A5101867679- Advanced biosensing and bioanalysis techniques
- Advanced Biosensing Techniques and Applications
- Microfluidic and Bio-sensing Technologies
- Biosensors and Analytical Detection
- Radiomics and Machine Learning in Medical Imaging
- Lung Cancer Diagnosis and Treatment
- Computational Drug Discovery Methods
- Gastric Cancer Management and Outcomes
- Quantum Dots Synthesis And Properties
- Molecular Biology Techniques and Applications
- Analytical Chemistry and Sensors
- Peptidase Inhibition and Analysis
- IoT and Edge/Fog Computing
- Magnetic properties of thin films
- Monoclonal and Polyclonal Antibodies Research
- Gene expression and cancer classification
- Non-Invasive Vital Sign Monitoring
- Microfluidic and Capillary Electrophoresis Applications
- Characterization and Applications of Magnetic Nanoparticles
- Cancer Cells and Metastasis
- AI and Multimedia in Education
- vaccines and immunoinformatics approaches
- Advanced Computing and Algorithms
- Wireless Body Area Networks
- Complement system in diseases
Nanjing University of Posts and Telecommunications
2024
Xuzhou Medical College
2024
Nanjing Normal University
2024
Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application
2024
Pingdingshan University
2013-2021
MagArray (United States)
2008-2021
Stanford University
2007-2021
Cotton (United States)
2021
Nanjing Medical University
2021
Nanjing Drum Tower Hospital
2021
Magnetic nanotags (MNTs) are a promising alternative to fluorescent labels in biomolecular detection assays, because minute quantities of MNTs can be detected with inexpensive giant magnetoresistive (GMR) sensors, such as spin valve (SV) sensors. However, translating this promise into easy use and multilplexed protein which highly sought after molecular diagnostics cancer diagnosis treatment monitoring, has been challenging. Here, we demonstrate multiplex potential markers at subpicomolar...
Abstract Radiographic imaging is routinely used to evaluate treatment response in solid tumors. Current metrics do not reliably predict the underlying biological response. Here, we present a multi-task deep learning approach that allows simultaneous tumor segmentation and prediction. We design two Siamese subnetworks are joined at multiple layers, which enables integration of multi-scale feature representations in-depth comparison pre-treatment post-treatment images. The network trained...
In the current scenario, it is significant to design active learning paradigms for analyzing human activities using Wearable Internet of Things (W-IoT) sensors health parameter analysis. Further, in healthcare sector, data collection decision-making tools uses wearable monitoring Cloud assisted (IoT). Although several conventional algorithms and deep models show promising results sensor analysis recognizing behaviors, evaluation their ambiguity still difficult systems are more complex. Due...
Objective: We aimed to develop a deep learning-based signature predict prognosis and benefit from adjuvant chemotherapy using preoperative computed tomography (CT) images. Background: Current staging methods do not accurately the risk of disease relapse for patients with gastric cancer. Methods: proposed novel neural network (S-net) construct CT predicting disease-free survival (DFS) overall in training cohort 457 patients, independently tested it an external validation 1158 patients. An...
Lung cancer is known to be one of the most dangerous diseases which are main reason for disease and death when diagnosed in primitive stages.Since lung can only detected more broadly after it spread parts occurrence earlier stage very difficult predict.It causes a greater risk as radiologists specialist doctors assess existence cancer.For this reason, important build smart automatic prediction system that accurate at or improve accuracy previous will help determines type treatment depth...
This paper presents an in-depth study and exploration of the health IoT architecture related implementation technologies from both theoretical practical aspects, with important significance application value. The research includes cloud fusion architecture, multimodal information acquisition in perception layer, multi-level service quality assurance based on human LAN, emotional interaction IoT. In terms convergence is proposed to deeply integrate platform layer by integrating multiple...
Lymph node metastasis (LNM) in gastric cancer is a prognostic factor and has implications for the extent of lymph dissection. The lymphatic drainage stomach involves multiple nodal stations with different risks metastases. aim this study was to develop deep learning system predicting LNMs based on preoperative CT images patients cancer.Preoperative from who underwent gastrectomy dissection at two medical centres were analysed retrospectively. Using discovery patient cohort, convolutional...
