98%
921
2 minutes
20
Toehold-mediated strand displacement (TMSD) provides a versatile toolbox for developing DNA digital computing systems. Although different logic circuits with diverse functions have achieved good performance in terms of complexity and scalability, most previous DNA logic circuits perform information processing only at the molecular level, and nonspecific signal leakages are often difficult to avoid. Here, we demonstrate the feasibility of constructing leakless digital computing systems in three-dimensionally ordered colloidal supercrystals. These systems possess a unique signal leakage resistance by integrating different TMSD-based logic gates with the catalytic assembly of DNA-functionalized gold colloids. A complete set of basic Boolean logic gates and different cascaded logic circuits is constructed on the basis of the catalytic assembly strategy enabled by a facilely designed catassembler, where the output signals are recognized by determining whether specific colloidal supercrystals are formed or not. In addition, a half adder is built through a combination of XOR and AND logic gates with two distinct crystal types as readouts. Finally, a leakless two-digit DNA keypad lock for information security protection is demonstrated. The combination of TMSD-based logic circuits with the universal nanoparticle catalytic assembly offers the possibility to develop highly complicated and leakage-free digital computing systems and promotes macroscopic colloidal superlattice materials with programmable logic functions.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1021/jacs.4c12078 | DOI Listing |
Background: Transforming Clinical Practice Guideline (CPG) recommendations into computer readable language is a complex and ongoing process that requires significant resources, including time, expertise, and funds. The objective is to provide an extension of the widely used GIN-McMaster Guideline Development Checklist (GDC) and Tool for the development of computable guidelines (CGs).
Methods: Based on an outcome from the Human Centered Design (HCD) workshop hosted by the Guidelines International Network North America (GIN-NA), a team was formed to develop the checklist extension.
Radiol Adv
September 2024
Department of Radiology, Northwestern University and Northwestern Medicine, Chicago, IL, 60611, United States.
Background: In clinical practice, digital subtraction angiography (DSA) often suffers from misregistration artifact resulting from voluntary, respiratory, and cardiac motion during acquisition. Most prior efforts to register the background DSA mask to subsequent postcontrast images rely on key point registration using iterative optimization, which has limited real-time application.
Purpose: Leveraging state-of-the-art, unsupervised deep learning, we aim to develop a fast, deformable registration model to substantially reduce DSA misregistration in craniocervical angiography without compromising spatial resolution or introducing new artifacts.
Front Vet Sci
August 2025
Pathobiology and Population Science, Royal Veterinary College, Hatfield, United Kingdom.
Diffuse large B-cell lymphoma is the most common type of non-Hodgkin lymphoma (NHL) in humans, accounting for about 30-40% of NHL cases worldwide. Canine diffuse large B-cell lymphoma (cDLBCL) is the most common lymphoma subtype in dogs and demonstrates an aggressive biologic behaviour. For tissue biopsies, current confirmatory diagnostic approaches for enlarged lymph nodes rely on expert histopathological assessment, which is time-consuming and requires specialist expertise.
View Article and Find Full Text PDFPatterns (N Y)
July 2025
University of Washington, Department of Astronomy, Seattle, WA, USA.
Machine learning and artificial intelligence promise to accelerate research and understanding across many scientific disciplines. Harnessing the power of these techniques requires aggregating scientific data. In tandem, the importance of open data for reproducibility and scientific transparency is gaining recognition, and data are increasingly available through digital repositories.
View Article and Find Full Text PDFNEJM AI
September 2025
Department of Bioengineering, Stanford University, Stanford, CA.
Background: Assessing human movement is essential for diagnosing and monitoring movement-related conditions like neuromuscular disorders. Timed function tests (TFTs) are among the most widespread types of assessments due to their speed and simplicity, but they cannot capture disease-specific movement patterns. Conversely, biomechanical analysis can produce sensitive disease-specific biomarkers, but it is traditionally confined to laboratory settings.
View Article and Find Full Text PDF