220 research outputs found

    Resolving HD 100546 disc in the mid-infrared: Small inner disc and asymmetry near the gap

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    A region of roughly half of the solar system scale around the star HD 100546 is largely cleared of gas and dust, in contrast to the bright outer disc. However, some material is observed in the immediate vicinity of the star. We investigate how the dust is distributed within and outside the gap, and constrain the disc geometry with mid-infrared interferometric observations using VLTI/MIDI. With baseline lengths of 40m, our long baseline observations are sensitive to the inner few AU from the star, and we combined them with observations at shorter, 15m baselines, to probe emission beyond the gap at up to 20AU from the star. We modelled the mid-infrared emission using radial temperature profiles. Our model is composed of infinitesimal concentric annuli emitting as black bodies, and it has distinct inner and outer disc components. We derived an upper limit of 0.7AU for the radial size of the inner disc, from our longest baseline data. This small dusty disc is separated from the edge of the outer disc by a large, roughly 10AU wide gap. Our short baseline data place a bright ring of emission at 11+-1AU, consistent with prior observations of the transition region between the gap and the outer disc, known as the disc wall. The inclination and position angle are constrained by our data to i=53+-8deg and PA=145+-5deg. Compared to the rim and outer disc geometry this suggests co-planarity. Brightness asymmetry is evident in both short and long baseline data, and it is unequivocally discernible from any atmospheric or instrumental effects. The origin of the asymmetry is consistent with the bright disc wall, which we find to be 1-2AU wide. The gap is cleared of micron-sized dust, but we cannot rule out the presence of larger particles and/or perturbing bodies.Comment: 12 pages, 9 figures, accepted for publication in A&

    Deep learning to segment liver metastases on CT images: Impact on a radiomics method to predict response to chemotherapy

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    Predicting response to neo-adjuvant chemotherapy of liver metastases (mts) using CT images is of key importance to provide personalized treatments. However, manual segmentation of mts should be avoid to develop methods that could be integrated into the clinical practice. The aim of this study is to evaluate if and how much automatic segmentation can affect a radiomics-based method to predict response to neoadjuvant chemotherapy of individual liver mts. To this scope, we developed an automatic deep learning method to segment liver mts, based on the U-net architecture, and we compared the classification results of a classifier fed with manual and automatic masks. In the validation set composed of 39 liver mts, the automatic deeplearning algorithm was able to detect 82% of mts, with a median precision of 67%. Using manual and automatic masks, we obtained the same classification in 19/32 mts. In case of mts with largest diameter > 20 mm, the precision of the segmentation does not impact the classification results and we obtained the same classification with both masks. Conversely, with smaller mts, we showed that a Dice coefficient of at least 0.5 should be obtained to extract the same information from the two segmentations. This are very important results in the perspective of using radiomics-based approach to predict response to therapy into clinical practice. Indeed, either precisely manually segment all lesions or refine them after automatic segmentation is a time-consuming task that cannot be performed on a daily basis

    Testing lupus anticoagulants in a real-life scenario - a retrospective cohort study

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    Introduction: Lupus anticoagulant (LAC) testing is challenging. Most data are derived from a well-controlled study environment with potential alterations to daily routines. The aim of this retrospective cohort study was to assess the capacity of various LAC screening tests and derived mixing tests to predict a positive result in subsequent confirmation tests in a large cohort of patients. Materials and methods: In 5832 individuals, we retrospectively evaluated the accuracy of the aPTT-A, aPTT-LAscreen, aPTT-FS and dRVVTscreen and of their derived mixing tests in detecting a positive confirmation test result within the same blood specimen. The group differences, degree of correlation and the predictive accuracy of LAC coagulation tests were analysed using the Mann-Whitney U test, the Spearman-rank-correlation and by area under the receiver operating characteristic curve (ROC-AUC) analysis. ROC-AUCs were compared with the Venkatraman´s permutation test. Results: The pre-test probability of patients with clinically suspected LAC was 36% in patients without factor deficiency or anticoagulation therapy. The aPTT-LAscreen showed the best diagnostic accuracy with a ROC-AUC of 0.84 (95% CI: 0.82 – 0.86). No clear advantage of the dRVVT-derived mixing test was detectable when compared to the dRVVTscreen (P = 0.829). Usage of the index of circulating anticoagulant (ICA) did not improve the diagnostic power of respective mixing tests. Conclusions: Among the parameters evaluated, aPTT-LAscreen and derived mixing test parameters were the most accurate tests. In our study cohort, neither other mixing test nor the ICA presented any further advantage in LAC diagnostics

    Comparison of different classifiers to recognize active bone marrow from CT images

