bluuebunny/crossref_metadata_2025_split huggingface dataset:
Link between aging and atheroprotection in Mif-deficient atherosclerotic mice
Authors: Krammer Christine , Yang Bishan , Reichl Sabrina , Bolini Verena , Schulte Corinna , Noels Heidi , Bounkari Omar El , Kapurniotu Aphrodite , Weber Christian , Mohanta Sarajo , Bernhagen Jürgen 
Published: December 2021

AbstractAtherosclerosis is a lipid-triggered chronic inflammatory condition of our arteries and the main underlying pathology of myocardial infarction and stroke. Pathogenesis is age-dependent, but the mechanistic links between disease progression, age, and atherogenic cytokines and chemokines are incompletely understood. Here, we studied the chemokine-like inflammatory cytokine macrophage migration inhibitory factor (MIF) in atherogenic Apoe−/− mice across different stages of aging and cholesterol-rich high-fat diet (HFD). MIF promotes atherosclerosis by mediating atherogenic monocyte and T-cell recruitment, amplifying lesional inflammation, and suppressing atheroprotective B-cell responses. However, age-related links between atherogenesis and MIF and its role in advanced atherosclerosis in aged mice have not been systematically explored. We compared effects of global Mif-gene deficiency in 30-, 42-, and 48-week-old Apoe−/− mice on HFD for 24, 36, or 42 weeks, respectively, and in 52-week-old mice on a 6-week HFD. While a regio-specific atheroprotective phenotype of Mif-deficiency was observed in the 30/24-week-old group, atheroprotection was not detected in the 48/42- and 52/6-week-old groups, suggesting that atheroprotection afforded by global Mif-gene deletion differs across aging stages and atherogenic diet duration. We identify a combination of mechanisms that could explain this phenotype: i) Mif-deficiency promotes lesional Trem2+ macrophage numbers in younger but not aged mice; ii) Mif-deficiency favors formation of lymphocyte-rich stage-I/II ATLOs in younger mice but ATLO numbers equalize with those in Apoe−/− controls in the older mice; and iii) plasma anti-oxLDL-IgM antibody levels are decreased in aged Mif-deficient mice. Of note, these three markers (Trem2+ macrophages, ATLOs, anti-oxLDL-IgM antibodies) have been previously linked to atheroprotection. Together, our study thus suggests that regio-specific atheroprotection due to global Mif-gene deficiency in atherogenic Apoe−/− mice is lost upon advanced aging and identifies mechanisms that could explain this phenotype shift. These observations may have implications for translational MIF- directed strategies.
Genome editing excisase origins illuminated by somatic genome of Blepharisma
Authors: Singh Minakshi , Brandon Seah Kwee Boon , Emmerich Christiane , Singh Aditi , Woehle Christian , Huettel Bruno , Byerly Adam , Stover Naomi Alexandra , Sugiura Mayumi , Harumoto Terue , Swart Estienne Carl 
Published: December 2021

SummaryMassive DNA excision occurs regularly in ciliates, ubiquitous microbial eukaryotes with somatic and germline nuclei in the same cell. Tens of thousands of internally eliminated sequences (IESs) scattered throughout a copy of the ciliate germline genome are deleted during development of the streamlined somatic genome. Blepharisma represents one of the two earliest diverging ciliate classes, and, unusually, has dual pathways of somatic nuclear development, making it ideal for investigating the functioning and evolution of these processes. Here, we report the somatic genome assembly of Blepharisma stoltei strain ATCC 30299 (41 Mb), arranged as numerous alternative telomere-capped minichromosomes. This genome encodes eight PiggyBac transposase homologs liberated from transposons. All are subject to purifying selection, but just one, the putative IES excisase, has a complete catalytic triad. We propose PiggyBac homologs were ancestral excisases that enabled evolution of extensive, natural genome editing.
The ColR/S two-component system is a conserved determinant of host association across Pseudomonas species
Authors: Wiesmann Christina L. , Zhang Yue , Alford Morgan , Thoms David , Dostert Melanie , Wilson Andrew , Pletzer Daniel , Hancock Robert E. W. , Haney Cara H. 
Published: December 2021

