Mooring in the Homeless City. A Practice Theoretical Account of Homeless Urban Dwelling and Emplacement

Taking a practice theoretical approach and building on the research conducted with a group of people who live their lives on the streets of two Polish cities, this paper provides an account of the homeless city dwellers’ mode of emplacement. It offers the terms licensed, invisible, motile, material, relational, affective, and ad hoc mooring to describe how homeless people establish a place of and for various activities that make up their everyday practice of inhabiting the city. While highlighting the accomplishments of homeless places, the paper also underscores their tentativeness and instability. It situates the homeless mode of emplacement within a wider landscape of normative urban geography, against which the ways homeless people establish themselves in place are often judged out-of-place. It attends to the role that this transgressive potential plays in limiting homeless dwellers’ capabilities for mooring and considers how they might be enhanced

Caspase-8 controls the gut response to microbial challenges by Tnf-alpha-dependent and independent pathways

Objectives: Intestinal epithelial cells (IEC) express toll-like receptors (TLR) that facilitate microbial recognition. Stimulation of TLR ligands induces a transient increase in epithelial cell shedding, a mechanism that serves the antibacterial and antiviral host defence of the epithelium and promotes elimination of intracellular pathogens. Although activation of the extrinsic apoptosis pathway has been described during inflammatory shedding, its functional involvement is currently unclear. Design: We investigated the functional involvement of caspase-8 signalling in microbial-induced intestinal cell shedding by injecting Lipopolysaccharide (LPS) to mimic bacterial pathogens and poly(I:C) as a probe for RNA viruses in vivo. Results: TLR stimulation of IEC was associated with a rapid activation of caspase-8 and increased epithelial cell shedding. In mice with an epithelial cell-specific deletion of caspase-8 TLR stimulation caused Rip3-dependent epithelial necroptosis instead of apoptosis. Mortality and tissue damage were more severe in mice in which IECs died by necroptosis than apoptosis. Inhibition of receptor-interacting protein (Rip) kinases rescued the epithelium from TLR-induced gut damage. TLR3-induced necroptosis was directly mediated via TRIF-dependent pathways, independent of Tnf-α and type III interferons, whereas TLR4-induced tissue damage was critically dependent on Tnf-α. Conclusions: Together, our data demonstrate an essential role for caspase-8 in maintaining the gut barrier in response to mucosal pathogens by permitting inflammatory shedding and preventing necroptosis of infected cells. These data suggest that therapeutic strategies targeting the cell death machinery represent a promising new option for the treatment of inflammatory and infective enteropathies

QUEM SÃO OS ATUAIS ESTUDANTES DE LICENCIATURA? UM ESTUDO DESDE O CONTEXTO DOS CURSOS DE FÍSICA E MATEMÁTICA DO IFC CAMPUS CONCÓRDIA

A temática do trabalho é a formação de professores, especificamente o perfil do estudante ingressante. Aproblemática é ampla e historicamente conhecida no Brasil: altos índices de evasão e dificuldades dossujeitos em permanecer nas licenciaturas, dadas as condições socioeconômicas, mesmo em um espaçotemporal caracterizado pela ampliação do acesso gratuito ao ensino superior. Os parâmetros quefundamentaram a pesquisa foram publicados em 2019 pela Organização das Nações Unidas e pelaRepresentação da UNESCO no Brasil, em cooperação com a Fundação Carlos Chagas. O objetivo épromover análise comparativa entre dados nacionais e locais (licenciaturas do IFC Campus Concórdia), noque compete às características/perfil dos estudantes, buscando contribuir nas discussões sobre evasão eretenção e propor ações de enfrentamento. Os sujeitos foram os estudantes regularmente matriculados em2020 e a metodologia foi de natureza quantitativa e qualitativa, com aplicação de instrumento: umquestionário com dezesseis perguntas fechadas e uma questão aberta. O instrumento, desenvolvido nosistema Google Forms, foi enviado aos estudantes por meio de e-mails e compartilhamento em grupos. Operíodo de respostas foi de dois meses. O tratamento de dados foi realizado a partir da análise e dacomparação das informações obtidas com o referencial de escala nacional. Observou-se que 48,48% dosestudantes ativos responderam, os quais 89,06% têm idades entre 18 e 29 anos. Na Matemática, 75% foramdo sexo feminino e 92,5% declararam-se brancos. Na Física, 58% do sexo masculino, 70,83% declararam-sebrancos e 29,16% pardos/mulatos. Em relação à escola de origem, os dados locais acordam com o estudonacional, pois a maioria cursou Ensino Médio Tradicional público. No entanto, os dados locais mostramquantitativo maior de estudantes que cursaram Ensino Profissionalizante Técnico. Quanto à escolaridade dospais, os dados da Matemática foram semelhantes aos nacionais, na Física observou-se pequenasdiferenças. No que diz respeito à escolaridade das mães, os dados convergem com o estudo nacional emrelação ao quantitativo de concluintes do Ensino Fundamental até o 5° ano, mas diferem quanto às demaismodalidades de ensino. Os dados locais se aproximam aos nacionais em relação à renda familiar e à cargahorária de atividade remunerada, mas se distanciam às questões referentes a estudo, trabalho e sustentofamiliar e motivos que levaram a escolha da licenciatura. 73,43% dos sujeitos não recebe nenhum tipo debolsa ou auxílio para os estudos, 20% dos acadêmicos da Matemática recebem Programa de AssistênciaEstudantil, assim como 12,5% dos estudantes da Física. As intenções de atuação pós conclusão maiscitadas foram: “ingressar em uma pós-graduação” (71,87%) e “exercer a docência em instituição de ensino”(65,62%). Quanto aos obstáculos para a integralização, 25% responderam não ter dificuldade, 21,87%relataram dificuldade em conciliar trabalho e estudos e 14,06% questões financeiras. Desde o objetivobuscado, percebeu-se aproximações e distanciamentos com relação aos índices nacionais, podendo asinformações servirem para pensar estratégias de acesso e permanência dos estudantes nas licenciaturas doIFC. Pontua-se que o desenvolvimento da pesquisa teve impactos significativos com relação à perspectivainicial, uma vez que discussões presenciais e estudo aprofundado no coletivo não puderam ser realizados.Embora tenham sido coletados dados de uma parte importante dos licenciandos, a intenção era atingir 80%do grupo, o que não foi possível pelo distanciamento dos sujeitos com a pesquisa, frente a situaçãopandêmica instalada. Nesses termos, o atraso na coleta de dados implicou em outros atrasos, inclusive deum traçado de ações possíveis frente ao diagnóstico delineado. Porém, como hipótese de progressão aoestudo, esses dados ainda podem ser discutidos e levados ao conhecimento do corpo colegiado dos cursospara apreciação e, daí, o traçado de ações concretas

