A computational framework to emulate the human perspective in flow cytometric data analysis

Background: In recent years, intense research efforts have focused on developing methods for automated flow cytometric data analysis. However, while designing such applications, little or no attention has been paid to the human perspective that is absolutely central to the manual gating process of identifying and characterizing cell populations. In particular, the assumption of many common techniques that cell populations could be modeled reliably with pre-specified distributions may not hold true in real-life samples, which can have populations of arbitrary shapes and considerable inter-sample variation. <p/>Results: To address this, we developed a new framework flowScape for emulating certain key aspects of the human perspective in analyzing flow data, which we implemented in multiple steps. First, flowScape begins with creating a mathematically rigorous map of the high-dimensional flow data landscape based on dense and sparse regions defined by relative concentrations of events around modes. In the second step, these modal clusters are connected with a global hierarchical structure. This representation allows flowScape to perform ridgeline analysis for both traversing the landscape and isolating cell populations at different levels of resolution. Finally, we extended manual gating with a new capacity for constructing templates that can identify target populations in terms of their relative parameters, as opposed to the more commonly used absolute or physical parameters. This allows flowScape to apply such templates in batch mode for detecting the corresponding populations in a flexible, sample-specific manner. We also demonstrated different applications of our framework to flow data analysis and show its superiority over other analytical methods. <p/>Conclusions: The human perspective, built on top of intuition and experience, is a very important component of flow cytometric data analysis. By emulating some of its approaches and extending these with automation and rigor, flowScape provides a flexible and robust framework for computational cytomics

Representing complex data using localized principal components with application to astronomical data

Often the relation between the variables constituting a multivariate data space might be characterized by one or more of the terms: ``nonlinear'', ``branched'', ``disconnected'', ``bended'', ``curved'', ``heterogeneous'', or, more general, ``complex''. In these cases, simple principal component analysis (PCA) as a tool for dimension reduction can fail badly. Of the many alternative approaches proposed so far, local approximations of PCA are among the most promising. This paper will give a short review of localized versions of PCA, focusing on local principal curves and local partitioning algorithms. Furthermore we discuss projections other than the local principal components. When performing local dimension reduction for regression or classification problems it is important to focus not only on the manifold structure of the covariates, but also on the response variable(s). Local principal components only achieve the former, whereas localized regression approaches concentrate on the latter. Local projection directions derived from the partial least squares (PLS) algorithm offer an interesting trade-off between these two objectives. We apply these methods to several real data sets. In particular, we consider simulated astrophysical data from the future Galactic survey mission Gaia.Comment: 25 pages. In "Principal Manifolds for Data Visualization and Dimension Reduction", A. Gorban, B. Kegl, D. Wunsch, and A. Zinovyev (eds), Lecture Notes in Computational Science and Engineering, Springer, 2007, pp. 180--204, http://www.springer.com/dal/home/generic/search/results?SGWID=1-40109-22-173750210-

A network linking scene perception and spatial memory systems in posterior cerebral cortex

The neural systems supporting scene-perception and spatial-memory systems of the human brain are well-described. But how do these neural systems interact? Here, using fine-grained individual-subject fMRI, we report three cortical areas of the human brain, each lying immediately anterior to a region of the scene perception network in posterior cerebral cortex, that selectively activate when recalling familiar real-world locations. Despite their close proximity to the scene-perception areas, network analyses show that these regions constitute a distinct functional network that interfaces with spatial memory systems during naturalistic scene understanding. These “place-memory areas” offer a new framework for understanding how the brain implements memory-guided visual behaviors, including navigation

Cost-efficiency assessment of Advanced Life Support (ALS) courses based on the comparison of advanced simulators with conventional manikins

<p>Abstract</p> <p>Background</p> <p>Simulation is an essential tool in modern medical education. The object of this study was to assess, in cost-effective measures, the introduction of new generation simulators in an adult life support (ALS) education program.</p> <p>Methods</p> <p>Two hundred fifty primary care physicians and nurses were admitted to ten ALS courses (25 students per course). Students were distributed at random in two groups (125 each). Group A candidates were trained and tested with standard ALS manikins and Group B ones with new generation emergency and life support integrated simulator systems.</p> <p>Results</p> <p>In group A, 98 (78%) candidates passed the course, compared with 110 (88%) in group B (p < 0.01). The total cost of conventional courses was €7689 per course and the cost of the advanced simulator courses was €29034 per course (p < 0.001). Cost per passed student was €392 in group A and €1320 in group B (p < 0.001).</p> <p>Conclusion</p> <p>Although ALS advanced simulator systems may slightly increase the rate of students who pass the course, the cost-effectiveness of ALS courses with standard manikins is clearly superior.</p

The effectiveness of a low-intensity problem-solving intervention for common adolescent mental health problems in New Delhi, India: protocol for a school-based, individually randomized controlled trial with an embedded stepped-wedge cluster randomized controlled recruitment trial

