Search Results (1,452)

Photodynamic therapy (PDT) exploits photoactivated materials that generate reactive oxygen species (ROS) to induce selective cancer cell death. Nitrogen-doped carbon dots (N-CDs) have emerged as promising photosensitizers owing to their favorable optical properties, while hybridization with titanium dioxide (TiO₂) may further enhance photoinduced ROS generation through improved charge separation. Here, we synthesized a series of N-CD/TiO₂ hybrid composites with varying TiO₂ content using a hydrothermal approach and systematically investigated the relationship between their physicochemical characteristics and biological activity. The hybrid materials were characterized by Fourier-transform infrared spectroscopy, X-ray diffraction, scanning electron microscopy, dynamic light scattering, and UV–visible spectroscopy. Among the formulations investigated, the composite containing 90% N-CDs and 10% TiO₂ (N-CDs10T) exhibited the smallest hydrodynamic diameter, a relatively narrow particle size distribution, favorable optical properties, and the strongest irradiation-dependent biological responses. Biological activity was evaluated in A549 lung adenocarcinoma and Kelly neuroblastoma cells. Under dark conditions, all formulations displayed relatively low intrinsic cytotoxicity. Following irradiation with 365 nm UVA light, however, N-CDs10T induced a marked increase in intracellular ROS production, activation of antioxidant response element (ARE)-dependent signaling, disruption of cell-cycle progression, apoptosis-associated cell death, and inhibition of cell proliferation and migration. Kelly cells exhibited greater sensitivity than A549 cells, with IC₅₀ values decreasing from 0.98 mg/mL under dark conditions to 0.52 mg/mL following irradiation. Collectively, these findings demonstrate that N-CD/TiO₂ hybrid composites function as photoresponsive materials that enhance ROS-mediated cytotoxicity upon light activation. Beyond demonstrating phototoxicity, this study systematically links hybrid composition with oxidative stress signaling and multiple cellular responses, providing a comprehensive biological evaluation of N-CD/TiO₂ hybrid materials. While additional studies are required to identify the predominant ROS, evaluate selectivity in non-malignant cells, and optimize activation at clinically relevant wavelengths, the present work establishes a proof of concept for the development of N-CD/TiO₂ hybrid composites for photodynamic applications. Full article

Molecularly imprinted polymers (MIPs) have emerged as promising recognition materials for antibiotic sensing owing to their high stability, low cost, and tunable selectivity. However, enhanced recognition capability does not necessarily translate into high-performance sensing. A critical yet often overlooked bottleneck lies in the inherently indirect nature of this conversion: molecular binding occurs within an insulating polymer matrix that is spatially and functionally decoupled from the underlying signal transducer, particularly in complex environmental matrices. To address this limitation, this review proposes a unified framework centered on recognition–structure–signal interplay. Within this framework, sensing performance depends not on the simple addition of independently optimized components, but on the synergistic integration of recognition fidelity, structural accessibility, and signal transduction efficiency. Recent advances in electrochemical, optical, photoelectrochemical, and electrochemiluminescent MIP sensors are critically examined through this lens, with emphasis on platform-specific failure modes-including inaccessible recognition sites, insufficient site-transducer integration, weak binding-induced signal modulation, signal amplification-dominated responses, and matrix-induced decoupling. Machine learning is further critically assessed as an emerging data-driven tool for MIP design, signal decoding, experimental optimization, and sensor-level performance prediction, while its broader applicability remains constrained by limited datasets, insufficient external validation, and poor cross-platform transferability. Despite major progress in sensitivity, unresolved challenges persist, including weak intrinsic conversion efficiency, structural trade-offs, limited reliability in real-world samples, a lack of standardized validation protocols, and poor scalability of laboratory fabrication. This review concludes that next-generation MIP-based antibiotic sensors require a paradigm shift from affinity-oriented imprinting and signal amplification toward co-localized recognition-transduction interfaces, matrix-tolerant architectures, interpretable data-driven design, and manufacturable field-deployable systems. Full article

Hybrid terahertz (THz)/free-space optical (FSO) systems offer a promising paradigm for high-capacity, all-weather wireless communication, yet their deployment is often hindered by the bulky size and high complexity of discrete transceivers. This paper experimentally demonstrates a low-complexity hybrid THz/FSO transmission architecture featuring a unified photonic transmitter. By leveraging a polymethyl methacrylate (PMMA) plate serving as a dichroic beam combiner—which reflects the 1550 nm optical signal while transmitting the 300 GHz THz signal—we realize simultaneous signal propagation over a shared aperture and link. Photonics-aided techniques are employed to generate both carriers, ensuring system integration and coherence. The experimental results verify that both the THz and FSO links independently support 30-GBaud quadrature phase-shift keying (QPSK) transmission over a 10-m wireless distance, achieving a net data rate of 60 Gbps per link while satisfying the 7% hard-decision forward error correction (HD-FEC) threshold of 3.8 × 10⁻³. This work validates the feasibility of shared-transmitter designs and provides a compact, cost-effective solution for future high-speed fronthaul/backhaul networks. Full article

