A comparison of methods for differential expression analysis of RNA-seq data.

BACKGROUND: Finding genes that are differentially expressed between conditions is an integral part of understanding the molecular basis of phenotypic variation. In the past decades, DNA microarrays have been used extensively to quantify the abundance of mRNA corresponding to different genes, and more recently high-throughput sequencing of cDNA (RNA-seq) has emerged as a powerful competitor. As the cost of sequencing decreases, it is conceivable that the use of RNA-seq for differential expression analysis will increase rapidly. To exploit the possibilities and address the challenges posed by this relatively new type of data, a number of software packages have been developed especially for differential expression analysis of RNA-seq data. RESULTS: We conducted an extensive comparison of eleven methods for differential expression analysis of RNA-seq data. All methods are freely available within the R framework and take as input a matrix of counts, i.e. the number of reads mapping to each genomic feature of interest in each of a number of samples. We evaluate the methods based on both simulated data and real RNA-seq data. CONCLUSIONS: Very small sample sizes, which are still common in RNA-seq experiments, impose problems for all evaluated methods and any results obtained under such conditions should be interpreted with caution. For larger sample sizes, the methods combining a variance-stabilizing transformation with the 'limma' method for differential expression analysis perform well under many different conditions, as does the nonparametric SAMseq method.

Uncertainty Quantification with Support Vector Regression Prediction Models

Uncertainty quantification of petroleum reservoir models is one of the present challenges, which is usually approached with a wide range of geostatistical tools linked with statistical optimisation or/and inference algorithms. The paper considers a data driven approach in modelling uncertainty in spatial predictions. Proposed semi-supervised Support Vector Regression (SVR) model has demonstrated its capability to represent realistic features and describe stochastic variability and non-uniqueness of spatial properties. It is able to capture and preserve key spatial dependencies such as connectivity, which is often difficult to achieve with two-point geostatistical models. Semi-supervised SVR is designed to integrate various kinds of conditioning data and learn dependences from them. A stochastic semi-supervised SVR model is integrated into a Bayesian framework to quantify uncertainty with multiple models fitted to dynamic observations. The developed approach is illustrated with a reservoir case study. The resulting probabilistic production forecasts are described by uncertainty envelopes.

Measures of health and disease in Africa: are current methods giving us useful information about trends in cardiovascular diseases?

An enormous burst of interest in the public health burden from chronic disease in Africa has emerged as a consequence of efforts to estimate global population health. Detailed estimates are now published for Africa as a whole and each country on the continent. These data have formed the basis for warnings about sharp increases in cardiovascular disease (CVD) in the coming decades. In this essay we briefly examine the trajectory of social development on the continent and its consequences for the epidemiology of CVD and potential control strategies. Since full vital registration has only been implemented in segments of South Africa and the island nations of Seychelles and Mauritius - formally part of WHO-AFRO - mortality data are extremely limited. Numerous sample surveys have been conducted but they often lack standardization or objective measures of health status. Trend data are even less informative. However, using the best quality data available, age-standardized trends in CVD are downward, and in the case of stroke, sharply so. While acknowledging that the extremely limited available data cannot be used as the basis for inference to the continent, we raise the concern that general estimates based on imputation to fill in the missing mortality tables may be even more misleading. No immediate remedies to this problem can be identified, however bilateral collaborative efforts to strength local educational institutions and governmental agencies rank as the highest priority for near term development.

