Two Decades' advancements and Research trends in needle-type Sensor technology: A scientometric analysis.

Needle-type sensor, characterized by its slender, elongated shape, is a promising sensing method due to its rapid response, high sensitivity, and portability. Recently, the needle-type sensor technology has garnered increasing attention, leading to its accelerated development and extensive use in medical and healthcare, environmental monitoring, and geosciences. However, there remains a need for a comprehensive review of existing research. Here, we utilize scientometric analysis, which is booming recently, to conduct a comprehensive investigation of the needle-type sensor field. This analysis covers various aspects, including annual trends, journals, institutions, countries, disciplines, authors, references, and keywords of 136,667 publications from the Web of Science Core Collection (WoSCC) database spanning from January 1, 2004, to January 1, 2024. Additionally, we identify current hotspots, frontiers, and predict future trends. Eventually, three research hotspots are refined: multidisciplinary materials science, sensor miniaturization and integration, and biomedical engineering, indicating that further investigations may focus on creating biocompatible materials to enhance sensing properties, optimizing sensor structure through miniaturization and integration methods, and improving clinical applications in biomedical engineering. This work may facilitate the development of needle-type sensors.

Correction: Immunoassay-aptasensor for the determination of tumor-derived exosomes based on the combination of magnetic nanoparticles and hybridization chain reaction.

[This corrects the article DOI: 10.1039/D0RA10159A.].

Efficacy and safety of acupressure in nausea and vomiting during pregnancy: a systematic review and meta-analysis of randomized controlled trials.

OBJECTIVE: The purpose of this study was to evaluate the efficacy and safety of acupressure on nausea and vomiting during pregnancy. METHODS: PubMed, Embase, Springer, Web of Science, and the Cochrane Library were searched for all randomized controlled trials (RCT) of treating nausea and vomiting during pregnancy by acupressure from the inception date of database to July 31st, 2023. Study selection, data extraction, and risk of bias assessment were conducted independently by researchers. The methodological quality of included studies was evaluated by the Cochrane Collaboration's bias risk assessment tool, meta-analysis by Stata 17.0 software, and publication bias by Begg's test. RESULTS: A total of 11 RCTs involving 1378 pregnant women were included in this review, which was assessed to be moderate quality. 10 RCTs involving 1298 pregnant women were assessed for the meta-analysis. The results revealed that acupressure showed significant difference on improvement in symptom score compared with sham acupressure (pooled MD, - 1.33; 95%CI [- 2.06, - 0.61]; P < 0.001) or control group (pooled MD, - 0.73; 95%CI [- 1.08, - 0.39]; P < 0.001), and incidence of effective rate compared with sham acupressure group (pooled RR, 1.78; 95%CI [1.03, 3.07]; P = 0.039). However, no statistical significance was found between acupressure and control group (pooled RR, 4.53; 95%CI [0.67, 30.48]; P = 0.120) on effective rate. On comparing acupressure with sham acupressure, there was no beneficial effect on preventing nausea and vomiting during pregnancy (pooled RR, 0.83; 95%CI [0.50, 1.38]; P = 0.476), shortening the duration of hospital stay (pooled MD, - 0.78; 95%CI [- 1.98, 0.41]; P = 0.199) and improving patient satisfaction (pooled RR, 1.36; 95%CI [0.47, 3.91]; P = 0.570). Begg's test did not reveal any publication bias. Only one RCT reported minimal acupressure-related adverse events. CONCLUSION: Acupressure may have potential favorable or encouraging effect on treating nausea and vomiting during pregnancy, but strong supportive data are not yet available. Well-designed and large-scale RCTs should be conducted for assessing and confirming the efficacy and safety of acupressure in nausea and vomiting during pregnancy.

The effects of reflexology on symptoms in pregnancy: A systematic review of randomized controlled trials.

