Risk-based lung cancer screening performance in a universal healthcare setting.

Globally, lung cancer is the leading cause of cancer death. Previous trials demonstrated that low-dose computed tomography lung cancer screening of high-risk individuals can reduce lung cancer mortality by 20% or more. Lung cancer screening has been approved by major guidelines in the United States, and over 4,000 sites offer screening. Adoption of lung screening outside the United States has, until recently, been slow. Between June 2017 and May 2019, the Ontario Lung Cancer Screening Pilot successfully recruited 7,768 individuals at high risk identified by using the PLCOm2012noRace lung cancer risk prediction model. In total, 4,451 participants were successfully screened, retained and provided with high-quality follow-up, including appropriate treatment. In the Ontario Lung Cancer Screening Pilot, the lung cancer detection rate and the proportion of early-stage cancers were 2.4% and 79.2%, respectively; serious harms were infrequent; and sensitivity to detect lung cancers was 95.3% or more. With abnormal scans defined as ones leading to diagnostic investigation, specificity was 95.5% (positive predictive value, 35.1%), and adherence to annual recall and early surveillance scans and clinical investigations were high (>85%). The Ontario Lung Cancer Screening Pilot provides insights into how a risk-based organized lung screening program can be implemented in a large, diverse, populous geographic area within a universal healthcare system.

The oral sensory organs in Bathochordaeus stygius (Tunicata Appendicularia) are unique in structure and homologous to the coronal organ.

BACKGROUND: Appendicularia consists of approximately 70 purely marine species that belong to Tunicata the probable sister taxon to Craniota. Therefore, Appendicularia plays a pivotal role for our understanding of chordate evolution. In addition, appendicularians are an important part of the epipelagic marine plankton. Nevertheless, little is known about appendicularian species, especially from deeper water. RESULTS: Using µCT, scanning electron microscopy, and digital 3D-reconstruction techniques we describe three pairs of complex oral sensory organs in the mesopelagic appendicularian Bathochordaeus stygius. The oral sensory organs are situated at the anterior and lateral margin of the mouth and inside the mouth cavity. A single organ consists of 22-90 secondary receptor cells that project apical cilia through a narrow hole in the epidermis. The receptor cells are innervated by branches of the second brain nerve. CONCLUSIONS: Based on position, morphology, and innervation we suggest that the oral sensory organs are homologues of the coronal organs in other tunicates. We discuss the hypothesized homology of coronal organs and the lateral line system of primary aquatic vertebrates. The complex oral sensory organs of B. stygius are unique in tunicates and could be adaptations to the more muffled environment of the mesopelagic.

Evolutionary traces of miniaturization in a giant-Comparative anatomy of brain and brain nerves in Bathochordaeus stygius (Tunicata, Appendicularia).

Appendicularia comprises 70 marine, invertebrate, chordate species. Appendicularians play important ecological and evolutionary roles, yet their morphological disparity remains understudied. Most appendicularians are small, develop rapidly, and with a stereotyped cell lineage, leading to the hypothesis that Appendicularia derived progenetically from an ascidian-like ancestor. Here, we describe the detailed anatomy of the central nervous system of Bathochordaeus stygius, a giant appendicularian from the mesopelagic. We show that the brain consists of a forebrain with on average smaller and more uniform cells and a hindbrain, in which cell shapes and sizes vary to a greater extent. Cell count for the brain was 102. We demonstrate the presence of three paired brain nerves. Brain nerve 1 traces into the epidermis of the upper lip region and consists of several fibers with some supportive bulb cells in its course. Brain nerve 2 innervates oral sensory organs and brain nerve 3 innervates the ciliary ring of the gill slits and lateral epidermis. Brain nerve 3 is asymmetric, with the right nerve consisting of two neurites originating posterior to the left one that contains three neurites. Similarities and differences to the anatomy of the brain of the model species Oikopleura dioica are discussed. We interpret the small number of cells in the brain of B. stygius as an evolutionary trace of miniaturization and conclude that giant appendicularians evolved from a small, progenetic ancestor that secondarily increased in size within Appendicularia.

