{"title":"Label-Free Intraoperative Diagnosis of Breast Cancer Based on Multi-Angle Orthogonal Polarization Microscopy and Multimodal Fusion.","authors":"Jianbo Zhu, Wenhui Sun, Jinjin Wu, Sheng Ding, Chongyan Liu, Zichen Ling, Linwei Shang, Huijie Wang, Jing Pei, Jianhua Yin","doi":"10.1002/jbio.70259","DOIUrl":"10.1002/jbio.70259","url":null,"abstract":"<p><p>Breast cancer surgery urgently requires a rapid and objective intraoperative diagnostic strategy, as conventional frozen-section pathology depends on time-consuming staining and subjective interpretation, limiting timely surgical decision-making. However, existing label-free microscopic imaging approaches exclude conventional pathological information and lack diagnostic power. To overcome these limitations, a multimodal fusion framework based on unstained multi-angle orthogonal polarization micro-imaging (OPMI) and bright-field micro-imaging (BFMI) was proposed for rapid intraoperative breast cancer diagnosis. By superimposing and differencing multi-angle polarized images, optical contrast of anisotropic collagen fibers was markedly enhanced without staining, enabling objective visualization of collagen morphology and spatial alterations associated with malignancy. Local radial alignment and increased density of collagen fibers corresponding to invasive progression were identified. A dual-encoder fusion network integrating global and local feature representation improved lesion structure and boundary delineation. The method achieved 91.83% accuracy and area under the curve (AUC) of 0.9295, outperforming unimodal and bimodal approaches, offering a promising label-free intraoperative decision-support strategy.</p>","PeriodicalId":94068,"journal":{"name":"Journal of biophotonics","volume":"19 3","pages":"e70259"},"PeriodicalIF":2.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147517919","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Liang Zhang, Yan Zhou, Binlin Wu, Shengjia Zhang, Ke Zhu, Cheng-Hui Liu, Robert Alfano, Xinguang Yu
{"title":"Optical Molecular Signatures of IDH Genotype for Classification of Human Glioma Using Visible Resonance Raman Spectroscopy.","authors":"Liang Zhang, Yan Zhou, Binlin Wu, Shengjia Zhang, Ke Zhu, Cheng-Hui Liu, Robert Alfano, Xinguang Yu","doi":"10.1002/jbio.70239","DOIUrl":"10.1002/jbio.70239","url":null,"abstract":"<p><p>Glioma is the most common brain neoplasm that features aggressive behavior with a dismal prognosis. Isocitrate dehydrogenase (IDH) gene mutation in glioma is an early genetic event in gliomagenesis that occurs in virtually every tumor cell and can cause profound metabolic changes. In this manuscript, we report for the first time the analysis of Raman optical signatures of IDH genotypes for human glioma using visible resonance Raman (VRR) spectroscopy. We demonstrated that VRR is a rapid, label-free, and objective method as an alternative to the existing methods for the rapid intraoperative determination of IDH mutation status with high accuracy. This study shows AI-assisted VRR has the potential to provide a new optical molecular biomarker and perform early diagnosis of glioma, which is of great importance for current guiding surgical strategies and even for targeting in situ therapies in the future.</p>","PeriodicalId":94068,"journal":{"name":"Journal of biophotonics","volume":"19 3","pages":"e70239"},"PeriodicalIF":2.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147438477","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Lucía Píriz Trindade, Maria Jose Urruty, Laura Hermida Bruno, Federico Todeschini, Luis Eduardo Pascuali Moya, Valentina Lestido, Tainá Caroline Dos Santos Malavazzi, Lara Jansiski Motta, Sandra Kalil Bussadori, Kristianne Porta Santos Fernandes, Anna Carolina Ratto Tempestini Horliana, Raquel Agnelli Mesquita-Ferrari