Objective: This review assessed the effects of reflexology on symptoms in pregnancy. Methods and analysis: PubMed, Embase, Springer, Web of Science, the Cochrane Library, and reference lists of previous systematic reviews were searched for the eligible randomized controlled trials (RCT) from the inception date of each predefined database up to May 31st, 2023. Data were extracted, and methodological quality was evaluated by the Revised Cochrane risk-of-bias tool for randomized trials (RoB 2). The efficacy of treatment was assessed using pooled effect sizes (Hedges' g) and 95% confidence intervals (CI). Meta-analysis was performed using the RevMan 5.4 manager, and publication bias was evaluated by Begg's test. Results: The included a total of 13 RCTs in this review, of eleven was high risk of bias and two were low, reported the effects of reflexology on low back and/or pelvic pain (LBPP), labor pain, duration of labor, anxiety, fatigue, sleep quality, constipation symptoms, and ankle and foot edema in pregnancy. The effect sizes (Hedges' g) for reflexology in labor pain, duration of labor, anxiety, fatigue, and sleep quality showed statistical significance, which the meta-analysis also confirmed except for fatigue and sleep quality due to insufficient studies. Conclusion: Reflexology is probably effective and safe for labor pain, duration of labor, and anxiety in pregnancy, while the evidences for reflexology in LBPP, fatigue, sleep quality, constipation symptoms, and ankle and foot edema during pregnancy were insufficient. Based on the low to high quality of included studies, strong supportive evidence is not yet available. Rigorous-design and large-scale clinical trials should be conducted to provide higher-quality, reliable evidence.

The cognitive dysfunction of claustrum on Alzheimer's disease: A mini-review.

Alzheimer's disease (AD) is one of the most common neurodegenerative diseases characterized by cognitive deficits and dementia. AD entails predominant pathological characteristics including amyloid beta (Aß) plaque formation, neurofibrillary entanglements, and brain atrophy, which gradually result in cognitive dysfunctions. Studies showed that these pathological changes are found in a myriad of brain structures, including the claustrum (CLA), a nucleus that penetrates deeply into the brain and is extensively interconnected to various brain structures. The CLA modulates many aspects of cognitive functions, with attention, executive function, visuospatial ability, language, and memory in particular. It is also implicated in multiple neuropsychiatric disorders, of which one worthy of particular attention is AD-related cognitive impairments. To inspire novel AD treatment strategies, this review has summarized the CLA functionality in discriminative cognitive dysfunctions in AD. And then propose an array of potential mechanisms that might contribute to the cognitive impairments caused by an abnormal CLA physiology. We advocate that the CLA might be a new promising therapeutic target in combination with existing anti-AD drugs and brain stimulation approaches for future AD treatment.

CSDR Coupling with Exo III for Ultrasensitive Electrochemistry Determination of miR-145.

Recently, miRNAs have become a promising biomarker for disease diagnostics. miRNA-145 is closely related to strokes. The accuracy determination of miRNA-145 (miR-145) in stroke patients still remains challenging due to its heterogeneity and low abundance, as well as the complexity of the blood matrix. In this work, we developed a novel electrochemical miRNA-145 biosensor via subtly coupling the cascade strand displacement reaction (CSDR), exonuclease III (Exo III), and magnetic nanoparticles (MNPs). The developed electrochemical biosensor can quantitatively detect miRNA-145 ranging from 1 × 102 to 1 × 106 aM with a detection limit as low down as 100 aM. This biosensor also exhibits excellent specificity to distinguish similar miRNA sequences even with single-base differences. It has been successfully applied to distinguish healthy people from stroke patients. The results of this biosensor are consistent with the results of the reverse transcription quantitative polymerase chain reaction (RT-qPCR). The proposed electrochemical biosensor has great potential applications for biomedical research on and clinical diagnosis of strokes.

Identification and quantification of nine compounds in Fangwen Jiuwei decoction by liquid chromatography-mass spectrometry.

