Identification of optimal structural connectivity using functional connectivity and neural modeling.

The complex network dynamics that arise from the interaction of the brain's structural and functional architectures give rise to mental function. Theoretical models demonstrate that the structure-function relation is maximal when the global network dynamics operate at a critical point of state transition. In the present work, we used a dynamic mean-field neural model to fit empirical structural connectivity (SC) and functional connectivity (FC) data acquired in humans and macaques and developed a new iterative-fitting algorithm to optimize the SC matrix based on the FC matrix. A dramatic improvement of the fitting of the matrices was obtained with the addition of a small number of anatomical links, particularly cross-hemispheric connections, and reweighting of existing connections. We suggest that the notion of a critical working point, where the structure-function interplay is maximal, may provide a new way to link behavior and cognition, and a new perspective to understand recovery of function in clinical conditions.

Physiologically based pharmacokinetic modeling of arsenic in the mouse

A remarkable feature of the carcinogenicity of inorganic arsenic is that while human exposures to high concentrations of inorganic arsenic in drinking water are associated with increases in skin, lung, and bladder cancer, inorganic arsenic has not typically caused tumors in standard laboratory animal test protocols. Inorganic arsenic administered for periods of up to 2 yr to various strains of laboratory mice, including the Swiss CD-1, Swiss CR:NIH(S), C57Bl/6p53(+/-), and C57Bl/6p53(+/+), has not resulted in significant increases in tumor incidence. However, Ng et al. (1999) have reported a 40% tumor incidence in C57Bl/6J mice exposed to arsenic in their drinking water throughout their lifetime, with no tumors reported in controls. In order to investigate the potential role of tissue dosimetry in differential susceptibility to arsenic carcinogenicity, a physiologically based pharmacokinetic (PBPK) model for inorganic arsenic in the rat, hamster, monkey, and human (Mann et al., 1996a, 1996b) was extended to describe the kinetics in the mouse. The PBPK model was parameterized in the mouse using published data from acute exposures of B6C3F1 mice to arsenate, arsenite, monomethylarsonic acid (MMA), and dimethylarsinic acid (DMA) and validated using data from acute exposures of C57Black mice. Predictions of the acute model were then compared with data from chronic exposures. There was no evidence of changes in the apparent volume of distribution or in the tissue-plasma concentration ratios between acute and chronic exposure that might support the possibility of inducible arsenite efflux. The PBPK model was also used to project tissue dosimetry in the C57Bl/6J study, in comparison with tissue levels in studies having shorter duration but higher arsenic treatment concentrations. The model evaluation indicates that pharmacokinetic factors do not provide an explanation for the difference in outcomes across the various mouse bioassays. Other possible explanations may relate to strain-specific differences, or to the different durations of dosing in each of the mouse studies, given the evidence that inorganic arsenic is likely to be active in the later stages of the carcinogenic process. [Authors]

Modeling the impact of lesions in the human brain.

Lesions of anatomical brain networks result in functional disturbances of brain systems and behavior which depend sensitively, often unpredictably, on the lesion site. The availability of whole-brain maps of structural connections within the human cerebrum and our increased understanding of the physiology and large-scale dynamics of cortical networks allow us to investigate the functional consequences of focal brain lesions in a computational model. We simulate the dynamic effects of lesions placed in different regions of the cerebral cortex by recording changes in the pattern of endogenous ("resting-state") neural activity. We find that lesions produce specific patterns of altered functional connectivity among distant regions of cortex, often affecting both cortical hemispheres. The magnitude of these dynamic effects depends on the lesion location and is partly predicted by structural network properties of the lesion site. In the model, lesions along the cortical midline and in the vicinity of the temporo-parietal junction result in large and widely distributed changes in functional connectivity, while lesions of primary sensory or motor regions remain more localized. The model suggests that dynamic lesion effects can be predicted on the basis of specific network measures of structural brain networks and that these effects may be related to known behavioral and cognitive consequences of brain lesions.

Determinants of brain cell metabolic phenotypes and energy substrate utilization unraveled with a modeling approach.

