974 resultados para Metabolic disorder predictor
Resumo:
Activation dynamics of hippocampal subregions during spatial learning and their interplay with neocortical regions is an important dimension in the understanding of hippocampal function. Using the (14C)-2-deoxyglucose autoradiographic method, we have characterized the metabolic changes occurring in hippocampal subregions in mice while learning an eight-arm radial maze task. Autoradiogram densitometry revealed a heterogeneous and evolving pattern of enhanced metabolic activity throughout the hippocampus during the training period and on recall. In the early stages of training, activity was enhanced in the CA1 area from the intermediate portion to the posterior end as well as in the CA3 area within the intermediate portion of the hippocampus. At later stages, CA1 and CA3 activations spread over the entire longitudinal axis, while dentate gyrus (DG) activation occurred from the anterior to the intermediate zone. Activation of the retrosplenial cortex but not the amygdala was also observed during the learning process. On recall, only DG activation was observed in the same anterior part of the hippocampus. These results suggest the existence of a functional segmentation of the hippocampus, each subregion being dynamically but also differentially recruited along the acquisition, consolidation, and retrieval process in parallel with some neocortical sites.
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Major depressive disorder (MDD) is a highly prevalent disorder with substantial heritability. Heritability has been shown to be substantial and higher in the variant of MDD characterized by recurrent episodes of depression. Genetic studies have thus far failed to identify clear and consistent evidence of genetic risk factors for MDD. We conducted a genome-wide association study (GWAS) in two independent datasets. The first GWAS was performed on 1022 recurrent MDD patients and 1000 controls genotyped on the Illumina 550 platform. The second was conducted on 492 recurrent MDD patients and 1052 controls selected from a population-based collection, genotyped on the Affymetrix 5.0 platform. Neither GWAS identified any SNP that achieved GWAS significance. We obtained imputed genotypes at the Illumina loci for the individuals genotyped on the Affymetrix platform, and performed a meta-analysis of the two GWASs for this common set of approximately half a million SNPs. The meta-analysis did not yield genome-wide significant results either. The results from our study suggest that SNPs with substantial odds ratio are unlikely to exist for MDD, at least in our datasets and among the relatively common SNPs genotyped or tagged by the half-million-loci arrays. Meta-analysis of larger datasets is warranted to identify SNPs with smaller effects or with rarer allele frequencies that contribute to the risk of MDD.
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Background.Schizo-affective disorder has not been studied to any significant extent using functional imaging. The aim of this study was to examine patterns of brain activation and deactivation in patients meeting strict diagnostic criteria for the disorder. METHOD: Thirty-two patients meeting research diagnostic criteria (RDC) for schizo-affective disorder (16 schizomanic and 16 schizodepressive) and 32 matched healthy controls underwent functional magnetic resonance imaging (fMRI) during performance of the n-back task. Linear models were used to obtain maps of activations and deactivations in the groups. RESULTS: Controls showed activation in a network of frontal and other areas and also deactivation in the medial frontal cortex, the precuneus and the parietal cortex. Schizo-affective patients activated significantly less in prefrontal, parietal and temporal regions than the controls, and also showed failure of deactivation in the medial frontal cortex. When task performance was controlled for, the reduced activation in the dorsolateral prefrontal cortex (DLPFC) and the failure of deactivation of the medial frontal cortex remained significant. CONCLUSIONS: Schizo-affective disorder shows a similar pattern of reduced frontal activation to schizophrenia. The disorder is also characterized by failure of deactivation suggestive of default mode network dysfunction.
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OBJECTIVES: In this study, we investigated the structural plasticity of the contralesional motor network in ischemic stroke patients using diffusion magnetic resonance imaging (MRI) and explored a model that combines a MRI-based metric of contralesional network integrity and clinical data to predict functional outcome at 6 months after stroke. METHODS: MRI and clinical examinations were performed in 12 patients in the acute phase, at 1 and 6 months after stroke. Twelve age- and gender-matched controls underwent 2 MRIs 1 month apart. Structural remodeling after stroke was assessed using diffusion MRI with an automated measurement of generalized fractional anisotropy (GFA), which was calculated along connections between contralesional cortical motor areas. The predictive model of poststroke functional outcome was computed using a linear regression of acute GFA measures and the clinical assessment. RESULTS: GFA changes in the contralesional motor tracts were found in all patients and differed significantly from controls (0.001 ≤ p < 0.05). GFA changes in intrahemispheric and interhemispheric motor tracts correlated with age (p ≤ 0.01); those in intrahemispheric motor tracts correlated strongly with clinical scores and stroke sizes (p ≤ 0.001). GFA measured in the acute phase together with a routine motor score and age were a strong predictor of motor outcome at 6 months (r(2) = 0.96, p = 0.0002). CONCLUSION: These findings represent a proof of principle that contralesional diffusion MRI measures may provide reliable information for personalized rehabilitation planning after ischemic motor stroke. Neurology® 2012;79:39-46.
