Genetic diversity in an indigenous horse breed: implications for mating strategies and the control of future inbreeding

The Franches-Montagnes is an indigenous Swiss horse breed, with approximately 2500 foalings per year. The stud book is closed, and no introgression from other horse breeds was conducted since 1998. Since 2006, breeding values for 43 different traits (conformation, performance and coat colour) are estimated with a best linear unbiased prediction (BLUP) multiple trait animal model. In this study, we evaluated the genetic diversity for the breeding population, considering the years from 2003 to 2008. Only horses with at least one progeny during that time span were included. Results were obtained based on pedigree information as well as from molecular markers. A series of software packages were screened to combine best the best linear unbiased prediction (BLUP) methodology with optimal genetic contribution theory. We looked for stallions with highest breeding values and lowest average relationship to the dam population. Breeding with such stallions is expected to lead to a selection gain, while lowering the future increase in inbreeding within the breed.

Telomeres and prognosis in patients with chronic lymphocytic leukaemia

In the present study, telomere length, telomerase activity, the mutation load of immunoglobulin variable heavy chain (IGHV) genes, and established prognostic factors were investigated in 78 patients with chronic lymphocytic leukaemia (CLL) to determine the impact of telomere biology on the pathogenesis of CLL. Telomere length was measured by an automated multi-colour flow-FISH, and an age-independent delta telomere length ( TL) was calculated. CLL with unmutated IGHV genes was associated with shorter telomeres (p = 0.002). Furthermore, we observed a linear correlation between the frequency of IGHV gene mutations and elongation of telomeres (r = 0.509, p < 0.001). With respect to prognosis, a threshold TL of -4.2 kb was the best predictor for progression-free and overall survival. TL was not significantly altered over time or with therapy. The correlation between the mutational load in IGHV genes and the TL in CLL might reflect the initial telomere length of the putative cell of origin (pre- versus post-germinal center B cells). In conclusion, the TL is a reliable prognostic marker for patients with CLL. Short telomeres and high telomerase activity as occurs in some patients with CLL with a worse prognosis might be an ideal target for treatment with telomerase inhibitors.

Genuine cross-correlations: Which surrogate based measure reproduces analytical results best?

The analysis of short segments of noise-contaminated, multivariate real world data constitutes a challenge. In this paper we compare several techniques of analysis, which are supposed to correctly extract the amount of genuine cross-correlations from a multivariate data set. In order to test for the quality of their performance we derive time series from a linear test model, which allows the analytical derivation of genuine correlations. We compare the numerical estimates of the four measures with the analytical results for different correlation pattern. In the bivariate case all but one measure performs similarly well. However, in the multivariate case measures based on the eigenvalues of the equal-time cross-correlation matrix do not extract exclusively information about the amount of genuine correlations, but they rather reflect the spatial organization of the correlation pattern. This may lead to failures when interpreting the numerical results as illustrated by an application to three electroencephalographic recordings of three patients suffering from pharmacoresistent epilepsy.

An integrative transcranial magnetic stimulation mapping technique using non-linear curve fitting

The aim of this study is to develop a new simple method for analyzing one-dimensional transcranial magnetic stimulation (TMS) mapping studies in humans. Motor evoked potentials (MEP) were recorded from the abductor pollicis brevis (APB) muscle during stimulation at nine different positions on the scalp along a line passing through the APB hot spot and the vertex. Non-linear curve fitting according to the Levenberg-Marquardt algorithm was performed on the averaged amplitude values obtained at all points to find the best-fitting symmetrical and asymmetrical peak functions. Several peak functions could be fitted to the experimental data. Across all subjects, a symmetric, bell-shaped curve, the complementary error function (erfc) gave the best results. This function is characterized by three parameters giving its amplitude, position, and width. None of the mathematical functions tested with less or more than three parameters fitted better. The amplitude and position parameters of the erfc were highly correlated with the amplitude at the hot spot and with the location of the center of gravity of the TMS curve. In conclusion, non-linear curve fitting is an accurate method for the mathematical characterization of one-dimensional TMS curves. This is the first method that provides information on amplitude, position and width simultaneously.

