Targeted cortical reorganization using optogenetics in non-human primates.

Brain stimulation modulates the excitability of neural circuits and drives neuroplasticity. While the local effects of stimulation have been an active area of investigation, the effects on large-scale networks remain largely unexplored. We studied stimulation-induced changes in network dynamics in two macaques. A large-scale optogenetic interface enabled simultaneous stimulation of excitatory neurons and electrocorticographic recording across primary somatosensory (S1) and motor (M1) cortex (Yazdan-Shahmorad et al., 2016). We tracked two measures of network connectivity, the network response to focal stimulation and the baseline coherence between pairs of electrodes; these were strongly correlated before stimulation. Within minutes, stimulation in S1 or M1 significantly strengthened the gross functional connectivity between these areas. At a finer scale, stimulation led to heterogeneous connectivity changes across the network. These changes reflected the correlations introduced by stimulation-evoked activity, consistent with Hebbian plasticity models. This work extends Hebbian plasticity models to large-scale circuits, with significant implications for stimulation-based neurorehabilitation

Construction of Novel Phytochelatins by Overlap Oligonucleotides

Synthetic phytochelatins are protein analogs of phytochelatin with similar heavy metal binding affinities that can be easily produced from a synthetic DNA template. We design synthetic phytochelatin [(Glu-Cys)n Gly] linked to hexahistidine by viral linker peptide and then followed by gene synthesis and cloning of it. Then peptide coding gene (synthetic phytochelatin with linker and hexahistidine) was designed exactly and constructed with step by step methods by overlapping oligonucleotides using T4 DNA Ligase. Finally, synthesized gene amplified by PCR, cloned in pTZ57R/T and transformed to Escherichia coli (DH5α). The results of sequencing show that some types of synthetic phytochelatin (EC4, EC12, and EC20) with linker and hexahistidine were constructed and cloned in vector

A Novel Shortwave Infrared Proximal Sensing Approach to Quantify the Water Stability of Soil Aggregates

Soil structure and aggregate stability (AS) are critical soil properties affecting water infiltration, root growth, and resistance to soil and wind erosion. Changes in AS may be early indicators of soil degradation, pointing to low organic matter (OM) content, reduced biological activity, or poor nutrient cycling. Hence, efficient and reliable AS measurement techniques are essential for detection, management, and remediation of degraded soil resources. Here we quantify soil AS by developing a novel proximal sensing technique based on shortwave infrared (SWIR) reflectance measurements. The novel approach is similar to the well-documented high energy moisture characteristic (HEMC) method, which yields a stability ratio (SR) derived from comparison of hydraulic and structural characteristics of slowly- and rapidly-wetted soil samples near-saturation. We rapidly wetted aggregated soil samples (i.e., high energy input) and hypothesized that an AS index can be derived from SWIR surface reflectance spectra due to differences in post-wetting surface roughness that is intimately linked to AS. To test this hypothesis, surface reflectance spectra from a wide range of structured soil textures under both slowly- and rapidly-wetted samples, were measured with a SWIR spectroradiometer (350–2500 nm). The ratio between pre- and post-wetting spectra was determined and compared with the HEMC method’s volume of drainable pore ratio (VDPR). We found a strong correlation (R2 = 0.87) between the VDPR and the SWIR-derived reflectance index (RI) and also between the SR (R2 = 0.90) and the RI for all soils. These results point to the feasibility and appeal of quantifying AS using the newly proposed and more time-efficient proximal sensing method

Erdheim Chester Disease treated successfully with cladribine

AbstractA 61-year-old previously healthy male with a history of progressive fatigue, lower extremity edema, and dyspnea for 4 months was hospitalized with pericardial and pleural effusions (Figure 1A, B). Lung, pleural, and pericardial biopsies were consistent with Erdheim-Chester disease. He was treated with systemic steroids, and ultimately tried on PEG-interferon. He deteriorated clinically and the disease progressed to include CNS manifestations. Ultimately he was treated with Cladribine, at a dose 0.014 mg/kg on day 1, followed by 0.09 mg/kg/day = 6.4 mg IV for 6 additional days. He received 2 further cycles of 0.14 mg kg/day for 7 days (1 month apart). After 3 cycles he improved significantly both clinically and radiographically. Six months post-treatment objective testing showed improvement in cardiac, neurologic, and pulmonary disease.Erdheim Chester Disease (ECD) is a rare non Langerhans cell histiocytosis. Only several hundred cases have been reported in the literature. Treatment for ECD is reserved for those with symptomatic disease, asymptomatic CNS involvement, or evidence of organ dysfunction. There is no standard treatment regimen: Current options include corticosteroids, Interferon alpha (IFN), systemic chemotherapy, and radiation therapy. The occurrence of the V600EBRAF mutation in about 50% of patients can make these patients amenable to targeted therapy with BRAF kinase inhibitors (e.g. Vemurafenib). More recently the presence of N/KRAS, and PIK3CA mutations have provided further rational for targeted therapies. The cytokine profile in patients with ECD suggests monocyte activation cladribine, a purine analogue toxic to monocytes, has also been studied as a treatment for ECD, especially in patients who test negative for the BRAF mutation

Metadata of the chapter that will be visualized in SpringerLink Book Title Combinatorial Optimization and Applications Series Title Chapter Title Optimal Strategy for Walking in Streets with Minimum Number of Turns for a Simple Robot Optimal Strategy for

Abstract We consider the problem of walking a simple robot in an unknown street. The robot that cannot infer any geometric properties of the street traverses the environment to reach a target , starting from a point . The robot has a minimal sensing capability that can only report the discontinuities in the depth information (gaps), and location of the target point once it enters in its visibility region. Also, the robot can only move towards the gaps while moving along straight lines is cheap, but rotation is expensive for the robot. We maintain the location of some gaps in a tree data structure of constant size. The tree is dynamically updated during the movement. Using the data structure, we present an online strategy that generates a search path for the robot with optimal number of turns. Keywords (separated by '-') Computational geometry -Minimum link path -Simple robot -Street polygon -Unknown environment Abstract. We consider the problem of walking a simple robot in an unknown street. The robot that cannot infer any geometric properties of the street traverses the environment to reach a target t, starting from a point s. The robot has a minimal sensing capability that can only report the discontinuities in the depth information (gaps), and location of the target point once it enters in its visibility region. Also, the robot can only move towards the gaps while moving along straight lines is cheap, but rotation is expensive for the robot. We maintain the location of some gaps in a tree data structure of constant size. The tree is dynamically updated during the movement. Using the data structure, we present an online strategy that generates a search path for the robot with optimal number of turns

A Brain-Computer Interface Based on Bilateral Transcranial Doppler Ultrasound

In this study, we investigate the feasibility of a BCI based on transcranial Doppler ultrasound (TCD), a medical imaging technique used to monitor cerebral blood flow velocity. We classified the cerebral blood flow velocity changes associated with two mental tasks - a word generation task, and a mental rotation task. Cerebral blood flow velocity was measured simultaneously within the left and right middle cerebral arteries while nine able-bodied adults alternated between mental activity (i.e. word generation or mental rotation) and relaxation. Using linear discriminant analysis and a set of time-domain features, word generation and mental rotation were classified with respective average accuracies of 82.9%10.5 and 85.7%10.0 across all participants. Accuracies for all participants significantly exceeded chance. These results indicate that TCD is a promising measurement modality for BCI research