Search Results (142)

Background/Objectives: Insect oils have gained attention as sustainable cosmetic ingredients due to their bioactive lipid content. This study aimed to characterize oils from cricket and to evaluate their safety, biological activities, and performance in sunscreen formulations. Methods: Oils were extracted from Gryllus bimaculatus, Teleogryllus mitratus, and Acheta domesticus by cold pressing following hot-air drying. Fatty acid composition was determined using gas chromatography–mass spectrometry. Safety was assessed by cytotoxicity testing in normal human dermal fibroblasts (NHDF) and the hen’s egg chorioallantoic membrane (HET-CAM) assay. Antioxidant and anti-inflammatory activities were evaluated by intracellular reactive oxygen species (ROS) and nitric oxide (NO^•) assays. Based on biological performance, T. mitratus oil (TMO) was incorporated into sunscreen creams containing physical and chemical ultraviolet (UV) filters. Physical stability, viscosity, pH, sun protection factor (SPF), persistent pigment darkening/ultraviolet A protection factor (PPD/UVA-PF), and blue light protection were evaluated. Results: All cricket oils were non-cytotoxic to NHDF cells and were classified as non-irritating in the HET-CAM assay. TMO exhibited the strongest antioxidant activity, reducing intracellular ROS and significantly inhibiting NO^• production in lipopolysaccharide-stimulated cells. Only TMO showed measurable UVA protection (PPD/UVA-PF = 12.1, PA+++). Sunscreen creams formulated with TMO achieved higher photoprotective efficacy than olive oil-based creams, with SPF values up to 40.51 and PPD/UVA-PF up to 39.17. The inclusion of foundation pigments further increased SPF to 43.09 and enhanced blue light protection to 35.1%. Conclusions: TMO is a safe and effective multifunctional ingredient that enhances sunscreen performance and supports sustainable cosmetic formulation. Full article

Lensless on-chip microscopy enables high-throughput, wide-FOV imaging; however, the Bayer color filter array (CFA) in standard color sensors spatially multiplexes spectral channels, introducing sub-sampling and spectral crosstalk that degrade phase retrieval. We propose a Wirtinger Poly-Gradient Solver (WPGS) for quantitative phase reconstruction with Bayer-filtered color sensors under sequential Red–Green–Blue Light-Emitting Diode (RGB-LED) illumination. The method combines Transport of Intensity Equation (TIE)-based initialization with polychromatic Wirtinger optimization to suppress CFA-induced artifacts and enable pixel super-resolution (PSR). Experiments resolve a $2.76 \mu \mathrm{m}$ linewidth using a $1.85 \mu \mathrm{m}$ pixel-pitch sensor, exceeding the nominal Nyquist limit imposed by pixel sampling. We further demonstrate label-free imaging of HeLa cells and unstained tissue sections, supporting high-throughput digital pathology and offering potential for longitudinal biological observation. Full article

This paper investigates a novel optical method that uses a high-responsivity a-Si:H photodiode for label-free detection of luminescence from HeLa cervical cancer cells excited by a blue LED. We examine the energy distribution of the energy-gap density of states (DOS) from the photodiode’s long-time transient current, which shows exponential decay kinetics in the HeLa cell reaction. We analysed the transient response of a-Si:H p-i-n photodiode upon the illumination of the analyte with a pulsed blue LED light to better understand the HeLa cells activity and the fundamental defect kinetics processes in the a-Si:H material. Results suggest that the characteristic very low-level, time-varying light response of HeLa cells is due to chemiluminescence within cells, resulting from the reaction between nitric oxide (NO) and hydrogen peroxide (H₂O₂). Given the low signal intensity and noise, we applied a Savitzky–Golay (SG) filter to post-process the data. By reducing noise without attenuating chemiluminescent peaks, the Savitzky–Golay filter enabled accurate, reproducible quantification of the photocurrent response, reflecting the kinetics of cellular reactions. Further studies and more precise measurement instruments are needed for this real-time, label-free, non-destructive method, which applies SG-filtered signal processing to microfluidic optical biosensors. Full article

We present a Genetic Algorithm (GA)-based inverse design framework for creating a single-layer, fabrication-compatible dielectric nano-patterned surface that enables efficient color routing in both transmissive and reflective optical systems. Unlike traditional multilayer or absorption-based color filters, the proposed structure employs a fabrication-compatible architecture that spatially routes red, green, and blue light into designated output channels, significantly enhancing light utilization and color fidelity. The design process integrates a GA with full-wave finite-difference time-domain (FDTD) simulations to optimize the structural pillar height distribution, using a figure of merit that simultaneously maximizes optical efficiency and minimizes spectral crosstalk. For CMOS image sensor-scale designs, the nano-patterned surface achieved peak optical efficiencies of 76%, 72%, and 78% for blue, green, and red channels, respectively, with an average efficiency of 75.5%. Parametric studies further revealed the dependence of performance on pillar geometry, refractive index, and unit cell scaling, providing practical design insights for scalable fabrication using nanoimprint or grayscale lithography. Extending the approach to reflective displays, we demonstrate tunable-mirror-based architectures that emulate electrophoretic microcapsules, achieving efficient color reflection and an expanded color gamut beyond the sRGB standard. This single-layer, inverse-designed nano-patterned surface offers a high-performance and fabrication-ready solution for compact, energy-efficient imaging and display technologies. Full article

Display-driven optical stimuli underpin a major class of clinically validated digital therapeutics (DTx) now expanding from neuropsychiatric disorders to chronic diseases. The display’s optical characteristics—spectral power distribution, luminance, contrast, and temporal modulation—therefore define the delivered dose of these software-based interventions. In this context, blue-rich emission in the 450–480 nm band, particularly with evening exposure, can suppress melatonin via melanopsin-mediated intrinsically photo-sensitive retinal ganglion cell (ipRGC) pathways and perturb circadian timing, potentially attenuating therapeutic efficacy. This review summarizes clinical evidence for display-enabled DTx across major indications and synthesizes mechanistic and experimental data linking blue light to sleep and circadian disruption, with downstream mood, cognitive, cardiovascular, and metabolic effects, as well as increased risk of cancer and skin damage. This review distinguishes wavelength-dependent hazards by separating retinal photochemical risk in the roughly 415–450 nm range from circadian-disruptive melanopic effects in the 450–480 nm range, informing spectrum optimization for therapeutic use. It then synthesizes mitigation strategies spanning display emitter spectrum engineering, optical filtering or conversion films, and software controls such as color temperature tuning, high-frequency dimming, metameric spectrum design, and personalized circadian lighting. The review concludes with design, prescription, and standards considerations to align display output with therapeutic intent. Full article

Advanced glycation end products (AGEs) are important biomarkers associated with diabetes and metabolic disorders; yet existing detection methods are invasive and unsuitable for frequent monitoring. This study aimed to develop a non-invasive and portable AGEs detection device, optimize strategies for mitigating pigmentation-related interference, and evaluate its feasibility for metabolic assessment. The proposed system employs a 365 nm ultraviolet LED excitation source, an optical filter assembly integrated into an ergonomic dark chamber, and an eyelid-signal-based algorithm to suppress ambient light and skin pigmentation interference. Simulation experiments were conducted to evaluate the influence of different pigment colors and skin tones on fluorescence measurements. A clinical study was performed in 200 participants, among whom 42 underwent concurrent serum AGEs measurement as the reference standard. Predictive models combining corneal fluorescence signals and body mass index (BMI) were constructed and evaluated. The results indicated that purple and blue pigments introduced greater interference, whereas green and pink pigments had minimal effects. Device-derived AGEs estimates demonstrated good agreement with serum AGEs, with a mean error below 8%. A hybrid model incorporating BMI achieved improved predictive accuracy compared with single-parameter models. Participants with high-AGE dietary habits exhibited elevated fluorescence signals and BMI. These findings suggest that the proposed device enables stable and accurate non-invasive AGEs assessment, with potential utility for metabolic monitoring. Incorporating lifestyle-related parameters may further enhance predictive performance and expand clinical applicability. Full article