Fluctuation analysis of lung function as a predictor of long-term response to beta2-agonists

The response to beta(2)-agonists differs between asthmatics and has been linked to subsequent adverse events, even death. Possible determinants include beta(2)-adrenoceptor genotype at position 16, lung function and airway hyperresponsiveness. Fluctuation analysis provides a simple parameter alpha measuring the complex correlation properties of day-to-day peak expiratory flow. The present study investigated whether alpha predicts clinical response to beta(2)-agonist treatment, taking into account other conventional predictors. Analysis was performed on previously published twice-daily peak expiratory flow measurements in 66 asthmatic adults over three 6-month randomised order treatment periods: placebo, salbutamol and salmeterol. Multiple linear regression was used to determine the association between alpha during the placebo period and response to treatment (change in the number of days with symptoms), taking into account other predictors namely beta(2)-adrenoceptor genotype, lung function and its variability, and airway hyperresponsiveness. The current authors found that alpha measured during the placebo period considerably improved the prediction of response to salmeterol treatment, taking into account genotype, lung function or its variability, or airway hyperresponsiveness. The present study provides further evidence that response to beta(2)-agonists is related to the time correlation properties of lung function in asthma. The current authors conclude that fluctuation analysis of lung function offers a novel predictor to identify patients who may respond well or poorly to treatment.

Right ventricle best predicts the race performance in amateur ironman athletes

PURPOSE The ironman (IM) triathlon is a popular ultraendurance competition, consisting of 3.8 km of swimming, 180.2 km of cycling, and 42.2 km of running. The aim of this study was to investigate the predictors of IM race time, comparing echocardiographic findings, anthropometric measures, and training characteristics. METHODS Amateur IM athletes (ATHL) participating in the Zurich IM race in 2010 were included. Participants were examined the day before the race by a comprehensive echocardiographic examination. Moreover, anthropometric measurements were obtained the same day. During the 3 months before the race, each IM-ATHL maintained a detailed training diary. Recorded data were related to total IM race time. RESULTS Thirty-eight IM finishers (mean ± SD age = 38 ± 9 yr, 32 men [84%]) were evaluated. Total race time was 684 ± 89 min (mean ± SD). For right ventricular fractional area change (45% ± 7%, Spearman ρ = -0.33, P = 0.05), a weak correlation with race time was observed. Race performance exhibited stronger associations with percent body fat (15.2 ± 5.6%, ρ = 0.56, P = 0.001), speed in running training (11.7 ± 1.2 km · h(-1), ρ = -0.52, P = 0.002), and left ventricular myocardial mass index (98 ± 24 g · m(-2), ρ = -0.42, P = 0.009). The strongest association was found between race time and right ventricular end-diastolic area (22 ± 4 cm2, ρ = -0.64, P < 0.0001). In multivariate analysis, right ventricular end-diastolic area (β = -16.7, 95% confidence interval = -27.3 to -6.1, P = 0.003) and percent body fat (β = 6.8, 95% confidence interval = 1.1-12.6, P = 0.02) were independently predictive of IM race time. CONCLUSIONS In amateur IM-ATHL, RV end-diastolic area and percent body fat were independently related to race performance. RV end-diastolic area was the strongest predictor of race time. The role of the RV in endurance exercise may thus be more important than previously thought and needs to be further studied.

Is the relation between early post-session reports and treatment outcome an epiphenomenon of intake distress and early response? A multi-predictor analysis in outpatient psychotherapy

The early phase of psychotherapy has been regarded as a sensitive period in the unfolding of psychotherapy leading to positive outcomes. However, there is disagreement about the degree to which early (especially relationship-related) session experiences predict outcome over and above initial levels of distress and early response to treatment. The goal of the present study was to simultaneously examine outcome at post treatment as a function of (a) intake symptom and interpersonal distress as well as early change in well-being and symptoms, (b) the patient's early session-experiences, (c) the therapist's early session-experiences/interventions, and (d) their interactions. The data of 430 psychotherapy completers treated by 151 therapists were analyzed using hierarchical linear models. Results indicate that early positive intra- and interpersonal session experiences as reported by patients and therapists after the sessions explained 58% of variance of a composite outcome measure, taking intake distress and early response into account. All predictors (other than problem-activating therapists' interventions) contributed to later treatment outcomes if entered as single predictors. However, the multi-predictor analyses indicated that interpersonal distress at intake as well as the early interpersonal session experiences by patients and therapists remained robust predictors of outcome. The findings underscore that early in therapy therapists (and their supervisors) need to understand and monitor multiple interconnected components simultaneously

