Transfer of the brachialis to the anterior interosseous nerve as a treatment strategy for cervical spinal cord injury: Technical note

Study Design Technical report. Objective To provide a technical description of the transfer of the brachialis to the anterior interosseous nerve (AIN) for the treatment of tetraplegia after a cervical spinal cord injury (SCI). Methods In this technical report, the authors present a case illustration of an ideal surgical candidate for a brachialis-to-AIN transfer: a 21-year-old patient with a complete C7 spinal cord injury and failure of any hand motor recovery. The authors provide detailed description including images and video showing how to perform the brachialis-to-AIN transfer. Results The brachialis nerve and AIN fascicles can be successfully isolated using visual inspection and motor mapping. Then, careful dissection and microsurgical coaptation can be used for a successful anterior interosseous reinnervation. Conclusion The nerve transfer techniques for reinnervation have been described predominantly for the treatment of brachial plexus injuries. The majority of the nerve transfer techniques have focused on the upper brachial plexus or distal nerves of the lower brachial plexus. More recently, nerve transfers have reemerged as a potential reinnervation strategy for select patients with cervical SCI. The brachialis-to-AIN transfer technique offers a potential means for restoration of intrinsic hand function in patients with SCI

Functional disruptions of the brain in low back pain: A potential imaging biomarker of functional disability

Chronic low back pain (LBP) is one of the leading causes of disability worldwide. While LBP research has largely focused on the spine, many studies have demonstrated a restructuring of human brain architecture accompanying LBP and other chronic pain states. Brain imaging presents a promising source for discovering noninvasive biomarkers that can improve diagnostic and prognostication outcomes for chronic LBP. This study evaluated graph theory measures derived from brain resting-state functional connectivity (rsFC) as prospective noninvasive biomarkers of LBP. We also proposed and tested a hybrid feature selection method (Enet-subset) that combines Elastic Net and an optimal subset selection method. We collected resting-state functional MRI scans from 24 LBP patients and 27 age-matched healthy controls (HC). We then derived graph-theoretical features and trained a support vector machine (SVM) to classify patient group. The degree centrality (DC), clustering coefficient (CC), and betweenness centrality (BC) were found to be significant predictors of patient group. We achieved an average classification accuracy of 83.1%

Influence of white and gray matter connections on endogenous human cortical oscillations

Brain oscillations reflect changes in electrical potentials summated across neuronal populations. Low- and high-frequency rhythms have different modulation patterns. Slower rhythms are spatially broad, while faster rhythms are more local. From this observation, we hypothesized that low- and high-frequency oscillations reflect white- and gray-matter communications, respectively, and synchronization between low-frequency phase with high-frequency amplitude represents a mechanism enabling distributed brain-networks to coordinate local processing. Testing this common understanding, we selectively disrupted white or gray matter connections to human cortex while recording surface field potentials. Counter to our original hypotheses, we found that cortex consists of independent oscillatory-units (IOUs) that maintain their own complex endogenous rhythm structure. IOUs are differentially modulated by white and gray matter connections. White-matter connections maintain topographical anatomic heterogeneity (i.e., separable processing in cortical space) and gray-matter connections segregate cortical synchronization patterns (i.e., separable temporal processing through phase-power coupling). Modulation of distinct oscillatory modules enables the functional diversity necessary for complex processing in the human brain

The role of laser interstitial thermal therapy in enhancing progression-free survival of difficult-to-access high-grade gliomas: A multicenter study

Surgical extent-of-resection has been shown to have an impact on high-grade glioma (HGG) outcomes; however, complete resection is rarely achievable in difficult-to-access (DTA) tumors. Controlled thermal damage to the tumor may have the same impact in DTA-HGGs. We report our multicenter results of laser interstitial thermal therapy (LITT) in DTA-HGGs. We retrospectively reviewed 34 consecutive DTA-HGG patients (24 glioblastoma, 10 anaplastic) who underwent LITT at Cleveland Clinic, Washington University, and Wake Forest University (May 2011–December 2012) using the NeuroBlate® System. The extent of thermal damage was determined using thermal damage threshold (TDT) lines: yellow TDT line (43°C for 2 min) and blue TDT line (43°C for 10 min). Volumetric analysis was performed to determine the extent-of-coverage of tumor volume by TDT lines. Patient outcomes were evaluated statistically. LITT was delivered as upfront in 19 and delivered as salvage in 16 cases. After 7.2 months of follow-up, 71% of cases demonstrated progression and 34% died. The median overall survival (OS) for the cohort was not reached; however, the 1-year estimate of OS was 68 ± 9%. Median progression-free survival (PFS) was 5.1 months. Thirteen cases who met the following two criteria—(1) <0.05 cm(3) tumor volume not covered by the yellow TDT line and (2) <1.5 cm(3) additional tumor volume not covered by the blue TDT line—had better PFS than the other 21 cases (9.7 vs. 4.6 months; P = 0.02). LITT can be used effectively for treatment of DTA-HGGs. More complete coverage of tumor by TDT lines improves PFS which can be translated as the extent of resection concept for surgery

