136 research outputs found
TRIM5 Suppresses Cross-Species Transmission of a Primate Immunodeficiency Virus and Selects for Emergence of Resistant Variants in the New Species
Cross-species transmission of simian immunodeficiency virus from sooty mangabeys (SIVsm) into rhesus macaques, and subsequent emergence of pathogenic SIVmac, required adaptation to overcome restriction encoded by the macaque TRIM5 gene
Single amino acid change in gp41 region of HIV-1 alters bystander apoptosis and CD4 decline in humanized mice
<p>Abstract</p> <p>Background</p> <p>The mechanism by which HIV infection leads to a selective depletion of CD4 cells leading to immunodeficiency remains highly debated. Whether the loss of CD4 cells is a direct consequence of virus infection or bystander apoptosis of uninfected cells is also uncertain.</p> <p>Results</p> <p>We have addressed this issue in the humanized mouse model of HIV infection using a HIV variant with a point mutation in the gp41 region of the Env glycoprotein that alters its fusogenic activity. We demonstrate here that a single amino acid change (V38E) altering the cell-to-cell fusion activity of the Env minimizes CD4 loss in humanized mice without altering viral replication. This differential pathogenesis was associated with a lack of bystander apoptosis induction by V38E virus even in the presence of similar levels of infected cells. Interestingly, immune activation was observed with both WT and V38E infection suggesting that the two phenomena are likely not interdependent in the mouse model.</p> <p>Conclusions</p> <p>We conclude that Env fusion activity is one of the determinants of HIV pathogenesis and it may be possible to attenuate HIV by targeting gp41.</p
Similar Impact of CD8+ T Cell Responses on Early Virus Dynamics during SIV Infections of Rhesus Macaques and Sooty Mangabeys
Despite comparable levels of virus replication, simian immunodeficiency viruses (SIV) infection is non-pathogenic in natural hosts, such as sooty mangabeys (SM), whereas it is pathogenic in non-natural hosts, such as rhesus macaques (RM). Comparative studies of pathogenic and non-pathogenic SIV infection can thus shed light on the role of specific factors in SIV pathogenesis. Here, we determine the impact of target-cell limitation, CD8+ T cells, and Natural Killer (NK) cells on virus replication in the early SIV infection. To this end, we fit previously published data of experimental SIV infections in SMs and RMs with mathematical models incorporating these factors and assess to what extent the inclusion of individual factors determines the quality of the fits. We find that for both rhesus macaques and sooty mangabeys, target-cell limitation alone cannot explain the control of early virus replication, whereas including CD8+ T cells into the models significantly improves the fits. By contrast, including NK cells does only significantly improve the fits in SMs. These findings have important implications for our understanding of SIV pathogenesis as they suggest that the level of early CD8+ T cell responses is not the key difference between pathogenic and non-pathogenic SIV infection
Multimodal surface-based morphometry reveals diffuse cortical atrophy in traumatic brain injury.
