FARSB Facilitates Hepatocellular Carcinoma Progression by Activating the mTORC1 Signaling Pathway.

Hepatocellular carcinoma (HCC) is a common malignant tumor with high mortality. Human phenylalanine tRNA synthetase (PheRS) comprises two α catalytic subunits encoded by the FARSA gene and two ß regulatory subunits encoded by the FARSB gene. FARSB is a potential oncogene, but no experimental data show the relationship between FARSB and HCC progression. We found that the high expression of FARSB in liver cancer is closely related to patients' low survival and poor prognosis. In liver cancer cells, the mRNA and protein expression levels of FARSB are increased and promote cell proliferation and migration. Mechanistically, FARSB activates the mTOR complex 1 (mTORC1) signaling pathway by binding to the component Raptor of the mTORC1 complex to play a role in promoting cancer. In addition, we found that FARSB can inhibit erastin-induced ferroptosis by regulating the mTOR signaling pathway, which may be another mechanism by which FARSB promotes HCC progression. In summary, FARSB promotes HCC progression and is associated with the poor prognosis of patients. FARSB is expected to be a biomarker for early screening and treatment of HCC.

Self-Referenced Smartphone-Based Nanoplasmonic Imaging Platform for Colorimetric Biochemical Sensing.

Colorimetric sensors usually suffer due to errors from variation in light source intensity, the type of light source, the Bayer filter algorithm, and the sensitivity of the camera to incoming light. Here, we demonstrate a self-referenced portable smartphone-based plasmonic sensing platform integrated with an internal reference sample along with an image processing method to perform colorimetric sensing. Two sensing principles based on unique nanoplasmonics enabled phenomena from a nanostructured plasmonic sensor, named as nanoLCA (nano Lycurgus cup array), were demonstrated here for colorimetric biochemical sensing: liquid refractive index sensing and optical absorbance enhancement sensing. Refractive indices of colorless liquids were measured by simple smartphone imaging and color analysis. Optical absorbance enhancement in the colorimetric biochemical assay was achieved by matching the plasmon resonance wavelength with the chromophore's absorbance peak wavelength. Such a sensing mechanism improved the limit of detection (LoD) by 100 times in a microplate reader format. Compared with a traditional colorimetric assay such as urine testing strips, a smartphone plasmon enhanced colorimetric sensing system provided 30 times improvement in the LoD. The platform was applied for simulated urine testing to precisely identify the samples with higher protein concentration, which showed potential point-of-care and early detection of kidney disease with the smartphone plasmonic resonance sensing system.

Application of an advanced maximum likelihood estimation restoration method for enhanced-resolution and contrast in second-harmonic generation microscopy.

Second-harmonic generation (SHG) microscopy has gained popularity because of its ability to perform submicron, label-free imaging of noncentrosymmetric biological structures, such as fibrillar collagen in the extracellular matrix environment of various organs with high contrast and specificity. Because SHG is a two-photon coherent scattering process, it is difficult to define a point spread function (PSF) for this modality. Hence, compared to incoherent two-photon processes like two-photon fluorescence, it is challenging to apply the various PSF-engineering methods to improve the spatial resolution to be close to the diffraction limit. Using a synthetic PSF and application of an advanced maximum likelihood estimation (AdvMLE) deconvolution algorithm, we demonstrate restoration of the spatial resolution in SHG images to that closer to the theoretical diffraction limit. The AdvMLE algorithm adaptively and iteratively develops a PSF for the supplied image and succeeds in improving the signal to noise ratio (SNR) for images where the SHG signals are derived from various sources such as collagen in tendon and myosin in heart sarcomere. Approximately 3.5 times improvement in SNR is observed for tissue images at depths of up to ∼480 nm, which helps in revealing the underlying helical structures in collagen fibres with an ∼26% improvement in the amplitude contrast in a fibre pitch. Our approach could be adapted to noisy and low resolution modalities such as micro-nano CT and MRI, impacting precision of diagnosis and treatment of human diseases.

Sensitivity Tuning through Additive Heterogeneous Plasmon Coupling between 3D Assembled Plasmonic Nanoparticle and Nanocup Arrays.

