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Article ; Online: Epidemiology of Escherichia coli bloodstream infection antimicrobial resistance trends across South West England during the first 2 years of the coronavirus disease 2019 pandemic response.

Stanley, Jack / Sullivan, Brian / Dowsey, Andrew W / Jones, Koren / Beck, Charles R

Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases

2024

Abstract: Objectives: Between 2016 and 2019, the proportion of Escherichia coli bloodstream infection (BSI) with resistance to at least one antibiotic increased nationally. Public health interventions implemented in response to the COVID-19 pandemic changed ... ...

Abstract	Objectives: Between 2016 and 2019, the proportion of Escherichia coli bloodstream infection (BSI) with resistance to at least one antibiotic increased nationally. Public health interventions implemented in response to the COVID-19 pandemic changed population contact patterns and healthcare systems, with consequent effects on epidemiological trends of numerous pathogens. We investigated the impact of COVID-19 restrictions on epidemiological trends of E. coli BSI antimicrobial resistance (AMR) across South West England. Methods: We undertook a retrospective ecological analysis utilizing routine surveillance data of E. coli BSI cases reported to the UK Health Security Agency between 2016 and 2021. We analysed AMR trends for antimicrobial agents including amoxicillin-clavulanate, ciprofloxacin, piperacillin-tazobactam, gentamicin, third-generation cephalosporins and carbapenems before and after the implementation of COVID-19 restrictions (23 March 2020) using Bayesian segmented regression. Results: We identified 19 055 cases. A total of 50.2% were male. Median age was 76 (interquartile range, 65-85 years). Piperacillin-tazobactam (-2.90% [95% highest density interval {HDI} -4.51%, -0.48%]) and ciprofloxacin (-2.40% [95% HDI -4.35%, 0.48%]) resistance demonstrated immediate step changes at the implementation of COVID-19 restrictions. Gentamicin (odds ratio [OR] 0.92 [95% HDI 0.76, 1.12]) and third-generation cephalosporins (OR 0.95 [95% HDI 0.80, 1.14]) exhibited decreasing annual resistance trends after the implementation of COVID-19 restrictions, with moderate evidence for a lower OR after restrictions as compared to the period before (gentamicin Bayes Factor = 5.10, third-generation cephalosporins Bayes Factor = 6.67). Discussion: COVID-19 restrictions led to abrupt and longer term changes to E.coli BSI AMR. The immediate effects suggest altered transmission, whereas changes to resistant E. coli reservoirs may explain trend effects.
Language	English
Publishing date	2024-03-23
Publishing country	England
Document type	Journal Article
ZDB-ID	1328418-6
ISSN	1469-0691 ; 1470-9465 ; 1198-743X
ISSN (online)	1469-0691
ISSN	1470-9465 ; 1198-743X
DOI	10.1016/j.cmi.2024.03.018
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Article ; Online: Uncertainty-Aware Protein-Level Quantification and Differential Expression Analysis of Proteomics Data with seaMass.

Phillips, Alexander M / Unwin, Richard D / Hubbard, Simon J / Dowsey, Andrew W

Methods in molecular biology (Clifton, N.J.)

2022 Volume 2426, Page(s) 141–162

Abstract: seaMass is an R package for protein-level quantification, normalization, and differential expression analysis of proteomics mass spectrometry data after peptide identification, protein grouping, and feature-level quantification. Using the concept of a ... ...

Abstract	seaMass is an R package for protein-level quantification, normalization, and differential expression analysis of proteomics mass spectrometry data after peptide identification, protein grouping, and feature-level quantification. Using the concept of a blocked experimental design, seaMass can analyze all common discovery proteomics paradigms, including label-free (e.g., Waters Progenesis input), SILAC (e.g., MaxQuant input), isotope labelling (e.g., SCIEX ProteinPilot iTraq and Thermo ProteomeDiscoverer TMT input), and data-independent acquisition (e.g., OpenSWATH-PyProphet input), and is able to scale to study with hundreds of assays or more. By utilizing hierarchical Bayesian modelling, seaMass assesses the quantification reliability of each feature and peptide across assays so that only those in consensus influence the resulting protein group quantification strongly. Similarly, unexplained variation in each individual assay is captured, providing both a metric for quality control and automatic down-weighting of suspect assays. To achieve this, each protein group-level quantification outputted by seaMass is accompanied by the standard deviation of its posterior uncertainty. Moreover, seaMass integrates a flexible differential expression analysis subsystem with false discovery rate control based on the popular MCMCglmm package for Bayesian mixed-effects modelling, and also provides uncertainty-aware principal components analysis. We provide a description for using seaMass to perform an end-to-end analysis using a real dataset associated with a published clinical proteomics study.
MeSH term(s)	Proteomics/methods ; Uncertainty ; Reproducibility of Results ; Bayes Theorem ; Proteins ; Peptides ; Proteome/metabolism
Chemical Substances	Proteins ; Peptides ; Proteome
Language	English
Publishing date	2022-10-29
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ISSN	1940-6029
ISSN (online)	1940-6029
DOI	10.1007/978-1-0716-1967-4_8
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Article ; Online: Diagnostic MALDI-TOF MS can differentiate between high and low toxic

