Modelling the impact of wastewater flows and management practices on antimicrobial resistance in dairy farms.

Dairy slurry is a major source of environmental contamination with antimicrobial resistant genes and bacteria. We developed mathematical models and conducted on-farm research to explore the impact of wastewater flows and management practices on antimicrobial resistance (AMR) in slurry. Temporal fluctuations in cephalosporin-resistant Escherichia coli were observed and attributed to farm activities, specifically the disposal of spent copper and zinc footbath into the slurry system. Our model revealed that resistance should be more frequently observed with relevant determinants encoded chromosomally rather than on plasmids, which was supported by reanalysis of sequenced genomes from the farm. Additionally, lower resistance levels were predicted in conditions with lower growth and higher death rates. The use of muck heap effluent for washing dirty channels did not explain the fluctuations in cephalosporin resistance. These results highlight farm-specific opportunities to reduce AMR pollution, beyond antibiotic use reduction, including careful disposal or recycling of waste antimicrobial metals.

Grandiose narcissism associates with higher cognitive performance under stress through more efficient attention distribution: An eye-tracking study.

Narcissism is a part of the Dark Triad that consists also of the traits of Machiavellianism and psychopathy. Two main types of narcissism exist: grandiose and vulnerable narcissism. Being a Dark Triad trait, narcissism is typically associated with negative outcomes. However, recent research suggests that at least the grandiose type may be linked (directly or indirectly) to positive outcomes including lower levels of psychopathology, higher school grades in adolescents, deeper and more strategic learning in university students and higher cognitive performance in experimental settings. The current pre-registered, quasi-experimental study implemented eye-tracking to assess whether grandiose narcissism indirectly predicts cognitive performance through wider distribution of attention on the Raven's Progressive Matrices task. Fifty-four adults completed measures of the Dark Triad, self-esteem and psychopathology. Eight months to one year later, participants completed the Raven's, while their eye-movements were monitored during high stress conditions. When controlling for previous levels of psychopathology, grandiose narcissism predicted higher Raven's scores indirectly, through increased variability in the number of fixations across trials. These findings suggest that grandiose narcissism predicts higher cognitive performance, at least in experimental settings, and call for further research to understand the implications of this seemingly dark trait for performance across various settings.

Toward confident prostate cancer detection using ultrasound: a multi-center study.

PURPOSE: Deep learning-based analysis of micro-ultrasound images to detect cancerous lesions is a promising tool for improving prostate cancer (PCa) diagnosis. An ideal model should confidently identify cancer while responding with appropriate uncertainty when presented with out-of-distribution inputs that arise during deployment due to imaging artifacts and the biological heterogeneity of patients and prostatic tissue. METHODS: Using micro-ultrasound data from 693 patients across 5 clinical centers who underwent micro-ultrasound guided prostate biopsy, we train and evaluate convolutional neural network models for PCa detection. To improve robustness to out-of-distribution inputs, we employ and comprehensively benchmark several state-of-the-art uncertainty estimation methods. RESULTS: PCa detection models achieve performance scores up to 76 % average AUROC with a 10-fold cross validation setup. Models with uncertainty estimation obtain expected calibration error scores as low as 2 % , indicating that confident predictions are very likely to be correct. Visualizations of the model output demonstrate that the model correctly identifies healthy versus malignant tissue. CONCLUSION: Deep learning models have been developed to confidently detect PCa lesions from micro-ultrasound. The performance of these models, determined from a large and diverse dataset, is competitive with visual analysis of magnetic resonance imaging, the clinical benchmark to identify PCa lesions for targeted biopsy. Deep learning with micro-ultrasound should be further studied as an avenue for targeted prostate biopsy.

Public preferences for pharmacogenetic testing in the NHS: Embedding a discrete choice experiment within service design to better meet user needs.

