High fidelity detection of miRNAs from complex physiological samples through electrochemical nanosensors empowered by proximity catalysis and magnetic separation.

Electrochemical detection of miRNA biomarkers in complex physiological samples holds great promise for accurate evaluation of tumor burden in the perioperative period, yet limited by reproducibility and bias issues. Here, nanosensors installed with hybrid probes that responsively release catalytic DNAzymes (G-quadruplexes/hemin) were developed to solve the fidelity challenge in an immobilization-free detection. miRNA targets triggered toehold-mediated strand displacement reactions on the sensor surface and resulted in amplified shedding of DNAzymes. Subsequently, the interference background was removed by Fe3O4 core-facilitated magnetic separation. Binding aptamers of the electrochemical reporter (dopamine) were tethered closely to the catalytic units for boosting H2O2-mediated oxidation through proximity catalysis. The one-to-many conversion by dual amplification from biological-chemical catalysis facilitated sufficient homogeneous sensing signals on electrodes. Thereby, the nanosensor exhibited a low detection limit (2.08 fM), and high reproducibility (relative standard deviation of 1.99%). Most importantly, smaller variations (RSD of 0.51-1.04%) of quantified miRNAs were observed for detection from cell lysates, multiplexed detection from unprocessed serum, and successful discrimination of small upregulations in lysates of tumor tissue samples. The nanosensor showed superior diagnostic performance with an area under curve (AUC) of 0.97 and 94% accuracy in classifying breast cancer patients and healthy donors. These findings demonstrated the synergy of signal amplification and interference removal in achieving high-fidelity miRNA detection for practical clinical applications.

Constraint Coupling of Redox Cascade and Electron Transfer Synchronization on Electrode-Nanosensor Interface for Repeatable Detection of Tumor Biomarkers.

Quantitative analysis of up-regulated biomarkers in pathological tissues is helpful to tumor surgery yet the loss of biomarker extraction and time-consuming operation limited the accurate and quick judgement in preoperative or intraoperative diagnosis. Herein, an immobilization-free electrochemical sensing platform is developed by constraint coupling of electron transfer cascade on electrode-nanosensor interface. Specifically, electrochemical indicator (Ri)-labeled single-stranded DNA on electroactive nanodonor (polydopamine, PDA) can be responsively detached by formation of DNA complex through the recognition and binding with targets. By applying the oxidation potential of Ri, nanosensor collisions on electrode surface trigger a cascade redox cycling of PDA and Ri through synchronous electron transfer, which boost the amplification of current signal output. The developed nanosensor exhibit excellent linear response toward up-regulated biomarkers (miRNA-21, ATP, and VEGF) with low detection limits (32 fM, 386 pM, and 2.8 pM). Moreover, background influence from physiological interferent is greatly reduced by restricted electron transfer coupling on electrode. The practical applicability is illustrated in sensitive and highly repeatable profiling of miRNA-21 in lysate of tumor cells and tumor tissue, beneficial for more reliable diagnosis. This electrochemical platform by employing electron transfer cascades at heterogeneous interfaces offers a route to anti-interference detection of biomarkers in tumor tissues.

Feasibility Study of Combining Hyperspectral Imaging with Deep Learning for Chestnut-Quality Detection.

The rapid detection of chestnut quality is a critical aspect of chestnut processing. However, traditional imaging methods pose a challenge for chestnut-quality detection due to the absence of visible epidermis symptoms. This study aims to develop a quick and efficient detection method using hyperspectral imaging (HSI, 935-1720 nm) and deep learning modeling for qualitative and quantitative identification of chestnut quality. Firstly, we used principal component analysis (PCA) to visualize the qualitative analysis of chestnut quality, followed by the application of three pre-processing methods to the spectra. To compare the accuracy of different models for chestnut-quality detection, traditional machine learning models and deep learning models were constructed. Results showed that deep learning models were more accurate, with FD-LSTM achieving the highest accuracy of 99.72%. Moreover, the study identified important wavelengths for chestnut-quality detection at around 1000, 1400 and 1600 nm, to improve the efficiency of the model. The FD-UVE-CNN model achieved the highest accuracy of 97.33% after incorporating the important wavelength identification process. By using the important wavelengths as input for the deep learning network model, recognition time decreased on average by 39 s. After a comprehensive analysis, FD-UVE-CNN was deter-mined to be the most effective model for chestnut-quality detection. This study suggests that deep learning combined with HSI has potential for chestnut-quality detection, and the results are encouraging.

Flower-like Nanozyme with Highly Porous Carbon Matrix Induces Robust Oxidative Storm against Drug-Resistant Cancer.

