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Ice nucleating particle concentrations of the past: insights from a
600 year old Greenland ice core
(2020)
Ice nucleating particles (INPs) affect the microphysics in cloud and precipitation processes. Hence, they modulate the radiative properties of clouds. However, atmospheric INP concentrations of the past are basically unknown. Here, we present INP measurements from an ice core in Greenland, which dates back to the year 1370. In total 135 samples were analyzed with the FRIDGE droplet freezing assay in the temperature range from −14 ◦C to −35 ◦C. The sampling frequency was set to 1 in 10 years from 1370 to 1960. From 1960 to 1990 the frequency was increased to 1 sample per year. Additionally, a number of special events were probed, including volcanic episodes. The typical time coverage of a sample was on the order of a few months. Historical atmospheric INP concentrations were estimated with a conversion factor, which depends on the snow accumulation rate of the ice core, particle dry deposition velocity and the wet scavenging ratio. Typical atmospheric INP concentrations were on the order of 0.1 L -1 at −25 ◦C. The INP variability was found to be about 1 – 2 orders of magnitude. Yet, the short-term variability from samples over a seasonal cycle was considerably lower. INP concentrations were significantly correlated to chemical tracers derived from continuous flow analysis (CFA) and ion chromatography (IC) over a broad range of nucleation temperatures. The highest correlation coefficients were found for the particle concentration (dp > 1.2 µm). The correlation is higher for the seasonal samples, where INP concentrations follow a clear annual pattern, highlighting the importance of the annual dust input in Greenland from East Asian deserts during spring. Scanning electron microscopy (SEM) of single particles retrieved from selected samples found particles of soil origin to be the dominant fraction, verifying the significance of mineral dust particles as INPs. Overall, the concentrations compare reasonably well to present day INP concentrations, albeit they are on the lower side. However, we found that the INP concentration at medium supercooled temperatures differed before and after 1960. Average INP concentrations at −23 ◦C, −24 ◦C, −25 ◦C, −26 ◦C and −28 ◦C were significantly higher (and more variable) in the modern day period, which could indicate a potential anthropogenic impact or some post-coring contamination of the topmost, very porous firn.
As a surrogate of live cells, proteo-lipobeads are presented, encapsulating functional membrane proteins in a strict orientation into a lipid bilayer. Assays can be performed just as on live cells, for example using fluorescence measurements. As a proof of concept, we have demonstrated proton transport through cytochrome c oxidase.
CXCL12-CXCR4 signaling controls multiple physiological processes and its dysregulation is associated with cancers and inflammatory diseases. To discover as-yet-unknown endogenous ligands of CXCR4, we screened a blood-derived peptide library for inhibitors of CXCR4-tropic HIV-1 strains. This approach identified a 16 amino acid fragment of serum albumin as an effective and highly specific CXCR4 antagonist. The endogenous peptide, termed EPI-X4, is evolutionarily conserved and generated from the highly abundant albumin precursor by pH-regulated proteases. EPI-X4 forms an unusual lasso-like structure and antagonizes CXCL12-induced tumor cell migration, mobilizes stem cells, and suppresses inflammatory responses in mice. Furthermore, the peptide is abundant in the urine of patients with inflammatory kidney diseases and may serve as a biomarker. Our results identify EPI-X4 as a key regulator of CXCR4 signaling and introduce proteolysis of an abundant precursor protein as an alternative concept for chemokine receptor regulation.
In this paper we will explore the similarities and differences between two feature logic-based approaches to the composition of semantic representations. The first approach is formulated for Lexicalized Tree Adjoining Grammar (LTAG, Joshi and Schabes 1997), the second is Lexical Ressource Semantics (LRS, Richter and Sailer 2004) and was first defined in Head-driven Phrase Structure Grammar. The two frameworks have several common characteristics that make them easy to compare: 1 They use languages of two sorted type theory for semantic representations. 2. They allow underspecification. LTAG uses scope constraints while LRS provides component-of contraints. 3 They use feature logics for computing semantic representations. 4. they are designed for computational applications. By comparing the two frameworks we will also point outsome characteristics and advantages of feature logic-based semantic computation in genereal.
The project focuses on the efficiency of combined technologies to reduce the release of micropollutants and bacteria into surface waters via sewage treatment plants of different size and via stormwater overflow basins of different types. As a model river in a highly populated catchment area, the river Schussen and, as a control, the river Argen, two tributaries of Lake Constance, Southern Germany, are under investigation in this project. The efficiency of the different cleaning technologies is monitored by a wide range of exposure and effect analyses including chemical and microbiological techniques as well as effect studies ranging from molecules to communities.
