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The Atmospheric LAser Doppler INstrument (ALADIN) on board Aeolus was the first high-spectral-resolution lidar (HSRL) in space. It was launched in 2018 and re-entered in 2023. The FeatureMask (A-FM) and extinction profile algorithms (A-PRO) developed for the Earth Cloud Aerosol and Radiation Explorer (EarthCARE) HSRL ATmospheric LIDar (ATLID) have been adapted to Aeolus and called AEL-FM and AEL-PRO, respectively. These algorithms have been purposely built to process low signal-to-noise ratio space-based lidar signals. A short description of the AEL-FM and AEL-PRO algorithms is provided in this paper. AEL-FM and AEL-PRO prototype products (v1.7) have been evaluated using the collocated Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) vertical feature mask (VFM) product and level 2 aerosol profile product for 2 months of data in October 2018 and May 2019. Aeolus and CALIPSO are both polar-orbiting satellites, but they have different overpass times. The evaluations are focused on desert dust aerosols over Africa. These types of scenes are often stable in space (tens of kilometres) and time (on the order of 0.5–1 h), and thus, a useful number of collocated cases can be collected. We have found that the AEL-FM feature mask and the CALIPSO VFM show similar aerosol patterns in the collocated orbits, but AEL-FM does not separate aerosol and cloud features. Aeolus and CALIPSO have a good agreement for the extinction coefficients for the dust aerosols, especially for the cloud-free scenes. The Aeolus aerosol optical thickness (AOT) is larger than the CALIPSO AOT, mainly due to cloud contamination. Because of the missing a cross-polar channel, it is difficult to distinguish aerosols and thin ice clouds using the Aeolus extinction coefficients alone. The AEL-FM and AEL-PRO algorithms have been implemented in the Aeolus level 2A (L2A) processor. The findings here are applicable to the AEL-FM and AEL-PRO products in L2A Baseline 17. This is the first time that the AEL-FM and AEL-PRO products have been evaluated using CALIPSO data.

Abstract Nuclear receptors are ligand-activated transcription factors that can often be useful drug targets. Unfortunately, ligand promiscuity leads to two-thirds of receptors remaining clinically untargeted. PXR is a nuclear receptor that can be activated by diverse compounds to elevate metabolism, negatively impacting drug efficacy and safety. This presents a barrier to drug development because compounds designed to target other proteins must avoid PXR activation while retaining potency for the desired target. This problem could be avoided by using PXR antagonists, but these compounds are rare, and their molecular mechanisms remain unknown. Here, we report structurally related PXR-selective agonists and antagonists and their corresponding co-crystal structures to describe mechanisms of antagonism and selectivity. Structural and computational approaches show that antagonists induce PXR conformational changes incompatible with transcriptional coactivator recruitment. These results guide the design of compounds with predictable agonist/antagonist activities and bolster efforts to generate antagonists to prevent PXR activation interfering with other drugs.

Complementary structural biology approaches reveal how an agonist and a covalent inhibitor simultaneously bind to a nuclear receptor.

CYP3A5 is a cytochrome P450 (CYP) enzyme that metabolizes drugs and contributes to drug resistance in cancer. However, it remains unclear whether CYP3A5 directly influences cancer progression. In this report, we demonstrate that CYP3A5 regulates glucose metabolism in pancreatic ductal adenocarcinoma. Multi-omics analysis showed that CYP3A5 knockdown results in a decrease in various glucose-related metabolites through its effect on glucose transport. A mechanistic study revealed that CYP3A5 enriches the glucose transporter GLUT1 at the plasma membrane by restricting the translation of TXNIP, a negative regulator of GLUT1. Notably, CYP3A5-generated reactive oxygen species were proved to be responsible for attenuating the AKT–4EBP1–TXNIP signaling pathway. CYP3A5 contributes to cell migration by maintaining high glucose uptake in pancreatic cancer. Taken together, our results, for the first time, reveal a role of CYP3A5 in glucose metabolism in pancreatic ductal adenocarcinoma and identify a novel mechanism that is a potential therapeutic target.

