A Simple and Robust Exponential Amplification Reaction (EXPAR)-Based Hairpin Template (exp-Hairpin) for Highly Specific, Sensitive, and Universal MicroRNA Detection.

Specific and sensitive detection of microRNAs continues to encounter significant challenges, especially in the development of rapid and efficient isothermal amplification strategies for point-of-care settings. The exponential amplification reaction (EXPAR) has garnered significant attention owing to its simplicity and rapid amplification of signals within a short period. However, a substantial loss of amplification efficiency, difficulty in distinguishing closely related homologous sequences, and adapting the designed templates to other targets seriously hamper the practical application of the EXPAR. In this work, a hairpin template tailored for the EXPAR system (exp-Hairpin) was constructed by adding identical trigger sequences and enzyme cleavage sites on two arms of the hairpin, achieving theoretically more than 2n amplification efficiency and minimal background amplification of EXPAR. Modulating the stability of the exp-Hairpin template by increasing the stem length, the specificity of detecting target miRNA in highly homologous sequences could be significantly improved. Using miRNA let-7a as a target model, the exp-Hairpin with 8 bp stem length for EXPAR amplification curves could effectively distinguish target let-7a and nontarget let-7b/7c/7f/7g/7i homologous sequences. This strategy enabled the sensitive and accurate analysis of let-7a in diluted human serum with satisfactory recoveries. By simply replacing the loop recognition sequence of exp-Hairpin, the specific detection of miR-200b was also achieved, demonstrating the universality of this strategy. The exp-Hairpin EXPAR accelerates simple and rapid molecular diagnostic applications for short nucleic acids.

MiRNA and mRNA-Controlled Double-Cascaded Amplifying Circuit Nanosensor for Accurate Discrimination of Breast Cancers in Living Cells, Animals, and Organoids.

Metastasis is the leading cause of death in patients with breast cancer. Detecting high-risk breast cancer, including micrometastasis, at an early stage is vital for customizing the right and efficient therapies. In this study, we propose an enzyme-free isothermal cascade amplification-based DNA logic circuit in situ biomineralization nanosensor, HDNAzyme@ZIF-8, for simultaneous imaging of multidimensional biomarkers in live cells. Taking miR-21 and Ki-67 mRNA as the dual detection targets achieved sensitive logic operations and molecular recognition through the cascade hybridization chain reaction and DNAzyme. The HDNAzyme@ZIF-8 nanosensor has the ability to accurately differentiate breast cancer cells and their subtypes by comparing their relative fluorescence intensities. Of note, our nanosensor can also achieve visualization within breast cancer organoids, faithfully recapitulating the functional characteristics of parental tumor. Overall, the combination of these techniques offers a universal strategy for detecting cancers with high sensitivity and holds vast potential in clinical cancer diagnosis.

Dephosphorylation Switch DNAzyme-RCA Circuit: A Robust Strategy for the Homogeneous and Reliable Detection of FTO Demethylase.

Fat mass and obesity-associated protein (FTO) plays a crucial role in regulating the dynamic modification of N6-methyladenosine (m6A) in eukaryotic mRNA. Sensitive detection of the FTO level and efficient evaluation of the FTO demethylase activity are of great importance to early cancer diagnosis and anticancer drug discovery, which are currently challenged by limited sensitivity/precision and low throughput. Herein, a robust strategy based on the dephosphorylation switch DNAzyme-rolling circle amplification (RCA) circuit, termed DSD-RCA, is developed for highly sensitive detection of FTO and inhibitor screening. Initially, the catalytic activity of DNAzyme is silenced by engineering with an m6A modification in its catalytic core. Only in the presence of target FTO can the methyl group on DNAzyme be eliminated, resulting in the activation of the catalytic activity of DNAzyme and thus cleaving the hairpin substrate to release numerous primers. Different from the conventional methods that use the downstream cleavage primer with the original 3'-hydroxyl end directly as the RCA primer with the problem of high background signal, which should be compensated by additional separation and wash steps in heterogeneous format, our DSD-RCA assay uses the upstream cleavage primer with a 2',3'-cyclic phosphate terminus at the 3'-end serving as an intrinsically blocked 3' end. Only after a dephosphorylation reaction mediated by T4 polynucleotide kinase can the upstream cleavage primers with a resultant 3'-hydroxyl end be extended by RCA. With the high signal-to-noise ratio and homogeneous property, the proposed platform can sensitively detect FTO with a limit of detection of 31.4 pM, and the relative standard deviations (RSDs %) ranging from 0.8 to 2.0% were much lower than the heterogeneous methods. The DSD-RCA method was applied for analyzing FTO in cytoplasmic lysates from different cell lines and tissues of breast cancer patients and further used for screening FTO inhibitors without the need for separation or cleaning, providing an opportunity for achieving high throughput and demonstrating the potential applications of this strategy in disease diagnostics, drug discovery, and biological applications.

