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Mathematical modeling is a pivotal tool for deciphering the complexities of biological systems and their control mechanisms, providing substantial benefits for industrial applications and answering relevant biological questions. BioModels’ Model of the Year 2023 competition was established to recognize and highlight exciting modeling-based research in the life sciences, particularly by non-independent early-career researchers. It further aims to endorse reproducibility and FAIR principles of model sharing among these researchers. We here delineate the competition’s criteria for participation and selection, introduce the award recipients, and provide an overview of their contributions. Their models provide crucial insights into cell division regulation, protein stability, and cell fate determination, illustrating the role of mathematical modeling in advancing biological research.

Individuals with PhDs and postdoctoral experience in the life sciences can pursue a variety of career paths. Many PhD students and postdocs aspire to a permanent research position at a university or research institute, but competition for such positions has increased. Here, we report a time-resolved analysis of the career paths of 2284 researchers who completed a PhD or a postdoc at the European Molecular Biology Laboratory (EMBL) between 1997 and 2020. The most prevalent career outcome was Academia: Principal Investigator (636/2284=27.8% of alumni), followed by Academia: Other (16.8%), Science-related Non-research (15.3%), Industry Research (14.5%), Academia: Postdoc (10.7%) and Non-science-related (4%); we were unable to determine the career path of the remaining 10.9% of alumni. While positions in Academia (Principal Investigator, Postdoc and Other) remained the most common destination for more recent alumni, entry into Science-related Non-research, Industry Research and Non-science-related positions has increased over time, and entry into Academia: Principal Investigator positions has decreased. Our analysis also reveals information on a number of factors – including publication records – that correlate with the career paths followed by researchers.

Proteomics can be used to refine cancer classification. Here, the authors characterise chronic lymphocytic leukaemia patients by proteogenomics, and identified a subtype of patients with poor prognosis associated with aberrant B cell receptor signalling.

Understanding the molecular and phenotypic heterogeneity of cancer is a prerequisite for effective treatment. For chronic lymphocytic leukemia (CLL), recurrent genetic driver events have been extensively cataloged, but this does not suffice to explain the disease’s diverse course. Here, we performed RNA sequencing on 184 CLL patient samples. Unsupervised analysis revealed two major, orthogonal axes of gene expression variation: the first one represented the mutational status of the immunoglobulin heavy variable (IGHV) genes, and concomitantly, the three-group stratification of CLL by global DNA methylation. The second axis aligned with trisomy 12 status and affected chemokine, MAPK and mTOR signaling. We discovered non-additive effects (epistasis) of IGHV mutation status and trisomy 12 on multiple phenotypes, including the expression of 893 genes. Multiple types of epistasis were observed, including synergy, buffering, suppression and inversion, suggesting that molecular understanding of disease heterogeneity requires studying such genetic events not only individually but in combination. We detected strong differentially expressed gene signatures associated with major gene mutations and copy number aberrations including SF3B1, BRAF and TP53, as well as del(17)(p13), del(13)(q14) and del(11)(q22.3) beyond dosage effect. Our study reveals previously underappreciated gene expression signatures for the major molecular subtypes in CLL and the presence of epistasis between them.

Abstract Background The prognostic value of extravascular lung water (EVLW) measured by transpulmonary thermodilution (TPTD) in critically ill patients is debated. We performed a systematic review and meta-analysis of studies assessing the effects of TPTD-estimated EVLW on mortality in critically ill patients. Methods Cohort studies published in English from Embase, MEDLINE, and the Cochrane Database of Systematic Reviews from 1960 to 1 June 2021 were systematically searched. From eligible studies, the values of the odds ratio (OR) of EVLW as a risk factor for mortality, and the value of EVLW in survivors and non-survivors were extracted. Pooled OR were calculated from available studies. Mean differences and standard deviation of the EVLW between survivors and non-survivors were calculated. A random effects model was computed on the weighted mean differences across the two groups to estimate the pooled size effect. Subgroup analyses were performed to explore the possible sources of heterogeneity. Results Of the 18 studies included (1296 patients), OR could be extracted from 11 studies including 905 patients (464 survivors vs. 441 non-survivors), and 17 studies reported EVLW values of survivors and non-survivors, including 1246 patients (680 survivors vs. 566 non-survivors). The pooled OR of EVLW for mortality from eleven studies was 1.69 (95% confidence interval (CI) [1.22; 2.34], p

Studying the contribution of pairs of genes to complex traits has been challenging. Here, the authors combine exome and genotype data with RNAi to screen for genetic interactions between 30 genes identified in lipid GWAS to hint at pairs whose joint modulation may improve lipid-lowering therapies.