Background: Lutein and zeaxanthin (LZ) are macular xanthophyll carotenoids with antioxidant and blue-light filtering properties, but their oral bioavailability is limited. Lipid-based delivery systems may enhance absorption. Methods: We compared four single-dose LZ delivery systems in male Sprague–Dawley rats: (G1) LZ in medium-chain triglyceride (MCT) oil; (G2) LZ in MCT + phosphatidylcholine (PC); (G3) LZ in MCT + phosphatidylserine (PS); (G4) LZ in liposomal powder. Following an overnight fast, each group (n = 6) received an oral gavage of the assigned formulation. Serial blood samples were collected up to 24 h post-dose. Plasma lutein + zeaxanthin concentrations were quantified by a validated LC–MS/MS method. Non-compartmental pharmacokinetic (PK) parameters were computed (Phoenix WinNonlin^®), and one-way ANOVA was used to make inter-group comparisons on ln-transformed metrics with Dunnett’s post hoc tests. Results: The PS-complexed formulation (G3) yielded the highest LZ exposure (mean C_max 69.63 ± 0.78 ng/mL; AUC_0-t 620.23 ± 16.41 ng·h/mL), significantly exceeding the MCT oil control (G1: 52.54 ± 0.70 ng/mL; 494.51 ± 13.70 ng·h/mL; p < 0.001). The PC-enriched oil (G2) and liposomal powder (G4) also produced higher C_max and AUC than G1 (p < 0.01). No differences in elimination half-life (t1/2 ≈ eight h) were observed between formulations. Conclusions: Phospholipids, especially PS, substantially improved the systemic availability of lutein and zeaxanthin compared with MCT oil alone. PS-based lipid complexes appear particularly effective, supporting their use in ocular-health formulations to maximise xanthophyll bioavailability. Full article

Recent studies have highlighted the key role of lighting in regulating circadian rhythms and its impact on human health. Exposure to blue light, especially at specific times of day, is now quantified using the melanopic Equivalent Daylight Illuminance (m-EDI) parameter, defined in the CIE S 026 standard. This parameter is proportional to the integral, in the visible range, of the spectral power distribution and the melanopic sensitivity function, which peaks near 490 nm, and is similar to a Gaussian distribution. Low-cost spectrometric sensors using photodiode arrays and narrowband filters offer a cost-effective way to estimate m-EDI through a weighted sum of channel responses. However, due to inherent sensor variability, individual calibration is recommended. The standard approach involves multiple linear regression to fit the sensor’s output to reference values using a set of test light sources. This method is easy to implement but depends heavily on the selection of calibration illuminants, which must outnumber the channels. This paper analyzes the sensitivity of this method to the sensor’s spectral response and the choice of calibration sources. A revised calibration approach is proposed, selectively discarding channels to reduce deviations from the target response. Applied to several sensors, this method significantly improves calibration accuracy and robustness, reducing the RMS error for several test LEDs from 17.6 to 1.36 lux. Full article

The total antioxidant capacity (TAC) of food products is a key parameter for assessing food quality and safety. In this work, iron-doped carbon dots (Fe-CDs) were successfully prepared using waste coffee grounds as a precursor with a satisfactory fluorescence quantum yield of 9.6%. The Fe-CDs exhibited exceptional peroxidase-like activity, which can oxidize colorless 3,3′,5,5′-tetramethylbenzidine (TMB) to form blue oxTMB. Concurrently, oxTMB induced an inner filter effect, quenching the fluorescence of Fe-CDs. After being added to antioxidants such as glutathione, ascorbic acid, and L-cysteine, the generated reactive oxygen species (ROS) are consumed, thereby preventing the oxidation of TMB. The color of the mixed solution changed from dark to light blue, accompanied by the fluorescence recovery of Fe-CDs. Nevertheless, these three antioxidants possessed remarkable differences in ROS elimination capability, which resulted in different signal responses in absorption and fluorescence, and were successfully used for constructing the colorimetric/fluorescent dual-channel sensor array. Furthermore, the sensor array signals were processed using principal component analysis to achieve simultaneous detection of glutathione, ascorbic acid, and L-cysteine, and were able to effectively discriminate between mixtures and individual antioxidants. The constructed sensor array was successfully applied for the TAC detection in various foods (including vegetables, fruit, and beverages) and for the precise differentiation of antioxidants in milk samples. Overall, the prepared sensor array exhibited outstanding potential in detecting food quality. Full article

