Signal Enhancement Research Articles

An super sensitive Multi-Modal controlled release biosensor with label- and enzyme- free assisted single step simultaneously detect multiple breast cancer biomarkers

Despite the fact that homogeneous biosensing strategies have been proven to be advantageous, it remains a difficult task to identify multiple tumor biomarkers. Our proposition entails the creation of a groundbreaking biosensor that combines electrochemical and fluorescent techniques, enabling simultaneous detect multiple biomarkers with label- and enzyme-free assistance in a single step. Porous UIO-66-NH2 nanovessels loaded with 3,3′,5,5′ −tetramethylbenzidine (TMB) and methylene blue (MB) double signal dyes, along with double-stranded DNA (dsDNA) formed by the aptamer chain of human epidermal growth factor receptor-2 (HER2) and estrogen receptor (ER) and its complementary chain as a gated switch to the envelope MOFs, were utilized to create functional MOFs (dsDNA@MB@UIO and dsDNA@TMB@UIO). When HER2 and ER targets are present, the chain replacement reaction led to the formation of a biomarker-aptamer complex, resulting in the destruction of the dsDNA structure on the surface of MOF and the liberation of MB and TMB. The concentration of the two target biomarkers determines the strength of the electrochemical and fluorescent signals produced. By combining targeted biomarkers, signal enhancement, and dual-signal detection into one unified process, the amount of test error caused by the multi-step detection needed in prior studies is significantly decreased. We executed the detect HER2 and ER, achieving detection limits of 4.7 and 5.9 fg/mL in 4.7–1000 pg/mL linear range with good selectivity, stability, reproducibility, and acceptable applicability. The proposed biosensor for developing dsDNA@MB@UIO and dsDNA@TMB@UIO is promising for the early and sensitive detection of cancer biomarkers.

P53 Status Influences the Anti-proliferative Effect Induced by IFITM1 Inhibition in Estrogen Receptor-positive Breast Cancer Cells.

Interferon-induced trans-membrane protein 1 (IFITM1) is known to be involved in breast cancer progression. We aimed to investigate its role in estrogen receptor (ER)-positive breast cancer cells with wild-type p53 and tamoxifen-resistant breast cancer cells. The ER-positive breast cancer cell lines, MCF-7 with wild-type p53 and T47D with mutant p53, were used. We established an MCF-7-derived tamoxifen-resistant cell line (TamR) by long-term culture of MCF-7 cells with 4-hydroxytamoxifen. IFITM1 inhibition in MCF-7 cells significantly decreased cell growth and migration. MCF-7 cells with suppression of IFITM1 using siRNA or ruxolitinib showed reduced cell viability after tamoxifen treatment compared with that in the control MCF-7 cells. Unexpectedly, mRNA and protein levels of IFITM1 were decreased in TamR cells compared with those in MCF-7 cells. TamR cells with suppression of IFITM1 using siRNA or ruxolitinib showed no change in cell viability after treatment with tamoxifen. P53 knockdown using siRNA reduced the mRNA levels of IRF9 and increased mRNA and protein levels of SOCS3 in MCF-7 cells, suggesting that loss or mutation of p53 can affect the induction of IFITM1 via the JAK/STAT signaling pathway in breast cancer. Furthermore, MCF-7 cells with p53 knockdown using siRNA showed no decrease in cell viability after tamoxifen treatment or IFITM1 inhibition, indicating that p53 status may be important for cell death after tamoxifen treatment or IFITM1 inhibition. IFITM1 inhibition may enhance the sensitivity to tamoxifen based on p53-dependent enhancement of IFN signaling in wild-type p53, ER-positive breast cancer cells.

A Deep Learning-Based Framework for Highly Accelerated Prostate MR Dispersion Imaging.

