Natural Polyphenol-Containing Gels against HSV-1 Infection: A Comparative Study

Herpes simplex virus type 1 infection commonly affects many people, causing perioral sores, as well as severe complications including encephalitis in immunocompromised patients. The main pharmacological approach involves synthetic antiviral drugs, among which acyclovir is the golden standard, often leading to resistant virus strains under long-term use. An alternative approach based on antiviral plant-derived compounds, such as quercetin and mangiferin, demonstrated an antiviral potential. In the present study, semisolid forms for cutaneous application of quercetin and mangiferin were designed and evaluated to treat HSV-1 infection. Phosphatidylcholine- and poloxamer-based gels were produced and characterized. Gel physical–chemical aspects were evaluated by rheological measurements and X-ray diffraction, evidencing the different thermoresponsive behaviors and supramolecular organizations of semisolid forms. Quercetin and mangiferin diffusion kinetics were compared in vitro by a Franz cell system, demonstrating the different gel efficacies to restrain the polyphenol diffusion. The capability of gels to control polyphenol antioxidant potential and stability was evaluated, indicating a higher stability and antioxidant activity in the case of quercetin loaded in poloxamer-based gel. Furthermore, a plaque reduction assay, conducted to compare the virucidal effect of quercetin and mangiferin loaded in gels against the HSV-1 KOS strain, demonstrated the suitability of poloxamer-based gel to prolong the polyphenol activity.

Highly divergent isolates of chrysanthemum virus B and chrysanthemum virus R infecting chrysanthemum in Russia

Background Chrysanthemum is a popular ornamental and medicinal plant that suffers from many viruses and viroids. Among them, chrysanthemum virus B (CVB, genus Carlavirus, family Betaflexiviridae) is widespread in all chrysanthemum-growing regions. Another carlavirus, chrysanthemum virus R (CVR), has been recently discovered in China. Information about chrysanthemum viruses in Russia is very scarce. The objective of this work was to study the prevalence and genetic diversity of CVB and CVR in Russia. Methods We surveyed the chrysanthemum (Chrysanthemum morifolium Ramat.) germplasm collection in the Nikita Botanical Gardens, Yalta, Russia. To detect CVB and CVR, we used RT-PCR with virus-specific primers. To reveal the complete genome sequences of CVB and CVR isolates, metatransciptomic analysis of the cultivars Ribonette, Fiji Yellow, and Golden Standard plants, naturally co-infected with CVB and CVR, was performed using Illumina high-throughput sequencing. The recombination detection tool (RDP4) was employed to search for recombination in assembled genomes. Results A total of 90 plants of 23 local and introduced chrysanthemum cultivars were surveyed. From these, 58 and 43% plants tested positive for CVB and CVR, respectively. RNA-Seq analysis confirmed the presence of CVB and CVR, and revealed tomato aspermy virus in each of the three transcriptomes. Six near complete genomes of CVB and CVR were assembled from the RNA-Seq reads. The CVR isolate X21 from the cultivar Golden Standard was 92% identical to the Chinese isolate BJ. In contrast, genomes of the CVR isolates X6 and X13 (from the cultivars Ribonette and Fiji Yellow, respectively), were only 76% to 77% identical to the X21 and BJ, and shared 95% identity to one another and appear to represent a divergent group of the CVR. Two distantly related CVB isolates, GS1 and GS2, were found in a plant of the cultivar Golden Standard. Their genomes shared from 82% to 87% identity to each other and the CVB genome from the cultivar Fiji Yellow (isolate FY), as well as to CVB isolates from Japan and China. A recombination event of 3,720 nucleotides long was predicted in the replicase gene of the FY genome. It was supported by seven algorithms implemented in RDP4 with statistically significant P-values. The inferred major parent was the Indian isolate Uttar Pradesh (AM765837), and minor parent was unknown. Conclusion We found a wide distribution of CVB and CVR in the chrysanthemum germplasm collection of the Nikita Botanical Gardens, which is the largest in Russia. Six near complete genomes of CVR and CVB isolates from Russia were assembled and characterized for the first time. This is the first report of CVR in Russia and outside of China thus expanding the information on the geographical distribution of the virus. Highly divergent CVB and CVR isolates have been identified that contributes the better understanding the genetic diversity of these viruses.

