Withanolides: Elucidating steroidal lactone biosynthesis in Nightshades

Withania somnifera (Solanaceae) is well known in ayurvedic medicine as a strengthening tonic for various medical purposes. Its effects are mainly due to withanolides, a class of steroidal lactones with diverse oxidation patterns present in various nightshade plants. Pharmacological studies attributed anti-proliferative and anti-inflammatory properties to withanolides. However, obtaining medicinally active withanolides can be complicated, as complex mixtures are present in producing plants and total synthesis of withanolides is costly and time consuming. Therefore, investigation of their biosynthesis is important to enable biotechnological enhancement and to provide novel insights into plant steroid biochemistry. This work aimed to investigate withanolide biosynthesis in Physalis peruviana and Withania somnifera. Both plants were investigated for their main withanolides, as producers can accumulate a diverse array of withanolides, depending on the cultivation conditions. Here, besides several known withanolides, two yet unknown, truncated withanolides (irinan A (1) and B (2)) were isolated from P. peruviana and their structures were elucidated. As intermediates of withanolide biosynthesis were needed for enzyme assays but are neither known, nor commercially available, metabolic engineering in yeast was attempted to divert yeast ergosterol biosynthesis towards production of 24-methyldesmosterol (3), the last known precursor in withanolide biosynthesis. However, while production of the precursor 24-methylenecholesterol (4) was temporarily observed, 3 did not accumulate. Furthermore, based on the biosynthetic hypothesis, 21 cytochrome P450 (P450) and 14 dehydratase (DH) gene candidates were selected after analysis of three withanolide-producing species. Of those, 17 P450 and 6 DH candidates could be cloned and evaluated by gene silencing in W. somnifera, identifying 5 P450 and 2 DH gene candidates where silencing evoked significant decrease of the main withanolide (withaferin A, 5). Those candidates were further examined by heterologous expression experiments in the model plant Nicotiana benthamiana. Here activity on the substrate 24-methyldesmosterol was detected for one candidate (P450-7), while another exhibited activity on native cycloartenol (6) from the host plant (P450-17). Further investigation of P450-17 revealed that orthologs were present in tomato and potato, both non-producers of withanolides. In both plants P450-17 homologous genes are arranged in gene clusters, with neither the genes nor the cluster being reported before. In conclusion, this work provides insights into oxidations involved in withanolide biosynthesis and yet unknown phytosterol pathways in Solanaceae plants

Improving Robustness of Jet Tagging Algorithms with Adversarial Training

Deep learning is a standard tool in the field of high-energy physics, facilitating considerable sensitivity enhancements for numerous analysis strategies. In particular, in identification of physics objects, such as jet flavor tagging, complex neural network architectures play a major role. However, these methods are reliant on accurate simulations. Mismodeling can lead to non-negligible differences in performance in data that need to be measured and calibrated against. We investigate the classifier response to input data with injected mismodelings and probe the vulnerability of flavor tagging algorithms via application of adversarial attacks. Subsequently, we present an adversarial training strategy that mitigates the impact of such simulated attacks and improves the classifier robustness. We examine the relationship between performance and vulnerability and show that this method constitutes a promising approach to reduce the vulnerability to poor modeling.Comment: 17 pages, 16 figures, 2 tables. Replaced with the published version. Added the journal reference and the DOI. Code accessible under https://github.com/AnnikaStein/Adversarial-Training-for-Jet-Taggin

Isolation and characterisation of irinans, androstane-type withanolides from Physalis peruviana L.

Withanolides are steroidal lactones widespread in Nightshade plants with often potent antiproliferative activities. Additionally, the structural diversity of this compound class holds much potential for the discovery of novel biological activity. Here, we report two newly characterised withanolides, named irinans, from Physalis peruviana with highly unusual truncated backbones that resemble mammalian androstane sex hormones. Based on biomimetic chemical reactions, we propose a model that links these compounds to withanolide biosynthesis. Irinans have potent antiproliferative activities, that are however lower than those of 4ß-hydroxywithanolide E. Our work establishes androwithanolides as a new subclass of withanolides

Life Satisfaction during the Second Lockdown of the COVID-19 Pandemic in Germany: The Effects of Local Restrictions and Respondents' Perceptions about the Pandemic

This study examines the consequences of the pandemic on subjective well-being. First, we investigate to what extent regional and temporal differences in COVID-19 restrictions can explain individuals' life satisfaction in Germany. Second, we examine to what extent "subjective" evaluations of the pandemic are related to life satisfaction. Third, we examine whether these relationships vary with gender, parenthood, and partnership status, or whether relationships changed regarding specific sub-populations (i.e., mothers, fathers, childless women/ men). Merging representative survey data from the German Family Demography Panel Study (FReDA) and contextual data on COVID-19 restrictions (i.e., the stringency index), we analyze a sample of 32,258 individuals living in Germany in their regional settings on the NUTS-3 level during the "second lockdown" in spring 2021. Furthermore, we use the FReDA field period between April and June 2021 to assess temporal variations in COVID-19 restrictions and their association with life satisfaction. To answer our research questions, we compare aggregated means and use variance decomposition and multivariate regression models. Our results show strong regional and temporal differences in COVID-19 restrictions, but neither temporal nor regional differences in "subjective" perceived pandemic burden or in life satisfaction at the aggregated level. At the individual level, we find substantive negative associations between perceived pandemic burden and life satisfaction, which are particularly strong among mothers. Our study shows that individuals' negative perceptions of the pandemic are an important correlate to life satisfaction, whereas regional differences or temporal changes in COVID-19 restrictions appear to be irrelevant for the period under investigation