Spinal cord injury disrupts resting-state networks in the human brain

Despite 253,000 spinal cord injury (SCI) patients in the United States, little is known about how SCI affects brain networks. Spinal MRI provides only structural information with no insight into functional connectivity. Resting-state functional MRI (RS-fMRI) quantifies network connectivity through the identification of resting-state networks (RSNs) and allows detection of functionally relevant changes during disease. Given the robust network of spinal cord afferents to the brain, we hypothesized that SCI produces meaningful changes in brain RSNs. RS-fMRIs and functional assessments were performed on 10 SCI subjects. Blood oxygen-dependent RS-fMRI sequences were acquired. Seed-based correlation mapping was performed using five RSNs: default-mode (DMN), dorsal-attention (DAN), salience (SAL), control (CON), and somatomotor (SMN). RSNs were compared with normal control subjects using false-discovery rate-corrected two way t tests. SCI reduced brain network connectivity within the SAL, SMN, and DMN and disrupted anti-correlated connectivity between CON and SMN. When divided into separate cohorts, complete but not incomplete SCI disrupted connectivity within SAL, DAN, SMN and DMN and between CON and SMN. Finally, connectivity changed over time after SCI: the primary motor cortex decreased connectivity with the primary somatosensory cortex, the visual cortex decreased connectivity with the primary motor cortex, and the visual cortex decreased connectivity with the sensory parietal cortex. These unique findings demonstrate the functional network plasticity that occurs in the brain as a result of injury to the spinal cord. Connectivity changes after SCI may serve as biomarkers to predict functional recovery following an SCI and guide future therapy

Multi-modal biomarkers of low back pain: A machine learning approach

Chronic low back pain (LBP) is a very common health problem worldwide and a major cause of disability. Yet, the lack of quantifiable metrics on which to base clinical decisions leads to imprecise treatments, unnecessary surgery and reduced patient outcomes. Although, the focus of LBP has largely focused on the spine, the literature demonstrates a robust reorganization of the human brain in the setting of LBP. Brain neuroimaging holds promise for the discovery of biomarkers that will improve the treatment of chronic LBP. In this study, we report on morphological changes in cerebral cortical thickness (CT) and resting-state functional connectivity (rsFC) measures as potential brain biomarkers for LBP. Structural MRI scans, resting state functional MRI scans and self-reported clinical scores were collected from 24 LBP patients and 27 age-matched healthy controls (HC). The results suggest widespread differences in CT in LBP patients relative to HC. These differences in CT are correlated with self-reported clinical summary scores, the Physical Component Summary and Mental Component Summary scores. The primary visual, secondary visual and default mode networks showed significant age-corrected increases in connectivity with multiple networks in LBP patients. Cortical regions classified as hubs based on their eigenvector centrality (EC) showed differences in their topology within motor and visual processing regions. Finally, a support vector machine trained using CT to classify LBP subjects from HC achieved an average classification accuracy of 74.51%, AUC = 0.787 (95% CI: 0.66-0.91). The findings from this study suggest widespread changes in CT and rsFC in patients with LBP while a machine learning algorithm trained using CT can predict patient group. Taken together, these findings suggest that CT and rsFC may act as potential biomarkers for LBP to guide therapy

Metastatic pleomorphic sarcoma to left atrium

Although several thousand patients are diagnosed with sarcoma annually in the United States, metastases to the heart are very uncommon. In this case report, an overall low frequency cancer presents masquerading with common cardiac symptomology. This case illustrates the importance for detailed diagnostic cardiac evaluations and heightened suspicion by physicians to consider metastatic disease to the heart in cancer patients with cardiovascular complications. Also discussed is a review of surgical and chemotherapeutic options for this problem

A hippocampal Cdk5 pathway regulates extinction of contextual fear

Treatment of emotional disorders involves the promotion of extinction processes, which are defined as the learned reduction of fear. The molecular mechanisms underlying extinction have only begun to be elucidated. By employing genetic and pharmacological approaches in mice, we show here that extinction requires downregulation of Rac-1 and cyclin-dependent kinase 5 (Cdk5), and upregulation of p21 activated kinase-1 (PAK-1) activity. This is physiologically achieved by a Rac-1–dependent relocation of the Cdk5 activator p35 from the membrane to the cytosol and dissociation of p35 from PAK-1. Moreover, our data suggest that Cdk5/p35 activity prevents extinction in part by inhibition of PAK-1 activity in a Rac-1–dependent manner. We propose that extinction of contextual fear is regulated by counteracting components of a molecular pathway involving Rac-1, Cdk5 and PAK-1. Our data suggest that this pathway could provide a suitable target for therapeutic treatment of emotional disorders.National Institutes of Health (U.S.) (Grant NS051874)Alexander von Humboldt-Stiftung (German Research Foundation Fellowship)European Neuroscience Institute Goettinge

Resistance to Volatile Anesthetics by Mutations Enhancing Excitatory Neurotransmitter Release in Caenorhabditis elegans

The molecular mechanisms whereby volatile general anesthetics (VAs) disrupt behavior remain undefined. In Caenorhabditis elegans mutations in the gene unc-64, which encodes the presynaptic protein syntaxin 1A, produce large allele-specific differences in VA sensitivity. UNC-64 syntaxin normally functions to mediate fusion of neurotransmitter vesicles with the presynaptic membrane. The precise role of syntaxin in the VA mechanism is as yet unclear, but a variety of results suggests that a protein interacting with syntaxin to regulate neurotransmitter release is essential for VA action in C. elegans. To identify additional proteins that function with syntaxin to control neurotransmitter release and VA action, we screened for suppressors of the phenotypes produced by unc-64 reduction of function. Loss-of-function mutations in slo-1, which encodes a Ca(2+)-activated K(+) channel, and in unc-43, which encodes CaM-kinase II, and a gain-of-function mutation in egl-30, which encodes Gqα, were isolated as syntaxin suppressors. The slo-1 and egl-30 mutations conferred resistance to VAs, but unc-43 mutations did not. The effects of slo-1 and egl-30 on VA sensitivity can be explained by their actions upstream or parallel to syntaxin to increase the level of excitatory neurotransmitter release. These results strengthen the link between transmitter release and VA action