Exosomes as a new frontier of cancer liquid biopsy

Molecular Cancer, Journal Year: 2022, Volume and Issue: 21(1)

Published: Feb. 18, 2022

Abstract Liquid biopsy, characterized by minimally invasive detection through biofluids such as blood, saliva, and urine, has emerged a revolutionary strategy for cancer diagnosis prognosis prediction. Exosomes are subset of extracellular vesicles (EVs) that shuttle molecular cargoes from donor cells to recipient play crucial role in mediating intercellular communication. Increasing studies suggest exosomes have great promise serve novel biomarkers liquid since large quantities enriched body fluids involved numerous physiological pathological processes. However, the further clinical application been greatly restrained lack high-quality separation component analysis methods. This review aims provide comprehensive overview on conventional technologies exosome isolation, characterization content detection. Additionally, roles serving potential biopsy diagnosis, treatment monitoring, prediction summarized. Finally, prospects challenges applying exosome-based precision medicine evaluated.

Language: Английский

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Advancing Biosensors with Machine Learning

ACS Sensors, Journal Year: 2020, Volume and Issue: 5(11), P. 3346 - 3364

Published: Nov. 13, 2020

Chemometrics play a critical role in biosensors-based detection, analysis, and diagnosis. Nowadays, as branch of artificial intelligence (AI), machine learning (ML) have achieved impressive advances. However, novel advanced ML methods, especially deep learning, which is famous for image facial recognition, speech has remained relatively elusive to the biosensor community. Herein, how can be beneficial biosensors systematically discussed. The advantages drawbacks most popular algorithms are summarized on basis sensing data analysis. Specially, methods such convolutional neural network (CNN) recurrent (RNN) emphasized. Diverse ML-assisted electrochemical biosensors, wearable electronics, SERS other spectra-based fluorescence colorimetric comprehensively Furthermore, networks multibiosensor fusion introduced. This review will nicely bridge with greatly expand chemometrics

Language: Английский

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Recent Advances in Electrochemical Biosensors: Applications, Challenges, and Future Scope

Biosensors, Journal Year: 2021, Volume and Issue: 11(9), P. 336 - 336

Published: Sept. 14, 2021

The electrochemical biosensors are a class of which convert biological information such as analyte concentration that is recognition element (biochemical receptor) into current or voltage. Electrochemical depict propitious diagnostic technology can detect biomarkers in body fluids sweat, blood, feces, urine. Combinations suitable immobilization techniques with effective transducers give rise to an efficient biosensor. They have been employed the food industry, medical sciences, defense, studying plant biology, etc. While sensing complex structures and entities, large data obtained, it becomes difficult manually interpret all data. Machine learning helps interpreting In case biosensors, presence impurity affects performance sensor machine removing signals obtained from contaminants obtain high sensitivity. this review, we discuss different types along their applications benefits learning. This followed by discussion on challenges, missing gaps knowledge, solutions field biosensors. review aims serve valuable resource for scientists engineers entering interdisciplinary Furthermore, provides insight type applications, importance (ML) biosensing, challenges future outlook.

Language: Английский

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Exosome Processing and Characterization Approaches for Research and Technology Development

Advanced Science, Journal Year: 2022, Volume and Issue: 9(15)

Published: March 25, 2022

Exosomes are extracellular vesicles that share components of their parent cells and attractive in biotechnology biomedical research as potential disease biomarkers well therapeutic agents. Crucial to realizing this is the ability manufacture high-quality exosomes; however, unlike biologics such proteins, exosomes lack standardized Good Manufacturing Practices for processing characterization. Furthermore, there a well-characterized reference exosome materials aid selection methods isolation, purification, analysis. This review informs technology development by comparing characterization recommending workflows. also provides detailed introduction exosomes, including physical chemical properties, roles normal biological processes progression, summarizes some on-going clinical trials.