<p>Abstract</p> <p>Background</p> <p>Patients with traumatic brain injury (TBI) often present with significant cognitive deficits without corresponding evidence of cortical damage on neuroradiological examinations. One explanation for this puzzling observation is that the diffuse cortical abnormalities that characterize TBI are difficult to detect with standard imaging procedures. Here we investigated a patient with severe TBI-related cognitive impairments whose scan was interpreted as normal by a board-certified radiologist in order to determine if quantitative neuroimaging could detect cortical abnormalities not evident with standard neuroimaging procedures.</p> <p>Methods</p> <p>Cortical abnormalities were quantified using multimodal surfaced-based morphometry (MSBM) that statistically combined information from high-resolution structural MRI and diffusion tensor imaging (DTI). Normal values of cortical anatomy and cortical and pericortical DTI properties were quantified in a population of 43 healthy control subjects. Corresponding measures from the patient were obtained in two independent imaging sessions. These data were quantified using both the average values for each lobe and the measurements from each point on the cortical surface. The results were statistically analyzed as z-scores from the mean with a p < 0.05 criterion, corrected for multiple comparisons. False positive rates were verified by comparing the data from each control subject with the data from the remaining control population using identical statistical procedures.</p> <p>Results</p> <p>The TBI patient showed significant regional abnormalities in cortical thickness, gray matter diffusivity and pericortical white matter integrity that replicated across imaging sessions. Consistent with the patient's impaired performance on neuropsychological tests of executive function, cortical abnormalities were most pronounced in the frontal lobes.</p> <p>Conclusions</p> <p>MSBM is a promising tool for detecting subtle cortical abnormalities with high sensitivity and selectivity. MSBM may be particularly useful in evaluating cortical structure in TBI and other neurological conditions that produce diffuse abnormalities in both cortical structure and tissue properties.</p
Use of hydrophilic and hydrophobic polymers for the development of controlled release tizanidine matrix tablets
Thalamic inflammation after brain trauma is associated with thalamo-cortical white matter damage
Voxel-based statistical analysis of thalamic glucose metabolism in traumatic brain injury: relationship with consciousness and cognition
Objective: To study the relationship between thalamic glucose metabolism and neurological outcome after severe traumatic
brain injury (TBI).
Methods: Forty-nine patients with severe and closed TBI and 10 healthy control subjects with 18F-FDG PET were studied.
Patients were divided into three groups: MCS&VS group (n ÂĽ 17), patients in a vegetative or a minimally conscious state;
In-PTA group (n ÂĽ 12), patients in a state of post-traumatic amnesia (PTA); and Out-PTA group (n ÂĽ 20), patients who
had emerged from PTA. SPM5 software implemented in MATLAB 7 was used to determine the quantitative differences
between patients and controls. FDG-PET images were spatially normalized and an automated thalamic ROI mask was
generated. Group differences were analysed with two sample voxel-wise t-tests.
Results: Thalamic hypometabolism was the most prominent in patients with low consciousness (MCS&VS group) and the
thalamic hypometabolism in the In-PTA group was more prominent than that in the Out-PTA group. Healthy control
