AFEI: adaptive optimized vertical federated learning for heterogeneous multi-omics data integration.

Vertical federated learning has gained popularity as a means of enabling collaboration and information sharing between different entities while maintaining data privacy and security. This approach has potential applications in disease healthcare, cancer prognosis prediction, and other industries where data privacy is a major concern. Although using multi-omics data for cancer prognosis prediction provides more information for treatment selection, collecting different types of omics data can be challenging due to their production in various medical institutions. Data owners must comply with strict data protection regulations such as European Union (EU) General Data Protection Regulation. To share patient data across multiple institutions, privacy and security issues must be addressed. Therefore, we propose an adaptive optimized vertical federated-learning-based framework adaptive optimized vertical federated learning for heterogeneous multi-omics data integration (AFEI) to integrate multi-omics data collected from multiple institutions for cancer prognosis prediction. AFEI enables participating parties to build an accurate joint evaluation model for learning more information related to cancer patients from different perspectives, based on the distributed and encrypted multi-omics features shared by multiple institutions. The experimental results demonstrate that AFEI achieves higher prediction accuracy (6.5% on average) than using single omics data by utilizing the encrypted multi-omics data from different institutions, and it performs almost as well as prognosis prediction by directly integrating multi-omics data. Overall, AFEI can be seen as an efficient solution for breaking down barriers to multi-institutional collaboration and promoting the development of cancer prognosis prediction.

DNA Nanostructure Disintegration-Assisted SPAAC Ligation for Electrochemical Biosensing.

MicroRNAs (MiRNAs) are valuable biomarkers for the diagnosis and prognosis of diseases. The development of reliable assays is an urgent pursuit. We herein fabricate a novel electrochemical sensing strategy based on the conformation transitions of DNA nanostructures and click chemistry. Duplex-specific nuclease (DSN)-catalyzed reaction is first used for the disintegration of the DNA triangular pyramid frustum (DNA TPF). A DNA triangle is formed, which in turn assists strain-promoted alkyne-azide cycloaddition (SPAAC) to localize single-stranded DNA probes (P1). After SPAAC ligation, multiple DNA hairpins are spontaneously folded, and the labeled electrochemical species are dragged near the electrode interface. By recording and analyzing the responses, a highly sensitive electrochemical biosensor is established, which exhibits high sensitivity and reproducibility. Clinical applications have been verified with good stability. This sensing strategy relies on the integration of DNA nanostructures and click chemistry, which may inspire further designs for the development of DNA nanotechnology and applications in clinical chemistry.

An uncertainty-based interpretable deep learning framework for predicting breast cancer outcome.

BACKGROUND: Predicting outcome of breast cancer is important for selecting appropriate treatments and prolonging the survival periods of patients. Recently, different deep learning-based methods have been carefully designed for cancer outcome prediction. However, the application of these methods is still challenged by interpretability. In this study, we proposed a novel multitask deep neural network called UISNet to predict the outcome of breast cancer. The UISNet is able to interpret the importance of features for the prediction model via an uncertainty-based integrated gradients algorithm. UISNet improved the prediction by introducing prior biological pathway knowledge and utilizing patient heterogeneity information. RESULTS: The model was tested in seven public datasets of breast cancer, and showed better performance (average C-index = 0.691) than the state-of-the-art methods (average C-index = 0.650, ranged from 0.619 to 0.677). Importantly, the UISNet identified 20 genes as associated with breast cancer, among which 11 have been proven to be associated with breast cancer by previous studies, and others are novel findings of this study. CONCLUSIONS: Our proposed method is accurate and robust in predicting breast cancer outcomes, and it is an effective way to identify breast cancer-associated genes. The method codes are available at: https://github.com/chh171/UISNet .

The management of non-culprit vessel(s) in patients with unstable angina/non-ST elevation myocardial infarction and chronic kidney dysfunction.

