The Representative Porcine Model for Human Cardiovascular Disease

To improve human health, scientific discoveries must be translated into practical applications. Inherent in the development of these technologies is the role of preclinical testing using animal models. Although significant insight into the molecular and cellular basis has come from small animal models, significant differences exist with regard to cardiovascular characteristics between these models and humans. Therefore, large animal models are essential to develop the discoveries from murine models into clinical therapies and interventions. This paper will provide an overview of the more frequently used large animal models, especially porcine models for preclinical studies

Phase Separation Kinetics in a Model with Order-Parameter Dependent Mobility

We present extensive results from 2-dimensional simulations of phase separation kinetics in a model with order-parameter dependent mobility. We find that the time-dependent structure factor exhibits dynamical scaling and the scaling function is numerically indistinguishable from that for the Cahn-Hilliard (CH) equation, even in the limit where surface diffusion is the mechanism for domain growth. This supports the view that the scaling form of the structure factor is "universal" and leads us to question the conventional wisdom that an accurate representation of the scaled structure factor for the CH equation can only be obtained from a theory which correctly models bulk diffusion.Comment: To appear in PRE, figures available on reques

A transient positive association between direct-acting antiviral therapy for hepatitis C infection and drug-related hospitalization among people who inject drugs: self-controlled case-series analysis of national data

Background and Aims: Direct-acting antiviral (DAA) treatment has an established positive effect on liver outcomes in people with hepatitis C infection; however, there is insufficient evidence regarding its effects on the 'extra-hepatic' outcomes of drug-related hospitalization and mortality (DRM) among people who inject drugs (PWID). We investigated associations between these outcomes and DAA treatment by comparing post-treatment to baseline periods using a within-subjects design to minimize selection bias concerns with cohort or case-control designs.Design: This was a self-controlled case-series study.Setting: Scotland, 1 January 2015-30 November 2020.Participants: The study population of non-cirrhotic, DAA-treated PWID was identified using a data set linking Scotland's hepatitis C diagnosis, HCV clinical databases, national inpatient/day-case hospital records and the national deaths register. Three principal outcomes (drug overdose admission, non-viral injecting related admission and drug-related mortality) were defined using ICD codes.Measurements: Self-controlled case-series methodology was used to estimate the relative incidence (RI) of each outcome associated with time on treatment and up to six 90-day exposure risk periods thereafter.Findings: A total of 6050 PWID were treated with DAAs in the sampling time-frame. Compared with the baseline period, there was a significantly lowered risk of a drug overdose hospital admission in the second to fifth exposure risk periods only [relative incidence (RI) = 0.86, 95% confidence interval (CI) = 0.80-0.99; 0.89, 95% CI = 0.80-0.99; 0.86, 95% CI = 0.77-0.96; 0.88, 95% CI = 0.78-0.99, respectively]. For non-viral injecting-related admission, there was a reduced risk in the first, third and fourth exposure risk periods (RI = 0.76, 95% CI = 0.64-0.90; 0.75, 95% CI = 0.62-0.90; 0.79, 95% CI = 0.66-0.96, respectively). There was no evidence for reduced DRM risk in any period following treatment end.Conclusions: Among people who inject drugs in Scotland, direct-acting antiviral treatment appears to be associated with a small, non-durable reduction in the risk of drug-related hospital admission, but not drug-related mortality. Direct-acting antiviral therapy, despite high effectiveness against liver disease, does not appear to offer a panacea for reducing other drug-related health harms.</p

Ageing phenomena without detailed balance: the contact process

The long-time dynamics of the 1D contact process suddenly brought out of an uncorrelated initial state is studied through a light-cone transfer-matrix renormalisation group approach. At criticality, the system undergoes ageing which is characterised through the dynamical scaling of the two-times autocorrelation and autoresponse functions. The observed non-equality of the ageing exponents a and b excludes the possibility of a finite fluctuation-dissipation ratio in the ageing regime. The scaling form of the critical autoresponse function is in agreement with the prediction of local scale-invariance.Comment: 20 pages, 15 figures, Latex2e with IOP macro

Domain Growth in a 1-D Driven Diffusive System

The low-temperature coarsening dynamics of a one-dimensional Ising model, with conserved magnetisation and subject to a small external driving force, is studied analytically in the limit where the volume fraction \mu of the minority phase is small, and numerically for general \mu. The mean domain size L(t) grows as t^{1/2} in all cases, and the domain-size distribution for domains of one sign is very well described by the form P_l(l) \propto (l/L^3)\exp[-\lambda(\mu)(l^2/L^2)], which is exact for small \mu (and possibly for all \mu). The persistence exponent for the minority phase has the value 3/2 for \mu \to 0.Comment: 8 pages, REVTeX, 7 Postscript figures, uses multicol.sty and epsf.sty. Submitted to Phys. Rev.

Competing risk bias in prognostic models predicting hepatocellular carcinoma occurrence: impact on clinical decision making

Existing models predicting hepatocellular carcinoma (HCC) occurrence do not account for competing risk events and, thus, may overestimate the probability of HCC. Our goal was to quantify this bias for patients with cirrhosis and cured hepatitis C. We analyzed a nationwide cohort of patients with cirrhosis and cured hepatitis C infection from Scotland. Two HCC prognostic models were developed: (1) a Cox regression model ignoring competing risk events and (2) a Fine-Gray regression model accounting for non-HCC mortality as a competing risk. Both models included the same set of prognostic factors used by previously developed HCC prognostic models. Two predictions were calculated for each patient: first, the 3-year probability of HCC predicted by model 1 and second, the 3-year probability of HCC predicted by model 2. The study population comprised 1629 patients with cirrhosis and cured HCV, followed for 3.8 years on average. A total of 82 incident HCC events and 159 competing risk events (ie, non-HCC deaths) were observed. The mean predicted 3-year probability of HCC was 3.37% for model 1 (Cox) and 3.24% for model 2 (Fine-Gray). For most patients (76%), the difference in the 3-year probability of HCC predicted by model 1 and model 2 was minimal (ie, within 0 to ±0.3%). A total of 2.6% of patients had a large discrepancy exceeding 2%; however, these were all patients with a 3-year probability exceeding >5% in both models. Prognostic models that ignore competing risks do overestimate the future probability of developing HCC. However, the degree of overestimation—and the way it is patterned—means that the impact on HCC screening decisions is likely to be modest