TU Dresden

The clubroot pathogen Plasmodiophora brassicae has an effector protein that can methylate the plant defense compound salicylic acid (SA), and the protein sequence is highly conserved in different isolates worldwide. Sequencing the full-length cDNA of P. brassicae Benzoic acid/Salicylic acid Methyltransferase (PbBSMT) from a small collection of clubs indicated the occurrence of a natural variation that differs by 18 amino acids, which was also found within the worldwide data collection for P. brassicae isolates. A search for more possible substrates including defense-inducing compounds revealed that PbBSMT was also able to convert a recently reported inductor of systemic defense, N-hydroxy pipecolic acid (NHP), to its methyl ester. PbBSMT showed much lower Km values for the substrates SA and NHP compared with the other two natural compounds previously identified to be methylated with high activities (benzoic and anthranilic acids), suggesting they are the most favored substrates in vitro. The two variants showed no difference in terms of being able to accept the four naturally occurring substrates. Mature clubs incubated for 21 d after inoculation with NHP or SA showed in vivo conversion to their respective methyl esters. The methyl ester of NHP was specifically detected in transgenic plants overexpressing PbBSMT under inductive conditions. Transgenic Arabidopsis with elevated NHP levels had reduced club weights, but no reduction in infection rate or disease severity was seen in these plants, or in mutants with decreased NHP levels. Treatment of infected plants with NHP did not reduce disease severity, and therefore a major function for NHP in defense against the clubroot pathogen is not apparent.

For psychoneuroendocrinology, accurate measurement of progesterone (P4) and estradiol (E2) in saliva is crucial for understanding the menstrual cycle phase and its impact on physiology and behavior. Although enzyme-linked immunosorbent assay (ELISA) and radioimmunoassay (RIA) are the preferred methods and are more often found in research labs, liquid chromatography-mass spectrometry (LC-MS/MS) may provide a more valid salivary steroids assessment. In this study, we aimed to compare the performance of LC-MS/MS, ELISA, and RIA to measure salivary P4 and E2. Samples were collected from 120 participants, 81 men and 39 women, in the morning and evening. Additionally, women provided samples during the early follicular (cycle days 3-5) and luteal cycle phases (cycle days 21-23) using the forward-count method. The study considered natural hormone fluctuations (e.g., the diurnal and menstrual cycles) and quality control samples as validity criteria for method evaluation. A total of 336 samples and quality control samples were analyzed using one RIA, two ELISA, and two LC-MS/MS methods across four labs. Correlational analyses were performed to assess inter-lab x inter-method reliability, intra-lab x inter-method reliability, and inter-lab x intra-method reliability. For P4, natural hormone fluctuations in menstrual cycles were detected by all methods. However, in contrast to both LC-MS/MS methods, all immunoassays (IAs) detected an unexpected diurnal decline of P4. For E2, they were found only by LC-MS/MS and RIA. In terms of means, for P4 and E2, ELISA and RIA produced higher values compared to LC-MS/MS. For P4, the inter- and intra-method convergence was r ≥ .92. As for E2, inter-method correlations were between r = -.12 and r = .23, while the ELISA intra-method comparison showed a correlation coefficient of r = .85. Our findings suggest that while LC-MS/MS, RIA, and ELISA were capable of meeting most of the specified criteria for P4, only LC-MS/MS and RIA were able to perform similarly sufficiently at low E2 levels. LC-MS/MS provided more accurate and reliable measurements for P4 and E2, especially at low concentrations, but encountered challenges, too. Although RIA showed comparable performance to LC-MS/MS, it still suffered partly from cross-reactivity. ELISA often overestimated hormone levels and exhibited greater divergence. These differences highlight the importance of carefully selecting methods and considering their limitations in research applications.

