IEEE Transactions on NanoBioscience最新文献_第4页

A Novel Method to Accelerate the Phagocytosis of Saccharomyces cerevisiae by Macrophages Based on Optically Induced Dielectrophoresis 基于光诱导介电泳的巨噬细胞加速酿酒酵母吞噬的新方法。

IF 4.2 4区生物学

IEEE Transactions on NanoBioscience Pub Date : 2026-07-01 Epub Date: 2026-01-21 DOI: 10.1109/TNB.2026.3656608

Mingao Du;Lixiang Zheng;Fei Liu;Na Liu;Gongxin Li

{"title":"A Novel Method to Accelerate the Phagocytosis of Saccharomyces cerevisiae by Macrophages Based on Optically Induced Dielectrophoresis","authors":"Mingao Du;Lixiang Zheng;Fei Liu;Na Liu;Gongxin Li","doi":"10.1109/TNB.2026.3656608","DOIUrl":"10.1109/TNB.2026.3656608","url":null,"abstract":"<italic>Saccharomyces cerevisiae (<italic>S. cerevisiae) can be used to treat diarrhea and the diseases associated with malaria, but it may cause invasive infections in individuals with weakened immune systems. While antibiotics are available for treating these infections, they can also produce side effects in the body. Additionally, macrophages in the human immune system can engulf infected <italic>S. cerevisiae, but they have some limitations, including a relatively weak active chemotactic response and a prolonged engulfing process. To address this, this paper proposes a novel method to enhance the phagocytosis of <italic>S. cerevisiae by macrophages using optically induced dielectrophoresis (ODEP). ODEP is a cellular micromanipulation technique that directs phagocytes towards <italic>S. cerevisiae cells, significantly improving phagocytosis efficiency. Furthermore, the optical electrodes created by ODEP expedite the phagocytosis process. To validate this approach, the optimal operating parameters for ODEP were determined through a combination of numerical simulations and experiments, enabling the swift and precise capture of phagocytes targeting <italic>S. cerevisiae. A comparative experiment was conducted to assess macrophage phagocytosis of <italic>S. cerevisiae with and without the aid of optical electrodes. Results showed that the time required for macrophages to engulf <italic>S. cerevisiae was reduced by 50%, highlighting a promising method for the early prevention or accelerated treatment of invasive <italic>S. cerevisiae fungal infections.","PeriodicalId":13264,"journal":{"name":"IEEE Transactions on NanoBioscience","volume":"25 3","pages":"301-311"},"PeriodicalIF":4.2,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146018427","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Unified Analysis of Spatio-Temporal Anomalous Diffusion for Nano-Bio Molecular Communication 纳米生物分子通信时空异常扩散的统一分析。

IF 4.2 4区生物学

IEEE Transactions on NanoBioscience Pub Date : 2026-07-01 Epub Date: 2026-03-31 DOI: 10.1109/TNB.2026.3679584

Neha Bhusari;Prabhat Kumar Sharma;Avinash G. Keskar

{"title":"Unified Analysis of Spatio-Temporal Anomalous Diffusion for Nano-Bio Molecular Communication","authors":"Neha Bhusari;Prabhat Kumar Sharma;Avinash G. Keskar","doi":"10.1109/TNB.2026.3679584","DOIUrl":"10.1109/TNB.2026.3679584","url":null,"abstract":"In this paper, we analyze molecular communication (MC) channels governed by spatio-temporal anomalous diffusion (STAD), a phenomenon commonly observed in complex biological environments such as intracellular transport and microfluidic systems. We consider that information molecules (IMs) undergo anomalous diffusion while the mobile nanomachines, transmitter (TX) and passive observer follow Brownian mobility. A unified mathematical framework is developed to characterize this time varying stochastic channel via the channel impulse response (CIR) across diverse observer geometries: point and bar shaped in one-dimensional (1-D) settings, and cuboidal, spherical, and cylindrical in three-dimensional (3-D) environments. Classical diffusion is included as a special case of the STAD model. Performance is evaluated using average error probability (AEP), receiver operating characteristics (ROC), and area under the curve (AUC) metrics to study the impact of mobility and space–time anomalies. Analytical results are validated through Monte Carlo simulations, offering insights relevant to nano-bio communication and drug delivery systems.","PeriodicalId":13264,"journal":{"name":"IEEE Transactions on NanoBioscience","volume":"25 3","pages":"371-380"},"PeriodicalIF":4.2,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147591767","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

MSGTrans: circRNA-Disease Association Prediction With Cluster-Based Negative Sampling and Multi-Scale Graph Transformer 基于聚类负采样和多尺度图转换器的circrna -疾病关联预测。