BACKGROUND AND AIMS: The clinical effects of multivessel interventions in patients with unstable angina/non-ST-segment elevation myocardial infarction (UA/NSTEMI), multivessel disease (MVD) and chronic kidney disease (CKD) remain uncertain. This study aimed to investigate the safety and effectiveness of intervention in non-culprit lession(s) among this cohort. METHODS: We consecutively included patients diagnosed with UA/NSTEMI, MVD and CKD between January 2008 and December 2018 at our centre. After successful percutaneous coronary intervention (PCI), we compared 48-month overall mortality between those undergoing multivessel PCI (MV-PCI) through a single-procedure or staged-procedure approach and culprit vessel-only PCI (CV-PCI) after 1:1 propensity score matching. We conducted stratified analyses and tests for interaction to investigate the modifying effects of critical covariates. Additionally, we recorded the incidence of contrast-induced nephropathy (CIN) to assess the perioperative safety of the two treatment strategies. RESULTS: Of the 749 eligible patients, 271 pairs were successfully matched. Those undergoing MV-PCI had reduced all-cause mortality (hazard ratio (HR): 0.67, 95% confidence interval (CI): 0.48-0.67). Subgroup analysis showed that those with advanced CKD (estimated glomerular filtration rate (eGFR) ≤ 30 mL/min/1.73 m2 ) could not benefit from MV-PCI (P = 0.250), and the survival advantage also tended to diminish in diabetes (P interaction < 0.01; HR = 0.95, 95% CI = 0.65-1.45). Although the staged-procedure approach (N = 157) failed to bring additional survival benefits compared to single-procedure MV-PCI (N = 290) (P = 0.460), it showed a tendency to decrease the death risk. CIN risks in MV-PCI and CV-PCI groups were not significantly different (risk ratio = 1.60, 95% CI = 0.94-2.73). CONCLUSION: Among patients with UA/NSTEMI and non-diabetic CKD and an eGFR > 30 mL/min/1.73 m2 , MV-PCI was associated with a reduced risk of long-term death but did not increase the incidence of CIN during the management of MVD compared to CV-PCI. And staged procedures might be a preferable option over single-procedure MV-PCI.

Analyzing the topological properties of resting-state brain function network connectivity based on graph theoretical methods in patients with high myopia.

AIM: Recent imaging studies have found significant abnormalities in the brain's functional or structural connectivity among patients with high myopia (HM), indicating a heightened risk of cognitive impairment and other behavioral changes. However, there is a lack of research on the topological characteristics and connectivity changes of the functional networks in HM patients. In this study, we employed graph theoretical analysis to investigate the topological structure and regional connectivity of the brain function network in HM patients. METHODS: We conducted rs-fMRI scans on 82 individuals with HM and 59 healthy controls (HC), ensuring that the two groups were matched for age and education level. Through graph theoretical analysis, we studied the topological structure of whole-brain functional networks among participants, exploring the topological properties and differences between the two groups. RESULTS: In the range of 0.05 to 0.50 of sparsity, both groups demonstrated a small-world architecture of the brain network. Compared to the control group, HM patients showed significantly lower values of normalized clustering coefficient (γ) (P = 0.0101) and small-worldness (σ) (P = 0.0168). Additionally, the HM group showed lower nodal centrality in the right Amygdala (P < 0.001, Bonferroni-corrected). Notably, there is an increase in functional connectivity (FC) between the saliency network (SN) and Sensorimotor Network (SMN) in the HM group, while the strength of FC between the basal ganglia is relatively weaker (P < 0.01). CONCLUSION: HM Patients exhibit reduced small-world characteristics in their brain networks, with significant drops in γ and σ values indicating weakened global interregional information transfer ability. Not only that, the topological properties of the amygdala nodes in HM patients significantly decline, indicating dysfunction within the brain network. In addition, there are abnormalities in the FC between the SN, SMN, and basal ganglia networks in HM patients, which is related to attention regulation, motor impairment, emotions, and cognitive performance. These findings may provide a new mechanism for central pathology in HM patients.

