Recent Advances in Cardiovascular Disease Biosensors and Monitoring Technologies

Enzyme-free amplification-enhanced ratiometric fluorescence method for highly sensitive detection of acute myocardial infarction biomarkers

A wide range of proteins, including enzymes, hormones, immune factors and regulatory proteins, are essential for a variety of physiological processes. Dysregulation of the levels of specific proteins in organisms is known to adversely affects the human body. Given the pathophysiological significance of cardiac troponin I (cTnI), simple methods for detecting the sensitivity and selectivity of cTnI in biological systems are in high demand and have therefore been extensively explored. Nonetheless, the early detection of low concentrations of cTnI in the human body continues to be a focal point and area of interest in bioassays, due to the low levels and intricate composition of biomarkers in bodily fluids (e.g., blood, sweat, urine, and saliva), which impose rigorous demands on the sensitivity and stability of detection methods. The assay platform is isothermal, homogeneous and has simple experimental conditions without proteases. Using ratiometric fluorescence with built-in self-correction, we achieved low background values and improved the accuracy of the assay results. Our method enhances detection sensitivity by utilizing the cycling of probe X during strand replacement. Triple sensitization was achieved by combining ratiometric fluorescence on the basis of normal strand displacement reaction. In the experiment, the dual sensitization was reflected by the high sensitivity (0.001 ng/mL) and wide linear detection range (0.001 ng/mL∼1000 ng/mL) of cTnI in real serum samples. In particular, the snapshots of the simulation process were recorded through accurate simulation calculations and multidimensional characterization analysis, which revealed the changes in the system energy during the simulation process. The sensing platform combines multiple technological advantages, and we are optimistic that the versatility of this research has great potential for application in the fields of early screening and diagnosis and military medical applications.

Ultrasensitive magnetic nanomechanical biosensors for simultaneous detection of multiple cardiovascular disease biomarkers in a single blood drop

Cardiovascular disease (CVD) is the number one cause of death, and the early prevention of CVD is considered the most useful and cost-effective intervention strategy, highlighting the critical need for frequent and long-term monitoring cardiac abnormalities. However, traditional blood test methods often require considerable volumes of blood (>10 mL), which could burden physical health, especially for individuals in poor health. Here, we report a novel magnetic nanomechanical sensor (MNS) capable of simultaneously detecting multiple CVD biomarkers (brain natriuretic peptide (BNP), cardiac troponin I (cTnI) and creatine kinase MB (CK-MB)) in a single drop of blood (<1 μL). Relying on the force-sensitive microcantilevers and robust magnetic force, MNS can directly detect blood samples with a detection sensitivity for BNP as low as 0.1 pg/mL. Moreover, we improved the MNS sensitivity by reducing nonspecific adsorption and focusing the force on specific locations on the sensor surface. The effectiveness of the MNS was demonstrated through the detection of samples from clinical CVD patients and healthy individuals. Given its ultrasensitive, trace-sample requirement, and ability to monitor multiple biomarkers, the MNS holds significant potential for frequent and long-term monitoring-not only for CVD but also for the prevention and management of other chronic diseases.

Innovative Applications and Perspectives of Surface-Enhanced Raman Spectroscopy Technology in Biomedicine

Surface-enhanced Raman spectroscopy (SERS) has become a revolutionary technique in the biomedical field, providing unparalleled sensitivity for the detection and characterization of biological samples. In this review, recent SERS innovations are comprehensively discussed, including advanced substrate materials, different SERS detection strategies, and multimodal approaches that combine SERS with other biotechnologies. Among them, the role of SERS in the accurate diagnosis of tumors is highlighted, which has promoted accurate molecular analysis and real-time monitoring of treatment effects. In addition, the growing potential of SERS in the treatment of chronic diseases such as cardiovascular disease, diabetes, and neurodegenerative diseases is discussed. Moreover, the integration with microfluidic chip systems for precise single-cell analysis is presented. To give a forward-looking view, the key challenges faced by SERS technology are also proposed, and possible solutions to overcome these obstacles are provided.

Zero Background Visualizing Phosphorescence Lateral Flow Immunoassay of Cardiac Troponin I for Rapid and Accurate Diagnosis of Myocardial Infarction

