University of Rostock

Transactive response DNA binding protein 43 kDa (TDP-43) pathology, is a central molecular hallmark of amyotrophic lateral sclerosis (ALS). However, the underlying triggers are incompletely understood. Here, we show that infection with herpes simplex virus (HSV) induces molecular hallmarks of ALS in various in vitro and in vivo models and is associated with an increased risk of ALS in human population data. German healthcare provider data (n = 238,440) and herpesvirus serology of an ALS patient and control cohort (n = 1,100) showed that HSV infection elevated the ALS risk by 210% and odds by ~65%, respectively. On a molecular level, HSV infection promoted TDP-43 pathology in neuronal cell models, human iPSC-derived motoneurons and cerebral organoids, mice, and human tissue sections. This effect was triggered by HSV-1 or 2, but not by several other related herpesviruses. Mechanistically, the infected cell protein 0 (ICP0) of HSV-1/2 drives TDP-43 pathology by disturbance of promyelocytic leukemia nuclear bodies (PML-NBs), thereby abrogating TDP-43 SUMO2/3ylation. Taken together, we reveal a previously unrecognized association between HSV infection and ALS and clarify the underlying molecular mechanism that drives TDP-43 pathology. Our data may guide future studies into therapeutic and prophylactic interventions against ALS.

Abstract Mycosporine-like amino acids (MAAs) are UV-absorbing, multifunctional metabolites with increasing biotechnological relevance. This study provides the first comprehensive characterization of MAAs profiles in two commercially important Peruvian red macroalgae, Chondracanthus chamissoi and Gracilariopsis lemaneiformis , cultivated in Pisco (Ica, Peru). Seasonal (spring vs. summer) and life-stage (gametophyte vs. tetrasporophyte) differences were analysed using HPLC–DAD for targeted quantification and UHPLC–HRMS/MS coupled with feature-based molecular networking (FBMN) for untargeted metabolite discovery. Both species were confirmed as high MAAs producers (> 2 mg g -1 DW) and shared the same set of 13 MAAs, although their relative abundances varied by species, season, and life stage. Chondracanthus chamissoi accumulated up to 3.39 mg g -1 DW and exhibited a SH-dominant profile (shinorine (SH), palythine (PA) and asterina-330 (AS)), complemented by ten additional low-abundance MAAs detected by FBMN. Gracilariopsis lemaneiformis reached higher total concentrations (up to 3.69 mg g -1 DW) and displayed a broader primary-MAAs repertoire, including porphyra-334 (PR), together with nine secondary metabolites detected at trace levels. Seasonal forcing produced pronounced summer maxima MAAs total concentration in both species, although the magnitude of induction was substantially greater in G. lemaneiformis - consistent with an inducible, habitat-dependent photoprotective strategy - whereas C. chamissoi showed a more constitutive response aligned with persistent intertidal UV exposure. Life-stage effects were also evident, tetrasporophytes of both species generally accumulated higher total MAAs levels and exhibited richer MAAs profiles. FBMN revealed several previously unreported MAAs in both taxa, expanding the known chemical diversity of Peruvian Rhodophyta. Collectively, these findings demonstrate strong environmental and ontogenetic modulation of MAAs biosynthesis and highlight both species - particularly G. lemaneiformis - as promising, sustainable sources of natural UV-protective compounds for cosmetic, pharmaceutical, and biomedical applications.

ABSTRACT Peak group analysis (PGA), an MCR algorithm, has proven to be very successful in extracting pure component spectra and concentration profiles from IR and Raman spectral data when investigating carbonylation reactions with transition metal catalysts. In this field of study, mixture spectra typically exhibit high spectral selectivity, meaning certain peaks belong exclusively to a single chemical species. Under this condition, PGA can extract the associated pure component spectrum from the mixture spectra, and there is no factor ambiguity in these profiles. Here, we present a short mathematical proof of this remarkable PGA property.

