\u27Struggling with Language\u27 : Indigenous movements for Linguistic Security and the Politics of Local Community

In this article, I explore the relationship between linguistic diversity and political power. Specifically, I outline some of the ways that linguistic diversity has served as a barrier to the centralization of power, thus constraining, for example, the political practice of empire-formation. A brief historical example of this dynamic is presented in the case of Spanish colonialism of the 16th-century. The article proceeds then to demonstrate how linguistic diversity remains tied to struggles against forms of domination. I argue that in contemporary indigenous movements for linguistic security, the languages themselves are not merely conceived of as the object of the political struggle, but also as the means to preserve a space for local action and deliberation – a ‘politics of local community’. I show that linguistic diversity and the devolution of political power to the local level are in a mutually reinforcing relationship. Finally, I consider the implications of this thesis for liberal theorizing on language rights, arguing that such theory cannot fully come to terms with this political-strategic dimension of language struggles

The state of play: securities of childhood - insecurities of children

This article is broadly concerned with the positioning of children, both within and outside the subject area of International Relations. It considers the costs of an adult- 5 centric standpoint in security studies and contrasts this with investments made seemingly on behalf of children and their security. It begins by looking at how children and childhoods are constructed and contained - yet also defy categorization - at some cost to their protection. The many competing children and childhoods that are invoked in security discourses and partially sustain their victimcy are then illustrated. It is 10 argued that at their entry point into academia they are essentialized and sentimentalized. Power relations which subvert, yet also rely on children and childhoods can only be disrupted through a reconfiguration of politics and agency which includes an engagement with political literacy on a societal level and acknowledgement of the ubiquitous presence of war in all our live

Alterations in ethanol-induced behaviors and consumption in knock-in mice expressing ethanol-resistant NMDA receptors

Ethanol's action on the brain likely reflects altered function of key ion channels such as glutamatergic N-methyl-D-aspartate receptors (NMDARs). In this study, we determined how expression of a mutant GluN1 subunit (F639A) that reduces ethanol inhibition of NMDARs affects ethanol-induced behaviors in mice. Mice homozygous for the F639A allele died prematurely while heterozygous knock-in mice grew and bred normally. Ethanol (44 mM; ∼0.2 g/dl) significantly inhibited NMDA-mediated EPSCs in wild-type mice but had little effect on responses in knock-in mice. Knock-in mice had normal expression of GluN1 and GluN2B protein across different brain regions and a small reduction in levels of GluN2A in medial prefrontal cortex. Ethanol (0.75-2.0 g/kg; IP) increased locomotor activity in wild-type mice but had no effect on knock-in mice while MK-801 enhanced activity to the same extent in both groups. Ethanol (2.0 g/kg) reduced rotarod performance equally in both groups but knock-in mice recovered faster following a higher dose (2.5 g/kg). In the elevated zero maze, knock-in mice had a blunted anxiolytic response to ethanol (1.25 g/kg) as compared to wild-type animals. No differences were noted between wild-type and knock-in mice for ethanol-induced loss of righting reflex, sleep time, hypothermia or ethanol metabolism. Knock-in mice consumed less ethanol than wild-type mice during daily limited-access sessions but drank more in an intermittent 24 h access paradigm with no change in taste reactivity or conditioned taste aversion. Overall, these data support the hypothesis that NMDA receptors are important in regulating a specific constellation of effects following exposure to ethanol. © 2013 den Hartog et al

Operons

Operons (clusters of co-regulated genes with related functions) are common features of bacterial genomes. More recently, functional gene clustering has been reported in eukaryotes, from yeasts to filamentous fungi, plants, and animals. Gene clusters can consist of paralogous genes that have most likely arisen by gene duplication. However, there are now many examples of eukaryotic gene clusters that contain functionally related but non-homologous genes and that represent functional gene organizations with operon-like features (physical clustering and co-regulation). These include gene clusters for use of different carbon and nitrogen sources in yeasts, for production of antibiotics, toxins, and virulence determinants in filamentous fungi, for production of defense compounds in plants, and for innate and adaptive immunity in animals (the major histocompatibility locus). The aim of this article is to review features of functional gene clusters in prokaryotes and eukaryotes and the significance of clustering for effective function

Federated learning enables big data for rare cancer boundary detection.

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing

Author Correction: Federated learning enables big data for rare cancer boundary detection.

10.1038/s41467-023-36188-7NATURE COMMUNICATIONS14

Federated Learning Enables Big Data for Rare Cancer Boundary Detection

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing

31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016) : part two

Background The immunological escape of tumors represents one of the main ob- stacles to the treatment of malignancies. The blockade of PD-1 or CTLA-4 receptors represented a milestone in the history of immunotherapy. However, immune checkpoint inhibitors seem to be effective in specific cohorts of patients. It has been proposed that their efficacy relies on the presence of an immunological response. Thus, we hypothesized that disruption of the PD-L1/PD-1 axis would synergize with our oncolytic vaccine platform PeptiCRAd. Methods We used murine B16OVA in vivo tumor models and flow cytometry analysis to investigate the immunological background. Results First, we found that high-burden B16OVA tumors were refractory to combination immunotherapy. However, with a more aggressive schedule, tumors with a lower burden were more susceptible to the combination of PeptiCRAd and PD-L1 blockade. The therapy signifi- cantly increased the median survival of mice (Fig. 7). Interestingly, the reduced growth of contralaterally injected B16F10 cells sug- gested the presence of a long lasting immunological memory also against non-targeted antigens. Concerning the functional state of tumor infiltrating lymphocytes (TILs), we found that all the immune therapies would enhance the percentage of activated (PD-1pos TIM- 3neg) T lymphocytes and reduce the amount of exhausted (PD-1pos TIM-3pos) cells compared to placebo. As expected, we found that PeptiCRAd monotherapy could increase the number of antigen spe- cific CD8+ T cells compared to other treatments. However, only the combination with PD-L1 blockade could significantly increase the ra- tio between activated and exhausted pentamer positive cells (p= 0.0058), suggesting that by disrupting the PD-1/PD-L1 axis we could decrease the amount of dysfunctional antigen specific T cells. We ob- served that the anatomical location deeply influenced the state of CD4+ and CD8+ T lymphocytes. In fact, TIM-3 expression was in- creased by 2 fold on TILs compared to splenic and lymphoid T cells. In the CD8+ compartment, the expression of PD-1 on the surface seemed to be restricted to the tumor micro-environment, while CD4 + T cells had a high expression of PD-1 also in lymphoid organs. Interestingly, we found that the levels of PD-1 were significantly higher on CD8+ T cells than on CD4+ T cells into the tumor micro- environment (p < 0.0001). Conclusions In conclusion, we demonstrated that the efficacy of immune check- point inhibitors might be strongly enhanced by their combination with cancer vaccines. PeptiCRAd was able to increase the number of antigen-specific T cells and PD-L1 blockade prevented their exhaus- tion, resulting in long-lasting immunological memory and increased median survival