Fluorescence lateral flow immunoassays (FL-LFIA) have attracted considerable attention in clinical diagnosis due to their outstanding merits of affordable, sensitive, on-site, and quick detection. However, they are still plagued by significant signal interference, such as autofluorescence and scattered light. The development of high-performance and robust phosphors, i.e., label probes featuring with the character of low/no optical background, remains a great challenge. Herein, we report a novel visualized phosphorescence LFIA (Phos-LFIA), where the composite microspheres, i.e., carbon dots (CDs) covalently embedded in dendritic mesoporous silicon nanoparticles (DMSNs), were designed and selected as the report probes. The obtained CDs@DMSNs revealed uniform morphologies and particle sizes, as well as ultralong (lifetime: 1.14 s, visible for over 8 s to naked eyes) room temperature phosphorescence (RTP) in aqueous solution. As competitive nanotags, CDs@DMSNs were designed for an ultralong phosphorescence-based time-gated LFIA for cardiac troponin I (cTnI) without optical interference. The fabricated Phos-LFIA test strips demonstrated zero-background signal and were applied for highly sensitive cTnI detection in both buffer and a complex serum matrix, with corresponding limits of detection (LODs) of 0.19 and 0.21 ng/mL, respectively. For a clinical validation, the proposed Phos-LFIA revealed an excellent clinical analytical performance (sensitivity: 95.45%, specificity: 88.9%, κ value: 0.85), demonstrating its potential for rapid and accurate diagnosis of myocardial infarction. This work provided a promising background-free probe for FL-LFIA, and it would also open an opportunity for developing highly sensitive screening platforms for other targets through modifying different recognition ligands onto CDs@DMSNs.

Nanoparticle biosensors for cardiovascular disease detection

Early detection and management of cardiovascular diseases (CVDs) are crucial for patient survival and long-term health. CVD biomarkers such as cardiac Troponin-I (cTnI), N-terminal pro-brain natriuretic peptide (NT-proBNP), creatine kinase MB (CK-MB), Galectin-3 (Gal-3), etc are released into the circulation following heart muscle injury, ie, acute myocardial infarction (AMI). Biosensor technology including the use of nanoparticles can be designed to target specific biomarkers associated with CVD, enabling early detection and more rapid intervention to decrease morbidity and mortality. To date, with the combination of developed nanoparticles, several optical and electrochemical-based biosensors have successfully been used detection of CVD biomarkers. Nanomaterials, when introduced as the modifiers of sensor surfaces like electrodes and gold chips, can result in the more comprehensive and more effective immobilization of capture molecules, ie, antibodies, aptamers and other ligands, due to their large surface area. In recent years, inorganic nanoparticles have regularly been used in the production of biosensors mostly due to their excellent response intensification, adaptable functionalization chemistry, shape control, good biocompatibility, and great stability. In this review, we discuss the application of different kinds of nanoparticles for the sensitive and specific detection of CVD biomarkers.

Biosensors for early stroke detection

This article aims to provide a comprehensive review of the latest advances in biosensor technology for early stroke diagnosis. Analyzing current research from authoritative databases highlights the significance of biosensors in improving stroke detection and treatment outcomes, discusses their diagnostic capabilities, and addresses the challenges that must be overcome for broader clinical application. This review utilizes updated information and valid research from ISI, Google Scholar, Science Direct, Scopus, and PubMed to examine recent developments in biosensors applicable to early stroke diagnosis. The results indicate that biosensors are crucial for the early detection of strokes, and enhance treatment efficacy. The biosensors studied in this research serve as rapid and non-intrusive diagnostic instruments with exceptional precision and detection capabilities. Cutting-edge biosensors can identify distinct stroke-related biomarkers, offering rapid and non-invasive diagnostic solutions to improve stroke care outcomes. Despite these advancements, significant challenges remain regarding the sensitivity, specificity, and reliability of biosensors. These issues must be resolved to facilitate their widespread implementation in clinical settings.

Clinical Laboratory Validation Study of a High Sensitivity Troponin I Assay on a POCT (Point of Care Testing) Device

Background

In Acute Coronary Syndrome without ST-segment elevation, the use of high-sensitivity troponins in rapid protocols is considered the gold standard for diagnostic exclusion/confirmation, in conjunction with clinical stratification. The biggest concern regarding the techniques for troponin evaluation is the time required between collection and delivery of the result.

Objective

The objective of the present study is the clinical/laboratory validation of a POCT device for TnI.

Methods

In the first phase of the study, samples from 108 patients with known troponin values High Sensitivity Automated Troponin T (TnT) assay from Roche Diagnostics were analyzed for analytical comparability between hs-cTnI of the Analyzer Atellica® vTLi and hs-cTnT Cobas®. The second phase of the study was performed with samples from 51 patients who reported to the emergency department with chest pain for a clinical prospective evaluation and correlation between the hs-cTnI assays of the Analyzer Atellica® vTLi, hs-cTnT Cobas® and Atellica IM 1300.

Results

There was a correlation between the POCT Atellica® vTLi and hs-cTnT Cobas® in the serum samples of the control group (r = 0.660, p < 0.0001). Besides, there was a correlation between the Atellica® vTLi, serum hs-cTnT Cobas®, plasma hs-cTnT Cobas®, serum Atellica IM and plasma Atellica IM 1300 platforms in the second phase (p < 0.0001 in all cases).