This study examines the association between fetal macrosomia (>5,000 g) and pregnancy and birth outcomes. This was a retrospective cohort study using data from the perinatal survey of Lower Saxony, Germany (2001-2009). Pregnancies complicated by advanced maternal age (>35 years), elevated BMI (>25.0), and excessive gestational weight gain were significantly more likely to result in macrosomic births. Additionally, pregnancies involving macrosomic fetuses were characterized by prolonged gestation and an increased likelihood of cesarean delivery. Neonates with macrosomia exhibited significantly lower Apgar scores at 1, 5, and 10 min (<7) compared to the control group (<5,000 g), though umbilical artery pH values did not differ significantly between groups. These findings highlight the need for targeted prenatal monitoring and risk assessment in pregnancies predisposed to fetal macrosomia.

This study investigates the combined effects of salinity and microplastic contamination on the evaporation process and salt crystallization in porous media through complementary column- and pore-scale experiments. Laboratory soil columns were packed with either pure sand or sand mixed with 5% (w/w) poly(vinyl chloride) (PVC) microplastics and subsequently saturated with freshwater or saline (NaCl) solution. Evaporation and crystallization dynamics were monitored by using mass loss measurements, surface optical and thermal imaging, and synchrotron X-ray tomography. Results show that salinity consistently suppressed evaporation by roughly 25–30%, whereas PVC microplastics enhanced it, generating substantial differences in cumulative water loss across treatments. Moreover, thermal imaging revealed distinct surface responses: NaCl samples developed salt crusts that progressively reduced local temperature contrasts and led to more spatially uniform surface conditions, whereas PVC-NaCl samples exhibited lower mean surface temperatures but substantially higher spatial variability, reflected in larger and more persistent temperature anomalies during drying. Pore-scale μCT imaging further confirmed that microplastics altered crystallization patterns by redistributing salt deposition over the upper part of the sand profile and modifying the nucleation behavior. Together, these findings underscore the complex interplay between microplastics and salinity, with implications for soil moisture regulation, surface energy flux, and environmental monitoring strategies.

The southern Baltic Sea coastline is a dynamic system, often bordered by coastal peatlands. Artificial dunes and dykes commonly separate these peatlands from the sea. Given their potential as carbon sinks and natural buffer zones against sea-level rise and flooding, interest in their restoration is increasing. Microphytobenthos, particularly diatoms, are key primary producers in coastal and peatland environments and serve as valuable bioindicators. While their use as bioindicators has focused on freshwater systems, their application in coastal contexts also holds promise. In contrast to their freshwater counterparts, the ecology, taxonomy and diversity of benthic diatoms along the southern Baltic Sea coast, particularly in coastal peatlands, remain poorly understood. Despite being separated from the Baltic Sea by a dune dyke, the coastal peatland in the nature reserve “Heiligensee und Hütelmoor” is periodically exposed to saltwater inflow during storm surges. Following a storm surge in January 2019, brackish water entered the peatland, providing a rare opportunity to study a coastal peatland with periodic salt water input. Over one year, diatom community compositions, biomass, and key environmental variables were monitored at two peatland sites and an adjacent marine site to assess spatial and temporal patterns along a marine–terrestrial gradient. Overall, 198 diatom taxa were found and the share between the Baltic Sea and the peatland was only 4% despite the recent saltwater intrusion. Diatom community compositions showed distinct seasonal and spatial variation within the peatland area. The main drivers of community differences in the dataset were salinity, temperature, pH and nitrogen-based nutrients.