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) measures microvascular perfusion by capturing the temporal changes of an MRI contrast agent in a target tissue, and it provides valuable information for the diagnosis and prognosis of a wide range of tumors. Quantitative DCE-MRI analysis commonly relies on the nonlinear least square (NLLS) fitting of a pharmacokinetic (PK) model to concentration curves. However, the voxel-wise application of such nonlinear curve fitting is highly time-consuming. The arterial input function (AIF) needs to be utilized in quantitative DCE-MRI analysis. and in practice, a population-based arterial AIF is often used in PK modeling. The contribution of intravascular dispersion to the measured signal enhancement is assumed to be negligible. The MR dispersion imaging (MRDI) model was recently proposed to account for intravascular dispersion, enabling more accurate PK modeling. However, the complexity of the MRDI hinders its practical usability and makes quantitative PK modeling even more time-consuming. In this paper, we propose fast MR dispersion imaging (fMRDI) to effectively represent the intravascular dispersion and highly accelerated PK parameter estimation. We also propose a deep learning-based, two-stage framework to accelerate PK parameter estimation. We used a deep neural network (NN) to estimate PK parameters directly from enhancement curves. The estimation from NN was further refined using several steps of NLLS, which is significantly faster than performing NLLS from random initializations. A data synthesis module is proposed to generate synthetic training data for the NN. Two data-processing modules were introduced to improve the model's stability against noise and variations. Experiments on our in-house clinical prostate MRI dataset demonstrated that our method significantly reduces the processing time, produces a better distinction between normal and clinically significant prostate cancer (csPCa) lesions, and is more robust against noise than conventional DCE-MRI analysis methods.

On Beamforming with the Single-Sideband Transform

In this paper, we examine the use of the Single-Sideband Transform (SSBT) for convolutive beamformers. We explore its unique properties and implications for beamformer design. Our study sheds light on the tradeoffs involved in using the SSBT in beamforming applications, offering insights into both its strengths and limitations. Despite the advantage of having real-valued coefficients, we show that the convolution handling of the transform presents challenges that impact fundamental beamforming principles. When compared to the Short-Time Fourier Transform (STFT), the SSBT displays lower robustness, especially in scenarios involving mismatch and modeling noise. Notably, we establish a direct equivalence between the SSBT and STFT when using identical transform parameters, enabling their seamless interchangeability and joint use in time–frequency signal enhancements. We validate our theoretical findings through realistic simulations using the Minimum-Power Distortionless Response beamformer. These simulations illustrate that although the STFT performs marginally better than the SSBT under optimal conditions, it outperforms significantly in non-ideal scenarios.

Pseudo-myometrial thinning in placental site trophoblastic tumors: a case series with multiparametric MRI.

Placental site trophoblastic tumor (PSTT) is a rare form of gestational trophoblastic neoplasm with few previous imaging case reports. We report multiparametric MRI findings in four cases of PSTT with special emphasis on the "pseudo-myometrial thinning" underlying the tumor. We reviewed multiparametric MRI and pathologic findings in four cases of PSTT from four institutions. Signal intensity, enhancement pattern, margins, and location of the tumors were evaluated, and myometrial thickness underlying the tumor and normal myometrial thickness contralateral to the tumor were measured on MRI. The myometrial thickness underlying the tumor was also measured in the resected specimen and compared with the myometrial thickness measured on MRI using the Friedman test. All tumors showed heterogeneous signal intensity on T1-weighted imaging, T2-weighted imaging (T2WI), and diffusion-weighted imaging. Three of the four tumors had a hypervascular area on dynamic contrast-enhanced (DCE) MRI. A hypointense rim on T2WI and DCE-MRI was seen in all tumors. All tumors protruded into the uterine cavity to varying degrees and extended into the myometrium close to the serosa. The myometrial thickness underlying the tumor measured on MRI (median thickness, 1.2mm) was significantly thinner than that measured on pathology (median thickness, 9.5mm) and normal myometrial thickness contralateral to the tumor on MRI (median thickness, 10.3mm) (P = 0.02), and there was no significant difference between the latter two. The thickness of the myometrium underlying the tumor on MRI was approximately one tenth of the thickness on pathology. Thus, the tumors appeared to have almost transmural invasion even when pathologically located within the superficial myometrium. This "pseudo-thinning" of the underlying myometrium and the hypointense rim on MRI could be caused by focal compression of the myometrium by the tumor, possibly due to the fragility of the myometrium at the placental site.

Using Adaptive Imaging Parameters to Improve PEGylated Ultrasmall Iron Oxide Nanoparticles-Enhanced Magnetic Resonance Angiography.

