Pub Date : 2025-04-24DOI: 10.1109/TNB.2025.3563382
Hoang Phuong Uyen Nguyen;Hoang Van Huy Dai;Anh Hue Luong;Wei-Chih Lin
This study highlights the structural, antioxidant, antibacterial, and anti-inflammatory properties of silver nanoparticles (AgNPs) and zinc oxide nanoparticles (ZnONPs), synthesized successfully using Hsiantsao aqueous extract as an eco-friendly alternative to traditional chemical methods. The antioxidant activity of the nanoparticles was assessed through DPPH, ABTS, and FRAP assays. The XRD spectra of biosynthesized silver nanoparticles (AgNPs) and zinc oxide nanoparticles (ZnONPs) are showed size average of 7 nm and 24-44 nm, respectively. AgNPs demonstrated notable antioxidant properties, achieving 70%±0.68 DPPH scavenging and 75%±0.82 ABTS inhibition at 0.1 mg/mL. ZnONPs showed superior efficacy, with 47.43%±0.68 DPPH scavenging and 80%±0.82 ABTS inhibition, as well as robust reducing power in the FRAP assay, comparable to standard ascorbic acid. Antibacterial assays revealed that AgNPs were particularly effective against Gram-positive bacteria, while ZnONPs exhibited activity against both Gram-positive and Gram-negative strains. Additionally, ZnONPs demonstrated exceptional anti-inflammatory potential, inhibiting protein denaturation by up to 91% at 0.01 mg/mL. These structural and functional characteristics position AgNPs and ZnONPs as promising candidates for biomedical applications. These findings underscore the versatility of AgNPs and ZnONPs in advancing modern healthcare solutions.
{"title":"Biosynthesis of Silver and Zinc Oxide Nanoparticles Using Platostoma palustre Aqueous Extract for Biomedical Applications","authors":"Hoang Phuong Uyen Nguyen;Hoang Van Huy Dai;Anh Hue Luong;Wei-Chih Lin","doi":"10.1109/TNB.2025.3563382","DOIUrl":"10.1109/TNB.2025.3563382","url":null,"abstract":"This study highlights the structural, antioxidant, antibacterial, and anti-inflammatory properties of silver nanoparticles (AgNPs) and zinc oxide nanoparticles (ZnONPs), synthesized successfully using Hsiantsao aqueous extract as an eco-friendly alternative to traditional chemical methods. The antioxidant activity of the nanoparticles was assessed through DPPH, ABTS, and FRAP assays. The XRD spectra of biosynthesized silver nanoparticles (AgNPs) and zinc oxide nanoparticles (ZnONPs) are showed size average of 7 nm and 24-44 nm, respectively. AgNPs demonstrated notable antioxidant properties, achieving 70%±0.68 DPPH scavenging and 75%±0.82 ABTS inhibition at 0.1 mg/mL. ZnONPs showed superior efficacy, with 47.43%±0.68 DPPH scavenging and 80%±0.82 ABTS inhibition, as well as robust reducing power in the FRAP assay, comparable to standard ascorbic acid. Antibacterial assays revealed that AgNPs were particularly effective against Gram-positive bacteria, while ZnONPs exhibited activity against both Gram-positive and Gram-negative strains. Additionally, ZnONPs demonstrated exceptional anti-inflammatory potential, inhibiting protein denaturation by up to 91% at 0.01 mg/mL. These structural and functional characteristics position AgNPs and ZnONPs as promising candidates for biomedical applications. These findings underscore the versatility of AgNPs and ZnONPs in advancing modern healthcare solutions.","PeriodicalId":13264,"journal":{"name":"IEEE Transactions on NanoBioscience","volume":"24 4","pages":"421-433"},"PeriodicalIF":4.4,"publicationDate":"2025-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143998102","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}
The experimental and theoretical realization of 10% graphene doped ZnO/Graphene thin film alcohol sensor has been reported. The alcohol sensor has been fabricated by sol-gel method and theoretically verified by DFT-based first principle calculations. The quality of the fabricated device has been studied using SEM and UV measurements. To determine its figures-of-merit, the conductivity, transfer characteristics, and response measurements have been analyzed. In addition, the device has undergone three different exposures of alcohol concentrations such as Brandy, Whiskey, and Rum with varying exposure times.
