Small molecules with anti-trypanosomal and anti-leishmanial activity

Parasitic diseases such as Human African Trypanosomiasis (HAT), Chagas disease and Leishmaniasis cause thousands of fatalities each year. Current chemotherapy is based on drugs discovered over 60 years ago that are expensive and difficult to administer. The drug-pipeline is virtually dry and the trickle of inhibitors that are in development are largely based on those that are already in use. Parasite resistance to these drugs is developing, underlining the urgent need for novel anti-parasitic drug therapies. This study focused on the identification of novel small molecular inhibitors with anti-parasitic activities against Trypanosoma brucei spp. (HAT), Trypanosoma cruzi spp. (Chagas disease) and Leishmania infantum spp. (Leishmaniasis) with a particular focus on combining broadspectrum activity with parasite-specificity. A two-pronged approach was used to develop an effective chemotherapy through the optimisation of known inhibitors of glycophosphatidylinositol (GPI)-anchor biosynthesis and improving the specificity of iron chelators. GPI anchor biosynthesis is a pathway essential for survival to all three parasites. Here, a rhodanine-N-acetic acid derivative served as the starting point for the development of a library of 379 thiazolidine-4-one and pyrazolone analogues. These were systematically screened against three species of parasitic protozoa and a mammalian cell line in order to identify inhibitors which demonstrate low-�M anti-parasitic activity and a good selectivity profile. Further target identification studies on the effect of these new inhibitors using in vitro assays confirmed inhibition of GPI anchor biosynthesis as a mode of action. This provides further evidence that the GPI anchor is a druggable target for the development of novel anti-parasitic agents against T. brucei, T. cruzi and L. infantum. Taken together, this work indicates that drugs targeting one feature common to all three protozoa can provide anti-parasitic activity with low toxicity against mammalian cells

Top management team characteristics and digital innovation:Exploring digital knowledge and TMT interfaces

On their journey toward digital transformation, industrial firms need to embrace digital innovation. The top management team (TMT) is expected to set the course for digital innovation, which is a challenging endeavour given the novel and cross-functional nature of digital innovation. We draw on role theory to make sense of emerging role requirements for the TMT and combine this view with upper echelon theory to hypothesize on the specific TMT characteristics that are needed for digital innovation. We first theorize that firms could benefit from TMT digital knowledge. Second, we argue that the effective utilization of TMT digital knowledge can be fostered at internal TMT interfaces, such as between the chief executive officer (CEO), respectively a chief digital officer (CDO), and other top managers. Finally, we consider the TMT hierarchical structure as a contextual factor in the stimulation of TMT integration processes by integrative CEOs and CDOs. We employ panel data regressions to a longitudinal dataset of US industrial firms and find a positive relation between TMT digital knowledge and digital innovation, on average. We additionally find evidence for the integrative roles of CEOs and CDOs. However, our findings also indicate that the CDO's integrating role can be hampered by a strong hierarchical structure in the TMT

An inducible CRISPR‐Kill system for temporally controlled cell type‐specific cell ablation in Arabidopsis thaliana

The application of the CRISPR/Cas system as a biotechnological tool for genome editing has revolutionized plant biology. Recently, the repertoire was expanded by CRISPR-Kill, enabling CRISPR/Cas-mediated tissue engineering through genome elimination by tissue-specific expression. Using the Cas9 nuclease from Staphylococcus aureus (SaCas9), CRISPR-Kill relies on the induction of multiple double-strand breaks (DSBs) in conserved repetitive genome regions, such as the rDNA, causing cell death of the targeted cells. Here, we show that in addition to spatial control by tissue-specific expression, temporal control of CRISPR-mediated cell death is feasible in Arabidopsis thaliana. We established a chemically inducible tissue-specific CRISPR-Kill system that allows the simultaneous detection of targeted cells by fluorescence markers. As proof of concept, we were able to eliminate lateral roots and ablate root stem cells. Moreover, using a multi-tissue promoter, we induced targeted cell death at defined time points in different organs at select developmental stages. Thus, using this system makes it possible to gain new insights into the developmental plasticity of certain cell types. In addition to enabling tissue engineering in plants, our system provides an invaluable tool to study the response of developing plant tissue to cell elimination through positional signaling and cell-to-cell communication

