78 resultados para Level-Set Method
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The trabecular bone score (TBS) is a gray-level textural metric that can be extracted from the two-dimensional lumbar spine dual-energy X-ray absorptiometry (DXA) image. TBS is related to bone microarchitecture and provides skeletal information that is not captured from the standard bone mineral density (BMD) measurement. Based on experimental variograms of the projected DXA image, TBS has the potential to discern differences between DXA scans that show similar BMD measurements. An elevated TBS value correlates with better skeletal microstructure; a low TBS value correlates with weaker skeletal microstructure. Lumbar spine TBS has been evaluated in cross-sectional and longitudinal studies. The following conclusions are based upon publications reviewed in this article: 1) TBS gives lower values in postmenopausal women and in men with previous fragility fractures than their nonfractured counterparts; 2) TBS is complementary to data available by lumbar spine DXA measurements; 3) TBS results are lower in women who have sustained a fragility fracture but in whom DXA does not indicate osteoporosis or even osteopenia; 4) TBS predicts fracture risk as well as lumbar spine BMD measurements in postmenopausal women; 5) efficacious therapies for osteoporosis differ in the extent to which they influence the TBS; 6) TBS is associated with fracture risk in individuals with conditions related to reduced bone mass or bone quality. Based on these data, lumbar spine TBS holds promise as an emerging technology that could well become a valuable clinical tool in the diagnosis of osteoporosis and in fracture risk assessment.
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BACKGROUND: Genes involved in arbuscular mycorrhizal (AM) symbiosis have been identified primarily by mutant screens, followed by identification of the mutated genes (forward genetics). In addition, a number of AM-related genes has been identified by their AM-related expression patterns, and their function has subsequently been elucidated by knock-down or knock-out approaches (reverse genetics). However, genes that are members of functionally redundant gene families, or genes that have a vital function and therefore result in lethal mutant phenotypes, are difficult to identify. If such genes are constitutively expressed and therefore escape differential expression analyses, they remain elusive. The goal of this study was to systematically search for AM-related genes with a bioinformatics strategy that is insensitive to these problems. The central element of our approach is based on the fact that many AM-related genes are conserved only among AM-competent species. RESULTS: Our approach involves genome-wide comparisons at the proteome level of AM-competent host species with non-mycorrhizal species. Using a clustering method we first established orthologous/paralogous relationships and subsequently identified protein clusters that contain members only of the AM-competent species. Proteins of these clusters were then analyzed in an extended set of 16 plant species and ranked based on their relatedness among AM-competent monocot and dicot species, relative to non-mycorrhizal species. In addition, we combined the information on the protein-coding sequence with gene expression data and with promoter analysis. As a result we present a list of yet uncharacterized proteins that show a strongly AM-related pattern of sequence conservation, indicating that the respective genes may have been under selection for a function in AM. Among the top candidates are three genes that encode a small family of similar receptor-like kinases that are related to the S-locus receptor kinases involved in sporophytic self-incompatibility. CONCLUSIONS: We present a new systematic strategy of gene discovery based on conservation of the protein-coding sequence that complements classical forward and reverse genetics. This strategy can be applied to diverse other biological phenomena if species with established genome sequences fall into distinguished groups that differ in a defined functional trait of interest.
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The human brain displays heterogeneous organization in both structure and function. Here we develop a method to characterize brain regions and networks in terms of information-theoretic measures. We look at how these measures scale when larger spatial regions as well as larger connectome sub-networks are considered. This framework is applied to human brain fMRI recordings of resting-state activity and DSI-inferred structural connectivity. We find that strong functional coupling across large spatial distances distinguishes functional hubs from unimodal low-level areas, and that this long-range functional coupling correlates with structural long-range efficiency on the connectome. We also find a set of connectome regions that are both internally integrated and coupled to the rest of the brain, and which resemble previously reported resting-state networks. Finally, we argue that information-theoretic measures are useful for characterizing the functional organization of the brain at multiple scales.
