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The investigation of the intramolecular charge transfer (ICT) process of gold nanoclusters (AuNCs) is critical to understand the unique features of the nanomaterials, which also benefits their further applications. Herein, 6-methyl-2-thiouracil (CH 3 -2-TU) and polyvinylpyrrolidone (PVP)-stabilized AuNCs are prepared, and the ICT behaviors are carefully studied. Protonation or deprotonation of the ligands around AuNCs could be used to regulate the ICT state, influencing the electron distribution and band gap. Shifted fluorescence emission phenomena are thus observed, which respond to external pH stimuli. In addition, the AuNCs are developed as color-switchable indicators for the highly sensitive detection of biogenic amines. As a proof of concept, the performance of this strategy in the evaluation of food spoilage by probing pH conditions is validated with satisfactory results. The discoveries in this work offer a convenient route to regulate the optical properties of AuNCs and the design of pH-based sensing applications.

The sensory neocortex has been suggested to be a substrate for long-term memory storage, yet which exact single cells could be specific candidates underlying such long-term memory storage remained neither known nor visible for over a century. Here, using a combination of day-by-day two-photon Ca 2+ imaging and targeted single-cell loose-patch recording in an auditory associative learning paradigm with composite sounds in male mice, we reveal sparsely distributed neurons in layer 2/3 of auditory cortex emerged step-wise from quiescence into bursting mode, which then invariably expressed holistic information of the learned composite sounds, referred to as holistic bursting (HB) cells. Notably, it was not shuffled populations but the same sparse HB cells that embodied the behavioral relevance of the learned composite sounds, pinpointing HB cells as physiologically-defined single-cell candidates of an engram underlying long-term memory storage in auditory cortex., (© 2023. The Author(s).)

Early quantification of multiplex biomarkers such as microRNAs (miRNAs) is critical during disease pathologic development and therapy. To tackle challenges of low abundance and multiplexing, we herein report a mass-encoded biosensing approach with duplex-specific nuclease (DSN) mediated signal amplification. Magnetic Fe 3 O 4 cores are coated with small gold nanoparticles (AuNPs), which are applied to achieve facile DNA immobilization subsequent separation. This biosensor integrates multiple mass reporters corresponding to different targets (five miRNAs as examples). Due to the excellent resolution of mass spectrometry, these targets can be successfully distinguished in a single spectrum. Wide detection ranges from 10 fM to 1 nM are achieved, and the limits of detection are estimated to be 10 fM. High selectivity is promised due to the enzyme activity of DSN, and practical application in human serum samples performs satisfactorily. The number of targets to be tested can be further expanded by designing different specific mass tags in theory. Therefore, the proposed method can be utilized as an important and valuable tool to quantify multiplex miRNAs for disease screening as well as biomedical investigations.

Integrating artificial intelligence and new diagnostic platforms into routine clinical microbiology laboratory procedures has grown increasingly intriguing, holding promises of reducing turnaround time and cost and maximizing efficiency. At least one billion people are suffering from fungal infections, leading to over 1.6 million mortality every year. Despite the increasing demand for fungal diagnosis, current approaches suffer from manual bias, long cultivation time (from days to months), and low sensitivity (only 50% produce positive fungal cultures). Delayed and inaccurate treatments consequently lead to higher hospital costs, mobility and mortality rates. Here, we developed single-cell Raman spectroscopy and artificial intelligence to achieve rapid identification of infectious fungi. The classification between fungi and bacteria infections was initially achieved with 100% sensitivity and specificity using single-cell Raman spectra (SCRS). Then, we constructed a Raman dataset from clinical fungal isolates obtained from 94 patients, consisting of 115,129 SCRS. By training a classification model with an optimized clinical feedback loop, just 5 cells per patient (acquisition time 2 s per cell) made the most accurate classification. This protocol has achieved 100% accuracies for fungal identification at the species level. This protocol was transformed to assessing clinical samples of urinary tract infection, obtaining the correct diagnosis from raw sample-to-result within 1 h., Competing Interests: Authors YL, XY, and YS were employed by Shanghai Hesen Biotech Co., Shanghai. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Xu, Luo, Wang, Tu, Yi, Xu, Song, Tang, Hua, Yu, Yin, Yang and Huang.)

