Nose-on-Chip Nanobiosensors for Early Detection of Lung Cancer Breath Biomarkers

ACS Sensors, Год журнала: 2024, Номер 9(9), С. 4469 - 4494

Опубликована: Сен. 9, 2024

Lung cancer remains a global health concern, demanding the development of noninvasive, prompt, selective, and point-of-care diagnostic tools. Correspondingly, breath analysis using nanobiosensors has emerged as promising noninvasive nose-on-chip technique for early detection lung through monitoring diversified biomarkers such volatile organic compounds/gases in exhaled breath. This comprehensive review summarizes state-of-the-art breath-based diagnosis employing chemiresistive-module supported by theoretical findings. It unveils fundamental mechanisms biological basis biomarker generation associated with cancer, technological advancements, clinical implementation nanobiosensor-based analysis. explores merits, challenges, potential alternate solutions implementing these settings, including standardization, biocompatibility/toxicity analysis, green sustainable technologies, life-cycle assessment, scheming regulatory modalities. highlights nanobiosensors' role facilitating precise, real-time, on-site leading to improved patient outcomes, enhanced management, remote personalized monitoring. Additionally, integrating biosensors artificial intelligence, machine learning, Internet-of-things, bioinformatics, omics technologies is discussed, providing insights into prospects intelligent sniffing nanobiosensors. Overall, this consolidates knowledge on breathomic biosensor-based screening, shedding light its significance applications advancing medical diagnostics reduce burden hospitals save human lives.

Язык: Английский

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Nanozyme-enhanced paper-based biosensor technologies

TrAC Trends in Analytical Chemistry, Год журнала: 2024, Номер 172, С. 117573 - 117573

Опубликована: Фев. 9, 2024

Nanozymes, enzyme-mimetic nanomaterials that combine features of nanoscale material with the catalytic properties enzymes, have undergone rapid development in recent years. While enzymes remained integral to biosensor technologies for past few decades, potential nanozymes overcome low stability and high production costs biological is turning them into promising candidates. Over decade, been explored a myriad biosensing applications. However, only small subset these efforts has resulted devices platforms are potentially suitable on-site/point-of-care monitoring. To promote this area, review first provides concise overview different paper-based technologies, their architecture functionality, language conducive nanozyme research community. The review, then, critically discusses progress made integration on-site detection food contaminants, environmental pollutants, disease biomarkers. challenges associated transition solution-based biosensors relevant highlighted, strategies those proposed. We envision could narrow gap impeding translation nanozyme-based from laboratories real-world scenarios by encouraging consolidated cross-disciplinary trans-sectoral efforts.

Язык: Английский

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Role of Machine Learning Assisted Biosensors in Point-of-Care-Testing For Clinical Decisions

ACS Sensors, Год журнала: 2024, Номер 9(9), С. 4495 - 4519

Опубликована: Авг. 15, 2024

Point-of-Care-Testing (PoCT) has emerged as an essential component of modern healthcare, providing rapid, low-cost, and simple diagnostic options. The integration Machine Learning (ML) into biosensors ushered in a new era innovation the field PoCT. This article investigates numerous uses transformational possibilities ML improving for algorithms, which are capable processing interpreting complicated biological data, have transformed accuracy, sensitivity, speed procedures variety healthcare contexts. review explores multifaceted applications models, including classification regression, displaying how they contribute to capabilities biosensors. roles ML-assisted electrochemical sensors, lab-on-a-chip electrochemiluminescence/chemiluminescence colorimetric wearable sensors diagnosis explained detail. Given increasingly important role PoCT, this study serves valuable reference researchers, clinicians, policymakers interested understanding emerging landscape point-of-care diagnostics.

Язык: Английский

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Graphene-Enhanced Terahertz Metamaterial Biosensor for Tuberculosis Detection with XGBoost-Based Machine Learning Optimization

Plasmonics, Год журнала: 2025, Номер unknown

Опубликована: Фев. 20, 2025

Язык: Английский

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Machine learning enabled microneedle-based colorimetric pH sensing patch for wound health monitoring and meat spoilage detection

Microchemical Journal, Год журнала: 2024, Номер 200, С. 110350 - 110350

Опубликована: Март 19, 2024

Язык: Английский

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Navigating the development of silver nanoparticles based food analysis through the power of artificial intelligence

Food Chemistry, Год журнала: 2024, Номер 445, С. 138800 - 138800

Опубликована: Фев. 18, 2024

Язык: Английский

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Artificial Intelligence−Powered Electrochemical Sensor: Recent Advances, Challenges, and Prospects

Heliyon, Год журнала: 2024, Номер 10(18), С. e37964 - e37964

Опубликована: Сен. 1, 2024

Язык: Английский

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Advances in Wearable Biosensors for Healthcare: Current Trends, Applications, and Future Perspectives

Biosensors, Год журнала: 2024, Номер 14(11), С. 560 - 560

Опубликована: Ноя. 18, 2024

Wearable biosensors are a fast-evolving topic at the intersection of healthcare, technology, and personalized medicine. These sensors, which frequently integrated into clothes accessories or directly applied to skin, provide continuous, real-time monitoring physiological biochemical parameters such as heart rate, glucose levels, hydration status. Recent breakthroughs in downsizing, materials science, wireless communication have greatly improved functionality, comfort, accessibility wearable biosensors. This review examines present status biosensor with an emphasis on advances sensor design, fabrication techniques, data analysis algorithms. We analyze diverse applications clinical diagnostics, chronic illness management, fitness tracking, emphasizing their capacity transform health facilitate early disease diagnosis. Additionally, this seeks shed light future healthcare wellness by summarizing existing trends new advancements.

Язык: Английский

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Cortisol: Biosensing and detection strategies

Clinica Chimica Acta, Год журнала: 2024, Номер 562, С. 119888 - 119888

Опубликована: Июль 24, 2024

Язык: Английский

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Integrating machine learning and biosensors in microfluidic devices: A review

Biosensors and Bioelectronics, Год журнала: 2024, Номер 263, С. 116632 - 116632

Опубликована: Авг. 3, 2024

Microfluidic devices are increasingly widespread in the literature, being applied to numerous exciting applications, from chemical research Point-of-Care devices, passing through drug development and clinical scenarios. Setting up these microenvironments, however, introduces necessity of locally controlling variables involved phenomena under investigation. For this reason, literature has deeply explored possibility introducing sensing elements investigate physical quantities biochemical concentration inside microfluidic devices. Biosensors, particularly, well known for their high accuracy, selectivity, responsiveness. However, signals could be challenging interpret must carefully analysed carry out correct information. In addition, proper data analysis been demonstrated even increase biosensors' mentioned qualities. To regard, machine learning algorithms undoubtedly among most suitable approaches undertake job, automatically highlighting biosensor signals' characteristics at best. Interestingly, it was also benefit themselves, a new paradigm that is starting name "intelligent microfluidics", ideally closing benefic interaction disciplines. This review aims demonstrate advantages triad microfluidics-biosensors-machine learning, which still little used but great perspective. After briefly describing single entities, different sections will benefits dual interactions, applications where reviewed employed.

Язык: Английский

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