Metabolomic and proteomic analyses of human plasma and serum samples harbor the power to advance our understanding of disease biology. Pre-analytical factors may contribute to variability and bias in the detection of analytes, especially when multiple labs are involved, caused by sample handling, processing time, and differing operating procedures. To better understand the impact of pre-analytical factors that are relevant to implementing a unified proteomic and metabolomic approach in a clinical setting, we assessed the influence of temperature, sitting times, and centrifugation speed on the plasma and serum metabolomes and proteomes from six healthy volunteers. We used targeted metabolic profiling (497 metabolites) and data-independent acquisition (DIA) proteomics (572 proteins) on the same samples generated with well-defined pre-analytical conditions to evaluate criteria for pre-analytical SOPs for plasma and serum samples. Time and temperature showed the strongest influence on the integrity of plasma and serum proteome and metabolome. While rapid handling and low temperatures (4°C) are imperative for metabolic profiling, the analyzed proteomics data set showed variability when exposed to temperatures of 4°C for more than 2 h, highlighting the need for compromises in a combined analysis. We formalized a quality control scoring system to objectively rate sample stability and tested this score using external data sets from other pre-analytical studies. Stringent and harmonized standard operating procedures (SOPs) are required for pre-analytical sample handling when combining proteomics and metabolomics of clinical samples to yield robust and interpretable data on a longitudinal scale and across different clinics. To ensure an adequate level of practicability in a clinical routine for metabolomics and proteomics studies, we suggest keeping blood samples up to 2 h on ice (4°C) prior to snap-freezing as a compromise between stability and operability. Finally, we provide the methodology as an open-source R package allowing the systematic scoring of proteomics and metabolomics data sets to assess the stability of plasma and serum samples.

Abstract Wnt pathways are important for the modulation of tissue homeostasis, and their deregulation is linked to cancer development. Canonical Wnt signaling is hyperactivated in many human colorectal cancers due to genetic alterations of the negative Wnt regulator APC. However, the expression levels of Wnt‐dependent targets vary between tumors, and the mechanisms of carcinogenesis concomitant with this Wnt signaling dosage have not been understood. In this study, we integrate whole‐genome CRISPR/Cas9 screens with large‐scale multi‐omic data to delineate functional subtypes of cancer. We engineer APC loss‐of‐function mutations and thereby hyperactivate Wnt signaling in cells with low endogenous Wnt activity and find that the resulting engineered cells have an unfavorable metabolic equilibrium compared with cells which naturally acquired Wnt hyperactivation. We show that the dosage level of oncogenic Wnt hyperactivation impacts the metabolic equilibrium and the mitochondrial phenotype of a given cell type in a context‐dependent manner. These findings illustrate the impact of context‐dependent genetic interactions on cellular phenotypes of a central cancer driver mutation and expand our understanding of quantitative modulation of oncogenic signaling in tumorigenesis.

Abstract The tumour microenvironment and genetic alterations collectively influence drug efficacy in cancer, but current evidence is limited and systematic analyses are lacking. Using chronic lymphocytic leukaemia (CLL) as a model disease, we investigated the influence of 17 microenvironmental stimuli on 12 drugs in 192 genetically characterised patient samples. Based on microenvironmental response, we identified four subgroups with distinct clinical outcomes beyond known prognostic markers. Response to multiple microenvironmental stimuli was amplified in trisomy 12 samples. Trisomy 12 was associated with a distinct epigenetic signature. Bromodomain inhibition reversed this epigenetic profile and could be used to target microenvironmental signalling in trisomy 12 CLL. We quantified the impact of microenvironmental stimuli on drug response and their dependence on genetic alterations, identifying interleukin 4 (IL4) and Toll‐like receptor (TLR) stimulation as the strongest actuators of drug resistance. IL4 and TLR signalling activity was increased in CLL‐infiltrated lymph nodes compared with healthy samples. High IL4 activity correlated with faster disease progression. The publicly available dataset can facilitate the investigation of cell‐extrinsic mechanisms of drug resistance and disease progression.