IF 4.2 4区生物学

IEEE Transactions on NanoBioscience Pub Date : 2026-07-01 Epub Date: 2026-03-31 DOI: 10.1109/TNB.2026.3679349

Jing Yang;Xiujuan Lei

引用次数: 0

IEEE Transactions on NanoBioscience Information for Authors IEEE纳米生物科学信息汇刊

IF 4.2 4区生物学

IEEE Transactions on NanoBioscience Pub Date : 2026-07-01 Epub Date: 2026-07-02 DOI: 10.1109/TNB.2026.3696735

引用次数: 0

IEEE Transactions on NanoBioscience Publication Information IEEE纳米生物科学学报

IF 4.2 4区生物学

IEEE Transactions on NanoBioscience Pub Date : 2026-07-01 Epub Date: 2026-07-02 DOI: 10.1109/TNB.2026.3696731

引用次数: 0

Ion Transmitter for Molecular Communication 用于分子通信的离子传递器。

IF 4.2 4区生物学

IEEE Transactions on NanoBioscience Pub Date : 2026-07-01 Epub Date: 2026-03-23 DOI: 10.1109/TNB.2026.3676352

Shaojie Zhang;Ozgur B. Akan

引用次数: 0

Dispersion Control in Stochastic Biomolecular Systems Without Peak Shifts 无峰移随机生物分子系统的色散控制。

IF 4.2 4区生物学

IEEE Transactions on NanoBioscience Pub Date : 2026-07-01 Epub Date: 2026-03-04 DOI: 10.1109/TNB.2026.3670609

Taishi Kotsuka;Enoch Yeung

{"title":"Dispersion Control in Stochastic Biomolecular Systems Without Peak Shifts","authors":"Taishi Kotsuka;Enoch Yeung","doi":"10.1109/TNB.2026.3670609","DOIUrl":"10.1109/TNB.2026.3670609","url":null,"abstract":"Intracellular biomolecular circuits often exhibit multimodal stationary distributions due to intrinsic noise, and the dispersion around each peak governs phenotypic robustness and adaptability. However, tuning dispersion by changing reaction parameters typically shifts peak positions or even alters modality. In this paper, we derive conditions that enable peak-shape control without peak shifts using the Chemical Fokker-Planck Equation. First, we formalize sharpness as a peak-local measure via probability ratios and show that the positions of peaks and valleys remain invariant as a control parameter varies. Second, we prove that sharpness varies monotonically as the control parameter increases, while the modality and the positions of extrema remain fixed. We validate these results with Monte Carlo simulations of two univariate networks: the burst-and-trickle gene expression system (unimodal) and the Schlögl system (bimodal), achieving dispersion tuning without peak shifts. Finally, we present preliminary multivariate evidence on the Genetic Toggle Switch, where the marginal distribution of one protein exhibits similar sharpness control. Our results provide structural design rules for engineering stochastic phenotypes while safeguarding the desired modal structure.","PeriodicalId":13264,"journal":{"name":"IEEE Transactions on NanoBioscience","volume":"25 3","pages":"340-348"},"PeriodicalIF":4.2,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147354870","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Channel Modeling for Mobile Molecular Communication With Anomalous Diffusion by Deep Neural Network 基于深度神经网络的异常扩散移动分子通信通道建模。

IF 4.2 4区生物学

IEEE Transactions on NanoBioscience Pub Date : 2026-07-01 Epub Date: 2026-01-19 DOI: 10.1109/TNB.2026.3654966

Zhen Cheng;Miaodi Chen;Ming Xia;Qu Li;Kaikai Chi;Xinwei Yao

{"title":"Channel Modeling for Mobile Molecular Communication With Anomalous Diffusion by Deep Neural Network","authors":"Zhen Cheng;Miaodi Chen;Ming Xia;Qu Li;Kaikai Chi;Xinwei Yao","doi":"10.1109/TNB.2026.3654966","DOIUrl":"10.1109/TNB.2026.3654966","url":null,"abstract":"Diffusion-based mobile molecular communication (MMC) systems have shown great potential in nanoscale communication, particularly in the scenarios involving anomalous diffusion. Accurately modeling the anomalous diffusion channel of MMC system with multiple receivers is a challenge. However, prior studies have predominantly addressed conventional analytical approaches to characterize the channel impulse response (CIR) of static molecular communication system under normal diffusion channel. However, the deduction method cannot adapt to time-varying and complex channel conditions. In this paper, we study a three dimensional MMC system with one transmitter and multiple receivers under anomalous diffusion channel. We propose a method based on deep neural network (DNN) to predict the parameters of the CIR of this MMC system. Simulation results demonstrate that the prediction ability of DNN-based model outperforms the recurrent neural networks (RNN) based and the long short-term memory (LSTM) based models in terms of prediction ability under different anomalous diffusion conditions. The DNN-based model can effectively improve the accuracy of predicting the CIR for this MMC system, providing a new approach for channel modeling in MMC systems with anomalous diffusion.","PeriodicalId":13264,"journal":{"name":"IEEE Transactions on NanoBioscience","volume":"25 3","pages":"289-300"},"PeriodicalIF":4.2,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146003267","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Recent Advancements and Emerging Trends in Biosensors: A Review on Disease Diagnosis and Personalized Medicine 生物传感器的最新进展和新趋势：疾病诊断和个性化医疗综述。

