Spatial representation and attention in toddlers with Williams syndrome and Down syndrome

The nature of the spatial representations that underlie simple visually guided actions early in life was investigated in toddlers with Williams syndrome (WS), Down syndrome (DS), and healthy chronological age- and mental age-matched controls, through the use of a "double-step" saccade paradigm. The experiment tested the hypothesis that, compared to typically developing infants and toddlers, and toddlers with DS, those with WS display a deficit in using spatial representations to guide actions. Levels of sustained attention were also measured within these groups, to establish whether differences in levels of engagement influenced performance on the double-step saccade task. The results showed that toddlers with WS were unable to combine extra-retinal information with retinal information to the same extent as the other groups, and displayed evidence of other deficits in saccade planning, suggesting a greater reliance on sub-cortical mechanisms than the other populations. Results also indicated that their exploration of the visual environment is less developed. The sustained attention task revealed shorter and fewer periods of sustained attention in toddlers with DS, but not those with WS, suggesting that WS performance on the double-step saccade task is not explained by poorer engagement. The findings are also discussed in relation to a possible attention disengagement deficit in WS toddlers. Our study highlights the importance of studying genetic disorders early in development. (C) 2002 Elsevier Science Ltd. All rights reserved.

I see happy people: attention bias towards happy but not angry facial expressions in Williams syndrome

Introduction: Observations of behaviour and research using eye-tracking technology have shown that individuals with Williams syndrome (WS) pay an unusual amount of attention to other people’s faces. The present research examines whether this attention to faces is moderated by the valence of emotional expression. Method: Sixteen participants with WS aged between 13 and 29 years (Mean=19 years 9 months) completed a dot-probe task in which pairs of faces displaying happy, angry and neutral expressions were presented. The performance of the WS group was compared to two groups of typically developing control participants, individually matched to the participants in the WS group on either chronological age or mental age. General mental age was assessed in the WS group using the Woodcock Johnson Test of Cognitive Ability Revised (WJ-COG-R; Woodcock & Johnson, 1989; 1990). Results: Compared to both control groups, the WS group exhibited a greater attention bias for happy faces. In contrast, no between-group differences in bias for angry faces were obtained. Conclusions: The results are discussed in relation to recent neuroimaging findings and the hypersocial behaviour that is characteristic of the WS population.

Ticagrelor Versus Clopidogrel in Patients With Acute Coronary Syndromes and a History of Stroke or Transient Ischemic Attack

Background-Patients with acute coronary syndromes and history of stroke or transient ischemic attack (TIA) have an increased rate of recurrent cardiac events and intracranial hemorrhages. Methods and Results-We evaluated treatment effects of ticagrelor versus clopidogrel in patients with acute coronary syndrome with and without a history of prior stroke or TIA in the PLATelet inhibition and patient Outcomes (PLATO) trial. Of the 18 624 randomized patients, 1152 (6.2%) had a history of stroke or TIA. Such patients had higher rates of myocardial infarction (11.5% versus 6.0%), death (10.5% versus 4.9%), stroke (3.4% versus 1.2%), and intracranial bleeding (0.8% versus 0.2%) than patients without prior stroke or TIA. Among patients with a history of stroke or TIA, the reduction of the primary composite outcome and total mortality at 1 year with ticagrelor versus clopidogrel was consistent with the overall trial results: 19.0% versus 20.8% (hazard ratio, 0.87; 95% confidence interval, 0.66-1.13; interaction P=0.84) and 7.9% versus 13.0% (hazard ratio, 0.62; 95% confidence interval, 0.42-0.91). The overall PLATO-defined bleeding rates were similar: 14.6% versus 14.9% (hazard ratio, 0.99; 95% confidence interval, 0.71-1.37), and intracranial bleeding occurred infrequently (4 versus 4 cases, respectively). Conclusions-Patients with acute coronary syndrome with a prior history of ischemic stroke or TIA had higher rates of clinical outcomes than patients without prior stroke or TIA. However, the efficacy and bleeding results of ticagrelor in these high-risk patients were consistent with the overall trial population, with a favorable clinical net benefit and associated impact on mortality.

