A Local Superlens

Superlenses enable near-field imaging beyond the optical diffraction limit. However, their widespread implementation in optical imaging technology so far has been limited by large-scale fabrication, fixed lens position, and specific object materials. Here we demonstrate that a dielectric lamella of subwavelength size in all three spatial dimensions behaves as a compact superlens that operates at infrared wavelengths and can be positioned to image any local microscopic area of interest on the sample. In particular, the lamella superlens may be placed in contact with any type of object and therefore enables examination of hard-to-scan samples, for example, with high topography or in liquids, without altering the specimen design. This lamella-based local superlens design is directly applicable to subwavelength light-based technology, such as integrated optics

Evidence for replicative mechanism in a CHD7 rearrangement in a patient with CHARGE syndrome

Haploinsufficiency of CHD7 (OMIM# 608892) is known to cause CHARGE syndrome (OMIM# 214800). Molecular testing supports a definitive diagnosis in approximately 65-70% of cases. Most CHD7 mutations arise de novo, and no mutations affecting exon-7 have been reported to date. We report on an 8-year-old girl diagnosed with CHARGE syndrome that was referred to our laboratory for comprehensive CHD7 gene screening. Genomic DNA from the subject with a suspected diagnosis of CHARGE was isolated from peripheral blood lymphocytes and comprehensive Sanger sequencing, along with deletion/duplication analysis of the CHD7 gene using multiplex ligation-dependent probe amplification (MLPA), was performed. MLPA analysis identified a reduced single probe signal for exon-7 of the CHD7 gene consistent with potential heterozygous deletion. Long-range PCR breakpoint analysis identified a complex genomic rearrangement (CGR) leading to the deletion of exon-7 and breakpoints consistent with a replicative mechanism such as fork stalling and template switching (FoSTeS) or microhomology-mediated break-induced replication (MMBIR). Taken together this represents the first evidence for a CHD7 intragenic CGR in a patient with CHARGE syndrome leading to what appears to be also the first report of a mutation specifically disrupting exon-7. Although likely rare, CGR may represent an overlooked mechanism in subjects with CHARGE syndrome that can be missed by current sequencing and dosage assays

Comparison of magnetic resonance imaging and computed tomography for breast target volume delineation in prone and supine positions

Purpose To\ua0determine whether T2-weighted MRI improves seroma cavity (SC) and whole breast (WB) interobserver conformity for radiation therapy purposes, compared with the gold standard of CT, both in the prone and supine positions. Methods and Materials Eleven observers (2 radiologists and 9 radiation oncologists) delineated SC and WB clinical target volumes (CTVs) on T2-weighted MRI and CT supine and prone scans (4 scans per patient) for 33 patient datasets. Individual observer's volumes were compared using the Dice similarity coefficient, volume overlap index, center of mass shift, and Hausdorff distances. An average cavity visualization score was also determined. Results Imaging modality did not affect interobserver variation for WB CTVs. Prone WB CTVs were larger in volume and more conformal than supine CTVs (on both MRI and CT). Seroma cavity volumes were larger on CT than on MRI. Seroma cavity volumes proved to be comparable in interobserver conformity in both modalities (volume overlap index of 0.57\ua0(95% Confidence Interval (CI) 0.54-0.60) for CT supine and 0.52\ua0(95% CI 0.48-0.56) for MRI supine, 0.56\ua0(95% CI 0.53-0.59) for CT prone and 0.55\ua0(95% CI 0.51-0.59) for MRI prone); however, after registering modalities together the intermodality variation (Dice similarity coefficient of 0.41\ua0(95% CI 0.36-0.46) for supine and 0.38\ua0(0.34-0.42) for prone) was larger than the interobserver variability for SC, despite the location typically remaining constant. Conclusions Magnetic resonance imaging interobserver variation was comparable to CT for the WB CTV and SC delineation, in both prone and supine positions. Although the cavity visualization score and interobserver concordance was not significantly higher for MRI than for CT, the SCs were smaller on MRI, potentially owing to clearer SC definition, especially on T2-weighted MR images

