We present a system consisting of a microfluidic device made of gas-permeable polydimethylsiloxane (PDMS) with two layers of microchannels and a computer-controlled multi-channel gas mixer. Concentrations of oxygen in the liquid-filled flow channels of the device are imposed by flowing gas mixtures with desired oxygen concentrations through gas channels directly above the flow channels. Oxygen gradients with different linear, exponential, and non-monotonic shapes are generated in the same liquid-filled microchannel and reconfigured in real time. The system can be used to study directed migration of cells and the development of cell and tissue cultures under gradients of oxygen.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2887752 | PMC |
http://dx.doi.org/10.1039/b920401f | DOI Listing |
Crit Care
January 2025
Department of Pediatric, West China Second University Hospital, Sichuan University, Chengdu, China.
Background: Patients supported by extracorporeal membrane oxygenation (ECMO) are at a high risk of brain injury, contributing to significant morbidity and mortality. This study aimed to employ machine learning (ML) techniques to predict brain injury in pediatric patients ECMO and identify key variables for future research.
Methods: Data from pediatric patients undergoing ECMO were collected from the Chinese Society of Extracorporeal Life Support (CSECLS) registry database and local hospitals.
Background: Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterised by cognitive decline, memory loss, and impaired daily functioning. As the global population ages, the prevalence of AD continues to rise, emphasising the urgent need for effective preventive and therapeutic strategies. Carotenoids, a group of naturally occurring pigments with antioxidant properties, have gained attention for their potential neuroprotective effects.
View Article and Find Full Text PDFAlzheimers Dement
December 2024
Washington University School of Medicine in St. Louis, St. Louis, MO, USA.
Background: There is a growing interest in investigating cerebrovascular dysfunction related to early Alzheimer disease (AD) pathology. The objective of this study is to evaluate changes in brain hemodynamic properties in relation to excess of β-amyloid (Aβ) deposition using the quantitative Gradient Recalled Echo (qGRE) MRI technique. Additionally, we aim to assess brain Aβ status by combining output metrics of qGRE and quantitative susceptibility maps (QSM).
View Article and Find Full Text PDFSAR QSAR Environ Res
December 2024
School of Computing and Data Sciences, FLAME University, Pune, India.
This study illustrates the use of chemical fingerprints with machine learning for blood-brain barrier (BBB) permeability prediction. Employing the Blood Brain Barrier Database (B3DB) dataset for BBB permeability prediction, we extracted nine different fingerprints. Support Vector Machine (SVM) and Extreme Gradient Boosting (XGBoost) algorithms were used to develop models for permeability prediction.
View Article and Find Full Text PDFChildren (Basel)
November 2024
Department of Neonatology, Beatrix Children's Hospital, University Medical Center Groningen, University of Groningen, Hanzeplein 1, P.O. Box 30.001, 9700 RB Groningen, The Netherlands.
Background/objectives: Necrotizing enterocolitis (NEC), a devastating neonatal gastrointestinal disease mostly seen in preterm infants, lacks accurate prediction despite known risk factors. This hinders the possibility of applying targeted preventive therapies. This study explores the use of vital signs, including cerebral and splanchnic oxygenation, measured with near-infrared spectroscopy in early NEC prediction.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!