{"title":"Fabrication and Characterization of ZnO/Graphene Thin Film Alcohol Sensor","authors":"Routu Santosh;Anuriddh Bahadur Yadav;Ball Mukund Mani Tripathi;Rahul Checker;Pankaj Kumar","doi":"10.1109/TNB.2025.3563456","DOIUrl":"10.1109/TNB.2025.3563456","url":null,"abstract":"The experimental and theoretical realization of 10% graphene doped ZnO/Graphene thin film alcohol sensor has been reported. The alcohol sensor has been fabricated by sol-gel method and theoretically verified by DFT-based first principle calculations. The quality of the fabricated device has been studied using SEM and UV measurements. To determine its figures-of-merit, the conductivity, transfer characteristics, and response measurements have been analyzed. In addition, the device has undergone three different exposures of alcohol concentrations such as Brandy, Whiskey, and Rum with varying exposure times.","PeriodicalId":13264,"journal":{"name":"IEEE Transactions on NanoBioscience","volume":"24 4","pages":"404-410"},"PeriodicalIF":4.4,"publicationDate":"2025-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143994810","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 : 2025-04-22DOI: 10.1109/TNB.2025.3563307
Hansa Gul;Haris Ahmed Khan;Zahida Nasreen;Nasir Assad;Syed Ali Turab;Muhammad Hanif
Iron oxide nanoparticles (Fe2O3 NPs) were successfully Synthesized in a green manner using Cucurbita pepo pulp extract as a natural capping and reducing agent. UV-vis spectroscopy verified the synthesis with a distinct absorption peak at 285 nm, while FTIR analysis revealed functional groups responsible for reduction and stabilization. X-ray diffraction (XRD) analysis confirmed the crystalline nature of the nanoparticles, with an average size of 21.5 nm. SEM and EDX analyses further validated the nanoparticles’ spherical morphology and elemental composition. Biosynthesized IONPs exhibited notable antibacterial activity against multidrug-resistant bacterial strains such as Klebsiella pneumoniae and Pseudomonas aeruginosa. The inhibition zones ranged between 5–22 mm for Klebsiella pneumoniae and from 4 to 12 mm for Pseudomonas aeruginosa, depending on the concentration of the nanoparticles. Hematological evaluations demonstrated strong anticoagulant and thrombolytic properties. Iron oxide nanoparticles effectively inhibited blood coagulation at $40~mu $ g/mL and showed significant thrombolytic activity by dissolving preformed clots at $50~mu $ g/mL. The biosynthesized IONPs showed remarkable antioxidant activity that was comparable to standard. This study underscores the potential of Cucurbita pepo as a sustainable and eco-friendly resource for synthesizing multifunctional IONPs. The results suggest promising applications to address antibiotic resistance and manage blood-related disorders. Furthermore, the findings highlight the critical role of green nanotechnology in the advancement of environmentally sustainable and biocompatible nanomaterials for diverse biomedical applications.
