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Ethylene oxide is mainly produced from fossil-based ethylene. Only minor amounts of EO are based on renewable ethanol in a three-step process consisting of an ethanol dehydration step, an ethylene purification step, and an epoxidation step. We herein present a new one-step process for the selective oxidation of ethanol to ethylene oxide by a novel dual-layer concept without intermediate ethylene purification. Ethanol is dehydrated in one reactor on a first catalyst bed to ethylene which is subsequently epoxidized over a silver catalyst. The dual-layer arrangement allowed stable operation over more than 60 h and state-of-the-art conversions and selectivities were obtained.

Abstract Background Metformin and sodium-glucose-cotransporter-2 inhibitors (SGLT2i) are cornerstone therapies for managing hyperglycemia in diabetes. However, their detailed impacts on metabolic processes, particularly within the citric acid (TCA) cycle and its anaplerotic pathways, remain unclear. This study investigates the tissue-specific metabolic effects of metformin, both as a monotherapy and in combination with SGLT2i, on the TCA cycle and associated anaplerotic reactions in both mice and humans. Methods Metformin-specific metabolic changes were initially identified by comparing metformin-treated diabetic mice (MET) with vehicle-treated db/db mice (VG). These findings were then assessed in two human cohorts (KORA and QBB) and a longitudinal KORA study of metformin-naïve patients with Type 2 Diabetes (T2D). We also compared MET with db/db mice on combination therapy (SGLT2i + MET). Metabolic profiling analyzed 716 metabolites from plasma, liver, and kidney tissues post-treatment, using linear regression and Bonferroni correction for statistical analysis, complemented by pathway analyses to explore the pathophysiological implications. Results Metformin monotherapy significantly upregulated TCA cycle intermediates such as malate, fumarate, and α-ketoglutarate (α-KG) in plasma, and anaplerotic substrates including hepatic glutamate and renal 2-hydroxyglutarate (2-HG) in diabetic mice. Downregulated hepatic taurine was also observed. The addition of SGLT2i, however, reversed these effects, such as downregulating circulating malate and α-KG, and hepatic glutamate and renal 2-HG, but upregulated hepatic taurine. In human T2D patients on metformin therapy, significant systemic alterations in metabolites were observed, including increased malate but decreased citrulline. The bidirectional modulation of TCA cycle intermediates in mice influenced key anaplerotic pathways linked to glutaminolysis, tumorigenesis, immune regulation, and antioxidative responses. Conclusion This study elucidates the specific metabolic consequences of metformin and SGLT2i on the TCA cycle, reflecting potential impacts on the immune system. Metformin shows promise for its anti-inflammatory properties, while the addition of SGLT2i may provide liver protection in conditions like metabolic dysfunction-associated steatotic liver disease (MASLD). These observations underscore the importance of personalized treatment strategies.

Abstract Music is ubiquitous in our everyday lives, and lyrics play an integral role when we listen to music. The complex relationships between lyrical content, its temporal evolution over the last decades, and genre-specific variations, however, are yet to be fully understood. In this work, we investigate the dynamics of English lyrics of Western, popular music over five decades and five genres, using a wide set of lyrics descriptors, including lyrical complexity, structure, emotion, and popularity. We find that pop music lyrics have become simpler and easier to comprehend over time: not only does the lexical complexity of lyrics decrease (for instance, captured by vocabulary richness or readability of lyrics), but we also observe that the structural complexity (for instance, the repetitiveness of lyrics) has decreased. In addition, we confirm previous analyses showing that the emotion described by lyrics has become more negative and that lyrics have become more personal over the last five decades. Finally, a comparison of lyrics view counts and listening counts shows that when it comes to the listeners’ interest in lyrics, for instance, rock fans mostly enjoy lyrics from older songs; country fans are more interested in new songs’ lyrics.

The global increase of the amount of microplastics in aquatic systems is an ever-growing problem. Household laundering of synthetic textiles has been identified as one significant reason for the release of fibrous microplastics (FMP), although a high proportion of the waste water generated by the washing process is filtered by wastewater treatment plants, e.g., in Germany, before it enters the environment. The washing of garments made of synthetic materials is considered particularly and was investigated during this study. Therefore, 11 fleece garments, one mixed batch and three non-raised garments were washed several times and under different conditions in houshold washing machines. However, this study utilizing different functional polyester garments showed that mechanical raised textiles (e.g., fleece) do not generally have higher emission values than non-raised textiles, such as sports shirts and sports pants. During the washing process, the release of FMP can be influenced by different washing parameters, always aiming for a good washing result. The experiments showed, that the release of FMP into the aquatic environment can be reduced by the washing habits—especially a high washing machine load and a shortened washing time were found to be effective.

Abstract Background This review summarises the present state of research on health inequalities using a social network perspective, and it explores the available studies examining the interrelations of social inequality, social networks, and health. Methods Using the strategy of a scoping review, as outlined by Arksey and O’Malley (Int J Sci Res Methodol 8:19–32, 2005), our team performed two searches across eight scientific, bibliographic databases including papers published until October 2021. Studies meeting pre-defined eligibility criteria were selected. The data were charted in a table, and then collated, summarised, and reported in this paper. Results Our search provided a total of 15,237 initial hits. After deduplication (n = 6,168 studies) and the removal of hits that did not meet our baseline criteria (n = 8,767 studies), the remaining 302 full text articles were examined. This resulted in 25 articles being included in the present review, many of which focused on moderating or mediating network effects. Such effects were found in the majority of these studies, but not in all. Social networks were found to buffer the harsher effects of poverty on health, while specific network characteristics were shown to intensify or attenuate the health effects of social inequalities. Conclusions Our review showed that the variables used for measuring health and social networks differed considerably across the selected studies. Thus, our attempt to establish a consensus of opinion across the included studies was not successful. Nevertheless, the usefulness of social network analysis in researching health inequalities and the employment of health-promoting interventions focusing on social relations was generally acknowledged in the studies. We close by suggesting ways to advance the research methodology, and argue for a greater orientation on theoretical models. We also call for the increased use of structural measures; the inclusion of measures on negative ties and interactions; and the use of more complex study designs, such as mixed-methods and longitudinal studies.

Inversion of the uterus is defined as the turning inside out of the fundus into the uterine cavity. According to the literature, uterine inversion occurs in 1/20,000 or even 1/1,584 deliveries. Mortality rates following acute uterine inversion were reported by some authors to have been as high as 80%. Therefore, it is very important to make an early diagnosis. The shorter the time between the moment of uterine inversion and its repositioning, the better the results of conservative treatment, and bigger chance of avoiding surgical management. The article presents two cases of patients hospitalised in 2010 – 2011 in the Gynaecologic and Obstetrics Department of the Regional Polyclinic Hospital in Kalisz, Central Poland, diagnosed with acute uterine inversion in accordance with the applicable classification. Surgical management was applied in one of the patients. The other patient was managed in a conservative manner. Both women were discharged from the hospital in a good general condition.

BackgroundChildren with medical complexity (CMC) are prone to medical errors and longer hospital stays, while residents do not feel prepared to provide adequate medical care for this vulnerable population. No educational guidance for the training of future pediatric tertiary care specialists outside their field of expertise involving the multidisciplinary care of CMC exists. We investigated pediatric residents past educational needs and challenges to identify key learning content for future training involving care for CMC.MethodsThis was a prospective mixed-methods study at a single pediatric tertiary care center. Qualitative semi-structured interviews with residents were conducted, submitted to thematic content analysis, linked to the American Board of Pediatrics (ABP) general pediatrics content outline, and analyzed with importance performance analysis (IPA). Quantitative validation was focused on key themes of pediatric nephrology within the scope of an online survey among pediatric residents and specialists.ResultsA total of 16 interviews, median duration 69 min [interquartile range IQR 35], were conducted. The 280 listed themes of the ABP general pediatrics content outline were reduced to 165 themes, with 86% (theoretical) knowledge, 12% practical skills, and 2% soft skills. IPA identified 23 knowledge themes to be of high importance where improvement is necessary and deemed fruitful. Quantitative validation among 84 residents and specialists (response rate 55%) of key themes in nephrology yielded high agreement among specialists in pediatric nephrology but low interrater agreement among trainees and “trained” non-nephrologists. The occurrence of themes in the qualitative interviews and their calculated importance in the quantitative survey were highly correlated (tau = 0.57, p = 0.001). Two clusters of high importance for other pediatric specialties emerged together with a contextual cluster of frequent encounters in both in- and outpatient care.ConclusionRegarding patient safety, this study revealed the heterogeneous aspects and the importance of training future pediatric tertiary care specialists outside their field of expertise involving the multidisciplinary care of CMC. Our results may lay the groundwork for future detailed analysis and development of training boot camps that might be able to aid the improvement of patient safety by decreasing preventable harm by medical errors, especially for vulnerable patient groups, such as CMC in tertiary care pediatrics.

