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DNA demethylation-mediated downregulation of MNX1 in acute myeloid leukemia: ACUTE MYELOID LEUKEMIA
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The magnetic and spin-down properties of slowly rotating fully convective M dwarfs
Get PDFThe evolution of the magnetism, winds, and rotation of low-mass stars are all linked. One of the most common ways to probe the magnetic properties of low-mass stars is with the Zeeman–Doppler imaging (ZDI) technique. The magnetic properties of partially convective stars has been relatively well explored with the ZDI technique, but the same is not true of fully convective stars. In this work, we analyse a sample of stars that have been mapped with ZDI. Notably, this sample contains a number of slowly rotating fully convective M dwarfs whose magnetic fields were recently reconstructed with ZDI. We find that the dipolar, quadrupolar, and octupolar field strengths of the slowly rotating fully convective stars do not follow the same Rossby number scaling in the unsaturated regime as partially convective stars. Based on these field strengths, we demonstrate that previous estimates of spin-down torques for slowly rotating fully convective stars could have been underestimated by an order of magnitude or more. Additionally, we also find that fully convective and partially convective stars fall into distinct sequences when comparing their poloidal and toroidal magnetic energies
Second cancers in 475 000 women with early invasive breast cancer diagnosed in England during 1993-2016: population based observational cohort study
Get PDFObjective: To describe long term risks of second non-breast primary cancers and contralateral breast cancers among women with early invasive breast cancer after primary surgery. Design: Population based observational cohort study. Setting: Routinely collected data from the National Cancer Registration and Analysis Service for England. Participants: All 476 373 women with breast cancer as their first invasive (index) cancer registered in England from January 1993 to December 2016 with follow-up until October 2021. Main outcome measures: Rates and cumulative risks of subsequent primary cancers, compared with those occurring in the general population; associations with characteristics of patients, index tumours, and adjuvant treatments. Results: Although 64 747 women developed a second primary cancer, the absolute excess risks compared with risks in the general population were small. By 20 years, 13.6% (95% confidence interval 13.5% to 13.7%) of women had developed a non-breast cancer, 2.1% (2.0% to 2.3%) more than expected in the general population, and 5.6% (5.5% to 5.6%) had developed a contralateral breast cancer, 3.1% (3.0% to 3.2%) more than expected. The absolute excess risk of contralateral breast cancer was greater in younger than in older women. Among specific types of non-breast cancer, the largest 20 year absolute excess risks were for uterine and lung cancers. Although for cancers of the uterus, soft tissue, bones and joints, and salivary glands, as well as acute leukaemias, standardised incidence ratios exceeded those of the general population by a factor of at least 1.5, absolute excess risks at 20 years were <1% for every individual non-breast cancer type. When patients were categorised according to adjuvant treatment, radiotherapy was associated with increased contralateral breast and lung cancer, endocrine therapy with increased uterine cancer (but reduced contralateral breast cancer), and chemotherapy with increased acute leukaemia. These were consistent with effects reported in randomised trials, but positive associations for soft tissue, head and neck, ovarian, and stomach cancers were also identified, and these have not previously been observed in trials. This suggested that approximately 2% of all the 64 747 second cancers and 7% of the 15 813 excess second cancers in the cohort may be attributable to adjuvant therapies. Conclusions: The risk of a second primary cancer in women treated for early invasive breast cancer is slightly higher than for women in the general population. Contralateral breast cancer accounts for around 60% of the overall increase, with higher risks in younger women. The risk associated with adjuvant therapies is small
The relationship between clinical disease activity, synovial inflammatory profile, and treatment response in rheumatoid arthritis
No full textSynovial tissue is widely considered to be a strong candidate for contributing to the development of individualised therapeutic strategies for the treatment and management of rheumatoid arthritis. Recently, several factors have enabled major developments in synovial tissue analysis: (1) improvement in synovial tissue biopsy techniques; (2) availability of powerful biotechnologies with increasing granularity; (3) recruitment of larger cohorts of patients; (4) development of recommendations to standardise synovial tissue analysis; and (5) an expanded therapeutic armamentarium of targeted therapies. Although recent studies have suggested the existence of rheumatoid arthritis subtypes based on the synovial tissue inflammatory profile, with potential therapeutic implications, other studies have yielded different results. In this Viewpoint we discuss and contextualise the findings of recent major studies in the field of synovial tissue. We highlight how disease activity, synovial tissue inflammatory burden, and response to therapy are interdependent features in rheumatoid arthritis, both earlier and later in the disease course. From there, we discuss how this multidirectional relationship has impacted (and potentially influenced the interpretation of) the findings of synovial tissue-based studies. Finally, we discuss the different hypotheses explaining the link between synovial tissue, clinical features, and therapeutic response
Exploring online polarisation in the United States: A computational social science approach
