Dual-mode biosensor for femtomolar miRNA-155 detection by electrochemiluminescence and adsorptive stripping voltammetry

Emerging Roles of Graphitic Carbon Nitride-based Materials in Biomedical Applications

Graphite carbon nitride (g-C3N4) is a two-dimensional conjugated polymer with a unique energy band structure similar to graphene. Due to its outstanding analytical advantages, such as relatively small band gap (2.7 eV), low-cost synthesis, high thermal stability, excellent photocatalytic ability, and good biocompatibility, g-C3N4 has attracted the interest of researchers and industry, especially in the medical field. This paper summarizes the latest research on g-C3N4-based composites in various biomedical applications, including therapy, diagnostic imaging, biosensors, antibacterial, and wearable devices. In addition, the application prospects and possible challenges of g-C3N4 in nanomedicine are also discussed in detail. This review is expected to inspire emerging biomedical applications based on g-C3N4.

Electrochemiluminescence in Graphitic Carbon Nitride Decorated with Silver Nanoparticles for Dopamine Determination Using Machine Learning

Electrochemiluminescence (ECL) luminophores with wavelength-tunable multicolor emissions are essential for multicolor ECL imaging detection and multiplexed analysis. In this work, silver nanoparticle (Ag NP)-decorated graphitic carbon nitride (g-CN@Ag) nanocomposites were synthesized. The morphology, chemical composition, structure, and ECL property of g-CN@Ag were investigated. The prepared g-CN, g-CN@Ag1, g-CN@Ag5, and g-CN@Ag10 can produce blue, blue-green, chartreuse, and yellow colored ECL emissions, respectively, by using K2S2O8 as the coreagent. The ECL emission wavelength of g-CN@Ag can be regulated from 460 to 565 nm by modulating the content of the immobilized Ag NPs. Then, a multicolor ECL detection array was fabricated by using g-CN, g-CN@Ag1, g-CN@Ag5, and g-CN@Ag10 as four ECL luminophores. Dopamine was detected based on its inhibition effect on the multicolor ECL emissions. The linear range is from 0.1 nM to 1 mM with the lowest detection limit of 44 pM. Then, machine learning-assisted multiparameter concentration prediction of dopamine was further carried out by combining the deep neural network (DNN) algorithm. This work provides a new avenue to regulate the ECL emission wavelength of g-CN by using the metal nanoparticle modification strategy and presents an effective machine learning-assisted multicolor ECL detection strategy for accurate multiparameter quantitative detection.

Highly sensitive detection of microRNA-21 by nitrogen-doped carbon dots-based ratio fluorescent probe via nuclease-assisted rolling circle amplification strategy

Highly sensitive and selective detection of microRNA-21 (miRNA-21) in biological samples is critical for the disease diagnosis and cancer treatment. In this study, a nitrogen-doped carbon dots (N-CDs)-based ratio fluorescence sensing strategy was constructed for miRNA-21 detection with high sensitivity and excellent specificity. Bright-blue N-CDs (λ_ex/λ_em = 378 nm/460 nm) were synthesized by facile one-step microwave-assisted pyrolysis method by using uric acid as the single precursor, and the absolute fluorescence quantum yield and fluorescence lifetime of N-CDs were 35.8% and 5.54 ns separately. The padlock probe hybridized with miRNA-21 firstly and then was cyclized by T4 RNA ligase 2 to form a circular template. At the present of dNTPs and phi29 DNA polymerase, the oligonucleotide sequence in miRNA-21 was prolonged to hybridize with the surplus oligonucleotide sequences in circular template, generating long and reduplicated oligonucleotide sequences containing abundant guanine nucleotides. Separate G-quadruplex sequences were generated after the addition of Nt.BbvCI nicking endonuclease, and then hemin bound with G-quadruplex sequence to construct the G-quadruplex DNAzyme. Such G-quadruplex DNAzyme catalyzed the redox reaction of o-phenylenediamine (OPD) with H₂O₂, finally producing the yellowish-brown 2,3-diaminophenazine (DAP) (λ_em = 562 nm). Due to the inner filter effect between N-CDs and DAP, the ratio fluorescence signal of DAP with N-CDs was utilized for sensitive detection of miRNA-21 with detection limit of 0.87 pM. Such approach has practical feasibility and excellent specificity for miRNA-21 analysis during highly homological miRNA family in HeLa cell lysates and human serum samples.

Tailored point-of-care biosensors for liquid biopsy in the field of oncology

In the field of cancer detection, technologies to analyze tumors using biomarkers circulating in fluids such as blood have developed rapidly based on liquid biopsy. A proactive approach to early cancer detection can lead to more effective treatments with minimal side effects and better long-term patient survival. However, early detection of cancer is hindered by the existing limitations of conventional cancer diagnostic methods. To enable early diagnosis and regular monitoring and improve automation, the development of integrated point-of-care (POC) and biosensors is needed. This is expected to fundamentally change the diagnosis, management, and monitoring of response to treatment of cancer. POC-based techniques will provide a way to avoid complications that occur after invasive tissue biopsy, such as bleeding, infection, and pain. The aim of this study is to provide a comprehensive view of biosensors and their clinical relevance in oncology for the detection of biomarkers with liquid biopsies of proteins, miRNA, ctDNA, exosomes, and cancer cells. The preceding discussion also illustrates the changing landscape of liquid biopsy-based cancer diagnosis through nanomaterials, machine learning, artificial intelligence, wearable devices, and sensors, many of which apply POC design principles. With the advent of sensitive, selective, and timely detection of cancer, we see the field of POC technology for cancer detection and treatment undergoing a positive paradigm shift in the foreseeable future.

Wearable Sensor for Continuous Sweat Biomarker Monitoring

In recent years, wearable sensors have enabled the unique mode of real-time and noninvasive monitoring to develop rapidly in medical care, sports, and other fields. Sweat contains a wide range of biomarkers such as metabolites, electrolytes, and various hormones. Combined with wearable technology, sweat can reflect human fatigue, disease, mental stress, dehydration, and so on. This paper comprehensively describes the analysis of sweat components such as glucose, lactic acid, electrolytes, pH, cortisol, vitamins, ethanol, and drugs by wearable sensing technology, and the application of sweat wearable devices in glasses, patches, fabrics, tattoos, and paper. The development trend of sweat wearable devices is prospected. It is believed that if the sweat collection, air permeability, biocompatibility, sensing array construction, continuous monitoring, self-healing technology, power consumption, real-time data transmission, specific recognition, and other problems of the wearable sweat sensor are solved, we can provide the wearer with important information about their health level in the true sense.