Introduction: Lime phytodermatitis, also known as margarita dermatitis, is a condition that results in a skin rash after sunlight exposure when handling certain plants. Misdiagnosis is common due to its resemblance to skin burns or allergic contact dermatitis. Detailed history and disease recognition is important to provide accurate treatment recommendations.
Case Report: A 32-year-old woman presented with a recurrent rash on her hands that would only occur in the summer months. She was previously misdiagnosed as allergic contact dermatitis. History revealed yearly vacations involving margaritas and squeezing lime into her drinks followed by exposure to sunlight. A presumptive diagnosis of lime phytodermatitis was made and she was advised to avoid contact with limes followed by exposure to direct sunlight.
Discussion: Lime phytodermatitis occurs after direct contact with lime and sunlight exposure. A phototoxic compound found in limes, Furocoumarin, has been implicated as a cause for lime disease. Detailed history is important in establishing a diagnosis of lime disease. Treatment is symptomatic with topical corticosteroids, avoidance of furocoumarin-containing objects, cold compresses, and subsequent UV exposure.
Conclusion: We present the first case of recurrent, bilateral phytodermatitis in a 32-year-old woman following contact with limes and subsequent sunlight exposure in the summer months.
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http://dx.doi.org/10.1177/21526567221074944 | DOI Listing |
J Neurol Sci
December 2024
Computational and Translational Neuroscience Laboratory, Institute of Cognitive Sciences and Technologies, National Research Council (CTNLab-ISTC-CNR), Via Gian Domenico Romagnosi 18A, Rome 00196, Italy; AI2Life s.r.l., Innovative Start-Up, ISTC-CNR Spin-Off, Via Sebino 32, Rome 00199, Italy. Electronic address:
Alzheimer's disease (AD), the most common neurodegenerative disorder world-wide, presents sex-specific differences in its manifestation and progression, necessitating personalized diagnostic approaches. Current procedures are often costly and invasive, lacking consideration of sex-based differences. This study introduces an explainable machine learning (ML) system to predict and differentiate the progression of AD based on sex, using non-invasive, easily collectible predictors such as neuropsychological test scores and sociodemographic data, enabling its application in every day clinical settings.
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ICT Convergence Research Centre, Soonchunhyang University, Asan, Republic of Korea.
One of the most prevalent disorders relating to neurodegenerative conditions and dementia is Alzheimer's disease (AD). In the age group 65 and older, the prevalence of Alzheimer's disease is increasing. Before symptoms showed up, the disease had grown to a severe stage and resulted in an irreversible brain disorder that is not treatable with medication or other therapies.
View Article and Find Full Text PDFJ Hazard Mater
December 2024
Centre for Technology in Water and Wastewater, School of Civil and Environmental Engineering, University of Technology Sydney, Sydney, NSW 2007, Australia.
The pathogens inactivation in wastewater sludges is vitally important for safely managing solid wastes and protecting public and environmental health especially in the emergency. Reports have shown the effectiveness of lime to kill virus pathogens in sludges, but mechanism of virus inactivation and related human diseases is unclear. This study evaluated representative limes of CaO/CaO on actual viral microorganism inactivation by viral metagenomic sequencing technology.
View Article and Find Full Text PDFJ Clin Med
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Function Perioperative Medicine and Intensive Care, Karolinska University Hospital, 171 76 Stockholm, Sweden.
The long-term risk of cardiovascular and thrombotic events following severe COVID-19 remains largely unknown. This study aimed to assess the risk of atherosclerotic cardiovascular disease (ASCVD) within one year after hospital discharge in patients who received intensive care for severe COVID-19. A register-based nationwide case-control study on a cohort of patients with severe COVID-19 (cases) requiring mechanical ventilation and discharged alive without experiencing cardiovascular or thrombotic events during their hospital stay.
View Article and Find Full Text PDFDiagnostics (Basel)
December 2024
Preclinical Department, Faculty of Medicine, Lucian Blaga University of Sibiu, 550024 Sibiu, Romania.
This study investigates disruptions in functional brain networks in Parkinson's Disease (PD), using advanced modeling and machine learning. Functional networks were constructed using the Nonlinear Autoregressive Distributed Lag (NARDL) model, which captures nonlinear and asymmetric dependencies between regions of interest (ROIs). Key network metrics and information-theoretic measures were extracted to classify PD patients and healthy controls (HC), using deep learning models, with explainability methods employed to identify influential features.
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