Although all brain cells bear in principle a comparable potential in terms of energetics, in reality they exhibit different metabolic profiles. The specific biochemical characteristics explaining such disparities and their relative importance are largely unknown. Using a modeling approach, we show that modifying the kinetic parameters of pyruvate dehydrogenase and mitochondrial NADH shuttling within a realistic interval can yield a striking switch in lactate flux direction. In this context, cells having essentially an oxidative profile exhibit pronounced extracellular lactate uptake and consumption. However, they can be turned into cells with prominent aerobic glycolysis by selectively reducing the aforementioned parameters. In the case of primarily oxidative cells, we also examined the role of glycolysis and lactate transport in providing pyruvate to mitochondria in order to sustain oxidative phosphorylation. The results show that changes in lactate transport capacity and extracellular lactate concentration within the range described experimentally can sustain enhanced oxidative metabolism upon activation. Such a demonstration provides key elements to understand why certain brain cell types constitutively adopt a particular metabolic profile and how specific features can be altered under different physiological and pathological conditions in order to face evolving energy demands.

Evaluation of occupational exposure: comparison of biological and environmental variabilities using physiologically based toxicokinetic modeling

PURPOSE: Few studies compare the variabilities that characterize environmental (EM) and biological monitoring (BM) data. Indeed, comparing their respective variabilities can help to identify the best strategy for evaluating occupational exposure. The objective of this study is to quantify the biological variability associated with 18 bio-indicators currently used in work environments. METHOD: Intra-individual (BV(intra)), inter-individual (BV(inter)), and total biological variability (BV(total)) were quantified using validated physiologically based toxicokinetic (PBTK) models coupled with Monte Carlo simulations. Two environmental exposure profiles with different levels of variability were considered (GSD of 1.5 and 2.0). RESULTS: PBTK models coupled with Monte Carlo simulations were successfully used to predict the biological variability of biological exposure indicators. The predicted values follow a lognormal distribution, characterized by GSD ranging from 1.1 to 2.3. Our results show that there is a link between biological variability and the half-life of bio-indicators, since BV(intra) and BV(total) both decrease as the biological indicator half-lives increase. BV(intra) is always lower than the variability in the air concentrations. On an individual basis, this means that the variability associated with the measurement of biological indicators is always lower than the variability characterizing airborne levels of contaminants. For a group of workers, BM is less variable than EM for bio-indicators with half-lives longer than 10-15 h. CONCLUSION: The variability data obtained in the present study can be useful in the development of BM strategies for exposure assessment and can be used to calculate the number of samples required for guiding industrial hygienists or medical doctors in decision-making.

CPPD crystal deposition disease in patients with rheumatoid arthritis.

The aim of this study was to assess the frequency and the outcome of patients suffering from rheumatoid arthritis in which calcium pyrophosphate dihydrate (CPPD) crystal deposits were found to coexist in synovial fluid analysis. Such association was more frequent than previously believed with CPPD crystals found in 25.8% of 93 patients with rheumatoid arthritis. As a group, a trend toward a worse outcome was suggested by more frequent prostheses of the lower limb.

Potential impact of climate change on vegetation in the European Alps: a review

Based on conclusions drawn from general climatic impact assessment in mountain regions, the review synthesizes results relevant to the European Alps published mainly from 1994 onward in the fields of population genetics, ecophysiology, phenology, phytogeography, modeling, paleoecology and vegetation dynamics. Other important factors of global change interacting synergistically with climatic factors are also mentioned, such as atmospheric CO2 concentration, eutrophication, ozone or changes in land-use. Topics addressed are general species distribution and populations (persistence, acclimation, genetic variability, dispersal, fragmentation, plant/animal interaction, species richness, conservation), potential response of vegetation (ecotonal shift - area, physiography - changes in the composition, structural changes), phenology, growth and productivity, and landscape. In conclusion, the European Alps appear to have a natural inertia and thus to tolerate an increase of 1-2 K of mean air temperature as far as plant species and ecosystems are concerned in general. However, the impact of land-use is very likely to negate this buffer in many areas. For a change of the order of 3 K or more, profound changes may be expected.

Involvement of Dab1 in APP processing and [beta]-amyloid deposition in sporadic Creutzfeldt-Jakob patients.