Adherence as a Predictor of the Development of Class-Specific Resistance Mutations: The Swiss HIV Cohort Study

Background Non-adherence is one of the strongest predictors of therapeutic failure in HIV-positive patients. Virologic failure with subsequent emergence of resistance reduces future treatment options and long-term clinical success. Methods Prospective observational cohort study including patients starting new class of antiretroviral therapy (ART) between 2003 and 2010. Participants were naïve to ART class and completed ≥1 adherence questionnaire prior to resistance testing. Outcomes were development of any IAS-USA, class-specific, or M184V mutations. Associations between adherence and resistance were estimated using logistic regression models stratified by ART class. Results Of 314 included individuals, 162 started NNRTI and 152 a PI/r regimen. Adherence was similar between groups with 85% reporting adherence ≥95%. Number of new mutations increased with increasing non-adherence. In NNRTI group, multivariable models indicated a significant linear association in odds of developing IAS-USA (odds ratio (OR) 1.66, 95% confidence interval (CI): 1.04-2.67) or class-specific (OR 1.65, 95% CI: 1.00-2.70) mutations. Levels of drug resistance were considerably lower in PI/r group and adherence was only significantly associated with M184V mutations (OR 8.38, 95% CI: 1.26-55.70). Adherence was significantly associated with HIV RNA in PI/r but not NNRTI regimens. Conclusion Therapies containing PI/r appear more forgiving to incomplete adherence compared with NNRTI regimens, which allow higher levels of resistance, even with adherence above 95%. However, in failing PI/r regimens good adherence may prevent accumulation of further resistance mutations and therefore help to preserve future drug options. In contrast, adherence levels have little impact on NNRTI treatments once the first mutations have emerged.

Trends and outcomes in the use of surgery and radiation for the treatment of locally advanced esophageal cancer: a propensity score adjusted analysis of the surveillance, epidemiology, and end results registry from 1998 to 2008

We examined outcomes and trends in surgery and radiation use for patients with locally advanced esophageal cancer, for whom optimal treatment isn't clear. Trends in surgery and radiation for patients with T1-T3N1M0 squamous cell or adenocarcinoma of the mid or distal esophagus in the Surveillance, Epidemiology, and End Results database from 1998 to 2008 were analyzed using generalized linear models including year as predictor; Surveillance, Epidemiology, and End Results doesn't record chemotherapy data. Local treatment was unimodal if patients had only surgery or radiation and bimodal if they had both. Five-year cancer-specific survival (CSS) and overall survival (OS) were analyzed using propensity-score adjusted Cox proportional-hazard models. Overall 5-year survival for the 3295 patients identified (mean age 65.1 years, standard deviation 11.0) was 18.9% (95% confidence interval: 17.3-20.7). Local treatment was bimodal for 1274 (38.7%) and unimodal for 2021 (61.3%) patients; 1325 (40.2%) had radiation alone and 696 (21.1%) underwent only surgery. The use of bimodal therapy (32.8-42.5%, P = 0.01) and radiation alone (29.3-44.5%, P < 0.001) increased significantly from 1998 to 2008. Bimodal therapy predicted improved CSS (hazard ratios [HR]: 0.68, P < 0.001) and OS (HR: 0.58, P < 0.001) compared with unimodal therapy. For the first 7 months (before survival curve crossing), CSS after radiation therapy alone was similar to surgery alone (HR: 0.86, P = 0.12) while OS was worse for surgery only (HR: 0.70, P = 0.001). However, worse CSS (HR: 1.43, P < 0.001) and OS (HR: 1.46, P < 0.001) after that initial timeframe were found for radiation therapy only. The use of radiation to treat locally advanced mid and distal esophageal cancers increased from 1998 to 2008. Survival was best when both surgery and radiation were used.

EGFR inhibitors erlotinib and lapatinib ameliorate epidermal blistering in pemphigus vulgaris in a non-linear, V-shaped relationship.