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    One of the main problems during in the treatment of anal cancer with chemotherapy and radiation is the occurrence of Hematologic Toxicity (HT). In particular, during radiotherapy it is crucial to spare Bone Marrow (BM), since the radiation dose received by BM in pelvic bones predicts the onset of HT. In this direction, the most popular strategies are based on the identification of the hematopoietically active BM (actBM), that is the part of BM in charge of blood cells generation, using MRI, SPECT or PET, but no approached have been proposed based on CT. In this study we compare four different classifiers in recognizing actBM from CT images using 36 radiomic features. We used Genetic Algorithms (GAs) to simultaneously optimize the feature subsets and the classifier parameters, separately for three pelvic subregions: iliac bone marrow (IBM), lower pelvis bone marrow (LPBM), and lumbosacral bone marrow (LSBM). The obtained classifiers were applied to CT sequences of a cohort of 25 patients affected by carcinoma of the anal canal. Classifiers results were compared with the actBM identified from 18FDG-PET (reference standard, RS). It emerged that the performances of the 4 classifiers are similar and they are satisfactory for IBM and LSBM subregions (Dice > 0.7) whereas they are poor for LPBM (Dice < 0.5)

    Deep learning model for automatic prostate segmentation on bicentric T2w images with and without endorectal coil

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    Automatic segmentation of the prostate on Magnetic Resonance Imaging (MRI) is one of the topics on which research has focused in recent years as it is a fundamental first step in the building process of a Computer aided diagnosis (CAD) system for cancer detection. Unfortunately, MRI acquired in different centers with different scanners leads to images with different characteristics. In this work, we propose an automatic algorithm for prostate segmentation, based on a U-Net applying transfer learning method in a bi-center setting. First, T2w images with and without endorectal coil from 80 patients acquired at Center A were used as training set and internal validation set. Then, T2w images without endorectal coil from 20 patients acquired at Center B were used as external validation. The reference standard for this study was manual segmentation of the prostate gland performed by an expert operator. The results showed a Dice similarity coefficient >85% in both internal and external validation datasets.Clinical Relevance- This segmentation algorithm could be integrated into a CAD system to optimize computational effort in prostate cancer detection

    Pancreatic Cancer Malnutrition and Pancreatic Exocrine Insufficiency in the Course of Chemotherapy in Unresectable Pancreatic Cancer

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    Background: Malnutrition and cachexia are common in patients with advanced pancreatic ductal adenocarcinoma (PDAC) and have a significant influence on the tolerance and response to treatments. If timely identified, malnourished PDAC patients could be treated to increase their capacity to complete the planned treatments and, therefore, possibly, improve their efficacy. Aims: The aim of this study is to assess the impact of nutritional status, pancreatic exocrine insufficiency (PEI), and other clinical factors on patient outcomes in patients with advanced PDAC. Methods: PAncreatic Cancer MAlnutrition and Pancreatic Exocrine INsufficiency in the Course of Chemotherapy in Unresectable Pancreatic Cancer (PAC-MAIN) is an international multicenter prospective observational cohort study. The nutritional status will be determined by means of Mini-Nutritional Assessment score and laboratory blood tests. PEI will be defined by reduced fecal elastase levels. MAIN OUTCOME: adherence to planned chemotherapy in the first 12 weeks following the diagnosis, according to patients' baseline nutritional status and quantified and reported as "percent of standard chemotherapy dose delivered." SECONDARY OUTCOMES: rate of chemotherapy-related toxicity, progression-free survival, survival at 6 months, overall survival, quality of life, and the number of hospitalizations. ANALYSIS: chemotherapy dosing over the first 12 weeks of therapy (i.e., percent of chemotherapy received in the first 12 weeks, as defined above) will be compared between well-nourished and malnourished patients. SAMPLE SIZE: based on an expected percentage of chemotherapy delivered of 70% in well-nourished patients, with a type I error of 0.05 and a type II error of 0.20, a sample size of 93 patients per group will be required in case of a percentage difference of chemotherapy delivered of 20% between well-nourished and malnourished patients, 163 patients per group in case of a difference of 15% between the groups, and 356 patients per group in case of a 10% difference. Centers from Russia, Romania, Turkey, Spain, Serbia, and Italy will participate in the study upon Local Ethics Committee approval. Discussion: PAC-MAIN will provide insights into the role of malnutrition and PEI in the outcomes of PDAC. The study protocol was registered at clinicaltrials.gov as NCT04112836

    Linking gastrointestinal microbiota and metabolome dynamics to clinical outcomes in paediatric haematopoietic stem cell transplantation