One of the main factors characterizing the dynamics in the atmosphere is its vertical density stratification. Gravity waves propagation upwards and breaking in the middle atmosphere play an essential role in large-scale energy transport, planetary-scale circulation and the generation of stratified turbulence, manifesting in phenomena such as the cold summer mesopause in the mesosphere. Direct observation or numerical simulation of these processes with high resolution proves difficult however due to the remoteness of the region combined with horizontal scales of 10-100km and vertical scales of 10-100m that have to be resolved for a detailed analysis of the underlying stratified turbulence.To tackle these limitations and further our knowledge on turbulence activity in the middle atmosphere, we combine the physics-informed machine learning method HYPER (Hydrodynamic Point‐wise Environment Reconstructor) with state-of-the-art radar observations from MAARSY (Middle Atmosphere Alomar Radar System) and SIMONe (Spread-spectrum Interferometric Multistatic Meteor Radar Observing Network). The method allows reconstruction of complete 4D wind fields (spatial+temporal) based on line-of-sight measurements while adhering to Navier-Stokes-based physics constraints and has been successfully deployed previously to extract winds on 10km-scales from inputs of SIMONe. In our work we extend the procedure to combine the input of MAARSY and SIMONe and predict complete 4D wind fields at unprecedented horizontal and vertical resolution. Using DNS of stratified turbulence with virtual radars as a validation case, we show that our improved method is able to produce accurate results in the entire prediction domain beyond the provided measurement points, while respecting the given physics constraints. Building on this, we aim to provide a first machine learning supported analysis of stratified turbulence in the mesopause region based on radar observations.

Summary The role of the peripheral immune system in Alzheimer’s Disease (AD) remains insufficiently resolved, limiting the understanding of systemic disease effects and mechanisms. Here, we employed three high-resolution single-cell techniques, including flow cytometry, single-cell RNA- and ATAC-sequencing, to investigate peripheral immunity in AD dementia and earlier stages of the AD trajectory in over 100 patients. We identified reduced humoral immune responses in AD, characterized by a diminished B cell compartment displaying an impaired activation phenotype. Classical monocytes expanded in mild cognitive impairment and early AD dementia, acquiring a NF- k B/AP-1-mediated low-grade inflammation phenotype. Our findings link peripheral dysregulation in innate and adaptive immunity at cell frequency, transcriptional and epigenetic levels to the AD trajectory and provide insights into distinct phenotypes that define AD progression in contrast to healthy aging across cohorts.

Peatland condition is a key indicator of ecosystem integrity and carbon storage potential, making reliable monitoring of degradation processes essential at regional to national scales. Mire breathing—the cyclic surface motion driven by hydrological dynamics—serves as an important proxy for peatland degradation. Drained or degraded peatlands typically exhibit weak oscillatory behaviour combined with persistent subsidence trends, whereas near-natural peatlands show pronounced seasonal surface dynamics. Quantifying peatland subsidence therefore provides a structural indicator for assessing peatland condition and its implications for carbon storage dynamics and greenhouse gas emissions.In this study, interferometric time-series analysis based on Sentinel-1 Synthetic Aperture Radar (SAR) data was applied to monitor large-scale peatland subsidence using a Small Baseline Subset (SBAS) approach implemented in MintPy. Additionally, hourly Radolan precipitation data were integrated to relate subsidence dynamics to hydrological forcing, and first in-situ measurements from extensometers were used to capture actual ground motion. The analysis covers peatlands across the federal state of Mecklenburg-Vorpommern (north-eastern Germany) for the period 2017–2024 and demonstrates a scalable monitoring framework applicable to national peatland inventories.The results reveal pronounced spatiotemporal subsidence patterns across the study region. At three representative sites, mean subsidence rates range from −4.3 to −9.6 cm yr⁻¹ in line of sight (LOS). In addition, distinct site-specific mire breathing signals were identified, with seasonal amplitudes between 5 and 15 cm (LOS). The time series show enhanced subsidence during summer months and partial surface recovery during wetter periods, highlighting the strong control of hydrological conditions on peatland surface dynamics.Overall, the findings demonstrate the capability of SBAS-based InSAR time-series analysis to capture both long-term subsidence trends and short-term oscillatory responses in peatlands. Comparison with in-situ extensometer measurements confirms the validity of the remote-sensing-derived deformation signals. This supports large-scale peatland mapping and monitoring efforts and provides a remote-sensing-based component relevant for greenhouse gas accounting and monitoring, reporting and verification (MRV) frameworks. Future work will focus on improving methodological robustness and validating the InSAR-derived deformation signals using in-situ subsidence measurements.This research was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Project-ID 531801029 (TRR 410).