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Background: Psoriatic arthritis (PsA) is a chronic systemic inflammatory disease that affects up to 30% of patients with psoriasis. Diagnosis and treatment could be improved by implementing an interdisciplinary dermatological-rheumatological consultation (IDRC). Objectives: This study aimed to assess the effect of a face-to-face IDRC involving both a dermatologist and a rheumatologist evaluating patients in a single visit, on disease activity and burden in patients with PsA. Design: Prospective, single-center, cohort study. Methods: 202 patients with psoriasis were enrolled, among whom 115 individuals with psoriasis and musculoskeletal symptoms underwent an IDRC. Disease manifestations, comorbidities, and both objective and subjective disease activity scores were evaluated. Results: Out of the participants, 56 were diagnosed with definite PsA, while the remaining 146 had psoriasis. Nail involvement was associated with axial PsA (odds ratio 4.11; 95% CI 1.22–13.82; p = 0.02). Patients with PsA often experienced a prolonged time to diagnosis (mean 187 weeks) and had a significant psychosocial burden (mean Hospital Anxiety and Depression Index Scale [HADS]-Anxiety score of 7.66 and mean HADS-Depression score of 5.63). Post-IDRC, both objective and subjective disease parameters showed improvement, and patients required less time for consultations with healthcare professionals compared to before the IDRC. Conclusion: These findings suggest that an IDRC approach could effectively expedite and optimize the diagnosis and treatment of patients with psoriasis and musculoskeletal symptoms.

Background: The COVID-19 pandemic severely impacted healthcare systems, affecting patient outcomes and resource allocation. This study applied automated machine learning (AutoML) to analyze key health outputs, such as discharge conditions, mortality, and COVID-19 cases, with the goal of improving responses to future crises. Methods: AutoML was used to train and validate models on an ICD-10 dataset covering the first wave of COVID-19 in Romania (January–September 2020). Results: For discharge outcomes, Light Gradient Boosted models achieved an F1 score of 0.9644, while for mortality 0.7545 was reached. A Generalized Linear Model blender achieved an F1 score of 0.9884 for “acute or emergency” cases, and an average blender reached 0.923 for COVID-19 cases. Older age, specific hospitals, and oncology wards were less associated with improved recovery rates, while mortality was linked to abnormal lab results and cardiovascular/respiratory diseases. Patients admitted without referral, or patients in hospitals in the central region and the capital region of Romania were more likely to be acute cases. Finally, counties such as Argeş (South-Muntenia) and Brașov (Center) showed higher COVID-19 infection rates regardless of age. Conclusions: AutoML provided valuable insights into patient outcomes, highlighting variations in care and the need for targeted health strategies for both COVID-19 and other health challenges.

Numerous cutaneous reactions following COVID-19 vaccination have already been described. Vasculitis, however, is a rare adverse event, occurring mainly after the first COVID-19 vaccination. Herein, we report a patient with IgA-positive cutaneous leukocytoclastic vasculitis, unresponsive to a moderate dose of systemic corticosteroid that erupted after the second dose of the Pfizer/BioNTech vaccine. Since booster vaccinations are being administered, we intend to raise awareness among clinicians and to highlight this potential reaction and its therapeutic approach.