Conclusion

In the present study, the Siemens POCT Atellica® vTLi device showed excellent performance in laboratory validation and correlation with the high-sensitivity TnT assay in different troponin concentration ranges. Given these results, the device can be used in institutions that intend to use a POCT device for 0- and 1-hour chest pain protocols.

How to identify patient perception of AI voice robots in the follow-up scenario? A multimodal identity perception method based on deep learning

OBJECTIVES

Post-discharge follow-up stands as a critical component of post-diagnosis management, and the constraints of healthcare resources impede comprehensive manual follow-up. However, patients are less cooperative with AI follow-up calls or may even hang up once AI voice robots are perceived. To improve the effectiveness of follow-up, alternative measures should be taken when patients perceive AI voice robots. Therefore, identifying how patients perceive AI voice robots is crucial. This study aims to construct a multimodal identity perception model based on deep learning to identify how patients perceive AI voice robots.

METHODS

Our dataset includes 2030 response audio recordings and corresponding texts from patients. We conduct comparative experiments and perform an ablation study. The proposed model employs a transfer learning approach, utilizing BERT and TextCNN for text feature extraction, AST and LSTM for audio feature extraction, and self-attention for feature fusion.

RESULTS

Our model demonstrates superior performance against existing baselines, with a precision of 86.67%, an AUC of 84%, and an accuracy of 94.38%. Additionally, a generalization experiment was conducted using 144 patients' response audio recordings and corresponding text data from other departments in the hospital, confirming the model's robustness and effectiveness.

CONCLUSION

Our multimodal identity perception model can identify how patients perceive AI voice robots effectively. Identifying how patients perceive AI not only helps to optimize the follow-up process and improve patient cooperation, but also provides support for the evaluation and optimization of AI voice robots.

DNA Nanomaterial-Based Electrochemical Biosensors for Clinical Diagnosis

Sensitive and quantitative detection of chemical and biological molecules for screening, diagnosis and monitoring diseases is essential to treatment planning and response monitoring. Electrochemical biosensors are fast, sensitive, and easy to miniaturize, which has led to rapid development in clinical diagnosis. Benefiting from their excellent molecular recognition ability and high programmability, DNA nanomaterials could overcome the Debye length of electrochemical biosensors by simple molecular design and are well suited as recognition elements for electrochemical biosensors. Therefore, to enhance the sensitivity and specificity of electrochemical biosensors, significant progress has been made in recent years by optimizing the DNA nanomaterials design. Here, the establishment of electrochemical sensing strategies based on DNA nanomaterials is reviewed in detail. First, the structural design of DNA nanomaterial is examined to enhance the sensitivity of electrochemical biosensors by improving recognition and overcoming Debye length. In addition, the strategies of electrical signal transduction and signal amplification based on DNA nanomaterials are reviewed, and the applications of DNA nanomaterial-based electrochemical biosensors and integrated devices in clinical diagnosis are further summarized. Finally, the main opportunities and challenges of DNA nanomaterial-based electrochemical biosensors in detecting disease biomarkers are presented in an aim to guide the design of DNA nanomaterial-based electrochemical devices with high sensitivity and specificity.

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

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

Wearable and Implantable Soft Robots

Soft robotics presents innovative solutions across different scales. The flexibility and mechanical characteristics of soft robots make them particularly appealing for wearable and implantable applications. The scale and level of invasiveness required for soft robots depend on the extent of human interaction. This review provides a comprehensive overview of wearable and implantable soft robots, including applications in rehabilitation, assistance, organ simulation, surgical tools, and therapy. We discuss challenges such as the complexity of fabrication processes, the integration of responsive materials, and the need for robust control strategies, while focusing on advances in materials, actuation and sensing mechanisms, and fabrication techniques. Finally, we discuss the future outlook, highlighting key challenges and proposing potential solutions.

A comprehensive review of transduction methods of lectin-based biosensors in biomedical applications

Biosensors have emerged as a pivotal technology in the biomedical field, significantly enhancing the rapidity and precision of biomolecule detection. These advancements are instrumental in refining diagnostic processes, optimizing treatments, and monitoring diseases more effectively. Central to the development of highly sensitive, selective, and stable biosensors are the bioreceptor and transducer components. This review paper discusses the use of lectin as a bioreceptor and explores the prevalent transducer methods employed in lectin-based biosensors, with a particular emphasis on their applications in biomedical research. The paper meticulously examines various transducers, with a spotlight on electrochemical and optical transduction methods, drawing from a wealth of previous studies to offer a comprehensive perspective on the application of these sensors in critical biomedical areas. These areas include early diagnosis, therapeutic interventions, and continuous health monitoring. Moreover, the review addresses the challenges of implementing lectin-based biosensors, such as specificity and stability issues. It also explores future possibilities, examining potential trends to overcome these challenges. In summary, this comprehensive analysis aspires to equip researchers with profound insights into the transformative potential of lectin-based biosensors, underscoring their significant role in the evolution of biomedical research and the broader healthcare landscape.

