bluuebunny/crossref_metadata_2025_split huggingface dataset:
Rapid evaluation of COVID-19 vaccine effectiveness against VOC/VOIs by genetic mismatch
Authors: Cao Lirong , Lou Jingzhi , Zheng Hong , Zhao Shi , Mok Chris Ka Pun , Yi Chan Renee Wan , Chong Marc Ka Chun , Chen Zigui , Yi Wong Eliza Lai , Chan Paul Kay Sheung , Zee Benny Chung-Ying , Yeoh Eng Kiong , Wang Maggie Haitian 
Published: April 2021

AbstractTimely evaluation of the protective effects of COVID-19 vaccines is challenging but urgently needed to inform the pandemic control planning. Based on vaccine efficacy/effectiveness (VE) data of 11 vaccine products and 297,055 SARS-CoV-2 sequences collected in 20 regions, we analyzed the relationship between genetic mismatch of circulating viruses against the vaccine strain and VE. Variations from technology platforms are controlled by a mixed-effects model. We found that the genetic mismatch measured on the RBD is highly predictive for vaccine protection and accounted for 72.0% (p-value < 0.01) of the VE change. The NTD and S protein also demonstrate significant but weaker per amino acid substitution association with VE (p-values < 0.01). The model is applied to predict vaccine protection of existing vaccines against new genetic variants and is validated by independent cohort studies. The estimated VE against the delta variant is 79.3% (95% prediction interval: 67.0 – 92.1) using the mRNA platform, and an independent survey reported a close match of 83.0%; against the beta variant (B.1.351) the predicted VE is 53.8% (95% prediction interval: 39.9 – 67.4) using the viral-vector vaccines, and an observational study reported a close match of 48.0%. Genetic mismatch provides an accurate prediction for vaccine protection and offers a rapid evaluation method against novel variants to facilitate vaccine deployment and public health responses.
Inverting the model of genomics data sharing with the NHGRI Genomic Data Science Analysis, Visualization, and Informatics Lab-space (AnVIL)
Authors: Schatz Michael C. , Philippakis Anthony A. , Afgan Enis , Banks Eric , Carey Vincent J. , Carroll Robert J. , Culotti Alessandro , Ellrott Kyle , Goecks Jeremy , Grossman Robert L. , Hall Ira M. , Hansen Kasper D. , Lawson Jonathan , Leek Jeffrey T. , O’Donnell Luria Anne , Mosher Stephen , Morgan Martin , Nekrutenko Anton , O’Connor Brian D. , Osborn Kevin , Paten Benedict , Patterson Candace , Tan Frederick J. , Taylor Casey Overby , Vessio Jennifer , Waldron Levi , Wang Ting , Wuichet Kristin , Team AnVIL 
Published: April 2021

AbstractThe traditional model of genomic data analysis - downloading data from centralized warehouses for analysis with local computing resources - is increasingly unsustainable. Not only are transfers slow and cost prohibitive, but this approach also leads to redundant and siloed compute infrastructure that makes it difficult to ensure security and compliance of protected data. The NHGRI Genomic Data Science Analysis, Visualization, and Informatics Lab-space (AnVIL;https://anvilproject.org) inverts this model, providing a unified cloud computing environment for data storage, management, and analysis. AnVIL eliminates the need for data movement, allows for active threat detection and monitoring, and provides scalable, shared computing resources that can be acquired by researchers as needed. This presents many new opportunities for collaboration and data sharing that will ultimately lead to scientific discoveries at scales not previously possible.
Evolutionary rate covariation identifies SLC30A9 (ZnT9) as a mitochondrial zinc transporter
Authors: Kowalczyk Amanda , Gbadamosi Omotola , Kolor Kathryn , Sosa Jahree , St Croix Claudette , Gibson Gregory , Chikina Maria , Aizenman Elias , Clark Nathan , Kiselyov Kirill 
Published: April 2021