Plasmonic substrates have fixed sensitivity once the geometry of the structure is defined. In order to improve the sensitivity, significant research effort has been focused on designing new plasmonic structures, which involves high fabrication costs; however, a method is reported for improving sensitivity not by redesigning the structure but by simply assembling plasmonic nanoparticles (NPs) near the evanescent field of the underlying 3D plasmonic nanostructure. Here, a nanoscale Lycurgus cup array (nanoLCA) is employed as a base colorimetric plasmonic substrate and an assembly template. Compared to the nanoLCA, the NP assembled nanoLCA (NP-nanoLCA) exhibits much higher sensitivity for both bulk refractive index sensing and biotin-streptavidin binding detection. The limit of detection of the NP-nanoLCA is at least ten times smaller when detecting biotin-streptavidin conjugation. The numerical calculations confirm the importance of the additive plasmon coupling between the NPs and the nanoLCA for a denser and stronger electric field in the same 3D volumetric space. Tunable sensitivity is accomplished by controlling the number of NPs in each nanocup, or the number density of the hot spots. This simple yet scalable and cost-effective method of using additive heterogeneous plasmon coupling effects will benefit various chemical, medical, and environmental plasmon-based sensors.

Large-area, lithography-free, low-cost SERS sensor with good flexibility and high performance.

Cost-effective, sensitive and bio-compatible surface-enhanced Raman spectroscopy (SERS) substrate has been in high demand since the Raman spectrum was designated as a significant tool for analyzing the composition of liquids, gases and solids in 1998 [1]. In this research, we presented the design, fabrication and characterization of an improved gold-based SERS substrate. With fine tuning of the SiO2 thickness we achieved a 3.391 times improvement and achieved an enhancement factor of 1.55 * 10(7) which is 15 times better than the current gold-standard Klarite substrate. Such improvement is ascribed to the localized surface plasmon resonance (SPR) and propagating SPR, which is proved by full-wave finite-difference time-domain simulations.

A wafer-scale backplane-assisted resonating nanoantenna array SERS device created by tunable thermal dewetting nanofabrication.

A tunable lithography-less nanofabrication process using a metal thin-film thermal dewetting technique has been developed to fabricate wafer-scale and uniform plasmonic substrates at low cost for optimal performance in surface enhanced Raman scattering (SERS) applications. The relationship between the tunable parameters of this process and the corresponding optical and plasmonic characteristic is investigated both experimentally and theoretically to understand the deterministic design of an optimal SERS device with a three-dimensional plasmonic nanoantenna structure. The enhancement of SERS using various nanoplasmonic particle sizes, structure lengths, lateral hot spot spacings and resonating effects are examined and demonstrated. We achieve a uniform optimal enhancement factor of 1.38 × 10(8) on a 4 in wafer-scale SERS substrate with a backplane-assisted resonating nanoantenna array design. Sensitive environmental nitrate sensing, vitamin detection and oligonucleotide identification are demonstrated on the high-performance SERS device.

Black silicon solar thin-film microcells integrating top nanocone structures for broadband and omnidirectional light-trapping.

Recently developed classes of monocrystalline silicon solar microcells (µ-cell) can be assembled into modules with characteristics (i.e., mechanically flexible forms, compact concentrator designs, and high-voltage outputs) that would be impossible to achieve using conventional, wafer-based approaches. In this paper, we describe a highly dense, uniform and non-periodic nanocone forest structure of black silicon (bSi) created on optically-thin (30 µm) µ-cells for broadband and omnidirectional light-trapping with a lithography-free and high-throughput plasma texturizing process. With optimized plasma etching conditions and a silicon nitride passivation layer, black silicon µ-cells, when embedded in a polymer waveguiding layer, display dramatic increases of as much as 65.7% in short circuit current, as compared to a bare silicon device. The conversion efficiency increases from 8.1% to 11.5% with a small drop in open circuit voltage and fill factor.

Application of plasmonic bowtie nanoantenna arrays for optical trapping, stacking, and sorting.