Enhancing visual seismocardiography in noisy environments with adaptive bidirectional filtering for Cardiac Health Monitoring

BACKGROUND

Wearable sensors have revolutionized cardiac health monitoring, with Seismocardiography (SCG) at the forefront due to its non-invasive nature. However, the substantial motion artefacts have hindered the translation of SCG-based medical applications, primarily induced by walking. In contrast, our innovative technique, Adaptive Bidirectional Filtering (ABF), surpasses these challenges by refining SCG signals more effectively than any motion-induced noise. ABF leverages a noise-cancellation algorithm, operating on the benefits of the Redundant Multi-Scale Wavelet Decomposition (RMWD) and the bidirectional filtering framework, to achieve optimal signal quality.

METHODOLOGY

The ABF technique is a two-stage process that diminishes the artefacts emanating from motion. The first step by RMWD is the identification of the heart-associated signals and the isolating samples with those related frequencies. Subsequently, the adaptive bidirectional filter operates in two dimensions: it uses Time-Frequency masking that eliminates temporal noise while engaging in non-negative matrix Decomposition to ensure spatial correlation and dorsoventral vibration reduction jointly. The main component that is altered from the other filters is the recursive structure that changes to the motion-adapted filter, which uses vertical axis accelerometer data to differentiate better between accurate SCG signals and motion artefacts.

OUTCOME

Our empirical tests demonstrate exceptional signal improvement with the application of our ABF approach. The accuracy in heart rate estimation reached an impressive r-squared value of 0.95 at - 20 dB SNR, significantly outperforming the baseline value, which ranged from 0.1 to 0.85. The effectiveness of the motion-artifact-reduction methodology is also notable at an SNR of - 22 dB. Consequently, ECG inputs are not required. This method can be seamlessly integrated into noisy environments, enhancing ECG filtering, automatic beat detection, and rhythm interpretation processes, even in highly variable conditions. The ABF method effectively filters out up to 97% of motion-related noise components within the SCG signal from implantable devices. This advancement is poised to become an integral part of routine patient monitoring.

Soft Bioelectronics for Heart Monitoring

Cardiovascular diseases (CVDs) are a predominant global health concern, accounting for over 17.9 million deaths in 2019, representing approximately 32% of all global fatalities. In North America and Europe, over a million adults undergo cardiac surgeries annually. Despite the benefits, such surgeries pose risks and require precise postsurgery monitoring. However, during the postdischarge period, where monitoring infrastructures are limited, continuous monitoring of vital signals is hindered. In this area, the introduction of implantable electronics is altering medical practices by enabling real-time and out-of-hospital monitoring of physiological signals and biological information postsurgery. The multimodal implantable bioelectronic platforms have the capability of continuous heart sensing and stimulation, in both postsurgery and out-of-hospital settings. Furthermore, with the emergence of machine learning algorithms into healthcare devices, next-generation implantables will benefit artificial intelligence (AI) and connectivity with skin-interfaced electronics to provide more precise and user-specific results. This Review outlines recent advancements in implantable bioelectronics and their utilization in cardiovascular health monitoring, highlighting their transformative deployment in sensing and stimulation to the heart toward reaching truly personalized healthcare platforms compatible with the Sustainable Development Goal 3.4 of the WHO 2030 observatory roadmap. This Review also discusses the challenges and future prospects of these devices.

A Plasmonic Nanoledge Array Sensor for Selective Detection of Cardiovascular Disease Biomarkers in Human Whole Blood

Optical sensors face challenges when detecting ultralow amounts of analytes in whole blood, including signal quenching due to optical absorption and false positives due to nonspecific binding. This study introduces gold nanoscale array features termed nanoledges (NLs), which interact with incident white light to produce a transmitted surface plasmon resonance (tSPR) signal. This extraordinary optical transmission (EOT) spectrum occurs in the near-infrared (NIR) region, thereby minimizing signal quenching caused by visible-light absorption from blood proteins and pigments. To develop a sensitive, selective, and label-free optical biosensor for detecting various levels of cardiac troponin I (cTnI) in very small volumes of whole blood samples, DNA aptamers are tethered to the NL surface, specifically binding to the cTnI biomarker. This biological binding activity alters the refractive index at the NL surface, causing a peak shift in the EOT spectrum and enabling quantification of cTnI levels. The NL array chip demonstrated high sensitivity for cTnI detection in buffer, human serum (HS), and human whole blood (HB), with detection limits of 0.079, 0.084, and 0.097 ng/mL, respectively. Control measurements using blank target mediums and those containing up to 125 ng/mL of other proteins, such as myoglobin, creatine kinase, and heparin, showed minimal interference and high specificity. The NL plasmonic array's performance in biosensing underscores its promise for clinical analysis and its potential development as a point-of-care platform for early cardiovascular disease (CVD) diagnostics.