SummaryMembers of the bacterial genus Pseudomonas form mutualistic, commensal and pathogenic associations with diverse hosts. The prevalence of host association across the genus suggests that symbiosis may be a conserved ancestral trait and that distinct symbiotic lifestyles may be more recently evolved. Here we show that the ColR/S two-component system, part of the Pseudomonas core genome, is functionally conserved between Pseudomonas aeruginosa and Pseudomonas fluorescens. Using plant rhizosphere colonization and virulence in a murine abscess model, we show that colR is required for commensalism with plants and virulence in animals. Comparative transcriptomics revealed that the ColR regulon has diverged between P. aeruginosa and P. fluorescens and deleting components of the ColR regulon revealed strain-specific, but not hostspecific, requirements for ColR-dependent genes. Collectively, our results suggest that ColR/S allows Pseudomonas to sense and respond to a host, but that the ColR-regulon has diverged between Pseudomonas strains with distinct lifestyles.
Simulated visual hallucinations in virtual reality enhance cognitive flexibility
Authors: Rastelli Clara , Greco Antonino , Kenett Yoed N. , Finocchiaro Chiara , De Pisapia Nicola 
Published: December 2021

ABSTRACTHistorically, psychedelic drugs are known to modulate cognitive flexibility, a central aspect of cognition permitting adaptation to changing environmental demands. Despite proof suggesting phenomenological similarities between artificially-induced and actual psychedelic altered perception, experimental evidence is still lacking about whether the former is also able to modulate cognitive flexibility. To address this, we measure participants’ cognitive flexibility through behavioral tasks after the exposure to virtual reality panoramic videos and their hallucinatory-like counterparts generated by the DeepDream algorithm. Results show that the estimated semantic network has a flexible structure when preceded by altered videos. Crucially, following the simulated psychedelic exposure, individuals also show an attenuated contribution of the automatic process and chaotic dynamics underlying the decision process. This suggests that simulated altered perceptual phenomenology enhances cognitive flexibility, presumably due to a reorganization in the cognitive dynamics that facilitates the exploration of uncommon decision strategies and inhibits automated choices.
The blackgrass genome reveals patterns of divergent evolution of non-target site resistance to herbicides
Authors: Cai Lichun , Comont David , MacGregor Dana , Lowe Claudia , Beffa Roland , Saski Christopher , Neve Paul 
Published: December 2021

SummaryGlobally, weedy plants result in more crop yield loss than plant pathogens and insect pests combined. Much of the success of weeds rests with their ability to rapidly adapt in the face of human-mediated environmental management and change. The evolution of resistance to herbicides is an emblematic example of this rapid adaptation. Here, we focus on Alopecurus myosuroides (blackgrass), the most impactful agricultural weed in Europe. To gain insights into the evolutionary history and genomic mechanisms underlying adaptation in blackgrass, we assembled and annotated its large, complex genome. We show that non-target site herbicide resistance is oligogenic and likely evolves from standing genetic variation. We present evidence for divergent selection of resistance at the level of the genome in wild, evolved populations, though at the transcriptional level, resistance mechanisms are underpinned by similar patterns of up-regulation of stress- and defence-responsive gene families. These gene families are expanded in the blackgrass genome, suggesting that the large, duplicated, and dynamic genome plays a role in enabling rapid adaptation in blackgrass. These observations have wide significance for understanding rapid plant adaptation in novel stressful environments.
Combined SHP2 and ERK inhibition for the treatment of KRAS-driven Pancreatic Ductal Adenocarcinoma
Authors: Ciecielski Katrin J. , Mulero-Sánchez Antonio , Berninger Alexandra , Cañas Laura Ruiz , Bosma Astrid , Görgülü Kıvanç , Wu Nan , Diakopoulos Kalliope N. , Kaya-Aksoy Ezgi , Ruess Dietrich A. , Kabacaoğlu Derya , Schmidt Fränze , Heinemann Larissa , Fan Yuhui , Thijssen Bram , van de Ven Marieke , Proost Natalie , Kossatz Susanne , Weber Wolfgang A. , Sainz Bruno , Bernards Rene , Algül Hana , Lesina Marina , Mainardi Sara 
Published: December 2021