The development of cancer therapies may be improved by the discovery of tumor-specific molecular dependencies. The requisite tools include genetic and chemical perturbations, each with its strengths and limitations. Chemical perturbations can be readily applied to primary cancer samples at large scale, but mechanistic understanding of hits and further pharmaceutical development is often complicated by the fact that a chemical compound has affinities to multiple proteins. To computationally infer specific molecular dependencies of individual cancers from their ex vivo drug sensitivity profiles, we developed a mathematical model that deconvolutes these data using measurements of protein-drug affinity profiles. Through integrating a drug-kinase profiling dataset and several drug response datasets, our method, DepInfeR, correctly identified known protein kinase dependencies, including the EGFR dependence of HER2+ breast cancer cell lines, the FLT3 dependence of acute myeloid leukemia (AML) with FLT3-ITD mutations and the differential dependencies on the B-cell receptor pathway in the two major subtypes of chronic lymphocytic leukemia (CLL). Furthermore, our method uncovered new subgroup-specific dependencies, including a previously unreported dependence of high-risk CLL on Checkpoint kinase 1 (CHEK1). The method also produced a detailed map of the kinase dependencies in a heterogeneous set of 117 CLL samples. The ability to deconvolute polypharmacological phenotypes into underlying causal molecular dependencies should increase the utility of high-throughput drug response assays for functional precision oncology.

Abstract Nearly 5% of patients suffering from COVID-19 develop acute respiratory distress syndrome (ARDS). Extravascular lung water index (EVLWI) is a marker of pulmonary oedema which is associated with mortality in ARDS. In this study, we evaluate whether EVLWI is higher in patients with COVID-19 associated ARDS as compared to COVID-19 negative, ventilated patients with ARDS and whether EVLWI has the potential to monitor disease progression. EVLWI and cardiac function were monitored by transpulmonary thermodilution in 25 patients with COVID-19 ARDS subsequent to intubation and compared to a control group of 49 non-COVID-19 ARDS patients. At intubation, EVLWI was noticeably elevated and significantly higher in COVID-19 patients than in the control group (17 (11–38) vs. 11 (6–26) mL/kg; p

2D-thermal proteome profiling (2D-TPP) is a powerful assay for probing interactions of proteins with small molecules in their native context. Here the authors provide a statistical method for false discovery rate controlled analysis for 2D-TPP applications.

The Pan-Cancer Analysis of Whole Genomes project generated a vast array of data. In this article, the authors describe five different online resources to enable readers to explore and visualize the data.

Abstract Pooled CRISPR screens are a powerful tool to probe genotype-phenotype relationships at genome-wide scale. However, criteria for optimal design are missing, and it remains unclear how experimental parameters affect results. Here, we report that random decreases in gRNA abundance are more likely than increases due to bottle-neck effects during the cell proliferation phase. Failure to consider this asymmetry leads to loss of detection power. We provide a new statistical test that addresses this problem and improves hit detection at reduced experiment size. The method is implemented in the R package gscreend, which is available at http://bioconductor.org/packages/gscreend .