Novel insights into intra-cellular signalling involved in pemphigus vulgaris (PV), an autoimmune blistering disease of skin and mucous membranes, are now revealing new therapeutic approaches such as the chemical inhibition of PV-associated signals in conjunction with standard immunosuppressive therapy. However, extensive inhibition of signalling molecules that are required for normal tissue function and integrity may hamper this approach. Using a neonatal PV mouse model, we demonstrate that epidermal blistering can be prevented in a dose-dependent manner by clinically approved EGFR inhibitors erlotinib and lapatinib, but only up to approximately 50% of normal EGFR activity. At lower EGFR activity, blisters again aggravated and were highly exacerbated in mice with a conditional deletion of EGFR. Statistical analysis of the relation between EGFR activity and the extent of skin blistering revealed the best fit with a non-linear, V-shaped curve with a median break point at 52% EGFR activity (P = 0.0005). Moreover, lapatinib (a dual EGFR/ErbB2 inhibitor) but not erlotinib significantly reduced blistering in the oral cavity, suggesting that signalling mechanisms differ between PV predilection sites. Our results demonstrate that future clinical trials evaluating EGFR/ErbB2 inhibitors in PV patients must select treatment doses that retain a specific level of signal molecule activity. These findings may also be of relevance for cancer patients treated with EGFR inhibitors, for whom skin lesions due to extensive EGFR inhibition represent a major threat.

New anthropometry-based age- and sex-specific reference values for urinary 24-hour creatinine excretion based on the adult Swiss population.

BACKGROUND Urinary creatinine excretion is used as a marker of completeness of timed urine collections, which are a keystone of several metabolic evaluations in clinical investigations and epidemiological surveys. The current reference values for 24-hour urinary creatinine excretion rely on observations performed in the 1960s and 1970s in relatively small and mostly selected groups, and may thus poorly fit to the present-day general European population. The aim of this study was to establish and validate anthropometry-based age- and sex-specific reference values of the 24-hour urinary creatinine excretion on adult populations with preserved renal function. METHODS We used data from two independent Swiss cross-sectional population-based studies with standardised 24-hour urinary collection and measured anthropometric variables. Only data from adults of European descent, with estimated glomerular filtration rate (eGFR) ≥60 ml/min/1.73 m(2) and reported completeness of the urinary collection were retained. A linear regression model was developed to predict centiles of the 24-hour urinary creatinine excretion in 1,137 participants from the Swiss Survey on Salt and validated in 994 participants from the Swiss Kidney Project on Genes in Hypertension. RESULTS The mean urinary creatinine excretion was 193 ± 41 μmol/kg/24 hours in men and 151 ± 38 μmol/kg/24 hours in women in the Swiss Survey on Salt. The values were inversely correlated with age and body mass index (BMI). Based on current reference values (177 to 221 μmol/kg/24 hours in men and 133 to 177 μmol/kg/24 hours in women), 56% of the urinary collections in the whole population and 67% in people >60 years old would have been considered as inaccurate. A linear regression model with sex, BMI and age as predictor variables was found to provide the best prediction of the observed values and showed a good fit when applied to the validation population. CONCLUSIONS We propose a validated prediction equation for 24-hour urinary creatinine excretion in the general European population, based on readily available variables such as age, sex and BMI, and a few derived normograms to ease its clinical application. This should help healthcare providers to interpret the completeness of a 24-hour urine collection in daily clinical practice and in epidemiological population studies.

Velocity of early BCR-ABL transcript elimination as an optimized predictor of outcome in chronic myeloid leukemia (CML) patients in chronic phase on treatment with imatinib

UNLABELLED Early assessment of response at 3 months of tyrosine kinase inhibitor treatment has become an important tool to predict favorable outcome. We sought to investigate the impact of relative changes of BCR-ABL transcript levels within the initial 3 months of therapy. In order to achieve accurate data for high BCR-ABL levels at diagnosis, beta glucuronidase (GUS) was used as a reference gene. Within the German CML-Study IV, samples of 408 imatinib-treated patients were available in a single laboratory for both times, diagnosis and 3 months on treatment. In total, 301 of these were treatment-naïve at sample collection. RESULTS (i) with regard to absolute transcript levels at diagnosis, no predictive cutoff could be identified; (ii) at 3 months, an individual reduction of BCR-ABL transcripts to the 0.35-fold of baseline level (0.46-log reduction, that is, roughly half-log) separated best (high risk: 16% of patients, 5-year overall survival (OS) 83% vs 98%, hazard ratio (HR) 6.3, P=0.001); (iii) at 3 months, a 6% BCR-ABL(IS) cutoff derived from BCR-ABL/GUS yielded a good and sensitive discrimination (high risk: 22% of patients, 5-year OS 85% vs 98%, HR 6.1, P=0.002). Patients at risk of disease progression can be identified precisely by the lack of a half-log reduction of BCR-ABL transcripts at 3 months.