AIMS: Genetic testing can be used to improve the safety and effectiveness of commonly prescribed medicines-a concept known as pharmacogenetics. This study aimed to quantify members of the UK public's preferences for a pharmacogenetic service to be delivered in primary care in the National Health Service. METHODS: Members of the UK population were surveyed via an online panel company. Respondents completed 1 of 2 survey versions, asking respondents to select their preferred pharmacogenetic testing service in the context of a presentation of low mood or pain. A conditional logit model was estimated, before the best functional form for the dataset was identified. Preference heterogeneity was identified via latent class analysis. Coefficients from the final selected models were used to estimate uptake in the context of different hypothetical pharmacogenetic services. RESULTS: Responses from 1993 individuals were included in the analysis. There were no differences observed in preference between the 2 clinical scenarios. Conditional logit analysis, using maximum likelihood estimation, indicated that respondents preferred to have noninvasive tests and wanted their data to be shared between different healthcare organizations to guide future prescribing. There was a preference for regional over national data sharing initiatives, and respondents preferred to have access to their data. Predicted uptake varied considerably, ranging from 51% to >99%, depending on design of the service. CONCLUSION: This study identifies public preferences for a pharmacogenetic testing service and demonstrates how predicted uptake can be impacted by relatively minor adaptations. This highlights areas for prioritization during development of future pharmacogenetic services.

LensePro: label noise-tolerant prototype-based network for improving cancer detection in prostate ultrasound with limited annotations.

PURPOSE: The standard of care for prostate cancer (PCa) diagnosis is the histopathological analysis of tissue samples obtained via transrectal ultrasound (TRUS) guided biopsy. Models built with deep neural networks (DNNs) hold the potential for direct PCa detection from TRUS, which allows targeted biopsy and subsequently enhances outcomes. Yet, there are ongoing challenges with training robust models, stemming from issues such as noisy labels, out-of-distribution (OOD) data, and limited labeled data. METHODS: This study presents LensePro, a unified method that not only excels in label efficiency but also demonstrates robustness against label noise and OOD data. LensePro comprises two key stages: first, self-supervised learning to extract high-quality feature representations from abundant unlabeled TRUS data and, second, label noise-tolerant prototype-based learning to classify the extracted features. RESULTS: Using data from 124 patients who underwent systematic prostate biopsy, LensePro achieves an AUROC, sensitivity, and specificity of 77.9%, 85.9%, and 57.5%, respectively, for detecting PCa in ultrasound. Our model shows it is effective for detecting OOD data in test time, critical for clinical deployment. Ablation studies demonstrate that each component of our method improves PCa detection by addressing one of the three challenges, reinforcing the benefits of a unified approach. CONCLUSION: Through comprehensive experiments, LensePro demonstrates its state-of-the-art performance for TRUS-based PCa detection. Although further research is necessary to confirm its clinical applicability, LensePro marks a notable advancement in enhancing automated computer-aided systems for detecting prostate cancer in ultrasound.

The impact of devolution on local health systems: Evidence from Greater Manchester, England.

Devolution and decentralisation policies involving health and other government sectors have been promoted with a view to improve efficiency and equity in local service provision. Evaluations of these reforms have focused on specific health or care measures, but little is known about their full impact on local health systems. We evaluated the impact of devolution in Greater Manchester (England) on multiple outcomes using a whole system approach. We estimated the impact of devolution until February 2020 on 98 measures of health system performance, using the generalised synthetic control method and adjusting for multiple hypothesis testing. We selected measures from existing monitoring frameworks to populate the WHO Health System Performance Assessment framework. The included measures captured information on health system functions, intermediatory objectives, final goals, and social determinants of health. We identified which indicators were targeted in response to devolution from an analysis of 170 health policy intervention documents. Life expectancy (0.233 years, S.E. 0.012) and healthy life expectancy (0.603 years, S.E. 0.391) increased more in GM than in the estimated synthetic control group following devolution. These increases were driven by improvements in public health, primary care, hospital, and adult social care services as well as factors associated with social determinants of health, including a reduction in alcohol-related admissions (-110.1 admission per 100,000, S.E. 9.07). In contrast, the impact on outpatient, mental health, maternity, and dental services was mixed. Devolution was associated with improved population health, driven by improvements in health services and wider social determinants of health. These changes occurred despite limited devolved powers over health service resources suggesting that other mechanisms played an important role, including the allocation of sustainability and transformation funding and the alignment of decision-making across health, social care, and wider public services in the region.