Assessment of peripheral perfusion and comparison of surface and body core temperature (BST; BCT) are diagnostic cornerstones of critical care. Infrared non-contact thermometers facilitate the accurate measurement of BST. Additionally, a corrected measurement of BST on the forehead provides an estimate of BCT (BCT_Forehead). In clinical routine BCT is measured by ear thermometers (BCT_Ear). The PiCCO-device (PiCCO: Pulse contour analysis) provides thermodilution-derived Cardiac Index (CI_TD) using an arterial catheter with a thermistor tip in the distal aorta. Therefore, the PiCCO-catheter might be used for continuous BCT-measurement (BCT_PiCCO) in addition to intermittent CI-measurement. To the best of our knowledge, BCT_PiCCO has not been validated compared to standard techniques of BCT-measurement including measurement of urinary bladder temperature (BCT_Bladder). Therefore, we compared BCT_PiCCO to BCT_Ear and BCT_Bladder in 52 patients equipped with the PiCCO-device (Pulsion; Germany). Furthermore, this setting allowed to compare different BSTs and their differences to BCT with CI_TD. BCT_PiCCO, BCT_Ear (ThermoScan; Braun), BCT_Bladder (UROSID; ASID BONZ), BCT_Forehead and BSTs (Thermofocus; Tecnimed) were measured four times within 24h. BSTs were determined on the great toe, finger pad and forearm. Immediately afterwards TPTD was performed to obtain CI_TD. 32 (62%) male, 20 (38%) female patients; APACHE-II 23.8 ±8.3. Bland-Altman-analysis demonstrated low bias and percentage error (PE) values for the comparisons of BCT_PiCCO vs. BCT_Bladder (bias 0.05 ±0.27° Celsius; PE = 1.4%), BCT_PiCCO vs. BCT_Ear (bias 0.08 ±0.38° Celsius; PE = 2.0%) and BCT_Ear vs. BCT_Bladder (bias 0.04 ±0.42° Celsius; PE = 2.2). While BCT_PiCCO, BCT_Ear and BCT_Bladder can be considered interchangeable, Bland-Altman-analyses of BCT_Forehead vs. BCT_PiCCO (bias = -0.63 ±0.75° Celsius; PE = 3.9%) Celsisus, BCT_Ear (bias = -0.58 ±0.68° Celsius; PE = 3.6%) and BCT_Bladder (bias = -0.55 ±0.74° Celsius; PE = 3.9%) demonstrate a substantial underestimation of BCT by BCT_Forehead. BSTs and differences between BCT and BST (DCST) significantly correlated with CI_TD with r-values between 0.230 and 0.307 and p-values between 0.002 and p < 0.001. The strongest association with CI_TD was found for BST_forearm (r = 0.307; p < 0.001). In a multivariate analysis regarding CI_TD and including biometric data, BSTs and and their differences to core-temperatures (DCST), only higher temperatures on the forearm and the great toe, young age, low height and male gender were independently associated with CI_TD. The estimate of CI based on this model (CI_estimated) correlated with CI_TD (r = 0.594; p < 0.001). CI_estimated provided large ROC-areas under the curve (AUC) regarding the critical thresholds of CI_TD ≤ 2.5 L/min/m2 (AUC = 0.862) and CI_TD ≥ 5.0 L/min/m2 (AUC = 0.782). 1.) BCT_PiCCO, BCT_Ear and BCT_Bladder are interchangeable. 2.) BCT_Forehead significantly underestimates BCT by about 0.5° Celsius. 3.) All measured BSTs and DCSTs were significantly associated with CI_TD. 4.) CI_estimated is promising, in particular for the prediction of critical thresholds of CI.

Abstract Background Leptospirosis is one of the leading global zoonotic causes of morbidity and mortality. It is induced by a pathogenic spirochete of the genus Leptospira. The icteric form of leptospirosis is characterized by pronounced hyperbilirubinemia and associated with significantly increased mortality. Conventional static liver function tests insufficiently assess hepatic damage and have limited prognostic value. Dynamic tests, such as indocyanine green plasma (ICG) clearance, more adequately reflect hepatic functional status. In this case report we describe the ICG plasma disappearance rates (ICG-PDR) in a patient with leptospirosis and massive hyperbilirubinemia, expanding our knowledge of liver dysfunction in icteric leptospirosis. Case presentation A 21-year-old Caucasian man presented with acute-onset jaundice, myalgia, fever and headaches. Laboratory tests upon admission revealed, most notably, acute kidney failure and hyperbilirubinemia of 17 mg/dl with mild elevation of aminotransferases. In the course of the following 4 days, total serum bilirubin increased to 54 mg/dl. The clinical outcome was favorable with intravenous ceftriaxone and doxycycline. Presumptive diagnosis of leptospirosis was later confirmed by PCR-based amplification of leptospiral DNA in the blood. ICG-PDR values, bilirubin as well as aminotransferases were recorded throughout hospitalization and a 3-month follow-up period. Initially dramatically reduced ICG-PDR (2.0%/min, normal range: 18–25%/min) rapidly normalized within 10 days, while bilirubin remained elevated up to week 7. Mild elevation of serum alanine aminotransferase was at its peak of 124 U/l by day 12 and reached close to normal levels by week 7 upon admission. Conclusions Markedly diminished ICG-PDR values presented in this case report suggest severe liver function impairment in the acute phase of icteric leptospirosis. Prolonged elevation of serum bilirubin may not adequately reflect recovery of liver injury in this disease. ICG clearance appears to be a promising marker for the detection of hepatic dysfunction and recovery in icteric leptospirosis in addition to the static tests.

ATP can function as a biological hydrotrope, but its global effects on protein solubility have not yet been characterized. Here, the authors quantify the effect of ATP on the thermal stability and solubility of the cellular proteome, providing insights into protein solubility regulation by ATP.

