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Nerve agents (NAs) produce acute and long-term brain injury and dysfunction, as evident from the Japan and Syria incidents. Magnetic resonance imaging (MRI) is a versatile technique to examine such chronic anatomical, functional, and neuronal damage in the brain. The objective of this study was to investigate long-term structural and neuronal lesion abnormalities in rats exposed to acute soman intoxication. T2-weighted MRI images of 10 control and 17 soman-exposed rats were acquired using a Siemens MRI system at 90 days after soman exposure. Quantification of brain tissue volumes and T2 signal intensity was conducted using the Inveon Research Workplace software and the extent of damage was correlated with histopathology and cognitive function. Soman-exposed rats showed drastic hippocampal atrophy with neuronal loss and reduced hippocampal volume (HV), indicating severe damage, but had similar T2 relaxation times to the control group, suggesting limited scarring and fluid density changes despite the volume decrease. Conversely, soman-exposed rats displayed significant increases in lateral ventricle volumes and T2 times, signifying strong cerebrospinal fluid expansion in compensation for tissue atrophy. The total brain volume, thalamic volume, and thalamic T2 time were similar in both groups, however, suggesting that some brain regions remained more intact long-term after soman intoxication. The MRI neuronal lesions were positively correlated with the histological markers of neurodegeneration and neuroinflammation 90 days after soman exposure. The predominant MRI hippocampal atrophy (25%) was highly consistent with massive reduction (35%) of neuronal nuclear antigen-positive (NeuN+ ) principal neurons and parvalbumin-positive (PV+ ) inhibitory interneurons within this brain region. The HV was significantly correlated with both inflammatory markers of GFAP+ astrogliosis and IBA1+ microgliosis. The reduced HV was also directly correlated with significant memory deficits in the soman-exposed cohort, confirming a possible neurobiological basis for neurological dysfunction. Together, these findings provide powerful insight on long-term region-specific neurodegenerative patterns after soman exposure and demonstrate the feasibility of in vivo neuroimaging to monitor neuropathology, predict the risk of neurological deficits, and evaluate response to medical countermeasures for NAs.

This article provides an overview of neuroimaging biomarkers in experimental epileptogenesis and refractory epilepsy. Neuroimaging represents a gold standard and clinically translatable technique to identify neuropathological changes in epileptogenesis and longitudinally monitor its progression after a precipitating injury. Neuroimaging studies, along with molecular studies from animal models, have greatly improved our understanding of the neuropathology of epilepsy, such as the hallmark hippocampus sclerosis. Animal models are effective for differentiating the different stages of epileptogenesis. Neuroimaging in experimental epilepsy provides unique information about anatomic, functional, and metabolic alterations linked to epileptogenesis. Recently, several in vivo biomarkers for epileptogenesis have been investigated for characterizing neuronal loss, inflammation, blood-brain barrier alterations, changes in neurotransmitter density, neurovascular coupling, cerebral blood flow and volume, network connectivity, and metabolic activity in the brain. Magnetic resonance imaging (MRI) is a sensitive method for detecting structural and functional changes in the brain, especially to identify region-specific neuronal damage patterns in epilepsy. Positron emission tomography (PET) and single-photon emission computerized tomography are helpful to elucidate key functional alterations, especially in areas of brain metabolism and molecular patterns, and can help monitor pathology of epileptic disorders. Multimodal procedures such as PET-MRI integrated systems are desired for refractory epilepsy. Validated biomarkers are warranted for early identification of people at risk for epilepsy and monitoring of the progression of medical interventions.

Purpose Metabolic dysfunction in Duchenne muscular dystrophy (DMD) is characterized by reduced glycolytic and oxidative enzymes, decreased and abnormal mitochondria, decreased ATP, and increased oxidative stress. We analyzed glucose metabolism as a potential disease biomarker in the genetically homologous golden retriever muscular dystrophy (GRMD) dog with molecular, biochemical, and in vivo imaging. Procedures Pelvic limb skeletal muscle and left ventricle tissue from the heart were analyzed by mRNA profiling, qPCR, western blotting, and immunofluorescence microscopy for the primary glucose transporter (GLUT4). Physiologic glucose handling was measured by fasting glucose tolerance test (GTT), insulin levels, and skeletal and cardiac positron emission tomography/X-ray computed tomography (PET/CT) using the glucose analog 2-deoxy-2-[18F]fluoro-d-glucose ([18F]FDG). Results MRNA profiles showed decreased GLUT4 in the cranial sartorius (CS), vastus lateralis (VL), and long digital extensor (LDE) of GRMD vs. normal dogs. QPCR confirmed GLUT4 downregulation but increased hexokinase-1. GLUT4 protein levels were not different in the CS, VL, or left ventricle but increased in the LDE of GRMD vs. normal. Microscopy revealed diffuse membrane expression of GLUT4 in GRMD skeletal but not cardiac muscle. GTT showed higher basal glucose and insulin in GRMD but rapid tissue glucose uptake at 5 min post-dextrose injection in GRMD vs. normal/carrier dogs. PET/ CT with [18F]FDG and simultaneous insulin stimulation showed a significant increase (p = 0.03) in mean standard uptake values (SUV) in GRMD skeletal muscle but not pelvic fat at 5 min post-[18F]FDG /insulin injection. Conversely, mean cardiac SUV was lower in GRMD than carrier/normal (p

Growth and development of multimedia technology has led to an exponential increase in visual information. Where traditional keyword based information retrieval techniques just do not meet the users demand, CBIR hopes to prevail. CBIR refers to the retrieval of images from a database using information derived from the images themselves rather than solely from accompanying text indices. In this paper we describe an approach of content based retrieval of images from a database, based on dominant colors in the foreground and background of the image. These dominant colors along with histogram and some statistical features form a substantial set to determine the overall similarity between the images. This technique is tested on Simplicity test database and promising results are observed.