Pregnane X receptor (PXR) is a ligand-activated nuclear receptor that transcriptionally upregulates drug-metabolizing enzymes [e.g., cytochrome P450 3A4 (CYP3A4)] and transporters. Although the regulation of PXR target genes is well-characterized, less is known about the regulation of PXR protein level. By screening an RNAi library, we identified the F-box-only protein 44 (FBXO44) as a novel E3 ligase for PXR. PXR abundance increases upon knockdown of FBXO44, and, inversely, decreases upon overexpression of FBXO44. Further analysis revealed that FBXO44 interacts with PXR, leading to its ubiquitination and proteasomal degradation, and we determined that the F-box associated domain of FBXO44 and the ligand binding domain of PXR are required for the functional interaction. In summary, FBXO44 regulates PXR protein abundance, which has downstream consequences for CYP3A4 levels and drug–drug interactions. The results of this study provide new insight into the molecular mechanisms that regulate PXR protein level and activity and suggest the importance of considering how modulating E3 ubiquitin ligase activities will affect PXR-mediated drug metabolism.

Abstract Statistical tests for molecular evolution provide quantifiable insights into the selection pressures that govern a genome's evolution. Increasing sample sizes used for analysis leads to higher statistical power. However, this requires more computational nodes or longer computational time. CATE (CUDA Accelerated Testing of Evolution) is a computational solution to this problem comprised of two main innovations. The first is a file organization system coupled with a novel search algorithm and the second is a large‐scale parallelization of algorithms using both graphical processing unit (GPU) and central processing unit. CATE is capable of conducting evolutionary tests such as Tajima's D, Fu and Li's, and Fay and Wu's test statistics, McDonald–Kreitman Neutrality Index, Fixation Index and Extended Haplotype Homozygosity. CATE is magnitudes faster than standard tools with benchmarks estimating it being on average over 180 times faster. For instance, CATE processes all 54,849 human genes for all 22 autosomal chromosomes across the five super populations present in the 1000 Genomes Project in less than 30 min while counterpart software took 3.62 days. This proven framework has the potential to be adapted for GPU‐accelerated large‐scale parallel analyses of many evolutionary and genomic analyses.

Engineering long-range interacting spin systems with ultracold atoms offers the possibility to explore exotic magnetically ordered phases in strongly-correlated scenarios. Quantum gases in optical cavities provide a versatile experimental platform to further engineer photon-mediated interactions and access the underlying microscopic processes by probing the cavity field. Here, we study a two-component spin Bose-Hubbard system with cavity-mediated interactions. We provide a comprehensive overview of its phase diagram and transitions in experimentally relevant regimes. The interplay of different energy scales yields a rich phase diagram with superfluid and insulating phases exhibiting density modulation or spin ordering. In particular, the combined effect of contact and global-range interactions gives rise to an antiferromagnetically ordered phase for arbitrarily small spin-dependent light-matter coupling, while global-range and inter-spin contact interactions introduce regions of instability and phase separation in the phase diagram. We further study the low energy excitations above the antiferromagnetic phase. Besides particle-hole branches, it hosts spin-exchange excitations with a tunable energy gap. The studied lattice model can be readily realized in cold-atom experiments with optical cavities.

In August 2018, the European Space Agency (ESA) launched the first Doppler wind lidar into space, which has since then been providing continuous profiles of the horizontal line-of-sight wind component at a global scale. Aeolus data have been successfully assimilated into several numerical weather prediction (NWP) models and demonstrated a positive impact on the quality of the weather forecasts. To provide valuable input data for NWP models, a detailed characterization of the Aeolus instrumental performance as well as the realization and minimization of systematic error sources is crucial. In this paper, Aeolus interferometer spectral drifts and their potential as systematic error sources for the aerosol and wind products are investigated by means of instrument spectral registration (ISR) measurements that are performed on a weekly basis. During these measurements, the laser frequency is scanned over a range of 11 GHz in steps of 25 MHz and thus spectrally resolves the transmission curves of the Fizeau interferometer and the Fabry–Pérot interferometers (FPIs) used in Aeolus. Mathematical model functions are derived to analyze the measured transmission curves by means of non-linear fit procedures. The obtained fit parameters are used to draw conclusions about the Aeolus instrumental alignment and potentially ongoing drifts. The introduced instrumental functions and analysis tools may also be applied for upcoming missions using similar spectrometers as for instance EarthCARE (ESA), which is based on the Aeolus FPI design.