Alzheimer"s disease and prion pathologies (e.g., Creutzfeldt-Jakob disease) display profound neural lesions associated with aberrant protein processing and extracellular amyloid deposits. For APP processing, emerging data suggest that the adaptor protein Dab1 plays a relevant role in regulating its intracellular trafficking and secretase-mediated proteolysis. Although some data have been presented, a putative relationship between human prion diseases and Dab1/APP interactions is lacking. Therefore, we have studied the putative relation between Dab1, APP processing and Aβ deposition, targets in sCJD cases. Our biochemical results categorized two groups of sCJD cases, which also correlated with PrPsc types 1 and 2 respectively. One group, with PrPsc type 1 showed increased Dab1 phosphorylation, and lower βCTF production with an absence of Aβ deposition. The second sCJD group, which carried PrPsc type 2, showed lower levels of Dab1 phosphorylation and βCTF production, similar to control cases. Relevant Aβ deposition in the second sCJD group was measured. Thus, a direct correlation between Dab1 phosphorylation, Aβ deposition and PrPsc type in human sCJD is presented for the first time.

Molecular modeling of peptide-MHC class I complexes : applications to peptide based immunotherapy

Summary The specific CD8+ T cell immune response against tumors relies on the recognition by the T cell receptor (TCR) on cytotoxic T lymphocytes (CTL) of antigenic peptides bound to the class I major histocompatibility complex (MHC) molecule. Such tumor associated antigenic peptides are the focus of tumor immunotherapy with peptide vaccines. The strategy for obtaining an improved immune response often involves the design of modified tumor associated antigenic peptides. Such modifications aim at creating higher affinity and/or degradation resistant peptides and require precise structures of the peptide-MHC class I complex. In addition, the modified peptide must be cross-recognized by CTLs specific for the parental peptide, i.e. preserve the structure of the epitope. Detailed structural information on the modified peptide in complex with MHC is necessary for such predictions. In this thesis, the main focus is the development of theoretical in silico methods for prediction of both structure and cross-reactivity of peptide-MHC class I complexes. Applications of these methods in the context of immunotherapy are also presented. First, a theoretical method for structure prediction of peptide-MHC class I complexes is developed and validated. The approach is based on a molecular dynamics protocol to sample the conformational space of the peptide in its MHC environment. The sampled conformers are evaluated using conformational free energy calculations. The method, which is evaluated for its ability to reproduce 41 X-ray crystallographic structures of different peptide-MHC class I complexes, shows an overall prediction success of 83%. Importantly, in the clinically highly relevant subset of peptide-HLAA*0201 complexes, the prediction success is 100%. Based on these structure predictions, a theoretical approach for prediction of cross-reactivity is developed and validated. This method involves the generation of quantitative structure-activity relationships using three-dimensional molecular descriptors and a genetic neural network. The generated relationships are highly predictive as proved by high cross-validated correlation coefficients (0.78-0.79). Together, the here developed theoretical methods open the door for efficient rational design of improved peptides to be used in immunotherapy. Résumé La réponse immunitaire spécifique contre des tumeurs dépend de la reconnaissance par les récepteurs des cellules T CD8+ de peptides antigéniques présentés par les complexes majeurs d'histocompatibilité (CMH) de classe I. Ces peptides sont utilisés comme cible dans l'immunothérapie par vaccins peptidiques. Afin d'augmenter la réponse immunitaire, les peptides sont modifiés de façon à améliorer l'affinité et/ou la résistance à la dégradation. Ceci nécessite de connaître la structure tridimensionnelle des complexes peptide-CMH. De plus, les peptides modifiés doivent être reconnus par des cellules T spécifiques du peptide natif. La structure de l'épitope doit donc être préservée et des structures détaillées des complexes peptide-CMH sont nécessaires. Dans cette thèse, le thème central est le développement des méthodes computationnelles de prédiction des structures des complexes peptide-CMH classe I et de la reconnaissance croisée. Des applications de ces méthodes de prédiction à l'immunothérapie sont également présentées. Premièrement, une méthode théorique de prédiction des structures des complexes peptide-CMH classe I est développée et validée. Cette méthode est basée sur un échantillonnage de l'espace conformationnel du peptide dans le contexte du récepteur CMH classe I par dynamique moléculaire. Les conformations sont évaluées par leurs énergies libres conformationnelles. La méthode est validée par sa capacité à reproduire 41 structures des complexes peptide-CMH classe I obtenues par cristallographie aux rayons X. Le succès prédictif général est de 83%. Pour le sous-groupe HLA-A*0201 de complexes de grande importance pour l'immunothérapie, ce succès est de 100%. Deuxièmement, à partir de ces structures prédites in silico, une méthode théorique de prédiction de la reconnaissance croisée est développée et validée. Celle-ci consiste à générer des relations structure-activité quantitatives en utilisant des descripteurs moléculaires tridimensionnels et un réseau de neurones couplé à un algorithme génétique. Les relations générées montrent une capacité de prédiction remarquable avec des valeurs de coefficients de corrélation de validation croisée élevées (0.78-0.79). Les méthodes théoriques développées dans le cadre de cette thèse ouvrent la voie du design de vaccins peptidiques améliorés.

