Journal of Biophotonics最新文献

{"title":"Correction to “On the Misinterpretation of Fluorescence-Based Quantification in Theranostic Corneal Cross-Linking”","authors":"","doi":"10.1002/jbio.70307","DOIUrl":"https://doi.org/10.1002/jbio.70307","url":null,"abstract":"<p>\u0000 <span>C. Caruso</span> and <span>G. Barbaro</span>, “ <span>On the Misinterpretation of Fluorescence-Based Quantification in Theranostic Corneal Cross-Linking</span>,” <i>Journal of Biophotonics</i> <span>19</span>, no. <span>6</span> (<span>2026</span>): e70288, https://doi.org/10.1002/jbio.70288.\u0000 </p><p>This contribution was first published as “Letter,” which is the wrong article type. The correct article type is “Comment.” This has also been updated in the article itself.</p><p>We apologize for this error.</p>","PeriodicalId":184,"journal":{"name":"Journal of Biophotonics","volume":"19 6","pages":""},"PeriodicalIF":2.0,"publicationDate":"2026-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jbio.70307","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148238098","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Molecular Profiling Thyroid Cancer Using 2T2D-FTIR Spectroscopy Integrated With Machine Learning Models","authors":"Gustavo Jesus Vazquez-Zapien,&nbsp;Monica Maribel Mata-Miranda,&nbsp;Adriana Martinez-Cuazitl,&nbsp;Francisco Garibay-Gonzalez,&nbsp;Juan Salvador Garcia-Hernandez,&nbsp;Alberto Lopez-Reyes,&nbsp;Gabriela Angelica Martinez-Nava,&nbsp;Laura E. Martinez-Gomez,&nbsp;Carlos Martinez-Armenta,&nbsp;Sivakumaran Karthikeyan","doi":"10.1002/jbio.70302","DOIUrl":"10.1002/jbio.70302","url":null,"abstract":"<div>\u0000 \u0000 <p>Thyroid cancer is the most common endocrine malignancy. Two-trace two-dimensional Fourier transform infrared spectroscopy (2T2D-FTIR) shows great promise in cancer research by providing detailed molecular information that helps distinguish tumor types and stages. In this study, we used 2T2D-FTIR combined with machine learning (ML) to diagnose thyroid cancer across different population groups. The study population was divided into three groups: G1 (20–40 ± 2 years, female), G2 (45–60 ± 2 years, male and female), and G3 (65–80 ± 2 years, female). This advanced technique enhances the comparison between healthy and malignant tissues by detecting subtle molecular changes in two-dimensional space. Our findings support the use of 2T2D-FTIR combined with ML for early thyroid cancer detection, and possibly for other cancers as well. The study had a limited sample size due to ethical and availability constraints; however, the ML approach improved accuracy and could potentially achieve better results with larger datasets.</p>\u0000 </div>","PeriodicalId":184,"journal":{"name":"Journal of Biophotonics","volume":"19 6","pages":""},"PeriodicalIF":2.0,"publicationDate":"2026-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148221326","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optical-Resolution Photoacoustic Microscopy–Based Virtual Staining: A Wavelet-Enhanced Contrastive Translation Approach With Structure Preservation","authors":"Ruotong Mu,&nbsp;Siyuan Guo,&nbsp;Zhennian Xie,&nbsp;Dongbing Li,&nbsp;Xiaojing An,&nbsp;Jingtao Li,&nbsp;Yuyang Han,&nbsp;Zhe Liu,&nbsp;Chaojun Niu,&nbsp;Qiang Yang,&nbsp;Qiang Liu","doi":"10.1002/jbio.70308","DOIUrl":"10.1002/jbio.70308","url":null,"abstract":"<div>\u0000 \u0000 <p>Photoacoustic microscopy (PAM) provides label-free and high-resolution imaging capabilities. However, its optical absorption-based contrast differs fundamentally from hematoxylin and eosin (H&amp;E) staining, hindering integration into standard pathological interpretation workflows and limiting clinical translation and adoption. To address this limitation, we employ a low-cost, radiation-free 532 nm optical-resolution PAM (OR-PAM) system to construct a specimen-level cross-modal dataset for colorectal cancer. Based on this dataset, we propose a virtual H&amp;E staining generation workflow that eliminates pixel-level alignment, enabling conversion of single-wavelength OR-PAM image data into H&amp;E-style images with interpretable tissue structures. Quantitative evaluations demonstrate that our method's virtual sections outperform state-of-the-art unsupervised image-to-image translation models in overall structural fidelity, visual authenticity, and distribution consistency across key assessment metrics. This indicates that virtual staining can act as an efficient visualization layer for preliminary pathological assessment, offering a potential translational pathway for PAM in colorectal cancer clinical imaging.