Fangwen Jiuwei Decoction is a traditional Chinese medicine preparation for the treatment of pneumonia developed by Shenzhen Bao'an Chinese Medicine Hospital, which shows remarkable clinical responses. Qualitative and quantitative analyses of the main active compounds are crucial for the quality control of traditional Chinese medicine prescription in clinical application. In this study, we identified nine active compounds essential for the pharmacological effects of Fangwen Jiuwei Decoction based on the analysis of the Network Pharmacology and relevant literature. Moreover, these compounds can interact with several crucial drug targets in pneumonia based on molecular docking. We applied high-performance liquid chromatography-tandem mass spectrometry method was established these nine active ingredients' qualitative and quantitative detections. The possible cleavage pathways of nine active components were determined based on secondary ions mass spectrometry. The results of high-performance liquid chromatography-tandem mass spectrometry were further validated, which show a satisfactory correlation coefficient (r > 0.99), recovery rate (≥93.31%), repeatability rate (≤5.62%), stability (≤7.95%), intra-day precision (≤6.68%), and inter-day precision (≤9.78%). The limit of detection was as low as 0.01 ng/ml. In this study, we established a high-performance liquid chromatography-tandem mass spectrometry method to qualitatively and quantitatively analyze the chemical components in the Fangwen Jiuwei Decoction extract.

ESCNet: An End-to-End Superpixel-Enhanced Change Detection Network for Very-High-Resolution Remote Sensing Images.

Change detection (CD), as one of the central problems in Earth observation, has attracted a lot of research interest over recent decades. Due to the rapid development of satellite sensors in recent years, we have witnessed an enrichment of the CD source data with the availability of very-high-resolution (VHR) multispectral imagery, which provides abundant change clues. However, precisely locating real changed areas still remains a challenge. In this article, we propose an end-to-end superpixel-enhanced CD network (ESCNet) for VHR images, which combines differentiable superpixel segmentation and a deep convolutional neural network (DCNN). Two weight-sharing superpixel sampling networks (SSNs) are tailored for the feature extraction and superpixel segmentation of bitemporal image pairs. A UNet-based Siamese neural network is then employed to mine the different information. The superpixels are then leveraged to reduce the latent noise in the pixel-level feature maps while preserving the edges, where a novel superpixelation module is used to serve this purpose. Furthermore, to compensate for the dependence on the number of superpixels, we propose an innovative adaptive superpixel merging (ASM) module, which has a concise form and is fully differentiable. A pixel-level refinement module making use of the multilevel decoded features is also appended to the end of the framework. Experiments on two public datasets confirmed the superiority of ESCNet compared to the traditional and state-of-the-art (SOTA) deep learning-based CD (DLCD) methods.

Isoginkgetin, a potential CDK6 inhibitor, suppresses SLC2A1/GLUT1 enhancer activity to induce AMPK-ULK1-mediated cytotoxic autophagy in hepatocellular carcinoma.

Isoginkgetin (ISO), a natural biflavonoid, exhibited cytotoxic activity against several types of cancer cells. However, its effects on hepatocellular carcinoma (HCC) cells and mechanism remain unclear. Here, we revealed that ISO effectively inhibited HCC cell proliferation and migration in vitro. LC3-II expression and autophagosomes were increased under ISO treatment. In addition, ISO-induced cell death was attenuated by treatment with chloroquine or knockdown of autophagy-related genes (ATG5 or ULK1). ISO significantly suppressed SLC2A1/GLUT1 (solute carrier family 2 member 1) expression and glucose uptake, leading to activation of the AMPK-ULK1 axis in HepG2 cells. Overexpression of SLC2A1/GLUT1 abrogated ISO-induced autophagy. Combining molecular docking with thermal shift analysis, we confirmed that ISO directly bound to the N terminus of CDK6 (cyclin-dependent kinase 6) and promoted its degradation. Overexpression of CDK6 abrogated ISO-induced inhibition of SLC2A1/GLUT1 transcription and induction of autophagy. Furthermore, ISO treatment significantly decreased the H3K27ac, H4K8ac and H3K4me1 levels on the SLC2A1/GLUT1 enhancer in HepG2 cells. Finally, ISO suppressed the hepatocarcinogenesis in the HepG2 xenograft mice and the diethylnitrosamine+carbon tetrachloride (DEN+CCl4)-induced primary HCC mice and we confirmed SLC2A1/GLUT1 and CDK6 as promising oncogenes in HCC by analysis of TCGA data and human HCC tissues. Our results provide a new molecular mechanism by which ISO treatment or CDK6 deletion promotes autophagy; that is, ISO targeting the N terminus of CDK6 for degradation inhibits the expression of SLC2A1/GLUT1 by decreasing the enhancer activity of SLC2A1/GLUT1, resulting in decreased glucose levels and inducing the AMPK-ULK1 pathway.