IF 4.2 4区生物学

IEEE Transactions on NanoBioscience Pub Date : 2026-07-01 Epub Date: 2026-02-16 DOI: 10.1109/TNB.2026.3664930

Vivek Arya;Dharmendra Kumar;Vijay Shanker Chaudhary;Smita Kumari;Anupam Sahu;Sneha Sharma;Ragini Singh

{"title":"Recent Advancements and Emerging Trends in Biosensors: A Review on Disease Diagnosis and Personalized Medicine","authors":"Vivek Arya;Dharmendra Kumar;Vijay Shanker Chaudhary;Smita Kumari;Anupam Sahu;Sneha Sharma;Ragini Singh","doi":"10.1109/TNB.2026.3664930","DOIUrl":"10.1109/TNB.2026.3664930","url":null,"abstract":"Recent research advances and developments in biosensor technology and an overview of its innovative applications for the healthcare industry are reviewed in this article. Biosensors can monitor and detect a variety of biological and chemical characteristics with accuracy and less or minimal invasiveness. It can be classified depending upon their working principle and transducing property, like electrochemical, optical, and piezoelectric processes, and are deployed for various medical applications discussed in this article. This paper provides a brief review of the novel applications of biosensors in healthcare, including illness diagnosis, medication development, and personalized medicine. Difficulties in healthcare biosensor technology as well as the future directions for research and development is highlighted. The fundamental elements of biosensors, their types—such as electrochemical, piezoelectric, thermometric, and optical—as well as current developments in the area, operating theories, and their potential applications, have been covered. This article provides a thorough understanding of the most current advancements in biosensor technology for healthcare and how they may further enhance outcomes and treatment for patients.","PeriodicalId":13264,"journal":{"name":"IEEE Transactions on NanoBioscience","volume":"25 3","pages":"332-339"},"PeriodicalIF":4.2,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146206650","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Automation of Fluorescence-Activated Droplet Release by Deep-Learning-Based Droplet Detector 基于深度学习的荧光激活液滴检测器自动释放液滴。

IF 4.2 4区生物学

IEEE Transactions on NanoBioscience Pub Date : 2026-07-01 Epub Date: 2026-01-19 DOI: 10.1109/TNB.2026.3655030

Guangyao Cheng;Yi-Ping Ho

{"title":"Automation of Fluorescence-Activated Droplet Release by Deep-Learning-Based Droplet Detector","authors":"Guangyao Cheng;Yi-Ping Ho","doi":"10.1109/TNB.2026.3655030","DOIUrl":"10.1109/TNB.2026.3655030","url":null,"abstract":"Droplet-based microfluidics enables miniaturized, high-throughput biochemical assays but faces challenges in selective droplet retrieval, particularly after long-term monitoring. While light-induced bubble generation offers a promising, hardware-simplified strategy for releasing individual droplets from passive traps, current implementations suffer from fabrication complexity or slow-release kinetics. To overcome these limitations, we previously developed a light-responsive fluorosurfactant using fluorinated plasmonic nanoparticles (f-PNPs) that enables millisecond-scale vapor bubble formation and efficient droplet release using a 532 nm laser, without requiring integrated photothermal materials. However, automation of this approach was limited by the need for manual droplet identification and release decisions. In this work, we introduce a fully automated Fluorescence-Activated Droplet Release (FADR) system by integrating the light-triggered release mechanism with a deep-learning-based droplet detector. This AI module autonomously identifies and localizes droplets in real-time, triggering selective release based on fluorescence intensity without human intervention. The closed-loop FADR platform offers a scalable and intelligent solution for precise droplet manipulation, enabling robust, high-throughput screening workflows with minimal hardware complexity.","PeriodicalId":13264,"journal":{"name":"IEEE Transactions on NanoBioscience","volume":"25 3","pages":"271-277"},"PeriodicalIF":4.2,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11358754","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146003246","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0