Aeolus carries the Atmospheric LAser Doppler INstrument (ALADIN), the first high-spectral-resolution lidar (HSRL) in space. Although ALADIN is optimized to measure winds, its two measurement channels can also be used to derive optical properties of atmospheric particles, including a direct retrieval of the lidar ratio. This paper presents the standard correct algorithm and the Mie correct algorithm, the two main algorithms of the optical properties product called the Level-2A product, as they are implemented in version 3.12 of the processor, corresponding to the data labelled Baseline 12. The theoretical basis is the same as in Flamant et al. (2008). Here, we also show the in-orbit performance of these algorithms. We also explain the adaptation of the calibration method, which is needed to cope with unforeseen variations of the instrument radiometric performance due to the in-orbit strain of the primary mirror under varying thermal conditions. Then we discuss the limitations of the algorithms and future improvements. We demonstrate that the L2A product provides valuable information about airborne particles; in particular, we demonstrate the capacity to retrieve a useful lidar ratio from Aeolus observations. This is illustrated using Saharan dust aerosol observed in June 2020.

Even just shortly after the successful launch of the European Space Agency satellite Aeolus in August 2018, it turned out that dark current signal anomalies of single pixels (so-called “hot pixels”) on the accumulation charge-coupled devices (ACCDs) of the Aeolus detectors detrimentally impact the quality of the aerosol and wind products, potentially leading to wind errors of up to several meters per second. This paper provides a detailed characterization of the hot pixels that occurred during the first 1.5 years in orbit. The hot pixels are classified according to their characteristics to discuss their impact on wind measurements. Furthermore, mitigation approaches for the wind retrieval are presented and potential root causes for hot pixel occurrence are discussed. The analysis of the dark current signal anomalies reveals a large variety of anomalies ranging from pixels with random telegraph signal (RTS)-like characteristics to pixels with sporadic shifts in the median dark current signal. Moreover, the results indicate that the number of hot pixels almost linearly increased during the observing period between 2 September 2018 and 20 May 2020 with 6 % of the ACCD pixels affected in total at the end of the period leading to 9.5 % at the end of the mission lifetime. This work introduces dedicated instrument calibration modes and ground processors, which allowed for a correction shortly after a hot pixel occurrence. The achieved performance with this approach avoids risky adjustments to the in-flight hardware operation. It is demonstrated that the success of the correction scheme varies depending on the characteristics of each hot pixel itself. With the herein presented categorization, it is shown that multi-level RTS pixels with high fluctuation are the biggest challenge for the hot pixel correction scheme. Despite a detailed analysis in this framework, no conclusion could be drawn about the root cause of the hot pixel issue.

Several direct-acting antivirals (DAAs) are available, providing interferon-free strategies for a hepatitis C cure. In contrast to DAAs, host-targeting agents (HTAs) interfere with host cellular factors that are essential in the viral replication cycle; as host genes, they are less likely to rapidly mutate under drug pressure, thus potentially exhibiting a high barrier to resistance, in addition to distinct mechanisms of action. We compared the effects of cyclosporin A (CsA), a HTA that targets cyclophilin A (CypA), to DAAs, including inhibitors of nonstructural protein 5A (NS5A), NS3/4A, and NS5B, in Huh7.5.1 cells. Our data show that CsA suppressed HCV infection as rapidly as the fastest-acting DAAs. CsA and inhibitors of NS5A and NS3/4A, but not of NS5B, suppressed the production and release of infectious HCV particles. Intriguingly, while CsA rapidly suppressed infectious extracellular virus levels, it had no significant effect on the intracellular infectious virus, suggesting that, unlike the DAAs tested here, it may block a post-assembly step in the viral replication cycle. Hence, our findings shed light on the biological processes involved in HCV replication and the role of CypA.

