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Background: Evaluation of automated attenuation-based tube potential selection and its impact on image quality and radiation dose in CT (computed tomography) examinations for cancer staging.
Methods: A total of 110 (59 men, 51 women) patients underwent chest-abdomen-pelvis CT examinations; 55 using a fixed tube potential of 120 kV/current of 210 Reference mAs (using CareDose4D), and 55 using automated attenuation-based tube potential selection (CAREkV) also using a current of 210 Reference mAs. This evaluation was performed as a single-centre, observer-blinded retrospective analysis. Image quality was assessed by two readers in consensus. Attenuation, image noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were measured or calculated for objective image evaluation. For the evaluation of radiation exposure, dose-length-product (DLP) values were compared and Size-specific dose estimates (SSDE) values were calculated.
Results: Diagnostic image quality was obtained from all patients. The median DLP (703.5 mGy · cm, range 390–2203 mGy · cm) was 7.9% lower when using the algorithm compared with the standard 120 kV protocol (median 756 mGy · cm, range 345–2267 mGy · cm). A reduction in potential to 100 kV occurred in 32 cases; therefore, these patients received significantly lower radiation exposure compared with the 120 kV protocol.
Conclusion: Automated attenuation-based tube potential selection produces good diagnostic image quality in chest-abdomen-pelvis CT and reduces the patient’s overall radiation dose by 7.9% compared to the standard 120 kV protocol.
Objectives: The aim of our study was to find out how much energy is applicable in second-generation dual source high-pitch computed tomography (CT) in imaging of the abdomen.
Materials and methods: We examined an upper abdominal phantom using a Somatom Definition Flash CT-Scanner (Siemens, Forchheim, Germany). The study protocol consisted of a scan-series at 100 kV and 120 kV. In each scan series we started with a pitch of 3.2 and reduced it in steps of 0.2, until a pitch of 1.6 was reached. The current was adjusted to the maximum the scanner could achieve. Energy values, image noise, image quality, and radiation exposure were evaluated.
Results: For a pitch of 3.2 the maximum applicable current was 142 mAs at 120 kV and in 100 kV the maximum applicable current was 114 mAs. For conventional abdominal imaging, current levels of 200 to 260 mAs are generally used. To achieve similar current levels, we had to decrease the pitch to 1.8 at 100 kV - at this pitch we could perform our imaging at 204 mAs. At a pitch of 2.2 in 120 kV we could apply a current of 206 mAs.
Conclusion: We conclude our study by stating that if there is a need for a higher current, we have to reduce the pitch. In a high-pitch dual source CT, we always have to remember where our main focus is, so we can adjust the pitch to the energy we need in the area of the body that has to be imaged, to find answers to the clinical question being raised.
The success of social insects is largely intertwined with their highly advanced chemical communication system that facilitates recognition and discrimination of species and nest-mates, recruitment, and division of labor. Hydrocarbons, which cover the cuticle of insects, not only serve as waterproofing agents but also constitute a major component of this communication system. Two cryptic Crematogaster species, which share their nest with Camponotus ants, show striking diversity in their cuticular hydrocarbon (CHC) profile. This mutualistic system therefore offers a great opportunity to study the genetic basis of CHC divergence between sister species. As a basis for further genome-wide studies high-quality genomes are needed. Here, we present the annotated draft genome for Crematogaster levior A. By combining the three most commonly used sequencing techniques—Illumina, PacBio, and Oxford Nanopore—we constructed a high-quality de novo ant genome. We show that even low coverage of long reads can add significantly to overall genome contiguity. Annotation of desaturase and elongase genes, which play a role in CHC biosynthesis revealed one of the largest repertoires in ants and a higher number of desaturases in general than in other Hymenoptera. This may provide a mechanistic explanation for the high diversity observed in C. levior CHC profiles.
Movement of organisms is one of the key mechanisms shaping biodiversity, e.g. the distribution of genes, individuals and species in space and time. Recent technological and conceptual advances have improved our ability to assess the causes and consequences of individual movement, and led to the emergence of the new field of ‘movement ecology’. Here, we outline how movement ecology can contribute to the broad field of biodiversity research, i.e. the study of processes and patterns of life among and across different scales, from genes to ecosystems, and we propose a conceptual framework linking these hitherto largely separated fields of research. Our framework builds on the concept of movement ecology for individuals, and demonstrates its importance for linking individual organismal movement with biodiversity. First, organismal movements can provide ‘mobile links’ between habitats or ecosystems, thereby connecting resources, genes, and processes among otherwise separate locations. Understanding these mobile links and their impact on biodiversity will be facilitated by movement ecology, because mobile links can be created by different modes of movement (i.e., foraging, dispersal, migration) that relate to different spatiotemporal scales and have differential effects on biodiversity. Second, organismal movements can also mediate coexistence in communities, through ‘equalizing’ and ‘stabilizing’ mechanisms. This novel integrated framework provides a conceptual starting point for a better understanding of biodiversity dynamics in light of individual movement and space-use behavior across spatiotemporal scales. By illustrating this framework with examples, we argue that the integration of movement ecology and biodiversity research will also enhance our ability to conserve diversity at the genetic, species, and ecosystem levels.
