Estudo de Usabilidade de Assinaturas Digitais em Objetos Metrológicos

INMETR

Enhanced CellClassifier: a multi-class classification tool for microscopy images

BACKGROUND: Light microscopy is of central importance in cell biology. The recent introduction of automated high content screening has expanded this technology towards automation of experiments and performing large scale perturbation assays. Nevertheless, evaluation of microscopy data continues to be a bottleneck in many projects. Currently, among open source software, CellProfiler and its extension Analyst are widely used in automated image processing. Even though revolutionizing image analysis in current biology, some routine and many advanced tasks are either not supported or require programming skills of the researcher. This represents a significant obstacle in many biology laboratories. RESULTS: We have developed a tool, Enhanced CellClassifier, which circumvents this obstacle. Enhanced CellClassifier starts from images analyzed by CellProfiler, and allows multi-class classification using a Support Vector Machine algorithm. Training of objects can be done by clicking directly "on the microscopy image" in several intuitive training modes. Many routine tasks like out-of focus exclusion and well summary are also supported. Classification results can be integrated with other object measurements including inter-object relationships. This makes a detailed interpretation of the image possible, allowing the differentiation of many complex phenotypes. For the generation of the output, image, well and plate data are dynamically extracted and summarized. The output can be generated as graphs, Excel-files, images with projections of the final analysis and exported as variables. CONCLUSION: Here we describe Enhanced CellClassifier which allows multiple class classification, elucidating complex phenotypes. Our tool is designed for the biologist who wants both, simple and flexible analysis of images without requiring programming skills. This should facilitate the implementation of automated high-content screening

Treatments for people who use anabolic androgenic steroids: a scoping review.

BACKGROUND: A growing body of evidence suggests that anabolic androgenic steroids (AAS) are used globally by a diverse population with varying motivations. Evidence has increased greatly in recent years to support understanding of this form of substance use and the associated health harms, but there remains little evidence regarding interventions to support cessation and treat the consequences of use. In this scoping review, we identify and describe what is known about interventions that aim to support and achieve cessation of AAS, and treat and prevent associated health problems. METHODS: A comprehensive search strategy was developed in four bibliographic databases, supported by an iterative citation searching process to identify eligible studies. Studies of any psychological or medical treatment interventions delivered in response to non-prescribed use of AAS or an associated harm in any setting were eligible. RESULTS: In total, 109 eligible studies were identified, which included case reports representing a diverse range of disciplines and sources. Studies predominantly focussed on treatments for harms associated with AAS use, with scant evidence on interventions to support cessation of AAS use or responding to dependence. The types of conditions requiring treatment included psychiatric, neuroendocrine, hepatic, kidney, cardiovascular, musculoskeletal and infectious. There was limited evidence of engagement with users or delivery of psychosocial interventions as part of treatment for any condition, and of harm reduction interventions initiated alongside, or following, treatment. Findings were limited throughout by the case report study designs and limited information was provided. CONCLUSION: This scoping review indicates that while a range of case reports describe treatments provided to AAS users, there is scarce evidence on treating dependence, managing withdrawal, or initiating behaviour change in users in any settings. Evidence is urgently required to support the development of effective services for users and of evidence-based guidance and interventions to respond to users in a range of healthcare settings. More consistent reporting in articles of whether engagement or assessment relating to AAS was initiated, and publication within broader health- or drug-related journals, will support development of the evidence base

All-sky search for gravitational-wave bursts in the second joint LIGO-Virgo run

We present results from a search for gravitational-wave bursts in the data collected by the LIGO and Virgo detectors between July 7, 2009 and October 20, 2010: data are analyzed when at least two of the three LIGO-Virgo detectors are in coincident operation, with a total observation time of 207 days. The analysis searches for transients of duration < 1 s over the frequency band 64-5000 Hz, without other assumptions on the signal waveform, polarization, direction or occurrence time. All identified events are consistent with the expected accidental background. We set frequentist upper limits on the rate of gravitational-wave bursts by combining this search with the previous LIGO-Virgo search on the data collected between November 2005 and October 2007. The upper limit on the rate of strong gravitational-wave bursts at the Earth is 1.3 events per year at 90% confidence. We also present upper limits on source rate density per year and Mpc^3 for sample populations of standard-candle sources. As in the previous joint run, typical sensitivities of the search in terms of the root-sum-squared strain amplitude for these waveforms lie in the range 5 10^-22 Hz^-1/2 to 1 10^-20 Hz^-1/2. The combination of the two joint runs entails the most sensitive all-sky search for generic gravitational-wave bursts and synthesizes the results achieved by the initial generation of interferometric detectors.Comment: 15 pages, 7 figures: data for plots and archived public version at https://dcc.ligo.org/cgi-bin/DocDB/ShowDocument?docid=70814&version=19, see also the public announcement at http://www.ligo.org/science/Publication-S6BurstAllSky