Improvement of allocentric spatial memory resolution in children from 2 to 4 years of age

Allocentric spatial memory, the memory for locations coded in relation to objects comprising our environment, is a fundamental component of episodic memory and is dependent on the integrity of the hippocampal formation in adulthood. Previous research from different laboratories reported that basic allocentric spatial memory abilities are reliably observed in children after 2 years of age. Based on work performed in monkeys and rats, we had proposed that the functional maturation of direct entorhinal cortex projections to the CA1 field of the hippocampus might underlie the emergence of basic allocentric spatial memory. We also proposed that the protracted development of the dentate gyrus and its projections to the CA3 field of the hippocampus might underlie the development of high-resolution allocentric spatial memory capacities, based on the essential contribution of these structures to the process known as pattern separation. Here, we present an experiment designed to assess the development of spatial pattern separation capacities and its impact on allocentric spatial memory performance in children from 18 to 48 months of age. We found that: (1) allocentric spatial memory performance improved with age, (2) as compared to younger children, a greater number of children older than 36 months advanced to the final stage requiring the highest degree of spatial resolution, and (3) children that failed at different stages exhibited difficulties in discriminating locations that required higher spatial resolution abilities. These results are consistent with the hypothesis that improvements in human spatial memory performance might be linked to improvements in pattern separation capacities.

Accélération de la guérison fracturaire par le tériparatide: série de 22 cas et revue de la littérature [Improvement of fracture healing with teriparatide: series of 22 cases and review of the literature].

La pseudarthrose est définie comme une fracture qui ne guérit pas sans intervention additionnelle neuf mois après le traumatisme et en l'absence de progression radiologique pendant les trois derniers mois. Les fractures ostéoporotiques sont à plus grand risque de complications chirurgicales. On se pose de plus en plus souvent la question d'ajouter un traitement médicamenteux pour accélérer le processus de guérison fracturaire. Il existe des données montrant que le tériparatide (anabolisant osseux issu de l'hormone parathyroïdienne) accélère la guérison osseuse et améliore le devenir fonctionnel, avec ou sans chirurgie, dans des situations de fractures typiques ou atypiques. Les risques liés à ce traitement sont faibles, mais la prescription nécessite l'accord de l'assurance-maladie dans cette indication. Nous rapportons notre expérience sur l'utilisation de cette molécule, hors indication officielle, dans des cas complexes de non-guérison fracturaire. Pseudoarthrosis is defined as a non healing fracture 9 months after trauma and without radiological progression within the last three months. Osteoporotic fractures have a greater risk of chirurgical complications. The question of giving a medical treatment in the purpose of accelerating fracture healing is an increasing concern. There are data showing that with teriparatide (bone anabolic treatment derived from the parathyroid hormone) bone healing and functional status are improved, with or without surgery, in the case of either typical or atypical fractures. The risks of this treatment are low but health insurance agreement is needed in this indication. We report our experience with the use of this molecule, out of the official indication, in complex situations of non healing fractures.

Analyzing the temporal regulation of translation efficiency in mouse liver.

Mammalian physiology and behavior follow daily rhythms that are orchestrated by endogenous timekeepers known as circadian clocks. Rhythms in transcription are considered the main mechanism to engender rhythmic gene expression, but important roles for posttranscriptional mechanisms have recently emerged as well (reviewed in Lim and Allada (2013) [1]). We have recently reported on the use of ribosome profiling (RPF-seq), a method based on the high-throughput sequencing of ribosome protected mRNA fragments, to explore the temporal regulation of translation efficiency (Janich et al., 2015 [2]). Through the comparison of around-the-clock RPF-seq and matching RNA-seq data we were able to identify 150 genes, involved in ribosome biogenesis, iron metabolism and other pathways, whose rhythmicity is generated entirely at the level of protein synthesis. The temporal transcriptome and translatome data sets from this study have been deposited in NCBI's Gene Expression Omnibus under the accession number GSE67305. Here we provide additional information on the experimental setup and on important optimization steps pertaining to the ribosome profiling technique in mouse liver and to data analysis.

Estimating parameters for generalized mass action models using constraint propagation.

As modern molecular biology moves towards the analysis of biological systems as opposed to their individual components, the need for appropriate mathematical and computational techniques for understanding the dynamics and structure of such systems is becoming more pressing. For example, the modeling of biochemical systems using ordinary differential equations (ODEs) based on high-throughput, time-dense profiles is becoming more common-place, which is necessitating the development of improved techniques to estimate model parameters from such data. Due to the high dimensionality of this estimation problem, straight-forward optimization strategies rarely produce correct parameter values, and hence current methods tend to utilize genetic/evolutionary algorithms to perform non-linear parameter fitting. Here, we describe a completely deterministic approach, which is based on interval analysis. This allows us to examine entire sets of parameters, and thus to exhaust the global search within a finite number of steps. In particular, we show how our method may be applied to a generic class of ODEs used for modeling biochemical systems called Generalized Mass Action Models (GMAs). In addition, we show that for GMAs our method is amenable to the technique in interval arithmetic called constraint propagation, which allows great improvement of its efficiency. To illustrate the applicability of our method we apply it to some networks of biochemical reactions appearing in the literature, showing in particular that, in addition to estimating system parameters in the absence of noise, our method may also be used to recover the topology of these networks.