Improving physicochemical properties and pharmacological activities of ternary co-amorphous systems.

The formation of co-amorphous by combining low molecular weight compounds with drugs is a relatively new technology in the pharmaceutical field, which can significantly improve the solubility, dissolution, and stability of poorly water-soluble drugs. However, in our previous studies, the binary co-amorphous system of andrographolide-oxymatrine (AP-OMT) was found to have obvious recrystallization and poor dissolution behavior. Therefore, in this study, we designed three stable ternary co-amorphous systems to improve the physicochemical properties of the binary co-amorphous system of AP-OMT. The ternary co-amorphous systems were prepared with AP, OMT, and trans-cinnamic acid (CA), p-hydroxycinnamic acid (pHCA), or ferulic acid (FA). Intermolecular hydrogen bonds were confirmed by spectroscopy and molecular dynamics simulation. Solubility studies showed that the solubility of the ternary co-amorphous systems of AP-OMT-CA/pHCA/FA was significantly increased compared with that of crystalline AP. Dissolution experiments suggested that the ternary co-amorphous systems of AP-OMT-CA/pHCA/FA exhibited better dissolution behavior without significant recrystallization compared to the binary co-amorphous AP-OMT. The stability study confirmed that the ternary co-amorphous system of AP-OMT-CA/pHCA/FA maintained good physical stability in the long term for 18 months. In addition, pharmacological experiments revealed that the ternary co-amorphous systems of AP-OMT-CA/pHCA/FA have an excellent safety profile and its anti-Alzheimer's disease effects are significantly improved compared to that of the binary co-amorphous systems of AP-OMT. Moreover, this study also found that reducing the pKa value of low molecular weight co-formers would affect the intermolecular interactions and improve the solubility of drugs in the ternary co-amorphous systems. In conclusion, we have successfully prepared ternary co-amorphous systems of AP-OMT-CA/pHCA/FA by amorphization technique, which improves the physicochemical properties of the binary co-amorphous systems of AP-OMT and anti-Alzheimer's disease activity in the Caenorhabditis elegans model. The mechanism for the influence of the pKa value of the co-formers on the physicochemical properties of the ternary co-amorphous system was preliminarily explored, providing theoretical guidance for the development of the ternary co-amorphous system.

Hider: A Hyperspectral Image Denoising Transformer With Spatial-Spectral Constraints for Hybrid Noise Removal.

Hyperspectral image (HSI) qualities are limited by a mixture of Gaussian noise, impulse noise, stripes, and deadlines during the sensor imaging process, resulting in weak application performance. To enhance HSI qualities, methods based on convolutional neural networks have been successively applied to restore clean data from the observed data. However, the architecture of these methods lacks spectral and spatial constraints, and the convolution operators have limited receptive fields and inflexible model inferences. Thus, in this study, we propose an efficient end-to-end transformer, named HSI denoising transformer (Hider), for mixed HSI noise removal. First, a U-shaped 3-D transformer architecture is built for multiscale feature aggregation. Second, a multihead global spectral attention module within the spectral transformer block is designed to excavate information in different spectral patterns. Finally, an additional locally enhanced cross-spatial attention module within the spatial-spectral transformer block is constructed to build the long-range spatial relationship to avoid the high computational complexity of global spatial self-attention. Through the imposition of global correlations along spectrum and spatial self-similarity constraints on the transformer, our proposed Hider aims to capture long-range spatial contextual information and cluster objects with the same spectral pattern for HSI denoising. To verify the effectiveness and efficiency of Hider, we conducted extensive simulated and real experiments. The denoising results on both simulated and real-world datasets show that Hider achieves superior evaluation metrics and visual assessments compared with other state-of-the-art methods.