BackgroundPsychotherapeutic consultation services in the workplace (PSIW) have been developed to provide collaborative mental health care for employees. The aim of this study was to analyze participant characteristics, the role of PSIW in treatment courses, and the development of sick leave before and after PSIW start.MethodsRoutine data from PSIW and health insurance of 155 participants were analyzed descriptively and by means of a multilevel negative binomial regression.ResultsEighty-four percent of users were male, and 72% were diagnosed with a mental disorder. The number of PSIW consultations varied from 1 to 13 (mean = 4). For 34% of participants, PSIW sessions were sufficient, 33% received a recommendation for outpatient psychotherapy, and 20% for inpatient mental health treatment. While recommendations for inpatient treatment displayed a high adherence rate (74%), recommendations for outpatient treatment were followed by 37%. Compared with the period of a half-year before PSIW, sick-leave days were reduced from the period of the second half-year after PSIW start and in the subsequent observed half-year periods. Trajectories of sick leave by subgroups showed differences.ConclusionsPSIW is a flexible care offer, and results indicate a possible effect of PSIW on sick leave. In future studies, control group designs and inclusion of further variables are needed.

Air contaminants can have detrimental effects on the performance and durability of proton exchange membrane (PEM) fuel cell vehicles. This research focuses on the experimental investigation of the effect of nitrogen monoxide (NO) in the cathode gas stream, which provokes a cell voltage decrease due to the partially reversible adsorption of NO on the platinum catalyst. The concentration and exposure time of NO in the cathode gas stream are varied at selected constant current densities and load ramps to assess the effects throughout the fuel cell system operating range. The results show the cell voltage loss in the presence of NO and reveal a near-catalyst saturation with increased injected NO mass. Additionally, several voltage recovery and mitigation strategies are introduced and discussed by presenting conclusions about the general effect of NO on a fuel cell system in operation. The most promising recovery strategy for fuel cell systems is identified, and the overall system degradation is discussed. All experiments are performed in a test bed environment on a 25 kW low-temperature fuel cell system via controlled injection of NO into the cathode gas stream.

The filtering of gut microbial datasets to retain high prevalence taxa is often performed to identify a common core gut microbiome that may be important for host biological functions. However, prevalence thresholds used to identify a common core are highly variable, and it remains unclear how they affect diversity estimates and whether insights stemming from core microbiomes are comparable across studies. We hypothesized that if macroecological patterns in gut microbiome prevalence and abundance are similar across host species, then we would expect that increasing prevalence thresholds would yield similar changes to alpha diversity and beta dissimilarity scores across host species datasets. We analyzed eight gut microbiome datasets based on 16S rRNA gene amplicon sequencing and collected from different host species to (1) compare macroecological patterns across datasets, including amplicon sequence variant (ASV) detection rate with sequencing depth and sample size, occupancy-abundance curves, and rank-abundance curves; (2) test whether increasing prevalence thresholds generate universal or host-species specific effects on alpha and beta diversity scores; and (3) test whether diversity scores from prevalence-filtered core communities correlate with unfiltered data. We found that gut microbiomes collected from diverse hosts demonstrated similar ASV detection rates with sequencing depth, yet required different sample sizes to sufficiently capture rare ASVs across the host population. This suggests that sample size rather than sequencing depth tends to limit the ability of studies to detect rare ASVs across the host population. Despite differences in the distribution and detection of rare ASVs, microbiomes exhibited similar occupancy-abundance and rank-abundance curves. Consequently, increasing prevalence thresholds generated remarkably similar trends in standardized alpha diversity and beta dissimilarity across species datasets until high thresholds above 70%. At this point, diversity scores tended to become unpredictable for some diversity measures. Moreover, high prevalence thresholds tended to generate diversity scores that correlated poorly with the original unfiltered data. Overall, we recommend that high prevalence thresholds over 70% are avoided, and promote the use of diversity measures that account for phylogeny and abundance (Balance-weighted phylogenetic diversity and Weighted Unifrac for alpha and beta diversity, respectively), because we show that these measures are insensitive to prevalence filtering and therefore allow for the consistent comparison of core gut microbiomes across studies without the need for prevalence filtering.

The genetic landscape of diseases associated with changes in bone mineral density (BMD), such as osteoporosis, is only partially understood. Here, we explored data from 3,823 mutant mouse strains for BMD, a measure that is frequently altered in a range of bone pathologies, including osteoporosis. A total of 200 genes were found to significantly affect BMD. This pool of BMD genes comprised 141 genes with previously unknown functions in bone biology and was complementary to pools derived from recent human studies. Nineteen of the 141 genes also caused skeletal abnormalities. Examination of the BMD genes in osteoclasts and osteoblasts underscored BMD pathways, including vesicle transport, in these cells and together with in silico bone turnover studies resulted in the prioritization of candidate genes for further investigation. Overall, the results add novel pathophysiological and molecular insight into bone health and disease.

The analysis of the gut microbiome with respect to health care prevention and diagnostic purposes is increasingly the focus of current research. We analyzed around 2000 stool samples from the KORA (Cooperative Health Research in the Region of Augsburg) cohort using high-throughput 16S rRNA gene amplicon sequencing representing a total microbial diversity of 2089 operational taxonomic units (OTUs). We evaluated the combination of three different components to assess the reflection of obesity related to microbiota profiles: (i) four prediction methods (i.e., partial least squares (PLS), support vector machine regression (SVMReg), random forest (RF), and M5Rules); (ii) five OTU data transformation approaches (i.e., no transformation, relative abundance without and with log-transformation, as well as centered and isometric log-ratio transformations); and (iii) predictions from nine measurements of obesity (i.e., body mass index, three measures of body shape, and five measures of body composition). Our results showed a substantial impact of all three components. The applications of SVMReg and PLS in combination with logarithmic data transformations resulted in considerably predictive models for waist circumference-related endpoints. These combinations were at best able to explain almost 40% of the variance in obesity measurements based on stool microbiota data (i.e., OTUs) only. A reduced loss in predictive performance was seen after sex-stratification in waist–height ratio compared to other waist-related measurements. Moreover, our analysis showed that the contribution of OTUs less prevalent and abundant is minor concerning the predictive power of our models.

[This corrects the article DOI: 10.1371/journal.pgen.1006379.].

By using fluorescence correlation spectroscopy (FCS), we have studied the adsorption of human serum albumin (HSA) onto Fe–Pt nanoparticles (NPs, 6 nm radius), CdSe/ZnS quantum dots (QDs, 5 nm radius) and Au and Ag nanoclusters (1–4 nm radius), which are enshrouded by various water-solubilizing surface layers exposing different chemical functional groups (carboxyl, amino and both), thereby endowing the NPs with different surface charges. We have also measured the effects of modified surface functionalizations on the protein via succinylation and amination. A step-wise increase in hydrodynamic radius with protein concentration was always observed, revealing formation of protein monolayers coating the NPs, independent of their surface charge. The differences in the thickness of the protein corona were rationalized in terms of the different orientations in which HSA adsorbs onto the NPs. The midpoints of the binding transition, which quantifies the affinity of HSA toward the NP, were observed to differ by almost four orders of magnitude. These variations can be understood in terms of specific Coulombic interactions between the proteins and the NP surfaces.

Ageing, one of the largest risk factors for many complex diseases, is highly interconnected to metabolic processes. Investigating the changes in metabolite concentration during ageing among healthy individuals offers us unique insights to healthy ageing. We aim to identify ageing-associated metabolites that are independent from chronological age to deepen our understanding of the long-term changes in metabolites upon ageing. Sex-stratified longitudinal analyses were performed using fasting serum samples of 590 healthy KORA individuals (317 women and 273 men) who participated in both baseline (KORA S4) and seven-year follow-up (KORA F4) studies. Replication was conducted using serum samples of 386 healthy CARLA participants (195 women and 191 men) in both baseline (CARLA-0) and four-year follow-up (CARLA-1) studies. Generalized estimation equation models were performed on each metabolite to identify ageing-associated metabolites after adjusting for baseline chronological age, body mass index, physical activity, smoking status, alcohol intake and systolic blood pressure. Literature researches were conducted to understand their biochemical relevance. Out of 122 metabolites analysed, we identified and replicated five (C18, arginine, ornithine, serine and tyrosine) and four (arginine, ornithine, PC aa C36:3 and PC ae C40:5) significant metabolites in women and men respectively. Arginine decreased, while ornithine increased in both sexes. These metabolites are involved in several ageing processes: apoptosis, mitochondrial dysfunction, inflammation, lipid metabolism, autophagy and oxidative stress resistance. The study reveals several significant ageing-associated metabolite changes with two-time-point measurements on healthy individuals. Larger studies are required to confirm our findings.

Insulin resistance (IR) and impaired insulin secretion contribute to type 2 diabetes and cardiovascular disease. Both are associated with changes in the circulating metabolome, but causal directions have been difficult to disentangle. We combined untargeted plasma metabolomics by liquid chromatography/mass spectrometry in three non-diabetic cohorts with Mendelian Randomization (MR) analysis to obtain new insights into early metabolic alterations in IR and impaired insulin secretion. In up to 910 elderly men we found associations of 52 metabolites with hyperinsulinemic-euglycemic clamp-measured IR and/or β-cell responsiveness (disposition index) during an oral glucose tolerance test. These implicated bile acid, glycerophospholipid and caffeine metabolism for IR and fatty acid biosynthesis for impaired insulin secretion. In MR analysis in two separate cohorts (n = 2,613) followed by replication in three independent studies profiled on different metabolomics platforms (n = 7,824 / 8,961 / 8,330), we discovered and replicated causal effects of IR on lower levels of palmitoleic acid and oleic acid. A trend for a causal effect of IR on higher levels of tyrosine reached significance only in meta-analysis. In one of the largest studies combining "gold standard" measures for insulin responsiveness with non-targeted metabolomics, we found distinct metabolic profiles related to IR or impaired insulin secretion. We speculate that the causal effects on monounsaturated fatty acid levels could explain parts of the raised cardiovascular disease risk in IR that is independent of diabetes development.

Night shift work can have a serious impact on health. Here, we assess whether and how night shift work influences the metabolite profiles, specifically with respect to different chronotype classes. We have recruited 100 women including 68 nurses working both, day shift and night shifts for up to 5 consecutive days and collected 3640 spontaneous urine samples. About 424 waking-up urine samples were measured using a targeted metabolomics approach. To account for urine dilution, we applied three methods to normalize the metabolite values: creatinine-, osmolality- and regression-based normalization. Based on linear mixed effect models, we found 31 metabolites significantly (false discovery rate

The quality criteria for experimental design approaches in chemoinformatics are numerous. Not only the error performance of a model resulting from the selected compounds is of importance, but also reliability, consistency, stability and robustness against small variations in the dataset or structurally diverse compounds. We developed a new stepwise, adaptive approach, DescRep, combining an iteratively refined descriptor selection with a sampling based on the putatively most representative compounds. A comparison of the proposed strategy was based on statistical performance of models derived from such a selection to those derived by other popular and frequently used approaches, such as the Kennard-Stone algorithm or the most descriptive compound selection. We used three datasets to carry out a statistical evaluation of the performance, reliability and robustness of the resulting models. Our results indicate that stepwise and adaptive approaches have a better adaptability to changes within a dataset and that this adaptability results in a better error performance and stability of the resulting models.

The type III secretion system (TTSS) is a key mechanism for host cell interaction used by a variety of bacterial pathogens and symbionts of plants and animals including humans. The TTSS represents a molecular syringe with which the bacteria deliver effector proteins directly into the host cell cytosol. Despite the importance of the TTSS for bacterial pathogenesis, recognition and targeting of type III secreted proteins has up until now been poorly understood. Several hypotheses are discussed, including an mRNA-based signal, a chaperon-mediated process, or an N-terminal signal peptide. In this study, we systematically analyzed the amino acid composition and secondary structure of N-termini of 100 experimentally verified effector proteins. Based on this, we developed a machine-learning approach for the prediction of TTSS effector proteins, taking into account N-terminal sequence features such as frequencies of amino acids, short peptides, or residues with certain physico-chemical properties. The resulting computational model revealed a strong type III secretion signal in the N-terminus that can be used to detect effectors with sensitivity of approximately 71% and selectivity of approximately 85%. This signal seems to be taxonomically universal and conserved among animal pathogens and plant symbionts, since we could successfully detect effector proteins if the respective group was excluded from training. The application of our prediction approach to 739 complete bacterial and archaeal genome sequences resulted in the identification of between 0% and 12% putative TTSS effector proteins. Comparison of effector proteins with orthologs that are not secreted by the TTSS showed no clear pattern of signal acquisition by fusion, suggesting convergent evolutionary processes shaping the type III secretion signal. The newly developed program EffectiveT3 (http://www.chlamydiaedb.org) is the first universal in silico prediction program for the identification of novel TTSS effectors. Our findings will facilitate further studies on and improve our understanding of type III secretion and its role in pathogen-host interactions.