</p>\u0000 </div>","PeriodicalId":184,"journal":{"name":"Journal of Biophotonics","volume":"19 6","pages":""},"PeriodicalIF":2.0,"publicationDate":"2026-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148213827","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deep Learning-Based OCT Segmentation for Stiffness Quantification in Evaluating Low-Level Laser Therapy for Wound Healing","authors":"Gilang Titah Ramadhan,&nbsp;Yih-Kuen Jan,&nbsp;Ben-Yi Liau,&nbsp;Hsu-Tang Cheng,&nbsp;Wei-Cheng Shen,&nbsp;Chien-Cheng Tai,&nbsp;Sheena Christabel Pravin,&nbsp;Kiruthika Venkataramani,&nbsp;Winson Chiu-Chun Lee,&nbsp;Congo Tak Shing Ching,&nbsp;Chi-Wen Lung","doi":"10.1002/jbio.70291","DOIUrl":"10.1002/jbio.70291","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>This study evaluated the short-term biomechanical response of wound tissue following low-level laser therapy (LLLT) by examining changes in skin stiffness, a surrogate biomechanical indicator of short-term tissue response, across different limb regions.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>A 660 nm LLLT protocol was applied to wound sites. Skin stiffness was quantified using optical coherence tomography (OCT) combined with an air-jet indentation system, enabling non-contact measurement of tissue deformation. For accurate layer-specific assessment, a U-Net–based model was employed to automate OCT image segmentation.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The automated segmentation by the U-Net model achieved a segmentation accuracy of 92%, facilitated precise segmentation of skin layers. LLLT significantly reduced skin stiffness after treatment, indicating an acute modulation of tissue compliance.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>Short-duration LLLT reduces skin stiffness immediately post-treatment, indicating its potential as a non-invasive intervention to modulate the biomechanical environment of wounds.</p>\u0000 \u0000 <p><b>Trial Registration:</b> ClinicalTrials.gov identifier: NCT07177274</p>\u0000 </section>\u0000 </div>","PeriodicalId":184,"journal":{"name":"Journal of Biophotonics","volume":"19 6","pages":""},"PeriodicalIF":2.0,"publicationDate":"2026-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jbio.70291","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148201801","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Nonlinear Imaging Allows to Characterize Granulomas and Fibrosis in Mice Tissue From Experimental Schistosomiasis","authors":"Gladystone Rocha da Fonseca,&nbsp;Rennan R. M. Lima,&nbsp;Ronald Eduardo Soares,&nbsp;Bárbara Regina Melo Ribeiro,&nbsp;Paulo E. Cabral Filho,&nbsp;Adriana Fontes,&nbsp;Ana Maria de Paula","doi":"10.1002/jbio.70295","DOIUrl":"10.1002/jbio.70295","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <p>Schistosomiasis is a neglected disease caused by parasites of the genus <i>Schistosoma</i> that poses serious public health problems. The liver is one of the organs seriously affected by the disease as it lodges <i>Schistosoma</i> eggs. We show results by nonlinear imaging techniques, Second Harmonic Generation and Two-Photon Excitation Fluorescence, to characterize mice tissues infected with <i>Schistosoma mansoni</i> in an experimental model. We followed the evolution of the disease in liver tissue sections through three stages: 30, 60, and 120 days post-infection—the pre-patent, acute, and early chronic phases, respectively. The presence of the <i>Schistosoma</i> eggs causes an increase in the collagen content and also changes in its architecture. The results allow us to clearly evaluate the disease progress helping to improve the understanding of liver fibrosis.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <p>Second Harmonic Generation and Two-Photon Excitation Fluorescence microscopy allows to characterize mice tissues infected with <i>Schistosoma mansoni</i> in an experimental model.