On algebraic structures in supersymmetric principal chiral model

Using the Poisson current algebra of the supersymmetric principal chiral model, we develop the algebraic canonical structure of the model by evaluating the fundamental Poisson bracket of the Lax matrices that fits into the rs matrix formalism of non-ultralocal integrable models. The fundamental Poisson bracket has been used to compute the Poisson bracket algebra of the monodromy matrix that gives the conserved quantities in involution

Superconformal Selfdual Sigma-Models

A range of bosonic models can be expressed as (sometimes generalized) $\sigma$-models, with equations of motion coming from a selfduality constraint. We show that in D=2, this is easily extended to supersymmetric cases, in a superspace approach. In particular, we find that the configurations of fields of a superconformal $\mathfrak{G}/\mathfrak{H}$ coset models which satisfy some selfduality constraint are automatically solutions to the equations of motion of the model. Finally, we show that symmetric space $\sigma$-models can be seen as infinite-dimensional \tfG/\tfH models constrained by a selfduality equation, with \tfG the loop extension of $\mathfrak{G}$ and \tfH a maximal subgroup. It ensures that these models have a hidden global \tfG symmetry together with a local \tfH gauge symmetry.Comment: 21 pages; v2 few corrections and references added; v3 exposition change

Antibodies against endogenous retroviruses promote lung cancer immunotherapy

B cells are frequently found in the margins of solid tumours as organized follicles in ectopic lymphoid organs called tertiary lymphoid structures (TLS)1,2. Although TLS have been found to correlate with improved patient survival and response to immune checkpoint blockade (ICB), the underlying mechanisms of this association remain elusive1,2. Here we investigate lung-resident B cell responses in patients from the TRACERx 421 (Tracking Non-Small-Cell Lung Cancer Evolution Through Therapy) and other lung cancer cohorts, and in a recently established immunogenic mouse model for lung adenocarcinoma3. We find that both human and mouse lung adenocarcinomas elicit local germinal centre responses and tumour-binding antibodies, and further identify endogenous retrovirus (ERV) envelope glycoproteins as a dominant anti-tumour antibody target. ERV-targeting B cell responses are amplified by ICB in both humans and mice, and by targeted inhibition of KRAS(G12C) in the mouse model. ERV-reactive antibodies exert anti-tumour activity that extends survival in the mouse model, and ERV expression predicts the outcome of ICB in human lung adenocarcinoma. Finally, we find that effective immunotherapy in the mouse model requires CXCL13-dependent TLS formation. Conversely, therapeutic CXCL13 treatment potentiates anti-tumour immunity and synergizes with ICB. Our findings provide a possible mechanistic basis for the association of TLS with immunotherapy response

Sedentary behaviour and risk of mortality from all-causes and cardiometabolic diseases in adults: evidence from the HUNT3 population cohort

Background: Sedentary behaviour is a potential risk factor for chronic-ill health and mortality, that is, independent of health-enhancing physical activity. Few studies have investigated the risk of mortality associated with multiple contexts of sedentary behaviour. Objective: To examine the prospective associations of total sitting time, TV-viewing time and occupational sitting with mortality from all causes and cardiometabolic diseases. Methods: Data from 50 817 adults aged ≥20 years from the Nord-Trøndelag Health Study 3 (HUNT3) in 2006-2008 were linked to the Norwegian Cause of Death Registry up to 31 December 2010. Cox proportional hazards models examined all-cause and cardiometabolic disease-related mortality associated with total sitting time, TV-viewing and occupational sitting, adjusting for multiple potential confounders including physical activity. Results: After mean follow-up of 3.3 years (137 315.8 person-years), 1068 deaths were recorded of which 388 were related to cardiometabolic diseases. HRs for all-cause mortality associated with total sitting time were 1.12 (95% CI 0.89 to 1.42), 1.18 (95% CI 0.90 to 1.57) and 1.65 (95% CI 1.24 to 2.21) for total sitting time 4-<7, 7-<10 and ≥10 h/day, respectively, relative to <4 h/day after adjusting for confounders ( p-trend=0.001). A similar pattern of associations was observed between total sitting time and mortality from cardiometabolic diseases, but TV-viewing time and occupational sitting showed no or borderline significant associations with all-cause or cardiometabolic disease-related mortality over the same follow-up period. Conclusions: Total sitting time is associated with all-cause and cardiometabolic disease-related mortality in the short term. However, prolonged sitting in specific contexts (ie, watching TV, at work) do not adversely impact health in the same timeframe. These findings suggest that adults should be encouraged to sit less throughout the day to reduce their daily total sitting time

