Estimating the confidence level of white matter connections obtained with MRI tractography.

BACKGROUND: Since the emergence of diffusion tensor imaging, a lot of work has been done to better understand the properties of diffusion MRI tractography. However, the validation of the reconstructed fiber connections remains problematic in many respects. For example, it is difficult to assess whether a connection is the result of the diffusion coherence contrast itself or the simple result of other uncontrolled parameters like for example: noise, brain geometry and algorithmic characteristics. METHODOLOGY/PRINCIPAL FINDINGS: In this work, we propose a method to estimate the respective contributions of diffusion coherence versus other effects to a tractography result by comparing data sets with and without diffusion coherence contrast. We use this methodology to assign a confidence level to every gray matter to gray matter connection and add this new information directly in the connectivity matrix. CONCLUSIONS/SIGNIFICANCE: Our results demonstrate that whereas we can have a strong confidence in mid- and long-range connections obtained by a tractography experiment, it is difficult to distinguish between short connections traced due to diffusion coherence contrast from those produced by chance due to the other uncontrolled factors of the tractography methodology.

Does the physical disector method provide an accurate estimation of sensory neuron number in rat dorsal root ganglia?

The physical disector is a method of choice for estimating unbiased neuron numbers; nevertheless, calibration is needed to evaluate each counting method. The validity of this method can be assessed by comparing the estimated cell number with the true number determined by a direct counting method in serial sections. We reconstructed a 1/5 of rat lumbar dorsal root ganglia taken from two experimental conditions. From each ganglion, images of 200 adjacent semi-thin sections were used to reconstruct a volumetric dataset (stack of voxels). On these stacks the number of sensory neurons was estimated and counted respectively by physical disector and direct counting methods. Also, using the coordinates of nuclei from the direct counting, we simulate, by a Matlab program, disector pairs separated by increasing distances in a ganglion model. The comparison between the results of these approaches clearly demonstrates that the physical disector method provides a valid and reliable estimate of the number of sensory neurons only when the distance between the consecutive disector pairs is 60 microm or smaller. In these conditions the size of error between the results of physical disector and direct counting does not exceed 6%. In contrast when the distance between two pairs is larger than 60 microm (70-200 microm) the size of error increases rapidly to 27%. We conclude that the physical dissector method provides a reliable estimate of the number of rat sensory neurons only when the separating distance between the consecutive dissector pairs is no larger than 60 microm.

GAP-independent functions of DLC1 in metastasis.

Metastases are responsible for most cancer-related deaths. One of the hallmarks of metastatic cells is increased motility and migration through extracellular matrixes. These processes rely on specific small GTPases, in particular those of the Rho family. Deleted in liver cancer-1 (DLC1) is a tumor suppressor that bears a RhoGAP activity. This protein is lost in most cancers, allowing malignant cells to proliferate and disseminate in a Rho-dependent manner. However, DLC1 is also a scaffold protein involved in alternative pathways leading to tumor and metastasis suppressor activities. Recently, substantial information has been gathered on these mechanisms and this review is aiming at describing the potential and known alternative GAP-independent mechanisms allowing DLC1 to impair migration, invasion, and metastasis formation.

Estimating vadose zone hydraulic properties using ground penetrating radar: The impact of prior information

A number of geophysical methods, such as ground-penetrating radar (GPR), have the potential to provide valuable information on hydrological properties in the unsaturated zone. In particular, the stochastic inversion of such data within a coupled geophysical-hydrological framework may allow for the effective estimation of vadose zone hydraulic parameters and their corresponding uncertainties. A critical issue in stochastic inversion is choosing prior parameter probability distributions from which potential model configurations are drawn and tested against observed data. A well chosen prior should reflect as honestly as possible the initial state of knowledge regarding the parameters and be neither overly specific nor too conservative. In a Bayesian context, combining the prior with available data yields a posterior state of knowledge about the parameters, which can then be used statistically for predictions and risk assessment. Here we investigate the influence of prior information regarding the van Genuchten-Mualem (VGM) parameters, which describe vadose zone hydraulic properties, on the stochastic inversion of crosshole GPR data collected under steady state, natural-loading conditions. We do this using a Bayesian Markov chain Monte Carlo (MCMC) inversion approach, considering first noninformative uniform prior distributions and then more informative priors derived from soil property databases. For the informative priors, we further explore the effect of including information regarding parameter correlation. Analysis of both synthetic and field data indicates that the geophysical data alone contain valuable information regarding the VGM parameters. However, significantly better results are obtained when we combine these data with a realistic, informative prior.

