Predictive mathematical models for the spread and treatment of hyperoxia-induced photoreceptor degeneration in retinitis pigmentosa

Purpose: To determine whether the oxygen toxicity hypothesis can explain the distinctive spatio-temporal patterns of retinal degeneration associated with human retinitis pigmentosa (RP) and to predict the effects of antioxidant and trophic factor treatments under this hypothesis. Methods: Three mathematical models were derived to describe the evolution of the retinal oxygen concentration and photoreceptor density over time. The first model considers only hyperoxia-induced degeneration, while the second and third models include mutation-induced rod and cone loss respectively. The models were formulated as systems of partial differential equations, defined on a two-dimensional domain spanning the region between the foveal center and the ora serrata, and were solved numerically using the finite element method. Results: The mathematical models recapitulate patterns of retinal degeneration which involve preferential loss of photoreceptors in the parafoveal/perifoveal and far-peripheral retina, while those which involve a preferential loss of midperipheral photoreceptors cannot be reproduced. Treatment with antioxidants or trophic factors is predicted to delay, halt, or partially reverse retinal degeneration, depending upon the strength and timing of treatment and disease severity. Conclusions: The model simulations indicate that while the oxygen toxicity hypothesis is sufficient to explain some of the patterns of retinal degeneration observed in human RP, additional mechanisms are necessary to explain the full range of behaviors. The models further suggest that antioxidant and trophic factor treatments have the potential to reduce hyperoxia-induced disease severity and that, where possible, these treatments should be targeted at retinal regions with low photoreceptor density to maximize their efficacy

Predicting radiotherapy patient outcomes with real-time clinical data using mathematical modelling

Longitudinal tumour volume data from head-and-neck cancer patients show that tumours of comparable pre-treatment size and stage may respond very differently to the same radiotherapy fractionation protocol. Mathematical models are often proposed to predict treatment outcome in this context, and have the potential to guide clinical decision-making and inform personalised fractionation protocols. Hindering effective use of models in this context is the sparsity of clinical measurements juxtaposed with the model complexity required to produce the full range of possible patient responses. In this work, we present a compartment model of tumour volume and tumour composition, which, despite relative simplicity, is capable of producing a wide range of patient responses. We then develop novel statistical methodology and leverage a cohort of existing clinical data to produce a predictive model of both tumour volume progression and the associated level of uncertainty that evolves throughout a patient's course of treatment. To capture inter-patient variability, all model parameters are patient specific, with a bootstrap particle filter-like Bayesian approach developed to model a set of training data as prior knowledge. We validate our approach against a subset of unseen data, and demonstrate both the predictive ability of our trained model and its limitations

Predicting radiotherapy patient outcomes with real-time clinical data using mathematical modelling

Longitudinal tumour volume data from head-and-neck cancer patients show that tumours of comparable pre-treatment size and stage may respond very differently to the same radiotherapy fractionation protocol. Mathematical models are often proposed to predict treatment outcome in this context, and have the potential to guide clinical decision-making and inform personalised fractionation protocols. Hindering effective use of models in this context is the sparsity of clinical measurements juxtaposed with the model complexity required to produce the full range of possible patient responses. In this work, we present a compartment model of tumour volume and tumour composition, which, despite relative simplicity, is capable of producing a wide range of patient responses. We then develop novel statistical methodology and leverage a cohort of existing clinical data to produce a predictive model of both tumour volume progression and the associated level of uncertainty that evolves throughout a patient’s course of treatment. To capture inter-patient variability, all model parameters are patient specific, with a bootstrap particle filter-like Bayesian approach developed to model a set of training data as prior knowledge. We validate our approach against a subset of unseen data, and demonstrate both the predictive ability of our trained model and its limitations

