Search for: All records

A biomarker is a physiological observable marker that acts as a stand-in and, in the best-case scenario, forecasts a clinically significant outcome. Diagnostic biomarkers are more convenient and cost-effective than directly measuring the ultimate clinical outcome. Cancer is among the most prominent global health problems and a major cause of morbidity and death globally. Therefore, cancer biomarker assays that are trustworthy, consistent, precise, and verified are desperately needed. Biomarker-based tumor detection holds a lot of promise for improving disease knowledge at the molecular scale and early detection and surveillance. In contrast to conventional approaches, surface plasmon resonance (SPR) allows for the quick and less invasive screening of a variety of circulating indicators, such as circulating tumor DNA (ctDNA), microRNA (miRNA), circulating tumor cells (CTCs), lipids, and proteins. With several advantages, the SPR technique is a particularly beneficial choice for the point-of-care identification of biomarkers. As a result, it enables the timely detection of tumor markers, which could be used to track cancer development and suppress the relapse of malignant tumors. This review emphasizes advancements in SPR biosensing technologies for cancer detection. 

Rotational dynamics at the molecular level could provide additional data regarding protein diffusion and cytoskeleton formation at the cellular level. Due to the isotropic emission pattern of fluorescence molecules, it is challenging to extract rotational information from them during imaging. Metal nanoparticles show a polarization-dependent response and could be used for sensing rotational motion. Nanoparticles as an orientation sensing probe offer bio-compatibility and robustness against photo-blinking and photo-bleaching compared to conventional fluorescent molecules. Previously, asymmetric geometrical structures such as nanorods have been used for orientational imaging. Here, we show orientational imaging of symmetric geometrical structures such as 100 nm isolated silver nanocubes by coupling a hyperspectral detector and a focused ion beam (FIB)-fabricated correlating substrate. More than 100 nanocubes are analyzed to confirm spectral shifts in the scattering spectra due to variations in the orientation of the nanocubes with respect to the incoming light. Results are further validated using finite-difference time-domain simulations. Our observations suggest a novel strategy for high-throughput orientation imaging of nanoparticles. 

This paper delves into the intricate world of whispering gallery mode (WGM) resonators within complex microsphere configurations, exploring their optical properties and behavior. Integrated with optical sensing and processing technology, WGM resonators offer compact size, high sensitivity, rapid response, and tunability. The study investigates the impact of configuration, size, excitation, polarization, and coupling effects on WGM properties. Notable findings include enhanced sensitivity in single microsphere resonators, influence of unequal sphere sizes and excitation locations on WGM modes, and higher quality factors (Q‐factors) in triangular three‐microsphere resonator configurations. Circular polarization was found to elevate Q‐factors, while the nine‐microsphere resonator configuration exhibited increased intensity of dominant WGM peaks with higher laser power, suppressing other peaks. These insights guide the design and optimization of microsphere resonator systems, positioning them for applications in sensing and optical information processing.

 

In this study, we explored machine learning approaches for predictive diagnosis using surface-enhanced Raman scattering (SERS), applied to the detection of COVID-19 infection in biological samples. To do this, we utilized SERS data collected from 20 patients at the University of Maryland Baltimore School of Medicine. As a preprocessing step, the positive-negative labels are obtained using Polymerase Chain Reaction (PCR) testing. First, we compared the performance of linear and nonlinear dimensionality techniques for projecting the high-dimensional Raman spectra to a low-dimensional space where a smaller number of variables defines each sample. The appropriate number of reduced features used was obtained by comparing the mean accuracy from a 10-fold cross-validation. Finally, we employed Gaussian process (GP) classification, a probabilistic machine learning approach, to correctly predict the occurrence of a negative or positive sample as a function of the low-dimensional space variables. As opposed to providing rigid class labels, the GP classifier provides a probability (ranging from zero to one) that a given sample is positive or negative. In practice, the proposed framework can be used to provide high-throughput rapid testing, and a follow-up PCR can be used for confirmation in cases where the model’s uncertainty is unacceptably high. 