The PEGylated ultrasmall iron oxide nanoparticles (PUSIONPs) exhibit longer blood residence time and better biodegradability than conventional gadolinium-based contrast agents (GBCAs), enabling prolonged acquisitions in contrast-enhanced magnetic resonance angiography (CE-MRA) applications. The image quality of CE-MRA is dependent on the contrast agent concentration and the parameters of the pulse sequences. Here, a closed-form mathematical model is demonstrated and validated to automatically optimize the concentration, echo time (TE), repetition time (TR) and flip angle (FA). The pharmacokinetic studies are performed to estimate the dynamic intravascular concentrations within 12h postinjection, and the adaptive concentration-dependent sequence parameters are determined to achieve optimal signal enhancement during a prolonged measurement window. The presented model is tested on phantom and in vivo rat images acquired from a 3T scanner. Imaging results demonstrate excellent agreement between experimental measurements and theoretical predictions, and the adaptive sequence parameters obtain better signal enhancement than the fixed ones. The low-dose PUSIONPs (0.03mmol kg-1 and 0.05mmol kg-1) give a comparable signal intensity to the high-dose one (0.10mmol kg-1) within 2h postinjection. The presented mathematical model provides guidance for the optimization of the concentration and sequence parameters in PUSIONPs-enhanced MRA, and has great potential for further clinical translation.

Prefrontal Excitation/ Inhibition Balance Supports Adolescent Enhancements in Circuit Signal to Noise Ratio.

The development and refinement of neuronal circuitry allow for stabilized and efficient neural recruitment, supporting adult-like behavioral performance. During adolescence, the maturation of PFC is proposed to be a critical period (CP) for executive function, driven by a break in balance between glutamatergic excitation and GABAergic inhibition (E/I) neurotransmission. During CPs, cortical circuitry fine-tunes to improve information processing and reliable responses to stimuli, shifting from spontaneous to evoked activity, enhancing the SNR, and promoting neural synchronization. Harnessing 7T MR spectroscopy and EEG in a longitudinal cohort (N = 164, ages 10-32 years, 283 neuroimaging sessions), we outline associations between age-related changes in glutamate and GABA neurotransmitters and EEG measures of cortical SNR. We find developmental decreases in spontaneous activity and increases in cortical SNR during our auditory steady state task using 40 Hz stimuli. Decreases in spontaneous activity were associated with glutamate levels in DLPFC, while increases in cortical SNR were associated with more balanced Glu and GABA levels. These changes were associated with improvements in working memory performance. This study provides evidence of CP plasticity in the human PFC during adolescence, leading to stabilized circuitry that allows for the optimal recruitment and integration of multisensory input, resulting in improved executive function.

Low-cost heat assisted ambient ionization source for mass spectrometry in food and pharmaceutical screening.

Ambient Ionization Mass Spectrometry (AI-MS) techniques have revolutionized analytical chemistry by enabling rapid analysis of samples under atmospheric conditions with minimal to no preparation. In this study, the optimization of a cold atmospheric plasma for the analysis of food and pharmaceutical samples, liquid and solid, using a Heat-Assisted Dielectric Barrier Discharge Ionization (HA-DBDI) source is described. A significant enhancement in analyte signals was observed when a heating element was introduced into the design, potentially allowing for greater sensitivity. Furthermore, the synergy between the inlet temperature of the mass spectrometer and the heating element allows for precise control over the analytical process, leading to improved detection sensitivity and selectivity. Incorporating computational fluid dynamic (CFD) simulations into the study elucidated how heating modifications can influence gas transport properties, thereby facilitating enhanced analyte detection and increased signal intensity. These findings advance the understanding of HA-DBDI technology and provide valuable insights for optimizing AI-MS methodologies for a wide range of applications in food and pharmaceutical analysis.

A Comprehensive Approach to ECG Signal Enhancement Using Multi-Filter SNR Improvement and Baseline Shift Correction

A Comprehensive Approach to ECG Signal Enhancement Using Multi-Filter SNR Improvement and Baseline Shift Correction

Light-Switch Electrochemiluminescence-Driven microfluidic sensor for rapid and sensitive detection of Mpox virus

Rapid, real-time, and accurate detection of pathogenic nucleic acids is crucial for the control and treatment of Mpox virus infection; however, classical detection methods are limited by time-consuming amplification steps, cumbersome equipment, and the requirement for professional operators. Herein, we developed an electrochemiluminescence (ECL)-driven microfluidic detection chip based on a light-switch molecule, which when coupled with rapid recombinase polymerase amplification (RPA) enabled the detection of Mpox within 30 min. [Ru(phen)2dppz]2+ was used as the ECL light-switch molecule owing to its significant ECL signal enhancement property when intercalated into double-stranded RPA products. The microfluidic chip included two independent liquid storage tanks preloaded with an RPA reagent mixture and [Ru(phen)2dppz]2+, which were mixed via centrifugation to produce ECL signals. The developed sensing platform effectively detected Mpox virus with high sensitivity, and the limit of detection was as low as 10 copies/µL. Moreover, it showed 100 % sensitivity and 100 % specificity when validated against the quantitative polymerase chain reaction assay using clinical samples from the pustules, throat, urine, blood, saliva, and anus of Mpox-positive patients. Combined with a hand-held detection device, this platform can facilitate the early diagnosis of Mpox cases in point-of-care testing without trained personnel and specialized equipment.

