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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.
Background: Biological psychiatry aims to understand mental disorders in terms of altered neurobiological pathways. However, for one of the most prevalent and disabling mental disorders, Major Depressive Disorder (MDD), patients only marginally differ from healthy individuals on the group-level. Whether Precision Psychiatry can solve this discrepancy and provide specific, reliable biomarkers remains unclear as current Machine Learning (ML) studies suffer from shortcomings pertaining to methods and data, which lead to substantial over-as well as underestimation of true model accuracy.
Methods: Addressing these issues, we quantify classification accuracy on a single-subject level in N=1,801 patients with MDD and healthy controls employing an extensive multivariate approach across a comprehensive range of neuroimaging modalities in a well-curated cohort, including structural and functional Magnetic Resonance Imaging, Diffusion Tensor Imaging as well as a polygenic risk score for depression.
Findings Training and testing a total of 2.4 million ML models, we find accuracies for diagnostic classification between 48.1% and 62.0%. Multimodal data integration of all neuroimaging modalities does not improve model performance. Similarly, training ML models on individuals stratified based on age, sex, or remission status does not lead to better classification. Even under simulated conditions of perfect reliability, performance does not substantially improve. Importantly, model error analysis identifies symptom severity as one potential target for MDD subgroup identification.
Interpretation: Although multivariate neuroimaging markers increase predictive power compared to univariate analyses, single-subject classification – even under conditions of extensive, best-practice Machine Learning optimization in a large, harmonized sample of patients diagnosed using state-of-the-art clinical assessments – does not reach clinically relevant performance. Based on this evidence, we sketch a course of action for Precision Psychiatry and future MDD biomarker research.
The ALICE collaboration at the LHC reports measurement of the inclusive production cross section of electrons from semi-leptonic decays of beauty hadrons with rapidity |y|<0.8 and transverse momentum 1<pT<10 GeV/c, in pp collisions at s√= 2.76 TeV. Electrons not originating from semi-electronic decay of beauty hadrons are suppressed using the impact parameter of the corresponding tracks. The production cross section of beauty decay electrons is compared to the result obtained with an alternative method which uses the distribution of the azimuthal angle between heavy-flavour decay electrons and charged hadrons. Perturbative QCD calculations agree with the measured cross section within the experimental and theoretical uncertainties. The integrated visible cross section, σb→e=3.47±0.40(stat)+1.12−1.33(sys)±0.07(norm)μb, was extrapolated to full phase space using Fixed Order plus Next-to-Leading Log (FONLL) predictions to obtain the total bb¯ production cross section, σbb¯=130±15.1(stat)+42.1−49.8(sys)+3.4−3.1(extr)±2.5(norm)±4.4(BR)μb.
The ALICE collaboration at the LHC reports measurement of the inclusive production cross section of electrons from semi-leptonic decays of beauty hadrons with rapidity |y|<0.8 and transverse momentum 1<pT<10 GeV/c, in pp collisions at s√= 2.76 TeV. Electrons not originating from semi-electronic decay of beauty hadrons are suppressed using the impact parameter of the corresponding tracks. The production cross section of beauty decay electrons is compared to the result obtained with an alternative method which uses the distribution of the azimuthal angle between heavy-flavour decay electrons and charged hadrons. Perturbative QCD calculations agree with the measured cross section within the experimental and theoretical uncertainties. The integrated visible cross section, σb→e=3.47±0.40(stat)+1.12−1.33(sys)±0.07(norm)μb, was extrapolated to full phase space using Fixed Order plus Next-to-Leading Log (FONLL) predictions to obtain the total bb¯ production cross section, σbb¯=130±15.1(stat)+42.1−49.8(sys)+3.4−3.1(extr)±2.5(norm)±4.4(BR)μb.
The differential charged jet cross sections, jet fragmentation distributions, and jet shapes are measured in minimum bias proton-proton collisions at centre-of-mass energy s√=7 TeV using the ALICE detector at the LHC. Jets are reconstructed from charged particle momenta in the mid-rapidity region using the sequential recombination kT and anti-kT as well as the SISCone jet finding algorithms with several resolution parameters in the range R=0.2 to 0.6. Differential jet production cross sections measured with the three jet finders are in agreement in the transverse momentum (pT) interval 20<pjet,chT<100 GeV/c. They are also consistent with prior measurements carried out at the LHC by the ATLAS collaboration. The jet charged particle multiplicity rises monotonically with increasing jet pT, in qualitative agreement with prior observations at lower energies. The transverse profiles of leading jets are investigated using radial momentum density distributions as well as distributions of the average radius containing 80% (⟨R80⟩) of the reconstructed jet pT. The fragmentation of leading jets with R=0.4 using scaled pT spectra of the jet constituents is studied. The measurements are compared to model calculations from event generators (PYTHIA, PHOJET, HERWIG). The measured radial density distributions and ⟨R80⟩ distributions are well described by the PYTHIA model (tune Perugia-2011). The fragmentation distributions are better described by HERWIG.
The differential charged jet cross sections, jet fragmentation distributions, and jet shapes are measured in minimum bias proton-proton collisions at centre-of-mass energy s√=7 TeV using the ALICE detector at the LHC. Jets are reconstructed from charged particle momenta in the mid-rapidity region using the sequential recombination kT and anti-kT as well as the SISCone jet finding algorithms with several resolution parameters in the range R=0.2 to 0.6. Differential jet production cross sections measured with the three jet finders are in agreement in the transverse momentum (pT) interval 20<pjet,chT<100 GeV/c. They are also consistent with prior measurements carried out at the LHC by the ATLAS collaboration. The jet charged particle multiplicity rises monotonically with increasing jet pT, in qualitative agreement with prior observations at lower energies. The transverse profiles of leading jets are investigated using radial momentum density distributions as well as distributions of the average radius containing 80% (⟨R80⟩) of the reconstructed jet pT. The fragmentation of leading jets with R=0.4 using scaled pT spectra of the jet constituents is studied. The measurements are compared to model calculations from event generators (PYTHIA, PHOJET, HERWIG). The measured radial density distributions and ⟨R80⟩ distributions are well described by the PYTHIA model (tune Perugia-2011). The fragmentation distributions are better described by HERWIG.
