523 research outputs found
Co-Adaptive Control of Bionic Limbs via Unsupervised Adaptation of Muscle Synergies
Objective: In this work, we present a myoelectric interface that extracts natural motor synergies from multi-muscle signals and adapts in real-time with new user inputs. With this unsupervised adaptive myocontrol (UAM) system, optimal synergies for control are continuously co-adapted with changes in user motor control, or as a function of perturbed conditions via online non-negative matrix factorization guided by physiologically informed sparseness constraints in lieu of explicit data labelling. Methods: UAM was tested in a set of virtual target reaching tasks completed by able-bodied and amputee subjects. Tests were conducted under normative and electrode perturbed conditions to gauge control robustness with comparisons to non-adaptive and supervised adaptive myocontrol schemes. Furthermore, UAM was used to interface an amputee with a multi-functional powered hand prosthesis during standardized Clothespin Relocation Tests, also conducted in normative and perturbed conditions. Results: In virtual tests, UAM effectively mitigated performance degradation caused by electrode displacement, affording greater resilience over an existing supervised adaptive system for amputee subjects. Induced electrode shifts also had negligible effect on the real world control performance of UAM with consistent completion times (23.91 +/- 1.33 s) achieved across Clothespin Relocation Tests in the normative and electrode perturbed conditions. Conclusion: UAM affords comparable robustness improvements to existing supervised adaptive myocontrol interfaces whilst providing additional practical advantages for clinical deployment. Significance: The proposed system uniquely incorporates neuromuscular control principles with unsupervised online learning methods and presents a working example of a freely co-adaptive bionic interface.Peer reviewe
Effects of genistein following fractionated lung irradiation in mice.
BACKGROUND AND PURPOSE: This study investigated protection of lung injury by genistein following fractionated doses of radiation and its effect on tumor response.
MATERIAL AND METHODS: C3H/HeJ mice were irradiated (100 kVp X-rays) with 9 fractions of 3.1 Gy over 30 days (approximately equivalent to 10 Gy single dose) and were maintained on a genistein diet ( approximately 10mg/kg). Damage was assessed over 28 weeks in lung cells by a cytokinesis block micronucleus (MN) assay and by changes in breathing rate and histology. Tumor protection was assessed using a colony assay to determine cell survival following in situ irradiation of small lung nodules (KHT fibrosarcoma).
RESULTS: Genistein caused about a 50% reduction in the MN damage observed during the fractionated radiation treatment and this damage continued to decrease at later times to background levels by 16 weeks. In mice not receiving Genistein MN levels remained well above background out to 28 weeks after irradiation. Genistein reduced macrophage accumulation by 22% and reduced collagen deposition by 28%. There was minimal protection against increases in breathing rate or severe morbidity during pneumonitis. No tumor protection by genistein treatment was observed.
CONCLUSIONS: Genistein at the dose levels used in this study partially reduced the extent of fibrosis developing in mouse lung caused by irradiation but gave minimal protection against pneumonitis. There was no evidence that genistein caused protection of small tumors growing in the lung
Radiomics of Lung Nodules: A Multi-Institutional Study of Robustness and Agreement of Quantitative Imaging Features.
Radiomics is to provide quantitative descriptors of normal and abnormal tissues during classification and prediction tasks in radiology and oncology. Quantitative Imaging Network members are developing radiomic "feature" sets to characterize tumors, in general, the size, shape, texture, intensity, margin, and other aspects of the imaging features of nodules and lesions. Efforts are ongoing for developing an ontology to describe radiomic features for lung nodules, with the main classes consisting of size, local and global shape descriptors, margin, intensity, and texture-based features, which are based on wavelets, Laplacian of Gaussians, Law's features, gray-level co-occurrence matrices, and run-length features. The purpose of this study is to investigate the sensitivity of quantitative descriptors of pulmonary nodules to segmentations and to illustrate comparisons across different feature types and features computed by different implementations of feature extraction algorithms. We calculated the concordance correlation coefficients of the features as a measure of their stability with the underlying segmentation; 68% of the 830 features in this study had a concordance CC of ≥0.75. Pairwise correlation coefficients between pairs of features were used to uncover associations between features, particularly as measured by different participants. A graphical model approach was used to enumerate the number of uncorrelated feature groups at given thresholds of correlation. At a threshold of 0.75 and 0.95, there were 75 and 246 subgroups, respectively, providing a measure for the features' redundancy
pGQL: A probabilistic graphical query language for gene expression time courses
<p>Abstract</p> <p>Background</p> <p>Timeboxes are graphical user interface widgets that were proposed to specify queries on time course data. As queries can be very easily defined, an exploratory analysis of time course data is greatly facilitated. While timeboxes are effective, they have no provisions for dealing with noisy data or data with fluctuations along the time axis, which is very common in many applications. In particular, this is true for the analysis of gene expression time courses, which are mostly derived from noisy microarray measurements at few unevenly sampled time points. From a data mining point of view the robust handling of data through a sound statistical model is of great importance.</p> <p>Results</p> <p>We propose probabilistic timeboxes, which correspond to a specific class of Hidden Markov Models, that constitutes an established method in data mining. Since HMMs are a particular class of probabilistic graphical models we call our method Probabilistic Graphical Query Language. Its implementation was realized in the free software package pGQL. We evaluate its effectiveness in exploratory analysis on a yeast sporulation data set.</p> <p>Conclusions</p> <p>We introduce a new approach to define dynamic, statistical queries on time course data. It supports an interactive exploration of reasonably large amounts of data and enables users without expert knowledge to specify fairly complex statistical models with ease. The expressivity of our approach is by its statistical nature greater and more robust with respect to amplitude and frequency fluctuation than the prior, deterministic timeboxes.</p
