Gold nanorods (AuNRs), as versatile sensing materials, have wide analytical applications due to their unique optical properties. Cetyltrimethylammonium bromide (C16TAB), a conventional reagent in AuNR synthesis, also often acts as a stabilizer of AuNRs in applications. However, C16TAB-stabilized AuNRs undergo severe spontaneous aggregation and etching under extreme pH conditions, greatly limiting their optical sensing applications. Herein, we accidentally discovered that octadecyl trimethylammonium bromide (C18TAB), a rarely used surfactant for AuNRs, has a substantially higher stabilizing ability than C16TAB in preventing spontaneous aggregation and etching of AuNRs, which enables C18TAB-stabilized AuNRs as a superior sensing platform, demonstrating a 100-fold higher sensitivity than C16TAB-stabilized AuNRs for detection of model analytes. The excellent stability of C18TAB-stabilized AuNRs can be attributed to the higher surfactant coverage density on the gold surface, evidenced by the red-shifted longitudinal band (5 nm), which is tuned by the metal surface refraction index. The experimental results show that C18TAB-stabilized AuNRs can keep monodispersed and unchanged optical properties at very acidic and alkaline conditions with a low concentration of surfactant (0.05 mM). Moreover, the C18TAB-stabilized AuNRs can prevent spontaneous etching in the acidic sensing system and maintain their unchanged plasmon band, therefore decreasing the intensity of the noise signal. Benefiting from these findings, we established a reliable and ultrasensitive C18TAB-stabilized AuNR sensing platform and achieved the ultrasensitive detection of the model biomarker p-aminophenol (pAP), with a visual detection limit of 8 nM. This sensitivity represents at least a 100-fold improvement over the existing method using C16TAB-stabilized AuNRs. Moreover, C18TAB-stabilized AuNRs were successfully applied to detect pAP in urine samples with satisfactory recovery rates of 99.84-114.91%, further validating its reliability in practical applications. In summary, C18TAB-stabilized AuNRs provide a powerful tool for trace-level visual detection in chemo- and biosensing.

Exploring the intricate interplay within and between nucleic acids, as well as their interactions with proteins, holds pivotal significance in unraveling the molecular complexities steering cancer initiation and progression. To investigate these interactions, a diverse array of highly specific and sensitive molecular techniques has been developed. The selection of a particular technique depends on the specific nature of the interactions. Typically, researchers employ an amalgamation of these different techniques to obtain a comprehensive and holistic understanding of inter- and intramolecular interactions involving DNA-DNA, RNA-RNA, DNA-RNA, or protein-DNA/RNA. Examining nucleic acid conformation reveals alternative secondary structures beyond conventional ones that have implications for cancer pathways. Mutational hotspots in cancer often lie within sequences prone to adopting these alternative structures, highlighting the importance of investigating intra-genomic and intra-transcriptomic interactions, especially in the context of mutations, to deepen our understanding of oncology. Beyond these intramolecular interactions, the interplay between DNA and RNA leads to formations like DNA:RNA hybrids (known as R-loops) or even DNA:DNA:RNA triplex structures, both influencing biological processes that ultimately impact cancer. Protein-nucleic acid interactions are intrinsic cellular phenomena crucial in both normal and pathological conditions. In particular, genetic mutations or single amino acid variations can alter a protein's structure, function, and binding affinity, thus influencing cancer progression. It is thus, imperative to understand the differences between wild-type (WT) and mutated (MT) genes, transcripts, and proteins. The review aims to summarize the frequently employed methods and techniques for investigating interactions involving nucleic acids and proteins, highlighting recent advancements and diverse adaptations of each technique.

The differential diagnosis between mild cognitive impairment (MCI) and Alzheimer's disease (AD) has been highly demanded for its effectiveness in preventing and contributing to early diagnosis of AD. To this end, we developed a single plasmonic asymmetric nanobridge (PAN)-based biosensor to differentially diagnose MCI and AD by quantitative profiling of phosphorylated tau proteins (p-tau) in clinical plasma samples, which revealed a significant correlation with AD development and progression. The PAN was designed to have a conductive junction and asymmetric structure, which was unable to be synthesized by the traditional thermodynamical methods. For its unique morphological characteristics, PAN features high electromagnetic field enhancement, enabling the biosensor to achieve high sensitivity, with a limit of detection in the attomolar regime for quantitative analysis of p-tau. By introducing support vector machine (SVM)-based machine learning algorithm, the improved diagnostic system was achieved for prediction of healthy controls, MCI, and AD groups with an accuracy of 94.47 % by detecting various p-tau species levels in human plasma. Thus, our proposed PAN-based plasmonic biosensor has a powerful potential in clinical utility for predicting the onset of AD progression in the asymptomatic phase.

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.

Plasma nanoparticles offer promise in data storage, biosensing, optical imaging, photoelectric integration, etc. This review highlights the local surface plasmon resonance (LSPR) excitation mechanism of plasmonic nanoprobes and its critical significance in the control of dark-field sensing, as well as three main sensing strategies based on plasmonic nanomaterial dielectric environment modification, electromagnetic coupling, and charge transfer. This review then describes the component materials of plasmonic nanoprobes based on gold, silver, and other noble metals, as well as their applications. According to this summary, researchers raised the LSPR performance of composite plasmonic nanomaterials by combining noble metals with other metals or oxides and using them in process analysis and quantitative detection.

