Scatteract: Automated extraction of data from scatter plots

Charts are an excellent way to convey patterns and trends in data, but they do not facilitate further modeling of the data or close inspection of individual data points. We present a fully automated system for extracting the numerical values of data points from images of scatter plots. We use deep learning techniques to identify the key components of the chart, and optical character recognition together with robust regression to map from pixels to the coordinate system of the chart. We focus on scatter plots with linear scales, which already have several interesting challenges. Previous work has done fully automatic extraction for other types of charts, but to our knowledge this is the first approach that is fully automatic for scatter plots. Our method performs well, achieving successful data extraction on 89% of the plots in our test set.Comment: Submitted to ECML PKDD 2017 proceedings, 16 page

Psychiatrists injured by patient attack

The seven staff psychiatrists injured by patient attack in a large forensic hospital in five years were compared with the 47 who were not injured by attack. Thirteen percent of the psychiatrists were injured by patient attack (2.6 percent per year); 5.5 injuries per 100 person-years occurred. This rate is comparable to the rate of injury from patient attack noted among ward nursing staff during the Same period. Younger psychiatrists, and psychiatrists more recently out of residency, were more likely to be injured. Male psychiatrists were injured at a rate approximately 50 percent higher than female psychiatrists, and graduates of university-affiliated residencies were three times as likely to be injured as graduates of public-sector residencies, though these differences did not reach statistical significance. A slightly higher rate of injury was noted among graduates from non-North American medical schools. Board-certification and length of service in the hospital were not related to being injured

Edible crabs “Go West”: migrations and incubation cycle of Cancer pagurus revealed by electronic tags

Crustaceans are key components of marine ecosystems which, like other exploited marine taxa, show seasonable patterns of distribution and activity, with consequences for their availability to capture by targeted fisheries. Despite concerns over the sustainability of crab fisheries worldwide, difficulties in observing crabs’ behaviour over their annual cycles, and the timings and durations of reproduction, remain poorly understood. From the release of 128 mature female edible crabs tagged with electronic data storage tags (DSTs), we demonstrate predominantly westward migration in the English Channel. Eastern Channel crabs migrated further than western Channel crabs, while crabs released outside the Channel showed little or no migration. Individual migrations were punctuated by a 7-month hiatus, when crabs remained stationary, coincident with the main period of crab spawning and egg incubation. Incubation commenced earlier in the west, from late October onwards, and brooding locations, determined using tidal geolocation, occurred throughout the species range. With an overall return rate of 34%, our results demonstrate that previous reluctance to tag crabs with relatively high-cost DSTs for fear of loss following moulting is unfounded, and that DSTs can generate precise information with regards life-history metrics that would be unachievable using other conventional means

A robust, low- to medium-throughput prnp genotyping system in sheep

BACKGROUND: In many countries breeding programs for resistance to scrapie in sheep are established. Therefore, the demand on genotyping capacities of the polymorphisms of the prion protein gene (prnp) relevant to presently known disease associations and EU regulations is steadily increasing. Most published typing methods are not well suited for routine typing of large sample numbers in smaller service laboratories for different reasons: they require partly manual data processing, sophisticated and sensitive protocols, high efforts regarding time and manpower, multiple step reactions or substantial hardware investments. To overcome these drawbacks, we developed a prnp typing method that is based on a `multiplex amplification refractory mutation system' (ARMS) reaction. METHODS: In this study we combined the amplification refractory mutation system (ARMS) with standard fluorescent based fragment length analyses method to develop a prnp genotyping method (PRNP ARMS). RESULTS: By optimised primer design it was possible to type the 4 relevant single nucleotide polymorphisms (SNPs) in the prnp simultaneously in one multiplex reaction. Automated fragment length analysis enabled automated allele designation. Suitability of the PRNP ARMS for routine application was proven by typing samples with known genotypes and larger sample numbers from half-sib families. CONCLUSION: The ARMS PRNP typing method established in this study is universally suited for a broad range of typing projects with different requirements. It provides an efficient and inexpensive diagnostic mutation analysis that will improve the quality of prnp genotyping compared with other low-cost methods. It can be implemented by most molecular genetic laboratories using standard equipment