Inorganic lead-halide perovskite, cesium lead bromide (CsPbBr3), shows outstanding optoelectronic properties. Both solution- and melt-based methods have been proposed for CsPbBr3 crystal growth. The solution-based growth was done at low-temperature, whereas the melt-based growth was done at high-temperature. However, the comparison of optical, physical, and defect states using these two different growth conditions has been scarcely studied. Here, we have compared the thermal and optical properties of solution-grown and melt-grown single crystals of CsPbBr3. Positron Annihilation Lifetime Spectroscopy (PALS) analysis showed that melt-grown crystal has a relatively smaller number of defects than the chemical synthesis method. In addition, crystals grown using the chemical method showed a higher fluorescence lifetime than melt-grown CsPbBr3. 

Matrix metalloproteinase-12 ( Mmp12 ) is upregulated by cigarette smoke (CS) and plays a critical role in extracellular matrix remodeling, a key mechanism involved in physiological repair processes, and in the pathogenesis of emphysema, asthma, and lung cancer. While cigarette smoking is associated with the development of chronic obstructive pulmonary diseases (COPD) and lung cancer, in utero exposures to CS and second-hand smoke (SHS) are associated with asthma development in the offspring. SHS is an indoor air pollutant that causes known adverse health effects; however, the mechanisms by which in utero SHS exposures predispose to adult lung diseases, including COPD, asthma, and lung cancer, are poorly understood. In this study, we tested the hypothesis that in utero SHS exposure aggravates adult-induced emphysema, asthma, and lung cancer. Methods: Pregnant BALB/c mice were exposed from gestational days 6–19 to either 3 or 10mg/m 3 of SHS or filtered air. At 10, 11, 16, or 17weeks of age, female offspring were treated with either saline for controls, elastase to induce emphysema, house-dust mite (HDM) to initiate asthma, or urethane to promote lung cancer. At sacrifice, specific disease-related lung responses including lung function, inflammation, gene, and protein expression were assessed. Results: In the elastase-induced emphysema model, in utero SHS-exposed mice had significantly enlarged airspaces and up-regulated expression of Mmp12 (10.3-fold compared to air-elastase controls). In the HDM-induced asthma model, in utero exposures to SHS produced eosinophilic lung inflammation and potentiated Mmp12 gene expression (5.7-fold compared to air-HDM controls). In the lung cancer model, in utero exposures to SHS significantly increased the number of intrapulmonary metastases at 58weeks of age and up-regulated Mmp12 (9.3-fold compared to air-urethane controls). In all lung disease models, Mmp12 upregulation was supported at the protein level. Conclusion: Our findings revealed that in utero SHS exposures exacerbate lung responses to adult-induced emphysema, asthma, and lung cancer. Our data show that MMP12 is up-regulated at the gene and protein levels in three distinct adult lung disease models following in utero SHS exposures, suggesting that MMP12 is central to in utero SHS-aggravated lung responses. 

Lipid metabolism and glycolysis play crucial roles in the progression and metastasis of cancer, and the use of 3‐bromopyruvate (3‐BP) as an antiglycolytic agent has shown promise in killing pancreatic cancer cells. However, developing an effective strategy to avoid chemoresistance requires the ability to probe the interaction of cancer drugs with complex tumor‐associated microenvironments (TAMs). Unfortunately, no robust and multiplexed molecular imaging technology is currently available to analyze TAMs. In this study, the simultaneous profiling of three protein biomarkers using SERS nanotags and antibody‐functionalized nanoparticles in a syngeneic mouse model of pancreatic cancer (PC) is demonstrated. This allows for comprehensive information about biomarkers and TAM alterations before and after treatment. These multimodal imaging techniques include surface‐enhanced Raman spectroscopy (SERS), immunohistochemistry (IHC), polarized light microscopy, second harmonic generation (SHG) microscopy, fluorescence lifetime imaging microscopy (FLIM), and untargeted liquid chromatography and mass spectrometry (LC‐MS) analysis. The study reveals the efficacy of 3‐BP in treating pancreatic cancer and identifies drug treatment‐induced lipid species remodeling and associated pathways through bioinformatics analysis.