CRISPR/Pepper-tDeg: A Live Imaging System Enables Non-Repetitive Genomic Locus Analysis with One Single-Guide RNA.

CRISPR-based genomic-imaging systems have been utilized for spatiotemporal imaging of the repetitive genomic loci in living cells, but they are still challenged by limited signal-to-noise ratio (SNR) at a non-repetitive genomic locus. Here, an efficient genomic-imaging system is proposed, termed CRISPR/Pepper-tDeg, by engineering the CRISPR sgRNA scaffolds with the degron-binding Pepper aptamers for binding fluorogenic proteins fused with Tat peptide derived degron domain (tDeg). The target-dependent stability switches of both sgRNA and fluorogenic protein allow this system to image repetitive telomeres sensitively with a 5-fold higher SNR than conventional CRISPR/MS2-MCP system using "always-on" fluorescent protein tag.

Identifying Protein Phosphorylation Site-Disease Associations Based on Multi-Similarity Fusion and Negative Sample Selection by Convolutional Neural Network.

As one of the most important post-translational modifications (PTMs), protein phosphorylation plays a key role in a variety of biological processes. Many studies have shown that protein phosphorylation is associated with various human diseases. Therefore, identifying protein phosphorylation site-disease associations can help to elucidate the pathogenesis of disease and discover new drug targets.

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 -methyladenosine (mA) 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.

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.

A DNAzyme dual-feedback autocatalytic exponential amplification biocircuit for microRNA imaging in living cells.

Autocatalytic biocircuit are powerful tools for analysing intracellular biomarkers, but these tools are constrained by limitations in amplification capacity and intracellular delivery efficiency. In this work, we developed a DNAzyme-based dual-feedback autocatalytic exponential amplification biocircuit sustained by a honeycomb MnO nanosponge (EDA@hMNS) for live-cell imaging of intracellular low-abundance microRNAs (miRNA). The EDA biocircuit comprises a blocked DNAzyme (b-DNAzyme), a Fuel strand and a Substrate strand.

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.

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.

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).

Dual-Locked DNAzyme Platform for and 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 MnO 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.

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.

Identification of MiRNA-Disease Associations Based on Information of Multi-Module and Meta-Path.

Cumulative research reveals that microRNAs (miRNAs) are involved in many critical biological processes including cell proliferation, differentiation and apoptosis. It is of great significance to figure out the associations between miRNAs and human diseases that are the basis for finding biomarkers for diagnosis and targets for treatment. To overcome the time-consuming and labor-intensive problems faced by traditional experiments, a computational method was developed to identify potential associations between miRNAs and diseases based on the graph attention network (GAT) with different meta-path mode and support vector (SVM).

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.

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.

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.

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.

Identification of Chemical-Disease Associations Through Integration of Molecular Fingerprint, Gene Ontology and Pathway Information.

The identification of chemical-disease association types is helpful not only to discovery lead compounds and study drug repositioning, but also to treat disease and decipher pathomechanism. It is very urgent to develop computational method for identifying potential chemical-disease association types, since wet methods are usually expensive, laborious and time-consuming. In this study, molecular fingerprint, gene ontology and pathway are utilized to characterize chemicals and diseases.

Cell-Selective Encapsulation within Metal-Organic Framework Shells via Precursor-Functionalized Aptamer Identification for Whole-Cell Cancer Vaccine.

Single-cell encapsulation is an emerging technology to endow cells with various functions, of which developing new applications in vivo is in high demand. Currently, metal-organic frameworks (MOFs) that are used as nanometric shells to coat living cells, however, have not realized cell-selective encapsulation. Here, a biocompatible and selective cell encapsulation strategy based on precursor-functionalized nucleolin aptamer and in situ MOF mineralization on the aptamer-identified cancer cell surface are developed.

A MOF-Shell-Confined I-Motif-Based pH Probe (MOFC-i) Strategy for Sensitive and Dynamic Imaging of Cell Surface pH.

