Journal of biophotonics最新文献

Fibrosis is a pathological scarring process that disrupts tissue architecture, and is characterized by excessive extracellular matrix (ECM) deposition, leading to tissue stiffening and impaired organ function. Accurate quantification and spatial mapping of fibrotic tissue mechanics are critical for diagnosis, monitoring disease progression, and evaluating therapeutic responses. Here, we employ Brillouin microspectroscopy, a non-invasive, label-free optical technique, to quantify the mechanical properties of human fibrotic tissue in in situ. We show that Brillouin spectroscopy distinguishes fibrotic tissue from healthy tissue on the basis of localized differences in the complex longitudinal modulus and enables real-time monitoring of dynamic alterations in viscoelastic properties during fibrogenesis. To our knowledge, this is the first demonstration of Brillouin spectroscopy for in situ characterization of fibrosis and wound healing in a human model. These findings underscore Brillouin microspectroscopy's potential application as a promising diagnostic and monitoring tool for fibrotic diseases.

Extracellular vesicles (EVs) are critical in cellular communication and pathological biomarkers. Post-translationally deiminated/citrullinated proteins are reported in EV cargoes by LC-MS/MS but it is unknown in which EV sub-types they are exported, as part of EVs' intraluminal cargo or on the EV surface. Here, dSTORM super-resolution microscopy is used to co-localise total citrullinated proteins (pan-Cit), and citrullinated histone H3 (CitH3) to EV subtypes of three cancer cell lines, captured by tetraspanin trio (TT) or phosphatidylserine (PS). Permeabilised and non-permeabilised EVs are analysed with a Bayesian framework using beta-distributed posteriors for binomial outcomes. Pan-Cit and CitH3 labelling is confirmed in EVs as intraluminal cargo and on the EV surface, with higher levels detected in the permeabilized EVs. Pan-Cit staining is higher in TT-bound EVs, but CitH3 staining higher in PS-bound EVs. This study expands the landscape of EV-associated post-translational modifications with translational potential for EV-citrullinome based liquid biopsy tools.

Alzheimer's disease (AD) and vascular dementia (VaD) are two common forms of dementia. Differentiating between them is challenging due to the lack of clear clinical and auxiliary test differences. In this study, we developed a novel diagnostic method combining near-infrared spectroscopy with a convolutional neural network and self-attention mechanism (CNN-SAM). The CNN-SAM model, which integrates the self-attention mechanism to highlight important spectral features, outperformed other models with 99.3% accuracy. Data pre-processing, feature extraction, and parameter optimization further enhanced the model's performance. Visualization using the self-attention mechanism revealed key spectral bands at 1364 and 1484 nm as crucial for distinguishing AD and VaD. This approach offers a rapid, non-invasive, and accurate method for the diagnosis of AD and VaD, potentially advancing clinical practice.

Multispectral photoacoustic microscopy (PAM) using stimulated Raman scattering (SRS) has been employed to measure oxygen saturation (sO₂) in biological tissue. However, laser-scanning photoacoustic microscopy (LS-PAM) inherently suffers from low detection sensitivity due to the use of a flat transducer and non-coaxial alignment of the transducer with the optical scan. Although wide-field-of-view LS-PAM has been implemented, it typically results in coarser lateral resolution and hence lower sensitivity than existing LS-PAM systems. Here, we present a wide-field multispectral LS-PAM system for measuring sO₂ in biological tissue. Instead of relying on two discrete wavelengths, our method employs two wavelength groups-a isosbestic group (532 nm and 545 nm) and a deoxyhemoglobin-dominant group (545 nm and 558 nm). We demonstrate that using these groups improves the signal-to-noise ratio (SNR) of the detected signals, leading to more accurate sO₂ measurements. The performance of this system is validated through both phantom and in vivo studies.

Bacterial persistence is a transient phenotypic state in which a subpopulation of cells survives antibiotic exposure without genetic resistance. These dormant, low-metabolic cells are linked to recurrent infections and reduced antibiotic efficacy. Photodynamic inactivation (PDI), which generates reactive oxygen species (ROS) through photosensitizer activation under visible light, is a promising strategy to counteract persistence. This study evaluated PDI effects on Escherichia coli under amoxicillin and gentamicin pressure, using time-kill assays and MDK₉₉/MDK_99.99 metrics. PDI, optimized with methylene blue (10 μM) and 10 J/cm² light at 660 nm, was applied to antibiotic-exposed cells and progeny. For amoxicillin, PDI reduced MDK99 from > 3 to 2 h; for gentamicin, it suppressed regrowth in progeny and reduced MDK_99.99 from 3 to 2 h. Scanning electron microscopy showed morphological damage consistent with persistence. PDI enhanced antibiotic efficacy and shortened treatment time, supporting further investigation of PDI-antibiotic combinations for chronic infections.

