Laboratory Investigation最新文献

Diagnosing myeloproliferative neoplasms (MPNs) is challenging due to the nuanced and overlapping clinical manifestations of the various subtypes. Precise classification is essential for effective treatment and management of these disorders. This study introduces a novel Dual-Stream Deep Feature and Cell Phenotype Fusion Model (DS-DFCPF) to improve the diagnosis of MPNs. The model integrates deep learning features from whole-slide images (WSIs) with detailed phenotypic data extracted from cellular components, particularly megakaryocytes, which are pivotal in MPN pathology. The DS-DFCPF employs a bifurcated approach, wherein one stream processes deep features from segmented WSIs using convolutional neural networks (CNNs), and the other analyzes cell phenotype characteristics using advanced image processing techniques. The outputs of both streams are fused, significantly enhancing the model's capacity to discriminate between MPN subtypes. The efficacy of this model was rigorously evaluated through a series of experiments using a dataset comprising 411 patient samples annotated with detailed clinical and histopathological information. Our results reveal that the DS-DFCPF significantly outperforms previous diagnostic models, offering a reliable and reproducible tool for MPN subtype differentiation. This model offers a promising new tool for pathologists and clinicians, providing a more accurate, efficient, and automated approach to diagnosing MPNs, thereby facilitating timely and tailored therapeutic interventions. This study not only underscores the potential of integrating multiple data streams in medical diagnostics but also establishes a benchmark for future innovations in the field of computational pathology.

Abnormal signal transduction within glandular epithelial cells is a pathological feature of advanced Sjögren syndrome (SS). Preliminary investigations have demonstrated that the progression of SS is marked by a substantial accumulation of metabolic byproducts, notably lactate, in the salivary glands. This study corroborated the accumulation of lactate within the salivary glands by analyzing peripheral blood and lip gland tissue samples from patients with SS in addition to constructing an experimental Sjögren syndrome mouse model. Lactate exacerbates the severity of xerostomia and the extent of immune cell infiltration in the salivary glands. Moreover, the ability of lactate transport proteins, including MCT1 and SLC5A12, to regulate the transport of lactate in and out of cells, thereby facilitating the process of histone lactylation, was confirmed via experimental methodologies such as western blotting. Preliminary findings derived from chromatin immunoprecipitation sequencing and Kyoto Encyclopedia of Genes and Genomes enrichment analysis indicated that H3K18la directly influences the downstream autophagy signaling pathway. Subsequent validation using western blot analysis revealed associations between various key regulatory and autophagy-related proteins and the lactate microenvironment. Moreover, the relationship between apoptosis and autophagy levels was elucidated through annexin/propidium iodide staining. Flow cytometry confirmed that lactate levels regulate the level of the autophagy marker protein LC3B-II. Transmission electron microscopy confirmed an increase in the number of autophagosomes in a high-lactate environment. These findings indicate that lactate exacerbates SS symptoms and the degree of immune cell infiltration and that H3K18la directly regulates the autophagy signaling pathway within glandular epithelial cells, thus contributing to the progression of SS.

The complement system plays a central role in glomerular disease development and resolution. Currently, renal biopsies assess the presence of complement through limited immunofluorescence stains (C3 and C1q). With >50 total proteins and fragments involved in the complement cascade, this method offers a severely limited view into the mechanisms of tissue injury orchestrated by complement activation. A more comprehensive evaluation of complement components will advance the understanding of complement involvement in glomerular diseases by allowing for multiplex detection of complement cascade proteins and activation products, which can be achieved by mass spectrometry (MS). Data-independent acquisition MS was performed following extraction of proteins from tissue lysates, microdissected glomeruli, or protein G immunoprecipitates from residual kidney biopsy tissue. Cohorts included patients with lupus nephritis, membranous nephropathy and membranous lupus nephritis, diabetic glomerulosclerosis, C3 glomerulonephritis, and control biopsies. Abundances of complement components by MS correlated with immunofluorescence intensity of C1q on kidney biopsies. Increased abundances of complement classical, lectin, final common pathway, and regulatory proteins correlated with disease activity in lupus nephritis. Complement protein abundances of final common pathway components were heterogeneous between patients with the same disease state, including diabetic glomerulosclerosis and various forms of proliferative glomerulonephritis. Finally, complement proteins and their activation products can be mapped to determine which components are impacted among individuals and between disease states. In conclusion, complement proteins and some of their split products can be reliably measured by MS of kidney biopsies, which can enhance our understanding of complement-mediated tissue injury and heterogeneity in glomerular diseases.

The syncytial variant of nodular sclerosis classical Hodgkin lymphoma (SV-NSCHL) is associated with inferior outcomes. However, the complexity of tumor microenvironment (TME) in SV-NSCHL is poorly understood. Therefore, we aimed to depict and compare the TME among SV-NSCHL and common nodular sclerosis classical Hodgkin lymphoma (cNSCHL). Using Xenium In Situ spatial transcriptomics on 20 regions of interest from 10 specimens (4 cNSCHL, 4 SV-NSCHL, and 2 reactive lymph nodes), we profiled 317,762 cells to map tumor intrinsic characteristics and spatially resolved immune ecosystems. The paternally expressed gene (PEG10) was among the top unregulated genes of Hodgkin and Reed-Sternberg (HRS) cells in SV-NSCHL. Immunohistochemistry (IHC) analysis in an independent cohort (n = 121) confirmed significantly higher PEG10 protein expression in HRS cells from SV-NSCHL and association with proliferation hallmarks. Patients with high PEG10 expression in NSCHL exhibited inferior progression-free survival (PFS), and multivariate analysis identified PEG10 as an independent prognostic factor. Besides, SV-NSCHL demonstrated a distinctly immunosuppressive microenvironment characterized by depletion and functional dampening of CD8⁺ T cells, expansion and higher immunosuppression scores of regulatory T cells (Tregs), altered B cell dynamics, and enrichment of M2-like macrophages with reduced phagocytosis and antigen presentation. Furthermore, although overall ligand-receptor crosstalk was attenuated in SV-NSCHL, specific inhibitory ligand-receptor interactions were preserved and upregulated between HRS cells and Tregs. Collectively, our study provided the first comprehensive spatial atlas of SV-NSCHL. It implicated PEG10 as a candidate contributor to HRS cell proliferation and identified actionable immune evasion signatures, offering a roadmap for targeted therapeutic interventions.