Intermittent hemodialysis treatment in cefepime-induced neurotoxicity: Case report, pharmacokinetic modeling, and review of the literature.

Cefepime is a broad-spectrum cephalosporin indicated for in-hospital treatment of severe infections. Acute neurotoxicity, an increasingly recognized adverse effect of this drug in an overdose, predominantly affects patients with reduced renal function. Although dialytic approaches have been advocated to treat this condition, their role in this indication remains unclear. We report the case of an 88-year-old female patient with impaired renal function who developed life-threatening neurologic symptoms during cefepime therapy. She was treated with two intermittent 3-hour high-flux, high-efficiency hemodialysis sessions. Serial pre-, post-, and peridialytic (pre- and postfilter) serum cefepime concentrations were measured. Pharmacokinetic modeling showed that this dialytic strategy allowed for serum cefepime concentrations to return to the estimated nontoxic range 15 hours earlier than would have been the case without an intervention. The patient made a full clinical recovery over the next 48 hours. We conclude that at least 1 session of intermittent hemodialysis may shorten the time to return to the nontoxic range in severe clinically patent intoxication. It should be considered early in its clinical course pending chemical confirmation, even in frail elderly patients. Careful dosage adjustment and a high index of suspicion are essential in this population.

Gas collisions and pressure quenching of the photoluminescence of silicon nanopowder grown by plasma-enhanced chemical vapor deposition

The quenching of the photoluminescence of Si nanopowder grown by plasma-enhanced chemical vapor deposition due to pressure was measured for various gases ( H2, O2, N2, He, Ne, Ar, and Kr) and at different temperatures. The characteristic pressure, P0, of the general dependence I(P) = I0¿exp(¿P/P0) is gas and temperature dependent. However, when the number of gas collisions is taken as the variable instead of pressure, then the quenching is the same within a gas family (mono- or diatomic) and it is temperature independent. So it is concluded that the effect depends on the number of gas collisions irrespective of the nature of the gas or its temperature.

The cervical spine in calcium pyrophosphate dihydrate deposition disease. A prevalent case-control study.

OBJECTIVE: To test the hypothesis that calcium pyrophosphate dihydrate (CPPD) deposition disease is a risk factor for neck pain. METHODS: A prevalent case-control study was conducted to assess cervical calcifications and neck pain between patients with and without known peripheral CPPD deposition disease. CPPD cases were included if diagnosed with CPPD deposition disease of peripheral joints, and excluded if their chief complaint was neck pain. Controls were randomly selected among consecutive patients, hospitalized for conditions unrelated to CPPD deposition disease or neck pain, and matched to CPPD cases by age and sex. Cervical calcifications were assessed by lateral cervical radiographs and computed tomography scans of the upper cervical spine; neck pain and cervical function were appraised by a validated questionnaire. RESULTS: Cervical calcifications were found in 24 out of 35 patients (69%) in the CPPD group compared to 4 out of 35 patients (11%) in the control group (p < 0.001). Patients with CPPD deposition disease reported significantly more neck pain and discomfort than controls (p < 0.001), and were 5 times more likely to report any neck pain (odds ratio 5.5; 95% confidence interval: 1.9, 21.9). Among male patients, more extensive cervical calcified deposits correlated with more severe neck pain (rs = 0.58, p = 0.03). CONCLUSION: These results suggest that CPPD deposition disease frequently involves the cervical spine and may be associated with the development of neck pain.