[Current data on rheumatological care: annual report from the National database (NDB) of the regional collaborative arthritis centres in Germany]. / Aktuelle Zahlen zur rheumatologischen Versorgung ­ Jahresbericht aus der Kerndokumentation der regionalen kooperativen Rheumazentren.

In the National database (NDB) of the German regional collaborative arthritis centres, annual data on the rheumatological care of patients with inflammatory rheumatic diseases have been collected since 1993. This first annual report presents current cross-sectional data on medication and patient-reported outcomes gathered in 2022.

Impact of DMARD treatment and systemic inflammation on all-cause mortality in patients with rheumatoid arthritis and interstitial lung disease: a cohort study from the German RABBIT register.

OBJECTIVES: To investigate the impact of disease activity and treatment with disease-modifying antirheumatic drugs (DMARDs) on all-cause mortality in patients with rheumatoid arthritis and prevalent interstitial lung disease (RA-ILD). METHODS: Patients with RA-ILD were selected from the biologics register Rheumatoid Arthritis: Observation of Biologic Therapy (RABBIT). Using time-varying Cox regression, the association between clinical measures and mortality was investigated. The impact of DMARDs was analysed by (1) Cox regression considering cumulative exposure (ie, treatment months divided by total months) and (2) time-varying Cox regression as main approach (treatment exposures at monthly level). RESULTS: Out of 15 566 participants, 381 were identified as RA-ILD cases with 1258 person-years of observation and 2.6 years median length of follow-up. Ninety-seven patients (25.5%) died and 34 (35.1%) of these were not receiving DMARD therapy at the time of death. Higher inflammatory biomarkers but not swollen and tender joint count were significantly associated with mortality. Compared with tumour necrosis factor inhibitors (TNFi), non-TNFi biologic DMARDs (bDMARDs) exhibited adjusted HRs (aHRs) for mortality below 1, lacking statistical significance. This finding was stable in various sensitivity analyses. Joint aHR for non-TNFi biologics and JAKi versus TNFi was 0.56 (95% CI 0.33 to 0.97). Receiving no DMARD treatment was associated with a twofold higher mortality risk compared with receiving any DMARD treatment, aHR 2.03 (95% CI 1.23 to 3.35). CONCLUSIONS: Inflammatory biomarkers and absence of DMARD treatment were associated with increased risk of mortality in patients with RA-ILD. Non-TNFi bDMARDs may confer enhanced therapeutic benefits in patients with RA-ILD.

Global trends and scenarios for terrestrial biodiversity and ecosystem services from 1900 to 2050.

Based on an extensive model intercomparison, we assessed trends in biodiversity and ecosystem services from historical reconstructions and future scenarios of land-use and climate change. During the 20th century, biodiversity declined globally by 2 to 11%, as estimated by a range of indicators. Provisioning ecosystem services increased several fold, and regulating services decreased moderately. Going forward, policies toward sustainability have the potential to slow biodiversity loss resulting from land-use change and the demand for provisioning services while reducing or reversing declines in regulating services. However, negative impacts on biodiversity due to climate change appear poised to increase, particularly in the higher-emissions scenarios. Our assessment identifies remaining modeling uncertainties but also robustly shows that renewed policy efforts are needed to meet the goals of the Convention on Biological Diversity.

Quantifying the impact of key factors on the carbon mitigation potential of managed temperate forests.

