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Background and aims Hypertension is a leading risk factor for cardiovascular disease. Electronic health records (EHRs) are routinely collected throughout a person’s care, recording all aspects of health status, including current and past conditions, prescriptions and test results. EHRs can be used for epidemiological research. However, there are nuances in the way conditions are recorded using clinical coding; it is important to understand the methods which have been applied to define exposures, covariates and outcomes to enable interpretation of study findings. This study aimed to identify codelists used to define hypertension in studies that use EHRs and generate recommended codelists to support reproducibility and consistency.Eligibility criteria Studies included populations with hypertension defined within an EHR between January 2010 and August 2023 and were systematically identified using MEDLINE and Embase. A summary of the most frequently used sources and codes is described. Due to an absence of Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) codelists in the literature, a recommended SNOMED CT codelist was developed to aid consistency and standardisation of hypertension research using EHRs.Findings 375 manuscripts met the study criteria and were eligible for inclusion, and 112 (29.9%) reported codelists. The International Classification of Diseases (ICD) was the most frequently used clinical terminology, 59 manuscripts provided ICD 9 codelists (53%) and 58 included ICD 10 codelists (52%). Informed by commonly used ICD and Read codes, usage recommendations were made. We derived SNOMED CT codelists informed by National Institute for Health and Care Excellence guidelines for hypertension management. It is recommended that these codelists be used to identify hypertension in EHRs using SNOMED CT codes.Conclusions Less than one-third of hypertension studies using EHRs included their codelists. Transparent methodology for codelist creation is essential for replication and will aid interpretation of study findings. We created SNOMED CT codelists to support and standardise hypertension definitions in EHR studies.

Abstract The most common malignant brain tumour in children, medulloblastoma (MB), is subdivided into four clinically relevant molecular subgroups, although targeted therapy options informed by understanding of different cellular features are lacking. Here, by comparing the most aggressive subgroup (Group 3) with the intermediate (SHH) subgroup, we identify crucial differences in tumour heterogeneity, including unique metabolism-driven subpopulations in Group 3 and matrix-producing subpopulations in SHH. To analyse tumour heterogeneity, we profiled individual tumour nodules at the cellular level in 3D MB hydrogel models, which recapitulate subgroup specific phenotypes, by single cell RNA sequencing (scRNAseq) and 3D OrbiTrap Secondary Ion Mass Spectrometry (3D OrbiSIMS) imaging. In addition to identifying known metabolites characteristic of MB, we observed intra- and internodular heterogeneity and identified subgroup-specific tumour subpopulations. We showed that extracellular matrix factors and adhesion pathways defined unique SHH subpopulations, and made up a distinct shell-like structure of sulphur-containing species, comprising a combination of small leucine-rich proteoglycans (SLRPs) including the collagen organiser lumican. In contrast, the Group 3 tumour model was characterized by multiple subpopulations with greatly enhanced oxidative phosphorylation and tricarboxylic acid (TCA) cycle activity. Extensive TCA cycle metabolite measurements revealed very high levels of succinate and fumarate with malate levels almost undetectable particularly in Group 3 tumour models. In patients, high fumarate levels (NMR spectroscopy) alongside activated stress response pathways and high Nuclear Factor Erythroid 2-Related Factor 2 (NRF2; gene expression analyses) were associated with poorer survival. Based on these findings we predicted and confirmed that NRF2 inhibition increased sensitivity to vincristine in a long-term 3D drug treatment assay of Group 3 MB. Thus, by combining scRNAseq and 3D OrbiSIMS in a relevant model system we were able to define MB subgroup heterogeneity at the single cell level and elucidate new druggable biomarkers for aggressive Group 3 and low-risk SHH MB.

BackgroundCOVID-19 data have been generated across the United Kingdom as a by-product of clinical care and public health provision, as well as numerous bespoke and repurposed research endeavors. Analysis of these data has underpinned the United Kingdom’s response to the pandemic, and informed public health policies and clinical guidelines. However, these data are held by different organizations, and this fragmented landscape has presented challenges for public health agencies and researchers as they struggle to find relevant data to access and interrogate the data they need to inform the pandemic response at pace. ObjectiveWe aimed to transform UK COVID-19 diagnostic data sets to be findable, accessible, interoperable, and reusable (FAIR). MethodsA federated infrastructure model (COVID - Curated and Open Analysis and Research Platform [CO-CONNECT]) was rapidly built to enable the automated and reproducible mapping of health data partners’ pseudonymized data to the Observational Medical Outcomes Partnership Common Data Model without the need for any data to leave the data controllers’ secure environments, and to support federated cohort discovery queries and meta-analysis. ResultsA total of 56 data sets from 19 organizations are being connected to the federated network. The data include research cohorts and COVID-19 data collected through routine health care provision linked to longitudinal health care records and demographics. The infrastructure is live, supporting aggregate-level querying of data across the United Kingdom. ConclusionsCO-CONNECT was developed by a multidisciplinary team. It enables rapid COVID-19 data discovery and instantaneous meta-analysis across data sources, and it is researching streamlined data extraction for use in a Trusted Research Environment for research and public health analysis. CO-CONNECT has the potential to make UK health data more interconnected and better able to answer national-level research questions while maintaining patient confidentiality and local governance procedures.

