High-performance plasmonics nanostructures in gas sensing: a comprehensive review.

Plasmonic nanostructures have emerged as indispensable components in the construction of high-performance gas sensors, playing a pivotal role across diverse applications, including industrial safety, medical diagnostics, and environmental monitoring. This review paper critically examines seminal research that underscores the remarkable efficacy of plasmonic materials in achieving superior attributes such as heightened sensitivity, selectivity, and rapid response times in gas detection. Offering a synthesis of pivotal studies, this review aims to furnish a comprehensive discourse on the contemporary advancements within the burgeoning domain of plasmonic gas sensing.

Recognition of breast cancer subtypes using FTIR hyperspectral data.

Fourier-transform infrared spectroscopy (FTIR) is a powerful, non-destructive, highly sensitive and a promising analytical technique to provide spectrochemical signatures of biological samples, where markers like carbohydrates, proteins, and phosphate groups of DNA can be recognized in biological micro-environment. However, method of measurements of large cells need an excessive time to achieve high quality images, making its clinical use difficult due to speed of data-acquisition and lack of optimized computational procedures. To address such challenges, Machine Learning (ML) based technologies can assist to assess an accurate prognostication of breast cancer (BC) subtypes with high performance.

Rapid identification of breast cancer subtypes using micro-FTIR and machine learning methods.

Breast cancer (BC) molecular subtypes diagnosis involves improving clinical uptake by Fourier transform infrared (FTIR) spectroscopic imaging, which is a non-destructive and powerful technique, enabling label free extraction of biochemical information towards prognostic stratification and evaluation of cell functionality. However, methods of measurements of samples demand a long time to achieve high quality images, making its clinical use impractical because of the data acquisition speed, poor signal to noise ratio, and deficiency of optimized computational framework procedures. To address those challenges, machine learning (ML) tools can facilitate obtaining an accurate classification of BC subtypes with high actionability and accuracy.

Selecting High-Performance Gold Nanorods for Photothermal Conversion.

In this work, we establish a new paradigm on identifying optimal arbitrarily shaped metallic nanostructures for photothermal applications. Crucial thermo-optical parameters that rule plasmonic heating are appraised, exploring a nanoparticle size-dependence approach. Our results indicate two distinct figures of merit for the optimization of metallic nanoheaters, under both non-cumulative femtosecond and continuum laser excitation.

Tailoring the Scattering Response of Optical Nanocircuits Using Modular Assembly.

Owing to the localized plasmon resonance of an ensemble of interacting plasmonic nanoparticles (NPs), there has been a tremendous drive to conceptualize complex optical nanocircuits with versatile functionalities. In comparison to modern research, there is still not a sufficient level of sophistication to treat the nanostructures as lumped circuits that can be adjusted into complex systems on the basis of a metatronic touchstone. Here, we present the design, assembly, and characterization of single relatively complex photonic nanocircuits by accurately positioning several metallic and dielectric nanoparticles acting as modular lumped elements.

Optimizing and Quantifying Gold Nanospheres Based on LSPR Label-Free Biosensor for Dengue Diagnosis.

The localized surface plasmon resonance (LSPR) due to light-particle interaction and its dependence on the surrounding medium have been widely manipulated for sensing applications. The sensing efficiency is governed by the refractive index-based sensitivity (ηRIS) and the full width half maximum (FWHM) of the LSPR spectra. Thereby, a sensor with high precision must possess both requisites: an effective ηRIS and a narrow FWHM of plasmon spectrum.

Identifying high performance gold nanoshells for singlet oxygen generation enhancement.

Metallic nanostructures can improve the production of singlet oxygen (O) of a photosensitizer during photodynamic therapy (PDT) . Engineering a high performance nanoparticle is mandatory for an appropriate use of plasmonic nanostructures in PDT. Metal enhanced singlet oxygen generation requires the use of nanoparticles with high scattering efficiency, capable of inducing a significant electric field enhancement and with plasmon peak overlapping the photosensitizer absorption spectrum.

Photodynamic inactivation assisted by localized surface plasmon resonance of silver nanoparticles: In vitro evaluation on Escherichia coli and Streptococcus mutans.

Localized surface plasmon resonance (LSPR) of gold nanoparticles has been reported to increase the antimicrobial effect of the photodynamic therapy. Although silver nanoparticles (AgNPs) are an efficient growth inhibitor of microorganisms, no studies exploring LSPR of AgNPs to enhance the photodynamic inactivation (PDI) have been related. In this work, we described the LSPR phenomenon of AgNP sand investigated its interaction with riboflavin, a natural photosensitizer.

Acute chest syndrome in sickle cell disease.

Acute chest syndrome (ACS) is a leading complication of sickle cell disease (SCD) with significant morbidity and mortality. ACS is the most common cause of death and the second most common cause of hospitalization in patients with SCD. Delineating the specific cause of ACS is often difficult, and multiple risk factors that precipitate ACS frequently coexist.

Correction: Optimizing SIEM Throughput on the Cloud Using Parallelization.

[This corrects the article DOI: 10.1371/journal.pone.

Salvage Plasmapheresis for Post-hepatectomy Liver Failure.

In the latest decades, an important change has been registered in liver surgery related to the progress of surgical techniques, critical care, and postoperative treatment, allowing a sharp decrease in mortality and morbidity. However, management of post-hepatectomy liver failure (PHLF) still remains a challenge and no supportive treatment has been found to be generally effective. The present study is a reappraisal of plasmapheresis as a potential supportive measure in patients with PHLF following major liver resection.

Optimizing SIEM Throughput on the Cloud Using Parallelization.

Processing large amounts of data in real time for identifying security issues pose several performance challenges, especially when hardware infrastructure is limited. Managed Security Service Providers (MSSP), mostly hosting their applications on the Cloud, receive events at a very high rate that varies from a few hundred to a couple of thousand events per second (EPS). It is critical to process this data efficiently, so that attacks could be identified quickly and necessary response could be initiated.