Biology subjects

Holden, J.

Publications and source records attributed to Holden, J..

5 recordsLinked to original sources

bioRxiv2026

HuR Regulates GATA3-Driven Type 2 Inflammation in CD4⁺ T cells and ILC2 in Airway Inflammation

Type 2-high asthma is driven by coordinated GATA3-dependent programs in CD4 T cells and group 2 innate lymphoid cells (ILC2). Although biologics targeting Th2 cytokines benefit subsets of patients, many remain symptomatic, suggesting upstream regulatory mechanisms may sustain type 2 inflammation. We investigated whether the RNA-binding protein HuR (ELAVL1) functions as a post-transcriptional regulator of GATA3-driven type 2 inflammation in allergic asthma. Using a house dust mite (HDM) model in vivo, HuR inhibition with KH-3 reduced lung inflammation, suppressed Th2 cytokine expression, accelerated Gata3 mRNA decay in lung CD4 T cells, and attenuated airway hyperresponsiveness toward control levels. In ex vivo-activated human lung CD4 T cells, KH-3 accelerated GATA3 mRNA decay with minimal effects on RORC or TBX21 and selectively reduced Th2 cytokine secretion, while IL-10 and IL-2 were unchanged. Similarly, ILC2s isolated from PBMCs of type 2-high asthmatic donors showed reduced GATA3 mRNA stability and diminished Th2 cytokine production following KH-3 treatment. Single-cell transcriptomic analysis of bronchoalveolar lavage fluid after allergen challenge in asthmatic subjects demonstrated co-enrichment of ELAVL1 and GATA3 within Th2 clusters in human airways. Together, these findings identify HuR as a therapeutically targetable upstream regulator of GATA3-driven type 2 inflammation in allergic asthma.

immunology↗

bioRxiv2023

Estimating the reproduction number, R0, from agent-based models of tree disease spread

Tree populations worldwide are facing an unprecedented threat from a variety of tree diseases and invasive pests. Their spread, exacerbated by increasing globalisation and climate change, has an enormous environmental, economic and social impact. Computational agent-based models are a popular tool for describing and forecasting the spread of tree diseases due to their flexibility and ability to reveal collective behaviours. In this paper we present a versatile agentbased model with a Gaussian infectivity kernel to describe the spread of a generic tree disease through a synthetic treescape. We then explore several methods of calculating the basic reproduction number R0, a characteristic measurement of disease infectivity, defining the expected number of new infections resulting from one newly infected individual throughout their infectious period. It is a useful comparative summary parameter of a disease and can be used to explore the threshold dynamics of epidemics through mathematical models. We demonstrate several methods of estimating R0 through the agent-based model, including contact tracing, inferring the Kermack-McKendrick SIR model parameters using the linear noise approximation, and an analytical approximation. As an illustrative example, we then use the model and each of the methods to calculate estimates of R0 for the ash dieback epidemic in the UK.

ecology↗

bioRxiv2020

Impact of trimethoprim on the river microbiome and antimicrobial resistance.

Recent evidence suggests that anthropogenic activity can increase the levels of antimicrobial resistance (AMR) in the environment. Rivers and waterways are significant examples of environmental settings that have become repositories of antibiotics and antibiotic resistance genes (ARGs). Our recent study quantified drug concentrations in freshwater samples taken at a range of sites located on the Thames catchment; the highest levels of antibiotics and other drugs were recorded downstream of waste water treatment plants (WWTPs). One specific antibiotic: Trimethoprim (TMP) was shown at elevated concentrations reaching 2000ng/L at particular sites. We have also shown a correlative relationship between the residue of TMP and the prevalence of sulfonamide antibiotic resistance genes such as sul1. Despite this, there is still no evidence of a causative relationship between TMP concentrations and the prevalence of the ARGs at river sites. The aim of the current study was to conduct in-depth analysis using a combination of large metagenomic, geospatial and chemical datasets, in order to conduct a comparison between those sites with the highest TMP and lowest TMP levels across the Thames catchment. We aimed to establish the proximity of these sites to WWTPs, their population equivalence (PE) and land coverage. A secondary aim was to investigate seasonal variation in TMP and ARGs. Exploring these factors will help to decipher the clinical relevance of ARG accumulation at river sites. A significant correlation was shown between TMP levels at river sites and their distance downstream from a WWTP. Three sites located on the Rivers Cut and Ray showed significantly higher TMP concentrations in winter compared to summer. The population equivalence (PE) for sites with the highest TMP levels was significantly higher than those with the lowest levels. The land coverage of sites with the highest TMP levels was significantly more urban/suburban than sites with the lowest TMP concentrations, which were found to be significantly more arable. Five ARGs relevant to TMP and sulfonamides were identified across the Thames catchment. The most prevalent ARG was sul1, which was significantly more prevalent in winter compared to summer. By contrast sul2 was found to be significantly more prevalent in summer compared to winter at a site on the River Coln. The prevalence of the class 1 integron marker gene (inti1) did not differ significantly by season or between sites with the highest/lowest TMP levels.

