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Overcoming missed diagnoses of primary central nervous system Lymphoma-The key role of cerebrospinal fluid cytology: a case report.
Diagn Pathol
March 2025
Department of Laboratory Medicine, Affiliated Hangzhou First People's Hospital, Westlake University School of Medicine, Hangzhou, 310006, China.
Background: Central nervous system (CNS) involvement in diffuse large B-cell lymphoma (DLBCL) is relatively rare, occurring at a rate of approximately 5%. Primary CNS lymphoma (CNS-DLBCL), a subtype of DLBCL, is rare clinically but highly malignant and invasive. Its atypical clinical symptoms and imaging features contribute to a high rate of misdiagnosis and a poor prognosis.
View Article and Find Full Text PDFStatistical overview of the Sniffin' sticks olfactory test from the perspectives of anosmia and hyposmia.
Sci Rep
March 2025
Research Laboratory on Engineering & Management Intelligence, HUN-REN Institute for Computer Science and Control (SZTAKI), 1111 Kende u. 13-17, Budapest, Hungary.
The Sniffin' Sticks test is evaluated by summing the scores of threshold, discrimination, and identification subtests to establish an olfactory diagnosis (anosmia, hyposmia, normosmia). However, variations in thresholds, ranges and inconsistencies have been observed. Statistical analyses (distributions, quantiles), protocol simulation, and implementations of the Sniffin' Sticks test were conducted.
View Article and Find Full Text PDFMachine learning-based prediction models for renal impairment in Chinese adults with hyperuricaemia: risk factor analysis.
Sci Rep
March 2025
Department of Endocrinology, Nanjing Hospital of Chinese Medicine Affiliated to Nanjing University of Chinese Medicine, Nanjing, China.
In hyperuricaemic populations, multiple factors may contribute to impaired renal function. This study aimed to establish a machine learning-based model to identify characteristic factors related to renal impairment in hyperuricaemic patients, determine dose‒response relationships, and facilitate early intervention strategies. Data were collected through the big data platform of Nanjing Hospital of Traditional Chinese Medicine, encompassing 2,705 patients with hyperuricaemia (1,577 with renal impairment, 828 without) from June 2019 to June 2022.
View Article and Find Full Text PDFA Novel Fusion Framework Combining Graph Embedding Class-Based Convolutional Recurrent Attention Network with Brown Bear Optimization Algorithm for EEG-Based Parkinson's Disease Recognition.
J Mol Neurosci
March 2025
Department of Physics, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Science (SIMATS), Thandalam, Chennai, 602105, India.
Parkinson's disease recognition (PDR) involves identifying Parkinson's disease using clinical evaluations, imaging studies, and biomarkers, focusing on early symptoms like tremors, rigidity, and bradykinesia to facilitate timely treatment. However, due to noise, variability, and the non-stationary nature of EEG signals, distinguishing PD remains a challenge. Traditional deep learning methods struggle to capture the intricate temporal and spatial dependencies in EEG data, limiting their precision.
View Article and Find Full Text PDFRandom regression in comparison with finite-dimensional models for estimation of genetic parameters for growth traits in goats.
Trop Anim Health Prod
March 2025
International Livestock Research Institute (ILRI), Addis Ababa, Ethiopia.
The application of the random regression model in comparison with finite-dimensional models (univariate and multivariate animal models) for genetic parameter estimation of growth traits in goats was evaluated in this study. A total of 2888 body weight records from 875 animals, recorded from birth to yearling age were used. All models included direct additive genetic and maternal genetic effects as a random effect in addition to fixed effects.
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