Innovations in Biosensor Technologies for Healthcare Diagnostics and Therapeutic Drug Monitoring: Applications, Recent Progress, and Future Research Challenges

This comprehensive review delves into the forefront of biosensor technologies and their critical roles in disease biomarker detection and therapeutic drug monitoring. It provides an in-depth analysis of various biosensor types and applications, including enzymatic sensors, immunosensors, and DNA sensors, elucidating their mechanisms and specific healthcare applications. The review highlights recent innovations such as integrating nanotechnology, developing wearable devices, and trends in miniaturisation, showcasing their transformative potential in healthcare. In addition, it addresses significant sensitivity, specificity, reproducibility, and data security challenges, proposing strategic solutions to overcome these obstacles. It is envisaged that it will inform strategic decision-making, drive technological innovation, and enhance global healthcare outcomes by synthesising multidisciplinary insights.

An integrated electronic tag-based vertical flow assay (e-VFA) with micro-sieve and AlGaN/GaN HEMT sensors for multi-target detection in actual saliva

Vertical flow assay (VFA) is an effective point-of-care (POC) diagnostic tool for widespread application. Nevertheless, the lack of multi-target detection and multi-signal readout capability still remains a challenge. Herein, a brand new VFA scheme for multi-target saliva detection based on electronic tags was proposed, where AlGaN/GaN HEMT sensors modified with different bio-receptors as electronic tags endowed the VFA with multi-target detection capability. In addition, the use of electronic tags instead of optical tags allowed the VFA to simultaneously carry out direct multi-target readouts, which ensure effective POC diagnostics for saliva analysis. Moreover, by integrating a hydrophilically optimized micro-sieve, impurities like sticky filaments, epidermal cells and other large-scale charged particles in saliva were effectively screened, which enabled the direct detection of saliva using AlGaN/GaN HEMT sensors. Glucose, urea, and cortisol were selected to verify the feasibility of the multi-target e-VFA scheme, and the results showed that the limit of detection (LOD) was as low as 100 aM. The linear response was demonstrated in the dynamic range of 100 aM to 100 μM, and the specificity, long-term stability and validity of the actual saliva test were also verified. These results demonstrated that the as-proposed e-VFA has potential for application in saliva detection for simultaneous multi-target detection, and it is expected to achieve the real-time detection of more biological targets in saliva.

Cardiac Troponin I-Responsive Nanocomposite Materials for Voltammetric Monitoring of Acute Myocardial Infarction

Acute myocardial infarction (AMI) is a severe cardiovascular disease characterized by heart muscle damage due to inadequate blood supply, leading to a life-threatening risk of heart attack. Herein, we report on the design of polyaminophenol-based thin film functional polymers and their thorough optimization by electrochemical, spectroscopic, and microscopic techniques to develop a high-performance point-of-care voltammetric monitoring system. Molecularly imprinted polymer-based cTnI-responsive nanocomposite materials were prepared on an electrode surface by imprinting a specific cTnI epitope, integrating polyaminophenol electrodeposition, along with gold nanoparticles (AuNPs) and graphene quantum dots (GQDs). The characterization techniques, including cyclic and square wave voltammetries, electrochemical impedance spectroscopy, atomic force microscopy, fluorescence microscopy, attenuated total reflection-Fourier transform infrared spectroscopy (ATR-FTIR), and contact angle measurements proved the efficient fabrication of the voltammetric monitoring system relying on cTnI-responsive functional thin films. The sensing platform prepared with the optimized nanocomposite composition of AuNPs, GQDs, and molecularly imprinted polymers exhibited very high sensitivity, reproducibility, specificity, and affinity toward cTnI. The sensor showed a storage stability of 30 days, demonstrating great potential for use in early and point-of-care diagnosis of AMI with its 18 min detection time.

Wearable biosensors in cardiovascular disease

This review provides a comprehensive overview of the latest advancements in wearable biosensors, emphasizing their applications in cardiovascular disease monitoring. Initially, the key sensing signals and biomarkers crucial for cardiovascular health, such as electrocardiogram, phonocardiography, pulse wave velocity, blood pressure, and specific biomarkers, are highlighted. Following this, advanced sensing techniques for cardiovascular disease monitoring are examined, including wearable electrophysiology devices, optical fibers, electrochemical sensors, and implantable cardiac devices. The review also delves into hydrogel-based wearable electrochemical biosensors, which detect biomarkers in sweat, interstitial fluids, saliva, and tears. Further attention is given to flexible electronics-based biosensors, including resistive, capacitive, and piezoelectric force sensors, as well as resistive and pyroelectric temperature sensors, flexible biochemical sensors, and sensor arrays. Moreover, the discussion extends to polymer-based wearable sensors, focusing on innovations in contact lens, textile-type, patch-type, and tattoo-type sensors. Finally, the review addresses the challenges associated with recent wearable biosensing technologies and explores future perspectives, highlighting potential groundbreaking avenues for transforming wearable sensing devices into advanced diagnostic tools with multifunctional capabilities for cardiovascular disease monitoring and other healthcare applications.

