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Background: Patients with rare diseases (RDs) are often diagnosed too late or not at all. Clinical decision support systems (CDSSs) could support the diagnosis in RDs. The MIRACUM (Medical Informatics in Research and Medicine) consortium, which is one of four funded consortia in the German Medical Informatics Initiative, will develop a CDSS for RDs based on distributed clinical data from ten university hospitals. This qualitative study aims to investigate (1) the relevant organizational conditions for the operation of a CDSS for RDs when diagnose patients (e.g. the diagnosis workflow), (2) which data is necessary for decision support, and (3) the appropriate user group for such a CDSS.
Methods: Interviews were carried out with RDs experts. Participants were recruited from staff physicians at the Rare Disease Centers (RDCs) at the MIRACUM locations, which offer diagnosis and treatment of RDs.
An interview guide was developed with a category-guided deductive approach. The interviews were recorded on an audio device and then transcribed into written form. We continued data collection until all interviews were completed. Afterwards, data analysis was performed using Mayring’s qualitative content analysis approach.
Results: A total of seven experts were included in the study. The results show that medical center guides and physicians from RDC B-centers (with a focus on different RDs) are involved in the diagnostic process. Furthermore, interdisciplinary case discussions between physicians are conducted.
The experts explained that RDs exist which cannot be fully differentiated, but rather described only by their overall symptoms or findings: diagnosis is dependent on the disease or disease group. At the end of the diagnostic process, most centers prepare a summary of the patient case. Furthermore, the experts considered both physicians and experts from the B-centers to be potential users of a CDSS. The experts also have different experiences with CDSS for RDs.
Conclusions: This qualitative study is a first step towards establishing the requirements for the development of a CDSS for RDs. Further research is necessary to create solutions by also including the experts on RDs.
Bipolar disorder (BD) is a heritable mental illness with complex etiology. While the largest published genome-wide association study identified 64 BD risk loci, the causal SNPs and genes within these loci remain unknown. We applied a suite of statistical and functional fine-mapping methods to these loci, and prioritized 22 likely causal SNPs for BD. We mapped these SNPs to genes, and investigated their likely functional consequences by integrating variant annotations, brain cell-type epigenomic annotations, brain quantitative trait loci, and results from rare variant exome sequencing in BD. Convergent lines of evidence supported the roles of SCN2A, TRANK1, DCLK3, INSYN2B, SYNE1, THSD7A, CACNA1B, TUBBP5, PLCB3, PRDX5, KCNK4, AP001453.3, TRPT1, FKBP2, DNAJC4, RASGRP1, FURIN, FES, YWHAE, DPH1, GSDMB, MED24, THRA, EEF1A2, and KCNQ2 in BD. These represent promising candidates for functional experiments to understand biological mechanisms and therapeutic potential. Additionally, we demonstrated that fine-mapping effect sizes can improve performance and transferability of BD polygenic risk scores across ancestrally diverse populations, and present a high-throughput fine-mapping pipeline (https://github.com/mkoromina/SAFFARI).
SARS-CoV-2 is causing the coronavirus disease 2019 (COVID-19) pandemic, for which effective pharmacological therapies are needed. SARS-CoV-2 induces a shift of the host cell metabolism towards glycolysis, and the glycolysis inhibitor 2-deoxy-d-glucose (2DG), which interferes with SARS-CoV-2 infection, is under development for the treatment of COVID-19 patients. The glycolytic pathway generates intermediates that supply the non-oxidative branch of the pentose phosphate pathway (PPP). In this study, the analysis of proteomics data indicated increased transketolase (TKT) levels in SARS-CoV-2-infected cells, suggesting that a role is played by the non-oxidative PPP. In agreement, the TKT inhibitor benfooxythiamine (BOT) inhibited SARS-CoV-2 replication and increased the anti-SARS-CoV-2 activity of 2DG. In conclusion, SARS-CoV-2 infection is associated with changes in the regulation of the PPP. The TKT inhibitor BOT inhibited SARS-CoV-2 replication and increased the activity of the glycolysis inhibitor 2DG. Notably, metabolic drugs like BOT and 2DG may also interfere with COVID-19-associated immunopathology by modifying the metabolism of immune cells in addition to inhibiting SARS-CoV-2 replication. Hence, they may improve COVID-19 therapy outcomes by exerting antiviral and immunomodulatory effects.
In Baden-Württemberg sind in dem 30-jährigen Zeitraum einschließlich dervorliegenden insgesamt fünf Fassungen der Roten Liste der gefährdeten Vogelarten erschienen, die jeweils auf den neuesten Stand der Erforschung der Vogelwelt Baden-Württembergs gebracht wurden. Die einzelnen Fassungen der Roten Liste sind 1973 (1. Fassung, Berthold, Ertel & Hölzinger 1974, 1975), 1977 (2. Fassung, Berthold, Ertel, Hölzinger, Kalchreuter & Ruge 1977), 1981 (3. Fassung, Hölzinger, Berthold, Kroymann & Ruge 1981), 1996 (4. Fassung, Hölzinger, Berthold, König & Mahler 1996) und 2007 (5., vorliegende Fassung) herausgegeben worden. In diesem über 30-jährigen Zeitraum wurden die Kriterien für die Roten Listen entsprechend dem Fortschritt der ornithologischen Forschung zunehmend mehr auf quantitative Grundlagen gestellt. Die Roten Listen waren und sind das Ergebnis systematischer und programmatisch orientierter Bestandsaufnahmen der Vogelwelt abseits emotionaler und naturschutzpolitischer Beurteilung.
