The SPHERE data center: a reference for high contrast imaging processing

The objective of the SPHERE Data Center is to optimize the scientific return of SPHERE at the VLT, by providing optimized reduction procedures, services to users and publicly available reduced data. This paper describes our motivation, the implementation of the service (partners, infrastructure and developments), services, description of the on-line data, and future developments. The SPHERE Data Center is operational and has already provided reduced data with a good reactivity to many observers. The first public reduced data have been made available in 2017. The SPHERE Data Center is gathering a strong expertise on SPHERE data and is in a very good position to propose new reduced data in the future, as well as improved reduction procedures.Comment: SF2A proceeding

Breast cancer spatial heterogeneity in near-infrared spectra and the prediction of neoadjuvant chemotherapy response

We describe an algorithm to calculate an index that characterizes spatial differences in broadband near-infrared [(NIR), 650–1000 nm] absorption spectra of tumor-containing breast tissue. Patient-specific tumor spatial heterogeneities are visualized through a heterogeneity spectrum function (HS). HS is a biomarker that can be attributed to different molecular distributions within the tumor. To classify lesion heterogeneities, we built a heterogeneity index (HI) derived from the HS by weighing the HS in specific NIR absorption bands. It is shown that neoadjuvant chemotherapy (NAC) response is potentially related to the tumor heterogeneity. Therefore, we correlate the heterogeneity index obtained prior to treatment with the final response to NAC. From a pilot study of 15 cancer patients treated with NAC, pathological complete responders (pCR) were separated from non-pCR according to their HI (–44 ± 12 and 43 ± 17, p = 3 × 10(−8), respectively). We conclude that the HS function is a biomarker that can be used to visualize spatial heterogeneities in lesions, and the baseline HI prior to therapy correlates with chemotherapy pathological response

Intrinsic Near-Infrared Spectroscopic Markers of Breast Tumors

We have discovered quantitative optical biomarkers unique to cancer by developing a double-differential spectroscopic analysis method for near-infrared (NIR, 650–1000 nm) spectra acquired non-invasively from breast tumors. These biomarkers are characterized by specific NIR absorption bands. The double-differential method removes patient specific variations in molecular composition which are not related to cancer, and reveals these specific cancer biomarkers. Based on the spectral regions of absorption, we identify these biomarkers with lipids that are present in tumors either in different abundance than in the normal breast or new lipid components that are generated by tumor metabolism. Furthermore, the O-H overtone regions (980–1000 nm) show distinct variations in the tumor as compared to the normal breast. To quantify spectral variation in the absorption bands, we constructed the Specific Tumor Component (STC) index. In a pilot study of 12 cancer patients we found 100% sensitivity and 100% specificity for lesion identification. The STC index, combined with other previously described tissue optical indices, further improves the diagnostic power of NIR for breast cancer detection

A qualitative study of the knowledge-brokering role of middle-level managers in service innovation: managing the translation gap in patient safety for older persons’ care

Background: Brokering of evidence into service delivery is crucial for patient safety. We study knowledge brokering by ‘hybrid’ middle-level managers (H-MLMs), who hold responsibility for clinical service delivery as well as a managerial role, in the context of falls, medication management and transition, in care of older people. Objectives: Generate insight into processes and structures for brokering of patient safety knowledge (PSK) by H-MLMs. Design: We utilise mixed methods: semistructured interviews, social network analysis, observation, documentary analysis, tracer studies and focus groups. Setting: NHS East and NHS West Midlands. Participants: One hundred and twenty-seven H-MLMs, senior managers and professionals, in three hospitals, and external producers of PSK. Main outcome measures: Which H-MLMs broker what PSK, and why? (1) How do H-MLMs broker PSK? (2) What are contextual features for H-MLM knowledge brokering? (3) How can H-MLMs be enabled to broker PSK more effectively in older persons’ care? Results: Health-care organisations fail to leverage PSK for service improvement. Attempts by H-MLMs to broker PSK downwards or upwards are framed by policy directives and professional/managerial hierarchy. External performance targets and incentives compel H-MLMs in clinical governance to focus upon compliance. This diverts attention from pulling knowledge downwards, or upwards, for service improvement. Lower-status H-MLMs, closer to service delivery, struggle to push endogenous knowledge upwards, because they lack professional and managerial legitimacy. There is a difference between how PSK is brokered within ranks of nurses and doctors, due to differences in hierarchal characteristics. Rather than a ‘broker chain’ upwards and downwards, a ‘broken chain’ ensues, which constrains learning and service improvement. Conclusions: Clinical governance is decoupled from service delivery. Brokering knowledge for service improvement is a ‘peopled’ activity in which H-MLMs are central. Intervention needs to mediate interprofessional and intraprofessional hierarchy, which, combined with compliance pressures, engender a ‘broken’ chain for applying PSK for service improvement, rather than a ‘brokering’ chain. Lower-status H-MLMs need to have their legitimacy and disposition enhanced to broker knowledge for service improvement. More informal ‘social mechanisms’ are required to complement clinical governance for development of a brokering chain. More research is needed to (1) examine why some H-MLMs are more disposed and able than others to broker PSK for service improvement, and (2) understand how knowledge brokering might be enhanced so that exogenous and endogenous knowledge is better fused for service improvement

Fluorescence Lifetime Imaging Detects Long-Lifetime Signal Associated with Reduced Pyocyanin at the Surface of Pseudomonas aeruginosa Biofilms and in Cross-Feeding Conditions