Toehold Strand Displacement-Mediated Exponential HCR for Highly Sensitive and Specific Analysis of miRNA in Living Cells.

As an important disease biomarker, the development of sensitive detection strategies for miRNA, especially intracellular miRNA imaging strategies, is helpful for early diagnosis of diseases, pathological research, and drug development. Hybridization chain reaction (HCR) is widely used for miRNA imaging analysis because of its high specificity and lack of biological enzymes. However, the classic HCR reaction exhibits linear amplification with low efficiency, limiting its use for the rapid analysis of trace miRNA in living cells. To address this problem, we proposed a toehold-mediated exponential HCR (TEHCR) to achieve highly sensitive and efficient imaging of miRNA in living cells using ß-FeOOH nanoparticles as transfection vectors. The detection limit of TEHCR was as low as 92.7 fM, which was 8.8 × 103 times lower compared to traditional HCR, and it can effectively distinguish single-base mismatch with high specificity. The TEHCR can also effectively distinguish the different expression levels of miRNA in cancer cells and normal cells. Furthermore, TEHCR can be used to construct OR logic gates for dual miRNA analysis without the need for additional probes, demonstrating high flexibility. This method is expected to play an important role in clinical miRNA-related disease diagnosis and drug development as well as to promote the development of logic gates.

Dual-Signal Amplification Strategy Based on Catalytic Hairpin Assembly and APE1-Assisted Amplification for High-Contrast miRNA Imaging in Living Cells.

Early tumor diagnosis is crucial to successful treatment. Earlier studies have shown that microRNA is a biomarker for early tumor diagnosis. The development of highly sensitive miRNA detection methods, especially in living cells, plays an indispensable role for early diagnosis and treatment of tumor. Although the catalytic hairpin assembly (CHA)-based miRNA analysis strategy is commonly used for disease diagnosis, further application of CHA is hindered due to its low amplification efficiency and low tumor recognition contrast. To address these limitations, we propose a dual-signal amplification strategy based on CHA and APE1-assisted amplification, enabling highly sensitive and high-contrast miRNA imaging. The miR-221 was selected as a target model. This dual-signal amplification strategy has exhibited high amplification efficiency, which could analyze miRNA as low as 21 fM. This strategy also exhibited high specificity, which could distinguish target miRNA and nontarget with single-base differences. Moreover, this method showed significant potential for practical application, as it could successfully distinguish the expression difference of miR-221 in the plasma samples of normal people and patients. Most importantly, the expression level of the APE1 enzyme in tumor cells is higher than that in normal cells, allowing this strategy to sensitively and specifically image miRNA within tumor cells. This proposed method has also been successfully used to indicate fluctuations of intracellular miRNA and to distinguish miRNA expression between normal cells and cancer cells with high contrast. We anticipate that this method will provide fresh insights and can be a powerful tool for tumor diagnosis and treatment based on miRNA analysis.

Dual miRNA-Triggered DNA Walker Assisted by APE1 for Specific Recognition of Tumor Cells.

