Mechanism and function of drosophila capa GPCR: a desiccation stress-responsive receptor with functional homology to human neuromedinU receptor

The capa peptide receptor, capaR (CG14575), is a G-protein coupled receptor (GPCR) for the D. melanogaster capa neuropeptides, Drm-capa-1 and -2 (capa-1 and -2). To date, the capa peptide family constitutes the only known nitridergic peptides in insects, so the mechanisms and physiological function of ligand-receptor signalling of this peptide family are of interest. Capa peptide induces calcium signaling via capaR with EC50 values for capa-1 = 3.06 nM and capa-2 = 4.32 nM. capaR undergoes rapid desensitization, with internalization via a b-arrestin-2 mediated mechanism but is rapidly re-sensitized in the absence of capa-1. Drosophila capa peptides have a C-terminal -FPRXamide motif and insect-PRXamide peptides are evolutionarily related to vertebrate peptide neuromedinU (NMU). Potential agonist effects of human NMU-25 and the insect -PRLamides [Drosophila pyrokinins Drm-PK-1 (capa-3), Drm-PK-2 and hugin-gamma [hugg]] against capaR were investigated. NMU-25, but not hugg nor Drm-PK-2, increases intracellular calcium ([Ca2+]i) levels via capaR. In vivo, NMU-25 increases [Ca2+]i and fluid transport by the Drosophila Malpighian (renal) tubule. Ectopic expression of human NMU receptor 2 in tubules of transgenic flies results in increased [Ca2+]i and fluid transport. Finally, anti-porcine NMU-8 staining of larval CNS shows that the most highly immunoreactive cells are capa-producing neurons. These structural and functional data suggest that vertebrate NMU is a putative functional homolog of Drm-capa-1 and -2. capaR is almost exclusively expressed in tubule principal cells; cell-specific targeted capaR RNAi significantly reduces capa-1 stimulated [Ca2+]i and fluid transport. Adult capaR RNAi transgenic flies also display resistance to desiccation. Thus, capaR acts in the key fluid-transporting tissue to regulate responses to desiccation stress in the fly

Low-temperature anharmonicity and symmetry breaking in the sodalite

©2018 Walter de Gruyter GmbH, Berlin/Boston 2018. The aluminosilicate iodide sodalite |Na8I2|[AlSiO4]6 was examined by temperature-dependent neutron time-of-flight powder diffraction from 5 K to 290 K and X-ray diffraction from 298 K to 1200 K. The temperature-dependent properties of the mean structure in space group P4 3n were obtained by Rietveld analysis. A negative slope for the thermal expansion coefficient below 50 K could be observed, and the displacement parameters of the iodide ions indicate anharmonic effects. Local structure models (8×8×8 super cells) were refined against pair-distribution functions calculated from total scattering data collected at 5 K, 165 K and 240 K. The results indicate isotropic displacements for all atoms except for I-atoms, showing the effects of an anharmonic potential around this anion at very low temperatures

Detecting CTP truncation artifacts in acute stroke imaging from the arterial input and the vascular output functions

Background: Current guidelines for CT perfusion (CTP) in acute stroke suggest acquiring scans with a minimal duration of 60-70 s. But even then, CTP analysis can be affected by truncation artifacts. Conversely, shorter acquisitions are still widely used in clinical practice and may, sometimes, be sufficient to reliably estimate lesion volumes. We aim to devise an automatic method that detects scans affected by truncation artifacts. Methods: Shorter scan durations are simulated from the ISLES’18 dataset by consecutively removing the last CTP time-point until reaching a 10 s duration. For each truncated series, perfusion lesion volumes are quantified and used to label the series as unreliable if the lesion volumes considerably deviate from the original untruncated ones. Afterwards, nine features from the arterial input function (AIF) and the vascular output function (VOF) are derived and used to fit machine-learning models with the goal of detecting unreliably truncated scans. Methods are compared against a baseline classifier solely based on the scan duration, which is the current clinical standard. The ROC-AUC, precision-recall AUC and the F1-score are measured in a 5-fold cross-validation setting. Results: The best performing classifier obtained an ROC-AUC of 0.982, precision-recall AUC of 0.985 and F1-score of 0.938. The most important feature was the AIF$_{coverage}$, measured as the time difference between the scan duration and the AIF peak. When using the AIF$_{coverage}$ to build a single feature classifier, an ROC-AUC of 0.981, precision-recall AUC of 0.984 and F1-score of 0.932 were obtained. In comparison, the baseline classifier obtained an ROC-AUC of 0.954, precision-recall AUC of 0.958 and F1-Score of 0.875. Conclusions: Machine learning models fed with AIF and VOF features accurately detected unreliable stroke lesion measurements due to insufficient acquisition duration. The AIF$_{coverage}$ was the most predictive feature of truncation and identified unreliable short scans almost as good as machine learning. We conclude that AIF/VOF based classifiers are more accurate than the scans’ duration for detecting truncation. These methods could be transferred to perfusion analysis software in order to increase the interpretability of CTP outputs

AIFNet: Automatic Vascular Function Estimation for Perfusion Analysis Using Deep Learning