Metopic and sagittal synostosis in Greig cephalopolysyndactyly syndrome: five cases with intragenic mutations or complete deletions of GLI3

Greig cephalopolysyndactyly syndrome (GCPS) is a multiple congenital malformation characterised by limb and craniofacial anomalies, caused by heterozygous mutation or deletion of GLI3. We report four boys and a girl who were presented with trigonocephaly due to metopic synostosis, in association with pre- and post-axial polydactyly and cutaneous syndactyly of hands and feet. Two cases had additional sagittal synostosis. None had a family history of similar features. In all five children, the diagnosis of GCPS was confirmed by molecular analysis of GLI3 (two had intragenic mutations and three had complete gene deletions detected on array comparative genomic hybridisation), thus highlighting the importance of trigonocephaly or overt metopic or sagittal synostosis as a distinct presenting feature of GCPS. These observations confirm and extend a recently proposed association of intragenic GLI3 mutations with metopic synostosis; moreover, the three individuals with complete deletion of GLI3 were previously considered to have Carpenter syndrome, highlighting an important source of diagnostic confusion.

Depression, the metabolic syndrome and cardiovascular risk

BACKGROUND: The relationship between depression and the metabolic syndrome is unclear, and whether metabolic syndrome explains the association between depression and cardiovascular disease (CVD) risk is unknown. METHODS: We studied 652 women who received coronary angiography as part of the Women's Ischemia Syndrome Evaluation (WISE) study and completed the Beck Depression Inventory (BDI). Women who had both elevated depressive symptoms (BDI > or =10) and a previous diagnosis of depression were considered at highest risk, whereas those with one of the two conditions represented an intermediate group. The metabolic syndrome was defined according to the ATP-III criteria. The main outcome was incidence of adverse CVD events (hospitalizations for myocardial infarction, stroke, congestive heart failure, and CVD-related mortality) over a median follow-up of 5.9 years. RESULTS: After adjusting for demographic factors, lifestyle and functional status, both depression categories were associated with about 60% increased odds for metabolic syndrome compared with no depression (p = .03). The number of metabolic syndrome risk factors increased gradually across the three depression categories (p = .003). During follow-up, 104 women (15.9%) experienced CVD events. In multivariable analysis, women with both elevated symptoms and a previous diagnosis of depression had 2.6 times higher risk of CVD. When metabolic syndrome was added to the model, the risk associated with depression only decreased by 7%, and both depression and metabolic syndrome remained significant predictors of CVD. CONCLUSIONS: In women with suspected coronary artery disease, the metabolic syndrome is independently associated with depression but explains only a small portion of the association between depression and incident CVD.

Extent of coronary artery disease and outcomes after ticagrelor administration in patients with an acute coronary syndrome: Insights from the PLATelet inhibition and patient Outcomes (PLATO) trial.

BACKGROUND Extensive coronary artery disease (CAD) is associated with higher risk. In this substudy of the PLATO trial, we examined the effects of randomized treatment on outcome events and safety in relation to the extent of CAD. METHODS Patients were classified according to presence of extensive CAD (defined as 3-vessel disease, left main disease, or prior coronary artery bypass graft surgery). The trial's primary and secondary end points were compared using Cox proportional hazards regression. RESULTS Among 15,388 study patients for whom the extent of CAD was known, 4,646 (30%) had extensive CAD. Patients with extensive CAD had more high-risk characteristics and experienced more clinical events during follow-up. They were less likely to undergo percutaneous coronary intervention (58% vs 79%, P < .001) but more likely to undergo coronary artery bypass graft surgery (16% vs 2%, P < .001). Ticagrelor, compared with clopidogrel, reduced the composite of cardiovascular death, myocardial infarction, and stroke in patients with extensive CAD (14.9% vs 17.6%, hazard ratio [HR] 0.85 [0.73-0.98]) similar to its reduction in those without extensive CAD (6.8% vs 8.0%, HR 0.85 [0.74-0.98], Pinteraction = .99). Major bleeding was similar with ticagrelor vs clopidogrel among patients with (25.7% vs 25.5%, HR 1.02 [0.90-1.15]) and without (7.3% vs 6.4%, HR 1.14 [0.98-1.33], Pinteraction = .24) extensive CAD. CONCLUSIONS Patients with extensive CAD have higher rates of recurrent cardiovascular events and bleeding. Ticagrelor reduced ischemic events to a similar extent both in patients with and without extensive CAD, with bleeding rates similar to clopidogrel.

