Détermination de l'antigène HLA-G soluble dans le liquide folliculaire et dans le milieu de culture d'embryons comme indicateur du succès d'un traitement par FIV-ICSI [Soluble human leukocyte antigen-G (sHLA-G) in follicular fluid and embryo culture medium and its impact on pregnancy prediction in IVF-ICSI treatment]

In IVF around 70% of embryos fail to implant. Often more than one embryo is transferred in order to enhance the chances of pregnancy, but this is at the price of an increased multiple pregnancy risk. In the aim to increase the success rate with a single embryo, research projects on prognostic factors of embryo viability have been initiated, but no marker has found a routine clinical application to date. Effects of soluble human leukocyte antigen-G (sHLA-G) on both NK cell activity and on Th1/Th2 cytokine balance suggest a role in the embryo implantation process, but the relevance of sHLA-G measurements in embryo culture medium and in follicular fluid (FF) are inconsistent to date. In this study, we have investigated the potential of sHLA-G in predicting the achievement of a pregnancy after IVF-ICSI in a large number of patients (n = 221). sHLA-G was determined in media and in FF by ELISA. In both FF and embryo medium, no significant differences in sHLA-G concentrations were observed between the groups "pregnancy" and "implantation failure", or between the groups "ongoing" versus "miscarried pregnancies". Our results do not favour routine sHLA-G determinations in the FF nor in embryo conditioned media, with the current assay technology available.

A two-phase composite in simple shear: Effective mechanical anisotropy development and localization potential

We present a combined shape and mechanical anisotropy evolution model for a two-phase inclusion-bearing rock subject to large deformation. A single elliptical inclusion embedded in a homogeneous but anisotropic matrix is used to represent a simplified shape evolution enforced on all inclusions. The mechanical anisotropy develops due to the alignment of elongated inclusions. The effective anisotropy is quantified using the differential effective medium (DEM) approach. The model can be run for any deformation path and an arbitrary viscosity ratio between the inclusion and host phase. We focus on the case of simple shear and weak inclusions. The shape evolution of the representative inclusion is largely insensitive to the anisotropy development and to parameter variations in the studied range. An initial hardening stage is observed up to a shear strain of gamma = 1 irrespective of the inclusion fraction. The hardening is followed by a softening stage related to the developing anisotropy and its progressive rotation toward the shear direction. The traction needed to maintain a constant shear rate exhibits a fivefold drop at gamma = 5 in the limiting case of an inviscid inclusion. Numerical simulations show that our analytical model provides a good approximation to the actual evolution of a two-phase inclusion-host composite. However, the inclusions develop complex sigmoidal shapes resulting in the formation of an S-C fabric. We attribute the observed drop in the effective normal viscosity to this structural development. We study the localization potential in a rock column bearing varying fraction of inclusions. In the inviscid inclusion case, a strain jump from gamma = 3 to gamma = 100 is observed for a change of the inclusion fraction from 20% to 33%.

Defining the RNA polymerase III transcriptome: Genome-wide localization of the RNA polymerase III transcription machinery in human cells.

Our view of the RNA polymerase III (Pol III) transcription machinery in mammalian cells arises mostly from studies of the RN5S (5S) gene, the Ad2 VAI gene, and the RNU6 (U6) gene, as paradigms for genes with type 1, 2, and 3 promoters. Recruitment of Pol III onto these genes requires prior binding of well-characterized transcription factors. Technical limitations in dealing with repeated genomic units, typically found at mammalian Pol III genes, have so far hampered genome-wide studies of the Pol III transcription machinery and transcriptome. We have localized, genome-wide, Pol III and some of its transcription factors. Our results reveal broad usage of the known Pol III transcription machinery and define a minimal Pol III transcriptome in dividing IMR90hTert fibroblasts. This transcriptome consists of some 500 actively transcribed genes including a few dozen candidate novel genes, of which we confirmed nine as Pol III transcription units by additional methods. It does not contain any of the microRNA genes previously described as transcribed by Pol III, but reveals two other microRNA genes, MIR886 (hsa-mir-886) and MIR1975 (RNY5, hY5, hsa-mir-1975), which are genuine Pol III transcription units.

