Dental management considerations for the patient with an acquired coagulopathy. Part 1: Coagulopathies from systemic disease

Current teaching suggests that many patients are at risk for prolonged bleeding during and following invasive dental procedures, due to an acquired coagulopathy from systemic disease and/or from medications. However, treatment standards for these patients often are the result of long-standing dogma with little or no scientific basis. The medical history is critical for the identification of patients potentially at risk for prolonged bleeding from dental treatment. Some time-honoured laboratory tests have little or no use in community dental practice. Loss of functioning hepatic, renal, or bone marrow tissue predisposes to acquired coagulopathies through different mechanisms, but the relationship to oral haemostasis is poorly understood. Given the lack of established, science-based standards, proper dental management requires an understanding of certain principles of pathophysiology for these medical conditions and a few standard laboratory tests. Making changes in anticoagulant drug regimens are often unwarranted and/or expensive, and can put patients at far greater risk for morbidity and mortality than the unlikely outcome of postoperative bleeding. It should be recognised that prolonged bleeding is a rare event following invasive dental procedures, and therefore the vast majority of patients with suspected acquired coagulopathies are best managed in the community practice setting

Mouse models of neurodegenerative disease: preclinical imaging and neurovascular component.

Neurodegenerative diseases represent great challenges for basic science and clinical medicine because of their prevalence, pathologies, lack of mechanism-based treatments, and impacts on individuals. Translational research might contribute to the study of neurodegenerative diseases. The mouse has become a key model for studying disease mechanisms that might recapitulate in part some aspects of the corresponding human diseases. Neurode- generative disorders are very complicated and multifacto- rial. This has to be taken in account when testing drugs. Most of the drugs screening in mice are very di cult to be interpretated and often useless. Mouse models could be condiderated a ‘pathway models’, rather than as models for the whole complicated construct that makes a human disease. Non-invasive in vivo imaging in mice has gained increasing interest in preclinical research in the last years thanks to the availability of high-resolution single-photon emission computed tomography (SPECT), positron emission tomography (PET), high eld Magnetic resonance, Optical Imaging scanners and of highly speci c contrast agents. Behavioral test are useful tool to characterize di erent ani- mal models of neurodegenerative pathology. Furthermore, many authors have observed vascular pathological features associated to the di erent neurodegenerative disorders. Aim of this review is to focus on the di erent existing animal models of neurodegenerative disorders, describe behavioral tests and preclinical imaging techniques used for diagnose and describe the vascular pathological features associated to these diseases

Query Large Scale Microarray Compendium Datasets Using a Model-Based Bayesian Approach with Variable Selection

In microarray gene expression data analysis, it is often of interest to identify genes that share similar expression profiles with a particular gene such as a key regulatory protein. Multiple studies have been conducted using various correlation measures to identify co-expressed genes. While working well for small datasets, the heterogeneity introduced from increased sample size inevitably reduces the sensitivity and specificity of these approaches. This is because most co-expression relationships do not extend to all experimental conditions. With the rapid increase in the size of microarray datasets, identifying functionally related genes from large and diverse microarray gene expression datasets is a key challenge. We develop a model-based gene expression query algorithm built under the Bayesian model selection framework. It is capable of detecting co-expression profiles under a subset of samples/experimental conditions. In addition, it allows linearly transformed expression patterns to be recognized and is robust against sporadic outliers in the data. Both features are critically important for increasing the power of identifying co-expressed genes in large scale gene expression datasets. Our simulation studies suggest that this method outperforms existing correlation coefficients or mutual information-based query tools. When we apply this new method to the Escherichia coli microarray compendium data, it identifies a majority of known regulons as well as novel potential target genes of numerous key transcription factors

Evolutionary Determinants of Genetic Variation in Susceptibility to Infectious Diseases in Humans

Although genetic variation among humans in their susceptibility to infectious diseases has long been appreciated, little focus has been devoted to identifying patterns in levels of variation in susceptibility to different diseases. Levels of genetic variation in susceptibility associated with 40 human infectious diseases were assessed by a survey of studies on both pedigree-based quantitative variation, as well as studies on different classes of marker alleles. These estimates were correlated with pathogen traits, epidemiological characteristics, and effectiveness of the human immune response. The strongest predictors of levels of genetic variation in susceptibility were disease characteristics negatively associated with immune effectiveness. High levels of genetic variation were associated with diseases with long infectious periods and for which vaccine development attempts have been unsuccessful. These findings are consistent with predictions based on theoretical models incorporating fitness costs associated with the different types of resistance mechanisms. An appreciation of these observed patterns will be a valuable tool in directing future research given that genetic variation in disease susceptibility has large implications for vaccine development and epidemiology

A new method for class prediction based on signed-rank algorithms applied to Affymetrix® microarray experiments

