Pub Date : 2023-06-28DOI: 10.1109/TNB.2023.3287805
Mohammad Reza Ahmadpour;Mahdi Yousefi;Hassan Rakhshandeh;Majid Darroudi;Seyed Hadi Mousavi;Mohammad Soukhtanloo;Zahra Sabouri;Vahid Reza Askari;Alireza Hashemzadeh;Mohammad Azad Manjiri;Malihe Motavasselian
In this study, gold nanoparticles (Au-NPs) were synthesized using HAuCl4 and quince seed mucilage (QSM) extract, which was characterized by conventional methods including Fourier transforms electron microscopy (FTIR), UV-Visible spectroscopy (UV-Vis), Field emission electron microscopy (FESEM), Transmission electron microscopy (TEM), Dynamic light spectroscopy (DLS), and Zeta-potential. The QSM acted as reductant and stabilizing agents simultaneously. The NP’s anticancer activity was also investigated against osteosarcoma cell lines (MG-63), which showed an IC50 of $317 mu text{g}$ /mL.
{"title":"Biosynthesis of Gold Nanoparticles Using Quince Seed Water Extract and Investigation of Their Anticancer Effect Against Cancer Cell Lines","authors":"Mohammad Reza Ahmadpour;Mahdi Yousefi;Hassan Rakhshandeh;Majid Darroudi;Seyed Hadi Mousavi;Mohammad Soukhtanloo;Zahra Sabouri;Vahid Reza Askari;Alireza Hashemzadeh;Mohammad Azad Manjiri;Malihe Motavasselian","doi":"10.1109/TNB.2023.3287805","DOIUrl":"10.1109/TNB.2023.3287805","url":null,"abstract":"In this study, gold nanoparticles (Au-NPs) were synthesized using HAuCl4 and quince seed mucilage (QSM) extract, which was characterized by conventional methods including Fourier transforms electron microscopy (FTIR), UV-Visible spectroscopy (UV-Vis), Field emission electron microscopy (FESEM), Transmission electron microscopy (TEM), Dynamic light spectroscopy (DLS), and Zeta-potential. The QSM acted as reductant and stabilizing agents simultaneously. The NP’s anticancer activity was also investigated against osteosarcoma cell lines (MG-63), which showed an IC50 of \u0000<inline-formula> <tex-math>$317 mu text{g}$ </tex-math></inline-formula>\u0000/mL.","PeriodicalId":13264,"journal":{"name":"IEEE Transactions on NanoBioscience","volume":"23 1","pages":"118-126"},"PeriodicalIF":3.9,"publicationDate":"2023-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9695453","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}
Pub Date : 2023-06-19DOI: 10.1109/TNB.2023.3287637
Martin Damrath;Mladen Veletić;Hamid Khoshfekr Rudsari;Ilangko Balasingham
Targeted drug delivery is a promising approach for many serious diseases, such as glioblastoma multiforme, one of the most common and devastating brain tumor. In this context, this work addresses the optimization of the controlled release of drugs which are carried by extracellular vesicles. Towards this goal, we derive and numerically verify an analytical solution for the end-to-end system model. We then apply the analytical solution either to reduce the disease treatment time or to reduce the amount of required drugs. The latter is formulated as a bilevel optimization problem, whose quasiconvex/quasiconcave property is proved here. For solving the optimization problem, we propose and utilize a combination of bisection method and golden-section search. The numerical results demonstrate that the optimization can significantly reduce the treatment time and/or the required drugs carried by extracellular vesicles for a therapy compared to the steady state solution.
{"title":"Optimization of Extracellular Vesicle Release for Targeted Drug Delivery","authors":"Martin Damrath;Mladen Veletić;Hamid Khoshfekr Rudsari;Ilangko Balasingham","doi":"10.1109/TNB.2023.3287637","DOIUrl":"10.1109/TNB.2023.3287637","url":null,"abstract":"Targeted drug delivery is a promising approach for many serious diseases, such as glioblastoma multiforme, one of the most common and devastating brain tumor. In this context, this work addresses the optimization of the controlled release of drugs which are carried by extracellular vesicles. Towards this goal, we derive and numerically verify an analytical solution for the end-to-end system model. We then apply the analytical solution either to reduce the disease treatment time or to reduce the amount of required drugs. The latter is formulated as a bilevel optimization problem, whose quasiconvex/quasiconcave property is proved here. For solving the optimization problem, we propose and utilize a combination of bisection method and golden-section search. The numerical results demonstrate that the optimization can significantly reduce the treatment time and/or the required drugs carried by extracellular vesicles for a therapy compared to the steady state solution.","PeriodicalId":13264,"journal":{"name":"IEEE Transactions on NanoBioscience","volume":"23 1","pages":"109-117"},"PeriodicalIF":3.9,"publicationDate":"2023-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9667345","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}
Pub Date : 2023-06-14DOI: 10.1109/TNB.2023.3285973
Song Qiu;Zhuangkun Wei;Yu Huang;Mahmoud Abbaszadeh;Jerome Charmet;Bin Li;Weisi Guo
Molecular networking has been identified as a key enabling technology for Internet-of-Nano-Things (IoNT): microscopic devices that can monitor, process information, and take action in a wide range of medical applications. As the research matures into prototypes, the cybersecurity challenges of molecular networking are now being researched on at both the cryptographic and physical layer level. Due to the limited computation capabilities of IoNT devices, physical layer security (PLS) is of particular interest. As PLS leverages on channel physics and physical signal attributes, the fact that molecular signals differ significantly from radio frequency signals and propagation means new signal processing methods and hardware is needed. Here, we review new vectors of attack and new methods of PLS, focusing on 3 areas: (1) information theoretical secrecy bounds for molecular communications, (2) key-less steering and decentralized key-based PLS methods, and (3) new methods of achieving encoding and encryption through bio-molecular compounds. The review will also include prototype demonstrations from our own lab that will inform future research and related standardization efforts.
{"title":"Review of Physical Layer Security in Molecular Internet of Nano-Things","authors":"Song Qiu;Zhuangkun Wei;Yu Huang;Mahmoud Abbaszadeh;Jerome Charmet;Bin Li;Weisi Guo","doi":"10.1109/TNB.2023.3285973","DOIUrl":"10.1109/TNB.2023.3285973","url":null,"abstract":"Molecular networking has been identified as a key enabling technology for Internet-of-Nano-Things (IoNT): microscopic devices that can monitor, process information, and take action in a wide range of medical applications. As the research matures into prototypes, the cybersecurity challenges of molecular networking are now being researched on at both the cryptographic and physical layer level. Due to the limited computation capabilities of IoNT devices, physical layer security (PLS) is of particular interest. As PLS leverages on channel physics and physical signal attributes, the fact that molecular signals differ significantly from radio frequency signals and propagation means new signal processing methods and hardware is needed. Here, we review new vectors of attack and new methods of PLS, focusing on 3 areas: (1) information theoretical secrecy bounds for molecular communications, (2) key-less steering and decentralized key-based PLS methods, and (3) new methods of achieving encoding and encryption through bio-molecular compounds. The review will also include prototype demonstrations from our own lab that will inform future research and related standardization efforts.","PeriodicalId":13264,"journal":{"name":"IEEE Transactions on NanoBioscience","volume":"23 1","pages":"91-100"},"PeriodicalIF":3.9,"publicationDate":"2023-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10005367","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}
Pub Date : 2023-06-14DOI: 10.1109/TNB.2023.3286269
Rabeya Bosrin Rumi;Alok Kumar Paul;Salem A. Alyami;Mohammad Ali Moni
This research introduces a surface plasmon resonance (SPR)-based biosensor with multilayered structures for telecommunication wavelength in order to detect multiple diseases. The malaria and the chikungunya viruses are taken into account and the presence of these viruses are determined by examining several blood components in healthy and affected phases. Here, two distinct configurations (Al-BTO-Al-MoS2 and Cu-BTO-Cu-MoS2) are proposed and contrasted for the detection of numerous viruses. The performance characteristics of this work have been analyzed using Transfer Matrix Method (TMM) method and Finite Element Method (FEM) method under angle interrogation technique. From the TMM and FEM solutions, it is evident that the Al-BTO-Al-MoS2 structure provides the highest sensitivities of ~270 deg./RIU for malaria and ~262 deg./RIU for chikungunya viruses, with satisfactory detection accuracy of ~1.10 for malaria, ~1.64 for chikungunya, and quality factor of ~204.40 for malaria, ~208.20 for chikungunya. In addition, the Cu-BTO-Cu MoS2 structure offers the highest sensitivities of ~310 deg./RIU for malaria and ~298 deg./RIU for chikungunya, with satisfactory detection accuracy of ~0.40 for malaria, ~0.58 for chikungunya, and quality factor of ~89.85 for malaria, ~86.38 for chikungunya viruses. Therefore, the performance of the proposed sensors is analyzed using two distinct methods and gives around similar results. In a sum, this research could be utilized as a theoretical foundation and first step in the development of a real sensor.
