ALK1 controls hepatic vessel formation, angiodiversity, and angiocrine functions in hereditary hemorrhagic telangiectasia of the liver.

BACKGROUND AND AIMS: In hereditary hemorrhagic telangiectasia (HHT), severe liver vascular malformations are associated with mutations in the Activin A Receptor-Like Type 1 ( ACVRL1 ) gene encoding ALK1, the receptor for bone morphogenetic protein (BMP) 9/BMP10, which regulates blood vessel development. Here, we established an HHT mouse model with exclusive liver involvement and adequate life expectancy to investigate ALK1 signaling in liver vessel formation and metabolic function. APPROACH AND RESULTS: Liver sinusoidal endothelial cell (LSEC)-selective Cre deleter line, Stab2-iCreF3 , was crossed with Acvrl1 -floxed mice to generate LSEC-specific Acvrl1 -deficient mice ( Alk1HEC-KO ). Alk1HEC-KO mice revealed hepatic vascular malformations and increased posthepatic flow, causing right ventricular volume overload. Transcriptomic analyses demonstrated induction of proangiogenic/tip cell gene sets and arterialization of hepatic vessels at the expense of LSEC and central venous identities. Loss of LSEC angiokines Wnt2 , Wnt9b , and R-spondin-3 ( Rspo3 ) led to disruption of metabolic liver zonation in Alk1HEC-KO mice and in liver specimens of patients with HHT. Furthermore, prion-like protein doppel ( Prnd ) and placental growth factor ( Pgf ) were upregulated in Alk1HEC-KO hepatic endothelial cells, representing candidates driving the organ-specific pathogenesis of HHT. In LSEC in vitro , stimulation or inhibition of ALK1 signaling counter-regulated Inhibitors of DNA binding (ID)1-3, known Alk1 transcriptional targets. Stimulation of ALK1 signaling and inhibition of ID1-3 function confirmed regulation of Wnt2 and Rspo3 by the BMP9/ALK1/ID axis. CONCLUSIONS: Hepatic endothelial ALK1 signaling protects from development of vascular malformations preserving organ-specific endothelial differentiation and angiocrine signaling. The long-term surviving Alk1HEC-KO HHT model offers opportunities to develop targeted therapies for this severe disease.

Automated Machine Learning Analysis of Patients With Chronic Skin Disease Using a Medical Smartphone App: Retrospective Study.

BACKGROUND: Rapid 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. OBJECTIVE: We 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. METHODS: After 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. RESULTS: Itching 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. CONCLUSIONS: This 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.

Cutaneous leukocytoclastic vasculitis after second dose of mRNA COVID-19 vaccine.

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.

Angiocrine Hepatocyte Growth Factor Signaling Controls Physiological Organ and Body Size and Dynamic Hepatocyte Proliferation to Prevent Liver Damage during Regeneration.

Liver sinusoidal endothelial cells (LSECs) control organ functions, metabolism, and development through the secretion of angiokines. LSECs express hepatocyte growth factor (Hgf), which is involved in prenatal development, metabolic homeostasis, and liver regeneration. This study aimed to elucidate the precise contribution of LSEC-derived Hgf in physiological homeostasis and liver regeneration. Stab2-iCretg/wt;Hgffl/fl (HgfΔLSEC) mice were generated to abrogate Hgf expression selectively in LSECs from early fetal development onwards, to study global development, metabolic and endothelial zonation, and organ functions as well as liver regeneration in response to 70% partial hepatectomy (PH). Although zonation and liver/body weight ratios were not altered, total body weight and total liver weight were reduced in HgfΔLSEC. Necrotic organ damage was more marked in HgfΔLSEC mice, and regeneration was delayed 72 hours after PH. This was associated with decreased hepatocyte proliferation at 48 hours after PH. Molecularly, HgfΔLSEC mice showed down-regulation of Hgf/c-Met signaling and decreased expression of Deptor in hepatocytes. In vitro knockdown of Deptor was associated with decreased proliferation. Therefore, angiocrine Hgf controls hepatocyte proliferation and susceptibility to necrosis after partial hepatectomy via the Hgf/c-Met axis involving Deptor to prevent excessive organ damage.

Angiocrine Wnt signaling controls liver growth and metabolic maturation in mice.

Postnatal liver development is characterized by hepatocyte growth, proliferation, and functional maturation. Notably, canonical Wnt signaling in hepatocytes has been identified as an important regulator of final adult liver size and metabolic liver zonation. The cellular origin of Wnt ligands responsible for homeostatic liver/body weight ratio (LW/BW) remained unclear, which was also attributable to a lack of suitable endothelial Cre driver mice. To comprehensively analyze the effects of hepatic angiocrine Wnt signaling on liver development and metabolic functions, we used endothelial subtype-specific Stab2-Cre driver mice to delete Wls from hepatic endothelial cells (HECs). The resultant Stab2-Cretg/wt ;Wlsfl/fl (Wls-HECKO) mice were viable, but showed a significantly reduced LW/BW. Specifically, ablation of angiocrine Wnt signaling impaired metabolic zonation in the liver, as shown by loss of pericentral, ß-catenin-dependent target genes such as glutamine synthase (Glul), RhBg, Axin2, and cytochrome P450 2E1, as well as by extended expression of periportal genes such as arginase 1. Furthermore, endothelial subtype-specific expression of a c-terminally YFP-tagged Wls fusion protein in Wls-HECKO mice (Stab2-Cretg/wt ;Wlsfl/fl ;Rosa26:Wls-YFPfl/wt [Wls-rescue]) restored metabolic liver zonation. Interestingly, lipid metabolism was altered in Wls-HECKO mice exhibiting significantly reduced plasma cholesterol levels, while maintaining normal plasma triglyceride and blood glucose concentrations. On the contrary, zonal expression of Endomucin, LYVE1, and other markers of HEC heterogeneity were not altered in Wls-HECKO livers. CONCLUSION: Angiocrine Wnt signaling controls liver growth as well as development of metabolic liver zonation in mice, whereas intrahepatic HEC zonation is not affected. (Hepatology 2017).

