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Gram staining (GS) is one of the most routine pathogen diagnosing operations. A rapid Gram feature prediction method based on single-cell Raman spectroscopy skips the tedious staining process and promotes the accuracy and efficiency for diagnosis.

Biotin is widely used in biological applications due to its highly selective and stable interaction with avidin, which highlights the great potential value of the quantitative determination of biotin concentration. However, the currently reported methods have many defects such as complicated operation process and low sensitivity. Here, the time-resolved fluorescence resonance energy transfer (TR-FRET) assay is introduced to establish a convenient, rapid and sensitive biotin quantitative detection strategy. Europium cryptate (Eu3+) acts as an energy donor to label streptavidin, while APC acts as an energy acceptor to label biotin. Biotin in aqueous solution interacts with streptavidin in a competition model. The obtained biotin detection range is 0.05-100 nM and an optimal limit of detection (LOD) of 0.03 nM biotin is obtained. Furthermore, the enzyme digestion test and competition mode test are implemented to analyze biotin in different states. The method involved in this work has greatly improved the sensitivity of biotin quantitative detection. And it’s the first time to systematically study the difference between free and bound biotin on concentration results. It can be furtherly extended to the detection of other biological molecules, or multiplex detection of other small molecules.

MicroRNA (miRNA) in exosomes is a powerful molecular signature for early diagnosis of cancers with the merits of high specificity and high stability. Herein, we report an ultrasensitive electrochem...

The purpose of this study was to develop Bi-parametric Magnetic Resonance Imaging (BP-MRI) based radiomics models for differentiation between benign and malignant prostate lesions, and to cross-vendor validate the generalization ability of the models. The prebiopsy BP-MRI data (T2-Weighted Image [T2WI] and the Apparent Diffusion Coefficient [ADC]) of 459 patients with clinical suspicion of prostate cancer were acquired using two scanners from different vendors. The prostate biopsies are the reference standard for diagnosing benign and malignant prostate lesions. The training set was 168 patients' data from Siemens (Vendor 1), and the inner test set was 70 patients' data from the same vendor. The external test set was 221 patients' data from GE (Vendor 2). The lesion Region of Interest (ROI) was manually delineated by experienced radiologists. A total of 851 radiomics features including shape, first-order statistical, texture, and wavelet features were extracted from ROI in T2WI and ADC, respectively. Two feature-ranking methods (Minimum Redundancy Maximum Relevance [MRMR] and Wilcoxon Rank-Sum Test [WRST]) and three classifiers (Random Forest [RF], Support Vector Machine [SVM], and the Least Absolute Shrinkage and Selection Operator [LASSO] regression) were investigated for their efficacy in building single-parametric radiomics signatures. A biparametric radiomics model was built by combining the optimal single-parametric radiomics signatures. A comprehensive diagnosis model was built by combining the biparametric radiomics model with age and Prostate Specific Antigen (PSA) value using multivariable logistic regression. All models were built in the training set and independently validated in the inner and external test sets, and the performances of models in the diagnosis of benign and malignant prostate lesions were quantified by the Area Under the Receiver Operating Characteristic Curve (AUC). The mean AUCs of the inner and external test sets were calculated for each model. The non-inferiority test was used to test if the AUC of model in external test was not inferior to the AUC of model in inner test. Combining MRMR and LASSO produced the best-performing single-parametric radiomics signatures with the highest mean AUC of 0.673 for T2WI (inner test AUC = 0.729 vs. external test AUC = 0.616, p = 0.569) and the highest mean AUC of 0.810 for ADC (inner test AUC = 0.822 vs. external test AUC = 0.797, p = 0.102). The biparametric radiomics model produced a mean AUC of 0.833 (inner test AUC = 0.867 vs. external test AUC = 0.798, p = 0.051). The comprehensive diagnosis model had an improved mean AUC of 0.911 (inner test AUC = 0.935 vs. external test AUC = 0.886, p = 0.010). The comprehensive diagnosis model for differentiating benign from malignant prostate lesions was accurate and generalizable.

Herein, we develop a novel and effective combination nanoplatform for cancer theranostics. Folic acid (FA) is first modified on the photothermal agent of polydopamine (PDA), which possesses excellent near-infrared (NIR) absorbance and thermal conversion features. Temperature-sensitive silver nanoclusters (AgNCs) are then synthesized on the DNA template that also loads the anticancer drug doxorubicin (Dox). After accumulation in cancer cells, PDA generates cytotoxic heat upon excitation of NIR light for photothermal therapy. On the other hand, the temperature increment is able to destroy the template of AgNCs, leading to the fluorescence variation and controlled release of Dox for chemotherapy. The combined nanosystem exhibits outstanding fluorescence tracing, NIR photothermal transduction, as well as chemo drug delivery capabilities. Both in vitro and in vivo results demonstrate excellent tumor growth suppression phenomena and no apparent adverse effects. This research provides a powerful targeted nanoplatform for cancer theranostics, which may have great potential value for future clinical applications.

A three-dimensional DNA tetrahedral nanostructure is constructed to support a walker strand on top and multiple track strands around it via the assembly of triplex-forming oligonucleotide (TFO). This design facilitates the regeneration of the sensing interface by simply adjusting pH conditions. On the basis of the tetrahedral DNA supported walking nanomachine, ultrasensitive electrochemical analysis of miRNA (miR-141) is achieved. Target miRNA assists the formation of three-way junction nanostructure. It contains a duplex region (hybridized by track and walker strands) that could be specially recognized and digested by certain nicking endonuclease. As a result, walker strand and target miRNA are released and move around the attached tracks for continuous cleavage reactions, releasing a larger number of signal reporters. By measuring the variation of signal responses, ultrasensitive analysis of miRNA is achieved. The limit of detection (LOD) is calculated to be 4.9 aM, which is rather low. In addition, the proposed method is successfully applied for the detection of miRNA in cell and serum samples, which could distinguish pathological information from healthy controls.

Multilayer Halbach array magnets support portable NMR and MRI, but optimizing their design to maximize performance and minimize the use of expensive magnet materials is challenging. This is partly because our theoretical understanding of such arrays is incomplete and computationally intensive. Here we provide a theoretical description of the magnetic field distribution and we demonstrate that inhomogeneity is greatest along the z axis in multilayer Halbach array magnets. This allows the configuration of the multilayer Halbach array magnets to be optimized in a way that takes into account homogeneity, magnet volume, and magnetic flux density. At the same time, our description simplifies the design of multilayer array magnets, while accommodating the possibility of different outer radii, lengths for each layer array, or the presence of separation between the rings. We validated the theoretical description in simulations of a three-layer Halbach array magnet, then with a prototype three-layer 1-T Halbach array magnet. After adjusting the position of magnet blocks in the neighboring rings, we achieved homogeneity of 220 ppm for a standard 5 mm NMR tube while the inner diameter of the magnet is 20 mm. Our work provides a theoretical foundation for designing multilayer Halbach array magnets to maximize homogeneity and minimize the use of magnet materials.

Messenger RNA (mRNA) is a type of important gene regulation element and reliable biomarker for the early diagnosis of diseases. However, mRNA analysis in live cells cannot be easily realized since conventional techniques always require procedures like mRNA purification or cell fixation. Herein, we propose a powerful two-dimensional hybridization chain reaction (2D HCR) strategy for amplified sensing and imaging of intracellular mRNA. The basis is the design of ternary hairpin or dumbbell-structured DNA fuel strands. In the presence of mRNA, organized 2D DNA assembly reaction can be initiated, which leads to structural changes of a large number of fuel strands and produces an in situ 2D DNA network. An enhanced fluorescence signal is thus generated, allowing direct and quantitative analysis of mRNA with high signal-to-noise ratio. Moreover, MnO2 nanosheet/glutathione-aided transportation and release association are successfully applied to adapt the 2D HCR nanosystem in live cells. Therefore, this work provides a promising quantitative endogenous mRNA analysis tool for clinical applications.

Nucleic acids, including circulating tumor DNA (ctDNA), microRNA, and virus DNA/RNA, have been widely applied as potential disease biomarkers for early clinical diagnosis. In this study, we present a concept of DNA nanostructures transitions for the construction of DNA bipedal walking nanomachine, which integrates dual signal amplification for direct nucleic acid assay. DNA hairpins transition is developed to facilitate the generation of multiple target sequences; meanwhile, the subsequent DNA dumbbell-wheel transition is controlled to achieve the bipedal walker, which cleaves multiple tracks around electrode surface. Through combination of strand displacement reaction and digestion cycles, DNA monolayer at the electrode interface could be engineered and target-induced signal variation is realized. In addition, pH-assisted detachable intermolecular DNA triplex design is utilized for the regeneration of electrochemical biosensor. The high consistency between this work and standard quantitative polymerase chain reaction is validated. Moreover, the feasibilities of this biosensor to detect ctDNA and SARS-CoV-2 RNA in clinical samples are demonstrated with satisfactory accuracy and reliability. Therefore, the proposed approach has great potential applications for nucleic acid based clinical diagnostics.