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The aim was to propose a strategy for finding reasonable compromises between image noise and dose as a function of patient weight. Weighted CT dose index (CTDI(w)) was measured on a multidetector-row CT unit using CTDI test objects of 16, 24 and 32 cm in diameter at 80, 100, 120 and 140 kV. These test objects were then scanned in helical mode using a wide range of tube currents and voltages with a reconstructed slice thickness of 5 mm. For each set of acquisition parameter image noise was measured and the Rose model observer was used to test two strategies for proposing a reasonable compromise between dose and low-contrast detection performance: (1) the use of a unique noise level for all test object diameters, and (2) the use of a unique dose efficacy level defined as the noise reduction per unit dose. Published data were used to define four weight classes and an acquisition protocol was proposed for each class. The protocols have been applied in clinical routine for more than one year. CTDI(vol) values of 6.7, 9.4, 15.9 and 24.5 mGy were proposed for the following weight classes: 2.5-5, 5-15, 15-30 and 30-50 kg with image noise levels in the range of 10-15 HU. The proposed method allows patient dose and image noise to be controlled in such a way that dose reduction does not impair the detection of low-contrast lesions. The proposed values correspond to high- quality images and can be reduced if only high-contrast organs are assessed.
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An analysis is presented of the diversity and faunal turnover of Jurassic ammonites related to transgressive /regressive events. The data set contained 400 genera and 1548 species belonging to 67 ammonite zones covering the entire Jurassic System. These data were used in the construction of faunal turnover curves and ammonite diversities, that correlate with sea-level fluctuation curves. Twenty-four events of ammonite faunal turnover are analyzed throughout the Jurassic. The most important took place at the Sinemurian-Carixian boundary, latest Carixian-Middle Domerian, Domerian-Toarcian boundary, latest Middle Toarcian-Late Toarcian, Toarcian-Aalenian boundary, latest Aalenian-earliest Bajocian, latest Early Bajocian-earliest Late Bojocian, Early Bathonian-Middle Bathonian boundary, latest Middle Bathonian-earliest Late Bathonian, latest Bathonian-Early Callovian, earliest Early Oxfordian-Middle Oxfordian, earliest Late Oxfordian-latest Oxfordian, latest Early Kimmeridgian, Late Kimmeridgian, middle Early Tithonian and Early Tithonian-Late Tithonian boundary. More than 75 percent of these turnovers correlate with regressive-transgressive cycles in the Exxon, and /or Hallam's sea-level curves. Inmost cases the extinction events coincide with regressive intervals, whereas origination and radiation events are related to transgressive cycles. The turnovers frequently coincide with major or minor discontinuities in the Subbetic basin (Betic Cordillera).
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Geographical body size variation has long interested evolutionary biologists, and a range of mechanisms have been proposed to explain the observed patterns. It is considered to be more puzzling in ectotherms than in endotherms, and integrative approaches are necessary for testing non-exclusive alternative mechanisms. Using lacertid lizards as a model, we adopted an integrative approach, testing different hypotheses for both sexes while incorporating temporal, spatial, and phylogenetic autocorrelation at the individual level. We used data on the Spanish Sand Racer species group from a field survey to disentangle different sources of body size variation through environmental and individual genetic data, while accounting for temporal and spatial autocorrelation. A variation partitioning method was applied to separate independent and shared components of ecology and phylogeny, and estimated their significance. Then, we fed-back our models by controlling for relevant independent components. The pattern was consistent with the geographical Bergmann's cline and the experimental temperature-size rule: adults were larger at lower temperatures (and/or higher elevations). This result was confirmed with additional multi-year independent data-set derived from the literature. Variation partitioning showed no sex differences in phylogenetic inertia but showed sex differences in the independent component of ecology; primarily due to growth differences. Interestingly, only after controlling for independent components did primary productivity also emerge as an important predictor explaining size variation in both sexes. This study highlights the importance of integrating individual-based genetic information, relevant ecological parameters, and temporal and spatial autocorrelation in sex-specific models to detect potentially important hidden effects. Our individual-based approach devoted to extract and control for independent components was useful to reveal hidden effects linked with alternative non-exclusive hypothesis, such as those of primary productivity. Also, including measurement date allowed disentangling and controlling for short-term temporal autocorrelation reflecting sex-specific growth plasticity.
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This paper examines the application of the guidelines for evidence-based treatments in family therapy developed by Sexton and collaborators to a set of treatment models. These guidelines classify the models using criteria that take into account the distinctive features of couple and family treatments. A two-step approach was taken: (1) The quality of each of the studies supporting the treatment models was assessed according to a list of ad hoc core criteria; (2) the level of evidence of each treatment model was determined using the guidelines. To reflect the stages of empirical validation present in the literature, nine models were selected: three models each with high, moderate, and low levels of empirical validation, determined by the number of randomized clinical trials (RCTs). The quality ratings highlighted the strengths and limitations of each of the studies that provided evidence backing the treatment models. The classification by level of evidence indicated that four of the models were level III, "evidence-based" treatments; one was a level II, "evidence-informed treatment with promising preliminary evidence-based results"; and four were level I, "evidence-informed" treatments. Using the guidelines helped identify treatments that are solid in terms of not only the number of RCTs but also the quality of the evidence supporting the efficacy of a given treatment. From a research perspective, this analysis highlighted areas to be addressed before some models can move up to a higher level of evidence. From a clinical perspective, the guidelines can help identify the models whose studies have produced clinically relevant results.
