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ABSTRACT MicroRNAs (miRNAs) play critical regulatory roles in diverse biological processes and are key biomarkers in a wide range of physiological and pathological conditions, including cancer. However, their inherently low concentrations in biological samples pose a major challenge for reliable detection and quantification. To overcome this limitation, we developed a fluorescence‐based biosensing platform that integrates rolling circle amplification (RCA) and multi‐primed chain amplification (MCA) to enhance signal and detection sensitivity. The system is engineered to allow flexible reconfiguration for different miRNA targets by altering probe and primer sequences. In this modular system, miR‐i, a miRNA commonly expressed in healthy and cancerous samples, serves as a universal initiator for RCA. Signal amplification was subsequently driven by hybridization with two randomly selected miRNAs (miR‐A and miR‐D), enabling evaluation of system performance under varied input conditions. Fluorescence emission was measured following the addition of a molecular beacon and subsequent spectrofluorometric analysis. The biosensor exhibited a strong linear correlation between miRNA concentration and fluorescence intensity, achieving a limit of detection (LOD), and limit of quantification (LOQ) below 10 pM in both buffer and human serum. These findings demonstrate the platform's high sensitivity and robustness. Importantly, modular architecture allows for easy reconfiguration to detect a wide array of miRNAs or other non‐coding RNAs, positioning this platform as a broadly applicable tool for molecular diagnostics beyond any specific disease context. 

Abstract CRISPR ribonucleoproteins (RNPs) use a variable segment in their guide RNA (gRNA) called a spacer to determine the DNA sequence at which the effector protein will exhibit nuclease activity and generate target‐specific genetic mutations. However, nuclease activity with different gRNAs can vary considerably in a spacer sequence‐dependent manner that can be difficult to predict. While computational tools are helpful in predicting a CRISPR effector's activity and/or potential for off‐target mutagenesis with different gRNAs, individual gRNAs must still be validated in vitro prior to their use. Here, the study presents compartmentalized CRISPR reactions (CCR) for screening large numbers of spacer/target/off‐target combinations simultaneously in vitro for both CRISPR effector activity and specificity by confining the complete CRISPR reaction of gRNA transcription, RNP formation, and CRISPR target cleavage within individual water‐in‐oil microemulsions. With CCR, large numbers of the candidate gRNAs (output by computational design tools) can be immediately validated in parallel, and the study shows that CCR can be used to screen hundreds of thousands of extended gRNA (x‐gRNAs) variants that can completely block cleavage at off‐target sequences while maintaining high levels of on‐target activity. It is expected that CCR can help to streamline the gRNA generation and validation processes for applications in biological and biomedical research. 

Abstract While the archival digital memory industry approaches its physical limits, the demand is significantly increasing, therefore alternatives emerge. Recent efforts have demonstrated DNA’s enormous potential as a digital storage medium with superior information durability, capacity, and energy consumption. However, the majority of the proposed systems require on-demand de-novo DNA synthesis techniques that produce a large amount of toxic waste and therefore are not industrially scalable and environmentally friendly. Inspired by the architecture of semiconductor memory devices and recent developments in gene editing, we created a molecular digital data storage system called “DNA Mutational Overwriting Storage” (DMOS) that stores information by leveraging combinatorial, addressable, orthogonal, and independent in vitro CRISPR base-editing reactions to write data on a blank pool of greenly synthesized DNA tapes. As a proof of concept, this work illustrates writing and accurately reading of both a bitmap representation of our school’s logo and the title of this study on the DNA tapes. 

Abstract Microfluidic valves play a key role within microfluidic systems by regulating fluid flow through distinct microchannels, enabling many advanced applications in medical diagnostics, lab‐on‐chips, and laboratory automation. While microfluidic systems are often limited to planar structures, 3D printing enables new capabilities to generate complex designs for fluidic circuits with higher densities and integrated components. However, the control of fluids within 3D structures presents several difficulties, making it challenging to scale effectively and many fluidic devices are still often restricted to quasi‐planar structures. Incorporating mechanical metamaterials that exhibit spatially adjustable mechanical properties into microfluidic systems provides an opportunity to address these challenges. Here, systematic computational and experimental characterization of a modified re‐entrant honeycomb structure are performed to generate a modular metamaterial for an active device that allows us to directly regulate flow through integrated, multiplexed fluidic channels “one‐at‐a‐time,” in a manner that is highly scalable. A design algorithm is presented, so that this architecture can be extended to arbitrary geometries, and it is expected that by incorporation of mechanical metamaterial designs into 3D printed fluidic systems, which themselves are readily expandable to any complex geometries, will enable new biotechnological and biomedical applications of 3D printed devices. 

Abstract Deoxyribonucleic acid (DNA) is emerging as an alternative archival memory technology. Recent advancements in DNA synthesis and sequencing have both increased the capacity and decreased the cost of storing information in de novo synthesized DNA pools. In this survey, we review methods for translating digital data to and/or from DNA molecules. An emphasis is placed on methods which have been validated by storing and retrieving real-world data via in-vitro experiments.