Low current and nadir CD4+ T-cell counts are associated with higher hepatitis C virus RNA levels in the Swiss HIV cohort study.

BACKGROUND: The aim of this study was to evaluate the effect of CD4+ T-cell counts and other characteristics of HIV-infected individuals on hepatitis C virus (HCV) RNA levels. METHODS: All HIV-HCV-coinfected Swiss HIV Cohort Study participants with available HCV RNA levels and concurrent CD4+ T-cell counts before starting HCV therapy were included. Potential predictors of HCV RNA levels were assessed by multivariate censored linear regression models that adjust for censored values. RESULTS: The study included 1,031 individuals. Low current and nadir CD4+ T-cell counts were significantly associated with higher HCV RNA levels (P = 0.004 and 0.001, respectively). In individuals with current CD4+ T-cell counts < 200/microl, median HCV RNA levels (6.22 log10 IU/ml) were +0.14 and +0.24 log10 IU/ml higher than those with CD4+ T-cell counts of 200-500/microl and > 500/microl. Based on nadir CD4+ T-cell counts, median HCV RNA levels (6.12 log10 IU/ml) in individuals with < 200/microl CD4+ T-cells were +0.06 and +0.44 log10 IU/ml higher than those with nadir T-cell counts of 200-500/microl and > 500/microl. Median HCV RNA levels were also significantly associated with HCV genotype: lower values were associated with genotype 4 and higher values with genotype 2, as compared with genotype 1. Additional significant predictors of lower HCV RNA levels were female gender and HIV transmission through male homosexual contacts. In multivariate analyses, only CD4+ T-cell counts and HCV genotype remained significant predictors of HCV RNA levels. Conclusions: Higher HCV RNA levels were associated with CD4+ T-cell depletion. This finding is in line with the crucial role of CD4+ T-cells in the control of HCV infection.

Directional and fluctuating asymmetry in finger and a-b ridge counts in psychosis: a case-control study

Background: Several studies have reported alterations in finger and a-b ridge counts, and theirderived measures of asymmetry, in schizophrenia compared to controls. Because ridges are fully formed by the end of the second trimester, they may provide clues to disturbed early development. The aim of this study was to assess these measures in a sample of patients with psychosis and normal controls.Methods: Individuals with psychosis (n = 240), and normal controls (n = 228) were drawn from a catchment-area case-control study. Differences in finger and a-b ridge count and Fluctuating Asymmetry were assessed in three group comparisons (non-affective psychosis versus controls; affective psychosis versus controls; non-affective psychosis versus affective psychosis). The analyses were performed separately for males and females. Results: There were no significant group differences for finger nor a-b ridge counts. While there were no group difference for Directional Asymmetry, for Fluctuating Asymmetry measures men with non-affective psychosis had significantly higher fluctuating asymmetry of the index finger ridge count (a) when compared to controls (FA-correlation score, p = 0.02), and (b) when compared to affective psychosis (adjusted FA-difference score, p = 0.04). Conclusion: Overall, measures of finger and a-b ridge counts, and their derived measures of directional and fluctuating asymmetry were not prominent features of psychosis in this sample. While directional asymmetry in cerebral morphology is reduced in schizophrenia, this is not reflected in dermatoglyphic variables.

Behavioral Measures and their Correlation with IPM Iteration Counts on Semi-Definite Programming Problems

We study four measures of problem instance behavior that might account for the observed differences in interior-point method (IPM) iterations when these methods are used to solve semidefinite programming (SDP) problem instances: (i) an aggregate geometry measure related to the primal and dual feasible regions (aspect ratios) and norms of the optimal solutions, (ii) the (Renegar-) condition measure C(d) of the data instance, (iii) a measure of the near-absence of strict complementarity of the optimal solution, and (iv) the level of degeneracy of the optimal solution. We compute these measures for the SDPLIB suite problem instances and measure the correlation between these measures and IPM iteration counts (solved using the software SDPT3) when the measures have finite values. Our conclusions are roughly as follows: the aggregate geometry measure is highly correlated with IPM iterations (CORR = 0.896), and is a very good predictor of IPM iterations, particularly for problem instances with solutions of small norm and aspect ratio. The condition measure C(d) is also correlated with IPM iterations, but less so than the aggregate geometry measure (CORR = 0.630). The near-absence of strict complementarity is weakly correlated with IPM iterations (CORR = 0.423). The level of degeneracy of the optimal solution is essentially uncorrelated with IPM iterations.