A realistic assessment of methods for extracting gene/protein interactions from free text

Background: The automated extraction of gene and/or protein interactions from the literature is one of the most important targets of biomedical text mining research. In this paper we present a realistic evaluation of gene/protein interaction mining relevant to potential non-specialist users. Hence we have specifically avoided methods that are complex to install or require reimplementation, and we coupled our chosen extraction methods with a state-of-the-art biomedical named entity tagger. Results: Our results show: that performance across different evaluation corpora is extremely variable; that the use of tagged (as opposed to gold standard) gene and protein names has a significant impact on performance, with a drop in F-score of over 20 percentage points being commonplace; and that a simple keyword-based benchmark algorithm when coupled with a named entity tagger outperforms two of the tools most widely used to extract gene/protein interactions. Conclusion: In terms of availability, ease of use and performance, the potential non-specialist user community interested in automatically extracting gene and/or protein interactions from free text is poorly served by current tools and systems. The public release of extraction tools that are easy to install and use, and that achieve state-of-art levels of performance should be treated as a high priority by the biomedical text mining community

A Bayesian method for evaluating and discovering disease loci associations

Background: A genome-wide association study (GWAS) typically involves examining representative SNPs in individuals from some population. A GWAS data set can concern a million SNPs and may soon concern billions. Researchers investigate the association of each SNP individually with a disease, and it is becoming increasingly commonplace to also analyze multi-SNP associations. Techniques for handling so many hypotheses include the Bonferroni correction and recently developed Bayesian methods. These methods can encounter problems. Most importantly, they are not applicable to a complex multi-locus hypothesis which has several competing hypotheses rather than only a null hypothesis. A method that computes the posterior probability of complex hypotheses is a pressing need. Methodology/Findings: We introduce the Bayesian network posterior probability (BNPP) method which addresses the difficulties. The method represents the relationship between a disease and SNPs using a directed acyclic graph (DAG) model, and computes the likelihood of such models using a Bayesian network scoring criterion. The posterior probability of a hypothesis is computed based on the likelihoods of all competing hypotheses. The BNPP can not only be used to evaluate a hypothesis that has previously been discovered or suspected, but also to discover new disease loci associations. The results of experiments using simulated and real data sets are presented. Our results concerning simulated data sets indicate that the BNPP exhibits both better evaluation and discovery performance than does a p-value based method. For the real data sets, previous findings in the literature are confirmed and additional findings are found. Conclusions/Significance: We conclude that the BNPP resolves a pressing problem by providing a way to compute the posterior probability of complex multi-locus hypotheses. A researcher can use the BNPP to determine the expected utility of investigating a hypothesis further. Furthermore, we conclude that the BNPP is a promising method for discovering disease loci associations. © 2011 Jiang et al

An experimental model to measure the ability of headphones with active noise control to reduce patient's exposure to noise in an intensive care unit.

BACKGROUND: Defining the association between excessive noise in intensive care units, sleep disturbance and morbidity, including delirium, is confounded by the difficulty of implementing successful strategies to reduce patient's exposure to noise. Active noise control devices may prove to be useful adjuncts but there is currently little to quantify their ability to reduce noise in this complex environment. METHODS: Sound meters were embedded in the auditory meatus of three polystyrene model heads with no headphones (control), with headphones alone and with headphones using active noise control and placed in patient bays in a cardiac ICU. Ten days of recording sound levels at a frequency of 1 Hz were performed, and the noise levels in each group were compared using repeated measures MANOVA and subsequent pairwise testing. RESULTS: Multivariate testing demonstrated that there is a significant difference in the mean noise exposure levels between the three groups (p < 0.001). Subsequent pairwise testing between the three groups shows that the reduction in noise is greatest with headphones and active noise control. The mean reduction in noise exposure between the control and this group over 24 h is 6.8 (0.66) dB. The use of active noise control was also associated with a reduction in the exposure to high-intensity sound events over the course of the day. CONCLUSIONS: The use of active noise cancellation, as delivered by noise-cancelling headphones, is associated with a significant reduction in noise exposure in our model of noise exposure in a cardiac ICU. This is the first study to look at the potential effectiveness of active noise control in adult patients in an intensive care environment and shows that active noise control is a candidate technology to reduce noise exposure levels the patients experience during stays on intensive care

