Systems biological and mechanistic modelling of radiation-induced cancer

This paper summarises the five presentations at the First International Workshop on Systems Radiation Biology that were concerned with mechanistic models for carcinogenesis. The mathematical description of various hypotheses about the carcinogenic process, and its comparison with available data is an example of systems biology. It promises better understanding of effects at the whole body level based on properties of cells and signalling mechanisms between them. Of these five presentations, three dealt with multistage carcinogenesis within the framework of stochastic multistage clonal expansion models, another presented a deterministic multistage model incorporating chromosomal aberrations and neoplastic transformation, and the last presented a model of DNA double-strand break repair pathways for second breast cancers following radiation therapy

Discovery of the First Insect Nidovirus, a Missing Evolutionary Link in the Emergence of the Largest RNA Virus Genomes

Nidoviruses with large genomes (26.3–31.7 kb; ‘large nidoviruses’), including Coronaviridae and Roniviridae, are the most complex positive-sense single-stranded RNA (ssRNA+) viruses. Based on genome size, they are far separated from all other ssRNA+ viruses (below 19.6 kb), including the distantly related Arteriviridae (12.7–15.7 kb; ‘small nidoviruses’). Exceptionally for ssRNA+ viruses, large nidoviruses encode a 3′-5′exoribonuclease (ExoN) that was implicated in controlling RNA replication fidelity. Its acquisition may have given rise to the ancestor of large nidoviruses, a hypothesis for which we here provide evolutionary support using comparative genomics involving the newly discovered first insect-borne nidovirus. This Nam Dinh virus (NDiV), named after a Vietnamese province, was isolated from mosquitoes and is yet to be linked to any pathology. The genome of this enveloped 60–80 nm virus is 20,192 nt and has a nidovirus-like polycistronic organization including two large, partially overlapping open reading frames (ORF) 1a and 1b followed by several smaller 3′-proximal ORFs. Peptide sequencing assigned three virion proteins to ORFs 2a, 2b, and 3, which are expressed from two 3′-coterminal subgenomic RNAs. The NDiV ORF1a/ORF1b frameshifting signal and various replicative proteins were tentatively mapped to canonical positions in the nidovirus genome. They include six nidovirus-wide conserved replicase domains, as well as the ExoN and 2′-O-methyltransferase that are specific to large nidoviruses. NDiV ORF1b also encodes a putative N7-methyltransferase, identified in a subset of large nidoviruses, but not the uridylate-specific endonuclease that – in deviation from the current paradigm - is present exclusively in the currently known vertebrate nidoviruses. Rooted phylogenetic inference by Bayesian and Maximum Likelihood methods indicates that NDiV clusters with roniviruses and that its branch diverged from large nidoviruses early after they split from small nidoviruses. Together these characteristics identify NDiV as the prototype of a new nidovirus family and a missing link in the transition from small to large nidoviruses

Significance of vascular endothelial growth factor in growth and peritoneal dissemination of ovarian cancer

Vascular endothelial growth factor (VEGF) is a key regulator of angiogenesis which drives endothelial cell survival, proliferation, and migration while increasing vascular permeability. Playing an important role in the physiology of normal ovaries, VEGF has also been implicated in the pathogenesis of ovarian cancer. Essentially by promoting tumor angiogenesis and enhancing vascular permeability, VEGF contributes to the development of peritoneal carcinomatosis associated with malignant ascites formation, the characteristic feature of advanced ovarian cancer at diagnosis. In both experimental and clinical studies, VEGF levels have been inversely correlated with survival. Moreover, VEGF inhibition has been shown to inhibit tumor growth and ascites production and to suppress tumor invasion and metastasis. These findings have laid the basis for the clinical evaluation of agents targeting VEGF signaling pathway in patients with ovarian cancer. In this review, we will focus on VEGF involvement in the pathophysiology of ovarian cancer and its contribution to the disease progression and dissemination

Determinants of recovery from post-COVID-19 dyspnoea: analysis of UK prospective cohorts of hospitalised COVID-19 patients and community-based controls