There has been an increasing demand for high-resolution image sensing technologies in recent years due to their diverse and advanced optical applications. With recent advances in nanofabrication technologies, this can be achieved through the realization of high-density pixels. However, the development of high-density and miniaturized pixels introduces challenges to the conventional color filters, which generally transmit and absorb different spectral components of light. A significant portion of the incident light is inherently lost using conventional color filters. Moreover, as the pixel size is shrunk, optical losses appear to be substantial. To address these fundamental limitations, a novel nanophotonic optical router is proposed in this work. Our router utilizes a single-layer, all-dielectric metasurface as a spectral router. The metasurface is designed through an inverse design approach that exploits adjoint sensitivity analysis. A novel figure of merit is developed and incorporated in the inverse design process, enabling the metasurface design to effectively sort and route the incoming light into four targeted channels, each corresponding to a distinct spectral component—red, green, blue, and near-infrared. We demonstrate that the proposed quad-spectral metasurface router, having a compact footprint of $2 \mathsf{\mu }\mathrm{m}\times 2 \mathsf{\mu }\mathrm{m}$, achieves an average optical efficiency of approximately 39% across the broad spectral range, i.e., 400–850 nm, with each spectral channel exceeding an efficiency of 25%. This surpasses the maximum efficiency attainable by the conventional four-channel color filters. Our proposed quad-spectral metasurface router offers a wide range of applications in low-light imaging, image fusion, computational photography, and computer vision. In addition, this work highlights the applicability of an adjoint-based inverse design approach to accelerate the development of compact, efficient, and high-performance nanophotonic devices for the next generation of imaging and sensing systems. Full article

Understanding the mechanisms that assemble diverse forest communities is a central goal in ecology. Phylogenetic analyses based on DNA barcodes have advanced this field, but their use of sequences evolving at constant rates may not capture adaptations to specific environmental drivers. Light is a critical factor shaping forest structure, particularly in the vertical dimension. This study introduces a novel phylogenetic approach using the blue-light receptor gene, cryptochrome (Cry), which is directly involved in plant light perception and adaptation. We reconstructed a Cry-based phylogeny for 96 tree species in a 20 ha subtropical forest dynamics plot and analyzed community structure using the net relatedness index (NRI) and nearest taxon index (NTI) across horizontal habitats, successional stages, and vertical canopy layers. Compared to traditional DNA barcoding, the Cry phylogeny revealed distinct patterns, showing consistent phylogenetic structure across different habitats—a finding indicative of convergent evolution in light-sensing systems. Furthermore, the Cry-based analysis demonstrated a stronger and more consistent signal in the forest’s vertical structure, with significant phylogenetic clustering in upper canopy layers, directly linking light adaptation to community stratification. Over time, both NRI and NTI values increased, suggesting succession leads to greater phylogenetic overdispersion and highlighting an increased role for environmental filtering among closely related taxa. Our results validate Cry as a powerful functional gene marker for phylogenetics, providing unique insights into how light environment filters species and shapes the vertical assembly of forest communities. Full article

Ophthalmic lens coatings are increasingly designed to combine optical, mechanical, and biological functions. This systematic review, registered in PROSPERO and conducted according to PRISMA 2020 guidelines, synthesized 54 experimental, preclinical, and clinical studies on coatings for spectacle lenses, contact lenses, and intraocular lenses. Spectacle lens studies consistently showed that anti-reflective and blue-light filtering coatings reduce glare perception, improve contrast sensitivity, and provide UV protection, while laboratory tests demonstrated significant reductions in impact resistance, with fracture energy of CR-39 lenses decreasing by up to 63% when coated. Contact lens research revealed that plasma and polymeric coatings reduce water contact angles from >100° to <20°, enhancing wettability, while antimicrobial strategies such as melamine binding or nanoparticle-based films achieved >80% reductions in bacterial adhesion. Drug-eluting approaches sustained antibiotic or antioxidant release for periods ranging from 24 h to 6 days, with improved ocular bioavailability compared with drops. Intraocular lens studies demonstrated that heparin surface modifications reduced postoperative flare and anterior chamber cells, and phosphorylcholine or alkylphosphocholine coatings suppressed lens epithelial cell proliferation. Drug-loaded coatings with methotrexate, gefitinib, or amikacin significantly inhibited posterior capsule opacification and infection in ex vivo and animal models. Collectively, coatings improve visual comfort, photoprotection, wettability, and biocompatibility, but clinical translation requires solutions to mechanical trade-offs, long-term stability, and regulatory challenges. Full article