Teacher's Corner: An R Shiny App for Sensitivity Analysis for Latent Growth Curve Mediation.

Mechanisms of behavior change are the processes through which interventions are hypothesized to cause changes in outcomes. Latent growth curve mediation models (LGCMM) are recommended for investigating the mechanisms of behavior change because LGCMM models establish temporal precedence of change from the mediator to the outcome variable. The Correlated Augmented Mediation Sensitivity Analyses (CAMSA) App implements sensitivity analysis for LGCMM models to evaluate if a mediating path (mechanism) is robust to potential confounding variables. The CAMSA approach is described and applied to simulated data, and data from a research study exploring a mechanism of change in the treatment of substance use disorder.

Detection of Ticks and Tick-Borne Pathogens of Urban Stray Dogs in South Africa.

This study aimed to identify ticks infesting dogs admitted to the Potchefstroom Animal Welfare Society (PAWS) and to detect tick-borne pathogens they are harbouring. A total of 592 ticks were collected from 61 stray dogs admitted to PAWS originating from several suburbs in and near Potchefstroom, South Africa. The dog ticks were identified as Haemaphysalis elliptica (39%) and Rhipicephalus sanguineus (61%) by both morphological and DNA analyses. Of these ticks, H. elliptica consisted of 67.5% (156/231) and 32.5% (75/231) female and male ticks, respectively, whilst R. sanguineus consisted of 48.5% (175/361) and 51.5% (186/361) female and male ticks, respectively. Microscopic examination of blood smears from engorged female ticks indicated overall occurrences of 0.5% (1/204) for Babesia spp. from R. sanguineus, 1% (2/204) of Anaplasma spp. from H. elliptica, and 22% (45/204) of Rickettsia spp. from both H. elliptica and R. sanguineus. Using pooled samples molecular detection of tick-borne pathogens indicated overall occurrences of 1% (1/104) for A. phagocytophilum in H. elliptica, 9.6% (10/104) of Rickettsia spp. in H. elliptica and R. sanguineus, 5.8% (6/104) of Ehrlichia canis in H. elliptica and R. sanguineus, and 13.5% (14/104) of Coxiella spp. in both H. elliptica and R. sanguineus. Additionally, PCR detected 6.5% (2/31) of Coxiella spp. DNA from H. elliptica eggs. Our data indicate that urban stray dogs admitted at PAWS are infested by H. elliptica and R. sanguineus ticks which are harbouring several pathogenic organisms known to cause tick-borne diseases.

The incidence of medial end clavicle fractures is higher than had previously been considered.

BACKGROUND: Previous X-ray epidemiological studies have estimated the incidence of medial end clavicle fractures to account for 2-3% of all clavicle fractures. MATERIALS AND METHODS: At our institution X-rays of every patient attending the Emergency Department are reviewed at a Virtual Fracture Clinic by a Consultant Orthopaedic Surgeon. Patients with a fracture are referred to the Shoulder and Elbow Fracture Clinic. Patients without a fracture are contacted and, if there are on-going concerns, are referred to the Shoulder and Elbow Fracture Clinic. Over an 18-month period we identified every patient that attended our Emergency Department that had sustained a clavicle fracture. RESULTS: In total 558 clavicle fractures were identified (139 (24.9%) - lateral, 360 (64.5%) - middle, 59 (10.6%) - medial). Of the 59 medial end fractures, 31 (52.5%) were identified on presentation at the Emergency Department, 13 (22%) at the Virtual Fracture Clinic, 6 (10.2%) on computed tomography scan at the Shoulder and Elbow Fracture Clinic and 9 (15.3%) were admitted directly to the trauma unit. CONCLUSION: The results of this study suggest that the incidence of medial end clavicle fractures in the general population is higher than had previously been considered. LEVEL OF EVIDENCE: IV.

A permutation test for assessing the presence of individual differences in treatment effects.