Nucleolar localization of the Werner syndrome protein in human cells

Werner Syndrome (WS) is a human genetic disorder with many features of premature aging. The gene defective in WS (WRN) has been cloned and encodes a protein homologous to several helicases, including Escherichia coli RecQ, the human Bloom syndrome protein (BLM), and Saccharomyces cerevisiae Sgs1p. To better define the function of WRN protein we have determined its subcellular localization. Indirect immunofluorescence using polyclonal anti-human WRN shows a predominant nucleolar localization. Studies of WRN mutant cells lines confirmed the specificity of antibody recognition. No difference was seen in the subcellular localization of the WRN protein in a variety of normal and transformed human cell lines, including both carcinomas and sarcomas. The nucleolar localization of human WRN protein was supported by the finding that upon biochemical subcellular fractionation, WRN protein is present in an increased concentration in a subnuclear fraction enriched for nucleolar proteins. We have also determined the subcellular localization of the mouse WRN homologue (mWRN). In contrast to human WRN protein, mWRN protein is present diffusely throughout the nucleus. Understanding the function of WRN in these organisms of vastly differing lifespan may yield new insights into the mechanisms of lifespan determination.

Developmental abnormalities and age-related neurodegeneration in a mouse model of Down syndrome

To study the pathogenesis of central nervous system abnormalities in Down syndrome (DS), we have analyzed a new genetic model of DS, the partial trisomy 16 (Ts65Dn) mouse. Ts65Dn mice have an extra copy of the distal aspect of mouse chromosome 16, a segment homologous to human chromosome 21 that contains much of the genetic material responsible for the DS phenotype. Ts65Dn mice show developmental delay during the postnatal period as well as abnormal behaviors in both young and adult animals that may be analogous to mental retardation. Though the Ts65Dn brain is normal on gross examination, there is age-related degeneration of septohippocampal cholinergic neurons and astrocytic hypertrophy, markers of the Alzheimer disease pathology that is present in elderly DS individuals. These findings suggest that Ts65Dn mice may be used to study certain developmental and degenerative abnormalities in the DS brain.

Multiple genetic loci within 11p15 defined by Beckwith-Wiedemann syndrome rearrangement breakpoints and subchromosomal transferable fragments.

Beckwith-Wiedemann syndrome (BWS) involves fetal overgrowth and predisposition to a wide variety of embryonal tumors of childhood. We have previously found that BWS is genetically linked to 11p15 and that this same band shows loss of heterozygosity in the types of tumors to which children with BWS are susceptible. However, 11p15 contains > 20 megabases, and therefore, the BWS and tumor suppressor genes could be distinct. To determine the precise physical relationship between these loci, we isolated yeast artificial chromosomes, and cosmid libraries from them, within the region of loss of heterozygosity in embryonal tumors. Five germ-line balanced chromosomal rearrangement breakpoint sites from BWS patients, as well as a balanced chromosomal translocation breakpoint from a rhabdoid tumor, were isolated within a 295- to 320-kb cluster defined by a complete cosmid contig crossing these breakpoints. This breakpoint cluster terminated approximately 100 kb centromeric to the imprinted gene IGF2 and 100 kb telomeric to p57KIP2, an inhibitor of cyclin-dependent kinases, and was located within subchromosomal transferable fragments that suppressed the growth of embryonal tumor cells in genetic complementation experiments. We have identified 11 transcribed sequences in this BWS/tumor suppressor coincident region, one of which corresponded to p57KIP2. However, three additional BWS breakpoints were > 4 megabases centromeric to the other five breakpoints and were excluded from the tumor suppressor region defined by subchromosomal transferable fragments. Thus, multiple genetic loci define BWS and tumor suppression on 11p15.

