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Cirrus is the only cloud type capable of inducing daytime cooling or heating at the top of the atmosphere (TOA) and the sign of its radiative effect highly depends on its optical depth. However, the investigation of its geometrical and optical properties over the Arctic is limited. In this work the long-term properties of cirrus clouds are explored for the first time over an Arctic site (Ny-Alesund, Svalbard) using lidar and radiosonde measurements from 2011 to 2020. The optical properties were quality assured, taking into account the effects of specular reflections and multiple-scattering. Cirrus clouds were generally associated with colder and calmer wind conditions compared to the 2011-2020 climatology. However, the dependence of cirrus properties on temperature and wind speed was not strong. Even though the seasonal cycle was not pronounced, the winter-time cirrus appeared under lower temperatures and stronger wind conditions. Moreover, in winter, geometrically- and optically-thicker cirrus were found and their ice particles tended to be more spherical. The majority of cirrus was associated with westerly flow and westerly cirrus tended to be geometrically-thicker. Overall, optically-thinner layers tended to comprise smaller and less spherical ice crystals, most likely due to reduced water vapor deposition on the particle surface. Compared to lower latitudes, the cirrus layers over Ny-Alesund were more absorbing in the visible spectral region and they consisted of more spherical ice particles.
MALDI-TOF-MS-based identification of monoclonal murine Anti-SARS-CoV-2 antibodies within one hour
(2022)
During the SARS-CoV-2 pandemic, many virus-binding monoclonal antibodies have been developed for clinical and diagnostic purposes. This underlines the importance of antibodies as universal bioanalytical reagents. However, little attention is given to the reproducibility crisis that scientific studies are still facing to date. In a recent study, not even half of all research antibodies mentioned in publications could be identified at all. This should spark more efforts in the search for practical solutions for the traceability of antibodies. For this purpose, we used 35 monoclonal antibodies against SARS-CoV-2 to demonstrate how sequence-independent antibody identification can be achieved by simple means applied to the protein. First, we examined the intact and light chain masses of the antibodies relative to the reference material NIST-mAb 8671. Already half of the antibodies could be identified based solely on these two parameters. In addition, we developed two complementary peptide mass fingerprinting methods with MALDI-TOF-MS that can be performed in 60 min and had a combined sequence coverage of over 80%. One method is based on the partial acidic hydrolysis of the protein by 5 mM of sulfuric acid at 99 degrees C. Furthermore, we established a fast way for a tryptic digest without an alkylation step. We were able to show that the distinction of clones is possible simply by a brief visual comparison of the mass spectra. In this work, two clones originating from the same immunization gave the same fingerprints. Later, a hybridoma sequencing confirmed the sequence identity of these sister clones. In order to automate the spectral comparison for larger libraries of antibodies, we developed the online software ABID 2.0. This open-source software determines the number of matching peptides in the fingerprint spectra. We propose that publications and other documents critically relying on monoclonal antibodies with unknown amino acid sequences should include at least one antibody fingerprint. By fingerprinting an antibody in question, its identity can be confirmed by comparison with a library spectrum at any time and context.
Both climate change and land use regimes affect the viability of populations, but they are often studied separately. Moreover, population viability analyses (PVAs) often ignore the effects of large environmental gradients and use temporal resolutions that are too coarse to take into account that different stages of a population's life cycle may be affected differently by climate change. Here, we present the High-resolution Large Environmental Gradient (HiLEG) model and apply it in a PVA with daily resolution based on daily climate projections for Northwest Germany. We used the large marsh grasshopper (LMG) as the target species and investigated (1) the effects of climate change on the viability and spatial distribution of the species, (2) the influence of the timing of grassland mowing on the species and (3) the interaction between the effects of climate change and grassland mowing. The stageand cohort-based model was run for the spatially differentiated environmental conditions temperature and soil moisture across the whole study region. We implemented three climate change scenarios and analyzed the population dynamics for four consecutive 20-year periods. Climate change alone would lead to an expansion of the regions suitable for the LMG, as warming accelerates development and due to reduced drought stress. However, in combination with land use, the timing of mowing was crucial, as this disturbance causes a high mortality rate in the aboveground life stages. Assuming the same date of mowing throughout the region, the impact on viability varied greatly between regions due to the different climate conditions. The regional negative effects of the mowing date can be divided into five phases: (1) In early spring, the populations were largely unaffected in all the regions; (2) between late spring and early summer, they were severely affected only in warm regions; (3) in summer, all the populations were severely affected so that they could hardly survive; (4) between late summer and early autumn, they were severely affected in cold regions; and (5) in autumn, the populations were equally affected across all regions. The duration and start of each phase differed slightly depending on the climate change scenario and simulation period, but overall, they showed the same pattern. Our model can be used to identify regions of concern and devise management recommendations. The model can be adapted to the life cycle of different target species, climate projections and disturbance regimes. We show with our adaption of the HiLEG model that high-resolution PVAs and applications on large environmental gradients can be reconciled to develop conservation strategies capable of dealing with multiple stressors.