AbstractMutant KRAS is present in over 90% of pancreatic as well as 30-40% of lung and colorectal cancers and is one of the most common oncogenic drivers. Despite decades of research and the recent emergence of isoform-specific KRASG12C-inhibitors, most mutant KRAS isoforms, including the ones frequently associated with pancreatic ductal adenocarcinoma (PDAC), cannot be targeted directly. Moreover, targeting single RAS downstream effectors induces adaptive mechanisms leading to tumor recurrence or resistance. We report here on the combined inhibition of SHP2, a non-receptor tyrosine phosphatase upstream of KRAS, and ERK, a serine/threonine kinase and a key molecule downstream of KRAS in PDAC. This combination shows synergistic anticancer activity in vitro, superior disruption of the MAPK pathway, and significantly increased apoptosis induction compared to single-agent treatments. In vivo, we demonstrate good tolerability and efficacy of the combination. Concurrent inhibition of SHP2 and ERK induces significant tumor regression in multiple PDAC mouse models. Finally, we show evidence that 18F-FDG PET scans can be used to detect and predict early drug responses in animal models. Based on these compelling results, we will investigate this drug combination in a clinical trial (SHERPA, SHP2 and ERK inhibition in pancreatic cancer, NCT04916236), enrolling patients with KRAS-mutant PDAC.
Effects of habitat destruction on coevolving metacommunities
Authors: Gawecka Klementyna A. , Pedraza Fernando , Bascompte Jordi 
Published: December 2021

AbstractHabitat destruction is a growing threat to biodiversity and ecosystem services. The ecological consequences of habitat loss and fragmentation involve reductions in species abundance and even the extinction of species and interactions. However, we do not yet understand how habitat loss can alter the coevolutionary trajectories of the remaining species or how coevolution, in turn, affects their response to habitat loss. To investigate this, we develop a spatially explicit model which couples metacommunity and coevolutionary dynamics. We show that, by changing the size, composition and structure of local networks, habitat destruction increases the diversity of coevolutionary outcomes across the landscape. Furthermore, we show that while coevolution dampens the negative effects of habitat destruction in mutualistic networks, its effects on the persistence of antagonistic communities are less predictable.
Computational analysis of the effect of SARS-CoV-2 variant Omicron Spike protein mutations on dynamics, ACE2 binding and propensity for immune escape
Authors: Teruel Natalia , Crown Matthew , Bashton Matthew , Najmanovich Rafael 
Published: December 2021

