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Plants, fungi and algae are important components of global biodiversity and are fundamental to all ecosystems. They are the basis for human well-being, providing food, materials and medicines. Specimens of all three groups of organisms are accommodated in herbaria, where they are commonly referred to as botanical specimens.The large number of specimens in herbaria provides an ample, permanent and continuously improving knowledge base on these organisms and an indispensable source for the analysis of the distribution of species in space and time critical for current and future research relating to global biodiversity. In order to make full use of this resource, a research infrastructure has to be built that grants comprehensive and free access to the information in herbaria and botanical collections in general. This can be achieved through digitization of the botanical objects and associated data.The botanical research community can count on a long-standing tradition of collaboration among institutions and individuals. It agreed on data standards and standard services even before the advent of computerization and information networking, an example being the Index Herbariorum as a global registry of herbaria helping towards the unique identification of specimens cited in the literature.In the spirit of this collaborative history, 51 representatives from 30 institutions advocate to start the digitization of botanical collections with the overall wall-to-wall digitization of the flat objects stored in German herbaria. Germany has 70 herbaria holding almost 23 million specimens according to a national survey carried out in 2019. 87% of these specimens are not yet digitized. Experiences from other countries like France, the Netherlands, Finland, the US and Australia show that herbaria can be comprehensively and cost-efficiently digitized in a relatively short time due to established workflows and protocols for the high-throughput digitization of flat objects.Most of the herbaria are part of a university (34), fewer belong to municipal museums (10) or state museums (8), six herbaria belong to institutions also supported by federal funds such as Leibniz institutes, and four belong to non-governmental organizations. A common data infrastructure must therefore integrate different kinds of institutions.Making full use of the data gained by digitization requires the set-up of a digital infrastructure for storage, archiving, content indexing and networking as well as standardized access for the scientific use of digital objects. A standards-based portfolio of technical components has already been developed and successfully tested by the Biodiversity Informatics Community over the last two decades, comprising among others access protocols, collection databases, portals, tools for semantic enrichment and annotation, international networking, storage and archiving in accordance with international standards. This was achieved through the funding by national and international programs and initiatives, which also paved the road for the German contribution to the Global Biodiversity Information Facility (GBIF).Herbaria constitute a large part of the German botanical collections that also comprise living collections in botanical gardens and seed banks, DNA- and tissue samples, specimens preserved in fluids or on microscope slides and more. Once the herbaria are digitized, these resources can be integrated, adding to the value of the overall research infrastructure. The community has agreed on tasks that are shared between the herbaria, as the German GBIF model already successfully demonstrates.We have compiled nine scientific use cases of immediate societal relevance for an integrated infrastructure of botanical collections. They address accelerated biodiversity discovery and research, biomonitoring and conservation planning, biodiversity modelling, the generation of trait information, automated image recognition by artificial intelligence, automated pathogen detection, contextualization by interlinking objects, enabling provenance research, as well as education, outreach and citizen science.We propose to start this initiative now in order to valorize German botanical collections as a vital part of a worldwide biodiversity data pool.
Die auf dem ACDM-Modell beruhenden numerischen Simulationen der gravitativen Strukturbildung sind auf Skalen M >> 10 hoch 10 M sehr erfolgreich, insbesondere konvergieren die Verfahren hinsichtlich des vorhergesagten Masseanteils der Halos an der Gesamtmasse von Galaxien. Jedoch konvergieren die Simulationen nicht bezüglich der lokalen Überdichten von CDM in den Halos, vielmehr setzt sich gravitative Strukturbildung auf immer kleinere Skalen fort. Numerisch kann keine Massen-Schwelle berechnet werden, unterhalb derer keine CDM-Strukturen mehr gravitativ gebildet werden. Die Kenntnis der lokalen Überdichten in den CDM-Wolken und die Verteilung der CDM-Wolken ist jedoch für Experimente zum direkten und indirekten Nachweis von CDM-Teilchen essentiell. Aus den lokalen Überdichten folgen für Experimente zum direkten Nachweis die einfallende Stromdichten der CDM-Teilchen und für Experimente zum indirekten Nachweis die Stromdichte der Annihilationsprodukte. Außerdem können die lokalen Überdichten als Gravitationslinsen wirken. In dieser Arbeit werden Massen Schwellen analytisch berechnet, unterhalb derer akustische Störungen in CDM nicht mehr zur gravitativen Strukturbildung beitragen können. Das Massen-Spektrum von lokalen Überdichten ist nach unten durch zwei unterschiedliche Mechanismen beschränkt: (1) Während der kinetischen Entkopplung formieren sich Nichtgleichgewichtsprozesse, die sich kollektiv als Reihungsphänomene konstituieren. Im lineare Regime sind dies die Volumenviskosität, die Scherungsviskosität und die Wärmeleitung. Die dissipativen Prozesse deponieren Energie und Impuls der akustischen Störungen in die Ebene senkrecht zur Ausbreitungsrichtung der Störungen und schmieren diese so aus. (II) Nach dem kinetischen Entkopplungsprozeß strömt CDM frei auf Geodäten. Dies ermöglicht einen Strom von Teilchen von überdichten in unterdichte Regionen, so daß die Amplituden der lokalen Überdichten weiter gedämpft werden. Die lokalen Transportkoeffizienten in (1) werden durch einen legitimen Vergleich von hydrodynamischer und kinetischer Beschreibung schwach dissipativer Prozesse gewonnen. Dissipative Prozesse induzieren eine Dämpfungsmasse Mc ungefähr gleich 10 hoch minus 9 M in SUSY-CDM und beschränken damit das Spektrum akustischer Störungen in SUSY-CDM. Freies Strömen (II) von CDM-Teilchen auf Geodäten induziert eine weitere Dämpfungsmasse M fs ungefähr gleich 10 hoch minus 6 M in SUSY-CDM, wobei das berechnete M d als Anfangswert dient. Die berechneten Schwellen liefern konsistente Schranken für numerische Simulationen, die weit unterhalb des momentanen numerischen Auflösungsvermögens liegen. Weiterhin folgt aus den Schwellen die Masse der ersten rein gravitativ gebundenen CDM-Wolken. Aus diesen bilden sich im Rahmen der hierarchischen Strukturbildung größere Substrukturen bis hin zu den heute vorhandenen CDM-Halos.