BackgroundPsoriasis vulgaris (PsV) and psoriatic arthritis (PsA) are complex, multifactorial diseases significantly impacting health and quality of life. Predicting treatment response and disease progression is crucial for optimizing therapeutic interventions, yet challenging. Automated machine learning (AutoML) technology shows promise for rapidly creating accurate predictive models based on patient features and treatment data. ObjectiveThis study aims to develop highly accurate machine learning (ML) models using AutoML to address key clinical questions for PsV and PsA patients, including predicting therapy changes, identifying reasons for therapy changes, and factors influencing skin lesion progression or an abnormal Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) score. MethodsClinical study data from 309 PsV and PsA patients were extensively prepared and analyzed using AutoML to build and select the most accurate predictive models for each variable of interest. ResultsTherapy change at 24 weeks follow-up was modeled using the extreme gradient boosted trees classifier with early stopping (area under the receiver operating characteristic curve [AUC] of 0.9078 and logarithmic loss [LogLoss] of 0.3955 for the holdout partition). Key influencing factors included the initial systemic therapeutic agent, the Classification Criteria for Psoriatic Arthritis score at baseline, and changes in quality of life. An average blender incorporating three models (gradient boosted trees classifier, ExtraTrees classifier, and Eureqa generalized additive model classifier) with an AUC of 0.8750 and LogLoss of 0.4603 was used to predict therapy changes for 2 hypothetical patients, highlighting the significance of these factors. Treatments such as methotrexate or specific biologicals showed a lower propensity for change. An average blender of a random forest classifier, an extreme gradient boosted trees classifier, and a Eureqa classifier (AUC of 0.9241 and LogLoss of 0.4498) was used to estimate PASI (Psoriasis Area and Severity Index) change after 24 weeks. Primary predictors included the initial PASI score, change in pruritus levels, and change in therapy. A lower initial PASI score and consistently low pruritus were associated with better outcomes. BASDAI classification at onset was analyzed using an average blender of a Eureqa generalized additive model classifier, an extreme gradient boosted trees classifier with early stopping, and a dropout additive regression trees classifier with an AUC of 0.8274 and LogLoss of 0.5037. Influential factors included initial pain, disease activity, and Hospital Anxiety and Depression Scale scores for depression and anxiety. Increased pain, disease activity, and psychological distress generally led to higher BASDAI scores. ConclusionsThe practical implications of these models for clinical decision-making in PsV and PsA can guide early investigation and treatment, contributing to improved patient outcomes.

BackgroundRapid digitalization in health care has led to the adoption of digital technologies; however, limited trust in internet-based health decisions and the need for technical personnel hinder the use of smartphones and machine learning applications. To address this, automated machine learning (AutoML) is a promising tool that can empower health care professionals to enhance the effectiveness of mobile health apps. ObjectiveWe used AutoML to analyze data from clinical studies involving patients with chronic hand and/or foot eczema or psoriasis vulgaris who used a smartphone monitoring app. The analysis focused on itching, pain, Dermatology Life Quality Index (DLQI) development, and app use. MethodsAfter extensive data set preparation, which consisted of combining 3 primary data sets by extracting common features and by computing new features, a new pseudonymized secondary data set with a total of 368 patients was created. Next, multiple machine learning classification models were built during AutoML processing, with the most accurate models ultimately selected for further data set analysis. ResultsItching development for 6 months was accurately modeled using the light gradient boosted trees classifier model (log loss: 0.9302 for validation, 1.0193 for cross-validation, and 0.9167 for holdout). Pain development for 6 months was assessed using the random forest classifier model (log loss: 1.1799 for validation, 1.1561 for cross-validation, and 1.0976 for holdout). Then, the random forest classifier model (log loss: 1.3670 for validation, 1.4354 for cross-validation, and 1.3974 for holdout) was used again to estimate the DLQI development for 6 months. Finally, app use was analyzed using an elastic net blender model (area under the curve: 0.6567 for validation, 0.6207 for cross-validation, and 0.7232 for holdout). Influential feature correlations were identified, including BMI, age, disease activity, DLQI, and Hospital Anxiety and Depression Scale-Anxiety scores at follow-up. App use increased with BMI >35, was less common in patients aged >47 years and those aged 23 to 31 years, and was more common in those with higher disease activity. A Hospital Anxiety and Depression Scale-Anxiety score >8 had a slightly positive effect on app use. ConclusionsThis study provides valuable insights into the relationship between data characteristics and targeted outcomes in patients with chronic eczema or psoriasis, highlighting the potential of smartphone and AutoML techniques in improving chronic disease management and patient care.

Background Rheumatic immune-related adverse events (R-irAEs) occur in 5–15% of patients receiving immune checkpoint inhibitors (ICI) and, unlike other irAEs, tend to be chronic. Herein, we investigate the factors influencing cancer and R-irAEs outcomes with particular focus on adverse effects of anti-inflammatory treatment.Methods In this prospective, multicenter, long-term, observational study, R-irAEs were comprehensively analyzed in patients with malignant melanoma (MM, n=50) and non-small cell lung cancer (NSCLC, n=41) receiving ICI therapy who were enrolled in the study between August 1, 2018, and December 11, 2022.Results After a median follow-up of 33 months, progressive disease or death occurred in 66.0% and 30.0% of MM and 63.4% and 39.0% of patients with NSCLC. Male sex (progression-free survival (PFS): p=0.013, and overall survival (OS): p=0.009), flare of a pre-existing condition (vs de novo R-irAE, PFS: p=0.010) and in trend maximum glucocorticoid (GC) doses >10 mg and particularly ≥1 mg/kg prednisolone equivalent (sex-adjusted PFS: p=0.056, OS: p=0.051) were associated with worse cancer outcomes. Patients receiving disease-modifying antirheumatic drugs (DMARDs) showed significantly longer PFS (n=14, p=0.011) and OS (n=20, p=0.018). Effects of these variables on PFS and/or OS persisted in adjusted Cox regression models. Additionally, GC treatment negatively correlated with the time from diagnosis of malignancy and the latency from ICI start until R-irAE onset (all p