Long-term cognitive profile and incidence of dementia after STN-DBS in Parkinson's disease

An effect of subthalamic nucleus deep brain stimulation (STN-DBS) on cognition has been suspected but long-term observations are lacking. The aim of this study was to evaluate the long-term cognitive profile and the incidence of dementia in a cohort of Parkinson's disease (PD) patients treated by STN-DBS. 57 consecutive patients were prospectively assessed by the mean of a neuropsychological battery over 3 years after surgery. Dementia (DSM-IV) and UPDRS I to IV were recorded. 24.5% of patients converted to dementia over 3 years (incidence of 89 of 1,000 per year). This group of patients cognitively continuously worsened over 3 years up to fulfilling dementia criteria (PDD). The rest of the cohort remained cognitively stable (PD) over the whole follow-up. Preoperative differences between PDD and PD included older age (69.2 +/- 5.8 years; 62.6 +/- 8 years), presence of hallucinations and poorer executive score (10.1 +/- 5.9; 5.5 +/- 4.4). The incidence of dementia over 3 years after STN-DBS is similar to the one reported in medically treated patients. The PDD presented preoperative risk factors of developing dementia similar to those described in medically treated patients. These observations suggest dementia being secondary to the natural evolution of PD rather than a direct effect of STN-DBS.

Visual activity predicts auditory recovery from deafness after adult cochlear implantation.

Modern cochlear implantation technologies allow deaf patients to understand auditory speech; however, the implants deliver only a coarse auditory input and patients must use long-term adaptive processes to achieve coherent percepts. In adults with post-lingual deafness, the high progress of speech recovery is observed during the first year after cochlear implantation, but there is a large range of variability in the level of cochlear implant outcomes and the temporal evolution of recovery. It has been proposed that when profoundly deaf subjects receive a cochlear implant, the visual cross-modal reorganization of the brain is deleterious for auditory speech recovery. We tested this hypothesis in post-lingually deaf adults by analysing whether brain activity shortly after implantation correlated with the level of auditory recovery 6 months later. Based on brain activity induced by a speech-processing task, we found strong positive correlations in areas outside the auditory cortex. The highest positive correlations were found in the occipital cortex involved in visual processing, as well as in the posterior-temporal cortex known for audio-visual integration. The other area, which positively correlated with auditory speech recovery, was localized in the left inferior frontal area known for speech processing. Our results demonstrate that the visual modality's functional level is related to the proficiency level of auditory recovery. Based on the positive correlation of visual activity with auditory speech recovery, we suggest that visual modality may facilitate the perception of the word's auditory counterpart in communicative situations. The link demonstrated between visual activity and auditory speech perception indicates that visuoauditory synergy is crucial for cross-modal plasticity and fostering speech-comprehension recovery in adult cochlear-implanted deaf patients.

The effects of dominance, regular inbreeding and sampling design on Q(ST), an estimator of population differentiation for quantitative traits.

To test whether quantitative traits are under directional or homogenizing selection, it is common practice to compare population differentiation estimates at molecular markers (F(ST)) and quantitative traits (Q(ST)). If the trait is neutral and its determinism is additive, then theory predicts that Q(ST) = F(ST), while Q(ST) > F(ST) is predicted under directional selection for different local optima, and Q(ST) < F(ST) is predicted under homogenizing selection. However, nonadditive effects can alter these predictions. Here, we investigate the influence of dominance on the relation between Q(ST) and F(ST) for neutral traits. Using analytical results and computer simulations, we show that dominance generally deflates Q(ST) relative to F(ST). Under inbreeding, the effect of dominance vanishes, and we show that for selfing species, a better estimate of Q(ST) is obtained from selfed families than from half-sib families. We also compare several sampling designs and find that it is always best to sample many populations (>20) with few families (five) rather than few populations with many families. Provided that estimates of Q(ST) are derived from individuals originating from many populations, we conclude that the pattern Q(ST) > F(ST), and hence the inference of directional selection for different local optima, is robust to the effect of nonadditive gene actions.

Macrophage migration inhibitory factor deficiency leads to age-dependent impairment of glucose homeostasis in mice.

