Performing multi-step chemical reactions in microliter-sized droplets by leveraging a simple passive transport mechanism.

Lab Chip

Crump Institute for Molecular Imaging and Department of Molecular & Medical Pharmacology, David Geffen School of Medicine, University of California at Los Angeles (UCLA), Los Angeles, CA, USA.

Published: December 2017

Despite the increasing importance of positron emission tomography (PET) imaging in research and clinical management of disease, access to myriad new radioactive tracers is severely limited due to their short half-lives (which requires daily production) and the high cost and complexity of tracer production. The application of droplet microfluidics based on electrowetting-on-dielectric (EWOD) to the field of radiochemistry can significantly reduce the amount of radiation shielding necessary for safety and the amount of precursor and other reagents needed for the synthesis. Furthermore, significant improvements in the molar activity of the tracers have been observed. However, widespread use of this technology is currently hindered in part by the high cost of prototype chips and the operating complexity. To address these issues, we developed a novel microfluidic device based on patterned wettability for multi-step radiochemical reactions in microliter droplets and implemented automated systems for reagent loading and collection of the crude product after synthesis. In this paper, we describe a simple and inexpensive method for fabricating the chips, demonstrate the feasibility of prototype chips for performing multi-step radiochemical reactions to produce the PET tracers [F]fallypride and [F]FDG, and further show that synthesized [F]fallypride can be used for in vivo mouse imaging.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6530551PMC
http://dx.doi.org/10.1039/c7lc01009eDOI Listing

Publication Analysis

Top Keywords

performing multi-step
8
high cost
8
prototype chips
8
multi-step radiochemical
8
radiochemical reactions
8
multi-step chemical
4
chemical reactions
4
reactions microliter-sized
4
microliter-sized droplets
4
droplets leveraging
4

Similar Publications

This study evaluates three Machine Learning (ML) models-Temporal Kolmogorov-Arnold Networks (TKAN), Long Short-Term Memory (LSTM), and Temporal Convolutional Networks (TCN)-focusing on their capabilities to improve prediction accuracy and efficiency in streamflow forecasting. We adopt a data-centric approach, utilizing large, validated datasets to train the models, and apply SHapley Additive exPlanations (SHAP) to enhance the interpretability and reliability of the ML models. The results show that TKAN outperforms LSTM but slightly lags behind TCN in streamflow forecasting.

View Article and Find Full Text PDF

Comparison of the Performance of Nonlinear Time-Dependent Constitutive Models Calibrated with Minimal Test Data Applied to an Epoxy Resin.

Materials (Basel)

January 2025

CITAB-Centre for the Research and Technology of Agro-Environmental and Biological Sciences, School of Science and Technology, University of Trás-os-Montes and Alto Douro, 5000-801 Vila Real, Portugal.

Epoxy resins are extensively employed as adhesives and matrices in fibre-reinforced composites. As polymers, they possess a viscoelastic nature and are prone to creep and stress relaxation even at room temperature. This phenomenon is also responsible for time-dependent failure or creep fracture due to cumulative strain.

View Article and Find Full Text PDF

RGGB sensor arrays are commonly used in digital cameras and mobile photography. However, images of extreme dark-light conditions often suffer from insufficient exposure because the sensor receives insufficient light. The existing methods mainly employ U-Net variants, multi-stage camera parameter simulation, or image parameter processing to address this issue.

View Article and Find Full Text PDF

[Construction of a visual intelligent identification model for in Yunnan Province based on the EfficientNet-B4 model].

Zhongguo Xue Xi Chong Bing Fang Zhi Za Zhi

January 2025

School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China.

Objective: To construct a visual intelligent recognition model for in Yunnan Province based on the EfficientNet-B4 model, and to evaluate the impact of data augmentation methods and model hyperparameters on the recognition of .

Methods: A total of 400 and 400 snails were collected from Yongsheng County, Yunnan Province in June 2024, and snail images were captured following identification and classification of 300 and 300 snails. A total of 925 images and 1 062 snail images were collected as a dataset and divided into a training set and a validation set at a ratio of 8:2, while 352 images captured from the remaining 100 and 354 images from the remaining 100 snails served as an external test set.

View Article and Find Full Text PDF

Introduction: Breath Volatile organic compounds (VOCs) are promising biomarkers for clinical purposes due to their unique properties. Translation of VOC biomarkers into the clinic depends on identification and validation: a challenge requiring collaboration, well-established protocols, and cross-comparison of data. Previously, we developed a breath collection and analysis method, resulting in 148 breath-borne VOCs identified.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!