Automatic ultrasensitive lateral flow immunoassay based on a color-enhanced signal amplification strategy

Lateral flow immunoassays (LFIAs) are an essential and widely used point-of-care test for medical diagnoses. However, commercial LFIAs still have low sensitivity and specificity. Therefore, we developed an automatic ultrasensitive dual-color enhanced LFIA (DCE-LFIA) by applying an enzyme-induced tyramide signal amplification method to a double-antibody sandwich LFIA for antigen detection. The DCE-LFIA first specifically captured horseradish peroxidase (HRP)-labeled colored microspheres at the Test line, and then deposited a large amount of tyramide-modified signals under the catalytic action of HRP to achieve the color superposition. A limit of detection (LOD) of 3.9 pg/mL and a naked-eye cut-off limit of 7.8 pg/mL were achieved for detecting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) nucleoprotein. Additionally, in the inactivated virus detections, LOD equivalent to chemiluminescence (0.018 TCID50/mL) was obtained, and it had excellent specificity under the interference of other respiratory viruses. High sensitivity has also been achieved for detection of influenza A, influenza B, cardiac troponin I, and human chorionic gonadotrophin using this DCE-LFIA, suggesting the assay is universally applicable. To ensure the convenience and stability in practical applications, we created an automatic device. It provides a new practical option for point-of-care test immunoassays, especially ultra trace detection and at-home testing.

Advancements in electrochemical biosensing of cardiovascular disease biomarkers

Cardiovascular diseases (CVDs) stand as a predominant global health concern, introducing vast socioeconomic challenges. In addressing this pressing dilemma, enhanced diagnostic modalities have become paramount, positioning electrochemical biosensing as an instrumental innovation. This comprehensive review navigates the multifaceted terrain of CVDs, elucidating their defining characteristics, clinical manifestations, therapeutic avenues, and intrinsic risk factors. Notable emphasis is placed on pivotal diagnostic tools, spotlighting cardiac biomarkers distinguished by their unmatched clinical precision in terms of relevance, sensitivity, and specificity. Highlighting the broader repercussions of CVDs, there emerges an accentuated need for refined diagnostic strategies. Such an exploration segues into a profound analysis of electrochemical biosensing, encapsulating its foundational principles, diverse classifications, and integral components, notably recognition molecules and transducers. Contemporary advancements in biosensing technologies are brought to the fore, emphasizing pioneering electrode architectures, cutting-edge signal amplification processes, and the synergistic integration of biosensors with microfluidic platforms. At the core of this discourse is the demonstrated proficiency of biosensors in detecting cardiovascular anomalies, underpinned by empirical case studies, systematic evaluations, and clinical insights. As the narrative unfolds, it addresses an array of inherent challenges, spanning intricate technicalities, real-world applicability constraints, and regulatory considerations, finally, by casting an anticipatory gaze upon the future of electrochemical biosensing, heralding a new era of diagnostic tools primed to revolutionize cardiovascular healthcare.

Bioactive Metal-Organic Frameworks as a Distinctive Platform to Diagnosis and Treat Vascular Diseases

Vascular diseases (VDs) pose the leading threat worldwide due to high morbidity and mortality. The detection of VDs is commonly dependent on individual signs, which limits the accuracy and timeliness of therapies, especially for asymptomatic patients in clinical management. Therefore, more effective early diagnosis and lesion-targeted treatments remain a pressing clinical need. Metal-organic frameworks (MOFs) are porous crystalline materials formed by the coordination of inorganic metal ions and organic ligands. Due to their unique high specific surface area, structural flexibility, and functional versatility, MOFs are recognized as highly promising candidates for diagnostic and therapeutic applications in the field of VDs. In this review, the potential of MOFs to act as biosensors, contrast agents, artificial nanozymes, and multifunctional therapeutic agents in the diagnosis and treatment of VDs from the clinical perspective, highlighting the integration between clinical methods with MOFs is generalized. At the same time, multidisciplinary cooperation from chemistry, physics, biology, and medicine to promote the substantial commercial transformation of MOFs in tackling VDs is called for.

Smart Graphene Textiles for Biopotential Monitoring: Laser-Tailored Electrochemical Property Enhancement

While most of the research in graphene-based materials seeks high electroactive surface area and ion intercalation, here, we show an alternative electrochemical behavior that leverages graphene's potential in biosensing. We report a novel approach to fabricate graphene/polymer nanocomposites with near-record conductivity levels of 45 Ω sq-1 and enhanced biocompatibility. This is realized by laser processing of graphene oxide in a sandwich structure with a thin (100 μm) polyethylene terephthalate film on a textile substrate. Such hybrid materials exhibit high conductivity, low polarization, and stability. In addition, the nanocomposites are highly biocompatible, as evidenced by their low cytotoxicity and good skin adhesion. These results demonstrate the potential of graphene/polymer nanocomposites for smart clothing applications.

