383 research outputs found
New Image Statistics for Detecting Disturbed Galaxy Morphologies at High Redshift
Testing theories of hierarchical structure formation requires estimating the
distribution of galaxy morphologies and its change with redshift. One aspect of
this investigation involves identifying galaxies with disturbed morphologies
(e.g., merging galaxies). This is often done by summarizing galaxy images
using, e.g., the CAS and Gini-M20 statistics of Conselice (2003) and Lotz et
al. (2004), respectively, and associating particular statistic values with
disturbance. We introduce three statistics that enhance detection of disturbed
morphologies at high-redshift (z ~ 2): the multi-mode (M), intensity (I), and
deviation (D) statistics. We show their effectiveness by training a
machine-learning classifier, random forest, using 1,639 galaxies observed in
the H band by the Hubble Space Telescope WFC3, galaxies that had been
previously classified by eye by the CANDELS collaboration (Grogin et al. 2011,
Koekemoer et al. 2011). We find that the MID statistics (and the A statistic of
Conselice 2003) are the most useful for identifying disturbed morphologies.
We also explore whether human annotators are useful for identifying disturbed
morphologies. We demonstrate that they show limited ability to detect
disturbance at high redshift, and that increasing their number beyond
approximately 10 does not provably yield better classification performance. We
propose a simulation-based model-fitting algorithm that mitigates these issues
by bypassing annotation.Comment: 15 pages, 14 figures, accepted for publication in MNRA
Local Interpretation Methods to Machine Learning Using the Domain of the Feature Space
As machine learning becomes an important part of many real world applications
affecting human lives, new requirements, besides high predictive accuracy,
become important. One important requirement is transparency, which has been
associated with model interpretability. Many machine learning algorithms induce
models difficult to interpret, named black box. Moreover, people have
difficulty to trust models that cannot be explained. In particular for machine
learning, many groups are investigating new methods able to explain black box
models. These methods usually look inside the black models to explain their
inner work. By doing so, they allow the interpretation of the decision making
process used by black box models. Among the recently proposed model
interpretation methods, there is a group, named local estimators, which are
designed to explain how the label of particular instance is predicted. For
such, they induce interpretable models on the neighborhood of the instance to
be explained. Local estimators have been successfully used to explain specific
predictions. Although they provide some degree of model interpretability, it is
still not clear what is the best way to implement and apply them. Open
questions include: how to best define the neighborhood of an instance? How to
control the trade-off between the accuracy of the interpretation method and its
interpretability? How to make the obtained solution robust to small variations
on the instance to be explained? To answer to these questions, we propose and
investigate two strategies: (i) using data instance properties to provide
improved explanations, and (ii) making sure that the neighborhood of an
instance is properly defined by taking the geometry of the domain of the
feature space into account. We evaluate these strategies in a regression task
and present experimental results that show that they can improve local
explanations
Metastatic Esophageal Carcinoma Cells Exhibit Reduced Adhesion Strength and Enhanced Thermogenesis
Despite continuous improvements in multimodal therapeutic strategies, esophageal carcinoma maintains a high mortality rate. Metastases are a major life-limiting component; however, very little is known about why some tumors have high metastatic potential and others not. In this study, we investigated thermogenic activity and adhesion strength of primary tumor cells and corresponding metastatic cell lines derived from two patients with metastatic adenocarcinoma of the esophagus. We hypothesized that the increased metastatic potential of the metastatic cell lines correlates with higher thermogenic activity and decreased adhesion strength. Our data show that patient-derived metastatic esophageal tumor cells have a higher thermogenic profile as well as a decreased adhesion strength compared to their corresponding primary tumor cells. Using two paired esophageal carcinoma cell lines of primary tumor and lymph nodes makes the data unique. Both higher specific thermogenesis profile and decreased adhesion strength are associated with a higher metastatic potential. They are in congruence with the clinical patient presentation. Understanding these functional, biophysical properties of patient derived esophageal carcinoma cell lines will enable us to gain further insight into the mechanisms of metastatic potential of primary tumors and metastases. Microcalorimetric evaluation will furthermore allow for rapid assessment of new treatment options for primary tumor and metastases aimed at decreasing the metastatic potential
Optimal Duration and Timing of Adjuvant Chemotherapy After Definitive Surgery for Ductal Adenocarcinoma of the Pancreas: Ongoing Lessons From the ESPAC-3 Study
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Evaluation of probabilistic photometric redshift estimation approaches for the Rubin Observatory Legacy Survey of Space and Time (LSST)
Many scientific investigations of photometric galaxy surveys require redshift estimates, whose uncertainty properties are best encapsulated by photometric redshift (photo-z) posterior probability density functions (PDFs). A plethora of photo-z PDF estimation methodologies abound, producing discrepant results with no consensus on a preferred approach. We present the results of a comprehensive experiment comparing 12 photo-z algorithms applied to mock data produced for The Rubin Observatory Legacy Survey of Space and Time Dark Energy Science Collaboration. By supplying perfect prior information, in the form of the complete template library and a representative training set as inputs to each code, we demonstrate the impact of the assumptions underlying each technique on the output photo-z PDFs. In the absence of a notion of true, unbiased photo-z PDFs, we evaluate and interpret multiple metrics of the ensemble properties of the derived photo-z PDFs as well as traditional reductions to photo-z point estimates. We report systematic biases and overall over/underbreadth of the photo-z PDFs of many popular codes, which may indicate avenues for improvement in the algorithms or implementations. Furthermore, we raise attention to the limitations of established metrics for assessing photo-z PDF accuracy; though we identify the conditional density estimate loss as a promising metric of photo-z PDF performance in the case where true redshifts are available but true photo-z PDFs are not, we emphasize the need for science-specific performance metrics
Evaluation of probabilistic photometric redshift estimation approaches for The Rubin Observatory Legacy Survey of Space and Time (LSST)
Many scientific investigations of photometric galaxy surveys require redshift estimates, whose uncertainty properties are best encapsulated by photometric redshift (photo-z) posterior probability density functions (PDFs). A plethora of photo-z PDF estimation methodologies abound, producing discrepant results with no consensus on a preferred approach. We present the results of a comprehensive experiment comparing 12 photo-z algorithms applied to mock data produced for The Rubin Observatory Legacy Survey of Space and Time Dark Energy Science Collaboration. By supplying perfect prior information, in the form of the complete template library and a representative training set as inputs to each code, we demonstrate the impact of the assumptions underlying each technique on the output photo-z PDFs. In the absence of a notion of true, unbiased photo-z PDFs, we evaluate and interpret multiple metrics of the ensemble properties of the derived photo-z PDFs as well as traditional reductions to photo-z point estimates. We report systematic biases and overall over/underbreadth of the photo-z PDFs of many popular codes, which may indicate avenues for improvement in the algorithms or implementations. Furthermore, we raise attention to the limitations of established metrics for assessing photo-z PDF accuracy; though we identify the conditional density estimate loss as a promising metric of photo-z PDF performance in the case where true redshifts are available but true photo-z PDFs are not, we emphasize the need for science-specific performance metrics
Definition and classification of chyle leak after pancreatic operation: A consensus statement by the International Study Group on Pancreatic Surgery
Recent literature suggests that chyle leak may complicate up to 10% of pancreatic resections. Treatment depends on its severity, which may include chylous ascites. No international consensus definition or grading system of chyle leak currently is available. The International Study Group on Pancreatic Surgery, an international panel of pancreatic surgeons working in well-known, high-volume centers, reviewed the literature and worked together to establish a consensus on the definition and classification of chyle leak after pancreatic operation. Chyle leak was defined as output of milky-colored fluid from a drain, drain site, or wound on or after postoperative day 3, with a triglyceride content ≥110 mg/dL (≥1.2 mmol/L). Three different grades of severity were defined according to the management needed: grade A, no specific intervention other than oral dietary restrictions; grade B, prolongation of hospital stay, nasoenteral nutrition with dietary restriction, total parenteral nutrition, octreotide, maintenance of surgical drains, or placement of new percutaneous drains; and grade C, need for other more invasive in-hospital treatment, intensive care unit admission, or mortality. This classification and grading system for chyle leak after pancreatic resection allows for comparison of outcomes between series. As with the other the International Study Group on Pancreatic Surgery consensus statements, this classification should facilitate communication and evaluation of different approaches to the prevention and treatment of this complicatio
Veterinary Considerations for the Theoretical Resurrection of Extinct Species