Test result-based sampling: an efficient design for estimating the accuracy of patient safety indicators.

OBJECTIVE: Accuracy studies of Patient Safety Indicators (PSIs) are critical but limited by the large samples required due to low occurrence of most events. We tested a sampling design based on test results (verification-biased sampling [VBS]) that minimizes the number of subjects to be verified. METHODS: We considered 3 real PSIs, whose rates were calculated using 3 years of discharge data from a university hospital and a hypothetical screen of very rare events. Sample size estimates, based on the expected sensitivity and precision, were compared across 4 study designs: random and VBS, with and without constraints on the size of the population to be screened. RESULTS: Over sensitivities ranging from 0.3 to 0.7 and PSI prevalence levels ranging from 0.02 to 0.2, the optimal VBS strategy makes it possible to reduce sample size by up to 60% in comparison with simple random sampling. For PSI prevalence levels below 1%, the minimal sample size required was still over 5000. CONCLUSIONS: Verification-biased sampling permits substantial savings in the required sample size for PSI validation studies. However, sample sizes still need to be very large for many of the rarer PSIs.

Estimating the apparent transverse relaxation time (R2(*)) from images with different contrasts (ESTATICS) reduces motion artifacts.

Relaxation rates provide important information about tissue microstructure. Multi-parameter mapping (MPM) estimates multiple relaxation parameters from multi-echo FLASH acquisitions with different basic contrasts, i.e., proton density (PD), T1 or magnetization transfer (MT) weighting. Motion can particularly affect maps of the apparent transverse relaxation rate R2(*), which are derived from the signal of PD-weighted images acquired at different echo times. To address the motion artifacts, we introduce ESTATICS, which robustly estimates R2(*) from images even when acquired with different basic contrasts. ESTATICS extends the fitted signal model to account for inherent contrast differences in the PDw, T1w and MTw images. The fit was implemented as a conventional ordinary least squares optimization and as a robust fit with a small or large confidence interval. These three different implementations of ESTATICS were tested on data affected by severe motion artifacts and data with no prominent motion artifacts as determined by visual assessment or fast optical motion tracking. ESTATICS improved the quality of the R2(*) maps and reduced the coefficient of variation for both types of data-with average reductions of 30% when severe motion artifacts were present. ESTATICS can be applied to any protocol comprised of multiple 2D/3D multi-echo FLASH acquisitions as used in the general research and clinical setting.

How do the different components of episodic memory develop? Role of executive functions and short-term feature-binding abilities.

This study investigated the development of all 3 components of episodic memory (EM), as defined by Tulving, namely, core factual content, spatial context, and temporal context. To this end, a novel, ecologically valid test was administered to 109 participants aged 4-16 years. Results showed that each EM component develops at a different rate. Ability to memorize factual content emerges early, whereas context retrieval abilities continue to improve until adolescence, due to persistent encoding difficulties (isolated by comparing results on free recall and recognition tasks). Exploration of links with other cognitive functions revealed that short-term feature-binding abilities contribute to all EM components, and executive functions to temporal and spatial context, although ability to memorize temporal context is predicted mainly by age.

Adapter and enzymatic functions of proteases in T-cell activation.

Proteases control many vital aspects of humoral and cellular immune responses, including the maturation of cytokines and the killing of target cells. Recently, it has become evident that triggering of the T-cell receptor controls T-cell proliferation through proteases such as mucosa-associated lymphoid tissue 1 (MALT1) and Caspase-8 that act both as adapters and enzymes. Here, we discuss the role of these and other proteases that are relevant to the control of the T-cell response and represent interesting targets of therapeutic immunomodulation.