Effects of photoperiod and temperature on the developmental duration and diapause in Dolycoris baccarum (Heteroptera: Pentatomidae) from Hohhot, Inner Mongolia, China.

The shield bug, Dolycoris baccarum (L.) (Heteroptera: Pentatomidae), is widely distributed across Asia and Europe. At high latitudes, it overwinters, as adult in diapause, which then becomes the insect source for the following year. To fully understand the developmental duration and diapause characteristics of D. baccarum, the effects of photoperiod and temperature were studied in a population from Hohhot, Inner Mongolia, China. The results indicated that the developmental duration was significantly prolonged at temperatures of 20 or 25 °C, with a prolonged light period; however, when the light period was prolonged to 16L:8D and 18L:6D, the developmental duration was shortened significantly. Furthermore, the developmental duration was also shortened significantly with increasing temperature, when the photoperiod was 12L:12D for short days and 16L:8D for long days. All individuals entered diapause under short-day conditions of 10L:14D and 12L:12D at a temperature of 20 °C; however, the diapause rate decreased significantly under 14L:10D and 16L:8D photoperiods, and the diapause rate decreased significantly at a temperature of 25 °C with prolonged photoperiod. Interestingly, when the photoperiod was fixed at 12L:12D, the diapause rates at different temperatures (20, 25, 28, and 30 °C) exceeded 95%; while the effect of temperature on diapauses was nonsignificant under this photoperiod, it was still sensitive to the photoperiod; at a photoperiod of 16L:8D, the effect of temperature on the diapause rate was noticeable, and the diapause rate decreased significantly with increasing temperature.

Experimental Research on Shipborne SINS Rapid Mooring Alignment with Variance-Constraint Kalman Filter and GNSS Position Updates.

Analytical coarse alignment and Kalman filter fine alignment based on zero-velocity are typically used to obtain initial attitude for inertial navigation systems (SINS) on a static base. However, in the shipboard mooring state, the static observation condition is corrupted. This paper presents a rapid alignment method for SINS on swaying bases. The proposed method begins with a coarse alignment technique in the inertial frame to obtain an initial rough attitude. Subsequently, a Kalman filter with position updates is employed to estimate the remaining misalignment error. To enhance the filter estimation performance, an appropriate lower boundary is set to the target states' variances according to a carefully designed relative convergence index. The variance-constraint Kalman filter (VCKF) approach is proposed in this paper, and the shipborne experiments validate its effectiveness. The results demonstrate that the VCKF approach significantly reduces the time requirement for fine alignment to achieve the same accuracy on a swaying base, from 90 min in the classic Kalman filter to 30 min. Additionally, the parameter estimation performance in the Kalman filter is also improved, particularly in situations where unpredicted external interference is involved during fine alignment.

Predictive value of metabolism and its heterogeneity parameters measured by preoperative 18 F-FDG PET/CT for mediastinal occult lymph node metastasis in cN0 lung invasive adenocarcinoma.