{"title":"Exploring the Antibacterial, Anticoagulant, and Hemolytic Potential of Green-Synthesized Fe2O3 Nanoparticles by Cucurbita pepo Pulp","authors":"Hansa Gul;Haris Ahmed Khan;Zahida Nasreen;Nasir Assad;Syed Ali Turab;Muhammad Hanif","doi":"10.1109/TNB.2025.3563307","DOIUrl":"10.1109/TNB.2025.3563307","url":null,"abstract":"Iron oxide nanoparticles (Fe2O3 NPs) were successfully Synthesized in a green manner using Cucurbita pepo pulp extract as a natural capping and reducing agent. UV-vis spectroscopy verified the synthesis with a distinct absorption peak at 285 nm, while FTIR analysis revealed functional groups responsible for reduction and stabilization. X-ray diffraction (XRD) analysis confirmed the crystalline nature of the nanoparticles, with an average size of 21.5 nm. SEM and EDX analyses further validated the nanoparticles’ spherical morphology and elemental composition. Biosynthesized IONPs exhibited notable antibacterial activity against multidrug-resistant bacterial strains such as Klebsiella pneumoniae and Pseudomonas aeruginosa. The inhibition zones ranged between 5–22 mm for Klebsiella pneumoniae and from 4 to 12 mm for Pseudomonas aeruginosa, depending on the concentration of the nanoparticles. Hematological evaluations demonstrated strong anticoagulant and thrombolytic properties. Iron oxide nanoparticles effectively inhibited blood coagulation at <inline-formula> <tex-math>$40~mu $ </tex-math></inline-formula>g/mL and showed significant thrombolytic activity by dissolving preformed clots at <inline-formula> <tex-math>$50~mu $ </tex-math></inline-formula>g/mL. The biosynthesized IONPs showed remarkable antioxidant activity that was comparable to standard. This study underscores the potential of Cucurbita pepo as a sustainable and eco-friendly resource for synthesizing multifunctional IONPs. The results suggest promising applications to address antibiotic resistance and manage blood-related disorders. Furthermore, the findings highlight the critical role of green nanotechnology in the advancement of environmentally sustainable and biocompatible nanomaterials for diverse biomedical applications.","PeriodicalId":13264,"journal":{"name":"IEEE Transactions on NanoBioscience","volume":"24 4","pages":"411-420"},"PeriodicalIF":4.4,"publicationDate":"2025-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144011637","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}
DNA hybridization reaction is a significant technology in the field of semi-synthetic biology and holds great potential for use in biological computation. In this study, we propose a novel machine learning model based on a DNA hybridization reaction circuit. This circuit comprises a computation training component, a test component, and a learning algorithm. Compared to conventional machine learning models based on semiconductors, the proposed machine learning model harnesses the power of DNA hybridization reaction, with the learning algorithm implemented based on the unique properties of DNA computation, enabling parallel computation for the acquisition of learning results. In contrast to existing machine learning models based on DNA circuits, our proposed model constitutes a complete synthetic biology computation system, and utilizes the “dual-rail” mechanism to achieve the DNA compilation of the learning algorithm, which allows the weights to be updated to negative values. The proposed machine learning model based on DNA hybridization reaction demonstrates the ability to predict and fit linear functions. As such, this study is expected to make significant contributions to the development of machine learning through DNA hybridization reaction circuits.