Perfusion imaging is crucial in acute ischemic stroke for quantifying the salvageable penumbra and irreversibly damaged core lesions. As such, it helps clinicians to decide on the optimal reperfusion treatment. In perfusion CT imaging, deconvolution methods are used to obtain clinically interpretable perfusion parameters that allow identifying brain tissue abnormalities. Deconvolution methods require the selection of two reference vascular functions as inputs to the model: the arterial input function (AIF) and the venous output function, with the AIF as the most critical model input. When manually performed, the vascular function selection is time demanding, suffers from poor reproducibility and is subject to the professionals' experience. This leads to potentially unreliable quantification of the penumbra and core lesions and, hence, might harm the treatment decision process. In this work we automatize the perfusion analysis with AIFNet, a fully automatic and end-to-end trainable deep learning approach for estimating the vascular functions. Unlike previous methods using clustering or segmentation techniques to select vascular voxels, AIFNet is directly optimized at the vascular function estimation, which allows to better recognise the time-curve profiles. Validation on the public ISLES18 stroke database shows that AIFNet reaches inter-rater performance for the vascular function estimation and, subsequently, for the parameter maps and core lesion quantification obtained through deconvolution. We conclude that AIFNet has potential for clinical transfer and could be incorporated in perfusion deconvolution software.Comment: Preprint submitted to Elsevie

An empirical study of how the Dutch healthcare regulator first formulates the concept of trust and then puts it into practice

Background: Responsive regulation assumes that the parties being regulated are trustworthy and motivated by social responsibility. This assumes that regulation based upon trust will improve the regulated organization more effectively than other regulation models. The purpose of our qualitative study was to unravel the most important elements of trust in the inspectee which can support the inspector’s work and to develop a model and a framework of trust that can be used by the inspectors to legitimize their trust in the inspectee. Methods: We conducted an empirical study on trust regarding the regulation of care services to reveal how trust in the inspectee is conceptualized and assessed. Based on literature and empirical research, we synthesized the concept of trust into six elements, five regarding behavior, and a sixth looking at information about its context. We developed a practical framework for the concept to reduce the conceptual ambiguity, strengthen regulatory assessment, and support appropriate tailoring of the regulatory response. Results: Six elements with respect to trust emerged from the data: showing integrity; transparency; ability to learn; accepting feedback; showing actual change in behavior; context information. These five behavioral elements, plus the context information were merged into a Framework of Trust and designed into an interactive PDF document. Conclusions: This study has sought to address a gap in the empirical knowledge regarding the assessment of trust in the inspectee. The results aim to inform and clarify the regulatory conceptualization and understanding of trust in the inspectee. Other inspectorates may learn from these results for their own practice and explore whether operational deployment of our Framework of Trust effects their assessment and enforcement strategies. Keywords: Trust, Regulation, Inspector, Inspectee, Behavior, Contex

A cross-sectional study into medical students' perceptions of healthcare regulation and self-reported compliance

Background: Although healthcare regulation is commonplace, there is limited evidence of its impact. Making sure that healthcare professionals comply with the regulatory requirements is a prerequisite to achieving effective regulation. Therefore, investigating factors that influence compliance may provide better insights into how regulators can be more effective. This study aimed to find out if medical students' perceptions of regulation in the United Arab Emirates are associated with self-reported regulatory compliance. Methods: In the cross-sectional study, we administered a structured questionnaire to students of medicine with different statements concerning their perceptions of healthcare regulation and self-reported compliance. The statements included statement regarding the legitimacy, fairness and regulatory performance, as well as the risk to getting caught and being punished. The association between perceptions and self-reported compliance was analyzed using multiple regression models. Results: One hundred and six Year 3 and 4 pre-clinical medicine students (56.4% response rate) completed the survey. Almost 40% of the students rated their level of awareness and understanding of regulation as Good or Very Good., despite their lack of direct contact with the regulatory authorities (less than 10% reported monthly or more frequent contact). Self-reported compliance was high with almost 85% of the students either agreeing or strongly agreeing with the four compliance statements (mean score 4.1 out of 5). The findings suggest that positive perceptions of the regulator's performance (β 0.27; 95% CI 0.13-0.41), fairness of the regulatory processes (β 0.25; 95% CI 0.11-0.38) and its legitimacy (β 0.23; 95% CI 0.05-0.41), are stronger associated with compliance than the perceived risks of getting caught and being punished (β 0.10; 95% CI -0.04 - 0.23). Conclusions: To improve compliant behavior, healthcare regulators should pay more attention to their own perceived performance, as well as the perceived fairness and legitimacy of their regulatory processes rather than focusing on more traditional methods of deterrence, such as perceived risk of getting caught and being published

Helicity Control in the Aggregation of Achiral Squaraine Dyes in Solution and Thin Films

Squaraine dyes are well known for their strong absorption in the visible regime. Reports on chiral squaraine dyes are, however, scarce. To address this gap, we here report two novel chiral squaraine dyes and their achiral counterparts. The presented dyes are aggregated in solution and in thin films. A detailed chiroptical study shows that thin films formed by co-assembling the chiral dye with its achiral counterpart exhibit exceptional photophysical properties. The circular dichroism (CD) of the co-assembled structures reaches a maximum when just 25 % of the chiral dye are present in the mixture. The solid structures with the highest relative CD effect are achieved when the chiral dye is used solely as a director, rather than the structural component. The chiroptical data are further supported by selected spin-filtering measurements using mc-AFM. These findings provide a promising platform for investigating the relationship between the dissymmetry of a supramolecular structure and emerging material properties rather than a comparison between a chiral molecular structure and an achiral counterpart