CNN-KCL: Automatic myocarditis diagnosis using convolutional neural network combined with k-means clustering

<abstract> <p>Myocarditis is the form of an inflammation of the middle layer of the heart wall which is caused by a viral infection and can affect the heart muscle and its electrical system. It has remained one of the most challenging diagnoses in cardiology. Myocardial is the prime cause of unexpected death in approximately 20% of adults less than 40 years of age. Cardiac MRI (CMR) has been considered a noninvasive and golden standard diagnostic tool for suspected myocarditis and plays an indispensable role in diagnosing various cardiac diseases. However, the performance of CMR depends heavily on the clinical presentation and features such as chest pain, arrhythmia, and heart failure. Besides, other imaging factors like artifacts, technical errors, pulse sequence, acquisition parameters, contrast agent dose, and more importantly qualitatively visual interpretation can affect the result of the diagnosis. This paper introduces a new deep learning-based model called Convolutional Neural Network-Clustering (CNN-KCL) to diagnose Myocarditis. In this study, we used 47 subjects with a total number of 98,898 images to diagnose myocarditis disease. Our results demonstrate that the proposed method achieves an accuracy of 97.41% based on 10 fold-cross validation technique with 4 clusters for diagnosis of Myocarditis. To the best of our knowledge, this research is the first to use deep learning algorithms for the diagnosis of myocarditis.</p> </abstract>

Respiratory Adherence Care Enhancer Questionnaire: Identifying Self-Management Barriers of Inhalation Corticosteroids in Asthma

Introduction: Suboptimal self-management of inhaled corticosteroids (ICS) in asthma patients is frequently observed in clinical practice and associated with poor asthma control. Driving factors for suboptimal self-management are complex and consist of a range of behavioral barriers (cognitive, affective and practical) with a considerable inter-individual variability. Identification of individual barriers facilitates the use of corresponding behavior change techniques and tailored care to improve asthma treatment outcomes.Objective: This study describes the development and validation of the ‘Respiratory Adherence Care Enhancer’ (RACE) questionnaire to identify individual barriers to self-management of ICS therapy in asthma patients.Methods: The development included: 1) an inventory of self-management barriers based on a literature review, 2) expert assessment on relevance and completeness of this set, linking these barriers to behavioral domains of the Theoretical Domains Framework (TDF) and 3) the formulation of corresponding questions assessing each of the barriers. A cross-sectional study was performed for validation. Primary care asthma patients were invited to fill out the RACE-questionnaire prior to a semi-structured telephonic interview as golden standard. Barriers detected from the questionnaire were compared to those mentioned in the interview.Results: The developed questionnaire is made up of 6 TDF-domains, covering 10 self-management barriers with 23 questions. For the validation 64 patients completed the questionnaire, of whom 61 patients were interviewed. Cronbach’s alpha for the consistency of questions within the barriers ranged from 0.58 to 0.90. Optimal cut-off values for the presence of barriers were determined at a specificity between 67 and 92% with a sensitivity between 41 and 83%. Significant Areas Under the Receiver Operating Curves values were observed for 9 barriers with values between 0.69 and 0.86 (p-value &lt;0.05), except for ‘Knowledge of ICS medication’ with an insignificant value of 0.53.Conclusion: The RACE-questionnaire yields adequate psychometric characteristics to identify individual barriers to self-management of ICS therapy in asthma patients, facilitating tailored care.

A Novel QT Interval Analysis Method Based On Continuous Wavelet Transform and Philips Algorithm

QT surveillance is the most vital appliance to detect the possibility of sudden death sourced by using pro-arrhythmic drugs treating abnormal conditions in the heart. The repolarization of ventricles makes QT interval surveillance difficult since noisy conditions and individual cardiac situations. Besides, an automated QT algorithm is crucial due to a manual QT measurement with some disadvantages such as fatigue condition in reading long records. In this study, a fully novel automated method combining Continuous Wavelet Transform and Philips method was established to perform QT interval analysis. ECG recordings were obtained from PhyisoNet database marked by manual and standard automated methods. The proposed algorithm had scores of 15.46 and 11.87 millisecond mean error with 11.85 and 9.91 millisecond standard deviation in terms of gold and silver standards, respectively. Also, the entire QT database was utilized in order to test the algorithm performance with the score of 12.89 and 9.76 millisecond mean and standard deviation errors, respectively. The present algorithm performance had scores of -0.21±7.81 at golden standard, and -4.10±18.21 millisecond error for the whole QT database tests, respectively. The proposed algorithm is attained to more stable and robust results with a higher performance than the previous comparable studies.