Invasive fungal infection serves as a great threat to human health. Discrimination between fungal and bacterial infections at the earliest stage is vital for effective clinic practice; however, traditional culture-dependent microscopic diagnosis of fungal infection usually requires several days, meanwhile, culture-independent immunological and molecular methods are limited by the detectable type of pathogens and the issues with high false-positive rates. In this study, we proposed a novel culture-independent phenotyping method based on single-cell Raman spectroscopy for the rapid discrimination between fungal and bacterial infections. Three Raman biomarkers, including cytochrome c, peptidoglycan, and nucleic acid, were identified through hierarchical clustering analysis of Raman spectra across 12 types of most common yeast and bacterial pathogens. Compared to those of bacterial pathogens, the single cells of yeast pathogens demonstrated significantly stronger Raman peaks for cytochrome c, but weaker signals for peptidoglycan and nucleic acid. A two-step protocol combining the three biomarkers was established and able to differentiate fungal infections from bacterial infections with an overall accuracy of 94.9%. Our approach was also used to detect ten raw urinary tract infection samples. Successful identification of fungi was achieved within half an hour after sample obtainment. We further demonstrated the accurate fungal species taxonomy achieved with Raman-assisted cell ejection. Our findings demonstrate that Raman-based fungal identification is a novel, facile, reliable, and with a breadth of coverage approach, that has a great potential to be adopted in routine clinical practice to reduce the turn-around time of invasive fungal disease (IFD) diagnostics., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

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., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

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., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Gram staining (GS) is one of the routine microbiological operations to classify bacteria based on the cell wall structure. Accurate GS classification of pathogens is of great significance since it helps correct administration of antimicrobial treatment. The laborious procedure and low sensitivity results related to conventional GS have resulted in reluctance among clinicians. In this study, we integrate confocal Raman spectroscopy and machine learning techniques to distinguish Gram-negative (GN) or Gram-positive (GP) bacteria. A single-cell Raman database including seven most common clinical pathogens (three GP strains and four GN strains) was constructed. Machine learning algorithms including the support-vector machine (SVM), k -nearest neighbors' algorithm ( k -NN), gradient boosting machine (GBM), linear discriminant analysis (LDA), and t-distributed stochastic neighbor embedding (t-SNE) were trained to achieve the binary classification for GS. With such a relatively small database, the SVM model achieved the highest accuracy of 98.1%. The molecular signatures of GN and GP embedded in their Raman fingerprints were identified with hierarchical cluster analysis (HCA). The results indicated that Raman peaks for peptidoglycan and teichoic acid were the most significant factors that contributed to accurate classification. The Raman machine learning approach could greatly enhance the diagnosis of pathogenic infections.

Competing Interests: The authors declare no competing interests.

Objectives: This study used resting-state functional magnetic resonance imaging (rs-fMRI) scans to assess the dominant effects of 36 h total sleep deprivation (TSD) on vigilant attention and changes in the resting-state network., Materials and Methods: Twenty-two healthy college students were enrolled in this study. Participants underwent two rs-fMRI scans, once in rested wakefulness (RW) and once after 36 h of TSD. We used psychomotor vigilance tasks (PVT) to measure vigilant attention. The region-of-interest to region-of-interest correlation was employed to analyze the relationship within the salience network (SN) and between other networks after 36 h of TSD. Furthermore, Pearson's correlation analysis investigated the relationship between altered insular functional connectivity and PVT performance., Results: After 36 h of TSD, participants showed significantly decreased vigilant attention. Additionally, TSD induced decreased functional connectivity between the visual and parietal regions, whereas, a significant increase was observed between the anterior cingulate cortex and insula. Moreover, changes in functional connectivity in the anterior cingulate cortex and insula showed a significant positive correlation with the response time to PVT., Conclusion: Our results suggest that 36 h of TSD impaired vigilant visual attention, resulting in slower reaction times. The decrease in visual-parietal functional connectivity may be related to the decrease in the reception of information in the brain. Enhanced functional connectivity of the anterior cingulate cortex with the insula revealed that the brain network compensation occurs mainly in executive function., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Fu, Dai, Chen, Wang, Song, Peng, Xu, Xu, Tang and Shao.)