{"title":"LED Photobiomodulation for Pain Reduction in Temporomandibular Disorder: A Randomized, Controlled, and Blinded Clinical Trial.","authors":"Lucía Píriz Trindade, Maria Jose Urruty, Laura Hermida Bruno, Federico Todeschini, Luis Eduardo Pascuali Moya, Valentina Lestido, Tainá Caroline Dos Santos Malavazzi, Lara Jansiski Motta, Sandra Kalil Bussadori, Kristianne Porta Santos Fernandes, Anna Carolina Ratto Tempestini Horliana, Raquel Agnelli Mesquita-Ferrari","doi":"10.1002/jbio.70243","DOIUrl":"10.1002/jbio.70243","url":null,"abstract":"<p><p>This clinical, randomized, controlled, and blinded trial evaluated photobiomodulation (PBM) using 850 nm (infrared) and 660 nm (red) LED clusters on cervical and mandibular mobility and masticatory muscles in temporomandibular disorder (TMD) patients. PBM was applied to the temporomandibular joint (TMJ) region, masseter, temporal, scalene, and trapezius muscles over six non-consecutive sessions over 2 weeks. The Research Diagnostic Criteria for Temporomandibular Disorders (DC/TMD) were used to determine the presence of TMD. A caliper and goniometer were used to measure the mandibular and cervical range of motion, respectively. Pain was assessed with the visual analog scale (VAS) before and after intervention. Results showed pain reduction only in the LED group post-intervention; the placebo group showed no difference. No differences were observed in mouth opening, right laterality, flexion, or extension between groups, but left laterality increased in the LED group. In conclusion, PBM with LEDs effectively reduced pain in TMD patients. Trial Registration: ClinicalTrials.gov identifier: NCT06068959.</p>","PeriodicalId":94068,"journal":{"name":"Journal of biophotonics","volume":"19 3","pages":"e70243"},"PeriodicalIF":2.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12966631/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147370838","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Xing Huang, Dunxiang Zhang, Ning Xia, Jinmiao Guo, Ang Deng, Xuemei Yang, Han Wu, Bole Tian, Junjie Xiong, Houkun Liang
{"title":"Selective Laser Ablation of Malignant Solid Tumors Tuned to the Resonant Wavelength of Collagen.","authors":"Xing Huang, Dunxiang Zhang, Ning Xia, Jinmiao Guo, Ang Deng, Xuemei Yang, Han Wu, Bole Tian, Junjie Xiong, Houkun Liang","doi":"10.1002/jbio.70250","DOIUrl":"10.1002/jbio.70250","url":null,"abstract":"<p><p>Laser ablation is progressively introducing novel therapeutic approaches for treatment of solid tumors. Recently, our previous research demonstrated that mid-infrared femtosecond lasers tuned to the collagen resonance wavelength can selectively ablate solid tumors. However, the mechanisms underlying selectivity, as well as its potential clinical relevance, remain insufficiently understood. In this study, systematic investigations have been conducted on three orthotopic mice models of solid tumors: glioma, pancreatic ductal adenocarcinoma (PDAC), and colorectal cancer, employing a 6.1 μm femtosecond laser resonant with collagen. Selective ablation is observed in glioma and PDAC, but not in colorectal cancer, which is attributed to the markedly increased collagen content, particularly Collagen I, relative to their corresponding normal tissues, a disparity that is not present in colorectal cancer. Further analysis of clinical specimens through multiplex immunofluorescence and gene expression supports the translational potential of this collagen-mediated selective laser ablation mechanism, suggesting its applicability for tumor-targeted therapeutic interventions.</p>","PeriodicalId":94068,"journal":{"name":"Journal of biophotonics","volume":"19 3","pages":"e70250"},"PeriodicalIF":2.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147438466","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Integrated LC-OCT/Raman Microspectroscopy: A Novel Diagnostic Approach in Ophthalmology Demonstrated in a Case Study.","authors":"Ayadh Meriem, Dorado Cortez Christian, Ogien Jonas, Vanden-Bossche Arnaud, Camy Florian, Cinotti Elisa, Grivet Damien, Dubois Arnaud, Perrot Jean-Luc","doi":"10.1002/jbio.70245","DOIUrl":"10.1002/jbio.70245","url":null,"abstract":"<p><p>Integrated LC-OCT and Raman microspectroscopy enable the non-invasive identification of conjunctival hydroxyapatite calcifications, providing a dual morphological and molecular diagnostic approach. This bimodal technique successfully identifies microcrystals that are often undetectable by conventional histology due to their solubility and weak birefringence.</p>","PeriodicalId":94068,"journal":{"name":"Journal of biophotonics","volume":"19 3","pages":"e70245"},"PeriodicalIF":2.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147350071","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Letícia Palombo Martinelli, Natasha Ferreira Mezzacappo, Ana Paula Silva, Priscila Menezes, Vanderlei Salvador Bagnato