{"title":"Multi-Disease Detection Using a Prism-Based Surface Plasmon Resonance Sensor: A TMM and FEM Approach","authors":"Rabeya Bosrin Rumi;Alok Kumar Paul;Salem A. Alyami;Mohammad Ali Moni","doi":"10.1109/TNB.2023.3286269","DOIUrl":"10.1109/TNB.2023.3286269","url":null,"abstract":"This research introduces a surface plasmon resonance (SPR)-based biosensor with multilayered structures for telecommunication wavelength in order to detect multiple diseases. The malaria and the chikungunya viruses are taken into account and the presence of these viruses are determined by examining several blood components in healthy and affected phases. Here, two distinct configurations (Al-BTO-Al-MoS2 and Cu-BTO-Cu-MoS2) are proposed and contrasted for the detection of numerous viruses. The performance characteristics of this work have been analyzed using Transfer Matrix Method (TMM) method and Finite Element Method (FEM) method under angle interrogation technique. From the TMM and FEM solutions, it is evident that the Al-BTO-Al-MoS2 structure provides the highest sensitivities of ~270 deg./RIU for malaria and ~262 deg./RIU for chikungunya viruses, with satisfactory detection accuracy of ~1.10 for malaria, ~1.64 for chikungunya, and quality factor of ~204.40 for malaria, ~208.20 for chikungunya. In addition, the Cu-BTO-Cu MoS2 structure offers the highest sensitivities of ~310 deg./RIU for malaria and ~298 deg./RIU for chikungunya, with satisfactory detection accuracy of ~0.40 for malaria, ~0.58 for chikungunya, and quality factor of ~89.85 for malaria, ~86.38 for chikungunya viruses. Therefore, the performance of the proposed sensors is analyzed using two distinct methods and gives around similar results. In a sum, this research could be utilized as a theoretical foundation and first step in the development of a real sensor.","PeriodicalId":13264,"journal":{"name":"IEEE Transactions on NanoBioscience","volume":"23 1","pages":"51-62"},"PeriodicalIF":3.9,"publicationDate":"2023-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9853795","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}
Pub Date : 2023-06-12DOI: 10.1109/TNB.2023.3284090
Mohammad Zoofaghari;Fabrizio Pappalardo;Martin Damrath;Ilangko Balasingham
Interactions of cells via extracellular vesicles (EVs) manipulate various actions, including cancer initiation and progression, inflammation, anti-tumor signaling and cell migration, proliferation and apoptosis in the tumor microenvironment. EVs as the external stimulus can activate or inhibit some receptor pathways in a way that amplify or attenuate a kind of particle release at target cells. This can also be carried out in a biological feedback-loop where the transmitter is affected by the induced release initiated by the target cell due to the EVs received from the donor cell, to create a bilateral process. In this paper, at first we derive the frequency response of internalization function in the framework of a unilateral communication link. This solution is adapted to a closed-loop system to find the frequency response of a bilateral system. The overall releases of the cells, given by the combination of the natural release and the induced release, are reported at the end of this paper and the results are compared in terms of distance between the cells and reaction rates of EVs at the cell membranes.
