Mean-field cooperativity in chemical kinetics

We consider cooperative reactions and we study the effects of the interaction strength among the system components on the reaction rate, hence realizing a connection between microscopic and macroscopic observables. Our approach is based on statistical mechanics models and it is developed analytically via mean-field techniques. First of all, we show that, when the coupling strength is set positive, the model is able to consistently recover all the various cooperative measures previously introduced, hence obtaining a single unifying framework. Furthermore, we introduce a criterion to discriminate between weak and strong cooperativity, based on a measure of "susceptibility". We also properly extend the model in order to account for multiple attachments phenomena: this is realized by incorporating within the model $p$-body interactions, whose non-trivial cooperative capability is investigated too.Comment: 25 pages, 4 figure

Managing the Socially Marginalized: Attitudes Towards Welfare, Punishment and Race

Welfare and incarceration policies have converged to form a system of governance over socially marginalized groups, particularly racial minorities. In both of these policy areas, rehabilitative and social support objectives have been replaced with a more punitive and restrictive system. The authors examine the convergence in individual-level attitudes concerning welfare and criminal punishment, using national survey data. The authors\u27 analysis indicates a statistically significant relationship between punitive attitudes toward welfare and punishment. Furthermore, accounting for the respondents\u27 racial attitudes explains the bivariate relationship between welfare and punishment. Thus, racial attitudes seemingly link support for punitive approaches to opposition to welfare expenditures. The authors discuss the implications of this study for welfare and crime control policies by way of the conclusion

MetaWards: A flexible metapopulation framework for modelling disease spread

This is the final version. Available on open access from Open Journals via the DOI in this recordThe software is available at https://github.com/metawards/MetaWardsUnderstanding how disease spreads through populations is important when designing and implementing control measures. MetaWards implements a stochastic metapopulation model of disease transmission that enables geographical modelling of disease spread that can scale all the way from modelling local transmission up to full national-or international-scale outbreaks. It is built in Python and has a flexible plugin architecture to support complex scenario modelling. This enables the code to be adapted to model new situations and new control measures as they arise, e.g. emergence of new variants of disease, enaction of different types of movement restrictions, availability of different types of vaccines etc. It implements a userdefinable compartmental transmission model, such as an SIR model, that can be extended multi-dimensionally via multiple demographics or sub-populations, and multiple geographical regions. Models can be constructed from the various sources of movement and demographic data that are available, and are accelerated via Cython (Behnel et al., 2020), OpenMP, Scoop (Hold & Gagnon, 2019) and MPI4Py (Dalcin & Fang, 2021) to scale efficiently from running on personal laptops to large supercomputers. Python, R and command line interfaces and a complete set of tutorials empower researchers to adapt their models to a variety of scenarios.Engineering and Physical Sciences Research Council (EPSRC)Medical Research Council (MRC)Alan Turing InstitutePfize

\tau\to \mu \bar{\nu_i} \nu_i decay in the general two Higgs doublet model

We study \tau\to \mu \bar{\nu_i} \nu_i, i=e,\mu,\tau decay in the model III version of the two Higgs doublet model. We calculated the BR at the order of the magnitude of 10^{-6}-10^{-4} for the intermediate values of the Yukawa couplings. Furthermore, we predict the upper limit of the coupling for the \tau-h^0 (A^0)-\tau transition as \sim 0.3 in the case that the BR is \sim 10^{-6}. We observe that the experimental result of the process under consideration can give comprehensive information about the physics beyond the standard model and the free parameters existing.Comment: 9 pages, 5 figure

Systematic detection of putative tumor suppressor genes through the combined use of exome and transcriptome sequencing

Abstract Background To identify potential tumor suppressor genes, genome-wide data from exome and transcriptome sequencing were combined to search for genes with loss of heterozygosity and allele-specific expression. The analysis was conducted on the breast cancer cell line HCC1954, and a lymphoblast cell line from the same individual, HCC1954BL. Results By comparing exome sequences from the two cell lines, we identified loss of heterozygosity events at 403 genes in HCC1954 and at one gene in HCC1954BL. The combination of exome and transcriptome sequence data also revealed 86 and 50 genes with allele specific expression events in HCC1954 and HCC1954BL, which comprise 5.4% and 2.6% of genes surveyed, respectively. Many of these genes identified by loss of heterozygosity and allele-specific expression are known or putative tumor suppressor genes, such as BRCA1, MSH3 and SETX, which participate in DNA repair pathways. Conclusions Our results demonstrate that the combined application of high throughput sequencing to exome and allele-specific transcriptome analysis can reveal genes with known tumor suppressor characteristics, and a shortlist of novel candidates for the study of tumor suppressor activities

Epigenetic and transcriptional dysregulation in CD4+ T cells in patients with atopic dermatitis

Atopic dermatitis (AD) is one of the most common skin disorders among children. Disease etiology involves genetic and environmental factors, with 29 independent AD risk loci enriched for risk allele-dependent gene expression in the skin and CD4+ T cell compartments. We investigated the potential epigenetic mechanisms responsible for the genetic susceptibility of CD4+ T cells. To understand the differences in gene regulatory activity in peripheral blood T cells in AD, we measured chromatin accessibility (an assay based on transposase-accessible chromatin sequencing, ATAC-seq), nuclear factor kappa B subunit 1 (NFKB1) binding (chromatin immunoprecipitation with sequencing, ChIP-seq), and gene expression levels (RNA-seq) in stimulated CD4+ T cells from subjects with active moderate-to-severe AD, as well as in age-matched non-allergic controls. Open chromatin regions in stimulated CD4+ T cells were highly enriched for AD genetic risk variants, with almost half of the AD risk loci overlapping AD-dependent ATAC-seq peaks. AD-specific open chromatin regions were strongly enriched for NF-κB DNA-binding motifs. ChIP-seq identified hundreds of NFKB1-occupied genomic loci that were AD- or control-specific. As expected, the AD-specific ChIP-seq peaks were strongly enriched for NF-κB DNA-binding motifs. Surprisingly, control-specific NFKB1 ChIP-seq peaks were not enriched for NFKB1 motifs, but instead contained motifs for other classes of human transcription factors, suggesting a mechanism involving altered indirect NFKB1 binding. Using DNA sequencing data, we identified 63 instances of altered genotype-dependent chromatin accessibility at 36 AD risk variant loci (30% of AD risk loci) that might lead to genotype-dependent gene expression. Based on these findings, we propose that CD4+ T cells respond to stimulation in an AD-specific manner, resulting in disease- and genotype-dependent chromatin accessibility alterations involving NFKB1 binding