Does ultrasound-guided continuous suprascapular nerve block affect frozen shoulder rehabilitation programme outcome?

Background: Physical therapy (PT) is often recommended for patients with frozen shoulder. However, it could be painful for some patients, and this could hinder the rehabilitation programme. Some procedures like joint injection and suprascapular nerve block (SSNB) could alleviate pain during this setting. Objective: The purpose of this study was to compare the effectiveness of continuous SSNB plus PT compared to PT alone in managing frozen shoulder.Patients and methods: A total of 76 patients with frozen shoulder were included in this study. They were divided into two groups: 38 patients in the injection group (IG) received SSNB via catheter before PT, while the remaining 38 participants in the control group (CG) received no block prior to PT (CG). The functional state of the shoulder joint was assessed via the constant shoulder scale before and just after PT, then one month later.Results: General patient characteristics, including age, gender, BMI, comorbidities, and trauma history, were statistically comparable between the two groups. When we examined the constant scores of the two groups, we found that both had low scores before treatment, which increased immediately after treatment and then increased again one month later. Nonetheless, the injection group had a much greater increase than the control group.Conclusion: When used with PT for the treatment of adhesive capsulitis, continuous SSNB is an effective option that enhances the response to PT. It is associated with better improvement in shoulder function

Anti-inflammatory and anti-oxidant properties of Ipomoea nil (Linn.) Roth significantly alleviates cigarette smoke (CS)-induced acute lung injury via possibly inhibiting the NF-KB pathway

Acute respiratory distress syndrome (ARDS), a serious manifestation of acute lung injury (ALI), is a debilitating inflammatory lung disease that is caused by multiple risk factors. One of the primary causes that can lead to ALI/ ARDS is cigarette smoke (CS) and its primary mode of action is via oxidative stress. Despite extensive research, no appropriate therapy is currently available to treat ALI/ARDS, which means there is a dire need for new potential approaches. In our study we explored the protective effects of 70 % methanolic-aqueous extract of Ipomoea nil (Linn.) Roth, named as In.Mcx against CS-induced ALI mice models and RAW 264.7 macrophages because Ipomoea nil has traditionally been used to treat breathing irregularities. Male Swiss albino mice (20-25 +/- 2 g) were subjected to CS for 10 uninterrupted days in order to establish CS-induced ALI murine models. Dexamethasone (1 mg/kg), In.Mcx (100 200, and 300 mg/kg) and normal saline (10 mL/kg) were given to respective animal groups, 1 h before CS-exposure. 24 h after the last CS exposure, the lungs and bronchoalveolar lavage fluid (BALF) of all euthanized mice were harvested. Altered alveolar integrity and elevated lung weightcoefficient, total inflammatory cells, oxidative stress, expression of pro-inflammatory cytokines (IL-10 and IL-6) and chemokines (KC) were significantly decreased by In.Mcx in CS-exposed mice. In.Mcx also revealed significant lowering IL-10, IL-6 and KC expression in CSE (4 %)-activated RAW 264.7 macrophage. Additionally, In.Mcx showed marked enzyme inhibition activity against Acetylcholinesterase, Butyrylcholinesterase and Lipoxygenase. Importantly, In.Mcx dose-dependently and remarkably suppressed the CS-induced oxidative stress via not only reducing the MPO, TOS and MDA content but also improving TAC production in the lungs. Accordingly, HPLC analysis revealed the presence of many important antioxidant components. Finally, In.Mcx showed a marked decrease in the NF-KB expression both in in vivo and in vitro models. Our findings suggest that In.Mcx has positive therapeutic effects against CS-induced ALI via suppressing uncontrolled inflammatory response, oxidative stress, lipoxygenase and NF-KB p65 pathway

Molecular characterization of gliotoxin-producing Aspergillus fumigatus in dairy cattle feed