Absence of RKIP expression is an independent prognostic biomarker for gastric cancer patients
Gastric cancer is a leading cause of cancer-related mortality, and the presence of lymph node metastasis an important prognostic factor. Downregulation of RKIP has been associated with tumor progression and metastasis in several types of neoplasms, being currently categorized as a metastasis suppressor gene. Our aim was to determine the expression levels of RKIP in gastric tissues and to evaluate its impact in the clinical outcome of gastric carcinoma patients. RKIP expression levels were studied by immunohistochemistry in a series of gastric tissues. Overall, we analysed 222 non-neoplastic gastric tissues, 152 primary tumors and 42 lymph node metastasis samples. We observed that RKIP was highly expressed in ~83% of non-neoplastic tissues (including normal tissue and metaplasia), was lost in ~56% of primary tumors and in ~90% of lymph node metastasis samples. Loss of RKIP expression was significantly associated with several markers of poor clinical outcome, including the presence of lymph node metastasis. Furthermore, the absence of RKIP protein constitutes an independent prognostic marker for these patients. In conclusion, RKIP expression is significantly lost during gastric carcinoma progression being almost absent in lymph node metastasis samples. Of note, we showed that the absence of RKIP expression is associated with poor outcome features of gastric cancer patients, this being also an independent prognostic marker.Olga Martinho was recipient of a PhD fellowship (SFRH/BD/36463/2007) from Fundacao para a Ciencia e Tecnologia (FCT), Portugal
Glycosylation Failure Extends to Glycoproteins in Gestational Diabetes Mellitus: Evidence From Reduced α2-6 Sialylation and Impaired Immunomodulatory Activities of Pregnancy-Related Glycodelin-A
OBJECTIVE - Gestational diabetes mellitus (GDM) is a common metabolic disorder of pregnancy. Patients with GDM are at risk for high fetal mortality and gestational complications associated with reduced immune tolerance and abnormal carbohydrate metabolism. Glycodelin-A (GdA) is an abundant decidual glycoprotein with glycosylation-dependent immunomodulatory activities. We hypothesized that aberrant carbohydrate metabolism in GDM was associated with changes in glycosylation of GdA, leading to defective immunomodulatory activities. RESEARCH DESIGN AND METHODS - GdA in the amniotic fluid from women with normal (NGdA) and GDM (DGdA) pregnancies was purified by affinity chromatography. Structural analysis of protein glycosylation was preformed by lectin-binding assay and mass spectrometry. Cytotoxicity, cell death, cytokine secretion, and GdA binding of the GdA-treated lymphocytes and natural killer (NK) cells were determined. The sialidase activity in the placental tissue from normal and GDM patients was measured. RESULTS - GDM affected the glycosylation but not the protein core of GdA. Specifically, DGdA had a lower abundance of α2-6-sialylated and high-mannose glycans and a higher abundance of glycans with Sda (NeuAcα2-3[GalNAcβ1-4]Gal) epitopes compared with NGdA. DGdA had reduced immuosuppressive activities in terms of cytotoxicity on lymphocytes, inhibitory activities on interleukin (IL)-2 secretion by lymphocytes, stimulatory activities on IL-6 secretion by NK cells, and binding to these cells. Desialylation abolished the immunomodulation and binding of NGdA. Placental sialidase activity was increased in GDM patients, which may account for the reduced sialic acid content of DGdA. CONCLUSIONS - Taken together, this study provides the first direct evidence for altered enzymatic glycosylation and impaired bioactivity of GdA in GDM patients. © 2011 by the American Diabetes Association.published_or_final_versio
Differential actions of glycodelin-A on Th-1 and Th-2 cells: A paracrine mechanism that could produce the Th-2 dominant environment during pregnancy
Background: The maternalfetal interface has a unique immunological response towards the implanting placenta. It is generally accepted that a T-helper type-2 (Th-2) cytokine prevailing environment is important in pregnancy. The proportion of Th-2 cells in the peripheral blood and decidua is significantly higher in pregnant women in the first trimester than in non-pregnant women. Glycodelin-A (GdA) is a major endocrine-regulated decidual glycoprotein thought to be related to fetomaternal defence. Yet the relationship between its immunoregulatory activities and the shift towards Th-2 cytokine profile during pregnancy is unclear. Methods GdA was immunoaffinity purified from human amniotic fluid. T-helper, T-helper type-1 (Th-1) and Th-2 cells were isolated from the peripheral blood. The viability of these cells was studied by XTT assay. Immunophenotyping of CD4/CD294, cell death and GdA-binding were determined by flow cytometry. The mRNA expression, surface expression and secretion of Fas/Fas ligand (FasL) were determined by quantitative polymerase chain reaction, flow cytometry and ELISA, respectively. The activities of caspase-3, -8 and -9 were measured. The phosphorylation of extracellular signal-regulated kinases (ERK), p38 and, c-Jun N-terminal kinase was determined by western blotting. Results Although GdA bound to both Th-1 and Th-2 cells, it had differential actions on the two cell-types. GdA induced cell death of the Th-1 cells but not the Th-2 cells. The cell death was mediated through activation of caspase -3, -8 and -9 activities. GdA up-regulated the expression of Fas and inhibited ERK activation in the Th-1 cells, which might enhance the vulnerability of the cells to cell death caused by a trophoblast-derived FasL. Conclusions The data suggest that GdA could be an endometrial factor that contributes to the Th-2/Th-1 shift during pregnancy. © 2011 The Author.postprin
Semi-supervised learning for the identification of syn-expressed genes from fused microarray and in situ image data
Background:
Gene expression measurements during the development of the fly Drosophila melanogaster are routinely used to find functional modules of temporally co-expressed genes. Complimentary large data sets of in situ RNA hybridization images for different stages of the fly embryo elucidate the spatial expression patterns.