The differential charged jet cross sections, jet fragmentation distributions, and jet shapes are measured in minimum bias proton-proton collisions at centre-of-mass energy s√=7 TeV using the ALICE detector at the LHC. Jets are reconstructed from charged particle momenta in the mid-rapidity region using the sequential recombination kT and anti-kT as well as the SISCone jet finding algorithms with several resolution parameters in the range R=0.2 to 0.6. Differential jet production cross sections measured with the three jet finders are in agreement in the transverse momentum (pT) interval 20<pjet,chT<100 GeV/c. They are also consistent with prior measurements carried out at the LHC by the ATLAS collaboration. The jet charged particle multiplicity rises monotonically with increasing jet pT, in qualitative agreement with prior observations at lower energies. The transverse profiles of leading jets are investigated using radial momentum density distributions as well as distributions of the average radius containing 80% (⟨R80⟩) of the reconstructed jet pT. The fragmentation of leading jets with R=0.4 using scaled pT spectra of the jet constituents is studied. The measurements are compared to model calculations from event generators (PYTHIA, PHOJET, HERWIG). The measured radial density distributions and ⟨R80⟩ distributions are well described by the PYTHIA model (tune Perugia-2011). The fragmentation distributions are better described by HERWIG.
(1) Background: Refractory acute graft-versus-host disease (R-aGvHD) remains a leading cause of death after allogeneic stem cell transplantation. Survival rates of 15% after four years are currently achieved; deaths are only in part due to aGvHD itself, but mostly due to adverse effects of R-aGvHD treatment with immunosuppressive agents as these predispose patients to opportunistic infections and loss of graft-versus-leukemia surveillance resulting in relapse. Mesenchymal stromal cells (MSC) from different tissues and those generated by various protocols have been proposed as a remedy for R-aGvHD but the enthusiasm raised by initial reports has not been ubiquitously reproduced.
(2) Methods: We previously reported on a unique MSC product, which was generated from pooled bone marrow mononuclear cells of multiple third-party donors. The products showed dose-to-dose equipotency and greater immunosuppressive capacity than individually expanded MSCs from the same donors. This product, MSC-FFM, has entered clinical routine in Germany where it is licensed with a national hospital exemption authorization. We previously reported satisfying initial clinical outcomes, which we are now updating. The data were collected in our post-approval pharmacovigilance program, i.e., this is not a clinical study and the data is high-level and non-monitored.
(3) Results: Follow-up for 92 recipients of MSC-FFM was reported, 88 with GvHD ≥°III, one-third only steroid-refractory and two-thirds therapy resistant (refractory to steroids plus ≥2 additional lines of treatment). A median of three doses of MSC-FFM was administered without apparent toxicity. Overall response rates were 82% and 81% at the first and last evaluation, respectively. At six months, the estimated overall survival was 64%, while the cumulative incidence of death from underlying disease was 3%.
(4) Conclusions: MSC-FFM promises to be a safe and efficient treatment for severe R-aGvHD.
Event-by-event fluctuations of the mean transverse momentum of charged particles produced in pp collisions at s√ = 0.9, 2.76 and 7 TeV, and Pb-Pb collisions at sNN−−−−√ = 2.76 TeV are studied as a function of the charged-particle multiplicity using the ALICE detector at the LHC. Dynamical fluctuations indicative of correlated particle emission are observed in all systems. The results in pp collisions show little dependence on collision energy. The Monte Carlo event generators PYTHIA and PHOJET are in qualitative agreement with the data. Peripheral Pb-Pb data exhibit a similar multiplicity dependence as that observed in pp. In central Pb-Pb, the results deviate from this trend, featuring a significant reduction of the fluctuation strength. The results in Pb--Pb are in qualitative agreement with previous measurements in Au-Au at lower collision energies and with expectations from models that incorporate collective phenomena.
The strength of forward-backward (FB) multiplicity correlations is measured by the ALICE detector in proton-proton (pp) collisions at s√=0.9, 2.76 and 7 TeV. The measurement is performed in the central pseudorapidity region (|η|<0.8) for the transverse momentum pT>0.3 GeV/c. Two separate pseudorapidity windows of width (δη) ranging from 0.2 to 0.8 are chosen symmetrically around η=0. The multiplicity correlation strength (bcor) is studied as a function of the pseudorapidity gap (ηgap) between the two windows as well as the width of these windows. The correlation strength is found to decrease with increasing ηgap and shows a non-linear increase with δη. A sizable increase of the correlation strength with the collision energy, which cannot be explained exclusively by the increase of the mean multiplicity inside the windows, is observed. The correlation coefficient is also measured for multiplicities in different configurations of two azimuthal sectors selected within the symmetric FB η-windows. Two different contributions, the short-range (SR) and the long-range (LR), are observed. The energy dependence of bcor is found to be weak for the SR component while it is strong for the LR component. Moreover, the correlation coefficient is studied for particles belonging to various transverse momentum intervals chosen to have the same mean multiplicity. Both SR and LR contributions to bcor are found to increase with pT in this case. Results are compared to PYTHIA and PHOJET event generators and to a string-based phenomenological model. The observed dependencies of bcor add new constraints on phenomenological models.