DNA is a type of promising material for the construction of sensors owing to its sequence programmability to control the formation of certain structures. MicroRNA (miRNA) can be applied as promising ...biomarkers for the diagnosis of a range of diseases. Herein, a novel fluorescent sensing strategy for miRNA is proposed combining duplex-specific nuclease (DSN)-mediated amplification and dumbbell DNA structural switch. Gold nanoparticles (AuNPs) are employed, which provide a 3D reaction interface. They also act as effective fluorescence quenchers. The proposed sensor exhibits high sensitivity (sub-femtomolar level) with a wide dynamic range. In addition, excellent selectivity to distinguish homology sequences is achieved. It also performs satisfactorily in biological samples. Overall, this fluorescent sensor provides a powerful tool for the analysis of miRNA levels and can be applied for related biological studies and clinical diagnosis.
Leukemia is a severe blood disorder that poses a threat to the life and well-being of patients. Accurate diagnosis of leukemia typing is crucial for treatment and prognosis. However, manual diagnosis ...requires significant resources and is subject to observer variation. Computer-aided diagnostic (CAD) technologies have emerged as a promising approach to complement manual diagnosis and alleviate the workload of specialized physicians. With the recent advances in deep learning, the performance of CAD has been substantially enhanced. In this paper, we propose a novel classification model, AMLNet, for acute myeloid leukemia (AML) cells. AMLNet is a lightweight model based on the ShuffleNet V2 architecture. We first validate the performance of the convolutional neural network and Transformer architecture models on the largest AML cell dataset to date. Then, we enhance the data augmentation approach and model structure of the ShuffleNet V2 model to develop AMLNet. The AUC, sensitivity, and accuracy of AMLNet are up to 0.9935%, 63.91%, and 96.43%, respectively, which achieves the optimal classification performance. Finally, the classification performance of AMLNet is verified on other public datasets, which is superior to other methods. AMLNet presents a promising solution for practical diagnosis scenarios since the end devices of assisted diagnosis often have limited computational power. The proposed AMLNet model effectively improves the classification performance of ShuffleNet V2 while offering the advantages of high performance and low computational consumption. Overall, our study demonstrates the potential of lightweight deep learning models in improving the accuracy of leukemia typing and reducing the workload of specialized physicians.
With the development of technologies based on gold nanoparticles (AuNPs), bare AuNPs cannot meet the increasing requirements of biomedical applications. Modifications with different functional ...ligands are usually needed. DNA is not only the main genetic material, but also a good biological material, which has excellent biocompatibility, facile design, and accurate identification. DNA is a perfect ligand candidate for AuNPs, which can make up for the shortcoming of bare AuNPs. DNA-modified AuNPs (DNA-AuNPs) have exciting features and bright prospects in many fields, which have been intensively investigated in the past decade. In this review, we summarize the various approaches for the immobilization of DNA strands on the surface of AuNPs. Representative studies for biomedical applications based on DNA-AuNPs are also discussed. Finally, we present the challenges and future directions.
Indium tin oxide (ITO) is a functional material with great transparency, machinability, electrical conductivity and thermo–sensitivity. Based on its excellent thermoelectric performance, we designed ...and fabricated a multilayer transparent microfluidic chip with multiple sets of on–chip heating, local temperature measurement and positive on–chip cooling function units. Temperature control plays a significant role in microfluidic approaches, especially in the devices that are designed for bioengineering, chemical synthesis and disease detection. The transparency of the chip contributes to achieve the real–time observation of fluid flow and optical detection. The chip consists of a temperature control layer made with an etched ITO deposited glass, a PDMS (polydimethylsiloxane) fluid layer, a PDMS cooling and flow control layer. The performances of the ITO on–chip microheaters, ITO on–chip temperature sensors and two coolants were tested and analyzed in different working conditions. The positive on–chip heating and cooling were proved to be area-specific under a large temperature–regulating range. This PDMS–ITO–glass based chip could be applied to both temporal and spatial stable temperature–regulating principles for various purposes.
In this work, a novel strategy to fabricate a highly sensitive and selective biosensor for the detection of Ag(+) is proposed. Two DNA probes are designed and modified on a gold electrode surface by ...gold-sulfur chemistry and hybridization. In the presence of Ag(+), cytosine-Ag(+)-cytosine composite forms and facilitates the ligation event on the electrode surface, which can block the release of electrochemical signals labeled on one of the two DNA probes during denaturation process. Ag(+) can be sensitively detected with the detection limit of 0.1 nM, which is much lower than the toxicity level defined by U.S. Environmental Protection Agency. This biosensor can easily distinguish Ag(+) from other interfering ions and the performances in real water samples are also satisfactory. Moreover, the two DNA probes are designed to contain the recognition sequences of a nicking endonuclease, and the ligated DNA can thus be cleaved at the original site. Therefore, the electrode can be regenerated, which allows the biosensor to be reused for additional tests.