{"title":"A Novel Linear Machine Learning Method Based on DNA Hybridization Reaction Circuit","authors":"Chengye Zou;Qiang Zhang;Bin Wang;Changjun Zhou;Yongwei Yang;Xuncai Zhang","doi":"10.1109/TNB.2025.3559480","DOIUrl":"10.1109/TNB.2025.3559480","url":null,"abstract":"DNA hybridization reaction is a significant technology in the field of semi-synthetic biology and holds great potential for use in biological computation. In this study, we propose a novel machine learning model based on a DNA hybridization reaction circuit. This circuit comprises a computation training component, a test component, and a learning algorithm. Compared to conventional machine learning models based on semiconductors, the proposed machine learning model harnesses the power of DNA hybridization reaction, with the learning algorithm implemented based on the unique properties of DNA computation, enabling parallel computation for the acquisition of learning results. In contrast to existing machine learning models based on DNA circuits, our proposed model constitutes a complete synthetic biology computation system, and utilizes the “dual-rail” mechanism to achieve the DNA compilation of the learning algorithm, which allows the weights to be updated to negative values. The proposed machine learning model based on DNA hybridization reaction demonstrates the ability to predict and fit linear functions. As such, this study is expected to make significant contributions to the development of machine learning through DNA hybridization reaction circuits.","PeriodicalId":13264,"journal":{"name":"IEEE Transactions on NanoBioscience","volume":"24 3","pages":"374-385"},"PeriodicalIF":3.7,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143989744","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 : 2025-04-08DOI: 10.1109/TNB.2025.3558853
Caiyun Deng;Guojun Han;Pengchao Han;Yi Fang
DNA data storage is a cutting-edge storage technique due to its high density, replicability, and long-term capability. It involves encoding, insertion, deletion, and substitution (IDS) channels for data synthesis and sequencing, and decoding processes. The IDS channels that feature multiple output sequences are prone to IDS errors, complicating the decoding process and degrading the performance of DNA data storage. To address this issue, we investigate effective IDS error correction algorithms considering two encoding schemes in DNA data storage. Specifically in the encoding process, we use marker codes (MC) and embedded marker codes (EMC) as inner codes, respectively, both connected to low-density parity-check (LDPC) codes as outer codes. First, we propose the segmented progressive matching (SPM) algorithm to infer the consensus sequence from multiple output sequences, thereby facilitating the decoding processes. Moreover, when using MC as the inner code, we propose a synchronous decoding algorithm based on the Hidden Markov Model (SDH) to infer the a posteriori probability (APP) of base symbols, which supports the external decoding algorithm. Furthermore, when the inner code is EMC, we propose the iterative external decoding (IED) algorithm. IED integrates synchronous decoding with embedded normalized min-sum decoding (ENMS) to achieve an enhanced APP for external decoding, enabling lower bit-error rate (BER) transmission. Meanwhile, we reduce the complexity of the external decoder by minimizing checksum node computations. Comparing the two schemes reveals that the SDH algorithm with MC as the inner code offers a lightweight solution for DNA data storage. In contrast, the IED with EMC demonstrates superior decoding performance with a linear complexity scale by the number of iterations. Compared with existing studies, simulation results show that our proposed decoding algorithm reduces the BER by ${21}.{72}% sim {99}.{75}%$ .
DNA 数据存储因其高密度、可复制性和长期能力而成为一种尖端存储技术。它包括用于数据合成和测序的编码、插入、删除和替换（IDS）通道以及解码过程。具有多个输出序列的 IDS 通道容易出现 IDS 错误，从而使解码过程复杂化，并降低 DNA 数据存储的性能。针对这一问题，我们研究了有效的 IDS 纠错算法，其中考虑了 DNA 数据存储中的两种编码方案。具体来说，在编码过程中，我们分别使用标记码（MC）和嵌入标记码（EMC）作为内码，两者都与低密度奇偶校验码（LDPC）相连作为外码。首先，我们提出了分段渐进匹配（SPM）算法，从多个输出序列中推断出共识序列，从而简化了解码过程。此外，当使用 MC 作为内码时，我们提出了一种基于隐马尔可夫模型（SDH）的同步解码算法来推断基本符号的后验概率（APP），从而支持外部解码算法。此外，当内码为 EMC 时，我们提出了迭代外部解码（IED）算法。IED 将同步解码与嵌入式归一化最小和解码（ENMS）相结合，实现了外部解码的增强型 APP，从而实现了更低的误码率（BER）传输。同时，我们通过最大限度地减少校验和节点计算，降低了外部解码器的复杂性。比较这两种方案可以发现，以 MC 作为内码的 SDH 算法为 DNA 数据存储提供了一种轻量级解决方案。相比之下，以 EMC 为内码的 IED 则表现出更优越的解码性能，其复杂度与迭代次数成线性比例。与现有研究相比，仿真结果表明，我们提出的解码算法将误码率降低了 21.72% ~ 99.75%。
