Parameterizing neural networks for disease classification

Neural networks are one option to implement decision support systems for health care applications. In this paper, we identify optimal settings of neural networks for medical diagnoses: The study involves the application of supervised machine learning using an artificial neural network to distinguish between gout and leukaemia patients. With the objective to improve the base accuracy (calculated from the initial set-up of the neural network model), several enhancements are analysed, such as the use of hyperbolic tangent activation function instead of the sigmoid function, the use of two hidden layers instead of one, and transforming the measurements with linear regression to obtain a smoothened data set. Another setting we study is the impact on the accuracy when using a data set of reduced size but with higher data quality. We also discuss the tradeoff between accuracy and runtime efficiency

The ASY-EOS experiment at GSI: investigating the symmetry energy at supra-saturation densities

The elliptic-flow ratio of neutrons with respect to protons in reactions of neutron rich heavy-ions systems at intermediate energies has been proposed as an observable sensitive to the strength of the symmetry term in the nuclear Equation Of State (EOS) at supra-saturation densities. The recent results obtained from the existing FOPI/LAND data for $^{197}$Au+$^{197}$Au collisions at 400 MeV/nucleon in comparison with the UrQMD model allowed a first estimate of the symmetry term of the EOS but suffer from a considerable statistical uncertainty. In order to obtain an improved data set for Au+Au collisions and to extend the study to other systems, a new experiment was carried out at the GSI laboratory by the ASY-EOS collaboration in May 2011.Comment: Talk given by P. Russotto at the 11th International Conference on Nucleus-Nucleus Collisions (NN2012), San Antonio, Texas, USA, May 27-June 1, 2012. To appear in the NN2012 Proceedings in Journal of Physics: Conference Series (JPCS

Clinical assessment of the physical activity pattern of chronic fatigue syndrome patients: a validation of three methods

Contains fulltext : 79568.pdf (publisher's version ) (Open Access)BACKGROUND: Effective treatment of chronic fatigue syndrome (CFS) with cognitive behavioural therapy (CBT) relies on a correct classification of so called 'fluctuating active' versus 'passive' patients. For successful treatment with CBT is it especially important to recognise the passive patients and give them a tailored treatment protocol. In the present study it was evaluated whether CFS patient's physical activity pattern can be assessed most accurately with the 'Activity Pattern Interview' (API), the International Physical Activity Questionnaire (IPAQ) or the CFS-Activity Questionnaire (CFS-AQ). METHODS: The three instruments were validated compared to actometers. Actometers are until now the best and most objective instrument to measure physical activity, but they are too expensive and time consuming for most clinical practice settings. In total 226 CFS patients enrolled for CBT therapy answered the API at intake and filled in the two questionnaires. Directly after intake they wore the actometer for two weeks. Based on receiver operating characteristic (ROC) curves the validity of the three methods were assessed and compared. RESULTS: Both the API and the two questionnaires had an acceptable validity (0.64 to 0.71). None of the three instruments was significantly better than the others. The proportion of false predictions was rather high for all three instrument. The IPAQ had the highest proportion of correct passive predictions (sensitivity 70.1%). CONCLUSION: The validity of all three instruments appeared to be fair, and all showed rather high proportions of false classifications. Hence in fact none of the tested instruments could really be called satisfactory. Because the IPAQ showed to be the best in correctly predicting 'passive' CFS patients, which is most essentially related to treatment results, it was concluded that the IPAQ is the preferable alternative for an actometer when treating CFS patients in clinical practice