Microfluidic platforms for the characterization of in meso membrane protein crystallization

Membrane proteins, which reside in the membranes of cells, play a critical role in many important biological processes including cellular signaling, immune response, and material and energy transduction. Because of their key role in maintaining the environment within cells and facilitating intercellular interactions, understanding the function of these proteins is of tremendous medical and biochemical significance. Indeed, the malfunction of membrane proteins has been linked to numerous diseases including diabetes, cirrhosis of the liver, cystic fibrosis, cancer, Alzheimer's disease, hypertension, epilepsy, cataracts, tubulopathy, leukodystrophy, Leigh syndrome, anemia, sensorineural deafness, and hypertrophic cardiomyopathy.1-3 However, the structure of many of these proteins and the changes in their structure that lead to disease-related malfunctions are not well understood. Additionally, at least 60% of the pharmaceuticals currently available are thought to target membrane proteins, despite the fact that their exact mode of operation is not known.4-6 Developing a detailed understanding of the function of a protein is achieved by coupling biochemical experiments with knowledge of the structure of the protein. Currently the most common method for obtaining three-dimensional structure information is X-ray crystallography. However, no a priori methods are currently available to predict crystallization conditions for a given protein.7-14 This limitation is currently overcome by screening a large number of possible combinations of precipitants, buffer, salt, and pH conditions to identify conditions that are conducive to crystal nucleation and growth.7,9,11,15-24 Unfortunately, these screening efforts are often limited by difficulties associated with quantity and purity of available protein samples. While the two most significant bottlenecks for protein structure determination in general are the (i) obtaining sufficient quantities of high quality protein samples and (ii) growing high quality protein crystals that are suitable for X-ray structure determination,7,20,21,23,25-47 membrane proteins present additional challenges. For crystallization it is necessary to extract the membrane proteins from the cellular membrane. However, this process often leads to denaturation. In fact, membrane proteins have proven to be so difficult to crystallize that of the more than 66,000 structures deposited in the Protein Data Bank,48 less than 1% are for membrane proteins, with even fewer present at high resolution (< 2Å)4,6,49 and only a handful are human membrane proteins.49 A variety of strategies including detergent solubilization50-53 and the use of artificial membrane-like environments have been developed to circumvent this challenge.43,53-55 In recent years, the use of a lipidic mesophase as a medium for crystallizing membrane proteins has been demonstrated to increase success for a wide range of membrane proteins, including human receptor proteins.54,56-62 This in meso method for membrane protein crystallization, however, is still by no means routine due to challenges related to sample preparation at sub-microliter volumes and to crystal harvesting and X-ray data collection. This dissertation presents various aspects of the development of a microfluidic platform to enable high throughput in meso membrane protein crystallization at a level beyond the capabilities of current technologies. Microfluidic platforms for protein crystallization and other lab-on-a-chip applications have been well demonstrated.9,63-66 These integrated chips provide fine control over transport phenomena and the ability to perform high throughput analyses via highly integrated fluid networks. However, the development of microfluidic platforms for in meso protein crystallization required the development of strategies to cope with extremely viscous and non-Newtonian fluids. A theoretical treatment of highly viscous fluids in microfluidic devices is presented in Chapter 3, followed by the application of these strategies for the development of a microfluidic mixer capable of preparing a mesophase sample for in meso crystallization at a scale of less than 20 nL in Chapter 