Opal photonic crystal-enhanced upconversion turn-off fluorescent immunoassay for salivary CEA with oral cancer

Electrochemical biosensor based on composite of gold nanoparticle/reduced-graphene oxide/graphitic carbon nitride and a caprolactone polymer for highly sensitive detection of CEA

Carcinoembryonic antigen (CEA) is a broad-spectrum biomarker, and its accurate detection and analysis is important for early clinical diagnosis and treatment. This study aimed to develop a highly sensitive and selective sandwich-type immunosensor based on electrochemical impedance spectroscopy (EIS) for the accurate detection of CEA. A novel composite material, gold nanoparticle/reduced-graphene oxide/graphitic carbon nitride (AuNPs/rGO/g-C3N4), was synthesized with excellent electrical conductivity and a large specific surface area to immobilize biological probes. And ab1-CEA-ab2 formed a sandwich structure of 'antibody-antigen-antibody', which ensured the high selectivity of the biosensor. Furthermore, the introduction of caprolactone polymer (DMPA-PCL) significantly amplifies the impedance signal and improves the sensitivity of the analytical method. Scanning electron microscopy, x-ray diffraction, transmission electron microscopy Fourier transform infrared spectroscopy, and ultraviolet-visible spectrophotometry were used to characterise the prepared AuNPs/rGO/g-C3N4 and DMPA-PCL. Under the optimal conditions, the sensor showed good analytical performance for the detection of CEA with a linear range of 100 fg mL-1-100 ng mL-1 and a detection limit of 83.2 fg mL-1. And the sandwich-type immunosensor showed good selectivity and stability for the recognition of CEA in real samples.

Recent advances in bioactive materials: Future perspectives and opportunities in oral cancer biosensing

Bioactive materials and biosensing technologies are emerging as pivotal tools in the early detection and management of oral cancer, a disease characterized by high morbidity and mortality rates. Recent advancements in nanotechnology have facilitated the development of innovative biosensors that utilize bioactive materials for non-invasive diagnostics, particularly through salivary analysis. These biosensors, including electrochemical, optical, and molecular types, target specific biomarkers such as DNA, RNA, and proteins associated with oral cancer. For instance, metal oxide nanoparticles and gold nanoparticles have shown promise in enhancing the sensitivity and specificity of these diagnostic tools. The integration of these nanomaterials allows for real-time monitoring of biomarker levels in saliva, providing a rapid and accurate means of detecting oral cancer at its nascent stages. Furthermore, the utilization of biosensors can circumvent the limitations of traditional biopsy methods, which are often invasive and time-consuming. By focusing on salivary diagnostics, researchers aim to develop point-of-care testing devices that can be used in various settings, thus improving accessibility to early screening for at-risk populations. This innovative approach not only enhances diagnostic accuracy but also holds potential for personalized treatment strategies by enabling continuous monitoring of disease progression and response to therapy. As research continues to evolve, the combination of bioactive materials with advanced biosensing technologies promises to revolutionize oral cancer diagnostics, ultimately leading to improved patient outcomes through earlier intervention and tailored therapeutic approaches.

Label-free electrochemical biosensor based on AuNPs and PCL-b-PHEAA amphiphilic copolymer for highly sensitive detection of CEA

Carcinoembryonic antigen (CEA) is a broad-spectrum tumor marker expressed in various human cancers. In this study, the electrode loaded with AuNPs was used to replace the traditional electrode, providing more active sites for biological probes and significantly enhancing the sensitivity of the sensor. By constructing an aptamer-antigen-aptamer "sandwich structure," highly selective detection was achieved, effectively avoiding cross-reactions. In addition, the polymer PCL-b-PHEAA was introduced for signal amplification, further improving the detection performance. The label-free method directly utilizes the biological recognition system to obtain more accurate information and is more convenient to operate. Under the optimal conditions, the linear range of CEA detection by electrochemical impedance method was 100 fg mL-1 - 200 ng mL-1, and the limit of detection was 60 fg mL-1. Moreover, this approach demonstrates remarkable sensitivity and exceptional anti-interference capabilities when applied to the analysis of clinical samples. As such, it presents a far more efficient and precise detection solution for the biosensing domain.

Dual-functional co-crystal of streptavidin and ssDNA: electrostatic assembly with positively charged peptide tags

We have achieved a novel co-crystal in which the dual functions of the protein and single-stranded DNA are maintained by introducing a charged peptide tag at the C-terminus of the protein. The functionalities allowed the co-crystals to be modified with high selectivity. Additionally, we have confirmed that energy transfer occurs between the two molecules modified within the co-crystal. Therefore, this co-crystal has the potential as a novel biomaterial applicable to biosensors.

