Journal of Biophotonics最新文献

Neurological disorders such as Parkinson's disease (PD) often adversely affect the vascular system, leading to alterations in blood flow patterns. Functional near-infrared spectroscopy (fNIRS) is used to monitor hemodynamic changes via signal measurement. This study investigated the potential of using resting-state fNIRS data through a convolutional neural network (CNN) to evaluate PD with orthostatic hypotension. The CNN demonstrated significant efficacy in analyzing fNIRS data, and it outperformed the other machine learning methods. The results indicate that judicious input data selection can enhance accuracy by over 85%, while including the correlation matrix as an input further improves the accuracy to more than 90%. This study underscores the promising role of CNN-based fNIRS data analysis in the diagnosis and management of the PD. This approach enhances diagnostic accuracy, particularly in resting-state conditions, and can reduce the discomfort and risks associated with current diagnostic methods, such as the head-up tilt test.

Non-invasive screening for bladder cancer is crucial for treatment and postoperative follow-up. This study combines digital microfluidics (DMF) technology with fluorescence lifetime imaging microscopy (FLIM) for urine analysis and introduces a novel non-invasive bladder cancer screening technique. Initially, the DMF was utilized to perform preliminary screening and enrichment of urine exfoliated cells from 54 participants, followed by cell staining and FLIM analysis to assess the viscosity of the intracellular microenvironment. Subsequently, a deep learning residual convolutional neural network was employed to automatically classify FLIM images, achieving a three-class prediction of high-risk (malignant), low-risk (benign), and minimal risk (normal) categories. The results demonstrated a high consistency with pathological diagnosis, with an accuracy of 91% and a precision of 93%. Notably, the method is sensitive for both high-grade and low-grade bladder cancer cases. This highly accurate non-invasive screening method presents a promising approach for bladder cancer screening with significant clinical application potential.

The skin surface lipids (SSLs) film, composed of sebum and keratinocyte membrane lipids, is crucial to the barrier function of the stratum corneum (SC). The first part of this study investigated the impact of solar radiation on the SC based on a novel hydration and dehydration approach using Raman spectroscopy. The SSLs were found to absorb solar light, and thus participate to the protection of the skin surface. However, the protective function of the SSLs may be limited and is dependent to the heterogenous distribution of SSLs over the body surface. To ensure comprehensive protection, synergistic measures such as the application of solar filters are necessary. In this second part of the study, we have evaluated the limits of the protection capacity of SSLs and explored the protective action of a solar filters on both SSLs composition and the water hydration and dehydration kinetics in the SC.

Second-harmonic generation (SHG) microscopy provides a high-resolution label-free approach for noninvasively detecting collagen organization and its pathological alterations. Up to date, several imaging analysis algorithms for extracting collagen morphological features from SHG images—such as fiber size and length, order and anisotropy—have been developed. However, the dependence of extracted features on experimental setting represents a significant obstacle for translating the methodology in the clinical practice. We tackled this problem by acquiring SHG images of the same kind of collagenous sample in various laboratories using different experimental setups and imaging conditions. The acquired images were analyzed by commonly used algorithms, such as gray-level co-occurrence matrix or curvelet transform; the extracted morphological features were compared, finding that they strongly depend on some experimental parameters, whereas they are almost independent from others. We conclude with useful suggestions for comparing results obtained in different labs using different experimental setups and conditions.

Optical-resolution photoacoustic microscopy (OR-PAM) has been increasingly utilized for in vivo imaging of biological tissues, offering structural, functional, and molecular information. In OR-PAM, it is often necessary to make a trade-off between imaging depth, lateral resolution, field of view, and imaging speed. To improve the lateral resolution without sacrificing other performance metrics, we developed a virtual-point-based deconvolution algorithm for OR-PAM (VP-PAM). VP-PAM has achieved a resolution improvement ranging from 43% to 62.5% on a single-line target. In addition, it has outperformed Richardson-Lucy deconvolution with 15 iterations in both structural similarity index and peak signal-to-noise ratio on an OR-PAM image of mouse brain vasculature. When applied to an in vivo glass frog image obtained by a deep-penetrating OR-PAM system with compromised lateral resolution, VP-PAM yielded enhanced resolution and contrast with better-resolved microvessels.