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.

The diversity of bacteria and their ability to acquire drug resistance lead to many challenges in traditional antibacterial methods. Photothermal therapies that convert light energy into localized physical heat to kill target microorganisms do not induce resistance and provide an alternative for antibacterial treatment. However, many photothermal materials cannot specifically target bacteria, which can lead to thermal damage to normal tissues, thus seriously affecting their biological applications. Here, we designed and synthesized bacteria-affinitive photothermal carbon dots (BAPTCDs) targeting MurD ligase that catalyzes the synthesis of peptidoglycan (PG) in bacteria. BAPTCDs presented specific recognition ability and excellent photothermal properties. BAPTCDs can bind to bacteria very tightly due to their chiral structure and inhibit enzyme activity by competing with D-glutamic acid to bind to MurD ligases, thus inhibiting the synthesis of bacterial walls. It also improves the accuracy of bacteria treatment by laser irradiation. Through the synergy of biochemical and physical effects, the material offers outstanding antibacterial effects and potentially contributes to tackling the spread of antibiotic resistance and facilitation of antibiotic stewardship., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Qie, Zan, Gui, Chen, Wang, Lin, Mei, Ge, Zhang, Tang, Dong and Song.)

Sensitive and specific assay of hepatitis C virus (HCV) RNA has a great clinical significance for the diagnosis of hepatitis C in window period. A colorimetric assay is described for determination of the RNA of hepatitis C virus. The method is based on the in situ synthesis of graphene quantum dot-silver nano-composites (GQD/Ag NCs), magnetic separation and catalyzed hairpin assembly reaction (CHA). The silver component of GQD/Ag NCs react with H 2 O 2 generated by glucose oxidase, which are induced via CHA. Then the light-yellow solution turns into colorless transparent in the presence of the target RNAs. The method has a linear response in the 25-500 pM RNA concentration range, and the detection limit is 24.84 pM. The method is simple, stable and sensitive and might be extend to the assay of other RNA viruses. The retro-transcription free and visual distinguishable properties endow this strategy a promising application in the screening of HCV., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

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.

Microfluidic-based droplet generation approaches require the design of microfluidic chips and a precise lithography process, which require skilled technicians and a long manufacturing time. Here we developed a centrifugal buoyancy-based emulsification (CBbE) method for producing droplets with high efficiency and minimal fabrication time. Our approach is to fabricate a droplet generation module that can be easily assembled using syringe needles and PCR tubes. With this module and a common centrifuge, high-throughput droplet generation with controllable droplet size could be realized in a few minutes. Experiments showed that the droplet diameter depended mainly on centrifugal speed, and droplets with controllable diameter from 206 to 158 μm could be generated under a centrifugal acceleration range from 14 to 171.9 g . Excellent droplet uniformity was achieved (CV < 3%) when centrifugal acceleration was greater than 108 g . We performed digital PCR tests through the CBbE approach and demonstrated that this cost-effective method not only eliminates the usage of complex microfluidic devices and control systems but also greatly suppresses the loss of materials and cross-contamination. CBbE-enabled droplet generation combines both easiness and robustness, and breaks the technical challenges by using conventional lab equipment and supplies.

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 processes 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 (Eu 3+ ) 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 mode. The obtained biotin detection range is 0.05-100 nM and the optimal limit of detection (LOD) of 0.03 nM biotin is obtained. Furthermore, an enzyme digestion test and a competition mode test were performed to analyze biotin in different states. The method used in this work has greatly improved the sensitivity of biotin quantitative detection and it's for the first time that a systematic study on the difference between free and bound biotin based on concentration results is conducted. It can be further extended to the detection of other biological molecules or multiplex detection of other small molecules.

Introducing nonlinear fluorophore excitation into structured illumination microscopy (SIM) can further extend its spatial resolution without theoretical limitation. However, it is a great challenge to recover the weak higher-order harmonic signal and reconstruct high-fidelity super-resolution (SR) images. Here, we proposed a joint optimization strategy in both the frequency and spatial domains to reconstruct high-quality nonlinear SIM (NL-SIM) images. We demonstrate that our method can reconstruct SR images with fewer artifacts and higher fidelity on the BioSR dataset with patterned-activation NL-SIM. This method could robustly overcome one of the long-lived obstacles on NL-SIM imaging, thereby promoting its wide application in biology.