Direct protein functionalization provides synthetic antiferromagnetic nanoparticles with high chemical specificity and multifunctionality. These nanoparticle-protein conjugates function as improved magnetic labels for biological detection experiments, exhibit tunable responses to a small external field gradient, thus allowing the observation of distinctive single nanoparticle motion.
Giant magnetoresistive (GMR) nanosensors provide a novel approach for measuring protein concentrations in blood medical diagnosis. Using an vivo mouse radiation model, we developed protocols Flt3 ligand (Flt3lg) and serum amyloid A1 (Saa1) small amounts of collected during the first week after X-ray exposures sham, 0.1, 1, 2, 3, or 6 Gy. Flt3lg showed excellent dose discrimination at ≥ 1 Gy time window to 7 days exposure except day 7. Saa1 response was limited two exposure. A multiplex assay...
In order to strengthen school security and build a wireless smart campus, this article optimizes the existing video surveillance system based on Internet of Things. This paper first quality in system, proposes zero-copy buffer strategy, network congestion suppression codec rate coordination strategy. Secondly, for distributed wide area tracking optimization method multi-camera fusion is proposed. Finally, constructs Bayesian monitoring event modeling genetic algorithm. Experimental results...
A DNA microarray of 1008 magnetoresistive sensors employing multidivided array structures for detecting either tow concentration or large-scale gene information is integrated with a 0.25mum BiCMOS chip. The input-referred noise below 55nV/radicHz. Ionic solution interferences and drifts during biological reaction are removed by applying an in-plane AC magnetic field two DC states. Parallel readout realized combining FDM TDM.
A high density GMR sensor array was integrated with a standard CMOS chip for DNA hybridization detection. Absorption of magnetic nanoparticles by the hybridized alters resistance, and generated electrical signals are directly measured on-die circuitry. The proposed biochip can be applied to other bio-reaction detection, e.g. protein assay, through different surface modifications
Urban heat challenges caused by global climate change and urban islands have driven the need for effective mitigation strategies. It is important to evaluate these strategies prior implementation (e.g., through numerical modeling) provide science-based guidance policy decisions. These usually occur at small within a neighborhood) scales, which poses challenge physically based modeling. This study uses Parallelized Large-Eddy Simulation Model (PALM) simulate neighborhood-scale interventions...
Giant magnetoresistive (GMR) sensors are developed for a DNA microarray. Compared with the conventional fluorescent sensors, GMR cheaper, more sensitive, can generate fully electronic signals, and be easily integrated electronics microfluidics. The sensor used in this work has bottom spin valve structure an MR ratio of 12%. single-strand target detected length 20 bases. Assays concentrations down to 10 pM were performed, dynamic range 3 logs. A double modulation technique was signal...
Accumulated evidence suggests that binding kinetic properties—especially dissociation rate constant or drug-target residence time—are crucial factors affecting drug potency. However, quantitative prediction of properties has always been a challenging task in discovery. In this study, the VolSurf method was successfully applied to quantitatively predict koff values small ligands heat shock protein 90α (HSP90α), adenosine receptor (AR) and p38 mitogen-activated kinase (p38 MAPK). The results...
Abstract Background WD40 repeat (WDR)43 is an RNA-binding protein that belongs to the WDR domain family. Its biological function largely unclear, particularly in colorectal cancer (CRC). Methods In present study, we searched TCGA database and found correlation between WDR43 CRC. Subsequently, high expression of human clinical samples CRC was validated further examined functions it cells. Finally, explored potential downstream proteins or pathways established subcutaneous xenograft model...
As the complexity of GIS data continues to increase, there is a growing demand for automated map generalization. end-to-end generative models, GAN models offer new solutions This study explores impact different symbolization configurations on specifically using CycleGAN line feature The quality generated results was assessed by constructing various datasets (line width, type, and color) evaluating CycleGAN’s performance metrics such as MSE, SSIM, PSNR. indicate that moderate widths (0.5–1)...
Flood disasters are among the most severe natural calamities worldwide and typically occur in densely populated areas with abundant lakes high rainfall. These cause significant damage to environment human settlements. Therefore, accurately monitoring understanding occurrence evolution of floods, as well studying influencing factors, is great importance. This study employs CYGNSS satellite data from a constellation small satellites equipped reflective radar, which observe Earth's surface...