A novel two-stage heart arrhythmia ensemble classifier

Atrial fibrillation (AF) and ventricular arrhythmia (Arr) are among the most common and fatal cardiac arrhythmias in the world. Electrocardiogram (ECG) data, collected as part of the UK Biobank, represents an opportunity for analysis and classification of these two diseases in the UK. The main objective of our study is to investigate a two-stage model for the classification of individuals with AF and Arr in the UK Biobank dataset. The current literature addresses heart arrhythmia classification very extensively. However, the data used by most researchers lack enough instances of these common diseases. Moreover, by proposing the two-stage model and separation of normal and abnormal cases, we have improved the performance of the classifiers in detection of each specific disease. Our approach consists of two stages of classification. In the first stage, features of the ECG input are classified into two main classes: normal and abnormal. At the second stage, the features of the ECG are further categorised as abnormal and further classified into two diseases of AF and Arr. A diverse set of ECG features such as the QRS duration, PR interval and RR interval, as well as covariates such as sex, BMI, age and other factors, are used in the modelling process. For both stages, we use the XGBoost Classifier algorithm. The healthy population present in the data, has been undersampled to tackle the class imbalance present in the data. This technique has been applied and evaluated using an ECG dataset from the UKBioBank ECG taken at rest repository. The main results of our paper are as follows: The classification performance for the proposed approach has been measured using F1 score, Sensitivity (Recall) and Specificity (Precision). The results of the proposed system are 87.22%, 88.55% and 85.95%, for average F1 Score, average sensitivity and average specificity, respectively. Contribution and significance: The performance level indicates that automatic detection of AF and Arr in participants present in the UK Biobank is more precise and efficient if done in a two-stage manner. Automatic detection and classification of AF and Arr individuals this way would mean early diagnosis and prevention of more serious consequences later in their lives

OCP3 is an important modulator of NPR1-mediated jasmonic acid-dependent induced defenses in Arabidopsis

<p>Abstract</p> <p>Background</p> <p>Upon appropriate stimulation, plants increase their level of resistance against future pathogen attack. This phenomenon, known as induced resistance, presents an adaptive advantage due to its reduced fitness costs and its systemic and broad-spectrum nature. In <it>Arabidopsis</it>, different types of induced resistance have been defined based on the signaling pathways involved, particularly those dependent on salicylic acid (SA) and/or jasmonic acid (JA).</p> <p>Results</p> <p>Here, we have assessed the implication of the transcriptional regulator OCP3 in SA- and JA-dependent induced defenses. Through a series of double mutant analyses, we conclude that SA-dependent defense signaling does not require OCP3. However, we found that <it>ocp3 </it>plants are impaired in a <it>Pseudomonas fluorescens </it>WCS417r-triggered induced systemic resistance (ISR) against both <it>Pseudomonas syrinagae </it>DC3000 and <it>Hyaloperonospora arabidopsidis</it>, and we show that this impairment is not due to a defect in JA-perception. Likewise, exogenous application of JA failed to induce defenses in <it>ocp3 </it>plants. In addition, we provide evidence showing that the over-expression of an engineered cytosolic isoform of the disease resistance regulator NPR1 restores the impaired JA-induced disease resistance in <it>ocp3 </it>plants.</p> <p>Conclusions</p> <p>Our findings point to a model in which OCP3 may modulate the nucleocytosolic function of NPR1 in the regulation of JA-dependent induced defense responses.</p

Immune Profiling of Peripheral Blood Mononuclear Cells at Pancreas Acute Rejection Episodes in Kidney-Pancreas Transplant Recipients