<p>Abstract</p> <p>Background</p> <p>The huge amount of data generated by DNA chips is a powerful basis to classify various pathologies. However, constant evolution of microarray technology makes it difficult to mix data from different chip types for class prediction of limited sample populations. Affymetrix^®technology provides both a quantitative fluorescence signal and a decision (<it>detection call</it>: absent or present) based on signed-rank algorithms applied to several hybridization repeats of each gene, with a per-chip normalization. We developed a new prediction method for class belonging based on the detection call only from recent Affymetrix chip type. Biological data were obtained by hybridization on U133A, U133B and U133Plus 2.0 microarrays of purified normal B cells and cells from three independent groups of multiple myeloma (MM) patients.</p> <p>Results</p> <p>After a call-based data reduction step to filter out non class-discriminative probe sets, the gene list obtained was reduced to a predictor with correction for multiple testing by iterative deletion of probe sets that sequentially improve inter-class comparisons and their significance. The error rate of the method was determined using leave-one-out and 5-fold cross-validation. It was successfully applied to (i) determine a sex predictor with the normal donor group classifying gender with no error in all patient groups except for male MM samples with a Y chromosome deletion, (ii) predict the immunoglobulin light and heavy chains expressed by the malignant myeloma clones of the validation group and (iii) predict sex, light and heavy chain nature for every new patient. Finally, this method was shown powerful when compared to the popular classification method Prediction Analysis of Microarray (PAM).</p> <p>Conclusion</p> <p>This normalization-free method is routinely used for quality control and correction of collection errors in patient reports to clinicians. It can be easily extended to multiple class prediction suitable with clinical groups, and looks particularly promising through international cooperative projects like the "Microarray Quality Control project of US FDA" MAQC as a predictive classifier for diagnostic, prognostic and response to treatment. Finally, it can be used as a powerful tool to mine published data generated on Affymetrix systems and more generally classify samples with binary feature values.</p

Male Mating Rate Is Constrained by Seminal Fluid Availability in Bedbugs, Cimex lectularius

Sexual selection, differences in reproductive success between individuals, continues beyond acquiring a mating partner and affects ejaculate size and composition (sperm competition). Sperm and seminal fluid have very different roles in sperm competition but both components encompass production costs for the male. Theoretical models predict that males should spend ejaculate components prudently and differently for sperm and seminal fluid but empirical evidence for independent variation of sperm number and seminal fluid volume is scarce. It is also largely unknown how sperm and seminal fluid variation affect future mating rate. In bedbugs we developed a protocol to examine the role of seminal fluids in ejaculate allocation and its effect on future male mating rate. Using age-related changes in sperm and seminal fluid volume we estimated the lowest capacity at which mating activity started. We then showed that sexually active males allocate 12% of their sperm and 19% of their seminal fluid volume per mating and predicted that males would be depleted of seminal fluid but not of sperm. We tested (and confirmed) this prediction empirically. Finally, the slightly faster replenishment of seminal fluid compared to sperm did not outweigh the faster decrease during mating. Our results suggest that male mating rate can be constrained by the availability of seminal fluids. Our protocol might be applicable to a range of other organisms. We discuss the idea that economic considerations in sexual conflict research might benefit from distinguishing between costs and benefits that are ejaculate dose-dependent and those that are frequency-dependent on the mating rate per se

Optimization of Muscle Activity for Task-Level Goals Predicts Complex Changes in Limb Forces across Biomechanical Contexts

Optimality principles have been proposed as a general framework for understanding motor control in animals and humans largely based on their ability to predict general features movement in idealized motor tasks. However, generalizing these concepts past proof-of-principle to understand the neuromechanical transformation from task-level control to detailed execution-level muscle activity and forces during behaviorally-relevant motor tasks has proved difficult. In an unrestrained balance task in cats, we demonstrate that achieving task-level constraints center of mass forces and moments while minimizing control effort predicts detailed patterns of muscle activity and ground reaction forces in an anatomically-realistic musculoskeletal model. Whereas optimization is typically used to resolve redundancy at a single level of the motor hierarchy, we simultaneously resolved redundancy across both muscles and limbs and directly compared predictions to experimental measures across multiple perturbation directions that elicit different intra- and interlimb coordination patterns. Further, although some candidate task-level variables and cost functions generated indistinguishable predictions in a single biomechanical context, we identified a common optimization framework that could predict up to 48 experimental conditions per animal (n = 3) across both perturbation directions and different biomechanical contexts created by altering animals' postural configuration. Predictions were further improved by imposing experimentally-derived muscle synergy constraints, suggesting additional task variables or costs that may be relevant to the neural control of balance. These results suggested that reduced-dimension neural control mechanisms such as muscle synergies can achieve similar kinetics to the optimal solution, but with increased control effort (≈2×) compared to individual muscle control. Our results are consistent with the idea that hierarchical, task-level neural control mechanisms previously associated with voluntary tasks may also be used in automatic brainstem-mediated pathways for balance

Effect of leaving chronic oral foci untreated on infectious complications during intensive chemotherapy

BACKGROUND: Leukaemic patients receiving intensive chemotherapy and patients undergoing autologous stem-cell transplantation (ASCT) are routinely screened for oral foci of infection to reduce infectious complications that could occur during therapy. In this prospective study we assessed the effect of leaving chronic oral foci of infection untreated on the development of infectious complications in intensively treated haematological patients. METHODS: We included and prospectively evaluated all intensively treated leukaemic patients and patients undergoing ASCT who were referred to our medical centre between September 2012 and May 2014, and who matched the inclusion/exclusion criteria. Acute oral foci of infection were removed before chemotherapy or ASCT, whereas chronic oral foci were left untreated. RESULTS: In total 28 leukaemic and 35 ASCT patients were included. Acute oral foci of infection were found in 2 leukaemic (7%) and 2 ASCT patients (6%), and chronic oral foci of infection in 24 leukaemic (86%) and 22 ASCT patients (63%). Positive blood cultures with microorganisms potentially originating from the oral cavity occurred in 7 patients during treatment, but were uneventful on development of infectious complications. CONCLUSIONS: Our prospective study supports the hypothesis that chronic oral foci of infection can be left untreated as this does not increase infectious complications during intensive chemotherapy.British Journal of Cancer advance online publication, 22 March 2016; doi:10.1038/bjc.2016.60 www.bjcancer.com