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In this paper, we propose two active learning algorithms for semiautomatic definition of training samples in remote sensing image classification. Based on predefined heuristics, the classifier ranks the unlabeled pixels and automatically chooses those that are considered the most valuable for its improvement. Once the pixels have been selected, the analyst labels them manually and the process is iterated. Starting with a small and nonoptimal training set, the model itself builds the optimal set of samples which minimizes the classification error. We have applied the proposed algorithms to a variety of remote sensing data, including very high resolution and hyperspectral images, using support vector machines. Experimental results confirm the consistency of the methods. The required number of training samples can be reduced to 10% using the methods proposed, reaching the same level of accuracy as larger data sets. A comparison with a state-of-the-art active learning method, margin sampling, is provided, highlighting advantages of the methods proposed. The effect of spatial resolution and separability of the classes on the quality of the selection of pixels is also discussed.
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Aims/hypothesis We assessed systemic and local muscle fuel metabolism during aerobic exercise in patients with type I diabetes at euglycaemia and hyperglycaemia with identical insulin levels.Methods This was a single-blinded randomised crossover study at a university diabetes unit in Switzerland. We studied seven physically active men with type I diabetes (mean +/- SEM age 33.5 +/- 2.4 years, diabetes duration 20.1 +/- 3.6 years, HbA(1c) 6.7 +/- 0.2% and peak oxygen uptake [VO2peak] 50.3 +/- 4.5 ml min(-1) kg(-1)). Men were studied twice while cycling for 120 min at 55 to 60% of VO2peak, with a blood glucose level randomly set either at 5 or 11 mmol/l and identical insulinaemia. The participants were blinded to the glycaemic level; allocation concealment was by opaque, sealed envelopes. Magnetic resonance spectroscopy was used to quantify intramyocellular glycogen and lipids before and after exercise. Indirect calorimetry and measurement of stable isotopes and counter-regulatory hormones complemented the assessment of local and systemic fuel metabolism.Results The contribution of lipid oxidation to overall energy metabolism was higher in euglycaemia than in hyperglycaemia (49.4 +/- 4.8 vs 30.6 +/- 4.2%; p<0.05). Carbohydrate oxidation accounted for 48.2 +/- 4.7 and 66.6 +/- 4.2% of total energy expenditure in euglycaemia and hyperglycaemia, respectively (p<0.05). The level of intramyocellular glycogen before exercise was higher in hyperglycaemia than in euglycaemia (3.4 +/- 0.3 vs 2.7 +/- 0.2 arbitrary units [AU]; p<0.05). Absolute glycogen consumption tended to be higher in hyperglycaemia than in euglycaemia (1.3 +/- 0.3 vs 0.9 +/- 0.1 AU). Cortisol and growth hormone increased more strongly in euglycaemia than in hyperglycaemia (levels at the end of exercise 634 52 vs 501 +/- 32 nmol/l and 15.5 +/- 4.5 vs 7.4 +/- 2.0 ng/ml, respectively; p<0.05).Conclusions/interpretation Substrate oxidation in type I diabetic patients performing aerobic exercise in euglycaemia is similar to that in healthy individuals revealing a shift towards lipid oxidation during exercise. In hyperglycaemia fuel metabolism in these patients is dominated by carbohydrate oxidation. Intramyocellular glycogen was not spared in hyperglycaemia.