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., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

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., (© 2021. Australasian College of Physical Scientists and Engineers in Medicine.)

DNA logic gated operations empower the highly efficient analysis of multiplex nucleic acid inputs, which have attracted extensive attention. However, the integration of DNA logic gates with abundant computational functions and signal amplification for biomedical diagnosis is far from being fully achieved. Herein, we develop a bipedal DNA walker based amplified electrochemical method for miRNA detection, which is then used as the basic unit for the construction of various logic circuits, enabling the analysis of multiplex miRNAs. In the bipedal walking process, target triggered strand displacement polymerization is able to produce a large number of strands for the fabrication of three-way junction-structured bipedal walkers. The following catalytic hairpin assembly ensures the walking event and the immobilization of signal probes for output. Ultrahigh sensitivity is realized due to the integration of dual signal amplification. In addition, under logic function controls by input triggered cascade strand displacement reactions, NOT, AND, OR, NAND, NOR, XOR, and XNOR logic gates are successfully established. The as-developed DNA logic system can also be extended to multi-input modes, which holds great promise in the fields of DNA computing, multiplex analysis, and clinical diagnosis., Competing Interests: The authors declare no competing financial interest., (© 2021 The Authors. Published by American Chemical Society.)

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.

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., (© 2020 Wiley-VCH GmbH.)

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.

Structured illumination microscopy (SIM) has become a widely used tool for insight into biomedical challenges due to its rapid, long-term, and super-resolution (SR) imaging. However, artifacts that often appear in SIM images have long brought into question its fidelity, and might cause misinterpretation of biological structures. We present HiFi-SIM, a high-fidelity SIM reconstruction algorithm, by engineering the effective point spread function (PSF) into an ideal form. HiFi-SIM can effectively reduce commonly seen artifacts without loss of fine structures and improve the axial sectioning for samples with strong background. In particular, HiFi-SIM is not sensitive to the commonly used PSF and reconstruction parameters; hence, it lowers the requirements for dedicated PSF calibration and complicated parameter adjustment, thus promoting SIM as a daily imaging tool.

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.

miRNAs, a class of endogenous noncoding RNAs, are involved in many crucial biological processes, which have emerged as a new set of biomarkers for disease theranostics. Exploring efficient signal amplification strategy is highly desired to pursue a highly sensitive miRNA biosensing platform. DNA nanotechnology shows great promise in the fabrication of amplified miRNA biosensors. In this work, a novel DNA walking and rolling nanomachine is developed for highly sensitive and selective detection of miRNA. Particularly, this approach programs two forms of dynamic DNA nanomachines powered by corresponding enzymes, which are well integrated. It is able to achieve a limit of detection as low as 39 × 10 -18 m, along with excellent anti-interfering performance and clinical applications. In addition, by designing pH-controlled detachable intermolecular DNA triplex, the main sensing elements can be conveniently reset, which fulfills the requirements of point-of-care profiling of miRNA. The high consistency between the proposed approach and quantitative real-time polymerase chain reaction validates the robustness and reliability. Therefore, it is anticipated that the DNA walking and rolling nanomachine has attractive application prospects in miRNA assay for biological researches and clinical diagnosis., (© 2020 Wiley-VCH GmbH.)

Most of the current circulating tumor cell (CTC) isolation techniques are based on immunomagnetic beads with antibodies or aptamers that specifically target epithelial cell adhesion molecules (EpCAMs). However, these techniques are unsuitable for the isolation and purification of circulating tumor cells because they fail to recognize EpCAM-negative CTCs and thus lead to the non-specific adsorption of background leucocytes and EpCAM-positive circulating epithelial cells. Moreover, releasing the CTCs from the capture platform without disruption is a big challenge. To address these issues, herein, we developed biomimetic magnetic beads (MBs) by cloaking a cancer cell-leukocyte hybrid membrane on the MBs. These biomimetic MBs inherited homologous CTC binding capability from the cancer cell membrane and less affinity for the background cells from the leukocyte membrane, exhibitng a higher CTC capture efficiency and separation purity than EpCAM-based MBs. Importantly, the captured CTCs could be rapidly released by a facile method i.e. co-incubation with a trypsin-EDTA solution. We demonstrated the excellent performance of these MBs for the highly pure separation and non-destructive release of CTCs in metastatic mammary carcinoma models. Our results indicate that the proposed homologous cancer-leukocyte membrane coating strategy may provide a promising method for the ultrahigh-specific and sensitive detection of CTCs.