{"title":"Infrared Photobiomodulation Modulates PpIX Production After Topical Methyl Aminolevulinate in Normal Human Skin: An Exploratory Study.","authors":"Letícia Palombo Martinelli, Natasha Ferreira Mezzacappo, Ana Paula Silva, Priscila Menezes, Vanderlei Salvador Bagnato","doi":"10.1002/jbio.70262","DOIUrl":"10.1002/jbio.70262","url":null,"abstract":"<p><p>Photodynamic therapy (PDT) for skin lesions requires optimized photosensitizer accumulation. Since protoporphyrin IX (PpIX) synthesis is linked to mitochondrial activity, photobiomodulation (PBM) may modulate this process. This exploratory study examined the effects of PBM at 780 or 808 nm on MAL-induced PpIX in normal human skin. Eleven volunteers received paired-arm treatments (5, 10, or 15 J/cm<sup>2</sup>). Following 30 min of MAL, PBM was applied, with total incubation lasting 210 min. PpIX was assessed via spectroscopy and widefield imaging. Although mean PBM/no-PBM ratios were nominally above 1, no statistically significant differences were found among fluences or against unity, primarily due to high interindividual variability (CV up to 35%). These findings suggest that while PBM shows a trend toward modulating photosensitizer accumulation, the response is highly heterogeneous. This study provides a rationale for further investigation into personalized PBM-assisted PDT protocols to manage biological variability and refine clinical outcomes.</p>","PeriodicalId":94068,"journal":{"name":"Journal of biophotonics","volume":"19 3","pages":"e70262"},"PeriodicalIF":2.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13022744/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147523217","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Journal of biophotonicsPub Date : 2026-03-01Epub Date: 2025-12-19DOI: 10.1002/jbio.202500515
Jun Huang, Mingkun Luo, Letian Wang, Hao Cui, Yiru Xia, JingJing Nan
{"title":"Investigation on Effects of Process Parameters on Tissue Fusion Performance and Thermal Damage in Laser-Assisted Vascular Anastomosis.","authors":"Jun Huang, Mingkun Luo, Letian Wang, Hao Cui, Yiru Xia, JingJing Nan","doi":"10.1002/jbio.202500515","DOIUrl":"10.1002/jbio.202500515","url":null,"abstract":"<p><p>This study conducted laser-assisted vascular anastomosis experiments using a YAG continuous-wave fiber laser (wavelength: 1064 ± 4 nm, maximum power: 10 W) to investigate the effects of process parameters-including laser power, scanning speed, and defocus distance-on the burst pressure strength of vascular tissue. Thermal damage was evaluated based on the thermal damage parameter (Ω), collagen content, and microstructural characteristics. The results indicate that laser power and defocus distance significantly influence the burst pressure strength, while laser power notably affects the extent of thermal injury. The optimal process parameters were identified as a laser power of 6 W, a scanning speed of 300 mm/s, and a defocus distance of 3 mm. Under these conditions, the burst pressure strength reached 52.58 kPa, with a thermal damage parameter Ω of only 0.0623, meeting the requirements for vascular anastomosis.</p>","PeriodicalId":94068,"journal":{"name":"Journal of biophotonics","volume":" ","pages":"e202500515"},"PeriodicalIF":2.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145795774","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Leveraging Laser-Induced Breakdown Spectroscopy and Machine Learning Methods for Rapid Detection of AMR Profiles in Pathogenic Bacterial Isolates.","authors":"Vivek Sivakumar, Sujatha N Unni, Nilesh J Vasa","doi":"10.1002/jbio.70249","DOIUrl":"10.1002/jbio.70249","url":null,"abstract":"<p><p>Rapid antimicrobial resistance (AMR) detection is critical for clinical treatment efficacy and infection control. We present a Laser-Induced Breakdown Spectroscopy (LIBS) method for antimicrobial susceptibility testing and detection of various resistance profiles in pathogenic bacteria. A controlled growth environment is utilized for regulated culture of different bacterial strains which induces strain-specific adaptation under controlled nutrient stress and also minimizes spectral variability due to differences in media composition and bacterial growth phases. By leveraging minimal yet robust spectral features (emission lines from Sodium, Potassium and Calcium), this method enables accurate AMR detection by employing machine learning algorithms. An accuracy of 94.7% and ROC-AUC > 0.99 was achieved using a Support Vector Machine model for classifying seven bacterial strains (3 susceptible and 4 resistant), without requiring outlier filtering or averaging of spectra. This tailored LIBS framework establishes a quick and cost-effective diagnostic tool for rapid AMR profiling compared to conventional culture-based susceptibility testing.