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Résumé La protéomique basée sur la spectrométrie de masse est l'étude du proteome l'ensemble des protéines exprimées au sein d'une cellule, d'un tissu ou d'un organisme - par cette technique. Les protéines sont coupées à l'aide d'enzymes en plus petits morceaux -les peptides -, et, séparées par différentes techniques. Les différentes fractions contenant quelques centaines de peptides sont ensuite analysées dans un spectromètre de masse. La masse des peptides est enregistrée et chaque peptide est séquentiellement fragmenté pour en obtenir sa séquence. L'information de masse et séquence est ensuite comparée à une base de données de protéines afin d'identifier la protéine d'origine. Dans une première partie, la thèse décrit le développement de méthodes d'identification. Elle montre l'importance de l'enrichissement de protéines comme moyen d'accès à des protéines de moyenne à faible abondance dans le lait humain. Elle utilise des injections répétées pour augmenter la couverture en protéines et la confiance dans l'identification. L'impacte de nouvelle version de base de données sur la liste des protéines identifiées est aussi démontré. De plus, elle utilise avec succès la spectrométrie de masse comme alternative aux anticorps, pour valider la présence de 34 constructions de protéines pathogéniques du staphylocoque doré exprimées dans une souche de lactocoque. Dans une deuxième partie, la thèse décrit le développement de méthodes de quantification. Elle expose de nouvelles approches de marquage des terminus des protéines aux isotopes stables et décrit la première méthode de marquage des groupements carboxyliques au niveau protéine à l'aide de réactifs composé de carbone 13. De plus, une nouvelle méthode, appelée ANIBAL, marquant tous les groupements amines et carboxyliques au niveau de la protéine, est exposée. Summary Mass spectrometry-based proteomics is the study of the proteome -the set of all expressed proteins in a cell, tissue or organism -using mass spectrometry. Proteins are cut into smaller pieces - peptides - using proteolytic enzymes and separated using different separation techniques. The different fractions containing several hundreds of peptides are than analyzed by mass spectrometry. The mass of the peptides entering the instrument are recorded and each peptide is sequentially fragmented to obtain its amino acid sequence. Each peptide sequence with its corresponding mass is then searched against a protein database to identify the protein to which it belongs. This thesis presents new method developments in this field. In a first part, the thesis describes development of identification methods. It shows the importance of protein enrichment methods to gain access to medium-to-low abundant proteins in a human milk sample. It uses repeated injection to increase protein coverage and confidence in identification and demonstrates the impact of new database releases on protein identification lists. In addition, it successfully uses mass spectrometry as an alternative to antibody-based assays to validate the presence of 34 different recombinant constructs of Staphylococcus aureus pathogenic proteins expressed in a Lactococcus lactis strain. In a second part, development of quantification methods is described. It shows new stable isotope labeling approaches based on N- and C-terminus labeling of proteins and describes the first method of labeling of carboxylic groups at the protein level using 13C stable isotopes. In addition, a new quantitative approach called ANIBAL is explained that labels all amino and carboxylic groups at the protein level.
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The purpose of this study was to evaluate a new method of measuring rolling resistance in treadmill cycling and to establish its sensitivity and reproducibility. One participant was asked to keep a bicycle in equilibrium on a treadmill without pedalling at a constant speed of 5.56 m x s(-1), which was held in place in the front by a dynamometer. For each condition, the method consisted of 11 measurements of the force required to hold the cycle at different treadmill slopes (0-10%, increment 1%). The coefficient of rolling resistance was calculated based on the forces applied to the bicycle in equilibrium. To test the sensitivity of the method, the bicycle was successively equipped with three tyre types (700 x 28, 700 x 23, 700 x 22) and inflation pressure was set at 150, 300, 600, 900, and 1100 kPa. To test the reproducibility of the method, a second experimenter repeated all measurements done with the 700 x 23 tyres. The method was sensitive enough to detect an effect of both tyre type and inflation pressure (P < 0.001: two-way ANOVA). The measurement of the coefficient of rolling resistance by two separate experimenters resulted in a small bias of 0.00029 (95% CI, -0.00011 to 0.00068). In conclusion, the new method is sensitive and reliable, as well as being simple and affordable.
