The impact of an interprofessional training ward on the development of interprofessional competencies: study protocol of a longitudinal mixed-methods study

Background: To meet the patients’ needs and to provide adequate health care, students need to be prepared for interprofessional collaborative practice during their undergraduate education. On interprofessional training wards (IPTW) undergraduates of various health care professions potentially develop a mutual understanding and improve their interprofessional competencies in clinical practice. To enhance collaboration of 6th-year medical students and nursing trainees in the third year of their vocational training an IPTW (Heidelberger Interprofessionelle Ausbildungsstation – HIPSTA) was implemented at the University Hospital Heidelberg, Germany. On HIPSTA future physicians and nurses take care of the patients self responsibly and in close interprofessional collaboration, supervised by facilitators of both professions. Although there are positive experiences with IPTWs internationally, little is known about the impact of IPTW on the acquisition of interprofessional competencies. For future interprofessional training and implementation of IPTWs evaluation of interprofessional learning and collaborative practice on Germany’s first IPTW is of high relevance. Methods: To evaluate the acquisition of interprofessional competencies the study follows a mixed-methods approach. Quantitative data is collected from undergraduate participants, staff participants and facilitators on HIPSTA (intervention group) and undergraduate participants and staff participants on a comparable ‘conventional’ ward without special interprofessional training (comparison group) immediately pre and post HIPSTA and, as follow-up, after three to six months (T0, T1, T2), using three questionnaires, namely the University of the West of England Interprofessional Questionnaire (UWE-IP), the Interprofessional Socialization and Valuing Scale (ISVS) and the Assessment of Interprofessional Team Collaboration Scale (AITCS). Qualitative data is gathered in form of interviews and focus groups based on semi structured guidelines, video recordings of handovers and overt non-participant observations of daily rounds. Quantitative data will be analysed in a longitudinal comparison, presented descriptively and tested with an analysis of variance. Qualitative data will be analysed deductively and inductively. Discussion: The results of the evaluation will give insight in undergraduates’, staff’s and facilitators’ experiences and their self-perception of competency development. In addition the results will help identify benefits, challenges and areas for modification when implementing and establishing similar interprofessional training wards

A clinical approach to the diagnosis of patients with leukodystrophies and genetic leukoencephelopathies

Leukodystrophies (LD) and genetic leukoencephalopathies (gLE) are disorders that result in white matter abnormalities in the central nervous system (CNS). Magnetic resonance (MR) imaging (MRI) has dramatically improved and systematized the diagnosis of LDs and gLEs, and in combination with specific clinical features, such as Addison’s disease in Adrenoleukodystrophy or hypodontia in Pol-III related or 4H leukodystrophy, can often resolve a case with a minimum of testing. The diagnostic odyssey for the majority LD and gLE patients, however, remains extensive – many patients will wait nearly a decade for a definitive diagnosis and at least half will remain unresolved. The combination of MRI, careful clinical evaluation and next generation genetic sequencing holds promise for both expediting the diagnostic process and dramatically reducing the number of unresolved cases. Here we present a workflow detailing the Global Leukodystrophy Initiative (GLIA) consensus recommendations for an approach to clinical diagnosis, including salient clinical features suggesting a specific diagnosis, neuroimaging features and molecular genetic testing. We also discuss recommendations on the use of broad-spectrum next-generation sequencing in instances of ambiguous MRI or clinical findings. We conclude with a proposal for systematic trials of genome-wide agnostic testing as a first line diagnostic in LDs and gLEs given the increasing number of genes associated with these disorders

High density lipoprotein mediates anti-inflammatory transcriptional reprogramming of macrophages via the transcriptional repressor ATF3

High Density Lipoprotein (HDL) mediates reverse cholesterol transport and it is known to be protective against atherosclerosis. In addition, HDL has potent anti-inflammatory properties that may be critical for protection against other inflammatory diseases. The molecular mechanisms of how HDL can modulate inflammation, particularly in immune cells such as macrophages, remain poorly understood. Here we identify the transcriptional repressor ATF3, as an HDL-inducible target gene in macrophages that down-regulates the expression of Toll-like receptor (TLR)-induced pro-inflammatory cytokines. The protective effects of HDL against TLR-induced inflammation were fully dependent on ATF3 in vitro and in vivo. Our findings may explain the broad anti-inflammatory and metabolic actions of HDL and provide the basis for predicting the success of novel HDL-based therapies