4. This approach was validated with the successful on chip in meso crystallization of the membrane protein bacteriorhodopsin. In summary, this is the first report of a microfluidic platform capable of performing in meso crystallization on-chip, representing a 1000x reduction in the scale at which mesophase trials can be prepared. Once protein crystals have formed, they are typically harvested from the droplet they were grown in and mounted for crystallographic analysis. Despite the high throughput automation present in nearly all other aspects of protein structure determination, the harvesting and mounting of crystals is still largely a manual process. Furthermore, during mounting the fragile protein crystals can potentially be damaged, both from physical and environmental shock. To circumvent these challenges an X-ray transparent microfluidic device architecture was developed to couple the benefits of scale, integration, and precise fluid control with the ability to perform in situ X-ray analysis (Chapter 5). This approach was validated successfully by crystallization and subsequent on-chip analysis of the soluble proteins lysozyme, thaumatin, and ribonuclease A and will be extended to microfluidic platforms for in meso membrane protein crystallization. The ability to perform in situ X-ray analysis was shown to provide extremely high quality diffraction data, in part as a result of not being affected by damage due to physical handling of the crystals. As part of the work described in this thesis, a variety of data collection strategies for in situ data analysis were also tested, including merging of small slices of data from a large number of crystals grown on a single chip, to allow for diffraction analysis at biologically relevant temperatures. While such strategies have been applied previously,57,59,61,67 they are potentially challenging when applied via traditional methods due to the need to grow and then mount a large number of crystals with minimal crystal-to-crystal variability. The integrated nature of microfluidic platforms easily enables the generation of a large number of reproducible crystallization trials. This, coupled with in situ analysis capabilities has the potential of being able to acquire high resolution structural data of proteins at biologically relevant conditions for which only small crystals, or crystals which are adversely affected by standard cryocooling techniques, could be obtained (Chapters 5 and 6). While the main focus of protein crystallography is to obtain three-dimensional protein structures, the results of typical experiments provide only a static picture of the protein. The use of polychromatic or Laue X-ray diffraction methods enables the collection of time resolved structural information. These experiments are very sensitive to crystal quality, however, and often suffer from severe radiation damage due to the intense polychromatic X-ray beams. Here, as before, the ability to perform in situ X-ray analysis on many small protein crystals within a microfluidic crystallization platform has the potential to overcome these challenges. An automated method for collecting a "single-shot" of data from a large number of crystals was developed in collaboration with the BioCARS team at the Advanced Photon Source at Argonne National Laboratory (Chapter 6). The work described in this thesis shows that, even more so than for traditional structure determination efforts, the ability to grow and analyze a large number of high quality crystals is critical to enable time resolved structural studies of novel proteins. In addition to enabling X-ray crystallography experiments, the development of X-ray transparent microfluidic platforms also has tremendous potential to answer other scientific questions, such as unraveling the mechanism of in meso crystallization. For instance, the lipidic mesophases utilized during in meso membrane protein crystallization can be characterized by small angle X-ray diffraction analysis. Coupling in situ analysis with microfluidic platforms capable of preparing these difficult mesophase samples at very small volumes has tremendous potential to enable the high throughput analysis of these systems on a scale that is not reasonably achievable using conventional sample preparation