An Inducible Luminescent System to Explore Parkinson's Disease-Associated Genes.

With emerging genetic association studies, new genes and pathways are revealed as causative factors in the development of Parkinson's disease (PD). However, many of these PD genes are poorly characterized in terms of their function, subcellular localization, and interaction with other components in cellular pathways. This represents a major obstacle towards a better understanding of the molecular causes of PD, with deeper molecular studies often hindered by a lack of high-quality, validated antibodies for detecting the corresponding proteins of interest.

Stratified epidemic model using a latent marked Hawkes process.

We extend the unstructured homogeneously mixing epidemic model introduced by Lamprinakou et al. (2023) to a finite population stratified by age bands. We model the actual unobserved infections using a latent marked Hawkes process and the reported aggregated infections as random quantities driven by the underlying Hawkes process.

Analysis of the Structure of Heavy Ion Irradiated LaFeO Using Grazing Angle X-ray Absorption Spectroscopy.

Crystalline ceramics are candidate materials for the immobilization of radionuclides, particularly transuranics (such as U, Pu, and Am), arising from the nuclear fuel cycle. Due to the α-decay of transuranics and the associated recoil of the parent nucleus, crystalline materials may eventually be rendered amorphous through changes to the crystal lattice caused by these recoil events. Previous work has shown irradiation of titanate-based ceramics to change the local cation environment significantly, particularly in the case of Ti which was shown to change from 6- to 5-fold coordination.

Using a latent Hawkes process for epidemiological modelling.

Understanding the spread of COVID-19 has been the subject of numerous studies, highlighting the significance of reliable epidemic models. Here, we introduce a novel epidemic model using a latent Hawkes process with temporal covariates for modelling the infections. Unlike other models, we model the reported cases via a probability distribution driven by the underlying Hawkes process.

A COVID-19 model for local authorities of the United Kingdom.

We propose a new framework to model the COVID-19 epidemic of the United Kingdom at the local authority level. The model fits within a general framework for semi-mechanistic Bayesian models of the epidemic based on renewal equations, with some important innovations, including a random walk modelling the reproduction number, incorporating information from different sources, including surveys to estimate the time-varying proportion of infections that lead to reported cases or deaths, and modelling the underlying infections as latent random variables. The model is designed to be updated daily using publicly available data.

Effects of Acute 2,3,7,8-Tetrachlorodibenzo-p-Dioxin Exposure on the Circulating and Cecal Metabolome Profile.

2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) is a polyhalogenated planar hydrocarbon belonging to a group of highly toxic and persistent environmental contaminants known as "dioxins". TCDD is an animal teratogen and carcinogen that is well characterized for causing immunosuppression through activation of aryl hydrocarbon receptor (AHR). In this study, we investigated the effect of exposure of mice to an acute dose of TCDD on the metabolic profile within the serum and cecal contents to better define the effects of TCDD on host physiology.

Changing composition of SARS-CoV-2 lineages and rise of Delta variant in England.

Background: Since its emergence in Autumn 2020, the SARS-CoV-2 Variant of Concern (VOC) B.1.1.

Comparing the responses of the UK, Sweden and Denmark to COVID-19 using counterfactual modelling.

The UK and Sweden have among the worst per-capita COVID-19 mortality in Europe. Sweden stands out for its greater reliance on voluntary, rather than mandatory, control measures. We explore how the timing and effectiveness of control measures in the UK, Sweden and Denmark shaped COVID-19 mortality in each country, using a counterfactual assessment: what would the impact have been, had each country adopted the others' policies? Using a Bayesian semi-mechanistic model without prior assumptions on the mechanism or effectiveness of interventions, we estimate the time-varying reproduction number for the UK, Sweden and Denmark from daily mortality data.

Skin Mast Cell-Driven Ceramides Drive Early Apoptosis in Pre-Symptomatic Eczema in Mice.

Atopic dermatitis (AD or eczema) is the most common chronic inflammatory skin disorder worldwide. Ceramides (Cer) maintain skin barrier functions, which are disrupted in lesional skin of AD patients. However, Cer status during the pre-lesional phase of AD is not well defined.

Modelling the impact of the tier system on SARS-CoV-2 transmission in the UK between the first and second national lockdowns.

Objective: To measure the effects of the tier system on the COVID-19 pandemic in the UK between the first and second national lockdowns, before the emergence of the B.1.1.

