Adaptive search and information updating in sequential mate choice

Classical treatments of problems of sequential mate choice assume that the distribution of the quality of potential mates is known a priori. This assumption, made for analytical purposes, may seem unrealistic, opposing empirical data as well as evolutionary arguments. Using stochastic dynamic programming, we develop a model that includes the possibility for searching individuals to learn about the distribution and in particular to update mean and variance during the search. In a constant environment, a priori knowledge of the parameter values brings strong benefits in both time needed to make a decision and average value of mate obtained. Knowing the variance yields more benefits than knowing the mean, and benefits increase with variance. However, the costs of learning become progressively lower as more time is available for choice. When parameter values differ between demes and/or searching periods, a strategy relying on fixed a priori information might lead to erroneous decisions, which confers advantages on the learning strategy. However, time for choice plays an important role as well: if a decision must be made rapidly, a fixed strategy may do better even when the fixed image does not coincide with the local parameter values. These results help in delineating the ecological-behavior context in which learning strategies may spread.

Transapical aortic valve implantation without angiography: proof of concept.

Background: Cardiac computed tomographic scans, coronary angiograms, and aortographies are routinely performed in transcatheter heart valve therapies. Consequently, all patients are exposed to multiple contrast injections with a following risk of nephrotoxicity and postoperative renal failure. The transapical aortic valve implantation without angiography can prevent contrast-related complications. Methods: Between November 2008 and November 2009, 30 consecutive high-risk patients (16 female, 53.3%) underwent transapical aortic valve implantation without angiography. The landmarks identification, the stent-valve positioning, and the postoperative control were routinely performed under transesophageal echocardiogram and fluoroscopic visualization without contrast injections. Results: Mean age was 80.1 +/- 8.7 years. Mean valve gradient, aortic orifice area, and ejection fraction were 60.3 +/- 20.9 mm Hg, 0.7 +/- 0.16 cm(2), and 0.526 +/- 0.128, respectively. Risk factors were pulmonary hypertension (60%), peripheral vascular disease (70%), chronic pulmonary disease (50%), previous cardiac surgery (13.3%), and chronic renal insufficiency (40%) (mean blood creatinine and urea levels: 96.8 +/- 54 mu g/dL and 8.45 +/- 5.15 mmol/L). Average European System for Cardiac Operative Risk Evaluation was 32.2 +/- 13.3%. Valve deployment in the ideal landing zone was 96.7% successful and valve embolization occurred once. Thirty-day mortality was 10% (3 patients). Causes of death were the following: intraoperative ventricular rupture (conversion to sternotomy), right ventricular failure, and bilateral pneumonia. Stroke occurred in one patient at postoperative day 9. Renal failure (postoperative mean blood creatinine and urea levels: 91.1 +/- 66.8 mu g/dL and 7.27 +/- 3.45 mmol/L), myocardial infarction, and atrioventricular block were not detected. Conclusions: Transapical aortic valve implantation without angiography requires a short learning curve and can be performed routinely by experienced teams. Our report confirms that this procedure is feasible and safe, and provides good results with low incidence of postoperative renal disorders. (Ann Thorac Surg 2010; 89: 1925-33) (C) 2010 by The Society of Thoracic Surgeons

Role of T-cell-mediated inflammation in psoriasis: pathogenesis and targeted therapy

Psoriasis is one of the most common chronic, inflammatory, T-cell-mediated autoimmune diseases. Over the past decade, increased knowledge of disease pathogenesis has fundamentally changed psoriasis treatment, with the introduction of biologics, and this has led to a multitude of improved selective targets providing potential therapeutic options. Indeed, numerous pathogenesis-based treatments are currently in development, as psoriasis has also become increasingly relevant for proof-of-concept studies. The purpose of this review was to summarize current knowledge of psoriasis immunopathogenesis, focusing on the T-cell-mediated immune response and its initiation. The authors describe recent advances in psoriasis treatment and discuss pathogenesis-based therapies that are currently in development or which could be envisioned for the future. Although current biologics are well tolerated, several issues such as long-term efficacy, long-term safety, and high costs keep driving the search for new and better therapies. With further advances in understanding disease pathogenesis, more genomic data from psoriasis patients becoming available, and potentially the identification of autoantigens in psoriasis, current research should lead to the development of a growing arsenal of improved targeted treatments and to further breakthrough immunotherapies.

Reverse transcription quantitative real-time polymerase chain reaction reference genes in the spared nerve injury model of neuropathic pain: validation and literature search.