Determination of six core components from Mahuang Xuanfei Zhike syrup in rat plasma and tissues by UPLC-MS/MS: Application to a pharmacokinetics and tissue distribution study.

Mahuang Xuanfei Zhike (MXZ) syrup, a Chinese patent medicine, has been widely used in the clinical treatment of cough. However, there is no reported method for the quantitative analysis of the effective components of MXZ syrup in biological samples. In this study, the effective components of MXZ syrup were screened by network pharmacology and molecular docking technology. A sensitive and rapid ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method was established to test the active components of MXZ syrup in rat plasma and tissue homogenates, including ephedrine, amygdalin, chlorogenic acid, harpagoside, forsythin and forsythoside A. Chromatographic separation was performed on a Waters Acquity UPLC HSS T3 column (2.1 × 50 mm, 1.8 µm) and the mass analysis was conducted using a Waters Xevo TQ mass spectrometer using multiple reaction positive and negative ion simultaneous monitoring mode. The results showed that the linearity ranged from 0.3 to 409.4 ng/ml. The extraction recoveries were all <8.33%, and the matrix effects were all <8.45, which met the requirements. The pharmacokinetic and tissue distribution results indicated that the main active components of MXZ syrup were absorbed quickly and eliminated slowly in vivo, and there may be a reabsorption process.

Efficacy and Safety of Apatinib plus Neoadjuvant Chemotherapy for Locally Advanced Esophageal Squamous Cancer: A Phase II Trial.

Evidence for neoadjuvant chemotherapy combined with targeted therapy for locally advanced esophageal squamous cancer (ESCC) is inadequate. We conducted a single-arm phase II trial to evaluate the efficacy and safety of apatinib combined with taxol and cisplatin (ATP) for locally advanced ESCC. All patients were cT3-4aN0-3 M0 (IIIb-IVa) stage, which were confirmed by histopathology. Apatinib was taken orally (425 mg/d) for two cycles, followed by one cycle of rest. Taxol was administered at 135 mg/m2 intravenously on day 1, and cisplatin was administered at 20 mg/m2 intravenously on day 1 to day 3. Radical ESCC resection was performed 4 weeks after ATP. The primary endpoint was pathological response rate (pCR). Secondary endpoints were pathologic response rate (MPR), disease-free survival (DFS), overall survival (OS), R0 resection rate, and safety profile. This trial was registered. We evaluated 41 patients for screening from Oct 2018 to July 2020, of whom 39 were enrolled in the study, with a median age of 65 years (range 49-75 years), and 29 (74.4%) were male. Among the 39 patients, 1 was considered unresectable by the multidisciplinary team due to tumor progression, and 38 patients underwent surgery eventually. The median follow-up was 22 months (range 5-29 months), and the follow-up rate was 100%. The 1-year and 2-year OS was 95% and 95%, and the 1-year and 2-year DFS was 85% and 82%, respectively. Thirty-eight (97.3%) successfully underwent R0 resection. Of the 38 evaluable patients, 9 (23.6%) were pCR, and 15 (39.5%) were MPR. The most common ATP-related AEs were nausea (76.9%), leucopenia (53.8%), neutropenia (51.2%) and vomit (51.2%), anemia (41.0%), and hypertension (25.6%). The most frequent grade 3-4 events included leucopenia (15.3%), neutropenia (15.3%), nausea (12.8%), vomit (12.8%), and hypertension (10.2%). No treatment-related death occurred. Neoadjuvant apatinib combined with taxol and cisplatin for locally advanced ESCC showed favorable activity and manageable safety.

Anti-Alzheimer's disease active components screened out and identified from Hedyotis diffusa combining bioaffinity ultrafiltration LC-MS with acetylcholinesterase.