Cross-sectional associations of total sitting and leisure screen time with cardiometabolic risk in adults. Results from the HUNT Study, Norway

Objectives: To examine associations of total sitting time, TV-viewing and leisure-time computer use with cardiometabolic risk biomarkers in adults. Design: Population based cross-sectional study. Methods: Waist circumference, BMI, total cholesterol, HDL cholesterol, blood pressure, non-fasting glucose, gamma glutamyltransferase (GGT) and triglycerides were measured in 48,882 adults aged 20 years or older from the Nord-Trøndelag Health Study 2006-2008 (HUNT3). Adjusted multiple regression models were used to test for associations between these biomarkers and self-reported total sitting time, TV-viewing and leisure-time computer use in the whole sample and by cardiometabolic disease status sub-groups. Results: In the whole sample, reporting total sitting time ≥10. h/day was associated with poorer BMI, waist circumference, total cholesterol, HDL cholesterol, diastolic blood pressure, systolic blood pressure, non-fasting glucose, GGT and triglyceride levels compared to those reporting total sitting time <4. h/day (all p<. 0.05). TV-viewing ≥4. h/day was associated with poorer BMI, waist circumference, total cholesterol, HDL cholesterol, systolic blood pressure, GGT and triglycerides compared to TV-viewing <. 1. h/day (all p<. 0.05). Leisure-time computer use ≥1. h/day was associated with poorer BMI, total cholesterol, diastolic blood pressure, GGT and triglycerides compared with those reporting no leisure-time computing. Sub-group analyses by cardiometabolic disease status showed similar patterns in participants free of cardiometabolic disease, while similar albeit non-significant patterns were observed in those with cardiometabolic disease. Conclusions: Total sitting time, TV-viewing and leisure-time computer use are associated with poorer cardiometabolic risk profiles in adults. Reducing sedentary behaviour throughout the day and limiting TV-viewing and leisure-time computer use may have health benefits. © 2013 Sports Medicine Australia

Zips : mining compressing sequential patterns in streams

We propose a streaming algorithm, based on the minimal description length (MDL) principle, for extracting non-redundant sequential patterns. For static databases, the MDL-based approach that selects patterns based on their capacity to compress data rather than their frequency, was shown to be remarkably effective for extracting meaningful patterns and solving the redundancy issue in frequent itemset and sequence mining. The existing MDL-based algorithms, however, either start from a seed set of frequent patterns, or require multiple passes through the data. As such, the existing approaches scale poorly and are unsuitable for large datasets. Therefore, our main contribution is the proposal of a new, streaming algorithm, called Zips, that does not require a seed set of patterns and requires only one scan over the data. For Zips, we extended the Lempel-Ziv (LZ) compression algorithm in three ways: first, whereas LZ assigns codes uniformly as it builds up its dictionary while scanning the input, Zips assigns codewords according to the usage of the dictionary words; more heaviliy used words get shorter code-lengths. Secondly, Zips exploits also non-consecutive occurences of dictionary words for compression. And, third, the well-known space-saving algorithm is used to evict unpromising words from the dictionary. Experiments on one synthetic and two real-world large-scale datasets show that our approach extracts meaningful compressing patterns with similar quality to the state-of-the-art multi-pass algorithms proposed for static databases of sequences. Moreover, our approach scales linearly with the size of data streams while all the existing algorithms do not