AbstractThe recently reported Omicron (B.1.1.529) SARS-CoV-2 variant has a large number of mutations in the Spike (S) protein compared to previous variants. Here we evaluate the potential effect of Omicron S mutations on S protein dynamics and ACE2 binding as contributing factors to infectivity as well as propensity for immune escape. We define a consensus set of mutations from 77 sequences assigned as Omicron in GISAID as of November 25. We create structural models of the Omicron S protein in the open and closed states, as part of a complex with ACE2 and for each of 77 complexes of S bound to different antibodies with known structures. We have previously utilized Dynamical Signatures (DS) and the Vibrational Entropy Score (VDS) to evaluate the propensity of S variants to favour the open state. Here, we introduce the Binding Influence Score (BIS) to evaluate the influence of mutations on binding affinity based on the net gain or loss of interactions within the protein-protein interface. BIS shows excellent correlation with experimental data (Pearson correlation coefficient of 0.87) on individual mutations in the ACE2 interface for the Alpha, Beta, Gamma, Delta and Omicron variants combined. On the one hand, the DS of Omicron highly favours a more rigid open state and a more flexible closed state with the largest VDS of all variants to date, suggesting a large increase in the chances to interact with ACE2. On the other hand, the BIS shows that apart from N501Y, all other mutations in the interface reduce ACE2 binding affinity. VDS and BIS show opposing effects on the overall effectiveness of Omicron mutations to promote binding to ACE2 and therefore initiate infection. To evaluate the propensity for immune escape we calculated the net change of favourable and unfavourable interactions within each S-antibody interface. The net change of interactions shows a positive score (a net increase of favourable interactions and decrease of unfavourable ones) for 41 out of 77 antibodies, a nil score for 15 and a negative score for 21 antibodies. Therefore, in only 28% of S-antibody complexes (21/77) we predict some level of immune escape due to a weakening of the interactions with Omicron S. Considering that most antibody epitopes and the mutations are within the S-ACE2 interface our results suggest that mutations within the RBD of Omicron may give rise to only partial immune escape, which comes at the expense of reduced ACE2 binding affinity. However, this reduced ACE2 affinity appears to have been offset by increasing the occupancy of the open state of the Spike protein.
Caveats to deep learning approaches to RNA secondary structure prediction
Authors: Flamm Christoph , Wielach Julia , Wolfinger Michael T. , Badelt Stefan , Lorenz Ronny , Hofacker Ivo L. 
Published: December 2021

AbstractMachine learning (ML) and in particular deep learning techniques have gained popularity for predicting structures from biopolymer sequences. An interesting case is the prediction of RNA secondary structures, where well established biophysics based methods exist. The accuracy of these classical methods is limited due to lack of experimental parameters and certain simplifying assumptions and has seen little improvement over the last decade. This makes RNA folding an attractive target for machine learning and consequently several deep learning models have been proposed in recent years. However, for ML approaches to be competitive for de-novo structure prediction, the models must not just demonstrate good phenomenological fits, but be able to learn a (complex) biophysical model. In this contribution we discuss limitations of current approaches, in particular due to biases in the training data. Furthermore, we propose to study capabilities and limitations of ML models by first applying them on synthetic data (obtained from a simplified biophysical model) that can be generated in arbitrary amounts and where all biases can be controlled. We assume that a deep learning model that performs well on these synthetic, would also perform well on real data, and vice versa. We apply this idea by testing several ML models of varying complexity. Finally, we show that the best models are capable of capturing many, but not all, properties of RNA secondary structures. Most severely, the number of predicted base pairs scales quadratically with sequence length, even though a secondary structure can only accommodate a linear number of pairs.
Childhood trajectories of internalising and externalising problems associated with a polygenic risk score for neuroticism in a UK birth cohort study
Authors: Costantini Ilaria , Sallis Hannah , Tilling Kate , Major-Smith Daniel , Pearson Rebecca M , Kounali Daphne-Zacharenia 
Published: December 2021

AbstractNeuroticism represents a personality disposition towards experiencing negative emotions more frequently and intensely. Longitudinal studies suggest that neuroticism increases risk of several psychological and physical problems. Improved understanding of how this trait manifests in early life could help inform preventative strategies in those liable to neuroticism.This study explored how a polygenic risk score (PRS) for neuroticism is expressed from infancy to late childhood across various psychological outcomes and how it associates with trajectories of internalising and externalising problems from ages 4-11 in the Avon Longitudinal Study of Parents and Children (N=5,279). We employed multivariable linear and ordinal regression models to estimate associations between a child neuroticism PRS and psychological outcomes. A three-level mixed-effect model was employed to characterise child internalising and externalising trajectories and estimate how a child PRS associated with both their overall levels and rates of change.We found evidence that the PRS for neuroticism was associated with a more sensitive temperament in early infancy in addition to higher emotional and behavioural problems and a higher risk of being diagnosed with a variety of clinical disorders, particularly anxiety disorders, in childhood. We also found strong evidence that the PRS for neuroticism was associated with overall levels of internalising and externalising trajectories, with a larger magnitude of effect on the internalising trajectory. The PRS was also associated with slower rates of reduction of internalising problems.Our findings using a large, well-characterised birth cohort study suggest that phenotypic manifestations of a PRS for adult neuroticism can be detected as early as in infancy and that this PRS associates with several mental health problems and differences in emotional trajectories across childhood.
Vaccines provide disproportional protection to the increased hospitalisation risk posed by the Delta variant of SARS-CoV2: a meta-analysis
Authors: Simons Mirre J P 
Published: December 2021