In the upcoming years, the internet of things (IoT)will enrich daily life. The combination of artificial intelligence(AI) and highly interoperable systems will bring context-sensitive multi-domain services to reality. This paper describesa concept for an AI-based smart living platform with open-HAB, a smart home middleware, and Web of Things (WoT) askey components of our approach. The platform concept con-siders different stakeholders, i.e. the housing industry, serviceproviders, and tenants. These activities are part of the Fore-Sight project, an AI-driven, context-sensitive smart living plat-form.
Despite the progress to understand inflammatory reactions, mechanisms causing their resolution remain poorly understood. Prostanoids, especially prostaglandin E2 (PGE2), are well-characterized mediators of inflammation. PGE2 is produced in an inducible manner in macrophages (Mϕ) by microsomal PGE2-synthase-1 (mPGES-1), with the notion that it also conveys pro-resolving properties. We aimed to characterize the role of mPGES-1 during resolution of acute, zymosan-induced peritonitis. Experimentally, we applied the mPGES-1 inhibitor compound III (CIII) once the inflammatory response was established and confirmed its potent PGE2-blocking efficacy. mPGES-1 inhibition resulted in an incomplete removal of neutrophils and a concomitant increase in monocytes and Mϕ during the resolution process. The mRNA-seq analysis identified enhanced C-X3-C motif receptor 1 (CX3CR1) expression in resident and infiltrating Mϕ upon mPGES-1 inhibition. Besides elevated Cx3cr1 expression, its ligand CX3CL1 was enriched in the peritoneal lavage of the mice, produced by epithelial cells upon mPGES-1 inhibition. CX3CL1 not only increased adhesion and survival of Mϕ but its neutralization also completely reversed elevated inflammatory cell numbers, thereby normalizing the cellular, peritoneal composition during resolution. Our data suggest that mPGES-1-derived PGE2 contributes to the resolution of inflammation by preventing CX3CL1-mediated retention of activated myeloid cells at sites of injury.
Background: Perioperative anaemia leads to impaired oxygen supply with a risk of vital organ ischaemia. In healthy and fit individuals, anaemia can be compensated by several mechanisms. Elderly patients, however, have less compensatory mechanisms because of multiple co-morbidities and age-related decline of functional reserves. The purpose of the study is to evaluate whether elderly surgical patients may benefit from a liberal red blood cell (RBC) transfusion strategy compared to a restrictive transfusion strategy.
Methods: The LIBERAL Trial is a prospective, randomized, multicentre, controlled clinical phase IV trial randomising 2470 elderly (≥ 70 years) patients undergoing intermediate- or high-risk non-cardiac surgery. Registered patients will be randomised only if Haemoglobin (Hb) reaches ≤9 g/dl during surgery or within 3 days after surgery either to the LIBERAL group (transfusion of a single RBC unit when Hb ≤ 9 g/dl with a target range for the post-transfusion Hb level of 9–10.5 g/dl) or the RESTRICTIVE group (transfusion of a single RBC unit when Hb ≤ 7.5 g/dl with a target range for the post-transfusion Hb level of 7.5–9 g/dl). The intervention per patient will be followed until hospital discharge or up to 30 days after surgery, whichever occurs first. The primary efficacy outcome is defined as a composite of all-cause mortality, acute myocardial infarction, acute ischaemic stroke, acute kidney injury (stage III), acute mesenteric ischaemia and acute peripheral vascular ischaemia within 90 days after surgery. Infections requiring iv antibiotics with re-hospitalisation are assessed as important secondary endpoint. The primary endpoint will be analysed by logistic regression adjusting for age, cancer surgery (y/n), type of surgery (intermediate- or high-risk), and incorporating centres as random effect.
Discussion: The LIBERAL-Trial will evaluate whether a liberal transfusion strategy reduces the occurrence of major adverse events after non-cardiac surgery in the geriatric population compared to a restrictive strategy within 90 days after surgery.