Abstract Streptococcus uberis is one of the leading pathogens causing mastitis worldwide. Identification of S. uberis strains that fail to respond to treatment with antibiotics is essential for better decision making and treatment selection. We demonstrate that the combination of supervised machine learning and matrix-assisted laser desorption ionization/time of flight (MALDI-TOF) mass spectrometry can discriminate strains of S. uberis causing clinical mastitis that are likely to be responsive or unresponsive to treatment. Diagnostics prediction systems trained on 90 individuals from 26 different farms achieved up to 86.2% and 71.5% in terms of accuracy and Cohen’s kappa. The performance was further increased by adding metadata (parity, somatic cell count of previous lactation and count of positive mastitis cases) to encoded MALDI-TOF spectra, which increased accuracy and Cohen’s kappa to 92.2% and 84.1% respectively. A computational framework integrating protein–protein networks and structural protein information to the machine learning results unveiled the molecular determinants underlying the responsive and unresponsive phenotypes.

Staphylococcus aureus is a serious human and animal pathogen threat exhibiting extraordinary capacity for acquiring new antibiotic resistance traits in the pathogen population worldwide. The development of fast, affordable and effective diagnostic solutions capable of discriminating between antibiotic-resistant and susceptible S. aureus strains would be of huge benefit for effective disease detection and treatment. Here we develop a diagnostics solution that uses Matrix-Assisted Laser Desorption/Ionisation-Time of Flight Mass Spectrometry (MALDI-TOF) and machine learning, to identify signature profiles of antibiotic resistance to either multidrug or benzylpenicillin in S. aureus isolates. Using ten different supervised learning techniques, we have analysed a set of 82 S. aureus isolates collected from 67 cows diagnosed with bovine mastitis across 24 farms. For the multidrug phenotyping analysis, LDA, linear SVM, RBF SVM, logistic regression, naïve Bayes, MLP neural network and QDA had Cohen's kappa values over 85.00%. For the benzylpenicillin phenotyping analysis, RBF SVM, MLP neural network, naïve Bayes, logistic regression, linear SVM, QDA, LDA, and random forests had Cohen's kappa values over 85.00%. For the benzylpenicillin the diagnostic systems achieved up to (mean result ± standard deviation over 30 runs on the test set): accuracy = 97.54% ± 1.91%, sensitivity = 99.93% ± 0.25%, specificity = 95.04% ± 3.83%, and Cohen's kappa = 95.04% ± 3.83%. Moreover, the diagnostic platform complemented by a protein-protein network and 3D structural protein information framework allowed the identification of five molecular determinants underlying the susceptible and resistant profiles. Four proteins were able to classify multidrug-resistant and susceptible strains with 96.81% ± 0.43% accuracy. Five proteins, including the previous four, were able to classify benzylpenicillin resistant and susceptible strains with 97.54% ± 1.91% accuracy. Our approach may open up new avenues for the development of a fast, affordable and effective day-to-day diagnostic solution, which would offer new opportunities for targeting resistant bacteria.

Influenza A virus is a major global pathogen of humans, and there is an unmet need for effective antivirals. Current antivirals against influenza A virus directly target the virus and are vulnerable to mutational resistance. Harnessing an effective host antiviral response is an attractive alternative. We show that brief exposure to low, non-toxic doses of thapsigargin (TG), an inhibitor of the sarcoplasmic/endoplasmic reticulum (ER) Ca2+ ATPase pump, promptly elicits an extended antiviral state that dramatically blocks influenza A virus production. Crucially, oral administration of TG protected mice against lethal virus infection and reduced virus titres in the lungs of treated mice. TG-induced ER stress unfolded protein response appears as a key driver responsible for activating a spectrum of host antiviral defences that include an enhanced type I/III interferon response. Our findings suggest that TG is potentially a viable host-centric antiviral for the treatment of influenza A virus infection without the inherent problem of drug resistance.

Introduction Venous thromboembolism (VTE) is a serious, frequent, and preventable medical complication in hospitalized patients. Although the efficacy of prophylaxis (pharmacological and/or mechanical) has been demonstrated, compliance with prophylaxis is poor at international and national levels. Aim To determine the indication and use of pharmacological thromboprophylaxis in hospitalized patients in Uruguay. Methods An observational, descriptive, cross-sectional, multicentre study involving 31 nationwide healthcare facilities was conducted. Baseline characteristics associated with hospital admission, the percentage of the population with an indication for thromboprophylaxis, and the percentage of patients receiving pharmacological thromboprophylaxis were assessed. The VTE risk was determined using the Padua score for medical patients; the Caprini score for surgical patients; the Royal College of Obstetricians and Gynaecologists (RCOG) guidelines for pregnant-postpartum patients. Results 1925 patients were included, representing 26% of hospitalized patients in Uruguay. 71.9% of all patients were at risk of VTE. Of all patients at risk of VTE, 58.6% received pharmacological thromboprophylaxis. The reasons for not receiving thromboprophylaxis were prescribing omissions in 16.1% of cases, contraindication in 15.9% and 9.4% of patients were already anticoagulated for other reasons. Overall, just 68% of patients were “protected” against VTE. Recommendations of major thromboprophylaxis guidelines were followed in 70.1% of patients at risk. Conclusions Despite the progress made in adherence to thromboprophylaxis indications, nonadherence remains a problem, affecting one in six patients at risk of VTE in Uruguay