Uniform and stable droplet generation is critical for accurate and efficient digital nucleic acid analysis (dNAA). In this study, an integrated microfluidic step emulsification device with wide-range ...droplet generation capability, small device dimensions, convenient fabrication strategy, low contamination and high robustness was developed. A tree-shaped droplet generation nozzle distribution design was proposed to increase the uniformity of droplet generation by equating flow rates, and the flow field in the design was numerically simulated. Theoretical analysis and comparative experiments on droplet size were performed regarding the influences of nozzle dimensions and surface properties. With incubation and hydrophobic reagent treatment, droplets as small as 73.1 μm were generated with multiplex nozzles of 18 μm (h) × 80 μm (w). The droplets were then collected into a standard PCR tube and an on-chip monolayer droplet collection chamber, without manual transfer and sample contamination. The oil-to-sample volume ratio in the PCR tube was recorded during collection. In the end, the droplets generated and collected using the microfluidic device proved to be stable and uniform for nucleic acid amplification and detection. This study provides reliable characteristic information for the design and fabrication of a micro-droplet generation device, and represents a promising approach for the realization of a three-in-one dNAA device under a step emulsification method.
The wire rope is a key part of the surgical instrument in robot-assisted minimally invasive surgery, which plays an important role in transmitting the motions of the doctor. During the operation, the ...failure of wire rope may cause some adverse medical events. To make clear the performance change law and failure mechanism of wire rope, this study involved accelerated life testing, tensile test and microscopic inspection of wire rope. Results indicate that wire rope will experience wear, fatigue and plastic deformation during the operation, which will lead to the deterioration of wire rope performance, and finally the failure occurs under the joint action of them. Results also indicate that the fatigue life of wire rope decreases with the increase in working stress. The results of this study can provide guidance for the use and maintenance of the wire rope in surgical instruments.
Sign language is the main means of communication for deaf and mute individuals, special populations, and special situations. However, the current low popularity of sign language has also hindered the ...deep contact between deaf and mute people and the current society. In order to further promote the application level and service ability of sign language, establish a convenient communication bridge for special populations and scenes, and meet the application requirements of portability, real-time, reliability, and stability, this paper designs a gesture recognition system based on multiple sensors. This system combines transfer learning and has functions such as Bluetooth communication, data acquisition and processing, gesture recognition, and result display. The transfer experiment results showed that the accuracy of gesture recognition reached 94.07% and 92.53%, respectively, which were 9.41% and 11.73% higher than before the transfer. Moreover, the accuracy and stability of gesture recognition were improved through transfer learning, and the universality and robustness of the model were improved. Through the testing and gesture recognition experiments of the gesture recognition system, it has been shown that the recognition system can recognize gesture movements of different groups of people, with good recognition rate and stability.
Organoids are 3D cultures that are commonly used for biological and medical research in vitro due to their functional and structural similarity to source organs. The development of organoids can be ...assessed by morphological tests. However, manual analysis of organoid morphology requires intensive labor from professionals and is prone to observer discrepancies.
Computer-assisted methods alleviate the pressure of manual labor, especially with the development of deep learning, the performance of morphological detection has been further improved. The aim of this paper is to automate the assessment of organoid morphology using deep learning techniques to reduce the labor pressure of professionals.
Based on the lightweight model YOLOX, a lightweight intestinal organoid detection model named Deep-Orga is proposed. First, the performance of the Deep-Orga model is compared with other classical models on the intestinal organoids dataset. Then, ablation experiments are used to validate the improvement of the model detection performance by the improved module. Finally, Deep-Orga is compared with other methods.
Deep-Orga achieves optimal organoid detection with a partial increase in computational effort. Using Deep-Orga to replace the manual analysis process provides a new automated method for organoid morphology evaluation.
Deep-Orga proposed in this paper is able to accurately assess organoid development, effectively relieving the labor pressure of professionals and avoiding the subjectivity of assessment. This paper demonstrates the potential application of deep learning in the field of organoid morphology analysis.
•Lightweight modeling can be used for intestinal organoid detection.•RepVGG introduces reparameterization to enhance inference speed.•BFP module makes the layers of features more distinguishable.•Balanced L1 Loss balances classification and localization loss.•The proposed Deep-Orga can be used for the evaluation of organoid culture status.
Digital polymerase chain reaction (dPCR) is an approach for absolute nucleic acid quantification with high sensitivity. Although several successful commercial dPCR devices have been developed to ...date, further miniaturizing device dimensions, decreasing cross-contamination, and improving automation level are still research highlights. In this study, we developed a fully contamination-free dPCR detection chip with fluorescence flow cytometry and micro droplet approach. A bifunctional cross-structure (BFCS) was designed to realize monodisperse sample droplet generation in forward flow and droplet detection in backward flow with simple pneumatic control and fixed chip position. In order to improve droplet detection efficiency and accuracy, droplets morphology and sequence pattern during microfluidic droplet generation and backward flow droplet detection at the same cross-structure were observed and analyzed under different pneumatic pressures. In addition, during backward flow droplet detection, an optimized declination angle of the chip was applied to increase droplet reflux rates. For the validation of PCR performance, temperature changing processes during PCR cycles were achieved by heating the monodispersed droplet array with a customized PCR amplification device. The fluorescence signal of each droplet right after passing the cross-structure was excitated and detected. The absolute quantification ability of our integrated dPCR microfluidic chip utilizing flow fluorescence cytometry was tested and verified with Influenza A virus gene (from 7.5 copies/μL to 30000 copies/μL). Thus, our platform provides a novel and integrated approach for ddPCR analysis.
Fig.1. Schematics of ddPCR NA detection with bifunctional microfluidic cross-structure. Display omitted
•A bifunctional cross-structure is firstly proposed to realize both droplet generation and detection.•Droplet morphology and distance are considered for flow fluorescence detection.•Influenza A is quantified by an integrated microfluidic chip with proposed structure.•The proposed approach can be applied in other droplet-based quantification scenarios.
PDF
