Journal of Histochemistry & Cytochemistry

Pediatric sarcomas comprise approximately 10% of all childhood solid malignancies and are characterized by distinct genetic and proteomic alterations that have potential diagnostic, prognostic, and therapeutic significance. We have utilized digital spatial profiling (DSP) to identify protein expression in pediatric Ewing sarcoma (ES), Osteosarcoma (OS), Alveolar rhabdomyosarcoma (ARMS), and Embryonal rhabdomyosarcoma (ERMS), in association with clinical outcomes. Formalin-fixed, paraffin-embedded sections from a tissue microarray block containing eight ES, eight OS, five ARMS, and three ERMS cases were subjected to proteomic DSP on a GeoMx NanoString platform yielding information on expression of 580 proteins. Proteins related to epigenetic regulation, signaling pathways, and mesenchymal differentiation were broadly expressed across all tumor types. Tumor-specific protein profiles were defined based on highly expressed proteins. Differentially expressed proteins include Cyclin D1 in ES, S100A4 in OS and IKKi/IKKe in ARMS and ERMS. Immunohistochemical validation confirmed variable expression of H3K27me3 across the tumors, and elevated expression of Cyclin D1 in ES and S100 in OS. These findings underscore the utility of DSP as a high-resolution proteomic tool for the identification of clinically relevant biomarkers in pediatric sarcomas. The results provide a foundation for further investigation of candidate proteins with potential diagnostic, prognostic, and therapeutic applications:

Artificial intelligence (AI) is transforming how cell biologists generate, analyze, and interpret visual data. Automated pipelines and large-scale image analysis increase throughput and reproducibility, yet they also modify how visual evidence is validated and trusted. This Perspective examines the conceptual implications of this shift, arguing that the integration of AI into imaging demands rather than replaces human morphological expertise. We distinguish between three conceptually distinct phenomena: (1) automation of acquisition, (2) AI-driven interpretation, and (3) the emergence of synthetic images generated without experimental basis. Through examples ranging from classical morphological misinterpretations to the rise of generative models, we show how both human and algorithmic systems can distort meaning when interpretation is detached from context. While AI can match or surpass human precision, metavisual competence remains essential to distinguish signals from artifacts. The current challenge is not technological but scientific: to ensure that computational power and human insight co-evolve toward reliable visual knowledge. We call for a renewed education in critical visual literacy, formal recognition of imaging specialists, and transparent standards of image provenance, such as the publication of raw instrument metadata. Preserving interpretative competence is crucial for the integrity of visual evidence in biomedical science:

Collagen has a major role in the structural organization of tendons. Picrosirius red (PSR) staining viewed under polarized light microscopy is the standard method to evaluate the organization of collagen fibers in tissues. It is also used to distinguish between type I and type III collagen in tissue sections. However, accurate analysis and interpretation of PSR images are challenging because of technical factors and historical misconceptions. The aim of this study was to clarify whether collagen types I and III can be distinguished by PSR staining in rat Achilles tendons, using double immunohistochemistry as the positive control. Our findings showed that PSR staining viewed with polarized light microscopy was suitable for qualitative and quantitative assessment of total collagen but was not able to distinguish collagen types. We found it critical to use a polarizing microscope equipped with a rotating stage; tendon section orientation at 45° with respect to crossed polarizers was optimal for the qualitative and quantitative assessment of collagen organization. Immunohistochemistry was superior to PSR staining for detection of collagen type III. We also compared formalin and Bouin solution as fixatives. Both produced similar birefringence, but formalin-fixed tendons provided higher quality histological detail with both hematoxylin–eosin and immunostaining: