Helmholtz Zentrum München

Biomedical thermography, when used to monitor changes in metabolic heat released from human legs, allows the disclosure of metabolic deficiencies associated with asymmetric alterations in the presence of long-term type 2 diabetes mellitus. In this case series a clinical evaluation was performed in 10 patients clinically diagnosed with a time evolution of type 2 diabetes mellitus for more than 5 years: 5 males (62 ± 10 years) and 5 females (56 ± 10 years). The clinical examination relied on infrared thermography as the only auxiliary imaging technique to diagnose diabetic peripheral neuropathy and peripheral arterial disease. The clinical evaluation indicates 100% agreement with the image analysis according to the quantitative thermal indices: asymmetry and thermal response index (ATR) and the thermal response index (TRI). These findings indicate that the proposed image analysis is a useful and adaptable tool for detecting subtle clinical signs and supporting timely diagnostic and therapeutic decisions.

Abstract Heart weight (HW) is a critical parameter in cardiology and mouse research, commonly normalized to body weight (BW) or tibia length (TL) to account for size differences. Ratio-based normalization, however, assumes strict proportionality between variables, an assumption that is rarely tested and may bias group comparisons. We analysed HW, BW, and TL measurements from over 25,000 C57BL/6N wildtype mice generated by the International Mouse Phenotyping Consortium. Sex- and age-stratified analyses were combined with simulation-based modelling to evaluate empirical scaling relationships and the statistical behaviour of ratio-based normalization. Across all age and sex groups, correlations between HW, BW, and TL were negligible to weak, indicating substantial deviations from proportionality. Simulations demonstrated that ratio-based normalization can generate misleading results, including spurious or reversed group differences, when proportionality assumptions are violated. Ratios were consistent with linear and allometric models only under strictly proportional conditions, characterized by regression lines passing through the origin. Linear models with covariate adjustment and allometric scaling provide more robust and biologically meaningful frameworks for organ weight analysis. Ratio-based normalization should be avoided unless key mathematical assumptions are met.

Petrichor – a strong scent released from desiccated soil upon rewetting – is a mixture of volatile organic compounds (VOCs) that impact atmospheric chemistry and originates from the abiotic desorption of stored compounds and the de novo microbial production. The aridity gradient of the Negev Desert soils provides a particularly suitable system for studying petrichor emissions due to their distinctive and well-studied microbial communities (e.g., Actinobacteria and Cyanobacteria) but similar physical properties that control VOC physical evaporation, and absence of plant material as confounding sources of VOCs. While the chemical and microbial origins of petrichor are relatively well described, the controlling factors of its emission remain unclear. This study investigated the influences of desiccation dynamics on petrichor emissions and microbial succession in soils from an aridity gradient of the Negev Desert in Israel. Soil cores were subjected to three sequential rain events followed by contrasting desiccation regimes (long drought, rapid desiccation and slow desiccation) in a realistic climate simulation. Their VOC emissions and microbial metatranscriptomics were studied at five time points, including three upon rewetting and two during slow desiccation. The results showed that VOCs were produced during soil drying, with compound-specific release patterns occurring either during desiccation or upon rehydration. Despite having a common biosynthetic pathway, monoterpenoid and sesquiterpenoid emissions exhibited distinct temporal dynamics, suggesting different underlying physical control or microbial activity. The abundances and chemical diversity of petrichor decreased with increasing aridity, closely following the decline in microbial diversity. The microbial communities varied among rewetting scenarios and exhibited clear temporal succession during slow desiccation, likely regulating petrichor emissions through microbial activation. Greater community dispersion at 24 hours after rewetting indicated rapid and heterogeneous microbial reactivation, potentially contributing to increased variability and reduced predictability of early petrichor emissions. These findings highlighted the importance of desiccation rate in controlling petrichor emissions in desert ecosystems. Further field measurements and functional microbial analyses will be essential to understand how changing desiccation regimes will reshape petrichor emissions and the microbial communities in desert ecosystems.

Membrane protection against oxidative insults is achieved by the concerted action of glutathione peroxidase 4 (GPX4) and endogenous lipophilic antioxidants such as ubiquinone and vitamin E. More recently, ferroptosis suppressor protein 1 (FSP1) was identified as a critical ferroptosis inhibitor, acting via the regeneration of membrane-embedded antioxidants. Yet, regulators of FSP1 are largely uncharacterized, and their identification is essential for understanding the mechanisms buffering phospholipid peroxidation and ferroptosis. Here we report a focused CRISPR-Cas9 screen to uncover factors influencing FSP1 function, identifying riboflavin (vitamin B2) as a modulator of ferroptosis sensitivity. We demonstrate that riboflavin supports FSP1 stability and the recycling of lipid-soluble antioxidants, thereby mitigating phospholipid peroxidation. Furthermore, we show that the riboflavin antimetabolite roseoflavin markedly impairs FSP1 function and sensitizes cancer cells to ferroptosis. Our findings provide a rational strategy to modulate the FSP1-antioxidant recycling pathway and underscore the therapeutic potential of targeting riboflavin metabolism, with implications for understanding the interaction of nutrients, as well as their contributions to a cell's antioxidant capacity.

Endothelial cells (ECs) are central regulators of vascular and metabolic homeostasis, yet their organ- and depot-specific diversity remains underexplored. Two major types of adipose tissue (AT) can be distinguished that differ substantially in their physiological function and vascularization: white AT (WAT), which is the major energy storage and brown AT (BAT), which is highly vascularized and dissipates energy [1–5]. While ECs from these depots likely contribute to adipose function, their characterization has been hindered by technical limitations in isolation and culture. Here, we establish a protocol for isolating and expanding ECs from murine BAT and WAT, enabling transcriptomic and functional analyses across depots. We demonstrate that freshly isolated BAT-ECs express depot-enriched gene signatures, including Rgcc, Cdkn1c, Tcf15, Meox2, and Efnb1, several of which are dynamically regulated during cold-induced BAT activation. These findings reveal novel BAT-EC markers and highlight specialized endothelial programs that may support BAT function. However, we also uncover that culturing BAT-ECs profoundly remodels EC identity. Transcriptomic profiling shows that BAT-ECs rapidly downregulate BAT-enriched endothelial markers and acquire features resembling WAT-ECs. This dedifferentiation is accompanied by signatures of proliferation, adhesion remodeling, and endothelial-to-mesenchymal transition. While these changes present challenges for maintaining depot-specific identity in culture, they also provide a framework to better interpret experimental outcomes and to investigate EC plasticity. Taken together, our study delivers a novel isolation and culture protocol for adipose ECs, defines BAT-EC markers, and demonstrates how culture conditions reshape their identity. These insights build the foundation for future research of AT vasculature.

ABSTRACT In this paper, we consider a system of semilinear partial differential equations (PDEs) representing a spatially extended SIR epidemic model. A brief analytical investigation of the well‐posedness and positivity of the solutions is provided in the appendix, while the main focus is on the numerical treatment of the model. We examine the performance of several time‐stepping schemes, including the standard forward Euler, semi‐implicit Crank–Nicolson, their Mickens‐type nonstandard counterparts, and explicit exponential Runge–Kutta methods. Particular attention is given to the preservation of positivity in the numerical solutions, which is crucial for maintaining biological relevance. Two step‐size functions are employed, and the results are compared in terms of theoretical accuracy and computational runtime to identify the most efficient method for simulations. Our numerical results show that positivity is preserved by the standard and exponential methods only under certain restrictions on the time‐step size. In contrast, the corresponding nonstandard methods maintain positivity unconditionally, regardless of the time‐step size. These findings underscore the effectiveness of nonstandard schemes in modeling epidemic dynamics governed by reaction‐diffusion systems.