Retrocrural space involvement on computed tomography as a predictor of mortality and disease severity in acute pancreatitis

BACKGROUND Because computed tomography (CT) has advantages for visualizing the manifestation of necrosis and local complications, a series of scoring systems based on CT manifestations have been developed for assessing the clinical outcomes of acute pancreatitis (AP), including the CT severity index (CTSI), modified CTSI, etc. Despite the internationally accepted CTSI having been successfully used to predict the overall mortality and disease severity of AP, recent literature has revealed the limitations of the CTSI. Using the Delphi method, we establish a new scoring system based on retrocrural space involvement (RCSI), and compared its effectiveness at evaluating the mortality and severity of AP with that of the CTSI. METHODS We reviewed CT images of 257 patients with AP taken within 3-5 days of admission in 2012. The RCSI scoring system, which includes assessment of infectious conditions involving the retrocrural space and the adjacent pleural cavity, was established using the Delphi method. Two radiologists independently assessed the RCSI and CTSI scores. The predictive points of the RCSI and CTSI scoring systems in evaluating the mortality and severity of AP were estimated using receiver operating characteristic (ROC) curves. PRINCIPAL FINDINGS The RCSI score can accurately predict the mortality and disease severity. The area under the ROC curve for the RCSI versus CTSI score was 0.962±0.011 versus 0.900±0.021 for predicting the mortality, and 0.888±0.025 versus 0.904±0.020 for predicting the severity of AP. Applying ROC analysis to our data showed that a RCSI score of 4 was the best cutoff value, above which mortality could be identified. CONCLUSION The Delphi method was innovatively adopted to establish a scoring system to predict the clinical outcome of AP. The RCSI scoring system can predict the mortality of AP better than the CTSI system, and the severity of AP equally as well.

Effect sizes and standardization in neighbourhood models of forest stands: potential biases and misinterpretations

Effects of conspecific neighbours on survival and growth of trees have been found to be related to species abundance. Both positive and negative relationships may explain observed abundance patterns. Surprisingly, it is rarely tested whether such relationships could be biased or even spurious due to transforming neighbourhood variables or influences of spatial aggregation, distance decay of neighbour effects and standardization of effect sizes. To investigate potential biases, communities of 20 identical species were simulated with log-series abundances but without species-specific interactions. No relationship of conspecific neighbour effects on survival or growth with species abundance was expected. Survival and growth of individuals was simulated in random and aggregated spatial patterns using no, linear, or squared distance decay of neighbour effects. Regression coefficients of statistical neighbourhood models were unbiased and unrelated to species abundance. However, variation in the number of conspecific neighbours was positively or negatively related to species abundance depending on transformations of neighbourhood variables, spatial pattern and distance decay. Consequently, effect sizes and standardized regression coefficients, often used in model fitting across large numbers of species, were also positively or negatively related to species abundance depending on transformation of neighbourhood variables, spatial pattern and distance decay. Tests using randomized tree positions and identities provide the best benchmarks by which to critically evaluate relationships of effect sizes or standardized regression coefficients with tree species abundance. This will better guard against potential misinterpretations.

Index Tracking Using Data-Mining Techniques and Mixed-Binary Linear Programming

Index tracking has become one of the most common strategies in asset management. The index-tracking problem consists of constructing a portfolio that replicates the future performance of an index by including only a subset of the index constituents in the portfolio. Finding the most representative subset is challenging when the number of stocks in the index is large. We introduce a new three-stage approach that at first identifies promising subsets by employing data-mining techniques, then determines the stock weights in the subsets using mixed-binary linear programming, and finally evaluates the subsets based on cross validation. The best subset is returned as the tracking portfolio. Our approach outperforms state-of-the-art methods in terms of out-of-sample performance and running times.