Free-living amoebae (FLA) are amphizoic protozoans with a cosmopolitan distribution. Some strains of species are associated with infections in humans. They feed on microorganisms by phagocytosis; however, some of these can become endocytobionts by resisting this process and taking shelter inside the amoeba. The whole world is experiencing increasing shortage of water, and sewage is being reused, so the study of this environment is important in public health context. The objective of this work was to identify FLA present in sewage treatment plants in Porto Alegre, Brazil. About 1 L samples were collected from eight stations (raw and treated sewage) in January, February, July, and August 2022. The samples were sown in monoxenic culture, and the isolated amoebae were subjected to morphological and molecular identification. Polymerase chain reaction results indicated the presence of the genus Acanthamoeba in 100% of the samples. Gene sequencing showed the presence of Acanthamoeba lenticulata and Acanthamoeba polyphaga - T5 and T4 genotypes - respectively, which are related to pathogenicity. The environment where the sewage is released can be used in recreational activities, exposing individuals to potential interactions with these amoebae and their potential endocytobionts, which may pose risks to public health. HIGHLIGHTS Free-living amoebae were isolated for the first time in sewage treatment plants (STPs) in Brazil.; In the STPs of Porto Alegre, RS, Brazil, only the genus Acanthamoeba was isolated, and genotypes associated with pathogenicity (T4 and T5) were identified.; The Guaíba lake and the Gravataí river receive the city's sewage and, consequently, can disperse Acanthamoeba spp.; Further research on the prevalence and identification of free-living amoebae in sewage is still needed in Brazil.;

[This corrects the article DOI: 10.1371/journal.pone.0264826.].

O número de sistemas de Geração Distribuída cresce de forma exponencial no Brasil desde a sua primeira regulamentação. Entretanto, com a aprovação do seu novo marco legal, os consumidores passaram a pagar pelo uso do sistema de distribuição de energia elétrica, impactando o mercado. Assim, é objetivo deste artigo avaliar a influência desta nova regulamentação na viabilidade econômica dos sistemas para consumidores residenciais, tipos de sistemas de maior representatividade no setor. Para tanto, analisaram-se as tarifas de energia homologadas para as concessionárias, bem como o impacto no fluxo de caixa de sistemas instalados no período de vacância da lei, caso eles fossem instalados sob a vigência da nova regulamentação em cinco cenários de análise, por meio de parâmetros econométricos e da comparação com investimentos de renda fixa tradicionais no Brasil. Pôde-se constatar que não existe um padrão para as tarifas de energia elétrica e que o impacto da nova regulamentação varia em função da componente tarifária da remuneração do uso do sistema de distribuição, identificando-se as regiões do país mais impactadas. Constatou-se que, mesmo com a diminuição da atratividade, em todos os cenários analisados os sistemas são viáveis, mesmo não havendo uma transição suave para as novas regras. Por fim, recomendou-se fortemente a instalação dos novos sistemas com a maior brevidade possível, além da gestão energética nas unidades consumidoras, com a priorização da utilização de energia nos horários de maior geração.

Free-living amoebae (FLA) are protozoa dispersed in different environments and are responsible for different infections caused to humans and other animals. Microorganisms such as Acanthamoeba spp., Vermamoeba sp., and Naegleria sp. are associated with diseases that affect the central nervous system, in addition to skin infections and keratitis, as occurs in the genus Acanthamoeba and with Vermamoeba vermiformis. Due to the concerns of these FLA in anthropogenic aquatic environments, this work aimed to identify these microorganisms present in waters of Porto Alegre, Brazil. One litre sample was collected in two watercourses during the summer of 2022 and inoculated onto non-nutrient agar plates containing heat-inactivated Escherichia coli. Polymerase chain reaction results indicated the presence of FLA of the genera Acanthamoeba, Vermamoeba, and Naegleria in the study areas. Genetic sequencing indicated the presence of V. vermiformis and Naegleria gruberi. These aquatic and anthropogenic environments can serve as a means of spread and contamination by FLA, which gives valuable information on public health in the city. HIGHLIGHTS Identify microorganisms present in anthropogenic aquatic environments.; First report of free-living amoebae in southern Brazil.; Detection of Acanthamoeba spp., Naegleria gruberi, and Vermamoeba vermiformis in watercourses.; These microorganisms are responsible for causing fatal diseases that affect the central nervous system.; These environments can serve as a means of spread and contamination.;