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Dense and aligned Collagen I fibers are associated with collective cancer invasion led by protrusive tumor cells, leader cells. In some breast tumors, a population of cancer cells (basal-like cells) maintain several epithelial characteristics and express the myoepithelial/basal cell marker Keratin 14 (K14). Emergence of leader cells and K14 expression are regarded as interconnected events triggered by Collagen I, however the underlying mechanisms remain unknown. Using breast carcinoma organoids, we show that Collagen I drives a force-dependent loop, specifically in basal-like cancer cells. The feed-forward loop is centered around the mechanotransducer Yap and independent of K14 expression. Yap promotes a transcriptional program that enhances Collagen I alignment and tension, which further activates Yap. Active Yap is detected in invading breast cancer cells in patients and required for collective invasion in 3D Collagen I and in the mammary fat pad of mice. Our work uncovers an essential function for Yap in leader cell selection during collective cancer invasion.

Objectives: Minimal residual disease status in multiple myeloma is an important prognostic biomarker. Recently, personalized blood-based targeted mass spectrometry (MS-MRD) was shown to provide a sensitive and minimally invasive alternative to measure minimal residual disease. However, quantification of MS-MRD requires a unique calibrator for each patient. The use of patient-specific stable isotope labelled (SIL) peptides is relatively costly and time-consuming, thus hindering clinical implementation. Here, we introduce a simplification of MS-MRD by using an off-the-shelf calibrator. Methods: SILuMAB-based MS-MRD was performed by spiking a monoclonal stable isotope labeled IgG, SILuMAB-K1, in the patient serum. The abundance of both M-protein-specific peptides and SILuMAB-specific peptides were monitored by mass spectrometry. The relative ratio between M-protein peptides and SILuMAB peptides allowed for M-protein quantification. We assessed linearity, sensitivity and reproducibility of SILuMAB-based MS-MRD in longitudinally collected sera from the IFM-2009 clinical trial. Results: A linear dynamic range was achieved of over 5 log scales, allowing for M-protein quantification down to 0.001 g/L. The inter-assay CV of SILuMAB-based MS-MRD was on average 11 %. Excellent concordance between SIL- and SILuMAB-based MS-MRD was shown (R 2>0.985). Additionally, signal intensity of spiked SILuMAB can be used for quality control purpose to assess system performance and incomplete SILuMAB digestion can be used as quality control for sample preparation. Conclusions: Compared to SIL peptides, SILuMAB-based MS-MRD improves the reproducibility, turn-around-times and cost-efficacy of MS-MRD without diminishing its sensitivity and specificity. Furthermore, SILuMAB can be used as a MS-MRD quality control tool to monitor sample preparation efficacy and assay performance.

Objectives: Multiple myeloma (MM) is a plasma cell malignancy characterized by a monoclonal expansion of plasma cells that secrete a characteristic M-protein. This M-protein is crucial for diagnosis and monitoring of MM in the blood of patients. Recent evidence has emerged suggesting that N-glycosylation of the M-protein variable (Fab) region contributes to M-protein pathogenicity, and that it is a risk factor for disease progression of plasma cell disorders. Current methodologies lack the specificity to provide a site-specific glycoprofile of the Fab regions of M-proteins. Here, we introduce a novel glycoproteogenomics method that allows detailed M-protein glycoprofiling by integrating patient specific Fab region sequences (genomics) with glycoprofiling by glycoproteomics. Methods: Glycoproteogenomics was used for the detailed analysis of de novo N-glycosylation sites of M-proteins. First, Genomic analysis of the M-protein variable region was used to identify de novo N-glycosylation sites. Subsequently glycopeptide analysis with LC-MS/MS was used for detailed analysis of the M-protein glycan sites. Results: Genomic analysis uncovered a more than two-fold increase in the Fab Light Chain N-glycosylation of M-proteins of patients with Multiple Myeloma compared to Fab Light Chain N-glycosylation of polyclonal antibodies from healthy individuals. Subsequent glycoproteogenomics analysis of 41 patients enrolled in the IFM 2009 clinical trial revealed that the majority of the Fab N-glycosylation sites were fully occupied with complex type glycans, distinguishable from Fc region glycans due to high levels of sialylation, fucosylation and bisecting structures. Conclusions: Together, glycoproteogenomics is a powerful tool to study de novo Fab N-glycosylation in plasma cell dyscrasias.

With this article, I explore the connections between blockchain technology, coloniality, and decolonial practices. Drawing on Sylvia Wynter’s thought on the interdependent systems of colonialism, capitalism, and knowledge, as well as more recent work on the coloniality of digital technologies, I argue that blockchain-based systems reproduce certain dynamics at work in historical colonialism. Additionally, Wynter’s decolonial propositions provide a generative framework to understand countercultural practices with. Inspired by Wynter, Patricia de Vries explores the notion of “plot work as artistic praxis” to ask how artistic work, implicated as it is in capitalist logics, can create space for relating dierently in the context of the exploitations of those dominant logics. I apply this notion to examine how Decentralised Autonomous Organisations (DAOs) in the countercultural blockchain space might contribute to this praxis.

We examine the ideological differences in the debate surrounding large language models (LLMs) and AI regulation, focusing on the contrasting positions of the Future of Life Institute (FLI) and the Distributed AI Research (DAIR) institute. The study employs a humanistic HCI methodology, applying narrative theory to HCI-related topics and analyzing the political differences between FLI and DAIR, as they are brought to bear on research on LLMs. Two conceptual lenses, “existential risk” and “ongoing harm,” are applied to reveal differing perspectives on AI's societal and cultural significance. Adopting a longtermist perspective, FLI prioritizes preventing existential risks, whereas DAIR emphasizes addressing ongoing harm and human rights violations. The analysis further discusses these organizations’ stances on risk priorities, AI regulation, and attribution of responsibility, ultimately revealing the diverse ideological underpinnings of the AI and LLMs debate. Our analysis highlights the need for more studies of longtermism's impact on vulnerable populations, and we urge HCI researchers to consider the subtle yet significant differences in the discourse on LLMs.

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Item does not contain fulltext, OBJECTIVE: Fibroblast growth factor 21 (FGF21) is a peptide hormone synthesized by several organs and regulates, among others, energy homeostasis. In obesity, insulin resistance and type 2 diabetes (T2D), higher circulating FGF21 concentrations have been found. Temporal analyses in murine studies demonstrate that FGF21 increases before insulin resistance occurs. The current study aims to investigate in time-to-event analyses whether FGF21 may be an early biomarker in the development of T2D. RESEARCH DESIGN AND METHODS: Circulating FGF21 was measured using an immunoassay of the Mesoscale U-PLEX assay platform. The study outcome was incident T2D. Associations of circulating FGF21 concentration with T2D were quantified using Cox proportional hazards models with adjustments for potential confounders. RESULTS: We included 5244 participants aged 52 ± 12 years, of whom 50% were male. Median [interquartile range] circulating FGF21 concentration was 860 [525-1329] pg/mL. During 7.3 [6.1-7.7] years of follow-up, 299 (5.7%) participants developed T2D. In fully adjusted analyses, higher circulating FGF21 concentration was associated with an increased risk of incident T2D (hazard ratio per doubling: 1.26 [95% CI, 1.06-1.51]; P = 0.008), with effect modification by fasting plasma glucose, consistent with strengthening of the association at lower fasting glucose (interaction coefficient: -0.12; P = 0.022). CONCLUSION: Higher circulating FGF21 concentrations are independently associated with an increased risk of incident T2D in participants with a low fasting plasma glucose, making circulating FGF21 concentration a potential early biomarker for type 2 diabetes.

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Contains fulltext : 296018.pdf (Publisher’s version ) (Open Access), Mechanisms of infection and pathogenesis have predominantly been studied based on differential gene or protein expression. Less is known about posttranslational modifications, which are essential for protein functional diversity. We applied an innovative glycoproteomics method to study the systemic proteome-wide glycosylation in response to infection. The protein site-specific glycosylation was characterized in plasma derived from well-defined controls and patients. We found 3862 unique features, of which we identified 463 distinct intact glycopeptides, that could be mapped to more than 30 different proteins. Statistical analyses were used to derive a glycopeptide signature that enabled significant differentiation between patients with a bacterial or viral infection. Furthermore, supported by a machine learning algorithm, we demonstrated the ability to identify the causative pathogens based on the distinctive host blood plasma glycopeptide signatures. These results illustrate that glycoproteomics holds enormous potential as an innovative approach to improve the interpretation of relevant biological changes in response to infection.