An important goal of personalized medicine is to identify heterogeneity in treatment effects and then use that heterogeneity to target the intervention to those most likely to benefit. Heterogeneity is assessed using the predicted individual treatment effects framework, and a permutation test is proposed to establish if significant heterogeneity is present given the covariates and predictive model or algorithm used for predicted individual treatment effects. We first show evidence for heterogeneity in the effects of treatment across an illustrative example data set. We then use simulations with two different predictive methods (linear regression model and Random Forests) to show that the permutation test has adequate type-I error control. Next, we use an example dataset as the basis for simulations to demonstrate the ability of the permutation test to find heterogeneity in treatment effects for a predicted individual treatment effects estimate as a function of both effect size and sample size. We find that the proposed test has good power for detecting heterogeneity in treatment effects when the heterogeneity was due primarily to a single predictor, or when it was spread across the predictors. Power was found to be greater for predictions from a linear model than from random forests. This non-parametric permutation test can be used to test for significant differences across individuals in predicted individual treatment effects obtained with a given set of covariates using any predictive method with no additional assumptions.

The filter-house of the larvacean Oikopleura dioica. A complex extracellular architecture: From fiber production to rudimentary state to inflated house.

While cellulose is the most abundant macromolecule in the biosphere, most animals are unable to produce cellulose with the exception of tunicates. Some tunicates have evolved the ability to secrete a complex house containing cellulosic fibers, yet little is known about the early stages of the house building process. Here, we investigate the rudimentary house of Oikopleura dioica for the first time using complementary light and electron microscopic techniques. In addition, we digitally modeled the arrangement of chambers, nets, and filters of the functional, expanded house in three dimensions based on life-video-imaging. Combining 3D-reconstructions based on serial histological semithin-sections, confocal laser scanning microscopy, transmission electron microscopy, scanning electron microscopy (SEM), and focused ion beam (FIB)-SEM, we were able to elucidate the arrangement of structural components, including cellulosic fibers, of the rudimentary house with a focus on the food concentration filter. We developed a model for the arrangement of folded structures in the house rudiment and show it is a precisely preformed structure with identifiable components intricately correlated with specific cells. Moreover, we demonstrate that structural details of the apical surfaces of Nasse cells provide the exact locations and shapes to produce the fibers of the house and interact among each other, with Giant Fol cells, and with the fibers to arrange them in the precise positions necessary for expansion of the house rudiment into the functional state. The presented data and hypotheses advance our knowledge about the interrelation of structure and function on different biological levels and prompt investigations into this astonishing biological object.

Latent Class Mediation: A Comparison of Six Approaches.

Latent class mediation modeling is designed to estimate the mediation effect when both the mediator and the outcome are latent class variables. We suggest using an adjusted one-step approach in which the latent class models for the mediator and the outcome are estimated first to decide on the number of classes, then the latent class models and the mediation model are jointly estimated. We present both an empirical demonstration and a simulation study to compare the performance of this one-step approach to a standard three-step approach with modal assignment (modal) and four different modern three-step approaches. Results from the study indicate that unadjusted modal, which ignores the classification errors of the latent class models, produced biased mediation effects. On the other hand, the adjusted one-step approach and the modern three-step approaches performed well with respect to bias for estimating mediation effects, regardless of measurement quality (i.e., model entropy) and latent class size. Among the three-step approaches we investigated, the maximum likelihood method with modal assignment and the BCH correction with robust standard error estimators are good alternatives to the adjusted one-step approach, given their unbiased standard error estimations.

Not everything is as it seems.

We report a case of a patient operated for shoulder rotator cuff injury under interscalene brachial plexus block and general anesthesia, who developed neurological deficit in the nonoperative upper limb in the immediate postoperative period. As our patient developed neurological deficit on the nonoperative side, it was clear from the beginning that neither the nerve block nor the operative procedure was responsible for it. However, had he developed neurological symptoms on the operative side after having a peripheral nerve block, it would have possibly delayed the timely investigation and diagnosis. This case report underlines the need to keep an open mind when investigating neurological symptoms arising in the perioperative period, rather than assuming it to be secondary to either nerve block or as a complication of surgical procedure.