subjects showed the greatest thalamic metabolism. These differences in metabolism were more pronounced in the internal
regions of the thalamus.
Conclusions: The results confirm the vulnerability of the thalamus to suffer the effect of the dynamic forces generated during
a TBI. Patients with thalamic hypometabolism could represent a sub-set of subjects that are highly vulnerable to
neurological disability after TBI.Lull Noguera, N.; NoĂ©, E.; Lull Noguera, JJ.; Garcia Panach, J.; Chirivella, J.; Ferri, J.; LĂłpez-Aznar, D.... (2010). Voxel-based statistical analysis of thalamic glucose metabolism in traumatic brain injury: relationship with consciousness and cognition. Brain Injury. 24(9):1098-1107. doi:10.3109/02699052.2010.494592S10981107249Gallagher, C. N., Hutchinson, P. J., & Pickard, J. D. (2007). Neuroimaging in trauma. Current Opinion in Neurology, 20(4), 403-409. doi:10.1097/wco.0b013e32821b987bWoischneck, D., Klein, S., Reiďż˝berg, S., Dďż˝hring, W., Peters, B., & Firsching, R. (2001). Classification of Severe Head Injury Based on Magnetic Resonance Imaging. Acta Neurochirurgica, 143(3), 263-271. doi:10.1007/s007010170106Grados, M. A. (2001). Depth of lesion model in children and adolescents with moderate to severe traumatic brain injury: use of SPGR MRI to predict severity and outcome. Journal of Neurology, Neurosurgery & Psychiatry, 70(3), 350-358. doi:10.1136/jnnp.70.3.350Meythaler, J. M., Peduzzi, J. D., Eleftheriou, E., & Novack, T. A. (2001). Current concepts: Diffuse axonal injury–associated traumatic brain injury. Archives of Physical Medicine and Rehabilitation, 82(10), 1461-1471. doi:10.1053/apmr.2001.25137Scheid, R., Walther, K., Guthke, T., Preul, C., & von Cramon, D. Y. (2006). Cognitive Sequelae of Diffuse Axonal Injury. Archives of Neurology, 63(3), 418. doi:10.1001/archneur.63.3.418Brandstack, N., Kurki, T., Tenovuo, O., & Isoniemi, H. (2006). MR imaging of head trauma: Visibility of contusions and other intraparenchymal injuries in early and late stage. Brain Injury, 20(4), 409-416. doi:10.1080/02699050500487951Xu, J., Rasmussen, I.-A., Lagopoulos, J., & HĂĄberg, A. (2007). Diffuse Axonal Injury in Severe Traumatic Brain Injury Visualized Using High-Resolution Diffusion Tensor Imaging. Journal of Neurotrauma, 24(5), 753-765. doi:10.1089/neu.2006.0208Levine, B., Fujiwara, E., O’connor, C., Richard, N., Kovacevic, N., Mandic, M., … Black, S. E. (2006). In Vivo Characterization of Traumatic Brain Injury Neuropathology with Structural and Functional Neuroimaging. Journal of Neurotrauma, 23(10), 1396-1411. doi:10.1089/neu.2006.23.1396Metting, Z., Rödiger, L. A., De Keyser, J., & van der Naalt, J. (2007). Structural and functional neuroimaging in mild-to-moderate head injury. The Lancet Neurology, 6(8), 699-710. doi:10.1016/s1474-4422(07)70191-6Nakayama, N. (2006). Relationship between regional cerebral metabolism and consciousness disturbance in traumatic diffuse brain injury without large focal lesions: an FDG-PET study with statistical parametric mapping analysis. Journal of Neurology, Neurosurgery & Psychiatry, 77(7), 856-862. doi:10.1136/jnnp.2005.080523Nakayama, N. (2006). Evidence for white matter disruption in traumatic brain injury without macroscopic lesions. Journal of Neurology, Neurosurgery & Psychiatry, 77(7), 850-855. doi:10.1136/jnnp.2005.077875O’Leary, D. D. M., Schlaggar, B. L., & Tuttle, R. (1994). Specification of Neocortical Areas and Thalamocortical Connections. Annual Review of Neuroscience, 17(1), 419-439. doi:10.1146/annurev.ne.17.030194.002223Mitelman, S. A., Byne, W., Kemether, E. M., Newmark, R. E., Hazlett, E. A., Haznedar, M. M., & Buchsbaum, M. S. (2006). Metabolic thalamocortical correlations during a verbal