AbstractVariants of SARS-CoV2 that achieved global dominance (Alpha and Delta) have been associated with increased hospitalisation risk. A quantification of this risk across studies is currently lacking for Delta. Furthermore, how risk for severe disease changes in both vaccinated and unvaccinated individuals is important as the underlying risks determine public health impact. The surplus risk of Delta versus Alpha on hospitalisation was determined using random-effects meta-analysis. Infection with the Delta compared to the Alpha variant increased hospitalisation risk (unvaccinated: log HR 0.62, CI: 0.41 – 0.84, P < 0.0001; linear HR 1.87). This finding should inform our response to future variants of concern, currently Omicron. SARS-CoV2 variants that achieve dominance, have achieved this through a higher rate of infection and this evolutionary trajectory has also come with a correlated higher risk of severe disease. The surplus risk posed by Delta was significantly lower however in the vaccinated (model estimate -0.40, CI: -0.73 – -0.07, P = 0.017). Vaccination thus provided a disproportionate level of protection to hospitalisation with the Delta variant and provides further rationale for vaccination for SARS-CoV2 as a durable public health measure.
Potential severity, mitigation, and control of Omicron waves depending on pre-existing immunity and immune evasion
Authors: Bartha Ferenc A. , Boldog Péter , Tekeli Tamás , Vizi Zsolt , Dénes Attila , Röst Gergely 
Published: December 2021

AbstractWe assess the potential consequences of the upcoming SARS-CoV-2 waves caused by the Omicron variant. Our results suggest that even in those regions where the Delta variant is controlled at the moment by a combination of non-pharmaceutical interventions and population immunity, a significant Omicron wave can be expected. We stratify the population according to prior immunity status, and characterize the possible outbreaks depending on the population level of pre-existing immunity and the immune evasion capability of Omicron. We point out that two countries having similar effective reproduction numbers for the Delta variant can experience very different Omicron waves in terms of peak time, peak size and total number of infections among the high risk population.
Comparison of extraction methods for intracellular metabolomics
Authors: Andresen Carolin , Boch Tobias , Gegner Hagen M. , Mechtel Nils , Narr Andreas , Birgin Emrullah , Rasbach Erik , Rahbari Nuh , Trumpp Andreas , Poschet Gernot , Hübschmann Daniel 
Published: December 2021

AbstractMeasurements of metabolic compounds inside cells or tissues are of high informative potential since they represent the endpoint of biological information flow and a snapshot of the integration of many regulatory processes. However, it requires careful extraction to quantify their abundance. Here we present a comprehensive study using ten extraction protocols on four human sample types (liver tissue, bone marrow, HL60 and HEK cells) targeting 630 metabolites of different chemical classes. We show that the extraction efficiency and stability is highly variable across protocols and tissues by using different quality metrics including the limit of detection and variability between replicates as well as the sum of concentration as a global estimate of extraction stability. The profile of extracted metabolites depends on the used solvents - an observation which has implications for measurements of different sample types and metabolic compounds of interest. To identify the optimal extraction method for future metabolomics studies, the benchmark dataset was implemented in an easy-to-use, interactive and flexible online resource (R/shiny app MetaboExtract).