Abstract LOPES, the LOFAR prototype station, was an antenna array for cosmic-ray air showers operating from 2003 to 2013 within the KASCADE-Grande experiment. Meanwhile, the analysis is finished and the data of air-shower events measured by LOPES are available with open access in the KASCADE Cosmic Ray Data Center (KCDC). This article intends to provide a summary of the achievements, results, and lessons learned from LOPES. By digital, interferometric beamforming the detection of air showers became possible in the radio-loud environment of the Karlsruhe Institute of Technology (KIT). As a prototype experiment, LOPES tested several antenna types, array configurations and calibration techniques, and pioneered analysis methods for the reconstruction of the most important shower parameters, i.e., the arrival direction, the energy, and mass-dependent observables such as the position of the shower maximum. In addition to a review and update of previously published results, we also present new results based on end-to-end simulations including all known instrumental properties. For this, we applied the detector response to radio signals simulated with the CoREAS extension of CORSIKA, and analyzed them in the same way as measured data. Thus, we were able to study the detector performance more accurately than before, including some previously inaccessible features such as the impact of noise on the interferometric cross-correlation beam. These results led to several improvements, which are documented in this paper and can provide useful input for the design of future cosmic-ray experiments based on the digital radio-detection technique.

In acoustic systems, quantum spin Hall physics is rarely observed because the crucial ingredient spin-orbit coupling is missing. Here, the authors construct an acoustic crystal with synthetic spin-orbit coupling and observe gapless helical boundary states as well as spin flipping effect.

Variational methods have proven to be excellent tools to approximate the ground states of complex many-body Hamiltonians. Generic tools such as neural networks are extremely powerful, but their parameters are not necessarily physically motivated. Thus, an efficient parametrization of the wave function can become challenging. In this Letter we introduce a neural-network-based variational ansatz that retains the flexibility of these generic methods while allowing for a tunability with respect to the relevant correlations governing the physics of the system. We illustrate the success of this approach on topological, long-range correlated, and frustrated models. Additionally, we introduce compatible variational optimization methods for the exploration of low-lying excited states without symmetries that preserve the interpretability of the ansatz.

Research was conducted on the mechanical and anisotropic properties of 3-D printed plastics (PLA and ABS), and the prevailing orientation and deposition of additive layers. Samples were tested in accordance with ASTM D638 - Standard Test Method for Tensile Properties of Plastics. Five print orientations were tested, including 0°, 30°, 45°, 60°, and 90°. Six samples were tested in each orientation, with a total of 30 samples being tested in each iteration of the experiment. An initial, “proof of concept” iteration was conducted with PLA plastic, followed by a second iteration which tested both PLA and ABS.Testing was conducted and based on the hypothesis that the material printed in the 0° orientation (parallel to the direction of applied tension) would be stronger, and that the strength of test specimens would be largely dependent on orientation of the material. In contrast, it was believed that the strength of 90° samples (perpendicular to the direction of applied tension) would be largely dependent on the strength of the bonds formed during the layer by layer deposition of heated material, and comparatively weaker. This was largely proven during testing. Samples printed in the 0° orientation exhibited statistically higher properties of both stress and strain. Conversely, plastics printed in the 90° orientation exhibited statistically weaker properties. It was noted that samples printed in the 30°, 45°, and 60° orientations exhibited some measure of improved ductility, although this was not the focus of the study.

Phonon engineering enables tailored heat-transfer properties, controlled elastic and acoustic vibration propagation, and custom phonon-electron and phonon-photon interactions. Here, the authors present an approach for the observation and tunability of vibrational modes of nanocrystal superlattices.

ABSTRACT RNA viruses, such as hepatitis C virus (HCV), influenza virus, and SARS-CoV-2, are notorious for their ability to evolve rapidly under selection in novel environments. It is known that the high mutation rate of RNA viruses can generate huge genetic diversity to facilitate viral adaptation. However, less attention has been paid to the underlying fitness landscape that represents the selection forces on viral genomes, especially under different selection conditions. Here, we systematically quantified the distribution of fitness effects of about 1,600 single amino acid substitutions in the drug-targeted region of NS5A protein of HCV. We found that the majority of nonsynonymous substitutions incur large fitness costs, suggesting that NS5A protein is highly optimized. The replication fitness of viruses is correlated with the pattern of sequence conservation in nature, and viral evolution is constrained by the need to maintain protein stability. We characterized the adaptive potential of HCV by subjecting the mutant viruses to selection by the antiviral drug daclatasvir at multiple concentrations. Both the relative fitness values and the number of beneficial mutations were found to increase with the increasing concentrations of daclatasvir. The changes in the spectrum of beneficial mutations in NS5A protein can be explained by a pharmacodynamics model describing viral fitness as a function of drug concentration. Overall, our results show that the distribution of fitness effects of mutations is modulated by both the constraints on the biophysical properties of proteins (i.e., selection pressure for protein stability) and the level of environmental stress (i.e., selection pressure for drug resistance). IMPORTANCE Many viruses adapt rapidly to novel selection pressures, such as antiviral drugs. Understanding how pathogens evolve under drug selection is critical for the success of antiviral therapy against human pathogens. By combining deep sequencing with selection experiments in cell culture, we have quantified the distribution of fitness effects of mutations in hepatitis C virus (HCV) NS5A protein. Our results indicate that the majority of single amino acid substitutions in NS5A protein incur large fitness costs. Simulation of protein stability suggests viral evolution is constrained by the need to maintain protein stability. By subjecting the mutant viruses to selection under an antiviral drug, we find that the adaptive potential of viral proteins in a novel environment is modulated by the level of environmental stress, which can be explained by a pharmacodynamics model. Our comprehensive characterization of the fitness landscapes of NS5A can potentially guide the design of effective strategies to limit viral evolution.