strategies (Chapter 7). In collaboration with the LS-CAT team at the Advanced Photon Source, an experimental station for small angle X-ray analysis coupled with the high quality visualization capabilities needed to target specific microfluidic samples on a highly integrated chip is under development. Characterizing the phase behavior of these mesophase systems and the effects of various additives present in crystallization trials is key for developing an understanding of how in meso crystallization occurs. A long term goal of these studies is to enable the rational design of in meso crystallization experiments so as to avoid or limit the need for high throughput screening efforts. In summary, this thesis describes the development of microfluidic platforms for protein crystallization with in situ analysis capabilities. Coupling the ability to perform in situ analysis with the small scale, fine control, and the high throughput nature of microfluidic platforms has tremendous potential to enable a new generation of crystallographic studies and facilitate the structure determination of important biological targets. The development of platforms for in meso membrane protein crystallization is particularly significant because they enable the preparation of highly viscous mixtures at a previously unachievable scale. Work in these areas is ongoing and has tremendous potential to improve not only current the methods of protein crystallization and crystallography, but also to enhance our knowledge of the structure and function of proteins which could have a significant scientific and medical impact on society as a whole. The microfluidic technology described in this thesis has the potential to significantly advance our understanding of the structure and function of membrane proteins, thereby aiding the elucidation of human biology, the development of pharmaceuticals with fewer side effects for a wide range of diseases. References (1) Quick, M.; Javitch, J. A. P Natl Acad Sci USA 2007, 104, 3603. (2) Trubetskoy, V. S.; Burke, T. J. Am Lab 2005, 37, 19. (3) Pecina, P.; Houstkova, H.; Hansikova, H.; Zeman, J.; Houstek, J. Physiol Res 2004, 53, S213. (4) Arinaminpathy, Y.; Khurana, E.; Engelman, D. M.; Gerstein, M. B. Drug Discovery Today 2009, 14, 1130. (5) Overington, J. P.; Al-Lazikani, B.; Hopkins, A. L. Nat Rev Drug Discov 2006, 5, 993. (6) Dauter, Z.; Lamzin, V. S.; Wilson, K. S. Current Opinion in Structural Biology 1997, 7, 681. (7) Hansen, C.; Quake, S. R. Current Opinion in Structural Biology 2003, 13, 538. (8) Govada, L.; Carpenter, L.; da Fonseca, P. C. A.; Helliwell, J. R.; Rizkallah, P.; Flashman, E.; Chayen, N. E.; Redwood, C.; Squire, J. M. J Mol Biol 2008, 378, 387. (9) Hansen, C. L.; Skordalakes, E.; Berger, J. M.; Quake, S. R. P Natl Acad Sci USA 2002, 99, 16531. (10) Leng, J.; Salmon, J.-B. Lab Chip 2009, 9, 24. (11) Zheng, B.; Gerdts, C. J.; Ismagilov, R. F. Current Opinion in Structural Biology 2005, 15, 548. (12) Lorber, B.; Delucas, L. J.; Bishop, J. B. J Cryst Growth 1991, 110, 103. (13) Talreja, S.; Perry, S. L.; Guha, S.; Bhamidi, V.; Zukoski, C. F.; Kenis, P. J. A. The Journal of Physical Chemistry B 2010, 114, 4432. (14) Chayen, N. E. Current Opinion in Structural Biology 2004, 14, 577. (15) He, G. W.; Bhamidi, V.; Tan, R. B. H.; Kenis, P. J. A.; Zukoski, C. F. Cryst Growth Des 2006, 6, 1175. (16) Zheng, B.; Tice, J. D.; Roach, L. S.; Ismagilov, R. F. Angew Chem Int Edit 2004, 43, 2508. (17) Li, L.; Mustafi, D.; Fu, Q.; Tereshko, V.; Chen, D. L. L.; Tice, J. D.; Ismagilov, R. F. P Natl Acad Sci USA 2006, 103, 19243. (18) Song, H.; Chen, D. L.; Ismagilov, R. F. Angew Chem Int Edit 2006, 45, 7336. (19) van der Woerd, M.; Ferree, D.; Pusey, M. Journal of Structural Biology 2003, 142, 180. (20) Ng, J. D.; Gavira, J. A.; Garcia-Ruiz, J. M. Journal of Structural Biology 2003, 142, 218. (21) Talreja, S.; Kenis, P. J. A.; Zukoski, C. F. Langmuir 2007, 23, 4516. (22) Hansen, C. L.; Quake, S. R.; Berger, J. M. US, 2007. (23) Newman, J.; Fazio, V. J.; Lawson, B.; Peat, T. S. Cryst Growth Des 2010, 10, 2785. (24) Newman, J.; Xu, J.; Willis, M. C. Acta Crystallographica Section D 2007, 63, 826. (25) Collingsworth, P. D.; Bray, T. L.; Christopher, G. K. J Cryst Growth 2000, 219, 283. (26) Durbin, S. D.; Feher, G. Annu