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BACKGROUND: Differentiating between self-resolving viral infections and bacterial infections in children who are febrile is a common challenge, causing difficulties in identifying which individuals require antibiotics. Studying the host response to infection can provide useful insights and can lead to the identification of biomarkers of infection with diagnostic potential. This study aimed to identify host protein biomarkers for future development into an accurate, rapid point-of-care test that can distinguish between bacterial and viral infections, by recruiting children presenting to health-care settings with fever or a history of fever in the previous 72 h. METHODS: In this multi-cohort machine learning study, patient data were taken from EUCLIDS, the Swiss Pediatric Sepsis study, the GENDRES study, and the PERFORM study, which were all based in Europe. We generated three high-dimensional proteomic datasets (SomaScan and two via liquid chromatography tandem mass spectrometry, referred to as MS-A and MS-B) using targeted and untargeted platforms (SomaScan and liquid chromatography mass spectrometry). Protein biomarkers were then shortlisted using differential abundance analysis, feature selection using forward selection-partial least squares (FS-PLS; 100 iterations), along with a literature search. Identified proteins were tested with Luminex and ELISA and iterative FS-PLS was done again (25 iterations) on the Luminex results alone, and the Luminex and ELISA results together. A sparse protein signature for distinguishing between bacterial and viral infections was identified from the selected proteins. The performance of this signature was finally tested using Luminex assays and by calculating disease risk scores. FINDINGS:376 children provided serum or plasma samples for use in the discovery of protein biomarkers. 79 serum samples were collected for the generation of the SomaScan dataset, 147 plasma sample

Background: Poor prognosis in colon cancer is associated with a high content of cancer-associated fibroblasts (CAFs) and an immunosuppressive tumor microenvironment. The relationship between these two features is incompletely understood. Here, we aimed to generate a model system for studying the interaction between cancer cells and CAFs and their effect on immune-related cytokines and T cell proliferation. Methods: CAFs were isolated from colon cancer liver metastases and were immortalized to prolong lifespan and improve robustness and reproducibility. Established medium and matrix compositions that support the growth of patient-derived organoids were adapted to also support CAF growth. Changes in growth pattern and cellular re-organization were assessed by confocal microscopy, live cell imaging, and immunofluorescence. Single cell RNA sequencing was used to study CAF/organoid co-culture-induced phenotypic changes in both cell types. Conditioned media were used to quantify the production of immunosuppressive factors and to assess their effect on T cell proliferation. Results: We developed a co-culture system in which colon cancer organoids and CAFs spontaneously organize into superstructures with a high capacity to contract and stiffen the extracellular matrix (ECM). CAF-produced collagen IV provided a basement membrane supporting cancer cell organization into glandular structures, reminiscent of human cancer histology. Single cell RNA sequencing analysis showed that CAFs induced a partial epithelial-to-mesenchymal-transition in a subpopulation of cancer cells, similar to what is observed in the mesenchymal-like consensus molecular subtype 4 (CMS4) colon cancer. CAFs in co-culture were characterized by high expression of ECM components, ECM-remodeling enzymes, glycolysis, hypoxia, and genes involved in immunosuppression. An expression signature derived from CAFs in co-culture identified a subpopulation of glycolytic myofibroblasts specifically residing in CMS1 an

The main cause of cancer lethality is metastasis. Throughout cancer progression cells are affected by mechanical forces. Forces like tension, compression and shear of fluid flow can be generated and sensed by cells (mechanosensing), and can biochemically be transduced (mechanotransduction), leading to alterations in cellular fate and behavior. In tumors, changes can occur in how cells sense forces in the environment, or the environment can change. Tumor cells are affected by changes in extracellular matrix (ECM) composition and mechanical strength, of which these changes can also be induced by the tumor itself or tumor-recruited stromal cells. Mechanical forces and sensing of them are involved in many steps of metastasis, from the local environment of the primary tumor, to dissemination through circulation, re-entry into tissues and colonization of secondary sites. In this review we discuss our current understanding of the contribution of mechanosensing and mechanotransduction at several steps of the metastatic cascade, including mechanical changes prior to colonization caused by cancer, various pathologies and aging.

