The quality control of RNA has become increasingly crucial with the rise of mRNA-based vaccines and therapeutics. However, conventional methods such as LC-MS often require specialized equipment and expertise, limiting their applicability to high throughput experiments. Here, we optimize a previously characterized RNA integrity biosensor, that provides a simple colorimetric output, using Design of Experiments (DoE). Through iterative rounds of a Definitive Screening Design (DSD) and experimental validation, we systematically explored different assay conditions to enhance the biosensor's performance. Optimization led to a 4.1-fold increase in dynamic range and reduced RNA concentration requirements by one-third, significantly improving usability. Notable modifications included reducing the concentrations of reporter protein and poly-dT oligonucleotide and increasing DTT concentration, suggesting a reducing environment for optimal functionality. Importantly, the optimized biosensor retained its ability to discriminate between capped and uncapped RNA even at lower RNA concentrations. Overall, our improved biosensor offers enhanced performance and reduced sample requirements, paving the way for rapid, cost-effective RNA quality control in diverse settings, including resource-limited environments.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1002/btpr.70005 | DOI Listing |
PLoS One
March 2025
Alliance of Biodiversity International and CIAT, ILRI, Addis Ababa, Ethiopia.
Depletion of soil organic matter was found to be the primary biophysical factor causing declining per capita food production in sub-Saharan Africa. The magnitude of this problem was exacerbated by moisture-stress and imbalanced fertilizer application that caused Striga weed infestation. To address such confounded issues, two-year field experiments were conducted to evaluate the effect of residual vermicompost and preceding groundnut on soil fertility, sorghum yield, and Striga density.
View Article and Find Full Text PDFJMIRx Med
March 2025
Stelmith, LLC, 2333 Aberdeen Pl, Carollton, TX, 75007, United States, 1 9459001314.
Background: The increasing integration of artificial intelligence (AI) systems into critical societal sectors has created an urgent demand for robust privacy-preserving methods. Traditional approaches such as differential privacy and homomorphic encryption often struggle to maintain an effective balance between protecting sensitive information and preserving data utility for AI applications. This challenge has become particularly acute as organizations must comply with evolving AI governance frameworks while maintaining the effectiveness of their AI systems.
View Article and Find Full Text PDFIEEE Trans Cybern
March 2025
Neighborhood rough sets are an effective model for handling numerical and categorical data entangled with vagueness, imprecision, or uncertainty. However, existing neighborhood rough set models and their feature selection methods treat each sample equally, whereas different types of samples inherently play different roles in constructing neighborhood granules and evaluating the goodness of features. In this study, the sample weight information is first introduced into neighborhood rough sets, and a novel weighted neighborhood rough set model is consequently constructed.
View Article and Find Full Text PDFPsychol Res
March 2025
School of Education, Guangzhou University, Guangzhou, 510006, People's Republic of China.
Cognitive offloading refers to the use of external tools to assist in memory processes.This study investigates the effects of item difficulty and value on cognitive offloading during a word-pair learning task, comparing children and young adults in a context where both cues coexist. In Experiment 1, we examined the impact of difficulty and value cues on cognitive offloading using a 2 (difficulty: easy vs.
View Article and Find Full Text PDFLangmuir
March 2025
Shenzhen Key Laboratory of Environmental Chemistry and Ecological Remediation, College of Chemistry and Environmental Engineering, Shenzhen University, Shenzhen, Guangdong 518060, China.
Horseradish peroxidase (HRP) is a metalloenzyme widely used in various biochemical applications but is susceptible to activity loss and instability under suboptimal conditions. In this study, rhamnolipid (RL) was, for the first time, employed as an additive to enhance the catalytic performance of HRP, including in a dual-enzyme cascade system with glucose oxidase (GOx). We carried out catalytic experiments on phenol degradation and showed that protecting HRP from deactivation is critical in maintaining the high catalytic effect in the dual-enzyme cascade.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!