Language: Английский

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Designing deep learning studies in cancer diagnostics

Nature reviews. Cancer, Journal Year: 2021, Volume and Issue: 21(3), P. 199 - 211

Published: Jan. 29, 2021

Language: Английский

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The Role of Artificial Intelligence in Early Cancer Diagnosis

Cancers, Journal Year: 2022, Volume and Issue: 14(6), P. 1524 - 1524

Published: March 16, 2022

Improving the proportion of patients diagnosed with early-stage cancer is a key priority World Health Organisation. In many tumour groups, screening programmes have led to improvements in survival, but patient selection and risk stratification are challenges. addition, there concerns about limited diagnostic workforces, particularly light COVID-19 pandemic, placing strain on pathology radiology services. this review, we discuss how artificial intelligence algorithms could assist clinicians (1) asymptomatic at cancer, (2) investigating triaging symptomatic patients, (3) more effectively diagnosing recurrence. We provide an overview main approaches, including historical models such as logistic regression, well deep learning neural networks, highlight their early diagnosis applications. Many data types suitable for computational analysis, electronic healthcare records, images, slides peripheral blood, examples these can be utilised diagnose cancer. also potential clinical implications algorithms, currently used practice. Finally, limitations pitfalls, ethical concerns, resource demands, security reporting standards.

Language: Английский

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Single test-based diagnosis of multiple cancer types using Exosome-SERS-AI for early stage cancers

Nature Communications, Journal Year: 2023, Volume and Issue: 14(1)

Published: March 24, 2023

Abstract Early cancer detection has significant clinical value, but there remains no single method that can comprehensively identify multiple types of early-stage cancer. Here, we report the diagnostic accuracy simultaneous 6 cancers (lung, breast, colon, liver, pancreas, and stomach) by analyzing surface-enhanced Raman spectroscopy profiles exosomes using artificial intelligence in a retrospective study design. It includes classification models recognize signal patterns plasma to both their presence tissues origin. Using 520 test samples, our system identified with an area under curve value 0.970. Moreover, classified tumor organ type 278 patients mean 0.945. The final integrated decision model showed sensitivity 90.2% at specificity 94.4% while predicting 72% positive patients. Since utilizes non-specific analysis signatures, its scope could potentially be expanded include other diseases.

Language: Английский

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Materials with Tunable Optical Properties for Wearable Epidermal Sensing in Health Monitoring

Advanced Materials, Journal Year: 2022, Volume and Issue: 34(26)

Published: March 8, 2022

Advances in wearable epidermal sensors have revolutionized the way that physiological signals are captured and measured for health monitoring. One major challenge is to convert easily readable a convenient way. possibility based on visible readouts. There range of materials whose optical properties can be tuned by parameters such as temperature, pH, light, electric fields. Herein, this review covers highlights set with tunable their integration into Specifically, recent progress, fabrication, applications these summarized discussed. Finally, challenges perspectives next generation devices proposed.

Language: Английский

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Artificial Intelligence in Medical Sensors for Clinical Decisions

ACS Nano, Journal Year: 2021, Volume and Issue: 15(3), P. 3557 - 3567

Published: Feb. 23, 2021

Due to the limited ability of conventional methods and perspective human diagnostics, patients are often diagnosed incorrectly or at a late stage as their disease condition progresses. They may then undergo unnecessary treatments due inaccurate diagnoses. In this Perspective, we offer brief overview on integration nanotechnology-based medical sensors artificial intelligence (AI) for advanced clinical decision support systems help decision-makers healthcare improve how they approach information, insights, surrounding contexts, well promote uptake personalized medicine an individualized basis. Relying these milestones, wearable sensing devices could enable interactive evolving decisions that be used evidence-based analysis recommendations monitoring progress treatment. We present discuss ongoing challenges future opportunities associated with AI-enabled in decisions.

Language: Английский

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Rapid, label-free histopathological diagnosis of liver cancer based on Raman spectroscopy and deep learning

Nature Communications, Journal Year: 2023, Volume and Issue: 14(1)

Published: Jan. 4, 2023

Abstract Biopsy is the recommended standard for pathological diagnosis of liver carcinoma. However, this method usually requires sectioning and staining, well-trained pathologists to interpret tissue images. Here, we utilize Raman spectroscopy study human hepatic samples, developing validating a workflow in vitro intraoperative cancer. We distinguish carcinoma tissues from adjacent non-tumour rapid, non-disruptive, label-free manner by using combined with deep learning, which validated metabolomics. This technique allows detailed identification cancer tissues, including subtype, differentiation grade, tumour stage. 2D/3D images unprocessed slices submicrometric resolution are also acquired based on visualization molecular composition, could assist boundary recognition clinicopathologic diagnosis. Lastly, potential portable handheld system illustrated during surgery real-time

Language: Английский

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