Selective excitation of vibrations in a single molecule

The capability to excite, probe, and manipulate vibrational modes is essential for understanding and controlling chemical reactions at the molecular level. Recent advancements in tip-enhanced Raman spectroscopies have enabled the probing of vibrational fingerprints in a single molecule with Ångström-scale spatial resolution. However, achieving controllable excitation of specific vibrational modes in individual molecules remains challenging. Here, we demonstrate the selective excitation and probing of vibrational modes in single deprotonated phthalocyanine molecules utilizing resonance Raman spectroscopy in a scanning tunneling microscope. Selective excitation is achieved by finely tuning the excitation wavelength of the laser to be resonant with the vibronic transitions between the molecular ground electronic state and the vibrational levels in the excited electronic state, resulting in the state-selective enhancement of the resonance Raman signal. Our approach contributes to setting the stage for steering chemical transformations in molecules on surfaces by selective excitation of molecular vibrations.

Harnessing Biopolymer Gels for Theranostic Applications: Imaging Agent Integration and Real-Time Monitoring of Drug Delivery.

Biopolymer gels have gained tremendous potential for therapeutic applications due to their biocompatibility, biodegradability, and ability to adsorb and bind biological fluids, making them attractive for drug delivery and therapy. In this study, the versatility of biopolymer gels is explored in theranostic backgrounds, with a focus on integrating imaging features and facilitating real-time monitoring of drug delivery. Different methods of delivery are explored for incorporating imaging agents into biopolymer gels, including encapsulation, surface functionalization, nanoparticle encapsulation, and layer-by-layer assembly techniques. These methods exhibit the integration of agents and real-time monitoring drug delivery. We summarize the synthesis methods, general properties, and functional mechanisms of biopolymer gels, demonstrating their broad applications as multimodal systems for imaging-based therapeutics. These techniques not only enable multiple imaging but also provide signal enhancement and facilitate imaging targets, increasing the diagnostic accuracy and therapeutic efficacy. In addition, current techniques for incorporating imaging agents into biopolymer gels are discussed, as well as their role in precise drug delivery and monitoring.

A visual biosensor chip based on the enhanced electrochemiluminescence with low triggered potential for ochratoxin A detection

The introduction of a coreaction accelerator can effectively enhance the electrochemiluminescence (ECL) response. However, the development of coreaction accelerators for ruthenium (Ru) complex, one of the most widely used ECL emitters, is still in its early stages. In this study, the application of BiOI as a multifunctional coreaction accelerator for the Ru/N-Butyldiethanolamine (DBAE) system for the first time. The BiOI microspheres not only exhibit a fivefold enhancement in ECL signal but also reduce the trigger potential, potentially mitigating interference factors associated with high applied voltage. The nanoflower structure of BiOI microspheres also facilitates the immobilization of Ru(bpy)32+. Building upon this, a portable visual biosensor chip was developed for the detection of ochratoxin A (OTA). The biosensor chip comprises a sensing cell and a reporting cell. When OTA toxins are detected in the microenvironment, the aptamers attached to the surface of the sensing cell are released, resulting in a decrease in impedance on the electrode surface. Consequently, the ECL emission from Ru(bpy)32+/BiOI microspheres modified onto the reporting cell is enhanced. The concentration of OTA can be determined by analyzing the intensity change of ECL imaging, eliminating the need for specific instruments. This visual ECL biosensor chip offers the advantages of portability, ease of operation, low cost, and demonstrates excellent performance in detecting beer samples.

Photothermal Backscatter Interferometry for Enhanced Detection in Capillary Electrophoresis.

Refractive index (RI) detection using backscatter interferometry (BSI) enables universal detection in capillary electrophoresis (CE). BSI detection is a versatile on-capillary approach that is easily integrated with capillary or microfluidic channels, straightforward to miniaturize, and inexpensive. The focused BSI light source can also double as the excitation source for fluorescence, enabling simultaneous universal (BSI) and specific (fluorescence) signals from the same detection volume. To improve BSI detection and expand orthogonal content, we integrate photothermal absorption with BSI detection. Nonradiative relaxation of an excited analyte releases heat into the surroundings, which modifies both the local RI and conductivity (viscosity) of the analyte zone. We recently showed that the BSI signal is sensitive to both RI and conductivity, which makes photothermal absorption a promising route to signal enhancement. Here, we use coaxially delivered BSI and photothermal absorption beams to characterize BSI, photothermal BSI, and fluorescence detection using the separation of test samples. We show that photothermal absorption leads to 3 orders of magnitude improvement in BSI detection limits at the powers studied and provides new opportunities for studying binding interactions with CE.