The (Lack of) Replication of Self-Reported Mindfulness as a Mechanism of Change in Mindfulness-Based Relapse Prevention for Substance Use Disorders.

The development and evaluation of mindfulness-based interventions for a variety of psychological and medical disorders has grown exponentially over the past 20 years. Yet, calls for increasing the rigor of mindfulness research and recognition of the difficulties of conducting research on the topic of mindfulness have also increased. One of the major difficulties is the measurement of mindfulness, with varying definitions across studies and ambiguity with respect to the meaning of mindfulness. There is also concern about the reproducibility of findings given few attempts at replication. The current secondary analysis addressed the issue of reproducibility and robustness of the construct of self-reported mindfulness across two separate randomized clinical trials of mindfulness-based relapse prevention (MBRP), as an aftercare treatment for substance use disorder. Specifically, we tested the robustness of our previously published findings, which identified a latent construct of mindfulness as a significant mediator of the effect of MBRP on reducing craving following treatment. First, we attempted to replicate the findings in a separate randomized clinical trial of MBRP. Second, we conducted sensitivity analyses to test the assumption of the no-omitted confounder bias in a mediation model. The effect of MBRP on self-reported mindfulness and overall mediation effect failed to replicate in a new sample. The effect of self-reported mindfulness in predicting craving following treatment did replicate and was robust to the no-omitted confounder bias. The results of this work shine a light on the difficulties in the measurement of mindfulness and the importance of examining the robustness of findings.

An evaluation of the bootstrap for model validation in mixture models.

Bootstrapping has been used as a diagnostic tool for validating model results for a wide array of statistical models. Here we evaluate the use of the non-parametric bootstrap for model validation in mixture models. We show that the bootstrap is problematic for validating the results of class enumeration and demonstrating the stability of parameter estimates in both finite mixture and regression mixture models. In only 44% of simulations did bootstrapping detect the correct number of classes in at least 90% of the bootstrap samples for a finite mixture model without any model violations. For regression mixture models and cases with violated model assumptions, the performance was even worse. Consequently, we cannot recommend the non-parametric bootstrap for validating mixture models. The cause of the problem is that when resampling is used influential individual observations have a high likelihood of being sampled many times. The presence of multiple replications of even moderately extreme observations is shown to lead to additional latent classes being extracted. To verify that these replications cause the problems we show that leave-k-out cross-validation where sub-samples taken without replacement does not suffer from the same problem.

Role of the BUB3 protein in phragmoplast microtubule reorganization during cytokinesis.

The evolutionarily conserved WD40 protein budding uninhibited by benzimidazole 3 (BUB3) is known for its function in spindle assembly checkpoint control. In the model plant Arabidopsis thaliana, nearly identical BUB3;1 and BUB3;2 proteins decorated the phragmoplast midline through interaction with the microtubule-associated protein MAP65-3 during cytokinesis. BUB3;1 and BUB3;2 interacted with the carboxy-terminal segment of MAP65-3 (but not MAP65-1), which harbours its microtubule-binding domain for its post-mitotic localization. Reciprocally, BUB3;1 and BUB3;2 also regulated MAP65-3 localization in the phragmoplast by enhancing its microtubule association. In the bub3;1 bub3;2 double mutant, MAP65-3 localization was often dissipated away from the phragmoplast midline and abolished upon treatment of low doses of the cytokinesis inhibitory drug caffeine that were tolerated by the control plant. The phragmoplast microtubule array exhibited uncoordinated expansion pattern in the double mutant cells as the phragmoplast edge reached the parental plasma membrane at different times in different areas. Upon caffeine treatment, phragmoplast expansion was halted as if the microtubule array was frozen. As a result, cytokinesis was abolished due to failed cell plate assembly. Our findings have uncovered a novel function of the plant BUB3 in MAP65-3-dependent microtubule reorganization during cytokinesis.

GPR68 Senses Flow and Is Essential for Vascular Physiology.