Improvement of therapeutic drug monitoring of imatinib by Bayesian prediction of trough levels. Personalized drug dosage

Aims: Plasma concentrations of imatinib differ largely between patients despite same dosage, owing to large inter-individual variability in pharmacokinetic (PK) parameters. As the drug concentration at the end of the dosage interval (Cmin) correlates with treatment response and tolerability, monitoring of Cmin is suggested for therapeutic drug monitoring (TDM) of imatinib. Due to logistic difficulties, random sampling during the dosage interval is however often performed in clinical practice, thus rendering the respective results not informative regarding Cmin values.Objectives: (I) To extrapolate randomly measured imatinib concentrations to more informative Cmin using classical Bayesian forecasting. (II) To extend the classical Bayesian method to account for correlation between PK parameters. (III) To evaluate the predictive performance of both methods.Methods: 31 paired blood samples (random and trough levels) were obtained from 19 cancer patients under imatinib. Two Bayesian maximum a posteriori (MAP) methods were implemented: (A) a classical method ignoring correlation between PK parameters, and (B) an extended one accounting for correlation. Both methods were applied to estimate individual PK parameters, conditional on random observations and covariate-adjusted priors from a population PK model. The PK parameter estimates were used to calculate trough levels. Relative prediction errors (PE) were analyzed to evaluate accuracy (one-sample t-test) and to compare precision between the methods (F-test to compare variances).Results: Both Bayesian MAP methods allowed non-biased predictions of individual Cmin compared to observations: (A) - 7% mean PE (CI95% - 18 to 4 %, p = 0.15) and (B) - 4% mean PE (CI95% - 18 to 10 %, p = 0.69). Relative standard deviations of actual observations from predictions were 22% (A) and 30% (B), i.e. comparable to the intraindividual variability reported. Precision was not improved by taking into account correlation between PK parameters (p = 0.22).Conclusion: Clinical interpretation of randomly measured imatinib concentrations can be assisted by Bayesian extrapolation to maximum likelihood Cmin. Classical Bayesian estimation can be applied for TDM without the need to include correlation between PK parameters. Both methods could be adapted in the future to evaluate other individual pharmacokinetic measures correlated to clinical outcomes, such as area under the curve(AUC).

Prediction of free imatinib concentrations based on total plasma concentrations in patients with gastrointestinal stromal tumours.

AIM: Total imatinib concentrations are currently measured for the therapeutic drug monitoring of imatinib, whereas only free drug equilibrates with cells for pharmacological action. Due to technical and cost limitations, routine measurement of free concentrations is generally not performed. In this study, free and total imatinib concentrations were measured to establish a model allowing the confident prediction of imatinib free concentrations based on total concentrations and plasma proteins measurements. METHODS: One hundred and fifty total and free plasma concentrations of imatinib were measured in 49 patients with gastrointestinal stromal tumours. A population pharmacokinetic model was built up to characterize mean total and free concentrations with inter-patient and intrapatient variability, while taking into account α1 -acid glycoprotein (AGP) and human serum albumin (HSA) concentrations, in addition to other demographic and environmental covariates. RESULTS: A one compartment model with first order absorption was used to characterize total and free imatinib concentrations. Only AGP influenced imatinib total clearance. Imatinib free concentrations were best predicted using a non-linear binding model to AGP, with a dissociation constant Kd of 319 ng ml(-1) , assuming a 1:1 molar binding ratio. The addition of HSA in the equation did not improve the prediction of imatinib unbound concentrations. CONCLUSION: Although free concentration monitoring is probably more appropriate than total concentrations, it requires an additional ultrafiltration step and sensitive analytical technology, not always available in clinical laboratories. The model proposed might represent a convenient approach to estimate imatinib free concentrations. However, therapeutic ranges for free imatinib concentrations remain to be established before it enters into routine practice.

Changes in D-serine levels and localization during postnatal development of the rat vestibular nuclei.