Circulating tumor DNA (ctDNA) serves as a powerful noninvasive and viable biomarker for the diagnosis of cancers. The abundance of ctDNA in patients with advanced stages is significantly higher than that in patients with early stages. Herein, a ratiometric electrochemical biosensor for the detection of ctDNA is developed by smart design of DNA probes and recycles of DNAzyme activation. The conformational variation of DNA structures leads to the changes of two types of electrochemical species. This enzyme-free sensing strategy promotes excellent amplification efficiency upon target recognition. The obtained results assure good analytical performances and a limit of detection as low as 25 aM is achieved. Additionally, this method exhibits outstanding selectivity and great application prospects in biological sample analysis.

Accurate and sensitive analysis of biomarkers is a promising way to provide comprehensive physio-pathological information that is significant for early diagnosis of certain diseases. miRNA is a type of noncoding small RNAs which are involved in the regulation of a number of cellular processes. It has been regarded as an important tumor biomarker. Herein, we have constructed a three-dimensional DNA layer on electrode interface and achieved ladder hybridization chain reaction strategy for the enrichment of electrochemical signals. In addition, duplex-specific nuclease catalyzed amplification is previously performed on magnetic nanocomposites, which further improves the sensitivity for the detection of target miRNA initiator. This approach shows great molecular recognition efficiency as well as cascade signal amplification. The analytical performances are superior. In addition, the identification of cancer cell types according to target biomarker information is achieved and the testing results in clinical serum samples further demonstrate its great potential utility for diagnosis.

Studies show that centrifugal step emulsification is an effective method for high throughput droplet generation and has been widely used over the past ten years. However, there is no in-depth understanding of the physics underlying emulsification and the effect of centrifugal force on the droplet volume. Aiming at resolving this shortcoming, this article is focused on the dynamics of the droplet formation process subjected to centrifugal acceleration, and a theoretical model is proposed for accurately predicting the droplet size. A critical time and a critical bulb length are introduced to describe the droplet formation and divide this process into stable and rapid filling regimes. It is worth noting that the centrifugal force was considered in the dispersed phase profile. Finally, a theoretical model was established to predict the droplet size. Numerical simulation and high-speed measurements demonstrate that there is a critical time and bulb length, and the critical bulb length is in good agreement with the proposed theory. To evaluate the performance of the model, experiments with different centrifugal accelerations, terrace heights, and terrace lengths were carried out. The obtained results are in excellent agreement with the experiments, and the relative diameter error was less than 4%. The performed analyses demonstrate that the established model can be applied to accurately calculate the droplet size and obtain the correlation between the droplet size and different parameters, such as terrace height, terrace length, and centrifugal acceleration. This model has great potential in guiding the designs of centrifugal step emulsification systems.

Herein, a highly sensitive electrochemical genosensor is proposed by the construction of an innovative DNA walking machine. Generally, a number of tetrahedral DNA (TDNA)-supported tracks and walkers are comodified on the electrode surface. DNA walking is inhibited in the absence of target DNA. After the interaction between a DNA walker strand and target DNA, a single-stranded primer sequence could be released, which initiates subsequent rolling circle amplification (RCA). The generated long single-stranded product contains multiple DNAzyme cores, which facilitate highly efficient cleavage of track strands and subsequent DNA walking. The electrode then loses the ability to localize silver nanoparticles (AgNPs) as the electrochemical species. Thus, when the reduced silver stripping current is recorded, a highly sensitive method for the detection of DNA is fabricated. Under optimal conditions, it achieves an admirable sensitivity with the limit of detection as low as 0.1 fM. Satisfactory specificity is also guaranteed. In addition, the practicality is further confirmed by applying human serum samples, which show great potential utility for clinical diagnosis.

We present a novel ratiometric fluorescent biosensor for ctDNA analysis based on the construction of a DNA four-way junction (FWJ). Three fuel strands for the FWJ are firstly designed and prepared. Another essential strand for the formation of the structure is the DNA product generated from target ctDNA initiated strand displacement amplification. With the transformation of the DNA structure, the FRET states of two fluorophores change and the ratiometric fluorescence response can be recorded to indicate the level of the initial ctDNA. The proposed method also has excellent capability to discriminate mismatches and shows potential practical utility for clinical samples.

We have fabricated an ultrasensitive exosome biosensor based on a multipedal DNA walker with a core of target exosomes. Specific recognition is achieved by introducing a CD63 aptamer and facile separation is obtained with magnetic Fe3O4@Au nanoparticles. A limit of detection down to 6/μL is obtained with excellent selectivity.