OBJECTIVE: To explore the potential of intratumoral metabolism and its heterogeneous parameters, as measured by preoperative fluorine-18-fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) imaging, to predict mediastinal occult lymph node metastasis in cN0 lung invasive adenocarcinoma. SUBJECTS AND METHODS: Seventy five patients were consecutively enrolled from January 2018 to December 2022. All patients underwent 18F-FDG PET/CT scans within two weeks before surgery, and had mediastinal lymph node metastasis confirmed by pathologic diagnosis after surgery. Metabolic parameters including the maximum standardized uptake value (SUVmax), mean SUV (SUVmean), maximum average SUV (SUVpeak), tumor metabolic volume (MTV), and metabolic heterogeneity (HF) were measured. The relationship between primary focal metabolism, its heterogeneity parameters, and occult mediastinal lymph node metastasis was analyzed using an independent-sample t-test, analysis of covariance, and Mann-Whitney U test. A multivariate logistic regression model was used to analyze independent risk factors for mediastinal lymph node metastasis, while the receiver operating characteristic (ROC) curve assessed the predictive value of metabolic heterogeneity parameters for mediastinal occult lymph node metastasis. RESULTS: A total of 20 out of 75 patients (26.7%) were pathologically confirmed to have mediastinal lymph node metastasis. Analysis of covariance showed that the SUVmax, SUVmean, SUVpeak and MTV were significantly higher in patients with metastasis than in those without (all P<0.05). The metabolic heterogeneity parameters HF2 and HF3 were significantly higher in patients with mediastinal lymph node metastasis than in those without (P=0.013, 0.001), but not HF1. Multivariate Logistic regression analysis identified that tumor size, SUVmax, SUVpeak, lymph node SUVmax, and HF2 of the primary tumor as independent risk factors for mediastinal lymph node metastasis. Metabolic heterogeneity 3 demonstrated high predictive value for mediastinal occult lymph node metastasis (AUC=0.720, P=0.004). CONCLUSION: Metabolism and heterogeneity, as measured by preoperative 18F-FDG PET/CT in lung invasive adenocarcinoma, potentially have clinical value for predicting mediastinal occult lymph node metastasis.

Irregular DNA Triangular Prism/Triplex Assembly for Duplicate MiRNA Analysis with Nicking Endonuclease-Mediated Amplification.

Highly sensitive and selective detection of microRNA (miRNA) is becoming more and more important in the discovery, diagnosis, and prognosis of various diseases. Herein, we develop a three-dimensional DNA nanostructure based electrochemical platform for duplicate detection of miRNA amplified by nicking endonuclease. Target miRNA first helps construction of three-way junction structures on the surfaces of gold nanoparticles. After nicking endonuclease-powered cleavage reactions, single-stranded DNAs labeled with electrochemical species are released. These strands can be facilely immobilized at four edges of the irregular triangular prism DNA (iTPDNA) nanostructure via triplex assembly. By evaluating the electrochemical response, target miRNA levels can be determined. In addition, the triplexes can be disassociated by simply changing pH conditions, and the iTPDNA biointerface can be regenerated for duplicate analyses. The developed electrochemical method not only exhibits an excellent prospect in the detection of miRNA but also may inspire the engineering of recyclable biointerfaces for biosensing platforms.

scAdapt: virtual adversarial domain adaptation network for single cell RNA-seq data classification across platforms and species.

In single cell analyses, cell types are conventionally identified based on expressions of known marker genes, whose identifications are time-consuming and irreproducible. To solve this issue, many supervised approaches have been developed to identify cell types based on the rapid accumulation of public datasets. However, these approaches are sensitive to batch effects or biological variations since the data distributions are different in cross-platforms or species predictions. In this study, we developed scAdapt, a virtual adversarial domain adaptation network, to transfer cell labels between datasets with batch effects. scAdapt used both the labeled source and unlabeled target data to train an enhanced classifier and aligned the labeled source centroids and pseudo-labeled target centroids to generate a joint embedding. The scAdapt was demonstrated to outperform existing methods for classification in simulated, cross-platforms, cross-species, spatial transcriptomic and COVID-19 immune datasets. Further quantitative evaluations and visualizations for the aligned embeddings confirm the superiority in cell mixing and the ability to preserve discriminative cluster structure present in the original datasets.

Performance of the Risk Scores for Predicting In-Hospital Mortality in Patients with Acute Coronary Syndrome in a Chinese Cohort.

Background: The prognosis of patients with acute coronary syndrome (ACS) varies greatly, and risk assessment models can help clinicians to identify and manage high-risk patients. While the Global Registry of Acute Coronary Events (GRACE) model is widely used, the clinical pathways for acute coronary syndromes (CPACS), which was constructed based on the Chinese population, and acute coronary treatment and intervention outcomes network (ACTION) have not yet been validated in the Chinese population. Methods: Patients with ACS who underwent coronary angiography or percutaneous coronary intervention from 2011 to 2020, were retrospectively recruited and the appropriate corresponding clinical indicators was obtained. The primary endpoint was in-hospital mortality. The performance of the GRACE, GRACE 2.0, ACTION, thrombolysis in myocardial infarction (TIMI) and CPACS risk models was evaluated and compared. Results: A total of 19,237 patients with ACS were included. Overall, in-hospital mortality was 2.2%. ACTION showed the highest accuracy in predicting discriminated risk (c-index 0.945, 95% confidence interval [CI] 0.922-0.955), but the calibration was not satisfactory. GRACE and GRACE 2.0 did not significantly differ in discrimination (p = 0.1480). GRACE showed the most accurate calibration in all patients and in the subgroup analysis of all models. CPACS (c-index 0.841, 95% CI 0.821-0.861) and TIMI (c-index 0.811, 95% CI 0.787-0.835) did not outperform (c-index 0.926, 95% CI 0.911-0.940). Conclusions: In contemporary Chinese ACS patients, the ACTION risk model's calibration is not satisfactory, although outperformed the gold standard GRACE model in predicting hospital mortality. The CPACS model developed for Chinese patients did not show better predictive performance than the GRACE model.

Ultrasensitive electrochemical detection and inhibition evaluation of DNA methyltransferase based on cascade strand displacement amplification.

An electrochemical sensing approach for ultrasensitive DNA methyltransferase (MTase) activity assay is proposed. After specific cleavage reaction in the presence of a methylated state, strand displacement polymerization (SDP) is initiated in the solution. The product of upstream SDP further triggers downstream SDP, which enriches abundant electrochemical species at the electrode. The whole process is quite convenient with shared enzymes. Due to the cascade signal amplification, ultrahigh sensitivity is promised. Inhibitor screening results are also demonstrated to be good. Besides, target MTase can be accurately determined in human serum samples, confirming excellent practical utility. This work provides a reliable approach for the analysis of MTase activity, which is of vital importance for related biological studies and clinical applications.

DNA-MnO2 Nanoconjugates Investigation and Application for Electrochemical Polymerase Chain Reaction.

Manganese dioxide (MnO2) nanosheets are emerging for biomedical applications with excellent physical and chemical properties. Adsorption of DNA on MnO2 is important for biosensing, bioimaging, and therapy. Nevertheless, current fundamental understanding about the interaction is preliminary. Herein, UV-vis absorption spectra are applied to systematically explore the biointerfacial interaction between DNA and MnO2 with the factors of salt concentration, pH value, temperature, DNA concentration, and length. The results offer important fundamental insights into the investigation of DNA-MnO2 nanocomposites. Meanwhile, the optimal parameters are applied to construct a screen-printed electrode (SPE) modified with polymerase chain reaction (PCR) primer-decorated MnO2 nanosheets. An electrochemical PCR system is then developed for ultrasensitive detection of circulating tumor DNA (ctDNA). The limit of detection is determined to be 0.1 fM, and high selectivity is demonstrated. Combining the merits of SPE, DNA-MnO2 nanosheets, and an amplified reaction, this developed strategy shows great promise in bioanalysis, clinical disease diagnosis, and biomedicine applications.

Tetrahedral DNA Supported Walking Nanomachine for Ultrasensitive miRNA Detection in Cancer Cells and Serums.

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.

Ratiometric Electrochemical Switch for Circulating Tumor DNA through Recycling Activation of Blocked DNAzymes.

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.

Zedoarondiol inhibits atherosclerosis by regulating monocyte migration and adhesion via CXCL12/CXCR4 pathway.

