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The 2015 European Society of Cardiology/European Respiratory Society treatment guidelines recommend frequent risk assessment in pulmonary arterial hypertension utilizing risk variables. Our objectives were: (1) to investigate the impact of inhaled treprostinil on risk stratification using the French noninvasive approach and REVEAL 2.0, and (2) to analyze the prognostic utility of both risk stratification methods in the predominantly New York Heart Association/World Health Organization functional class III/IV cohorts of TRIUMPH and BEAT. A post hoc analysis was performed to assess risk at baseline and follow-up at Week 12 in the TRIUMPH cohort (n = 148) and at Week 16, 21, and 30 in the inhaled treprostinil naïve placebo BEAT cohort (n = 73). Overall survival, clinical worsening-free survival, and pulmonary arterial hypertension-related hospitalization-free survival were all assessed in the pooled TRIUMPH and inhaled treprostinil naïve placebo BEAT cohorts based on risk group/strata at Week 12/16 follow-up. Inhaled treprostinil improved REVEAL 2.0 risk stratum (OR: 2.38, 95% CI: 1.09–5.19, p = 0.0298) and REVEAL 2.0 score (p = 0.0008) compared to placebo in the TRIUMPH cohort at Week 12. REVEAL 2.0 risk stratum and the number of low-risk criteria by the French approach improved at Weeks 16, 21, and 30 in the inhaled treprostinil naïve placebo BEAT cohort. Combining cohorts, REVEAL 2.0 risk stratification at follow-up was prognostic for clinical worsening-free, pulmonary arterial hypertension hospitalization-free, and overall survival, whereas the number of low-risk criteria was not. These post-hoc pooled analyses suggest inhaled treprostinil improves risk status and indicates that the REVEAL 2.0 calculator may be more suitable than the French noninvasive method for evaluating short-term clinical change in the New York Heart Association/World Health Organization functional class III/IV population.

IntroductionAlthough there is abundant evidence of vascular perturbation from studies of peripheral blood in systemic sclerosis (SSc), there are few data about the ability to use biomarkers of vascular injury and growth factors to predict vascular outcomes and response to therapy. We sought to explore the association between candidate vascular biomarkers and digital ulcerations (DU) in a clinical trial context.MethodsWe examined 19 circulating vascular, angiogenic, and inflammatory biomarkers in 124 patients with scleroderma and DU who participated in a randomized controlled trial of oral treprostinil diolamine (ClinicalTrials.gov identifier NCT00775463). Correlation, regression, and random forest analyses were conducted to assess biomarker relationships in response to drug treatment.ResultsOver the 20-week trial, 82 (66%) patients had their cardinal ulcer completely heal, 54 (44%) developed new ulcers, and 72 (58%) had complete healing of all ulcers; mean change in ulcer burden comparing week 20 with baseline was − 0.36 ± 1.70. Nineteen biomarkers were analyzed for their association and ability to predict clinical DU outcomes. After adjusting for multiple comparisons, no individual biomarker (baseline level, week 20 level, or change over time) was significantly associated with any of the clinical outcomes, suggesting that traditional vascular, angiogenic or inflammatory drivers are not predictive of ulcer fate.ConclusionsThe lack of strong response to any of the vascular, angiogenic, or inflammatory markers suggest that these pathways are not primary drivers in the development of DU clinical outcomes in a SSc population with prevalent DU.Key Points:• Currently we lack robust biomarkers to predict vascular outcomes or response to therapy in scleroderma patients with Raynaud’s phenomenon.• Longitudinal assessment of vascular biomarkers in a clinical trial setting provides a unique opportunity to define biomarkers that predict vascular outcomes.• In a randomized controlled trial of oral treprostinil diolamine for treatment of scleroderma-associated digital ulcers, biomarkers involved in several vascular, inflammatory, and angiogenic pathways did not predict short-term clinical response to therapy or digital ulcer outcomes.• Further study of these and other biomarkers should be considered in Raynaud’s clinical trials in scleroderma patients without prevalent digital ulcers.

Antiretroviral therapy (ART) requires lifelong daily oral therapy. While patient characteristics associated with suboptimal ART adherence and persistence have been described in cohorts of HIV-infected persons, these factors are poor predictors of individual medication taking behaviors. We aimed to create and test instruments for the estimation of future ART adherence and persistence for clinical and research applications. Following formative work, a battery of 148 items broadly related to HIV infection and treatment was developed and administered to 181 HIV-infected patients. ART adherence and persistence were assessed using electronic monitoring for 3 months. Perceived confidence in medication taking and self-reported barriers to adherence were strongest in predicting non-adherence over time. Barriers to adherence (e.g., affordability, scheduling) were the strongest predictors of non-adherence, as well as 3- and 7-day non-persistence. A ten-item battery for prediction of these outcomes (www.med.unc.edu/ncaidstraining/adherence/for-providers) and a 30-item battery reflective of underlying psychological constructs can help identify and study individuals at risk for suboptimal ART adherence and persistence.