Understanding bacterial physiology in real-world environments requires noninvasive approaches and is a challenging yet necessary endeavor to effectively treat infectious disease. Bacteria evolve strategies to tolerate chemical gradients associated with infections. The DIVER (Deep Imaging Via Enhanced Recovery) microscope can image autofluorescence and fluorescence lifetime throughout samples with high optical scattering, enabling the study of naturally formed chemical gradients throughout intact biofilms. Using the DIVER, a long fluorescent lifetime signal associated with reduced pyocyanin, a molecule for electron cycling in low oxygen, was detected in low-oxygen conditions at the surface of Pseudomonas aeruginosa biofilms and in the presence of fermentation metabolites from Rothia mucilaginosa, which cocolonizes infected airways with P. aeruginosa. These findings underscore the utility of the DIVER microscope and fluorescent lifetime for noninvasive studies of bacterial physiology within complex environments, which could inform on more effective strategies for managing chronic infection

An imaged 15Mjup companion within a hierarchical quadruple system

Since 2019, the direct imaging B-star Exoplanet Abundance Study (BEAST) at SPHERE@VLT has been scanning the surroundings of young B-type stars in order to ascertain the ultimate frontiers of giant planet formation. Recently, the $17^{+3}_{-4}$ Myr HIP 81208 was found to host a close-in (~50 au) brown dwarf and a wider (~230 au) late M star around the central 2.6Msun primary. Alongside the continuation of the survey, we are undertaking a complete reanalysis of archival data aimed at improving detection performances so as to uncover additional low-mass companions. We present here a new reduction of the observations of HIP 81208 using PACO ASDI, a recent and powerful algorithm dedicated to processing high-contrast imaging datasets, as well as more classical algorithms and a dedicated PSF-subtraction approach. The combination of different techniques allowed for a reliable extraction of astrometric and photometric parameters. A previously undetected source was recovered at a short separation from the C component of the system. Proper motion analysis provided robust evidence for the gravitational bond of the object to HIP 81208 C. Orbiting C at a distance of ~20 au, this 15Mjup brown dwarf becomes the fourth object of the hierarchical HIP 81208 system. Among the several BEAST stars which are being found to host substellar companions, HIP 81208 stands out as a particularly striking system. As the first stellar binary system with substellar companions around each component ever found by direct imaging, it yields exquisite opportunities for thorough formation and dynamical follow-up studies.Comment: 12 pages, 9 figures, 5 tables. Accepted for publication as a Letter in Astronomy and Astrophysics, section 1. Letters to the Edito

Genome-wide association study meta-analysis provides insights into the etiology of heart failure and its subtypes

Heart failure (HF) is a major contributor to global morbidity and mortality. While distinct clinical subtypes, defined by etiology and left ventricular ejection fraction, are well recognized, their genetic determinants remain inadequately understood. In this study, we report a genome-wide association study of HF and its subtypes in a sample of 1.9 million individuals. A total of 153,174 individuals had HF, of whom 44,012 had a nonischemic etiology (ni-HF). A subset of patients with ni-HF were stratified based on left ventricular systolic function, where data were available, identifying 5,406 individuals with reduced ejection fraction and 3,841 with preserved ejection fraction. We identify 66 genetic loci associated with HF and its subtypes, 37 of which have not previously been reported. Using functionally informed gene prioritization methods, we predict effector genes for each identified locus, and map these to etiologic disease clusters through phenome-wide association analysis, network analysis and colocalization. Through heritability enrichment analysis, we highlight the role of extracardiac tissues in disease etiology. We then examine the differential associations of upstream risk factors with HF subtypes using Mendelian randomization. These findings extend our understanding of the mechanisms underlying HF etiology and may inform future approaches to prevention and treatment

Genome-wide association study meta-analysis provides insights into the etiology of heart failure and its subtypes

Heart failure (HF) is a major contributor to global morbidity and mortality. While distinct clinical subtypes, defined by etiology and left ventricular ejection fraction, are well recognized, their genetic determinants remain inadequately understood. In this study, we report a genome-wide association study of HF and its subtypes in a sample of 1.9 million individuals. A total of 153,174 individuals had HF, of whom 44,012 had a nonischemic etiology (ni-HF). A subset of patients with ni-HF were stratified based on left ventricular systolic function, where data were available, identifying 5,406 individuals with reduced ejection fraction and 3,841 with preserved ejection fraction. We identify 66 genetic loci associated with HF and its subtypes, 37 of which have not previously been reported. Using functionally informed gene prioritization methods, we predict effector genes for each identified locus, and map these to etiologic disease clusters through phenome-wide association analysis, network analysis and colocalization. Through heritability enrichment analysis, we highlight the role of extracardiac tissues in disease etiology. We then examine the differential associations of upstream risk factors with HF subtypes using Mendelian randomization. These findings extend our understanding of the mechanisms underlying HF etiology and may inform future approaches to prevention and treatment.</p

Genome-wide association study meta-analysis provides insights into the etiology of heart failure and its subtypes

Heart failure (HF) is a major contributor to global morbidity and mortality. While distinct clinical subtypes, defined by etiology and left ventricular ejection fraction, are well recognized, their genetic determinants remain inadequately understood. In this study, we report a genome-wide association study of HF and its subtypes in a sample of 1.9 million individuals. A total of 153,174 individuals had HF, of whom 44,012 had a nonischemic etiology (ni-HF). A subset of patients with ni-HF were stratified based on left ventricular systolic function, where data were available, identifying 5,406 individuals with reduced ejection fraction and 3,841 with preserved ejection fraction. We identify 66 genetic loci associated with HF and its subtypes, 37 of which have not previously been reported. Using functionally informed gene prioritization methods, we predict effector genes for each identified locus, and map these to etiologic disease clusters through phenome-wide association analysis, network analysis and colocalization. Through heritability enrichment analysis, we highlight the role of extracardiac tissues in disease etiology. We then examine the differential associations of upstream risk factors with HF subtypes using Mendelian randomization. These findings extend our understanding of the mechanisms underlying HF etiology and may inform future approaches to prevention and treatment