Parent activation and pediatric primary care outcomes for vulnerable children: A mixed methods study

ObjectiveAmong children in low-income families 1) examine associations between parent activation and pediatric primary care outcomes and 2) explore parent perspectives on Parent-Patient Activation Measure (P-PAM) questions in relation to pediatric primary care experiences.MethodsWe examined associations between P-PAM score via Spanish- or English-language survey and healthcare outcomes abstracted from electronic medical records for parent/child dyads at an urban general pediatrics clinic. Parent perspectives were elicited via qualitative interviews with a subsample of parents who “thought aloud” during P-PAM completion.ResultsAmong 316 Spanish (68%) and English-language parent/child dyads, we found associations between parent activation and primary care outcomes only among Spanish-language dyads and only for weight and health status. Findings from 21 interviews provided possible explanations for quantitative findings including question limitations in assessing knowledge, skills, and confidence in pediatric primary care and P-PAM cultural and linguistic appropriateness for low-income Latino populations.ConclusionsPairing quantitative and qualitative methods provided insight on P-PAM measurement limitations and raised questions about its use in patient engagement interventions to reduce health disparities.Practice implicationsPractices serving vulnerable children and families should consider the limitations of the P-PAM for measuring parent healthcare engagement before utilizing the P-PAM in patient engagement interventions.     

Novel machine learning methods for ERP analysis: a validation from research on infants at risk for autism

Machine learning and other computer intensive pattern recognition methods are successfully applied to a variety of fields that deal with high-dimensional data and often small sample sizes such as genetic microarray, functional magnetic resonance imaging (fMRI) and, more recently, electroencephalogram (EEG) data. The aim of this article is to discuss the use of machine learning and discrimination methods and their possible application to the analysis of infant event-related potential (ERP) data. The usefulness of two methods, regularized discriminant function analyses and support vector machines, will be demonstrated by reanalyzing an ERP dataset from infants ( Elsabbagh et al., 2009 ). Using cross-validation, both methods successfully discriminated above chance between groups of infants at high and low risk of a later diagnosis of autism. The suitability of machine learning methods for the use of single trial or averaged ERP data is discussed.     

Sleep,fatigue, and medical training: setting an agenda for optimal learning and patient care

The difficult issues surrounding discussions of sleep, fatigue, and medical education stem from an ironic biologic truth: physicians share a common physiology with their patients, a physiology that includes an absolute need for sleep and endogenous circadian rhythms governing alertness and performance. We cannot ignore the fact that patients become ill and require medical care at all times of the day and night, but we also cannot escape the fact that providing such care requires that medical professionals, including medical trainees, be awake and functioning at times that are in conflict with their endogenous sleep and circadian physiology. Finally, we cannot avoid the reality that medical education requires long hours in a constrained number of years. Solutions to the problem of sleep and fatigue in medical education will require the active involvement of numerous parties, ranging from trainees themselves to training program directors, hospital administrators, sleep and circadian scientists, and government funding and regulatory agencies. Each of these parties can be informed by previous laboratory and field studies in a variety of operational settings. including medical environments. Education regarding the known effects of sleep. circadian rhythms, and sleep deprivation can help to elevate the general level of discourse and point to potential solutions. Empiric research addressing the effects of sleep loss on patient safety, education outcomes, and resident health is urgently needed: equally important are the development and assessment of innovative countermeasures to maximize performance and learning. Addressing the economic realities of any changes in resident work hours is an essential component of any discussion of these issues. Finally, work-hour regulations may serve as one component of improved sleep and circadian health for medical trainees. but they should not be seen as substitutes for more original solutions that rely less on enforcement and more on collaboration. By working together to address the problems of sleep and fatigue in its own trainees, the medical field can provide a valuable legacy to patients and to future generations of healthcare providers--a legacy or optimal medical education, healthy doctors, and healthy patients.     