Brignoli, Tarcisio / Recker, Mario / Lee, Winnie W Y / Dong, Tim / Bhamber, Ranjeet / Albur, Mahableshwar / Williams, Philip / Dowsey, Andrew W / Massey, Ruth C

Microbiology (Reading, England)

2022 Volume 168, Issue 8

Abstract: Staphylococcus ... ...

Abstract	Staphylococcus aureus
MeSH term(s)	Bacteremia/diagnosis ; Bacteremia/microbiology ; Humans ; Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization ; Staphylococcal Infections/diagnosis ; Staphylococcal Infections/microbiology ; Staphylococcus aureus
Language	English
Publishing date	2022-08-17
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	1180712-x
ISSN	1465-2080 ; 1350-0872
ISSN (online)	1465-2080
ISSN	1350-0872
DOI	10.1099/mic.0.001223
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Article: Visual identification of individual Holstein-Friesian cattle via deep metric learning

Andrew, William / Gao, Jing / Mullan, Siobhan / Campbell, Neill / Dowsey, Andrew W / Burghardt, Tilo

Computers and electronics in agriculture. 2021 June, v. 185

2021

Abstract: Holstein-Friesian cattle exhibit individually-characteristic black and white coat patterns visually akin to those arising from Turing’s reaction-diffusion systems. This work takes advantage of these natural markings in order to automate visual detection ... ...

Abstract	Holstein-Friesian cattle exhibit individually-characteristic black and white coat patterns visually akin to those arising from Turing’s reaction-diffusion systems. This work takes advantage of these natural markings in order to automate visual detection and biometric identification of individual Holstein-Friesians via convolutional neural networks and deep metric learning techniques. Existing approaches rely on markings, tags or wearables with a variety of maintenance requirements, whereas we present a totally hands-off method for the automated detection, localisation, and identification of individual animals from overhead imaging in an open herd setting, i.e. where new additions to the herd are identified without re-training. We find that deep metric learning systems show strong performance even when many cattle unseen during system training are to be identified and re-identified – achieving 93.8% accuracy when trained on just half of the population. This work paves the way for facilitating the non-intrusive monitoring of cattle applicable to precision farming and surveillance for automated productivity, health and welfare monitoring, and to veterinary research such as behavioural analysis, disease outbreak tracing, and more. Key parts of the source code, network weights and underpinning datasets are available publicly (OpenCows2020).
Keywords	Holstein ; agriculture ; automation ; biometry ; cattle ; data collection ; disease outbreaks ; electronics ; herds ; monitoring ; veterinary medicine
Language	English
Dates of publication	2021-06
Publishing place	Elsevier B.V.
Document type	Article
Note	NAL-AP-2-clean
ZDB-ID	395514-x
ISSN	0168-1699
ISSN	0168-1699
DOI	10.1016/j.compag.2021.106133
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Article ; Online: mzMLb: A Future-Proof Raw Mass Spectrometry Data Format Based on Standards-Compliant mzML and Optimized for Speed and Storage Requirements.

Bhamber, Ranjeet S / Jankevics, Andris / Deutsch, Eric W / Jones, Andrew R / Dowsey, Andrew W

Journal of proteome research

2020 Volume 20, Issue 1, Page(s) 172–183

Abstract: With ever-increasing amounts of data produced by mass spectrometry (MS) proteomics and metabolomics, and the sheer volume of samples now analyzed, the need for a common open format possessing both file size efficiency and faster read/write speeds has ... ...

