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Acquisition of cell fate is thought to rely on the specific interaction of remote cis -regulatory modules (CRMs), for example, enhancers and target promoters. However, the precise interplay between chromatin structure and gene expression is still unclear, particularly within multicellular developing organisms. In the present study, we employ Hi-M, a single-cell spatial genomics approach, to detect CRM–promoter looping interactions within topologically associating domains (TADs) during early Drosophila development. By comparing cis -regulatory loops in alternate cell types, we show that physical proximity does not necessarily instruct transcriptional states. Moreover, multi-way analyses reveal that multiple CRMs spatially coalesce to form hubs. Loops and CRM hubs are established early during development, before the emergence of TADs. Moreover, CRM hubs are formed, in part, via the action of the pioneer transcription factor Zelda and precede transcriptional activation. Our approach provides insight into the role of CRM–promoter interactions in defining transcriptional states, as well as distinct cell types. Single-cell analysis of Drosophila development with Hi-M suggests that physical proximity between regulatory regions does not necessarily instruct transcriptional states. Multi-way analyses identify the existence of regulatory hubs that emerge before topologically associating domains.

Concentrating solar power plants are a clean energy source capable of competitive electricity generation even during night time, as well as the production of carbon-neutral fuels, offering a complementary role alongside photovoltaic plants. In these power plants, thousands of mirrors (heliostats) redirect sunlight onto a receiver, potentially generating temperatures exceeding 1000°C. Practically, such efficient temperatures are never attained. Several unknown, yet operationally crucial parameters, e.g., misalignment in sun-tracking and surface deformations can cause dangerous temperature spikes, necessitating high safety margins. For competitive levelized cost of energy and large-scale deployment, in-situ error measurements are an essential, yet unattained factor. To tackle this, we introduce a differentiable ray tracing machine learning approach that can derive the irradiance distribution of heliostats in a data-driven manner from a small number of calibration images already collected in most solar towers. By applying gradient-based optimization and a learning non-uniform rational B-spline heliostat model, our approach is able to determine sub-millimeter imperfections in a real-world setting and predict heliostat-specific irradiance profiles, exceeding the precision of the state-of-the-art and establishing full automatization. The new optimization pipeline enables concurrent training of physical and data-driven models, representing a pioneering effort in unifying both paradigms for concentrating solar power plants and can be a blueprint for other domains. Solar tower power plants’ efficiency is hindered due to component defects such as heliostat misalignment and surface deformations. Authors propose machine learning with differentiable ray tracing to identify these errors from calibration images and predict irradiance profiles, enhancing operational efficiency.

The spatial organization of chromatin at the scale of topologically associating domains (TADs) and below displays large cell-to-cell variations. Up until now, how this heterogeneity in chromatin conformation is shaped by chromatin condensation, TAD insulation, and transcription has remained mostly elusive. Here, we used Hi-M, a multiplexed DNA-FISH imaging technique providing developmental timing and transcriptional status, to show that the emergence of TADs at the ensemble level partially segregates the conformational space explored by single nuclei during the early development of Drosophila embryos. Surprisingly, a substantial fraction of nuclei display strong insulation even before TADs emerge. Moreover, active transcription within a TAD leads to minor changes to the local inter- and intra-TAD chromatin conformation in single nuclei and only weakly affects insulation to the neighboring TAD. Overall, our results indicate that multiple parameters contribute to shaping the chromatin architecture of single nuclei at the TAD scale. Here the authors applied their recently developed multiplexed DNA-FISH Hi-M method to dissect the sources of heterogeneity in topologically associating domain (TAD)-like organization during Drosophila embryogenesis. This single-nucleus analysis allows them to reveal that multiple parameters contribute to shaping the trace of the chromatin path from a single nucleus.

5‐Hydroxymethylfurfural (HMF) is a versatile platform chemical for a fossil free, bio‐based chemical industry. HMF can be produced by using fructose as a feedstock. Using edible, first‐generation biomass to produce chemicals has been questioned in terms of potential competition with food supply. Second‐generation biomass like miscanthus could be an alternative. However, there is a lack of information if second‐generation lignocellulosic biomass is a more sustainable feedstock to produce HMF. Therefore, a life cycle assessment was performed in this study to determine the environmental impacts of HMF production from miscanthus and to compare it with HMF from high‐fructose corn syrup (HFCS). HFCS from either Hungary or Baden‐Württemberg (Germany) was considered. Compared to the HFCS biorefineries the miscanthus concept is producing less emissions in all impact categories studied, except land occupation. Overall, the production and usage of second‐generation biomass could be especially beneficial in areas where the use of N fertilizers is restricted. Besides, conclusions for the further development of the on‐farm biorefinery concept were elaborated. For this purpose, process simulations from a previous study were used. Results of the previous study in terms of TEA and the current LCA study in terms of environmental sustainability indicate that the lignin depolymerization unit in the miscanthus biorefinery has to be improved. The scenario without lignin depolymerization performs better in all impact categories. The authors recommend to not further convert the lignin to products like phenol and other aromatic compounds. The results of the contribution analyses show that the major impact in the HMF production is caused by the auxiliary materials in the separation units and the required heat. Further technical development should focus on efficient heat as well as solvent use and solvent recovery. At this point further optimizations will lead to reduced emissions and costs at the same time. A comparative LCA of two feedstock biomasses was prepared for the Hohenheim process for the production of 5‐hydroxymethylfurfural. In most impact categories, the lignocellulosic biorefinery is superior to the fructose biorefinery. At the same time, this work provides indications for further optimization.

Genome-wide ensemble sequencing methods improved our understanding of chromatin organization in eukaryotes but lack the ability to capture single-cell heterogeneity and spatial organization. To overcome these limitations, new imaging-based methods have emerged, giving rise to the field of spatial genomics. Here, we present pyHiM, a user-friendly python toolbox specifically designed for the analysis of multiplexed DNA-FISH data and the reconstruction of chromatin traces in individual cells. pyHiM employs a modular architecture, allowing independent execution of analysis steps and customization according to sample specificity and computing resources. pyHiM aims to facilitate the democratization and standardization of spatial genomics analysis.

Background Colorectal liver metastases (CRLM) are a major cause of cancer-related deaths. Glucose transporter 1 (GLUT1) is a key mediator of glycolytic metabolism in malignant and immune cells; however, the prognostic relevance of compartment-specific GLUT1 patterns in CRLM remains undefined. We hypothesized that spatial GLUT1 expression at the tumor–liver interface may reflect clinically relevant microenvironmental biology. Methods We retrospectively analyzed data of 192 patients who underwent curative-intent resection for CRLM (75 solitary; 117 multiple). GLUT1 expression was assessed by immunohistochemistry in the tumor tissue (Tu) and infiltration margin (Im) and was correlated with overall survival using Cox regression. Double immunofluorescence for CD8 and GLUT1 was performed for qualitative visualization at the infiltration margin. In an exploratory subset (n = 5), flow cytometry and in vitro killing assays were conducted on GLUT1⁺ versus GLUT1⁻ CD8⁺ tumor-infiltrating lymphocytes (TILs). Results Tumoral GLUT1 correlated with Ki67 (Spearman’s ρ = 0.31, p = 0.003) but was not independently associated with overall survival in the main cohort (multivariable HR 1.183, 95% CI 0.74–1.90; p  = 0.485). In the main cohort, capsule presence remained strongly associated with improved survival (HR 0.35, 95% CI 0.21–0.58; p  < 0.001). In contrast, high invasive-margin GLUT1 was independently associated with improved survival in the predefined solitary cohort (HR 0.379, 95% CI 0.18–0.81; p  = 0.012). Double immunofluorescence demonstrated the qualitative co-localization of the GLUT1 signal with CD8⁺ cells at the infiltration margin. In exploratory assays (n = 5), flow cytometry suggested GLUT1 enrichment in CD8⁺ terminally differentiated effector memory T cells re-expressing CD45RA (TEMRA), and GLUT1⁺ TIL fractions showed higher in vitro tumor cell killing compared with GLUT1⁻ cells. Conclusion GLUT1 shows compartment- and context-dependent associations in the CRLM. While tumor-core GLUT1 is linked to proliferative activity, invasive-margin GLUT1 is associated with favorable outcomes in solitary metastases. Immunofluorescence and functional data provide hypothesis-generating context and warrant validation with quantitative spatial immune profiling and independent cohorts.

Thermochemical biorefineries for the production of chemicals and materials can play an important role in the bioeconomy. However, their economic viability is often questioned under the premise of the economy of scale. This paper presents a regional, modular biorefinery concept for the production of the platform chemicals hydroxymethylfurfural (HMF), furfural and phenols from the lignocellulosic perennial miscanthus, which can be cultivated on marginal and degraded areas. The paper focuses on the question of the minimum selling price of HMF and the optimal plant size for this purpose, using the region of Baden‐Württemberg, Germany, as an example. Based on small pilot plant results, a scalable process simulation was created via AspenPlus. This allows different scenarios and process combinations of this multi‐output biorefinery concept to be compared with each other. Using this, a minimum sales price for the main product HMF is calculated using methods of dynamic investment cost calculation according to the net present value method. Based on this, the plant capacity was scaled. The scenarios and sensitivity analyses show that, with an accuracy of ±15%, regional biorefineries could already offer platform chemicals at prices of 2.21–2.90 EUR/kg HMF at the current stage of development. This corresponds to three to four times the price of today's comparative fossil base chemicals and is thus a competitive option from the authors’ point of view. The local biomass and the heat prices were identified as the main influencing factors. As a result, the selection of the location will have a decisive influence on the economic viability of such concepts in the case of further development and optimization of the process in first demonstration plants. This paper presents a regional, modular biorefinery concept for the production of the platform chemicals hydroxymethylfurfural (HMF), furfural and phenols from the lignocellulosic perennial miscanthus, which can be cultivated on marginal and degraded areas. The paper focuses on the question of the minimum selling price of HMF and the optimal plant size for this purpose, using the region of Baden‐Württemberg, Germany, as an example. Based on small pilot plant results, a scalable process simulation was created via AspenPlus.

Single-molecule FRET (smFRET) is a versatile technique to study the dynamics and function of biomolecules since it makes nanoscale movements detectable as fluorescence signals. The powerful ability to infer quantitative kinetic information from smFRET data is, however, complicated by experimental limitations. Diverse analysis tools have been developed to overcome these hurdles but a systematic comparison is lacking. Here, we report the results of a blind benchmark study assessing eleven analysis tools used to infer kinetic rate constants from smFRET trajectories. We test them against simulated and experimental data containing the most prominent difficulties encountered in analyzing smFRET experiments: different noise levels, varied model complexity, non-equilibrium dynamics, and kinetic heterogeneity. Our results highlight the current strengths and limitations in inferring kinetic information from smFRET trajectories. In addition, we formulate concrete recommendations and identify key targets for future developments, aimed to advance our understanding of biomolecular dynamics through quantitative experiment-derived models. The ability to infer quantitative kinetic information from single-molecule FRET (smFRET) data can be challenging. Here the authors perform a blind benchmark study assessing different analysis tools used to infer kinetic rate constants from smFRET trajectories, testing on simulated and experimental data.

Background Hepatic metastases from epithelial ovarian cancer (EOC) represent an advanced disease stage, yet national guidelines provide no standardized recommendations for liver resection. This study aimed to describe the national trends and patterns of hepatic resections in EOC patients based on German hospital billing data (DRG system) from 2020 to 2024. Methods A retrospective epidemiological analysis was conducted using InEK (Institute for Hospital Remuneration Systems) datasets from 2020 to 2024. We extracted data related to diagnosis ICD code C56 (malignant neoplasm of the ovary) and OPS codes for hepatic resections (5-501.0, 5-502.0, 5-502.2, 5-502.3, 5-502.4, 5-502.5, 5-502.6). Case numbers, procedure frequency, hospital characteristics, and DRG classifications were analyzed. Results A total of 1,273 hepatic resections were performed in patients with ovarian cancer between 2020 and 2024. Annual case numbers ranged from 225 to 283, indicating stable surgical practice over time. Local excisions / atypical resections accounted for the majority ( n  = 1,165; 91%), while segmentectomies ( n  = 85; 6.7%) and major resections ( n  = 23; 1.8%) were less frequent but consistently performed. Age group analysis showed that the largest proportion of patients undergoing hepatic resection were aged 65–74 years (range 23%–27% yearly). followed by the 60–64 and 55–59 age groups. Younger patients (< 40 years) represented less than 5%. Most procedures (54.6%) were conducted in public hospitals with ≥ 1000 beds, with additional contributions from private non-profit (20.9%) and private for-profit (10.5%) institutions. A gradual increase in the share of private institutions was observed over time. The mean hospital stay varied by resection type: 16.7 days for local excisions, 17.1 days for segmentectomies, and 20.1 days for major resections. Conclusion Hepatic resection for ovarian cancer is performed regularly in Germany, primarily at high-volume centers, suggesting a growing clinical acceptance of aggressive cytoreduction strategies despite the absence of formal recommendations. Our findings underline the need for prospective, multicenter studies and guideline updates addressing hepatic metastases in ovarian cancer.