细胞通过胞外囊泡（EVs）的相互作用操纵着各种行为，包括癌症的诱发和发展、炎症、抗肿瘤信号传导以及肿瘤微环境中的细胞迁移、增殖和凋亡。作为外部刺激物，EVs 可以激活或抑制某些受体通路，从而放大或减弱靶细胞中某种粒子的释放。这也可以在一个生物反馈环路中进行，在这个环路中，发射器受到靶细胞从供体细胞接收到的 EVs 引发的诱导释放的影响，从而形成一个双边过程。在本文中，我们首先推导了单边通信链路框架下内化函数的频率响应。我们将这一解决方案应用于闭环系统，以求得双边系统的频率响应。本文最后报告了由自然释放和诱导释放相结合得出的细胞整体释放量，并从细胞间距和细胞膜上的 EV 反应速率方面对结果进行了比较。
{"title":"Modeling Extracellular Vesicles-Mediated Interactions of Cells in the Tumor Microenvironment","authors":"Mohammad Zoofaghari;Fabrizio Pappalardo;Martin Damrath;Ilangko Balasingham","doi":"10.1109/TNB.2023.3284090","DOIUrl":"10.1109/TNB.2023.3284090","url":null,"abstract":"Interactions of cells via extracellular vesicles (EVs) manipulate various actions, including cancer initiation and progression, inflammation, anti-tumor signaling and cell migration, proliferation and apoptosis in the tumor microenvironment. EVs as the external stimulus can activate or inhibit some receptor pathways in a way that amplify or attenuate a kind of particle release at target cells. This can also be carried out in a biological feedback-loop where the transmitter is affected by the induced release initiated by the target cell due to the EVs received from the donor cell, to create a bilateral process. In this paper, at first we derive the frequency response of internalization function in the framework of a unilateral communication link. This solution is adapted to a closed-loop system to find the frequency response of a bilateral system. The overall releases of the cells, given by the combination of the natural release and the induced release, are reported at the end of this paper and the results are compared in terms of distance between the cells and reaction rates of EVs at the cell membranes.","PeriodicalId":13264,"journal":{"name":"IEEE Transactions on NanoBioscience","volume":"23 1","pages":"71-80"},"PeriodicalIF":3.9,"publicationDate":"2023-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9680469","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}
Pub Date : 2023-06-12DOI: 10.1109/TNB.2023.3278653
Yueguo Luo;Yuzhen Zhao;Yi Liu
Tissue P systems with channel states are a variant of tissue P systems that can be employed as highly parallel computing devices, where the channel states can control the movements of objects. In a sense, the time-free approach can improve the robustness of P systems; hence, in this work, we introduce the time-free property into such P systems and explore their computational performances. Specifically, in a time-free manner, it is proved that this type of P systems have Turing universality by using two cells and four channel states with a maximum rule length of 2, or by using two cells and noncooperative symport rules with a maximum rule length of 1. Moreover, in terms of computational efficiency, it is proved that a uniform solution of the satisfiability ( $mathcal {SAT}$ ) problem can be obtained in a time-free manner by applying noncooperative symport rules with a maximum rule length of 1. The research results of this paper show that a highly robust dynamic membrane computing system is constructed. Theoretically, relative to the existing system, our constructed system can enhance robustness and expand its application scope.