Bayesian tools for zero counts in compositional data

The log-ratio methodology makes available powerful tools for analyzing compositional data. Nevertheless, the use of this methodology is only possible for those data sets without null values. Consequently, in those data sets where the zeros are present, a previous treatment becomes necessary. Last advances in the treatment of compositional zeros have been centered especially in the zeros of structural nature and in the rounded zeros. These tools do not contemplate the particular case of count compositional data sets with null values. In this work we deal with \count zeros" and we introduce a treatment based on a mixed Bayesian-multiplicative estimation. We use the Dirichlet probability distribution as a prior and we estimate the posterior probabilities. Then we apply a multiplicative modi¯cation for the non-zero values. We present a case study where this new methodology is applied. Key words: count data, multiplicative replacement, composition, log-ratio analysis

What counts as response and intervention in RTI? : A sociocultural an??lisis

Resumen tomado de la publicaci??n

A Field Evaluation of the Time-of-Detection Method to Estimate Population Size and Density for Aural Avian Point Counts

The time-of-detection method for aural avian point counts is a new method of estimating abundance, allowing for uncertain probability of detection. The method has been specifically designed to allow for variation in singing rates of birds. It involves dividing the time interval of the point count into several subintervals and recording the detection history of the subintervals when each bird sings. The method can be viewed as generating data equivalent to closed capture–recapture information. The method is different from the distance and multiple-observer methods in that it is not required that all the birds sing during the point count. As this method is new and there is some concern as to how well individual birds can be followed, we carried out a field test of the method using simulated known populations of singing birds, using a laptop computer to send signals to audio stations distributed around a point. The system mimics actual aural avian point counts, but also allows us to know the size and spatial distribution of the populations we are sampling. Fifty 8-min point counts (broken into four 2-min intervals) using eight species of birds were simulated. Singing rate of an individual bird of a species was simulated following a Markovian process (singing bouts followed by periods of silence), which we felt was more realistic than a truly random process. The main emphasis of our paper is to compare results from species singing at (high and low) homogenous rates per interval with those singing at (high and low) heterogeneous rates. Population size was estimated accurately for the species simulated, with a high homogeneous probability of singing. Populations of simulated species with lower but homogeneous singing probabilities were somewhat underestimated. Populations of species simulated with heterogeneous singing probabilities were substantially underestimated. Underestimation was caused by both the very low detection probabilities of all distant individuals and by individuals with low singing rates also having very low detection probabilities.

Data assimilation: From photon counts to Earth System forecasts

Data assimilation – the set of techniques whereby information from observing systems and models is combined optimally – is rapidly becoming prominent in endeavours to exploit Earth Observation for Earth sciences, including climate prediction. This paper explains the broad principles of data assimilation, outlining different approaches (optimal interpolation, three-dimensional and four-dimensional variational methods, the Kalman Filter), together with the approximations that are often necessary to make them practicable. After pointing out a variety of benefits of data assimilation, the paper then outlines some practical applications of the exploitation of Earth Observation by data assimilation in the areas of operational oceanography, chemical weather forecasting and carbon cycle modelling. Finally, some challenges for the future are noted.

A novel variant on chromosome 7q22.3 associated with mean platelet volume, counts, and function

Mean platelet volume (MPV) and platelet count (PLT) are highly heritable and tightly regulated traits. We performed a genome-wide association study for MPV and identified one SNP, rs342293, as having highly significant and reproducible association with MPV (per-G allele effect 0.016 +/- 0.001 log fL; P < 1.08 x 10(-24)) and PLT (per-G effect -4.55 +/- 0.80 10(9)/L; P < 7.19 x 10(-8)) in 8586 healthy subjects. Whole-genome expression analysis in the 1-MB region showed a significant association with platelet transcript levels for PIK3CG (n = 35; P = .047). The G allele at rs342293 was also associated with decreased binding of annexin V to platelets activated with collagen-related peptide (n = 84; P = .003). The region 7q22.3 identifies the first QTL influencing platelet volume, counts, and function in healthy subjects. Notably, the association signal maps to a chromosome region implicated in myeloid malignancies, indicating this site as an important regulatory site for hematopoiesis. The identification of loci regulating MPV by this and other studies will increase our insight in the processes of megakaryopoiesis and proplatelet formation, and it may aid the identification of genes that are somatically mutated in essential thrombocytosis. (Blood. 2009; 113: 3831-3837)