Electroporation: theory and methods,perspectives for drug delivery,gene therapy and research

Electroporation designates the use of short high‐voltage pulses to overcome the barrier of the cell membrane. By applying an external electric field, which just surpasses the capacitance of the cell membrane, transient and reversible breakdown of the membrane can be induced. This transient, permeabilized state can be used to load cells with a variety of different molecules, either through simple diffusion in the case of small molecules, or through electrophoretically driven processes allowing passage through the destabilized membrane – as is the case for DNA transfer. Initially developed for gene transfer, electroporation is now in use for delivery of a large variety of molecules: From ions to drugs, dyes, tracers, antibodies, and oligonucleotides to RNA and DNA. Electroporation has proven useful both in vitro, in vivo and in patients, where drug delivery to malignant tumours has been performed. Whereas initial electroporation procedures caused considerable cell damage, developments over the past decades have led to sophistication of equipment and optimization of protocols. The electroporation procedures used in many laboratories could be optimized with limited effort. This review (i) outlines the theory of electroporation, (ii) discusses factors of importance for optimization of electroporation protocols for mammalian cells, (iii) addresses particular concerns when using electroporation in vivo, e.g. effects on blood flow and considerations regarding choice of electrodes, (iv) describes DNA electrotransfer with emphasis on use in the in vivo setting, and (v) sums up data on safety and efficacy of electroporation used to enhance delivery of chemotherapy to tumours in cancer patients.     

Electroporation: theory and methods,perspectives for drug delivery,gene therapy and research

Electroporation designates the use of short high-voltage pulses to overcome the barrier of the cell membrane. By applying an external electric field, which just surpasses the capacitance of the cell membrane, transient and reversible breakdown of the membrane can be induced. This transient, permeabilized state can be used to load cells with a variety of different molecules, either through simple diffusion in the case of small molecules, or through electrophoretically driven processes allowing passage through the destabilized membrane--as is the case for DNA transfer. Initially developed for gene transfer, electroporation is now in use for delivery of a large variety of molecules: From ions to drugs, dyes, tracers, antibodies, and oligonucleotides to RNA and DNA. Electroporation has proven useful both in vitro, in vivo and in patients, where drug delivery to malignant tumours has been performed. Whereas initial electroporation procedures caused considerable cell damage, developments over the past decades have led to sophistication of equipment and optimization of protocols. The electroporation procedures used in many laboratories could be optimized with limited effort. This review (i) outlines the theory of electroporation, (ii) discusses factors of importance for optimization of electroporation protocols for mammalian cells, (iii) addresses particular concerns when using electroporation in vivo, e.g. effects on blood flow and considerations regarding choice of electrodes, (iv) describes DNA electrotransfer with emphasis on use in the in vivo setting, and (v) sums up data on safety and efficacy of electroporation used to enhance delivery of chemotherapy to tumours in cancer patients.     

Quantity versus quality: optimal methods for cell-free DNA isolation from plasma of pregnant women.

PURPOSE: Methods to isolate cell-free fetal DNA from maternal plasma are critical in developing noninvasive fetal DNA testing strategies. Given that plasma consists of heterogeneous DNA-size fragments in a complex mix of proteins, recovery and analysis of this DNA are understandably inefficient. To facilitate recovery, we performed qualitative and quantitative analysis of DNA isolated from maternal plasma. METHODS: DNA isolated from maternal blood (n = 15) was compared using five different DNA isolation protocols: two conventional, two column-based, and one magnetic-bead based. Purity and concentration of DNA recovered were determined with a NanoDrop spectrophotometer. Real-time polymerase chain reaction quantification of the beta-globin and DYS1 loci was performed to determine total and fetal-specific genome equivalents, respectively. RESULTS: DNA quality and quantity were different among the five methods tested. Although purity and concentration of total DNA were greatest with the conventional boiling-lysis approach, correct detection of a male fetus was achieved in only 62.5% of cases. DNA isolation using the magnetic beads yielded the highest quantity of total DNA (2018.83 +/- 4.09 GEq/mL), with 100% fetal DNA detection. CONCLUSIONS: Optimal plasma DNA recovery protocols must take into account DNA purity and concentration. We confirm that the magnetic-beads method provides a fast, simple, sensitive, and specific approach to purify plasma DNA. The resulting high-quality DNA facilitates efficient examination of fetal DNA sequences.     

Psychophysiological treatment for learning disabilities: controlled research and evidence.

