Journal of biophotonics最新文献

Rapid detection of infectious diseases like COVID-19, flu, and dengue is crucial for healthcare professionals preparing for contagious outbreaks. Given the constant mutations in viruses and the recurring emergence of threats like Nipah and Zika, there is an urgent demand for a technology capable of distinguishing between infections that share similar symptoms. In this paper, we utilize laser-based Raman scattered signals from a drop of dried blood plasma, combined with generative artificial intelligence, to provide a rapid and precise diagnosis. Our optimized model exhibits exceptional performance, yielding high predictive scores of 96%, 98%, and 100% for flu, COVID-19, and dengue, respectively. The proposed Raman spectroscopic analysis, with a rapid turnaround time, can ensure a near-accurate diagnosis and proper quarantining of highly infectious cases. Furthermore, the potential extension of our method to include other viral diseases offers an alternative to the challenge of developing different diagnostic kits for each disease.

While SERS-based detection can bring some advantages, it is far away from being established as a routine method in clinical diagnostics. In this study, a SERS-labeled immunochromatographic test paper was prepared. The rapid detection of SARS-CoV-2 was realized by the machine learning algorithm of the Raman probe; the whole testing process takes less than 25 min, and the rapid detection of SARS-CoV-2 can be realized. After experimental evaluation, the sensitivity of the test strip for SARS-CoV-2 N protein detection can be 1 pg/mL, which is 3 orders of magnitude higher than that of the colloidal gold antigen detection strip on the market. In the detection of clinical samples, nucleic acid detection was used as the gold standard, and the accuracy was 84.21%.

This study investigated the use of thermography as a non-invasive tool to monitor physiological responses to mechanical workload in Division-I female soccer players. A total of 29 student-athletes (age: 19.8 ± 1.1 years) participated, with thermographic imaging conducted throughout training across the competitive season. A total of 8106 observations were analyzed, revealing a weak but significant negative correlation between total player load (TPL) and changes in body region temperature (∆t) (βTPL = -0.00047; p < 0.0001). For every one unit increase in TPL, skin temperature decreased by 0.00047°C on average. Similar patterns were observed in high-minute players (βTPL = -0.0046; p < 0.0001) and when excluding goalkeepers (βTPL = -0.00027, p < 0.001). Interestingly, cooler temperatures were linked to higher workloads in field players, contrasting with previous research. These findings suggest thermography may reflect physiological responses to external workload, with position-specific demands requiring tailored metrics for accurate monitoring.

Accurate diagnosis is vital for treating primary central nervous system lymphoma (PCNSL) and determining patient prognosis in clinical practice. Currently, histological analysis stands as the gold standard for definitively diagnosing PCNSL, yet it is time-consuming and invasive. This study introduces multiphoton microscopy (MPM), utilizing second harmonic generation (SHG) and two-photon excited fluorescence (TPEF), to detect human PCNSL. Several diagnostic features of PCNSL, such as increased cellularity, angiocentric infiltration pattern, geographic necrosis, perivascular reticulin deposits, and apoptosis niche, are captured. Moreover, with image processing, the extent of necrosis and perivascular reticulin deposits can be automatically assessed. These research findings underscore the capability of MPM for PCNSL identification. With the advancements in multiphoton endoscopes, in vivo detection of PCNSL may be achievable.

This study explores using unsupervised deep learning to find a low-dimensional representation of infrared molecular fingerprints of human blood. We developed a fully convolutional denoising autoencoder to process Fourier transform infrared (FTIR) spectroscopy data, aiming to condense the spectra into a set of latent variables. By utilizing the autoencoder's bottleneck architecture and a custom loss function, we effectively reduced noise while retaining essential molecular information. This method improved lung cancer detection accuracy by 2.6 percentage points in a case-control study. The resulting latent space not only compacts spectral data, but also highlights variables linked to disease presence, offering potential for improving diagnostics. Trial Registration: German Clinical Trials Register (DRKS): DRKS00013217.