Auswertung der zeitlichen Lichtmodulation unter Verwendung von bildauflösenden Messgeräten

Reale Lichtszenen weisen oft eine Kombination aus verschiedenen Lichtquellen und auch Tageslicht auf. Die herkömmliche Messmethode erfordert für eine solche Szene mehrere Einzelmessungen mit einem Leuchtdichtephotometer (als Spot-TLMMessgerät) oder einem nah an der Lichtquelle platzierten Beleuchtungsstärke-Photometer. Diese Szenen können aber auch mit Hochgeschwindigkeitskameras oder bildgebende Leuchtdichtemessgeräten (engl. Imaging luminance measurement devices, ILMD) in einer Messung aufgenommen und ausgewertet werden. Ein derartiges Messverfahren beschreibt damit eine Alternative zur gängigen Methode und wird in diesem Beitrag anhand von gängigen Lampentypen demonstriert. Aus den Aufnahmen werden die Metriken zur zeitlichen Lichtmodulation (engl. temporal light modulation, TLM) berechnet, dabei werden die Parameter der einzelnen und der überlagerten Lichtquellen extrahiert und bewertet. Ein wesentlicher Vorteil der Aufnahme einer gesamten Szene ist es, dass auch die räumliche Verteilung der TLM betrachtet und in der Bewertung berücksichtig werden kann. In dieser Arbeit werden die Möglichkeiten und die Grenzen der bildgebenden TLM-Messung anhand von unter Laborbedingungen erstellten Beispiele aufgezeigt

First Steps Toward an Autonomous Accelerator, a Common Project Between DESY and KIT

Reinforcement Learning algorithms have risen in popularity in recent years in the accelerator physics community, showing potential in beam control and in the optimization and automation of tasks in accelerator operation. The Helmholtz AI project "Machine Learning toward Autonomous Accelerators" is a collaboration between DESY and KIT that works on investigating and developing RL applications for the automatic start-up of electron linear accelerators. The work is carried out in parallel at two similar research accelerators: ARES at DESY and FLUTE at KIT, giving the unique opportunity of transfer learning between facilities. One of the first steps of this project is the establishment of a common interface between the simulations and the machine, in order to test and apply various optimization approaches interchangeably between the two accelerators. In this paper we present the first results on the common interface and its application to beam focusing in ARES, and the idea of laser shaping with spatial light modulators at FLUTE

The effect of cleft lip on adults' responses to faces: cross-species findings

Cleft lip and palate is the most common of the congenital conditions affecting the face and cranial bones and is associated with a raised risk of difficulties in infant-caregiver interaction; the reasons for such difficulties are not fully understood. Here, we report two experiments designed to explore how adults respond to infant faces with and without cleft lip, using behavioural measures of attractiveness appraisal (‘liking’) and willingness to work to view or remove the images (‘wanting’). We found that infants with cleft lip were rated as less attractive and were viewed for shorter durations than healthy infants, an effect that was particularly apparent where the cleft lip was severe. Women rated the infant faces as more attractive than men did, but there were no differences in men and women's viewing times of these faces. In a second experiment, we found that the presence of a cleft lip in domestic animals affected adults' ‘liking’ and ‘wanting’ responses in a comparable way to that seen for human infants. Adults' responses were also remarkably similar for images of infants and animals with cleft lip, although no gender difference in attractiveness ratings or viewing times emerged for animals. We suggest that the presence of a cleft lip can substantially change the way in which adults respond to human and animal faces. Furthermore, women may respond in different ways to men when asked to appraise infant attractiveness, despite the fact that men and women ‘want’ to view images of infants for similar durations

Learning to Do or Learning While Doing: Reinforcement Learning and Bayesian Optimisation for Online Continuous Tuning

Online tuning of real-world plants is a complex optimisation problem that continues to require manual intervention by experienced human operators. Autonomous tuning is a rapidly expanding field of research, where learning-based methods, such as Reinforcement Learning-trained Optimisation (RLO) and Bayesian optimisation (BO), hold great promise for achieving outstanding plant performance and reducing tuning times. Which algorithm to choose in different scenarios, however, remains an open question. Here we present a comparative study using a routine task in a real particle accelerator as an example, showing that RLO generally outperforms BO, but is not always the best choice. Based on the study's results, we provide a clear set of criteria to guide the choice of algorithm for a given tuning task. These can ease the adoption of learning-based autonomous tuning solutions to the operation of complex real-world plants, ultimately improving the availability and pushing the limits of operability of these facilities, thereby enabling scientific and engineering advancements.Comment: 17 pages, 8 figures, 2 table