Macrophage migration inhibitory factor (MIF) is a proinflammatory cytokine produced by many cells and tissues including pancreatic beta-cells, liver, skeletal muscle, and adipocytes. This study investigates the potential role of MIF in carbohydrate homeostasis in a physiological setting outside of severe inflammation, utilizing Mif knockout (MIF-/-) mice. Compared with wild-type (WT) mice, MIF-/- mice had a lower body weight, from birth until 4 months of age, but subsequently gained weight faster, resulting in a higher body weight at 12 months of age. The lower weight in young mice was related to a higher energy expenditure, and the higher weight in older mice was related to an increased food intake and a higher fat mass. Fasting blood insulin level was higher in MIF-/- mice compared with WT mice at any age. After i.p. glucose injection, the elevation of blood insulin level was higher in MIF-/- mice compared with WT mice, at 2 months of age, but was lower in 12-month-old MIF-/- mice. As a result, the glucose clearance during intraperitoneal glucose tolerance tests was higher in MIF-/- mice compared with WT mice until 4 months of age, and was lower in 12-month-old MIF-/- mice. Insulin resistance was estimated (euglycemic-hyperinsulinemic clamp tests), and the phosphorylation activity of AKT was similar in MIF-/- mice and WT mice. In conclusion, this mouse model provides evidence for the role of MIF in the control of glucose homeostasis.

The abrupt climate change at the Eocene-Oligocene boundary and the emergence of South-East Asia triggered the spread of sapindaceous lineages.

Background and Aims Paleoclimatic data indicate that an abrupt climate change occurred at the Eocene-Oligocene (E-O) boundary affecting the distribution of tropical forests on Earth. The same period has seen the emergence of South-East (SE) Asia, caused by the collision of the Eurasian and Australian plates. How the combination of these climatic and geomorphological factors affected the spatio-temporal history of angiosperms is little known. This topic is investigated by using the worldwide sapindaceous clade as a case study. Methods Analyses of divergence time inference, diversification and biogeography (constrained by paleogeography) are applied to a combined plastid and nuclear DNA sequence data set. Biogeographical and diversification analyses are performed over a set of trees to take phylogenetic and dating uncertainty into account. Results are analysed in the context of past climatic fluctuations. Key Results An increase in the number of dispersal events at the E-O boundary is recorded, which intensified during the Miocene. This pattern is associated with a higher rate in the emergence of new genera. These results are discussed in light of the geomorphological importance of SE Asia, which acted as a tropical bridge allowing multiple contacts between areas and additional speciation across landmasses derived from Laurasia and Gondwana. Conclusions This study demonstrates the importance of the combined effect of geomorphological (the emergence of most islands in SE Asia approx. 30 million years ago) and climatic (the dramatic E-O climate change that shifted the tropical belt and reduced sea levels) factors in shaping species distribution within the sapindaceous clade.

Evaluation of the potential use of trabecular bone score to complement bone mineral density in the diagnosis of osteoporosis: a preliminary spine BMD-matched, case-control study.

The trabecular bone score (TBS) is a new parameter that is determined from gray-level analysis of dual-energy X-ray absorptiometry (DXA) images. It relies on the mean thickness and volume fraction of trabecular bone microarchitecture. This was a preliminary case-control study to evaluate the potential diagnostic value of TBS as a complement to bone mineral density (BMD), by comparing postmenopausal women with and without fractures. The sample consisted of 45 women with osteoporotic fractures (5 hip fractures, 20 vertebral fractures, and 20 other types of fracture) and 155 women without a fracture. Stratification was performed, taking into account each type of fracture (except hip), and women with and without fractures were matched for age and spine BMD. BMD and TBS were measured at the total spine. TBS measured at the total spine revealed a significant difference between the fracture and age- and spine BMD-matched nonfracture group, when considering all types of fractures and vertebral fractures. In these cases, the diagnostic value of the combination of BMD and TBS likely will be higher compared with that of BMD alone. TBS, as evaluated from standard DXA scans directly, potentially complements BMD in the detection of osteoporotic fractures. Prospective studies are necessary to fully evaluate the potential role of TBS as a complementary risk factor for fracture.

Correction for heart rate variability during 3D whole heart MR coronary angiography.