</p>","PeriodicalId":94068,"journal":{"name":"Journal of biophotonics","volume":"19 3","pages":"e70249"},"PeriodicalIF":2.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147370787","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Thi Thu Ha Vu, Soonhyuk Tak, Tan Hung Vo, Van Bang Nguyen, Dinh Tuan Nguyen, Le Khuong Phan, Jaeyeop Choi, Sudip Mondal, Junghwan Oh
{"title":"Deep Learning-Based Super-Resolution for Vessel Enhancement in Photoacoustic Microscopy Imaging.","authors":"Thi Thu Ha Vu, Soonhyuk Tak, Tan Hung Vo, Van Bang Nguyen, Dinh Tuan Nguyen, Le Khuong Phan, Jaeyeop Choi, Sudip Mondal, Junghwan Oh","doi":"10.1002/jbio.70221","DOIUrl":"10.1002/jbio.70221","url":null,"abstract":"<p><p>Photoacoustic imaging (PAI) is an advanced imaging technique for high-resolution (HR), non-invasive visualization of vascular networks, offering distinct advantages in functional and structural imaging. However, its performance is often constrained by trade-offs between spatial resolution and imaging depth, as well as noise and artifacts caused by system limitations and tissue properties. Here, we introduce GDSU-Net, a fine-tuned neural network designed for super-resolution (SR) reconstruction of PAI. GDSU-Net builds on the U-Net architecture and incorporates four key components: group normalization, depthwise separable convolutions, squeeze-and-excitation (SE) blocks, and a pixelshuffle-based decoder. Experimental results demonstrate that GDSU-Net achieves a structural similarity index of 0.889 and a peak signal-to-noise ratio (PSNR) of 31.979 dB, while reducing the root mean square error (RMSE) to 0.032 and the mean absolute error (MAE) to 0.025. Visual evaluations confirm its effectiveness in restoring vascular details with preserved anatomical fidelity. These findings highlight GDSU-Net as a computationally efficient solution for super-resolution enhancement in PAI.</p>","PeriodicalId":94068,"journal":{"name":"Journal of biophotonics","volume":"19 3","pages":"e70221"},"PeriodicalIF":2.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147358196","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Junfang Xie, Yifei Zhan, Jin Wang, Zhichao Deng, Jian-Guo Tian, Qing Ye
{"title":"In Situ 3D Super Resolution Nanoscale Imaging of Cell Spheroids by Expansion Microscopy.","authors":"Junfang Xie, Yifei Zhan, Jin Wang, Zhichao Deng, Jian-Guo Tian, Qing Ye","doi":"10.1002/jbio.70253","DOIUrl":"10.1002/jbio.70253","url":null,"abstract":"<p><p>Three-dimensional (3D) cell models provide a physiologically relevant environment similar for improving drug screening. However, subcellular structure observation remains challenging due to light scattering. This study developed 3D HeLa cell spheroids in gelatin methacryloyl (GelMA) hydrogel as the in vitro 3D cell model for drug screening. A 4.6-fold expansion protocol enabled in situ high-resolution 3D mitochondrial imaging for cell spheroids cultured in GelMA. Notably, to our knowledge, this is the first instance of revealing mitochondrial morphology at the individual mitochondrial level within cell spheroids. Furthermore, quantitative analysis reveals the mitochondrial morphology change after drug treatment. This work establishes a high-content 3D cell model-based drug screening method, in which in situ subcellular structure imaging in 3D cell spheroids embedded in GelMA can be achieved with unprecedented resolution (about 90 nm) by commercial confocal microscope, facilitating a deeper understanding of drug mechanisms in cell spheroid-based drug screening.</p>","PeriodicalId":94068,"journal":{"name":"Journal of biophotonics","volume":"19 3","pages":"e70253"},"PeriodicalIF":2.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147470477","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}