Background: Differentiating between self-resolving viral infections and bacterial infections in children who are febrile is a common challenge, causing difficulties in identifying which individuals require antibiotics. Studying the host response to infection can provide useful insights and can lead to the identification of biomarkers of infection with diagnostic potential. This study aimed to identify host protein biomarkers for future development into an accurate, rapid point-of-care test that can distinguish between bacterial and viral infections, by recruiting children presenting to health-care settings with fever or a history of fever in the previous 72 h. Methods: In this multi-cohort machine learning study, patient data were taken from EUCLIDS, the Swiss Pediatric Sepsis study, the GENDRES study, and the PERFORM study, which were all based in Europe. We generated three high-dimensional proteomic datasets (SomaScan and two via liquid chromatography tandem mass spectrometry, referred to as MS-A and MS-B) using targeted and untargeted platforms (SomaScan and liquid chromatography mass spectrometry). Protein biomarkers were then shortlisted using differential abundance analysis, feature selection using forward selection-partial least squares (FS-PLS; 100 iterations), along with a literature search. Identified proteins were tested with Luminex and ELISA and iterative FS-PLS was done again (25 iterations) on the Luminex results alone, and the Luminex and ELISA results together. A sparse protein signature for distinguishing between bacterial and viral infections was identified from the selected proteins. The performance of this signature was finally tested using Luminex assays and by calculating disease risk scores. Findings: 376 children provided serum or plasma samples for use in the discovery of protein biomarkers. 79 serum samples were collected for the generation of the SomaScan dataset, 147 plasma samples for the MS-A dataset, and 150 plasma samples for the MS

Mechanisms of infection and pathogenesis have predominantly been studied based on differential gene or protein expression. Less is known about posttranslational modifications, which are essential for protein functional diversity. We applied an innovative glycoproteomics method to study the systemic proteome-wide glycosylation in response to infection. The protein site-specific glycosylation was characterized in plasma derived from well-defined controls and patients. We found 3862 unique features, of which we identified 463 distinct intact glycopeptides, that could be mapped to more than 30 different proteins. Statistical analyses were used to derive a glycopeptide signature that enabled significant differentiation between patients with a bacterial or viral infection. Furthermore, supported by a machine learning algorithm, we demonstrated the ability to identify the causative pathogens based on the distinctive host blood plasma glycopeptide signatures. These results illustrate that glycoproteomics holds enormous potential as an innovative approach to improve the interpretation of relevant biological changes in response to infection.

Thinking about care in the organization of an ecology is central to the interdisciplinary research group Care Ecologies; found during a lockdown in the spring of 2021 and hosted by ARIAS Platform for Research Through the Arts and Sciences in Amsterdam. In Towards Becoming an Ecology of Care group members Valentina Curandi, Inte Gloerich, Ania Molenda, Maaike Muntinga, Natalia Sanchez Querubin, Nienke Scholts and Marloeke van der Vlugt, offer an initial articulation on their approaches and principles – performative practices, reflection, speculations - of what an ecology of care could be. While each bringing in different understandings of care, staying with those differences shaped the ways in which the agenda of the research group has been (un)settled. To exchange knowledge and experiences, the group uses various on- and off-line frameworks, like presentations and practice sessions. Exploring how activities that sustain a research group – coordinating, meeting, writing and documenting – may be done with care, this paper attempts to present a speculative proposition for functioning as a research ecology on and around care. Bringing into focus what care can do, while being attentive to what is neglected. This is not only done in writing but also becomes visible in the accompanying images compiled of material and immaterial memories. It is an ongoing process, for which the writing of this paper became a catalyst for reflection. While not aiming for clear answers the authors invite themselves and others to become more aware, devising and testing work strategies for care-based practices.

Talking about money can be difficult; designing with it, harder still. Though design is increasingly ‘value-centred’, this theme-track proposes the need for critical attention to how we actually represent, transact and exchange what we value. In this editorial, we offer some background to the topic, describe potential areas of develop- ment for design researchers and practitioners, and introduce the papers presented through this theme at DRS 2022.