Leveraging Saliva for Insights into Head and Neck Cancer

Head and neck cancer (HNC) represents a heterogeneous group of malignancies with increasing global incidence and notable mortality. Early detection is essential for improving survival rates and minimizing recurrence; however, existing diagnostic methods are often invasive and complex. There is a need for noninvasive and more effective approaches for early detection and real-time monitoring of HNC. Saliva contains various biomolecules that may serve as indicators of HNC. As a result, saliva-based biomarkers have emerged as a transformative approach in the diagnosis and treatment of HNC due to their ease of collection, non-invasiveness, and potential to provide details about biomolecular changes associated with cancer progression. This narrative review synthesizes the current literature on the potential of saliva as a noninvasive diagnostic tool for HNC. It highlights various biomarkers found in saliva, including cell-free DNA, RNA, proteins, and metabolites, and explores emerging technologies in saliva detection that could transform the future of HNC management. Continued research efforts and larger-scale validation studies are essential to fully realize the potential of saliva-based biopsy and help pinpoint notable biomarkers to improve patient outcomes and reduce mortality associated with HNC worldwide.

A review: early detection of oral cancer biomarkers using microfluidic colorimetric point-of-care devices

Oral squamous cell carcinoma (OSCC) is the most common type of head and neck cancers. OSCC constitutes 90% of the head and neck malignancies. The delayed identification of oral cancer is the primary cause of ineffective medical treatment. To address this issue, low-cost, reliable point-of-care devices that can be utilized for large-scale screening, even in low-resource settings, including rural areas and primary healthcare centers, are of great interest. Herein, a comprehensive analysis of numerous salivary biomarkers that exhibit significant variations in concentration between individuals with oral cancer and those without is given. Furthermore, the article explores several point-of-care devices that exhibit potential in the realm of oral cancer detection. The biomarkers are discussed with a focus on their structural characteristics and role in oral cancer progression. The devices based on colorimetry and microfluidics are discussed in detail, considering their compliance with the 'REASSURED' criteria given by the World Health Organization (WHO) and suitability for mass screening in low-resource settings. Finally, the discourse revolves around the fundamental aspects pertaining to the advancement of multiplex, cost-effective point-of-care devices designed for widespread screening purposes.

Ultrasensitive Detection of Cancer Biomarkers Using Photonic-Crystal-Enhanced Single-Molecule Imaging

The rapid and sensitive quantification of low-abundance protein markers holds immense significance in early disease diagnosis and treatment. Single-molecule fluorescence imaging exhibits very high detection sensitivity and thus has great application potential in this area. The single-molecule signal, however, is often susceptible to interference from background noise due to its inherently weak intensity. A variety of signal amplification techniques based on cascading reactions have been developed to improve the signal-to-noise ratio of single-molecule imaging. Nevertheless, the operation of these methods is typically complicated and time-consuming, which limits the clinical application. Herein, we introduce an enzyme-free, photonic-crystal-based single-molecule (PC-SM) biochip for cost-effective, time-efficient, and ultrasensitive detection of disease markers. The PC-SM biochip can enhance the signal-to-noise ratio of single molecules by nearly 3-fold compared with unamplified samples, through coupling of the single-molecule photon energy with the optical band gap of the photonic crystal. We used the PC-SM biochip to detect the low-abundance leukemia inhibitory factor in the blood of pancreatic cancer patients and healthy people and achieved a detection limit of 2.0 pg/L and an AUC of 0.9067. The method exhibits exceptional sensitivity and specificity, showing great application potential in various clinical settings.

AI-Assisted Detection of Biomarkers by Sensors and Biosensors for Early Diagnosis and Monitoring

The steady progress in consumer electronics, together with improvement in microflow techniques, nanotechnology, and data processing, has led to implementation of cost-effective, user-friendly portable devices, which play the role of not only gadgets but also diagnostic tools. Moreover, numerous smart devices monitor patients' health, and some of them are applied in point-of-care (PoC) tests as a reliable source of evaluation of a patient's condition. Current diagnostic practices are still based on laboratory tests, preceded by the collection of biological samples, which are then tested in clinical conditions by trained personnel with specialistic equipment. In practice, collecting passive/active physiological and behavioral data from patients in real time and feeding them to artificial intelligence (AI) models can significantly improve the decision process regarding diagnosis and treatment procedures via the omission of conventional sampling and diagnostic procedures while also excluding the role of pathologists. A combination of conventional and novel methods of digital and traditional biomarker detection with portable, autonomous, and miniaturized devices can revolutionize medical diagnostics in the coming years. This article focuses on a comparison of traditional clinical practices with modern diagnostic techniques based on AI and machine learning (ML). The presented technologies will bypass laboratories and start being commercialized, which should lead to improvement or substitution of current diagnostic tools. Their application in PoC settings or as a consumer technology accessible to every patient appears to be a real possibility. Research in this field is expected to intensify in the coming years. Technological advancements in sensors and biosensors are anticipated to enable the continuous real-time analysis of various omics fields, fostering early disease detection and intervention strategies. The integration of AI with digital health platforms would enable predictive analysis and personalized healthcare, emphasizing the importance of interdisciplinary collaboration in related scientific fields.

