Knowledge-to-Action Guides: Preparing Families to Be Partners in Making Educational Decisions

Posted in application of the KU Faculty's Open Access policy

Pancreatic cancer is marked by complement-high blood monocytes and tumor-associated macrophages

Pancreatic ductal adenocarcinoma (PDA) is accompanied by reprogramming of the local microenvironment, but changes at distal sites are poorly understood. We implanted biomaterial scaffolds, which act as an artificial premetastatic niche, into immunocompetent tumor-bearing and control mice, and identified a unique tumor-specific gene expression signature that includes high expression of C1qa, C1qb, Trem2, and Chil3 Single-cell RNA sequencing mapped these genes to two distinct macrophage populations in the scaffolds, one marked by elevated C1qa, C1qb, and Trem2, the other with high Chil3, Ly6c2 and Plac8 In mice, expression of these genes in the corresponding populations was elevated in tumor-associated macrophages compared with macrophages in the normal pancreas. We then analyzed single-cell RNA sequencing from patient samples, and determined expression of C1QA, C1QB, and TREM2 is elevated in human macrophages in primary tumors and liver metastases. Single-cell sequencing analysis of patient blood revealed a substantial enrichment of the same gene signature in monocytes. Taken together, our study identifies two distinct tumor-associated macrophage and monocyte populations that reflects systemic immune changes in pancreatic ductal adenocarcinoma patients

The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data

The FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.Peer reviewe

Plasma lipid profiles discriminate bacterial from viral infection in febrile children

Fever is the most common reason that children present to Emergency Departments. Clinical signs and symptoms suggestive of bacterial infection are often non-specific, and there is no definitive test for the accurate diagnosis of infection. The 'omics' approaches to identifying biomarkers from the host-response to bacterial infection are promising. In this study, lipidomic analysis was carried out with plasma samples obtained from febrile children with confirmed bacterial infection (n = 20) and confirmed viral infection (n = 20). We show for the first time that bacterial and viral infection produces distinct profile in the host lipidome. Some species of glycerophosphoinositol, sphingomyelin, lysophosphatidylcholine and cholesterol sulfate were higher in the confirmed virus infected group, while some species of fatty acids, glycerophosphocholine, glycerophosphoserine, lactosylceramide and bilirubin were lower in the confirmed virus infected group when compared with confirmed bacterial infected group. A combination of three lipids achieved an area under the receiver operating characteristic (ROC) curve of 0.911 (95% CI 0.81 to 0.98). This pilot study demonstrates the potential of metabolic biomarkers to assist clinicians in distinguishing bacterial from viral infection in febrile children, to facilitate effective clinical management and to the limit inappropriate use of antibiotics

Plasma lipid profiles discriminate bacterial from viral infection in febrile children

Fever is the most common reason that children present to Emergency Departments. Clinical signs and symptoms suggestive of bacterial infection are often non-specific, and there is no definitive test for the accurate diagnosis of infection. The 'omics' approaches to identifying biomarkers from the host-response to bacterial infection are promising. In this study, lipidomic analysis was carried out with plasma samples obtained from febrile children with confirmed bacterial infection (n = 20) and confirmed viral infection (n = 20). We show for the first time that bacterial and viral infection produces distinct profile in the host lipidome. Some species of glycerophosphoinositol, sphingomyelin, lysophosphatidylcholine and cholesterol sulfate were higher in the confirmed virus infected group, while some species of fatty acids, glycerophosphocholine, glycerophosphoserine, lactosylceramide and bilirubin were lower in the confirmed virus infected group when compared with confirmed bacterial infected group. A combination of three lipids achieved an area under the receiver operating characteristic (ROC) curve of 0.911 (95% CI 0.81 to 0.98). This pilot study demonstrates the potential of metabolic biomarkers to assist clinicians in distinguishing bacterial from viral infection in febrile children, to facilitate effective clinical management and to the limit inappropriate use of antibiotics

Relationship between molecular pathogen detection and clinical disease in febrile children across Europe: a multicentre, prospective observational study

BackgroundThe PERFORM study aimed to understand causes of febrile childhood illness by comparing molecular pathogen detection with current clinical practice.MethodsFebrile children and controls were recruited on presentation to hospital in 9 European countries 2016-2020. Each child was assigned a standardized diagnostic category based on retrospective review of local clinical and microbiological data. Subsequently, centralised molecular tests (CMTs) for 19 respiratory and 27 blood pathogens were performed.FindingsOf 4611 febrile children, 643 (14%) were classified as definite bacterial infection (DB), 491 (11%) as definite viral infection (DV), and 3477 (75%) had uncertain aetiology. 1061 controls without infection were recruited. CMTs detected blood bacteria more frequently in DB than DV cases for N. meningitidis (OR: 3.37, 95% CI: 1.92-5.99), S. pneumoniae (OR: 3.89, 95% CI: 2.07-7.59), Group A streptococcus (OR 2.73, 95% CI 1.13-6.09) and E. coli (OR 2.7, 95% CI 1.02-6.71). Respiratory viruses were more common in febrile children than controls, but only influenza A (OR 0.24, 95% CI 0.11-0.46), influenza B (OR 0.12, 95% CI 0.02-0.37) and RSV (OR 0.16, 95% CI: 0.06-0.36) were less common in DB than DV cases. Of 16 blood viruses, enterovirus (OR 0.43, 95% CI 0.23-0.72) and EBV (OR 0.71, 95% CI 0.56-0.90) were detected less often in DB than DV cases. Combined local diagnostics and CMTs respectively detected blood viruses and respiratory viruses in 360 (56%) and 161 (25%) of DB cases, and virus detection ruled-out bacterial infection poorly, with predictive values of 0.64 and 0.68 respectively.InterpretationMost febrile children cannot be conclusively defined as having bacterial or viral infection when molecular tests supplement conventional approaches. Viruses are detected in most patients with bacterial infections, and the clinical value of individual pathogen detection in determining treatment is low. New approaches are needed to help determine which febrile children require antibiotics.FundingEU Horizon 2020 grant 668303

Plasma lipid profiles discriminate bacterial from viral infection in febrile children

Fever is the most common reason that children present to Emergency Departments. Clinical signs and symptoms suggestive of bacterial infection ar

Impact of infection on proteome-wide glycosylation revealed by distinct signatures for bacterial and viral pathogens

Mechanisms of infection and pathogenesis have predominantly been studied based on differential gene or protein expression. Less is known about posttranslational modifications, which are essential for protein functional diversity. We applied an innovative glycoproteomics method to study the systemic proteome-wide glycosylation in response to infection. The protein site-specific glycosylation was characterized in plasma derived from well-defined controls and patients. We found 3862 unique features, of which we identified 463 distinct intact glycopeptides, that could be mapped to more than 30 different proteins. Statistical analyses were used to derive a glycopeptide signature that enabled significant differentiation between patients with a bacterial or viral infection. Furthermore, supported by a machine learning algorithm, we demonstrated the ability to identify the causative pathogens based on the distinctive host blood plasma glycopeptide signatures. These results illustrate that glycoproteomics holds enormous potential as an innovative approach to improve the interpretation of relevant biological changes in response to infection