577 research outputs found
Ancestral genome estimation reveals the history of ecological diversification in Agrobacterium
Horizontal gene transfer (HGT) is considered as a major source of innovation in bacteria, and as such is expected to drive adaptation to new ecological niches. However, among the many genes acquired through HGT along the diversification history of genomes, only a fraction may have actively contributed to sustained ecological adaptation. We used a phylogenetic approach accounting for the transfer of genes (or groups of genes) to estimate the history of genomes in Agrobacterium biovar 1, a diverse group of soil and plant-dwelling bacterial species. We identified clade-specific blocks of cotransferred genes encoding coherent biochemical pathways that may have contributed to the evolutionary success of key Agrobacterium clades. This pattern of gene coevolution rejects a neutral model of transfer, in which neighboring genes would be transferred independently of their function and rather suggests purifying selection on collectively coded acquired pathways. The acquisition of these synapomorphic blocks of cofunctioning genes probably drove the ecological diversification of Agrobacterium and defined features of ancestral ecological niches, which consistently hint at a strong selective role of host plant rhizospheres
Exploring adversarial attacks in federated learning for medical imaging
Federated learning offers a privacy-preserving framework for medical image
analysis but exposes the system to adversarial attacks. This paper aims to
evaluate the vulnerabilities of federated learning networks in medical image
analysis against such attacks. Employing domain-specific MRI tumor and
pathology imaging datasets, we assess the effectiveness of known threat
scenarios in a federated learning environment. Our tests reveal that
domain-specific configurations can increase the attacker's success rate
significantly. The findings emphasize the urgent need for effective defense
mechanisms and suggest a critical re-evaluation of current security protocols
in federated medical image analysis systems
The Leiodolide B Puzzle
Out of options? Even though a systematic approach was chosen, which led to a set of four diastereomeric macrolides modeled around the proposed structure of leiodolide B (see picture), the puzzle concerning the stereostructure of this cytotoxic metabolite derived from a deep-sea sponge still remains unsolved
The Hidden Adversarial Vulnerabilities of Medical Federated Learning
In this paper, we delve into the susceptibility of federated medical image
analysis systems to adversarial attacks. Our analysis uncovers a novel
exploitation avenue: using gradient information from prior global model
updates, adversaries can enhance the efficiency and transferability of their
attacks. Specifically, we demonstrate that single-step attacks (e.g. FGSM),
when aptly initialized, can outperform the efficiency of their iterative
counterparts but with reduced computational demand. Our findings underscore the
need to revisit our understanding of AI security in federated healthcare
settings
Spectral Data Augmentation Techniques to quantify Lung Pathology from CT-images
Data augmentation is of paramount importance in biomedical image processing
tasks, characterized by inadequate amounts of labelled data, to best use all of
the data that is present. In-use techniques range from intensity
transformations and elastic deformations, to linearly combining existing data
points to make new ones. In this work, we propose the use of spectral
techniques for data augmentation, using the discrete cosine and wavelet
transforms. We empirically evaluate our approaches on a CT texture analysis
task to detect abnormal lung-tissue in patients with cystic fibrosis. Empirical
experiments show that the proposed spectral methods perform favourably as
compared to the existing methods. When used in combination with existing
methods, our proposed approach can increase the relative minor class
segmentation performance by 44.1% over a simple replication baseline.Comment: 5 pages including references, accepted as Oral presentation at IEEE
ISBI 202
Certified quantum non-demolition measurement of material systems
An extensive debate on quantum non-demolition (QND) measurement, reviewed in
Grangier et al. [Nature, {\bf 396}, 537 (1998)], finds that true QND
measurements must have both non-classical state-preparation capability and
non-classical information-damage tradeoff. Existing figures of merit for these
non-classicality criteria require direct measurement of the signal variable and
are thus difficult to apply to optically-probed material systems. Here we
describe a method to demonstrate both criteria without need for to direct
signal measurements. Using a covariance matrix formalism and a general noise
model, we compute meter observables for QND measurement triples, which suffice
to compute all QND figures of merit. The result will allow certified QND
measurement of atomic spin ensembles using existing techniques.Comment: 11 pages, zero figure
Quantification of Lung Abnormalities in Cystic Fibrosis using Deep Networks
Cystic fibrosis is a genetic disease which may appear in early life with
structural abnormalities in lung tissues. We propose to detect these
abnormalities using a texture classification approach. Our method is a cascade
of two convolutional neural networks. The first network detects the presence of
abnormal tissues. The second network identifies the type of the structural
abnormalities: bronchiectasis, atelectasis or mucus plugging.We also propose a
network computing pixel-wise heatmaps of abnormality presence learning only
from the patch-wise annotations. Our database consists of CT scans of 194
subjects. We use 154 subjects to train our algorithms and the 40 remaining ones
as a test set. We compare our method with random forest and a single neural
network approach. The first network reaches an accuracy of 0,94 for disease
detection, 0,18 higher than the random forest classifier and 0,37 higher than
the single neural network. Our cascade approach yields a final class-averaged
F1-score of 0,33, outperforming the baseline method and the single network by
0,10 and 0,12.Comment: SPIE - Medical Imaging 2018: Image Processin
IL-6 gene amplification and expression in human glioblastomas
The aggressiveness of human gliomas appears to be correlated with the upregulation of interleukin 6 (IL-6) gene. Using quantitative PCR methods, we detected amplification and expression of the IL-6 gene in 5 of 5 primary glioblastoma samples and in 4 of 5 glioblastoma cell lines. This finding suggests that the amplification of IL-6 gene may be a common feature in glioblastomas and may contribute to the IL-6 over-expression. © 2001 Cancer Research Campaign http://www.bjcancer.co
Acute mesenteric ischaemia in refractory shock on veno-arterial extracorporeal membrane oxygenation
Background: Acute mesenteric ischaemia is a severe complication in critically ill patients, but has never been evaluated in patients on veno-arterial extracorporeal membrane oxygenation (V-A ECMO). This study was designed to determine the prevalence of mesenteric ischaemia in patients supported by V-A ECMO and to evaluate its risk factors, as well as to appreciate therapeutic modalities and outcome. Methods: In a retrospective single centre study (January 2013 to January 2017), all consecutive adult patients who underwent V-A ECMO were included, with exclusion of those dying in the first 24 hours. Diagnosis of mesenteric ischaemia was performed using digestive endoscopy, computed tomography scan or first-line laparotomy. Results: One hundred and fifty V-A ECMOs were implanted (65 for post-cardiotomy shock, 85 for acute cardiogenic shock, including 39 patients after refractory cardiac arrest). Overall, median age was 58 (48-69) years and mortality 56%. Acute mesenteric ischaemia was suspected in 38 patients, with a delay of four (2-7) days after ECMO implantation, and confirmed in 14 patients, that is, a prevalence of 9%. Exploratory laparotomy was performed in six out of 14 patients, the others being too unstable to undergo surgery. All patients with mesenteric ischaemia died. Independent risk factors for developing mesenteric ischaemia were renal replacement therapy (odds ratio (OR) 4.5, 95% confidence interval (CI) 1.3-15.7, p=0.02) and onset of a second shock within the first five days (OR 7.8, 95% CI 1.5-41.3, p=0.02). Conversely, early initiation of enteral nutrition was negatively associated with mesenteric ischaemia (OR 0.15, 95% CI 0.03-0.69, p=0.02). Conclusions: Acute mesenteric ischaemia is a relatively frequent but dramatic complication among patients on V-A ECMO
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