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, MnO 2 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.

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.

Objectives: The evaluation of lymph node (LN) status by radiologists based on preoperative computed tomography (CT) lacks high precision for early lung cancer patients; erroneous evaluations result in inappropriate therapeutic plans and increase the risk of complications. This study aims to develop a cross-modal 3D neural network based on CT images and prior clinical knowledge for accurate prediction of LN metastasis in clinical stage T1 lung adenocarcinoma., Patients and Methods: Five hundred one lung adenocarcinoma patients with clinical stage T1 were enrolled. Data including: corresponding 3D nodule-centered patches of CT; prior clinical features; and pathological labels of LN status were obtained. We proposed a cross-modal deep learning system, which can successfully incorporate prior clinical knowledge and CT images into a 3D neural network to predict LN metastasis. We trained and validated our system with 401 cases and tested its performance with 100 cases. The result was compared with that of the logistic regression integration model, the single deep learning model without prior clinical knowledge integration, radiomics method, and manual evaluation by radiologists., Results: The model proposed DensePriNet achieved an AUC of 0.926, which is significantly higher than the logistic regression integration model (0.904) single deep learning model (0.880), and radiomics method (0.891). The Matthews Correlation Coefficient (MCC) of DensePriNet (0.705) was significantly higher than manual classification by one senior radiologist (0.534) and one junior radiologist (0.416), respectively., Conclusion: The performance of the single deep learning method is significantly higher than the radiomics method and the radiologists, and integration of prior clinical knowledge into the deep learning model enhance the diagnostic precision of LN status and facilitate the application of precision medicine., Competing Interests: Declaration of Competing Interest All authors have declared no conflicts of interest., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Immunomagnetic beads are important tools for the isolation and detection of circulating tumor cells (CTCs). However, the current immunomagnetic bead technique provides poor CTC separation purity due to nonspecific binding of background cells. Furthermore, immunomagnetic beads have not been appropriately functionalized for enabling CTC analysis and quantification. In this work, bimetallic magnetic gold nanoparticles were prepared and coated with leukocyte membranes to form leukocyte membrane-camouflaged nanoparticles. After conjugation with the antibody of epithelial cell adhesion molecule (EpCAM), the biomimetic immunomagnetic gold nanoparticles (CM-Fe 3 O 4 @Au-Ab) showed a high specific recognition ability on mock (EpCAM-positive) CTCs and a reduced interaction with leukocytes. We subsequently optimized the conditions for CTC separation, including the concentration of nanoparticles and the incubation time. Under the optimized conditions, CM-Fe 3 O 4 @Au-Ab exhibited high CTC capture efficiency with negligible background cell binding in mock clinical blood samples. More importantly, gold probes were tagged on the surface of these separated CTCs. When coupled with ICP-MS analysis, the number of CTCs and gold signals exhibited a good linear relationship, and a low limit of detection was obtained, enabling us to estimate the number of CTCs in blood samples. Hence, we expected that CM-Fe 3 O 4 @Au-Ab could provide an opportunity to surmount the limitations of current CTC detection.

Background: Accurate lymph nodes (LNs) assessment is important for rectal cancer (RC) staging in multiparametric magnetic resonance imaging (mpMRI). However, it is incredibly time-consumming to identify all the LNs in scan region. This study aims to develop and validate a deep-learning-based, fully-automated lymph node detection and segmentation (auto-LNDS) model based on mpMRI., Methods: In total, 5789 annotated LNs (diameter ≥ 3 mm) in mpMRI from 293 patients with RC in a single center were enrolled. Fused T2-weighted images (T2WI) and diffusion-weighted images (DWI) provided input for the deep learning framework Mask R-CNN through transfer learning to generate the auto-LNDS model. The model was then validated both on the internal and external datasets consisting of 935 LNs and 1198 LNs, respectively. The performance for LNs detection was evaluated using sensitivity, positive predictive value (PPV), and false positive rate per case (FP/vol), and segmentation performance was evaluated using the Dice similarity coefficient (DSC)., Findings: For LNs detection, auto-LNDS achieved sensitivity, PPV, and FP/vol of 80.0%, 73.5% and 8.6 in internal testing, and 62.6%, 64.5%, and 8.2 in external testing, respectively, significantly better than the performance of junior radiologists. The time taken for model detection and segmentation was 1.3 s/case, compared with 200 s/case for the radiologists. For LNs segmentation, the DSC of the model was in the range of 0.81-0.82., Interpretation: This deep learning-based auto-LNDS model can achieve pelvic LNseffectively based on mpMRI for RC, and holds great potential for facilitating N-staging in clinical practice., (Copyright © 2020 The Authors. Published by Elsevier B.V. All rights reserved.)

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 Fe 3 O 4 @Au nanoparticles. A limit of detection down to 6/μL is obtained with excellent selectivity.

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 developed a bright carbon nanodot-based miRNA detection method with signal amplification by concatenated hybridization chain reaction (CHCR). In the presence of target miRNA, CHCR was triggered and a frond-like DNA product was formed, which recovered remarkable fluorescence. The location and level of the target miRNA were then indicated.

Sensitive and accurate quantification of circulating tumor cell (CTC) can provide new insights for early diagnosis and prognosis of cancers. Herein, we have developed a multipedal DNA walker for ultrasensitive detection of CTC for the first time. Generally, a number of walker strands are simply modified on gold nanoparticle (AuNPs). The integrated aptamer sequence can specially interact with the transmembrane receptor protein of CTC and facilitate the enrichment of AuNPs on the surface of cells. After a low speed centrifugation, the complex of CTC and AuNPs could be precipitated and the supernate represents decreased UV-vis absorbance response of AuNPs. On the other hand, since multiple walker strands are modified on a single AuNP, hybridization with several tracks on the electrode occurs simultaneously for the following nicking endonuclease-catalyzed cleaving. Experimental results verify that the rate of multipedal walking is much faster. In addition, TCEP-mediated electrochemical amplification is employed to further enhance the electrochemical signal. By comparing the variations of electrochemical and UV-vis absorbance responses, ultrahigh sensitivity for CTC assay is achieved. The limit of detection is down to 1 cell/mL. The results of selectivity confirmation and blood sample test are also satisfactory. This AuNPs-based multipedal DNA walker offers a speedy analysis of CTC and shows great potential use for early clinical diagnosis and treatment of cancers.

In this study, gene expression alterations of phase I to III enzymes, transcription factors, and microRNA (miRNA) in embryonic zebrafish fibroblasts (ZF4) cells after the treatment of Pb(NO 3 ) 2 and AgNO 3 were investigated, to illustrate the possible detoxification pathway of heavy metal ions. It was observed that both metals caused concentration-dependent death and moderate elevation of oxidative stress in ZF4 cells. In response to such toxicity, upregulation of multidrug resistance protein (mdr)4 and multiresistance-associated protein (mrp)1 were found. However, enhanced expression of glutathione S-transferase (gst) and cytochrome P450 (cyp)1a could only be detected during the exposure of Pb 2+ . In addition, both metals induced extensive upregulation of pregnane X receptor (pxr), but only moderate elevation of E2-related factor (nrf2), while they suppressed the expression of miR-122 and miR-126. In conclusion, Pb 2+ and Ag + shared the same detoxification mechanism including ABC transporters, Pxr, and miRNA in ZF4 cells, which needs further investigation., (© 2019 Wiley Periodicals, Inc.)

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.