The patterns of development of the vestibular nuclei (VN) and their main connections involving glutamate neurotransmission offer a good model for studying the function of the glial-derived neuromodulator D-serine in synaptic plasticity. In this study we show that D-serine is present in the VN and we analyzed its distribution and the levels of expression of serine racemase and D-amino acid oxidase (D-AAO) at different stages of postnatal (P) development. From birth to P21, high levels of D-serine were detected in glial cells and processes in all parts of the VN. This period corresponded to high expression of serine racemase and low expression of D-AAO. On the other hand, in the mature VN D-serine displayed very low levels and was mainly localized in neuronal cell bodies and dendrites. This drop of D-serine in adult stages corresponded to an increasing expression of D-AAO at mature stages. High levels of glial D-serine during the first 3 weeks of postnatal development correspond to an intense period of plasticity and synaptogenesis and maturation of VN afferents, suggesting that D-serine could be involved in these phenomena. These results demonstrate for the first time that changes in D-serine levels and distribution occur during postnatal development in the central nervous system. The strong decrease of D-serine levels and the glial-to-neuronal switch suggests that D-serine may have distinct functional roles depending on the developmental stage of the vestibular network.

Prediction of cross-recognition of peptide-HLA A2 by Melan-A-specific cytotoxic T lymphocytes using three-dimensional quantitative structure-activity relationships.

The cross-recognition of peptides by cytotoxic T lymphocytes is a key element in immunology and in particular in peptide based immunotherapy. Here we develop three-dimensional (3D) quantitative structure-activity relationships (QSARs) to predict cross-recognition by Melan-A-specific cytotoxic T lymphocytes of peptides bound to HLA A*0201 (hereafter referred to as HLA A2). First, we predict the structure of a set of self- and pathogen-derived peptides bound to HLA A2 using a previously developed ab initio structure prediction approach [Fagerberg et al., J. Mol. Biol., 521-46 (2006)]. Second, shape and electrostatic energy calculations are performed on a 3D grid to produce similarity matrices which are combined with a genetic neural network method [So et al., J. Med. Chem., 4347-59 (1997)] to generate 3D-QSAR models. The models are extensively validated using several different approaches. During the model generation, the leave-one-out cross-validated correlation coefficient (q (2)) is used as the fitness criterion and all obtained models are evaluated based on their q (2) values. Moreover, the best model obtained for a partitioned data set is evaluated by its correlation coefficient (r = 0.92 for the external test set). The physical relevance of all models is tested using a functional dependence analysis and the robustness of the models obtained for the entire data set is confirmed using y-randomization. Finally, the validated models are tested for their utility in the setting of rational peptide design: their ability to discriminate between peptides that only contain side chain substitutions in a single secondary anchor position is evaluated. In addition, the predicted cross-recognition of the mono-substituted peptides is confirmed experimentally in chromium-release assays. These results underline the utility of 3D-QSARs in peptide mimetic design and suggest that the properties of the unbound epitope are sufficient to capture most of the information to determine the cross-recognition.

A combined computational and functional approach identifies new residues involved in pH-dependent gating of ASIC1a.

Acid-sensing ion channels (ASICs) are key receptors for extracellular protons. These neuronal nonvoltage-gated Na(+) channels are involved in learning, the expression of fear, neurodegeneration after ischemia, and pain sensation. We have applied a systematic approach to identify potential pH sensors in ASIC1a and to elucidate the mechanisms by which pH variations govern ASIC gating. We first calculated the pK(a) value of all extracellular His, Glu, and Asp residues using a Poisson-Boltzmann continuum approach, based on the ASIC three-dimensional structure, to identify candidate pH-sensing residues. The role of these residues was then assessed by site-directed mutagenesis and chemical modification, combined with functional analysis. The localization of putative pH-sensing residues suggests that pH changes control ASIC gating by protonation/deprotonation of many residues per subunit in different channel domains. Analysis of the function of residues in the palm domain close to the central vertical axis of the channel allowed for prediction of conformational changes of this region during gating. Our study provides a basis for the intrinsic ASIC pH dependence and describes an approach that can also be applied to the investigation of the mechanisms of the pH dependence of other proteins.