Profiling of circulating immune cells provides valuable insight to the pathophysiology of acute rejection in organ transplantation. Herein we characterized the peripheral blood mononuclear cells in simultaneous kidney-pancreas transplant recipients. We conducted a retrospective analysis in a biopsy-matched cohort (n = 67) and compared patients with biopsy proven acute rejection (BPAR; 41%) to those without rejection (No-AR). We observed that CD3+ T cells, both CD8+ and CD4+, as well as CD19+ B cells were increased in patients with BPAR, particularly in biopsies performed in the early post-transplant period (<3 months). During this period immune subsets presented a good discriminative ability (CD4+ AUC 0.79; CD8+ AUC 0.80; B cells AUC 0.86; p < 0.05) and outperformed lipase (AUC 0.62; p = 0.12) for the diagnosis of acute rejection. We further evaluated whether this could be explained by differences in frequencies prior to transplantation. Patients presenting with early post-transplant rejection (<3 months) had a significant increase in T-cell frequencies pre-transplant, both CD4+ T cells and CD8+ T cells (p < 0.01), which were associated with a significant inferior rejection-free graft survival. T cell frequencies in peripheral blood correlated with pancreas acute rejection episodes, and variations prior to transplantation were associated with pancreas early acute rejection.Copyright © 2022 Rovira, Ramirez-Bajo, Bañón-Maneus, Hierro-Garcia, Lazo-Rodriguez, Piñeiro, Montagud-Marrahi, Cucchiari, Revuelta, Cuatrecasas, Campistol, Ricart, Diekmann, Garcia-Criado and Ventura-Aguiar

High Sensitivity C Reactive Protein in Patients with Rheumatoid Arthritis Treated with Antibodies against IL-6 or Jak Inhibitors: A Clinical and Ultrasonographic Study

Background: We examined whether high-sensitivity CRP (hsCRP) reflected the inflammatory disease status evaluated by clinical and ultrasound (US) parameters in RA patients receiving IL-6 receptor antibodies (anti-IL-6R) or JAK inhibitors (JAKi). Methods: We conducted a cross-sectional study of patients with established RA receiving anti-IL-6R (tocilizumab, sarilumab) or JAKi (tofacitinib, baricitinib). Serum hsCRP and US synovitis in both hands were measured. Associations between hsCRP and clinical inflammatory activity were evaluated using composite activity indices. The association between hsCRP and US synovitis was analyzed. Results: 63 (92% female) patients (42 anti- IL-6R and 21 JAKi) were included, and the median disease duration was 14.4 (0.2–37.5) years. Most patients were in remission or had low levels of disease. Overall hsCRP values were very low, and significantly lower in anti-IL-6R patients (median 0.04 mg/dL vs. 0.16 mg/dL). Anti-IL-6R (82.4%) patients and 48% of JAKi patients had very low hsCRP levels (≤0.1 mg/dL) (p = 0.002). In the anti-IL-6R group, hsCRP did not correlate with the composite activity index or US synovitis. In the JAKi group, hsCRP moderately correlated with US parameters (r = 0.5) but not clinical disease activity, and hsCRP levels were higher in patients with US synovitis (0.02 vs. 0.42 mg/dL) (p = 0.001). Conclusion: In anti-IL-6R RA-treated patients, hsCRP does not reflect the inflammatory disease state, but in those treated with JAKi, hsCRP was associated with US synovitis

Environmentally friendly analysis of emerging contaminants by pressurized hot water extraction-stir bar sorptive extraction-derivatization and gas chromatography-mass spectrometry

This work describes the development, optimiza- tion, and validation of a new method for the simultaneous determination of a wide range of pharmaceuticals (beta- blockers, lipid regulators ... ) and personal care products (fragrances, UV filters, phthalates ... ) in both aqueous and solid environmental matrices. Target compounds were extracted from sediments using pressurized hot water ex- traction followed by stir bar sorptive extraction. The first stage was performed at 1,500 psi during three static extrac- tion cycles of 5 min each after optimizing the extraction temperature (50 – 150 °C) and addition of organic modifiers (% methanol) to water, the extraction solvent. Next, aqueous extracts and water samples were processed using polydime- thylsiloxane bars. Several parameters were optimized for this technique, including extraction and desorption time, ionic strength, presence of organic modifiers, and pH. Fi- nally, analytes were extracted from the bars by ultrasonic irradiation using a reduced amount of solvent (0.2 mL) prior to derivatization and gas chromatography – mass spectrome- try analysis. The optimized protocol uses minimal amounts of organic solvents (<10 mL/sample) and time ( ≈ 8 h/sam- ple) compared to previous ex isting methodologies. Low standard deviation (usually below 10 %) and limits of de- tection (sub-ppb) vouch for the applicability of the method- ology for the analysis of target compounds at trace levels. Once developed, the method was applied to determin