Objectives: To evaluate the efficiency of radiomics model on CT images of intratumoral and peritumoral lung parenchyma for preoperative prediction of lymph node (LN) metastasis in clinical stage T1 peripheral lung adenocarcinoma patients., Methods: Three hundred sixty-six peripheral lung adenocarcinoma patients with clinical stage T1 were evaluated using five CT scanners. For each patient, two volumes of interest (VOIs) on CT were defined as the gross tumor volume (GTV) and the peritumoral volume (PTV, 1.5 cm around the tumor). One thousand nine hundred forty-six radiomic features were obtained from each VOI, and then refined for reproducibility and redundancy. The refined features were investigated for usefulness in building radiomic signatures by mRMR feature ranking method and LASSO classifier. Multivariable logistic regression analysis was used to develop a radiomic nomogram incorporating the radiomic signature and clinical parameters. The prediction performance was evaluated on the validation cohort., Results: The radiomic signatures using the features of GTV and PTV showed a good ability in predicting LN metastasis with an AUC of 0.829 (95% CI, 0.745-0.913) and 0.825 (95% CI, 0.733-0.918), respectively. By incorporating the features of GTV and PTV, the AUC of radiomic signature increased to 0.843 (95% CI, 0.770-0.916). The AUC of radiomic nomogram was 0.869 (95% CI, 0.800-0.938)., Conclusions: Radiomic signatures of GTV and PTV both had a good prediction ability in the prediction of LN metastasis, and there is no significant difference of AUC between the two groups. The proposed nomogram can be conveniently used to facilitate the preoperative prediction of LN metastasis in T1 peripheral lung adenocarcinomas., Key Points: • Radiomics from peritumoral lung parenchyma increase the efficiency of the prediction for lymph node metastasis in clinical stage T1 lung adenocarcinoma on CT. • A radiomic nomogram was developed and validated to predict LN metastasis. • Different scan parameters on CT showed that radiomics signature had good predictive performance.

Circulating tumor DNA (ctDNA) is a tumor-derived fragmented DNA in the bloodstream that is not associated with cells. It has been greatly focused in the recent decade because of its potential clinical utility for liquid biopsies. Development of ctDNA analytical techniques with high sensitivity and cost-efficiency will undoubtedly promote the clinical spread of ctDNA testing. In this paper, we propose a novel flow cytometry-based ctDNA sensing strategy which combines enzyme-free amplification and magnetic separation. The target DNA is capable of triggering a hybridization chain reaction, producing a fluorescent long linear assembly of DNA, which can be further captured by magnetic beads to present fluorescent signals using flow cytometry. In comparison with some conventional methods, our strategy has the advantages of easy operation and cost-efficiency, and thereby shows a promising application in clinical diagnosis. Graphical abstract.

A concept for position adjustment of the diamond in a ruling engine to enable nanoscale groove positioning is proposed. Based on this concept, we fabricate a diamond carriage, design an optical path, and propose an appropriate control method. Several high-quality gratings are ruled for spectrometer or interferometer applications. After implementation of the improvements, the maximum intensity of ghosts and scattered light of the echelle grating with 79 grooves/mm is reduced to half of that before the improvement, and the highest achievable groove density is increased from 6000 grooves/mm to 8000 grooves/mm. The grating ruling results indicate that the proposed concept and the related improvements to the engine significantly improve the accuracy of the CIOMP-6 ruling engine.

There is an increasing demand to establish a convenient and stable analytical methodology for screening multiplex tumor markers in early diagnosis of cancers. In this work, an innovative fluorescence method is proposed for simultaneous detection of alpha-fetoprotein (AFP) and carcinoembryonic antigen (CEA). A polydopamine nanosphere@silver nanocluster (PDAN@AgNC) system is introduced for fluorescence quenching and recovery. The AgNCs with different emissions are synthesized using different DNA templates, which also contain aptamer sequences towards AFP and CEA, respectively. These single-stranded DNA sequences could be adsorbed on the surface of the PDAN through π-π stacking, which results in the quenching of AgNCs. However, in the presence of the corresponding tumor marker, the aptamer/target complex forms which releases AgNCs from the surface of the PDAN and the recovered fluorescence could be used to indicate the concentration of the tumor marker. This PDAN@AgNC system has been validated preliminarily to screen human serum samples with excellent results. Taking advantages of simplicity, enzyme/antibody-free nature, low cost and convenient operation, the proposed biosensor has great potential to be used in biomedical research studies and clinical diagnosis.

