Prevalence of Baker's cyst in patients with knee pain: an ultrasonographic study

The objectives of this study are to investigate the prevalence of Baker's cyst (BC) in patients with knee pain, and to assess the correlation between BC and severity of osteophytes and joint effusion. A retrospective study was conducted on a group of patients with knee pain referred to our outpatient clinic for ultrasonography of the knee between January 2010 and February 2011. Patients underwent an ultrasonographic exam of the knees to assess the presence of marginal femorotibial osteophytosis, joint effusion and BC. A dichotomous score was assigned to each item (1 present, 0 absent) and severity of US signs of osteoarthritis and joint effusion were also graded semiquantitatively. Collected data were processed using logistic regression analysis to evaluate the correlation between degree of osteophytosis and joint effusion and BC. Patients affected by inflammatory joint conditions or with history of joint surgery or recent trauma were excluded. A total of 399 patients with knee pain were studied (299 women), in the age range 18-89 years (mean 56.2, SD 16.3 years). 293 patients (73.4%) showed sonographic features of osteoarthritis and 251 (62.9%) joint effusion. BC was found in 102 patients (25.8%) together with a positive association with sonographic features of osteoarthritis and joint effusion. Our data show a prevalence of BC of 25.8% in a population of patients with knee pain, and suggest that BC is positively related to osteoarthritis and joint effusion. Ultrasonographic examination of knee is worthwhile in patients with painful osteoarthritis or evidence of effusion

Capturing accelerometer outputs in healthy volunteers under normal and simulated-pathological conditions using ML classifiers

Wearable devices offer a possible solution for acquiring objective measurements of physical activity. Most current algorithms are derived using data from healthy volunteers. It is unclear whether such algorithms are suitable in specific clinical scenarios, such as when an individual has altered gait. We hypothesized that algorithms trained on healthy population will result in less accurate results when tested in individuals with altered gait. We further hypothesized that algorithms trained on simulated-pathological gait would prove better at classifying abnormal activity.We studied healthy volunteers to assess whether activity classification accuracy differed for those with healthy and simulated-pathological conditions. Healthy participants (n=30) were recruited from the University of Leeds to perform nine predefined activities under healthy and simulated-pathological conditions. Activities were captured using a wrist-worn MOX accelerometer (Maastricht Instruments, NL). Data were analyzed based on the Activity-Recognition-Chain process. We trained a Neural-Network, Random-Forests, k-Nearest-Neighbors (k-NN), Support-Vector-Machines (SVM) and Naive Bayes models to classify activity. Algorithms were trained four times; once with 'healthy' data, and once with 'simulated-pathological data' for each of activity-type and activity-task classification. In activity-type instances, the SVM provided the best results; the accuracy was 98.4% when the algorithm was trained and then tested with unseen data from the same group of healthy individuals. Accuracy dropped to 52.8% when tested on simulated-pathological data. When the model was retrained with simulated-pathological data, prediction accuracy for the corresponding test set was 96.7%. Algorithms developed on healthy data are less accurate for pathological conditions. When evaluating pathological conditions, classifier algorithms developed using data from a target sub-population can restore accuracy to above 95%.Clinical Relevance - This method remotely establishes health-related data of objective outcome measures of activities of daily living

Ultrasound in the diagnosis of calcium pyrophosphate dihydrate deposition disease. A systematic literature review and a meta-analysis

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Mycoviral Population Dynamics in Spanish Isolates of the Entomopathogenic Fungus Beauveria bassiana

The use of mycoviruses to manipulate the virulence of entomopathogenic fungi employed as biocontrol agents may lead to the development of novel methods to control attacks by insect pests. Such approaches are urgently required, as existing agrochemicals are being withdrawn from the market due to environmental and health concerns. The aim of this work is to investigate the presence and diversity of mycoviruses in large panels of entomopathogenic fungi, mostly from Spain and Denmark. In total, 151 isolates belonging to the genera Beauveria, Metarhizium, Lecanicillium, Purpureocillium, Isaria, and Paecilomyces were screened for the presence of dsRNA elements and 12 Spanish B. bassiana isolates were found to harbor mycoviruses. All identified mycoviruses belong to three previously characterised species, the officially recognised Beauveria bassiana victorivirus 1 (BbVV-1) and the proposed Beauveria bassiana partitivirus 2 (BbPV-2) and Beauveria bassiana polymycovirus 1 (BbPmV-1); individual B. bassiana isolates may harbor up to three of these mycoviruses. Notably, these mycovirus species are under distinct selection pressures, while recombination of viral genomes increases population diversity. Phylogenetic analysis of the RNA-dependent RNA polymerase gene sequences revealed that the current population structure in Spain is potentially a result of both vertical and horizontal mycovirus transmission. Finally, pathogenicity experiments using the Mediterranean fruit fly Ceratitis capitata showed no direct correlation between the presence of any particular mycovirus and the virulence of the B. bassiana isolates, but illustrated potentially interesting isolates that exhibit relatively high virulence, which will be used in more detailed virulence experimentation in the futur

