Purpose: Assessment of cognitive impairment with a valid cognitive screening tool is essential in neurorehabilitation. The aim of this study was to test the reliability and validity of the Turkish-adapted version of the Middlesex Elderly Assessment of Mental State (MEAMS) among acquired brain injury patients in Turkey.
Methods: Some 155 patients with acquired brain injury admitted for rehabilitation were assessed by the adapted version of MEAMS at admission and discharge. Reliability was tested by internal consistency, intra-class correlation coefficient (ICC) and person separation index; internal construct validity by Rasch analysis; external construct validity by associations with physical and cognitive disability (FIM); and responsiveness by Effect Size.
Results: Reliability was found to be good with Cronbach's alpha of 0.82 at both admission and discharge; and likewise an ICC of 0.80. Person separation index was 0.813. Internal construct validity was good by fit of the data to the Rasch model (mean item fit -0.178; SD 1.019). Items were substantially free of differential item functioning. External construct validity was confirmed by expected associations with physical and cognitive disability. Effect size was 0.42 compared with 0.22 for cognitive FIM.
Conclusion: The reliability and validity of the Turkish version of MEAMS as a cognitive impairment screening tool in acquired brain injury has been demonstrated.
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http://dx.doi.org/10.1080/09638280600756612 | DOI Listing |
Neuroimage
January 2025
School of Biomedical Sciences and Engineering, South China University of Technology, Guangzhou International Campus, Guangzhou 511442, China; National Engineering Research Center for Tissue Restoration and Reconstruction, South China University of Technology, Guangzhou 510006, China; Department of Aging Research and Geriatric Medicine, Institute of Development, Aging and Cancer, Tohoku University, Sendai 980-8575, Japan. Electronic address:
The association between the human brain and gut microbiota, known as the "brain-gut-microbiota axis", is involved in the neuropathological mechanisms of schizophrenia (SZ); however, its association patterns and correlations with symptom severity and neurocognition are still largely unknown. In this study, 43 SZ patients and 55 normal controls (NCs) were included, and resting-state functional magnetic resonance imaging (rs-fMRI) and gut microbiota data were acquired for each participant. First, the brain features of brain images and functional brain networks were computed from rs-fMRI data; the gut features of gut microbiota abundance and the gut microbiota network were computed from gut microbiota data.
View Article and Find Full Text PDFMach Learn Clin Neuroimaging (2024)
December 2024
Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA.
Many longitudinal neuroimaging studies aim to improve the understanding of brain aging and diseases by studying the dynamic interactions between brain function and cognition. Doing so requires accurate encoding of their multidimensional relationship while accounting for individual variability over time. For this purpose, we propose an unsupervised learning model (called ntrastive Learning-based ph Generalized nonical Correlation Analysis (CoGraCa)) that encodes their relationship via Graph Attention Networks and generalized Canonical Correlational Analysis.
View Article and Find Full Text PDFFront Pharmacol
January 2025
Department of Radiation Oncology, The First Affiliated Hospital, Dalian Medical University, Dalian, Liaoning, China.
Introduction: Pemetrexed is a first line drug for brain metastases from lung cancer, either as monotherapy or combined with other drugs. The frequent occurrence of initial and acquired resistance to pemetrexed results in limited treatment effectiveness in brain metastases. CD146 was recently found to play important roles in chemoresistance and tumor progression.
View Article and Find Full Text PDFNat Methods
January 2025
Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada.
Teravoxel-scale, cellular-resolution images of cleared rodent brains acquired with light-sheet fluorescence microscopy have transformed the way we study the brain. Realizing the potential of this technology requires computational pipelines that generalize across experimental protocols and map neuronal activity at the laminar and subpopulation-specific levels, beyond atlas-defined regions. Here, we present artficial intelligence-based cartography of ensembles (ACE), an end-to-end pipeline that employs three-dimensional deep learning segmentation models and advanced cluster-wise statistical algorithms, to enable unbiased mapping of local neuronal activity and connectivity.
View Article and Find Full Text PDFJ Neurosci
January 2025
Department of Anatomy, Physiology, and Pharmacology, College of Veterinary Medicine, Auburn University, Auburn, AL, USA.
Animal models are commonly used to investigate developmental processes and disease risk, but humans and model systems (e.g., mice) differ substantially in the pace of development and aging.
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