Impact of duration thresholds on Atlantic tropical cyclone counts*

Records of Atlantic basin tropical cyclones (TCs) since the late nineteenth century indicate a very large upward trend in storm frequency. This increase in documented TCs has been previously interpreted as resulting from anthropogenic climate change. However, improvements in observing and recording practices provide an alternative interpretation for these changes: recent studies suggest that the number of potentially missed TCs is sufficient to explain a large part of the recorded increase in TC counts. This study explores the influence of another factor—TC duration—on observed changes in TC frequency, using a widely used Atlantic hurricane database (HURDAT). It is found that the occurrence of short-lived storms (duration of 2 days or less) in the database has increased dramatically, from less than one per year in the late nineteenth–early twentieth century to about five per year since about 2000, while medium- to long-lived storms have increased little, if at all. Thus, the previously documented increase in total TC frequency since the late nineteenth century in the database is primarily due to an increase in very short-lived TCs. The authors also undertake a sampling study based upon the distribution of ship observations, which provides quantitative estimates of the frequency of missed TCs, focusing just on the moderate to long-lived systems with durations exceeding 2 days in the raw HURDAT. Upon adding the estimated numbers of missed TCs, the time series of moderate to long-lived Atlantic TCs show substantial multidecadal variability, but neither time series exhibits a significant trend since the late nineteenth century, with a nominal decrease in the adjusted time series. Thus, to understand the source of the century-scale increase in Atlantic TC counts in HURDAT, one must explain the relatively monotonic increase in very short-duration storms since the late nineteenth century. While it is possible that the recorded increase in short-duration TCs represents a real climate signal, the authors consider that it is more plausible that the increase arises primarily from improvements in the quantity and quality of observations, along with enhanced interpretation techniques. These have allowed National Hurricane Center forecasters to better monitor and detect initial TC formation, and thus incorporate increasing numbers of very short-lived systems into the TC database.

Therapist characteristics and their effect on training outcomes: what counts?

Background: Evidence exists for a relationship between individual characteristics and both job and training performance; however relationships may not be generalizable. Little is known about the impact of therapist characteristics on performance in postgraduate therapist training programmes. Aims: The aim of this study was to investigate associations between the grades of trainee Low-Intensity and High-Intensity cognitive behavioural therapists and individual characteristics. Method: Trainee Low-Intensity (n=81) and High-Intensity (n=59) therapists completed measures of personality and cognitive ability; demographic and course grade data for participants were collected. Results: Degree classification emerged as the only variable to be significantly associated with performance across assessments and courses. Higher undergraduate degree classifications were associated with superior academic and clinical performance. Agreeableness was the only dimension of personality to be associated (positively) with clinical skill. Age was weakly and negatively associated with performance. Conclusions: Relationships between individual characteristics and training outcomes are complex and may be context specific. These results could have important implications for the selection and development of therapists for Low or High-Intensity cognitive behavioural therapy (CBT) training.

Effect of somatic cell counts on lipolysis, proteolysis and apparent viscosity of UHT milk during storage

In this work, lipolysis, proteolysis and viscosity of ultra-high temperature (UHT) milk containing different somatic cell counts (SCC) were investigated. UHT milks were analysed on days 8, 30, 60, 90 and 120 of storage. Lipolysis as measured by free fatty acids increase, casein degradation and viscosity of UHT milk were not affected by SCC but increased during storage. A negative relationship was observed between SCC and casein as a percentage of true protein on the 120th day of storage, hence indicating that high SCC increases the proteolysis of UHT milk by the end of its shelf life.

Beta-binomial/Poisson regression models for repeated bivariate counts

We analyze data obtained from a study designed to evaluate training effects on the performance of certain motor activities of Parkinson`s disease patients. Maximum likelihood methods were used to fit beta-binomial/Poisson regression models tailored to evaluate the effects of training on the numbers of attempted and successful specified manual movements in 1 min periods, controlling for disease stage and use of the preferred hand. We extend models previously considered by other authors in univariate settings to account for the repeated measures nature of the data. The results suggest that the expected number of attempts and successes increase with training, except for patients with advanced stages of the disease using the non-preferred hand. Copyright (c) 2008 John Wiley & Sons, Ltd.