Objective: To compare the predictive validity of the Bayley Scales of Infant Development, Second Edition (BSID-II) and the Bayley Scales of Infant and Toddler Development, Third Edition (Bayley-III) for cognitive function at early school age in very preterm infants. Methods: Seventy-seven former preterm infants (born

Comparative genomic approaches have been used to identify sites where mutations are under purifying selection and of functional consequence by searching for sequences that are conserved across distantly related species. However, the performance of these approaches has not been rigorously evaluated under population genetic models. Further, short-lived functional elements may not leave a footprint of sequence conservation across many species. We use simulations to study how one measure of conservation, the Genomic Evolutionary Rate Profiling (GERP) score, relates to the strength of selection (Nes). We show that the GERP score is related to the strength of purifying selection. However, changes in selection coefficients or functional elements over time (i.e. functional turnover) can strongly affect the GERP distribution, leading to unexpected relationships between GERP and Nes. Further, we show that for functional elements that have a high turnover rate, adding more species to the analysis does not necessarily increase statistical power. Finally, we use the distribution of GERP scores across the human genome to compare models with and without turnover of sites where mutations are under purifying selection. We show that mutations in 4.51% of the noncoding human genome are under purifying selection and that most of this sequence has likely experienced changes in selection coefficients throughout mammalian evolution. Our work reveals limitations to using comparative genomic approaches to identify deleterious mutations. Commonly used GERP score thresholds miss over half of the noncoding sites in the human genome where mutations are under purifying selection.

Machine-learning driven models have proven to be powerful tools for the identification of phases of matter. In particular, unsupervised methods hold the promise to help discover new phases of matter without the need for any prior theoretical knowledge. While for phases characterized by a broken symmetry, the use of unsupervised methods has proven to be successful, topological phases without a local order parameter seem to be much harder to identify without supervision. Here, we use an unsupervised approach to identify boundaries of the topological phases. We train artificial neural nets to relate configurational data or measurement outcomes to quantities like temperature or tuning parameters in the Hamiltonian. The accuracy of these predictive models can then serve as an indicator for phase transitions. We successfully illustrate this approach on both the classical Ising gauge theory as well as on the quantum ground state of a generalized toric code.

Pyrenestes finches have a bill size polymorphism thought to be maintained by disruptive selection. Here, the authors identify a single candidate region, including insulin-like growth factor 1, differentiating small and large bill size morphs and a wider region differentiating the mega-billed morph.

Abstract Direct or indirect exposure to an explosion can induce traumatic brain injury (TBI) of various severity levels. Primary TBI from blast exposure is commonly characterized by internal injuries, such as vascular damage, neuronal injury, and contusion, without external injuries. Current animal models of blast-induced TBI (bTBI) have helped to understand the deleterious effects of moderate to severe blast forces. However, the neurological effects of mild blast forces remain poorly characterized. Here, we investigated the effects caused by mild blast forces combining neuropathological, histological, biochemical and neurophysiological analysis. For this purpose, we employed a rodent blast TBI model with blast forces below the level that causes macroscopic neuropathological changes. We found that mild blast forces induced neuroinflammation in cerebral cortex, striatum and hippocampus. Moreover, mild blast triggered microvascular damage and axonal injury. Furthermore, mild blast caused deficits in hippocampal short-term plasticity and synaptic excitability, but no impairments in long-term potentiation. Finally, mild blast exposure induced proteolytic cleavage of spectrin and the cyclin-dependent kinase 5 activator, p35 in hippocampus. Together, these findings show that mild blast forces can cause aberrant neurological changes that critically impact neuronal functions. These results are consistent with the idea that mild blast forces may induce subclinical pathophysiological changes that may contribute to neurological and psychiatric disorders.