Biofunctionalized quantum dots (QDs) are effective target fluorescent labels for bioimaging. However, conventional synthesis of biofunctionalized I-III-VI core-shell CuInS2/ZnS QDs requires complex bench-top operations, resulting in limited product performance and variety, and is not amenable to a 'one-step' approach. In this work, we have successfully demonstrated a fully automated method for preparing denatured bovine serum albumin (dBSA)-CuInS2/ZnS QDs by introducing microfluidic (MF) chips to synthesize biofunctionalized QDs, hence establishing a 'one-step' procedure. We have also studied and optimized the reaction synthesis parameters. The emission wavelength of the dBSA-CuInS2/ZnS QDs is located in the near-infrared range and can be tuned from 650 to 750 nm by simply varying the reaction parameters. In addition, the 'one-step'-synthesized dBSA-CuInS2/ZnS QDs have a long average fluorescence lifetime of 153.76 ns and a small particle size of 5 ± 2 nm. To demonstrate the applicability of the 'one-step'-synthesized dBSA-CuInS2/ZnS QDs in bioimaging studies, we modified the QDs with folic acid and hyaluronic acid, and then performed target bioimaging and cytotoxicity tests on macrophages, liver cancer cells and pancreatic cancer cells. The cell images show that the red emission signals originate from the QDs, which indicates that the dBSA-CuInS2/ZnS QDs prepared by the MF approach are suitable optical contrast agents for target bioimaging. This 'one-step' MF-based QD synthesis approach could serve as a rapid, cost-effective, and small-scale nanocrystal production platform for complex QD formulations for a wide range of bioapplications.

Abnormal miRNA expressions are closely related to the occurrence and development of cancers. It is of great significance to monitor miRNA expression levels for early diagnosis and therapy of the diseases. This study presents two independent colorimetric strategies for simultaneously monitoring multiple miRNAs based on cross-linking or non-cross-linking aggregations of gold nanoparticles (AuNPs). By introducing a Y shaped DNA structure and two types of DNA modified AuNPs, a triple-input DNA AND logic gate is facilely developed with the cross-linking aggregation of AuNPs as the signal output. To improve the sensitivity and shorten reaction time, the logic gate is modified by further employing a three DNA strands formed duplex and hybridization chain reaction. Non-cross-linking aggregation of AuNPs is used to evaluate the concentration of initial miRNA inputs. This strategy does not require DNA modification of AuNPs and ultrahigh sensitivity is achieved with the amplification of hybridization chain reaction. The present work may provide powerful tools for multiple miRNAs diagnostics and inspire further development of DNA based logic gates.

The diagnosis of preoperative lymph node (LN) metastasis is crucial to evaluate possible therapy options for T1 lung adenocarcinoma patients. Radiologists preoperatively diagnose LN metastasis by evaluating signs related to LN metastasis, like spiculation or lobulation of pulmonary nodules in CT images. However, this type of evaluation is subjective and time-consuming, which may result in poor consistency and low efficiency of diagnoses. In this study, a 3D Multi-scale, Multi-task, and Multi-label classification network (3M‐CN) was proposed to predict LN metastasis, as well as evaluate multiple related signs of pulmonary nodules in order to improve the accuracy of LN metastasis prediction. The following key approaches were adapted for this method. First, a multi-scale feature fusion module was proposed to aggregate the features from different levels for which different labels be best modeled at different levels; second, an auxiliary segmentation task was applied to force the model to focus more on the nodule region and less on surrounding unrelated structures; and third, a cross-modal integration module called the refine layer was designed to integrate the related risk factors into the model to further improve its confidence level. The 3M‐CN was trained using data from 401 cases and then validated on both internal and external datasets, which consisted of 100 cases and 53 cases, respectively. The proposed 3M‐CN model was then compared with existing state-of-the-art methods for prediction of LN metastasis. The proposed model outperformed other methods, achieving the best performance with AUCs of 0.945 and 0.948 in the internal and external test datasets, respectively. The proposed model not only obtain strong generalization, but greatly enhance the interpretability of the deep learning model, increase doctors' confidence in the model results, conform to doctors' diagnostic process, and may also be transferable to the diagnosis of other diseases.

Simple Summary Raman spectroscopy and imaging are label-free, non-destructive techniques to study cellular metabolism with subcellular spatial resolution. This review focuses on applications of Raman-based methods in a combination of stable isotope probing on cancer metabolism and cancer imaging. Abstract Metabolic reprogramming is a common hallmark in cancer. The high complexity and heterogeneity in cancer render it challenging for scientists to study cancer metabolism. Despite the recent advances in single-cell metabolomics based on mass spectrometry, the analysis of metabolites is still a destructive process, thus limiting in vivo investigations. Being label-free and nonperturbative, Raman spectroscopy offers intrinsic information for elucidating active biochemical processes at subcellular level. This review summarizes recent applications of Raman-based techniques, including spontaneous Raman spectroscopy and imaging, coherent Raman imaging, and Raman-stable isotope probing, in contribution to the molecular understanding of the complex biological processes in the disease. In addition, this review discusses possible future directions of Raman-based technologies in cancer research.