High performance of a GPU-accelerated variant calling tool in genome data analysis

Rapid advances in next-generation sequencing (NGS) have facilitated ultralarge population and cohort studies that utilized whole-genome sequencing (WGS) to identify DNA variants that may impact gene function. Massive sequencing data require highly efficient bioinformatics tools to complete read alignment and variant calling as the fundamental analysis. Multiple software and hardware acceleration strategies have been developed to boost the analysis speed. This study comprehensively evaluated the germline variant calling of a GPU-based acceleration tool, BaseNumber, using WGS datasets from several sources, including gold-standard samples from the Genome in a Bottle (GIAB) project and the Golden Standard of China Genome (GSCG) project, resequenced GSCG samples, and 100 in-house samples from the China Deafness Genetics Consortium (CDGC) project. Sequencing data were analyzed on the GPU server using BaseNumber, the variant calling outputs of which were compared to the reference VCF or the results generated by the Burrows-Wheeler Aligner (BWA) + Genome Analysis Toolkit (GATK) pipeline on a generic CPU server. BaseNumber demonstrated high precision (99.32%) and recall (99.86%) rates in variant calls compared to the standard reference. The variant calling outputs of the BaseNumber and GATK pipelines were very similar, with a mean F1 of 99.69%. Additionally, BaseNumber took only 23 minutes on average to analyze a 48X WGS sample, which was 215.33 times shorter than the GATK workflow. The GPU-based BaseNumber provides a highly accurate and ultrafast variant calling capability, significantly improving the WGS analysis efficiency and facilitating time-sensitive tests, such as clinical WGS genetic diagnosis, and sheds light on the GPU-based acceleration of other omics data analyses.

ENDOTHELIAL FUNCTION IN PATIENTS WITH COPD AND CARDIOVASCULAR DISEASE (REVIEW)

Cardiovascular pathology is one of the frequent comorbidities in patients with chronic obstructive pulmonary disease, due to both genetic predisposition and common risk factors (smoking, senile age, male gender, sedentary lifestyle, obesity). The article shows that development of endothelial dysfunction is one of the earliest phases of pathogenesis in this setting. Endothelial dysfunction mechanisms are defined and characterized, including an imbalance of vasoconstricting and vasodilating agents with the emergence of "vicious circles" that violate hemo-vascular homeostasis. The role of nitric oxide, endothelin-1, intercellular adhesion molecule-1 (ICAM-1) in the development of endothelial dysfunction in COPD patients is discussed. The article defines the concept of oxidative stress, the most potent oxidants and mechanisms of their damaging effect arebeing listed. A particular attention is paid to 8-isoprostane as a golden standard in assessment of oxidative stress in patients with COPD.

A Fast Markovian Method For Modeling Channel Noise In Neurons

Channel noise results from rapid transitions of protein channels from closed to open state and is generally considered as the most dominant source of electrical noise causing membrane-potential fluctuations even in the absence of synaptic inputs. The simulation of a realistic channel noise remains a source of possible error. Although the Markovian method is considered as the golden standard for appropriate description of channel noise, its computation time increasing exponentially with numbers of channels, it is poorly suitable to simulate realistic features. We describe here a novel algorithm for simulating ion channel noise based on Markov chains (MC). Although this new algorithm refers to a Monte-Carlo process, it only needs few random numbers whatever the number of channels involved. Our fast MC (FMC) model does not exhibit the drawbacks due to approximations based on stochastic differential equations. In fact, we show here, that these drawbacks can be highlighted even for a high number of channels.