Contains fulltext : 253148.pdf (Publisher’s version ) (Open Access)

Contains fulltext : 252075.pdf (Publisher’s version ) (Open Access), Gastric cancer is globally the fourth leading cause of cancer-related deaths. Patients with diffuse-type gastric cancer (DGC) particularly have a poor prognosis that only marginally improved over the last decades, as conventional chemotherapies are frequently ineffective and specific therapies are unavailable. Early-stage DGC is characterized by intramucosal lesions of discohesive cells, which can be present for many years before the emergence of advanced DGC consisting of highly proliferative and invasive cells. The mechanisms underlying the key steps of DGC development and transition to aggressive tumors are starting to emerge. Novel mouse and organoid models for DGC, together with multi-omic analyses of DGC tumors, revealed contributions of both tumor cell-intrinsic alterations and gradual changes in the tumor microenvironment to DGC progression. In this review, we will discuss how these recent findings are leading towards an understanding of the cellular and molecular mechanisms responsible for DGC initiation and malignancy, which may provide opportunities for targeted therapies.

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Contains fulltext : 252075.pdf (Publisher’s version ) (Open Access), Gastric cancer is globally the fourth leading cause of cancer-related deaths. Patients with diffuse-type gastric cancer (DGC) particularly have a poor prognosis that only marginally improved over the last decades, as conventional chemotherapies are frequently ineffective and specific therapies are unavailable. Early-stage DGC is characterized by intramucosal lesions of discohesive cells, which can be present for many years before the emergence of advanced DGC consisting of highly proliferative and invasive cells. The mechanisms underlying the key steps of DGC development and transition to aggressive tumors are starting to emerge. Novel mouse and organoid models for DGC, together with multi-omic analyses of DGC tumors, revealed contributions of both tumor cell-intrinsic alterations and gradual changes in the tumor microenvironment to DGC progression. In this review, we will discuss how these recent findings are leading towards an understanding of the cellular and molecular mechanisms responsible for DGC initiation and malignancy, which may provide opportunities for targeted therapies.

Contains fulltext : 283000.pdf (Publisher’s version ) (Open Access)

Item does not contain fulltext, BACKGROUND: Inappropriate antibiotic prescribing often occurs in children with self-limiting respiratory tract infections, contributing to antimicrobial resistance. It has been suggested that rapid viral testing can reduce inappropriate antibiotic prescribing. We aimed to assess the association between rapid viral testing at the Emergency Department (ED) and antibiotic prescription in febrile children. METHODS: This study is part of the MOFICHE study, which is an observational multicenter study including routine data of febrile children (0-18 years) attending 12 European EDs. In children with respiratory symptoms visiting 6 EDs equipped with rapid viral testing, we performed multivariable logistic regression analysis regarding rapid viral testing and antibiotic prescription adjusted for patient characteristics, disease severity, diagnostic tests, focus of infection, admission, and ED. RESULTS: A rapid viral test was performed in 1061 children (8%) and not performed in 11,463 children. Rapid viral test usage was not associated with antibiotic prescription (aOR 0.9, 95% CI: 0.8-1.1). A positive rapid viral test was associated with less antibiotic prescription compared with children without test performed (aOR 0.6, 95% CI: 0.5-0.8), which remained significant after adjustment for CRP and chest radiograph result. Twenty percent of the positively tested children received antibiotics. A negative rapid viral test was not associated with antibiotic prescription (aOR 1.2, 95% CI: 1.0-1.4). CONCLUSIONS: Rapid viral test usage did not reduce overall antibiotic prescription, whereas a positive rapid viral test did reduce antibiotic prescription at the ED. Implementation of rapid viral testing in routine emergency care and compliance to the rapid viral test outcome will reduce inappropriate antibiotic prescribing at the ED.

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© 2022 The Author(s), Epithelial cell divisions are coordinated with cell loss to preserve epithelial integrity. However, how epithelia adapt their rate of cell division to changes in cell number, for instance during homeostatic turnover or wounding, is not well understood. Here, we show that epithelial cells sense local cell density through mechanosensitive E-cadherin adhesions to control G2/M cell-cycle progression. As local cell density increases, tensile forces on E-cadherin adhesions are reduced, which prompts the accumulation of the G2 checkpoint kinase Wee1 and downstream inhibitory phosphorylation of Cdk1. Consequently, dense epithelia contain a pool of cells that are temporarily halted in G2 phase. These cells are readily triggered to divide following epithelial wounding due to the consequent increase in intercellular forces and resulting degradation of Wee1. Our data collectively show that epithelial cell division is controlled by a mechanical G2 checkpoint, which is regulated by cell-density-dependent intercellular forces sensed and transduced by E-cadherin adhesions., Peer Reviewed, Postprint (published version)