Background Conduct, anxiety and depressive disorders account for over 75% of the adolescent mental health burden globally. The current protocol will test a low-intensity problem-solving intervention for school-going adolescents with common mental health problems in India. The protocol also tests the effects of a classroom-based sensitization intervention on the demand for counselling services in an embedded recruitment trial. Methods We will conduct a two-arm individually randomized controlled trial in six Government-run secondary schools in New Delhi. The targeted sample is 240 adolescents in grades 9-12 with persistent, elevated mental health symptoms and associated impact. Participants will receive either a brief problem-solving intervention delivered over 3 weeks by lay counsellors (intervention), or enhanced usual care comprised of problem-solving booklets (control). Self-reported adolescent mental health symptoms and idiographic problems will be assessed at 6 weeks (co-primary outcomes) and again at 12 weeks post-randomization. In addition, adolescent-reported impact of mental health difficulties, perceived stress, mental wellbeing and clinical remission, as well as parent-reported adolescent mental health symptoms and impact scores, will be assessed at 6 and 12 weeks post-randomization. We will also complete a parallel process evaluation, including estimations of the costs of delivering the interventions. An embedded recruitment trial will apply a stepped-wedge, cluster (class)-randomized controlled design in 70 classes across the six schools. This will evaluate the added impact of a classroom-based sensitization intervention over school-level recruitment sensitization activities on the primary outcome of referral rate into the host trial (i.e. the proportion of adolescents referred as a function of the total sampling frame in each condition of the embedded recruitment trial). Other outcomes will be the proportion of referrals eligible to participate in the host trial, proportion of self-generated referrals, and severity and pattern of symptoms among referred adolescents in each condition. Power calculations were undertaken separately for each trial. A detailed statistical analysis plan will be developed separately for each trial prior to unblinding. Discussion Both trials were initiated on 20 August 2018. A single research protocol for both trials offers a resource-efficient methodology for testing the effectiveness of linked procedures to enhance uptake and outcomes of a school-based psychological intervention for common adolescent mental health problems

Evaluating a Modular Approach to Therapy for Children With Anxiety, Depression, Trauma, or Conduct Problems (MATCH) in School-Based Mental Health Care: Study Protocol for a Randomized Controlled Trial

Introduction: Schools have become a primary setting for providing mental health care to youths in the U.S. School-based interventions have proliferated, but their effects on mental health and academic outcomes remain understudied. In this study we will implement and evaluate the effects of a flexible multidiagnostic treatment called Modular Approach to Therapy for Children with Anxiety, Depression, Trauma, or Conduct Problems (MATCH) on students' mental health and academic outcomes. Methods and Analysis: This is an assessor-blind randomized controlled effectiveness trial conducted across five school districts. School clinicians are randomized to either MATCH or usual care (UC) treatment conditions. The target sample includes 168 youths (ages 7-14) referred for mental health services and presenting with elevated symptoms of anxiety, depression, trauma, and/or conduct problems. Clinicians randomly assigned to MATCH or UC treat the youths who are assigned to them through normal school referral procedures. The project will evaluate the effectiveness of MATCH compared to UC on youths' mental health and school related outcomes and assess whether changes in school outcomes are mediated by changes in youth mental health. Ethics and Dissemination: This study was approved by the Harvard University Institutional Review Board (IRB14-3365). We plan to publish the findings in peer-reviewed journals and present them at academic conferences. Clinical Trial Registration: ClinicalTrials.gov ID: NCT02877875. Registered on August 24, 2016

Germline bias dictates cross-serotype reactivity in a common dengue-virus-specific CD8(+) T cell response.

Adaptive immune responses protect against infection with dengue virus (DENV), yet cross-reactivity with distinct serotypes can precipitate life-threatening clinical disease. We found that clonotypes expressing the T cell antigen receptor (TCR) β-chain variable region 11 (TRBV11-2) were 'preferentially' activated and mobilized within immunodominant human-leukocyte-antigen-(HLA)-A*11:01-restricted CD8(+) T cell populations specific for variants of the nonstructural protein epitope NS3133 that characterize the serotypes DENV1, DENV3 and DENV4. In contrast, the NS3133-DENV2-specific repertoire was largely devoid of such TCRs. Structural analysis of a representative TRBV11-2(+) TCR demonstrated that cross-serotype reactivity was governed by unique interplay between the variable antigenic determinant and germline-encoded residues in the second β-chain complementarity-determining region (CDR2β). Extensive mutagenesis studies of three distinct TRBV11-2(+) TCRs further confirmed that antigen recognition was dependent on key contacts between the serotype-defined peptide and discrete residues in the CDR2β loop. Collectively, these data reveal an innate-like mode of epitope recognition with potential implications for the outcome of sequential exposure to heterologous DENVs