Atherosclerosis (AS) is an essential pathological changes of ischemic cardio-cerebrovascular disease, and monocyte migration and adhesion to endothelial cells are the critical pathological process in AS. Our previous studies demonstrated a beneficial effect of zedoarondiol in AS, but whether the mechanism is associated with monocyte migration and adhesion to endothelial cells remains unclear. In this study, we investigated whether the anti-atherosclerotic effects of zedoarondiol were associated with decreasing migration and adhesion of monocytes. The oil red O staining demonstrated that zedoarondiol ameliorated AS plaques in en face aorta and aortic root of apolipoprotein E gene knocked (apoE-/-) mice. In vitro, zedoarondiol decreased human monocytic macrophage-like cell line (THP-1) monocytes migration and adhesion to endothelial cells. Single-cell RNA sequencing analysis (scRNA-seq) in mice indicated that zedoarondiol decreased monocytes adhesion to endothelial cells by regulating CXC chemokine ligand 12/CXC chemokine receptor 4 (CXCL12/CXCR4) pathway, which was verified by Western blot of THP-1 monocytes；zedoarondiol also decreased the expressions of phosphoinositide 3-kinase (PI3K), protein kinase B (AKT) and nuclear factor-kappa B (NF/κB), the downstream proteins of CXCL12/CXCR4 pathway. In conclusion, zedoarondiol ameliorated AS plaque and inhibited monocyte migration and adhesion to endothelial cells via regulating CXCL12/CXCR4 pathway, suggesting that zedoarondiol might be a new promising drug for AS.

Substance use among adolescents and young adults with chronic kidney disease or kidney failure.

Substance use, a significant public health issue, is well described in the adult chronic kidney disease (CKD) population. Knowledge about substance use in the adolescent and young adult (AYA) CKD population such as prevalence, impact on kidney function, medication adherence, and psychosocial well-being remain largely unknown. Awareness of and inquiring about substance use is paramount to providing evidence-based care and preparation to transition to adult-focused health services. The authors in this review identify commonly used substances (alcohol, tobacco, marijuana, etc.) and how they impact kidney function and care of the AYA with CKD or kidney failure. Recommendations for screening and intervention strategies are provided.

Propofol Affects EGF's Activity in Intestinal Cell by Down-Regulating EGFR-Mediated Intracellular Signaling.

Propofol is a commonly used anesthetic drug in clinic. In recent years, a series of non-anesthetic effects of propofol have been discovered. Studies have shown that propofol has many effects on the intestine. Epidermal growth factor (EGF) is one of the most important growth factors that could regulate intestinal growth and development. In the current study, we studied the effect of protocol on the biological activity of EGF on intestinal tissue and cell models. Through flow cytometry, indirect immunofluorescence and Western-blot and other technologies, it was found that propofol reduced the activity of EGF on intestinal cells, which inhibited EGF-induced intestinal cell proliferation and changed the cell behavior of EGF. To further explore the potential mechanism by which propofol down-regulated epidermal growth factor receptor (EGFR)-induced signaling, we carried out a series of related experiments, and found that propofol may inhibit the proliferation of intestinal cells by inhibiting the EGFR-mediated intracellular signaling pathway. The current research will lay the theoretical and experimental basis for further study of the effect of propofol on the intestine.

Highly Sensitive Genosensing Coupling Rolling Circle Amplification with Multiple DNAzyme Cores for DNA Walking.

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.

Bipedal DNA Walker Based Electrochemical Genosensing Strategy.

DNAs are one of the most fundamental molecules for life. Quantification of specific sequences is of great importance for biological research and clinical diagnosis. In order to determine extremely low abundant DNAs, we herein develop a novel electrochemical genosensor taking advantage of a smart bipedal DNA walking machine. Magnetic nanomaterials are first employed to enrich target DNA. Strand displacement amplification initiated by target DNA is then designed on the surface of the nanomaterials, the products of which can be used to trigger bipedal DNA walking on the surface of an electrode. Benefiting from triple amplification, ultrahigh sensitivity is achieved for electrochemical analysis of DNA. More importantly, the proposed strategy opens a new avenue for employing the bipedal DNA walker for sensitive detection of various biomolecules with signal amplification.