Search Results (14,113)

Optogenetic modulation employs light-sensitive proteins known as opsins to regulate cellular activity. A unique therapeutic application of this technique involves modulating pain perception by selectively targeting neural pathways within the spinal cord. Multi-Characteristic Opsin (MCO) represents an innovative optogenetic actuator capable of activation across a broad spectrum of light wavelengths, exhibiting a slow depolarizing phase that resembles natural photoreceptors. This study examines the current advancements in spinal optogenetic modulation utilizing MCO for pain management. Due to its high sensitivity, MCO facilitates minimally invasive, remotely controlled optogenetic modulation of spinal neurons. This approach enables the regulation of extensive spatial regions, provided the MCO channel receives sufficient light intensity to surpass the activation threshold. Nano-enhanced optical delivery (NOD) successfully transfected spinal neurons with the GAD67-MCO2-mCherry construct, as confirmed by membrane-localized mCherry fluorescence with DAPI-labeled nuclei. Using this platform, 5 Hz spinal optogenetic stimulation produced a significant reduction in formalin-evoked pain behaviors, demonstrating frequency-specific modulation of spinal pain circuits. Neither 2 Hz nor 10 Hz stimulation yielded comparable analgesic effects, underscoring the importance of precise stimulation parameters. The therapeutic impact also depended on transfection efficiency: reducing the fGNR–plasmid concentration diminished MCO expression and weakened the analgesic response. Together, these results show that effective spinal optogenetic pain modulation requires both optimal stimulation frequency and robust gene delivery. Full article

This study evaluated the effects of different light-emitting diode (LED) spectral qualities on the early growth of kale at the baby-leaf harvest stage in a plant factory with artificial lighting (PFAL) by integrating morphological traits, biomass accumulation, plant quality indices, vegetation indices, and chlorophyll a fluorescence. Two kale (Brassica oleracea L.) cultivars, ‘Jellujon’ and ‘Manchoo Collard’, were grown for four weeks under monochromatic red, green, and blue LEDs, a purple composite LED with far-red wavelengths, and three white LEDs with different correlated color temperatures (3000, 4100, and 6500 K). Blue LED increased shoot height by approximately 14–28%, depending on cultivar and comparison among the white LED treatments, but this elongation did not translate into superior biomass production. In contrast, white LEDs, particularly at 3000–4100 K, increased leaf area to 24.2–24.9 cm² and SPAD units to 47.3–50.2, whereas blue or green LEDs generally resulted in smaller leaves and lower SPAD units. Shoot dry weight under 3000–4100 K white LEDs reached 0.25–0.26 g in ‘Jellujon’ and 0.26–0.29 g in ‘Manchoo Collard’, approximately twofold higher than under blue or green LEDs. Compactness, Dickson quality index, root investment ratio, and leaf efficiency index were also more favorable under white LEDs, indicating improved plant sturdiness and structural stability. Green LED light was associated with lower maximum photochemical efficiency (Φ_Po) and greater energy dissipation (Φ_Do and DI_o/RC), whereas photochemical reflectance index and PI_ABS tended to be more favorable under selected white LED treatments, although these responses were partly cultivar- and treatment-dependent. Taken together, among the LED spectral quality treatments tested, 3000–4100 K white LEDs provided the most consistently favorable conditions for producing structurally robust, high-quality kale at the early growth stage in PFAL systems. The purple LED showed partial advantages in leaf development and selected physiological responses, but these effects were less consistent across cultivars and indices. Full article

Glyphosate is the most widely used herbicide worldwide, but many current detection methods rely on lab-based chromatography, requiring costly equipment and expert users. Here, we describe a low-cost, field-deployable fluorescence biosensing platform for glyphosate detection in water and soil. An engineered variant of the Escherichia coli periplasmic binding protein PhnD was optimized through strategic fluorophore placement to produce a robust fluorescence signal increase upon glyphosate binding. The biosensor was integrated into a self-contained, 3D-printed device that functions as a miniature fluorometer, providing a simple yes-or-no output for non-expert users while retaining access to raw fluorescence data. The device exhibits nanomolar fluorescence sensitivity with results comparable to a benchtop fluorometer. Using this platform, glyphosate was reliably detected in buffered solutions, commercial herbicides, tap water, and soil extracts. To mitigate false positives arising from phosphate interference, we developed a dual-sensor strategy incorporating an independent phosphate biosensor and a second-generation device capable of multi-wavelength fluorescence detection. Together, these results demonstrate an affordable and versatile biosensing platform with strong potential for field-based environmental monitoring. Full article

