Search

Acetaminophen (APAP) overdose is the leading cause of acute liver injury in the USA and the UK. Increasingly, liver injury is caused by sustained overuse rather than a single-time overdose. We have recently developed a mathematical model, the Model of APAP-induced Liver Damage (MALD), to predict the outcome of patients with APAP-induced liver damage. The model is based on a single-time overdose and uses measurable markers of liver injury to estimate time since overdose and overdose amount, two variables critical for survival. Here, we extend the model to study liver injury from chronic APAP use. We find that there is a threshold in the model, such that liver injury occurs rapidly or not at all, even with chronic use. Fits of synthetic data derived from chronic use overdose scenarios to MALD lead to accurate predictions of outcome, even when liver injury is the result of sustained overuse. [ABSTRACT FROM AUTHOR]

The role of African savannahs in the evolution of early hominins has been debated for nearly a century. Resolution of this issue has been hindered by difficulty in quantifying the fraction of woody cover in the fossil record. Here we show that the fraction of woody cover in tropical ecosystems can be quantified using stable carbon isotopes in soils. Furthermore, we use fossil soils from hominin sites in the Awash and Omo-Turkana basins in eastern Africa to reconstruct the fraction of woody cover since the Late Miocene epoch (about 7 million years ago). 13C/12C ratio data from 1,300 palaeosols at or adjacent to hominin sites dating to at least 6?million years ago show that woody cover was predominantly less than ?40% at most sites. These data point to the prevalence of open environments at the majority of hominin fossil sites in eastern Africa over the past 6?million years. [ABSTRACT FROM AUTHOR]

While isotopes are frequently used as tracers in investigations of disease physiology (i.e., 14C labeled glucose), few studies have examined the impact that disease, and disease-related alterations in metabolism, may have on stable isotope ratios at natural abundance levels. The isotopic composition of body water is heavily influenced by water metabolism and dietary patterns and may provide a platform for disease detection. By utilizing a model of streptozotocin (STZ)-induced diabetes as an index case of aberrant water homeostasis, we demonstrate that untreated diabetes mellitus results in distinct combinations, or signatures, of the hydrogen (δ²H) and oxygen (δ18O) isotope ratios in body water. Additionally, we show that the δ²H and δ18O values of body water are correlated with increased water flux, suggesting altered blood osmolality, due to hyperglycemia, as the mechanism behind this correlation. Further, we present a mathematical model describing the impact of water flux on the isotopic composition of body water and compare model predicted values with actual values. These data highlight the importance of factors such as water flux and energy expenditure on predictive models of body water and additionally provide a framework for using naturally occurring stable isotope ratios to monitor diseases that impact water homeostasis. [ABSTRACT FROM AUTHOR]

Spillover of infectious diseases from wild animal populations constitutes a long-standing threat to human health for which few globally viable solutions have been developed. The use of oral baits laden with conventional vaccines distributed en masse represents one success story but is costly and practicable primarily for rabies risk reduction in North American and European carnivores. Efforts to expand vaccination to control pathogens within less accessible wildlife populations have raised interest in a new kind of vaccine capable of spreading pathogen-specific immunity through autonomous spread. However, such 'transmissible' vaccines raise concerns about the irrevocable release of genetically modified viruses into the environment. Herein, we explore the feasibility of an intrinsic strategy for transgene control within these vaccines based on the genetic destabilizing effect of cis -acting sequences flanking the heterologous transgene of interest. While suitable for the control of transgene stability within all types of DNA-viral vectored vaccines, this strategy has particular applicability to transmissible vaccines. Using a combination of experiments, mathematical modelling and whole-genome sequencing, we show that the rate of transgene loss can be controlled by varying the lengths of the direct repeat sequences. This opens a way for fine-tuning the lifespan of a transmissible vaccine in the wild.

Zoonotic pathogens spread by wildlife continue to spill into human populations and threaten human lives. A potential way to reduce this threat is by vaccinating wildlife species that harbor pathogens that are infectious to humans. Unfortunately, even in cases where vaccines can be distributed en masse as edible baits, achieving levels of vaccine coverage sufficient for pathogen elimination is rare. Developing vaccines that self-disseminate may help solve this problem by magnifying the impact of limited direct vaccination. Although models exist that quantify how well these self-disseminating vaccines will work when introduced into temporally stable wildlife populations, how well they will perform when introduced into populations with pronounced seasonal population dynamics remains unknown. Here we develop and analyze mathematical models of fluctuating wildlife populations that allow us to study how reservoir ecology, vaccine design, and vaccine delivery interact to influence vaccine coverage and opportunities for pathogen elimination. Our results demonstrate that the timing of vaccine delivery can make or break the success of vaccination programs. As a general rule, the effectiveness of self-disseminating vaccines is optimized by introducing after the peak of seasonal reproduction when the number of susceptible animals is near its maximum., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Schreiner et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Respiratory virus infections are a leading cause of disease worldwide with multiple viruses detected in 20-30% of cases and several viruses simultaneously circulating. Some infections with viral copathogens have been shown to result in reduced pathogenicity while other virus pairings can worsen disease. The mechanisms driving these dichotomous outcomes are likely variable and have only begun to be examined in the laboratory and clinic. To better understand viral-viral coinfections and predict potential mechanisms that result in distinct disease outcomes, we first systematically fit mathematical models to viral load data from ferrets infected with respiratory syncytial virus (RSV) followed by influenza A virus (IAV) after 3 days. The results suggested that IAV reduced the rate of RSV production while RSV reduced the rate of IAV infected cell clearance. We then explored the realm of possible dynamics for scenarios not examined experimentally, including different infection order, coinfection timing, interaction mechanisms, and viral pairings. IAV coinfection with rhinovirus (RV) or SARS-CoV-2 (CoV2) was examined by using human viral load data from single infections together with murine weight loss data from IAV-RV, RV-IAV, and IAV-CoV2 coinfections to guide the interpretation of the model results. Similar to the results with RSV-IAV coinfection, this analysis showed that the increased disease severity observed during murine IAV-RV or IAV-CoV2 coinfection was likely due to slower clearance of IAV infected cells by the other viruses. On the contrary, the improved outcome when IAV followed RV could be replicated when the rate of RV infected cell clearance was reduced by IAV. Simulating viral-viral coinfections in this way provides new insights about how viral-viral interactions can regulate disease severity during coinfection and yields testable hypotheses ripe for experimental evaluation.