Research data are presented on the effects of a psychophysiological treatment method for learning disabilities. A total of 238 subjects with learning disabilities were selected based on their school records. Of these, 105 received the full treatment which consisted of the manipulation and maintenance of bilateral electrodermal activity between 6.5-8.5 mu mhos simultaneously combined with increasingly complex perceptual tasks (Mangina, 1981a, b, c; Mangina and Beuzeron-Mangina, 1988). Another 133 subjects with learning disabilities were assigned into four different conditions: (a) classmate controls; (b) only attachment of electrodes; (c) only optimal activation; (d) only perceptual stimulation. Evidence for the effectiveness of the treatment method was found based on different experimental conditions which are presented in this paper. ANOVA and multiple comparison tests indicate that beneficial effects were only obtained by the administration of the full treatment method and were significant at all three time intervals investigated (P less than 0.001). The evidence supports that the treatment method has induced a 'synergistic simultaneity' which is required by the brain both in terms of its bilaterally 'optimal' physiological activation and the appropriate quality of incoming stimulation in order to produce a beneficial neural integration.     

Applying machine learning methods to psychosocial screening data to improve identification of prenatal depression: Implications for clinical practice and research

We utilized machine learning (ML) methods on data from the PROMOTE, a novel psychosocial screening tool, to quantify risk for prenatal depression for individual patients and identify contributing factors that impart greater risk for depression. Random forest algorithms were used to predict likelihood for being at high risk for prenatal depression (Edinburgh Postnatal Depression Scale; EPDS ≥ 13 and/or positive self-injury item) using data from 1715 patients who completed the PROMOTE. Performance matrices were calculated to assess the ability of the PROMOTE to accurately classify patients. Probability for depression was calculated for individual patients. Finally, recursive feature elimination was used to evaluate the importance of each PROMOTE item in the classification of depression risk. PROMOTE data were successfully used to predict depression with acceptable performance matrices (accuracy = 0.80; sensitivity = 0.75; specificity = 0.81; positive predictive value = 0.79; negative predictive value = 0.97). Perceived stress, emotional problems, family support, age, major life events, partner support, unplanned pregnancy, current employment, lifetime abuse, and financial state were the most important PROMOTE items in the classification of depression risk. Results affirm the value of the PROMOTE as a psychosocial screening tool for prenatal depression and the benefit of using it in conjunction with ML methods. Using such methods can help detect underreported outcomes and identify what in patients’ lives makes them more vulnerable, thus paving the way for effective individually tailored precision medicine.

     

Physical methods for structure, dynamics and binding in immunological research

We present four experimental physical methods--X-ray and neutron diffraction, nuclear magnetic resonance spectroscopy, mass spectrometry and calorimetry--and two computational methods--molecular dynamics simulations and electrostatics calculations--which are general and widely applicable in the study of protein structure, dynamics and binding. These methods are useful tools for biologists that lead to structure-function, dynamics-function and binding-function correlations, in efforts to understand biomolecular function. Standard and emerging technologies within these methods are discussed and representative examples of applications in immunology are presented, from antigen-antibody, complement and MHC-T-cell receptor research. The examples demonstrate the power of the reviewed methods in immunological studies at the molecular level.     

A paradigm shift from teaching to learning gross anatomy: meta-analysis of implications for instructional methods

Anatomy teaching in terms of content and methodology has undergone major changes in the recent times due to time constraints, scarcity of cadavers, rapid advances in information technology, and changes in the demands of the medical profession. Moreover, there has been a major paradigm shift in medical education from passive, didactic, and teacher-centered approach to active, clinical-based, and student-centered approach. The debate on how to teach anatomy in the most effective way continues, and there is not yet a workable solution to integrate the two lines of thought (teacher-centered/student-centered) that can resolve the dispute between the two approaches. The present article therefore meta-analyses the role and effectiveness of various instructional modalities in teaching and learning anatomy in the context of the shifting paradigm from teaching to learning. The available literature on the use of various instructional strategies employed for teaching-learning anatomy suggests that the challenge should not be to determine superiority of one methodology over another but to capitalize on the learning benefits offered by the different methods. Learners should be provided opportunity to use multiple resources, thus favoring flexibility in the acquisition of knowledge. Proper amalgamation of traditional teaching methodologies such as lectures and dissection and the newer instructional methods, namely problem-based learning and computer-aided learning, would help to catalyze the shift from pedagogy to andragogy, where educators no longer serve chiefly as the dispensers of the subject content, but act as facilitators of learning and evaluators of competency. The net result should be to produce lifelong learners committed to continuous improvement of skills and knowledge.     

