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Multiple myeloma (MM) is a malignant disease characterized by the proliferation of plasma cells, primarily in the bone marrow. It accounts for approximately 1% of all cancers and 10% of hematologic malignancies. Clinical manifestations include hypercalcemia, anemia, renal failure, and bone lesions.

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Article Synopsis
  • The study examined the relationship between serum levels of 25-hydroxyvitamin D, IGF-1, and beta-2 microglobulin in elderly patients with cognitive dysfunction after ischemic stroke.
  • Data from 160 geriatric patients were analyzed, revealing that lower levels of 25-OH-VD and IGF-1 were linked to worse cognitive scores, while higher β2-MG levels correlated with greater cognitive decline.
  • Factors such as diabetes, low education levels, age, and certain serum markers were identified as independent risk factors for developing cognitive dysfunction post-stroke, suggesting the importance of monitoring these serum levels in clinical settings.
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This study evaluated the long-term efficacy and safety of the widely used drugs entecavir (ETV) and tenofovir alafenamide (TAF), as well as the incidence of HCC.A nonrandomized, prospective, observational analysis included 77 patients with chronic hepatitis B who were assigned to continue ETV or switch TAF. After 240 weeks, the mean changes in serum hepatitis B surface antigen (- 0.

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Beta-2 microglobulin-associated amyloidosis: A forgotten link to remember.

Nefrologia (Engl Ed)

January 2025

Nephrology Service, University Hospital Reina Sofia, Cordoba-Spain; Maimonides Biomedical Research Institute of Cordoba (IMIBIC), Cordoba, Spain University of Cordoba, Cordoba, Spain; Redes de Investigación Cooperativa Orientadas a Resultados en Salud, RICORS2040, Institute of Health Carlos III, Madrid, Spain; European Uremic Toxins Group (EUTOx). Electronic address:

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A machine learning-based model to predict POD24 in follicular lymphoma: a study by the Chinese workshop on follicular lymphoma.

Biomark Res

January 2025

Department of Hematology, The First Affiliated Hospital of Xiamen University and Institute of Hematology, School of Medicine, Xiamen University, Xiamen, 361003, P.R. China.

Background: Disease progression within 24 months (POD24) significantly impacts overall survival (OS) in patients with follicular lymphoma (FL). This study aimed to develop a robust predictive model, FLIPI-C, using a machine learning approach to identify FL patients at high risk of POD24.

Methods: A cohort of 1,938 FL patients (FL1-3a) from seventeen centers nationwide in China was randomly divided into training and internal validation sets (2:1 ratio).

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