Search Results (196)

Phenol red is a widely used, low-cost, label-free colorimetric pH indicator that bridges traditional colorimetric assays with modern quantitative imaging and cell-based screening platforms. Its protonation-dependent absorbance shift (430–560 nm) allows for the real-time monitoring of extracellular acidification, which indirectly reflects cellular metabolism, growth, and respiration. Although phenol red lacks the molecular specificity of genetically encoded or fluorogenic biosensors, it remains useful in systems where pH changes are effective proxies for physiological processes. Existing tissue digestion protocols often overlook key parameters, especially pH control and enzyme cofactor use. This study presents a straightforward, spectrophotometric method to monitor and adjust the pH of low-volume (1 mL) buffered enzymatic dissociation media using phenol red and a plate reader. We titrated dissociation solutions to physiological pH (~7.4) using spectrophotometric pH measurements validated against conventional glass pH probe readings, confirming method reliability. Accurate pH assessment is critical for isolating viable primary cells for downstream applications such as tissue engineering, single-cell omics, and neurophysiological assays. We highlight that papain-based dissociation media supplemented with L-cysteine can be acidic (pH 6.6) if unadjusted, compromising cell viability. This accessible approach enhances reproducibility by promoting pH documentation concerning dissociation conditions that contribute to advancing consistency in biomedical, cellular, neuronal, and tissue engineering research. Full article

A 70-year-old Japanese woman with longstanding hearing loss and asthma developed floating sensations, left finger numbness, and postural instability one day after influenza vaccination, leading to hospital admission. Neurological examinations showed hearing loss, hyperreflexia, left-predominant ataxia, bilateral mild bathyanesthesia, and inability to tandem gait. Cerebrospinal fluid (CSF) analysis showed no pleocytosis or malignant cells, but revealed positive oligoclonal bands and elevated myelin basic protein. Despite no contrast agent use due to asthma, brain magnetic resonance imaging (MRI) revealed pontine hyperintensities on diffusion-weighted imaging (DWI) and T2-fluid attenuated inversion recovery (T2-FLAIR) sequences, along with hyperperfusion on arterial spin labeling (ASL) imaging. Serum anti-aquaporin-4 antibodies (AQP4-Ab) were negative by ELISA. Given the temporal proximity to vaccination and elevated demyelination markers, brainstem-type acute disseminated encephalomyelitis (ADEM) was initially suspected. Symptoms nearly resolved after two cycles of methylprednisolone pulse therapy. Notably, hyperperfusion gradually improved on ASL imaging. Post-discharge, a cell-based assay confirmed the diagnosis of neuromyelitis optica spectrum disorder (NMOSD) by detecting positive anti-AQP4-Ab. She has been relapse-free for about a year without any immunosuppressants or biologics. Although contrast-enhanced MRI remains the gold standard modality for lesion evaluation due to its high sensitivity, hyperperfusion on ASL may provide a useful alternative in patients for whom contrast agents are contraindicated, such as those with asthma or impaired renal function. Full article

Staining-based assays are widely used for cell analysis but are invasive, alter physiology, and prevent longitudinal monitoring. Label-free, morphology-based approaches could enable real-time, non-invasive drug testing, yet detection of subtle and dynamic changes has remained difficult. We developed a deep learning framework for stain-free monitoring of leukemia cell cultures using automated bright-field microscopy in a semi-automated culture system (AICE3, LABMaiTE, Augsburg, Germany). YOLOv8 models were trained on images from K562, HL-60, and Kasumi-1 cells, using an NVIDIA DGX A100 GPU for training and tested on GPU and CPU environments for real-time performance. Comparative benchmarking with RT-DETR and interpretability analyses using Eigen-CAM and radiomics (RedTell) was performed. YOLOv8 achieved high accuracy (mAP@0.5 > 98%, precision/sensitivity > 97%), with reproducibility confirmed on an independent dataset from a second laboratory and an AICE3 setup. The model distinguished between morphologically similar leukemia lines and reliably classified untreated versus differentiated K562 cells (hemin-induced erythroid and PMA-induced megakaryocytic; >95% accuracy). Incorporation of decitabine-treated cells demonstrated applicability to drug testing, revealing treatment-specific and intermediate phenotypes. Longitudinal monitoring captured culture- and time-dependent drift, enabling separation of temporal from drug-induced changes. Radiomics highlighted interpretable features such as size, elongation, and texture, but with lower accuracy than the deep learning approach. To our knowledge, this is the first demonstration that deep learning resolves subtle, drug-induced, and time-dependent morphological changes in unstained leukemia cells in real time. This approach provides a robust, accessible framework for label-free longitudinal drug testing and establishes a foundation for future autonomous, feedback-driven platforms in precision oncology. Ultimately, this approach may also contribute to more precise and adaptive clinical decision-making, advancing the field of personalized medicine. Full article

