Dclk1 Defines Quiescent Pancreatic Progenitors that Promote Injury-Induced Regeneration and Tumorigenesis

The existence of adult pancreatic progenitor cells has been debated. While some favor the concept of facultative progenitors involved in homeostasis and repair, neither a location nor markers for such cells have been defined. Using genetic lineage tracing, we show that Doublecortin-like kinase-1 (Dclk1) labels a rare population of long-lived, quiescent pancreatic cells. In vitro, Dclk1+ cells proliferate readily and sustain pancreatic organoid growth. In vivo, Dclk1+ cells are necessary for pancreatic regeneration following injury and chronic inflammation. Accordingly, their loss has detrimental effects after cerulein-induced pancreatitis. Expression of mutant Kras in Dclk1+ cells does not affect their quiescence or longevity. However, experimental pancreatitis converts Kras mutant Dclk1+ cells into potent cancer-initiating cells. As a potential effector of Kras, Dclk1 contributes functionally to the pathogenesis of pancreatic cancer. Taken together, these observations indicate that Dclk1 marks quiescent pancreatic progenitors that are candidates for the origin of pancreatic cancer

Bone Marrow Myeloid Cells Regulate Myeloid-Biased Hematopoietic Stem Cells via a Histamine-Dependent Feedback Loop

Myeloid-biased hematopoietic stem cells (MB-HSCs) play critical roles in recovery from injury, but little is known about how they are regulated within the bone marrow niche. Here we describe an auto-/paracrine physiologic circuit that controls quiescence of MB-HSCs and hematopoietic progenitors marked by histidine decarboxylase (Hdc). Committed Hdc+ myeloid cells lie in close anatomical proximity to MB-HSCs and produce histamine, which activates the H2 receptor on MB-HSCs to promote their quiescence and self-renewal. Depleting histamine-producing cells enforces cell cycle entry, induces loss of serial transplant capacity, and sensitizes animals to chemotherapeutic injury. Increasing demand for myeloid cells via lipopolysaccharide (LPS) treatment specifically recruits MB-HSCs and progenitors into the cell cycle; cycling MB-HSCs fail to revert into quiescence in the absence of histamine feedback, leading to their depletion, while an H2 agonist protects MB-HSCs from depletion after sepsis. Thus, histamine couples lineage-specific physiological demands to intrinsically primed MB-HSCs to enforce homeostasis. Chen et al. show that histidine decarboxylase (Hdc) marks quiescent myeloid-biased HSCs (MB-HSCs). Daughter myeloid cells form a spatial cluster with Hdc+ MB-HSCs and secrete histamine to enforce their quiescence and protect them from depletion, following activation by a variety of physiologic insults

Christliche Wandmalereien in Syrien. Qara und das Kloster Mar Yakub

Die in den letzten Jahren intensivierte Erforschung der mittelalterlichen Malerei im Christlichen Orient wird durch den angekündigten Band um eine beachtliche Reihe von Wandbildern bereichert, die erst jüngst im Rahmen von Restaurierungsarbeiten und Ausgrabungen zu Tage kamen. Der Schwerpunkt liegt mit dem Jakobskloster bei Qara und der Eliasgrotte von Macarrat Saydanaya auf dem Qalamungebirge nördlich von Damaskus, der Horizont ist mit dem Kastron von Androna aber bis in das syrische Steppengebiet östlich von Hama gesteckt. Neben einer ausführlichen Dokumentation behandeln die kunsthistorischen Beiträge auch den künstlerischen Austausch Syriens mit Zypern und die Ausbildung eines syrischen Regionalstils um das Jahr 1200. Vorangestellt ist ein historischer Abriß der Ortschaft Qara, die bis 1266 rein melkitisch war. Weitere Beiträge sind der Restaurierung und der chemischen Probenanlayse der Wandmalereien sowie der syrischen und griechischen Epigraphik gewidmet

Liver fat accumulation after islet transplantation and graft survival

Our objective is to evaluate if there is an association between liver fat accumulation after islet transplantation (ITx) and graft survival. A cohort study was conducted in 34 subjects with type 1 diabetes postallogeneic ITx. Liver fat content was evaluated by magnetic resonance imaging (MRI) (change in liver signal intensity on inphase and opposed-phase images). Kaplan–Meier curves and Cox regression analysis were performed with islet dysfunction duration as the dependent variable and fat liver content as an independent one. Values of p < 0.05 were significant (SSPS®18.0 and MedCalc®12.5). Patients’ mean age was 40 ± 8 years (diabetes duration: 31 ± 12 years; male: 41%). Islet survival did not differ in patients without (51 months, 95% CI 40–62 months) or with steatosis (48 months, 95% CI 38–58 months; p = 0.55) during islet dysfunction period. Nevertheless, survival curves appear to separate late in the follow-up, and after 40 months steatosis was associated with shorter graft survival (p log rank = 0.049). This association remained (RR 23.5, 95% CI 1.1–516.0; p = 0.045) after adjustments for possible confounding factors. In this sample of subjects with type 1 diabetes submitted to ITx, steatosis was not associated with islet failure in the whole cohort. However, in subjects with functional islets after 40 months, a shorter graft survival was observed in those with steatosis during the islet dysfunction period, even after adjustments to variables known to be associated with islet failure

Liver fat accumulation after islet transplantation and graft survival

Our objective is to evaluate if there is an association between liver fat accumulation after islet transplantation (ITx) and graft survival. A cohort study was conducted in 34 subjects with type 1 diabetes postallogeneic ITx. Liver fat content was evaluated by magnetic resonance imaging (MRI) (change in liver signal intensity on inphase and opposed-phase images). Kaplan–Meier curves and Cox regression analysis were performed with islet dysfunction duration as the dependent variable and fat liver content as an independent one. Values of p < 0.05 were significant (SSPS®18.0 and MedCalc®12.5). Patients’ mean age was 40 ± 8 years (diabetes duration: 31 ± 12 years; male: 41%). Islet survival did not differ in patients without (51 months, 95% CI 40–62 months) or with steatosis (48 months, 95% CI 38–58 months; p = 0.55) during islet dysfunction period. Nevertheless, survival curves appear to separate late in the follow-up, and after 40 months steatosis was associated with shorter graft survival (p log rank = 0.049). This association remained (RR 23.5, 95% CI 1.1–516.0; p = 0.045) after adjustments for possible confounding factors. In this sample of subjects with type 1 diabetes submitted to ITx, steatosis was not associated with islet failure in the whole cohort. However, in subjects with functional islets after 40 months, a shorter graft survival was observed in those with steatosis during the islet dysfunction period, even after adjustments to variables known to be associated with islet failure

PLA-Abfälle im Abfallstrom

Biobased plastics are now being used more and more frequently, especially in packaging. Waste disposal providers and their established recycling systems face new challenges. Many of them fear that bio-based plastics disrupt the traditional waste and disposal pathways. In order to investigate to what extent bio-plastics can be recycled in the established plastic recycling system, the Federal Ministry of Food and Agriculture (BMEL) funded, through its project executing agency, agency of renewable resources e. V. (FNR), a collaborative project. The project partners have dealt with the mechanical (mechanical, physical) and feedstock (chemical) recycling of packaging from the biobased plastic polylactic acid (PLA). The focus was on both industrial and post-consumer waste. PLA is one of the most chemically novel bioplastics and is often used in the packaging sector. In terms of recycling, however, there are still great precautions that it could disrupt conventional disposal flows. Following the completion of the research project, the project partners have presented recommendations for the waste management of bio-based plastics in the form of a result paper, which is printed below. The detailed study entitled „Sustainable recycling strategies for products and waste from bio-based plastics“ will be published in the form of a final report. Further information on the project can also be found at: www.fnr.de/projektfoerderung/projekte-und-ergebnisse/projektverzeichnis under the project numbers: 22010814, 22031812, 22019212, 22031312, 22012414

Machine learning using the extreme gradient boosting (XGBoost) algorithm predicts 5-day delta of SOFA score at ICU admission in COVID-19 patients

Background: Accurate risk stratification of critically ill patients with coronavirus disease 2019 (COVID-19) is essential for optimizing resource allocation, delivering targeted interventions, and maximizing patient survival probability. Machine learning (ML) techniques are attracting increased interest for the development of prediction models as they excel in the analysis of complex signals in data-rich environments such as critical care. Methods: We retrieved data on patients with COVID-19 admitted to an intensive care unit (ICU) between March and October 2020 from the RIsk Stratification in COVID-19 patients in the Intensive Care Unit (RISC-19-ICU) registry. We applied the Extreme Gradient Boosting (XGBoost) algorithm to the data to predict as a binary out- come the increase or decrease in patients’ Sequential Organ Failure Assessment (SOFA) score on day 5 after ICU admission. The model was iteratively cross-validated in different subsets of the study cohort. Results: The final study population consisted of 675 patients. The XGBoost model correctly predicted a decrease in SOFA score in 320/385 (83%) critically ill COVID-19 patients, and an increase in the score in 210/290 (72%) patients. The area under the mean receiver operating characteristic curve for XGBoost was significantly higher than that for the logistic regression model (0.86 vs . 0.69, P < 0.01 [paired t -test with 95% confidence interval]). Conclusions: The XGBoost model predicted the change in SOFA score in critically ill COVID-19 patients admitted to the ICU and can guide clinical decision support systems (CDSSs) aimed at optimizing available resources