Background: In malignant melanoma, liver metastases significantly reduce survival, even despite highly effective new therapies. Given the increase in metabolic liver diseases such as metabolic dysfunction-associated steatotic liver disease (MASLD) and metabolic dysfunction-associated steatohepatitis (MASH), this study investigated the impact of liver sinusoidal endothelial cell (LSEC)-specific alterations in MASLD/MASH on hepatic melanoma metastasis. Methods: Mice were fed a choline-deficient L-amino acid-defined (CDAA) diet for ten weeks to induce MASH-associated liver fibrosis, or a CDAA diet or a high fat diet (HFD) for shorter periods of time to induce early steatosis-associated alterations. Liver metastasis formation was assessed using melanoma cell lines B16F10Luc2 and Wt31. LSEC-specific GATA4 knockout mice (Gata4LSEC−KO/BL) developing MASH-like liver fibrosis without steatosis via a pathogenic angiocrine switch were included to compare the impact of liver fibrosis versus hepatic steatosis on hepatic melanoma metastasis. Bulk RNA-Seq of isolated LSECs from CDAA-fed and control mice was performed. Levels of adhesion molecules (VCAM1, ICAM1, E-selectin) were monitored, and ICAM1 and VCAM1 antibody therapy was employed. Results: Feeding a CDAA diet, in contrast to a HFD, led to increased metastasis before the development of liver fibrosis. Gata4LSEC−KO/BL mice characterized by vascular changes ensuing perisinusoidal liver fibrosis without steatosis also exhibited increased metastasis. Early molecular alterations in the hepatic vascular niche, rather than fibrosis or steatosis, correlated with metastasis, as shown by LSEC dedifferentiation and upregulation of endothelial adhesion molecules. The metastatic process in CDAA-fed mice was also dependent on the respective melanoma cell lines used and on the route of their metastatic spread. ICAM1 inhibition, but not VCAM1 inhibition reduced melanoma cell retention. Conclusion: We discovered that the hepatic vascular niche acts as a delicate sensor to even short-term nutritional alterations during the development of MASLD/MASH. The dynamic adaptations to the metabolic challenges of developing MASLD/MASH caused an early shift from the normal hepatic vascular niche to a pre-metastatic vascular niche that promoted hepatic melanoma metastasis in the context of cell-autonomous and acquired melanoma cell features. Altogether, our findings provide a potential avenue for angiotargeted therapies to prevent hepatic melanoma metastasis. [ABSTRACT FROM AUTHOR]

Noncommunicable diseases (NCDs) and maternal newborn and child health (MNCH) are two deeply intertwined health areas that have been artificially separated by global health policies, resource allocations and programming. Optimal MNCH care can provide a unique opportunity to screen for, prevent and manage early signs of NCDs developing in both the woman and the neonate. This paper considers how NCDs, NCD modifiable risk factors, and NCD metabolic risk factors impact MNCH. We argue that integrated management is essential, but this faces challenges that manifest across all levels of domestic health systems. Progress toward Sustainable Development targets requires joined-up action.

Abstract Background Cutaneous melanoma exhibits heterogeneous metastatic patterns and prognosis. In this regard, liver metastasis, which is detected in ~ 10–20% of stage 4 patients, came to the fore of melanoma research, as it recently evolved as decisive indicator of treatment resistance to immune checkpoint inhibition. Methods Hepatic metastases were induced by intrasplenic injection of five different murine melanoma cell lines. The efficiencies of hepatic colonization, morphologic patterns, gene expression profiles and degree of vascularization were analyzed and Sorafenib was applied as anti-angiogenic treatment. Results WT31 melanoma showed the highest efficiency of hepatic colonization, while intermediate efficiencies were observed for B16F10 and RET, and low efficiencies for D4M and HCmel12. RNAseq-based gene expression profiles of high and intermediate metastatic melanomas in comparison to low metastatic melanomas indicated that this efficiency predominantly associates with gene clusters involved in cell migration and angiogenesis. Indeed, heterogeneous vascularization patterns were found in the five models. Although the degree of vascularization of WT31 and B16F10 metastases differed, both showed a strong response to Sorafenib with a successful abrogation of the vascularization. Conclusion Our data indicate that molecular heterogeneity of melanomas can be associated with phenotypic and prognostic features of hepatic metastasis paving the way for organ-specific anti-angiogenic therapeutic approaches.