Abstract	With ever-increasing amounts of data produced by mass spectrometry (MS) proteomics and metabolomics, and the sheer volume of samples now analyzed, the need for a common open format possessing both file size efficiency and faster read/write speeds has become paramount to drive the next generation of data analysis pipelines. The Proteomics Standards Initiative (PSI) has established a clear and precise extensible markup language (XML) representation for data interchange, mzML, receiving substantial uptake; nevertheless, storage and file access efficiency has not been the main focus. We propose an HDF5 file format "mzMLb" that is optimized for both read/write speed and storage of the raw mass spectrometry data. We provide an extensive validation of the write speed, random read speed, and storage size, demonstrating a flexible format that with or without compression is faster than all existing approaches in virtually all cases, while with compression is comparable in size to proprietary vendor file formats. Since our approach uniquely preserves the XML encoding of the metadata, the format implicitly supports future versions of mzML and is straightforward to implement: mzMLb's design adheres to both HDF5 and NetCDF4 standard implementations, which allows it to be easily utilized by third parties due to their widespread programming language support. A reference implementation within the established ProteoWizard toolkit is provided.
MeSH term(s)	Databases, Protein ; Mass Spectrometry ; Metabolomics ; Programming Languages ; Proteomics ; Software
Language	English
Publishing date	2020-10-29
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	2078618-9
ISSN	1535-3907 ; 1535-3893
ISSN (online)	1535-3907
ISSN	1535-3893
DOI	10.1021/acs.jproteome.0c00192
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Article ; Online: Widespread severe cerebral elevations of haptoglobin and haemopexin in sporadic Alzheimer's disease: Evidence for a pervasive microvasculopathy.

Philbert, Sasha A / Xu, Jingshu / Unwin, Richard D / Dowsey, Andrew W / Cooper, Garth J S

Biochemical and biophysical research communications

2021 Volume 555, Page(s) 89–94

Abstract: Sporadic Alzheimer's disease (sAD) is the commonest cause of age-related neurodegeneration but there are no available treatments with demonstrated disease-modifying actions. It is therefore relevant to study hitherto-unknown aspects of brain structure ... ...

Abstract	Sporadic Alzheimer's disease (sAD) is the commonest cause of age-related neurodegeneration but there are no available treatments with demonstrated disease-modifying actions. It is therefore relevant to study hitherto-unknown aspects of brain structure and function to seek new disease-related mechanisms that might be targeted by novel disease-modifying interventions. During hypothesis-generating proteomic investigations in a case-control study of sAD, we observed widespread elevations of haptoglobin and haemopexin in all six brain-regions studied, which together represent much of the brain. Measured perturbations were significant, with the posterior probability of upregulation generally >95% and haptoglobin doubling in expression levels on average across deep brain structures (hippocampus, entorhinal cortex and cingulate gyrus) as well as sensory and motor cortices, and cerebellum. Haptoglobin and haemopexin are often regarded as circulating proteins whose main functions are to bind, respectively, the strongly pro-inflammatory extracellular haemoglobin and haeme molecules that form following haemolysis, thereby promoting their clearance and suppressing damage they might otherwise cause, for example, acute kidney injury. To our knowledge, elevations in neither cerebral haptoglobin nor haemopexin have previously been linked to the pathogenesis of sAD. Post-mortem examination of these cases showed no signs of macroscopic cerebral haemorrhage. These findings demonstrate pervasive cerebral elevation of haptoglobin and haemopexin, consistent with low-level intracerebral leakage of haemoglobin and consequent haeme formation throughout sAD brain. They point to a widespread underlying microvasculopathy that facilitates erythrocyte leakage, thereby triggering elevated tissue-free haemoglobin and driving the measured elevations in haptoglobin and haemopexin.
MeSH term(s)	Aged ; Alzheimer Disease/metabolism ; Blood-Brain Barrier/physiopathology ; Brain/blood supply ; Brain/metabolism ; Brain/physiopathology ; Case-Control Studies ; Cerebrovascular Disorders/metabolism ; Cerebrovascular Disorders/physiopathology ; Female ; Haptoglobins/analysis ; Hemopexin/analysis ; Humans ; Iron/analysis ; Iron/metabolism ; Male
Chemical Substances	Haptoglobins ; Hemopexin (9013-71-2) ; Iron (E1UOL152H7)
Language	English
Publishing date	2021-04-01
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	205723-2
ISSN	1090-2104 ; 0006-291X ; 0006-291X
ISSN (online)	1090-2104 ; 0006-291X
ISSN	0006-291X
DOI	10.1016/j.bbrc.2021.02.107
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Article: Coenzyme A-Dependent Tricarboxylic Acid Cycle Enzymes Are Decreased in Alzheimer's Disease Consistent With Cerebral Pantothenate Deficiency.

