3D bioprinting is a promising technique for creating artificial tissues and organs. One of the main challenges of bioprinting is cell damage, due to high pressures and tensions. During the biofabrication process, extrusion bioprinting usually results in low cell viability, typically ranging from 40% to 80%, although better printing performance with higher cell viability can be achieved by optimising the experimental design and operating conditions, with nozzle geometry being a key factor. This article presents a review of studies that have used computational fluid dynamics (CFD) to optimise nozzle geometry. They show that the optimal ranges for diameter and length are 0.2 mm to 1 mm and 8 mm to 10 mm, respectively. In addition, it is recommended that the nozzle should have an internal angle of 20 to 30 degrees, an internal coating of ethylenediaminetetraacetic acid (EDTA), and a shear stress of less than 10 kPa. In addition, a design of experiments technique to obtain an optimal 3D bioprinting configuration for a bioink is also presented. This experimental design would identify bioprinting conditions that minimise cell damage and improve the viability of the printed cells.
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http://dx.doi.org/10.3390/biomimetics9080460 | DOI Listing |
ACS Appl Bio Mater
January 2025
Department of Materials Engineering, Indian Institute of Science Bangalore, Karnataka 560012, India.
The cartilage possesses limited regenerative capacity, necessitating advanced approaches for its repair. This study introduces a bioink designed for cartilage tissue engineering (TE) by incorporating ionically cross-linkable alginate into the photo-cross-linkable MuMA bioink, resulting in a double cross-linked interpenetrating network (IPN) hydrogel. Additionally, hyaluronic acid (HA), a natural component of cartilage and synovial fluid, was added to enhance the scaffold's properties.
View Article and Find Full Text PDFEnviron Res
January 2025
Department of Civil, Environmental, & Architectural Engineering, Worcester Polytechnic Institute, Worcester, MA, United States. Electronic address:
The growing impact of climate change and escalating wildfire seasons has led to heightened ambient air pollution, potentially affecting children's sleep health. However, current epidemiological research often relies on outdoor weather data to model the environmental impacts on sleep health, potentially mischaracterizing the actual bedroom environment. To address these challenges, we conducted experiments to investigate the relationships among ambient, indoor, and personal exposure to PM concentrations and obstructive sleep apnea (OSA) in children.
View Article and Find Full Text PDFJ Mol Diagn
January 2025
Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, United States. Electronic address:
Single nucleotide variations (SNVs) and polymorphisms (SNPs) are characteristic biomarkers in various biological contexts, including pathogen drug resistances and human diseases. Tools that lower the implementation barrier of molecular SNV detection methods would provide greater leverage of the expanding SNP/SNV database. The oligonucleotide ligation assay (OLA) is a highly specific means for detection of known SNVs and is especially powerful when coupled with polymerase chain reaction (PCR).
View Article and Find Full Text PDFSci Total Environ
January 2025
School of the Environment, University of Queensland, QLD, Australia.
The transition to net zero emissions requires the capture of carbon dioxide from industrial point sources, and direct air capture (DAC) from the atmosphere for geological storage. Dissolved CO has reactivity to rock core, and while the majority of previous studies have concentrated on reservoir rock or cap-rock reactivity, the underlying seal formation may also react with CO. Drill core from the underlying seal of a target CO storage site was reacted at in situ conditions with pure CO, and compared with an impure CO stream with SO, NO and O that could be expected from hard to abate industries.
View Article and Find Full Text PDFNeural Netw
January 2025
Tsinghua University, Beijing, China. Electronic address:
Artificial neural networks (ANNs) can help camera-based remote photoplethysmography (rPPG) in measuring cardiac activity and physiological signals from facial videos, such as pulse wave, heart rate and respiration rate with better accuracy. However, most existing ANN-based methods require substantial computing resources, which poses challenges for effective deployment on mobile devices. Spiking neural networks (SNNs), on the other hand, hold immense potential for energy-efficient deep learning owing to their binary and event-driven architecture.
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