Background and Aim: Several strains of Aspergillus fumigatus produce mycotoxins that affect the health and productivity of dairy cattle, and their presence in dairy cattle feed is a serious concern. This study aimed to determine the densities of A. fumigatus and gliotoxin in commercial dairy feed. Materials and Methods: More than 60 dairy feed samples were examined for fungal contamination, specifically for A. fumigatus, using phenotypic approaches and DNA sequencing of the internal transcribed spacer (ITS) and β-tubulin regions. Thin-layer chromatography and high-performance liquid chromatography (HPLC) were used to assess gliotoxin production in A. fumigatus. Real-time polymerase chain reaction (RT-PCR) was used to investigate the expression of gliZ, which was responsible for gliotoxin production. High-performance liquid chromatography was used to detect gliotoxin in feed samples. Results: Aspergillus was the most commonly identified genus (68.3%). Aspergillus fumigatus was isolated from 18.3% of dairy feed samples. Only four of the 11 A. fumigatus isolates yielded detectable gliotoxins by HPLC. In total, 7/11 (43.7%) feed samples tested had gliotoxin contamination above the threshold known to induce immunosuppressive and apoptotic effects in vitro. The HPLC-based classification of isolates as high, moderate, or non-producers of gliotoxin was confirmed by RT-PCR, and the evaluation of gliZ expression levels corroborated this classification. Conclusion: The identification of A. fumigatus from animal feed greatly depended on ITS and β-tubulin sequencing. Significant concentrations of gliotoxin were found in dairy cattle feed, and its presence may affect dairy cow productivity and health. Furthermore, workers face contamination risks when handling and storing animal feed

Forecasting wind power based on an improved al-Biruni Earth radius metaheuristic optimization algorithm

Wind power forecasting is pivotal in optimizing renewable energy generation and grid stability. This paper presents a groundbreaking optimization algorithm to enhance wind power forecasting through an improved al-Biruni Earth radius (BER) metaheuristic optimization algorithm. The BER algorithm, based on stochastic fractal search (SFS) principles, has been refined and optimized to achieve superior accuracy in wind power prediction. The proposed algorithm is denoted by BERSFS and is used in an ensemble model’s feature selection and optimization to boost prediction accuracy. In the experiments, the first scenario covers the proposed binary BERSFS algorithm’s feature selection capabilities for the dataset under test, while the second scenario demonstrates the algorithm’s regression capabilities. The BERSFS algorithm is investigated and compared to state-of-the-art algorithms of BER, SFS, particle swarm optimization, gray wolf optimizer, and whale optimization algorithm. The proposed optimizing ensemble BERSFS-based model is also compared to the basic models of long short-term memory, bidirectional long short-term memory, gated recurrent unit, and the k-nearest neighbor ensemble model. The statistical investigation utilized Wilcoxon’s rank-sum and analysis of variance tests to investigate the robustness of the created BERSFS-based model. The achieved results and analysis confirm the effectiveness and superiority of the proposed approach in wind power forecasting

Evaluation of Some Prognostic Biomarkers in Human Papillomavirus-Related Multiphenotypic Sinonasal Carcinoma