The environmental behavior and phytotoxicity of functionalized ionic liquids (FILs) featuring imidazolium cations bearing a cyclic (-)-menthol or a linear 1-decanol-derived substituent and fluorinated anions were evaluated in a soil bioassay (Raphanus sativus). Structure-activity relationships were determined by integrating measurements (water solubility, surface tension, molecular volume) with in-silico descriptors (n-octanol-water partition coefficient, log KOW; bioconcentration factor, log BCF; asymmetry). Lipophilicity and bioaccumulation correlated with fresh-mass inhibition (EC50). More-fluorinated, larger, and charge-delocalized anions were more hydrophobic, elevating bioaccumulation and toxicity. Within menthol-based series, sulfonylimide-based FILs were more phytotoxic (EC50 74.7, 107.3 mg·kg-1 soil dry weight) than sulfonate analogues (e.g., 299.1 mg·kg-1). FILs with linear cations were more phytotoxic and showed higher log KOW/BCF than cyclic analogues, consistent with greater molecular volume, higher asymmetry, and reduced hydration. Antioxidant responses paralleled EC50, implicating oxidative stress. This workflow improves risk assessment and provides green-by-design criteria to prioritise safer ILs.

As climate challenges intensify, ecological objectives are gaining importance alongside traditional objectives in distributed scheduling, giving rise to distributed green scheduling problems. However, current models and objectives fail to capture key characteristics of geographically distributed manufacturing systems, particularly the emission intensity of electricity generation and the distribution of goods. Since the environmental impact of electricity consumption varies with local emission factors, they are critical in distributed permutation flowshop scheduling problems. Further, the validity of ecological optimization can be compromised, as energy savings may be offset by increased transportation-related emissions. Based on an experimental analysis calibrated to real-world European production networks and including makespan as an economic objective, we find that optimizing total energy consumption results in an average hypervolume RPD of 42.12%, questioning its validity as an indicator of environmental performance in distributed scheduling. Moreover, focusing solely on production-related emissions still results in an average deviation of 26.13%, highlighting the bias caused by neglecting the distribution stage — an effect that becomes more pronounced with increasing product weight. To further enhance real-world applicability, we assess the impact of eligibility constraints — arising from limited redundancy in tools and raw materials — on the potential to minimize both makespan and carbon emissions, and propose distance- and emission-aware strategies for factory qualification. Finally, the problem is solved using a novel parameter-less iterated greedy algorithm that incorporates problem-specific knowledge into speed factor adjustment, removes the need for parameter tuning, and demonstrates strong solution quality in extensive computational experiments. • Minimization of makespan and carbon emissions in distributed flowshop scheduling. • Environmental impact is quantified based on the choice of optimization objective. • A novel context-aware, parameter-less iterated greedy algorithm is introduced. • Impact of factory eligibility constraints is assessed in distributed scheduling. • Carbon emission objective shown to be essential for ecological impact reduction.

Adaptive behavior is central to coping with dynamic environmental changes. Although functional neuroanatomical and neurophysiological considerations suggest that information must be exchanged during adaptive behavior and similar predictions can be derived from cognitive science concepts, attempts to delineate the directed information transfer in theta and alpha networks during behavioral adaptation are rare. Using task switching as an experimental vehicle, we examined directed communication in theta and alpha band networks in n = 51 healthy individuals. We combined EEG-beamforming with an artificial neural network-based estimation of linear and nonlinear directed information transfer between cortical regions. We show increased theta and alpha band activities during switch trials, which aligns with the cognitive control demands of task switching. EEG-beamforming indicated oscillatory modulations in distinct brain-wide networks depending on frequency and time window, with theta and alpha activities strongly tied to task-set reconfiguration and inhibitory control. Directed connectivity analysis revealed overlapping alpha and theta clusters, highlighting their interplay in cognitive flexibility. Directed communication in a cortical alpha band network involving fronto-temporal, temporoparietal, occipital, and precentral activity clusters was critical when preparing for task switching. We observed a bidirectional information transfer across four neuroanatomical clusters with more substantial connectivity modulations correlating with better task performance. These findings emphasize the importance of directed information transfer in a cortical alpha band activity network in supporting adaptive behavior.