Telomerase catalyzes the elongation of telomeres, which is closely associated with tumorigenesis. Therefore, development of reliable and convenient methods for telomerase activity analysis is critical for clinical diagnosis of cancers. However, most of the current probes for intracellular telomerase activity assay suffer from inevitable false-positive interferences. In this study, we have proposed a novel fluorescence resonance energy transfer (FRET)-based strategy for ultrasensitive monitoring intracellular telomerase activity with an amplification-free procedure. DNA nanoprobes constructed using a DNA tetrahedron and Flare DNA are designed to circumvent the problem of false-positive interference. Generally, telomerase catalyzes DNA extension and changes the configuration of the DNA nanoprobe, which finally leads to the increase of the distance between two labelled fluorophores. Based on the notably decreased FRET efficiency, a simple ratiometric sensor is established for the detection of telomerase activity at the single-cell level, which is much suitable for clinical applications. In addition, this method can be further applied in the detection of telomerase inhibitors, which is important for anti-cancer drug discovery.

Herein, a novel electrochemical biosensor for sensitive analysis of prostate specific antigen (PSA) is demonstrated. A specific peptide is employed on the gold electrode as a molecular recognition element for target induced cleavage. In the absence of PSA, graphene oxide (GO) is directly immobilized on the peptide modified electrode, which triggers the aggregation of silver ions and subsequent reduction reaction to form silver nanoparticles (AgNPs). Well defined sharp silver stripping peak can thus be achieved, which stands for a highly characteristic solid-state Ag/AgCl reaction. However, in the presence of PSA, the peptide is specifically recognized and cleaved. The resulted product on the electrode surface cannot aid the immobilization of GO and subsequent formation of AgNPs. Therefore, electrochemical response is decreased remarkably, which can be used to indicate the concentration of PSA. This work demonstrates that the combination of the transduction of peptide cleavage event with GO/AgNPs nanocomposites is a promising attempt for PSA analysis with high sensitivity and selectivity., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Auricularia auricula-judae is an edible mushroom and a traditional medicine in China as well as the fourth largest cultivated mushroom species in the world. Here for the first time, we present comparative transcriptome analyses of the fruiting bodies of three morphologically distinguishable A. auricula-judae cultivated varieties (Wujin, smooth; Banjin, partially wrinkled; and Quanjin, fully wrinkled) collected from Jilin Province, China. Biological triplicates were performed to determine the expression levels of 13,937 unigenes. Among them, only 13 unigenes were annotated to A. auricula-judae, highlighting the lack of publicly available reference sequences for this economically important species. Principal component analysis (PCA) determined that the gene expression profile of Quanjin was unique when compared to those of Banjin and Wujin. Such relationships were further supported by analyses of annotated and unannotated unigenes, differentially expressed unigenes, gene ontology functions, and the family of peroxidase genes. Using the KEGG database, significant alternations in biological pathways were detected among the three cultivars. This work contributes a large set of A. auricula-judae sequences to public database, establishes the relationships among major cultivars, and provides molecular guidance for breeding and cultivation.

Biological applications of core/shell near-infrared quantum dots (QDs) have attracted broad interest due to their unique optical and chemical properties. Additionally, the use of multifunctional nanomaterials with near-infrared QDs and plasmonic functional nanoparticles are promising for applications in electronics, bioimaging, energy, and environmental-related studies. In this work, we experimentally demonstrate how to construct a multifunctional nanoparticle comprised of CdSe/ZnS QDs and gold nanorods (GNRs) where the GNRs were applied to enhance the photoluminescence (PL) of the CdSe/ZnS QDs. In particular, we have obtained the scattering PL spectrum of a single CdSe/ZnS QD and GNR@CdSe/ZnS nanoparticle and comparison results show that the CdSe/ZnS QDs have an apparent PL enhancement of four-times after binding with GNRs. In addition, in vitro experimental results show that the biostability of the GNR@CdSe/ZnS nanoparticles can be improved by using folic acid. A bioimaging study has also been performed where GNR@CdSe/ZnS nanoparticles were used as an optical process for MCF-7 breast cancer cells.