Publications by authors named "Alice Milne"

Article Synopsis
  • Despite progress in understanding long COVID, key aspects are still unclear, necessitating more research for better symptom management.
  • The study involved interviews with 12 long COVID patients, examining their experiences and psychological needs post-hospitalization for COVID-19.
  • Findings highlight the severe psychological effects of emergency hospitalization on long COVID patients and advocate for early psychological support and improved patient advocacy during critical medical decisions in future pandemics.
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Pleural infection is usually treated with empirical broad-spectrum antibiotics, but limited data exist on their penetrance into the infected pleural space. We performed a pharmacokinetic study analysing the concentration of five intravenous antibiotics across 146 separate time points in 35 patients (amoxicillin, metronidazole, piperacillin-tazobactam, clindamycin and cotrimoxazole). All antibiotics tested, apart from co-trimoxazole, reach pleural fluid levels equivalent to levels within the blood and well above the relevant minimum inhibitory concentrations.

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Grazing livestock plays an important role in the context of food security, agricultural sustainability and climate change. Understanding how livestock move and interact with their environment may offer new insights on how grazing practices impact soil and ecosystem functions at spatial and temporal scales where knowledge is currently limited. We characterized daily and seasonal grazing patterns using Global Positioning System (GPS) data from two grazing strategies: conventionally- and rotationally-grazed pastures.

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Coronavirus disease-19 (COVID-19) causes immune perturbations which may persist long term, and patients frequently report ongoing symptoms for months after recovery. We assessed immune activation at 3-12 months post hospital admission in 187 samples from 63 patients with mild, moderate, or severe disease and investigated whether it associates with long COVID. At 3 months, patients with severe disease displayed persistent activation of CD4 and CD8 T-cells, based on expression of HLA-DR, CD38, Ki67, and granzyme B, and elevated plasma levels of interleukin-4 (IL-4), IL-7, IL-17, and tumor necrosis factor-alpha (TNF-α) compared to mild and/or moderate patients.

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Community supported agriculture (CSA) schemes (programs) provide an alternative means for obtaining produce, through direct purchase from farms. They are also often driven by a vision of transforming the current mainstream food system and seek to build a community of people who support this vision. Social capital refers to the networks and ties between people and groups and the impact of these ties on access to influence, information, opportunity, and ability to organize.

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Background: Patients with COVID-19 are at increased risk of thrombosis, which is associated with altered platelet function and coagulopathy, contributing to excess mortality.

Objectives: To characterize the mechanism of altered platelet function in COVID-19 patients.

Methods: The platelet proteome, platelet functional responses, and platelet-neutrophil aggregates were compared between patients hospitalized with COVID-19 and healthy control subjects using tandem mass tag proteomic analysis, Western blotting, and flow cytometry.

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Background: Pleural infection is a complex condition with a considerable healthcare burden. The average hospital stay for pleural infection is 14 days. Current standard of care defaults to chest tube insertion and intravenous antibiotics.

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Marked reductions in serum iron concentrations are commonly induced during the acute phase of infection. This phenomenon, termed hypoferremia of inflammation, leads to inflammatory anemia, but could also have broader pathophysiological implications. In patients with coronavirus disease 2019 (COVID-19), hypoferremia is associated with disease severity and poorer outcomes, although there are few reported cohorts.

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Background: Natural enemy pest control is becoming more desirable as restrictions increase on pesticide use. Carabid beetles are proven agents of natural-enemy pest control (NPC), controlling pests and weeds in crop areas. Agro-ecological measures can be effective for boosting carabid abundance and associated NPC, but the benefits of specific interventions to production are seldom communicated to farmers.

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Agriculture is challenged to produce healthy food and to contribute to cleaner energy whilst mitigating climate change and protecting ecosystems. To achieve this, policy-driven scenarios need to be evaluated with available data and models to explore trade-offs with robust accounting for the uncertainty in predictions. We developed a novel model ensemble using four complementary state-of-the-art agroecosystems models to explore the impacts of land management change.