Rev Phys Chem 1996, 47, 171. (27) Talreja, S.; Kim, D. Y.; Mirarefi, A. Y.; Zukoski, C. F.; Kenis, P. J. A. J Appl Crystallogr 2005, 38, 988. (28) Yoshizaki, I.; Nakamura, H.; Sato, T.; Igarashi, N.; Komatsu, H.; Yoda, S. J Cryst Growth 2002, 237, 295. (29) Anderson, M. J.; Hansen, C. L.; Quake, S. R. P Natl Acad Sci USA 2006, 103, 16746. (30) Hansen, C. L.; Sommer, M. O. A.; Quake, S. R. P Natl Acad Sci USA 2004, 101, 14431. (31) Lounaci, M.; Rigolet, P.; Abraham, C.; Le Berre, M.; Chen, Y. Microelectron Eng 2007, 84, 1758. (32) Zheng, B.; Roach, L. S.; Ismagilov, R. F. J Am Chem Soc 2003, 125, 11170. (33) Zhou, X.; Lau, L.; Lam, W. W. L.; Au, S. W. N.; Zheng, B. Anal. Chem. 2007. (34) Cherezov, V.; Caffrey, M. J Appl Crystallogr 2003, 36, 1372. (35) Qutub, Y.; Reviakine, I.; Maxwell, C.; Navarro, J.; Landau, E. M.; Vekilov, P. G. J Mol Biol 2004, 343, 1243. (36) Rummel, G.; Hardmeyer, A.; Widmer, C.; Chiu, M. L.; Nollert, P.; Locher, K. P.; Pedruzzi, I.; Landau, E. M.; Rosenbusch, J. P. Journal of Structural Biology 1998, 121, 82. (37) Gavira, J. A.; Toh, D.; Lopez-Jaramillo, J.; Garcia-Ruiz, J. M.; Ng, J. D. Acta Crystallogr D 2002, 58, 1147. (38) Stevens, R. C. Current Opinion in Structural Biology 2000, 10, 558. (39) Baker, M. Nat Methods 2010, 7, 429. (40) McPherson, A. In Current Topics in Membranes, Volume 63; Volume 63 ed.; DeLucas, L., Ed.; Academic Press: 2009, p 5. (41) Gabrielsen, M.; Gardiner, A. T.; Fromme, P.; Cogdell, R. J. In Current Topics in Membranes, Volume 63; Volume 63 ed.; DeLucas, L., Ed.; Academic Press: 2009, p 127. (42) Page, R. In Methods in Molecular Biology: Structural Proteomics - High Throughput Methods; Kobe, B., Guss, M., Huber, T., Eds.; Humana Press: Totowa, NJ, 2008; Vol. 426, p 345. (43) Caffrey, M. Ann Rev Biophys 2009, 38, 29. (44) Doerr, A. Nat Methods 2006, 3, 244. (45) Brostromer, E.; Nan, J.; Li, L.-F.; Su, X.-D. Biochemical and Biophysical Research Communications 2009, 386, 634. (46) Li, G.; Chen, Q.; Li, J.; Hu, X.; Zhao, J. Anal Chem 2010, 82, 4362. (47) Jia, Y.; Liu, X.-Y. The Journal of Physical Chemistry B 2006, 110, 6949. (48) RCSB Protein Data Bank. http://www.rcsb.org/ (July 11, 2010). (49) Membrane Proteins of Known 3D Structure. http://blanco.biomol.uci.edu/Membrane_Proteins_xtal.html (July 11, 2010). (50) Michel, H. Trends Biochem Sci 1983, 8, 56. (51) Rosenbusch, J. P. Journal of Structural Biology 1990, 104, 134. (52) Garavito, R. M.; Picot, D. Methods 1990, 1, 57. (53) Kulkarni, C. V. 2010; Vol. 12, p 237. (54) Landau, E. M.; Rosenbusch, J. P. P Natl Acad Sci USA 1996, 93, 14532. (55) Pebay-Peyroula, E.; Rummel, G.; Rosenbusch, J. P.; Landau, E. M. Science 1997, 277, 1676. (56) Cherezov, V.; Liu, W.; Derrick, J. P.; Luan, B.; Aksimentiev, A.; Katritch, V.; Caffrey, M. Proteins: Structure, Function, and Bioinformatics 2008, 71, 24. (57) Cherezov, V.; Rosenbaum, D. M.; Hanson, M. A.; Rasmussen, S. G. F.; Thian, F. S.; Kobilka, T. S.; Choi, H. J.; Kuhn, P.; Weis, W. I.; Kobilka, B. K.; Stevens, R. C. Science 2007, 318, 1258. (58) Cherezov, V.; Yamashita, E.; Liu, W.; Zhalnina, M.; Cramer, W. A.; Caffrey, M. J Mol Biol 2006, 364, 716. (59) Jaakola, V. P.; Griffith, M. T.; Hanson, M. A.; Cherezov, V.; Chien, E. Y. T.; Lane, J. R.; IJzerman, A. P.; Stevens, R. C. Science 2008, 322, 1211. (60) Rosenbaum, D. M.; Cherezov, V.; Hanson, M. A.; Rasmussen, S. G. F.; Thian, F. S.; Kobilka, T. S.; Choi, H. J.; Yao, X. J.; Weis, W. I.; Stevens, R. C.; Kobilka, B. K. Science 2007, 318, 1266. (61) Wacker, D.; Fenalti, G.; Brown, M. A.; Katritch, V.; Abagyan, R.; Cherezov, V.; Stevens, R. C. J Am Chem Soc 2010, 132, 11443. (62) Höfer, N.; Aragão, D.; Caffrey, M. Biophys J 2010, 99, L23. (63) Li, L.; Ismagilov, R. F. Ann Rev Biophys 2010. (64) Pal, R.; Yang, M.; Lin, R.; Johnson, B. N.; Srivastava, N.; Razzacki, S. Z.; Chomistek, K. J.; Heldsinger, D. C.; Haque, R. M.; Ugaz, V. M.; Thwar, P. K.; Chen, Z.; Alfano, K.; Yim, M. B.; Krishnan, M.; Fuller, A. O.; Larson, R. G.; Burke, D. T.; Burns, M. A. Lab Chip 2005, 5, 1024. (65) Jayashree, R. S.; Gancs, L.; Choban, E. R.; Primak, A.; Natarajan, D.; Markoski, L. J.; Kenis, P. J. A. J Am Chem Soc 2005, 127, 16758. (66) Wootton, R. C. R.; deMello, A. J. Chem Commun 2004, 266. (67) McPherson, A. J Appl Crystallogr 2000, 33, 397.

