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Anaplastic lymphoma kinase (ALK) is a tyrosine kinase receptor which has been implicated in numerous solid and hematologic cancers. ALK mutations are reported in about 5-7% of neuroblastoma cases but the ALK-positive percentage increases significantly in the relapsed patient population. Crizotinib, the first clinically approved ALK inhibitor for the treatment of ALK-positive lung cancer has had le
Tumors with anaplastic lymphoma kinase (ALK) fusion rearrangements, including non-small-cell lung cancer and anaplastic large cell lymphoma, are highly sensitive to ALK tyrosine kinase inhibitors (TKIs), underscoring the notion that such cancers are addicted to ALK activity. Although mutations in ALK are heavily implicated in childhood neuroblastoma, response to the ALK TKI crizotinib has been dis
Activating mutations in full length anaplastic lymphoma kinase (ALK) have been reported in neuroblastoma and in anaplastic thyroid cancer. ALK-L1198F and ALKG1201E mutations were originally identified in anaplastic thyroid cancer (ATC) and characterized as constitutively activating mutations. In this study, we employed in vitro cell culture assays together with biochemical and in vivo Drosophila a
Anaplastic lymphoma kinase (ALK) is a receptor tyrosine kinase (RTK) that is mutated in approximately 10% of pediatric neuroblastoma (NB). To shed light on ALK-driven signaling processes, we employed BioID-based in vivo proximity labeling to identify molecules that interact intracellularly with ALK. NB-derived SK-N-AS and SK-N-BE(2) cells expressing inducible ALK-BirA* fusion proteins were generat
High-risk neuroblastoma (NB) often involves MYCN amplification as well as mutations in ALK. Currently, high-risk NB presents significant clinical challenges, and additional therapeutic options are needed. Oncogenes like MYCN and ALK result in increased replication stress in cancer cells, offering therapeutically exploitable options. We have pursued phosphoproteomic analyses highlighting ATR activi
Our understanding of public support for climate policies predominantly stems from studies in the Global North and a focus on isolated policy types. Here, we examine how public support for four different climate policy types and the effect of ideological explanatory variables on such support vary among countries of the Global North and Global South. We surveyed representative samples of each three
Six novel Bifidobacterium strains H1HS16NT, Bin2N, Hma3N, H6bp22N, H1HS10N, and H6bp9N, were isolated from the honey stomach of Apis mellifera. Cells are Gram-positive, non-motile, non-sporulating, facultatively anaerobic, and fructose 6-phosphate phosphoketolase-positive. Optimal growth conditions occur at 37 °C in anaerobiosis in MRS medium added with 2 % fructose and 0.1 % L-cysteine. The 16S r
This article takes departure in the notion of intimacy to identify the critical dependencies with contemporary algorithms. The presented concept of algorithmic intimacies points to how contemporary life is premised on the co-habitation with algorithms which poses various challenges to tactical approaches against algorithmic forms of governance. The article argues that thinking through these algori
In contemporary society, big tech platforms have leveraged their ownership over global data infrastructures and have established powerful influence over the conditions of digitally mediated life. The ubiquity of platform-mediated information technology has engendered a growing sense of unease about surveillance and loss of personal autonomy. This awareness has motivated repeated calls for expandin
Discussions around digital technologies, new media, platforms and information have long centred on the protection of personal data and privacy. This timely volume extends the conversation to address fundamental societal and structural issues from three perspectives: people, practices and politics. Organised around an international collection of case studies, the book provides a valuable contributi
The increasing development and adaptation of synthetic data raises critical concerns about the perpetuation of datafication logics. In examining some of synthetic data’s core promises, this dialogue paper aims to uncover the potential harm of further de-politicizing synthetic data. With synthetic data, technological opportunities are introduced that promise to resolve a growing demand for data nee
In this chapter, I draw on the artwork LAUREN by Lauren Lee McCarthy and the theoretical ideas of algorithmic intimacies and datafication to reveal the messy contradictions of the datafied home. What I term as the concept of algorithmic intimacies is a way to think anew about the intimate relations between subjects, algorithms, and proximities in data.¹ As the analysis aims to surface, these messy
BACKGROUND: In 2013, it was discovered that a subset of the population in Ronneby, Sweden was exposed to high levels of perfluorinated compounds (PFAS) from drinking water that had been provided by the local Brantafors waterworks and was contaminated by fire-fighting foam from a nearby airport. The start and time-course of population exposures are not known.OBJECTIVE: To investigate the start of P
Historisk översikt över idealet om den flitiga kvinnan genom tiderna.
Ekonomihögskolan vid Lunds universitet har anmodats att lämna ett yttrande över Från överskottsmål till balansmål (SOU 2024:76). Remissyttrandet har utarbetats av Fredrik N G Andersson, Lars Jonung och Elias Bengtsson.
Today, the overwhelming majority of Internet of Things (IoT) and mobile edge devices have extreme resource limitations, e.g., in terms of computing, memory, and energy. As a result, training Deep Neural Networks (DNNs) using the complex Backpropagation (BP) algorithm on such edge devices presents a major challenge. Forward-only algorithms have emerged as more computation- and memory-efficient alte
Internet of Things (IoT) are one of the key enablers of personalized health. However, IoT devices often have stringent constraints in terms of resources, e.g., energy budget, and, therefore, limited possibilities to exploit the state-of-the-art Deep Neural Networks (DNNs). Energy-aware Neural Architecture Search (NAS) is proposed to tackle this challenge, by exploring lightweight DNN (DNN) archite