Genomics and epidemiology of the P.1 SARS-CoV-2 lineage in Manaus, Brazil.

Cases of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in Manaus, Brazil, resurged in late 2020 despite previously high levels of infection. Genome sequencing of viruses sampled in Manaus between November 2020 and January 2021 revealed the emergence and circulation of a novel SARS-CoV-2 variant of concern. Lineage P.

Assessing transmissibility of SARS-CoV-2 lineage B.1.1.7 in England.

The SARS-CoV-2 lineage B.1.1.

Genomics and epidemiology of a novel SARS-CoV-2 lineage in Manaus, Brazil.

Cases of SARS-CoV-2 infection in Manaus, Brazil, resurged in late 2020, despite high levels of previous infection there. Through genome sequencing of viruses sampled in Manaus between November 2020 and January 2021, we identified the emergence and circulation of a novel SARS-CoV-2 variant of concern, lineage P.1, that acquired 17 mutations, including a trio in the spike protein (K417T, E484K and N501Y) associated with increased binding to the human ACE2 receptor.

Age groups that sustain resurging COVID-19 epidemics in the United States.

After initial declines, in mid-2020 a resurgence in transmission of novel coronavirus disease (COVID-19) occurred in the United States and Europe. As efforts to control COVID-19 disease are reintensified, understanding the age demographics driving transmission and how these affect the loosening of interventions is crucial. We analyze aggregated, age-specific mobility trends from more than 10 million individuals in the United States and link these mechanistically to age-specific COVID-19 mortality data.

High-Entropy Alloys for Advanced Nuclear Applications.

The expanded compositional freedom afforded by high-entropy alloys (HEAs) represents a unique opportunity for the design of alloys for advanced nuclear applications, in particular for applications where current engineering alloys fall short. This review assesses the work done to date in the field of HEAs for nuclear applications, provides critical insight into the conclusions drawn, and highlights possibilities and challenges for future study. It is found that our understanding of the irradiation responses of HEAs remains in its infancy, and much work is needed in order for our knowledge of any single HEA system to match our understanding of conventional alloys such as austenitic steels.

State-level tracking of COVID-19 in the United States.

As of 1st June 2020, the US Centres for Disease Control and Prevention reported 104,232 confirmed or probable COVID-19-related deaths in the US. This was more than twice the number of deaths reported in the next most severely impacted country. We jointly model the US epidemic at the state-level, using publicly available death data within a Bayesian hierarchical semi-mechanistic framework.

Inference of COVID-19 epidemiological distributions from Brazilian hospital data.

Knowing COVID-19 epidemiological distributions, such as the time from patient admission to death, is directly relevant to effective primary and secondary care planning, and moreover, the mathematical modelling of the pandemic generally. We determine epidemiological distributions for patients hospitalized with COVID-19 using a large dataset ( = 21 000 - 157 000) from the Brazilian Sistema de Informação de Vigilância Epidemiológica da Gripe database. A joint Bayesian subnational model with partial pooling is used to simultaneously describe the 26 states and one federal district of Brazil, and shows significant variation in the mean of the symptom-onset-to-death time, with ranges between 11.

Estimating the effects of non-pharmaceutical interventions on COVID-19 in Europe.

Following the detection of the new coronavirus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its spread outside of China, Europe has experienced large epidemics of coronavirus disease 2019 (COVID-19). In response, many European countries have implemented non-pharmaceutical interventions, such as the closure of schools and national lockdowns. Here we study the effect of major interventions across 11 European countries for the period from the start of the COVID-19 epidemics in February 2020 until 4 May 2020, when lockdowns started to be lifted.

CD44 deletion leading to attenuation of experimental autoimmune encephalomyelitis results from alterations in gut microbiome in mice.

Dysbiosis in gut microbiome has been shown to be associated with inflammatory and autoimmune diseases. Previous studies from our laboratory demonstrated the pivotal role played by CD44 in the regulation of EAE, a murine model of multiple sclerosis. In the current study, we determined whether these effects resulted from an alteration in gut microbiota and the short-chain fatty acid (SCFA) production in CD44 knockout (CD44KO) mice.

An omnibus CUSUM chart for monitoring time to event data.

A non-parametric method is proposed for monitoring time-to-event data. A cumulative sum chart is constructed that is able to detect an unknown out-of-control state. This method exploits the absolute differences between the Kaplan-Meier estimator and the in-control distribution over specific time intervals.