This paper proposes Non-Uniform Adaptive Acquisition (NUAA), a signal-feature-matched non-uniform adaptive photonic sampling framework that recovers broadband radio-frequency (RF) waveforms from highly sparse programmable non-uniform photonic sampling points. A 200 MHz mode-locked laser together with five electrical optical delay lines (EDLs; motor-actuated optical delay units) arranges the non-uniform sampling instants. Benefiting from the joint design of the photodetector/track-and-hold amplifier (PD/THA) response model and programmable non-uniform optical pulse spacing, a low-bandwidth PD infers neighboring pulse amplitudes from their deterministic superposition at the readout. In numerical simulations of this physical forward operator, that construction corresponds to a 1 THz equivalent sampling rate on the 1 ps EDL grid, while the electrical front end operates at a 1 GHz average sampling rate (cascaded PD–THA analog 3 dB bandwidth $\approx 0.676$ GHz). Under severe blocking interference and low signal-to-noise ratio (SNR), the numerical simulations show that the strongest broadband chirplet result uses a scene prior with support locking: with the NUAA–MU (Mamba–Unfolding) reconstructor at 0.1% multi-coset sparsity, all $N_{\mathrm{trial}}=50$ Monte Carlo trials succeed within 200 ms (Wilson 95% CI $[93, 100]\%$; cumulative-best NMSE $-28.0$ dB), whereas the configuration without a scene prior is substantially weaker in the same window. A scene prior may come from known radar or communication waveform families, coarse occupancy reported by a companion sensor, or accumulation across related tasks. Full article

Light fidelity (LiFi) is progressively evolving as a highly promising communication technology because of its unique benefits, available spectrum, low implementation costs, and adaptive beamforming capabilities. Despite their advantages, existing LiFi networks remain constrained by limited data rates, coverage area, and information security in practical environments. Therefore, a high-speed, high-capacity, and secure quantum key distribution (QKD)-assisted integrated multi-wavelengths (450/532/620 nm) LiFi system using mode division multiplexing (MDM) is proposed. The results demonstrate that the proposed system achieves maximum transmission distances of 20.5–22 m and 19–22 m using different Laguerre–Gaussian (LG) and Hermite–Gaussian (HG) mode indices {[0,0], [0,10], [0,20], [0,30]}, at an aggregate data rate of 40 Gbps. Furthermore, the minimum acceptable transmitter angles of 30–90° for irradiance angles of 20–80° are required to maintain the target bit error rate (BER) of 10⁻⁹. The minimum photodetector detection areas required at transmission distances of 20–30 m are 1–2 cm² at the minimum BER limit. Moreover, the proposed system exhibits optimum performance, achieving an optical loss of −39.47 dB, −49.03 dBm received power, and 45.39 dB signal-to-noise ratio for 1–10 photons/pulse. Compared with existing studies, the proposed system demonstrates enhanced overall performance across various communication metrics. Full article

Optical Camera Communication (OCC) enables data reception using common CMOS cameras and commercial webcams. However, applying multi-level modulation with rolling-shutter sensors is constrained by temporal acquisition parameters that may be undocumented or not directly accessible, making it challenging since many existing solutions rely on specialized hardware or require high processing complexity. This paper demonstrates that reliable multi-level OCC can be achieved using only unmodified commercial hardware and straightforward signal processing by experimentally characterizing and validating a 4-level pulse width modulation (4-PWM) link. Data are encoded in the duty cycle of the transmitted signal and recoveblack from the width of the captublack rolling-shutter stripes. Two internal timing parameters are estimated directly from the captublack images without access to the internal camera timing: the row readout period (34.38 $\mathsf{\mu }$s), obtained from the spatial periodicity of the stripes, and the effective integration time (490 $\mathsf{\mu }$s), inferblack from the deformation of the received constellation with carrier frequency. A single-parameter model is derived to describe this deformation and is validated at two carrier frequencies differing by a factor of four, pblackicting constellation compression, a fixed point at a duty cycle of 0.5, and constellation collapse (followed by inversion) when the exposure-to-carrier-period ratio reaches 0.5. We evaluate system performance under different exposure settings, showing that automatic camera control strongly degrades multi-level detection (BER of 0.290, with mean image level variation constrained to $0.14\%$ compablack to $61\%$ under fixed exposure). Under optimal fixed-exposure operating conditions, a prospective 15 min transmission achieved zero bit errors over 35,878 bits at 40 bps, corresponding to a $95\%$ upper confidence bound on the BER of $8.4\times {10}^{-5}$. These results reveal a practical balance between cost, complexity, and performance, demonstrating that 4-PWM rolling-shutter OCC is a viable solution for Internet of Things (IoT) signaling and low-rate data transmission using commercially available devices. Full article

