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In situ monitoring of correlated DNA repair enzyme activities in living cells is crucial for clinical and biomedical research. Here, we introduce a versatile, programmable dual-mode logic gold nanoflares strategy for OR/AND gate logic imaging the activity of apurinic/apyrimidinic endonuclease 1 (APE1) and flap endonuclease 1 (FEN1) within cells. The logic gold nanoflares were designed via conjugating enzyme-activatable sites modified branched double-stranded DNA structures to gold nanoparticles. These meticulously engineered nanoflares specifically respond to APE1 and FEN1 in living cells through logic biocomputing, emitting a fluorescent signal that allows for the sensitive monitor of APE1 and FEN1 activities. In vitro experiments demonstrate that the nanoflares are highly biocompatible and can make effectively and sensitively judgments on the two enzyme targets across various cancer cell lines. This OR/AND dual-mode logic gold nanoflare strategy offers a straightforward tool for the comprehensive analysis of multiple DNA repair enzymes, presenting promising applications in disease diagnosis, drug efficacy evaluation, and programmable therapeutics.
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http://dx.doi.org/10.1016/j.bios.2025.117501 | DOI Listing |
Anal Chem
September 2025
College of Natural Resources and Environment, South China Agricultural University, Guangzhou 510642, China.
A series of molecular logic gates with multiple biocomputing capabilities have been successfully fabricated by using four antibiotic residues [tetracycline (TET), chloramphenicol (CHL), kanamycin (KAN), and streptomycin (STR)] as inputs. The lateral flow strip biosensor was utilized to realize the visual and portable sensing of logic events. Four basic logic gates (OR, AND, XOR, and INHIBIT) and three cascade logic circuits (OR-INHIBIT-AND, 3AND-OR, and XOR-INHIBIT-OR-AND) were constructed.
View Article and Find Full Text PDFBiology (Basel)
July 2025
Department of Integrated Traditional Chinese and Western Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China.
The zebrafish () has emerged as a powerful model organism for investigating the mechanisms of post-traumatic stress disorder (PTSD), offering unique advantages in translational relevance, genetic trackability, and cost-effectiveness. As a logical continuation of our recent systematic review, this manuscript critically examines the spectrum of experimental strategies used to model PTSD in zebrafish, with a focus on the comparative efficacy and validity of acute, chronic, and complex stress paradigms. Among these, 14-15-day chronic unpredictable stress (CUS/UCS) protocols are identified as the gold standard, reliably inducing core PTSD-like phenotypes-such as anxiety-like behavior, cortisol dysregulation, and neuroinflammatory gene activation.
View Article and Find Full Text PDFAnalyst
August 2025
Department of Thoracic Surgical Oncology, Shanghai Lung Cancer Center, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Exosomes are critical biomarkers for early cancer diagnosis and prognosis due to their rich biological information. Nevertheless, analyzing exosomal biomarkers comprehensively remains challenging. Surface-enhanced Raman scattering (SERS) has been employed to detect exosomes due to its high sensitivity and reliable fingerprint.
View Article and Find Full Text PDFSleep
August 2025
Seoul National University Graduate School, Seoul, Republic of Korea, Graduate School of Data Science.
Study Objectives: Polysomnography (PSG) is the current gold standard for sleep staging but requires laboratory equipment, multiple sensors, and labor-intensive manual scoring. We developed DistillSleep, a single-channel electroencephalogram (EEG) framework that delivers accurate, real-time, and interpretable sleep staging on resource-constrained devices.
Methods: DistillSleep consists of (1) a high-capacity teacher model and (2) a 109 k-parameter student model designed for edge deployment.
MethodsX
December 2025
Assistant Professor, Sreenivasa Institute of Technology and Management Studies, India.
Accurate forecasting of gold prices is crucial for financial decision-making in various sectors, including investment and mining. This study introduces a multi-objective optimization framework that utilizes the Pareto alpha-cut technique to evaluate and enhance forecasting models for gold prices. We employed three distinct models: the Autoregressive Distributed Lag (ARDL) model, a stochastic model, and the Autoregressive Integrated Moving Average (ARIMA) model, to capture the underlying dynamics of gold price fluctuations influenced by macroeconomic factors.
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