The de-extinction of the dinosaur is a dubious possibility but its consideration brings forth some issues that are at least worthy of scientific discussion. In this review, we discuss two distinct issues that have implications for a de-extinct species such as a dinosaur: the ability, or lack thereof, to safely sedate a rare and potentially fractious animal capable of harming the veterinary staff tasked with its care; and, disease risks associated with a species that has been extinct for millions of years. To identify potential sedatives, comparative pharmacology will be needed to uncover the links between receptor pharmacology and the desired clinical outcomes of activating established alpha-2 adrenergic, opioid, and benzodiazepine receptors. Specific to disease control, it will be necessary to understand the unique susceptibility of the new species to current diseases as well as predicting their reservoir capacity for potential human and veterinary pandemic diseases. While the topics presented herein are not exhaustive, this review highlights some of the foremost research that should be conducted in order to serve the unique veterinary needs of a de-extinct species using the dinosaur as a paradigm. Addressing these issues should be considered if an intact dinosaur genome becomes available, regardless of the feasibility of dinosaur resurrection
Abscess of adrenal gland caused by disseminated subacute Nocardia farcinica pneumonia. A case report and mini-review of the literature
<p>Abstract</p> <p>Background</p> <p>Infections caused by <it>Nocardia farcinica </it>are uncommon and show a great variety of clinical manifestations in immunocompetent and immunocompromised patients. Because of its unspecific symptoms and tendency to disseminate it may mimic the clinical symptoms and radiologic findings of a tumour disease and the diagnosis of nocardiosis can easily be missed, because there are no characteristic symptoms.</p> <p>Case presentation</p> <p>We present a case of an adrenal gland abscess caused by subacute disseminated <it>N. farcinica </it>pneumonia.</p> <p>Conclusion</p> <p>An infection with <it>N. farcinica </it>is potentially lethal because of its tendency to disseminate -particularly in the brain- and its high resistance to antibiotics. Awareness of this differential diagnosis allows early and appropriate treatment to be administered.</p
Evidence Map of Pancreatic Surgery–A living systematic review with meta-analyses by the International Study Group of Pancreatic Surgery (ISGPS)
Background: Pancreatic surgery is associated with considerable morbidity and, consequently, offers a large and complex field for research. To prioritize relevant future scientific projects, it is of utmost importance to identify existing evidence and uncover research gaps. Thus, the aim of this project was to create a systematic and living Evidence Map of Pancreatic Surgery. Methods: PubMed, the Cochrane Central Register of Controlled Trials, and Web of Science were systematically searched for all randomized controlled trials and systematic reviews on pancreatic surgery. Outcomes from every existing randomized controlled trial were extracted, and trial quality was assessed. Systematic reviews were used to identify an absence of randomized controlled trials. Randomized controlled trials and systematic reviews on identical subjects were grouped according to research topics. A web-based evidence map modeled after a mind map was created to visualize existing evidence. Meta-analyses of specific outcomes of pancreatic surgery were performed for all research topics with more than 3 randomized controlled trials. For partial pancreatoduodenectomy and distal pancreatectomy, pooled benchmarks for outcomes were calculated with a 99% confidence interval. The evidence map undergoes regular updates. Results: Out of 30, 860 articles reviewed, 328 randomized controlled trials on 35, 600 patients and 332 systematic reviews were included and grouped into 76 research topics. Most randomized controlled trials were from Europe (46%) and most systematic reviews were from Asia (51%). A living meta-analysis of 21 out of 76 research topics (28%) was performed and included in the web-based evidence map. Evidence gaps were identified in 11 out of 76 research topics (14%). The benchmark for mortality was 2% (99% confidence interval: 1%–2%) for partial pancreatoduodenectomy and <1% (99% confidence interval: 0%–1%) for distal pancreatectomy. The benchmark for overall complications was 53% (99%confidence interval: 46%–61%) for partial pancreatoduodenectomy and 59% (99% confidence interval: 44%–80%) for distal pancreatectomy. Conclusion: The International Study Group of Pancreatic Surgery Evidence Map of Pancreatic Surgery, which is freely accessible via www.evidencemap.surgery and as a mobile phone app, provides a regularly updated overview of the available literature displayed in an intuitive fashion. Clinical decision making and evidence-based patient information are supported by the primary data provided, as well as by living meta-analyses. Researchers can use the systematic literature search and processed data for their own projects, and funding bodies can base their research priorities on evidence gaps that the map uncovers. © 2021 The Author
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