Biosensing Platforms for Cardiac Biomarker Detection

Myocardial infarction (MI) is a cardiovascular disease that occurs when there is an elevated demand for myocardial oxygen as a result of the rupture or erosion of atherosclerotic plaques. Globally, the mortality rates associated with MI are steadily on the rise. Traditional diagnostic biomarkers employed in clinical settings for MI diagnosis have various drawbacks, prompting researchers to investigate fast, precise, and highly sensitive biosensor platforms and technologies. Biosensors are analytical devices that combine biological elements with physicochemical transducers to detect and quantify specific compounds or analytes. These devices play a crucial role in various fields including healthcare, environmental monitoring, food safety, and biotechnology. Biosensors developed for the detection of cardiac biomarkers are typically electrochemical, mass, and optical biosensors. Nanomaterials have emerged as revolutionary components in the field of biosensing, offering unique properties that significantly enhance the sensitivity and specificity of the detection systems. This review provides a comprehensive overview of the advancements and applications of nanomaterial-based biosensing systems. Beginning with an exploration of the fundamental principles governing nanomaterials, we delve into their diverse properties, including but not limited to electrical, optical, magnetic, and thermal characteristics. The integration of these nanomaterials as transducers in biosensors has paved the way for unprecedented developments in analytical techniques. Moreover, the principles and types of biosensors and their applications in cardiovascular disease diagnosis are explained in detail. The current biosensors for cardiac biomarker detection are also discussed, with an elaboration of the pros and cons of existing platforms and concluding with future perspectives.

Telehealth of cardiac devices for CVD treatment

This review covers currently available cardiac implantable electronic devices (CIEDs) as well as updated progress in real-time monitoring techniques for CIEDs. A variety of implantable and wearable devices that can diagnose and monitor patients with cardiovascular diseases are summarized, and various working mechanisms and principles of monitoring techniques for Telehealth and mHealth are discussed. In addition, future research directions are presented based on the rapidly evolving research landscape including Artificial Intelligence (AI).

Biosensors for the detection of pathogenic bacteria: current status and future perspectives

Pathogenic microorganisms pose significant threats to human health, food safety and environmental integrity. Rapid and accurate detection of these pathogens is essential to mitigate their impact. Fast, sensitive detection methods such as biosensors also play a critical role in preventing outbreaks and controlling their spread. In recent years, biosensors have emerged as a revolutionary technology for pathogen detection. This review aims to present the current developments in biosensor technology, investigate the methods by which these developments are used in the detection of pathogenic bacteria and highlight future perspectives on the subject.

One-Stop Plasmonic Nanocube-Excited SERS Immunoassay Platform of Multiple Cardiac Biomarkers for Rapid Screening and Progressive Tracing of Acute Myocardial Infarction

Rapid and precise acute myocardial infarction (AMI) diagnosis is essential for preventing patient death. In addition, the complementary roles of creatine kinase muscle brain (CK-MB) and cardiac troponin I (cTnI) cardiac biomarkers in the early and late stages of AMI demand their simultaneous detection, which is difficult to implement using conventional fluorescence and electrochemical technologies. Here, a nanotechnology-based one-stop immuno-surface-enhanced Raman scattering (SERS) detection platform is reported for multiple cardiac indicators for the rapid screening and progressive tracing of AMI events. Optimal SERS is achieved using optical property-based, excitation wavelength-optimized, and high-yield anisotropic plasmonic gold nanocubes. Optimal immunoassay reaction efficiencies are achieved by increasing immobilized antibodies. Multiple simultaneous detection strategies are implemented by incorporating two different Raman reports with narrow wavenumbers corresponding to two indicators and by establishing a computational SERS mapping process to accurately detect their concentrations, irrespective of multiple enzymes in the human serum. The SERS platform precisely estimated AMI onset and progressive timing in human serum and made rapid AMI identification feasible using a portable Raman spectrometer. This integrated platform is hypothesized to significantly contribute to emergency medicine and forensic science by providing timely treatment and observation.

A review on hybridization of plasmonic and photonic crystal biosensors for effective cancer cell diagnosis

Cancer causes one in six deaths worldwide, and 1.6 million cancer patients face annual out-of-pocket medical expenditures. In response to these, portable, label-free, highly sensitive, specific, and responsive optical biosensors are under development. Therefore, in this review, the recent advances, advantages, performance analysis, and current challenges associated with the fabrication of plasmonic biosensors, photonic crystals, and the hybridization of both for cancer diagnosis are assessed. The primary focus is on the development of biosensors that combine different shapes, sizes, and optical properties of metallic and dielectric nanoparticles with various coupling techniques. The latter part discusses the challenges and prospects of developing effective biosensors for early cancer diagnosis using dielectric and metallic nanoparticles. These data will help the audience advance research and development of next-generation plasmonic biosensors for effective cancer diagnosis.

