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Background Endothelial dysfunction is a hallmark feature of cardiovascular disease (CVD), yet the underlying mechanisms are still poorly understood. This has impeded the development of effective therapies, particularly for peripheral artery disease. FK506-binding protein like (FKBPL) and its therapeutic peptide mimetic, AD-01, are crucial negative regulators of angiogenesis, however their roles in CVD are unknown. In this study, we aimed to elucidate the FKBPL-mediated mechanisms involved in regulating endothelial dysfunction induced by hypoxia or inflammation, and to determine whether AD-01 can effectively restore endothelial function under these conditions. Methods Hindlimb ischemia was induced in mice by ligating the proximal and distal ends of the right femoral artery, and, after three days, the gastrocnemius muscle was collected for immunofluorescence staining, and RNA extraction. A 3D in vitro microfluidics model was developed to determine the endothelial cell migration and impact of FKBPL following treatments with: (i) 24 µM FKBPL targeted siRNA, (ii) 1 mM hypoxia inducible factor (HIF-1)α activator (DMOG), (iii) 50% (v/v) macrophage conditioned media (MCM), ± 100 nM AD-01. Unbiased, untargeted proteomic analysis was conducted via LC-MS/MS to identify protein targets of AD-01. Results FKBPL expression is substantially downregulated in mice after hindlimb ischemia ( p  < 0.05, protein; p  < 0.001, mRNA), correlating with increased neovascularization and altered vascular adhesion molecule expression. In our real-time advanced 3D microfluidics model, hypoxia suppressed FKBPL ( p  < 0.05) and VE-cadherin ( p  < 0.001) expression, leading to increased endothelial cell number and migration ( p  < 0.001), which was restored by AD-01 treatment ( p  < 0.01). Under inflammatory conditions, FKBPL ( p  < 0.01) and HIF-1α ( p  < 0.05) expression was elevated, correlating with increased endothelial cell migration ( p  < 0.05). Unlike hypoxia, AD-01 did not influence endothelial cell migration under inflammatory conditions, but normalized FKBPL ( p  < 0.001), HIF-1α ( p  < 0.05) and CD31 ( P  < 0.05), expression, in 3D microfluidic cell culture. Proteomic analysis revealed that AD-01 treatment in hypoxia enhanced the abundance of tissue remodelling and vascular integrity proteins including collagen alpha-1(XIX) chain and junctional cadherin associated-5 (JCAD) proteins. Conclusions FKBPL represents an important novel mechanism in hypoxia and inflammation-induced angiogenesis. The FKBPL-based therapeutic peptide, AD-01, could be a viable treatment option for CVD-related endothelial cell dysfunction.

Opinion statement Prostate cancer (PCa) is the second most diagnosed malignant neoplasm and is one of the leading causes of cancer-related death in men worldwide. Despite significant advances in screening and treatment of PCa, given the heterogeneity of this disease, optimal personalized therapeutic strategies remain limited. However, emerging predictive and prognostic biomarkers based on individual patient profiles in combination with computer-assisted diagnostics have the potential to guide precision medicine, where patients may benefit from therapeutic approaches optimally suited to their disease. Also, the integration of genotypic and phenotypic diagnostic methods is supporting better informed treatment decisions. Focusing on advanced PCa, this review discusses polygenic risk scores for screening of PCa and common genomic aberrations in androgen receptor (AR), PTEN-PI3K-AKT, and DNA damage response (DDR) pathways, considering clinical implications for diagnosis, prognosis, and treatment prediction. Furthermore, we evaluate liquid biopsy, protein biomarkers such as serum testosterone levels, SLFN11 expression, total alkaline phosphatase (tALP), neutrophil-to-lymphocyte ratio (NLR), tissue biopsy, and advanced imaging tools, summarizing current phenotypic biomarkers and envisaging more effective utilization of diagnostic and prognostic biomarkers in advanced PCa. We conclude that prognostic and treatment predictive biomarker discovery can improve the management of patients, especially in metastatic stages of advanced PCa. This will result in decreased mortality and enhanced quality of life and help design a personalized treatment regimen.