BACKGROUND: Forests mitigate climate change by reducing atmospheric CO 2 -concentrations through the carbon sink in the forest and in wood products, and substitution effects when wood products replace carbon-intensive materials and fuels. Quantifying the carbon mitigation potential of forests is highly challenging due to the influence of multiple important factors such as forest age and type, climate change and associated natural disturbances, harvest intensities, wood usage patterns, salvage logging practices, and the carbon-intensity of substituted products. Here, we developed a framework to quantify the impact of these factors through factorial simulation experiments with an ecosystem model at the example of central European (Bavarian) forests. RESULTS: Our simulations showed higher mitigation potentials of young forests compared to mature forests, and similar ones in broad-leaved and needle-leaved forests. Long-lived wood products significantly contributed to mitigation, particularly in needle-leaved forests due to their wood product portfolio, and increased material usage of wood showed considerable climate benefits. Consequently, the ongoing conversion of needle-leaved to more broad-leaved forests should be accompanied by the promotion of long-lived products from broad-leaved species to maintain the product sink. Climate change (especially increasing disturbances) and decarbonization were among the most critical factors influencing mitigation potentials and introduced substantial uncertainty. Nevertheless, until 2050 this uncertainty was narrow enough to derive robust findings. For instance, reducing harvest intensities enhanced the carbon sink in our simulations, but diminished substitution effects, leading to a decreased total mitigation potential until 2050. However, when considering longer time horizons (i.e. until 2100), substitution effects became low enough in our simulations due to expected decarbonization such that decreasing harvests often seemed the more favorable solution. CONCLUSION: Our results underscore the need to tailor mitigation strategies to the specific conditions of different forest sites. Furthermore, considering substitution effects, and thoroughly assessing the amount of avoided emissions by using wood products, is critical to determine mitigation potentials. While short-term recommendations are possible, we suggest risk diversification and methodologies like robust optimization to address increasing uncertainties from climate change and decarbonization paces past 2050. Finally, curbing emissions reduces the threat of climate change on forests, safeguarding their carbon sink and ecosystem services.

The protective effect of tumor necrosis factor-alpha inhibitors in COVID-19 in patients with inflammatory rheumatic diseases compared to the general population-A comparison of two German registries.

Objectives: To investigate, whether inflammatory rheumatic diseases (IRD) inpatients are at higher risk to develop a severe course of SARS-CoV-2 infections compared to the general population, data from the German COVID-19 registry for IRD patients and data from the Lean European Survey on SARS-CoV-2 (LEOSS) infected patients covering inpatients from the general population with SARS-CoV-2 infections were compared. Methods: 4310 (LEOSS registry) and 1139 cases (IRD registry) were collected in general. Data were matched for age and gender. From both registries, 732 matched inpatients (LEOSS registry: n = 366 and IRD registry: n = 366) were included for analyses in total. Results: Regarding the COVID-19 associated lethality, no significant difference between both registries was observed. Age > 65°years, chronic obstructive pulmonary disease, diabetes mellitus, rheumatoid arthritis, spondyloarthritis and the use of rituximab were associated with more severe courses of COVID-19. Female gender and the use of tumor necrosis factor-alpha inhibitors (TNF-I) were associated with a better outcome of COVID-19. Conclusion: Inflammatory rheumatic diseases (IRD) patients have the same risk factors for severe COVID-19 regarding comorbidities compared to the general population without any immune-mediated disease or immunomodulation. The use of rituximab was associated with an increased risk for severe COVID-19. On the other hand, the use of TNF-I was associated with less severe COVID-19 compared to the general population, which might indicate a protective effect of TNF-I against severe COVID-19 disease.

Population pharmacokinetics of the dual endothelin receptor antagonist aprocitentan in subjects with or without essential or resistant hypertension.

Aprocitentan is a novel, potent, dual endothelin receptor antagonist that recently demonstrated efficacy in the treatment of difficult-to-treat (resistant) hypertension. The aim of this study was to develop a population pharmacokinetic (PK) model describing aprocitentan plasma concentration over time, to investigate relationships between subject-specific factors (covariates) and model parameters, and to quantify the influence of the identified covariates on the exposure to aprocitentan via model-based simulations, enabling judgment about the clinical relevance of the covariates.PK data from 902 subjects in ten Phase 1, one Phase 2, and one Phase 3 study were pooled to develop a joint population PK model. The concentration-time course of aprocitentan was described by a two-compartment model with absorption lag time, first-order absorption and elimination, and reduced relative bioavailability following very high doses of 300 and 600 mg.The population PK model described the observed data well. Volume and clearance parameters were associated with body weight. Renal function as reflected by estimated glomerular filtration rate (eGFR), hepatic impairment, and sex were identified as relevant covariates on clearance.The subject-specific characteristics of body weight, eGFR, hepatic impairment, and sex were shown to influence exposure parameters area under the concentration-time curve and maximum concentration in steady state to a limited extent, i.e., not more than 25% different from a reference subject, and therefore do not warrant dose adjustments.