Cloning, functional expression, and chromosomal localization of the human pancreatic islet glucose-dependent insulinotropic polypeptide receptor.

Glucose-dependent insulinotropic polypeptide (GIP) is a hormone secreted by the endocrine K-cells from the duodenum that stimulates glucose-induced insulin secretion. Here, we present the molecular characterization of the human pancreatic islet GIP receptor. cDNA clones for the GIP receptor were isolated from a human pancreatic islet cDNA library. They encoded two different forms of the receptor, which differed by a 27-amino acid insertion in the COOH-terminal cytoplasmic tail. The receptor protein sequence was 81% identical to that of the rat GIP receptor. When expressed in Chinese hamster lung fibroblasts, both forms of the receptor displayed high-affinity binding for GIP (180 and 600 pmol/l). GIP binding was displaced by < 20% by 1 mumol/l glucagon, glucagon-like peptide (GLP-I)(7-36) amide, vasoactive intestinal peptide, and secretin. However exendin-4 and exendin-(9-39) at 1 mumol/l displaced binding by approximately 70 and approximately 100% at 10 mumol/l. GIP binding to both forms of the receptor induced a dose-dependent increase in intracellular cAMP levels (EC50 values of 0.6-0.8 nmol/l) but no elevation of cytoplasmic calcium concentrations. Interestingly, both exendin-4 and exendin-(9-39) were antagonists of the receptor, inhibiting GIP-induced cAMP formation by up to 60% when present at a concentration of 10 mumol/l. Finally, the physical and genetic chromosomal localization of the receptor gene was determined to be on 19q13.3, close to the ApoC2 gene. These data will help study the physiology and pathophysiology of the human GIP receptor.

Visualizing olfactory receptor expression and localization in Drosophila.

Odor detection and discrimination by olfactory systems in vertebrates and invertebrates depend both on the selective expression of individual olfactory receptor genes in subpopulations of olfactory sensory neurons, and on the targeting of the encoded proteins to the exposed, ciliated endings of sensory dendrites. Techniques to visualize the expression and localization of olfactory receptor gene products in vivo have been essential to reveal the molecular logic of peripheral odor coding and to permit investigation of the developmental and cellular neurobiology of this sensory system. Here, we describe methods for detection of olfactory receptor transcripts and proteins in the antennal olfactory organ of the fruit fly, Drosophila melanogaster, an important genetic model organism. We include protocols both for antennal cryosections and whole-mount antennae. These methods can be adapted for detection of receptor expression in other olfactory and gustatory tissues in Drosophila, as well as in the chemosensory systems of other insects.

Symptomatic intracranial hemorrhage after stroke thrombolysis: comparison of prediction scores.

BACKGROUND AND PURPOSE: Several prognostic scores have been developed to predict the risk of symptomatic intracranial hemorrhage (sICH) after ischemic stroke thrombolysis. We compared the performance of these scores in a multicenter cohort. METHODS: We merged prospectively collected data of patients with consecutive ischemic stroke who received intravenous thrombolysis in 7 stroke centers. We identified and evaluated 6 scores that can provide an estimate of the risk of sICH in hyperacute settings: MSS (Multicenter Stroke Survey); HAT (Hemorrhage After Thrombolysis); SEDAN (blood sugar, early infarct signs, [hyper]dense cerebral artery sign, age, NIH Stroke Scale); GRASPS (glucose at presentation, race [Asian], age, sex [male], systolic blood pressure at presentation, and severity of stroke at presentation [NIH Stroke Scale]); SITS (Safe Implementation of Thrombolysis in Stroke); and SPAN (stroke prognostication using age and NIH Stroke Scale)-100 positive index. We included only patients with available variables for all scores. We calculated the area under the receiver operating characteristic curve (AUC-ROC) and also performed logistic regression and the Hosmer-Lemeshow test. RESULTS: The final cohort comprised 3012 eligible patients, of whom 221 (7.3%) had sICH per National Institute of Neurological Disorders and Stroke, 141 (4.7%) per European Cooperative Acute Stroke Study II, and 86 (2.9%) per Safe Implementation of Thrombolysis in Stroke criteria. The performance of the scores assessed with AUC-ROC for predicting European Cooperative Acute Stroke Study II sICH was: MSS, 0.63 (95% confidence interval, 0.58-0.68); HAT, 0.65 (0.60-0.70); SEDAN, 0.70 (0.66-0.73); GRASPS, 0.67 (0.62-0.72); SITS, 0.64 (0.59-0.69); and SPAN-100 positive index, 0.56 (0.50-0.61). SEDAN had significantly higher AUC-ROC values compared with all other scores, except for GRASPS where the difference was nonsignificant. SPAN-100 performed significantly worse compared with other scores. The discriminative ranking of the scores was the same for the National Institute of Neurological Disorders and Stroke, and Safe Implementation of Thrombolysis in Stroke definitions, with SEDAN performing best, GRASPS second, and SPAN-100 worst. CONCLUSIONS: SPAN-100 had the worst predictive power, and SEDAN constantly the highest predictive power. However, none of the scores had better than moderate performance.

Evolution of a polymineralic mantle shear zone and the role of second phases in the localization of deformation

The influence of second phases (e.g., pyroxenes) on olivine grain size was studied by quantitative microfabric analyses of samples of the Hilti massif mantle shear zone (Semail ophiolite, Oman). The microstructures range from porphyroclastic tectonites to ultramylonites, from outside to the center of the shear zone. Starting at conditions of ridge-related flow, they formed under continuous cooling leading to progressive strain localization. The dependence of the average olivine grain size on the second-phase content can be split into a second-phase controlled and a dynamic recrystallization-controlled field. In the former, the olivine grain size is related to the ratio between the second-phase grain size and volume fraction (Zener parameter). In the latter, dynamic recrystallization manifested by a balance between grain growth and grain size reduction processes yields a stable olivine grain size. In both fields the average olivine and second-phase grain size decreases with decreasing temperature. Combining the microstructural information with deformation mechanism maps suggests that the porphyroclastic tectonites (similar to 1100 degrees C) and mylonites (similar to 800 degrees C) formed under the predominance of dislocation creep. Since olivine-rich layers are intercalated with layer parallel, polymineralic bands in the mylonites, nearly equiviscous conditions can be assumed. In the ultramylonites, diffusion creep represents the major deformation mechanism in the polymineralic layers. It is this switch in deformation mechanism from dislocation creep to diffusion creep that forces strain to localize in the fine-grained polymineralic domains at low temperatures (<similar to 700 degrees C), underlining the role of the second phases on strain localization in cooling mantle rocks.

Improvement of walking speed prediction by accelerometry and altimetry, validated by satellite positioning.

Activity monitors based on accelerometry are used to predict the speed and energy cost of walking at 0% slope, but not at other inclinations. Parallel measurements of body accelerations and altitude variation were studied to determine whether walking speed prediction could be improved. Fourteen subjects walked twice along a 1.3 km circuit with substantial slope variations (-17% to +17%). The parameters recorded were body acceleration using a uni-axial accelerometer, altitude variation using differential barometry, and walking speed using satellite positioning (DGPS). Linear regressions were calculated between acceleration and walking speed, and between acceleration/altitude and walking speed. These predictive models, calculated using the data from the first circuit run, were used to predict speed during the second circuit. Finally the predicted velocity was compared with the measured one. The result was that acceleration alone failed to predict speed (mean r = 0.4). Adding altitude variation improved the prediction (mean r = 0.7). With regard to the altitude/acceleration-speed relationship, substantial inter-individual variation was found. It is concluded that accelerometry, combined with altitude measurement, can assess position variations of humans provided inter-individual variation is taken into account. It is also confirmed that DGPS can be used for outdoor walking speed measurements, opening up new perspectives in the field of biomechanics.