Chronic lymphocytic leukemia (CLL) is the most common leukemia in adults. Emerging data suggest that CLL-cells efficiently evade immunosurveillance. T-cell deficiencies in CLL include immuno(metabolic) exhaustion that is achieved by inhibitory molecules, with programmed cell death 1/programmed cell death ligand 1 (PD-L1) signaling emerging as a major underlying mechanism. Moreover, CLL-cells are characterized by a close and recurrent interaction with their stromal niches in the bone marrow and lymph nodes. Here, they receive nurturing signals within a well-protected environment. We could previously show that the interaction of CLL-cells with stroma leads to c-Myc activation that is followed by metabolic adaptations. Recent data indicate that c-Myc also controls expression of the immune checkpoint molecule PD-L1. Therefore, we sought out to determine the role of stromal contact for the CLL-cells’ PD-L1 expression and thus their immuno-evasive phenotype.To do so, we analyzed PD-L1 expression on CLL cell (subsets) in untreated patients and on healthy donor-derived B-cells. Impact of stromal contact on PD-L1 expression on CLL-cells and the underlying signaling pathways were assessed in well-established in vitro niche models. Ex vivo and in vitro findings were validated in the Eµ-TCL1 transgenic CLL mouse model.We found increased PD-L1 expression on CLL-cells as compared with B-cells that was further enhanced in a cell-to-cell contact-dependent manner by stromal cells. In fact, circulating recent stromal-niche emigrants displayed higher PD-L1 levels than long-time circulating CLL-cells. Using our in vitro niche model, we show that a novel Notch-c-Myc-enhancer of zeste homolog 2 (EZH2) signaling axis controls PD-L1 upregulation. Ultimately, elevated PD-L1 levels conferred increased resistance towards activated autologous T-cells.In summary, our findings support the notion that the CLL microenvironment contributes to immune escape variants. In addition, several targetable molecules (eg, Notch or EZH2) could be exploited in view of improving immune responses in patients with CLL, which warrants further in-depth investigation.

BackgroundSuperinfections, including invasive pulmonary aspergillosis (IPA), are well-known complications of critically ill patients with severe viral pneumonia. Aim of this study was to evaluate the incidence, risk factors and outcome of IPA in critically ill patients with severe COVID-19 pneumonia.MethodsWe prospectively screened 32 critically ill patients with severe COVID-19 pneumonia for a time period of 28 days using a standardized study protocol for oberservation of developement of COVID-19 associated invasive pulmonary aspergillosis (CAPA). We collected laboratory, microbiological, virological and clinical parameters at defined timepoints in combination with galactomannan-antigen-detection from nondirected bronchial lavage (NBL). We used logistic regression analyses to assess if COVID-19 was independently associated with IPA and compared it with matched controls.FindingsCAPA was diagnosed at a median of 4 days after ICU admission in 11/32 (34%) of critically ill patients with severe COVID-19 pneumonia as compared to 8% in the control cohort. In the COVID-19 cohort, mean age, APACHE II score and ICU mortality were higher in patients with CAPA than in patients without CAPA (36% versus 9.5%; pInterpretationCAPA is highly prevalent and associated with a high mortality rate. COVID-19 is independently associated with invasive pulmonary aspergillosis. A standardized screening and diagnostic approach as presented in our study can help to identify affected patients at an early stage.

Abstract A progressive loss of protein homeostasis is characteristic of aging and a driver of neurodegeneration. To investigate this process quantitatively, we characterized proteome dynamics during brain aging in the short‐lived vertebrate Nothobranchius furzeri combining transcriptomics and proteomics. We detected a progressive reduction in the correlation between protein and mRNA, mainly due to post‐transcriptional mechanisms that account for over 40% of the age‐regulated proteins. These changes cause a progressive loss of stoichiometry in several protein complexes, including ribosomes, which show impaired assembly/disassembly and are enriched in protein aggregates in old brains. Mechanistically, we show that reduction of proteasome activity is an early event during brain aging and is sufficient to induce proteomic signatures of aging and loss of stoichiometry in vivo. Using longitudinal transcriptomic data, we show that the magnitude of early life decline in proteasome levels is a major risk factor for mortality. Our work defines causative events in the aging process that can be targeted to prevent loss of protein homeostasis and delay the onset of age‐related neurodegeneration.

