An open-path observatory for greenhouse gases based on near-infrared Fourier transform spectroscopy

Monitoring the atmospheric concentrations of the greenhouse gases (GHG) carbon dioxide (CO$_2$) and methane (CH$_4$) is a key ingredient for fostering our understanding of the mechanisms behind the sources and sinks of these gases and for verifying and quantitatively attributing their anthropogenic emissions. Here, we present the instrumen- tal setup and performance evaluation of an open-path GHG observatory in the city of Heidelberg, Germany. The obser- vatory measures path-averaged concentrations of CO$_2$ and CH$_4$ along a 1.55 km path in the urban boundary layer above the city. We combine these open-path data with local in situ measurements to evaluate the representativeness of these ob- servation types on the kilometer scale. This representative- ness is necessary to accurately quantify emissions, since at- mospheric models tasked with this job typically operate on kilometer-scale horizontal grids. For the operational period between 8 February and 11 July 2023, we find a precision of 2.7 ppm (0.58 %) and 18 ppb (0.89 %) for the dry-air mole fractions of CO$_2$ (xCO$_2$) and CH$_4$ (xCH$_4$) in 5 min measurements, respectively. After bias correction, the open-path measurements show excellent agreement with the local in situ data under atmospheric back- ground conditions. Both datasets show clear signals of traffic CO$_2$ emissions in the diurnal xCO$_2$ cycle. However, there are particular situations, such as under southeasterly wind condi- tions, in which the in situ and open-path data reveal distinct differences up to 20 ppm in xCO$_2$, most likely related to their different sensitivity to local emission and transport patterns. Our setup is based on a Bruker IFS 125HR Fourier trans- form spectrometer, which offers a spacious and modular de- sign providing ample opportunities for future refinements of the technique with respect to finer spectral resolution and wider spectral coverage to provide information on gases such as carbon monoxide and nitrogen dioxide

Generation of synthetic nanobodies against delicate proteins

Here, we provide a protocol to generate synthetic nanobodies, known as sybodies, against any purified protein or protein complex within a 3-week period. Unlike methods that require animals for antibody generation, sybody selections are carried out entirely in vitro under controlled experimental conditions. This is particularly relevant for the generation of conformation-specific binders against labile membrane proteins or protein complexes and allows selections in the presence of non-covalent ligands. Sybodies are especially suited for cases where binder generation via immune libraries fails due to high sequence conservation, toxicity or insufficient stability of the target protein. The procedure entails a single round of ribosome display using the sybody libraries encoded by mRNA, followed by two rounds of phage display and binder identification by ELISA. The protocol is optimized to avoid undesired reduction in binder diversity and enrichment of non-specific binders to ensure the best possible selection outcome. Using the efficient fragment exchange (FX) cloning method, the sybody sequences are transferred from the phagemid to different expression vectors without the need to amplify them by PCR, which avoids unintentional shuffling of complementary determining regions. Using quantitative PCR (qPCR), the efficiency of each selection round is monitored to provide immediate feedback and guide troubleshooting. Our protocol can be carried out by any trained biochemist or molecular biologist using commercially available reagents and typically gives rise to 10-30 unique sybodies exhibiting binding affinities in the range of 500 pM-500 nM

Amyloid fibril structure from the vascular variant of systemic AA amyloidosis

Systemic AA amyloidosis is a debilitating protein misfolding disease in humans and animals. In humans, it occurs in two variants that are called ‘vascular’ and ‘glomerular’, depending on the main amyloid deposition site in the kidneys. Using cryo electron microscopy, we here show the amyloid fibril structure underlying the vascular disease variant. Fibrils purified from the tissue of such patients are mainly left-hand twisted and contain two non-equal stacks of fibril proteins. They contrast in these properties to the fibrils from the glomerular disease variant which are right-hand twisted and consist of two structurally equal stacks of fibril proteins. Our data demonstrate that the different disease variants in systemic AA amyloidosis are associated with different fibril morphologies

Modeling spatiotemporal information generation

Maintaining knowledge about the provenance of datasets, that is, about how they were obtained, is crucial for their further use. Contrary to what the overused metaphors of ‘data mining’ and ‘big data’ are implying, it is hardly possible to use data in a meaningful way if information about sources and types of conversions is discarded in the process of data gathering. A generative model of spatiotemporal information could not only help automating the description of derivation processes but also assessing the scope of a dataset’s future use by exploring possible transformations. Even though there are technical approaches to document data provenance, models for describing how spatiotemporal data are generated are still missing. To fill this gap, we introduce an algebra that models data generation and describes how datasets are derived, in terms of types of reference systems. We illustrate its versatility by applying it to a number of derivation scenarios, ranging from field aggregation to trajectory generation, and discuss its potential for retrieval, analysis support systems, as well as for assessing the space of meaningful computations