PURPOSE: To evaluate the effect of a real-time adaptive trigger delay on image quality to correct for heart rate variability in 3D whole-heart coronary MR angiography (MRA). MATERIALS AND METHODS: Twelve healthy adults underwent 3D whole-heart coronary MRA with and without the use of an adaptive trigger delay. The moment of minimal coronary artery motion was visually determined on a high temporal resolution MRI. Throughout the scan performed without adaptive trigger delay, trigger delay was kept constant, whereas during the scan performed with adaptive trigger delay, trigger delay was continuously updated after each RR-interval using physiological modeling. Signal-to-noise, contrast-to-noise, vessel length, vessel sharpness, and subjective image quality were compared in a blinded manner. RESULTS: Vessel sharpness improved significantly for the middle segment of the right coronary artery (RCA) with the use of the adaptive trigger delay (52.3 +/- 7.1% versus 48.9 +/- 7.9%, P = 0.026). Subjective image quality was significantly better in the middle segments of the RCA and left anterior descending artery (LAD) when the scan was performed with adaptive trigger delay compared to constant trigger delay. CONCLUSION: Our results demonstrate that the use of an adaptive trigger delay to correct for heart rate variability improves image quality mainly in the middle segments of the RCA and LAD.

Gastric banding interferes with esophageal motility and gastroesophageal reflux.

BACKGROUND: Gastroesophageal reflux and progressive esophageal dilatation can develop after gastric banding (GB). HYPOTHESIS: Gastric banding may interfere with esophageal motility, enhance reflux, or promote esophageal dilatation. DESIGN: Before-after trial in patients undergoing GB. SETTING: University teaching hospital. PATIENTS AND METHODS: Between January 1999 and August 2002, 43 patients undergoing laparoscopic GB for morbid obesity underwent upper gastrointestinal endoscopy, 24-hour pH monitoring, and stationary esophageal manometry before GB and between 6 and 18 months postoperatively. MAIN OUTCOME MEASURES: Reflux symptoms, endoscopic esophagitis, pressures measured at manometry, esophageal acid exposure. RESULTS: There was no difference in the prevalence of reflux symptoms or esophagitis before and after GB. The lower esophageal sphincter was unaffected by surgery, but contractions in the lower esophagus weakened after GB, in correlation with preoperative values. There was a trend toward more postoperative nonspecific motility disorders. Esophageal acid exposure tended to decrease after GB, with fewer reflux episodes. A few patients developed massive postoperative reflux. There was no clear correlation between preoperative testing and postoperative esophageal acid exposure, although patients with abnormal preoperative acid exposure tended to maintain high values after GB. CONCLUSIONS: Postoperative esophageal dysmotility and gastroesophageal reflux are not uncommon after GB. Preoperative testing should be done routinely. Low amplitude of contraction in the lower esophagus and increased esophageal acid exposure should be regarded as contraindications to GB. Patients with such findings should be offered an alternative procedure, such as Roux-en-Y gastric bypass.

Quality of care and survival of haemodialysed patients in western Switzerland.

BACKGROUND: Many factors affect survival in haemodialysis (HD) patients. Our aim was to study whether quality of clinical care may affect survival in this population, when adjusted for demographic characteristics and co-morbidities. METHODS: We studied survival in 553 patients treated by chronic HD during March 2001 in 21 dialysis facilities in western Switzerland. Indicators of quality of care were established for anaemia control, calcium and phosphate product, serum albumin, pre-dialysis blood pressure (BP), type of vascular access and dialysis adequacy (spKt/V) and their baseline values were related to 3-year survival. The modified Charlson co-morbidity index (including age) and transplantation status were also considered as a predictor of survival. RESULTS: Three-year survival was obtained for 96% of the patients; 39% (211/541) of these patients had died. The 3-year survival was 50, 62 and 69%, respectively, in patients who had 0-2, 3 and >or=4 fulfilled indicators of quality of care (test for linear trend, P < 0.001). In a Cox multivariate analysis model, the absence of transplantation, a higher modified Charlson's score, decreased fulfilment of indicators of good clinical care and low pre-dialysis systolic BP were independent predictors of death. CONCLUSION: Good clinical care improves survival in HD patients, even after adjustment for availability of transplantation and co-morbidities.