Label-free and liquid state SERS detection of multi-scaled bioanalytes via light-induced pinpoint colloidal assembly

Surface-enhanced Raman scattering (SERS) has been extensively applied to detect complex analytes due to its ability to enhance the fingerprint signals of molecules around nanostructured metallic surfaces. Thus, it is essential to design SERS-active nanostructures with abundant electromagnetic hotspots in a probed volume according to the dimensions of the analytes, as the analytes must be located in their hotspots for maximum signal enhancement. Herein, we demonstrate a simple method for detecting robust SERS signals from multi-scaled bioanalytes, regardless of their dimensions in the liquid state, through a photothermally driven co-assembly with colloidal plasmonic nanoparticles as signal enhancers. Under resonant light illumination, plasmonic nanoparticles and analytes in the solution quickly assemble at the focused surface area by convective movements induced by the photothermal heating of the plasmonic nanoparticles without any surface modification. Such collective assemblies of plasmonic nanoparticles and analytes were optimized by varying the optical density and surface charge of the nanoparticles, the viscosity of the solvent, and the light illumination time to maximize the SERS signals. Using these light-induced co-assemblies, the intrinsic SERS signals of small biomolecules can be detected down to nanomolar concentrations based on their fingerprint spectra. Furthermore, large-sized biomarkers, such as viruses and exosomes, were successfully detected without labels, and the complexity of the collected spectra was statistically analyzed using t-distributed stochastic neighbor embedding combined with support vector machine (t-SNE + SVM). The proposed method is expected to provide a robust and convenient method to sensitively detect biologically and environmentally relevant analytes at multiple scales in liquid samples.

Concurrent performance and security enhancement of ultrahigh-order DSM signals via null subcarriers.

In this paper, we propose leveraging null subcarriers in discrete multi-tone modulation (DMT) to process the DMT signal in both time and frequency domains. Additionally, we employ discrete memory enhanced chaos (DMEC) to scramble the signal in the frequency domain, thereby achieving physical layer signal encryption while ensuring a more uniform power distribution in the time-domain waveform. In our experimental demonstration, we achieved high-security transmission of a DSM-based 65536-QAM signal at a data rate of 16.01 Gb/s over a 25 km single-mode fiber (SMF) in an intensity-modulation direct-detection (IMDD) system. Additionally, in the transmission experiments for 13684-QAM and 65536-QAM signals, the proposed method demonstrated a receiver sensitivity gain of over 0.5 dB compared to the traditional DSM-based ultrahigh-order transmission.

Zr-MOF Carrier-Enhanced Dual-Mode Biosensing Platforms for Rapid and Sensitive Diagnosis of Mpox.

Dual-mode readout platforms with colorimetric and electrochemiluminescence (ECL) signal enhancement are proposed for the ultrasensitive and flexible detection of the monkeypox virus (MPXV) in different scenes. A new nanotag, Ru@U6-Ru/Pt NPs is constructed for dual-mode platforms by integrating double-layered ECL luminophores and the nanozyme using Zr-MOF (UiO-66-NH2) as the carrier, which not only generates enhanced ECL and colorimetric signals but also provide greater stability than that of commonly used nanotags. Dual-mode platforms are used within 15min from the "sample in" to the "result out" steps, without nucleic acid amplification. The colorimetric mode allows the screening of MPXV with the visual limit of detection (vLOD) of 0.1 pM (6 × 108 copies µL-1) and the ECL mode supports quantitative detection of MPXV with an LOD as low as 10 aM (6 copies·µL-1), resulting in a broad sensing range of 60 to 3 × 1011 copies·µL-1 (10 orders of magnitude). Validation is conducted using 50 clinical samples, which is 100% concordant to those of quantitative polymerase chain reaction (qPCR), indicating that Ru@U6-Ru/Pt NPs-based dual-mode sensing platforms showed great promise as rapid, sensitive, and accurate tools for diagnosis of the nucleic acid of MPXV and other infectious pathogens.