Evaluación del desempeño de pruebas diagnósticas de tuberculosis en pacientes VIH positivo en dos hospitales públicos de Bogotá

La tuberculosis TB es una de las principales causas de muerte en el mundo en individuos con infección por VIH. En Colombia esta coinfección soporta una carga importante en la población general convirtiéndose en un problema de salud pública. En estos pacientes las pruebas diagnósticas tienen sensibilidad inferior y la enfermedad evoluciona con mayor frecuencia hacia formas diseminadas y rápidamente progresivas y su diagnóstico oportuno representa un reto en Salud. El objetivo de este proyecto es evaluar el desempeño de las pruebas diagnósticas convencionales y moleculares, para la detección de TB latente y activa pacientes con VIH, en dos hospitales públicos de Bogotá. Para TB latente se evaluó la concordancia entre las pruebas QuantiFERON-TB (QTF) y Tuberculina (PPD), sugiriendo superioridad del QTF sobre la PPD. Se evaluaron tres pruebas diagnósticas por su sensibilidad y especificidad, baciloscopia (BK), GenoType®MTBDR plus (Genotype) y PCR IS6110 teniendo como estándar de oro el cultivo. Los resultados de sensibilidad (S) y especificidad (E) de cada prueba con una prevalencia del 19,4 % de TB pulmonar y extrapulmonar en los pacientes que participaron del estudio fue: BK S: 64% E: 99,1%; Genotype S: 77,8% E: 94,5%; PCRIS6110 S: 73% E: 95,5%, de la misma forma se determinaron los valores predictivos positivos y negativos (VPP y VPN) BK: 88,9% y 94,8%, Genotype S: 77,8% E: 94,5%; PCRIS6110 S: 90% y 95,7%. Se concluyó bajo análisis de curva ROC que las pruebas muestran un rendimiento diagnóstico similar por separado en el diagnóstico de TB en pacientes con VIH, aumentando su rendimiento diagnostico cuando se combinan