The physical characteristics of a heated non-Newtonian Eyring–Powell fluid in a conduit with sinusoidally moving ciliated walls are highlighted in this analytical study. The impact of mass transmission is considered in this model. The dimensional form of the governing equations is simplified using the long-wavelength estimation and suitable transformations to produce a set of dimensionless partial differential equations with pertinent boundary conditions. To solve it, the perturbation technique is utilized applying polynomial solutions. The solutions of temperature, concentrations, and velocity profiles are obtained, and then are further analyzed through graphical results. An accurate mathematical solution for the pressure gradient is achieved by integrating the velocity profile over the elliptic cross-section. The non-Newtonian Eyring–Powell fluid flows quicker through this vertical ciliated elliptic duct than the Newtonian fluid. Moreover, the cilia elliptic movement eccentricity and the wave number for metachronal wave have a dual effect on the velocity profile. Increasing the dimensionless flow rate and occlusion leads to an increase in closed contour size, as seen in the streamline description. Full article

Conventional multispectral photodetectors typically rely on multiple electrical terminals to discriminate different wavelengths, which inevitably increases structural complexity. Here, we break this paradigm by demonstrating a dual-color visible–infrared photodetector based on a simple two-terminal Au/MoS₂/Te heterostructure. The device operates through a bias-switching mechanism: reversing the voltage polarity selectively activates either the MoS₂/Au Schottky junction for visible-light detection (520 nm) or the Te/MoS₂ heterojunction for infrared detection (1550 nm). This bias-controlled wavelength selectivity is unambiguously verified by scanning photocurrent mapping. Beyond dual-color discrimination, an adaptive convolutional neural network is employed to decode the nonlinear current–voltage characteristics and enable precise spectral identification, achieving a reconstruction error of approximately 4.5%. Furthermore, high-fidelity dual-color imaging is demonstrated at room temperature. These results establish a hardware–algorithm co-design strategy based on a minimalist two-terminal architecture, providing a viable route toward compact and intelligent spectral-sensing systems. Full article

Grasslands globally are threatened by loss and degradation as shifting factors in climate and management put them at risk. These grassland ecosystems support local economies and are a center of biodiversity, which makes understanding the risks that affect them key to effectively protecting them. One major risk to grasslands is woody plant encroachment, and reliable management hinges on understanding its patterns. A major challenge of woody plant encroachment is detecting it at early stages (<20% cover). This study investigated the utility of a combination of environmental features and remotely sensed data for differentiating varying levels of woody plant encroachment in a montane Canadian grassland. The response of woody species to environmental factors including slope and available moisture varied by individual species. As in past studies, it was challenging to separate the early stages of encroachment using base spectral bands or NDVI, even with the use of higher-resolution satellite imagery. Bands in the yellow and red wavelength regions both showed promise for shrub detection, providing more between band separability and key modeling components. The spatial resolution and band combinations used here were able to model woody plant cover levels, helping to facilitate the implementation of effective management in combating woody plant encroachment. Full article

Red- and near-infrared (NIR)-emissive quantum dots (QDs) hold great promise in optoelectronic devices, sensors, and biomedicine owing to their advantages of low optical scattering, deep-tissue penetration, and compatibility with advanced photonic technologies. However, the toxicity of conventional cadmium (Cd)- and lead (Pb)-based QDs has led to growing demand for eco-friendly alternatives. Here, we provide a comprehensive review of sustainable classes of red/NIR-emissive QDs, including indium phosphide (InP), I-III-VI chalcogenides (CuInS₂, AgInSe, and so on), group-IV (Si, Ge, and SiGe) nanocrystals, and carbon-based QDs (graphene QDs or carbon dots). InP QDs are leading candidates for display technologies due to their high efficiencies and narrow bandwidths in emission properties, enabled by advanced core/shell engineering. In contrast, I-III-VI chalcogenides, group-IV, and carbon-based QDs offer advantages for biocompatible NIR bioimaging, photothermal therapy, and silicon photonics integration. We discuss synthesis strategies for achieving long-wavelength emission, the mechanisms of red/NIR photoluminescence (PL), and representative applications in displays, sensors, and bioimaging. Finally, we outline the remaining challenges, such as large-scale manufacturing and long-term stability, which should be addressed for commercial and clinical viability. Full article

In this paper, we propose a high-sensitivity fiber Bragg grating (FBG) pressure sensor based on an X-shaped mechanical transducer that converts external pressure into predominantly axial strain, thereby helping to alleviate bending-dominant spectral distortion and improve measurement stability. A theoretical model is developed to describe the relationship between applied force, pressure, and grating wavelength shift. Experimental optimization was conducted by varying Ethylene Propylene Diene Monomer (EPDM) thickness, bonding materials, and contact area to achieve sensitivities of 0.291 nm/N, 0.409 nm/N, and 0.462 nm/N, respectively, within the investigated force range of 0–10 N. For measuring the under water pressure, the sensor exhibits a high sensitivity of 0.596 nm/kPa within the investigated pressure range of 0–6 kPa. The results demonstrate the nice sensing performance with high sensitivity, good linearity, and excellent repeatability. This work provides an effective approach for high-performance FBG-based pressure sensing in underwater and harsh environments. Full article

Research into the spatial reshaping of monochromatic laser beams grew significantly in the late 1990s due to improvements in the fabrication of diffractive optical elements. Nowadays, some applications, such as optical coherence tomography, necessitate the use of broadband light beams with a spectral width of hundreds of nanometers. The difficulty in reshaping such spectrally broadened beams lies in the wavelength dependence of the beam shaping process. This paper presents a numerical study of the wavelength dependence of two beam shaping techniques that allow a Gaussian beam to be transformed into a flat-top or doughnut intensity profile in the focal plane of a focusing lens. The first technique is based on the diffraction of an incident Gaussian beam passing through a simple binary diffractive optical element. The second technique can be described as an interferometric method, as it involves the coaxial superposition of two Gaussian beams emerging from a Michelson interferometer. We compared the stability of these two techniques’ ability to reshape the beam versus the spectral bandwidth of the incident Gaussian beam. We showed that the interferometric method is more resilient than the diffractive method to changes in the spectral bandwidth of the Gaussian beam. We also considered the case of a quasi-monochromatic beam delivered by a widely tunable laser and reshaped using the interferometric method, where the dispersion of beam reshaping could be mitigated by two programmable liquid lenses that enable control of the curvature of the Michelson interferometer mirrors. Full article

Laser acupuncture (LA) integrates principles of traditional acupuncture with photobiomodulation (PBM) and has gained increasing attention as a non-invasive modality for pain management. PBM-based integrative LA in medicine refers to the application of low-level laser irradiation to acupuncture points, combining contemporary biomedical mechanisms with holistic, system-oriented therapeutic principles. This narrative review aimed to critically assess the scientific evidence on the efficacy of LA for pain management within the framework of the Principles of Clinical Integration of Photobiomodulation (PCIPBM) in LA, summarizing frequently used laser parameters and clinical indications. LA involves special protocols in standardized acupoints, using defined parameters of wavelength, irradiation, and energy density, consistent with PBM dosing principles. Therapeutic effects are mediated through point-specific neuromodulation and photobiological mechanisms, including modulation of peripheral and central nociceptive processing, reduction in pro-inflammatory mediators, improvement of microcirculation, and mitochondrial activation via cytochrome c oxidase-dependent adenosine triphosphate (ATP) synthesis. Clinical studies report statistically and clinically significant analgesic effects, particularly in chronic musculoskeletal pain, osteoarthritis, low back and neck pain, temporomandibular disorders, neuropathic pain, and selected postoperative pain conditions, when appropriate laser parameters are applied. Reported adverse effects are minimal, and tolerability is high. LA represents a safe, non-invasive therapeutic option and patient-friendly approach with clinically relevant efficacy in pain management. When applied according to PCIPBM, including evidence-based PBM parameters, it may serve as an effective adjunct or alternative to conventional pharmacologic and interventional approaches. Further standardization and high-quality randomized controlled trials are still required. Full article

To ensure high-quality and reliable service provision for customers, advanced optical networks without active elements have been developed to increase operating reliability, network scalability, and resource efficiency. To this end, wavelength division multiplexing-based passive optical networks (WDM-PON) now have a markedly enhanced role. An important aspect of the WDM-PON design is represented by traffic protection schemes, which play a key role in network reliability. Managing the power budget for optical links allows us to achieve a practically sustainable and realizable infrastructure of advanced passive optical networks. In this work, we focused on simulation model development for the power budget calculation for the WDM-PON optical link and the subsequent optical power budget evaluation of presumptive WDM-PON traffic protection schemes. Full article

The starch and moisture content of saffron corms are critical indicators of their flowering potential and yield. This study investigated the use of rapid, minimally invasive VNIR reflectance spectroscopy measurement to assess these parameters. The measurements were used to develop predictive models through four machine learning algorithms (PLSR, RF, SVR, and GPR). Spectral data were obtained from 130 fresh corm samples. Wavelength analysis identified key starch-sensitive intervals (~930–1000 nm and ~1150–1220 nm) and a broad moisture-sensitive region (~900–1350 nm). Among the evaluated models, the combination of the multiplicative scatter correction pre-processing method and Gaussian process regression (MSC-GPR) demonstrated the optimal predictive performance for water content (R² = 0.92, RMSE = 0.71%, RPD = 4.56, RPIQ = 5.37), and the combination of the MSC method and partial least squares regression (PLSR-MSC) demonstrated moderate performance for starch content (R² = 0.73, RMSE = 28.7 mg g⁻¹, RPD = 2.14, RPIQ = 2.81, dry weight). These results demonstrate the viability of VNIR spectroscopy as a minimally invasive tool for the pre-planting assessment of saffron corm quality under laboratory conditions. The method provides a laboratory-based framework for corm screening and selection, with potential for future adaptation to field settings using portable spectrometers following expanded calibrations and advanced modeling techniques. Full article