Prediction of Preterm Deliveries from EHG Signals Using Machine Learning

There has been some improvement in the treatment of preterm infants, which has helped to increase their chance of survival. However, the rate of premature births is still globally increasing. As a result, this group of infants are most at risk of developing severe medical conditions that can affect the respiratory, gastrointestinal, immune, central nervous, auditory and visual systems. In extreme cases, this can also lead to long-term conditions, such as cerebral palsy, mental retardation, learning difficulties, including poor health and growth. In the US alone, the societal and economic cost of preterm births, in 2005, was estimated to be $26.2 billion, per annum. In the UK, this value was close to £2.95 billion, in 2009. Many believe that a better understanding of why preterm births occur, and a strategic focus on prevention, will help to improve the health of children and reduce healthcare costs. At present, most methods of preterm birth prediction are subjective. However, a strong body of evidence suggests the analysis of uterine electrical signals (Electrohysterography), could provide a viable way of diagnosing true labour and predict preterm deliveries. Most Electrohysterography studies focus on true labour detection during the final seven days, before labour. The challenge is to utilise Electrohysterography techniques to predict preterm delivery earlier in the pregnancy. This paper explores this idea further and presents a supervised machine learning approach that classifies term and preterm records, using an open source dataset containing 300 records (38 preterm and 262 term). The synthetic minority oversampling technique is used to oversample the minority preterm class, and cross validation techniques, are used to evaluate the dataset against other similar studies. Our approach shows an improvement on existing studies with 96% sensitivity, 90% specificity, and a 95% area under the curve value with 8% global error using the polynomial classifier

Hierarchy of nonhomologous end-joining, single-strand annealing and gene conversion at site-directed DNA double-strand breaks

In mammalian cells, DNA double-strand breaks (DSBs) are repaired by three pathways, nonhomologous end-joining (NHEJ), gene conversion (GC) and single-strand annealing (SSA). These pathways are distinct with regard to repair efficiency and mutagenic potential and must be tightly controlled to preserve viability and genomic stability. Here, we employed chromosomal reporter constructs to characterize the hierarchy of NHEJ, GC and SSA at a single I-SceI-induced DSB in Chinese hamster ovary cells. We discovered that the use of GC and SSA was increased by 6- to 8-fold upon loss of Ku80 function, suggesting that NHEJ is dominant over the other two pathways. However, NHEJ efficiency was not altered if GC was impaired by Rad51 knockdown. Interestingly, when SSA was made available as an alternative mode for DSB repair, loss of Rad51 function led to an increase in SSA activity at the expense of NHEJ, implying that Rad51 may indirectly promote NHEJ by limiting SSA. We conclude that a repair hierarchy exists to limit the access of the most mutagenic mechanism, SSA, to the break site. Furthermore, the cellular choice of repair pathways is reversible and can be influenced at the level of effector proteins such as Ku80 or Rad51

Genome-Wide Identification of Alternatively Spliced mRNA Targets of Specific RNA-Binding Proteins

BACKGROUND: Alternative splicing plays an important role in generating molecular and functional diversity in multi-cellular organisms. RNA binding proteins play crucial roles in modulating splice site choice. The majority of known binding sites for regulatory proteins are short, degenerate consensus sequences that occur frequently throughout the genome. This poses an important challenge to distinguish between functionally relevant sequences and a vast array of those occurring by chance. METHODOLOGY/PRINCIPAL FINDINGS: Here we have used a computational approach that combines a series of biological constraints to identify uridine-rich sequence motifs that are present within relevant biological contexts and thus are potential targets of the Drosophila master sex-switch protein Sex-lethal (SXL). This strategy led to the identification of one novel target. Moreover, our systematic analysis provides a starting point for the molecular and functional characterization of an additional target, which is dependent on SXL activity, either directly or indirectly, for regulation in a germline-specific manner. CONCLUSIONS/SIGNIFICANCE: This approach has successfully identified previously known, new, and potential SXL targets. Our analysis suggests that only a subset of potential SXL sites are regulated by SXL. Finally, this approach should be directly relevant to the large majority of splicing regulatory proteins for which bonafide targets are unknown

Comparative determination of HIV-1 co-receptor tropism by Enhanced Sensitivity Trofile, gp120 V3-loop RNA and DNA genotyping