Get PDFAffective polarisation—the profound divide between political groups—has emerged as a critical threat to American democracy, vividly illustrated by events like the January 6th 2021 Capitol Hill attack. Despite widespread concern, existing research has struggled to adequately measure polarisation at scale, trace its evolution across actors and time, and map its structural underpinnings in online networks. This thesis addresses these gaps by means of three papers, leveraging theoretical and methodological innovations, and large-scale empirical analysis of US Twitter data from 2015 to 2020. The first paper introduces a novel framework for detecting polarising language using supervised machine learning classifiers based on transformer models. By integrating the political affiliations of human coders and benchmarking against generative artificial intelligence (AI), the study demonstrates that coder ideology shapes perceptions of divisiveness, with combined human coders’ perspectives yielding more balanced and accurate classification than single-affiliation or AI-only models. These classifiers, which will be made publicly available, establish a robust foundation for scalable and nuanced measurement of affective polarisation. Building on this measurement advance, the second paper investigates the temporal and directional dynamics of polarisation among US politicians, news media, and the public. Applying vector-autoregressive models to a comprehensive tweet dataset, the analysis reveals that polarising rhetoric is driven by a dynamic feedback loop: politicians, media, and citizens alternately lead and respond to shifts in divisive language. The media acts as a catalyst, while cross-party interactions often escalate polarisation, underscoring the complex, reciprocal nature of digital political discourse. The third paper turns to the network structures that sustain elite polarisation. Using hierarchical exponential random graph models, it maps the relational architecture of political communication. It finds that party-based homophily dominates network formation. Democrat politicians hold stronger connections to other powerful nodes in the network than Republicans. The most divisive language is concentrated in the rare ties bridging partisan clusters, highlighting the joint role of network structure and rhetoric in entrenching polarisation. Together, these studies advance both the measurement and substantive understanding of affective polarisation in digital public spheres, offering new tools and theoretical insights for researchers, policymakers, and platform designers seeking to address the challenges of polarisation in contemporary democracies
Self-censorship: should scientific journals decline to publish self-experimentation?
No full textA virologist recently made headlines after successfully using an experimental form of oncolytic virotherapy (OVT) to treat her own recurrent breast cancer. This case has come at a time when regulators are increasingly having to grapple with the proliferation of self-experimentation outside of accredited research institutions. There is therefore a pressing need to outline the key ethical dimensions of self-experimentation, and to develop ethical guidance for journals that may be faced with decisions about whether to publish research involving self-experimentation. In this paper, we aim to provide such guidance. We argue that whilst self-experimentation is not always ethically problematic, neither is there an in principle moral reason for exempting self-experimentation from ethical evaluation. After summarising the details of the recent case report of self-experimentation, and briefly placing it in historical context, we suggest that it is possible to navigate the ethical issues raised in cases of self-experimentation by returning to fundamental values in research ethics, focusing on the implications of self-experimentation for respect for respect for autonomy, reasonable risk, and preventing harm to others. We apply these principles to the case report, and explain why the publication of this report can be morally justified. We ultimately advocate for a case-by-case assessment of studies involving self-experimentation submitted for publication by ethical review boards and journal editors, and we propose a decision-making algorithm to help guide such decisions
Negative ties highlight hidden extremes in social media polarization
Get PDFHuman interactions in the online world comprise a combination of positive and negative exchanges. These diverse interactions can be captured using signed network representations, where edges take positive or negative weights to indicate the sentiment of the interaction between individuals. Signed networks offer valuable insights into online political polarization by capturing antagonistic interactions and ideological divides on social media platforms. This study analyzes polarization on Menéame, a Spanish social media platform that facilitates engagement with news stories through comments and voting. Using a dual-method approach—Signed Hamiltonian Eigenvector Embedding for Proximity for signed networks and Correspondence Analysis for unsigned networks—we investigate how including negative ties enhances the understanding of structural polarization levels across different conversation topics on the platform. While the unsigned Menéame network effectively delineates ideological communities, only by incorporating negative ties can we identify ideologically extreme users who engage in antagonistic behaviors: without them, the most extreme users remain indistinguishable from their less confrontational ideological peers
Tetrahydropyrazolopyridinones as a Novel Class of Potent and Highly Selective LIMK Inhibitors
Get PDFLIMKs are serine/threonine and tyrosine kinases that play critical roles in regulating actin filament turnover, affecting key cellular processes such as cytoskeletal remodeling, proliferation and migration. Aberrant LIMK overactivation has been implicated in several diseases, including cancers and neurodegenerative disorders. Understanding the precise molecular mechanisms by which LIMKs modulate actin cytoskeletal dynamics necessitates highly potent and selective LIMK pharmacological inhibitors. We report the discovery of a novel class of allosteric dual-LIMK1/2 inhibitors based on the tetrahydropyrazolopyridinone scaffold. Using structure-based drug design, we identified MDI-117740 (69) as a highly potent dual-LIMK1/2 inhibitor with significantly improved DMPK properties compared to prior inhibitors, suitable for in vivo evaluation. Importantly, 69 has very low kinome promiscuity, including former off-target RIPK1, representing the most selective LIMK inhibitor reported to date. Such a chemical probe will enable researchers to selectively dissect LIMK activation under physiological or disease conditions and spur translation of new therapeutics targeting LIMK pathologies