</p>\u0000 </section>\u0000 </div>","PeriodicalId":184,"journal":{"name":"Journal of Biophotonics","volume":"19 6","pages":""},"PeriodicalIF":2.0,"publicationDate":"2026-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jbio.70295","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148166084","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Highly Sensitive 1D Photonic Crystal Biosensor for Early Malaria Detection via Refractive Index","authors":"Kasrolourdhina Kaspar,&nbsp;Kathiresan Karuppiah,&nbsp;Poovendran Karuppiah,&nbsp;Nambi Ramachary Ramanujam","doi":"10.1002/jbio.70298","DOIUrl":"10.1002/jbio.70298","url":null,"abstract":"<div>\u0000 \u0000 <p>This article presents a theoretical investigation of a highly sensitive one-dimensional photonic crystal (1D-PC) biosensor for early malaria detection using the Transfer Matrix Method (TMM). The proposed structure, Air/(PbS/SiO₂)₄/defect/(PbS/SiO₂)₄/substrate, is optimized by adjusting the defect layer thickness and incidence angle to enhance defect-mode resonance characteristics. The design enables strong resonant peaks and significant wavelength shifts at 1550 nm. The sensor operates over a refractive index range of 1.371–1.402 RIU, corresponding to different malaria infection stages. A maximum sensitivity of 977.74 nm/RIU and a quality factor of 93.8 × 10³ are achieved at a defect thickness of 1.2d_a. Increasing the thickness to 1.4d_a improves sensitivity to 1163.22 nm/RIU with a quality factor of 82.57 × 10³. The design also exhibits a low detection limit of ~10⁻⁶ RIU and a high figure of merit, indicating strong potential for rapid, accurate, and cost-effective malaria diagnosis.</p>\u0000 </div>","PeriodicalId":184,"journal":{"name":"Journal of Biophotonics","volume":"19 6","pages":""},"PeriodicalIF":2.0,"publicationDate":"2026-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148166065","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ho:YAG and Thulium Fiber Laser Radiation Transmission Through Vapor Channels in Laser Lithotripsy","authors":"Kimberley Lühring,&nbsp;Birgit Lange,&nbsp;Ralf Brinkmann","doi":"10.1002/jbio.70304","DOIUrl":"10.1002/jbio.70304","url":null,"abstract":"<div>\u0000 \u0000 <p>The efficiency of energy deposition during laser lithotripsy is strongly influenced by the interaction between laser radiation and the water layer between fiber tip and stone. This study investigates the transmission of holmium:YAG (Ho:YAG) and thulium fiber laser (TFL) radiation through vapor channels under varying fiber-to-target distances (0.5–3 mm). Both lasers were set to deliver pulses of 1 J. The fiber was positioned in a water-filled cuvette on top of an integrating sphere to measure transmittance through different water layer thicknesses. A 580 μs, high-power (up to 7 kW) Ho:YAG laser pulse creates a vapor channel that enables continuous transmission of the laser energy to the target surface for standoff distances &gt; 0.5 mm. With the TFL's longer (2 ms), lower peak power (500 W) pulses, repeated cycles of vaporization and bubble collapse occur, resulting in a reduced energy transmission efficiency compared to the Ho:YAG laser pulses.</p>\u0000 </div>","PeriodicalId":184,"journal":{"name":"Journal of Biophotonics","volume":"19 6","pages":""},"PeriodicalIF":2.0,"publicationDate":"2026-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148159745","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine Learning–Integrated Raman Spectroscopy Identifies Race-Associated Biochemical Signatures in Prostate Cancer","authors":"Maria Iftesum,&nbsp;Gyana Ranjan Sahoo,&nbsp;Elnaz Sheikh,&nbsp;Madhur Srivastava,&nbsp;Sanjit Roy,&nbsp;Hem D. Shukla,&nbsp;Nrusingh C. Biswal,&nbsp;Manas Ranjan Gartia","doi":"10.1002/jbio.70293","DOIUrl":"10.1002/jbio.70293","url":null,"abstract":"<div>\u0000 \u0000 <p>Black men experience disproportionately higher prostate cancer incidence and mortality, yet the underlying biochemical contributors remain unclear. In this study, we integrate Raman spectroscopy with advanced multivariate and machine-learning methods to characterize molecular differences in clinical formalin-fixed, paraffin-embedded (FFPE) prostate tissues from Black and White patients. Raman spectra were corrected using ICA-PLS, wavelet-denoised, and unmixed with Multivariate Curve Resolution–Alternating Least Squares (MCR-ALS) to quantify cellular components. Random forest (RF) models were trained on denoised spectra to classify cancer versus control tissues. MCR-ALS revealed elevated protein, collagen, lipid, and nucleic acid signatures in tumors from Black patients, aligning with clinically observed aggressive disease phenotypes. RF classification achieved &gt; 90% accuracy, 95% sensitivity, 85% specificity, and an AUC &gt; 0.96, demonstrating robust diagnostic performance. These findings show that Raman spectroscopy integrated with computational analysis provides a powerful label-free approach to probe biochemical drivers of racial disparities in prostate cancer.