Niche crosstalk with Haematopoietic cells underlies normal haematopoiesis and myeloid disorders. Here the authors report a Stabilin2-Cre driver mouse with Cre-activity restricted to bone marrow sinusoidal endothelial cells, and that Stabilin2-Cre driven overactivation of b-catenin leads to erythroid differentiation defects and anaemia.

Background: The COVID-19 pandemic severely impacted healthcare systems, affecting patient outcomes and resource allocation. This study applied automated machine learning (AutoML) to analyze key health outputs, such as discharge conditions, mortality, and COVID-19 cases, with the goal of improving responses to future crises. Methods: AutoML was used to train and validate models on an ICD-10 dataset covering the first wave of COVID-19 in Romania (January–September 2020). Results: For discharge outcomes, Light Gradient Boosted models achieved an F1 score of 0.9644, while for mortality 0.7545 was reached. A Generalized Linear Model blender achieved an F1 score of 0.9884 for "acute or emergency" cases, and an average blender reached 0.923 for COVID-19 cases. Older age, specific hospitals, and oncology wards were less associated with improved recovery rates, while mortality was linked to abnormal lab results and cardiovascular/respiratory diseases. Patients admitted without referral, or patients in hospitals in the central region and the capital region of Romania were more likely to be acute cases. Finally, counties such as Argeş (South-Muntenia) and Brașov (Center) showed higher COVID-19 infection rates regardless of age. Conclusions: AutoML provided valuable insights into patient outcomes, highlighting variations in care and the need for targeted health strategies for both COVID-19 and other health challenges. [ABSTRACT FROM AUTHOR]

BackgroundPsoriasis is a chronic inflammatory skin disease. The visibility of erythematous plaques on the skin as well as the pain and itchiness caused by the skin lesions frequently leads to psychological distress in patients. Smartphone apps are widespread and easily accessible. Earlier studies have shown that apps can effectively complement current management strategies for patients with psoriasis. However, no analysis of such apps has been published to date. ObjectiveThe aim of this study is to systematically identify and objectively assess the quality of current publicly available German apps for patients with psoriasis using the Mobile Application Rating Scale (MARS) and compile brief ready-to-use app descriptions. MethodsWe conducted a systematic search and assessment of German apps for patients with psoriasis available in the Google Play Store and Apple App Store. The identified apps were randomly assigned to 1 of 3 reviewers, who independently rated them using the German MARS (MARS-G). The MARS-G includes 15 items from 4 different sections (engagement, functionality, aesthetics, and information) to create an overall mean score for every app. Scores can range from 1 for the lowest-quality apps to 5 for the highest-quality apps. Apps were ranked according to their mean MARS-G rating, and the highest-ranked app was evaluated independently by 2 patients with psoriasis using the user version of the MARS-G (uMARS-G). Furthermore, app information, including origin, main function, and technical aspects, was compiled into a brief overview. ResultsIn total, we were able to identify 95 unique apps for psoriasis, of which 15 were available in both app stores. Of these apps, 5 were not specifically intended for patients with psoriasis, 1 was designed for clinical trials only, and 1 was no longer available at the time the evaluation process began. Consequently, the remaining 8 apps were included in the final evaluation. The mean MARS-G scores ranged from 3.51 to 4.18. The app with the highest mean MARS-G score was Psoriasis Helferin (4.18/5.00). When rated by patients, however, the app was rated lower in all subcategories, resulting in a mean uMARS-G score of 3.48. Most apps had a commercial background and a focus on symptom tracking. However, only a fraction of the apps assessed used validated instruments to measure the user’s disease activity. ConclusionsApp quality was heterogeneous, and only a minority of the identified apps were available in both app stores. When evaluated by patients, app ratings were lower than when evaluated by health care professionals. This discrepancy highlights the importance of involving patients when developing and evaluating health-related apps as the factors that make an app appealing to users may differ between these 2 groups. Trial RegistrationDeutsches Register Klinischer Studien DRKS00020963; https://tinyurl.com/ye98an5b