The title compound, C37H67NO13·2C2H6OS·1.43H2O, is a macrolide antibiotic with better solubility and better dermal penetration abilities than erythromycin A itself. The asymmetric unit of this form contains one erythromycin A molecule, two dimethyl sulfoxide (DMSO) solvent molecules, a fully occupied water molecule and a partially occupied water molecule with an occupancy factor of 0.432 (11). The 14-membered ring of the erythronolide fragment has a conformation which differs considerably from that in erythromycin A dihydrate [Stephenson, Stowell, Toma, Pfeiffer & Byrn (1997[Stephenson, G. A., Stowell, J. G., Toma, P. H., Pfeiffer, R. R. & Byrn, S. R. (1997). J. Pharm. Sci. 86, 1239-1244.]). J. Pharm. Sci. 86, 1239–1244]. One of the two DMSO molecules is disordered over two orientations; the orientation depends on the presence or absence of the second, partially occupied, water molecule. In the crystal, erythromycin molecules are connected by O—H⋯O hydrogen bonds involving the hydroxy groups and the fully occupied water molecule to form layers parallel to (010). These layers are connected along the b-axis direction only by a possible hydrogen-bonding contact involving the partially occupied water molecule.
Antisynthetase syndrome (ASSD) is a rare clinical condition that is characterized by the occurrence of a classic clinical triad, encompassing myositis, arthritis, and interstitial lung disease (ILD), along with specific autoantibodies that are addressed to different aminoacyl tRNA synthetases (ARS). Until now, it has been unknown whether the presence of a different ARS might affect the clinical presentation, evolution, and outcome of ASSD. In this study, we retrospectively recorded the time of onset, characteristics, clustering of triad findings, and survival of 828 ASSD patients (593 anti-Jo1, 95 anti-PL7, 84 anti-PL12, 38 anti-EJ, and 18 anti-OJ), referring to AENEAS (American and European NEtwork of Antisynthetase Syndrome) collaborative group’s cohort. Comparisons were performed first between all ARS cases and then, in the case of significance, while using anti-Jo1 positive patients as the reference group. The characteristics of triad findings were similar and the onset mainly began with a single triad finding in all groups despite some differences in overall prevalence. The “ex-novo” occurrence of triad findings was only reduced in the anti-PL12-positive cohort, however, it occurred in a clinically relevant percentage of patients (30%). Moreover, survival was not influenced by the underlying anti-aminoacyl tRNA synthetase antibodies’ positivity, which confirmed that antisynthetase syndrome is a heterogeneous condition and that antibody specificity only partially influences the clinical presentation and evolution of this condition.
Simple Summary: Pseudoprogression detection in glioblastoma patients remains a challenging task. Although pseudoprogression has only a moderate prevalence of 10–30% following first-line treatment of glioblastoma patients, it bears critical implications for affected patients. Non-invasive techniques, such as amino acid PET imaging using the tracer O-(2-[18F]-fluoroethyl)-L-tyrosine (FET), expose features that have been shown to provide useful information to distinguish tumor progression from pseudoprogression. The usefulness of FET-PET in IDH-wildtype glioblastoma exclusively, however, has not been investigated so far. Recently, machine learning (ML) algorithms have been shown to offer great potential particularly when multiparametric data is available. In this preliminary study, a Linear Discriminant Analysis-based ML algorithm was deployed in a cohort of newly diagnosed IDH-wildtype glioblastoma patients (n = 44) and demonstrated a significantly better diagnostic performance than conventional ROC analysis. This preliminary study is the first to assess the performance of ML in FET-PET for diagnosing pseudoprogression exclusively in IDH-wildtype glioblastoma and demonstrates its potential.
Abstract: Pseudoprogression (PSP) detection in glioblastoma remains challenging and has important clinical implications. We investigated the potential of machine learning (ML) in improving the performance of PET using O-(2-[18F]-fluoroethyl)-L-tyrosine (FET) for differentiation of tumor progression from PSP in IDH-wildtype glioblastoma. We retrospectively evaluated the PET data of patients with newly diagnosed IDH-wildtype glioblastoma following chemoradiation. Contrast-enhanced MRI suspected PSP/TP and all patients underwent subsequently an additional dynamic FET-PET scan. The modified Response Assessment in Neuro-Oncology (RANO) criteria served to diagnose PSP. We trained a Linear Discriminant Analysis (LDA)-based classifier using FET-PET derived features on a hold-out validation set. The results of the ML model were compared with a conventional FET-PET analysis using the receiver-operating-characteristic (ROC) curve. Of the 44 patients included in this preliminary study, 14 patients were diagnosed with PSP. The mean (TBRmean) and maximum tumor-to-brain ratios (TBRmax) were significantly higher in the TP group as compared to the PSP group (p = 0.014 and p = 0.033, respectively). The area under the ROC curve (AUC) for TBRmax and TBRmean was 0.68 and 0.74, respectively. Using the LDA-based algorithm, the AUC (0.93) was significantly higher than the AUC for TBRmax. This preliminary study shows that in IDH-wildtype glioblastoma, ML-based PSP detection leads to better diagnostic performance.