The identification of a specific tumor cell is crucial for the early diagnosis and treatment of cancer. However, it remains a challenge due to the limited sensitivity and accuracy, long response time, and low contrast of the recent approaches. In this study, we develop a dual miRNA-triggered DNA walker (DMTDW) assisted by APE1 for the specific recognition of tumor cells. miR-10b and miR-155 were selected as the research models. Without miR-10b and miR-155 presence, the DNA walker remains inactive as its walking strand of W is locked by L1 and L2. After miR-10b and miR-155 are input, the DNA walker is triggered as miR-10b and miR-155 bind to L1 and L2 of W-L1-L2, respectively, unlocking W. The DNA walker is driven by endogenous APE1 that is highly catalytic and is highly expressed in the cytoplasm of tumor cells but barely expressed in normal cells, ensuring high contrast and reaction efficiency for specific recognition of tumor cells. Dual miRNA input is required to trigger the DNA walker, making this strategy with a high accuracy. The DMTDW strategy exhibited high sensitivity for miRNA analysis with a detection limit of 44.05 pM. Living cell-imaging experiments confirmed that the DMTDW could effectively respond to the fluctuation of miRNA and specifically identified MDA-MB-231 cells from different cell lines. The proposed DMTDW is sensitive, rapid, and accurate for specific tumor cell recognition. We believe that the DMTDW strategy can become a powerful diagnostic tool for the specific recognition of tumor cells.

Aptasensor based on gold nanostructure-decorated 2D Cu metal-organic framework nanosheets for highly sensitive and specific electrochemical lipopolysaccharide detection.

Detecting lipopolysaccharide (LPS) using electrochemical methods is significant because of their exceptional sensitivity, simplicity, and user-friendliness. Two-dimensional metal-organic framework (2D-MOF) that merges the benefits of MOF and 2D nanostructure has exhibited remarkable performance in constructing electrochemical sensors, notably surpassing traditional 3D-MOFs. In this study, Cu[tetrakis(4-carboxylphenyl)porphyrin] (Cu-TCPP) and Cu(tetrahydroxyquinone) (Cu-THQ) 2D nanosheets were synthesized and applied on a glassy carbon electrode (GCE). The 2D-MOF nanosheets, which serve as supporting layers, exhibit improved electron transfer and electronic conductivity characteristics. Subsequently, the modified electrode was subjected to electrodeposition with Au nanostructures, resulting in the formation of Au/Cu-TCPP/GCE and Au/Cu-THQ/GCE. Notably, the Au/Cu-THQ/GCE demonstrated superior electrochemical activity because of the 2D morphology, redox ligand, dense Cu sites, and improved deposition of flower-like Au nanostructure based on Cu-THQ. The electron transfer specific surface area was increased by the improved deposition of Au nanostructures, which facilitates enriched binding of LPS aptamer and significantly improved the detection performance of Apt/Au/Cu-THQ/GCE electrochemical aptasensor. The limit of detection for LPS reached 0.15 fg/mL with a linear range of 1 fg/mL - 100 pg/mL. The proposed aptasensor demonstrated the ability to detect LPS in serum samples with satisfactory accuracy, indicating significant potential for clinical diagnosis.

On-Site-Activated Transmembrane Logic DNA Nanodevice Enables Highly Specific Imaging of Cancer Cells by Targeting Tumor-Related Nucleolin and Intracellular MicroRNA.

The ability to specifically image cancer cells is essential for cancer diagnosis; however, this ability is limited by the false positive associated with single-biomarker sensors and off-site activation of "always active" nucleic acid probes. Herein, we propose an on-site, activatable, transmembrane logic DNA (TLD) nanodevice that enables dual-biomarker sensing of tumor-related nucleolin and intracellular microRNA for highly specific cancer cell imaging. The TLD nanodevice is constructed by assembling a tetrahedral DNA nanostructure containing a linker (L)-blocker (B)-DNAzyme (D)-substrate (S) unit. AS-apt, a DNA strand containing an elongated segment and the AS1411 aptamer, is pre-anchored to nucleolin protein, which is specifically expressed on the membrane of cancer cells. Initially, the TLD nanodevice is firmly sealed by the blocker containing an AS-apt recognition zone, which prevents off-site activation. When the nanodevice encounters a target cancer cell, AS-apt (input 1) binds to the blocker and unlocks the sensing ability of the nanodevice for miR-21 (input 2). The TLD nanodevice achieves dual-biomarker sensing from the cell membrane to the cytoplasm, thereby ensuring cancer cell-specific imaging. This TLD nanodevice represents a promising strategy for the highly reliable analysis of intracellular biomarkers and a promising platform for cancer diagnosis and related biomedical applications.