Early onset obesity and adrenal insufficiency associated with a homozygous POMC mutation

Isolated hypocortisolism due to ACTH deficiency is a rare condition that can be caused by homozygous or compound heterozygous mutations in the gene encoding proopiomelanocortin (POMC). Loss of function mutations of POMC gene typically results in adrenal insufficiency, obesity and red hair. We describe an 18 month old Hispanic female with congenital adrenal insufficiency, a novel POMC mutation and atypical clinical features. The patient presented at the age of 9 months with hypoglycemia and the endocrine evaluation resulted in a diagnosis of ACTH deficiency. She developed extreme weight gain prompting sequence analysis of POMC, which revealed a homozygous c.231C > A change which is predicted to result in a premature termination codon. The case we report had obesity, hypocortisolism but lacked red hair which is typical for subjects with POMC mutations. Mutations of POMC should be considered in individuals with severe early onset obesity and adrenal insufficiency even when they lack the typical pigmentary phenotype

PAH–DNA Adducts, Cigarette Smoking, GST Polymorphisms, and Breast Cancer Risk

BackgroundPolycyclic aromatic hydrocarbons (PAHs) may increase breast cancer risk, and the association may be modified by inherited differences in deactivation of PAH intermediates by glutathione S-transferases (GSTs). Few breast cancer studies have investigated the joint effects of multiple GSTs and a PAH biomarker.ObjectiveWe estimated the breast cancer risk associated with multiple polymorphisms in the GST gene (GSTA1, GSTM1, GSTP1, and GSTT1) and the interaction with PAH–DNA adducts and cigarette smoking.MethodsWe conducted unconditional logistic regression using data from a population-based sample of women (cases/controls, respectively): GST polymorphisms were genotyped using polymerase chain reaction and matrix-assisted laser desorption/ionization time-of-flight assays (n = 926 of 916), PAH–DNA adduct blood levels were measured by competitive enzyme-linked immunosorbent assay (n = 873 of 941), and smoking status was assessed by in-person questionnaires (n = 943 of 973).ResultsOdds ratios for joint effects on breast cancer risk among women with at least three variant alleles were 1.56 [95% confidence interval (CI), 1.13–2.16] for detectable PAH–DNA adducts and 0.93 (95% CI, 0.56–1.56) for no detectable adducts; corresponding odds ratios for three or more variants were 1.18 (95% CI, 0.82–1.69) for ever smokers and 1.44 (95% CI, 0.97–2.14) for never smokers. Neither interaction was statistically significant (p = 0.43 and 0.62, respectively).ConclusionWe found little statistical evidence that PAHs interacted with GSTT1, GSTM1, GSTP1, and GSTA1 polymorphisms to further increase breast cancer risk

Beyond adoption: A new framework for theorising and evaluating Non-adoption, Abandonment and challenges to Scale-up, Spread and Sustainability (NASSS) of health and care technologies

