What Do Eye Gaze Metrics Tell Us about Motor Imagery?

Many of the brain structures involved in performing real movements also have increased activity during imagined movements or during motor observation, and this could be the neural substrate underlying the effects of motor imagery in motor learning or motor rehabilitation. In the absence of any objective physiological method of measurement, it is currently impossible to be sure that the patient is indeed performing the task as instructed. Eye gaze recording during a motor imagery task could be a possible way to “spy” on the activity an individual is really engaged in. The aim of the present study was to compare the pattern of eye movement metrics during motor observation, visual and kinesthetic motor imagery (VI, KI), target fixation, and mental calculation. Twenty-two healthy subjects (16 females and 6 males), were required to perform tests in five conditions using imagery in the Box and Block Test tasks following the procedure described by Liepert et al. Eye movements were analysed by a non-invasive oculometric measure (SMI RED250 system). Two parameters describing gaze pattern were calculated: the index of ocular mobility (saccade duration over saccade + fixation duration) and the number of midline crossings (i.e. the number of times the subjects gaze crossed the midline of the screen when performing the different tasks). Both parameters were significantly different between visual imagery and kinesthesic imagery, visual imagery and mental calculation, and visual imagery and target fixation. For the first time we were able to show that eye movement patterns are different during VI and KI tasks. Our results suggest gaze metric parameters could be used as an objective unobtrusive approach to assess engagement in a motor imagery task. Further studies should define how oculomotor parameters could be used as an indicator of the rehabilitation task a patient is engaged in.     

Synaptic Efficacy as a Function of Ionotropic Receptor Distribution: A Computational Study

Glutamatergic synapses are the most prevalent functional elements of information processing in the brain. Changes in pre-synaptic activity and in the function of various post-synaptic elements contribute to generate a large variety of synaptic responses. Previous studies have explored postsynaptic factors responsible for regulating synaptic strength variations, but have given far less importance to synaptic geometry, and more specifically to the subcellular distribution of ionotropic receptors. We analyzed the functional effects resulting from changing the subsynaptic localization of ionotropic receptors by using a hippocampal synaptic computational framework. The present study was performed using the EONS (Elementary Objects of the Nervous System) synaptic modeling platform, which was specifically developed to explore the roles of subsynaptic elements as well as their interactions, and that of synaptic geometry. More specifically, we determined the effects of changing the localization of ionotropic receptors relative to the presynaptic glutamate release site, on synaptic efficacy and its variations following single pulse and paired-pulse stimulation protocols. The results indicate that changes in synaptic geometry do have consequences on synaptic efficacy and its dynamics.     

Tumor-Targeted Human T Cells Expressing CD28-Based Chimeric Antigen Receptors Circumvent CTLA-4 Inhibition

Adoptive T cell therapy represents a promising treatment for cancer. Human T cells engineered to express a chimeric antigen receptor (CAR) recognize and kill tumor cells in a MHC-unrestricted manner and persist in vivo when the CAR includes a CD28 costimulatory domain. However, the intensity of the CAR-mediated CD28 activation signal and its regulation by the CTLA-4 checkpoint are unknown. We investigated whether T cells expressing an anti-CD19, CD3 zeta and CD28-based CAR (19-28z) displayed the same proliferation and anti-tumor abilities than T cells expressing a CD3 zeta-based CAR (19z1) costimulated through the CD80/CD28, ligand/receptor pathway. Repeated in vitro antigen-specific stimulations indicated that 19-28z⁺ T cells secreted higher levels of Th1 cytokines and showed enhanced proliferation compared to those of 19z1⁺ or 19z1-CD80⁺ T cells. In an aggressive pre-B cell leukemia model, mice treated with 19-28z⁺ T cells had 10-fold reduced tumor progression compared to those treated with 19z1⁺ or 19z1-CD80⁺ T cells. shRNA-mediated CTLA-4 down-regulation in 19z1-CD80⁺ T cells significantly increased their in vivo expansion and anti-tumor properties, but had no effect in 19-28z⁺ T cells. Our results establish that CTLA-4 down-regulation may benefit human adoptive T cell therapy and demonstrate that CAR design can elude negative checkpoints to better sustain T cell function.     

Mutations in DOCK7 in Individuals with Epileptic Encephalopathy and Cortical Blindness

Epileptic encephalopathies are increasingly thought to be of genetic origin, although the exact etiology remains uncertain in many cases. We describe here three girls from two nonconsanguineous families affected by a clinical entity characterized by dysmorphic features, early-onset intractable epilepsy, intellectual disability, and cortical blindness. In individuals from each family, brain imaging also showed specific changes, including an abnormally marked pontobulbar sulcus and abnormal signals (T2 hyperintensities) and atrophy in the occipital lobe. Exome sequencing performed in the first family did not reveal any gene with rare homozygous variants shared by both affected siblings. It did, however, show one gene, DOCK7, with two rare heterozygous variants (c.2510delA [p.Asp837Alafs^∗48] and c.3709C>T [p.Arg1237^∗]) found in both affected sisters. Exome sequencing performed in the proband of the second family also showed the presence of two rare heterozygous variants (c.983C>G [p.Ser328^∗] and c.6232G>T [p.Glu2078^∗]) in DOCK7. Sanger sequencing confirmed that all three individuals are compound heterozygotes for these truncating mutations in DOCK7. These mutations have not been observed in public SNP databases and are predicted to abolish domains critical for DOCK7 function. DOCK7 codes for a Rac guanine nucleotide exchange factor that has been implicated in the genesis and polarization of newborn pyramidal neurons and in the morphological differentiation of GABAergic interneurons in the developing cortex. All together, these observations suggest that loss of DOCK7 function causes a syndromic form of epileptic encephalopathy by affecting multiple neuronal processes.     

Loss of α1β1 Soluble Guanylate Cyclase,the Major Nitric Oxide Receptor,Leads to Moyamoya and Achalasia

Moyamoya is a cerebrovascular condition characterized by a progressive stenosis of the terminal part of the internal carotid arteries (ICAs) and the compensatory development of abnormal “moyamoya” vessels. The pathophysiological mechanisms of this condition, which leads to ischemic and hemorrhagic stroke, remain unknown. It can occur as an isolated cerebral angiopathy (so-called moyamoya disease) or in association with various conditions (moyamoya syndromes). Here, we describe an autosomal-recessive disease leading to severe moyamoya and early-onset achalasia in three unrelated families. This syndrome is associated in all three families with homozygous mutations in GUCY1A3, which encodes the α1 subunit of soluble guanylate cyclase (sGC), the major receptor for nitric oxide (NO). Platelet analysis showed a complete loss of the soluble α1β1 guanylate cyclase and showed an unexpected stimulatory role of sGC within platelets. The NO-sGC-cGMP pathway is a major pathway controlling vascular smooth-muscle relaxation, vascular tone, and vascular remodeling. Our data suggest that alterations of this pathway might lead to an abnormal vascular-remodeling process in sensitive vascular areas such as ICA bifurcations. These data provide treatment options for affected individuals and strongly suggest that investigation of GUCY1A3 and other members of the NO-sGC-cGMP pathway is warranted in both isolated early-onset achalasia and nonsyndromic moyamoya.     

Structure determination of α-helical membrane proteins by solution-state NMR: Emphasis on retinal proteins

The biochemical processes of living cells involve a numerous series of reactions that work with exceptional specificity and efficiency. The tight control of this intricate reaction network stems from the architecture of the proteins that drive the chemical reactions and mediate protein–protein interactions. Indeed, the structure of these proteins will determine both their function and interaction partners. A detailed understanding of the proximity and orientation of pivotal functional groups can reveal the molecular mechanistic basis for the activity of a protein. Together with X-ray crystallography and electron microscopy, NMR spectroscopy plays an important role in solving three-dimensional structures of proteins at atomic resolution. In the challenging field of membrane proteins, retinal-binding proteins are often employed as model systems and prototypes to develop biophysical techniques for the study of structural and functional mechanistic aspects. The recent determination of two 3D structures of seven-helical trans-membrane retinal proteins by solution-state NMR spectroscopy highlights the potential of solution NMR techniques in contributing to our understanding of membrane proteins. This review summarizes the multiple strategies available for expression of isotopically labeled membrane proteins. Different environments for mimicking lipid bilayers will be presented, along with the most important NMR methods and labeling schemes used to generate high-quality NMR spectra. The article concludes with an overview of types of conformational restraints used for generation of high-resolution structures of membrane proteins. This article is part of a Special Issue entitled: Retinal Proteins — You can teach an old dog new tricks.     

Detecting and Measuring Selection from Gene Frequency Data

The recent advent of high-throughput sequencing and genotyping technologies makes it possible to produce, easily and cost effectively, large amounts of detailed data on the genotype composition of populations. Detecting locus-specific effects may help identify those genes that have been, or are currently, targeted by natural selection. How best to identify these selected regions, loci, or single nucleotides remains a challenging issue. Here, we introduce a new model-based method, called SelEstim, to distinguish putative selected polymorphisms from the background of neutral (or nearly neutral) ones and to estimate the intensity of selection at the former. The underlying population genetic model is a diffusion approximation for the distribution of allele frequency in a population subdivided into a number of demes that exchange migrants. We use a Markov chain Monte Carlo algorithm for sampling from the joint posterior distribution of the model parameters, in a hierarchical Bayesian framework. We present evidence from stochastic simulations, which demonstrates the good power of SelEstim to identify loci targeted by selection and to estimate the strength of selection acting on these loci, within each deme. We also reanalyze a subset of SNP data from the Stanford HGDP–CEPH Human Genome Diversity Cell Line Panel to illustrate the performance of SelEstim on real data. In agreement with previous studies, our analyses point to a very strong signal of positive selection upstream of the LCT gene, which encodes for the enzyme lactase–phlorizin hydrolase and is associated with adult-type hypolactasia. The geographical distribution of the strength of positive selection across the Old World matches the interpolated map of lactase persistence phenotype frequencies, with the strongest selection coefficients in Europe and in the Indus Valley.     

Prediction of human core body temperature using non-invasive measurement methods

The measurement of core body temperature is an efficient method for monitoring heat stress amongst workers in hot conditions. However, invasive measurement of core body temperature (e.g. rectal, intestinal, oesophageal temperature) is impractical for such applications. Therefore, the aim of this study was to define relevant non-invasive measures to predict core body temperature under various conditions. We conducted two human subject studies with different experimental protocols, different environmental temperatures (10 °C, 30 °C) and different subjects. In both studies the same non-invasive measurement methods (skin temperature, skin heat flux, heart rate) were applied. A principle component analysis was conducted to extract independent factors, which were then used in a linear regression model. We identified six parameters (three skin temperatures, two skin heat fluxes and heart rate), which were included for the calculation of two factors. The predictive value of these factors for core body temperature was evaluated by a multiple regression analysis. The calculated root mean square deviation (rmsd) was in the range from 0.28 °C to 0.34 °C for all environmental conditions. These errors are similar to previous models using non-invasive measures to predict core body temperature. The results from this study illustrate that multiple physiological parameters (e.g. skin temperature and skin heat fluxes) are needed to predict core body temperature. In addition, the physiological measurements chosen in this study and the algorithm defined in this work are potentially applicable as real-time core body temperature monitoring to assess health risk in broad range of working conditions.