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We summarise modelling studies of the most economically important cassava diseases and arthropods, highlighting research gaps where modelling can contribute to the better management of these in the areas of surveillance, control, and host-pest dynamics understanding the effects of climate change and future challenges in modelling. For over 30 years, experimental and theoretical studies have sought to better understand the epidemiology of cassava diseases and arthropods that affect production and lead to considerable yield loss, to detect and control them more effectively. In this review, we consider the contribution of modelling studies to that understanding.

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The brain is highly sensitive to auditory regularities and exploits the predictable order of sounds in many situations, from parsing complex auditory scenes, to the acquisition of language. To understand the impact of stimulus predictability on perception, it is important to determine how the detection of predictable structure influences processing and attention. Here, we use pupillometry to gain insight into the effect of sensory regularity on arousal.

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Peak flow events can lead to flooding which can have negative impacts on human life and ecosystem services. Therefore, accurate forecasting of such peak flows is important. Physically-based process models are commonly used to simulate water flow, but they often under-predict peak events (i.

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Soybean (Glycine max) offers an important source of plant-based protein. Currently much of Europe's soybean is imported, but there are strong economic and agronomic arguments for boosting local production. Soybean is grown in central and eastern Europe but is less favoured in the North due to climate.

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Online experimental platforms can be used as an alternative to, or complement, lab-based research. However, when conducting auditory experiments via online methods, the researcher has limited control over the participants' listening environment. We offer a new method to probe one aspect of that environment, headphone use.

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The longer-term consequences of SARS-CoV-2 infection are uncertain. Consecutive patients hospitalised with COVID-19 were prospectively recruited to this observational study (n=163). At 8-12 weeks postadmission, survivors were invited to a systematic clinical follow-up.

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To manage agricultural landscapes more sustainably, we must understand and quantify the synergies and trade-offs between environmental impact, production, and other ecosystem services. Models play an important role in this type of analysis as generally it is infeasible to test multiple scenarios by experiment. These models can be linked with algorithms that optimise for multiple objectives by searching a space of allowable management interventions (the control variables).

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Predicting the response of biological communities to changes in the environment or management is a fundamental pursuit of community ecology. Meeting this challenge requires the integration of multiple processes: habitat filtering, niche differentiation, biotic interactions, competitive exclusion, and stochastic demographic events. Most approaches to this long-standing problem focus either on the role of the environment, using trait-based filtering approaches, or on quantifying biotic interactions with process-based community dynamics models.

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Diseases in humans, animals and plants remain an important challenge in our society. Effective control of invasive pathogens often requires coordinated concerted action of a large group of stakeholders. Both epidemiological and human behavioural factors influence the outcome of a disease control campaign.

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The ability to sustain attention on a task-relevant sound source while avoiding distraction from concurrent sounds is fundamental to listening in crowded environments. We aimed to (a) devise an experimental paradigm with which this aspect of listening can be isolated and (b) evaluate the applicability of pupillometry as an objective measure of sustained attention in young and older populations. We designed a paradigm that continuously measured behavioral responses and pupillometry during 25-s trials.

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Efficient farm management can be aided by the identification of zones in the landscape. These zones can be informed from different measured variables by ensuring a sense of spatial coherence. Forming spatially coherent zones is an established method in the literature, but has been found to perform poorly when data are sparse.

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Agricultural landscapes provide many functions simultaneously including food production, regulation of water and regulation of greenhouse gases. Thus, it is challenging to make land management decisions, particularly transformative changes, that improve on one function without unintended consequences for other functions. To make informed decisions the trade-offs between different landscape functions must be considered.

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Background: The efficacy of pre-emergence herbicides within fields is spatially variable as a consequence of soil heterogeneity. We quantified the effect of soil organic matter on the efficacy of two pre-emergence herbicides, flufenacet and pendimethalin, against Alopecurus myosuroides and investigated the implications of variation in organic matter for weed management using a crop-weed competition model.

Results: Soil organic matter played a critical role in determining the level of control achieved.

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We describe a model framework that simulates spatial and temporal interactions in agricultural landscapes and that can be used to explore trade-offs between production and environment so helping to determine solutions to the problems of sustainable food production. Here we focus on models of agricultural production, water movement and nutrient flow in a landscape. We validate these models against data from two long-term experiments, (the first a continuous wheat experiment and the other a permanent grass-land experiment) and an experiment where water and nutrient flow are measured from isolated catchments.

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