Abstract A dynamic actin cytoskeleton, characterized by rapid filament turnover, is essential for driving intracellular transport and cellular movement. Despite extensive study, the contributions of many actin-binding proteins (ABPs) that regulate the different steps of the actin turnover cycle (filament assembly, disassembly and recycling into polymerizable actin monomers) remain ill-defined. Here, we introduce novel sensitive in vitro assays to quantitatively assess how ABPs catalyze actin turnover. By accurately measuring nucleotide exchange dynamics and ATP consumption, these assays enable robust characterization of ABP activity across broad concentration ranges. Using these methods and modeling of these reactions, we systematically examined the contributions of five conserved regulators, both individually and in combination, and identified conditions that maximize turnover efficiency. We also determined that increasing F-actin concentration to cellular levels affects ABP activity. Finally, we demonstrated that rapid actin turnover is preserved during encapsulation in cell-sized vesicles using the cDICE method. Together, these advances provide versatile tools and new insights into actin cytoskeletal dynamics under physiologically relevant conditions.

Rheumatoid arthritis (RA) pathogenesis involves early gut immune alterations that precede clinical onset and systemic bone involvement. Using mouse and human imaging mass cytometry (IMC) and tissue sequencing, this study shows that intestinal endothelial and immune changes emerge before or coincide with arthritis symptom development. In the collagen-induced arthritis (CIA) model, intestinal vascular permeability and endothelial gene activation promoting leukocyte trafficking appeared prior to synovial inflammation. Spatial mapping of murine and human ileal tissues predicted enhanced epithelial–immune interactions and lymphoid activation, suggesting mucosal immune priming before joint pathology. Both gut–selective α4β7 integrin blockade with vedolizumab and endothelial barrier enhancement by imatinib significantly reduced arthritis severity in CIA mice. After clinical onset, microbiota–specific IgG responses expanded to recognize rare gut bacteria, reflecting increased microbial exposure. Bone marrow endothelium exhibited interferon I–driven inflammation and vascular activation, indicating tissue–specific endothelial dysfunction. Microbiota–reactive IgG increased during CIA – likely a response to translocating gut bacteria and immune cell activation. Integrating mouse and human data, these findings define a mechanistic framework where endothelial barrier impairment, microbial translocation, and systemic endothelial activation initiate RA autoimmunity, revealing endothelial and mucosal pathways as targets for early intervention.

IntroductionInternet-based interventions are effective in the prevention of eating disorders (EDs) but are rarely translated from controlled study settings into practice. This study aimed to assess short- and long-term outcomes and adherence of a suite of internet-based screening and ED prevention programs.MethodsIn a 5-arm non-randomized dissemination trial, internet-based ED prevention interventions were offered to women recruited from the general population (N = 3,654). Each arm offered a different version of the ED prevention program, tailored for populations at different levels of risk. The interventions comprised 4 to 12 weekly modules based on cognitive-behavioral principles, including psychoeducation, exercises to promote body image and balanced eating, and—if applicable—to reduce ED symptoms. Primary outcome was the change in weight concerns from pre to post, using t-tests and completer data. Secondary outcomes included ED symptoms, eating habits, self-esteem and quality of life.ResultsPre-post within-subject comparisons in the completer sample showed significant reductions in weight concerns in 4 of 5 study arms (effect sizes between d = -0.45 and d = -0.94). ED symptoms were reduced and the ability to eat intuitively was improved in all study arms, with some effects persisting up to 12 months. Assessment drop-out ranged from 60.6% to 78.1% at post, and between 18.0% and 44.0% of participants completed the whole intervention.DiscussionThe trial demonstrates the feasibility of reaching different risk groups for prevention with a combined screening and tailored interventions as well as feasibility of larger scale dissemination of the interventions in the general population.Clinical trial registrationhttp://www.isrctn.org, identifier ISRCTN13716228.