A Multichannel Fluorescence Isothermal Amplification Device with Integrated Internet of Medical Things for Rapid Sensing of Pathogens through Deep Learning

The landscape of diagnostic assessments has experienced a paradigm shift driven by the advent of isothermal amplification techniques on point-of-care testing (POCT). The development of compact, portable isothermal amplification devices further emphasizes their transformative influence on diagnostic approaches. However, in prioritizing portability, these devices may exhibit limitations in functionality, rendering them less effective in addressing urgent public health emergencies during sudden pathogen outbreaks. In this paper, an efficient isothermal fluorescence amplification device has been fabricated for the rapid detection of pathogens during public health crises. The device features multichannel capability for simultaneous detection of various targets, integrates with the Internet of Medical Things (IoMT) for remote control and data uploading, and includes a deep learning-based batch processing system for rapid (9.4 ms) and accurate discrimination of pathogen type with excellent accuracy. The device has been successfully employed to simultaneously detect Staphylococcus aureus (SA) and methicillin-resistant Staphylococcus aureus (MRSA) with limits of detection (LODs) of 18 CFU/mL (SA) and 20 CFU/mL (MRSA) within 35 min by multiplex RPA assay and CRISPR/Cas12a-mediated nucleic acid detection assay.

Using Machine Learning and Silver Nanoparticle-Based Surface-Enhanced Raman Spectroscopy for Classification of Cardiovascular Disease Biomarkers

Characterizing complex biofluids using surface-enhanced Raman spectroscopy (SERS) coupled with machine learning (ML) has been proposed as a powerful tool for point-of-care detection of clinical disease. ML is well-suited to categorizing otherwise uninterpretable, patient-derived SERS spectra that contain a multitude of low concentration, disease-specific molecular biomarkers among a dense spectral background of biological molecules. However, ML can generate false, non-generalizable models when data sets used for model training are inadequate. It is thus critical to determine how different SERS experimental methodologies and workflow parameters can potentially impact ML disease classification of clinical samples. In this study, a label-free, broadband, Ag nanoparticle-based SERS platform was coupled with ML to assess simulated clinical samples for cardiovascular disease (CVD), containing randomized combinations of five key CVD biomarkers at clinically relevant concentrations in serum. Raman spectra obtained at 532, 633, and 785 nm from up to 300 unique samples were classified into physiological and pathological categories using two standard ML models. Label-free SERS and ML could correctly classify randomized CVD samples with high accuracies of up to 90.0% at 532 nm using as few as 200 training samples. Spectra obtained at 532 nm produced the highest accuracies with no significant increase achieved using multiwavelength SERS. Sample preparation and measurement methodologies (e.g., different SERS substrate lots, sample volumes, sample sizes, and known variations in randomization and experimental handling) were shown to strongly influence the ML classification and could artificially increase classification accuracies by as much as 27%. This detailed investigation into the proper application of ML techniques for CVD classification can lead to improved data set acquisition required for the SERS community, such that ML on labeled and robust SERS data sets can be practically applied for future point-of-care testing in patients.

Smart Detecting and Versatile Wearable Electrical Sensing Mediums for Healthcare

A rapidly expanding global population and a sizeable portion of it that is aging are the main causes of the significant increase in healthcare costs. Healthcare in terms of monitoring systems is undergoing radical changes, making it possible to gauge or monitor the health conditions of people constantly, while also removing some minor possibilities of going to the hospital. The development of automated devices that are either attached to organs or the skin, continually monitoring human activity, has been made feasible by advancements in sensor technologies, embedded systems, wireless communication technologies, nanotechnologies, and miniaturization being ultra-thin, lightweight, highly flexible, and stretchable. Wearable sensors track physiological signs together with other symptoms such as respiration, pulse, and gait pattern, etc., to spot unusual or unexpected events. Help may therefore be provided when it is required. In this study, wearable sensor-based activity-monitoring systems for people are reviewed, along with the problems that need to be overcome. In this review, we have shown smart detecting and versatile wearable electrical sensing mediums in healthcare. We have compiled piezoelectric-, electrostatic-, and thermoelectric-based wearable sensors and their working mechanisms, along with their principles, while keeping in view the different medical and healthcare conditions and a discussion on the application of these biosensors in human health. A comparison is also made between the three types of wearable energy-harvesting sensors: piezoelectric-, electrostatic-, and thermoelectric-based on their output performance. Finally, we provide a future outlook on the current challenges and opportunities.