We present the use of Au bowtie nanoantenna arrays (BNAs) for highly efficient, multipurpose particle manipulation with unprecedented low input power and low-numerical aperture (NA) focusing. Optical trapping efficiencies measured are up to 20× the efficiencies of conventional high-NA optical traps and are among the highest reported to date. Empirically obtained plasmonic optical trapping "phase diagrams" are introduced to detail the trapping response of the BNAs as a function of input power, wavelength, polarization, particle diameter, and BNA array spacing (number density). Using these diagrams, parameters are chosen, employing strictly the degrees-of-freedom of the input light, to engineer specific trapping tasks including (1) dexterous, single-particle trapping and manipulation, (2) trapping and manipulation of two- and three-dimensional particle clusters, and (3) particle sorting. The use of low input power densities (power and NA) suggests that this bowtie nanoantenna trapping system will be particularly attractive for lab-on-a-chip technology or biological applications aimed at reducing specimen photodamage.

A Metasurface Plasmonic Analysis Platform Combined with Gold Nanoparticles for Ultrasensitive Quantitative Detection of Small Molecules.

Food safety related to drug residues in food has become a widespread public concern. Small-molecule drug residue analysis often relies on mass spectrometry, thin-layer chromatography, or enzyme-linked immunosorbent assays (ELISA). Some of these techniques have limited sensitivity and accuracy, while others are time-consuming, costly, and rely on specialized equipment that requires skilled operation. Therefore, the development of a sensitive, fast, and easy-to-operate biosensor could provide an accessible alternative to conventional small-molecule analysis. Here, we developed a nanocup array-enhanced metasurface plasmon resonance (MetaSPR) chip coupled with gold nanoparticles (AuNPs) (MSPRAN) to detect small molecules. As sulfamethazine drug residues in poultry eggs may cause health issues, we selected this as a model to evaluate the feasibility of using MSPRAN for small-molecule detection. The MSPRAN biosensor employed competitive immunoassay technology for sulfamethazine detection. The limit of detection was calculated as 73 pg/mL, with sensitivity approximately twice that of previously reported detection methods. Additionally, the recovery rate of the biosensor, tested in egg samples, was similar to that measured using ELISA. Overall, this newly developed MSPRAN biosensor platform for small-molecule detection provides fast and reliable results, facile operation, and is relatively cost-effective for application in food safety testing, environmental monitoring, or clinical diagnostics.

Nuclear respiratory factor 1 drives hepatocellular carcinoma progression by activating LPCAT1-ERK1/2-CREB axis.

BACKGROUND: Nuclear respiratory factor 1 (NRF1) is a transcription factor that participates in several kinds of tumor, but its role in hepatocellular carcinoma (HCC) remains elusive. This study aims to explore the role of NRF1 in HCC progression and investigate the underlying mechanisms. RESULTS: NRF1 was overexpressed and hyperactive in HCC tissue and cell lines and high expression of NRF1 indicated unfavorable prognosis of HCC patients. NRF1 promoted proliferation, migration and invasion of HCC cells both in vitro and in vivo. Mechanistically, NRF1 activated ERK1/2-CREB signaling pathway by transactivating lysophosphatidylcholine acyltransferase 1 (LPCAT1), thus promoting cell cycle progression and epithelial mesenchymal transition (EMT) of HCC cells. Meanwhile, LPCAT1 upregulated the expression of NRF1 by activating ERK1/2-CREB signaling pathway, forming a positive feedback loop. CONCLUSIONS: NRF1 is overexpressed in HCC and promotes HCC progression by activating LPCAT1-ERK1/2-CREB axis. NRF1 is a promising therapeutic target for HCC patients.

Lithography-free sub-100 nm nanocone array antireflection layer for low-cost silicon solar cell.

A high-density and -uniformity sub-100 nm surface-oxidized silicon nanocone forest structure is created and integrated onto the existing texturization microstructures on a photovoltaic device surface by a one-step high-throughput plasma-enhanced texturization method. We suppressed the broadband optical reflection on chemically textured grade-B silicon solar cells for up to 70.25% through this nanomanufacturing method. The performance of the solar cell is improved with the short-circuit current increased by 7.1%, fill factor increased by 7.0%, and conversion efficiency increased by 14.66%. Our method demonstrates the potential to improve the photovoltaic device performance with low-cost and high-throughput nanomanufacturing technology.

The microelectronic wireless nitrate sensor network for environmental water monitoring.