Background: Human papillomavirus (HPV)-related multi phenotypic sinonasal carcinoma (HMSC) is a recently described tumor subtype with an unknown prognosis, often misdiagnosed with other sinonasal carcinomas, and associated with high-risk HPV (HR-HPV). The present study aimed to evaluate the expression of vascular endothelial growth factor (VEGF), Bcl-2-associated X protein (BAX), epidermal growth factor receptors (EGFR), ProEx™C, and human telomerase reverse transcriptase (hTERT) and assess their association with survival and clinicopathological characteristics.Methods: Between 2017 and 2022, 40 HMSC patients underwent surgical resection at the School of Medicine, Zagazig University Hospitals (Zagazig, Egypt). Tissue samples were examined for the presence of HR-HPV; absence of myeloblastosis (MYB), MYB proto-oncogene like 1 (MYBL1), and nuclear factor I/B (NFIB) fusions and the presence of myoepithelial proteins (calponin, S100, SMA), squamous differentiation markers (p63, p40, calponin), VEGF, BAX, ProEx™C, and hTERT by immunohistochemistry. All patients were followed up for about 54 months until death or the last known survival data. Data were analyzed using the Chi square test and Kaplan-Meier method.Results: The expression of VEGF, hTERT, and ProEx™C was significantly associated with age, advanced tumor stages, lymph node metastasis, tumor size, mortality, relapse, poor disease-free survival (DFS), and overall survival (OS) (P<0.001). BAX expression was significantly associated with tumor size, age, poor DFS, and relapse (P=0.01, P<0.001, P=0.035, and P=0.002, respectively). Conclusion: HMSC is strongly associated with HR-HPV. The expression of VEGF, EGFR, BAX, hTERT, and ProEx™C is associated with aggressive malignant behavior, poor survival, and poor prognosis, making them novel prognostic biomarkers for targeted therapeutics in HMSC

A novel voting classifier for electric vehicles population at different locations using Al-Biruni earth radius optimization algorithm

The rising popularity of electric vehicles (EVs) can be attributed to their positive impact on the environment and their ability to lower operational expenses. Nevertheless, the task of determining the most suitable EV types for a specific site continues to pose difficulties, mostly due to the wide range of consumer preferences and the inherent limits of EVs. This study introduces a new voting classifier model that incorporates the Al-Biruni earth radius optimization algorithm, which is derived from the stochastic fractal search. The model aims to predict the optimal EV type for a given location by considering factors such as user preferences, availability of charging infrastructure, and distance to the destination. The proposed classification methodology entails the utilization of ensemble learning, which can be subdivided into two distinct stages: pre-classification and classification. During the initial stage of classification, the process of data preprocessing involves converting unprocessed data into a refined, systematic, and well-arranged format that is appropriate for subsequent analysis or modeling. During the classification phase, a majority vote ensemble learning method is utilized to categorize unlabeled data properly and efficiently. This method consists of three independent classifiers. The efficacy and efficiency of the suggested method are showcased through simulation experiments. The results indicate that the collaborative classification method performs very well and consistently in classifying EV populations. In comparison to similar classification approaches, the suggested method demonstrates improved performance in terms of assessment metrics such as accuracy, sensitivity, specificity, and F-score. The improvements observed in these metrics are 91.22%, 94.34%, 89.5%, and 88.5%, respectively. These results highlight the overall effectiveness of the proposed method. Hence, the suggested approach is seen more favorable for implementing the voting classifier in the context of the EV population across different geographical areas

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

Exome-wide association study to identify rare variants influencing COVID-19 outcomes : Results from the Host Genetics Initiative

Publisher Copyright: Copyright: © 2022 Butler-Laporte et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Host genetics is a key determinant of COVID-19 outcomes. Previously, the COVID-19 Host Genetics Initiative genome-wide association study used common variants to identify multiple loci associated with COVID-19 outcomes. However, variants with the largest impact on COVID-19 outcomes are expected to be rare in the population. Hence, studying rare variants may provide additional insights into disease susceptibility and pathogenesis, thereby informing therapeutics development. Here, we combined whole-exome and whole-genome sequencing from 21 cohorts across 12 countries and performed rare variant exome-wide burden analyses for COVID-19 outcomes. In an analysis of 5,085 severe disease cases and 571,737 controls, we observed that carrying a rare deleterious variant in the SARS-CoV-2 sensor toll-like receptor TLR7 (on chromosome X) was associated with a 5.3-fold increase in severe disease (95% CI: 2.75–10.05, p = 5.41x10-7). This association was consistent across sexes. These results further support TLR7 as a genetic determinant of severe disease and suggest that larger studies on rare variants influencing COVID-19 outcomes could provide additional insights.Peer reviewe