The adipokine visfatin, also termed pre-B-cell colony-enhancing factor (PBEF), is mainly derived from adipose tissue but has been implicated in the regulation of innate immune responses. We hypothesized that visfatin could be a potential circulating biomarker in critical illness and sepsis. We therefore measured serum levels of visfatin in a cohort of 229 critically ill medical patients upon admission to the intensive care unit (ICU). In comparison to 53 healthy controls, visfatin levels were significantly elevated in medical ICU patients, especially in patients with sepsis. Visfatin serum concentrations were strongly associated with disease severity and organ failure but did not differ between patients with or without obesity or type 2 diabetes. Visfatin levels correlated with biomarkers of renal failure, liver dysfunction, and other adipokines (e.g., resistin, leptin, and adiponectin) in critically ill patients. High visfatin levels at ICU admission indicated an increased mortality, both at the ICU and during long-term follow-up of approximately two years. Our data therefore demonstrate that circulating visfatin is a valuable biomarker for risk and prognosis assessment in critically ill patients. Furthermore, visfatin seems to be involved in the pathogenesis of excessive systemic inflammation, supporting further research on visfatin as a therapeutic target.

Disruption of the circadian clock exacerbates metabolic diseases, including obesity and diabetes. We show that histone deacetylase 3 (HDAC3) recruitment to the genome displays a circadian rhythm in mouse liver. Histone acetylation is inversely related to HDAC3 binding, and this rhythm is lost when HDAC3 is absent. Although amounts of HDAC3 are constant, its genomic recruitment in liver corresponds to the expression pattern of the circadian nuclear receptor Rev-erbα. Rev-erbα colocalizes with HDAC3 near genes regulating lipid metabolism, and deletion of HDAC3 or Rev-erbα in mouse liver causes hepatic steatosis. Thus, genomic recruitment of HDAC3 by Rev-erbα directs a circadian rhythm of histone acetylation and gene expression required for normal hepatic lipid homeostasis.

BACKGROUND: Extracellular release of high mobility group box 1 (HMGB1) acts as a danger-associated molecular pattern, thereby "alarming" the immune system and promoting systemic inflammation. We investigated plasma HMGB1 concentrations as a potential diagnostic and prognostic biomarker in critical illness. METHODS: Our study included 218 critically ill patients (145 with sepsis, 73 without sepsis), of whom blood samples were obtained at the time-point of admission to the medical intensive care unit (ICU). RESULTS: High mobility group box 1 levels were significantly elevated in critically ill patients (n = 218) compared with healthy controls (n = 66). Elevated HMGB1 plasma levels were independent from the presence of sepsis. Moreover, HMGB1 was not associated with disease severity, organ failure, or mortality in the ICU. We observed a trend toward lower HMGB1 levels in ICU patients with pre-existing obesity, type 2 diabetes and end-stage renal disease patients on chronic hemodialysis. CONCLUSION: In conclusion, our study did not reveal significant associations between HMGB1 levels at ICU admission and clinical outcomes in critically ill patients. Due to the pathogenic role of HMGB1 in the late phases of experimental sepsis, future studies might assess the potential value of HMGB1 by measuring its plasma concentrations at later time points during the course of critical illness.

Pancreatic ductal adenocarcinoma (PDAC) is often diagnosed when liver metastases already emerged. This study elucidated the impact of hepatic stromal cells on growth behavior of premalignant and malignant pancreatic ductal epithelial cells (PDECs). Liver sections of tumor-bearing KPC mice comprised micrometastases displaying low proliferation located in an unobtrusive hepatic microenvironment whereas macrometastases containing more proliferating cells were surrounded by hepatic myofibroblasts (HMFs). In an age-related syngeneic PDAC mouse model livers with signs of age-related inflammation exhibited significantly more proliferating disseminated tumor cells (DTCs) and micrometastases despite comparable primary tumor growth and DTC numbers. Hepatic stellate cells (HSC), representing a physiologic liver stroma, promoted an IL-8 mediated quiescence-associated phenotype (QAP) of PDECs in coculture. QAP included flattened cell morphology, Ki67-negativity and reduced proliferation, elevated senescence-associated β galactosidase activity and diminished p-Erk/p-p38-ratio. In contrast, proliferation of PDECs was enhanced by VEGF in the presence of HMF. Switching the micromilieu from HSC to HMF or blocking VEGF reversed QAP in PDECs. This study demonstrates how HSCs induce and maintain a reversible QAP in disseminated PDAC cells, while inflammatory HMFs foster QAP reversal and metastatic outgrowth. Overall, the importance of the hepatic microenvironment in induction and reversal of dormancy during PDAC metastasis is emphasized.

Introduction: Recently, we were the first to identify that hepatocytes (PC) are the major cellular source of connective tissue growth factor (CTGF/CCN2) (Gressner OA et al., J Hepatol [2007], in press). In comparison to hepatic stellate cells (HSC), expression of CTGF increases spontaneously in cultured PC and is upregulated in PC of diseased rat liver. Since CTGF/CCN2 acts as an important paracrine modulator protein (38kd) of TGF-β downstream signaling, which is widely recognized as the most important profibrogenic cytokine, we currently aim at dissecting the regulatory pathways of CTGF/CCN2 in PC.

BACKGROUND: Mitochondrial dysfunction participates in the progression of several pathologies. Although there is increasing evidence for a mitochondrial role in liver disease, little is known about its contribution to hepatic stellate cell (HSC) activation. In this study we investigated the role of mitochondrial activity through mild uncoupling during in vitro activation of HSCs.METHODS: Cultured primary human and mouse HSCs were treated with the chemical uncouplers FCCP and Valinomycin. ATP levels were measured by luciferase assay and production of reactive oxygen species was determined using the fluorescent probe DCFH-DA. Possible cytotoxicity by uncoupler treatment was evaluated by caspase 3/7 activity and cytoplasmic protease leakage. Activation of HSCs and their response to the pro-fibrogenic cytokine TGF-β was evaluated by gene expression of activation markers and signal mediators using RT-qPCR. Proliferation was measured by incorporation of EdU and protein expression of α-smooth muscle actin was analyzed by immunocytochemistry and western blot.RESULTS: FCCP and Valinomycin treatment mildly decreased ATP and reactive oxygen species levels. Both uncouplers increased the expression of mitochondrial genes such as Tfam and COXIV while inducing morphological features of quiescent mouse HSCs and abrogating TGF-β signal transduction. Mild uncoupling reduced HSC proliferation and expression of pro-fibrogenic markers of mouse and human HSCs.CONCLUSIONS: Mild mitochondrial uncoupling inhibits culture-induced HSC activation and their response to pro-fibrogenic cytokines like TGF-β. These results therefore suggest mitochondrial uncoupling of HSCs as a strategy to reduce progression of liver fibrosis. PMID: 22686625

Background/Objectives: The causes of low milk supply are multifactorial, including factors such as gene mutations, endocrine disorders, and infrequent milk removal. These factors affect the functional capacity of the mammary gland and, potentially, the concentrations of milk components. This study aimed to investigate the differences in milk composition between mothers with low and normal milk supply and develop predictive machine learning models for identifying low milk supply. Methods: Twenty-four-hour milk production measurements were conducted using the test-weigh method. An array of milk components was measured in 58 women with low milk supply (<600 mL/24 h) and 106 with normal milk supply (≥600 mL/24 h). Machine learning algorithms were employed to develop prediction models integrating milk composition and maternal and infant characteristics. Results: Among the six machine learning algorithms tested, deep learning and gradient boosting machines methods had the best performance metrics. The best-performing model, incorporating 14 milk components and maternal and infant characteristics, achieved an accuracy of 87.9%, an area under the precision-recall curve (AUPRC) of 0.893, and an area under the receiver operating characteristic curve (AUC) of 0.917. Additionally, a simplified model, optimised for clinical applicability, maintained a reasonable accuracy of 78.8%, an AUPRC of 0.776, and an AUC of 0.794. Conclusions: These findings demonstrate the potential of machine learning models to predict low milk supply with high accuracy. Integrating milk composition and maternal and infant characteristics offers a practical approach to identify women at risk of low milk supply, facilitating timely interventions to support breastfeeding and ensure adequate infant nutrition.