A Call for Gene Expression Analysis in Whole Blood of Patients With Rheumatoid Arthritis (RA) as a Biomarker for RA-Associated Interstitial Lung Disease.

OBJECTIVE: Rheumatoid arthritis (RA)-associated interstitial lung disease (ILD) is one of the most common and prognostic organ manifestations of RA. Therefore, to allow effective treatment, it is of crucial importance to diagnose RA-ILD at the earliest possible stage. So far, the gold standard of early detection has been high-resolution computed tomography (HRCT) of the lungs. This procedure involves considerable radiation exposure for the patient and is therefore unsuitable as a routine screening measure for ethical reasons. Here, we propose the analysis of characteristic gene expression patterns as a biomarker to aid in the early detection and initiation of appropriate, possibly antifibrotic, therapy. METHODS: To investigate unique molecular patterns of RA-ILD, whole blood samples were taken from 12 female patients with RA-ILD (n = 7) or RA (n = 5). The RNA was extracted, sequenced by RNA-Seq, and analyzed for characteristic differences in the gene expression patterns between patients with RA-ILD and those with RA without ILD. RESULTS: The differential gene expression analysis revealed 9 significantly upregulated genes in RA-ILD compared to RA without ILD: arginase 1 (ARG1), thymidylate synthetase (TYMS), sortilin 1 (SORT1), marker of proliferation Ki-67 (MKI67), olfactomedin 4 (OLFM4), baculoviral inhibitor of apoptosis repeat containing 5 (BIRC5), membrane spanning 4-domains A4A (MS4A4A), C-type lectin domain family 12 member A (CLEC12A), and the long intergenic nonprotein coding RNA (LINC02967). CONCLUSION: All gene products of these genes (except for LINC02967) are known from the literature to be involved in the pathogenesis of fibrosis. Further, for some, a contribution to the development of pulmonary fibrosis has even been demonstrated in experimental studies. Therefore, the results presented here provide an encouraging perspective for using specific gene expression patterns as biomarkers for the early detection and differential diagnosis of RA-ILD as a routine screening test.

Training the next generation of pharmacometric modelers: a multisector perspective.

The current demand for pharmacometricians outmatches the supply provided by academic institutions and considerable investments are made to develop the competencies of these scientists on-the-job. Even with the observed increase in academic programs related to pharmacometrics, this need is unlikely to change in the foreseeable future, as the demand and scope of pharmacometrics applications keep expanding. Further, the field of pharmacometrics is changing. The field largely started when Lewis Sheiner and Stuart Beal published their seminal papers on population pharmacokinetics in the late 1970's and early 1980's and has continued to grow in impact and use since its inception. Physiological-based pharmacokinetics and systems pharmacology have grown rapidly in scope and impact in the last decade and machine learning is just on the horizon. While all these methodologies are categorized as pharmacometrics, no one person can be an expert in everything. So how do you train future pharmacometricians? Leading experts in academia, industry, contract research organizations, clinical medicine, and regulatory gave their opinions on how to best train future pharmacometricians. Their opinions were collected and synthesized to create some general recommendations.

Survey on the working, training, and research conditions of resident physicians in internistic and rheumatological continuing education-BEWUSST.