具有通道状态的组织 P 系统是组织 P 系统的一种变体，可用作高度并行计算设备，其中通道状态可控制物体的运动。从某种意义上说，无时间方法可以提高 P 系统的鲁棒性；因此，在这项工作中，我们将无时间特性引入此类 P 系统，并探索其计算性能。具体来说，在无时间方式下，通过使用最大规则长度为 2 的两个单元和四个通道状态，或使用最大规则长度为 1 的两个单元和非合作交配规则，证明了这类 P 系统具有图灵普遍性。此外，在计算效率方面，本文证明了通过应用最大规则长度为 1 的非合作交配规则，可以在无时间限制的情况下获得可满足性（SAT）问题的统一解。从理论上讲，相对于现有系统，我们构建的系统可以增强鲁棒性并扩大其应用范围。
{"title":"Timed Tissue P Systems With Channel States","authors":"Yueguo Luo;Yuzhen Zhao;Yi Liu","doi":"10.1109/TNB.2023.3278653","DOIUrl":"10.1109/TNB.2023.3278653","url":null,"abstract":"Tissue P systems with channel states are a variant of tissue P systems that can be employed as highly parallel computing devices, where the channel states can control the movements of objects. In a sense, the time-free approach can improve the robustness of P systems; hence, in this work, we introduce the time-free property into such P systems and explore their computational performances. Specifically, in a time-free manner, it is proved that this type of P systems have Turing universality by using two cells and four channel states with a maximum rule length of 2, or by using two cells and noncooperative symport rules with a maximum rule length of 1. Moreover, in terms of computational efficiency, it is proved that a uniform solution of the satisfiability (\u0000<inline-formula> <tex-math>$mathcal {SAT}$ </tex-math></inline-formula>\u0000) problem can be obtained in a time-free manner by applying noncooperative symport rules with a maximum rule length of 1. The research results of this paper show that a highly robust dynamic membrane computing system is constructed. Theoretically, relative to the existing system, our constructed system can enhance robustness and expand its application scope.","PeriodicalId":13264,"journal":{"name":"IEEE Transactions on NanoBioscience","volume":"23 1","pages":"26-34"},"PeriodicalIF":3.9,"publicationDate":"2023-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9675270","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}
Pub Date : 2023-06-09DOI: 10.1109/TNB.2023.3284406
Jaeho Jeong;Hosung Park;Hee-Youl Kwak;Jong-Seon No;Hahyeon Jeon;Jeong Wook Lee;Jae-Won Kim
Ever since deoxyribonucleic acid (DNA) was considered as a next-generation data-storage medium, lots of research efforts have been made to correct errors occurred during the synthesis, storage, and sequencing processes using error correcting codes (ECCs). Previous works on recovering the data from the sequenced DNA pool with errors have utilized hard decoding algorithms based on a majority decision rule. To improve the correction capability of ECCs and robustness of the DNA storage system, we propose a new iterative soft decoding algorithm, where soft information is obtained from FASTQ files and channel statistics. In particular, we propose a new formula for log-likelihood ratio (LLR) calculation using quality scores (Q-scores) and a redecoding method which may be suitable for the error correction and detection in the DNA sequencing area. Based on the widely adopted encoding scheme of the fountain code structure proposed by Erlich et al., we use three different sets of sequenced data to show consistency for the performance evaluation. The proposed soft decoding algorithm gives 2.3% $sim $ 7.0% improvement of the reading number reduction compared to the state-of-the-art decoding method and it is shown that it can deal with erroneous sequenced oligo reads with insertion and deletion errors.
自从脱氧核糖核酸（DNA）被视为下一代数据存储介质以来，人们一直在努力研究如何利用纠错码（ECC）纠正在合成、存储和测序过程中出现的错误。以前从有错误的 DNA 测序池中恢复数据的工作采用的是基于多数决定规则的硬解码算法。为了提高 ECC 的纠错能力和 DNA 存储系统的鲁棒性，我们提出了一种新的迭代软解码算法，其中软信息来自 FASTQ 文件和信道统计数据。特别是，我们提出了一种使用质量分数（Q-scores）计算对数似然比（LLR）的新公式和一种适合 DNA 测序领域纠错和检测的重解码方法。基于 Erlich 等人提出的被广泛采用的喷泉代码结构编码方案，我们使用了三组不同的测序数据来显示性能评估的一致性。与最先进的解码方法相比，所提出的软解码算法的读数减少率提高了 2.3% ∼ 7.0%，并证明它能处理带有插入和删除错误的错误寡核苷酸测序读数。
{"title":"Iterative Soft Decoding Algorithm for DNA Storage Using Quality Score and Redecoding","authors":"Jaeho Jeong;Hosung Park;Hee-Youl Kwak;Jong-Seon No;Hahyeon Jeon;Jeong Wook Lee;Jae-Won Kim","doi":"10.1109/TNB.2023.3284406","DOIUrl":"10.1109/TNB.2023.3284406","url":null,"abstract":"Ever since deoxyribonucleic acid (DNA) was considered as a next-generation data-storage medium, lots of research efforts have been made to correct errors occurred during the synthesis, storage, and sequencing processes using error correcting codes (ECCs). Previous works on recovering the data from the sequenced DNA pool with errors have utilized hard decoding algorithms based on a majority decision rule. To improve the correction capability of ECCs and robustness of the DNA storage system, we propose a new iterative soft decoding algorithm, where soft information is obtained from FASTQ files and channel statistics. In particular, we propose a new formula for