Trial registration: ClinicalTrials.gov (identifier: NCT03369210).
Background: Biological psychiatry aims to understand mental disorders in terms of altered neurobiological pathways. However, for one of the most prevalent and disabling mental disorders, Major Depressive Disorder (MDD), patients only marginally differ from healthy individuals on the group-level. Whether Precision Psychiatry can solve this discrepancy and provide specific, reliable biomarkers remains unclear as current Machine Learning (ML) studies suffer from shortcomings pertaining to methods and data, which lead to substantial over-as well as underestimation of true model accuracy.
Methods: Addressing these issues, we quantify classification accuracy on a single-subject level in N=1,801 patients with MDD and healthy controls employing an extensive multivariate approach across a comprehensive range of neuroimaging modalities in a well-curated cohort, including structural and functional Magnetic Resonance Imaging, Diffusion Tensor Imaging as well as a polygenic risk score for depression.
Findings Training and testing a total of 2.4 million ML models, we find accuracies for diagnostic classification between 48.1% and 62.0%. Multimodal data integration of all neuroimaging modalities does not improve model performance. Similarly, training ML models on individuals stratified based on age, sex, or remission status does not lead to better classification. Even under simulated conditions of perfect reliability, performance does not substantially improve. Importantly, model error analysis identifies symptom severity as one potential target for MDD subgroup identification.
Interpretation: Although multivariate neuroimaging markers increase predictive power compared to univariate analyses, single-subject classification – even under conditions of extensive, best-practice Machine Learning optimization in a large, harmonized sample of patients diagnosed using state-of-the-art clinical assessments – does not reach clinically relevant performance. Based on this evidence, we sketch a course of action for Precision Psychiatry and future MDD biomarker research.
Background: There are no blood-based molecular biomarkers of temporal lobe epilepsy (TLE) to support clinical diagnosis. MicroRNAs are short noncoding RNAs with strong biomarker potential due to their cell-specific expression, mechanistic links to brain excitability, and stable detection in biofluids. Altered levels of circulating microRNAs have been reported in human epilepsy, but most studies collected samples from one clinical site, used a single profiling platform or conducted minimal validation.
Method: Using a case-control design, we collected plasma samples from video-electroencephalogram-monitored adult TLE patients at epilepsy specialist centers in two countries, performed genome-wide PCR-based and RNA sequencing during the discovery phase and validated findings in a large (>250) cohort of samples that included patients with psychogenic non-epileptic seizures (PNES).
Findings: After profiling and validation, we identified miR-27a-3p, miR-328-3p and miR-654-3p with biomarker potential. Plasma levels of these microRNAs were also changed in a mouse model of TLE but were not different to healthy controls in PNES patients. We determined copy number of the three microRNAs in plasma and demonstrate their rapid detection using an electrochemical RNA microfluidic disk as a prototype point-of-care device. Analysis of the microRNAs within the exosome-enriched fraction provided high diagnostic accuracy while Argonaute-bound miR-328-3p selectively increased in patient samples after seizures. In situ hybridization localized miR-27a-3p and miR-328-3p within neurons in human brain and bioinformatics predicted targets linked to growth factor signaling and apoptosis.
Interpretation: This study demonstrates the biomarker potential of circulating microRNAs for epilepsy diagnosis and mechanistic links to underlying pathomechanisms.
The last decade has seen a sharp increase in the number of scientific publications describing physiological and pathological functions of extracellular vesicles (EVs), a collective term covering various subtypes of cell-released, membranous structures, called exosomes, microvesicles, microparticles, ectosomes, oncosomes, apoptotic bodies, and many other names. However, specific issues arise when working with these entities, whose size and amount often make them difficult to obtain as relatively pure preparations, and to characterize properly. The International Society for Extracellular Vesicles (ISEV) proposed Minimal Information for Studies of Extracellular Vesicles (“MISEV”) guidelines for the field in 2014. We now update these “MISEV2014” guidelines based on evolution of the collective knowledge in the last four years. An important point to consider is that ascribing a specific function to EVs in general, or to subtypes of EVs, requires reporting of specific information beyond mere description of function in a crude, potentially contaminated, and heterogeneous preparation. For example, claims that exosomes are endowed with exquisite and specific activities remain difficult to support experimentally, given our still limited knowledge of their specific molecular machineries of biogenesis and release, as compared with other biophysically similar EVs. The MISEV2018 guidelines include tables and outlines of suggested protocols and steps to follow to document specific EV-associated functional activities. Finally, a checklist is provided with summaries of key points.