Sang, Crystal / Philbert, Sasha A / Hartland, Danielle / Unwin, Richard D / Dowsey, Andrew W / Xu, Jingshu / Cooper, Garth J S

Frontiers in aging neuroscience

2022 Volume 14, Page(s) 893159

Abstract: Sporadic Alzheimer's disease (sAD) is the commonest cause of age-related neurodegeneration and dementia globally, and a leading cause of premature disability and death. To date, the quest for a disease-modifying therapy for sAD has failed, probably ... ...

Abstract	Sporadic Alzheimer's disease (sAD) is the commonest cause of age-related neurodegeneration and dementia globally, and a leading cause of premature disability and death. To date, the quest for a disease-modifying therapy for sAD has failed, probably reflecting our incomplete understanding of aetiology and pathogenesis. Drugs that target aggregated Aβ/tau are ineffective, and metabolic defects are now considered to play substantive roles in sAD pathobiology. We tested the hypothesis that the recently identified, pervasive cerebral deficiency of pantothenate (vitamin B5) in sAD, might undermine brain energy metabolism by impairing levels of tricarboxylic acid (TCA)-cycle enzymes and enzyme complexes, some of which require the pantothenate-derived cofactor, coenzyme A (CoA) for their normal functioning. We applied proteomics to measure levels of the multi-subunit TCA-cycle enzymes and their cytoplasmic homologues. We analysed six functionally distinct brain regions from nine sAD cases and nine controls, measuring 33 cerebral proteins that comprise the nine enzymes of the mitochondrial-TCA cycle. Remarkably, we found widespread perturbations affecting only two multi-subunit enzymes and two enzyme complexes, whose function is modulated, directly or indirectly by CoA: pyruvate dehydrogenase complex, isocitrate dehydrogenase, 2-oxoglutarate dehydrogenase complex, and succinyl-CoA synthetase. The sAD cases we studied here displayed widespread deficiency of pantothenate, the obligatory precursor of CoA. Therefore, deficient cerebral pantothenate can damage brain-energy metabolism in sAD, at least in part through impairing levels of these four mitochondrial-TCA-cycle enzymes.
Language	English
Publishing date	2022-06-10
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2558898-9
ISSN	1663-4365
ISSN	1663-4365
DOI	10.3389/fnagi.2022.893159
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Book ; Online: Towards Self-Supervision for Video Identification of Individual Holstein-Friesian Cattle

Gao, Jing / Burghardt, Tilo / Andrew, William / Dowsey, Andrew W. / Campbell, Neill W.

The Cows2021 Dataset

2021

Abstract: In this paper we publish the largest identity-annotated Holstein-Friesian cattle dataset Cows2021 and a first self-supervision framework for video identification of individual animals. The dataset contains 10,402 RGB images with labels for localisation ... ...

Abstract	In this paper we publish the largest identity-annotated Holstein-Friesian cattle dataset Cows2021 and a first self-supervision framework for video identification of individual animals. The dataset contains 10,402 RGB images with labels for localisation and identity as well as 301 videos from the same herd. The data shows top-down in-barn imagery, which captures the breed's individually distinctive black and white coat pattern. Motivated by the labelling burden involved in constructing visual cattle identification systems, we propose exploiting the temporal coat pattern appearance across videos as a self-supervision signal for animal identity learning. Using an individual-agnostic cattle detector that yields oriented bounding-boxes, rotation-normalised tracklets of individuals are formed via tracking-by-detection and enriched via augmentations. This produces a `positive' sample set per tracklet, which is paired against a `negative' set sampled from random cattle of other videos. Frame-triplet contrastive learning is then employed to construct a metric latent space. The fitting of a Gaussian Mixture Model to this space yields a cattle identity classifier. Results show an accuracy of Top-1 57.0% and Top-4: 76.9% and an Adjusted Rand Index: 0.53 compared to the ground truth. Whilst supervised training surpasses this benchmark by a large margin, we conclude that self-supervision can nevertheless play a highly effective role in speeding up labelling efforts when initially constructing supervision information. We provide all data and full source code alongside an analysis and evaluation of the system. Comment: 6 pages, 8 figures, 1 table, dataset will be available, code will be available
Keywords	Computer Science - Computer Vision and Pattern Recognition
Subject code	006
Publishing date	2021-05-05
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: National farm assurance scheme demonstrates welfare outcome improvements for sustainable intensification of dairy production

Mullan, Siobhan / Wiltshire, Philippa / Cross, Kate / Main, David CJ / Still, Kate / Crawley, Madeleine / Dowsey, Andrew W.