BackgroundAlthough rates of sustained virologic response (SVR) after hepatitis C virus (HCV) treatment with direct-acting antivirals (DAAs) surpass 90% in trials and some more “real world” settings, some patients, such as those with substance use disorders, will be challenged to adhere to HCV care.MethodsTo assess the feasibility of 2 strategies for financially incentivizing adherence to HCV care, patients with a substance use history prescribed 12 weeks of a sofosbuvir-containing regimen were randomized to either fixed or lottery-based monetary incentives for attending clinic appointments, pill count adherence >90%, and SVR achievement. Electronic medication monitoring provided an objective measure of DAA adherence.ResultsFifty-nine participants were randomized to the lottery (n = 31) or fixed-incentive (n = 28) arms. All 31 (100%) in the lottery arm and 24 of 28 (86%) in the fixed arm completed 12 weeks of therapy. By intent-to-treat, 93% in the lottery arm and 92% in the fixed arm achieved SVR (estimated difference: 0.5%; 95% confidence interval, −17.5 to 18.8). Overall, 92% of scheduled visits were attended without significant differences between arms. The mean adherence ratio (days with ≥1 bottle opening:monitored days) was 0.91 for lottery and 0.92 for fixed arms.ConclusionsIn this pilot, fixed- and lottery-based financial incentives were successfully implemented and accepted by patients with a substance use history. High levels of HCV therapy and care adherence, as well as rates of SVR, were observed. Financial incentives may be useful to support treatment adherence in patients with substance use disorders and should be tested in a larger, randomized, controlled trial.

Oral treprostinil has recently been shown to delay disease progression in patients with pulmonary arterial hypertension in a long-term outcomes study. The potential advantages of an oral formulation have resulted in patients transitioning from inhaled to oral treprostinil. The current study reports a retrospective analysis of patients who transitioned from treatment with inhaled to oral treprostinil. A multicenter retrospective chart review was conducted for 29 patients with pulmonary hypertension that transitioned from inhaled to oral treprostinil. Data were collected from inhaled treprostinil initiation and patients were followed until discontinuation of oral treprostinil or the end of the observation period. Persistence was calculated using Kaplan–Meier estimates. Prior to transition to oral treprostinil, patients had received inhaled treprostinil for a median of 643 (IQR: 322–991) days and 52% of patients were New York Heart Association/World Health Organization Functional Class III. For patients that cross-titrated between formulations, the median time to complete the cross titration was 24 (IQR: 1–57) days. At 16- and 24-weeks post-transition, oral treprostinil persistence was 86 and 76%, respectively. Persistence was 59% at 52 weeks post-transition. Clinical stability for the majority of patients at first follow-up post-transition was suggested based on available New York Heart Association/World Health Organization Functional Classification. Transitions from inhaled to oral treprostinil appeared safe and tolerable in the short-term. Additional prospective studies are needed to fully evaluate the safety and efficacy of transitions from inhaled to oral treprostinil.

Progression of technology and computational power have led to a new age in data where the number of variables, p, is greater than the number of observations, n. These types of data, commonly called High-Dimensional Low Sample Size (HDLSS) data, are becoming prominent in statistical applications. One such HDLSS application where small samples are unavoidable is in the development and pre-clinical assessment of new drugs, such as in repeated low-dose challenge (RLC) studies. In RLC experiments, animals are assigned to an active or placebo candidate vaccine and then are repeatedly challenged (exposed) with some target pathogen, either until infection or some maximum number of challenges is reached (Nolen et al., 2015). Many times, the number of animals n in an RLC study is small (e.g. ≤ 20) and number of features p is large (e.g. ≥ 100), due to the high cost of each animal and the high number of antibody and functional measure features of interest (Chaudhury et al., 2018; Choi et al., 2015).Penalized regression techniques, like the lasso, are sometimes used in RLC experiments where n is typically small and p is large. However, the performance of such methods is not well established for this experiment setting. The performance of the lasso, elastic net, and a newly proposed discrete survival time penalized regression model is assessed via a simulation study. These methods are also applied to a recent RLC study evaluating a candidate HIV vaccine. All three methods rarely selected true positives regardless of the effect size, number of predictors, or the number of non-zero coefficients, with many models containing only false positives. Thus, penalized regression models should be used cautiously in the RLC setting when n is small and p is large.To improve upon penalized regression in the RCL setting, a recently-developed high-dimensional test known as the direction-projection-permutation (DiProPerm) test is suggested and adapted to the RLC setting. The DiProPerm test was designed specifically for the HDLSS setting and has many alluring qualities. The DiProPerm test is applied to the RLC setting to test whether animals are more likely to become infected early (i.e., before the median infection time) as opposed to late, given a set of antibody and functional measurements. The DiProPerm test has never been implemented in RLC settings as a valid tool for inference until now. Simulation processes revealed the advantages of using the DiProPerm test on RLC data when n is small and p is large. An RLC study evaluating a candidate HIV vaccine is used to demonstrate the DiProPerm test on a real-world dataset.To help disseminate the DiProPerm test to researchers, an R package was created. The diproperm R package can be used to conduct a DiProPerm test, display corresponding plots of interest, and look at the loadings of the binary linear classifier. The functionality of the diproperm package is explained and demonstrated on a real-world data set. The R package is freely available on CRAN and GitHub (https://github.com/allmondrew/diproperm) for anyone to use.