Extracellular vesicles (EVs) from mesenchymal stem cells hold therapeutic promise for inflammatory and degenerative diseases; however, limited delivery and targeting capabilities hinder their clinical use. In this study, we sought to enhance the anti-inflammatory and chondroprotective effects of EVs through CAP-LAMP2b (chondrocyte affinity peptide fused to an EV membrane protein) engineering and ADAMTS4 gene editing hybrid vesicle formation. Human umbilical cord MSCs (hUCMSCs) were characterized via morphology, immunophenotyping, and trilineage differentiation. EVs from control and CAP-LAMP2b-transfected hUCMSCs were fused with liposomes carrying CRISPR-Cas9 ADAMTS4 gRNA. DiI-labeled EV uptake was assessed via fluorescence imaging. CAP-LAMP2b was expressed in hUCMSCs and their EVs. EVs exhibited the expected size (~120 nm), morphology, and exosomal markers (CD9, CD63, CD81, HSP70). CAP-modified hybrid EVs significantly enhanced chondrocyte uptake compared to control EVs and liposomes. IL-1β increased ADAMTS4 expression, whereas CAP-LAMP2b-ADAMTS4 EVs, particularly clone SG3, reversed these effects by reducing ADAMTS4 and restoring aggrecan. Western blotting confirmed suppressed ADAMTS4 and elevated aggrecan protein. CAP-LAMP2b-ADAMTS4 EVs, therefore, showed superior uptake and therapeutic efficacy in inflamed chondrocytes, attenuating inflammatory gene expression and preserving matrix integrity. These results support engineered EVs as a promising cell-free approach for cartilage repair and osteoarthritis treatment. Full article

Cellular senescence, a state of irreversible growth arrest in response to stress, plays a dual role in physiology and pathology. While essential for processes such as embryogenesis, wound healing, and tumor suppression, senescence also contributes to aging and age-related diseases, including cancer and neurodegeneration. The accumulation of senescent cells is linked to aging and numerous age-associated pathologies, making the detection of these cells crucial for understanding and potentially mitigating age-related diseases. Lipid metabolism is a key feature of senescent cells, which undergo significant alterations in lipid composition that influence membrane remodeling and cellular function. Here, we propose the use of third harmonic generation (THG) microscopy, a label-free imaging modality, to assess lipid profiles in senescent and nonsenescent cells. Our study demonstrated that THG can discriminate between senescent and nonsenescent fibroblasts based on their lipid content, suggesting a noninvasive approach for the detection and characterization of cellular senescence. In addition, these findings reveal that lipid content is increased in senescent cells. This methodology has potential applications in the diagnosis and study of age-related pathologies where lipid dysregulation is a hallmark feature. Full article