{"title":"Effective IDS Error Correction Algorithms for DNA Storage Channels With Multiple Output Sequences","authors":"Caiyun Deng;Guojun Han;Pengchao Han;Yi Fang","doi":"10.1109/TNB.2025.3558853","DOIUrl":"10.1109/TNB.2025.3558853","url":null,"abstract":"DNA data storage is a cutting-edge storage technique due to its high density, replicability, and long-term capability. It involves encoding, insertion, deletion, and substitution (IDS) channels for data synthesis and sequencing, and decoding processes. The IDS channels that feature multiple output sequences are prone to IDS errors, complicating the decoding process and degrading the performance of DNA data storage. To address this issue, we investigate effective IDS error correction algorithms considering two encoding schemes in DNA data storage. Specifically in the encoding process, we use marker codes (MC) and embedded marker codes (EMC) as inner codes, respectively, both connected to low-density parity-check (LDPC) codes as outer codes. First, we propose the segmented progressive matching (SPM) algorithm to infer the consensus sequence from multiple output sequences, thereby facilitating the decoding processes. Moreover, when using MC as the inner code, we propose a synchronous decoding algorithm based on the Hidden Markov Model (SDH) to infer the a posteriori probability (APP) of base symbols, which supports the external decoding algorithm. Furthermore, when the inner code is EMC, we propose the iterative external decoding (IED) algorithm. IED integrates synchronous decoding with embedded normalized min-sum decoding (ENMS) to achieve an enhanced APP for external decoding, enabling lower bit-error rate (BER) transmission. Meanwhile, we reduce the complexity of the external decoder by minimizing checksum node computations. Comparing the two schemes reveals that the SDH algorithm with MC as the inner code offers a lightweight solution for DNA data storage. In contrast, the IED with EMC demonstrates superior decoding performance with a linear complexity scale by the number of iterations. Compared with existing studies, simulation results show that our proposed decoding algorithm reduces the BER by <inline-formula> <tex-math>${21}.{72}% sim {99}.{75}%$ </tex-math></inline-formula>.","PeriodicalId":13264,"journal":{"name":"IEEE Transactions on NanoBioscience","volume":"24 3","pages":"386-394"},"PeriodicalIF":3.7,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143811400","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 : 2025-03-26DOI: 10.1109/TNB.2025.3551711
{"title":"IEEE Transactions on NanoBioscience Information for Authors","authors":"","doi":"10.1109/TNB.2025.3551711","DOIUrl":"https://doi.org/10.1109/TNB.2025.3551711","url":null,"abstract":"","PeriodicalId":13264,"journal":{"name":"IEEE Transactions on NanoBioscience","volume":"24 2","pages":"C3-C3"},"PeriodicalIF":3.7,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10941706","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143706683","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}
The new generation of glucose biosensors has attracted significant research interest due to its fast response, high stability, reproducibility, portability and low detection limit. In this work, various types of high-performance non-enzymatic glucose sensors are proposed, based on carbon nitride supported copper oxide nanoparticles (CNCO). The hybrid system was synthesized using a modified deposition-precipitation route where the copper oxide nanoparticles were dispersed on the carbon nitride matrix. The X-ray diffraction pattern revealed that the copper oxide nanoparticles exhibit a high degree of crystallinity with a monoclinic structure. The synthesized hybrid material was used as a catalyst for the electrochemical detection of glucose in the range of 0 to 15.6 mM, demonstrating a detection limit of 0.59 mM and a sensitivity of 0.53 mA.mM${}^{-{1}}$ .cm${}^{-{2}}$ . The CNCO based extended gate field effect transistor, at different glucose concentrations (1-9 mM), showed limit of detection and sensitivity values of 0.59 mM and 0.065 mA.mM${}^{-{1}}$ .cm${}^{-{2}}$ , respectively. A microcontroller-based glucose sensor was also implemented in this study that exhibited the sensitivity value of 1.46 mV/mM within the concentration range of 2-8 mM. The carbon nitride-supported copper oxide-based glucose sensors exhibit excellent reproducibility, sufficient stability and high selectivity, making them a promising candidate for real-life sensing applications.
