Uncertainties in the Quantification of Aerosol-Cloud Interactions

Aerosole dienen als Kondensationskerne (CCN) und verändern die Wolkentropfenkonzentration (Nd) und weitere Wolkeneigenschaften. Nd ist daher ein Schlüsselparameter von Aerosol-Wolken-Wechselwirkungen (ACI). ACI sind bezüglich ihrer Klimarelevanz nur unzureichend bestimmt. ACI wurden auf verschiedenen Skalen und mit unterschiedlichen Methoden von unterschiedlichen Perspektiven aus untersucht, was zu einer großen Variabilität von ACI Metriken in der Literatur führt. Für eine genauere Quantifizierung von ACI, wurden in dieser Arbeit damit verbundene, entscheidende Unsicherheiten diskutiert, u.a. das Einmischen trockener Luft, Unsicherheiten von Retrieval-Methoden und die Konsistenz von Schlüsselparametern auf verschiedenen Skalen. Um Nd und weitere Wolkeneigenschaften aus passiven Satellitenbeobachtungen für Flüssigwasserwolken abzuleiten, wird oft das adiabatische Modell herangezogen. Es wurde untersucht, inwiefern dieses Modell reale Bedingungen wiedergibt. Es wurde gezeigt, dass Wolken typischerweise subadiabatisch sind, mit stark reduziertem Flüssigwassergehalt nahe der Wolkenoberkante. Der Einmischprozess variiert zeitlich stark und erschwert die Quantizierung von ACI. Für unterschiedliche Cloudnet-Stationen variieren die Medianwerte des subadiabatischen Faktors von 0.35+/-0.12 bis 0.48+/-0.22. Dieser hängt stark von der geometrischen Wolkendicke ab, wobei dickere Wolken subadiabatischer sind. Die Ableitung von Nd aus bodenbasierten Radar-Radiometer-Beobachtungen ist sehr sensitiv gegenüber a-priori Annahmen. Um zusätzliche Beobachtungen und Unsicherheiten berücksichtigen zu können, wurde ein neuartiges Optimal Estimation (OE) Retrieval entwickelt und mittels synthetischer Wolkenprofile evaluiert. Mittels einer Sensitivitätsstudie konnte die Verbesserung der Retrieval-Genauigkeit für die OE Methode gezeigt werden, wenn die Beobachtungen der optischen Dicke mit berücksichtigt werden. Die Annahme einer typischen Breite der Tropfengrößenverteilung ist dabei eine der größten Unsicherheiten von Nd (Unsicherheit für die OE Methode etwa 150%, für die Radar-Radiometer-Methode etwa 200%). Desweiteren wurden aus unterschiedlichen Perspektiven abgeleitete wolkenmikrophysikalische Größen hinsichtlich ihrer Konsistenz untersucht. Beim Vergleich von Nd und des Effektivradius (re) vom bodengebundenen Retrieval mit in-situ Beobachtungen für einen Falltag wurde eine gute Übereinstimmung gefunden. Beim Vergleich der von SEVIRI und Bodenstationen abgeleiteten Wolkeneigenschaften haben sich mittlere quadratische Abweichungen des Flüssigwasserpfads und der optischen Dicke von jeweils 65 gm2 und 14 ohne signifikanten Bias gezeigt. Damit zeigt sich SEVIRI für großskalige, statistische ACI-Untersuchungen repräsentativ zur Bodenperspektive. Für individuelle Falltage traten jedoch teils größere Unterschiede auf, welche durch Inhomogenitäten und Auflösungseffekte erklärt werden können. Mit SEVIRI Beobachtungen und aus der MACC Reanalyse abgeleiteten CCN Konzentrationen wurde eine Quantifizierung von ACI für das Jahr 2012 durchgeführt. Dabei wurde für Europa ein deutlicher, mikrophysikalischer Effekt gefunden, d.h. eine Abnahme von re und eine Zunahme von Nd mit zunehmender CCN Konzentration. Im Gegensatz dazu wurde für die Wolkenalbedo kein eindeutiger Anstieg mit der CCN-Konzentration gefunden. Verwendet man die Aerosol-optische Dicke (AOD) anstelle der CCN-Konzentration, sind die Werte der ACI Metrik nur halb so groß. Dieses Ergebnis deutet darauf hin, dass die AOD kein optimaler CCN-Proxy ist

Influence of ZDDP Tribofilm on Micropitting Formation and Progression

This paper presents insights into how Zinc Dialkyl Dithiophosphate (ZDDP) influences the formation and progression of micropitting. Experimental investigations were conducted using a twin-disc tribometer in rolling-sliding contacts under mixed or boundary lubrication conditions, focusing on the impact of ZDDP on micropitting in bearing steel samples. Results show that ZDDP reduces wear and increases surface friction by forming a tribofilm. This facilitates micropitting formation, but also retards the progression of micropitting. It highlights that understanding the chemical and mechanical interactions at the tribological interface is essential for designing effective mitigation strategies for managing micropitting and avoiding related issues in bearing applications

Structural Modification of the Natural Product Valerenic Acid Tunes RXR Homodimer Agonism

Retinoid X receptors (RXR) are ligand-sensing transcription factors with a unique role in nuclear receptor signaling as universal heterodimer partners. RXR modulation holds potential in cancer, neurodegeneration and metabolic diseases but adverse effects of RXR activation and lack of selective modulators prevent further exploration as therapeutic target. The natural product valerenic acid has been discovered as RXR agonist with unprecedented preference for RXR subtype and homodimer activation. To capture structural determinants of this activity profile and identify potential for optimization, we have studied effects of structural modification of the natural product on RXR modulation and identified an analogue with enhanced RXR homodimer agonism