Bacterial detection and identification are crucial tasks in today's world due to increasing casualties and severity caused by bacteria in hospital-acquired infections, food-borne infections, etc. This warrants an urgent need for rapid detection and identification of different bacterial strains. Fluorescence spectroscopy is a widely used technique for bacteria characterization owing to its high sensitivity, real-time, and simple measurement capabilities. In this work, fluorescence excitation spectra of 200 bacteria isolates belonging to eight different species were acquired under identical conditions with 25 isolates per species. The fluorescence excitation spectra were subjected to spectral deconvolution to extract four Gaussian components viz., tryptophan in protein under buried and exposed conditions, nucleic acids and anthranilic acid. Linear discriminant analysis applied to normalized fluorescence excitation spectra of 200 samples classified the bacterial strains with 100% accuracy using leave-one-out cross-validation.

Accurate identification of driver mutations such as ALK, EGFR, and KRAS in lung adenocarcinoma is essential for guiding personalized therapies, yet standard genomic assays are invasive and may alter tissue integrity. In this study, we introduce a non-destructive genotyping approach that combines visible-to-near-infrared hyperspectral imaging (400-1000 nm) of unstained pathological sections with a dual-branch deep-learning fusion framework and gradient-boosting classification. The imaging system captures rich spectral-spatial signatures, which are processed by a fusion network that synergistically extracts global contextual features and local textural details. These fused representations are then classified by an optimized XGBoost model. Evaluation on 90 clinical specimens yielded class-specific accuracies between 83.5% and 90.2%, and area under the ROC curve values from 0.83 to 0.91. Our results demonstrate that hyperspectral imaging coupled with deep-learning fusion enables rapid, tumor genotyping, offering a promising tool for real-time clinical diagnostics in the field of biomedical photonics.

We designed a handheld and fast mid-infrared fiber-optic spectral probe using a quantum cascade laser (QCL) and a reduced range of wavelengths, to see if keratinocytic carcinoma (KC) could be distinguished from adjacent nonmalignant tissue using discarded skin tissues from Mohs surgery. This study employed two adjacent frozen sections of discarded tissue: one was stained with H&E (the gold standard for skin cancer diagnosis) to identify the location of cancer by a pathologist, while the other was left unstained for mid-infrared spectral probing on and off cancer as guided by the adjacent H&E stain. A total of 346 spectra from 18 consenting patients were collected during Mohs surgery. After adding a dehumidifier, an accuracy of 95% was obtained on a case sample basis. It will be worthwhile to assess the probe's utility at the surface of live human skin (study approved by the Advarra Institutional Review Board [PRO00044823]).

Spinal cord injury (SCI) leads to severe functional deficits, underscoring the critical need for new therapies. This study evaluated the efficacy of photobiomodulation (PBM) as an early, noninvasive treatment for induced SCI, using specific parameters (808 nm, 72 J/cm², 100 mW). A total of 15 rats were divided into Control (C), SCI, and PBM groups. Efficacy was determined by an integrated approach, correlating ground reaction force (GRF) with quantitative histological assessment. The PBM group showed a significant reduction of secondary damage (33.3 ± 5.5 vs. 53.9 ± 7.0 in the SCI group; p = 0.0002) and preserved neural structure. This tissue preservation aligns with the GRF analysis, which demonstrated that the PBM group recovered gait patterns similar to the Control group. In conclusion, PBM effectively mitigates necrosis aerea, maintaining tissue integrity, improving functional recovery, and reinforcing the PBM's therapeutic potential as a promising translatable strategy for outcomes after SCI. Further research should include immunostaining of cells and larger samples.

This study identifies fluorescence excitation-emission pairs correlated with atherosclerotic pathology in an ex vivo human aorta. Fluorescence spectroscopy, wide-field fluorescence imaging, gross pathologic and histologic evaluation of ex vivo cadaveric human aorta are performed. A matrix of Pearson correlation coefficients are determined for the relationship between relevant histologic features and fluorescence intensity for 427 excitation-emission pairs. A multiple linear regression analysis indicates that tryptophan and elastin fluorescence intensity predicts 58% of the variance in intima thickness (R-squared = 0.588, F(2, 18) = 12.8, p = 0.0003), and 48% of the variance in media thickness (R-squared = 0.483, F(2, 18) = 8.42, p = 0.002). Excluding lesions identified as necrotic lipid cores on histology from analysis, a combination of tyrosine, tryptophan, collagen and elastin autofluorescence predicted 86.0% of the variance in intima thickness (R-squared = 0.8598, F(4, 13) = 19.9, p = 1.87 × 10^-5) and 51.8% of the variance in media thickness (R-squared = 0.518, F(4, 13) = 3.49, p = 0.0382).