log-likelihood ratio (LLR) calculation using quality scores (Q-scores) and a redecoding method which may be suitable for the error correction and detection in the DNA sequencing area. Based on the widely adopted encoding scheme of the fountain code structure proposed by Erlich et al., we use three different sets of sequenced data to show consistency for the performance evaluation. The proposed soft decoding algorithm gives 2.3%\u0000<inline-formula> <tex-math>$sim $ </tex-math></inline-formula>\u00007.0% improvement of the reading number reduction compared to the state-of-the-art decoding method and it is shown that it can deal with erroneous sequenced oligo reads with insertion and deletion errors.","PeriodicalId":13264,"journal":{"name":"IEEE Transactions on NanoBioscience","volume":"23 1","pages":"81-90"},"PeriodicalIF":3.9,"publicationDate":"2023-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9601921","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}
Pub Date : 2023-06-08DOI: 10.1109/TNB.2023.3284092
Abinitha Gourabathina;Zhiyu Wan;J. Thomas Brown;Chao Yan;Bradley A. Malin
Sharing individual-level pandemic data is essential for accelerating the understanding of a disease. For example, COVID-19 data have been widely collected to support public health surveillance and research. In the United States, these data are typically de-identified before publication to protect the privacy of the corresponding individuals. However, current data publishing approaches for this type of data, such as those adopted by the U.S. Centers for Disease Control and Prevention (CDC), have not flexed over time to account for the dynamic nature of infection rates. Thus, the policies generated by these strategies have the potential to both raise privacy risks or overprotect the data and impair the data utility (or usability). To optimize the tradeoff between privacy risk and data utility, we introduce a game theoretic model that adaptively generates policies for the publication of individual-level COVID-19 data according to infection dynamics. We model the data publishing process as a two-player Stackelberg game between a data publisher and a data recipient and then search for the best strategy for the publisher. In this game, we consider 1) average performance of predicting future case counts; and 2) mutual information between the original data and the released data. We use COVID-19 case data from Vanderbilt University Medical Center from March 2020 to December 2021 to demonstrate the effectiveness of the new model. The results indicate that the game theoretic model outperforms all state-of-the-art baseline approaches, including those adopted by CDC, while maintaining low privacy risk. We further perform an extensive sensitivity analyses to show that our findings are robust to order-of-magnitude parameter fluctuations.
{"title":"PanDa Game: Optimized Privacy-Preserving Publishing of Individual-Level Pandemic Data Based on a Game Theoretic Model","authors":"Abinitha Gourabathina;Zhiyu Wan;J. Thomas Brown;Chao Yan;Bradley A. Malin","doi":"10.1109/TNB.2023.3284092","DOIUrl":"10.1109/TNB.2023.3284092","url":null,"abstract":"Sharing individual-level pandemic data is essential for accelerating the understanding of a disease. For example, COVID-19 data have been widely collected to support public health surveillance and research. In the United States, these data are typically de-identified before publication to protect the privacy of the corresponding individuals. However, current data publishing approaches for this type of data, such as those adopted by the U.S. Centers for Disease Control and Prevention (CDC), have not flexed over time to account for the dynamic nature of infection rates. Thus, the policies generated by these strategies have the potential to both raise privacy risks or overprotect the data and impair the data utility (or usability). To optimize the tradeoff between privacy risk and data utility, we introduce a game theoretic model that adaptively generates policies for the publication of individual-level COVID-19 data according to infection dynamics. We model the data publishing process as a two-player Stackelberg game between a data publisher and a data recipient and then search for the best strategy for the publisher. In this game, we consider 1) average performance of predicting future case counts; and 2) mutual information between the original data and the released data. We use COVID-19 case data from Vanderbilt University Medical Center from March 2020 to December 2021 to demonstrate the effectiveness of the new model. The results indicate that the game theoretic model outperforms all state-of-the-art baseline approaches, including those adopted by CDC, while maintaining low privacy risk. We further perform an extensive sensitivity analyses to show that our findings are robust to order-of-magnitude parameter fluctuations.","PeriodicalId":13264,"journal":{"name":"IEEE Transactions on NanoBioscience","volume":"22 4","pages":"808-817"},"PeriodicalIF":3.9,"publicationDate":"2023-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9950843","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}