Background: The Catechol-O-methyltransferase (COMT) represents the key enzyme in catecholamine degradation. Recent studies suggest that the COMT rs4680 polymorphism is associated with the response to endogenous and exogenous catecholamines. There are, however, conflicting data regarding the COMT Met/Met phenotype being associated with an increased risk of acute kidney injury (AKI) after cardiac surgery. The aim of the current study is to prospectively investigate the impact of the COMT rs4680 polymorphism on the incidence of AKI in patients undergoing cardiac surgery.
Methods: In this prospective single center cohort study consecutive patients hospitalized for elective cardiac surgery including cardiopulmonary-bypass (CPB) were screened for participation. Demographic clinical data, blood, urine and tissue samples were collected at predefined time points throughout the clinical stay. AKI was defined according to recent recommendations of the Kidney Disease Improving Global Outcome (KDIGO) group. Genetic analysis was performed after patient enrolment was completed.
Results: Between April and December 2014, 150 patients were recruited. The COMT genotypes were distributed as follows: Val/Met 48.7%, Met/Met 29.3%, Val/Val 21.3%. No significant differences were found for demography, comorbidities, or operative strategy according to the underlying COMT genotype. AKI occurred in 35 patients (23.5%) of the total cohort, and no differences were evident between the COMT genotypes (20.5% Met/Met, 24.7% Val/Met, 25.0% Val/Val, p = 0.66). There were also no differences in the post-operative period, including ICU or in-hospital stay.
Conclusions: We did not find statistically significant variations in the risk for postoperative AKI, length of ICU or in-hospital stay according to the underlying COMT genotype.
Inositol, 1,2,3,4,5,6-hexahydroxycyclohexane, exists in nine stereoisomers with different crystal structures and melting points. In a previous paper on the relationship between the melting points of the inositols and the hydrogen-bonding patterns in their crystal structures [Simperler et al. (2006[Simperler, A., Watt, S. W., Bonnet, P. A., Jones, W. & Motherwell, W. D. S. (2006). CrystEngComm, 8, 589-600.]). CrystEngComm 8, 589], it was noted that although all inositol crystal structures known at that time contained 12 hydrogen bonds per molecule, their melting points span a large range of about 170 °C. Our preliminary investigations suggested that the highest melting point must be corrected for the effect of molecular symmetry, and that the three lowest melting points may need to be revised. This prompted a full investigation, with additional experiments on six of the nine inositols. Thirteen new phases were discovered; for all of these their crystal structures were examined. The crystal structures of eight ordered phases could be determined, of which seven were obtained from laboratory X-ray powder diffraction data. Five additional phases turned out to be rotator phases and only their unit cells could be determined. Two previously unknown melting points were measured, as well as most enthalpies of melting. Several previously reported melting points were shown to be solid-to-solid phase transitions or decomposition points. Our experiments have revealed a complex picture of phases, rotator phases and phase transitions, in which a simple correlation between melting points and hydrogen-bonding patterns is not feasible.
Background: This study assessed the ability of mid-regional proadrenomedullin (MR-proADM) in comparison to conventional biomarkers (procalcitonin (PCT), lactate, C-reactive protein) and clinical scores to identify disease severity in patients with sepsis.
Methods: This is a secondary analysis of a randomised controlled trial in patients with severe sepsis or septic shock across 33 German intensive care units. The association between biomarkers and clinical scores with mortality was assessed by Cox regression analysis, area under the receiver operating characteristic and Kaplan-Meier curves. Patients were stratified into three severity groups (low, intermediate, high) for all biomarkers and scores based on cutoffs with either a 90% sensitivity or specificity.
Results: 1089 patients with a 28-day mortality rate of 26.9% were analysed. According to the Sepsis-3 definition, 41.2% and 58.8% fulfilled the criteria for sepsis and septic shock, with respective mortality rates of 20.0% and 32.1%. MR-proADM had the strongest association with mortality across all Sepsis-1 and Sepsis-3 subgroups and could facilitate a more accurate classification of low (e.g. MR-proADM vs. SOFA: N = 265 vs. 232; 9.8% vs. 13.8% mortality) and high (e.g. MR-proADM vs. SOFA: N = 161 vs. 155; 55.9% vs. 41.3% mortality) disease severity. Patients with decreasing PCT concentrations of either ≥ 20% (baseline to day 1) or ≥ 50% (baseline to day 4) but continuously high MR-proADM concentrations had a significantly increased mortality risk (HR (95% CI): 19.1 (8.0–45.9) and 43.1 (10.1–184.0)).
Conclusions: MR-proADM identifies disease severity and treatment response more accurately than established biomarkers and scores, adding additional information to facilitate rapid clinical decision-making and improve personalised sepsis treatment.