{"title":"Carbon Nitride-Supported Copper Oxide for Non-Enzymatic Glucose Sensor: A Multi-Platform Approach Utilizing Electrochemical, Field Effect Transistor, and Microcontroller-Based IoT Systems","authors":"Chandan Saha;Pooja Kumari;Lungelo Mgenge;Sarit Ghosh;Venkata Perla;Harishchandra Singh;Kaushik Mallick","doi":"10.1109/TNB.2025.3553622","DOIUrl":"10.1109/TNB.2025.3553622","url":null,"abstract":"The new generation of glucose biosensors has attracted significant research interest due to its fast response, high stability, reproducibility, portability and low detection limit. In this work, various types of high-performance non-enzymatic glucose sensors are proposed, based on carbon nitride supported copper oxide nanoparticles (CNCO). The hybrid system was synthesized using a modified deposition-precipitation route where the copper oxide nanoparticles were dispersed on the carbon nitride matrix. The X-ray diffraction pattern revealed that the copper oxide nanoparticles exhibit a high degree of crystallinity with a monoclinic structure. The synthesized hybrid material was used as a catalyst for the electrochemical detection of glucose in the range of 0 to 15.6 mM, demonstrating a detection limit of 0.59 mM and a sensitivity of 0.53 mA.mM<inline-formula> <tex-math>${}^{-{1}}$ </tex-math></inline-formula>.cm<inline-formula> <tex-math>${}^{-{2}}$ </tex-math></inline-formula>. The CNCO based extended gate field effect transistor, at different glucose concentrations (1-9 mM), showed limit of detection and sensitivity values of 0.59 mM and 0.065 mA.mM<inline-formula> <tex-math>${}^{-{1}}$ </tex-math></inline-formula>.cm<inline-formula> <tex-math>${}^{-{2}}$ </tex-math></inline-formula>, respectively. A microcontroller-based glucose sensor was also implemented in this study that exhibited the sensitivity value of 1.46 mV/mM within the concentration range of 2-8 mM. The carbon nitride-supported copper oxide-based glucose sensors exhibit excellent reproducibility, sufficient stability and high selectivity, making them a promising candidate for real-life sensing applications.","PeriodicalId":13264,"journal":{"name":"IEEE Transactions on NanoBioscience","volume":"24 3","pages":"348-356"},"PeriodicalIF":3.7,"publicationDate":"2025-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143673712","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 : 2025-03-20DOI: 10.1109/TNB.2025.3553183
Liwei Mu
This paper introduces an improved redundant residue number system (RRNS) encoding method to enhance the reliability of information transmission in diffusive molecular communication (DMC). In addressing the 2-1 mapping issue in RRNS encoding, we propose a simplified low-mapping solution that effectively avoids the 2-1 mapping problem, thereby simplifying the decoding process. Leveraging the superior performance of the low-mapping algorithm, we further developed a direct decision algorithm that further simplifies the decoding algorithm by omitting the traditional minimum distance decision-making steps. Furthermore, this study delves into the impact of modulus selection on RRNS decoding performance and provides guidelines for optimizing code construction. Through simulation experiments on DMC channels, we have validated the effectiveness of the proposed RRNS encoding method, especially when employing binary concentration shift keying (BCSK) modulation and considering intersymbol interference (ISI). The simulation results show that the proposed encoding method not only significantly reduces the bit error rate (BER) but also fully meets the requirements of DMC systems, offering a promising new direction for the development of molecular communication technology. With these improvements, our method not only enhances the reliability of information transmission in DMC systems but also lays a solid foundation for future research and applications in molecular communication technology.
{"title":"Enhanced Redundant Residue Number System Codes for Reliable Diffusive Molecular Communication","authors":"Liwei Mu","doi":"10.1109/TNB.2025.3553183","DOIUrl":"10.1109/TNB.2025.3553183","url":null,"abstract":"This paper introduces an improved redundant residue number system (RRNS) encoding method to enhance the reliability of information transmission in diffusive molecular communication (DMC). In addressing the 2-1 mapping issue in RRNS encoding, we propose a simplified low-mapping solution that effectively avoids the 2-1 mapping problem, thereby simplifying the decoding process. Leveraging the superior performance of the low-mapping algorithm, we further developed a direct decision algorithm that further simplifies the decoding algorithm by omitting the traditional minimum distance decision-making steps. Furthermore, this study delves into the impact of modulus selection on RRNS decoding performance and provides guidelines for