Dynamical percolation on general trees

H\"aggstr\"om, Peres, and Steif (1997) have introduced a dynamical version of percolation on a graph $G$. When $G$ is a tree they derived a necessary and sufficient condition for percolation to exist at some time $t$. In the case that $G$ is a spherically symmetric tree, H\"aggstr\"om, Peres, and Steif (1997) derived a necessary and sufficient condition for percolation to exist at some time $t$ in a given target set $D$. The main result of the present paper is a necessary and sufficient condition for the existence of percolation, at some time $t\in D$, in the case that the underlying tree is not necessary spherically symmetric. This answers a question of Yuval Peres (personal communication). We present also a formula for the Hausdorff dimension of the set of exceptional times of percolation.Comment: 24 pages; to appear in Probability Theory and Related Field

A workflow for patient-specific fluid-structure interaction analysis of the mitral valve: A proof of concept on a mitral regurgitation case

The mechanics of the mitral valve (MV) are the result of the interaction of different anatomical structures complexly arranged within the left heart (LH), with the blood flow. MV structure abnormalities might cause valve regurgitation which in turn can lead to heart failure. Patient-specific computational models of the MV could provide a personalised understanding of MV mechanics, dysfunctions and possible interventions. In this study, we propose a semi-automatic pipeline for MV modelling based on the integration of state-of-the-art medical imaging, i.e. cardiac magnetic resonance (CMR) and 3D transoesophageal-echocardiogram (TOE) with fluid-structure interaction (FSI) simulations. An FSI model of a patient with MV regurgitation was implemented using the finite element (FE) method and smoothed particle hydrodynamics (SPH). Our study showed the feasibility of combining image information and computer simulations to reproduce patient-specific MV mechanics as seen on medical images, and the potential for efficient in-silico studies of MV disease, personalised treatments and device design

The construction of mental health as a technological problem in India

This paper points to an underexplored relationship of reinforcement between processes of quantification and digitization in the construction of mental health as amenable to technological intervention, in India. Increasingly, technology is used to collect mental health data, to diagnose mental health problems, and as a route of mental health intervention and clinical management. At the same time, mental health has become recognized as a new public health priority in India, and within national and global public health agendas. We explore two sites of the technological problematisation of mental health in India: a large-scale survey calculating prevalence, and a smartphone app to manage stress. We show how digital technology is deployed both to frame a ‘need’ for, and to implement, mental health interventions. We then trace the epistemologies and colonial histories of ‘psy’ technologies, which question assumptions of digital empowerment and of top-down ‘western’ imposition. Our findings show that in India such technologies work both to discipline and liberate users. The paper aims to encourage global debate inclusive of those positioned inside and outside of the ‘black box’ of mental health technology and data production, and to contribute to shaping a future research agenda that analyzes quantification and digitization as key drivers in global advocacy to make mental health count

The construction of mental health as a technological problem in India

This paper points to an underexplored relationship of reinforcement between processes of quantification and digitisation in the construction of mental health as amenable to technological intervention, in India. Increasingly, technology is used to collect mental health data, to diagnose mental health problems, and as a route of mental health intervention and clinical management. At the same time, mental health has become recognised as a new public health priority in India, and within national and global public health agendas. We explore two sites of the technological problematisation of mental health in India: a large-scale survey calculating prevalence, and a smartphone app to manage stress. We show how digital technology is deployed both to frame a ‘need’ for, and to implement, mental health interventions. We then trace the epistemologies and colonial histories of ‘psy’ technologies, which question assumptions of digital empowerment and of top-down ‘western’ imposition. Our findings show that in India such technologies work both to discipline and liberate users. The paper aims to encourage global debate inclusive of those positioned inside and outside of the ‘black box’ of mental health technology and data production, and to contribute to shaping a future research agenda that analyses quantification and digitisation as key drivers in global advocacy to make mental health count

Expression of lymphoid structure-associated cytokine/chemokine gene transcripts in tumor and protein in serum are prognostic of melanoma patient outcomes

BackgroundProinflammatory chemokines/cytokines support development and maturation of tertiary lymphoid structures (TLS) within the tumor microenvironment (TME). In the current study, we sought to investigate the prognostic value of TLS-associated chemokines/cytokines (TLS-kines) expression levels in melanoma patients by performing serum protein and tissue transcriptomic analyses, and to then correlate these data with patients clinicopathological and TME characteristics.MethodsLevels of TLS-kines in patients’ sera were quantitated using a custom Luminex Multiplex Assay. The Cancer Genomic Atlas melanoma cohort (TCGA-SKCM) and a Moffitt Melanoma cohort were used for tissue transcriptomic analyses. Associations between target analytes and survival outcomes, clinicopathological variables, and correlations between TLS-kines were statistically analyzed.ResultsSerum of 95 patients with melanoma were evaluated; 48 (50%) female, median age of 63, IQR 51-70 years. Serum levels of APRIL/TNFSF13 were positively correlated with levels of both CXCL10 and CXCL13. In multivariate analyses, high levels of serum APRIL/TNFSF13 were associated with improved event-free survival after adjusting for age and stage (HR = 0.64, 95% CI 0.43-0.95; p = 0.03). High expression of APRIL/TNFSF13 tumor transcripts was significantly associated with improved OS in TCGA-SKCM (HR = 0.69, 95% CI 0.52-0.93; p = 0.01) and in Moffitt Melanoma patients (HR = 0.51, 95% CI: 0.32-0.82; p = 0.006). Further incorporation of CXCL13 and CXCL10 tumor transcript levels in a 3-gene index revealed that high APRIL/CXCL10/CXCL13 expression was associated with improved OS in the TCGA SKCM cohort (HR = 0.42, 95% CI 0.19-0.94; p = 0.035). Melanoma differentially expressed genes positively associated with high APRIL/CXCL10/CXCL13 tumor expression were linked to tumor infiltration by a diverse array of proinflammatory immune cell types.ConclusionSerum protein and tumor transcript levels of APRIL/TNFSF13 are associated with improved survival outcomes. Patients exhibiting high coordinate expression of APRIL/CXCL10/CXCL13 transcripts in their tumors displayed superior OS. Further investigation of TLS-kine expression profiles related to clinical outcomes in larger cohort studies is warranted

Clinical applications of PD-L1 bioassays for cancer immunotherapy

Abstract Programmed death ligand 1 (PD-L1) has emerged as a biomarker that can help to predict responses to immunotherapies targeted against PD-L1 and its receptor (PD-1). Companion tests for evaluating PD-L1 expression as a biomarker of response have been developed for many cancer immunotherapy agents. These assays use a variety of detection platforms at different levels (protein, mRNA), employ diverse biopsy and surgical samples, and have disparate positivity cutoff points and scoring systems, all of which complicate the standardization of clinical decision-making. This review summarizes the current understanding and ongoing investigations regarding PD-L1 expression as a potential biomarker for clinical outcomes of anti-PD-1/PD-L1 immunotherapy