bodies in the spinal ganglia that regulate vascular tone in the distal arteries. We identify a population of mechanosensitive neurons, marked by tropomyosin receptor kinase C (TrkC) and tyrosine hydroxylase in the dorsal root ganglia, which projects to blood vessels. Local stimulation of TrkC neurons decreases vessel diameter and blood flow, whereas systemic activation increases systolic blood pressure and heart rate variability via the sympathetic nervous system. Ablation of the neurons provokes variability in local blood flow, leading to a reduction in systolic blood pressure, increased heart rate variability, and ultimately lethality within 48 h. Thus, a population of TrkC + sensory neurons forms part of a sensory-feedback mechanism that maintains cardiovascular homeostasis through the autonomic nervous system.
The COVID-19 pandemic is inevitably changing the world in a dramatic way, and the role of computed tomography (CT) scans can be pivotal for the prognosis of COVID-19 patients. Since the start of the pandemic, great care has been given to the relationship between interstitial pneumonia caused by the infection and the onset of thromboembolic phenomena. In this preliminary study, we collected n = 20 CT scans from the Polyclinic of Bari, all from patients positive with COVID-19, nine of which developed pulmonary thromboembolism (PTE). For eight CT scans, we obtained masks of the lesions caused by the infection, annotated by expert radiologists; whereas for the other four CT scans, we obtained masks of the lungs (including both healthy parenchyma and lesions). We developed a deep learning-based segmentation model that utilizes convolutional neural networks (CNNs) in order to accurately segment the lung and lesions. By considering the images from publicly available datasets, we also realized a training set composed of 32 CT scans and a validation set of 10 CT scans. The results obtained from the segmentation task are promising, allowing to reach a Dice coefficient higher than 97%, posing the basis for analysis concerning the assessment of PTE onset. We characterized the segmented region in order to individuate radiomic features that can be useful for the prognosis of PTE. Out of 919 extracted radiomic features, we found that 109 present different distributions according to the Mann–Whitney U test with corrected p-values less than 0.01. Lastly, nine uncorrelated features were retained that can be exploited to realize a prognostic signature.
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