N-Terminal Modifications Improve the Receptor Affinity and Pharmacokinetics of Radiolabeled Peptidic Gastrin-Releasing Peptide Receptor Antagonists: Examples of 68Ga- and 64Cu-Labeled Peptides for PET Imaging.

Gastrin-releasing peptide receptors (GRPrs) are overexpressed on a variety of human cancers, providing the opportunity for peptide receptor targeting via radiolabeled bombesin-based peptides. As part of our ongoing investigations into the development of improved GRPr antagonists, this study aimed at verifying whether and how N-terminal modulations improve the affinity and pharmacokinetics of radiolabeled GRPr antagonists. METHODS: The potent GRPr antagonist MJ9, Pip-d-Phe-Gln-Trp-Ala-Val-Gly-His-Sta-Leu-NH2 (Pip, 4-amino-1-carboxymethyl-piperidine), was conjugated to 1,4,7-triazacyclononane, 1-glutaric acid-4,7 acetic acid (NODAGA), and 1,4,7-triazacyclononane-1,4,7-triacetic acid (NOTA) and radiolabeled with (68)Ga and (64)Cu. The GRPr affinity of the corresponding metalloconjugates was determined using (125)I-Tyr(4)-BN as a radioligand. The labeling efficiency of (68)Ga(3+) was compared between NODAGA-MJ9 and NOTA-MJ9 in acetate buffer, at room temperature and at 95°C. The (68)Ga and (64)Cu conjugates were further evaluated in vivo in PC3 tumor xenografts by biodistribution and PET imaging studies. RESULTS: The half maximum inhibitory concentrations of all the metalloconjugates are in the high picomolar-low nanomolar range, and these are the most affine-radiolabeled GRPr antagonists we have studied so far in our laboratory. NODAGA-MJ9 incorporates (68)Ga(3+) nearly quantitatively (>98%) at room temperature within 10 min and at much lower peptide concentrations (1.4 × 10(-6) M) than NOTA-MJ9, for which the labeling yield was approximately 45% under the same conditions and increased to 75% at 95°C for 5 min. Biodistribution studies showed high and specific tumor uptake, with a maximum of 23.3 ± 2.0 percentage injected activity per gram of tissue (%IA/g) for (68)Ga-NOTA-MJ9 and 16.7 ± 2.0 %IA/g for (68)Ga-NODAGA-MJ9 at 1 h after injection. The acquisition of PET images with the (64)Cu-MJ9 conjugates at later time points clearly showed the efficient clearance of the accumulated activity from the background already at 4 h after injection, whereas tumor uptake still remained high. The high pancreas uptake for all radiotracers at 1 h after injection was rapidly washed out, resulting in an increased tumor-to-pancreas ratio at later time points. CONCLUSION: We have developed 2 GRPr antagonistic radioligands, which are improved in terms of binding affinity and overall biodistribution profile. Their promising in vivo pharmacokinetic performance may contribute to the improvement of the diagnostic imaging of tumors overexpressing GRPr.