BACKGROUND: Data on the training and continuing education situation of residents in the field of internal medicine and rheumatology are not available for Germany. For this reason, the Commission for Education and Training of the German Society of Rheumatology (DGRh) initiated the BEWUSST survey on the working, training and research conditions of residents in rheumatology. METHODS: A total of 102 questions on the topics of working conditions in everyday professional life, continuing medical education and training, compatibility of career and family, compatibility of work and research, perspectives as a rheumatologist and practical activities were included in an online questionnaire. RESULTS: A total of 102 participants took part in the survey. Of the respondents 48.1% were satisfied with their professional situation, 40.2% of the participants were supervised by a specialist mentor and 54.9% were working as scientists during their work as a physician. A compatibility of family and career was possible for 34.7%. After completion of the residency 52.9% of the respondents aspired to a combined clinical and outpatient activity. CONCLUSION: Half of the trainee rheumatologists are satisfied with their professional activities, although mentoring of the assistants in training should be further improved. With respect to the desired combined clinical and outpatient activity, the existing options should be expanded or new professional fields of activity should be established, so that the specialty remains attractive for the upcoming generations.

ChromaX: a fast and scalable breeding program simulator.

SUMMARY: ChromaX is a Python library that enables the simulation of genetic recombination, genomic estimated breeding value calculations, and selection processes. By utilizing GPU processing, it can perform these simulations up to two orders of magnitude faster than existing tools with standard hardware. This offers breeders and scientists new opportunities to simulate genetic gain and optimize breeding schemes. AVAILABILITY AND IMPLEMENTATION: The documentation is available at https://chromax.readthedocs.io. The code is available at https://github.com/kora-labs/chromax.

Mind the Gap: Model-Based Switching from Selatogrel to Maintenance Therapy with Oral P2Y12 Receptor Antagonists.

Background: The P2Y12 receptor antagonist selatogrel is being developed for subcutaneous self-administration with a ready-to-use autoinjector at the onset of acute myocardial infarction (AMI) symptoms. The unique pharmacological profile of selatogrel (fast, potent, and short-acting) can bridge the time gap between the onset of AMI and first medical care. A clinical Phase 1 study showed a time-dependent pharmacodynamic interaction between selatogrel and loading doses of clopidogrel and prasugrel. As treatment switching is a common clinical practice, the assessment of subsequent switching from a clopidogrel loading dose to the first maintenance dose of oral P2Y12 receptor antagonists is highly relevant. Objectives: Model-based predictions of inhibition of platelet aggregation (IPA) for the drugs triggering pharmacodynamic interactions were to be derived to support clinical guidance on the transition from selatogrel to oral P2Y12 receptor antagonists. Methods: Scenarios with selatogrel 16 mg administration or placebo followed by a clopidogrel loading dose and, in turn, prasugrel or ticagrelor maintenance doses at different times of administration were studied. Population pharmacokinetic/pharmacodynamic modeling and simulations of different treatment scenarios were used to derive quantitative estimates for IPA over time. Results: Following selatogrel/placebo and a clopidogrel loading dose, maintenance treatment with ticagrelor or a prasugrel loading dose followed by maintenance treatment quickly achieved sustained IPA levels above 80%. Prior to maintenance treatment, a short time span from 18 to 24 h was identified where IPA levels were predicted to be lower with selatogrel than with placebo if clopidogrel was administered 12 h after selatogrel or placebo. Predicted IPA levels reached with placebo alone and a clopidogrel loading dose at 4 h were consistently lower than with selatogrel administration, followed by a clopidogrel loading dose at 12 h. If a clopidogrel loading dose is administered at 12 h, selatogrel maintains higher IPA levels up to 16 h. IPA levels are subsequently lower than on the placebo until the administration of the first maintenance dose. Conclusions: Model-based predictions informed the transition from selatogrel subcutaneous administration to oral P2Y12 therapy. The application of modeling techniques illustrates the value of employing pharmacokinetic and pharmacodynamic modeling for the simulation of various clinical scenarios of switching therapies.

Bayesian optimization with safety constraints: safe and automatic parameter tuning in robotics.

