High Accuracy of Clinical Verification of Electrohydrodynamic-Driven Nanobox-on-Mirror Platform for Molecular Identification of Respiratory Viruses

The molecular detection of multiple respiratory viruses provides evidence for the rational use of drugs and effective health management. Herein, we developed and tested the clinical performance of an electrohydrodynamic-driven nanobox-on-mirror platform (E-NoM) for the parallel, accurate, and sensitive detection of four respiratory viral antigens. The E-NoM platform uses gold-silver alloy nanoboxes as the core material with the deposition of a silver layer as a shell on the core surfaces to amplify and enable a reproducible Raman signal readout that facilitates accurate detection. Additionally, the E-NoM platform employs gold microelectrode arrays as the mirror with electrohydrodynamics to manipulate the fluid flow and enhance molecular interactions for an improved biosensing response. The presence of viral antigens binds the nanobox-based core-shell nanostructure on the gold microelectrode and creates the nanocavity with extremely strong "hot spots" to benefit sensitive analysis. Significantly, in a large clinical cohort with 227 patients, the designed E-NoM platform demonstrates the capability of screening respiratory infection with achieved clinical specificity, sensitivity, and accuracy of 100.0, 96.48, and 96.91%, respectively. It is anticipated that the E-NoM platform can find a position in clinical usage for respiratory disease diagnosis.

Recent development of surface-enhanced Raman scattering for biosensing

Surface-Enhanced Raman Scattering (SERS) technology, as a powerful tool to identify molecular species by collecting molecular spectral signals at the single-molecule level, has achieved substantial progresses in the fields of environmental science, medical diagnosis, food safety, and biological analysis. As deepening research is delved into SERS sensing, more and more high-performance or multifunctional SERS substrate materials emerge, which are expected to push Raman sensing into more application fields. Especially in the field of biological analysis, intrinsic and extrinsic SERS sensing schemes have been widely used and explored due to their fast, sensitive and reliable advantages. Herein, recent developments of SERS substrates and their applications in biomolecular detection (SARS-CoV-2 virus, tumor etc.), biological imaging and pesticide detection are summarized. The SERS concepts (including its basic theory and sensing mechanism) and the important strategies (extending from nanomaterials with tunable shapes and nanostructures to surface bio-functionalization by modifying affinity groups or specific biomolecules) for improving SERS biosensing performance are comprehensively discussed. For data analysis and identification, the applications of machine learning methods and software acquisition sources in SERS biosensing and diagnosing are discussed in detail. In conclusion, the challenges and perspectives of SERS biosensing in the future are presented.

Nucleic Acid Probes in Bio-Imaging and Diagnostics: Recent Advances in ODN-Based Fluorescent and Surface-Enhanced Raman Scattering Nanoparticle and Nanostructured Systems

Raman nanoparticle probes are a potent class of optical labels for the interrogation of pathological and physiological processes in cells, bioassays, and tissues. Herein, we review the recent advancements in fluorescent and Raman imaging using oligodeoxyribonucleotide (ODN)-based nanoparticles and nanostructures, which show promise as effective tools for live-cell analysis. These nanodevices can be used to investigate a vast number of biological processes occurring at various levels, starting from those involving organelles, cells, tissues, and whole living organisms. ODN-based fluorescent and Raman probes have contributed to the achievement of significant advancements in the comprehension of the role played by specific analytes in pathological processes and have inaugurated new possibilities for diagnosing health conditions. The technological implications that have emerged from the studies herein described could open new avenues for innovative diagnostics aimed at identifying socially relevant diseases like cancer through the utilization of intracellular markers and/or guide surgical procedures based on fluorescent or Raman imaging. Particularly complex probe structures have been developed within the past five years, creating a versatile toolbox for live-cell analysis, with each tool possessing its own strengths and limitations for specific studies. Analyzing the literature reports in the field, we predict that the development of ODN-based fluorescent and Raman probes will continue in the near future, disclosing novel ideas on their application in therapeutic and diagnostic strategies.

Advancing cervical cancer diagnosis and screening with spectroscopy and machine learning

INTRODUCTION

In the UK alone, the incidence of cervical cancer is increasing, hence an urgent need for early and rapid detection of cancer before it develops. Spectroscopy in conjunction with machine learning offers a disruptive technology that promises to be pick up cancer early as compared to the current diagnostic techniques used.

AREAS COVERED

This review article explores the different spectroscopy techniques that have been used for the analysis of cervical cancer. Along with the extensive description of spectroscopic techniques, the various machine learning techniques are also described as well as the applications that have been explored in the diagnosis of cervical cancer. This review delimits the literature specifically associated with cervical cancer studies performed solely with the use of a spectroscopy technique, and machine learning.

EXPERT OPINION

Although there are several methods and techniques to detect cervical cancer, the clinical sector requires to introduce new diagnostic technologies that help improving the quality of life of patient. These innovative technologies involve spectroscopy as a qualitative method and machine learning as a quantitative method. In this article, both the techniques and methodologies that allow and promise to be a new screening tool for the detection of cervical cancer is covered.

SERS-Based Biosensors Combined with Machine Learning for Medical Application

Surface-enhanced Raman spectroscopy (SERS) has shown strength in non-invasive, rapid, trace analysis and has been used in many fields in medicine. Machine learning (ML) is an algorithm that can imitate human learning styles and structure existing content with the knowledge to effectively improve learning efficiency. Integrating SERS and ML can have a promising future in the medical field. In this review, we summarize the applications of SERS combined with ML in recent years, such as the recognition of biological molecules, rapid diagnosis of diseases, developing of new immunoassay techniques, and enhancing SERS capabilities in semi-quantitative measurements. Ultimately, the possible opportunities and challenges of combining SERS with ML are addressed.

Involvement of endoplasmic reticulum stress-activated PERK-eIF2α-ATF4 signaling pathway in T-2 toxin-induced apoptosis of porcine renal epithelial cells

T-2 toxin is a highly toxic trichothecene that can induce toxic effects in a variety of organs and tissues, but the pathogenesis of its nephrotoxicity has not been elucidated. In this study, we assessed the involvement of protein kinase RNA-like ER kinase (PERK)-mediated endoplasmic reticulum (ER) stress and apoptosis in PK-15 cells cultured at different concentrations of T-2 toxin. Cell viability, antioxidant capacity, intracellular calcium (Ca²⁺) content, apoptotic rate, levels of ER stress, and apoptosis-related proteins were studied. T-2 toxin inhibited cell proliferation; increased the apoptosis rate; and was accompanied by increased cleaved caspase-3 expression, altered intracellular oxidative stress marker levels, and intracellular Ca²⁺ overloading. The ER stress inhibitor 4-phenylbutyrate (4-PBA) and PERK selective inhibitor GSK2606414 prevented the decrease of cell activity and apoptosis caused by T-2 toxin. The altered expression of glucose regulatory protein 78 (GRP78), C/EBP homologous protein (CHOP), and caspase-12 proved that ER stress was involved in cell injury triggered by T-2 toxin. T-2 toxin activated the phosphorylation of PERK and the alpha subunit of eukaryotic initiation factor 2 (eIF2α) and upregulated the activating transcription factor 4 (ATF4), thereby triggering ER stress via the GRP78/PERK/CHOP signaling pathway. This study provides a new perspective for understanding the nephrotoxicity of T-2 toxin.

Effect of magnesium ammonium phosphate on the expression of adhesion molecules in sheep renal tubular epithelial cells

Adhesion molecules play an important role in urinary calculus formation. The expressions of adhesion molecules in renal tubular has been reported in some animals. However, the role of adhesion molecules in the process of sheep urinary calculus formation is still unclear. The magnesium ammonium phosphate (MAP) is the main component of sheep urinary calculus. In this paper, the sheep renal tubular epithelial cells (RTECs) were isolated and treated with MAP, the expressions of osteopontin (OPN), intercellular adhesion molecule-1 (ICAM-1), vascular cell adhesion molecule-1 (VCAM-1) and apoptosis-related indicators caspase-3, Bcl-2 and Bax in RTECs were observed, the viability of RTECs was detected by Cell Counting Kit-8 (CCK-8). The levels of superoxide dismutase (SOD) and malondialdehyde (MDA), and the expressions of inflammatory factors Interleukin-6 (IL-6), Interleukin-1 (IL-1), Interleukin-17 (IL-17) and tumor necrosis factor-α (TNF-α) were measured by enzyme-linked immunosorbent (ELISA). The histopathological observation of kidney in urolithiasis sheep was made. The results showed that MAP could reduce the viability and SOD activity, enhance the activity of MDA significantly and promote the expressions of IL-1, IL-6, IL-17 and TNF-α of RTECs. By western blot and qPCR methods, the expressions of ICAM-1, VCAM-1 and OPN increased in 48 h. In addition, the expression of caspase-3 increased significantly and the ratio of Bcl-2/Bax reduced with exposure to MAP. The renal tissue structure was seriously damaged, the RTECs in urolithiasis sheep were degenerative and necrotic.