learning task and their comparison with correlations among regional volumes. Brain Research, 1114(1), 125-137. doi:10.1016/j.brainres.2006.07.043Laureys, S., Faymonville, M., Luxen, A., Lamy, M., Franck, G., & Maquet, P. (2000). Restoration of thalamocortical connectivity after recovery from persistent vegetative state. The Lancet, 355(9217), 1790-1791. doi:10.1016/s0140-6736(00)02271-6Laureys, S., Goldman, S., Phillips, C., Van Bogaert, P., Aerts, J., Luxen, A., … Maquet, P. (1999). Impaired Effective Cortical Connectivity in Vegetative State: Preliminary Investigation Using PET. NeuroImage, 9(4), 377-382. doi:10.1006/nimg.1998.0414Laureys, S., Owen, A. M., & Schiff, N. D. (2004). Brain function in coma, vegetative state, and related disorders. The Lancet Neurology, 3(9), 537-546. doi:10.1016/s1474-4422(04)00852-xGuye, M., Bartolomei, F., & Ranjeva, J.-P. (2008). Imaging structural and functional connectivity: towards a unified definition of human brain organization? Current Opinion in Neurology, 24(4), 393-403. doi:10.1097/wco.0b013e3283065cfbPrice, C. J., & Friston, K. J. (2002). Functional Imaging Studies of Neuropsychological Patients: Applications and Limitations. Neurocase, 8(5), 345-354. doi:10.1076/neur.8.4.345.16186Kim, J., Avants, B., Patel, S., Whyte, J., Coslett, B. H., Pluta, J., … Gee, J. C. (2008). Structural consequences of diffuse traumatic brain injury: A large deformation tensor-based morphometry study. NeuroImage, 39(3), 1014-1026. doi:10.1016/j.neuroimage.2007.10.005Maxwell, W. L., MacKinnon, M. A., Smith, D. H., McIntosh, T. K., & Graham, D. I. (2006). Thalamic Nuclei After Human Blunt Head Injury. Journal of Neuropathology & Experimental Neurology, 65(5), 478-488. doi:10.1097/01.jnen.0000229241.28619.75SIDAROS, A., SKIMMINGE, A., LIPTROT, M., SIDAROS, K., ENGBERG, A., HERNING, M., … ROSTRUP, E. (2009). Long-term global and regional brain volume changes following severe traumatic brain injury: A longitudinal study with clinical correlates. NeuroImage, 44(1), 1-8. doi:10.1016/j.neuroimage.2008.08.030Ashburner, J., & Friston, K. J. (2000). Voxel-Based Morphometry—The Methods. NeuroImage, 11(6), 805-821. doi:10.1006/nimg.2000.0582Good, C. D., Johnsrude, I. S., Ashburner, J., Henson, R. N. A., Friston, K. J., & Frackowiak, R. S. J. (2001). A Voxel-Based Morphometric Study of Ageing in 465 Normal Adult Human Brains. NeuroImage, 14(1), 21-36. doi:10.1006/nimg.2001.0786Giacino, J. T., Ashwal, S., Childs, N., Cranford, R., Jennett, B., Katz, D. I., … Zasler, N. D. (2002). The minimally conscious state: Definition and diagnostic criteria. Neurology, 58(3), 349-353. doi:10.1212/wnl.58.3.349Gispert, J. ., Pascau, J., Reig, S., MartĂnez-Lázaro, R., Molina, V., GarcĂa-Barreno, P., & Desco, M. (2003). Influence of the normalization template on the outcome of statistical parametric mapping of PET scans. NeuroImage, 19(3), 601-612. doi:10.1016/s1053-8119(03)00072-7Ashburner, J., & Friston, K. J. (1999). Nonlinear spatial normalization using basis functions. Human Brain Mapping, 7(4), 254-266. doi:10.1002/(sici)1097-0193(1999)7:43.0.co;2-gTzourio-Mazoyer, N., Landeau, B., Papathanassiou, D., Crivello, F., Etard, O., Delcroix, N., … Joliot, M. (2002). Automated Anatomical Labeling of Activations in SPM Using a Macroscopic Anatomical Parcellation of the MNI MRI Single-Subject Brain. NeuroImage, 15(1), 273-289. doi:10.1006/nimg.2001.0978Genovese, C. R., Lazar, N. A., & Nichols, T. (2002). Thresholding of Statistical Maps in Functional Neuroimaging Using the False Discovery Rate. NeuroImage, 15(4), 870-878. doi:10.1006/nimg.2001.1037LAUREYS, S., LEMAIRE, C., MAQUET, P., PHILLIPS, C., & FRANCK, G. (1999). Cerebral metabolism during vegetative state and after recovery to consciousness. Journal of Neurology, Neurosurgery & Psychiatry, 67(1), 121-122. doi:10.1136/jnnp.67.1.121Tommasino, C., Grana, C., Lucignani, G., Torri, G., & Fazio, F. (1995). Regional Cerebral Metabolism of Glucose in Comatose and Vegetative State Patients. Journal of Neurosurgical Anesthesiology, 7(2), 109-116. doi:10.1097/00008506-199504000-00006ANDERSON, C. V., WOOD, D.