BACKGROUND: The reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) is a widely used, highly sensitive laboratory technique to rapidly and easily detect, identify and quantify gene expression. Reliable RT-qPCR data necessitates accurate normalization with validated control genes (reference genes) whose expression is constant in all studied conditions. This stability has to be demonstrated.We performed a literature search for studies using quantitative or semi-quantitative PCR in the rat spared nerve injury (SNI) model of neuropathic pain to verify whether any reference genes had previously been validated. We then analyzed the stability over time of 7 commonly used reference genes in the nervous system - specifically in the spinal cord dorsal horn and the dorsal root ganglion (DRG). These were: Actin beta (Actb), Glyceraldehyde-3-phosphate dehydrogenase (GAPDH), ribosomal proteins 18S (18S), L13a (RPL13a) and L29 (RPL29), hypoxanthine phosphoribosyltransferase 1 (HPRT1) and hydroxymethylbilane synthase (HMBS). We compared the candidate genes and established a stability ranking using the geNorm algorithm. Finally, we assessed the number of reference genes necessary for accurate normalization in this neuropathic pain model. RESULTS: We found GAPDH, HMBS, Actb, HPRT1 and 18S cited as reference genes in literature on studies using the SNI model. Only HPRT1 and 18S had been once previously demonstrated as stable in RT-qPCR arrays. All the genes tested in this study, using the geNorm algorithm, presented gene stability values (M-value) acceptable enough for them to qualify as potential reference genes in both DRG and spinal cord. Using the coefficient of variation, 18S failed the 50% cut-off with a value of 61% in the DRG. The two most stable genes in the dorsal horn were RPL29 and RPL13a; in the DRG they were HPRT1 and Actb. Using a 0.15 cut-off for pairwise variations we found that any pair of stable reference gene was sufficient for the normalization process. CONCLUSIONS: In the rat SNI model, we validated and ranked Actb, RPL29, RPL13a, HMBS, GAPDH, HPRT1 and 18S as good reference genes in the spinal cord. In the DRG, 18S did not fulfill stability criteria. The combination of any two stable reference genes was sufficient to provide an accurate normalization.

Signal search analysis server.

Signal search analysis is a general method to discover and characterize sequence motifs that are positionally correlated with a functional site (e.g. a transcription or translation start site). The method has played an instrumental role in the analysis of eukaryotic promoter elements. The signal search analysis server provides access to four different computer programs as well as to a large number of precompiled functional site collections. The programs offered allow: (i) the identification of non-random sequence regions under evolutionary constraint; (ii) the detection of consensus sequence-based motifs that are over- or under-represented at a particular distance from a functional site; (iii) the analysis of the positional distribution of a consensus sequence- or weight matrix-based sequence motif around a functional site; and (iv) the optimization of a weight matrix description of a locally over-represented sequence motif. These programs can be accessed at: http://www.isrec.isb-sib.ch/ssa/.

Recent misconceptions about the "database search problem": a probabilistic analysis using Bayesian networks

This paper analyses and discusses arguments that emerge from a recent discussion about the proper assessment of the evidential value of correspondences observed between the characteristics of a crime stain and those of a sample from a suspect when (i) this latter individual is found as a result of a database search and (ii) remaining database members are excluded as potential sources (because of different analytical characteristics). Using a graphical probability approach (i.e., Bayesian networks), the paper here intends to clarify that there is no need to (i) introduce a correction factor equal to the size of the searched database (i.e., to reduce a likelihood ratio), nor to (ii) adopt a propositional level not directly related to the suspect matching the crime stain (i.e., a proposition of the kind 'some person in (outside) the database is the source of the crime stain' rather than 'the suspect (some other person) is the source of the crime stain'). The present research thus confirms existing literature on the topic that has repeatedly demonstrated that the latter two requirements (i) and (ii) should not be a cause of concern.

Genome-Wide Prediction Methods in Highly Diverse and Heterozygous Species: Proof-of-Concept through Simulation in Grapevine.

Nowadays, genome-wide association studies (GWAS) and genomic selection (GS) methods which use genome-wide marker data for phenotype prediction are of much potential interest in plant breeding. However, to our knowledge, no studies have been performed yet on the predictive ability of these methods for structured traits when using training populations with high levels of genetic diversity. Such an example of a highly heterozygous, perennial species is grapevine. The present study compares the accuracy of models based on GWAS or GS alone, or in combination, for predicting simple or complex traits, linked or not with population structure. In order to explore the relevance of these methods in this context, we performed simulations using approx 90,000 SNPs on a population of 3,000 individuals structured into three groups and corresponding to published diversity grapevine data. To estimate the parameters of the prediction models, we defined four training populations of 1,000 individuals, corresponding to these three groups and a core collection. Finally, to estimate the accuracy of the models, we also simulated four breeding populations of 200 individuals. Although prediction accuracy was low when breeding populations were too distant from the training populations, high accuracy levels were obtained using the sole core-collection as training population. The highest prediction accuracy was obtained (up to 0.9) using the combined GWAS-GS model. We thus recommend using the combined prediction model and a core-collection as training population for grapevine breeding or for other important economic crops with the same characteristics.

Internet use by patients with psychiatric disorders in search for general and medical informations

BACKGROUND: Internet is commonly used by the general population, notably for health information-seeking. There has been little research into its use by patients treated for a psychiatric disorder. AIM: To evaluate the use of internet by patients with psychiatric disorders in searching for general and medical information. METHODS: In 2007, 319 patients followed in a university hospital psychiatric out-patient clinic, completed a 28-items self-administered questionnaire. RESULTS: Two hundred patients surveyed were internet users. Most of them (68.5%) used internet in order to find health-related information. Only a small part of the patients knew and used criteria reflecting the quality of contents of the websites consulted. Knowledge of English and private Internet access were the factors significantly associated with the search of information on health on Internet. CONCLUSIONS: Internet is currently used by patients treated for psychiatric disorders, especially for medical seeking information.