Selecting the right tuning parameters for algorithms is a pravelent problem in machine learning that can significantly affect the performance of algorithms. Data-efficient optimization algorithms, such as Bayesian optimization, have been used to automate this process. During experiments on real-world systems such as robotic platforms these methods can evaluate unsafe parameters that lead to safety-critical system failures and can destroy the system. Recently, a safe Bayesian optimization algorithm, called SafeOpt, has been developed, which guarantees that the performance of the system never falls below a critical value; that is, safety is defined based on the performance function. However, coupling performance and safety is often not desirable in practice, since they are often opposing objectives. In this paper, we present a generalized algorithm that allows for multiple safety constraints separate from the objective. Given an initial set of safe parameters, the algorithm maximizes performance but only evaluates parameters that satisfy safety for all constraints with high probability. To this end, it carefully explores the parameter space by exploiting regularity assumptions in terms of a Gaussian process prior. Moreover, we show how context variables can be used to safely transfer knowledge to new situations and tasks. We provide a theoretical analysis and demonstrate that the proposed algorithm enables fast, automatic, and safe optimization of tuning parameters in experiments on a quadrotor vehicle.

Learning single-cell perturbation responses using neural optimal transport.

Understanding and predicting molecular responses in single cells upon chemical, genetic or mechanical perturbations is a core question in biology. Obtaining single-cell measurements typically requires the cells to be destroyed. This makes learning heterogeneous perturbation responses challenging as we only observe unpaired distributions of perturbed or non-perturbed cells. Here we leverage the theory of optimal transport and the recent advent of input convex neural architectures to present CellOT, a framework for learning the response of individual cells to a given perturbation by mapping these unpaired distributions. CellOT outperforms current methods at predicting single-cell drug responses, as profiled by scRNA-seq and a multiplexed protein-imaging technology. Further, we illustrate that CellOT generalizes well on unseen settings by (1) predicting the scRNA-seq responses of holdout patients with lupus exposed to interferon-ß and patients with glioblastoma to panobinostat; (2) inferring lipopolysaccharide responses across different species; and (3) modeling the hematopoietic developmental trajectories of different subpopulations.

[Survey on the working, training, and research conditions of resident physicians in internistic and rheumatological continuing education-BEWUSST]. / Befragung zu den Arbeits-, Weiterbildungs- und Forschungsbedingungen von Assistenzärztinnen und -ärzten in der internistisch-rheumatologischen Weiterbildung ­ BEWUSST.

BACKGROUND: Data on the training and continuing education situation of residents in the field of internal medicine and rheumatology are not available for Germany. For this reason, the Commission for Education and Training of the German Society of Rheumatology (DGRh) initiated the BEWUSST survey on the working, training and research conditions of residents in rheumatology. METHODS: A total of 102 questions on the topics of working conditions in everyday professional life, continuing medical education and training, compatibility of career and family, compatibility of work and research, perspectives as a rheumatologist and practical activities were included in an online questionnaire. RESULTS: A total of 102 participants took part in the survey. Of the respondents 48.1% were satisfied with their professional situation, 40.2% of the participants were supervised by a specialist mentor and 54.9% were working as scientists during their work as a physician. A compatibility of family and career was possible for 34.7%. After completion of the residency 52.9% of the respondents aspired to a combined clinical and outpatient activity. CONCLUSION: Half of the trainee rheumatologists are satisfied with their professional activities, although mentoring of the assistants in training should be further improved. With respect to the desired combined clinical and outpatient activity, the existing options should be expanded or new professional fields of activity should be established, so that the specialty remains attractive for the upcoming generations.

Modeling time-delayed concentration-QT effects with ACT-1014-6470, a novel oral complement factor 5a receptor 1 (C5a1 receptor) antagonist.