Background and Objectives: To clinically validate a semi-automatic measurement of Tear Meniscus Central Area (TMCA) to differentiate between Non-Aqueous Deficient Dry Eye (Non-ADDE) and Aqueous Deficient Dry Eye (ADDE) patients. Materials and Methods: 120 volunteer participants were included in the study. Following TFOS DEWS II diagnostic criteria, a battery of tests was conducted for dry eye diagnosis: Ocular Surface Disease Index questionnaire, tear film osmolarity, tear film break-up time, and corneal staining. Additionally, lower tear meniscus videos were captured with Tearscope illumination and, separately, with fluorescein using slit-lamp blue light and a yellow filter. Tear meniscus height was measured from Tearscope videos to differentiate Non-ADDE from ADDE participants, while TMCA was obtained from fluorescein videos. Both parameters were analyzed using the open-source software NIH ImageJ. Results: Receiver Operating Characteristics analysis showed that semi-automatic TMCA evaluation had significant diagnostic capability to differentiate between Non-ADDE and ADDE participants, with an optimal cut-off value to differentiate between the two groups of 54.62 mm² (Area Under the Curve = 0.714 ± 0.051, p < 0.001; specificity: 71.7%; sensitivity: 68.9%). Conclusions: The semi-automatic TMCA evaluation showed preliminary valuable results as a diagnostic tool for distinguishing between ADDE and Non-ADDE individuals. Full article

Image-assisted digital shade guides are increasingly popular for shade matching; however, research on their accuracy remains limited. This study aimed to compare the accuracy and reliability of color coordination in image-assisted digital shade guides constructed using calibrated images of their shade tabs captured by a mirrorless camera (Canon, Tokyo, Japan) (MC-DSG) and a smartphone camera (Samsung, Seoul, Korea) (SC-DSG), using a spectrophotometer as the reference standard. Twenty-nine VITA Linearguide 3D-Master shade tabs were photographed under controlled settings with both cameras equipped with cross-polarizing filters. Images were calibrated using Adobe Photoshop (Adobe Inc., San Jose, CA, USA). The L* (lightness), a* (red-green chromaticity), and b* (yellow-blue chromaticity) values, which represent the color attributes in the CIELAB color space, were computed at the middle third of each shade tab using Adobe Photoshop. Specifically, L* indicates the brightness of a color (ranging from black [0] to white [100]), a* denotes the position between red (+a*) and green (–a*), and b* represents the position between yellow (+b*) and blue (–b*). These values were used to quantify tooth shade and compare them to reference measurements obtained from a spectrophotometer (VITA Easyshade V, VITA Zahnfabrik, Bad Säckingen, Germany). Mean color differences (∆E₀₀) between MC-DSG and SC-DSG, relative to the spectrophotometer, were compared using a independent t-test. The ∆E₀₀ values were also evaluated against perceptibility (PT = 0.8) and acceptability (AT = 1.8) thresholds. Reliability was evaluated using intraclass correlation coefficients (ICC), and group differences were analyzed via one-way ANOVA and Bonferroni post hoc tests (α = 0.05). SC-DSG showed significantly lower ΔE₀₀ deviations than MC-DSG (p < 0.001), falling within acceptable clinical AT. The L* values from MC-DSG were significantly higher than SC-DSG (p = 0.024). All methods showed excellent reliability (ICC > 0.9). The findings support the potential of smartphone image-assisted digital shade guides for accurate and reliable tooth shade assessment. Full article

This study examines the influence of light wavelengths on the growth dynamics of five algal genera (Chlorella sp., Volvox sp., Gloeocapsa sp., Microspora sp., and Mougeotia sp.) in freshwater systems, using machine learning to optimize growth models. Natural light yielded the highest algal proliferation, increasing the total count from 90 to 1390 cells/mL in 30 days. Filtered wavelengths showed that blue light most effective (840 cells/mL), followed by red (490 cells/mL) and yellow (200 cells/mL), while green light minimally impacted growth (160 cells/mL). Genera-specific responses revealed that Gloeocapsa sp. and Mougeotia sp. thrived the most under blue light (240 and 750 cells/mL, respectively), with red and blue wavelengths generally enhancing growth across genera. Machine learning models achieved high accuracy (R² > 0.96 for total growth and R² > 0.8 for genera-specific and wavelength-based models), refining growth kinetics. These results suggest that spectral manipulation limiting blue/red wavelengths in water treatment to curb blooms while leveraging natural light for biofuel cultivation could optimize algal management. The integration of empirical data with machine learning offers a robust framework for predictive modeling in algal research and industrial applications. Full article