Transgenic rabbit models for biomedical research: Current status, basic methods and future perspectives

The creation of genetically modified laboratory and livestock animals is one of the most dramatic advances derived from recombinant DNA technology. Over the past decade, the development of a large mammal transgenic model, transgenic rabbits, has provided unprecedented opportunities for investigators to study the mechanisms of human diseases and has also provided a novel way to produce foreign proteins for both therapeutic and commercial purposes. Recent progress in gene targeting and animal cloning has opened new avenues for production of transgenic rabbits. In this review, we will introduce the reader to the progress that has been achieved in transgenic rabbits with emphasis on the application of these rabbits as human disease models and bioproducers of human therapeutic proteins.     

Fast permutation tests and related methods,for association between rare variants and binary outcomes

In large‐scale genetic studies, a primary aim is to test for an association between genetic variants and a disease outcome. The variants of interest are often rare and appear with low frequency among subjects. In this situation, statistical tests based on standard asymptotic results do not adequately control the type I error rate, especially if the case : control ratio is unbalanced. In this article, we propose the use of permutation and approximate unconditional tests for testing association with rare variants. We use novel analytical calculations to efficiently approximate the true type I error rate under common study designs, and in numerical studies show that the proposed classes of tests significantly improve upon standard testing methods. We also illustrate our methods in data from a recent case–control study for genetic causes of a severe side effect of a common drug treatment.     

Psychological and pharmacological therapy: methods and modes for comparative outcome research

Psychological and pharmacological comparative outcome studies are reviewed, typically using select examples of cognitive-behavioral interventions from among the psychological therapies and of depression from among the disorders. Special attention is given to methodological considerations such as selecting outcome measures, calibrating the quality of therapy, and investigating client and therapist characteristics and the therapeutic relationship. Discussion includes consideration of various modes of comparison (i.e., quickness of action, side effects, relapse, compliance, cost-effectiveness) that may be used in comparative outcome studies. A disorder-specific approach to comparative outcome research is seen as a necessary step in the progress toward an increasingly sophisticated discrimination of distinctive, complementary, and interactive therapeutic processes.     

Water insecurity: An agenda for research and call to action for human biology

Water insecurity—the lack of adequate and safe water for a healthy and productive life—is one of the greatest threats facing humans in the coming century. By 2030, half of the world is expected to be living in water‐stressed conditions, given current climate change scenarios. A key goal of the UN Water Action Decade and Sustainable Development Goal 6 is to improve water security for the three billion people globally affected, but the future looks grim. For many communities, from Cape Town, South Africa to Flint, United States, the imagined dystopian future of severe water shortages has already arrived—shaped not so much by lack of water, but by aging infrastructure, underfunded utilities, social exclusion, politicized commodification, and environmental racism. Stepping off from my biocultural research in Cochabamba, Bolivia, I discuss how recent research is dramatically advancing our understanding of water insecurity, such as new findings around the biocultural causes and consequences of dehydration, contamination, and water stress. But, much more needs be done to support local communities in creating fair and just water systems. I discuss how human biologists can make crucial contributions toward the advancement of a much‐needed science of water insecurity, while highlighting some practical and ethical challenges to advancing a core mission of providing safe, sufficient water to all.     

New tools for MHC research from machine learning and predictive algorithms to the tumour immunopeptidome

At a time when immunology seeks to progress ever more rapidly from characterization of a microbial or tumour antigen to the immune correlates that may define protective T‐cell immunity, there is a need for robust tools to enable accurate predictions of peptide–major histocompatibility complex (pMHC) and peptide–MHC–T‐cell receptor binding. Improvements in the curation of data sets from high throughput pMHC analysis, such as the NIH Immune Epitope Database (IEDB), and the associated developments of predictive tools rooted in machine‐learning approaches, are having significant impact. When such approaches are linked to the powerful empirical immunopeptidome data sets from peptide MHC elution and mass spectrometry, there is considerable potential for rapid translation to T‐cell therapies and vaccines.