Dynamic imaging of cell surface pH is extremely challenging due to the slight changes in pH and the fast diffusion of secreted acid to the extracellular environment. In this work, we construct a novel metal-organic framework (MOF)-shell-confined i-motif-based pH probe (MOFC-i) strategy that enables sensitive and dynamic imaging of cell surface pH. The CY3- and CY5-labeled i-motif, which is hybridized via its short complementary chain with two-base mismatches, is optimized for sensing at physiological pH.

Isothermal Self-Primer EXPonential Amplification Reaction (SPEXPAR) for Highly Sensitive Detection of Single-Stranded Nucleic Acids and Proteins.

Development of versatile sensing methods for sensitive and specific detection of clinically relevant nucleic acids and proteins is of great value for disease monitoring and diagnosis. In this work, we propose a novel isothermal Self-primer EXPonential Amplification Reaction (SPEXPAR) strategy based on a rationally engineered structure-switchable Metastable Hairpin template (MH-template). The MH-template initially keeps inactive with its self-primer overhanging a part of target recognition region to inhibit polymerization.

Cancer cell identification by facile imaging of intracellular reductive substances with fluorescent nanosensor.

Ascorbic acid (AA) and glutathione (GSH), the most abundant intracellular reductive substances, have been widely used as biomarkers for cancer cells identification. The current methods relying on imaging of AA or GSH alone to identify cancer cells may cause systematic errors, since a mutual conversion relationship exists between AA and GSH. In this work, we propose a fluorescent nanosensor for the simultaneous imaging of intracellular reductive substances including AA and GSH.

Pearl Necklacelike Strategy Enables Quantification of Global 5-Hydroxymethylcytosine and 5-Formylcytosine by Inductively Coupled Plasma-Atomic Emission Spectrometry.

5-Hydroxymethylcytosine (5hmC) and 5-formylcytosine (5fC) are key intermediates of active DNA demethylation, for which the global detection methods are still restricted by high cost and long operation time. Here, we demonstrate a pearl necklacelike strategy to accurately quantify global 5hmC and 5fC in genomic DNA. In this method, the metal-organic framework (MOF), [Cu(BTC)] (denoted as HKUST-1, HBTC = 1,3,5-benzenetricarboxylic acid), with a diameter of ∼30 nm that contains ∼15 000 copper ions (Cu) as the "super label" was grown in the carboxylated 5hmC and 5fC loci of genomic DNA via the coordination between Cu and the carboxyl group.

Novel Potential Small Molecule-MiRNA-Cancer Associations Prediction Model Based on Fingerprint, Sequence, and Clinical Symptoms.

As an important biomarker in organisms, miRNA is closely related to various small molecules and diseases. Research on small molecule-miRNA-cancer associations is helpful for the development of cancer treatment drugs and the discovery of pathogenesis. It is very urgent to develop theoretical methods for identifying potential small molecular-miRNA-cancer associations, because experimental approaches are usually time-consuming, laborious, and expensive.

Toehold-mediated ligation-free rolling circle amplification enables sensitive and rapid imaging of messenger RNAs in situ in cells.

In situ analysis of tumor-related messenger RNAs (mRNAs) is significant in identifying cancer cells at the genetic level in the early stage. Rolling circle amplification (RCA)-based methods are primary tools for in situ mRNA assay, however, the necessary ligation reaction not only shows low ligation efficiency, but also greatly prolongs the assay time that increases the risk of cells losing and mRNAs leakage. In this work, we propose a novel toehold-mediated ligation-free RCA (TMLFRCA) on a designed structure-switchable dumbbell-shaped probe (SDP).

Performance improvement for a 2D convolutional neural network by using SSC encoding on protein-protein interaction tasks.

Background: The interactions of proteins are determined by their sequences and affect the regulation of the cell cycle, signal transduction and metabolism, which is of extraordinary significance to modern proteomics research. Despite advances in experimental technology, it is still expensive, laborious, and time-consuming to determine protein-protein interactions (PPIs), and there is a strong demand for effective bioinformatics approaches to identify potential PPIs. Considering the large amount of PPI data, a high-performance processor can be utilized to enhance the capability of the deep learning method and directly predict protein sequences.