Background The risk factors for recovery from COVID-19 dyspnoea are poorly understood. We investigated determinants of recovery from dyspnoea in adults with COVID-19 and compared these to determinants of recovery from non-COVID-19 dyspnoea. Methods We used data from two prospective cohort studies: PHOSP-COVID (patients hospitalised between March 2020 and April 2021 with COVID-19) and COVIDENCE UK (community cohort studied over the same time period). PHOSP-COVID data were collected during hospitalisation and at 5-month and 1-year follow-up visits. COVIDENCE UK data were obtained through baseline and monthly online questionnaires. Dyspnoea was measured in both cohorts with the Medical Research Council Dyspnoea Scale. We used multivariable logistic regression to identify determinants associated with a reduction in dyspnoea between 5-month and 1-year follow-up. Findings We included 990 PHOSP-COVID and 3309 COVIDENCE UK participants. We observed higher odds of improvement between 5-month and 1-year follow-up among PHOSP-COVID participants who were younger (odds ratio 1.02 per year, 95% CI 1.01–1.03), male (1.54, 1.16–2.04), neither obese nor severely obese (1.82, 1.06–3.13 and 4.19, 2.14–8.19, respectively), had no pre-existing anxiety or depression (1.56, 1.09–2.22) or cardiovascular disease (1.33, 1.00–1.79), and shorter hospital admission (1.01 per day, 1.00–1.02). Similar associations were found in those recovering from non-COVID-19 dyspnoea, excluding age (and length of hospital admission). Interpretation Factors associated with dyspnoea recovery at 1-year post-discharge among patients hospitalised with COVID-19 were similar to those among community controls without COVID-19. Funding PHOSP-COVID is supported by a grant from the MRC-UK Research and Innovation and the Department of Health and Social Care through the National Institute for Health Research (NIHR) rapid response panel to tackle COVID-19. The views expressed in the publication are those of the author(s) and not necessarily those of the National Health Service (NHS), the NIHR or the Department of Health and Social Care. COVIDENCE UK is supported by the UK Research and Innovation, the National Institute for Health Research, and Barts Charity. The views expressed are those of the authors and not necessarily those of the funders

Clinical characteristics with inflammation profiling of long COVID and association with 1-year recovery following hospitalisation in the UK: a prospective observational study

Background No effective pharmacological or non-pharmacological interventions exist for patients with long COVID. We aimed to describe recovery 1 year after hospital discharge for COVID-19, identify factors associated with patient-perceived recovery, and identify potential therapeutic targets by describing the underlying inflammatory profiles of the previously described recovery clusters at 5 months after hospital discharge. Methods The Post-hospitalisation COVID-19 study (PHOSP-COVID) is a prospective, longitudinal cohort study recruiting adults (aged ≥18 years) discharged from hospital with COVID-19 across the UK. Recovery was assessed using patient-reported outcome measures, physical performance, and organ function at 5 months and 1 year after hospital discharge, and stratified by both patient-perceived recovery and recovery cluster. Hierarchical logistic regression modelling was performed for patient-perceived recovery at 1 year. Cluster analysis was done using the clustering large applications k-medoids approach using clinical outcomes at 5 months. Inflammatory protein profiling was analysed from plasma at the 5-month visit. This study is registered on the ISRCTN Registry, ISRCTN10980107, and recruitment is ongoing. Findings 2320 participants discharged from hospital between March 7, 2020, and April 18, 2021, were assessed at 5 months after discharge and 807 (32·7%) participants completed both the 5-month and 1-year visits. 279 (35·6%) of these 807 patients were women and 505 (64·4%) were men, with a mean age of 58·7 (SD 12·5) years, and 224 (27·8%) had received invasive mechanical ventilation (WHO class 7–9). The proportion of patients reporting full recovery was unchanged between 5 months (501 [25·5%] of 1965) and 1 year (232 [28·9%] of 804). Factors associated with being less likely to report full recovery at 1 year were female sex (odds ratio 0·68 [95% CI 0·46–0·99]), obesity (0·50 [0·34–0·74]) and invasive mechanical ventilation (0·42 [0·23–0·76]). Cluster analysis (n=1636) corroborated the previously reported four clusters: very severe, severe, moderate with cognitive impairment, and mild, relating to the severity of physical health, mental health, and cognitive impairment at 5 months. We found increased inflammatory mediators of tissue damage and repair in both the very severe and the moderate with cognitive impairment clusters compared with the mild cluster, including IL-6 concentration, which was increased in both comparisons (n=626 participants). We found a substantial deficit in median EQ-5D-5L utility index from before COVID-19 (retrospective assessment; 0·88 [IQR 0·74–1·00]), at 5 months (0·74 [0·64–0·88]) to 1 year (0·75 [0·62–0·88]), with minimal improvements across all outcome measures at 1 year after discharge in the whole cohort and within each of the four clusters. Interpretation The sequelae of a hospital admission with COVID-19 were substantial 1 year after discharge across a range of health domains, with the minority in our cohort feeling fully recovered. Patient-perceived health-related quality of life was reduced at 1 year compared with before hospital admission. Systematic inflammation and obesity are potential treatable traits that warrant further investigation in clinical trials. Funding UK Research and Innovation and National Institute for Health Research