Resumo:
Background.Schizo-affective disorder has not been studied to any significant extent using functional imaging. The aim of this study was to examine patterns of brain activation and deactivation in patients meeting strict diagnostic criteria for the disorder. METHOD: Thirty-two patients meeting research diagnostic criteria (RDC) for schizo-affective disorder (16 schizomanic and 16 schizodepressive) and 32 matched healthy controls underwent functional magnetic resonance imaging (fMRI) during performance of the n-back task. Linear models were used to obtain maps of activations and deactivations in the groups. RESULTS: Controls showed activation in a network of frontal and other areas and also deactivation in the medial frontal cortex, the precuneus and the parietal cortex. Schizo-affective patients activated significantly less in prefrontal, parietal and temporal regions than the controls, and also showed failure of deactivation in the medial frontal cortex. When task performance was controlled for, the reduced activation in the dorsolateral prefrontal cortex (DLPFC) and the failure of deactivation of the medial frontal cortex remained significant. CONCLUSIONS: Schizo-affective disorder shows a similar pattern of reduced frontal activation to schizophrenia. The disorder is also characterized by failure of deactivation suggestive of default mode network dysfunction.
Resumo:
Background.Schizo-affective disorder has not been studied to any significant extent using functional imaging. The aim of this study was to examine patterns of brain activation and deactivation in patients meeting strict diagnostic criteria for the disorder. METHOD: Thirty-two patients meeting research diagnostic criteria (RDC) for schizo-affective disorder (16 schizomanic and 16 schizodepressive) and 32 matched healthy controls underwent functional magnetic resonance imaging (fMRI) during performance of the n-back task. Linear models were used to obtain maps of activations and deactivations in the groups. RESULTS: Controls showed activation in a network of frontal and other areas and also deactivation in the medial frontal cortex, the precuneus and the parietal cortex. Schizo-affective patients activated significantly less in prefrontal, parietal and temporal regions than the controls, and also showed failure of deactivation in the medial frontal cortex. When task performance was controlled for, the reduced activation in the dorsolateral prefrontal cortex (DLPFC) and the failure of deactivation of the medial frontal cortex remained significant. CONCLUSIONS: Schizo-affective disorder shows a similar pattern of reduced frontal activation to schizophrenia. The disorder is also characterized by failure of deactivation suggestive of default mode network dysfunction.
Resumo:
PURPOSE: Acute limb ischemia after thrombosis of a popliteal aneurysm is a distinct and limb-threatening entity. Preoperative intra-arterial thrombolysis may improve the outcome in this challenging situation. This study retrospectively analyzed a consecutive series of patients treated with preoperative thrombolysis and subsequent revascularization. METHODS: Thirteen patients with acute limb ischemia caused by thrombosis of a popliteal aneurysm underwent catheter-directed intra-arterial thrombolysis with urokinase and subsequent vascular reconstruction. The angiographic and clinical outcome was analyzed and compared with that in the literature. RESULTS: Complete aneurysm thrombosis with absence of runoff was documented in 12 cases. Thrombolysis restored perfusion with patency of the popliteal artery and a one- or two-vessel runoff in 77% of cases (10/13). Early cumulative graft patency and limb salvage rates were 68% and 83%, respectively, with an ankle/brachial index of 0.8 +/- 0.2. Lytic failure followed by attempts at bypass grafting was present in three patients (23%) and resulted in above-knee amputation. Severe rhabdomyolysis and fatal pulmonary embolism were responsible for a 15% early mortality rate. CONCLUSION: Preoperative thrombolysis followed by bypass grafting is a valid treatment option for patients who can withstand an additional period of ischemia that does not require immediate revascularization and intraoperative lysis. Lytic failure identifies patients with a highly compromised runoff who are probably best treated by means of subsequent amputation, without any attempts at bypass grafting.