Endothelial dysfunction is a hallmark feature of cardiovascular disease (CVD), yet the underlying mechanisms are still poorly understood. This has impeded the development of effective therapies, particularly for peripheral artery disease. FK506-binding protein like (FKBPL) and its therapeutic peptide mimetic, AD-01, are crucial negative regulators of angiogenesis, however their roles in CVD are unknown. In this study, we aimed to elucidate the FKBPL-mediated mechanisms involved in regulating endothelial dysfunction induced by hypoxia or inflammation, and to determine whether AD-01 can effectively restore endothelial function under these conditions. Hindlimb ischemia was induced in mice by ligating the proximal and distal ends of the right femoral artery, and, after three days, the gastrocnemius muscle was collected for immunofluorescence staining, and RNA extraction. A 3D in vitro microfluidics model was developed to determine the endothelial cell migration and impact of FKBPL following treatments with: (i) 24 µM FKBPL targeted siRNA, (ii) 1 mM hypoxia inducible factor (HIF-1)[alpha] activator (DMOG), (iii) 50% (v/v) macrophage conditioned media (MCM), ± 100 nM AD-01. Unbiased, untargeted proteomic analysis was conducted via LC-MS/MS to identify protein targets of AD-01. FKBPL expression is substantially downregulated in mice after hindlimb ischemia (p < 0.05, protein; p < 0.001, mRNA), correlating with increased neovascularization and altered vascular adhesion molecule expression. In our real-time advanced 3D microfluidics model, hypoxia suppressed FKBPL (p < 0.05) and VE-cadherin (p < 0.001) expression, leading to increased endothelial cell number and migration (p < 0.001), which was restored by AD-01 treatment (p < 0.01). Under inflammatory conditions, FKBPL (p < 0.01) and HIF-1[alpha] (p < 0.05) expression was elevated, correlating with increased endothelial cell migration (p < 0.05). Unlike hypoxia, AD-01 did not influence endothelial cell migration under inflammatory conditions, but normalized FKBPL (p < 0.001), HIF-1[alpha] (p < 0.05) and CD31 (P < 0.05), expression, in 3D microfluidic cell culture. Proteomic analysis revealed that AD-01 treatment in hypoxia enhanced the abundance of tissue remodelling and vascular integrity proteins including collagen alpha-1(XIX) chain and junctional cadherin associated-5 (JCAD) proteins. FKBPL represents an important novel mechanism in hypoxia and inflammation-induced angiogenesis. The FKBPL-based therapeutic peptide, AD-01, could be a viable treatment option for CVD-related endothelial cell dysfunction.

From the development of high-throughput imaging platforms that integrate machine learning algorithms for the analysis of 3D organoids and immune cell co-cultures, to the creation of novel software tools like Trapalyzer for the quantitative analysis of neutrophil extracellular trap formation, the advancements in precision microscopy are revolutionizing the way we study and understand complex biological systems across millions of cells, through 2D to 3D tissue spatial dimensions, incorporating temporal aspects. The integration of advanced imaging techniques, multiplex staining methods, and AI-driven analysis for patient samples, pre-clinical models and in vitro cell cultures is not only enhancing our ability to visualize and analyze biological structures with unprecedented precision but is also paving the way for significant advancements in personalized medicine and precision diagnostics. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Progress in cancer research is substantially dependent on innovative technologies that permit a concerted analysis of the tumor microenvironment and the cellular phenotypes resulting from somatic mutations and post-translational modifications. In view of a large number of genes, multiplied by differential splicing as well as post-translational protein modifications, the ability to identify and quantify the actual phenotypes of individual cell populations in situ, i.e., in their tissue environment, has become a prerequisite for understanding tumorigenesis and cancer progression. The need for quantitative analyses has led to a renaissance of optical instruments and imaging techniques. With the emergence of precision medicine, automated analysis of a constantly increasing number of cellular markers and their measurement in spatial context have become increasingly necessary to understand the molecular mechanisms that lead to different pathways of disease progression in individual patients. In this review, we summarize the joint effort that academia and industry have undertaken to establish methods and protocols for molecular profiling and immunophenotyping of cancer tissues for next-generation digital histopathology—which is characterized by the use of whole-slide imaging (brightfield, widefield fluorescence, confocal, multispectral, and/or multiplexing technologies) combined with state-of-the-art image cytometry and advanced methods for machine and deep learning.

The composition of the gut microbiome influences the clinical course after allogeneic hematopoietic stem cell transplantation (HSCT), but little is known about the relevance of skin microorganisms. In a single-center, observational study, we recruited a cohort of 50 patients before undergoing conditioning treatment and took both stool and skin samples up to one year after HSCT. We could confirm intestinal dysbiosis following HSCT and report that the skin microbiome is likewise perturbed in HSCT-recipients. Overall bacterial colonization of the skin was decreased after conditioning. Particularly patients that developed acute skin graft-versus-host disease (aGVHD) presented with an overabundance of Staphylococcus spp. In addition, a loss in alpha diversity was indicative of aGVHD development already before disease onset and correlated with disease severity. Further, co-localization of CD45+ leukocytes and staphylococci was observed in the skin of aGVHD patients even before disease development and paralleled with upregulated genes required for antigen-presentation in mononuclear phagocytes. Overall, our data reveal disturbances of the skin microbiome as well as cutaneous immune response in HSCT recipients with changes associated with cutaneous aGVHD.