Background/Objectives: Mass-forming chronic pancreatitis (MFP) and pancreatic ductal adenocarcinoma (PDAC) can present with overlapping radiological, clinical, and serological features in patients with underlying chronic pancreatitis (CP), making differential diagnosis particularly challenging. Current diagnostic tools, including CA19-9 and endoscopic ultrasound (EUS) imaging, often lack the specificity needed to reliably distinguish between these conditions. The objective of this study was to investigate whether the proteomic profiling of endoscopic ultrasound-guided fine-needle aspiration (EUS-FNA) samples could provide molecular-level discrimination between MFP and PDAC in patients with CP. Methods: Thirty CP patients with solid pancreatic lesions were prospectively enrolled: 15 with histologically confirmed PDAC and 15 with MFP. Traditional diagnostic parameters, including CA19-9 levels and EUS characteristics, were recorded but found insufficient for differentiation. EUS-FNA samples were analyzed using label-free mass spectrometry. A total of 928 proteins were identified in PDAC samples and 555 in MFP samples. Differential abundance analysis and pathway enrichment were performed. Results: Overall, 88 proteins showed significant differential abundance between PDAC and MFP samples, of which 26 met stringent statistical thresholds. Among these, Carboxylesterase 2 (CES2), Carcinoembryonic Antigen-Related Cell Adhesion Molecule 1 (CEACAM1), Lumican (LUM), Transmembrane Protein 205 (TMEM205), and NAD(P)H Quinone Dehydrogenase 1 (NQO1) emerged as key discriminatory proteins. Pathway enrichment analysis revealed distinct biological processes between the groups, including mitochondrial fatty acid β-oxidation, Rho GTPase signaling, and platelet degranulation. Conclusions: Proteomic signatures derived from EUS-FNA samples offer a promising molecular approach to distinguish inflammatory pseudotumoral lesions from malignant pancreatic tumors in CP patients. This minimally invasive strategy could enhance diagnostic accuracy where current methods fall short. Further validation in larger, multicenter cohorts is warranted to confirm these findings and evaluate their clinical applicability. Full article

Full-field optical coherence tomography (FF-OCT) is a high-resolution interferometric imaging technique that enables label-free visualization of cellular structural changes. In this study, we employed a custom-built time-domain FF-OCT system to monitor morphological alterations in HeLa cells undergoing doxorubicin-induced apoptosis and ethanol-induced necrosis at the single-cell level. Apoptotic cells showed characteristic features such as echinoid spine formation, cell contraction, membrane blebbing, and filopodia reorganization. In contrast, necrotic cells exhibited rapid membrane rupture, intracellular content leakage, and abrupt loss of adhesion structure. These dynamic events were visualized using high-resolution tomography and three-dimensional surface topography mapping. Furthermore, FF-OCT-based interference reflection microscopy (IRM)-like imaging effectively highlighted changes in cell–substrate adhesion and cell boundary integrity during the cell death process. Our findings suggest that FF-OCT is a powerful imaging platform for distinguishing cell death pathways and assessing dynamic cellular states, with potential applications in drug toxicity testing, anticancer therapy evaluation, and regenerative medicine. Full article

Cell observation is crucial in life science research, and advancements in microscopy are essential for deciphering biological phenomena. These technological developments have significantly enhanced our understanding of cellular mechanisms and processes. Light, characterized by its wave-like properties, is fundamental to scientific observation. Recently, new technologies have been developed to detect changes in light wavelengths upon illumination, using them as signals for visualization. Three-dimensional optical wave field microscopy (3D-OWFM), a recent innovation in optimal imaging, leverages the wave properties of light to capture objects without labels, invasive procedures, or direct contact, thus facilitating non-invasive observation. In this study, we observed and analyzed mammalian cell structure and behaviors using 3D-OWFM. The 3D-OWFM revealed the intrinsic structure of the cells, including the cytoplasm and nucleus, with high clarity. The optical path difference (OPD) intensity effectively highlighted nuclear complexity. Furthermore, time-lapse imaging captured cell division process through variations in OPD signal intensity. These findings indicate that 3D-OWFM has significant potential for cell observation, offering insights not attainable with conventional microscopes. Full article

Label-free, high-throughput, and 3D morphological analysis of blood cells remains a major challenge in biomedical optics. In this study, we investigate this issue using flow cytometry with digital holographic microscopy (DHM) to enable real-time, label-free imaging of red blood cells (RBCs) and blood coagulation structures (BCSs) without the need for staining or chemical pretreatment. We demonstrate an approach for the automated quantification and statistical characterization of these cells using quantitative phase information reconstructed from digital holograms. Although established image processing techniques such as phase unwrapping and segmentation are used, this study presents, to the best of our knowledge, the first statistical characterization of the 3D morphological features of BCSs. This is particularly useful in analyzing the heterogeneous and complex 3D structures of BCSs, which are difficult to assess using conventional microscopy. The results suggest that this DHM-based flow cytometry system provides a promising platform for non-invasive, real-time morphological evaluation of blood samples and has potential applications in hematological diagnostics and research related to blood coagulation. Full article

Background: A previous published Phase 2 trial using 2–4 doses of neoadjuvant cemiplimab in stage II–IV resectable cutaneous squamous cell carcinoma (CSCC) demonstrated that a complete pathological (pCR) rate of 51% and major pathological response (mPR) rate of 13% could be achieved with durable disease control. Methods: In this open-label, single-institution phase II trial (NCT05878288), patients with stage II–IV resectable CSCC received up to four doses of neoadjuvant cemiplimab prior to surgery. The primary endpoint of the study was to perform comprehensive molecular profiling. The focus of this report are the secondary clinical endpoints of pCR rate, mPR (defined as <10% viable tumour) rate, overall response rate (ORR) using Response Evaluation Criteria in Solid Tumours (RECIST) 1.1, immune-modified RECIST (imRECIST) and Immune PET Response Criteria in Solid Tumours (iPERCIST), disease-free survival (DFS), overall survival (OS), safety, and to describe changes in planned surgery. Results: Eleven patients were enrolled, with all proceeding with surgery. An ORR and pCR rate of 73% (8/11; 95% CI 0.39–0.93) was achieved, whilst 3/11 patients progressed on treatment. On pre-operative imaging, all 8/11 pCR patients demonstrated a partial response (RECIST 1.1), whilst 6/8 achieved a complete metabolic response and 2/8 a partial metabolic response (iPERCIST). Median follow-up was 10.2 (IQR 6.7–16.4) months. DFS was 91% (95% CI 0.57–1) and OS was 100% (95% CI 0.68–1), with one non-responder patient who developed recurrent locoregional and distant metastatic disease. There were no unexpected safety signals. Pathological features of response to neoadjuvant immunotherapy most commonly were granulomatous inflammation with keratin, fibrosis and inflammation. No cases with a dense inflammatory infiltrate were observed. Neoadjuvant immunotherapy did not impact the intra-operative planning and execution of surgery, but in the eight pCR cases, it reduced the extent of required surgery, whilst in the three non-responder cases, surgery was more extensive than originally planned. Conclusions: The DISCERN trial confirms that an excellent complete response rate can be achieved with four doses of neoadjuvant immunotherapy in stage II–IV CSCC. Proposed refinements to the pathological assessment of response and metabolic response criteria in CSCC for the neoadjuvant context are provided. Full article

Nitroxides are stable organic free radicals with a wide range of applications. They have found applications in chemistry, biochemistry, biophysics, molecular biology, and biomedicine as EPR/NMR imaging techniques. As spin labels and probes, they are used in electron paramagnetic resonance (EPR) spectroscopy in the study of proteins, lipids, nucleic acids, and enzymes, as well as for measuring oxygen concentration in cells and cellular organelles, as well as tissues and intracellular pH. Their unique redox properties have allowed them to be used as exogenous antioxidants. In this review, we have discussed the chemical properties of nitroxides and their antioxidant properties. Furthermore, we have considered their use as radioprotectors and protective agents in ischemia/reperfusion in vivo and in vitro. We also presented other applications of nitroxides in protecting cells and tissues from oxidative stress and in protein studies and discussed their use in EPR/MRI. Full article