Endogenous Enzyme-Powered DNA Nanomotor Operating in Living Cells for microRNA Imaging.

Accurate and specific imaging of low-abundance microRNA (miRNA) in living cells is extremely important for disease diagnosis and monitoring of disease progression. DNA nanomotors have shown great potential for imaging molecules of interest in living cells. However, inappropriate driving forces and complex design and operation procedures have hindered their further application. Here, we proposed an endogenous enzyme-powered DNA nanomotor (EEPDN), which employs an endogenous APE1 enzyme as fuel to execute repetitive cycles of motion for miRNA imaging in living cells. The whole motor system is constructed based on gold nanoparticles without other auxiliary additives. Due to the high efficiency of APE1, this EEPDN system has achieved highly sensitive miRNA imaging in living cells within 1.5 h. This strategy was also successfully used to differentiate the expression of specific miRNA between tumor cells and normal cells, demonstrating a high tumor cell selectivity. This strategy can promote the development of novel nanomotors and is expected to be a perfect intracellular molecular imaging tool for biological and medical applications.

DNAzyme-Amplified Cascade Catalytic Hairpin Assembly Nanosystem for Sensitive MicroRNA Imaging in Living Cells.

Sensitive imaging of microRNAs (miRNAs) in living cells is significant for accurate cancer clinical diagnosis and prognosis research studies, but it is challenged by inefficient intracellular delivery, instability of nucleic acid probes, and limited amplification efficiency. Herein, we engineered a DNAzyme-amplified cascade catalytic hairpin assembly (CHA)-based nanosystem (DCC) that overcomes these challenges and improves the imaging sensitivity. This enzyme-free amplification nanosystem is based on the sequential activation of DNAzyme amplification and CHA. MnO2 nanosheets were used as nanocarriers for the delivery of nucleic acid probes, which can resist the degradation by nucleases and supply Mn2+ for the DNAzyme reaction. After entering into living cells, the MnO2 nanosheets can be decomposed by intracellular glutathione (GSH) and release the loaded nucleic acid probes. In the presence of target miRNA, the locking strand (L) was hybridized with target miRNA, and the DNAzyme was released, which then cleaved the substrate hairpin (H1). This cleavage reaction resulted in the formation of a trigger sequence (TS) that can activate CHA and recover the fluorescence readout. Meanwhile, the DNAzyme was released from the cleaved H1 and bound to other H1 for new rounds of DNAzyme-based amplification. The TS was also released from CHA and involved in the new cycle of CHA. By this DCC nanosystem, low-abundance target miRNA can activate many DNAzyme and generate numerous TS for CHA, resulting in sensitive and selective analysis of miRNAs with a limit of detection of 5.4 pM, which is 18-fold lower than that of the traditional CHA system. This stable, sensitive, and selective nanosystem holds great potential for miRNA analysis, clinical diagnosis, and other related biomedical applications.

NanoSuit-Assisted Liquid-Cell Scanning Electron Microscopy Enables Dynamic Gold Nanoparticle Monitoring for the Aggregation and Transmembrane Processes in Living Cells.

Dynamic observation of the behaviors of nanomaterials in the cellular environment is of great significance in mechanistic investigations on nanomaterial-based diagnostics and therapeutics. Realizing label-free observations with nanometer resolution is necessary but still has major challenges. Herein, we propose a NanoSuit-assisted liquid-cell scanning electron microscopy (NanoSuit-LCSEM) method that enables imaging of the behaviors of nanoparticles in living cells. Taking A549 cells and gold nanoparticles (AuNPs) as a cell-nanoparticle interaction model, the NanoSuit-LCSEM method showed a significantly improved resolution to 10 nm, which is high enough to distinguish single and two adjacent 30 nm AuNPs in cells. The continuous observation time for living cells is extended to 30 min, and the trajectories and velocities for the transmembrane movement of AuNP aggregates are obtained. This study provides a new approach for dynamic observation of nanomaterials in intact living cells and will greatly benefit the interdisciplinary research of nanomaterials, nanomedicine, and nanotechnology.