Attribution of multi-annual to decadal changes in the climate system: The Large Ensemble Single Forcing Model Intercomparison Project (LESFMIP)

Multi-annual to decadal changes in climate are accompanied by changes in extreme events that cause major impacts on society and severe challenges for adaptation. Early warnings of such changes are now potentially possible through operational decadal predictions. However, improved understanding of the causes of regional changes in climate on these timescales is needed both to attribute recent events and to gain further confidence in forecasts. Here we document the Large Ensemble Single Forcing Model Intercomparison Project that will address this need through coordinated model experiments enabling the impacts of different external drivers to be isolated. We highlight the need to account for model errors and propose an attribution approach that exploits differences between models to diagnose the real-world situation and overcomes potential errors in atmospheric circulation changes. The experiments and analysis proposed here will provide substantial improvements to our ability to understand near-term changes in climate and will support the World Climate Research Program Lighthouse Activity on Explaining and Predicting Earth System Change.publishedVersio

BRCA2 polymorphic stop codon K3326X and the risk of breast, prostate, and ovarian cancers

Background: The K3326X variant in BRCA2 (BRCA2*c.9976A>T; p.Lys3326*; rs11571833) has been found to be associated with small increased risks of breast cancer. However, it is not clear to what extent linkage disequilibrium with fully pathogenic mutations might account for this association. There is scant information about the effect of K3326X in other hormone-related cancers. Methods: Using weighted logistic regression, we analyzed data from the large iCOGS study including 76 637 cancer case patients and 83 796 control patients to estimate odds ratios (ORw) and 95% confidence intervals (CIs) for K3326X variant carriers in relation to breast, ovarian, and prostate cancer risks, with weights defined as probability of not having a pathogenic BRCA2 variant. Using Cox proportional hazards modeling, we also examined the associations of K3326X with breast and ovarian cancer risks among 7183 BRCA1 variant carriers. All statistical tests were two-sided. Results: The K3326X variant was associated with breast (ORw = 1.28, 95% CI = 1.17 to 1.40, P = 5.9x10- 6) and invasive ovarian cancer (ORw = 1.26, 95% CI = 1.10 to 1.43, P = 3.8x10-3). These associations were stronger for serous ovarian cancer and for estrogen receptor–negative breast cancer (ORw = 1.46, 95% CI = 1.2 to 1.70, P = 3.4x10-5 and ORw = 1.50, 95% CI = 1.28 to 1.76, P = 4.1x10-5, respectively). For BRCA1 mutation carriers, there was a statistically significant inverse association of the K3326X variant with risk of ovarian cancer (HR = 0.43, 95% CI = 0.22 to 0.84, P = .013) but no association with breast cancer. No association with prostate cancer was observed. Conclusions: Our study provides evidence that the K3326X variant is associated with risk of developing breast and ovarian cancers independent of other pathogenic variants in BRCA2. Further studies are needed to determine the biological mechanism of action responsible for these associations

Differential limit on the extremely-high-energy cosmic neutrino flux in the presence of astrophysical background from nine years of IceCube data

We report a quasi-differential upper limit on the extremely-high-energy (EHE) neutrino flux above $5\times 10^{6}$ GeV based on an analysis of nine years of IceCube data. The astrophysical neutrino flux measured by IceCube extends to PeV energies, and it is a background flux when searching for an independent signal flux at higher energies, such as the cosmogenic neutrino signal. We have developed a new method to place robust limits on the EHE neutrino flux in the presence of an astrophysical background, whose spectrum has yet to be understood with high precision at PeV energies. A distinct event with a deposited energy above $10^{6}$ GeV was found in the new two-year sample, in addition to the one event previously found in the seven-year EHE neutrino search. These two events represent a neutrino flux that is incompatible with predictions for a cosmogenic neutrino flux and are considered to be an astrophysical background in the current study. The obtained limit is the most stringent to date in the energy range between $5 \times 10^{6}$ and $5 \times 10^{10}$ GeV. This result constrains neutrino models predicting a three-flavor neutrino flux of $E_\nu^2\phi_{\nu_e+\nu_\mu+\nu_\tau}\simeq2\times 10^{-8}\ {\rm GeV}/{\rm cm}^2\ \sec\ {\rm sr}$at$10^9\ {\rm GeV}$. A significant part of the parameter-space for EHE neutrino production scenarios assuming a proton-dominated composition of ultra-high-energy cosmic rays is excluded.Comment: The version accepted for publication in Physical Review

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment