Temporal trends in patients with peripheral artery disease influenced by diabetes mellitus in Germany

Introduction In patients with peripheral artery disease (PAD) the presence of diabetes mellitus (DM) is associated with higher morbidity and mortality. Because huge efforts are made to improve medical care of patients with DM including chronic disease programs, the aim of the present study was to investigate temporal trends regarding the clinical burden of DM on PAD patients within a 15-year observational period. Methods We analyzed all patients hospitalized because of PAD between 2005 and 2019 in Germany stratified regarding DM. Results Overall, 2 654 871 hospitalizations of PAD patients (865 823 with DM) were included. Hospitalizations based on PAD inclined from 142 778 in 2005 to 190 135 in 2019 (β 3956 per year; 95% confidence interval [CI] 3034–4878, p < .001) with simultaneous increase of hospitalizations of PAD patients with DM (2005: 41609 (29.1%) versus 2019: 65 302 (34.3%); β 2019 per year [95% CI 1593–2446], p < .001). Amputation rates (β −0.42 [95% CI −0.44 to −0.40]; p < .001) as well as in-hospital case-fatality rate (2005: 4.7%, 2019: 2.8%; β −0.64 [95% CI −0.69 to −0.59]; p < .001) decreased in diabetic PAD patients during the observational time. In spite of improved morbidity and mortality in the last years of the observational period, patients with DM still suffered from an increased risk for morbidity and mortality during the observational period compared to nondiabetic PAD patients. Conclusions Despite the progress in DM treatments, DM still was associated with an unfavorable clinical patient profile and remained a substantial risk factor for morbidity and mortality in hospitalized patients with PAD and DM in Germany between 2005 and 2019

Total numbers and in-hospital mortality of patients with myocardial infarction in Germany during the FIFA soccer world cup 2014

Environmental stress like important soccer events can induce excitation, stress and anger. We aimed to investigate (i) whether the FIFA soccer world cup (WC) 2014 and (ii) whether the soccer games of the German national team had an impact on total numbers and in-hospital mortality of patients with myocardial infarction (MI) in Germany. We analyzed data of MI inpatients of the German nationwide inpatient sample (2013–2015). Patients admitted due to MI during FIFA WC 2014 (12th June–13th July2014) were compared to those during the same period 2013 and 2015 (12th June–13th July). Total number of MI patients was higher during WC 2014 than in the comparison-period 2013 (18,479 vs.18,089, P < 0.001) and 2015 (18,479 vs.17,794, P < 0.001). WC was independently associated with higher MI numbers (2014 vs. 2013: OR 1.04 [95% CI 1.01–1.07]; 2014 vs. 2015: OR 1.07 [95% CI 1.04–1.10], P < 0.001). Patient characteristics and in-hospital mortality rate (8.3% vs. 8.3% vs. 8.4%) were similar during periods. In-hospital mortality rate was not affected by games of the German national team (8.9% vs. 8.1%, P = 0.110). However, we observed an increase regarding in-hospital mortality from 7.9 to 9.3% before to 12.0% at final-match-day. Number of hospital admissions due to MI in Germany was 3.7% higher during WC 2014 than during the same 31-day period 2015. While in-hospital mortality was not affected by the WC, the in-hospital mortality was highest at WC final

Definition of tachycardia for risk stratification of pulmonary embolism.

Tachycardia is a reliable predictor of adverse outcomes in normotensive patients with acute pulmonary embolism (PE). However, different prognostic relevant heart rate thresholds have been proposed. The aim of the study was to investigate the prognostic performance of different thresholds used for defining tachycardia in normotensive PE patients.We performed a post-hoc analysis of normotensive patients with confirmed PE consecutively included in a single-centre and a multi-centre registry. An adverse outcome was defined as PE-related death, need for mechanical ventilation, cardiopulmonary resuscitation or administration of catecholamines.Of 1567 patients (median age: 72 [IQR, 59-79] years; females: 46.1%) included in the analysis, 78 patients (5.0%) had an in-hospital adverse outcome. The rate of an adverse outcome was higher in patients with a heart rate ≥100 bpm (7.6%) and ≥110 bpm (8.3%) compared to patients with a heart rate100 bpm (3.0%). A heart rate ≥100 bpm and ≥110 bpm was associated with a 2.7 (95% CI 1.7-4.3) and 2.4-fold (95% CI 1.5-3.7) increased risk for an adverse outcome, respectively. Receiver operating characteristics analysis revealed a similar area under the curve with regard to an adverse outcome for all scores and algorithm (ESC 2019 algorithm, modified FAST and Bova score) if calculated with a heart rate threshold of ≥100 bpm or of ≥110 bpm.Defining tachycardia by a heart rate ≥100 bpm is sufficient for risk stratification of normotensive patients with acute PE. The use of different heart rate thresholds for calculation of scores and algorithm does not appear necessary

The whole and its parts : why and how to disentangle plant communities and synusiae in vegetation classification

Most plant communities consist of different structural and ecological subsets, ranging from cryptogams to different tree layers. The completeness and approach with which these subsets are sampled have implications for vegetation classification. Non‐vascular plants are often omitted or sometimes treated separately, referring to their assemblages as “synusiae” (e.g. epiphytes on bark, saxicolous species on rocks). The distinction of complete plant communities (phytocoenoses or holocoenoses) from their parts (synusiae or merocoenoses) is crucial to avoid logical problems and inconsistencies of the resulting classification systems. We here describe theoretical differences between the phytocoenosis as a whole and its parts, and outline consequences of this distinction for practise and terminology in vegetation classification. To implement a clearer separation, we call for modifications of the International Code of Phytosociological Nomenclature and the EuroVegChecklist. We believe that these steps will make vegetation classification systems better applicable and raise the recognition of the importance of non‐vascular plants in the vegetation as well as their interplay with vascular plants

N-terminome analyses underscore the prevalence of SPPL3-mediated intramembrane proteolysis among Golgi-resident enzymes and its role in Golgi enzyme secretion

Golgi membrane proteins such as glycosyltransferases and other glycan-modifying enzymes are key to glycosylation of proteins and lipids. Secretion of soluble Golgi enzymes that are released from their membrane anchor by endoprotease activity is a wide-spread yet largely unexplored phenomenon. The intramembrane protease SPPL3 can specifically cleave select Golgi enzymes, enabling their secretion and concomitantly altering global cellular glycosylation, yet the entire range of Golgi enzymes cleaved by SPPL3 under physiological conditions remains to be defined. Here, we established isogenic SPPL3-deficient HEK293 and HeLa cell lines and applied N-terminomics to identify substrates cleaved by SPPL3 and released into cell culture supernatants. With high confidence, our study identifies more than 20 substrates of SPPL3, including entirely novel substrates. Notably, our N-terminome analyses provide a comprehensive list of SPPL3 cleavage sites demonstrating that SPPL3-mediated shedding of Golgi enzymes occurs through intramembrane proteolysis. Through the use of chimeric glycosyltransferase constructs we show that transmembrane domains can determine cleavage by SPPL3. Using our cleavage site data, we surveyed public proteome data and found that SPPL3 cleavage products are present in human blood. We also generated HEK293 knock-in cells expressing the active site mutant D271A from the endogenous SPPL3 locus. Immunoblot analyses revealed that secretion of select novel substrates such as the key mucin-type O-glycosylation enzyme GALNT2 is dependent on endogenous SPPL3 protease activity. In sum, our study expands the spectrum of known physiological substrates of SPPL3 corroborating its significant role in Golgi enzyme turnover and secretion as well as in the regulation of global glycosylation pathways

A series of PDB related databases for everyday needs

The Protein Data Bank (PDB) is the world-wide repository of macromolecular structure information. We present a series of databases that run parallel to the PDB. Each database holds one entry, if possible, for each PDB entry. DSSP holds the secondary structure of the proteins. PDBREPORT holds reports on the structure quality and lists errors. HSSP holds a multiple sequence alignment for all proteins. The PDBFINDER holds easy to parse summaries of the PDB file content, augmented with essentials from the other systems. PDB_REDO holds re-refined, and often improved, copies of all structures solved by X-ray. WHY_NOT summarizes why certain files could not be produced. All these systems are updated weekly. The data sets can be used for the analysis of properties of protein structures in areas ranging from structural genomics, to cancer biology and protein design

Acute exposure to simulated nocturnal traffic noise and cardiovascular complications and sleep disturbance : results from a pooled analysis of human field studies

Objectives A series of human field studies demonstrated that acute exposure to simulated nocturnal traffic noise is associated with cardiovascular complications and sleep disturbance, including endothelial dysfunction, increased blood pressure, and impaired sleep quality. A pooled analysis of these results remains to be established and is of tremendous interest to consolidate scientific knowledge. Methods We analyzed data from four randomized crossover studies (published between 2013 to 2021 and conducted at the University Medical Center Mainz, Germany). A total of 275 subjects (40.4% women, mean age 43.03 years) were each exposed to one control scenario (regular background noise) and at least to one traffic noise scenario (60 aircraft or train noise events) in their homes during nighttime. After each night, the subjects visited the study center for comprehensive cardiovascular function assessment, including the measurement of endothelial function and hemodynamic and biochemical parameters, as well as sleep-related variables. Results The pooled analysis revealed a significantly impaired endothelial function when comparing the two different noise sequences (0–60 vs. 60–0 simulated noise events, mean difference in flow-mediated dilation −2.00%, 95% CI −2.32; −1.68, p < 0.0001). In concordance, mean arterial pressure was significantly increased after traffic noise exposure (mean difference 2.50 mmHg, 95% CI 0.54; 4.45, p = 0.013). Self-reported sleep quality, the restfulness of sleep, and feeling in the morning were significantly impaired after traffic noise exposure (all p < 0.0001). Discussion Acute exposure to simulated nocturnal traffic noise is associated with endothelial dysfunction, increased mean arterial pressure, and sleep disturbance

Prediction of MHC class II binding affinity using SMM-align, a novel stabilization matrix alignment method

<p>Abstract</p> <p>Background</p> <p>Antigen presenting cells (APCs) sample the extra cellular space and present peptides from here to T helper cells, which can be activated if the peptides are of foreign origin. The peptides are presented on the surface of the cells in complex with major histocompatibility class II (MHC II) molecules. Identification of peptides that bind MHC II molecules is thus a key step in rational vaccine design and developing methods for accurate prediction of the peptide:MHC interactions play a central role in epitope discovery. The MHC class II binding groove is open at both ends making the correct alignment of a peptide in the binding groove a crucial part of identifying the core of an MHC class II binding motif. Here, we present a novel stabilization matrix alignment method, SMM-align, that allows for direct prediction of peptide:MHC binding affinities. The predictive performance of the method is validated on a large MHC class II benchmark data set covering 14 HLA-DR (human MHC) and three mouse H2-IA alleles.</p> <p>Results</p> <p>The predictive performance of the SMM-align method was demonstrated to be superior to that of the Gibbs sampler, TEPITOPE, SVRMHC, and MHCpred methods. Cross validation between peptide data set obtained from different sources demonstrated that direct incorporation of peptide length potentially results in over-fitting of the binding prediction method. Focusing on amino terminal peptide flanking residues (PFR), we demonstrate a consistent gain in predictive performance by favoring binding registers with a minimum PFR length of two amino acids. Visualizing the binding motif as obtained by the SMM-align and TEPITOPE methods highlights a series of fundamental discrepancies between the two predicted motifs. For the DRB1*1302 allele for instance, the TEPITOPE method favors basic amino acids at most anchor positions, whereas the SMM-align method identifies a preference for hydrophobic or neutral amino acids at the anchors.</p> <p>Conclusion</p> <p>The SMM-align method was shown to outperform other state of the art MHC class II prediction methods. The method predicts quantitative peptide:MHC binding affinity values, making it ideally suited for rational epitope discovery. The method has been trained and evaluated on the, to our knowledge, largest benchmark data set publicly available and covers the nine HLA-DR supertypes suggested as well as three mouse H2-IA allele. Both the peptide benchmark data set, and SMM-align prediction method (<it>NetMHCII</it>) are made publicly available.</p

Boosting the prediction and understanding of DNA-binding domains from sequence

DNA-binding proteins perform vital functions related to transcription, repair and replication. We have developed a new sequence-based machine learning protocol to identify DNA-binding proteins. We compare our method with an extensive benchmark of previously published structure-based machine learning methods as well as a standard sequence alignment technique, BLAST. Furthermore, we elucidate important feature interactions found in a learned model and analyze how specific rules capture general mechanisms that extend across DNA-binding motifs. This analysis is carried out using the malibu machine learning workbench available at http://proteomics.bioengr.uic.edu/malibu and the corresponding data sets and features are available at http://proteomics.bioengr.uic.edu/dna