A Knowledge-Graph-Based Multimodal Deep Learning Framework for Identifying Drug-Drug Interactions.

The identification of drug-drug interactions (DDIs) plays a crucial role in various areas of drug development. In this study, a deep learning framework (KGCN_NFM) is presented to recognize DDIs using coupling knowledge graph convolutional networks (KGCNs) with neural factorization machines (NFMs). A KGCN is used to learn the embedding representation containing high-order structural information and semantic information in the knowledge graph (KG). The embedding and the Morgan molecular fingerprint of drugs are then used as input of NFMs to predict DDIs. The performance and effectiveness of the current method have been evaluated and confirmed based on the two real-world datasets with different sizes, and the results demonstrate that KGCN_NFM outperforms the state-of-the-art algorithms. Moreover, the identified interactions between topotecan and dantron by KGCN_NFM were validated through MTT assays, apoptosis experiments, cell cycle analysis, and molecular docking. Our study shows that the combination therapy of the two drugs exerts a synergistic anticancer effect, which provides an effective treatment strategy against lung carcinoma. These results reveal that KGCN_NFM is a valuable tool for integrating heterogeneous information to identify potential DDIs.

Isolation of Structurally Heterogeneous TCR-CD3 Extracellular Vesicle Subpopulations Using Caliper Strategy.

Cells in different states can release diverse types of extracellular vesicles (EVs) that participate in intracellular communication or pathological processes. The identification and isolation of EV subpopulations are significant to explore their physiological functions and clinical value. In this study, structurally heterogeneous T-cell receptor (TCR)-CD3 EVs were proposed and verified for the first time using a caliper strategy. Two CD3-targeting aptamers were designed in the shape of a caliper with an optimized probe distance and were assembled on gold nanoparticles (Au-Caliper) to distinguish TCR-CD3 monomeric and dimeric EVs (m/dCD3 EVs) in skin-transplanted mouse plasma. Phenotyping and sequencing analysis revealed clear heterogeneity in the isolated m/dCD3 EVs, providing the potential for mCD3 EVs as a candidate biomarker of acute cellular rejection (ACR) and holding great prospects for distinguishing EV subpopulations based on protein oligomerization states.

Highly Efficient Isolation and Sensitive Detection of Small Extracellular Vesicles Using a Paper-Based Device.

Small extracellular vesicles (sEVs) play important roles in mediating intercellular communication and regulating biological processes. Facile sEV isolation is the essential and preliminary issue for their function investigation and downstream biomedical applications, while the traditional methods are challenged by tedious procedures, low purity, low yield, and potential damage. In this work, we developed an sEV isolation paper-based device (sEV-IsoPD) based on a three-dimensional (3D) paper chip, which is composed of a porous membrane for size exclusion and a metal-organic framework (MOF)/antibody-modified paper for immunoaffinity capture. In combination with a peristaltic pump-driven flow system, the sEV-IsoPD can efficiently isolate EV from cell culture medium and serum. Compared with the ultracentrifugation method, sEV-IsoPD exhibited a 5.1 times higher yield (1.7 × 109 mL-1), 1.6 times higher purity (1.6 × 1011 mg-1), and 7.5 times higher recovery (77.3%) with only 8.3% of the time (30 min) and 1.0% of the instrument cost ($710). Moreover, sEV concentration can be visually detected in a quantitative manner with this paper-based device with a linear range from 3.0 × 106 to 3.0 × 1010 mL-1 and a detection limit of 2.2 × 106 mL-1. The sEV-IsoPD provides an efficient and practical approach for the rapid isolation and visible detection of sEVs, which are promising for the preparation of sEVs and diagnosis of disease.

Smart Hairpins@MnO2 Nanosystem Enables Target-Triggered Enzyme-Free Exponential Amplification for Ultrasensitive Imaging of Intracellular MicroRNAs in Living Cells.