As all major dietary carotenoids are contained in blood, it is a suitable substrate to evaluate their content, in vivo. Following 18-month supplementation of open-angle glaucoma patients with macula-pigment carotenoids (Lutein, Zeaxanthin and Meso-Zeaxanthin) in the European Nutrition in Glaucoma Management trial, Raman spectroscopic analysis of the carotenoid content of pre- and post-supplementation participant blood serum was carried out, to investigate the systemic impact of the supplementation regimen and explore a more direct way of quantifying this impact using routine blood tests. Using a 532 nm laser source for optimal response, a consistent increase in serum carotenoid concentration was observed in the supplemented serum, highest in patients with initial high baseline carotenoid content. A shift in the 1519 cm⁻¹ carotenoid peak also revealed differences in the carotenoid structural profile of the two groups. The findings highlight the potential of Raman spectroscopy toquantify and differentiate carotenoids directly in blood serum.

Cutaneous melanoma is the most lethal skin cancer and noninvasively distinguishing it from benign tumor is a major challenge. Raman spectroscopic measurements were conducted on 65 suspected melanocytic lesions and surrounding healthy skin from 47 patients. Compared to the spectra of healthy skin, spectra of melanocytic lesions exhibited lower intensities in carotenoid bands and higher intensities in lipid and melanin bands, suggesting similar variations in the content of these components. Distinct variations were observed among the autofluorescence intensities of healthy skin, benign nevi and malignant melanoma. By incorporating autofluorescence information, the classification accuracy of the support vector machine for spectra of healthy skin, nevi, and melanoma reached 90.2%, surpassing the 87.9% accuracy achieved without autofluorescence, with this difference being statistically significant. These findings indicate the diagnostic value of autofluorescence intensity, which reflect differences in fluorophore content, chemical composition, and structure among healthy skin, nevi, and melanoma.

Photobiomodulation (PBM) using 460 nm blue light has been shown to have an inhibitory effect on skin cancer cells. In this study, we used a continuous LED light source with a wavelength of 460 nm and designed various combinations of power density (ranging from 6.4 to 25.6 mW) and dose (ranging from 0.96 to 30.72 J/cm²) to conduct treatment experiments on MeWo cells to investigate the effects of blue light on MeWo melanoma cells. We are focusing on cell viability, cytotoxicity, mitochondrial function, oxidative stress, and apoptosis. We found that blue light inhibits these melanoma cells through oxidative stress and DNA damage, and this inhibition intensifies at higher irradiance levels. Although the cells initially attempt to resist the stress induced by the treatment, they eventually undergo apoptosis over time. These findings contribute to understanding melanoma's molecular response to blue light PBM, lay the groundwork for future clinical applications.

The combination of polydioxanone (PDO) threads with other technologies has garnered significant interest for rejuvenation purposes. Photobiomodulation (PBM) has the potential to improve patient comfort and recovery after minimally invasive rejuvenation protocols and also contribute to the overall efficacy of these procedures, fostering an integrative approach to cutaneous rejuvenation. The objective os this work was to investigate concurrent application of PDO threads and red LED PBM on glabellar static wrinkles, in a parallel randomized sham-controlled trial. Forty individuals with Glogau aging classification levels 3 and 4, static glabellar wrinkles, and no significant comorbidities received PDO threads applied along glabellar line. Effective PBM group received 1.35 J and 630 nm red LED light punctually along threads, twice weekly for nine sessions over 30 days. The outcome measures were swelling assessment, dermal thickness and PDO thread degradation via linear ultrasound. No swelling was detected 24 h post-PDO thread application, hindering PBM effect assessment. PDO threads induced dermal thickening; no added effect with PBM. No significant difference in thread hydrolysis between groups, though some ultrasound records inconclusive on thread presence. The absence of swelling may stem from various factors, including the timing of post-procedure swelling assessment, operator proficiency in thread application, and procedural characteristics. No evidence supports the notion that PBM augments dermal thickening, however other light parameters should be studied. Insufficient data to demonstrate PBM's effectiveness in controlling post-procedure swelling. Combination of PBM with PDO thread application doesn't enhance dermal thickening, nor accelerate thread degradation at the parameters used here.

Image Photoplethysmography (IPPG) technology is a noncontact physiological parameter detection technology, which has been widely used in heart rate (HR) detection. However, traditional imaging devices still have issues such as narrower receiving spectral range and inferior motion detection performance. In this paper, we propose a HR detection method based on multi-spectral video. Our method combining multispectral imaging with IPPG technology provides more accurate physiological information. To realize real-time evaluation of HR directly from facial multispectral videos, we propose a new end-to-end neural network, namely IPPGResNet18. The IPPGResNet18 model was trained on the multispectral video dataset from which better results were achieved: MAE = 2.793, RMSE = 3.695, SD = 3.707, p = 0.304. The experimental results demonstrate a high accuracy of HR detection under motion state using this detection method. In respect of real-time monitoring of HR during movement, our method is obviously superior to the conventional technical solutions.