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Asparagine N-Glycosylation is one of the most important forms of protein post-translational modification in eukaryotes. This metabolic pathway can be subdivided into two parts: an upstream sub-pathway required for achieving proper folding for most of the proteins synthesized in the secretory pathway, and a downstream sub-pathway required to give variability to trans-membrane proteins, and involved in adaptation to the environment and innate immunity. Here we analyze the nucleotide variability of the genes of this pathway in human populations, identifying which genes show greater population differentiation and which genes show signatures of recent positive selection. We also compare how these signals are distributed between the upstream and the downstream parts of the pathway, with the aim of exploring how forces of population differentiation and positive selection vary among genes involved in the same metabolic pathway but subject to different functional constraints. Our results show that genes in the downstream part of the pathway are more likely to show a signature of population differentiation, while events of positive selection are equally distributed among the two parts of the pathway. Moreover, events of positive selection are frequent on genes that are known to be at bifurcation points, and that are identified as being in key position by a network-level analysis such as MGAT3 and GCS1. These findings indicate that the upstream part of the Asparagine N-Glycosylation pathway has lower diversity among populations, while the downstream part is freer to tolerate diversity among populations. Moreover, the distribution of signatures of population differentiation and positive selection can change between parts of a pathway, especially between parts that are exposed to different functional constraints. Our results support the hypothesis that genes involved in constitutive processes can be expected to show lower population differentiation, while genes involved in traits related to the environment should show higher variability. Taken together, this work broadens our knowledge on how events of population differentiation and of positive selection are distributed among different parts of a metabolic pathway.
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We report Monte Carlo results for a nonequilibrium Ising-like model in two and three dimensions. Nearest-neighbor interactions J change sign randomly with time due to competing kinetics. There follows a fast and random, i.e., spin-configuration-independent diffusion of Js, of the kind that takes place in dilute metallic alloys when magnetic ions diffuse. The system exhibits steady states of the ferromagnetic (antiferromagnetic) type when the probability p that J>0 is large (small) enough. No counterpart to the freezing phenomena found in quenched spin glasses occurs. We compare our results with existing mean-field and exact ones, and obtain information about critical behavior.
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BACKGROUND: The diagnostic and clinical overlap between schizophrenia and schizoaffective disorder is an important nosological issue in psychiatry that is yet to be resolved. The aim of this study was to compare the clinical and functional characteristics of an epidemiological treated cohort of first episode patients with an 18-month discharge diagnosis of schizophrenia (FES) or schizoaffective disorder (FESA). METHODS: This study was part of the larger First Episode Psychosis Outcome Study (FEPOS) which involved a medical file audit study of all 786 patients treated at the Early Psychosis Prevention and Intervention Centre between 1998 and 2000. Of this cohort, 283 patients had an 18-month discharge diagnosis of FES and 64 had a diagnosis of FESA. DSM-IV diagnoses and clinical and functional ratings were derived and validated by two consultant psychiatrists. RESULTS: Compared to FES patients, those with FESA were significantly more likely to have a later age of onset (p=.004), longer prodrome (p=.020), and a longer duration of untreated psychosis (p<.001). At service entry, FESA patients presented with a higher illness severity (p=.020), largely due to the presence of more severe manic symptoms (p<.001). FESA patients also had a greater number of subsequent inpatient admissions (p=.017), had more severe depressive symptoms (p=.011), and higher levels of functioning at discharge. DISCUSSION: The findings support the notion that these might be considered two discernable disorders; however, further research is required to ascertain the ways and extent to which these disorders are discriminable at presentation and over time.