</p>\u0000 </div>","PeriodicalId":184,"journal":{"name":"Journal of Biophotonics","volume":"19 6","pages":""},"PeriodicalIF":2.0,"publicationDate":"2026-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148159844","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multimodal Imaging-Based Quantitative Assessment of Autoimmune Uveitis in Experimental Mouse Model","authors":"Xiaolong Zhang,&nbsp;Sisi Chen,&nbsp;Meixiao Shen,&nbsp;Zi Jin,&nbsp;Wenjuan Wu,&nbsp;Cuixia Dai","doi":"10.1002/jbio.70301","DOIUrl":"10.1002/jbio.70301","url":null,"abstract":"<div>\u0000 \u0000 <p>Autoimmune uveitis is a sight-threatening disease mainly caused by immune dysregulation. Most existing clinical and biomedical studies still rely on subjective inflammatory assessment and semiquantitative molecular evaluation, and there is very little fairness research on multidimensional uveitis characterization exploration. With the advent of noninvasive and high-resolution imaging technology, there is a growing demand for objective, quantitative, and traceable indicators to support mechanistic investigation, accurate staging, precision therapy, and early relapse detection. In this study, we implemented a multiparametric, multimodal imaging platform to longitudinally monitor experimental autoimmune uveitis (EAU). Changes in retinal structure, vascular networks, and visual function were evaluated within 2 weeks after EAU induction. Based on quantitative analysis of optical coherence tomography (OCT), OCT angiography (OCTA), vascular density (VD), and vascular tortuosity (VT) were shown to correlate with retinal thickness, clinical scores, histopathological scores, and may be added as potential objective and noninvasive candidate indicators for uveitis detection.</p>\u0000 </div>","PeriodicalId":184,"journal":{"name":"Journal of Biophotonics","volume":"19 6","pages":""},"PeriodicalIF":2.0,"publicationDate":"2026-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148145897","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Denoising-Assisted Rapid Multiphoton Imaging for Analysing Traumatic Penumbra Microenvironment in Rat Brain","authors":"Pan Guo,&nbsp;Le Chen,&nbsp;Shanghai Jiang,&nbsp;Li Ai,&nbsp;Shenghui Shi,&nbsp;Duan Yang,&nbsp;Jian Xu,&nbsp;Jianxin Chen,&nbsp;Hong Lu","doi":"10.1002/jbio.70303","DOIUrl":"10.1002/jbio.70303","url":null,"abstract":"<div>\u0000 \u0000 <p>Accurate identification of the traumatic penumbra (TP) is essential for understanding secondary injury after traumatic brain injury. However, conventional imaging cannot capture microenvironmental alterations at subcellular resolution. In this study, denoising-assisted multiphoton microscopy (MPM) was used to investigate the microstructural features of the TP in rat brain tissue. Image processing and quantitative analysis were performed to characterize normal tissue, penumbra, and core regions. To accelerate high-quality imaging, we proposed a Dual-Branch Collaborative Network (DBCNet) to restore low-noise images from single-scan data using multi-scan references. The results show that MPM reveals key pathological features such as intracellular edema, vasogenic edema, and cytoplasmic matrix disruption. DBCNet effectively suppresses noise, enhances fine structures, and reduces imaging time to one-fourth without hardware modification. These findings demonstrate that denoising-assisted MPM provides a rapid and efficient strategy for high-resolution imaging and quantitative assessment of the TP microenvironment.</p>\u0000 </div>","PeriodicalId":184,"journal":{"name":"Journal of Biophotonics","volume":"19 6","pages":""},"PeriodicalIF":2.0,"publicationDate":"2026-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148145889","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}