In this article, we review an important cytogenetic technique - fluorescence in situ hybridization (FISH) - which is used for obtaining spatial genomic and transcriptomic information. FISH is widely utilized in genomic and cell biological research as well as for diagnostic applications in preventive and reproductive medicine, and oncology. It is the gold standard technique for the detection of chromosomal abnormalities. Despite the high specificity of FISH and the possibility of direct quantitative imaging, some of its key limitations prevent its regular use in diagnostics. To promote the extensive use of FISH for these applications, limitations in assay time and probe consumption will need to be addressed. Microfluidic technologies hold great promise in improving exactly these parameters. In the past two decades, microtechnology has matured and enabled a new line of analysis tools for biomedical and chemical sciences. Incidentally, the convergence of microtechnology with microfluidics is starting to have a decisive impact in the field of medical diagnostics. By miniaturizing implementations of diagnostic assays, the special characteristics of fluid flow in small volumes can be leveraged to modify reaction kinetics and thus reagent delivery time of assays. Here we highlight selected important historical views on FISH, review its current implementations, and provide a perspective on the future developments and the micro-scale implementations of FISH. Keywords: Fluorescence in situ hybridization, Diagnostics, Tissue sections, Hybridization kinetics, Microfluidics

Dominance is difficult to measure in natural populations as it is confounded with fitness. Here, Huber et al. developed a new approach to co-estimate dominance and selection coefficients, and found that the observed relationship is best fit by a new model of dominance based on gene expression level.

Technical limitations in simultaneous microscopic visualization of HIV transcription from individual integration sites have curtailed progress in the field. Here the authors report a branched DNA in situ hybridization method for direct single-cell visualization of HIV DNA, RNA, and protein.

Shallow lakes and ponds constitute a significant number of water bodies worldwide. Many are heterotrophic, indicating that they are likely net contributors to global carbon cycling. Climate change is likely to have important impacts on these waterbodies. In this study, we examined two small Minnesota ponds; a permanent woodland pond and a temporary prairie pond. The woodland pond had lower levels of phosphorus and phytoplankton than the prairie pond. Using the open water oxygen method, we found the prairie pond typically had a higher level of gross primary production (GPP) and respiration (R) than the woodland pond, although the differences between the ponds varied with season. Despite the differences in GPP and R between the ponds the net ecosystem production was similar with both being heterotrophic. Since abundant small ponds may play an important role in carbon cycling and are likely to undergo changes in temperature and hydroperiod associated with climate change, understanding pond metabolism is critical in predicting impacts and designing management schemes to mitigate changes.

The radio technique is a promising method for detection of cosmic-ray air showers of energies around 100PeV and higher with an array of radio antennas. Since the amplitude of the radio signal can be measured absolutely and increases with the shower energy, radio measurements can be used to determine the air-shower energy on an absolute scale. We show that calibrated measurements of radio detectors operated in coincidence with host experiments measuring air showers based on other techniques can be used for comparing the energy scales of these host experiments. Using two approaches, first via direct amplitude measurements, and second via comparison of measurements with air shower simulations, we compare the energy scales of the air-shower experiments Tunka-133 and KASCADE-Grande, using their radio extensions, Tunka-Rex and LOPES, respectively. Due to the consistent amplitude calibration for Tunka-Rex and LOPES achieved by using the same reference source, this comparison reaches an accuracy of approximately 10% – limited by some shortcomings of LOPES, which was a prototype experiment for the digital radio technique for air showers. In particular we show that the energy scales of cosmic-ray measurements by the independently calibrated experiments KASCADE-Grande and Tunka-133 are consistent with each other on this level. Keywords: Cosmic rays, Radio detection, LOPES, Tunka-Rex, Tunka-133, KASCADE-Grande