Heusler-based synthetic antiferrimagnets

Antiferromagnet spintronic devices eliminate or mitigate long-range dipolar fields, thereby promising ultrafast operation. For spin transport electronics, one of the most successful strategies is the creation of metallic synthetic antiferromagnets, which, to date, have largely been formed from transition metals and their alloys. Here, we show that synthetic antiferrimagnetic sandwiches can be formed using exchange coupling spacer layers composed of atomically ordered RuAl layers and ultrathin, perpendicularly magnetized, tetragonal ferrimagnetic Heusler layers. Chemically ordered RuAl layers can both be grown on top of a Heusler layer and allow for the growth of ordered Heusler layers deposited on top of it that are as thin as one unit cell. The RuAl spacer layer gives rise to a thickness-dependent oscillatory interlayer coupling with an oscillation period of ~1.1 nm. The observation of ultrathin ordered synthetic antiferrimagnets substantially expands the family of synthetic antiferromagnets and magnetic compounds for spintronic technologies

Identification and sequence determination of a new chrysovirus infecting the phytopathogenic fungus Dothistroma septosporum

© The Author(s) 2023. This article is licensed under a Creative Commons Attribution 4.0 International License, to view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.A new double-stranded (ds) RNA mycovirus has been identified in isolate Ds752-1 of the phytopathogenic fungus Dothistroma septosporum, the causal agent of Dothistroma needle blight, also known as red band needle blight or pine needle blight. Dothistroma septosporum chrysovirus 1 (DsCV-1) is a new member of the genus Alphachrysovirus in the family Chrysoviridae. The DsCV-1 genome comprises four dsRNA elements designated 1, 2, 3, and 4 from largest to smallest. dsRNA1 encodes an RNA-dependent RNA polymerase (RdRP) that is most similar to the RdRP of Erysiphe necator associated chrysovirus 3. dsRNA2 potentially encodes two hypothetical proteins, one of which is small and has no homology to known proteins, and one of which is large with significant sequence similarity to the alphachryso-P3 of other alphachrysoviruses. dsRNA3 and dsRNA4 encode a coat protein (CP) and a putative cysteine protease, respectively. This is the first report of a mycovirus infecting the fungus D. septosporum, and DsCV-1 is one of three Chrysoviridae family members found to possess genomic dsRNAs potentially encoding more than one protein.Peer reviewe

Radiomics-Based Assessment of Primary Sjögren's Syndrome From Salivary Gland Ultrasonography Images

Salivary gland ultrasonography (SGUS) has shown good potential in the diagnosis of primary Sjögren's syndrome (pSS). However, a series of international studies have reported needs for improvements of the existing pSS scoring procedures in terms of inter/intra observer reliability before being established as standardized diagnostic tools. The present study aims to solve this problem by employing radiomics features and artificial intelligence (AI) algorithms to make the pSS scoring more objective and faster compared to human expert scoring. The assessment of AI algorithms was performed on a two-centric cohort, which included 600 SGUS images (150 patients) annotated using the original SGUS scoring system proposed in 1992 for pSS. For each image, we extracted 907 histogram-based and descriptive statistics features from segmented salivary glands. Optimal feature subsets were found using the genetic algorithm based wrapper approach. Among the considered algorithms (seven classifiers and five regressors), the best preforming was the multilayer perceptron (MLP) classifier (κ = 0.7). The MLP over-performed average score achieved by the clinicians (κ = 0.67) by the considerable margin, whereas its reliability was on the level of human intra-observer variability (κ = 0.71). The presented findings indicate that the continuously increasing HarmonicSS cohort will enable further advancements in AI-based pSS scoring methods by SGUS. In turn, this may establish SGUS as an effective noninvasive pSS diagnostic tool, with the final goal to supplement current diagnostic tests

OMERACT Definitions for Ultrasonographic Pathology and Elementary Lesions Of Rheumatic Disorders Fifteen Years On

Objective. The Outcome Measures in Rheumatology (OMERACT) ultrasound (US) working group (WG) operates research activities for the validation of US as an outcome measurement instrument according to the Filter 2.0 framework Methods. From the onset of the WG research in 2005 through now, original publications on definitions and scoring systems for pathophysiological manifestations and elementary lesions of various rheumatic disorders were reviewed Results. Definitions and scoring systems according to new terminology are provided Conclusions. We have redefined OMERACT definitions of US pathology and elementary lesions as well as scoring systems which are now proposed for OMERACT approval for application in clinical trial