Supergenes are nonrecombining genomic regions ensuring the coinheritance of multiple, coadapted genes. Despite the importance of supergenes in adaptation, little is known on how they originate. A classic example of supergene is the S locus controlling heterostyly, a floral heteromorphism occurring in 28 angiosperm families. In Primula, heterostyly is characterized by the cooccurrence of two complementary, self-incompatible floral morphs and is controlled by five genes clustered in the hemizygous, ca. 300-kb S locus. Here, we present the first chromosome-scale genome assembly of any heterostylous species, that of Primula veris (cowslip). By leveraging the high contiguity of the P. veris assembly and comparative genomic analyses, we demonstrated that the S-locus evolved via multiple, asynchronous gene duplications and independent gene translocations. Furthermore, we discovered a new whole-genome duplication in Ericales that is specific to the Primula lineage. We also propose a mechanism for the origin of S-locus hemizygosity via nonhomologous recombination involving the newly discovered two pairs of CFB genes flanking the S locus. Finally, we detected only weak signatures of degeneration in the S locus, as predicted for hemizygous supergenes. The present study provides a useful resource for future research addressing key questions on the evolution of supergenes in general and the S locus in particular: How do supergenes arise? What is the role of genome architecture in the evolution of complex adaptations? Is the molecular architecture of heterostyly supergenes across angiosperms similar to that of Primula?
Ancient genome provides insights into the history of Eurasian lynx in Iberia and Western Europe
(2022)
The Eurasian lynx (Lynx lynx) is one of the most widely distributed felids in the world. However, most of its populations started to decline a few millennia ago. Historical declines have been especially severe in Europe, and particularly in Western Europe, from where the species disappeared in the last few centuries. Here, we analyze the genome of an Eurasian lynx inhabiting the Iberian Peninsula 2500 ya, to gain insights into the phylogeographic position and genetic status of this extinct population. Also, we contextualize previous ancient data in the light of new phylogeographic studies of the species. Our results suggest that the Iberian population is part of an extinct European lineage closely related to the current Carpathian-Baltic lineages. Also, this sample holds the lowest diversity reported for the species so far, and similar to that of the highly endangered Iberian lynx. A combination of historical factors, such as a founder effect while colonizing the peninsula, together with intensified human impacts during the Holocene in the Cantabrian strip, could have led to a genetic impoverishment of the population and precipitated its extinction. Mitogenomic lineages distribution in space and time support the long-term coexistence of several lineages of Eurasian lynx in Western Europe with fluctuating ranges. While mitochondrial sequences related to the lineages currently found in Balkans and Caucasus were predominant during the Pleistocene, those more closely related to the lineage currently distributed in Central Europe prevailed during the Holocene. The use of ancient genomics has proven to be a useful tool to understand the biogeographic pattern of the Eurasian lynx in the past.
The water vapor-induced swelling, as well as subsequent phase-transition kinetics, of thin films of a diblock copolymer (DBC) loaded with different amounts of the salt NaBr, is investigated in situ. In dilute aqueous solution, the DBC features an orthogonally thermoresponsive behavior. It consists of a zwitterionic poly(sulfobetaine) block, namely, poly(4-(N-(3'-methacrylamidopropyl)-N, N-dimethylammonio) butane-1-sulfonate) (PSBP), showing an upper critical solution temperature, and a nonionic block, namely, poly(N-isopropylmethacrylamide) (PNIPMAM), exhibiting a lower critical solution temperature. The swelling kinetics in D2O vapor at 15 degrees C and the phase transition kinetics upon heating the swollen film to 60 degrees C and cooling back to 15 degrees C are followed with simultaneous time-of-flight neutron reflectometry and spectral reflectance measurements. These are complemented by Fourier transform infrared spectroscopy. The collapse temperature of PNIPMAM and the swelling temperature of PSBP are found at lower temperatures than in aqueous solution, which is attributed to the high polymer concentration in the thin-film geometry. Upon inclusion of sub-stoichiometric amounts (relative to the monomer units) of NaBr in the films, the water incorporation is significantly increased. This increase is mainly attributed to a salting-in effect on the zwitterionic PSBP block. Whereas the addition of NaBr notably shifts the swelling temperature of PSBP to lower temperatures, the collapse temperature of PNIPMAM remains unaffected by the presence of salt in the films.