Evaluation of bone marrow-derived cell-based therapies in the hindlimb ischaemia model: a protocol for a systematic review and meta-analysis

ObjectiveBone marrow(BM)-derived cell-based therapies for critical limb ischamia showed less clinical benefit than expected. While this might be due to patient-specific factors, it remains possible that important details were lost in the bench-to-clinic translation. The hindlimb ischaemia model is the golden standard to evaluate cell-based therapies aimed at promoting neovascularisation. To inform future trial design and identify potential knowledge gaps, we propose a systematic review and meta-analysis of preclinical evidence to assess the efficacy of BM-derived cell administration in restoring relative perfusion in the hind limb model and identify determinants of therapeutic efficacy.Search strategyPubMed and EMBASE were searched for prospective studies in which the hindlimb ischaemia model was used to assess BM-derived therapies.Screening and annotationStudies with an outcome measure related to relative perfusion of the hindlimb will be included. Study characteristics which include model-related factors as well as details on BM therapy will be extracted.Data management and reportingFor the primary analysis, a random effects model will be constructed using the mean difference calculated from the maximum relative perfusion for each study arm in each study. A separate model will be constructed using the relative perfusion at the latest time point in each study. We will also assess the risk of bias using the SYRCLE tool for internal validity. Subgroup analysis will be performed on animal characteristics, administration route, dose and cell characteristics such as the cell donor.PROSPERO registration numberThis protocol has been registered at PROSPERO (CRD2021226592).

A comparison of over-the-counter available smartwatches and devices for electrocardiogram based detection of atrial fibrillation

Background There is an increasing number of smartwatches and devices commercially available that can generate and automatically interpret an electrocardiogram (ECG). Such devices have an enormous potential to improve population screening and telemonitoring of atrial fibrillation (AF). Purpose There is limited data on the sensitivity, specificity and interpretability of these devices and comparative studies are lacking. Our purpose was to compare three frequently used devices for AF detection. Methods We performed a single-center, prospective study in consecutive patients with AF presenting for electrical cardioversion (ECV). We collected a standard 12-lead ECG recording immediately followed by four times 30 seconds of ECG recordings from different devices for every patient prior to the ECV. These paired measurements were considered simultaneous. If the ECV was performed, the same measurements were repeated afterwards. The standard 12L-ECGs were interpreted by a cardiologist and used as golden standard for heart rhythm. The different devices used for the 30 second ECGs were: Withings Move ECG (lead I), Apple Watch series 5 (lead I), Kardia Mobile 6L (six leads) and Withings/Apple (1:1 ratio) on left knee (lead II). Sensitivity and specificity were determined for each AF detection algorithm excluding patients with atrial flutter (AFL) or uninterpretable ECGs. In addition, proportions of uninterpretable ECGs were determined including all patients and including only patients with sinus rhythm (SR) and compared between devices using McNemar's test. Results A total of 220 patients were included (age 70±10 years, female 35%, first ECV 44%) and in total 415 12-lead ECGs were performed (45% SR, 45% AF, 10% AFL). The sensitivity/specificity were overall similar for all devices (Withings 98%/95%, Apple 94%/98%, Kardia 99%/91%. P&gt;0.05 for all). In detail, Kardia was the most sensitive test with highest proportion of suspected AF (57%) whereas Apple was the most specific, as shown by the highest proportion of normal heart rate results by the device (55%, P=0.003 compared to Kardia (43%)). Overall, Withings, Apple and Kardia had a comparable proportion of uninterpretable ECGs (20%, 20%, 24%, respectively. P&gt;0.05 for all). Lead II had higher proportion of uninterpretable ECGs (32%, p&lt;0.01 compared to all). More specifically, Kardia had a higher rate of uninterpretable ECGs in those with SR (P&lt;0.05 compared to Withings (lead I) and Apple (lead I)). Conclusion In all devices, we found sensitivity/specificity for AF detection between 91%-99%, better than previous studies reported, and 20–24% of uninterpretable ECGs. Kardia was the most sensitive device, but less useful to rule out atrial fibrillation whereas Apple had numerically highest specificity. We aim to further evaluate both cardiologist interpretation and accuracy of atrial flutter detection using different leads to inform clinical use. Funding Acknowledgement Type of funding sources: Public hospital(s). Main funding source(s): Tergooi Cardiology department, J.P. Bokma was supported with a research grant by Amsterdam Cardiovascular Sciences Overview and comparison