Alzheimer's disease (AD) is a neurodegenerative disease of complex pathogenesis, with overt symptoms following disease progression. Early AD diagnosis is challenging due to the lack of robust biomarkers and limited patient access to diagnostics via neuroimaging and cerebrospinal fluid (CSF) tests. Exosomes present in body fluids are attracting attention as diagnostic biomarkers that directly reflect neuropathological features within the brain. In particular, exosomal miRNAs (exomiRs) signatures are involved in AD pathogenesis, showing a different expression between patients and the healthy controls (HCs). However, low yield and high homologous nature impede the accuracy and reproducibility of exosome blood-based AD diagnostics. Here, we developed a programmable curved plasmonic nanoarchitecture-based biosensor to analyze exomiRs in clinical serum samples for accurate AD diagnosis. To allow the detection of exomiRs in serum at attomolar levels, nanospaces (e.g., nanocrevice and nanocavity) were introduced into the nanostructures to dramatically increase the spectral sensitivity by adjusting the bending angle of the plasmonic nanostructure through sodium chloride concentration control. The developed biosensor classifies individuals into AD, mild cognitive impairment (MCI) patients, and HCs through profiling and quantifying exomiRs. Furthermore, integrating analysis expression patterns of multiple exosomal biomarkers improved serum-based diagnostic performance (average accuracy of 98.22%). Therefore, precise, highly sensitive serum-derived exosomal biomarker detection-based plasmonic biosensor has a robust capacity to predict the molecular pathologic of neurodegenerative disease, progression of cognitive decline, MCI/AD conversion, as well as early diagnosis and treatment.

Breast cancer with unpredictable metastatic recurrence is the leading cause of cancer-related mortality. Early cancer detection and optimized therapy are the principal determining factors for increased survival rate. Worldwide, researchers and clinicians are in search of efficient strategies for the timely management of cancer progression. Efficient preclinical models provide information on cancer initiation, malignancy progression, relapse, and drug efficacy. The distinct histopathological features and clinical heterogeneity allows no single model to mimic breast tumor. However, engineering three-dimensional (3D) in vitro models incorporating cells and biophysical cues using a combination of organoid culture, 3D printing, and microfluidic technology could recapitulate the tumor microenvironment. These models serve to be preferable predictive models bridging the translational research gap in drug development. Microfluidic device is a cost-effective advanced in vitro model for cancer research, diagnosis, and drug assay under physiologically relevant conditions. Integrating a biosensor with microfluidics allows rapid real-time analytical validation to provide highly sensitive, specific, reproducible, and reliable outcomes. In this manner, the multi-system approach in identifying biomarkers associated with cancer facilitates early detection, therapeutic window optimization, and post-treatment evaluation.This chapter showcases the advancements related to in vitro breast cancer metastasis models focusing on microfluidic devices. The chapter aims to provide an overview of microfluidic biosensor-based devices for cancer detection and high-throughput chemotherapeutic drug screening.

Alzheimer's disease (AD), the most common neurologic disorder, is characterized by progressive cognitive impairment. However, the low clinical significance of the currently used core AD biomarkers amyloid-beta and tau proteins remains a challenge. Recently, exosomes, found in human biological fluids, are gaining increasing attention because of their clinical significance in diagnosing of various diseases. In particular, blood-derived exosomal miRNAs are not only stable but also provide information regarding the different characteristics according to AD progression. However, quantitative and qualitative detection is difficult due to their characteristics, such as small size, low abundance, and high homology. Here, we present a DNA-assembled advanced plasmonic architecture (DAPA)-based plasmonic biosensor to accurately detect exosomal miRNAs in human serum. The designed nanoarchitecture possesses two narrow nanogaps that induce plasmon coupling; this significantly enhances its optical energy density, resulting in a 1.66-fold higher refractive-index (RI) sensitivity than nanorods at localized surface plasmon resonance (LSPR). Thus, the proposed biosensor is ultrasensitive and capable of selective single-nucleotide detection of exosomal miRNAs at the attomolar level. Furthermore, it identified AD patients from healthy controls by measuring the levels of exosomal miRNA-125b, miRNA-15a, and miRNA-361 in clinical serum samples. In particular, the combination of exosomal miRNA-125b and miRNA-361 showed the best diagnostic performance with a sensitivity of 91.67%, selectivity of 95.00%, and accuracy of 99.52%. These results demonstrate that our sensor can be clinically applied for AD diagnosis and has great potential to revolutionize the field of dementia research and treatment in the future.

DNA-protein interactions are essential for several molecular and cellular mechanisms, such as transcription, transcriptional regulation, DNA modifications, among others. For many decades scientists tried to unravel how DNA links to proteins, forming complex and vital interactions. However, the high number of techniques developed for the study of these interactions made the choice of the appropriate technique a difficult task. This review intends to provide a historical context and compile the methods that describe DNA-protein interactions according to the purpose of each approach, summarise the respective advantages and disadvantages and give some examples of recent uses for each technique. The final aim of this work is to help in deciding which technique to perform according to the objectives and capacities of each research team. Considering the DNA-binding proteins characterisation, filter binding assay and EMSA are easy in vitro methods that rapidly identify nucleic acid-protein binding interactions. To find DNA-binding sites, DNA-footprinting is indeed an easier, faster and reliable approach, however, techniques involving base analogues and base-site selection are more precise. Concerning binding kinetics and affinities, filter binding assay and EMSA are useful and easy methods, although SPR and spectroscopy techniques are more sensitive. Finally, relatively to genome-wide studies, ChIP-seq is the desired method, given the coverage and resolution of the technique. In conclusion, although some experiments are easier and faster than others, when designing a DNA-protein interaction study several concerns should be taken and different techniques may need to be considered, since different methods confer different precisions and accuracies.