The SARS-CoV-2 virus is the cause of the respiratory disease COVID-19. As of today, therapeutic interventions in severe COVID-19 cases are still not available as no effective therapeutics have been developed so far. Despite the ongoing development of a number of effective vaccines, therapeutics to fight the disease once it has been contracted will still be required. Promising targets for the development of antiviral agents against SARS-CoV-2 can be found in the viral RNA genome. The 5′- and 3′-genomic ends of the 30 kb SCoV-2 genome are highly conserved among Betacoronaviruses and contain structured RNA elements involved in the translation and replication of the viral genome. The 40 nucleotides (nt) long highly conserved stem-loop 4 (5_SL4) is located within the 5′-untranslated region (5′-UTR) important for viral replication. 5_SL4 features an extended stem structure disrupted by several pyrimidine mismatches and is capped by a pentaloop. Here, we report extensive 1H, 13C, 15N and 31P resonance assignments of 5_SL4 as the basis for in-depth structural and ligand screening studies by solution NMR spectroscopy.
The highly infectious disease COVID-19 caused by the Betacoronavirus SARS-CoV-2 poses a severe threat to humanity and demands the redirection of scientific efforts and criteria to organized research projects. The international COVID19-NMR consortium seeks to provide such new approaches by gathering scientific expertise worldwide. In particular, making available viral proteins and RNAs will pave the way to understanding the SARS-CoV-2 molecular components in detail. The research in COVID19-NMR and the resources provided through the consortium are fully disclosed to accelerate access and exploitation. NMR investigations of the viral molecular components are designated to provide the essential basis for further work, including macromolecular interaction studies and high-throughput drug screening. Here, we present the extensive catalog of a holistic SARS-CoV-2 protein preparation approach based on the consortium’s collective efforts. We provide protocols for the large-scale production of more than 80% of all SARS-CoV-2 proteins or essential parts of them. Several of the proteins were produced in more than one laboratory, demonstrating the high interoperability between NMR groups worldwide. For the majority of proteins, we can produce isotope-labeled samples of HSQC-grade. Together with several NMR chemical shift assignments made publicly available on covid19-nmr.com, we here provide highly valuable resources for the production of SARS-CoV-2 proteins in isotope-labeled form.
The current pandemic situation caused by the Betacoronavirus SARS-CoV-2 (SCoV2) highlights the need for coordinated research to combat COVID-19. A particularly important aspect is the development of medication. In addition to viral proteins, structured RNA elements represent a potent alternative as drug targets. The search for drugs that target RNA requires their high-resolution structural characterization. Using nuclear magnetic resonance (NMR) spectroscopy, a worldwide consortium of NMR researchers aims to characterize potential RNA drug targets of SCoV2. Here, we report the characterization of 15 conserved RNA elements located at the 5′ end, the ribosomal frameshift segment and the 3′-untranslated region (3′-UTR) of the SCoV2 genome, their large-scale production and NMR-based secondary structure determination. The NMR data are corroborated with secondary structure probing by DMS footprinting experiments. The close agreement of NMR secondary structure determination of isolated RNA elements with DMS footprinting and NMR performed on larger RNA regions shows that the secondary structure elements fold independently. The NMR data reported here provide the basis for NMR investigations of RNA function, RNA interactions with viral and host proteins and screening campaigns to identify potential RNA binders for pharmaceutical intervention.
The stem-loop (SL1) is the 5'-terminal structural element within the single-stranded SARS-CoV-2 RNA genome. It is formed by nucleotides 7–33 and consists of two short helical segments interrupted by an asymmetric internal loop. This architecture is conserved among Betacoronaviruses. SL1 is present in genomic SARS-CoV-2 RNA as well as in all subgenomic mRNA species produced by the virus during replication, thus representing a ubiquitous cis-regulatory RNA with potential functions at all stages of the viral life cycle. We present here the 1H, 13C and 15N chemical shift assignment of the 29 nucleotides-RNA construct 5_SL1, which denotes the native 27mer SL1 stabilized by an additional terminal G-C base-pair.
1H, 13C, and 15N backbone chemical shift assignments of coronavirus-2 non-structural protein Nsp10
(2020)
The international Covid19-NMR consortium aims at the comprehensive spectroscopic characterization of SARS-CoV-2 RNA elements and proteins and will provide NMR chemical shift assignments of the molecular components of this virus. The SARS-CoV-2 genome encodes approximately 30 different proteins. Four of these proteins are involved in forming the viral envelope or in the packaging of the RNA genome and are therefore called structural proteins. The other proteins fulfill a variety of functions during the viral life cycle and comprise the so-called non-structural proteins (nsps). Here, we report the near-complete NMR resonance assignment for the backbone chemical shifts of the non-structural protein 10 (nsp10). Nsp10 is part of the viral replication-transcription complex (RTC). It aids in synthesizing and modifying the genomic and subgenomic RNAs. Via its interaction with nsp14, it ensures transcriptional fidelity of the RNA-dependent RNA polymerase, and through its stimulation of the methyltransferase activity of nsp16, it aids in synthesizing the RNA cap structures which protect the viral RNAs from being recognized by the innate immune system. Both of these functions can be potentially targeted by drugs. Our data will aid in performing additional NMR-based characterizations, and provide a basis for the identification of possible small molecule ligands interfering with nsp10 exerting its essential role in viral replication.