BackgroundEarly recognition of high-risk-patients with acute respiratory distress syndrome (ARDS) might improve their outcome by less protracted allocation to intensified therapy including extracorporeal membrane oxygenation (ECMO). Among numerous predictors and classifications, the American European Consensus Conferenece (AECC)- and Berlin-definitions as well as the oxygenation index (OI) and the Murray-/Lung Injury Score are the most common. Most studies compared the prediction of mortality by these parameters on the day of intubation and/or diagnosis of ARDS. However, only few studies investigated prediction over time, in particular for more than three days.ObjectiveTherefore, our study aimed at characterization of the best predictor and the best day(s) to predict 28-days-mortality within four days after intubation of patients with ARDS.MethodsIn 100 consecutive patients with ARDS severity according to OI (mean airway pressure*FiO2/paO2), modified Murray-score without radiological points (Murray_mod), AECC- and Berlin-definition, were daily documented for four days after intubation. In the subgroup of 49 patients with transpulmonary thermodilution (TPTD) monitoring (PiCCO), extravascular lung water index (EVLWI) was measured daily.Primary endpointPrediction of 28-days-mortality (Area under the receiver-operating-characteristic curve (ROC-AUC)); IBM SPSS 26.ResultsIn the totality of patients the best prediction of 28-days-mortality was found on day-1 and day-2 (mean ROC-AUCs for all predictors/scores: 0.632 and 0.620). OI was the best predictor among the ARDS-scores (AUC=0.689 on day-1; 4-day-mean AUC = 0.625). AECC and Murray_mod had 4-day-means AUCs below 0.6. Among the 49 patients with TPTD, EVLWI (4-day-mean AUC=0.696) and OI (4-day-mean AUC=0.695) were the best predictors. AUCs were 0.789 for OI on day-1, and 0.786 for EVLWI on day-2. In binary regression analysis of patients with TPTD, EVLWI (B=-0.105; Wald=7.294; p=0.007) and OI (B=0.124; Wald=7.435; p=0.006) were independently associated with 28-days-mortality. Combining of EVLWI and OI provided ROC-AUCs of 0.801 (day-1) and 0.824 (day-2). Among the totality of patients, the use of TPTD-monitoring "per se" and a lower SOFA-score were independently associated with a lower 28-days-mortality.ConclusionsPrognosis of ARDS-patients can be estblished within two days after intubation. The best predictors were EVLWI and OI and their combination. TPTD-monitoring "per se" was independently associated with reduced mortality.

Summary: Transcription factors (TFs) regulate many cellular processes and can therefore serve as readouts of the signaling and regulatory state. Yet for many TFs, the mode of action—repressing or activating transcription of target genes—is unclear. Here, we present diffTF (https://git.embl.de/grp-zaugg/diffTF) to calculate differential TF activity (basic mode) and classify TFs into putative transcriptional activators or repressors (classification mode). In basic mode, it combines genome-wide chromatin accessibility/activity with putative TF binding sites that, in classification mode, are integrated with RNA-seq. We apply diffTF to compare (1) mutated and unmutated chronic lymphocytic leukemia patients and (2) two hematopoietic progenitor cell types. In both datasets, diffTF recovers most known biology and finds many previously unreported TFs. It classifies almost 40% of TFs based on their mode of action, which we validate experimentally. Overall, we demonstrate that diffTF recovers known biology, identifies less well-characterized TFs, and classifies TFs into transcriptional activators or repressors. : Berest et al. present a computational tool (diffTF) to estimate differential TF activity and classify TFs into activators or repressors. It requires active chromatin data (accessibility/ChIP-seq) and integrates with RNA-seq for classification. The authors apply it to two case studies (CLL and hematopoietic differentiation) and validate their predictions experimentally. Keywords: transcription factor, ATAC-seq, CLL, transcriptional activator and repressor, RNA-seq, TF footprint, open chromatin, snakemake, multiomics data integration

Abstract Background Ascites is a major complication of decompensated liver cirrhosis. Intraabdominal hypertension and structural alterations of parenchyma involve decisive changes in hepatosplanchnic blood flow. Clearance of indo-cyanine green (ICG) is mainly dependent on hepatic perfusion and hepatocellular function. As a consequence, plasma disappearance rate of ICG (ICG-PDR) is rated as a useful dynamic parameter of liver function. This study primarily evaluates the impact of large-volume paracentesis (LVP) on ICG-PDR in critically ill patients with decompensated cirrhosis. Additionally, it describes influences on intraabdominal pressure (IAP), abdominal perfusion pressure (APP), hepatic blood flow, hemodynamic and respiratory function. Methods We analyzed LVP in 22 patients with decompensated liver cirrhosis. ICG-PDR was assessed by using noninvasive LiMON technology (Pulsion® Medical Systems; Maquet Getinge Group), and hepatic blood flow was analyzed by color-coded duplex sonography. Results Paracentesis of a median volume of 3450 mL ascites evoked significant increases of ICG-PDR from 3.6 (2.8–4.6) to 5.1 (3.9–6.2)%/min (p