Cohenjain3375

Cerebral palsy (CP) is caused by a variety of factors attributed to early brain damage, resulting in permanently impaired motor control, marked by weakness and muscle stiffness. To find out if altered physiology of spinal motoneurons (MNs) could contribute to movement deficits, we performed whole-cell patch-clamp in neonatal rabbit spinal cord slices after developmental injury at 79% gestation. After preterm hypoxia-ischemia (HI), rabbits are born with motor deficits consistent with a spastic phenotype including hypertonia and hyperreflexia. There is a range in severity, thus kits are classified as severely affected, mildly affected, or unaffected based on modified Ashworth scores and other behavioral tests. At postnatal day (P)0-5, we recorded electrophysiological parameters of 40 MNs in transverse spinal cord slices using whole-cell patch-clamp. We found significant differences between groups (severe, mild, unaffected and sham control MNs). Severe HI MNs showed more sustained firing patterns, depolarized resting membrane potential, and fired action potentials at a higher frequency. These properties could contribute to muscle stiffness, a hallmark of spastic CP. Interestingly altered persistent inward currents (PICs) and morphology in severe HI MNs would dampen excitability (depolarized PIC onset and increased dendritic length). In summary, changes we observed in spinal MN physiology likely contribute to the severity of the phenotype, and therapeutic strategies for CP could target the excitability of spinal MNs. Copyright © 2020 Steele, Cavarsan, Dowaliby, Westefeld, Katenka, Drobyshevsky, Gorassini and Quinlan.Parkinson's disease is characterized by motor and nonmotor symptoms that gradually appear as a consequence of the selective loss of dopaminergic neurons in the substantia nigra pars compacta. Currently, no treatment can slow Parkinson's disease progression. Inasmuch, there is a need to develop animal models that can be used to understand the pathophysiological mechanisms underlying dopaminergic neuron death. The initial goal of this study was to determine if canine adenovirus type 2 (CAV-2) vectors are effective gene transfer tools in the monkey brain. A second objective was to explore the possibility of developing a large nonhuman primate that expresses one of the most common genetic mutations causing Parkinson's disease. Our studies demonstrate the neuronal tropism, retrograde transport, biodistribution, and efficacy of CAV-2 vectors expressing GFP and leucine-rich repeat kinase 2 (LRRK2G2019S) in the Macaca fascicularis brain. Our data also suggest that following optimization CAV-2-mediated LRRK2G2019S expression could help us model the neurodegenerative processes of this genetic subtype of Parkinson's disease in monkeys. Copyright © 2020 di Caudo, Martínez-Valbuena, Mundiñano, Gennetier, Hernandez, Carmona-Abellan, Marcilla Garcia, Kremer and Luquin.Sense of smell in humans has the capacity to detect certain volatiles from bacterial infections. Our olfactory senses were used in ancient medicine to diagnose diseases in patients. As humans are considered holobionts, each person's unique odor consists of volatile organic compounds (VOCs, volatilome) produced not only by the humans themselves but also by their beneficial and pathogenic micro-habitants. In the past decade it has been well documented that microorganisms (fungi and bacteria) are able to emit a broad range of olfactory active VOCs [summarized in the mVOC database (http//bioinformatics.charite.de/mvoc/)]. During microbial infection, the equilibrium between the human and its microbiome is altered, followed by a change in the volatilome. For several decades, physicians have been trying to utilize these changes in smell composition to develop fast and efficient diagnostic tools, particularly because volatiles detection is non-invasive and non-destructive, which would be a breakthrough in many therapies. Within this review, we discuss bacterial infections including gastrointestinal, respiratory or lung, and blood infections, focusing on the pathogens and their known corresponding volatile biomarkers. Furthermore, we cover the potential role of the human microbiota and their volatilome in certain diseases such as neurodegenerative diseases. We also report on discrete mVOCs that affect humans. Copyright © 2020 Elmassry and Piechulla.In the past, determination of absolute values of cerebral metabolic rate of glucose (CMRGlc) in clinical routine was rarely carried out due to the invasive nature of arterial sampling. With the advent of combined PET/MR imaging technology, CMRGlc values can be obtained non-invasively, thereby providing the opportunity to take advantage of fully quantitative data in clinical routine. However, CMRGlc values display high physiological variability, presumably due to fluctuations in the intrinsic activity of the brain at rest. To reduce CMRGlc variability associated with these fluctuations, the objective of this study was to determine whether functional connectivity measures derived from resting-state fMRI (rs-fMRI) could be used to correct for these fluctuations in intrinsic brain activity. METHODS We studied 10 healthy volunteers who underwent a test-retest dynamic [18F]FDG-PET study using a fully integrated PET/MR system (Siemens Biograph mMR). To validate the non-invasive derivation of an image-derived input fShiyam Sundar, Baajour, Beyer, Lanzenberger, Traub-Weidinger, Rausch, Pataraia, Hahn, Rischka, Hienert, Klebermass and Muzik.Most rewards in our lives require effort to obtain them. check details It is known that effort is seen by humans as carrying an intrinsic disutility which devalues the obtainable reward. Established models for effort discounting account for this by using participant-specific discounting parameters inferred from experiments. These parameters offer only a static glance into the bigger picture of effort exertion. The mechanism underlying the dynamic changes in a participant's willingness to exert effort is still unclear and an active topic of research. Here, we modeled dynamic effort exertion as a consequence of effort- and probability-discounting mechanisms during goal reaching, sequential behavior. To do this, we developed a novel sequential decision-making task in which participants made binary choices to reach a minimum number of points. Importantly, the time points and circumstances of effort allocation were decided by participants according to their own preferences and not imposed directly by the task. Using the computational model to analyze participants' choices, we show that the dynamics of effort exertion arise from a combination of changing task needs and forward planning.