Medicina
-
Background and Objectives: Polycystic ovary syndrome (PCOS) is a frequent and complex multidisciplinary disorder. Data regarding the role of genes involved in vitamin D metabolism in PCOS are as-yet elusive but suggest an association of VDR (vitamin D receptor) and vitamin D levels with metabolic, endocrine and cutaneous manifestations. The aim of this study was to evaluate the association between VDR gene polymorphisms and cutaneous manifestations, to find a correlation between hormonal parameters, oxidative stress and skin manifestations in women with PCOS, and to determine the impact of VDR gene polymorphisms on these parameters. ⋯ The results demonstrated a significant protective effect of the C allele on the odds of acne and seborrhea in PCOS cases. Moreover, the dominant genotype of VDR-TaqI could have a protective role against oxidative stress (lower MDA levels) compared to patients carrying the TT genotype. Conclusions: In summary, this is the first study to demonstrate that the FokI CC genotype may have a protective role against both acne and seborrhea in women with PCOS, while the VDR-TaqI dominant genotype is associated with diminished oxidative stress in PCOS patients.
-
Anemophilous weeds from the Asteraceae family are highly allergenic and represent a significant source of aeroallergens in late summer and autumn. Ragweed and mugwort pollen allergies have become a significant health burden in Europe. ⋯ General physicians, ear, nose, and throat (ENT) specialists, and pulmonologists need to be familiar with the diagnostic tests used by allergists in clinical practice to support accurate diagnosis in such patients. Allergists must also be aware of the suggestions of the European Medicines Agency (EMA)'s Herbal Medicinal Products Committee and the broad spectrum of herbal therapies to educate their patients about potential risks.
-
Review Case Reports
Cardiac Paraganglioma in a Young Patient Presents with Angina-like Symptoms: A Case Report and Literature Review.
Paragangliomas are rare extra-adrenal neuroendocrine tumors originating from chromaffin tissue that present a diagnostic and therapeutic challenge due to their diverse clinical manifestations and low incidence. While these tumors often manifest as catecholamine-secreting functional tumors, their clinical presentation can vary, leading to delayed diagnosis and challenging management. ⋯ Surgical excision, including pulmonary artery graft and CABG, was the primary management approach, which was accompanied by intraoperative complications that later led to CCU admission, followed by postoperative complications, ultimately leading to the patient's death. This case highlights the significance of early recognition and management of complications following a surgical approach to treat paragangliomas.
-
Background and Objectives: Neglected patellar dislocation in the presence of end-stage osteoarthritis (OA) is a rare condition characterized by the patella remaining laterally dislocated without reduction. Due to the scarcity of reported cases, the optimal management approach is still uncertain. However, primary total knee arthroplasty (TKA) can serve as an effective treatment option. ⋯ At a mean follow-up of 68 months, no major complications requiring revision surgery, including patellar dislocation, were reported. Conclusions: Primary TKA is an effective procedure for correcting various pathologies associated with neglected patellar dislocation in end-stage OA without necessitating additional bony procedures. Satisfactory clinical and radiological outcomes can be expected using pathology-specific procedures.
-
Background/Objectives: To develop a deep learning model for esophageal motility disorder diagnosis using high-resolution manometry images with the aid of Gemini. Methods: Gemini assisted in developing this model by aiding in code writing, preprocessing, model optimization, and troubleshooting. ⋯ It presented better results for multiple categories, particularly in the panesophageal pressurization category, with precision = 0.99 and recall = 0.99, yielding a balanced F1-score of 0.99. Conclusions: This study demonstrates the potential of artificial intelligence, particularly Gemini, in aiding the creation of robust deep learning models for medical image analysis, solving not just simple binary classification problems but more complex, multi-class image classification tasks.