Subclinical hepatitis E virus infection in laboratory ferrets in the UK

Ferrets are widely used for experimental modelling of viral infections. However, background disease in ferrets could potentially confound intended experimental interpretation. Here we report the detection of a subclinical infection of ferret hepatitis E virus (FRHEV) within a colony sub-group of female laboratory ferrets that had been enrolled on an experimental viral infection study (non-hepatitis). Lymphoplasmacytic cuffing of periportal spaces was identified on histopathology but was negative for the RNA and antigens of the administered virus. Follow-up viral metagenomic analysis conducted on liver specimens revealed sequences attributed to FRHEV and these were confirmed by reverse-transcriptase polymerase chain reaction. Further genomic analysis revealed contiguous sequences spanning 79-95 % of the FRHEV genome and that the sequences were closely related to those reported previously in Europe. Using in situ hybridization by RNAScope, we confirmed the presence of HEV-specific RNA in hepatocytes. The HEV open reading frame 2 (ORF2) protein was also detected by immunohistochemistry in the hepatocytes and the biliary canaliculi. In conclusion, the results of our study provide evidence of background infection with FRHEV in laboratory ferrets. As this infection can be subclinical, we recommend routine monitoring of ferret populations using virological and liver function tests to avoid incorrect causal attribution of any liver disease detected in in vivo studies

Does Bypass of the Proximal Small Intestine Impact Food Intake, Preference, and Taste Function in Humans? An Experimental Medicine Study Using the Duodenal-Jejunal Bypass Liner

The duodenal-jejunal bypass liner (Endobarrier) is an endoscopic treatment for obesity and type 2 diabetes mellitus (T2DM). It creates exclusion of the proximal small intestine similar to that after Roux-en-Y Gastric Bypass (RYGB) surgery. The objective of this study was to employ a reductionist approach to determine whether bypass of the proximal intestine is the component conferring the effects of RYGB on food intake and sweet taste preference using the Endobarrier as a research tool. A nested mechanistic study within a large randomised controlled trial compared the impact of lifestyle modification with vs. without Endobarrier insertion in patients with obesity and T2DM. Forty-seven participants were randomised and assessed at several timepoints using direct and indirect assessments of food intake, food preference and taste function. Patients within the Endobarrier group lost numerically more weight compared to the control group. Using food diaries, our results demonstrated similar reductions of food intake in both groups. There were no significant differences in food preference and sensory, appetitive reward, or consummatory reward domain of sweet taste function between groups or changes within groups. In conclusion, the superior weight loss seen in patients with obesity and T2DM who underwent the Endobarrier insertion was not due to a reduction in energy intake or change in food preferences

Experts' Judgments of Management Journal Quality:An Identity Concerns Model

Many lists that purport to gauge the quality of journals in management and organization studies (MOS) are based on the judgments of experts in the field. This article develops an identity concerns model (ICM) that suggests that such judgments are likely to be shaped by the personal and social identities of evaluators. The model was tested in a study in which 168 editorial board members rated 44 MOS journals. In line with the ICM, respondents rated journal quality more highly to the extent that a given journal reflected their personal concerns (associated with having published more articles in that journal) and the concerns of a relevant ingroup (associated with membership of the journal’s editorial board or a particular disciplinary or geographical background). However, judges’ ratings of journals in which they had published were more favorable when those journals had a low-quality reputation, and their ratings of journals that reflected their geographical and disciplinary affiliations were more favorable when those journals had a high-quality reputation. The findings are thus consistent with the view that identity concerns come to the fore in journal ratings when there is either a need to protect against personal identity threat or a meaningful opportunity to promote social identity

Cell proliferation within small intestinal crypts is the principal driving force for cell migration on villi