optimizing code construction. Through simulation experiments on DMC channels, we have validated the effectiveness of the proposed RRNS encoding method, especially when employing binary concentration shift keying (BCSK) modulation and considering intersymbol interference (ISI). The simulation results show that the proposed encoding method not only significantly reduces the bit error rate (BER) but also fully meets the requirements of DMC systems, offering a promising new direction for the development of molecular communication technology. With these improvements, our method not only enhances the reliability of information transmission in DMC systems but also lays a solid foundation for future research and applications in molecular communication technology.","PeriodicalId":13264,"journal":{"name":"IEEE Transactions on NanoBioscience","volume":"24 3","pages":"366-373"},"PeriodicalIF":3.7,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143669794","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 : 2025-03-06DOI: 10.1109/TNB.2025.3548823
M. Valliammai;J. Mohanraj;Balasubramanian Esakki;Lung-Jieh Yang;Chua-Chin Wang;A. Bakiya
The advent of evanescent field based fiber optic biosensor and advancements in nanotechnology has create an excellent opportunity in label-free detection of biomarkers which plays vital role in the early, rapid and accurate diagnosis of acute diseases. In this work, we demonstrate a high sensitive Molybdenum Tungsten Disulfide (MoWS2) coated side polished fiber (SPF) biosensor for accurate and early diagnosis of cardio vascular disease (CVD). The Cardiac Troponins I (cTnI) is identified as a biomarker of interest for early and rapid diagnosis of CVD. The proposed SPF biosensor exhibits surface plasmonic resonance (SPR) detection due to the evanescent field interaction between MoWS2 nano coated side polished region and anti-CTnI. The proposed SPF biosensor possess the high sensitivity of 82% to detect the cTnI antibody with a limit of detection (LOD) about 17.5 pg/mL. The peak SPR shift have been calculated as 61 nm for analyte concentrations of 500 pg/mL Moreover, the proposed SPF biosensor possess the high degree of selectivity and environmental stability to CTnI among three analytes such as CTnI, Estrogen and Glucose. The hydrophobic interactions of MoWS2 and cTnI antibody leads to chemical free biofunctionalization of antibody in the sensing region. Hence, the simulation results shows the surface interaction strength calculated as 1.29 KJ mol−1/nm2 in order to evaluate the hydrophobic interactions. Thus, the proposed optical biosensor is a promising candidate for “point-of-care” testing of CVD disorders and preclinical assessments.
{"title":"A High Sensitive Nanomaterial Coated Side Polished Fiber Sensor for Detection of Cardiac Troponin I Antibody","authors":"M. Valliammai;J. Mohanraj;Balasubramanian Esakki;Lung-Jieh Yang;Chua-Chin Wang;A. Bakiya","doi":"10.1109/TNB.2025.3548823","DOIUrl":"10.1109/TNB.2025.3548823","url":null,"abstract":"The advent of evanescent field based fiber optic biosensor and advancements in nanotechnology has create an excellent opportunity in label-free detection of biomarkers which plays vital role in the early, rapid and accurate diagnosis of acute diseases. In this work, we demonstrate a high sensitive Molybdenum Tungsten Disulfide (MoWS2) coated side polished fiber (SPF) biosensor for accurate and early diagnosis of cardio vascular disease (CVD). The Cardiac Troponins I (cTnI) is identified as a biomarker of interest for early and rapid diagnosis of CVD. The proposed SPF biosensor exhibits surface plasmonic resonance (SPR) detection due to the evanescent field interaction between MoWS2 nano coated side polished region and anti-CTnI. The proposed SPF biosensor possess the high sensitivity of 82% to detect the cTnI antibody with a limit of detection (LOD) about 17.5 pg/mL. The peak SPR shift have been calculated as 61 nm for analyte concentrations of 500 pg/mL Moreover, the proposed SPF biosensor possess the high degree of selectivity and environmental stability to CTnI among three analytes such as CTnI, Estrogen and Glucose. The hydrophobic interactions of MoWS2 and cTnI antibody leads to chemical free biofunctionalization of antibody in the sensing region. Hence, the simulation results shows the surface interaction strength calculated as 1.29 KJ mol−1/nm2 in order to evaluate the hydrophobic interactions. Thus, the proposed optical biosensor is a promising candidate for “point-of-care” testing of CVD disorders and preclinical assessments.","PeriodicalId":13264,"journal":{"name":"IEEE Transactions on NanoBioscience","volume":"24 3","pages":"357-365"},"PeriodicalIF":3.7,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143572947","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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