Metastatic model of HPV+ oropharyngeal squamous cell carcinoma demonstrates heterogeneity in tumor metastasis

Human papillomavirus induced (HPV+) cancer incidence is rapidly rising, comprising 60–80% of oropharyngeal squamous cell carcinomas (OPSCCs); while rare, recurrent/metastatic disease accounts for nearly all related deaths. An in vivo pre-clinical model for these invasive cancers is necessary for testing new therapies. We characterize an immune competent recurrent/metastatic HPV+ murine model of OPSSC which consists of four lung metastatic (MLM) cell lines isolated from an animal with HPV+ OPSCC that failed cisplatin/radiation treatment. These individual metastatic clonal cell lines were tested to verify their origin (parental transgene expression and define their physiological properties: proliferation, metastatic potential, heterogeneity and sensitivity/resistance to cisplatin and radiation. All MLMs retain expression of parental HPV16 E6 and E7 and degrade P53 yet are heterogeneous from one another and from the parental cell line as defined by Illumina expression microarray. Consistent with this, reverse phase protein array defines differences in protein expression/activation between MLMs as well as the parental line. While in vitro growth rates of MLMs are slower than the parental line, in vivo growth of MLM clones is greatly enhanced. Moreover, in vivo resistance to standard therapies is dramatically increased in 3 of the 4 MLMs. Lymphatic and/or lung metastasis occurs 100% of the time in one MLM line. This recurrent/metastatic model of HPV+ OPSCC retains the characteristics evident in refractory human disease (heterogeneity, resistance to therapy, metastasis in lymph nodes/lungs) thus serving as an ideal translational system to test novel therapeutics. Moreover, this system may provide insights into the molecular mechanisms of metastasis

Electoral news sharing:A study of changes in news coverage and Facebook sharing behaviour during the 2018 Mexican elections

Patterns of news consumption are changing drastically. Citizens increasingly rely on social media such as Facebook to read and share political news. With the power of these platforms to expose citizens to political information, the implications for democracy are profound, making understanding what is shared during elections a priority on the research agenda. Nevertheless, to the best of our knowledge, no study has yet explicitly explored how elections transform news sharing behaviour on Facebook. This study begins to remedy this by (a) investigating changes in news coverage and news sharing behaviour on Facebook by comparing election and routine periods, and by (b) addressing the ‘news gap’ between preferences of journalists and news consumers on social media. Employing a novel data set of news articles (N = 83,054) in Mexico, findings show that during periods of heightened political activity, both the publication and dissemination of political news increases, the gap between the news choices of journalists and consumers narrows, and that news sharing resembles a zero-sum game, with increased political news sharing leading to a decrease in the sharing of other news

URLs can facilitate machine learning classification of news stories across languages and contexts

Comparative scholars studying political news content at scale face the challenge of addressing multiple languages. While many train individual supervised machine learning classifiers for each language, this is a costly and time-consuming process. We propose that instead of rely-ing on thematic labels generated by manual coding, researchers can use ‘distant’ labels created by cues in article URLs. Sections reflected in URLs (e.g., nytimes.com/politics/) can therefore help create training material for supervised machine learning classifiers. Using cues provided by news media organizations, such an approach allows for efficient political news identification at scale while facilitating imple-mentation across languages. Using a dataset of approximately 870,000 URLs of news-related content from four countries (Italy, Germany, Netherlands, and Poland), we test this method by providing a comparison to ‘classical’ supervised machine learning and a multilingual BERT model, across four news topics. Our results suggest that the use of URL section cues to distantly annotate texts provides a cheap and easy-to-implement way of classifying large volumes of news texts that can save researchers many valuable resources without having to sacrifice quality

Stress-strain behavior and geometrical properties of packings of elongated particles

We present a numerical analysis of the effect of particle elongation on the quasistatic behavior of sheared granular media by means of the Contact Dynamics method. The particle shapes are rounded-cap rectangles characterized by their elongation. The macroscopic and microstructural properties of several packings subjected to biaxial compression are analyzed as a function of particle elongation. We find that the shear strength is an increasing linear function of elongation. Performing an additive decomposition of the stress tensor based on a harmonic approximation of the angular dependence of branch vectors, contact normals and forces, we show that the increasing mobilization of friction force and the associated anisotropy are key effects of particle elongation. These effects are correlated with partial nematic ordering of the particles which tend to be oriented perpendicular to the major principal stress direction and form side-to-side contacts. However, the force transmission is found to be mainly guided by cap-to-side contacts, which represent the largest fraction of contacts for the most elongated particles. Another interesting finding is that, in contrast to shear strength, the solid fraction first increases with particle elongation, but declines as the particles become more elongated. It is also remarkable that the coordination number does not follow this trend so that the packings of more elongated particles are looser but more strongly connected.Comment: Submited to Physical Review

Computational Communication Science in a Digital Society

Computational methods have added new approaches to the way many communication scientists do their work. We identify four developments that accelerated the adaption of computational methods: the increasing availability of digital data, the surge of large amounts of user-created data, the need to study new artefacts, and the improved accessibility of computational resources. We describe new data acquisition techniques, new research designs, and new analytical approaches that characterise the field. After discussing contributions to the open source community, to the methodological toolbox, as well as to the testing and development of theories, we sketch in broad strokes a research agenda for the coming years

Associative Learning Contributes to the Persistence of Fatigue-Like Behavior in Male Mice in a Model of Cancer Survivorship

Persistent fatigue is a debilitating side effect that impacts a significant proportion of cancer survivors for which there is not yet an FDA-approved treatment. While certainly a multi-factorial problem, persistent fatigue could be due, in part, to associations learned during treatment. Therefore, we sought to investigate the role of associative learning in the persistence of fatigue using a preclinical model of cancer survivorship. For this purpose, we used a murine model of human papilloma virus-related head and neck cancer paired with a curative regimen of cisplatin-based chemoradiation in male C57BL/6J mice. Fatigue-like behavior was assessed by measuring variations in voluntary wheel running using a longitudinal design. Treatment robustly decreased voluntary wheel running, and this effect persisted for more than a month posttreatment. However, when wheels were removed during treatment, to minimize treatment-related fatigue, mice showed a more rapid return to baseline running levels. We confirmed that the delayed recovery observed in mice with continual wheel access was not due to increased treatment-related toxicity, in fact running attenuated cisplatin-induced kidney toxicity. Finally, we demonstrated that re-exposure to a treatment-related olfactory cue acutely re-instated fatigue. These data provide the first demonstration that associative processes can modulate the persistence of cancer-related fatigue-like behavior

DNA unzipped under a constant force exhibits multiple metastable intermediates

Single molecule studies, at constant force, of the separation of double-stranded DNA into two separated single strands may provide information relevant to the dynamics of DNA replication. At constant applied force, theory predicts that the unzipped length as a function of time is characterized by jumps during which the strands separate rapidly, followed by long pauses where the number of separated base pairs remains constant. Here, we report previously uncharacterized observations of this striking behavior carried out on a number of identical single molecules simultaneously. When several single lphage molecules are subject to the same applied force, the pause positions are reproducible in each. This reproducibility shows that the positions and durations of the pauses in unzipping provide a sequence-dependent molecular fingerprint. For small forces, the DNA remains in a partially unzipped state for at least several hours. For larger forces, the separation is still characterized by jumps and pauses, but the double-stranded DNA will completely unzip in less than 30 min