Generation of macro- and microplastic databases by high-throughput FTIR analysis with microplate readers

FTIR spectral identification is today’s gold standard analytical procedure for plastic pollution material characterization. High-throughput FTIR techniques have been advanced for small microplastics (10–500 µm) but less so for large microplastics (500–5 mm) and macroplastics (> 5 mm). These larger plastics are typically analyzed using ATR, which is highly manual and can sometimes destroy particles of interest. Furthermore, spectral libraries are often inadequate due to the limited variety of reference materials and spectral collection modes, resulting from expensive spectral data collection. We advance a new high-throughput technique to remedy these problems using FTIR microplate readers for measuring large particles (> 500 µm). We created a new reference database of over 6000 spectra for transmission, ATR, and reflection spectral collection modes with over 600 plastic, organic, and mineral reference materials relevant to plastic pollution research. We also streamline future analysis in microplate readers by creating a new particle holder for transmission measurements using off-the-shelf parts and fabricating a nonplastic 96-well microplate for storing particles. We determined that particles should be presented to microplate readers as thin as possible due to thick particles causing poor-quality spectra and identifications. We validated the new database using Open Specy and demonstrated that additional transmission and reflection spectra reference data were needed in spectral libraries

Covalent inhibitors of LgtC: a blueprint for the discovery of non-substrate-like inhibitors for bacterial glycosyltransferases

Non-substrate-like inhibitors of glycosyltransferases are sought after as chemical tools and potential lead compounds for medicinal chemistry, chemical biology and drug discovery. Here, we describe the discovery of a novel small molecular inhibitor chemotype for LgtC, a retaining α-1,4-galactosyltransferase involved in bacterial lipooligosaccharide biosynthesis. The new inhibitors, which are structurally unrelated to both the donor and acceptor of LgtC, have low micromolar inhibitory activity, comparable to the best substrate-based inhibitors. We provide experimental evidence that these inhibitors react covalently with LgtC. Results from detailed enzymological experiments with wild-type and mutant LgtC suggest the non-catalytic active site residue Cys246 as a likely target residue for these inhibitors. Analysis of available sequence and structural data reveals that non-catalytic cysteines are a common motif in the active site of many bacterial glycosyltransferases. Our results can therefore serve as a blueprint for the rational design of non-substrate-like, covalent inhibitors against a broad range of other bacterial glycosyltransferases

EDGAR: An Autonomous Driving Research Platform -- From Feature Development to Real-World Application

While current research and development of autonomous driving primarily focuses on developing new features and algorithms, the transfer from isolated software components into an entire software stack has been covered sparsely. Besides that, due to the complexity of autonomous software stacks and public road traffic, the optimal validation of entire stacks is an open research problem. Our paper targets these two aspects. We present our autonomous research vehicle EDGAR and its digital twin, a detailed virtual duplication of the vehicle. While the vehicle's setup is closely related to the state of the art, its virtual duplication is a valuable contribution as it is crucial for a consistent validation process from simulation to real-world tests. In addition, different development teams can work with the same model, making integration and testing of the software stacks much easier, significantly accelerating the development process. The real and virtual vehicles are embedded in a comprehensive development environment, which is also introduced. All parameters of the digital twin are provided open-source at https://github.com/TUMFTM/edgar_digital_twin

NT-proBNP or Self-Reported Functional Capacity in Estimating Risk of Cardiovascular Events After Noncardiac Surgery