"PolSpec" is a flexible, cost-effective approach for rapid (including single-shot) spectrally resolved imaging. While established approaches, e.g., using cascades of dichroic beamsplitters, diffractive image splitters, or mosaic filters, typically have pre-determined spectral detection bands with cost and experimental complexity scaling with the number of spectral channels, PolSpec uses polarisation optics to provide continuously varying transmission across a configurable spectral range to generate "spectral modulation vectors" that can represent specific spectral signatures with lower data volumes than full spectral profiles. It can be implemented with almost any detector. Here we demonstrate low-cost single-shot widefield PolSpec-based hyperspectral imaging using a polarisation-resolving camera.

Immunophenotyping provides valuable prognostic and diagnostic information, but is technically complex and expensive. The assessment of autofluorescence is label-free and provides complex information on cell identity. However, research on its application to immunophenotyping has been heterogenous. This systematic review was carried out to identify and synthesise all available evidence on the use of autofluorescence for immunophenotyping. Eighty three full texts were included. There was a focus on neutrophils (20 papers) and macrophages (22 papers) with alveolar macrophages (13 papers) forming a subcategory. Seven studies investigated monocytes, three focused on microglia, two on dendritic cells, five on mast cells, nine on granulocytes, thirteen on eosinophils, one on erythrophagocytic cells, and one on natural killer cells. Eleven studies investigated uncategorised immune cell populations. Translation of findings into clinical immunophenotyping requires the application of reproducible methods, along with clear reporting of excitation and emission parameters, and a greater focus on clinical and primary samples.

Thyroid dysfunction is a prevalent global health concern that necessitates the development of effective and non-invasive screening methods to enable early detection. The application of Diffuse Reflectance Spectroscopy (DRS) in conjunction with preprocessing and predictive models for thyroid dysfunction diagnosis is investigated. The raw spectral data captured from 31 individuals with thyroid dysfunction are subjected to spectral preprocessing techniques like, Standard Normal Variate (SNV), Multiplicative Scatter Correction (MSC), and Baseline Correction. The preprocessed data subjected to regression models like Partial Least Squares Regression (PLSR), Principal Component Regression (PCR), LASSO, Random Forest, Ridge Regression, Gaussian Process Regression (GPR), and Bayesian Regression were employed to analyse the efficacy of the models. The PLSR model in concurrence with SNV outperforms other regression models by achieving an R² of 0.93, RMSE of 0.29, and MSE of 0.08, indicating low predictive error. The goodness of fit was also evaluated using Pearson's chi-squared test.

Aging is a process of progressive functional decline associated with increasing age. The process and mechanism of aging have long been widely concerned, but long-term in vivo evaluations of the visual nervous system have not been previously reported. In this study, naturally aging mouse models were used for long-term serial evaluation, and the changes in structure and blood flow of the retina and cerebral cortex were systematically analyzed. Optical Coherence Tomography (OCT) and Optical Coherence Tomography Angiography (OCTA) were performed on mice at 3, 6, 9, and 12 months of age, respectively. Structural and vascular changes with age were quantitatively evaluated. Results show that the reduction of structural thickness and vascular density of the retinal and cerebral cortex is observed. A significant correlation is also found between structural and vascular changes in the retina and cerebral cortex, indicating a consistent impact of aging on the visual nervous system.

Background: Transcranial photobiomodulation (tPBM) enhances cognitive and emotional states. We compared continuous-wave (CW) and pulsed-wave (PW) tPBM effects on 24 healthy males.

Method: Participants received 630 nm tPBM at 95 mW/cm² for 10 min: Sham, CW, or PW (500 Hz). Outcomes were assessed using the Karolinska Sleepiness Scale (KSS) (for measuring sleepiness), State-Trait Anxiety Inventory (STAI) (for assessing anxiety), Visual Analog Scale (VAS) (for measuring stress), and Beck Depression Inventory-II (BDI-II) (for evaluating depressive symptoms), and 32-channel EEG at baseline, treatment, and rest phases.

Results: Paired t-tests showed PW tPBM significantly improved sleepiness, anxiety, stress, and depression scores post-intervention (p < 0.05). ANOVA analyses indicated PW tPBM increased Alpha and Gamma band EEG power versus baseline (p < 0.05).

Conclusion: PW tPBM may improve cognitive and emotional outcomes and modulate brain activity, offering therapeutic insights.