On the use of IRMS in forensic science: proposals for a methodological approach

The flourishing number of publications on the use of isotope ratio mass spectrometry (IRMS) in forensic science denotes the enthusiasm and the attraction generated by this technology. IRMS has demonstrated its potential to distinguish chemically identical compounds coming from different sources. Despite the numerous applications of IRMS to a wide range of forensic materials, its implementation in a forensic framework is less straightforward than it appears. In addition, each laboratory has developed its own strategy of analysis on calibration, sequence design, standards utilisation and data treatment without a clear consensus.Through the experience acquired from research undertaken in different forensic fields, we propose a methodological framework of the whole process using IRMS methods. We emphasize the importance of considering isotopic results as part of a whole approach, when applying this technology to a particular forensic issue. The process is divided into six different steps, which should be considered for a thoughtful and relevant application. The dissection of this process into fundamental steps, further detailed, enables a better understanding of the essential, though not exhaustive, factors that have to be considered in order to obtain results of quality and sufficiently robust to proceed to retrospective analyses or interlaboratory comparisons.

Analysis, modelling and classification of geospatial data using machine learning

The research considers the problem of spatial data classification using machine learning algorithms: probabilistic neural networks (PNN) and support vector machines (SVM). As a benchmark model simple k-nearest neighbor algorithm is considered. PNN is a neural network reformulation of well known nonparametric principles of probability density modeling using kernel density estimator and Bayesian optimal or maximum a posteriori decision rules. PNN is well suited to problems where not only predictions but also quantification of accuracy and integration of prior information are necessary. An important property of PNN is that they can be easily used in decision support systems dealing with problems of automatic classification. Support vector machine is an implementation of the principles of statistical learning theory for the classification tasks. Recently they were successfully applied for different environmental topics: classification of soil types and hydro-geological units, optimization of monitoring networks, susceptibility mapping of natural hazards. In the present paper both simulated and real data case studies (low and high dimensional) are considered. The main attention is paid to the detection and learning of spatial patterns by the algorithms applied.

The evolutionary host switches of Polychromophilus: a multi-gene phylogeny of the bat malaria genus suggests a second invasion of mammals by a haemosporidian parasite.

BACKGROUND: The majority of Haemosporida species infect birds or reptiles, but many important genera, including Plasmodium, infect mammals. Dipteran vectors shared by avian, reptilian and mammalian Haemosporida, suggest multiple invasions of Mammalia during haemosporidian evolution; yet, phylogenetic analyses have detected only a single invasion event. Until now, several important mammal-infecting genera have been absent in these analyses. This study focuses on the evolutionary origin of Polychromophilus, a unique malaria genus that only infects bats (Microchiroptera) and is transmitted by bat flies (Nycteribiidae). METHODS: Two species of Polychromophilus were obtained from wild bats caught in Switzerland. These were molecularly characterized using four genes (asl, clpc, coI, cytb) from the three different genomes (nucleus, apicoplast, mitochondrion). These data were then combined with data of 60 taxa of Haemosporida available in GenBank. Bayesian inference, maximum likelihood and a range of rooting methods were used to test specific hypotheses concerning the phylogenetic relationships between Polychromophilus and the other haemosporidian genera. RESULTS: The Polychromophilus melanipherus and Polychromophilus murinus samples show genetically distinct patterns and group according to species. The Bayesian tree topology suggests that the monophyletic clade of Polychromophilus falls within the avian/saurian clade of Plasmodium and directed hypothesis testing confirms the Plasmodium origin. CONCLUSION: Polychromophilus' ancestor was most likely a bird- or reptile-infecting Plasmodium before it switched to bats. The invasion of mammals as hosts has, therefore, not been a unique event in the evolutionary history of Haemosporida, despite the suspected costs of adapting to a new host. This was, moreover, accompanied by a switch in dipteran host.