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BACKGROUND: Extensive research exists estimating the effect hazardous alcohol¦use on morbidity and mortality, but little research quantifies the association between¦alcohol consumption and utility scores in patients with alcohol dependence.¦In the context of comparative research, the World Health Organisation (WHO)¦proposed to categorise the risk for alcohol-related acute and chronic harm according¦to patients' average daily alcohol consumption. OBJECTIVES: To estimate utility¦scores associated with each category of the WHO drinking risk-level classification¦in patients with alcohol dependence (AD). METHODS: We used data from¦CONTROL, an observational cohort study including 143 AD patients from the Alcohol¦Treatment Center at Lausanne University Hospital, followed for 12 months.¦Average daily alcohol consumption was assessed monthly using the Timeline Follow-¦back method and patients were categorised according to the WHO drinking¦risk-level classification: abstinent, low, medium, high and very high. Other measures¦as sociodemographic characteristics and utility scores derived from the EuroQoL¦5-Dimensions questionnaire (EQ-5D) were collected every three months.¦Mixed models for repeated measures were used to estimate mean utility scores¦associated with WHO drinking risk-level categories. RESULTS: A total of 143 patients¦were included and the 12-month follow-up permitting the assessment of¦1318 person-months. At baseline the mean age of the patients was 44.6 (SD 11.8)¦and the majority of patients was male (63.6%). Using repeated measures analysis,¦utility scores decreased with increasing drinking levels, ranging from 0.80 in abstinent¦patients to 0.62 in patients with very high risk drinking level (p_0.0001).¦CONCLUSIONS: In this sample of patients with alcohol dependence undergoing¦specialized care, utility scores estimated from the EQ-5D appeared to substantially¦and consistently vary according to patients' WHO drinking level.
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Achieving a high degree of dependability in complex macro-systems is challenging. Because of the large number of components and numerous independent teams involved, an overview of the global system performance is usually lacking to support both design and operation adequately. A functional failure mode, effects and criticality analysis (FMECA) approach is proposed to address the dependability optimisation of large and complex systems. The basic inductive model FMECA has been enriched to include considerations such as operational procedures, alarm systems. environmental and human factors, as well as operation in degraded mode. Its implementation on a commercial software tool allows an active linking between the functional layers of the system and facilitates data processing and retrieval, which enables to contribute actively to the system optimisation. The proposed methodology has been applied to optimise dependability in a railway signalling system. Signalling systems are typical example of large complex systems made of multiple hierarchical layers. The proposed approach appears appropriate to assess the global risk- and availability-level of the system as well as to identify its vulnerabilities. This enriched-FMECA approach enables to overcome some of the limitations and pitfalls previously reported with classical FMECA approaches.
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Explicitly correlated coupled-cluster calculations of intermolecular interaction energies for the S22 benchmark set of Jurecka, Sponer, Cerny, and Hobza (Chem. Phys. Phys. Chem. 2006, 8, 1985) are presented. Results obtained with the recently proposed CCSD(T)-F12a method and augmented double-zeta basis sets are found to be in very close agreement with basis set extrapolated conventional CCSD(T) results. Furthermore, we propose a dispersion-weighted MP2 (DW-MP2) approximation that combines the good accuracy of MP2 for complexes with predominately electrostatic bonding and SCS-MP2 for dispersion-dominated ones. The MP2-F12 and SCS-MP2-F12 correlation energies are weighted by a switching function that depends on the relative HF and correlation contributions to the interaction energy. For the S22 set, this yields a mean absolute deviation of 0.2 kcal/mol from the CCSD(T)-F12a results. The method, which allows obtaining accurate results at low cost, is also tested for a number of dimers that are not in the training set.
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Background: Variable definitions of outcome (Constant score, Simple Shoulder Test [SST]) have been used to assess outcome after shoulder treatment, although none has been accepted as the universal standard. Physicians lack an objective method to reliably assess the activity of their patients in dynamic conditions. Our purpose was to clinically validate the shoulder kinematic scores given by a portable movement analysis device, using the activities of daily living described in the SST as a reference. The secondary objective was to determine whether this device could be used to document the effectiveness of shoulder treatments (for glenohumeral osteoarthritis and rotator cuff disease) and detect early failures.Methods: A clinical trial including 34 patients and a control group of 31 subjects over an observation period of 1 year was set up. Evaluations were made at baseline and 3, 6, and 12 months after surgery by 2 independent observers. Miniature sensors (3-dimensional gyroscopes and accelerometers) allowed kinematic scores to be computed. They were compared with the regular outcome scores: SST; Disabilities of the Arm, Shoulder and Hand; American Shoulder and Elbow Surgeons; and Constant.Results: Good to excellent correlations (0.61-0.80) were found between kinematics and clinical scores. Significant differences were found at each follow-up in comparison with the baseline status for all the kinematic scores (P < .015). The kinematic scores were able to point out abnormal patient outcomes at the first postoperative follow-up.Conclusion: Kinematic scores add information to the regular outcome tools. They offer an effective way to measure the functional performance of patients with shoulder pathology and have the potential to detect early treatment failures.Level of evidence: Level II, Development of Diagnostic Criteria, Diagnostic Study. (C) 2011 Journal of Shoulder and Elbow Surgery Board of Trustees.