Reactive oxygen species (ROS) generators are sparking breakthroughs in sensitization and treatment of therapy-resistant tumors, yet the efficacy is drastically compromised by limited substrate concentrations, short lifetimes of free radicals, and restricted oxidative damage. Herein, a flower-like nanozyme with highly permeable leaflets accommodating catalytic metal sites was developed to address the challenges by boosting substrate and product accessibility. In the formation of a zeolite imidazole framework, cobalt ions promoted catalytic polymerization and deposition of polydopamine. The polymers acted as a stiffener for preventing framework collapse and maneuvering pore reopening during carbonization. The cobalt single-atom/cluster sites in the highly porous matrix generated peroxidase/oxidase-like activities with high catalytic efficiency (Kcat/Km) up to 6 orders of magnitude greater than that of conventional nano-/biozymes. Thereby, a robust ROS storm induced by selective catalysis led to rapid accumulation of oxidative damage and failure of antioxidant and antiapoptotic defense synchronization in drug-resistant cancer cells. By synergy of a redox homeostasis disrupter co-delivered, a significantly high antitumor efficiency was realized in vivo. This work offers a route to kinetically favorable ROS generators for advancing the treatment of therapy-resistant tumors.

Dual factor coactivatable fluorescent nanosensor with boosted cytoplasmic biomarker accessibility toward selective tumor imaging.

Fluorescent nanosensor-based tumor imaging holds great promise in cancer diagnosis and treatment assistance, yet the signal contrast is heavily hampered by the unspecific/unwanted activation at microscopic regions with a highly restricted local abundance of biomarkers. Herein, we developed an activation boosting strategy by the integration and manipulation of dual-factor coactivation of sensing and lysosome escape facilitated the rise of cytosolic biomarker accessibility. By employing hybrid DNA probes on gold nanoquenchers, ATP sensing initiated conformation switch of the corresponding aptamer units triggered the exposure of a hidden toehold in a loop structure. Sequentially, miRNA-21 sensing was triggered by toehold-mediated strand displacement and detachment of the binding complexes. The application of lysosomotropic agent chloroquine at optimized time interval facilitated the release of nanosensors into the cytosol and a ∼10.5-fold increment of intracellular fluorescence in vitro, while coactivation improved the cancer-to-normal cell signal ratio by ∼5.9 times. The synergy effects led to a high tumor-to-normal tissue ratio value of ∼7.9 in the in vivo imaging results. This strategy establishes a new paradigm of fluorescent nanosensors for selective and specific tumor imaging.

A multiallelic indel in the promoter region of the Cyclin-dependent kinase inhibitor 3 gene is significantly associated with body weight and carcass traits in chickens.

Many studies have reported that cyclin-dependent kinase inhibitor 3 (CDKN3) is involved in the cell cycle. However, the function of CDKN3 has not been well elucidated in organisms. In this study, a multiallelic indel caused by a 19-bp fragment and a 2 × 19 bp fragment was shown for the first time to be inserted into the promoter of the CDKN3 gene in 1994 chickens from 9 different breeds. In addition, 6 genotypes (C5C5, C4C4, C3C3, C4C5, C3C4, and C3C5) were observed (C3C3, C4C4, C5C5 have 3 × 19 bp, 4 × 19 bp, and 5 × 19 bp, respectively). Among these genotypes, the C4C4 genotype was the most dominant genotype in 9 breeds. The results of χ2 analysis of CDKN3 gene in different breeds showed that there were significant differences in the distribution of genotypes among different cultivars (P < 0.01). In addition, association study with F2 chicken resource population which produced by Anka and Gushi chickens showed that the C3C4 genotypes had the greatest semi-evisceration weight (SEW, 1163.94 ± 46.84), evisceration weight (EW, 964.15 ± 41.16), head weight (HW, 45.55 ± 1.43), claw weight (CW, 63.42±2.86), wing weight (WW, 129.15±5.48), liver weight (LW, 29.96±1.27), carcass weight (cW, 1286.96±49.53), weight at 10 (1190.68±45.68) and 12 (1430.65±54.45) wk, followed by C3C3, C4C4, C5C5, C4C5, whereas C3C5 genotypes having the lowest SEW (989.21±47.71), EW (841.38±40.55), HW (41.03±1.46), CW (54.36±2.81), WW (116.31±5.39), LW (27.31±1.25), cW (1093.29±49.99), weight at 10 (1036.10±44.99) and 12 (1246.28±53.59) wk. Expression levels of CDKN3 in breast muscle of chickens with C4C4 (0.72±0.02), C3C3 (0.95±0.41), and C4C5 (0.74±0.13) genotypes were significantly lower than those with C5C5 (1.80±0.01) and C3C5 (2.14±0.17) genotypes (P < 0.05). In conclusion, we investigated the effect of a multiallelic indel in the CDKN3 gene on the economic traits of chickens, and this indel was significantly associated with growth and carcass traits in chickens. Collectively, our findings provide useful information about the repeat sequence indel in the promoter region of the CDKN3 gene as a potential molecular marker for chicken breeding.