Quantitative monitoring of water conditions in a field is a critical ability for environmental science studies. We report the design, fabrication and testing of a low cost, miniaturized and sensitive electrochemical based nitrate sensor for quantitative determination of nitrate concentrations in water samples. We have presented detailed analysis for the nitrate detection results using the miniaturized sensor. We have also demonstrated the integration of the sensor to a wireless network and carried out field water testing using the sensor. We envision that the field implementation of the wireless water sensor network will enable "smart farming" and "smart environmental monitoring".

Nonlinear optical response from arrays of Au bowtie nanoantennas.

We demonstrate that the optical response of a single Au bowtie nanoantenna can be favorably modified to increase the local intensity by a factor of 10(3) in the feed gap region when a periodic array of antennas are used. We find that the array periodicity can be used to modulate and shape the spectral emission. An analysis of the emission confirms the presence of second-harmonic generation and two-photon photoluminescence, typical of gold nanostructures, but also reveals a portion of the emitted spectrum that cannot be attributed to a single multiphoton process. Our investigations have important implications for understanding the role of resonant nanostructures in designing optical antennas for next-generation photonic technologies.

Applying Machine Learning with Localized Surface Plasmon Resonance Sensors to Detect SARS-CoV-2 Particles.

The sudden outbreak of COVID-19 rapidly developed into a global pandemic, which caused tens of millions of infections and millions of deaths. Although SARS-CoV-2 is known to cause COVID-19, effective approaches to detect SARS-CoV-2 using a convenient, rapid, accurate, and low-cost method are lacking. To date, most of the diagnostic methods for patients with early infections are limited to the detection of viral nucleic acids via polymerase chain reaction (PCR), or antigens, using an enzyme-linked immunosorbent assay or a chemiluminescence immunoassay. This study developed a novel method that uses localized surface plasmon resonance (LSPR) sensors, optical imaging, and artificial intelligence methods to directly detect the SARS-CoV-2 virus particles without any sample preparation. The virus concentration can be qualitatively and quantitatively detected in the range of 125.28 to 106 vp/mL through a few steps within 12 min with a limit of detection (LOD) of 100 vp/mL. The accuracy of the SARS-CoV-2 positive or negative assessment was found to be greater than 97%, and this was demonstrated by establishing a regression machine learning model for the virus concentration prediction (R2 > 0.95).

Ultrasensitive Detection of C-Reactive Protein by a Novel Nanoplasmonic Immunoturbidimetry Assay.

Nanotechnology has attracted much attention, and may become the key to a whole new world in the fields of food, agriculture, building materials, machinery, medicine, and electrical engineering, because of its unique physical and chemical properties, including high surface area and outstanding electrical and optical properties. The bottom-up approach in nanofabrication involves the growth of particles, and we were inspired to propose a novel nanoplasmonic method to detect the formation of nanoparticles in real time. This innovative idea may contribute to the promotion of nanotechnology development. An increase in nanometer particle size leads to optical extinction or density (OD)-value changes in our nanosensor chip at a specific wavelength measured in a generic microplate reader. Moreover, in applying this method, an ultrasensitive nanoplasmonic immunoturbidimetry assay (NanoPITA) was carried out for the high-throughput quantification of hypersensitive C-reactive protein (CRP), a well-known biomarker of cardiovascular, inflammatory, and tumor diseases. The one-step detection of the CRP concentration was completed in 10 min with high fidelity, using the endpoint analysis method. The new NanoPITA method not only produced a linear range from 1 ng/mL to 500 ng/mL CRP with the detection limit reduced to 0.54 ng/mL, which was an improvement of over 1000 times, with respect to regular immunoturbidity measurement, but was also effective in blood detection. This attractive method, combined with surface plasmon resonance and immunoturbidimetry, may become a new technology platform in the application of biological detection.

Metal-molecule Schottky junction effects in surface enhanced Raman scattering.

We propose a complementary interpretation of the mechanism responsible for the strong enhancement observed in surface enhanced raman scattering (SERS). The effect of a strong static local electric field due to the Schottky barrier at the metal-molecule junction on SERS is systematically investigated. The study provides a viable explanation to the low repeatability of SERS experiments as well as the Raman peak shifts as observed in SERS and raw Raman spectra. It was found that a strong electrostatic built-in field at the metal-molecule junction along specific orientations can result in 2-4 more orders of enhancement in SERS.