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.
Background: The progression of mild cognitive impairment (MCI) to Alzheimer’s disease (AD) dementia can be predicted by cognitive, neuroimaging, and cerebrospinal fluid (CSF) markers. Since most biomarkers reveal complementary information, a combination of biomarkers may increase the predictive power. We investigated which combination of the Mini-Mental State Examination (MMSE), Clinical Dementia Rating (CDR)-sum-of-boxes, the word list delayed free recall from the Consortium to Establish a Registry of Dementia (CERAD) test battery, hippocampal volume (HCV), amyloid-beta1–42 (Aβ42), amyloid-beta1–40 (Aβ40) levels, the ratio of Aβ42/Aβ40, phosphorylated tau, and total tau (t-Tau) levels in the CSF best predicted a short-term conversion from MCI to AD dementia.
Methods: We used 115 complete datasets from MCI patients of the "Dementia Competence Network", a German multicenter cohort study with annual follow-up up to 3 years. MCI was broadly defined to include amnestic and nonamnestic syndromes. Variables known to predict progression in MCI patients were selected a priori. Nine individual predictors were compared by receiver operating characteristic (ROC) curve analysis. ROC curves of the five best two-, three-, and four-parameter combinations were analyzed for significant superiority by a bootstrapping wrapper around a support vector machine with linear kernel. The incremental value of combinations was tested for statistical significance by comparing the specificities of the different classifiers at a given sensitivity of 85%.
Results: Out of 115 subjects, 28 (24.3%) with MCI progressed to AD dementia within a mean follow-up period of 25.5 months. At baseline, MCI-AD patients were no different from stable MCI in age and gender distribution, but had lower educational attainment. All single biomarkers were significantly different between the two groups at baseline. ROC curves of the individual predictors gave areas under the curve (AUC) between 0.66 and 0.77, and all single predictors were statistically superior to Aβ40. The AUC of the two-parameter combinations ranged from 0.77 to 0.81. The three-parameter combinations ranged from AUC 0.80–0.83, and the four-parameter combination from AUC 0.81–0.82. None of the predictor combinations was significantly superior to the two best single predictors (HCV and t-Tau). When maximizing the AUC differences by fixing sensitivity at 85%, the two- to four-parameter combinations were superior to HCV alone.
Conclusion: A combination of two biomarkers of neurodegeneration (e.g., HCV and t-Tau) is not superior over the single parameters in identifying patients with MCI who are most likely to progress to AD dementia, although there is a gradual increase in the statistical measures across increasing biomarker combinations. This may have implications for clinical diagnosis and for selecting subjects for participation in clinical trials.
Hepatocellular carcinoma (HCC) shows a remarkable heterogeneity and is recognized as a chemoresistant tumor with dismal prognosis. In previous studies, we observed significant alterations in the serum sphingolipids of patients with HCC. This study aimed to investigate the in vitro effects of sorafenib, which is the most widely used systemic HCC medication, on the sphingolipid pathway as well as the effects of inhibiting the sphingolipid pathway in HCC. Huh7.5 and HepG2 cells were stimulated with sorafenib, and inhibitors of the sphingolipid pathway and cell proliferation, viability, and concentrations of bioactive metabolites were assessed. We observed a significant downregulation of cell proliferation and viability and a simultaneous upregulation of dihydroceramides upon sorafenib stimulation. Interestingly, fumonisin B1 (FB1) and the general sphingosine kinase inhibitor SKI II were able to inhibit cell proliferation more prominently in HepG2 and Huh7.5 cells, whereas there were no consistent effects on the formation of dihydroceramides, thus implying an involvement of distinct metabolic pathways. In conclusion, our study demonstrates a significant downregulation of HCC proliferation upon sorafenib, FB1, and SKI II treatment, whereas it seems they exert antiproliferative effects independently from sphingolipids. Certainly, further data would be required to elucidate the potential of FB1 and SKI II as putative novel therapeutic targets in HCC.