MATERIALS AND METHODS: A retrospective analysis was done on 50 patients with proven CNS fungal infections. Fungal type was determined and grouped according to microbial classifications into four subtypes: hyalohyphomycetes, mucorales, yeasts and dematiaceous molds. MR findings were compared with histopathology/microbiology and associations between fungal groups were sought.
RESULTS: A total of 37 males and 13 females with a mean age of 39.3 years were included in the study. Aspergillus spp. infection (48%) was the most common. Most patients (54%) had an underlying risk factor for the infection. Pseudo-tumoral mass-like behavior was observed with Aspergillus, and the presence of meningitis was associated with yeast infections (p
METHODS: 48 newly diagnosed patients with hypercholesterolemia underwent 6 months intervention with statin and/or therapeutic lifestyle changes (TLC) in clinical setting. Lipid profile measurement and endothelial function assessment using PWA were performed pre- and post-intervention.
RESULTS: Significant reductions in low density lipoprotein cholesterol (LDL-C), non-high density lipoprotein cholesterol (non-HDL-C) and total cholesterol (TC) with corresponding significant improvement in EDV (2.94 ± 3.69 % to 7.50 ± 3.79 %, p
METHODS: This study presents a comprehensive systematic review focusing on the applications of deep learning in detecting MCI and AD using electroencephalogram (EEG) signals. Through a rigorous literature screening process based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, the research has investigated 74 different papers in detail to analyze the different approaches used to detect MCI and AD neurological disorders.
RESULTS: The findings of this study stand out as the first to deal with the classification of dual MCI and AD (MCI+AD) using EEG signals. This unique approach has enabled us to highlight the state-of-the-art high-performing models, specifically focusing on deep learning while examining their strengths and limitations in detecting the MCI, AD, and the MCI+AD comorbidity situations.
CONCLUSION: The present study has not only identified the current limitations in deep learning area for MCI and AD detection but also proposes specific future directions to address these neurological disorders by implement best practice deep learning approaches. Our main goal is to offer insights as references for future research encouraging the development of deep learning techniques in early detection and diagnosis of MCI and AD neurological disorders. By recommending the most effective deep learning tools, we have also provided a benchmark for future research, with clear implications for the practical use of these techniques in healthcare.
METHODS: A total of 88 BC women were randomly assigned into one of four groups: i) omega-3 fatty acid (ω3) group; ii) vitamin D (VitD) group; iii) ω3+VitD group, and iv) the control. Participants were received either two 300 mg ω3 capsules daily, or one 50,000IU VitD tablet weekly, or both supplementation for 9-weeks. The QoL status was assessed by the European Organization for Research and Treatment of Cancer (EORTC) instruments of QLQ-C30 and QLQ-BR23 tools, while blood inflammatory markers of TNF-α hsCRP were used. All measurements were taken from baseline to the end of the intervention period. The detailed procedures of the present study were registered on ClinicalTrial.gov with the identifier NCT05331807.
RESULTS: At the end of the trial, participants in the ω3+VitD group showed a significant increase in overall global health status (p
METHODS: We explored a collection of 4,392 well-characterized incident patients with RA of White European descent from the Epidemiological Investigation of Rheumatoid Arthritis (EIRA) new-onset RA study, as well as 1,199 cases of patients with RA of Southeast Asian origin from the Malaysian EIRA study. We focused on a quantitative analysis of the levels of anti-cyclic citrullinated peptide IgG antibodies, including those falling below the diagnostic threshold.
RESULTS: Our data show that non-shared epitope alleles HLA-DRB1*09 and *15 exhibit significant associations with ACPA levels. Notably, these novel associations were independent of ethnicity. To validate our findings, we conducted an additional replication study in an independent pool of 4,109 patients with RA of White European origin.
CONCLUSION: These results indicate a new, previously overlooked, role for the HLA locus in the regulation of the levels of ACPA RA-specific autoantibodies that goes beyond the shared epitope-defined gene variants.
METHODS AND RESULTS: We present a 50-year-old patient in whom a Medtronic EV ICD system was successfully removed without specialist extraction tools, 186 weeks after implantation, by an operator experienced in transvenous lead extraction but without formal training in EVICD implantation.
CONCLUSION: The successful extraction of an EV ICD system is possible without specialised tools at least 3.6 years post-implant.