Publisher Correction: Scaffold hopping from natural products to synthetic mimetics by holistic molecular similarity

n/

Development of Light‐Activated LXR Agonists

Activation of the oxysterol-sensing transcription factor liver X receptor (LXR) has been studied as a therapeutic strategy in metabolic diseases and cancer but is compromised by the side effects of LXR agonists. Local LXR activation in cancer treatment may offer an opportunity to overcome this issue suggesting potential uses of photopharmacology. We report the computer-aided development of photoswitchable LXR agonists based on the T0901317 scaffold, which is a known LXR agonist. Azologization and structure-guided structure-activity relationship evaluation enabled the design of an LXR agonist, which activated LXR with low micromolar potency in its light-induced (Z)-state and was inactive as (E)-isomer. This tool sensitized human lung cancer cells to chemotherapeutic treatment in a light-dependent manner supporting potential of locally activated LXR agonists as adjuvant cancer treatment

Neurogenesis from Sox2 expressing cells in the adult cerebellar cortex

We identified a rare undifferentiated cell population that is intermingled with the Bergmann glia of the adult murine cerebellar cortex, expresses the stem cell markers Sox2 and Nestin, and lacks markers of glial or neuronal differentiation. Interestingly, such Sox2(+) S100(-) cells of the adult cerebellum expanded after adequate physiological stimuli in mice (exercise), and Sox2(+) precursors acquired positivity for the neuronal marker NeuN over time and integrated into cellular networks. In human patients, SOX2(+) S100(-) cells similarly increased in number after relevant pathological insults (infarcts), suggesting a similar expansion of cells that lack terminal glial differentiation

Nurr1 Modulation Mediates Neuroprotective Effects of Statins

The ligand-sensing transcription factor Nurr1 emerges as a promising therapeutic target for neurodegenerative pathologies but Nurr1 ligands for functional studies and therapeutic validation are lacking. Here pronounced Nurr1 modulation by statins for which clinically relevant neuroprotective effects are demonstrated, is reported. Several statins directly affect Nurr1 activity in cellular and cell-free settings with low micromolar to sub-micromolar potencies. Simvastatin as example exhibits anti-inflammatory effects in astrocytes, which are abrogated by Nurr1 knockdown. Differential gene expression analysis in native and Nurr1-silenced cells reveals strong proinflammatory effects of Nurr1 knockdown while simvastatin treatment induces several neuroprotective mechanisms via Nurr1 involving changes in inflammatory, metabolic and cell cycle gene expression. Further in vitro evaluation confirms reduced inflammatory response, improved glucose metabolism, and cell cycle inhibition of simvastatin-treated neuronal cells. These findings suggest Nurr1 involvement in the well-documented but mechanistically elusive neuroprotection by statins

Utilising Assured Multi-Agent Reinforcement Learning within safety-critical scenarios

Multi-agent reinforcement learning allows a team of agents to learn how to work together to solve complex decision-making problems in a shared environment. However, this learning process utilises stochastic mechanisms, meaning that its use in safety-critical domains can be problematic. To overcome this issue, we propose an Assured Multi-Agent Reinforcement Learning (AMARL) approach that uses a model checking technique called quantitative verification to provide formal guarantees of agent compliance with safety, performance, and other non-functional requirements during and after the reinforcement learning process. We demonstrate the applicability of our AMARL approach in three different patrolling navigation domains in which multi-agent systems must learn to visit key areas by using different types of reinforcement learning algorithms (temporal difference learning, game theory, and direct policy search). Furthermore, we compare the effectiveness of these algorithms when used in combination with and without our approach. Our extensive experiments with both homogeneous and heterogeneous multi-agent systems of different sizes show that the use of AMARL leads to safety requirements being consistently satisfied and to better overall results than standard reinforcement learning

Dual soluble epoxide hydrolase inhibitor – farnesoid X receptor agonist interventional treatment attenuates renal inflammation and fibrosis

IntroductionRenal fibrosis associated with inflammation is a critical pathophysiological event in chronic kidney disease (CKD). We have developed DM509 which acts concurrently as a farnesoid X receptor agonist and a soluble epoxide hydrolase inhibitor and investigated DM509 efficacy as an interventional treatment using the unilateral ureteral obstruction (UUO) mouse model.MethodsMale mice went through either UUO or sham surgery. Interventional DM509 treatment (10mg/kg/d) was started three days after UUO induction and continued for 7 days. Plasma and kidney tissue were collected at the end of the experimental protocol.ResultsUUO mice demonstrated marked renal fibrosis with higher kidney hydroxyproline content and collagen positive area. Interventional DM509 treatment reduced hydroxyproline content by 41% and collagen positive area by 65%. Renal inflammation was evident in UUO mice with elevated MCP-1, CD45-positive immune cell positive infiltration, and profibrotic inflammatory gene expression. DM509 treatment reduced renal inflammation in UUO mice. Renal fibrosis in UUO was associated with epithelial-to-mesenchymal transition (EMT) and DM509 treatment reduced EMT. UUO mice also had tubular epithelial barrier injury with increased renal KIM-1, NGAL expression. DM509 reduced tubular injury markers by 25-50% and maintained tubular epithelial integrity in UUO mice. Vascular inflammation was evident in UUO mice with 9 to 20-fold higher ICAM and VCAM gene expression which was reduced by 40-50% with DM509 treatment. Peritubular vascular density was reduced by 35% in UUO mice and DM509 prevented vascular loss.DiscussionInterventional treatment with DM509 reduced renal fibrosis and inflammation in UUO mice demonstrating that DM509 is a promising drug that combats renal epithelial and vascular pathological events associated with progression of CKD