Caspase-cleaved fragments of the intermediate filament protein keratin 18 (cytokeratin-18 (CK18)) can be detected in serum as M30 levels and may serve as a circulating biomarker indicating apoptosis of epithelial and parenchymal cells. In order to evaluate M30 as a biomarker in critical illness, we analyzed circulating M30 levels in 243 critically ill patients (156 with sepsis, 87 without sepsis) at admission to the medical intensive care unit (ICU), in comparison to healthy controls (<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M1"><mml:mi>n</mml:mi><mml:mo>=</mml:mo><mml:mn>32</mml:mn></mml:math>). M30 levels were significantly elevated in ICU patients compared with healthy controls. Circulating M30 was closely associated with disease severity but did not differ between patients with sepsis and ICU patients without sepsis. M30 serum levels were correlated with biomarkers of inflammation, cell injury, renal failure, and liver failure in critically ill patients. Patients that died at the ICU showed increased M30 levels at admission, compared with surviving patients. A similar trend was observed for the overall survival. Regression analyses confirmed that M30 levels are associated with mortality, and patients with M30 levels above 250.8 U/L displayed an excessive short-term mortality. Thus, our data support the utility of circulating levels of the apoptosis-related keratin fragment M30 as a prognostic biomarker at ICU admission.

Based on their pivotal role in the initiation and progression of liver fibrogenesis, some major issues on fibrogenesis including the regulation of extracellular matrix (ECM) components, retinoid metabolism, and mechanisms of fibrogenic signalling are addressed in primary hepatic stellate cells (HSC) worldwide [1]. These cells execute a highly dynamic programme from quiescence to activation ending in a transdifferentiated phenotype termed myofibroblasts (MFB). Although the preparation of these primary cells is well established [2], the methodologies are time-consuming and most often require ethical and institutional approval by respective national and animal legislation committees, wasteful equipment and skilful assistants. To overcome these limitations, many investigators have transferred established concepts to develop permanent HSC cell lines [3]. The human HSC lines LX–1 and LX–2 were generated by either transformation with a plasmid encoding the SV40 large T antigen under the control of a Rous sarcoma virus promoter (LX–1) or by spontaneous immortalization of a subset of early LX–1 passages that were grown in low serum conditions (LX–2) [4]. Although this permanent line is used in many studies, a detailed genotypic characterisation of this cell line is still missing. Therefore, we performed an attempt to establish the karyotype of LX–2 cells by usage of different cytogenetic and molecular cytogenetic analyses techniques including chromosome multiprobe hybridisation and spectral karyotyping. We found that LX–2 cells encompass a complex karyotype with various numerical and structural abnormalities. However, despite the observed great genetic variability, we found a few cell line specific translocations that might be useful for cell line authentication and further might be of etiologic significance for the maintenance of an immortalized phenotype or in the control of other cellular features including partial serum independency.

Summary Global warming is driving climate change to levels not experienced since the advent of agriculture, primarily due to anthropogenic factors and the accumulation of CO 2 . Rising temperatures, frequent droughts, and elevated CO 2 levels are reducing crop productivity in key agricultural regions. Developing climate‐resilient crop varieties is essential. Metabolomics provides a powerful tool for quantifying plant responses to abiotic stressors and identifying predictive biomarkers for stress tolerance. While metabolite‐based diagnostics are well‐established in clinical research, their integration into crop breeding remains limited. This Tansley review highlights recent advances in metabolomics for predicting yield stability and quality under stress, emphasising the role of metabolic biomarkers in resolving complex genotype × environment interactions. We discuss the utility of metabolite quantitative trait loci, metabolome‐wide association studies, and machine learning‐driven metabolic marker‐assisted genomic prediction in enhancing trait prediction. These approaches complement genomic selection, improving accuracy and resilience forecasting. We also address methodological challenges in translating metabolomics into breeding pipelines, including standardisation and data integration. By combining metabolomics with genomics, modelling, and high‐throughput phenotyping, researchers can accelerate the development of stress‐resilient crops. This Tansley review presents a framework for leveraging metabolomics in predictive breeding, offering a transformative pathway toward sustainable agriculture in a changing climate.