microbiology↗

bioRxiv2019

Contextualising UK moorland burning studies: geographical versus potential sponsorship-bias effects on research conclusions

O_LIIt has recently been claimed that geographical variability resulted in false conclusions from some studies examining the impacts of prescribed moorland burning, including the Effects of Moorland Burning on the Ecohydrology of River basins (EMBER) project. We provide multiple lines of evidence to contradict these claims and show that the EMBER results are reliable.\nC_LIO_LIA systematic review of the literature also confirms that EMBER conclusions were not out of line with the majority of other published UK studies on responses to prescribed burning of Sphagnum growth/abundance, soil properties, hydrological change, or peat exposure and erosion.\nC_LIO_LIWe suggest that sponsorship-bias is associated with some recent research conclusions related to moorland burning. Thus, it is of grave concern when sponsorship or other potential conflicts of interest are not declared on publications related to moorland burning.\nC_LIO_LIWe show that sponsorship and other conflicts of interest were not declared on a recent publication that criticised the EMBER project, thereby entirely undermining that critical assessment.\nC_LIO_LIPolicy implications: The EMBER findings are robust. Our study suggests that publications on moorland burning that have been funded by pro-burning groups should be treated with extreme caution by the policy community. Publications that have been shown to have failed to declare conflicts of interest from the outset, when first submitted to a journal, should be disregarded by the policy community because peer reviewers and editors may have been unable to evaluate those pieces of work properly.\nC_LI

ecology↗

bioRxiv2019

Accuracy of different modalities of reaction time testing: Implications for online cognitive assessment tools.

Reaction time testing is widely used in computerized cognitive assessments, and clinical studies have repeatedly shown it to be a sensitive indicator of cognitive function. Typically, the reaction time test is administered by presenting a subject with a visual stimulus on a computer monitor and prompting the individual to respond (via keypad or computer mouse) as quickly as possible. The individuals reaction time is calculated as the interval between presentation of the stimulus and the time recorded from the mechanical response. However, there are many inherent latencies and variabilities that may be introduced to the measure by both hardware (computer monitor and mouse) and software (operating system). Because of these delays, we hypothesized that a comparison of hardware protocols (excluding human response) would demonstrate significant differences in the resulting reaction time measures. To simulate the delays of various components of the common systems used to obtain reaction time, we conducted a simple experiment in which either a visual or tactile stimulus evoked a movement from a mechanical transducer to respond to a computer peripheral or a dedicated response device. In the first condition, a simulated visual reaction time test was conducted by flashing a visual stimulus on a computer monitor. The stimulus was detected by a dedicated light sensor, and a linear actuator delivered the mechanical response via computer mouse. The second test condition employed a mobile device as the medium for the visual stimulus, and the mechanical response was delivered to the mobile devices touchscreen. The third and fourth test conditions simulated tactile reaction time tests in which the stimulus was generated by a dedicated hardware device. The third condition simulated a tactile stimulus, which was detected by a mechanical switch, and again a hardware device delivered the response via computer mouse. The fourth condition also simulated a tactile stimulus, but the response was delivered by a dedicated hardware device designed to store the interval between stimulus delivery and stimulus response. There were significant differences in the range of responses recorded from the four different conditions with the reaction time collected from a visual stimulus on a mobile device being the worst and the device with dedicated hardware designed for the task being the best. The results suggest that some of the commonly used visual tasks on consumer grade computers could be introducing significant errors for reaction time testing and that dedicated hardware designed for the reaction time task is needed to minimize testing errors.

bioengineering↗