Background: Accurate and rapid intraoperative tumor margin assessment remains a major challenge in surgical oncology. Current gold-standard methods, such as frozen section histology, are time-consuming, operator-dependent, and prone to misclassification, which limits their clinical utility. Objective: To develop and evaluate a novel hyperspectral imaging (HSI) workflow that integrates deep learning with three-dimensional (3D) tumor modeling for real-time, label-free tumor margin delineation in head and neck squamous cell carcinoma (HNSCC). Methods: Freshly resected HNSCC samples were snap-frozen and imaged ex vivo from multiple perspectives using a standardized HSI protocol, resulting in a 3D model derived from HSI. Each sample was serially sectioned, stained, and annotated by pathologists to create high-resolution 3D histological reconstructions. The volumetric histological models were co-registered with the HSI data (n = 712 Datacubes), enabling voxel-wise projection of tumor segmentation maps from the HSI-derived 3D model onto the corresponding histological ground truth. Three deep learning models were trained and validated on these datasets to differentiate tumor from non-tumor regions with high spatial precision. Results: This work demonstrates strong potential for the proposed HSI system, with an overall classification accuracy of 0.98 and a tumor sensitivity of 0.93, underscoring the system’s ability to reliably detect tumor regions and showing high concordance with histopathological findings. Conclusion: The integration of HSI with deep learning and 3D tumor modeling offers a promising approach for precise, real-time intraoperative tumor margin assessment in HNSCC. This novel workflow has the potential to improve surgical precision and patient outcomes by providing rapid, label-free tissue differentiation. Full article

Background/Objectives: Upregulation of phosphoglycerate mutase 5 (PGAM5) is correlated with reduced survival outcomes in hepatocellular carcinoma (HCC). PGAM5 knockdown or knockout attenuates HCC growth in in vitro and in vivo models. A novel small molecule inhibitor of PGAM5, LFHP-1c, has recently been characterized. The objective of this study was to determine if LFHP-1c effectively reduces HCC viability in cell models. Methods: The hepatoma and HCC cell lines, HepG2 and HuH7, respectively, were treated with LFHP-1c. Label-free imaging was used to quantify growth. Cellular viability and reactive oxygen species (ROS) production were measured using luminescent or fluorescent assays. Expression of antioxidant and metabolic proteins was measured by immunoblot. HepG2 and HuH7 PGAM5 knockout cell lines were used as negative controls. Results: Treatment with LFHP-1c reduced cell growth and viability in HepG2 and HuH7 cell lines. Reactive oxygen species production was upregulated in both wild-type and PGAM5 knockout cell lines following LFHP-1c exposure. Cell viability was reduced following LFHP-1c treatment in PGAM5 knockout cell lines. Conclusions: LFHP-1c reduces hepatoma and HCC viability and enhances ROS production, but these effects are independent of PGAM5. Full article

We propose a pulsed modulated digital holographic microscopy (PM-DHM) technique for the dynamic measurement of flowing microparticles in microfluidic systems. By digitally tuning the pulse width and the repetition rate of a laser source within a single-frame exposure, this method enables the recording of multiple images of flowing microparticles at different time points within a single hologram, allowing the quantification of velocity and acceleration. We demonstrate the feasibility of PM-DHM by measuring the velocity, acceleration, and forces exerted on PMMA microspheres and red blood cells flowing in microfluidic chips. Compared to traditional frame-sampling-based imaging methods, this technique has a much higher time resolution (in a range of microseconds) that is limited only by the pulse duration. This method demonstrates significant potential for high-throughput label-free flow cytometry detection and offers promising applications in drug development and cell analysis. Full article

Raman microspectroscopy is a powerful, label-free technique for the biochemical characterization of cells, but its complex spectral data require advanced computational methods for meaningful interpretation. Clustering analysis is widely used in spectroscopic imaging to extract meaningful biochemical information. Traditional methods, such as K-means clustering with Euclidean distance, often struggle to capture subtle spectral variations, leading to suboptimal segmentation. Alternative distance metrics, including cosine and Mahalanobis distances, have been explored to enhance cluster separability, yet challenges remain in distinguishing chemically relevant features while minimizing redundancy and noise. In this study, we introduce an asymmetric metric distance matrix with a tunable eccentricity parameter to improve clustering performance in Raman hyperspectral imaging. Our results demonstrate that suitable eccentricity values enhance the identification of subcellular structures while requiring fewer clusters than Euclidean-based approaches. Compared to polar metrics, the proposed asymmetric metric achieves better stability and reduced noise, leading to more accurate segmentation. Future research could explore its application in other clustering techniques and machine learning frameworks, as well as its application in broader spectral imaging techniques where the distance metric plays a fundamental role. Full article