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    Background: Haematopoietic stem cell transplantation is a curative procedure for a variety of conditions. Despite major advances, a plethora of adverse clinical outcomes can develop post-transplantation including graft-versus-host disease and infections, which remain the major causes of morbidity and mortality. There is increasing evidence that the gastrointestinal microbiota is associated with clinical outcomes post-haematopoietic stem cell transplantation. Herein, we investigated the longitudinal dynamics of the gut microbiota and metabolome and potential associations to clinical outcomes in paediatric haematopoietic stem cell transplantation at a single centre. Results: On admission (baseline), the majority of patients presented with a different gut microbial composition in comparison with healthy control children with a significantly lower alpha diversity. A further, marked decrease in alpha diversity was observed immediately post-transplantation and in most microbial diversity, and composition did not return to baseline status whilst hospitalised. Longitudinal trajectories identified continuous fluctuations in microbial composition, with the dominance of a single taxon in a significant proportion of patients. Using pam clustering, three clusters were observed in the dataset. Cluster 1 was common pre-transplantation, characterised by a higher abundance of Clostridium XIVa, Bacteroides and Lachnospiraceae; cluster 2 and cluster 3 were more common post-transplantation with a higher abundance of Streptococcus and Staphylococcus in the former whilst Enterococcus, Enterobacteriaceae and Escherichia predominated in the latter. Cluster 3 was also associated with a higher risk of viraemia. Likewise, further multivariate analysis reveals Enterobacteriaceae, viraemia, use of total parenteral nutrition and various antimicrobials contributing towards cluster 3, Streptococcaceae, Staphylococcaceae, Neisseriaceae, vancomycin and metronidazole contributing towards cluster 2. Lachnospiraceae, Ruminococcaceae, Bifidobacteriaceae and not being on total parenteral nutrition contributed to cluster 1. Untargeted metabolomic analyses revealed changes that paralleled fluctuations in microbiota composition; importantly, low faecal butyrate was associated with a higher risk of viraemia. Conclusions: These findings highlight the frequent shifts and dominations in the gut microbiota of paediatric patients undergoing haematopoietic stem cell transplantation. The study reveals associations between the faecal microbiota, metabolome and viraemia. To identify and explore the potential of microbial biomarkers that may predict the risk of complications post-HSCT, larger multi-centre studies investigating the longitudinal microbial profiling in paediatric haematopoietic stem cell transplantation are warranted

    Orally active antischistosomal early leads identified from the open access malaria box.

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    BACKGROUND: Worldwide hundreds of millions of schistosomiasis patients rely on treatment with a single drug, praziquantel. Therapeutic limitations and the threat of praziquantel resistance underline the need to discover and develop next generation drugs. METHODOLOGY: We studied the antischistosomal properties of the Medicines for Malaria Venture (MMV) malaria box containing 200 diverse drug-like and 200 probe-like compounds with confirmed in vitro activity against Plasmodium falciparum. Compounds were tested against schistosomula and adult Schistosoma mansoni in vitro. Based on in vitro performance, available pharmacokinetic profiles and toxicity data, selected compounds were investigated in vivo. PRINCIPAL FINDINGS: Promising antischistosomal activity (IC50: 1.4-9.5 µM) was observed for 34 compounds against schistosomula. Three compounds presented IC50 values between 0.8 and 1.3 µM against adult S. mansoni. Two promising early leads were identified, namely a N,N'-diarylurea and a 2,3-dianilinoquinoxaline. Treatment of S. mansoni infected mice with a single oral 400 mg/kg dose of these drugs resulted in significant worm burden reductions of 52.5% and 40.8%, respectively. CONCLUSIONS/SIGNIFICANCE: The two candidates identified by investigating the MMV malaria box are characterized by good pharmacokinetic profiles, low cytotoxic potential and easy chemistry and therefore offer an excellent starting point for antischistosomal drug discovery and development

    Sensitive limits on the abundance of cold water vapor in the DM Tau protoplanetary disk

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    We performed a sensitive search for the ground-state emission lines of ortho- and para-water vapor in the DM Tau protoplanetary disk using the Herschel/HIFI instrument. No strong lines are detected down to 3sigma levels in 0.5 km/s channels of 4.2 mK for the 1_{10}--1_{01} line and 12.6 mK for the 1_{11}--0_{00} line. We report a very tentative detection, however, of the 1_{10}--1_{01} line in the Wide Band Spectrometer, with a strength of T_{mb}=2.7 mK, a width of 5.6 km/s and an integrated intensity of 16.0 mK km/s. The latter constitutes a 6sigma detection. Regardless of the reality of this tentative detection, model calculations indicate that our sensitive limits on the line strengths preclude efficient desorption of water in the UV illuminated regions of the disk. We hypothesize that more than 95-99% of the water ice is locked up in coagulated grains that have settled to the midplane.Comment: 5 pages, 3 figures. Accepted for publication in the Herschel HIFI special issue of A&
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