Synergistic Antibacterial Effects of Metallic Nanoparticle Combinations

© The Author(s) 2019.Metallic nanoparticles have unique antimicrobial properties that make them suitable for use within medical and pharmaceutical devices to prevent the spread of infection in healthcare. The use of nanoparticles in healthcare is on the increase with silver being used in many devices. However, not all metallic nanoparticles can target and kill all disease-causing bacteria. To overcome this, a combination of several different metallic nanoparticles were used in this study to compare effects of multiple metallic nanoparticles when in combination than when used singly, as single elemental nanoparticles (SENPs), against two common hospital acquired pathogens (Staphylococcus aureus and Pseudomonas. aeruginosa). Flow cytometry LIVE/DEAD assay was used to determine rates of cell death within a bacterial population when exposed to the nanoparticles. Results were analysed using linear models to compare effectiveness of three different metallic nanoparticles, tungsten carbide (WC), silver (Ag) and copper (Cu), in combination and separately. Results show that when the nanoparticles are placed in combination (NPCs), antimicrobial effects significantly increase than when compared with SENPs (P < 0.01). This study demonstrates that certain metallic nanoparticles can be used in combination to improve the antimicrobial efficiency in destroying morphologically distinct pathogens within the healthcare and pharmaceutical industry.Peer reviewe

Global distribution of two fungal pathogens threatening endangered sea turtles

This work was supported by grants of Ministerio de Ciencia e Innovación, Spain (CGL2009-10032, CGL2012-32934). J.M.S.R was supported by PhD fellowship of the CSIC (JAEPre 0901804). The Natural Environment Research Council and the Biotechnology and Biological Sciences Research Council supported P.V.W. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Thanks Machalilla National Park in Ecuador, Pacuare Nature Reserve in Costa Rica, Foundations Natura 2000 in Cape Verde and Equilibrio Azul in Ecuador, Dr. Jesus Muñoz, Dr. Ian Bell, Dr. Juan Patiño for help and technical support during samplingPeer reviewedPublisher PD

Thermal Neutron Relative Biological Effectiveness Factors for Boron Neutron Capture Therapy from In Vitro Irradiations

The experimental determination of the relative biological effectiveness of thermal neutron factors is fundamental in Boron Neutron Capture Therapy. The present values have been obtained while using mixed beams that consist of both neutrons and photons of various energies. A common weighting factor has been used for both thermal and fast neutron doses, although such an approach has been questioned. At the nuclear reactor of the Institut Laue-Langevin a pure low-energy neutron beam has been used to determine thermal neutron relative biological effectiveness factors. Different cancer cell lines, which correspond to glioblastoma, melanoma, and head and neck squamous cell carcinoma, and non-tumor cell lines (lung fibroblast and embryonic kidney), have been irradiated while using an experimental arrangement designed to minimize neutron-induced secondary gamma radiation. Additionally, the cells were irradiated with photons at a medical linear accelerator, providing reference data for comparison with that from neutron irradiation. The survival and proliferation were studied after irradiation, yielding the Relative Biological Effectiveness that corresponds to the damage of thermal neutrons for the different tissue types.Asociacion Espanola Contra el Cancer (AECC) PS16163811PORRSpanish MINECO FIS2015-69941-C2-1-PJunta de Andalucia P11-FQM-8229Campus of International Excellence BioTic P-BS-64University of Granada Chair Neutrons for Medicine: the Spanish Fundacion ACSAsociacion Capitan AntonioFundacion ACSLa Kuadrilla de IznallozSonriendo Se Puede Gana

Multiple Imputation Ensembles (MIE) for dealing with missing data

Missing data is a significant issue in many real-world datasets, yet there are no robust methods for dealing with it appropriately. In this paper, we propose a robust approach to dealing with missing data in classification problems: Multiple Imputation Ensembles (MIE). Our method integrates two approaches: multiple imputation and ensemble methods and compares two types of ensembles: bagging and stacking. We also propose a robust experimental set-up using 20 benchmark datasets from the UCI machine learning repository. For each dataset, we introduce increasing amounts of data Missing Completely at Random. Firstly, we use a number of single/multiple imputation methods to recover the missing values and then ensemble a number of different classifiers built on the imputed data. We assess the quality of the imputation by using dissimilarity measures. We also evaluate the MIE performance by comparing classification accuracy on the complete and imputed data. Furthermore, we use the accuracy of simple imputation as a benchmark for comparison. We find that our proposed approach combining multiple imputation with ensemble techniques outperform others, particularly as missing data increases