Shaping the Future of the Neurotransmitter Sensor: Tailored CdS Nanostructures for State-of-the-Art Self-Powered Photoelectrochemical Devices.

Semiconductor-based photoelectrochemical (PEC) test protocols offer a viable solution for developing efficient individual health monitoring by converting light and chemical energy into electrical signals. However, slow reaction kinetics and electron-hole complexation at the interface limit their practical application. Here, we reported a triple-engineered CdS nanohierarchical structures (CdS NHs) modification scheme including morphology, defective states, and heterogeneous structure to achieve precise monitoring of the neurotransmitter dopamine (DA) in plasma and noninvasive body fluids. By precisely manipulating the Cd-S precursor, we achieved precise control over ternary CdS NHs and obtained well-defined layered self-assembled CdS NHs through a surface carbon treatment. The integration of defect states and the thin carbon layer effectively established carrier directional transfer pathways, thereby enhancing interface reaction sites and improving the conversion efficiency. The CdS NHs microelectrode fabricated demonstrated a remarkable negative response toward DA, thereby enabling the development of a miniature self-powered PEC device for precise quantification in human saliva. Additionally, the utilization of density functional theory calculations elucidated the structural characteristics of DA and the defect state of CdS, thus establishing crucial theoretical groundwork for optimizing the polymerization process of DA. The present study offers a potential engineering approach for developing high energy conversion efficiency PEC semiconductors as well as proposing a novel concept for designing sensitive testing strategies.

Programmable Molecular Signal Transmission Architecture and Reactant Regeneration Strategy Driven by EXO λ for DNA Circuits.

The characteristics of DNA hybridization enable molecular computing through strand displacement reactions, facilitating the construction of complex DNA circuits, which is an important way to realize information interaction and processing at a molecular level. However, signal attenuation in the cascade and shunt process hinders the reliability of the calculation results and further expansion of the DNA circuit scale. Here, we demonstrate a novel programmable exonuclease-assisted signal transmission architecture, where DNA strand with toehold employed to inhibit the hydrolysis process of EXO λ is applied in DNA circuits. We construct a series circuit with variable resistance and a parallel circuit with constant current source, ensuring excellent orthogonal properties between input and output sequences while maintaining low leakage (<5%) during the reaction. Additionally, a simple and flexible exonuclease-driven reactant regeneration (EDRR) strategy is proposed and applied to construct parallel circuits with constant voltage sources that could amplify the output signal without extra DNA fuel strands or energy. Furthermore, we demonstrate the effectiveness of the EDRR strategy in reducing signal attenuation during cascade and shunt processes by constructing a four-node DNA circuit. These findings offer a new approach to enhance the reliability of molecular computing systems and expand the scale of DNA circuits in the future.

Feature-correlation-aware history-preserving-sparse-coding framework for automatic vertebra recognition.

Automatic vertebra recognition from magnetic resonance imaging (MRI) is of significance in disease diagnosis and surgical treatment of spinal patients. Although modern methods have achieved remarkable progress, vertebra recognition still faces two challenges in practice: (1) Vertebral appearance challenge: The vertebral repetitive nature causes similar appearance among different vertebrae, while pathological variation causes different appearance among the same vertebrae; (2) Field of view (FOV) challenge: The FOVs of the input MRI images are unpredictable, which exacerbates the appearance challenge because there may be no specific-appearing vertebrae to assist recognition. In this paper, we propose a Feature-cOrrelation-aware history-pReserving-sparse-Coding framEwork (FORCE) to extract highly discriminative features and alleviate these challenges. FORCE is a recognition framework with two elaborated modules: (1) A feature similarity regularization (FSR) module to constrain the features of the vertebrae with the same label (but potentially with different appearances) to be closer in the latent feature space in an Eigenmap-based regularization manner. (2) A cumulative sparse representation (CSR) module to achieve feed-forward sparse coding while preventing historical features from being erased, which leverages both the intrinsic advantages of sparse codes and the historical features for obtaining more discriminative sparse codes encoding each vertebra. These two modules are embedded into the vertebra recognition framework in a plug-and-play manner to improve feature discrimination. FORCE is trained and evaluated on a challenging dataset containing 600 MRI images. The evaluation results show that FORCE achieves high performance in vertebra recognition and outperforms other state-of-the-art methods.

Colorimetric and visual determination of uric acid based on decolorization of manganese dioxide nanosheet dispersions.

Serum levels of uric acid (UA) play an important role in the prevention of diseases. Developing a rapid and accurate way to detect UA is still a meaningful task. Hence, positively charged manganese dioxide nanosheets (MnO2NSs) with an average latter size of 100 nm and an ultra-thin thickness of below 1 nm have been prepared. They can be well dispersed in water and form stable yellow-brown solutions. The MnO2NSs can be decomposed by UA via redox reaction, leading to a decline of a characteristic absorption peak (374 nm) and a color fading of MnO2NSs solution. On this basis, an enzyme-free colorimetric sensing system for the detection of UA has been developed. The sensing system shows many advantages, including a wide linear range of 0.10-50.0 µmol/L, a limit of quantitation (LOQ) of 0.10 µmol/L, a low limit of detection (LOD) of 0.047 µmol/L (3σ/m), and rapid response without need of strict time control. Moreover, a simple and convenient visual sensor for UA detection has also been developed by adding an appropriate amount of phthalocyanine to provide a blue background color, which helps to increase visual discrimination. Finally, the strategy has been successfully applied to detect UA in human serum and urine samples.