Geographic inequalities in need and provision of social prescribing link workers.

BACKGROUND: Long-term health conditions are major challenges for care systems. Social prescribing link workers have been introduced via Primary Care Networks (PCNs) across England since 2019 to address the wider determinants of health by connecting individuals to activities, groups, or services within their local community. AIM: To assess whether the rollout of social prescribing link workers was in areas with the highest need. DESIGN AND SETTING: A retrospective study of social prescribing link workers in England from 2019 to 2023. METHOD: We combined workforce, population, survey, and area-level data at the PCN-level from April 2020 to October 2023. We measured population need prior to the rollout of link workers using reported lack of support from local services in the 2019 GP Patient Survey. To assess if rollout reflected need, we used linear regression to relate provision of link workers (measured by full-time equivalent (FTE) per 10,000 patients) in each quarter to population need for support. RESULTS: Populations in urban, more deprived areas and with higher proportions of minority ethnicities had the highest reported lack of support. Geographically these were in the North West and London. Initially, there was no association between need and provision; then from July 2022, this became negative and significant. By October 2023, a 10-percentage point higher need for support was associated with a 0.035 (95%CI(-0.634 to -0.066)) lower FTE per 10,000 patients. CONCLUSION: Rollout of link workers has not been sufficiently targeted at areas with the highest need. Future deployments should be targeted at those areas.

pH-Responsive Amphiphilic Triblock Fluoropolymers as Assemble Oxygen Nanoshuttles for Enhancing PDT against Hypoxic Tumor.

Photodynamic therapy (PDT) is a cancer treatment strategy that utilizes photosensitizers to convert oxygen within tumors into reactive singlet oxygen (1O2) to lyse tumor cells. Nevertheless, pre-existing tumor hypoxia and oxygen consumption during PDT can lead to an insufficient oxygen supply, potentially reducing the photodynamic efficacy. In response to this issue, we have devised a pH-responsive amphiphilic triblock fluorinated polymer (PDP) using copper-mediated RDRP. This polymer, composed of poly(ethylene glycol) methyl ether acrylate, 2-(diethylamino)ethyl methacrylate, and (perfluorooctyl)ethyl acrylate, self-assembles in an aqueous environment. Oxygen, chlorine e6 (Ce6), and doxorubicin (DOX) can be codelivered efficiently by PDP. The incorporation of perfluorocarbon into the formulation enhances the oxygen-carrying capacity of PDP, consequently extending the lifetime of 1O2. This increased lifetime, in turn, amplifies the PDT effect and escalates the cellular cytotoxicity. Compared with PDT alone, PDP@Ce6-DOX-O2 NPs demonstrated significant inhibition of tumor growth. This study proposes a novel strategy for enhancing the efficacy of PDT.

High genetic load without purging in caribou, a diverse species at risk.

High intra-specific genetic diversity is associated with adaptive potential, which is key for resilience to global change. However, high variation may also support deleterious alleles through genetic load, thereby increasing the risk of inbreeding depression if population sizes decrease. Purging of deleterious variation has been demonstrated in some threatened species. However, less is known about the costs of declines and inbreeding in species with large population sizes and high genetic diversity even though this encompasses many species globally that are expected to undergo population declines. Caribou is a species of ecological and cultural significance in North America with a wide distribution supporting extensive phenotypic variation but with some populations undergoing significant declines resulting in their at-risk status in Canada. We assessed intra-specific genetic variation, adaptive divergence, inbreeding, and genetic load across populations with different demographic histories using an annotated chromosome-scale reference genome and 66 whole-genome sequences. We found high genetic diversity and nine phylogenomic lineages across the continent with adaptive diversification of genes, but also high genetic load among lineages. We found highly divergent levels of inbreeding across individuals, including the loss of alleles by drift but not increased purging in inbred individuals, which had more homozygous deleterious alleles. We also found comparable frequencies of homozygous deleterious alleles between lineages regardless of nucleotide diversity. Thus, further inbreeding may need to be mitigated through conservation efforts. Our results highlight the "double-edged sword" of genetic diversity that may be representative of other species atrisk affected by anthropogenic activities.