Even in the era of precision medicine, with various molecular tests based on omics technologies available to improve the diagnosis process, microscopic analysis of images derived from stained tissue sections remains crucial for diagnostic and treatment decisions. Among other cellular features, both nuclei number and shape provide essential diagnostic information. With the advent of digital pathology and emerging computerized methods to analyze the digitized images, nuclei detection, their instance segmentation and classification can be performed automatically. These computerized methods support human experts and allow for faster and more objective image analysis. While methods ranging from conventional image processing techniques to machine learning-based algorithms have been proposed, supervised convolutional neural network (CNN)-based techniques have delivered the best results. In this paper, we propose a CNN-based dual decoder U-Net-based model to perform nuclei instance segmentation in hematoxylin and eosin (H&E)-stained histological images. While the encoder path of the model is developed to perform standard feature extraction, the two decoder heads are designed to predict the foreground and distance maps of all nuclei. The outputs of the two decoder branches are then merged through a watershed algorithm, followed by post-processing refinements to generate the final instance segmentation results. Moreover, to additionally perform nuclei classification, we develop an independent U-Net-based model to classify the nuclei predicted by the dual decoder model. When applied to three publicly available datasets, our method achieves excellent segmentation performance, leading to average panoptic quality values of 50.8%, 51.3%, and 62.1% for the CryoNuSeg, NuInsSeg, and MoNuSAC datasets, respectively. Moreover, our model is the top-ranked method in the MoNuSAC post-challenge leaderboard.

Neuroblastoma is the most common extracranial solid tumor of childhood, with heterogeneous clinical manifestations ranging from spontaneous regression to aggressive metastatic disease. The calcium-sensing receptor (CaSR) is a G protein-coupled receptor (GPCR) that senses plasmatic fluctuation in the extracellular concentration of calcium and plays a key role in maintaining calcium homeostasis. We have previously reported that this receptor exhibits tumor suppressor properties in neuroblastoma. The activation of CaSR with cinacalcet, a positive allosteric modulator of CaSR, reduces neuroblastoma tumor growth by promoting differentiation, endoplasmic reticulum (ER) stress and apoptosis. However, cinacalcet treatment results in unmanageable hypocalcemia in patients. Based on the bias signaling shown by calcimimetics, we aimed to identify a new drug that might exert tumor-growth inhibition similar to cinacalcet, without affecting plasma calcium levels. We identified a structurally different calcimimetic, AC-265347, as a promising therapeutic agent for neuroblastoma, since it reduced tumor growth by induction of differentiation, without affecting plasma calcium levels. Microarray analysis suggested biased allosteric modulation of the CaSR signaling by AC-265347 and cinacalcet towards distinct intracellular pathways. No upregulation of genes involved in calcium signaling and ER stress were observed in patient-derived xenografts (PDX) models exposed to AC-265347. Moreover, the most significant upregulated biological pathways promoted by AC-265347 were linked to RHO GTPases signaling. AC-265347 upregulated cancer testis antigens (CTAs), providing new opportunities for CTA-based immunotherapies. Taken together, this study highlights the importance of the biased allosteric modulation when targeting GPCRs in cancer. More importantly, the capacity of AC-265347 to promote differentiation of malignant neuroblastoma cells provides new opportunities, alone or in combination with other drugs, to treat high-risk neuroblastoma patients.

Nuclei instance segmentation can be considered as a key point in the computer-mediated analysis of histological fluorescence-stained (FS) images. Many computer-assisted approaches have been proposed for this task, and among them, supervised deep learning (DL) methods deliver the best performances. An important criterion that can affect the DL-based nuclei instance segmentation performance of FS images is the utilised image bit depth, but to our knowledge, no study has been conducted so far to investigate this impact. In this work, we released a fully annotated FS histological image dataset of nuclei at different image magnifications and from five different mouse organs. Moreover, by different pre-processing techniques and using one of the state-of-the-art DL-based methods, we investigated the impact of image bit depth (i.e., eight bits vs. sixteen bits) on the nuclei instance segmentation performance. The results obtained from our dataset and another publicly available dataset showed very competitive nuclei instance segmentation performances for the models trained with 8 bit and 16 bit images. This suggested that processing 8 bit images is sufficient for nuclei instance segmentation of FS images in most cases. The dataset including the raw image patches, as well as the corresponding segmentation masks is publicly available in the published GitHub repository.