The functional integrity of the intestinal epithelial barrier relies on tight coordination of cell proliferation and migration, with failure to regulate these processes resulting in disease. It is not known whether cell proliferation is sufficient to drive epithelial cell migration during homoeostatic turnover of the epithelium. Nor is it known precisely how villus cell migration is affected when proliferation is perturbed. Some reports suggest that proliferation and migration may not be related while other studies support a direct relationship. We used established cell-tracking methods based on thymine analog cell labeling and developed tailored mathematical models to quantify cell proliferation and migration under normal conditions and when proliferation is reduced and when it is temporarily halted. We found that epithelial cell migration velocities along the villi are coupled to cell proliferation rates within the crypts in all conditions. Furthermore, halting and resuming proliferation results in the synchronized response of cell migration on the villi. We conclude that cell proliferation within the crypt is the primary force that drives cell migration along the villus. This methodology can be applied to interrogate intestinal epithelial dynamics and characterize situations in which processes involved in cell turnover become uncoupled, including pharmacological treatments and disease models

Genome-wide association study identifies 30 loci associated with bipolar disorder.

Bipolar disorder is a highly heritable psychiatric disorder. We performed a genome-wide association study (GWAS) including 20,352 cases and 31,358 controls of European descent, with follow-up analysis of 822 variants with P < 1 × 10-4 in an additional 9,412 cases and 137,760 controls. Eight of the 19 variants that were genome-wide significant (P < 5 × 10-8) in the discovery GWAS were not genome-wide significant in the combined analysis, consistent with small effect sizes and limited power but also with genetic heterogeneity. In the combined analysis, 30 loci were genome-wide significant, including 20 newly identified loci. The significant loci contain genes encoding ion channels, neurotransmitter transporters and synaptic components. Pathway analysis revealed nine significantly enriched gene sets, including regulation of insulin secretion and endocannabinoid signaling. Bipolar I disorder is strongly genetically correlated with schizophrenia, driven by psychosis, whereas bipolar II disorder is more strongly correlated with major depressive disorder. These findings address key clinical questions and provide potential biological mechanisms for bipolar disorder

Rapid automatized naming as an index of genetic liability to autism

This study investigated rapid automatized naming (RAN) ability in high functioning individuals with autism and parents of individuals with autism. Findings revealed parallel patterns of performance in parents and individuals with autism, where both groups had longer naming times than controls. Significant parent-child correlations were also detected, along with associations with language and personality features of the broad autism phenotype (retrospective reports of early language delay, socially reticent personality). Together, findings point towards RAN as a potential marker of genetic liability to autism

A Trait‐Based Framework for Assessing the Vulnerability of Marine Species to Human Impacts

Marine species and ecosystems are widely affected by anthropogenic stressors, ranging from pollution and fishing to climate change. Comprehensive assessments of how species and ecosystems are impacted by anthropogenic stressors are critical for guiding conservation and management investments. Previous global risk or vulnerability assessments have focused on marine habitats, or on limited taxa or specific regions. However, information about the susceptibility of marine species across a range of taxa to different stressors everywhere is required to predict how marine biodiversity will respond to human pressures. We present a novel framework that uses life-history traits to assess species’ vulnerability to a stressor, which we compare across more than 44,000 species from 12 taxonomic groups (classes). Using expert elicitation and literature review, we assessed every combination of each of 42 traits and 22 anthropogenic stressors to calculate each species’ or representative species group’s sensitivity and adaptive capacity to stressors, and then used these assessments to derive their overall relative vulnerability. The stressors with the greatest potential impact were related to biomass removal (e.g., fisheries), pollution, and climate change. The taxa with the highest vulnerabilities across the range of stressors were mollusks, corals, and echinoderms, while elasmobranchs had the highest vulnerability to fishing-related stressors. Traits likely to confer vulnerability to climate change stressors were related to the presence of calcium carbonate structures, and whether a species exists across the interface of marine, terrestrial, and atmospheric realms. Traits likely to confer vulnerability to pollution stressors were related to planktonic state, organism size, and respiration. Such a replicable, broadly applicable method is useful for informing ocean conservation and management decisions at a range of scales, and the framework is amenable to further testing and improvement. Our framework for assessing the vulnerability of marine species is the first critical step toward generating cumulative human impact maps based on comprehensive assessments of species, rather than habitats