Glycine-activated currents in 1- to 11-day-old rat medullary neurons were studied using patch clamp techniques. Glycine produced neither repeatable whole-cell current responses nor single-channel activity in the cell-attached mode until cells were in culture for a week or more. However, Cl- channels were present at the early stages because glycine-activated channels were seen in excised, inside-out patches. Furthermore, for cells less than a week in culture, 10 patches which did not exhibit glycine-activated Cl- channels in the cell-attached mode did upon excision. Consequently, the activation properties of these Cl- channels undergo a developmental change in that some cellular factor(s) presumably prevents the Cl- channels from opening in the intact cell during the initial stages in culture.
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http://dx.doi.org/10.1016/0165-3806(90)90288-a | DOI Listing |
Anal Chem
January 2025
Institute for Advanced Optics, Hunan Institute of Science and Technology, Yueyang, Hunan 414006, China.
Diffraction imaging of cells allows rapid phenotyping by the response of intracellular molecules to coherent illumination. However, its ability to distinguish numerous types of human leukocytes remains to be investigated. Here, we show that accurate classification of three lymphocyte subtypes can be achieved with features extracted from cross-polarized diffraction image (p-DI) pairs.
View Article and Find Full Text PDFBackground: Understanding the genetic etiology of Alzheimer's disease (AD) has been a major focus of research in neurodegenerative diseases. Amid the three common allelic variants of the apolipoprotein E (APOE) gene in humans, called APOE ε2, ε3 and ε4, the ε4 allele is the most common genetic risk factor for late-onset AD, being found in 20% of the world population.
Method: We used Event-Related Potentials (ERP) and Event-Related Spectral Perturbation (ERSP) as features for classification of apolipoprotein E ϵ4 (APOE ε4) allele carriers in AD patients and healthy controls.
Background: Cerebral microbleeds (CMBs) hold significant clinical relevance, linked to elevated risks of hemorrhages, cognitive decline, and mortality. Notably, with the recent advancement in Alzheimer's treatments, the number of CMBs serves as a crucial safety indicators to assess the risk and occurrence of amyloid-related imaging abnormalities. However, the commonly utilized manual detection process is time-consuming and labor-intensive, prompting the development of various automated detection models.
View Article and Find Full Text PDFAlzheimers Dement
December 2024
Centre for Brain Research (CBR), Indian Institute of Science, Bengaluru, Karnataka, India.
Background: Deep Neural Networks (DNNs) have emerged as powerful tools in the biomedical field, particularly for the early detection of neurodegenerative diseases. Despite their complexity and data-intensive nature, simpler fully connected Convolutional Neural Network (SFCN) architectures have shown effectiveness in accurately discerning between subjects affected by Alzheimer's disease (AD) and healthy controls (HC). This model draws inspiration from the work of Peng H et al.
View Article and Find Full Text PDFAlzheimers Dement
December 2024
University of Health Sciences and Pharmacy, St. Louis, MO, USA.
Background: Major Depressive Disorder (MDD) is a complex and multifaceted condition. Traditional screening methods may not capture the full spectrum of symptoms, causing delayed diagnoses or misdiagnoses. Further, MDD is highly prevalent among patients with mild cognitive impairment (MCI), which may then progress to Alzheimer's disease (AD).
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