Sensitive and specific imaging of microRNA (miRNA) in living cells is of great value for disease diagnosis and monitoring. Hybridization chain reaction (HCR) and DNAzyme-based methods have been considered as powerful tools for miRNA detection, with low efficient intracellular delivery and limited amplification efficiency. Herein, we propose a Hairpins@MnO2 nanosystem for intracellular enzyme-free exponential amplification for miRNA imaging. The enzyme-free exponential amplification is based on the synergistic cross-activation between HCR and DNAzymes. The MnO2 nanosheets were employed as the carrier of three kinds of hairpin DNA probes and further provided appropriate Mn2+ as DNAzyme cofactors in the living cell. Upon entering cells and in the presence of highly expressed glutathione (GSH) in tumors, MnO2 is reduced to release Mn2+ and the three kinds of hairpin DNA probes. In the presence of target miRNA, the released hairpin DNA H1 and H2 probes self-assemble via HCR into the wire-shaped active Mn2+-based DNAzymes which further catalyze the cleavage of H3 to generate numerous new triggers to reversely stimulate HCR amplifiers, thus offering tremendously amplified Förster resonance energy transfer readout. The method has a detection limit of 33 fM, which is 2.4 × 104 times lower than that of the traditional HCR system. The developed method also has a high specificity; even miRNAs with a single base difference can be distinguished. Live cell imaging experiments confirmed that this Hairpins@MnO2 nanosystem allows accurate differentiation of miRNA expression of cancer cells and normal cells. The method holds great potential in biological research of nucleic acids.

Dual-Locked DNAzyme Platform for In Vitro and In Vivo Discrimination of Cancer Cells.

Imaging of tumor-associated microRNAs (miRNAs) can provide abundant information for cancer diagnosis, whereas the occurrence of trace amounts of miRNAs in normal cells inevitably causes an undesired false-positive signal in the discrimination of cancer cells during miRNA imaging. In this study, we propose a dual-locked (D-locked) platform consisting of the enzyme/miRNA-D-locked DNAzyme sensor and the honeycomb MnO2 nanosponge (hMNS) nanocarrier for highly specific cancer cell imaging. For a proof-of-concept demonstration, apurinic/apyrimidinic endonuclease 1 (APE1) and miR-21 were chosen as key models. The hMNS nanocarrier can efficiently release the D-locked DNAzyme sensor in living cells due to the decomposition of hMNS by glutathione, which can also supply Mn2+ for DNAzyme cleavage. Ascribing to the smart design of the D-locked DNAzyme sensor, the fluorescence signal can only be generated by the synergistic response of APE1 and miR-21 that are overexpressed in cancer cells. Compared with the miRNA single-locked DNAzyme sensor and the small-molecule (ATP)/miRNA D-locked DNAzyme sensor, the proposed enzyme (APE1)/miRNA D-locked DNAzyme sensor exhibited 2.6-fold and 2.4-fold higher discrimination ratio (Fcancer/Fnormal) for cancer cell discrimination, respectively. Owing to the superior performance, the D-locked strategy can selectively generate a fluorescence signal in cancer cells, facilitating accurate discrimination of cancer both in vitro and in vivo. Furthermore, this D-locked platform is easily adaptable toward other target molecules by redesigning the DNA sequences. The outstanding performance and expansibility of this D-locked platform holds promising prospects for cancer diagnosis and related biomedical applications.

Light-Controlled Recruitable Hybridization Chain Reaction on Exosome Vehicles for Highly Sensitive MicroRNA Imaging in Living Cells.

Sensitive imaging of intracellular microRNA (miRNA) in living cells is of great significance. Isothermal hybridization chain reaction (HCR)-based methods, although have been widely used to monitor intracellular low-abundance miRNA, are still subjected to the challenges of limited signal amplification efficiency and compromised imaging resolution. In this work, we design a light-controlled recruitable HCR (LCR-HCR) strategy that enables us to well overcome these limitations. Exosomes as delivery and recruitment vehicles are modified with three cholesterol-modified hairpins (H1, H2, and H3), in which H1 is for anchoring target miRNA and H2 and H3 with photocleavable linkers (PC-linkers) are designed for spatiotemporal HCR. By controllably releasing probes with high local concentrations to efficiently trigger HCR and further recruiting the generated double-stranded DNA (dsDNA) polymers instead of dispersion in the cytoplasm, the LCR-HCR method can significantly improve the imaging contrast by confining all of the reactants on exosome vehicles. For a proof-of-concept demonstration, the miR-21 was analyzed by LCR-HCR with a limit of detection (LOD) down to 3.3 pM (corresponding to 165 amol per 50 µL) in vitro and four times higher response than traditional HCR in vivo. In general, the LCR-HCR method provides a powerful tool for sensitive miRNA imaging in living cells and cancer diagnosis.