The novel oral complement factor 5a receptor 1 antagonist ACT-1014-6470 was well tolerated in single- and multiple-ascending dose studies, including 24 h Holter electrocardiogram (ECG) recordings evaluating its cardiodynamics based on data from single doses of 30-200 mg and twice-daily (b.i.d.) dosing of 30-120 mg for 4.5 days. By-time point, categorical, and morphological analyses as well as concentration-QT modeling and simulations were performed. No relevant effect of ACT-1014-6470 on ECG parameters was observed in the categorical and morphological analyses. After single-dose administration, the by-time point analysis indicated a delayed dose-dependent increase in placebo-corrected change from baseline in QT interval corrected with Fridericia's formula (ΔΔQTcF) at >6 h postdose. After b.i.d. dosing, ΔΔQTcF remained elevated during the 24-h recording period, suggesting that the effect was not directly related to ACT-1014-6470 plasma concentration. The concentration-QT model described change from baseline in QTcF (ΔQTcF)-time profiles best with a 1-oscillator model of 24 h for circadian rhythm, an effect compartment, and a sigmoidal maximum effect model. Model-predicted ΔΔQTcF was derived for lower doses and less-frequent dosing than assessed clinically. Median and 90% prediction intervals of ΔΔQTcF for once-daily doses of 30 mg and b.i.d. doses of 10 mg did not exceed the regulatory threshold of 10 ms but would achieve ACT-1014-6470 plasma concentrations enabling adequate target engagement. Results from cardiodynamic assessments identified dose levels and dosing regimens that could be considered for future clinical trials, attempting to reduce QT liability.

Grain Size-Dependent Thermal Expansion of Nanocrystalline Metals.

In the present work, we have used classical molecular dynamics and quantum mechanical density functional theory modeling to investigate the grain size-dependent thermal expansion coefficient (CTE) of nanocrystalline Cu. We find that the CTE increases by up to 20% with a gradually decreasing grain size. This behavior emerges as a result of the increased population of occupied anti-bonding states and bond order variation in the grain boundary regions, which contribute to the reduced resistance against thermally-induced bond stretching and dictate the thermal expansion behavior in the small grain size limit. As a part of the present work, we have established a procedure to produce ab initio thermal expansion maps that can be used for the prediction of the grain size-dependent CTE. This can serve as a modeling tool, e.g., to explore the impact of grain boundary impurity segregation on the CTE.

Characteristics and outcomes of SARS-CoV-2 breakthrough infections among double-vaccinated and triple-vaccinated patients with inflammatory rheumatic diseases.

OBJECTIVE: To analyse the clinical profile of SARS-CoV-2 breakthrough infections in at least double-vaccinated patients with inflammatory rheumatic diseases (IRDs). METHODS: Data from the physician-reported German COVID-19-IRD registry collected between February 2021 and July 2022 were analysed. SARS-CoV-2 cases were stratified according to patients' vaccination status as being not vaccinated, double-vaccinated or triple-vaccinated prior to SARS-CoV-2 infection and descriptively compared. Independent associations between demographic and disease features and outcome of breakthrough infections were estimated by multivariable logistic regression. RESULTS: In total, 2314 cases were included in the analysis (unvaccinated n=923, double-vaccinated n=551, triple-vaccinated n=803, quadruple-vaccinated n=37). SARS-CoV-2 infections occurred after a median of 151 (range 14-347) days in patients being double-vaccinated, and after 88 (range 14-270) days in those with a third vaccination. Hospitalisation was required in 15% of unvaccinated, 8% of double-vaccinated and 3% of triple-vaccinated/quadruple-vaccinated patients (p<0.001). Mortality was 2% in unvaccinated, 1.8% in the double-vaccinated and 0.6% in triple-vaccinated patients. Compared with unvaccinated patients, double-vaccinated (OR 0.43, 95% CI 0.29 to 0.62) and triple-vaccinated (OR 0.13, 95% CI 0.08 to 0.21) patients showed a significant lower risk of COVID-19-related hospitalisation. Using multivariable analysis, the third vaccination was significantly associated with a lower risk for COVID-19-related death (OR 0.26; 95% CI 0.01 to 0.73). CONCLUSIONS: Our cross-sectional data of COVID-19 infections in patients with IRD showed a significant reduction of hospitalisation due to infection in double-vaccinated or triple-vaccinated patients compared with those without vaccination and even a significant reduction of COVID-19-related deaths in triple-vaccinated patients. These data strongly support the beneficial effect of COVID-19 vaccination in patients with IRD. TRIAL REGISTRATION NUMBER: EuDRACT 2020-001958-21.