International Journal of Agricultural Sustainability. 2022 July 04, v. 20, no. 4 p.558-575

2022

Abstract: Animal welfare is a key pillar of sustainability in livestock farming but can be challenging to deliver improvements when productivity is high. In October 2013, the Red Tractor UK national dairy assurance scheme introduced welfare outcome monitoring on ... ...

Abstract	Animal welfare is a key pillar of sustainability in livestock farming but can be challenging to deliver improvements when productivity is high. In October 2013, the Red Tractor UK national dairy assurance scheme introduced welfare outcome monitoring on its 11,500 farms, covering 95% of UK milk produced. Here we show that 98 farm assurance assessors achieved high levels of agreement with a gold standard and report data they collected for three years from 248,689 cows, typically 10 cows per farm, during 19,899 audits. Between 2013 and 2014, and 2015 and 2016, the estimated national prevalence fell significantly for lameness (from 10.0% to 7.9%), dirtiness (from 12.4% to 9.2%), ‘hairloss, lesions and swellings’ (from 9.3% to 6.5%), and fat cows (from 2.4% to 1.9%). This occurred at a time when milk yield per cow increased. We have demonstrated an effective implementation strategy suitable for uptake internationally to align with societal sustainability goals.
Keywords	animal welfare ; cows ; farms ; lameness ; milk ; milk yield ; sustainable agriculture ; tractors ; Sustainable intensification ; farm assurance ; dairy cows ; welfare outcomes
Language	English
Dates of publication	2022-0704
Size	p. 558-575.
Publishing place	Taylor & Francis
Document type	Article ; Online
ZDB-ID	2296084-3
ISSN	1747-762X ; 1473-5903
ISSN (online)	1747-762X
ISSN	1473-5903
DOI	10.1080/14735903.2021.1957348
Database	NAL-Catalogue (AGRICOLA)

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Book ; Online: Visual Identification of Individual Holstein-Friesian Cattle via Deep Metric Learning

Andrew, William / Gao, Jing / Mullan, Siobhan / Campbell, Neill / Dowsey, Andrew W / Burghardt, Tilo

2020

Abstract: Holstein-Friesian cattle exhibit individually-characteristic black and white coat patterns visually akin to those arising from Turing's reaction-diffusion systems. This work takes advantage of these natural markings in order to automate visual detection ... ...

Abstract	Holstein-Friesian cattle exhibit individually-characteristic black and white coat patterns visually akin to those arising from Turing's reaction-diffusion systems. This work takes advantage of these natural markings in order to automate visual detection and biometric identification of individual Holstein-Friesians via convolutional neural networks and deep metric learning techniques. Existing approaches rely on markings, tags or wearables with a variety of maintenance requirements, whereas we present a totally hands-off method for the automated detection, localisation, and identification of individual animals from overhead imaging in an open herd setting, i.e. where new additions to the herd are identified without re-training. We propose the use of SoftMax-based reciprocal triplet loss to address the identification problem and evaluate the techniques in detail against fixed herd paradigms. We find that deep metric learning systems show strong performance even when many cattle unseen during system training are to be identified and re-identified -- achieving 93.8% accuracy when trained on just half of the population. This work paves the way for facilitating the non-intrusive monitoring of cattle applicable to precision farming and surveillance for automated productivity, health and welfare monitoring, and to veterinary research such as behavioural analysis, disease outbreak tracing, and more. Key parts of the source code, network weights and datasets are available publicly. Comment: 41 pages, 18 figures, 2 tables; Submitted to Computers and Electronics in Agriculture Source code and network weights available at https://github.com/CWOA/MetricLearningIdentification OpenCows2020 dataset available at https://doi.org/10.5523/bris.10m32xl88x2b61zlkkgz3fml17
Keywords	Computer Science - Computer Vision and Pattern Recognition ; I.4.8 ; I.4.9
Subject code	006
Publishing date	2020-06-16
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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