Angiocrine Bmp2 signaling in murine liver controls normal iron homeostasis.

Microvascular endothelial cells (ECs) display a high degree of phenotypic and functional heterogeneity among different organs. Organ-specific ECs control their tissue microenvironment by angiocrine factors in health and disease. Liver sinusoidal endothelial cells (LSECs) are uniquely differentiated to fulfill important organ-specific functions in development, under homeostatic conditions, and in regeneration and liver pathology. Recently, Bmp2 has been identified by us as an organ-specific angiokine derived from LSECs. To study angiocrine Bmp2 signaling in the liver, we conditionally deleted Bmp2 in LSECs using EC subtype-specific Stab2-Cre mice. Genetic inactivation of hepatic angiocrine Bmp2 signaling in Stab2-Cre;Bmp2fl/fl (Bmp2LSECKO) mice caused massive iron overload in the liver and increased serum iron levels and iron deposition in several organs similar to classic hereditary hemochromatosis. Iron overload was mediated by decreased hepatic expression of hepcidin, a key regulator of iron homeostasis. Thus, angiocrine Bmp2 signaling within the hepatic vascular niche represents a constitutive pathway indispensable for iron homeostasis in vivo that is nonredundant with Bmp6. Notably, we demonstrate that organ-specific angiocrine signaling is essential not only for the homeostasis of the respective organ but also for the homeostasis of the whole organism.

Implementing the Code of Practice on International Recruitment in Romania - exploring the current state of implementation and what Romania is doing to retain its domestic health workforce.

BACKGROUND: The Romanian health system is struggling to retain its health workers, who are currently facing strong incentives for migration to Western European health systems. Retention issues, coupled with high levels of migration, complicate Romania's efforts in providing basic health services for rural, underserved, and marginalized populations, as well as in achieving equitable health access for all. The WHO Global Code of Practice on International Recruitment of Health Personnel (the Code) aims to promote ethical international recruitment and health systems strengthening. We explore Romania's implementation of the Code's principles and recommendations. METHODS: We analysed peer-reviewed and grey literature, in English and Romanian, and sought secondary data from the websites of Romania's largest medical universities. The analysis was guided by the following themes and recommendations in the Code: health personnel development and health systems sustainability, international cooperation, data gathering, information exchange, and implementation and monitoring of the Code. RESULTS: Romania's implementation of the Code was observed to be limited. Gaps were identified with regards to several aspects of the Romanian health system, including the lack of support to health personnel training, recruitment, and retention in order to increase the appeal for health providers to practice in Romania and in underserved areas. In terms of international cooperation, the Code recommends various policy instruments to guide recruitment, including bilateral agreements. However, we could not determine which of these instruments were used as a result of the Code and whether or not they were effective. We identified little evidence of initiatives for health workers' professional and personal support. Insufficient data and few information exchange platforms exist on health workforce issues, hindering active sharing of data on migration with European Union and WHO audiences. We could not identify any evidence of monitoring of the Code's implementation to date. CONCLUSIONS: In the absence of major system reforms, health workers will continue to migrate to urban areas and abroad. Romanian policymakers should address more of the Code's recommendations by developing a national policy for human resources for health, a central database to aid health workforce planning and management, stronger platforms for information exchange and civil society engagement, and updated and transparent bilateral agreements.

[Benefits of participatory involvement of patients in the development of a dermatological treatment app-A report from the practice]. / Nutzen der partizipatorischen Mitwirkung von PatientInnen an der Entwicklung einer dermatologischen Therapie-App ­ ein Bericht aus der Praxis.

Approximately 2% of the German population suffer from psoriasis. HybridVITA has developed a mobile application (app) that enables psoriasis patients to independently document the progression of the disease and the current psychological stress at home. The HybridVITA app was created in close collaboration with user groups to ensure optimal adaptation to their needs. Two interactive workshops were held with the user groups and the technical developers of the app as a core element of the developmental process. The workshops identified the needs and suggestions for improvement of the various user groups and formulated user stories for the further development of the app using the Scrum method. The participatory approach of the workshop enabled the project team to gather valuable practical knowledge at an early stage of development. The team's awareness of potential obstacles during the early stages of the project enabled them to proactively identify and address these issues prior to implementing the app in dermatological care. We are confident that a patient-centered and participatory approach to health app development can provide valuable insights for developers.

Using Automated Machine Learning to Predict Necessary Upcoming Therapy Changes in Patients With Psoriasis Vulgaris and Psoriatic Arthritis and Uncover New Influences on Disease Progression: Retrospective Study.

BACKGROUND: Psoriasis 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. OBJECTIVE: This 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. METHODS: Clinical 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. RESULTS: Therapy 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. CONCLUSIONS: The practical implications of these models for clinical decision-making in PsV and PsA can guide early investigation and treatment, contributing to improved patient outcomes.