Long-term continuous monitoring of microRNA in living cells using modified gold nanoprobe.

Long-term and continuous monitoring of the microRNA (miRNA) expression in living cells is essential in biomedical research, but it is currently limited by fast consumption and easy digestion of probes in the intracellular environment. Herein, we report polydopamine-modified gold nanoparticles (AuNPs@PDA) as protective and efficient nanocarriers for DNA hairpin probes (hpDNA), achieving long-term monitoring (48 h) of the miRNA (let-7a) levels in living cells after drug treatments. This method enabled excellent sensitivity and high selectivity toward let-7a with a limit of detection of 0.51 nM (n = 3) and a linear range from 1 to 100 nM. More importantly, AuNPs@PDA can not only efficiently improve the loading of hpDNA on each nanoparticle, but also effectively protect hpDNA from hydrolysis in the cell microenvironment, finally realizing the continuous monitoring of let-7a in living cells for 48 h. This simple method would be of great significance for drug screening and precision medicine.

Fluorescent on-site detection of multiple pathogens using smartphone-based portable device with paper-based isothermal amplification chip.

The development of cost-effective, portable, and ease-of-use sensing system for on-site genetic diagnostics is highly desirable for pathogen screening and infectious disease diagnosis. This study develops (1) a paper-based biochip which is able to integrate the loop-mediated isothermal amplification (LAMP) protocols for simultaneous detection of Escherichia coli O157:H7, Salmonella spp., and Staphylococcus aureus, and (2) a stand-alone smartphone-based portable device which can control exactly 65 °C for isothermal amplification as well as collect and analyze the thus generated fluorescence signals. The reported sensing system has been successfully demonstrated for foodborne pathogen detection with a limit of detection of 2.8 × 10-5 ng µL-1. Spiked milk samples with concentration as low as 10 CFU mL-1 were successfully determined within 4 h, demonstrating the practicality of the reported sensing system in the fields. The reported sensing system featuring simplicity and reliability is ideally suited for genetic diagnostics in low resource settings.

Identification of Potential Parkinson's Disease Drugs Based on Multi-Source Data Fusion and Convolutional Neural Network.

Parkinson's disease (PD) is a serious neurodegenerative disease. Most of the current treatment can only alleviate symptoms, but not stop the progress of the disease. Therefore, it is crucial to find medicines to completely cure PD. Finding new indications of existing drugs through drug repositioning can not only reduce risk and cost, but also improve research and development efficiently. A drug repurposing method was proposed to identify potential Parkinson's disease-related drugs based on multi-source data integration and convolutional neural network. Multi-source data were used to construct similarity networks, and topology information were utilized to characterize drugs and PD-associated proteins. Then, diffusion component analysis method was employed to reduce the feature dimension. Finally, a convolutional neural network model was constructed to identify potential associations between existing drugs and LProts (PD-associated proteins). Based on 10-fold cross-validation, the developed method achieved an accuracy of 91.57%, specificity of 87.24%, sensitivity of 95.27%, Matthews correlation coefficient of 0.8304, area under the receiver operating characteristic curve of 0.9731 and area under the precision-recall curve of 0.9727, respectively. Compared with the state-of-the-art approaches, the current method demonstrates superiority in some aspects, such as sensitivity, accuracy, robustness, etc. In addition, some of the predicted potential PD therapeutics through molecular docking further proved that they can exert their efficacy by acting on the known targets of PD, and may be potential PD therapeutic drugs for further experimental research. It is anticipated that the current method may be considered as a powerful tool for drug repurposing and pathological mechanism studies.