Exploring NICU nurses' views of a novel genetic point-of-care test identifying neonates at risk of antibiotic-induced ototoxicity: A qualitative study.

AIM: To explore the views of neonatal intensive care nursing staff on the deliverability of a novel genetic point-of-care test detecting a genetic variant associated with antibiotic-induced ototoxicity. DESIGN: An interpretive, descriptive, qualitative interview study. METHODS: Data were collected using semi-structured interviews undertaken between January and November 2020. Participants were neonatal intensive care nursing staff taking part in the Pharmacogenetics to Avoid Loss of Hearing trial. RESULTS: Thematic analysis resulted in four themes: perceived clinical utility; the golden hour; point-of-care device; training and support. Recommendations were made to streamline the protocol and ongoing training and support were considered key to incorporating the test into routine care. CONCLUSION: Exploring the views of nurses involved in the delivery of the point-of-care test was essential in its implementation. By the study endpoint, all participants could see the value of routine clinical introduction of the point-of care test. IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE: Nurses are in a key position to support the delivery of point-of-care genetic testing into mainstream settings. This study has implications for the successful integration of other genetic point-of-care tests in acute healthcare settings. IMPACT: The study will help to tailor the training and support required for routine deployment of the genetic point-of-care test. The study has relevance for nurses involved in the development and delivery of genetic point-of-care tests in other acute hospital settings. REPORTING METHOD: This qualitative study adheres to the Standards for Reporting Qualitative Research EQUATOR guidelines and utilizes COREQ and SRQR checklists. PATIENT OR PUBLIC CONTRIBUTION: All staff working on the participating neonatal intensive care units were trained to use the genetic point-of-care test. All inpatients on the participating units were eligible to have testing via the point-of-care test. The Pharmacogenetics to Avoid Loss of Hearing Patient and Public Involvement and Engagement group provided valuable feedback. TRIAL AND PROTOCOL REGISTRATION: Registered within the University of Manchester. Ethics approval reference numbers: IRAS: 253102 REC reference: 19/NW/0400. Also registered with the ISRCTN ref: ISRCTN13704894.

Seq2Sat and SatAnalyzer toolkit: Towards comprehensive microsatellite genotyping from sequencing data.

Accurate and efficient microsatellite loci genotyping is an essential process in population genetics that is also used in various demographic analyses. Protocols for next-generation sequencing of microsatellite loci enable high-throughput and cross-compatible allele scoring, common issues that are not addressed by conventional capillary-based approaches. To improve this process, we have developed an all-in-one software, called Seq2Sat (sequence to microsatellite), in C++ to support automated microsatellite genotyping. It directly takes raw reads of microsatellite amplicons and conducts read quality control before inferring genotypes based on depth-of-read, read ratio, sequence composition and length. We have also developed a module for sex identification based on sex chromosome-specific locus amplicons. To allow for greater user access and complement autoscoring, we developed SatAnalyzer (microsatellite analyzer), a user-friendly web-based platform that conducts reads-to-report analyses by calling Seq2Sat for genotype autoscoring and produces interactive genotype graphs for manual editing. SatAnalyzer also allows users to troubleshoot multiplex optimization by analysing read quality and distribution across loci and samples in support of high-quality library preparation. To evaluate its performance, we benchmarked our toolkit Seq2Sat/SatAnalyzer against a conventional capillary gel method and existing microsatellite genotyping software, MEGASAT, using two datasets. Results showed that SatAnalyzer can achieve >99.70% genotyping accuracy and Seq2Sat is ~5 times faster than MEGASAT despite many more informative tables and figures being generated. Seq2Sat and SatAnalyzer are freely available on github (https://github.com/ecogenomicscanada/Seq2Sat) and dockerhub (https://hub.docker.com/r/rocpengliu/satanalyzer).

MaDDOSY (Mass Determination Diffusion Ordered Spectroscopy) using an 80 MHz Bench Top NMR for the Rapid Determination of Polymer and Macromolecular Molecular Weight.