Estimation of jump-diffusion processes via empirical characteristic functions

Preface The starting point for this work and eventually the subject of the whole thesis was the question: how to estimate parameters of the affine stochastic volatility jump-diffusion models. These models are very important for contingent claim pricing. Their major advantage, availability T of analytical solutions for characteristic functions, made them the models of choice for many theoretical constructions and practical applications. At the same time, estimation of parameters of stochastic volatility jump-diffusion models is not a straightforward task. The problem is coming from the variance process, which is non-observable. There are several estimation methodologies that deal with estimation problems of latent variables. One appeared to be particularly interesting. It proposes the estimator that in contrast to the other methods requires neither discretization nor simulation of the process: the Continuous Empirical Characteristic function estimator (EGF) based on the unconditional characteristic function. However, the procedure was derived only for the stochastic volatility models without jumps. Thus, it has become the subject of my research. This thesis consists of three parts. Each one is written as independent and self contained article. At the same time, questions that are answered by the second and third parts of this Work arise naturally from the issues investigated and results obtained in the first one. The first chapter is the theoretical foundation of the thesis. It proposes an estimation procedure for the stochastic volatility models with jumps both in the asset price and variance processes. The estimation procedure is based on the joint unconditional characteristic function for the stochastic process. The major analytical result of this part as well as of the whole thesis is the closed form expression for the joint unconditional characteristic function for the stochastic volatility jump-diffusion models. The empirical part of the chapter suggests that besides a stochastic volatility, jumps both in the mean and the volatility equation are relevant for modelling returns of the S&P500 index, which has been chosen as a general representative of the stock asset class. Hence, the next question is: what jump process to use to model returns of the S&P500. The decision about the jump process in the framework of the affine jump- diffusion models boils down to defining the intensity of the compound Poisson process, a constant or some function of state variables, and to choosing the distribution of the jump size. While the jump in the variance process is usually assumed to be exponential, there are at least three distributions of the jump size which are currently used for the asset log-prices: normal, exponential and double exponential. The second part of this thesis shows that normal jumps in the asset log-returns should be used if we are to model S&P500 index by a stochastic volatility jump-diffusion model. This is a surprising result. Exponential distribution has fatter tails and for this reason either exponential or double exponential jump size was expected to provide the best it of the stochastic volatility jump-diffusion models to the data. The idea of testing the efficiency of the Continuous ECF estimator on the simulated data has already appeared when the first estimation results of the first chapter were obtained. In the absence of a benchmark or any ground for comparison it is unreasonable to be sure that our parameter estimates and the true parameters of the models coincide. The conclusion of the second chapter provides one more reason to do that kind of test. Thus, the third part of this thesis concentrates on the estimation of parameters of stochastic volatility jump- diffusion models on the basis of the asset price time-series simulated from various "true" parameter sets. The goal is to show that the Continuous ECF estimator based on the joint unconditional characteristic function is capable of finding the true parameters. And, the third chapter proves that our estimator indeed has the ability to do so. Once it is clear that the Continuous ECF estimator based on the unconditional characteristic function is working, the next question does not wait to appear. The question is whether the computation effort can be reduced without affecting the efficiency of the estimator, or whether the efficiency of the estimator can be improved without dramatically increasing the computational burden. The efficiency of the Continuous ECF estimator depends on the number of dimensions of the joint unconditional characteristic function which is used for its construction. Theoretically, the more dimensions there are, the more efficient is the estimation procedure. In practice, however, this relationship is not so straightforward due to the increasing computational difficulties. The second chapter, for example, in addition to the choice of the jump process, discusses the possibility of using the marginal, i.e. one-dimensional, unconditional characteristic function in the estimation instead of the joint, bi-dimensional, unconditional characteristic function. As result, the preference for one or the other depends on the model to be estimated. Thus, the computational effort can be reduced in some cases without affecting the efficiency of the estimator. The improvement of the estimator s efficiency by increasing its dimensionality faces more difficulties. The third chapter of this thesis, in addition to what was discussed above, compares the performance of the estimators with bi- and three-dimensional unconditional characteristic functions on the simulated data. It shows that the theoretical efficiency of the Continuous ECF estimator based on the three-dimensional unconditional characteristic function is not attainable in practice, at least for the moment, due to the limitations on the computer power and optimization toolboxes available to the general public. Thus, the Continuous ECF estimator based on the joint, bi-dimensional, unconditional characteristic function has all the reasons to exist and to be used for the estimation of parameters of the stochastic volatility jump-diffusion models.

Factors favoring a degradation or an improvement in activities of daily living (ADL) performance among nursing home (NH) residents: A survival analysis.

Different factors influence ADL performance among nursing home (NH) residents in long term care. The aim was to investigate which factors were associated with a significant change of ADL performance in NH residents, and whether or not these factors were gender-specific. The design was a survival analysis. The 10,199 participants resided in ninety Swiss NHs. Their ADL performance had been assessed by the Resident Assessment Instrument Minimum Data Set (RAI-MDS) in the period from 1997 to 2007. Relevant change in ADL performance was defined as 2 levels of change on the ADL scale between two successive assessments. The occurrence of either an improvement or a degradation of the ADL status) was analyzed using the Cox proportional hazard model. The analysis included a total of 10,199 NH residents. Each resident received between 2 and 23 assessments. Poor balance, incontinence, impaired cognition, a low BMI, impaired vision, no daily contact with proxies, impaired hearing and the presence of depression were, by hierarchical order, significant risk factors for NH residents to experience a degradation of ADL performance. Residents, who were incontinent, cognitively impaired or had a high BMI were significantly less likely to improve their ADL abilities. Male residents with cancer were prone to see their ADL improve. The year of NH entry was significantly associated with either degradation or improvement of ADL performance. Measures aiming at improving balance and continence, promoting physical activity, providing appropriate nourishment and cognitive enhancement are important for ADL performance in NH residents.