A Serpin shapes the extracellular environment to prevent influenza A virus maturation

Interferon-stimulated genes (ISGs) act in concert to provide a tight barrier against viruses. Recent studies have shed light on the contribution of individual ISG effectors to the antiviral state, but most have examined those acting on early, intracellular stages of the viral life cycle. Here, we applied an image-based screen to identify ISGs inhibiting late stages of influenza A virus (IAV) infection. We unraveled a directly antiviral function for the gene SERPINE1, encoding plasminogen activator inhibitor 1 (PAI-1). By targeting extracellular airway proteases, PAI-1 inhibits IAV glycoprotein cleavage, thereby reducing infectivity of progeny viruses. This was biologically relevant for IAV restriction in vivo. Further, partial PAI-1 deficiency, attributable to a polymorphism in human SERPINE1, conferred increased susceptibility to IAV in vitro. Together, our findings reveal that manipulating the extracellular environment to inhibit the last step in a virus life cycle is an important mechanism of the antiviral response

In vitro metabolic fate of nine LSD-based new psychoactive substances and their analytical detectability in different urinary screening procedures

The market of new psychoactive substances (NPS) is characterized by a high turnover and thus provides several challenges for analytical toxicology. The analysis of urine samples often requires detailed knowledge about metabolism given that parent compounds either may be present only in small amounts or may not even be excreted. Hence, knowledge of the metabolism of NPS is a prerequisite for the development of reliable analytical methods. The main aim of this work was to elucidate for the first time the pooled human liver S9 fraction metabolism of the nine d-lysergic acid diethylamide (LSD) derivatives 1-acetyl-LSD (ALD-52), 1-propionyl-LSD (1P-LSD), 1-butyryl-LSD (1B-LSD), N6-ethyl-nor-LSD (ETH-LAD), 1-propionyl-N6-ethyl-nor-LSD (1P-ETH-LAD), N6-allyl-nor-LSD (AL-LAD), N-ethyl-N-cyclopropyl lysergamide (ECPLA), (2′S,4′S)-lysergic acid 2,4-dimethylazetidide (LSZ), and lysergic acid morpholide (LSM-775) by means of liquid chromatography coupled to high-resolution tandem mass spectrometry. Identification of the monooxygenase enzymes involved in the initial metabolic steps was performed using recombinant human enzymes and their contribution confirmed by inhibition experiments. Overall, N-dealkylation and hydroxylation, as well as combinations of these steps predominantly catalyzed by CYP1A2 and CYP3A4, were found. For ALD-52, 1P-LSD, and 1B-LSD, deacylation to LSD was observed. The obtained mass spectral data of all metabolites are essential for reliable analytical detection particularly in urinalysis and for differentiation of the LSD-like compounds as biotransformations also led to structurally identical metabolites. However, in urine of rats after the administration of expected recreational doses and using standard urine screening approaches, parent drugs or metabolites could not be detected

Influence of Poly(L-Lactic Acid) Nanofibers and BMP-2–Containing Poly(L-Lactic Acid) Nanofibers on Growth and Osteogenic Differentiation of Human Mesenchymal Stem Cells

The aim of this study was to characterize synthetic poly-(L-lactic acid) (PLLA) nanofibers concerning their ability to promote growth and osteogenic differentiation of stem cells in vitro, as well as to test their suitability as a carrier system for growth factors. Fiber matrices composed of PLLA or BMP-2–incorporated PLLA were seeded with human mesenchymal stem cells and cultivated over a period of 22 days under growth and osteoinductive conditions, and analyzed during the course of culture, with respect to gene expression of alkaline phosphatase (ALP), osteocalcin (OC), and collagen I (COL-I). Furthermore, COL-I and OC deposition, as well as cell densities and proliferation, were analyzed using fluorescence microscopy. Although the presence of nanofibers diminished the dexamethasone-induced proliferation, there were no differences in cell densities or deposition of either COL-I or OC after 22 days of culture. The gene expression of ALP, OC, and COL-I decreased in the initial phase of cell cultivation on PLLA nanofibers as compared to cover slip control, but normalized during the course of cultivation. The initial down-regulation was not observed when BMP-2 was directly incorporated into PLLA nanofibers by electrospinning, indicating that growth factors like BMP-2 might survive the spinning process in a bioactive form

COVID-19 and emerging viral infections: The case for interferon lambda

With the first reports on coronavirus disease 2019 (COVID-19), which is caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the scientific community working in the field of type III IFNs (IFN-λ) realized that this class of IFNs could play an important role in this and other emerging viral infections. In this Viewpoint, we present our opinion on the benefits and potential limitations of using IFN-λ to prevent, limit, and treat these dangerous viral infections