ETHNOPHARMACOLOGICAL RELEVANCE: Hedyotis diffusa is a traditional ethnomedicinal plant in local communities in northeastern Asia and used to treat inflammation, nervous breakdown, among others. In recent years, it has been applied in the treatment of Alzheimer's disease (AD), while the specific chemical components responsible for the activity remain need to be explored. AIM OF THE STUDY: To prepare, screen and identify the potential anti-AD active components from Hedyotis diffusa. MATERIALS AND METHODS: The acetylcholinesterase (AChE) inhibitory activity of four different extracts of Hedyotis diffusa were initially assessed using a spectrophotometric Ellman's method. A more accurate LC-MS/MS screening method combining functional enzyme assay and affinity ultrafiltration (AU) screening assay was developed and applied for the screening of natural compound inhibitors of AChE from Hedyotis diffusa. The binding mode was further investigated between protein and ligands via molecular docking. Subsequently, CL4176, a transgenic nematode model for AD, was used for activity validation of one of these components. RESULTS: N-butanol extract of Hedyotis diffusa (NHD) appeared significant inhibitory activities on AChE, were chosen to delve deeper. Five bioactive components targeting AChE were screened out and identified using AU coupled to liquid chromatography-mass spectrometry. Molecular docking technique further confirmed the results of the screening assay. Finally, quercetin-3-O-sophoroside (QS) was confirmed as a potent anti-AD agent by in vivo experiments in C. elegans. CONCLUSION: This study explores a new idea for screening anti-AD active components from traditional medicine. The findings provide a molecular structure and bioactivity basis for future potential applications of Hedyotis diffusa in medical industries.

Transition Is a Process: Pair-to-Video Change Detection Networks for Very High Resolution Remote Sensing Images.

As an important yet challenging task in Earth observation, change detection (CD) is undergoing a technological revolution, given the broadening application of deep learning. Nevertheless, existing deep learning-based CD methods still suffer from two salient issues: 1) incomplete temporal modeling, and 2) space-time coupling. In view of these issues, we propose a more explicit and sophisticated modeling of time and accordingly establish a pair-to-video change detection (P2V-CD) framework. First, a pseudo transition video that carries rich temporal information is constructed from the input image pair, interpreting CD as a problem of video understanding. Then, two decoupled encoders are utilized to spatially and temporally recognize the type of transition, and the encoders are laterally connected for mutual promotion. Furthermore, the deep supervision technique is applied to accelerate the model training. We illustrate experimentally that the P2V-CD method compares favorably to other state-of-the-art CD approaches in terms of both the visual effect and the evaluation metrics, with a moderate model size and relatively lower computational overhead. Extensive feature map visualization experiments demonstrate how our method works beyond making contrasts between bi-temporal images. Source code is available at https://github.com/Bobholamovic/CDLab.

A Local-Global Dual-Stream Network for Building Extraction From Very-High-Resolution Remote Sensing Images.

Buildings constitute one of the most important landscapes in remote sensing (RS) images and have been broadly analyzed in a wide range of applications from urban planning to other socioeconomic studies. As very-high-resolution (VHR) RS imagery becomes more accessible, the current building extraction methods are confronted with the challenges of the diverse appearances, various scales, and complicated structures of buildings in complex scenes. With the development of context-aware deep learning methods, it has been proven by numerous works that capturing contextual information can offer spatial relation cues for robust recognition and detection of the objects. In this article, we propose a novel local-global dual-stream network (DS-Net) that adaptively captures local and long-range information for the accurate mapping of building rooftops in VHR RS images. The local branch and the global branch of DS-Net work in a complementary manner to each other with different fields of view on the input image. Through a well-defined dual-stream architecture, DS-Net learns hierarchical representations for both the local and global branches, and a deep feature sharing strategy is further developed to enforce more collaborative integration of the two branches. Extensive experiments were carried out to verify the effectiveness of our model on three widely used VHR RS data sets: the Massachusetts buildings data set, the Inria Aerial Image Labeling data set, and the DeepGlobe Building Detection Challenge data set. Empirically, the proposed DS-Net achieves competitive or superior performance compared with the current state-of-the-art methods in terms of quantitative measures and visual evaluations.