Measurement of molecular weight is an integral part of macromolecular and polymer characterization which usually has limitations. Herein, this article presents the use of a bench-top 80 MHz Nuclear Magnetic Resonance (NMR) spectrometer for diffusion-ordered spectroscopy as a practical and rapid approach for the determination of molecular weight/size using a novel solvent and polymer-independent universal calibration.

Evaluating whole system reforms: A structured approach for selecting multiple outcomes.

Whole-system reforms, including devolution and integration of health and social care services, have the potential to impact multiple dimensions of health system performance. Most evaluations focus on a single or narrow subsets of outcomes amenable to change. This approach may not: (i) capture the overall effect of the reform, (ii) identify the mechanisms through which system-wide changes may have occurred, (iii) prevent post-hoc selection of outcomes based on significant results; and (iv) facilitate comparisons across settings. We propose a structured approach for selecting multiple quantitative outcome measures, which we apply for evaluating health and social care devolution in Greater Manchester, England. The approach consists of five-steps: (i) defining outcome domains based on a framework, in our case the World Health Organisation's Health System Performance Assessment Framework; (ii) reviewing performance metrics from national monitoring frameworks; (iii) excluding similar and condition specific outcomes; (iv) excluding outcomes with insufficient data; and (v) mapping implemented policies to identify a subset of targeted outcomes. We identified 99 outcomes, of which 57 were targeted. The proposed approach is detail and time-intensive, but useful for both researchers and policymakers to promote transparency in evaluations and facilitate the interpretation of findings and cross-settings comparisons.

Virtual reality and augmented reality smartphone applications for upskilling care home workers in hand hygiene: a realist multi-site feasibility, usability, acceptability, and efficacy study.

OBJECTIVES: To assess the feasibility and implementation, usability, acceptability and efficacy of virtual reality (VR), and augmented reality (AR) smartphone applications for upskilling care home workers in hand hygiene and to explore underlying learning mechanisms. MATERIALS AND METHODS: Care homes in Northwest England were recruited. We took a mixed-methods and pre-test and post-test approach by analyzing uptake and completion rates of AR, immersive VR or non-immersive VR training, validated and bespoke questionnaires, observations, videos, and interviews. Quantitative data were analyzed descriptively. Qualitative data were analyzed using a combined inductive and deductive approach. RESULTS: Forty-eight care staff completed AR training (n = 19), immersive VR training (n = 21), or non-immersive VR training (n = 8). The immersive VR and AR training had good usability with System Usability Scale scores of 84.40 and 77.89 (of 100), respectively. They had high acceptability, with 95% of staff supporting further use. The non-immersive VR training had borderline poor usability, scoring 67.19 and only 63% would support further use. There was minimal improved knowledge, with an average of 6% increase to the knowledge questionnaire. Average hand hygiene technique scores increased from 4.77 (of 11) to 7.23 after the training. Repeated practice, task realism, feedback and reminding, and interactivity were important learning mechanisms triggered by AR/VR. Feasibility and implementation considerations included managerial support, physical space, providing support, screen size, lagging Internet, and fitting the headset. CONCLUSIONS: AR and immersive VR apps are feasible, usable, and acceptable for delivering training. Future work should explore whether they are more effective than previous training and ensure equity in training opportunities.

X-ray Absorption Spectroscopy as a Process Analytical Technology: Reaction Studies for the Manufacture of Sulfonate-Stabilized Calcium Carbonate Particles.

Process analytical technologies are widely used to inform process control by identifying relationships between reagents and products. Here, we present a novel process analytical technology system for operando XAS on multiphase multicomponent synthesis processes based on the combination of a conventional lab-scale agitated reactor with a liquid-jet cell. The preparation of sulfonate-stabilized CaCO3 particles from polyphasic Ca(OH)2 dispersions was monitored in real time by Ca K-edge XAS to identify changes in Ca speciation in the bulk solution/dispersion as a function of time and process conditions. Linear combination fitting of the spectra quantitatively resolved composition changes from the initial conversion of Ca(OH)2 to the Ca(R-SO3)2 surfactant to the ultimate formation of nCaCO3·mCa(R- SO3)2 particles. The system provides a novel tool with strong chemical specificity for probing multiphase synthesis processes at a molecular level, providing an avenue to establishing the relationships between critical quality attributes of a process and the quality and performance of the product.