Early cancer detection can expand treatment options and improve patient survival, but it requires tests that can be repeated with minimal patient burden. Urine and saliva can be collected non-invasively and may contain cancer-associated nucleic acids, proteins, and extracellular vesicles. Clinical analysis of these body fluids is complicated by low biomarker abundance, inter-individual variation, and matrix components that interfere with surface-based sensing. Plasmonic nanoarray biosensors address some of these analytical constraints by concentrating local electromagnetic fields, supporting multiplexed optical readout, and accommodating surface chemistry and microfluidic handling. This review examines nanoarray architectures, fabrication methods, surface functionalization, and signal generation for cancer-associated biomarkers in urine and saliva. Localized surface plasmon resonance, surface-enhanced Raman scattering, and metal-enhanced fluorescence are discussed together with applications to bladder, prostate, pancreatic, oral, and head-and-neck cancers. Remaining barriers include biofouling, pre-analytical variation, fabrication reproducibility, limited validation using authentic biofluids, and incomplete sample-to-answer integration. Addressing these challenges through standardized biofluid processing, scalable nanoarray fabrication, and integrated microfluidic platforms will be essential for translating plasmonic nanoarray biosensors into clinically applicable cancer screening tools. Full article

Nominal launch-power profiles can lose quality-of-transmission (QoT) margin when span and equipment parameters vary. We study this effect using C-band GNPy 2.14.1 simulations that recompute amplified-spontaneous-emission (ASE) noise and Gaussian-noise (GN)-model nonlinear interference under perturbations. Ten runs use 384 training scenarios and 1024 intensified-stress scenarios with scalar and spectral multipliers of 1.25 and 1.50. In paired within-GNPy comparisons, a finite-sample 5% lower-tail-mean selector, defined as the mean of the 20 worst training utilities, improves fifth-percentile minimum-channel generalized signal-to-noise-ratio (GSNR) margin over nominal optimization by 0.247 dB, with a 95% confidence-interval half-width of 0.014 dB. After normalization to the nominal total launch power, the gain remains 0.179 dB (half-width 0.017 dB), suggesting that spectral shape is a major contributor to the paired difference in this comparison. The gain lies between 0.245 and 0.248 dB when the training-tail fraction varies from 1% to 10%; relaxing the per-channel ceiling from 3.0 to 3.5 dBm removes almost all active bounds while retaining a 0.246 dB gain. Selected profiles mainly raise the low-frequency edge, and the benefit appears near the modeled reach boundary rather than on high-margin metro links. Erbium-doped fiber amplifier noise figure, gain ripple, and reconfigurable optical add-drop multiplexer equalization lead the sensitivity ranking. Reduced Manakov checks preserve power ordering while exposing model offsets. The results describe the specified GNPy configuration, finite search, and synthetic perturbation laws; field-calibrated performance remains to be established. Full article

Compact mobile optical wireless communication (OWC) terminals are constrained not only by link budget but also by mobile-side size, weight, power consumption, and cost (SWaP-C). This paper proposes and models a remodulation-based bidirectional OWC transceiver module that integrates a fluorescent concentrator (FC) receiver and a modulating retroreflector (MRR) transmitter. The FC receives the downlink by absorbing a wavelength-dependent fraction of an interrogation beam, Stokes-shifting the absorbed light, and guiding the emission to an edge photodetector. The transmitted fraction of the same interrogation beam reaches the MRR and is remodulated for low-power uplink transmission without a mobile-side optical source. The central design variable is therefore not the optical power alone, but the pair consisting of the interrogation wavelength and the downlink modulation depth. A fully absorbed wavelength with high modulation depth is used for downlink-only operation, a pass-through wavelength with zero modulation depth is used for uplink-only operation, and an absorption-shoulder wavelength with intermediate modulation depth is used for simultaneous downlink and uplink remodulation. A spectral photon-transfer model, a direct-detection communication model, a self-interference model, and a weighted rate-optimization framework are developed. Simulation results show that the optimized wavelength shifts from the FC absorption peak in downlink-dominant operation to the FC pass-through window in uplink-dominant operation, while the optimal downlink modulation depth decreases to preserve uplink carrier margin. The proposed architecture is particularly well-suited for drones, robots, vehicles, and distributed sensors requiring robust optical downlink reception and low-SWaP-C uplink signaling. Full article