The epidemiology of neglected tropical diseases (NTD) is persistently underprioritized, despite NTD being widespread among the poorest populations and in the least developed countries on earth. This situation necessitates thorough and efficient public health intervention. Romania is at the brink of becoming a developed country. However, this South-Eastern European country appears to be a region that is susceptible to an underestimated burden of parasitic diseases despite recent public health reforms. Moreover, there is an evident lack of new epidemiologic data on NTD after Romania’s accession to the European Union (EU) in 2007. Using the national ICD-10 dataset for hospitalized patients in Romania, we generated time series datasets for 2008–2018. The objective was to gain deep understanding of the epidemiological distribution of three selected and highly endemic parasitic diseases, namely, ascariasis, enterobiasis and cystic echinococcosis (CE), during this period and forecast their courses for the ensuing two years. Through descriptive and inferential analysis, we observed a decline in case numbers for all three NTD. Several distributional particularities at regional level emerged. Furthermore, we performed predictions using a novel automated time series (AutoTS) machine learning tool and could interestingly show a stable course for these parasitic NTD. Such predictions can help public health officials and medical organizations to implement targeted disease prevention and control. To our knowledge, this is the first study involving a retrospective analysis of ascariasis, enterobiasis and CE on a nationwide scale in Romania. It is also the first to use AutoTS technology for parasitic NTD. Author summary Eastern and South-Eastern Europe is known to be severely affected by parasitic neglected tropical diseases (NTD) due to its tumultuous historical events of the past decades and to its uncontrolled socio-economic fluctuations. Romania is an example of such a South-Eastern European country that was known to have a high parasitic NTD burden after the fall of Communism in 1989 but has since made significant developmental improvements. However, there is scarce data regarding the incidences of parasitic NTD in Romania after its accession to the European Union in 2007. By using the ICD-10 dataset of Romania over the period 2008–2018, we performed a retrospective epidemiologic analysis of three of its most relevant parasitic diseases, ascariasis, enterobiasis and cystic echinococcosis (CE) and confirmed a downward trend strongly correlating with the country’s decreasing poverty rate. By employing a novel technology called automated time series machine learning we predicted the progress of these diseases for the ensuing two years of 2019 and 2020. Forecasted rates were observed to be constant. Such machine learning tools can help public health officials in adapting and improving targeted measures to combat parasitic NTD.

Endothelial wingless-related integration site (Wnt)-/β-catenin signaling is a key regulator of the tightly sealed blood–brain barrier. In the hepatic vascular niche angiokine-mediated Wnt signaling was recently identified as an important regulator of hepatocyte function, including the determination of final adult liver size, liver regeneration, and metabolic liver zonation. Within the hepatic vasculature, the liver sinusoidal endothelial cells (LSECs) are morphologically unique and functionally specialized microvascular endothelial cells (ECs). Pathological changes of LSECs are involved in chronic liver diseases, hepatocarcinogenesis, and liver metastasis. To comprehensively analyze the effects of endothelial Wnt-/β-catenin signaling in the liver, we used endothelial subtype-specific Clec4g-iCre mice to generate hepatic ECs with overexpression of Ctnnb1. In the resultant Clec4g-iCretg/wt;Ctnnb1(Ex3)fl/wt (Ctnnb1OE−EC) mice, activation of endothelial Wnt-/β-catenin signaling resulted in sinusoidal transdifferentiation with disturbed endothelial zonation, that is, loss of midzonal LSEC marker lymphatic vessel endothelial hyaluronic acid receptor 1 (Lyve1) and enrichment of continuous EC genes, such as cluster of differentiation (CD)34 and Apln. Notably, gene set enrichment analysis revealed overrepresentation of brain endothelial transcripts. Activation of endothelial Wnt-/β-catenin signaling did not induce liver fibrosis or alter metabolic liver zonation, but Ctnnb1OE−EC mice exhibited significantly increased plasma triglyceride concentrations, while liver lipid content was slightly reduced. Ctnnb1 overexpression in arterial ECs of the heart has been reported previously to cause cardiomyopathy. As Clec4g-iCre is active in a subset of cardiac ECs, it was not unexpected that Ctnnb1OE−EC mice showed reduced overall survival and cardiac dysfunction. Altogether, balanced endothelial Wnt-/β-catenin signaling in the liver is required for normal LSEC differentiation and for maintenance of normal plasma triglyceride levels.