Mechanotransduction plays a crucial role in vascular biology. One example of this is the local regulation of vascular resistance via flow-mediated dilation (FMD). Impairment of this process is a hallmark of endothelial dysfunction and a precursor to a wide array of vascular diseases, such as hypertension and atherosclerosis. Yet the molecules responsible for sensing flow (shear stress) within endothelial cells remain largely unknown. We designed a 384-well screening system that applies shear stress on cultured cells. We identified a mechanosensitive cell line that exhibits shear stress-activated calcium transients, screened a focused RNAi library, and identified GPR68 as necessary and sufficient for shear stress responses. GPR68 is expressed in endothelial cells of small-diameter (resistance) arteries. Importantly, Gpr68-deficient mice display markedly impaired acute FMD and chronic flow-mediated outward remodeling in mesenteric arterioles. Therefore, GPR68 is an essential flow sensor in arteriolar endothelium and is a critical signaling component in cardiovascular pathophysiology.

Longitudinal relationships between self-concept for physical activity and neighborhood social life as predictors of physical activity among older African American adults.

BACKGROUND: Engaging in regular physical activity (PA) as an older adult has been associated with numerous physical and mental health benefits. The aim of this study is to directly compare how individual-level cognitive factors (self-efficacy for PA, self-determined motivation for PA, self-concept for PA) and neighborhood perceptions of the social factors (neighborhood satisfaction, neighborhood social life) impact moderate-to-vigorous physical activity (MVPA) longitudinally among older African American adults. METHODS: Data were analyzed from a sub-set of older African American adults (N = 224, M age = 63.23 years, SD = 8.74, 63.23% female, M Body Mass Index = 32.01, SD = 7.52) enrolled in the Positive Action for Today's Health trial. MVPA was assessed using 7-day accelerometry-estimates and psychosocial data (self-efficacy for PA, self-determined motivation for PA, self-concept for PA, neighborhood satisfaction, neighborhood social life) were collected at baseline, 12-, 18-, and 24-months. RESULTS: Multilevel growth modeling was used to examine within- and between-person effects of individual-level cognitive and social environmental factors on MVPA. At the between-person level, self-concept (b = 0.872, SE = 0.239, p < 0.001), and neighborhood social life (b = 0.826, SE = 0.176, p < 0.001) predicted greater MVPA, whereas neighborhood satisfaction predicted lower MVPA (b = -0.422, SE = 0.172, p = 0.015). Among the between-person effects, only average social life was moderated by time (b = 0.361, SE = 0.147, p = 0.014), indicating that the impact of a relatively positive social life on MVPA increased across time. At the within-person level, positive increases in self-concept (b = 0.294, SE = 0.145, p = 0.043) and neighborhood social life (b = 0.270, SE = 0.113, p = 0.017) were associated with increased MVPA. CONCLUSIONS: These results suggest that people with a higher average self-concept for PA and a more positive social life engaged in greater average MVPA. Additionally, changes in perceptions of one's neighborhood social life and one's self-concept for PA were associated with greater MVPA over 2 years. These factors may be particularly relevant for future interventions targeting long-term change and maintenance of MVPA in older African Americans. TRIAL REGISTRATION: ClinicalTrials.Gov # NCT01025726 registered 1 December 2009.

Modeling predictors of latent classes in regression mixture models.

The purpose of the current study is to provide guidance on a process for including latent class predictors in regression mixture models. We first examine the performance of current practice for using the 1-step and 3-step approaches where the direct covariate effect on the outcome is omitted. None of the approaches show adequate estimates of model parameters. Given that the step-1 of the three-step approach shows adequate results in class enumeration, we suggest using an alternative approach: 1) decide the number of latent classes without predictors of latent classes and 2) bring the latent class predictors into the model with the inclusion of hypothesized direct covariates effects. Our simulations show that this approach leads to good estimates for all model parameters. The proposed approach is demonstrated by using empirical data to examine the differential effects of family resources on students' academic achievement outcome. Implications of the study are discussed.

A multilevel approach to examining time-specific effects in accelerometer-assessed physical activity.