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Genetic variants influence the risk to develop certain diseases or give rise to differences in drug response. Recent progresses in cost-effective, high-throughput genome-wide techniques, such as microarrays measuring Single Nucleotide Polymorphisms (SNPs), have facilitated genotyping of large clinical and population cohorts. Combining the massive genotypic data with measurements of phenotypic traits allows for the determination of genetic differences that explain, at least in part, the phenotypic variations within a population. So far, models combining the most significant variants can only explain a small fraction of the variance, indicating the limitations of current models. In particular, researchers have only begun to address the possibility of interactions between genotypes and the environment. Elucidating the contributions of such interactions is a difficult task because of the large number of genetic as well as possible environmental factors.In this thesis, I worked on several projects within this context. My first and main project was the identification of possible SNP-environment interactions, where the phenotypes were serum lipid levels of patients from the Swiss HIV Cohort Study (SHCS) treated with antiretroviral therapy. Here the genotypes consisted of a limited set of SNPs in candidate genes relevant for lipid transport and metabolism. The environmental variables were the specific combinations of drugs given to each patient over the treatment period. My work explored bioinformatic and statistical approaches to relate patients' lipid responses to these SNPs, drugs and, importantly, their interactions. The goal of this project was to improve our understanding and to explore the possibility of predicting dyslipidemia, a well-known adverse drug reaction of antiretroviral therapy. Specifically, I quantified how much of the variance in lipid profiles could be explained by the host genetic variants, the administered drugs and SNP-drug interactions and assessed the predictive power of these features on lipid responses. Using cross-validation stratified by patients, we could not validate our hypothesis that models that select a subset of SNP-drug interactions in a principled way have better predictive power than the control models using "random" subsets. Nevertheless, all models tested containing SNP and/or drug terms, exhibited significant predictive power (as compared to a random predictor) and explained a sizable proportion of variance, in the patient stratified cross-validation context. Importantly, the model containing stepwise selected SNP terms showed higher capacity to predict triglyceride levels than a model containing randomly selected SNPs. Dyslipidemia is a complex trait for which many factors remain to be discovered, thus missing from the data, and possibly explaining the limitations of our analysis. In particular, the interactions of drugs with SNPs selected from the set of candidate genes likely have small effect sizes which we were unable to detect in a sample of the present size (<800 patients).In the second part of my thesis, I performed genome-wide association studies within the Cohorte Lausannoise (CoLaus). I have been involved in several international projects to identify SNPs that are associated with various traits, such as serum calcium, body mass index, two-hour glucose levels, as well as metabolic syndrome and its components. These phenotypes are all related to major human health issues, such as cardiovascular disease. I applied statistical methods to detect new variants associated with these phenotypes, contributing to the identification of new genetic loci that may lead to new insights into the genetic basis of these traits. This kind of research will lead to a better understanding of the mechanisms underlying these pathologies, a better evaluation of disease risk, the identification of new therapeutic leads and may ultimately lead to the realization of "personalized" medicine.
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The objective of this work was to evaluate the inclusion of sodium citrate and sodium bicarbonate in the diet of lactating Jersey cows, and its effects on the metabolic attributes, productivity and stability of milk. We evaluated urinary pH, levels of glucose and urea in blood, body weight, body condition score, milk yield, milk stability (ethanol test), and milk physicochemical properties of 17 cows fed diets containing sodium citrate (100 g per cow per day), sodium bicarbonate (40 g per cow per day) or no additives. Assessments were made at the 28th and 44th days. Supply of sodium citrate or bicarbonate has no influence on the metabolic attributes, productivity, body weight, and body condition score of the cows, neither on the composition and stability of milk.
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In recent years, considerable research has focused on the biological effect of endocrine-disrupting chemicals. Bisphenol A (BPA) has been implicated as an endocrine-disrupting chemical (EDC) due to its ability to mimic the action of endogenous estrogenic hormones. The aim of this study was to assess the effect of perinatal exposure to BPA on cerebral structural development and metabolism after birth. BPA (1mg/l) was administered in the drinking water of pregnant dams from day 6 of gestation until pup weaning. At postnatal day 20, in vivo metabolite concentrations in the rat pup hippocampus were measured using high field proton magnetic resonance spectroscopy. Further, brain was assessed histologically for growth, gross morphology, glial and neuronal development and extent of myelination. Localized proton magnetic resonance spectroscopy ((1)H MRS) showed in the BPA-exposed rat a significant increase in glutamate concentration in the hippocampus as well as in the Glu/Asp ratio. Interestingly these two metabolites are metabolically linked together in the malate-aspartate metabolic shuttle. Quantitative histological analysis revealed that the density of NeuN-positive neurons in the hippocampus was decreased in the BPA-treated offspring when compared to controls. Conversely, the density of GFAP-positive astrocytes in the cingulum was increased in BPA-treated offspring. In conclusion, exposure to low-dose BPA during gestation and lactation leads to significant changes in the Glu/Asp ratio in the hippocampus, which may reflect impaired mitochondrial function and also result in neuronal and glial developmental alterations.