Complex networks are abundant in nature and many share an important structural property: they contain a few nodes that are abnormally highly connected (hubs). Some of these hubs are called influencers because they couple strongly to the network and play fundamental dynamical and structural roles. Strikingly, despite the abundance of networks with influencers, little is known about their response to stochastic forcing. Here, for oscillatory dynamics on influencer networks, we show that subjecting influencers to an optimal intensity of noise can result in enhanced network synchronization. This new network dynamical effect, which we call coherence resonance in influencer networks, emerges from a synergy between network structure and stochasticity and is highly nonlinear, vanishing when the noise is too weak or too strong. Our results reveal that the influencer backbone can sharply increase the dynamical response in complex systems of coupled oscillators. Influencer networks include a small set of highly-connected nodes and can reach synchrony only via strong node interaction. Tonjes et al. show that introducing an optimal amount of noise enhances synchronization of such networks, which may be relevant for neuroscience or opinion dynamics applications.
The mean free path of ionizing photons, lambda(mfp), is a key factor in the photoionization of the intergalactic medium (IGM). At z greater than or similar to 5, however, lambda(mfp) may be short enough that measurements towards QSOs are biased by the QSO proximity effect. We present new direct measurements of lambda(mfp) that address this bias and extend up to z similar to 6 for the first time. Our measurements at z similar to 5 are based on data from the Giant Gemini GMOS survey and new Keck LRIS observations of low-luminosity QSOs. At z similar to 6 we use QSO spectra from Keck ESI and VLT X-Shooter. We measure lambda(mfp) = 9.09(-1.28)(+1.62) proper Mpc and 0.75(-0.45)(+0.65) proper Mpc (68 percent confidence) at z = 5.1 and 6.0, respectively. The results at z = 5.1 are consistent with existing measurements, suggesting that bias from the proximity effect is minor at this redshift. At z = 6.0, however, we find that neglecting the proximity effect biases the result high by a factor of two or more. Our measurement at z = 6.0 falls well below extrapolations from lower redshifts, indicating rapid evolution in lambda(mfp) over 5 < z < 6. This evolution disfavours models in which reionization ended early enough that the IGM had time to fully relax hydrodynamically by z = 6, but is qualitatively consistent with models wherein reionization completed at z = 6 or even significantly later. Our mean free path results are most consistent with late reionization models wherein the IGM is still 20 percent neutral at z = 6, although our measurement at z = 6.0 is even lower than these models prefer.
Ice-rich permafrost has been subject to abrupt thaw and thermokarst formation in the past and is vulnerable to current global warming. The ice-rich permafrost domain includes Yedoma sediments that have never thawed since deposition during the late Pleistocene and Alas sediments that were formed by previous thermokarst processes during the Lateglacial and Holocene warming. Permafrost thaw unlocks organic carbon (OC) and minerals from these deposits and exposes OC to mineralization. A portion of the OC can be associated with iron (Fe), a redox-sensitive element acting as a trap for OC. Post-depositional thaw processes may have induced changes in redox conditions in these deposits and thereby affected Fe distribution and interactions between OC and Fe, with knock-on effects on the role that Fe plays in mediating present day OC mineralization. To test this hypothesis, we measured Fe concentrations and proportion of Fe oxides and Fe complexed with OC in unthawed Yedoma and previously thawed Alas deposits. Total Fe concentrations were determined on 1,292 sediment samples from the Yedoma domain using portable X-ray fluorescence; these concentrations were corrected for trueness using a calibration based on a subset of 144 samples measured by inductively coupled plasma optical emission spectrometry after alkaline fusion (R (2) = 0.95). The total Fe concentration is stable with depth in Yedoma deposits, but we observe a depletion or accumulation of total Fe in Alas deposits, which experienced previous thaw and/or flooding events. Selective Fe extractions targeting reactive forms of Fe on unthawed and previously thawed deposits highlight that about 25% of the total Fe is present as reactive species, either as crystalline or amorphous oxides, or complexed with OC, with no significant difference in proportions of reactive Fe between Yedoma and Alas deposits. These results suggest that redox driven processes during past thermokarst formation impact the present-day distribution of total Fe, and thereby the total amount of reactive Fe in Alas versus Yedoma deposits. This study highlights that ongoing thermokarst lake formation and drainage dynamics in the Arctic influences reactive Fe distribution and thereby interactions between Fe and OC, OC mineralization rates, and greenhouse gas emissions.
How biased are our models?
(2021)
Geophysical process simulations play a crucial role in the understanding of the subsurface. This understanding is required to provide, for instance, clean energy sources such as geothermal energy. However, the calibration and validation of the physical models heavily rely on state measurements such as temperature. In this work, we demonstrate that focusing analyses purely on measurements introduces a high bias. This is illustrated through global sensitivity studies. The extensive exploration of the parameter space becomes feasible through the construction of suitable surrogate models via the reduced basis method, where the bias is found to result from very unequal data distribution. We propose schemes to compensate for parts of this bias. However, the bias cannot be entirely compensated. Therefore, we demonstrate the consequences of this bias with the example of a model calibration.