Epidemiology of Group A Streptococcal bacteraemia in Hunter New England Local Health District, 2008 to 2019.

Invasive Group A Streptococcal infection (iGAS) is an uncommon but serious infection with Streptococcus pyogenes in a normally sterile body site. Manifestations include bacteraemia, necrotising fasciitis and toxic shock syndrome with attendant serious morbidity and mortality. An increasing incidence of iGAS has been observed in some regions of Australia. iGAS became a nationally notifiable condition from 1 July 2021. To determine if regional incidence has increased, and to identify priority populations, we undertook a retrospective data analysis of Group A Streptococcal (GAS) bacteraemia cases in Hunter New England Local Health District (HNELHD), New South Wales, Australia, from 1 January 2008 to 31 December 2019, as identified by NSW Health Pathology, John Hunter Hospital. A total of 486 cases were identified (age-standardised rate: 4.05 cases per 100,000 population per year). Incidence in HNELHD gradually increased over the study period (adjusted incidence rate ratio: 1.04; 95% confidence interval: 1.01-1.07) and was significantly higher in children under 5 years of age; in adults over 70 years of age; in males; and in First Nations peoples. A significant peak occurred in 2017 (9.00 cases per 100,000 population), the cause of which remains unclear. GAS bacteraemia is uncommon but severe, and incidence in HNELHD has slowly increased. Public health and clinical guidelines must address the needs of priority populations, which include young children, older adults and First Nations peoples. Routine surveillance and genomic analysis will help improve our understanding of iGAS and inform best public health management.

A qualitative evaluation of the national rollout of a diabetes prevention programme in England.

BACKGROUND: The National Health Service Diabetes Prevention Programme (NHS DPP) was commissioned by NHS England in 2016 and rolled out in three 'waves' across the whole of England. It aims to help people with raised blood glucose levels reduce their risk of developing type 2 diabetes through behaviour change techniques (e.g., weight loss, dietary changes and exercise). An independent, longitudinal, mixed methods evaluation of the NHS DPP was undertaken. We report the findings from the implementation work package: a qualitative interview study with designated local leads, responsible for the local commissioning and implementation of the programme. The aim of the study was to explore how local implementation processes were enacted and adapted over time. METHODS: We conducted a telephone interview study across two time-points. Twenty-four semi-structured interviews with local leads across 19 sampled case sites were undertaken between October 2019 and January 2020 and 13 interviews with local leads across 13 sampled case sites were conducted between July 2020 and August 2020. Interviews aimed to reflect on the experience of implementation and explore how things changed over time. RESULTS: We identified four overarching themes to show how implementation was locally enacted and adapted across the sampled case sites: 1. Adapting to provider change; 2. Identification and referral; 3. Enhancing uptake in underserved populations; and 4. Digital and remote service options. CONCLUSION: This paper reports how designated local leads, responsible for local implementation of the NHS DPP, adapted implementation efforts over the course of a changing national diabetes prevention programme, including how local leads adapted implementation during the COVID-19 pandemic. This paper highlights three main factors that influence implementation: the importance of facilitation, the ability (or not) to tailor interventions to local needs and the role of context in implementation.

Making implementation science more efficient: capitalizing on opportunities beyond the field.

Implementation researchers often find themselves as research partners in practice improvement projects, clinical trials or other applied health studies. The implementation science component in these projects can be described as supportive, descriptive or explanatory. This commentary reflects on the potential contributions of such projects to implementation science. They may provide evidence on implementation strategies, so it is essential to identify and evaluate these separately from the clinical and preventive interventions of interest. The use of theory on implementation processes and associated factors can contribute to knowledge accumulation, particularly if the focus is on what actually gets implemented when, why and how. The development and validation of relevant measures is a third potential contribution to implementation science. Although not all issues in implementation science can be addressed in this way, capitalization on the opportunities beyond the field can contribute to implementation science.