LR-Net: Low-Rank Spatial-Spectral Network for Hyperspectral Image Denoising.

Due to the physical limitations of the imaging devices, hyperspectral images (HSIs) are commonly distorted by a mixture of Gaussian noise, impulse noise, stripes, and dead lines, leading to the decline in the performance of unmixing, classification, and other subsequent applications. In this paper, we propose a novel end-to-end low-rank spatial-spectral network (LR-Net) for the removal of the hybrid noise in HSIs. By integrating the low-rank physical property into a deep convolutional neural network (DCNN), the proposed LR-Net simultaneously enjoys the strong feature representation ability from DCNN and the implicit physical constraint of clean HSIs. Firstly, spatial-spectral atrous blocks (SSABs) are built to exploit spatial-spectral features of HSIs. Secondly, these spatial-spectral features are forwarded to a multi-atrous block (MAB) to aggregate the context in different receptive fields. Thirdly, the contextual features and spatial-spectral features from different levels are concatenated before being fed into a plug-and-play low-rank module (LRM) for feature reconstruction. With the help of the LRM, the workflow of low-rank matrix reconstruction can be streamlined in a differentiable manner. Finally, the low-rank features are utilized to capture the latent semantic relationships of the HSIs to recover clean HSIs. Extensive experiments on both simulated and real-world datasets were conducted. The experimental results show that the LR-Net outperforms other state-of-the-art denoising methods in terms of evaluation metrics and visual assessments. Particularly, through the collaborative integration of DCNNs and the low-rank property, the LR-Net shows strong stability and capacity for generalization.

A highly sensitive electrochemical aptasensor for vascular endothelial growth factor detection based on toehold-mediated strand displacement reaction.

An electrochemical aptasensor with high sensitivity, specificity, and good intra-day reproducibility is reported to meet the detection needs of vascular endothelial growth factor (VEGF). The toehold-mediated strand displacement recycling amplification and VEGF aptamer are integrated in the biosensor. The probe A is hybridized with the VEGF aptamer to form the probe A-aptamer complex. When VEGF is introduced, the aptamer specifically binds with VEGF, and probe A can be liberated. Then, the free probe A captures the toehold region of the Hp1, leading the exposure of the toehold region on the other end of Hp1. Similarly, Hp2 and Hp3 are also immobilized on the surface of the electrode; thus, the methylene blue labelled on Hp2 and Hp3 causes the current response. With the signal transduction mechanism, the expression level of VEGF can be detected quantitatively. With a series of optimizations of sensor parameters, high sensitivity and specificity of the VEGF detection sensor can be achieved with a detection limit as low as 10 pg mL-1. This significant performance has good intra-day reproducibility, and it can be applied to human biological samples such as serum, urine, and saliva to detect the VEGF content.

Determination of miRNA derived from exosomes of prostate cancer via toehold-aided cyclic amplification combined with HRP enzyme catalysis and magnetic nanoparticles.

MicroRNAs (miRNAs) play a significant role in tumorigenesis and tumor development. Exosomal microRNA-141 (miRNA-141, miR-141) has been reported to be overexpressed in prostate cancer (PCa) and has become a potential biomarker for the diagnosis of PCa. Herein, a novel fluorescent biosensor based on toehold-aided cyclic amplification combined with horseradish peroxidase (HRP) enzyme catalysis and magnetic nanoparticles (MNPs) was designed for determination of the exosomes-derived microRNA-141 (miRNA-141, miR-141). The synergy of HRP enzyme catalysis and toehold mediated strand display reaction (TSDR) increase the sensitivity of the method, and the good separation ability of MNPs ensures the specificity of the method. Therefore, under the optimized experimental conditions, the highly sensitive and specific detection of miRNA-141 can be realized, and the detection limit is as low as 10 fM. More importantly, the biosensor successfully determinates the exosomal miR-141 in the plasma of patients with PCa.