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Abstract: Purpose We have previously identified insulin-like growth factor 2 (IGF2) and insulin-like growth factor 1 receptor (IGF1R) as essential proteins for tip cell maintenance and sprouting angiogenesis. In this study, we aim to identify other IGF family members involved in endothelial sprouting angiogenesis. Methods Effects on sprouting were analyzed in human umbilical vein endothelial cells (HUVECs) using the spheroid-based sprouting model, and were quantified as mean number of sprouts per spheroid and average sprout length. RNA silencing technology was used to knockdown gene expression. Recombinant forms of the ligands (IGF1 and IGF2, insulin) and the IGF-binding proteins (IGFBP) 3 and 4 were used to induce excess effects. Effects on the tip cell phenotype were analyzed by measuring the fraction of CD34+ tip cells using flow cytometry and immunohistochemistry in a 3D angiogenesis model. Experiments were performed in the presence and absence of serum. Results Knockdown of IGF2 inhibited sprouting in HUVECs, in particular when cultured in the absence of serum, suggesting that components in serum influence the signaling of IGF2 in angiogenesis in vitro. We then determined the effects of IGFBP3 and IGFBP4, which are both present in serum, on IGF2-IGF1R signaling in sprouting angiogenesis in the absence of serum: knockdown of IGFBP3 significantly reduced sprouting angiogenesis, whereas knockdown of IGFBP4 resulted in increased sprouting angiogenesis in both flow cytometry analysis and immunohistochemical analysis of the 3D angiogenesis model. Other IGF family members except INSR did not affect IGF2-IGF1R signaling. Conclusions Serum components and IGF binding proteins regulate IGF2 effects on sprouting angiogenesis. Whereas IGFBP3 acts as co-factor for IGF2-IGF1R binding, IGFBP4 inhibits IGF2 signaling.
Keywords: Angiogenesis, tip cells, IGF2, IGF binding proteins, endothelial cells, cultured cells, endothelial growth factors
Published in DiRROS: 23.07.2024; Views: 307; Downloads: 233
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Abstract: Most women with epithelial ovarian cancer (EOC) suffer from peritoneal carcinomatosis upon first clinical presentation. Extensive peritoneal carcinomatosis has a poor prognosis and its pathophysiology is not well understood. Although treatment with systemic intravenous chemotherapy is often initially successful, peritoneal recurrences occur regularly. We hypothesized that insufficient or poorly-perfused microvasculature may impair the therapeutic efficacy of systemic intravenous chemotherapy but may also limit expansive and invasive growth characteristic of peritoneal EOC metastases. In 23 patients with advanced EOC or suspicion thereof, we determined the angioarchitecture and perfusion of the microvasculature in peritoneum and in peritoneal metastases using incident dark field (IDF) imaging. Additionally, we performed immunohistochemical analysis and 3-dimensional (3D) whole tumor imaging using light sheet fluorescence microscopy of IDF-imaged tissue sites. In all metastases, microvasculature was present but the angioarchitecture was chaotic and the vessel density and perfusion of vessels was significantly lower than in unaffected peritoneum. Immunohistochemical analysis showed expression of vascular endothelial growth factor and hypoxia inducible factor 1α, and 3D imaging demonstrated vascular continuity between metastases and the vascular network of the peritoneum beneath the elastic lamina of the peritoneum. We conclude that perfusion of the microvasculature within metastases is limited, which may cause hypoxia, affect the behavior of EOC metastases on the peritoneum and limit the response of EOC metastases to systemic treatment.
Keywords: microvasculature, microcirculation, EOC, peritoneal carcinomatosa, incident dark feld imaging
Published in DiRROS: 23.07.2024; Views: 370; Downloads: 248
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Abstract: Understanding how organisms adapt to complex environments is a central goal of evolutionary biology and ecology. This issue is of special interest in the current era of rapidly changing climatic conditions. Here, we investigate clinal variation and plastic responses in life history, morphology and physiology in the butterfly Pieris napi along a pan‐European gradient by exposing butterflies raised in captivity to different temperatures. We found clinal variation in body size, growth rates and concomitant development time, wing aspect ratio, wing melanization and heat tolerance. Individuals from warmer environments were more heat‐tolerant and had less melanised wings and a shorter development, but still they were larger than individuals from cooler environments. These findings suggest selection for rapid growth in the warmth and for wing melanization in the cold, and thus fine‐tuned genetic adaptation to local climates. Irrespective of the origin of butterflies, the effects of higher developmental temperature were largely as expected, speeding up development; reducing body size, potential metabolic activity and wing melanization; while increasing heat tolerance. At least in part, these patterns likely reflect adaptive phenotypic plasticity. In summary, our study revealed pronounced plastic and genetic responses, which may indicate high adaptive capacities in our study organism. Whether this may help such species, though, to deal with current climate change needs further investigation, as clinal patterns have typically evolved over long periods.
Published in DiRROS: 23.07.2024; Views: 304; Downloads: 147
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Abstract: Virtual reality (VR) technology is often referred to as the ‘ultimate empathy machine’ due to its capability to immerse users in alternate perspectives and environments beyond their immediate physical reality. In this study, participants will be immersed in 3-dimensional 360˚ VR videos where actors express different emotions (sadness, happiness, anger, and anxiousness). The primary objective is to investigate the potential relationship between participants’ empathy levels and the changes in their physiological attributes. The empathy levels will be self-reported with questionnaires, and physiological attributes will be measured using different sensors. The main outcome of the study will be a machine learning model to predict a person’s empathy level based on their physiological responses while watching VR videos. Despite the existence of established methodologies and metrics in research and clinical domains, our aim is to contribute to addressing the gap of a universally accepted “gold standard” for assessing empathy. Additionally, we expect to deepen our understanding of the relationship between different emotions and psychological attributes, gender differences in empathy, and the impact of narrative context on empathic responses.
Published in DiRROS: 23.07.2024; Views: 344; Downloads: 143
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Abstract: Setting up a reliable electric propulsion system in the automotive sector requires an intelligent condition monitoring device capable of reliably assessing the state and the health of the electric motor. To allow for a massive integration of such monitoring devices, they must be inexpensive and small. These requirements limit their accuracy. However, we show in this chapter that these limitations can be significantly reduced by appropriate processing of the sensor data. We have used machine learning models (random forest and XGBoost) to transform very noisy motor winding insulation resistance measurements made by a low-cost device into a much more reliable value that can compete with measurements made by a high-priced state-of-the-art measurement system. The proposed method is an important building block for a future smart condition monitoring system and enables a cost-effective and accurate assessment of the condition of electric motor health in connection with the condition of their winding insulation.
Keywords: machine learning models, low-cost device, electric motor
Published in DiRROS: 23.07.2024; Views: 318; Downloads: 137
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