Digital biomarkers: 3PM approach revolutionizing chronic disease management - EPMA 2024 position

Non-communicable chronic diseases (NCDs) have become a major global health concern. They constitute the leading cause of disabilities, increased morbidity, mortality, and socio-economic disasters worldwide. Medical condition-specific digital biomarker (DB) panels have emerged as valuable tools to manage NCDs. DBs refer to the measurable and quantifiable physiological, behavioral, and environmental parameters collected for an individual through innovative digital health technologies, including wearables, smart devices, and medical sensors. By leveraging digital technologies, healthcare providers can gather real-time data and insights, enabling them to deliver more proactive and tailored interventions to individuals at risk and patients diagnosed with NCDs. Continuous monitoring of relevant health parameters through wearable devices or smartphone applications allows patients and clinicians to track the progression of NCDs in real time. With the introduction of digital biomarker monitoring (DBM), a new quality of primary and secondary healthcare is being offered with promising opportunities for health risk assessment and protection against health-to-disease transitions in vulnerable sub-populations. DBM enables healthcare providers to take the most cost-effective targeted preventive measures, to detect disease developments early, and to introduce personalized interventions. Consequently, they benefit the quality of life (QoL) of affected individuals, healthcare economy, and society at large. DBM is instrumental for the paradigm shift from reactive medical services to 3PM approach promoted by the European Association for Predictive, Preventive, and Personalized Medicine (EPMA) involving 3PM experts from 55 countries worldwide. This position manuscript consolidates multi-professional expertise in the area, demonstrating clinically relevant examples and providing the roadmap for implementing 3PM concepts facilitated through DBs.

Nanomaterial Biosensors in Salivary Diagnosis of Oral Cancer: A Scoping Review

Oral cancer is among the highest in the Indian subcontinent. Advanced stages of oral cancer are associated with severe morbidity and higher mortality. Salivary diagnosis is novel and non-invasive. It could be employed on patients even with restricted mouth opening. Hence, an attempt was made to retrieve relevant data regarding this clinically relevant topic.  This article has reviewed metal oxide nanoparticles as a biosensor (BS) in salivary diagnosis for oral cancer. Gold, copper oxide, and carbon nanotubes (CNTs) were used in BS applications. A search from the PUBMED database collection (2004 to 2024) was performed to identify the nanoparticle biomarkers and salivary diagnosis in oral cancer. It revealed 30 articles. All the relevant data was extracted and tabulated in this review. We have discussed the relevance of these BS in salivary diagnosis with their corresponding clinical parameters and sensitivity. We hope that this review summarizes the available literature on this topic and incites dedicated research in prompt and early diagnosis of oral cancer, which directly influences the quality of life outcomes in such patients.

Fluorescent Selectivity-Enhanced FRET Based on 3D Photonic Crystals for Multianalyte Sensing

Fluorescence resonance energy transfer (FRET) finds widespread utility in biochemical sensing, single-molecule experiments, cell physiology, and various other domains due to its inherent simplicity and high sensitivity. Nevertheless, the efficiency of energy transfer between the FRET donor and acceptor is significantly contingent on the local photonic environment, a factor that limits its application in complex systems or multianalyte detections. Here, a fluorescent selectivity-enhanced acridine orange (AO)-aflatoxins (AFs) FRET system based on a range of 3D topological photonic crystals (PCs) was developed with the aim of enhancing the selectivity and discrimination capabilities of FRET. By exploring the angle-dependent characteristics of the photonic stopband, the stopband distribution across different 3D topological PCs pixels was investigated. This approach led to selective fluorescence enhancement in PCs that matched the stopbands, enabling the successful discrimination of six distinct aflatoxins and facilitating complex multianalysis of moldy food samples. In particular, the stopband, which was strategically positioned within the blue-purple structural color range, exhibited a strong alignment with the fluorescence peaks of both the FRET donor and acceptor. This alignment allowed the 3D three-pointed star PCs to be effectively employed for the identification of mixed samples containing six distinct aflatoxins as well as the detection of real aflatoxin samples present in moldy potatoes, bread, oats, and peanuts. Impressively, this approach achieved a remarkable accuracy rate of 100%. This innovative strategy not only presents a novel avenue for developing a multitarget discrimination analysis system but also offers a convenient pretreatment method for the quantitative detection of various aflatoxins.