(Digital Presentation) Cooperative Quantum Dynamics of Excitons in Colloidal Quantum Dots for Novel Optoelectronic Applications

Colloidal semiconductor quantum dots (QDs) are excellent materials for combining photonics and nanoscience. They have been extensively studied to understand the photophysics of quantum confined excitons and to develop efficient optoelectronic devices such as QD solar cells and light-emitting diodes. The photophysical processes of QD devices are governed by a large number of QDs constructing the devices. Therefore, cooperative quantum dynamics of QDs, i.e., synchronous responses of QD ensembles, have a great potential for boosting optoelectronic device performances.Before the use of cooperative quantum dynamics in QD devices, the understanding of quantum dynamics of excitons, i.e., coherent properties of multiexcitons, is required to draw out quantum cooperativity from QD ensembles. In order to elucidate coherent dynamics of multiexcitons during resonant laser-pulse excitation, we performed a quantum interference spectroscopy of QD responses. We found that multiexcitons generate the high-frequency coherent oscillations with integer multiples of the exciton resonance frequency, which is called harmonic quantum coherence, and that the coherent responses govern the microscopic processes in the resonant multiphoton absorption [1-3]. Furthermore, it was demonstrated that the coherent responses were detectable as photocurrent signals in thin films of QD ensembles [4]. These developments build up an essential base of quantum cooperativities emerging in optoelectronics.Here, we report recent investigations of cooperative quantum dynamics in QDs. In optoelectronic devices, electronic couplings between QDs are expected to generate a new type of quantum cooperativities. To generate electronic coupling, we fabricated closely packed PbS QDs by using a ligand exchange method. We found that nonlinear photocurrent signals are strongly enhanced in the QD solids. The comparison analysis of different ligands clarified that the enhancement ratio increases monotonically with the decrease of the inter-QD distance [5]. This means that the signal enhancement originates from the electronic coupling and cooperative behavior of QDs. These findings show that the cooperative quantum dynamics provide a new route to advanced optoelectronic technology such as nonlinear amplifiers.Part of this work was supported by JSPS KAKENHI (JP19H05465, JP22H01990, and JP23K17877), JST PRESTO (JPMJPR23H3), and JST CREST (JPMJCR21B4).

Hybrid Polystyrene-Plasmonic Systems as High Binding Density Biosensing Platforms.

Sensitive, accurate, and early detection of biomarkers is essential for prompt response to medical decisions for saving lives. Some infectious diseases are deadly even in small quantities and require early detection for patients and public health. The scarcity of these biomarkers necessitates signal amplification before diagnosis. Recently, we demonstrated single-molecule-level detection of tuberculosis biomarker, lipoarabinomannan, from patient urine using silver plasmonic gratings with thin plasma-activated alumina. While powerful, biomarker binding density was limited by the surface density of plasma-activated carbonyl groups, that degraded quickly, resulting in immediate use requirement after plasma activation. Therefore, development of stable high density binding surfaces such as high binding polystyrene is essential to improving shelf-life, reducing binding protocol complexity, and expanding to a wider range of applications. However, any layers topping the plasmonic grating must be ultra-thin (<10 nm) for the plasmonic enhancement of adjacent signals. Furthermore, fabricating thin polystyrene layers over alumina is nontrivial because of poor adhesion between polystyrene and alumina. Herein, we present the development of a stable, ultra-thin polystyrene layer on the gratings, which demonstrated 63.8 times brighter fluorescence compared to commercial polystyrene wellplates. Spike protein was examined for COVID-19 demonstrating the single-molecule counting capability of the hybrid polystyrene-plasmonic gratings.

STAR-RIS aided NOMA Networks: A Signal Enhancement Algorithm

In order to overcome the reflecting-only issue of the conventional reconfigurable intelligent surface (RIS), simultaneous-transmitting-and-reflecting reconfigurable intelligent surface (STAR-RIS) stands as a potential solution for providing access services to the users located at the full space. By utilizing the omnidirectional properties of STAR-RIS, non-orthogonal multiple access (NOMA) users on both sides can be served simultaneously. By making the signal reflected by STAR-RIS coherent superposition with the direct signal, using the Riemannian optimization algorithm (ROA), the proposed signal enhancement algorithm can greatly enhance the signal power of NOMA users, reduce the outage probability, and improve the ergodic rate performance. According to the simulation results, the random phase STAR-RIS can improve the spectral efficiency of 3.6bit/s/Hz compared without STAR-RIS. After using the proposed ROA, the spectral efficiency can be extra increased by 1.8bit/s/Hz, which verifies the superiority of the proposed algorithm.