ImportanceNearly 16 million surgical procedures are conducted in North America yearly, and postoperative cardiovascular events are frequent. Guidelines suggest functional capacity or B-type natriuretic peptides (BNP) to guide perioperative management. Data comparing the performance of these approaches are scarce.ObjectiveTo compare the addition of either N-terminal pro-BNP (NT-proBNP) or self-reported functional capacity to clinical scores to estimate the risk of major adverse cardiac events (MACE).Design, Setting, and ParticipantsThis cohort study included patients undergoing inpatient, elective, noncardiac surgery at 25 tertiary care hospitals in Europe between June 2017 and April 2020. Analysis was conducted in January 2023. Eligible patients were either aged 45 years or older with a Revised Cardiac Risk Index (RCRI) of 2 or higher or a National Surgical Quality Improvement Program, Risk Calculator for Myocardial Infarction and Cardiac (NSQIP MICA) above 1%, or they were aged 65 years or older and underwent intermediate or high-risk procedures.ExposuresPreoperative NT-proBNP and the following self-reported measures of functional capacity were the exposures: (1) questionnaire-estimated metabolic equivalents (METs), (2) ability to climb 1 floor, and (3) level of regular physical activity.Main Outcome and MeasuresMACE was defined as a composite end point of in-hospital cardiovascular mortality, cardiac arrest, myocardial infarction, stroke, and congestive heart failure requiring transfer to a higher unit of care.ResultsA total of 3731 eligible patients undergoing noncardiac surgery were analyzed; 3597 patients had complete data (1258 women [35.0%]; 1463 (40.7%) aged 75 years or older; 86 [2.4%] experienced a MACE). Discrimination of NT-proBNP or functional capacity measures added to clinical scores did not significantly differ (Area under the receiver operating curve: RCRI, age, and 4MET, 0.704; 95% CI, 0.646-0.763; RCRI, age, and 4MET plus floor climbing, 0.702; 95% CI, 0.645-0.760; RCRI, age, and 4MET plus physical activity, 0.724; 95% CI, 0.672-0.775; RCRI, age, and 4MET plus NT-proBNP, 0.736; 95% CI, 0.682-0.790). Benefit analysis favored NT-proBNP at a threshold of 5% or below, ie, if true positives were valued 20 times or more compared with false positives. The findings were similar for NSQIP MICA as baseline clinical scores.Conclusions and relevanceIn this cohort study of nearly 3600 patients with elevated cardiovascular risk undergoing noncardiac surgery, there was no conclusive evidence of a difference between a NT-proBNP–based and a self-reported functional capacity–based estimate of MACE risk.Trial RegistrationClinicalTrials.gov Identifier: NCT0301693

The Ontology of Biological Attributes (OBA)-computational traits for the life sciences.

Existing phenotype ontologies were originally developed to represent phenotypes that manifest as a character state in relation to a wild-type or other reference. However, these do not include the phenotypic trait or attribute categories required for the annotation of genome-wide association studies (GWAS), Quantitative Trait Loci (QTL) mappings or any population-focussed measurable trait data. The integration of trait and biological attribute information with an ever increasing body of chemical, environmental and biological data greatly facilitates computational analyses and it is also highly relevant to biomedical and clinical applications. The Ontology of Biological Attributes (OBA) is a formalised, species-independent collection of interoperable phenotypic trait categories that is intended to fulfil a data integration role. OBA is a standardised representational framework for observable attributes that are characteristics of biological entities, organisms, or parts of organisms. OBA has a modular design which provides several benefits for users and data integrators, including an automated and meaningful classification of trait terms computed on the basis of logical inferences drawn from domain-specific ontologies for cells, anatomical and other relevant entities. The logical axioms in OBA also provide a previously missing bridge that can computationally link Mendelian phenotypes with GWAS and quantitative traits. The term components in OBA provide semantic links and enable knowledge and data integration across specialised research community boundaries, thereby breaking silos

Overview of the PALM model system 6.0

In this paper, we describe the PALM model system 6.0. PALM (formerly an abbreviation for Parallelized Large-eddy Simulation Model and now an independent name) is a Fortran-based code and has been applied for studying a variety of atmospheric and oceanic boundary layers for about 20 years. The model is optimized for use on massively parallel computer architectures. This is a follow-up paper to the PALM 4.0 model description in Maronga et al. (2015). During the last years, PALM has been significantly improved and now offers a variety of new components. In particular, much effort was made to enhance the model with components needed for applications in urban environments, like fully interactive land surface and radiation schemes, chemistry, and an indoor model. This paper serves as an overview paper of the PALM 6.0 model system and we describe its current model core. The individual components for urban applications, case studies, validation runs, and issues with suitable input data are presented and discussed in a series of companion papers in this special issue.Peer reviewe