Loss of RNase J leads to multi-drug tolerance and accumulation of highly structured mRNA fragments in Mycobacterium tuberculosis

Despite the existence of well-characterized, canonical mutations that confer high-level drug resistance to Mycobacterium tuberculosis (Mtb), there is evidence that drug resistance mechanisms are more complex than simple acquisition of such mutations. Recent studies have shown that Mtb can acquire non-canonical resistance-associated mutations that confer survival advantages in the presence of certain drugs, likely acting as stepping-stones for acquisition of high-level resistance. Rv2752c/rnj, encoding RNase J, is disproportionately mutated in drug-resistant clinical Mtb isolates. Here we show that deletion of rnj confers increased tolerance to lethal concentrations of several drugs. RNAseq revealed that RNase J affects expression of a subset of genes enriched for PE/PPE genes and stable RNAs and is key for proper 23S rRNA maturation. Gene expression differences implicated two sRNAs and ppe50-ppe51 as important contributors to the drug tolerance phenotype. In addition, we found that in the absence of RNase J, many short RNA fragments accumulate because they are degraded at slower rates. We show that the accumulated transcript fragments are targets of RNase J and are characterized by strong secondary structure and high G+C content, indicating that RNase J has a rate-limiting role in degradation of highly structured RNAs. Taken together, our results demonstrate that RNase J indirectly affects drug tolerance, as well as reveal the endogenous roles of RNase J in mycobacterial RNA metabolism.Fil: Martini, María Carla. Worcester Polytechnic Institute; Estados Unidos. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Hicks, Nathan D.. Harvard University. Harvard School of Public Health; Estados UnidosFil: Xiao, Junpei. Worcester Polytechnic Institute; Estados UnidosFil: Alonso, Maria Natalia. Worcester Polytechnic Institute; Estados Unidos. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Barbier, Thibault. Harvard University. Harvard School of Public Health; Estados UnidosFil: Sixsmith, Jaimie. Harvard University. Harvard School of Public Health; Estados UnidosFil: Fortune, Sarah M.. Harvard University. Harvard School of Public Health; Estados UnidosFil: Shell, Scarlet S.. Worcester Polytechnic Institute; Estados Unido

Quasar Accretion Disk Sizes from Continuum Reverberation Mapping from the Dark Energy Survey

We present accretion disk size measurements for 15 luminous quasars at 0.7 ≤ z ≤ 1.9 derived from griz light curves from the Dark Energy Survey. We measure the disk sizes with continuum reverberation mapping using two methods, both of which are derived from the expectation that accretion disks have a radial temperature gradient and the continuum emission at a given radius is well described by a single blackbody. In the first method we measure the relative lags between the multiband light curves, which provides the relative time lag between shorter and longer wavelength variations. From this, we are only able to constrain upper limits on disk sizes, as many are consistent with no lag the 2σ level. The second method fits the model parameters for the canonical thin disk directly rather than solving for the individual time lags between the light curves. Our measurements demonstrate good agreement with the sizes predicted by this model for accretion rates between 0.3 and 1 times the Eddington rate. Given our large uncertainties, our measurements are also consistent with disk size measurements from gravitational microlensing studies of strongly lensed quasars, as well as other photometric reverberation mapping results, that find disk sizes that are a factor of a few (∼3) larger than predictions

Event reconstruction for KM3NeT/ORCA using convolutional neural networks

The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino detector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower- or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches