Screening of MAMLD1 Mutations in 70 Children with 46,XY DSD: Identification and Functional Analysis of Two New Mutations

More than 50% of children with severe 46,XY disorders of sex development (DSD) do not have a definitive etiological diagnosis. Besides gonadal dysgenesis, defects in androgen biosynthesis, and abnormalities in androgen sensitivity, the Mastermind-like domain containing 1 (MAMLD1) gene, which was identified as critical for the development of male genitalia, may be implicated. The present study investigated whether MAMLD1 is implicated in cases of severe 46,XY DSD and whether routine sequencing of MAMLD1 should be performed in these patients

Mathematical methodology to obtain and compare different embryo scores

In Vitro Fertilization (IVF) units need to decrease multiple pregnancies without affecting their overall success rate. In this study we propose a mathematical model to evaluate an embryo’s potential ability to implant in the uterus. Embryos are graded by the embryologist based on the number of blastomeres, evenness of growth and degree of fragmentation. Therefore, the following variables were considered: number of blastomeres produced by division of the egg after fertilisation (blastomeres), symmetry and fragmentation of the embryo (grade). This model evaluates the embryos assigning them a score which represents their quality. The main result derived from this model is the estimation of the significant improvement in the implantation rate due to the increase in blastomere values and the decrease in grade factor values. But the increase from two–three to four produces more improvement in the implantation rate than two–three to five–six blastomeres. First, statistical models were used to study embryo traceability from transfer to implantation and to evaluate the effect of the quality of the embryos (embryo score) and women’s age on implantation potential. This score was obtained by making predictions from the fitted model which was used to rank embryos in terms of implantation potential. Then we totalled the scores of embryos that had been transferred to each woman for obtaining the Embryo Quality Index (EQI). In addition, we studied the effects of EQI and women’s age on pregnancy. Finally, statistical techniques such as Receiver Operating Characteristics (ROC) and bootstrap procedures were used to assess the accuracy of this model. This embryo score is a quick, efficient and accurate tool to optimise embryo selection for transfers on the second day after fertilisation. This tool is especially useful for transfers involving non-top embryos.This work was partially supported by a grant from the Generalitat Valenciana (grant no. GVPRE/2008/103). The research of AD and SC was partially supported by a grant from Ministerio de Asuntos Exteriores (grant no. A/023444/09) too. The authors are indebted to the anonymous referee whose comments and suggestions improved the paper considerably.Debón Aucejo, AM.; Molina Botella, MI.; Cabrera García, S.; Pellicer, A. (2013). Mathematical methodology to obtain and compare different embryo scores. Mathematical and Computer Modelling. 57(5-6):1380-1394. https://doi.org/10.1016/j.mcm.2012.11.027S13801394575-

Follicular fluid content and oocyte quality: from single biochemical markers to metabolomics

The assessment of oocyte quality in human in vitro fertilization (IVF) is getting increasing attention from embryologists. Oocyte selection and the identification of the best oocytes, in fact, would help to limit embryo overproduction and to improve the results of oocyte cryostorage programs. Follicular fluid (FF) is easily available during oocyte pick-up and theorically represents an optimal source on non-invasive biochemical predictors of oocyte quality. Unfortunately, however, the studies aiming to find a good molecular predictor of oocyte quality in FF were not able to identify substances that could be used as reliable markers of oocyte competence to fertilization, embryo development and pregnancy. In the last years, a well definite trend toward passing from the research of single molecular markers to more complex techniques that study all metabolites of FF has been observed. The metabolomic approach is a powerful tool to study biochemical predictors of oocyte quality in FF, but its application in this area is still at the beginning. This review provides an overview of the current knowledge about the biochemical predictors of oocyte quality in FF, describing both the results coming from studies on single biochemical markers and those deriving from the most recent studies of metabolomic

Relativistic Brownian Motion

Stimulated by experimental progress in high energy physics and astrophysics, the unification of relativistic and stochastic concepts has re-attracted considerable interest during the past decade. Focusing on the framework of special relativity, we review, here, recent progress in the phenomenological description of relativistic diffusion processes. After a brief historical overview, we will summarize basic concepts from the Langevin theory of nonrelativistic Brownian motions and discuss relevant aspects of relativistic equilibrium thermostatistics. The introductory parts are followed by a detailed discussion of relativistic Langevin equations in phase space. We address the choice of time parameters, discretization rules, relativistic fluctuation-dissipation theorems, and Lorentz transformations of stochastic differential equations. The general theory is illustrated through analytical and numerical results for the diffusion of free relativistic Brownian particles. Subsequently, we discuss how Langevin-type equations can be obtained as approximations to microscopic models. The final part of the article is dedicated to relativistic diffusion processes in Minkowski spacetime. Due to the finiteness of velocities in relativity, nontrivial relativistic Markov processes in spacetime do not exist; i.e., relativistic generalizations of the nonrelativistic diffusion equation and its Gaussian solutions must necessarily be non-Markovian. We compare different proposals that were made in the literature and discuss their respective benefits and drawbacks. The review concludes with a summary of open questions, which may serve as a starting point for future investigations and extensions of the theory.Comment: review article, 159 pages, references updated, misprints corrected, App. A.4. correcte

Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen

The effectiveness of most cancer targeted therapies is short-lived. Tumors often develop resistance that might be overcome with drug combinations. However, the number of possible combinations is vast, necessitating data-driven approaches to find optimal patient-specific treatments. Here we report AstraZeneca’s large drug combination dataset, consisting of 11,576 experiments from 910 combinations across 85 molecularly characterized cancer cell lines, and results of a DREAM Challenge to evaluate computational strategies for predicting synergistic drug pairs and biomarkers. 160 teams participated to provide a comprehensive methodological development and benchmarking. Winning methods incorporate prior knowledge of drug-target interactions. Synergy is predicted with an accuracy matching biological replicates for >60% of combinations. However, 20% of drug combinations are poorly predicted by all methods. Genomic rationale for synergy predictions are identified, including ADAM17 inhibitor antagonism when combined with PIK3CB/D inhibition contrasting to synergy when combined with other PI3K-pathway inhibitors in PIK3CA mutant cells.Peer reviewe

ICAR: endoscopic skull‐base surgery

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[Diagnosis and therapy of depression in the heart disease patient]

Even though depressions and depressive symptoms are frequently observed in patients with medical diseases, their psychological problems are often neither diagnosed nor treated. Diagnosis of mood state might be easy in isolated cases yet it often is not since the precise nature of normal mood cannot be expressed in quantitative terms. Furthermore, depression can only be diagnosed based on the doctor's clinical appraisal and the patient's own description of his/her complaints. There is no gold standard on which depressive symptoms can be based on--and further on, depression is not a diagnosis. Instead, it is a syndrome that calls for differential diagnoses before treatment can be offered. Diagnosing depressive comorbidity in patients with medical complaints is even more difficult because of the overlap between symptoms of depression and accompanying symptoms of the somatic illness e.g. lack of energy. Although depressive states have been known to be a risk factor for the prognosis of patients with coronary heart disease for a long time, there is a paucity of research about the therapy these patients undergo due to the fact that tricyclic anti-depressants can have cardiotoxic effects on patients with heart disease. The treatment of depression in these patients has become a much lower risk since the introduction of serotonin reuptake inhibitors. There is widespread evidence that depressive comorbidity has a negative impact on the prognosis of medical disorders. Despite the complex nature of diagnosing depression, proper diagnosis and treatment is increasingly important in internal medicine and especially cardiology