Managing uncertainty: a review of food system scenario analysis and modelling

Complex socio-ecological systems like the food system are unpredictable, especially to long-term horizons such as 2050. In order to manage this uncertainty, scenario analysis has been used in conjunction with food system models to explore plausible future outcomes. Food system scenarios use a diversity of scenario types and modelling approaches determined by the purpose of the exercise and by technical, methodological and epistemological constraints. Our case studies do not suggest Malthusian futures for a projected global population of 9 billion in 2050; but international trade will be a crucial determinant of outcomes; and the concept of sustainability across the dimensions of the food system has been inadequately explored so far. The impact of scenario analysis at a global scale could be strengthened with participatory processes involving key actors at other geographical scales. Food system models are valuable in managing existing knowledge on system behaviour and ensuring the credibility of qualitative stories but they are limited by current datasets for global crop production and trade, land use and hydrology. Climate change is likely to challenge the adaptive capacity of agricultural production and there are important knowledge gaps for modelling research to address

PET imaging of the normal human auditory system: responses

Abstract The neural mechanisms involved in listening to sentences, and then detecting and verbalizing a specific word are poorly understood, but most likely involve complex neural networks. We used positron emission tomography to identify the areas of the human brain that are activated when young, normal hearing males and females were asked to listen to a sentence and repeat the last word from the Speech in Noise (SPIN) test. Listening conditions were (1) Quiet, (2) Speech, (3) Noise, and (4) SPIN with stimuli presented monaurally to either the left ear or the right ear. The least difficult listening task, Speech, resulted in bilateral activation of superior and middle temporal gyrus and pre-central gyrus. The Noise and SPIN conditions activated many of the same regions as Speech alone plus additional sites within the cerebellum, thalamus and superior/middle frontal gyri. Comparison of the SPIN condition versus Speech revealed additional activation in the right anterior lobe of the cerebellum and right medial frontal gyrus, near the cingulate. None of the left ear^right ear stimulus comparison revealed any significant differences except for the SPIN condition that showed greater activation in the left superior temporal gyrus for stimuli presented to the right ear. No gender differences were observed. These results demonstrate that repeating the last word in a sentence activates mainly auditory and motor areas of the brain when Speech is presented, whereas more difficult tasks, such as SPIN or multi-talker Noise, activate linguistic, attentional, cognitive, working memory, and motor planning areas.

The graph rewriting calculus: confluence and expressiveness

Introduced at the end of the nineties, the Rewriting Calculus (rho-calculus, for short) is a simple calculus that uniformly integrates term-rewriting and lambda-calculus. The Rhog has been recently introduced as an extension of the rho-calculus, handling structures with cycles and sharing. The calculus over terms is naturally generalized by using unification constraints in addition to the standard rho-calculus matching constraints. This leads to a term-graph representation in an equational style where terms consist of unordered lists of equations. In this paper we show that the (linear) Rhog is confluent. The proof of this result is quite elaborated, due to the non-termination of the system and to the fact that we work on equivalence classes of terms. We also show that the Rhog can be seen as a generalization of first-order term-graph rewriting, in the sense that for any term-graph rewrite step a corresponding sequence of rewritings can be found in the Rhog

Toxicity modelling of Plk1-targeted therapies in genetically engineered mice and cultured primary mammalian cells

High attrition rates of novel anti-cancer drugs highlight the need for improved models to predict toxicity. Although polo-like kinase 1 (Plk1) inhibitors are attractive candidates for drug development, the role of Plk1 in primary cells remains widely unexplored. Therefore, we evaluated the utility of an RNA interference-based model to assess responses to an inducible knockdown (iKD) of Plk1 in adult mice. Here we show that Plk1 silencing can be achieved in several organs, although adverse events are rare. We compared responses in Plk1-iKD mice with those in primary cells kept under controlled culture conditions. In contrast to the addiction of many cancer cell lines to the non-oncogene Plk1, the primary cells' proliferation, spindle assembly and apoptosis exhibit only a low dependency on Plk1. Responses to Plk1-depletion, both in cultured primary cells and in our iKD-mouse model, correspond well and thus provide the basis for using validated iKD mice in predicting responses to therapeutic interventions

Improving Metabolic Health Through Precision Dietetics in Mice

The incidence of diet-induced metabolic disease has soared over the last half-century, despite national efforts to improve health through universal dietary recommendations. Studies comparing dietary patterns of populations with health outcomes have historically provided the basis for healthy diet recommendations. However, evidence that population-level diet responses are reliable indicators of responses across individuals is lacking. This study investigated how genetic differences influence health responses to several popular diets in mice, which are similar to humans in genetic composition and the propensity to develop metabolic disease, but enable precise genetic and environmental control. We designed four human-comparable mouse diets that are representative of those eaten by historical human populations. Across four genetically distinct inbred mouse strains, we compared the American diet’s impact on metabolic health to three alternative diets (Mediterranean, Japanese, and Maasai/ketogenic). Furthermore, we investigated metabolomic and epigenetic alterations associated with diet response. Health effects of the diets were highly dependent on genetic background, demonstrating that individualized diet strategies improve health outcomes in mice. If similar genetic-dependent diet responses exist in humans, then a personalized, or “precision dietetics,” approach to dietary recommendations may yield better health outcomes than the traditional one-size-fits-all approach