© 2017 The Author(s). This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.Background: Many promising technological innovations in health and social care are characterized by nonadoption or abandonment by individuals or by failed attempts to scale up locally, spread distantly, or sustain the innovation long term at the organization or system level. Objective: Our objective was to produce an evidence-based, theory-informed, and pragmatic framework to help predict and evaluate the success of a technology-supported health or social care program. Methods: The study had 2 parallel components: (1) secondary research (hermeneutic systematic review) to identify key domains, and (2) empirical case studies of technology implementation to explore, test, and refine these domains. We studied 6 technology-supported programs—video outpatient consultations, global positioning system tracking for cognitive impairment, pendant alarm services, remote biomarker monitoring for heart failure, care organizing software, and integrated case management via data sharing—using longitudinal ethnography and action research for up to 3 years across more than 20 organizations. Data were collected at micro level (individual technology users), meso level (organizational processes and systems), and macro level (national policy and wider context). Analysis and synthesis was aided by sociotechnically informed theories of individual, organizational, and system change. The draft framework was shared with colleagues who were introducing or evaluating other technology-supported health or care programs and refined in response to feedback. Results: The literature review identified 28 previous technology implementation frameworks, of which 14 had taken a dynamic systems approach (including 2 integrative reviews of previous work). Our empirical dataset consisted of over 400 hours of ethnographic observation, 165 semistructured interviews, and 200 documents. The final nonadoption, abandonment, scale-up, spread, and sustainability (NASSS) framework included questions in 7 domains: the condition or illness, the technology, the value proposition, the adopter system (comprising professional staff, patient, and lay caregivers), the organization(s), the wider (institutional and societal) context, and the interaction and mutual adaptation between all these domains over time. Our empirical case studies raised a variety of challenges across all 7 domains, each classified as simple (straightforward, predictable, few components), complicated (multiple interacting components or issues), or complex (dynamic, unpredictable, not easily disaggregated into constituent components). Programs characterized by complicatedness proved difficult but not impossible to implement. Those characterized by complexity in multiple NASSS domains rarely, if ever, became mainstreamed. The framework showed promise when applied (both prospectively and retrospectively) to other programs.Peer reviewe

Polymorphisms in oxidative stress genes, physical activity, and breast cancer risk

The mechanisms driving the physical activity–breast cancer association are unclear. Exercise both increases reactive oxygen species production, which may transform normal epithelium to a malignant phenotype, and enhances antioxidant capacity, which could protect against subsequent oxidative insult. Given the paradoxical effects of physical activity, the oxidative stress pathway is of interest. Genetic variation in CAT or antioxidant-related polymorphisms may mediate the physical activity–breast cancer association

A visual and curatorial approach to clinical variant prioritization and disease gene discovery in genome-wide diagnostics

Background: Genome-wide data are increasingly important in the clinical evaluation of human disease. However, the large number of variants observed in individual patients challenges the efficiency and accuracy of diagnostic review. Recent work has shown that systematic integration of clinical phenotype data with genotype information can improve diagnostic workflows and prioritization of filtered rare variants. We have developed visually interactive, analytically transparent analysis software that leverages existing disease catalogs, such as the Online Mendelian Inheritance in Man database (OMIM) and the Human Phenotype Ontology (HPO), to integrate patient phenotype and variant data into ranked diagnostic alternatives. Methods: Our tool, “OMIM Explorer” (http://www.omimexplorer.com), extends the biomedical application of semantic similarity methods beyond those reported in previous studies. The tool also provides a simple interface for translating free-text clinical notes into HPO terms, enabling clinical providers and geneticists to contribute phenotypes to the diagnostic process. The visual approach uses semantic similarity with multidimensional scaling to collapse high-dimensional phenotype and genotype data from an individual into a graphical format that contextualizes the patient within a low-dimensional disease map. The map proposes a differential diagnosis and algorithmically suggests potential alternatives for phenotype queries—in essence, generating a computationally assisted differential diagnosis informed by the individual’s personal genome. Visual interactivity allows the user to filter and update variant rankings by interacting with intermediate results. The tool also implements an adaptive approach for disease gene discovery based on patient phenotypes. Results: We retrospectively analyzed pilot cohort data from the Baylor Miraca Genetics Laboratory, demonstrating performance of the tool and workflow in the re-analysis of clinical exomes. Our tool assigned to clinically reported variants a median rank of 2, placing causal variants in the top 1 % of filtered candidates across the 47 cohort cases with reported molecular diagnoses of exome variants in OMIM Morbidmap genes. Our tool outperformed Phen-Gen, eXtasy, PhenIX, PHIVE, and hiPHIVE in the prioritization of these clinically reported variants. Conclusions: Our integrative paradigm can improve efficiency and, potentially, the quality of genomic medicine by more effectively utilizing available phenotype information, catalog data, and genomic knowledge