Construction of DNA-based molecular circuits using normally open and normally closed switches driven by lambda exonuclease.

Building synthetic molecular circuits is an important way to realize ion detection, information processing, and molecular computing. However, it is still challenging to implement the NOT logic controlled by a single molecule input in synthetic molecular circuits wherein the presence or absence of the molecule represents the ON or OFF state of the input. Here, based on lambda exonuclease (λ exo), for the first time, we propose the normally open (NO) and normally closed (NC) switching strategy with a unified signal transmission mechanism to build molecular circuits. Specifically, the opposite logic can be output with or without a single signal, and the state of the switch can be adjusted by the addition order and time interval of the upstream signal and switch signal, which endows the switch with time-responsive characteristics. In addition, a time-delay relay with the function of delayed disconnection is developed to realize quantitative control of outputs, which has the potential to meet the automation control need of the system. Finally, digital square and square root circuits are constructed by cascading the NO and NC switches, which demonstrates the versatility of switches. Our design can be extended to time logic and complex digital computing circuits for use in information processing and nanomachines.

Multifunctional Exo III-assisted scalability strategy for constructing DNA molecular logic circuits.

The construction of logic circuits is critical to DNA computing. Simple and effective scalability methods have been the focus of attention in various fields related to constructing logic circuits. We propose a double-stranded separation (DSS) strategy to facilitate the construction of complex circuits. The strategy combines toehold-mediated strand displacement with exonuclease III (Exo III), which is a multifunctional nuclease. Exo III can quickly recognize an apurinic/apyrimidinic (AP) site. DNA oligos with an AP site can generate an output signal by the strand displacement reaction. However, in contrast to traditional strand displacement reactions, the double-stranded waste from the strand displacement can be further hydrolysed by the endonuclease function of Exo III, thus generating an additional output signal. The DSS strategy allows for the effective scalability of molecular logic circuits, enabling multiple logic computing capabilities simultaneously. In addition, we succeeded in constructing a logic circuit with dual logic functions that provides foundations for more complex circuits in the future and has a broad scope for development in logic computing, biosensing, and nanomachines.

Review of Deep Learning Approaches for the Segmentation of Multiple Sclerosis Lesions on Brain MRI.

In recent years, there have been multiple works of literature reviewing methods for automatically segmenting multiple sclerosis (MS) lesions. However, there is no literature systematically and individually review deep learning-based MS lesion segmentation methods. Although the previous review also included methods based on deep learning, there are some methods based on deep learning that they did not review. In addition, their review of deep learning methods did not go deep into the specific categories of Convolutional Neural Network (CNN). They only reviewed these methods in a generalized form, such as supervision strategy, input data handling strategy, etc. This paper presents a systematic review of the literature in automated multiple sclerosis lesion segmentation based on deep learning. Algorithms based on deep learning reviewed are classified into two categories through their CNN style, and their strengths and weaknesses will also be given through our investigation and analysis. We give a quantitative comparison of the methods reviewed through two metrics: Dice Similarity Coefficient (DSC) and Positive Predictive Value (PPV). Finally, the future direction of the application of deep learning in MS lesion segmentation will be discussed.

Postauricular injection glucocorticoid in the treatment of sudden hearing loss: A protocol for systematic review and meta-analysis.

BACKGROUND: Sudden hearing loss is an emergency health problem in the Department of Otolaryngology that must be treated in a timely manner, or may cause lifelong regrets. The application of postauricular injection of glucocorticoid is a popular treatment to recover patients hearing level in recent years. However, the effectiveness and safety of postauricular injection of glucocorticoid needs to be assessed systematically. METHODS AND ANALYSIS: The purpose of the study is to undertake a systematic review and meta-analysis on the effectiveness and safety of postauricular injection of glucocorticoid to treat patient diagnosed with sudden hearing loss. We will search the following databases from the date of publication to July 1, 2020: PubMed, EMBASE, Web of Science, the Cochrane Library, CNKI, Wanfang databases, the Chinese Biomedical Literature Database (CBM), the Chinese Science and Technology Periodical Database (VIP) and the Chinese Cochrane Centre's Clinical Trial Registry Platform. Observational studies regarding the association between postauricular injection of glucocorticoid and sudden hearing loss were written in English and Chinese were included. RevManV.5.3 software will be used for meta-analysis. According to the heterogeneity of the research results, fixed effects model, random effects model, subgroup analysis, sensitivity analysis, and others will be used. Ethics approval was not required for this protocol. The findings will be disseminated through journal articles and conference presentations. RESULTS: Objectively, evaluate the efficacy and safety of postauricular injection of glucocorticoid for sudden hearing loss. CONCLUSION: To provide evidence-based medicine for glucocorticoid treatment methods in patients with sudden hearing loss. OSF REGISTRATION NUMBER: DOI 10.17605/OSF.IO/N5RV3.