Results:
Using a semi-supervised approach, constrained clustering with mixture models, we can find clusters of genes exhibiting spatio-temporal similarities in expression, or syn-expression. The temporal gene expression measurements are taken as primary data for which pairwise constraints are computed in an automated fashion from raw in situ images without the need for manual annotation. We investigate the influence of these pairwise constraints in the clustering and discuss the biological relevance of our results.
Conclusion:
Spatial information contributes to a detailed, biological meaningful analysis of temporal gene expression data. Semi-supervised learning provides a flexible, robust and efficient framework for integrating data sources of differing quality and abundance
Antimicrobial resistance among migrants in Europe: a systematic review and meta-analysis
BACKGROUND: Rates of antimicrobial resistance (AMR) are rising globally and there is concern that increased migration is contributing to the burden of antibiotic resistance in Europe. However, the effect of migration on the burden of AMR in Europe has not yet been comprehensively examined. Therefore, we did a systematic review and meta-analysis to identify and synthesise data for AMR carriage or infection in migrants to Europe to examine differences in patterns of AMR across migrant groups and in different settings. METHODS: For this systematic review and meta-analysis, we searched MEDLINE, Embase, PubMed, and Scopus with no language restrictions from Jan 1, 2000, to Jan 18, 2017, for primary data from observational studies reporting antibacterial resistance in common bacterial pathogens among migrants to 21 European Union-15 and European Economic Area countries. To be eligible for inclusion, studies had to report data on carriage or infection with laboratory-confirmed antibiotic-resistant organisms in migrant populations. We extracted data from eligible studies and assessed quality using piloted, standardised forms. We did not examine drug resistance in tuberculosis and excluded articles solely reporting on this parameter. We also excluded articles in which migrant status was determined by ethnicity, country of birth of participants' parents, or was not defined, and articles in which data were not disaggregated by migrant status. Outcomes were carriage of or infection with antibiotic-resistant organisms. We used random-effects models to calculate the pooled prevalence of each outcome. The study protocol is registered with PROSPERO, number CRD42016043681. FINDINGS: We identified 2274 articles, of which 23 observational studies reporting on antibiotic resistance in 2319 migrants were included. The pooled prevalence of any AMR carriage or AMR infection in migrants was 25·4% (95% CI 19·1-31·8; I2 =98%), including meticillin-resistant Staphylococcus aureus (7·8%, 4·8-10·7; I2 =92%) and antibiotic-resistant Gram-negative bacteria (27·2%, 17·6-36·8; I2 =94%). The pooled prevalence of any AMR carriage or infection was higher in refugees and asylum seekers (33·0%, 18·3-47·6; I2 =98%) than in other migrant groups (6·6%, 1·8-11·3; I2 =92%). The pooled prevalence of antibiotic-resistant organisms was slightly higher in high-migrant community settings (33·1%, 11·1-55·1; I2 =96%) than in migrants in hospitals (24·3%, 16·1-32·6; I2 =98%). We did not find evidence of high rates of transmission of AMR from migrant to host populations. INTERPRETATION: Migrants are exposed to conditions favouring the emergence of drug resistance during transit and in host countries in Europe. Increased antibiotic resistance among refugees and asylum seekers and in high-migrant community settings (such as refugee camps and detention facilities) highlights the need for improved living conditions, access to health care, and initiatives to facilitate detection of and appropriate high-quality treatment for antibiotic-resistant infections during transit and in host countries. Protocols for the prevention and control of infection and for antibiotic surveillance need to be integrated in all aspects of health care, which should be accessible for all migrant groups, and should target determinants of AMR before, during, and after migration. FUNDING: UK National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare Charity, the Wellcome Trust, and UK National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infections and Antimictobial Resistance at Imperial College London
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