BACKGROUND: Trofile is the prospectively validated HIV-1 tropism assay. Its use is limited by high costs, long turn-around time, and inability to test patients with very low or undetectable viremia. We aimed at assessing the efficiency of population genotypic assays based on gp120 V3-loop sequencing for the determination of tropism in plasma viral RNA and in whole-blood viral DNA. Contemporary and follow-up plasma and whole-blood samples from patients undergoing tropism testing via the enhanced sensitivity Trofile (ESTA) were collected. Clinical and clonal geno2pheno[coreceptor] (G2P) models at 10% and at optimised 5.7% false positive rate cutoff were evaluated using viral DNA and RNA samples, compared against each other and ESTA, using Cohen's kappa, phylogenetic analysis, and area under the receiver operating characteristic (AUROC). RESULTS: Both clinical and clonal G2P (with different false positive rates) showed good performances in predicting the ESTA outcome (for V3 RNA-based clinical G2P at 10% false positive rate AUROC = 0.83, sensitivity = 90%, specificity = 75%). The rate of agreement between DNA- and RNA-based clinical G2P was fair (kappa = 0.74, p < 0.0001), and DNA-based clinical G2P accurately predicted the plasma ESTA (AUROC = 0.86). Significant differences in the viral populations were detected when comparing inter/intra patient diversity of viral DNA with RNA sequences. CONCLUSIONS: Plasma HIV RNA or whole-blood HIV DNA V3-loop sequencing interpreted with clinical G2P is cheap and can be a good surrogate for ESTA. Although there may be differences among viral RNA and DNA populations in the same host, DNA-based G2P may be used as an indication of viral tropism in patients with undetectable plasma viremia

Isoscaling in central Sn+Sn collisions at 270 MeV/u

Experimental information on fragment emissions is important in understanding the dynamics of nuclear collisions and in the development of transport model simulating heavy-ion collisions. The composition of complex fragments emitted in the heavy-ion collisions can be explained by statistical models, which assume that thermal equilibrium is achieved at collision energies below 100 MeV/u. Our new experimental data together with theoretical analyses for light particles from Sn+Sn collisions at 270 MeV/u, suggest that the hypothesis of thermal equilibrium breaks down for particles emitted with high transfer momentum. To inspect the system's properties in such limit, the scaling features of the yield ratios of particles from two systems, a neutron-rich system of ${}^{132}\mathrm{Sn}+{}^{124}\mathrm{Sn}$ and a nearly symmetric system of ${}^{108}\mathrm{Sn}+{}^{112}\mathrm{Sn}$, are examined in the framework of the statistical multifragmentation model and the antisymmetrized molecular dynamics model. The isoscaling from low energy particles agree with both models. However the observed breakdown of isoscaling for particles with high transverse momentum cannot be explained by the antisymmetrized molecular dynamics model

Sex and the Single Cell. II. There Is a Time and Place for Sex

In both male and female Drosophila, only a subset of cells have the potential to sexually differentiate, making both males and females mosaics of sexually differentiated and sexually undifferentiated cells

Blood pressure-lowering effects of nifedipine/candesartan combinations in high-risk individuals: Subgroup analysis of the DISTINCT randomised trial

The DISTINCT study (reDefining Intervention with Studies Testing Innovative Nifedipine GITS - Candesartan Therapy) investigated the efficacy and safety of nifedipine GITS/candesartan cilexetil combinations vs respective monotherapies and placebo in patients with hypertension. This descriptive sub-analysis examined blood pressure (BP)-lowering effects in high-risk participants, including those with renal impairment (estimated glomerular filtration rate<90 ml min-1, n=422), type 2 diabetes mellitus (n=202), hypercholesterolaemia (n=206) and cardiovascular (CV) risk factors (n=971), as well as the impact of gender, age and body mass index (BMI). Participants with grade I/II hypertension were randomised to treatment with nifedipine GITS (N) 20, 30, 60 mg and/or candesartan cilexetil (C) 4, 8, 16, 32 mg or placebo for 8 weeks. Mean systolic BP and diastolic BP reductions after treatment in high-risk participants were greater, overall, with N/C combinations vs respective monotherapies or placebo, with indicators of a dose-response effect. Highest rates of BP control (ESH/ESC 2013 guideline criteria) were also achieved with highest doses of N/C combinations in each high-risk subgroup. The benefits of combination therapy vs monotherapy were additionally observed in patient subgroups categorised by gender, age or BMI. All high-risk participants reported fewer vasodilatory adverse events in the pooled N/C combination therapy than the N monotherapy group. In conclusion, consistent with the DISTINCT main study outcomes, high-risk participants showed greater reductions in BP and higher control rates with N/C combinations compared with respective monotherapies and lesser vasodilatory side-effects compared with N monotherapy