A high-stability actively mode-locked fiber laser (AMLFL) is proposed and experimentally demonstrated. This AMLFL is based on a distributed feedback laser diode (DFB-LD) injection locking with Fabry-Perot (F-P) etalon frequency stabilization. In this system, a wavelength modulation method is employed to generate the feedback signal for frequency stabilization. The stabilization mechanism utilizes the linear response characteristic of the first-order derivative of the F-P etalon transmission peak. This achieves wavelength stabilization of the DFB-LD. Subsequently, the stabilized light source is injected into the ring cavity of the AMLFL. The proposed system does not require modification to the existing AMLFL cavity. It also features a simple structure and low implementation cost. Experimental results show that, with frequency stabilization, the wavelength drift of a selected spectral line is reduced to within the 10 pm resolution of the OSA. Meanwhile, the standard deviations of the 5 GHz spectral component power fluctuation and the average output optical pulse power are 0.01 dB and 0.01 dB, respectively. Full article

Cardiovascular disease remains the leading cause of death among women, yet female cardiovascular risk continues to be underrecognized, and women remain underrepresented in many cardiovascular trials. Sex-related differences in hormonal exposure, immune regulation, vascular function, pregnancy-related conditions, and clinical presentation contribute to heterogeneity in cardiovascular disease across the life course. Statins reduce atherosclerotic cardiovascular events in women and men, with no consistent evidence of treatment-effect heterogeneity by sex. In addition to lowering low-density lipoprotein cholesterol, statins influence inflammatory signaling, endothelial nitric oxide bioavailability, oxidative stress, thrombosis, and plaque biology. These effects are biologically relevant to atherosclerosis; however, current clinical evidence does not establish that LDL-independent statin effects confer a uniquely greater benefit in women. Historical pathological studies suggested that plaque erosion may contribute relatively more often to acute coronary thrombosis in selected younger women, whereas contemporary optical coherence tomography studies show similar overall frequencies of plaque rupture and erosion between sexes and important age-related variation. Evidence for a female-specific effect of statins on post-myocardial infarction remodeling, cognition, or pharmacogenomic susceptibility is also insufficient. This narrative review distinguishes established clinical evidence from mechanistic plausibility and unresolved sex-specific hypotheses. It emphasizes equitable implementation of guideline-directed lipid-lowering therapy, careful evaluation of statin-associated symptoms, and the need for adequately powered studies reporting sex-stratified estimates and formal treatment-by-sex interactions. Full article

Frame-based RGB image sensors and event-based vision sensors provide complementary sensing capabilities for human-perceptual imaging and machine vision. RGB image sensors capture dense spatial, color, and texture information that is essential for human-viewable imaging, semantic recognition, and conventional image signal processing pipelines. In contrast, dynamic vision sensors (DVSs) and event vision sensors (EVSs) asynchronously detect local brightness changes and provide sparse temporal information with low latency, high temporal resolution, and reduced redundant data output. Because neither modality alone satisfies all requirements of emerging vision systems, hybrid event–frame sensing has become an important direction for compact, low-latency, and energy-efficient sensing. This review presents a sensor-oriented taxonomy of hybrid event–frame sensing architectures and systems, including dual-camera event–frame systems, optically aligned event–frame systems, pixel-level shared hybrid image sensors, stacked CIS–DVS hybrid image sensors, homogeneous-pixel sensing systems, and event-only reconstruction systems. We analyze key sensor specifications, including latency, spatial resolution, color fidelity, power consumption, and form factor, and discuss how these specifications guide sensor configuration and design. The review identifies stacked CIS–DVS sensors as one of the most balanced and competitive architectures because they can support compact integration, synchronized event–frame sensing, and on-chip processing. However, important challenges remain, including color fidelity, demosaicing, event-pixel ratio optimization, calibration, benchmarking, and edge-AI deployment. Finally, we emphasize that future hybrid event–frame sensing systems should be developed through sensor–algorithm–ISP–AI co-design. This review provides practical guidelines for developing next-generation hybrid event–frame sensing systems for both human-perceptual imaging and machine vision. Full article