Assessing the “social brain” in dementia: Applying TASIT-S

The ability to recognise how other people are feeling and make judgements based on theirinferred thoughts is essential for successful social interactions, and is thought to dependon a complex network of brain regions, commonly referred to as the “social brain”. Theseabilities, together referred to as social cognition, are increasingly recognised as beingcompromised in some dementia syndromes, particularly in behavioural-variant frontotemporaldementia (bvFTD), which is characterised by changes in personality and socialconduct. Whether social cognition is impaired in other dementia syndromes, such asAlzheimer's disease (AD), or whether lower performance reflects general cognitiveimpairment, is less well established. Furthermore, ecologically valid tests with knownneurobiological correlates are currently lacking. Here, we investigated performance on anewly devised short version of The Awareness of Social Inference Test (TASIT-S) andassociated neural correlates in 25 bvFTD patients, 23 AD patients and 25 healthy controls.On Part 1-Emotion Evaluation, only bvFTD were impaired (p ¼ .033) (AD vs. controls:p ¼ .475) after controlling for cognitive impairment and education. On Part 2-Social Inference,both bvFTD and AD showed intact ability to interpret sincere exchanges (pvalues > .05). Importantly, however, bvFTD patients were impaired in interpreting sarcasm(p ¼ .008), whereas AD performed within normal limits (p ¼ .477). Voxel-basedmorphometry analyses demonstrated correlations between TASIT-S Part 1 performanceand integrity of emotion processing brain regions (amygdala, insula, fusiform) and Part 2performance with theory of mind brain regions (precuneus, temporal pole). These resultsdemonstrate the utility of TASIT-S in identifying social cognition impairment in dementiaand reveal that TASIT-S taps into integrity of key regions within the “social brain

Using a second-person approach to identify disease-specific profiles of social behavior in frontotemporal dementia and Alzheimer's disease.

Changes in social behavior are recognized as potential symptoms of behavioral-variant frontotemporal dementia (bvFTD) and semantic dementia (SD), yet objective ways to assess these behaviors in natural social situations are lacking. This study takes a truly social (or second-person) approach and examines changes in real-world social behavior in different dementia syndromes, by analyzing non-scripted social interactions in bvFTD patients (n = 20) and SD patients (n = 20), compared to patients with Alzheimer's disease (AD) (n = 20). Video recordings of 10-min conversations between patients and behavioral neurologists were analyzed for the presence of socially engaging (e.g., nodding, smiling, gesturing) and disengaging behavior (e.g., avoiding eye contact, self-grooming, interrupting). Results demonstrated disease-specific profiles, with bvFTD patients showing less nodding and more looking away than AD, and SD patients showing more gesturing than AD. A principal components analysis revealed the presence of four unobserved components, showing atypical disengaging patterns of behavior. Whole-brain voxel-based morphometry analyses revealed distinct neurobiological bases for each of these components, with the brain regions identified previously associated with behavior selection, abstract mentalization and processing of multi-sensory and socially-relevant information, in mediating socially engaging and disengaging behavior. This study demonstrates the utility of systematic behavioral observation of social interactions in the differential diagnosis of dementia

Design Patterns for Spatio-temporal Processes

Time is an essential dimension to analyse and understand real-world evolution. Although many temporal extensions to spatial models have been proposed, there is still a need to define modelling methods to describe and represent real-world phenomena. This paper presents a set of design patterns modelling spatio-temporal processes expressed in an object-relationship data model. The proposed framework is based on an analysis of spatio-temporal processes and on properties of object-oriented and entity-relationship data models. 1. Introduction Geographical processes involve entities and changes that are located in both space and time. Therefore, building a taxonomy of spatio-temporal processes (STP) implies an analysis of the representation of facts and events within a space-time framework. According to Peuquet (1994), scientists retain two complementary ontological views to define space-time structures. The absolute approach (introduced by Newton) identifies space as a collection of points..