Application of Machine Learning and Weighted Gene Co-expression Network Algorithm to Explore the Hub Genes in the Aging Brain.

Aging is a major risk factor contributing to neurodegeneration and dementia. However, it remains unclarified how aging promotes these diseases. Here, we use machine learning and weighted gene co-expression network (WGCNA) to explore the relationship between aging and gene expression in the human frontal cortex and reveal potential biomarkers and therapeutic targets of neurodegeneration and dementia related to aging. The transcriptional profiling data of the human frontal cortex from individuals ranging from 26 to 106 years old was obtained from the GEO database in NCBI. Self-Organizing Feature Map (SOM) was conducted to find the clusters in which gene expressions downregulate with aging. For WGCNA analysis, first, co-expressed genes were clustered into different modules, and modules of interest were identified through calculating the correlation coefficient between the module and phenotypic trait (age). Next, the overlapping genes between differentially expressed genes (DEG, between young and aged group) and genes in the module of interest were discovered. Random Forest classifier was performed to obtain the most significant genes in the overlapping genes. The disclosed significant genes were further identified through network analysis. Through WGCNA analysis, the greenyellow module is found to be highly negatively correlated with age, and functions mainly in long-term potentiation and calcium signaling pathways. Through step-by-step filtering of the module genes by overlapping with downregulated DEGs in aged group and Random Forest classifier analysis, we found that MAPT, KLHDC3, RAP2A, RAP2B, ELAVL2, and SYN1 were co-expressed and highly correlated with aging.

Printed Electrode for Measuring Phosphate in Environmental Water.

Phosphate is a major nonpoint source pollutant in both the Louisiana local streams as well as in the Gulf of Mexico coastal waters. Phosphates from agricultural run-off have contributed to the eutrophication of global surface waters. Phosphate environmental dissemination and eutrophication problems are not yet well understood. Thus, this study aimed to monitor phosphate in the local watershed to help identify potential hot spots in the local community (Mississippi River, Louisiana) that may contribute to nutrient loading downstream (in the Gulf of Mexico). An electrochemical method using a physical vapor deposited cobalt microelectrode was utilized for phosphate detection using cyclic voltammetry and amperometry. The testing results were utilized to evaluate the phosphate distribution in river water and characterize the performance of the microsensor. Various characterizations, including the limit of detection, sensitivity, and reliability, were conducted by measuring the effect of interferences, including dissolved oxygen, pH, and common ions. The electrochemical sensor performance was validated by comparing the results with the standard colorimetry phosphate detection method. X-ray photoelectron spectroscopy (XPS) measurements were performed to understand the phosphate sensing mechanism on the cobalt electrode. This proof-of-concept sensor chip could be utilized for on-field monitoring using a portable, hand-held potentiostat.

Quantized plasmon quenching dips nanospectroscopy via plasmon resonance energy transfer.

We observed quantized plasmon quenching dips in resonant Rayleigh scattering spectra by plasmon resonance energy transfer (PRET) from a single nanoplasmonic particle to adsorbed biomolecules. This label-free biomolecular absorption nanospectroscopic method has ultrahigh molecular sensitivity.

Surface-enhanced Raman nanodomes.

We demonstrate a surface-enhanced Raman scattering (SERS) substrate consisting of a closely spaced metal nanodome array fabricated on flexible plastic film. We used a low-cost, large-area replica molding process to produce a two-dimensional periodic array of cylinders that is subsequently overcoated with SiO(2) and silver thin films to form dome-shaped structures. Finite element modeling was used to investigate the electromagnetic field distribution of the nanodome array structure and the effect of the nanodome separation distance on the electromagnetic field enhancement. The SERS enhancement from the nanodome array substrates was experimentally verified using rhodamine 6G as the analyte. With a separation distance of 17 nm achieved between adjacent domes using a process that is precisely controlled during thin film deposition, a reproducible SERS enhancement factor of 1.37 × 10(8) was demonstrated. The nanoreplica molding process presented in this work allows for simple, low-cost, high-throughput fabrication of uniform nanoscale SERS substrates over large surface areas without the requirement for high resolution lithography or defect-free deposition of spherical microparticle monolayer templates.