Why Current Statistical Approaches to Ransomware Detection Fail

The frequent use of basic statistical techniques to detect ransomware is a popular and intuitive strategy; statistical tests can be used to identify randomness, which in turn can indicate the presence of encryption and, by extension, a ransomware attack. However, common file formats such as images and compressed data can look random from the perspective of some of these tests. In this work, we investigate the current frequent use of statistical tests in the context of ransomware detection, primarily focusing on false positive rates. The main aim of our work is to show that the current over-dependence on simple statistical tests within anti-ransomware tools can cause serious issues with the reliability and consistency of ransomware detection in the form of frequent false classifications. We determined thresholds for five key statistics frequently used in detecting randomness, namely Shannon entropy, chi-square, arithmetic mean, Monte Carlo estimation for Pi and serial correlation coefficient. We obtained a large data set of 84,327 files comprising of images, compressed data and encrypted data. We then tested these thresholds (taken from a variety of previous publications in the literature where possible) against our dataset, showing that the rate of false positives is far beyond what could be considered acceptable. False positive rates were often above 50% and even above 90% on several occasions. False negative rates were also generally between 5% and 20%, numbers which are also far too high. As a direct result of these experiments, we determine that relying on these simple statistical approaches is not good enough to detect ransomware attacks consistently. We instead recommend the exploration of higher-order statistics such as skewness and kurtosis for future ransomware detection techniques

Benznidazole biotransformation and multiple targets in <i>Trypanosoma</i> cruzi revealed by metabolomics

&lt;b&gt;Background&lt;/b&gt;&lt;p&gt;&lt;/p&gt; The first line treatment for Chagas disease, a neglected tropical disease caused by the protozoan parasite Trypanosoma cruzi, involves administration of benznidazole (Bzn). Bzn is a 2-nitroimidazole pro-drug which requires nitroreduction to become active, although its mode of action is not fully understood. In the present work we used a non-targeted MS-based metabolomics approach to study the metabolic response of T. cruzi to Bzn.&lt;p&gt;&lt;/p&gt; &lt;b&gt;Methodology/Principal findings&lt;/b&gt;&lt;p&gt;&lt;/p&gt; Parasites treated with Bzn were minimally altered compared to untreated trypanosomes, although the redox active thiols trypanothione, homotrypanothione and cysteine were significantly diminished in abundance post-treatment. In addition, multiple Bzn-derived metabolites were detected after treatment. These metabolites included reduction products, fragments and covalent adducts of reduced Bzn linked to each of the major low molecular weight thiols: trypanothione, glutathione, γ-glutamylcysteine, glutathionylspermidine, cysteine and ovothiol A. Bzn products known to be generated in vitro by the unusual trypanosomal nitroreductase, TcNTRI, were found within the parasites, but low molecular weight adducts of glyoxal, a proposed toxic end-product of NTRI Bzn metabolism, were not detected.&lt;p&gt;&lt;/p&gt; &lt;b&gt;Conclusions/significance&lt;/b&gt;&lt;p&gt;&lt;/p&gt; Our data is indicative of a major role of the thiol binding capacity of Bzn reduction products in the mechanism of Bzn toxicity against T. cruzi

Stem cell differentiation increases membrane-actin adhesion regulating cell blebability, migration and mechanics

This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder in order to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/K. S. is funded by an EPSRC PhD studentship. S.T. is funded by an EU Marie Curie Intra European Fellowship (GENOMICDIFF)