-M. G., BIGLER, E. D., & BLATTER, D. D. (1996). Lesion Volume, Injury Severity, and Thalamic Integrity following Head Injury. Journal of Neurotrauma, 13(2), 59-65. doi:10.1089/neu.1996.13.59Ge, Y., Patel, M. B., Chen, Q., Grossman, E. J., Zhang, K., Miles, L., … Grossman, R. I. (2009). Assessment of thalamic perfusion in patients with mild traumatic brain injury by true FISP arterial spin labelling MR imaging at 3T. Brain Injury, 23(7-8), 666-674. doi:10.1080/02699050903014899Uzan, M. (2003). Thalamic proton magnetic resonance spectroscopy in vegetative state induced by traumatic brain injury. Journal of Neurology, Neurosurgery & Psychiatry, 74(1), 33-38. doi:10.1136/jnnp.74.1.33OMMAYA, A. K., & GENNARELLI, T. A. (1974). CEREBRAL CONCUSSION AND TRAUMATIC UNCONSCIOUSNESS. Brain, 97(1), 633-654. doi:10.1093/brain/97.1.633Giacino, J., & Whyte, J. (2005). The Vegetative and Minimally Conscious States. Journal of Head Trauma Rehabilitation, 20(1), 30-50. doi:10.1097/00001199-200501000-00005Zeman, A. (2001). Consciousness. Brain, 124(7), 1263-1289. doi:10.1093/brain/124.7.1263Kinney, H. C., Korein, J., Panigrahy, A., Dikkes, P., & Goode, R. (1994). Neuropathological Findings in the Brain of Karen Ann Quinlan -- The Role of the Thalamus in the Persistent Vegetative State. New England Journal of Medicine, 330(21), 1469-1475. doi:10.1056/nejm199405263302101Saeeduddin Ahmed, Rex Bierley, Java. (2000). Post-traumatic amnesia after closed head injury: a review of the literature and some suggestions for further research. Brain Injury, 14(9), 765-780. doi:10.1080/026990500421886Wilson, J. T., Hadley, D. M., Wiedmann, K. D., & Teasdale, G. M. (1995). Neuropsychological consequences of two patterns of brain damage shown by MRI in survivors of severe head injury. Journal of Neurology, Neurosurgery & Psychiatry, 59(3), 328-331. doi:10.1136/jnnp.59.3.328Wilson, J. T., Teasdale, G. M., Hadley, D. M., Wiedmann, K. D., & Lang, D. (1994). Post-traumatic amnesia: still a valuable yardstick. Journal of Neurology, Neurosurgery & Psychiatry, 57(2), 198-201. doi:10.1136/jnnp.57.2.198Fearing, M. A., Bigler, E. D., Wilde, E. A., Johnson, J. L., Hunter, J. V., Xiaoqi Li, … Levin, H. S. (2008). Morphometric MRI Findings in the Thalamus and Brainstem in Children After Moderate to Severe Traumatic Brain Injury. Journal of Child Neurology, 23(7), 729-737. doi:10.1177/0883073808314159Little, D. M., Kraus, M. F., Joseph, J., Geary, E. K., Susmaras, T., Zhou, X. J., … Gorelick, P. B. (2010). Thalamic integrity underlies executive dysfunction in traumatic brain injury. Neurology, 74(7), 558-564. doi:10.1212/wnl.0b013e3181cff5d
Guidelines for management of ischaemic stroke and transient ischaemic attack 2008
This article represents the update of the European Stroke Initiative Recommendations for Stroke Management. These guidelines cover both ischaemic stroke and transient ischaemic attacks, which are now considered to be a single entity. The article covers referral and emergency management, Stroke Unit service, diagnostics, primary and secondary prevention, general stroke treatment, specific treatment including acute management, management of complications, and rehabilitation
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