Assessment of skinfold thickness equations in estimating body composition in children with inflammatory bowel

Introduction: Growth is a central process in paediatrics. Weight and height evaluation are therefore routine exams for every child but in some situation, particularly inflammatory bowel disease (IBD), a wider evaluation of nutritional status needs to be performed. The assessment of body composition is essential in order to maintain acceptable growth using the following techniques: Dual-energy X-ray absorptiometry (DEXA), bio-impedance-analysis (BIA) and anthropometric measurements (skinfold thickness skin), the latter being most easily available and most cost effective. Objectives: To assess the accuracy of skinfold equations in estimating percentage body fat (%BF) in children with inflammatory bowel disease (IBD), compared with assessment of body fat dual energy X-ray absorptiometry (DEXA). Methods: Twenty-one patients (11 females, 10 males; mean age: 14.3 years, range 12 - 16 years) with IBD (Crohn's disease n = 15, ulcerative colitis n = 6)). Estimated%BF was computed using 6 established equations based on the triceps, biceps, subscapular and suprailiac skinfolds (Deurenberg, Weststrate, Slaughter, Durnin & Rahaman, Johnston, Brook) and compared to DEXA. Concordance analysis was performed using Lin's concordance correlation and the Bland-Altman limits of agreement method. Results: Durnin & Rahaman's equation shows a higher Lin's concordance coefficient with a small difference amongst raw values for skinfolds and DEXA compared to the other equations. Correlation coefficient between mean and difference is close to zero with a non-significant Bradley-Blackwood test. Conclusion: Body composition in paediatric IBD patients using the Durnin & Rahaman skinfold-equation adequately reflects values obtained by DEXA.

A simple score for estimating ischemic heart disease in patients with non-traumatic chest pain in primary care

Background: Modelling epidemiological knowledge in validated clinical scores is a practical mean of integrating EBM to usual care. Existing scores about cardiovascular disease have been largely developed in emergency settings, but few in primary care. Such a toll is needed for general practitioners (GP) to evaluate the probability of ischemic heart disease (IHD) in patients with non-traumatic chest pain. Objective: To develop a predictive model to use as a clinical score for detecting IHD in patients with non-traumatic chest-pain in primary care. Methods: A post-hoc secondary analysis on data from an observational study including 672 patients with chest pain of which 85 had IHD diagnosed by their GP during the year following their inclusion. Best subset method was used to select 8 predictive variables from univariate analysis and fitted in a multivariate logistic regression model to define the score. Reliability of the model was assessed using split-group method. Results: Significant predictors were: age (0-3 points), gender (1 point), having at least one cardiovascular risks factor (hypertension, dyslipidemia, diabetes, smoking, family history of CVD; 3 points), personal history of cardiovascular disease (1 point), duration of chest pain from 1 to 60 minutes (2 points), substernal chest pain (1 point), pain increasing with exertion (1 point) and absence of tenderness at palpation (1 point). Area under the ROC curve for the score was of 0.95 (IC95% 0.93; 0.97). Patients were categorised in three groups, low risk of IHD (score under 6; n = 360), moderate risk of IHD (score from 6 to 8; n = 187) and high risk of IHD (score from 9-13; n = 125). Prevalence of IHD in each group was respectively of 0%, 6.7%, 58.5%. Reliability of the model seems satisfactory as the model developed from the derivation set predicted perfectly (p = 0.948) the number of patients in each group in the validation set. Conclusion: This clinical score based only on history and physical exams can be an important tool in the practice of the general physician for the prediction of ischemic heart disease in patients complaining of chest pain. The score below 6 points (in more than half of our population) can avoid demanding complementary exams for selected patients (ECG, laboratory tests) because of the very low risk of IHD. Score above 6 points needs investigation to detect or rule out IHD. Further external validation is required in ambulatory settings.

Circadian clock-dependent and -independent rhythmic proteomes implement distinct diurnal functions in mouse liver.

Diurnal oscillations of gene expression controlled by the circadian clock underlie rhythmic physiology across most living organisms. Although such rhythms have been extensively studied at the level of transcription and mRNA accumulation, little is known about the accumulation patterns of proteins. Here, we quantified temporal profiles in the murine hepatic proteome under physiological light-dark conditions using stable isotope labeling by amino acids quantitative MS. Our analysis identified over 5,000 proteins, of which several hundred showed robust diurnal oscillations with peak phases enriched in the morning and during the night and related to core hepatic physiological functions. Combined mathematical modeling of temporal protein and mRNA profiles indicated that proteins accumulate with reduced amplitudes and significant delays, consistent with protein half-life data. Moreover, a group comprising about one-half of the rhythmic proteins showed no corresponding rhythmic mRNAs, indicating significant translational or posttranslational diurnal control. Such rhythms were highly enriched in secreted proteins accumulating tightly during the night. Also, these rhythms persisted in clock-deficient animals subjected to rhythmic feeding, suggesting that food-related entrainment signals influence rhythms in circulating plasma factors.