Pub Date : 2023-06-06DOI: 10.1109/TNB.2023.3283462
Jyotsna Talreja Wassan;Haiying Wang;Huiru Zheng
Metagenomics is an unobtrusive science linking microbial genes to biological functions or environmental states. Classifying microbial genes into their functional repertoire is an important task in the downstream analysis of Metagenomic studies. The task involves Machine Learning (ML) based supervised methods to achieve good classification performance. Random Forest (RF) has been applied rigorously to microbial gene abundance profiles, mapping them to functional phenotypes. The current research targets tuning RF by the evolutionary ancestry of microbial phylogeny, developing a Phylogeny-RF model for functional classification of metagenomes. This method facilitates capturing the effects of phylogenetic relatedness in an ML classifier itself rather than just applying a supervised classifier over the raw abundances of microbial genes. The idea is rooted in the fact that closely related microbes by phylogeny are highly correlated and tend to have similar genetic and phenotypic traits. Such microbes behave similarly; and hence tend to be selected together, or one of these could be dropped from the analysis, to improve the ML process. The proposed Phylogeny-RF algorithm has been compared with state-of-the-art classification methods including RF and the phylogeny-aware methods of MetaPhyl and PhILR, using three real-world 16S rRNA metagenomic datasets. It has been observed that the proposed method not only achieved significantly better performance than the traditional RF model but also performed better than the other phylogeny-driven benchmarks (p < 0.05). For example, Phylogeny-RF attained a highest AUC of 0.949 and Kappa of 0.891 over soil microbiomes in comparison to other benchmarks.
{"title":"Developing a New Phylogeny-Driven Random Forest Model for Functional Metagenomics","authors":"Jyotsna Talreja Wassan;Haiying Wang;Huiru Zheng","doi":"10.1109/TNB.2023.3283462","DOIUrl":"10.1109/TNB.2023.3283462","url":null,"abstract":"Metagenomics is an unobtrusive science linking microbial genes to biological functions or environmental states. Classifying microbial genes into their functional repertoire is an important task in the downstream analysis of Metagenomic studies. The task involves Machine Learning (ML) based supervised methods to achieve good classification performance. Random Forest (RF) has been applied rigorously to microbial gene abundance profiles, mapping them to functional phenotypes. The current research targets tuning RF by the evolutionary ancestry of microbial phylogeny, developing a Phylogeny-RF model for functional classification of metagenomes. This method facilitates capturing the effects of phylogenetic relatedness in an ML classifier itself rather than just applying a supervised classifier over the raw abundances of microbial genes. The idea is rooted in the fact that closely related microbes by phylogeny are highly correlated and tend to have similar genetic and phenotypic traits. Such microbes behave similarly; and hence tend to be selected together, or one of these could be dropped from the analysis, to improve the ML process. The proposed Phylogeny-RF algorithm has been compared with state-of-the-art classification methods including RF and the phylogeny-aware methods of MetaPhyl and PhILR, using three real-world 16S rRNA metagenomic datasets. It has been observed that the proposed method not only achieved significantly better performance than the traditional RF model but also performed better than the other phylogeny-driven benchmarks (p < 0.05). For example, Phylogeny-RF attained a highest AUC of 0.949 and Kappa of 0.891 over soil microbiomes in comparison to other benchmarks.","PeriodicalId":13264,"journal":{"name":"IEEE Transactions on NanoBioscience","volume":"22 4","pages":"763-770"},"PeriodicalIF":3.9,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9576385","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}
Pub Date : 2023-06-05DOI: 10.1109/TNB.2023.3283049
Duo Tan;Jiayang Liu;Shanxiong Chen;Rui Yao;Yongmei Li;Shiyu Zhu;Linfeng Li