OBJECTIVES: Popular methods for analyzing accelerometer data often use a single physical activity outcome variable such as average-weekly or total physical activity. These approaches limit the types of research questions that can be answered and fail to utilize the detailed, time-specific information available from accelerometers. This study proposes the use of multilevel modeling, which tested intervention effects at specific time periods. DESIGN: The motivating example was the Active by Choice Today trial. Simulations were used to test whether the application of time-specific hypotheses about when physical activity intervention treatment effects were expected to occur (e.g., after-school hours) increased power to detect effects compared to traditional methods. METHODS: Six simulation conditions were tested: (1) no treatment effects (to test the type 1 error rate), (2) time-specific effects, but no traditionally-tested effects, (3) traditionally-tested effects, but no time-specific effects, and (4) combinations of traditional and time-specific effects in 3 proportions. RESULTS: Results showed the proposed multilevel approach demonstrated appropriate type 1 error rates and increased power to detect treatment effects during hypothesized times by 31-38 percentage points compared to traditional approaches. This was consistent across varying proportions of traditional versus time-specific effects, and there was no loss of power using the multilevel approach when only traditional effects were present. CONCLUSIONS: The current study showed potential advantages of testing time-specific hypotheses about intervention effects using a multilevel time-specific approach. This approach may show intervention effects when traditional approaches do not. Future research should explore the application of this additional analytic tool for accelerometer physical activity estimates.

Finite Mixtures for Simultaneously Modelling Differential Effects and Non-Normal Distributions.

Regression mixture models have been increasingly applied in the social and behavioral sciences as a method for identifying differential effects of predictors on outcomes. While the typical specification of this approach is sensitive to violations of distributional assumptions, alternative methods for capturing the number of differential effects have been shown to be robust. Yet, there is still a need to better describe differential effects that exist when using regression mixture models. The current study tests a new approach that uses sets of classes (called differential effects sets) to simultaneously model differential effects and account for non-normal error distributions. Monte Carlo simulations are used to examine the performance of the approach. The number of classes needed to represent departures from normality is shown to be dependent on the degree of skew. The use of differential effects sets reduced bias in parameter estimates. Applied analyses demonstrated the implementation of the approach for describing differential effects of parental health problems on adolescent body mass index using differential effects sets approach. Findings support the usefulness of the approach which overcomes the limitations of previous approaches for handling non-normal errors.

Not quite normal: Consequences of violating the assumption of normality in regression mixture models.

Regression mixture models are a new approach for finding differential effects which have only recently begun to be used in applied research. This approach comes at the cost of the assumption that error terms are normally distributed within classes. The current study uses Monte Carlo simulations to explore the effects of relatively minor violations of this assumption, the use of an ordered polytomous outcome is then examined as an alternative which makes somewhat weaker assumptions, and finally both approaches are demonstrated with an applied example looking at differences in the effects of family management on the highly skewed outcome of drug use. Results show that violating the assumption of normal errors results in systematic bias in both latent class enumeration and parameter estimates. Additional classes which reflect violations of distributional assumptions are found. Under some conditions it is possible to come to conclusions that are consistent with the effects in the population, but when errors are skewed in both classes the results typically no longer reflect even the pattern of effects in the population. The polytomous regression model performs better under all scenarios examined and comes to reasonable results with the highly skewed outcome in the applied example. We recommend that careful evaluation of model sensitivity to distributional assumptions be the norm when conducting regression mixture models.

Deletion of the potassium channel Kv12.2 causes hippocampal hyperexcitability and epilepsy.

We found the voltage-gated K+ channel Kv12.2 to be a potent regulator of excitability in hippocampal pyramidal neurons. Genetic deletion and pharmacologic block of Kv12.2 substantially reduced the firing threshold of these neurons. Kv12.2-/- (also known as Kcnh3-/-) mice showed signs of persistent neuronal hyperexcitability including frequent interictal spiking, spontaneous seizures and increased sensitivity to the chemoconvulsant pentylenetetrazol.