Accurate and non-invasive monitoring of glucose levels remains a critical challenge in diabetes management, motivating the development of highly sensitive optical biosensors. In this work, a surface plasmon resonance-based biosensor operating in the Kretschmann configuration is proposed and numerically investigated for glucose detection. The sensor architecture consists of a BK7 prism/TiO₂/Ag/graphene multilayer, and the effect of incorporating a hexagonal boron nitride (h-BN) interlayer with varying thicknesses is systematically analyzed to enhance sensing performance. Electromagnetic simulations were performed using the finite-difference time-domain method in Lumerical FDTD Solutions at a wavelength of 633 nm. Key performance parameters, including angular sensitivity, full width at half maximum, detection accuracy, figure of merit, signal-to-noise ratio, and limit of detection, were evaluated for glucose concentrations corresponding to refractive indices ranging from 1.3282 to 1.3767 RIU. The conventional BK7/TiO₂/Ag/TiO₂/Graphene/Sensing Medium (SM) configuration achieved a sensitivity of 167.48 deg/RIU. By introducing an h-BN layer, significant performance enhancement was observed. The optimized structure with an 8 nm h-BN layer exhibited a maximum angular sensitivity of 205.35 deg/RIU, representing an improvement of approximately 22.6% over the reference design, while maintaining a low detection limit of 2.43 × 10⁻⁴ RIU. The results further reveal that h-BN thickness plays a crucial role in balancing sensitivity and resonance quality, where excessive thickness broadens the resonance curve and degrades detection accuracy. The proposed graphene-h-BN-assisted SPR platform demonstrates high potential for high-performance, non-invasive glucose monitoring and provides practical design guidelines for next-generation plasmonic biosensors. Full article

Shigella is a foodborne bacterial pathogen with a low infectious dose and significant public health impact. Culture-based and molecular techniques provide reliable identification but are time-consuming. Nanoparticle-based biosensors offer sensitive, selective, and compact alternatives. Recent advances in nanoparticle-based biosensors for Shigella spp. (S. flexneri, S. sonnei, S. dysenteriae, and S. boydii) detection have been reviewed in terms of signal amplification, biorecognition, biological targets, sensor types, and performance in real food matrices. Detection strategies rely on gene-level and whole-cell recognition. Targeting virulence genes, invasion plasmid antigen H (ipaH), provides stable genus-level identification, whereas whole-cell recognition facilitates rapid detection without extensive sample preparation. Optical biosensors, including fluorescence-based methods, surface-enhanced Raman spectroscopy (SERS), and localized surface plasmon resonance (LSPR), achieve low detection limits with strong tolerance to complex food matrices. Electrochemical biosensors offer operational simplicity, portability, and suitability for food screening. Lateral flow and hybrid systems provide rapid detection through simplified assay formats and visual readout, with performance influenced by the balance between speed and sensitivity. Validation in real food matrices shows acceptable recoveries, minimal cross-reactivity, and agreement with reference methods. This overview provides a design-oriented framework for nanoparticle-based biosensor selection in food safety by integrating nanomaterial function, biosensor design, and performance characteristics. Full article

Remote sensing image super-resolution (SR) aims to enhance spatial resolution and recover image details, which typically enhances the quality of optical remote sensing imagery. However, interference from cloud haze cover and sensor noise often leads to distorted details and artifacts in reconstructed images of conventional deep learning SR approaches, significantly limiting reconstruction fidelity. To address these challenges, we propose a novel SR framework based on the flow matching paradigm and a diffusion transformer, named FlowT-SR, which achieves superior and reliable reconstruction quality by jointly mitigating sensor noise and thin cloud interference. First, an evolution path from low-resolution images to ground-truth images is constructed based on the optimal transport displacement interpolation mechanism, and the corresponding vector field that governs this evolution is employed as the supervision signal for subsequent model training. Then, a multi-scale interference suppression (MSIS) module is combined with a novel diffusion transformer network (DiTNet) to predict the vector field. The MSIS module performs preliminary denoising and captures the spatial distribution of thin cloud and haze in low-resolution images, providing degradation-aware feature representations for DiTNet. Subsequently, a DiTNet is presented to predict the evolution vector field obtained in the first stage, which consists of ten layers based on the diffusion transformer. By accurately predicting the vector field at any time step, the model effectively reduces the impact of cloud haze and noise interference to improve the reconstruction precision. Finally, driven by the predicted vector field along the evolution path, the SR remote sensing image is generated through solving the corresponding ordinary differential equation, yielding cloud-free and noise-reduced results. Extensive experiments on our dataset and the public CUHK Cloud Removal dataset demonstrate that FlowT-SR effectively suppresses cloud haze and noise interference, achieving superior reconstruction performance compared with current state-of-the-art methods in terms of both PSNR and SSIM. Full article