Stroke is one of the main causes of disability and death, and it can be divided into hemorrhagic stroke and ischemic stroke. Ischemic stroke is more common, and about 8 out of 10 stroke patients suffer from ischemic stroke. In clinical practice, doctors diagnose stroke by using computed tomography angiography (CTA) image to accurately evaluate the collateral circulation in stroke patients. This imaging information is of great significance in assisting doctors to determine the patient’s treatment plan and prognosis. Currently, great progress has been made in the field of computer-aided diagnosis technology in medicine by using artificial intelligence. However, in related research based on deep learning algorithms, researchers usually only use single-phase data for training, lacking the temporal dimension information of multi-phase image data. This makes it difficult for the model to learn more comprehensive and effective collateral circulation feature representation, thereby limiting its performance. Therefore, combining data for training is expected to improve the accuracy and reliability of collateral circulation evaluation. In this study, we propose an effective hybrid mechanism to assist the feature encoding network in evaluating the degree of collateral circulation in the brain. By using a hybrid attention mechanism, additional guidance and regularization are provided to enhance the collateral circulation feature representation across multiple stages. Time dimension information is added to the input, and multiple feature-level fusion modules are designed in the multi-branch network. The first fusion module in the single-stage feature extraction network completes the fusion of deep and shallow vessel features in the single-branch network, followed by the multi-stage network feature fusion module, which achieves feature fusion for four stages. Tested on a dataset of multi-phase cranial CTA images, the accuracy rate exceeding 90.43%. The experimental results demonstrate that the addition of these modules can fully explore collateral vessel features, improve feature expression capabilities, and optimize the performance of deep learning network model.
{"title":"Automatic Evaluating of Multi-Phase Cranial CTA Collateral Circulation Based on Feature Fusion Attention Network Model","authors":"Duo Tan;Jiayang Liu;Shanxiong Chen;Rui Yao;Yongmei Li;Shiyu Zhu;Linfeng Li","doi":"10.1109/TNB.2023.3283049","DOIUrl":"10.1109/TNB.2023.3283049","url":null,"abstract":"Stroke is one of the main causes of disability and death, and it can be divided into hemorrhagic stroke and ischemic stroke. Ischemic stroke is more common, and about 8 out of 10 stroke patients suffer from ischemic stroke. In clinical practice, doctors diagnose stroke by using computed tomography angiography (CTA) image to accurately evaluate the collateral circulation in stroke patients. This imaging information is of great significance in assisting doctors to determine the patient’s treatment plan and prognosis. Currently, great progress has been made in the field of computer-aided diagnosis technology in medicine by using artificial intelligence. However, in related research based on deep learning algorithms, researchers usually only use single-phase data for training, lacking the temporal dimension information of multi-phase image data. This makes it difficult for the model to learn more comprehensive and effective collateral circulation feature representation, thereby limiting its performance. Therefore, combining data for training is expected to improve the accuracy and reliability of collateral circulation evaluation. In this study, we propose an effective hybrid mechanism to assist the feature encoding network in evaluating the degree of collateral circulation in the brain. By using a hybrid attention mechanism, additional guidance and regularization are provided to enhance the collateral circulation feature representation across multiple stages. Time dimension information is added to the input, and multiple feature-level fusion modules are designed in the multi-branch network. The first fusion module in the single-stage feature extraction network completes the fusion of deep and shallow vessel features in the single-branch network, followed by the multi-stage network feature fusion module, which achieves feature fusion for four stages. Tested on a dataset of multi-phase cranial CTA images, the accuracy rate exceeding 90.43%. The experimental results demonstrate that the addition of these modules can fully explore collateral vessel features, improve feature expression capabilities, and optimize the performance of deep learning network model.","PeriodicalId":13264,"journal":{"name":"IEEE Transactions on NanoBioscience","volume":"22 4","pages":"789-799"},"PeriodicalIF":3.9,"publicationDate":"2023-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9632647","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}
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