Traumatic brain injury (TBI) is a significant public health problem in the US. Specific preexisting medical illnesses delay recovery after TBI and increase mortality or risk of repeat TBI. This study examined the impact of preexisting illness and substance use on patient rehabilitation outcomes following TBI. The Functional Independence Measure total score and Disability Rating Scale score measured functional outcomes at discharge from inpatient rehabilitation, while the Trail Making Test A and B and Total Trials 1-5 of the California Verbal Learning Test-II measured neuropsychological outcomes in 128 TBI survivors with moderate or severe TBI. Results showed that the presence of a heart condition or diabetes/high blood sugar was associated with lower functional outcomes by discharge. A history of a heart condition, stroke, or respiratory condition prior to TBI was associated with reduced cognitive flexibility. Those with preexisting diabetes/high blood sugar demonstrated poorer visual attention, visuomotor processing speed, and ability to learn and recall verbal information. Those with pre-TBI cancer also had greater auditory-verbal memory deficits. The findings showed that specific preexisting medical conditions are independently associated with lower functional and cognitive outcomes for patients with TBI. By screening patients for preexisting medical conditions, multidisciplinary TBI rehabilitation teams can identify patients who require more aggressive treatments or greater length of stay.

High-dimensional low sample size (HDLSS) data sets emerge frequently in many biomedical applications. A common task for analyzing HDLSS data is to assign data to the correct class using a classifier. Classifiers which use two labels and a linear combination of features are known as binary linear classifiers. The direction-projection-permutation (DiProPerm) test was developed for testing the difference of two high-dimensional distributions induced by a binary linear classifier. This paper discusses the key components of the DiProPerm test, introduces the diproperm R package, and demonstrates the package on a real-world data set.

Anthropogenic CO 2 is expected to drive ocean pCO 2 above 1,000 μatm by 2100 – inducing respiratory acidosis in fish that must be corrected through branchial ion transport. This study examined the time course and plasticity of branchial metabolic compensation in response to varying levels of CO 2 in an estuarine fish, the red drum, which regularly encounters elevated CO 2 and may therefore have intrinsic resilience. Under control conditions fish exhibited net base excretion; however, CO 2 exposure resulted in a dose dependent increase in acid excretion during the initial 2 h. This returned to baseline levels during the second 2 h interval for exposures up to 5,000 μatm, but remained elevated for exposures above 15,000 μatm. Plasticity was assessed via gene expression in three CO 2 treatments: environmentally realistic 1,000 and 6,000 μatm exposures, and a proof-of-principle 30,000 μatm exposure. Few differences were observed at 1,000 or 6,000 μatm; however, 30,000 μatm stimulated widespread up-regulation. Translocation of V-type ATPase after 1 h of exposure to 30,000 μatm was also assessed; however, no evidence of translocation was found. These results indicate that red drum can quickly compensate to environmentally relevant acid-base disturbances using baseline cellular machinery, yet are capable of plasticity in response to extreme acid-base challenges.

The natural world is infinitely complex and hierarchically structured, with smaller units forming the components of progressively larger systems: molecules make up cells, cells comprise tissues and organs that are, in turn, parts of individual organisms, which are united into populations and integrated into yet more encompassing ecosystems. In the face of such awe-inspiring complexity, there is a need for a comprehensive, non-reductionist evolutionary theory. Having emerged at the crossroads of paleobiology, genetics, and developmental biology, the hierarchical approach to evolution provides a unifying perspective on the natural world and offers an operational framework for scientists seeking to understand the way complex biological systems work and evolve. Coedited by one of the founders of hierarchy theory and featuring a diverse and renowned group of contributors, this volume provides an integrated, comprehensive, cutting-edge introduction to the hierarchy theory of evolution. From sweeping historical reviews to philosophical pieces, theoretical essays, and strictly empirical chapters, it reveals hierarchy theory as a vibrant field of scientific enterprise that holds promise for unification across the life sciences and offers new venues of empirical and theoretical research. Stretching from molecules to the biosphere, hierarchy theory aims to provide an all-encompassing understanding of evolution and—with this first collection devoted entirely to the concept—will help make transparent the fundamental patterns that propel living systems.