The coronavirus disease 2019 (COVID-19) pandemic has highlighted the need for rapid and accurate nucleic acid detection at the point of care. Here, we report an amplification-free nucleic acid immunoassay, implemented on a lateral flow strip, for the fluorescence detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA in less than one hour. The assay uses DNA probes that are designed to bind to the conserved open reading frame 1ab (ORF1ab), envelope protein (E) and the nucleocapsid (N) regions of the SARS-CoV-2 genome, and a fluorescent-nanoparticle-labelled monoclonal antibody that binds to double-stranded DNA-RNA hybrids. In a multi-hospital randomized double-blind trial involving 734 samples (593 throat swabs and 141 sputum) provided by 670 individuals, the assay achieved sensitivities of 100% and specificities of 99% for both types of sample (ground truth was determined using quantitative PCR with reverse transcription). The inexpensive amplification-free detection of SARS-CoV-2 RNA should facilitate the rapid diagnosis of COVID-19 at the point of care.

In this study, a tetrahedral DNA nanostructure was first self-assembled; this was then conjugated with gold nanoparticles (AuNPs) and carbon nanodots (CDs). The fabricated nanocomposites allow simultaneous analysis of telomerase activity and miRNA with dual fluorescence channels. By further introducing an iRGD peptide sequence, the nanoconjuates can be conveniently transferred inside living cells for in situ imaging. The analytical performances and anti-jamming capabilities are excellent. Meanwhile, the materials are highly biocompatible for intracellular applications. Therefore, the proposed biosystem shows great promise as a powerful tool for quantitative analysis of the dual biomarkers. The strategy can also be further exploited as a versatile platform for in situ detection of many other targets for early disease diagnosis.

Exosomal miRNA is an ideal source of noninvasive biomarker for the diagnosis of cancer. Sensitive and accurate analysis of exosomal miRNA plays an important role in facilitating clinical applications. Herein, we have developed a novel electrochemical method for exosomal miRNA assay coupling strand displacement amplification (SDA) and dumbbell hybridization chain reaction (DHCR). The target triggered isothermal SDA process generates a large number of single-stranded DNA products to assist the formation of the three-way junction structure on the electrode surface. In addition, dumbbell DNA fuel strands (DHP1 and DHP2) are designed for the hybridization chain reaction. This novel form of HCR produces DNA nanostructures with a tight conformation, which facilitates the enhancement of the electrochemical response. The combination of the dual signal amplification significantly improves the sensitivity for the exosomal miRNA assay, resulting in a limit of detection (LOD) as low as 7.3 aM. More importantly, the method is successfully applied in the analysis of cells and human serum samples, which demonstrates the potential utility in point-of-care testing (POCT) applications.

Biofunctionalized quantum dots (QDs) are effective target fluorescent labels for bioimaging. However, conventional synthesis of biofunctionalized I-III-VI core-shell CuInS2/ZnS QDs requires complex bench-top operations, resulting in limited product performance and variety, and is not amenable to a 'one-step' approach. In this work, we have successfully demonstrated a fully automated method for preparing denatured bovine serum albumin (dBSA)-CuInS2/ZnS QDs by introducing microfluidic (MF) chips to synthesize biofunctionalized QDs, hence establishing a 'one-step' procedure. We have also studied and optimized the reaction synthesis parameters. The emission wavelength of the dBSA-CuInS2/ZnS QDs is located in the near-infrared range and can be tuned from 650 to 750 nm by simply varying the reaction parameters. In addition, the 'one-step'-synthesized dBSA-CuInS2/ZnS QDs have a long average fluorescence lifetime of 153.76 ns and a small particle size of 5 ± 2 nm. To demonstrate the applicability of the 'one-step'-synthesized dBSA-CuInS2/ZnS QDs in bioimaging studies, we modified the QDs with folic acid and hyaluronic acid, and then performed target bioimaging and cytotoxicity tests on macrophages, liver cancer cells and pancreatic cancer cells. The cell images show that the red emission signals originate from the QDs, which indicates that the dBSA-CuInS2/ZnS QDs prepared by the MF approach are suitable optical contrast agents for target bioimaging. This 'one-step' MF-based QD synthesis approach could serve as a rapid, cost-effective, and small-scale nanocrystal production platform for complex QD formulations for a wide range of bioapplications.