A Principal Component-Based Spectral Standardization (PCSS) method was developed to standardize hyperspectral radiance spectra onto a fixed wavelength grid. This enables the direct comparison of radiance or reflectance spectra across different spatial pixels of an imaging spectrometer or between different instruments. The method was validated using simulated Climate Absolute Radiance and Refractivity Observatory (CLARREO) Pathfinder (CPF) spectra. The PCSS approach demonstrated high accuracy: the average root-mean-square uncertainty across all CPF channels remained below 0.07%, with maximum individual-channel uncertainties under 1%. Compared to methods based on spectral interpolation, PCSS produced significantly lower biases with tighter error distributions, particularly in spectrally rich regions. Measured Hyper Spectral Imager for Climate Science (HySICS) balloon data provided further validation. PCSS successfully estimated wavelength shifts that closely matched measured data, even when utilizing approximated Jacobians, demonstrating the method’s robustness. Because it relies on a pre-computed lookup table for model parameters, PCSS bypasses the need for intensive radiative transfer calculations, making it highly computationally efficient. Beyond CPF, this method can easily be adapted for other hyperspectral sensors by substituting their respective wavelength grids and instrument line shape functions, offering a powerful tool to improve cross-calibration between different satellite sensors. Full article

The increasing prevalence of antimicrobial resistance, together with recurring infectious disease outbreaks, has intensified the need for alternative strategies to control microbial infections beyond conventional antibiotic therapies. Antimicrobial photodynamic therapy has emerged as a promising non-antibiotic approach in which light-activated photosensitising compounds generate reactive oxygen species that induce oxidative damage to microbial cells. Plant-derived photosensitisers have attracted increasing attention due to their structural diversity, biocompatibility, natural abundance, and potential for sustainability. Natural compounds such as curcumin, hypericin, chlorophyll derivatives, flavonoids, anthraquinones, and riboflavin exhibit favourable photochemical properties that enable efficient production of reactive oxygen species upon irradiation with visible light. Through radical- and singlet-oxygen-mediated photochemical pathways, these molecules exhibit broad-spectrum antimicrobial activity against bacteria, fungi, viruses, and biofilm-associated microorganisms. This review examines the photophysical properties and mechanisms of reactive oxygen species generation associated with plant-derived photosensitisers, together with key factors influencing their antimicrobial performance. Recent advances in nanocarrier-based delivery systems, dual-wavelength activation strategies, and synergistic combination therapies are also discussed for their potential to improve photostability, enhance reactive oxygen species generation, and increase microbial inactivation efficiency. Finally, current progress, challenges, and future research directions for advancing plant-derived photosensitisers in antimicrobial photodynamic therapy are discussed. Full article

Global freshwater resources face severe water quality degradation, with chlorophyll-a (Chl-a) concentration serving as a critical eutrophication indicator. While deep learning methods enable accurate Chl-a retrieval from remote sensing reflectance (Rrs) spectra, the scarcity of paired Rrs-Chl-a samples limits model generalization and causes overfitting, particularly in optically complex inland waters. To address this data bottleneck, we propose a physics-constrained latent diffusion model for synthesizing high-fidelity paired Rrs-Chl-a data to augment limited training sets for deep learning-based water quality retrieval. Our framework integrates three key innovations: (1) a lightweight variational autoencoder achieving 8.6:1 latent space compression, reducing computational overhead while preserving spectral features; (2) band-selective attention mechanisms targeting chlorophyll-sensitive wavelengths (440, 550, 680, and 700–750 nm) based on bio-optical principles; and (3) physics-guided conditional encoding that captures concentration-dependent spectral responses across oligotrophic to eutrophic regimes. Evaluated on the GLORIA dataset, our model demonstrates superior performance in spectral similarity (0.535), sample diversity (0.072), and distribution matching (Fréchet distance 0.0008) compared to conventional generative models. When applied to data augmentation, synthetic spectra improved downstream Chl-a retrieval from R²= 0.75 to 0.91, reducing RMSE by 39%. This physics-informed generative approach addresses data scarcity in aquatic remote sensing research, supporting global needs for enhanced understanding of inland and coastal water quality dynamics in data-limited regions. Full article