Giant unilamellar vesicles (GUVs) are used extensively as models that mimic cell membranes. The cholesterol (Chol) content in the fiber cell plasma membranes of the eye lens is extremely high, exceeding the solubility threshold in the lenses of old humans. Thus, a methodological paper pertaining to preparations of model lipid bilayer membranes with high Chol content would significantly help the study of properties of these membranes. Lipid solutions containing 1-palmitoyl-2-oleoyl-glycero-3-phosphocholine (POPC) and Chol were fluorescently labeled with phospholipid analog 1,1'-dioctadecyl-3,3,3',3'-tetramethylindocarbocyanine perchlorate (DiIC(3)) and spin-coated to produce thin lipid films. GUVs were formed from these films using the electroformation method and the results were obtained using fluorescent microscopy. Electroformation outcomes were examined for different electrical parameters and different Chol concentrations. A wide range of field frequency-field strength (ff-fs) combinations was explored: 10-10,000 Hz and 0.625-9.375 V/mm peak-to-peak. Optimal values for GUVs preparation were found to be 10-100 Hz and 1.25-6.25 V/mm, with largest vesicles occurring for 10 Hz and 3.75 V/mm. Chol:POPC mixing ratios (expressed as a molar ratio) ranged from 0 to 3.5. We show that increasing the Chol concentration decreases the GUVs size, but this effect can be reduced by choosing the appropriate ff-fs combination.
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http://dx.doi.org/10.1007/s12013-020-00910-9 | DOI Listing |
PLoS One
January 2025
Department of Mathematics and Engineering Physics, Faculty of Engineering, Mansoura University, Mansoura, Egypt.
This paper focuses on modeling Resistor-Inductor (RL) electric circuits using a fractional Riccati initial value problem (IVP) framework. Conventional models frequently neglect the complex dynamics and memory effects intrinsic to actual RL circuits. This study aims to develop a more precise representation using a fractional-order Riccati model.
View Article and Find Full Text PDFSoft Matter
January 2025
Department of Mathematics, National Institute of Technology Durgapur, Durgapur-713209, India.
The present article deals with the modulation of oscillatory electroosmotic flow (EOF) and solute dispersion across a nanochannel filled with an electrolyte solution surrounded by a layer of a dielectric liquid. The dielectric permittivity of the liquid layer adjacent to supporting rigid walls is taken to be lower than that of the electrolyte solution. Besides, the aforesaid liquid layer may bear additional mobile charges, , free lipid molecules, charged surfactant molecules , which in turn lead to a nonzero charge along the liquid-liquid interface.
View Article and Find Full Text PDFSoft Matter
January 2025
Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran.
Microfluidic chips are powerful tools for investigating numerous variables including chemical and physical parameters on protein aggregation. This study investigated the aggregation of bovine serum albumin (BSA) in two different systems: a vial-based static system and a microfluidic chip-based dynamic system in which BSA aggregation was induced successfully. BSA aggregation induced in a microfluidic chip on a timescale of seconds enabled a dynamic investigation of the forces driving the aggregation process.
View Article and Find Full Text PDFChronobiol Int
January 2025
Google LLC, San Francisco, California, USA.
Circadian rhythms are governed by a biological clock, and are known to occur in a variety of physiological processes. We report results on the circadian rhythm of heart rate observed using a wrist-worn wearable device (Fitbit), consisting of over 17,000 individuals over the course of 30 days. We obtain an underlying heart rate circadian rhythm from the time series heart rate by modeling the circadian rhythm as a sum over the first two Fourier harmonics.
View Article and Find Full Text PDFVis Intell
December 2024
Department of Information Technology and Electrical Engineering, ETH Zurich, Sternwartstrasse 7, Zürich, Switzerland.
The LLaMA family, a collection of foundation language models ranging from 7B to 65B parameters, has become one of the most powerful open-source large language models (LLMs) and the popular LLM backbone of multi-modal large language models (MLLMs), widely used in computer vision and natural language understanding tasks. In particular, LLaMA3 models have recently been released and have achieved impressive performance in various domains with super-large scale pre-training on over 15T tokens of data. Given the wide application of low-bit quantization for LLMs in resource-constrained scenarios, we explore LLaMA3's capabilities when quantized to low bit-width.
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