Notes

Tachycardia and also hypertension boost tracer efflux through the vertebrae.
pon the socioeconomic forces for the acid deposition in China for the first time and provided the new information for government sectors to control the acid rain pollution in the future. Porcine circovirus type 2 (PCV2) has one of the highest evolutionary rates among DNA viruses. Traditionally, PCV2 vaccines have been based on the 2a genotype as this was the first genotype discovered. Today, eight genotypes of PCV2 viruses have been identified, and, taken together with the rapid evolutionary rate, propensity to recombine, and high rate of vaccination, further variation in PCV2 is expected. For these reasons, there is a growing genetic gap between available vaccines and field strains. When selecting vaccines, it is important to consider vaccines that contain T cell epitopes that are well-matched to the circulating strains. To quantify the relatedness between PCV2 vaccines and field strains, we predicted and compared their T cell epitope content and calculated Epitope Content Comparison (EpiCC) scores using established in silico tools. T cell epitopes predicted to bind common class I and class II swine leukocyte antigen (SLA) alleles were identified from two major structural proteins, the capsiEpiCC score. PCV2 continues to evolve and EpiCC analysis provides a new tool to assess the possible impact of virus genetic divergence on T cell epitope coverage of vaccine strains. Given that multiple genotypes are currently found and may co-exist on farms, this analysis suggests that a combination of PCV2a and PCV2b vaccine strains may be required to provide optimal coverage of current and future field isolates. BACKGROUND The role of the brain in processing pain has been extensively investigated using various functional imaging techniques coupled with well controlled noxious stimuli. Studies applying experimental pain have also used proton magnetic resonance spectroscopy (1H-MRS). The advantage of MRS compared to other techniques is the capacity to non-invasively examine metabolites involved in neurotransmission of pain, including glutamate, γ-aminobutyric acid (GABA), glutamate + glutamine (Glx), and glutamine. OBJECTIVE To systematically review MRS studies used in the context of studying experimental pain in healthy human participants. DATA SOURCES PubMed, Ovid Medline, and Embase databases were searched using pre-specified search terms. ELIGIBILITY CRITERIA Studies investigating glutamate, GABA, Glx and/or glutamine in relation to experimental pain (e.g., heat) in healthy participants via MRS. APPRAISAL CRITERIA Each study was evaluated with a modified quality criterion (used in previous imaging systematic revi a limited number of studies that used MRS to examine experimental pain. In light of this and major differences in study design, we did not attempt to aggregate results in a meta-analysis. As for the studies we reviewed, there was a limited number of brain areas were examined by studies included in our review. Moreover, the majority of studies included lacked an adequate control condition (i.e., non-noxious stimulation) or blinding, which represent a major source of potential bias. CONCLUSION MRS represents a promising tool to examine the brain in pain, functionally, and at rest with support for increased glutamate, glutamine and Glx levels in relation to pain. NSC 122758 IMPLICATIONS Resting and functional MRS should be viewed as complementary to existing neuroimaging techniques, and serve to investigate the brain in pain. Systematic review registration number- CRD42018112917. An object that is looming toward a subject or receding away contains important information for determining if this object is dangerous, beneficial or harmless. This information (motion, direction, identity, time-to-collision, size, velocity) is analyzed by the brain in order to execute the appropriate behavioral responses depending on the context fleeing, freezing, grasping, eating, exploring. In the current study, we performed ultra-high-field functional MRI (fMRI) at 9.4T in awake marmosets to explore the patterns of brain activation elicited by visual stimuli looming toward or receding away from the monkey. We found that looming and receding visual stimuli activated a large cortical network in frontal, parietal, temporal and occipital cortex in areas involved in the analysis of motion, shape, identity and features of the objects. Looming stimuli strongly activated a network composed of portions of the pulvinar, superior colliculus, putamen, parietal, prefrontal and temporal cortical areas. These activations suggest the existence of a network that processes visual stimuli looming toward peripersonal space to predict the consequence of these stimuli. Together with previous studies in macaque monkeys, these findings indicate that this network is preserved across Old and New World primates. BACKGROUND AND AIMS Preterm birth imposes a high risk for developing neuromotor delay. Earlier prediction of adverse outcome in preterm infants is crucial for referral to earlier intervention. This study aimed to predict abnormal motor outcome at 2 years from early brain diffusion magnetic resonance imaging (MRI) acquired between 29 and 35 weeks postmenstrual age (PMA) using a deep learning convolutional neural network (CNN) model. METHODS Seventy-seven very preterm infants (born less then 31 weeks gestational age (GA)) in a prospective longitudinal cohort underwent diffusion MR imaging (3T Siemens Trio; 64 directions, b=2000 s/mm2). Motor outcome at 2 years corrected age (CA) was measured by Neuro-Sensory Motor Developmental Assessment (NSMDA). Scores were dichotomised into normal (functional score 0, normal; n=48) and abnormal scores (functional score 1-5, mild-profound; n=29). MRIs were pre-processed to reduce artefacts, upsampled to 1.25 mm isotropic resolution and maps of fractional anisotropy (FA) werearound the motor cortex and somatosensory regions were most frequently identified by the model with high precision (74%) as a location associated with abnormal outcome. Part of the cerebellum, and occipital and frontal lobes were also highly associated with abnormal NSMDA/motor outcome. DISCUSSION/CONCLUSION This study established the potential of an early brain MRI-based deep learning CNN model to identify preterm infants at risk of a later motor impairment and to identify brain regions predictive of adverse outcome. Results suggest that predictions can be made from FA maps of diffusion MRIs well before term equivalent age (TEA) without any prior knowledge of which MRI features to extract and associated feature extraction steps. This method, therefore, is suitable for any case of brain condition/abnormality. Future studies should be conducted on a larger cohort to re-validate the robustness and effectiveness of these models.
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