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Two novel body/face wash gels enriched with emollient ingredients (including dexpanthenol) were developed for the daily care of dry skin. Two similarly designed 2-week studies (N = 42 each) were conducted to assess the biophysical and cosmetic performance of each of the new wash gels in healthy adults with dry skin. Instrumental measurements quantified the effects of the wash gels on stratum corneum (SC) hydration and transepidermal water loss (TEWL) (with and without a previous sodium lauryl sulfate (SLS) challenge) after single and repeated usage. Following single and repeated applications of the face wash gel to facial skin, as well as to dry SLS-undamaged and SLS-damaged skin of the forearm, skin hydration significantly increased. Similarly, after single and repeated usage of the body wash gel to dry SLS-undamaged and SLS-damaged skin of the forearm, skin moisturization increased significantly from baseline; comparisons with control areas provided inconsistent results for SLS-undamaged skin. No effects on TEWL were observed for either product. Both wash gels were well tolerated and the cosmetic performances were appreciated by the subjects. The study results suggest that daily use of the new wash gels was associated with significant skin-moisturizing effects without adversely affecting skin barrier function and repair.

Three studies were conducted with three new dexpanthenol-containing emollients containing increasing lipid contents (Emollients 1–3) to assess their performances in healthy adults with dry skin. All three studies (N = 42 each) followed virtually the same design. A single skin application of the study product was performed followed by once-daily usage. Skin hydration, transepidermal water loss (TEWL), skin biomechanical properties, and lipid content of the stratum corneum (SC) were regularly assessed over the 28-day study period; a subset (N = 22) underwent a sodium lauryl sulfate (SLS) challenge prior to product application. All three emollients were well tolerated and showed good performances with only minor differences in instrumental measurements. After single and prolonged once-daily applications of Emollients 1–3 to dry skin and dry SLS-damaged skin, skin hydration significantly increased from baseline (BL) (by 38.1–72.4% in unchallenged skin, p < 0.001 for all three). This was paralleled by significant increases in skin elasticity parameters. Usage of Emollients 1 and 3 caused increases from BL in SC cholesterol (by 9.8–12.5%, p < 0.05 for both) and SC free fatty acid levels (by 3.7–26.3%, p < 0.05 for both) at the end of the study. No sustained effects on TEWL were recorded. Our findings support the once-daily use of all three emollients in adults with dry skin.

Introduction Endothelial cells (ECs) line the inside of all blood vessels, forming a structurally and functionally heterogeneous cell population (1, 2). The diversity of ECs along the segments of the [...], Microvascular endothelial cells (ECs) are increasingly recognized as organ-specific gatekeepers of their microenvironment. Microvascular ECs instruct neighboring cells in their organ-specific vascular niches through angiocrine factors, which include secreted growth factors (angiokines), extracellular matrix molecules, and transmembrane proteins. However, the molecular regulators that drive organ-specific microvascular transcriptional programs and thereby regulate angiodiversity are largely elusive. In contrast to other ECs, which form a continuous cell layer, liver sinusoidal ECs (LSECs) constitute discontinuous, permeable microvessels. Here, we have shown that the transcription factor GATA4 controls murine LSEC specification and function. LSEC-restricted deletion of Gata4 caused transformation of discontinuous liver sinusoids into continuous capillaries. Capillarization was characterized by ectopic basement membrane deposition, formation of a continuous EC layer, and increased expression of VE-cadherin. Correspondingly, ectopic expression of GATA4 in cultured continuous ECs mediated the downregulation of continuous EC-associated transcripts and upregulation of LSEC-associated genes. The switch from discontinuous LSECs to continuous ECs during embryogenesis caused liver hypoplasia, fibrosis, and impaired colonization by hematopoietic progenitor cells, resulting in anemia and embryonic lethality. Thus, GATA4 acts as master regulator of hepatic microvascular specification and acquisition of organ-specific vascular competence, which are indispensable for liver development. The data also establish an essential role of the hepatic microvasculature in embryonic hematopoiesis.