Background Accurate preoperative risk assessment remains critical in hepatobiliary surgery. Established prediction models, such as POSSUM and P-POSSUM, have shown variable performance when applied to specialized procedures. This study externally validated and recalibrated both models to predict postoperative morbidity and mortality after elective hepatic resection. Methods All consecutive adult patients who underwent elective hepatic resection at the University Hospital Regensburg between December 2020 and December 2023 were retrospectively analyzed. POSSUM and P-POSSUM scores were calculated using the original logistic equations. Major morbidity (Clavien–Dindo ≥ IIIa) and in-hospital mortality were the predefined outcomes. Model discrimination was assessed using the area under the receiver operating characteristic curve (AUC), and calibration was evaluated using the Brier score, calibration-in-the-large (intercept), calibration slope, and out-of-bag (OOB) calibration plots derived from 1,000 bootstrap resamples. Logistic recalibration was applied to adjust the model intercepts (α) and slopes (β). The clinical utility was evaluated using decision curve analysis. Results Of the 200 elective hepatectomies assessed, six were excluded due to missing required physiological inputs, yielding 194 patients with computable predictions. Clinically relevant morbidity (Clavien–Dindo ≥ II) occurred in 146/194 (75.3%) patients, major morbidity (≥ IIIa) in 73/194 (37.6%), and in-hospital mortality in 15/194 (7.7%). Discrimination was fair for morbidity and higher for mortality: AUC 0.696 (95% CI 0.595–0.789) for clinically relevant morbidity, AUC 0.697 (95% CI 0.620–0.764) for major morbidity, and AUC 0.755 (95% CI 0.647–0.851) for in-hospital mortality. OOB bootstrap calibration showed slopes below 1 for all endpoints (clinically relevant morbidity: α 0.16, β 0.837, Brier 0.172; major morbidity: α − 0.051, β 0.907, Brier 0.215; mortality: α − 0.34, β 0.843, Brier 0.068), supporting the need for local model updating. Conclusion POSSUM and P-POSSUM can support perioperative risk prediction after hepatic resection when they are locally recalibrated and internally validated. Bootstrap-corrected recalibration yielded stable performance without evidence of overfitting, and decision curve analysis suggested clinical utility across relevant threshold probabilities. These findings support the use of POSSUM-based models in hepatobiliary surgery, provided that centers perform local validation and model updating before implementation in clinical decision-making. Key points • The POSSUM and P-POSSUM scores were externally validated in a contemporary cohort of 194 patients who underwent elective hepatic resection at the University Hospital Regensburg and the certified German Liver Center. • POSSUM showed fair discrimination for morbidity outcomes (AUC 0.697 for major morbidity, Clavien–Dindo ≥ IIIa, and AUC 0.696 for clinically relevant morbidity, ≥ II), whereas P-POSSUM achieved higher discrimination for in-hospital mortality (AUC 0.755). • Bootstrap out-of-bag validation (1,000 resamples) indicated imperfect calibration with optimism-corrected slopes < 1 (β 0.907, 0.837, and 0.843 for major morbidity, clinically relevant morbidity; β 0.843 and mortality, respectively), supporting the need for local model updating. • Decision curve analysis suggested a higher net benefit of the recalibrated models compared with “treat-all” and “treat-none” strategies across clinically relevant threshold probabilities, supporting their potential use for perioperative risk communication and institutional benchmarking. • POSSUM-based risk models can be clinically useful in hepatobiliary surgery, provided that centers perform local validation and recalibration before implementation.