AbstractRecent advances in genome sequencing have led to the identification of new ion and metabolite transporters, many of which have not been characterized. Due to the variety of subcellular localizations, cargo and transport mechanisms, such characterization is a daunting task, and predictive approaches focused on the functional context of transporters are very much needed. Here we present a case for identifying a transporter localization using evolutionary rate covariation (ERC), a computational approach based on pairwise correlations of amino acid sequence evolutionary rates across the mammalian phylogeny. As a case study, we find that poorly characterized transporter SLC30A9 (ZnT9) uniquely and prominently coevolves with several components of the mitochondrial oxidative phosphorylation chain, suggesting mitochondrial localization. We confirmed this computational finding experimentally using recombinant human SLC30A9. SLC30A9 loss caused zinc mishandling in the mitochondria, suggesting that under normal conditions it acts as a zinc exporter. We therefore propose that ERC can be used to predict the functional context of novel transporters and other poorly characterized proteins.
The role of neural flexibility in cognitive aging
Authors: Varangis Eleanna , Qi Weiwei , Stern Yaakov , Lee Seonjoo 
Published: April 2021

AbstractStudies assessing relationships between brain and cognitive changes in healthy aging have shown that a variety of aspects of brain structure and function explain a significant portion of the variability in cognitive outcomes throughout adulthood. Many studies assessing relationships between brain function and cognition have utilized time-averaged, or static functional connectivity methods to explore ways in which brain network organization may contribute to aspects of cognitive aging. However, recent studies in this field have suggested that time-varying, or dynamic measures of functional connectivity, which assess changes in functional connectivity throughout a scan session, may play a stronger role in explaining cognitive outcomes in healthy young adults. Further, both static and dynamic functional connectivity studies suggest that there may be differences in patterns of brain-cognition relationships as a function of whether or not the participant is performing a task during the scan. Thus, the goals of the present study were threefold: (1) assess whether dynamic connectivity (neural flexibility) during both resting as well as task-based scans is related to participant age and cognitive performance in a lifespan aging sample, (2) determine whether neural flexibility moderates relationships between age and cognitive performance, and (3) explore differences in neural flexibility between rest and task. Participants in the study were 423 healthy adults between the ages of 20-80 who provided resting state and/or task-based (Matrix Reasoning) functional magnetic resonance imaging (fMRI) scan data as part of their participation in two ongoing studies of cognitive aging. Neural flexibility measures from both resting and task-based scans reflected the number of times each node changed network assignment, and were averaged both across the whole brain (global neural flexibility) as well as within nine somatosensory/cognitive networks. Results showed that neural flexibility during the task was higher in older adults, and that neural flexibility in Default Mode and Visual networks was negatively related to performance on the Matrix Reasoning task. Resting state neural flexibility was not significantly related to either participant age or cognitive performance. Additionally, no neural flexibility measures that significantly moderated relationships between participant age and cognitive outcomes. Further, neural flexibility differed as a function of scan type, with resting state neural flexibility exhibiting significantly more variability than task-based neural flexibility. Thus, neural flexibility measures computed during a cognitive task may be more strongly related to cognitive performance across the adult lifespan, and are more sensitive to the effects of participant age on brain organization.
Identification of essential β-oxidation genes and corresponding metabolites for estrogen degradation by actinobacteria
Authors: Hsiao Tsun-Hsien , Lee Tzong-Huei , Chuang Meng-Rong , Wang Po-Hsiang , Meng Menghsiao , Horinouchi Masae , Hayashi Toshiaki , Chen Yi-Lung , Chiang Yin-Ru 
Published: April 2021

SummarySteroidal estrogens (C18) are contaminants receiving increasing attention due to their endocrine-disrupting activities at sub-nanomolar concentrations. Although estrogens can be eliminated through photodegradation, microbial function is critical for removing estrogens from ecosystems devoid of sunlight exposure including activated sludge, soils, and aquatic sediments. Actinobacteria were found to be key estrogen degraders in manure-contaminated soils and estuarine sediments. Previously, we used the actinobacteriumRhodococcussp. strain B50 as a model microorganism to identify two oxygenase genes,aedAandaedB, involved in the activation and subsequent cleavage of the estrogenic A-ring, respectively. However, genes responsible for the downstream degradation of estrogen A/B-rings remained completely unknown. In this study, we employed tiered comparative transcriptomics, gene disruption experiments, and mass spectrometry–based metabolite profile analysis to identify estrogen catabolic genes. We observed the up-regulation of thiolase-encodingaedFandaedKin the transcriptome of strain B50 grown with estrone. Consistently, two downstream estrogenic metabolites, 5-oxo-4-norestrogenic acid (C17) and 2,3,4-trinorestrogenic acid (C15), were accumulated inaedF-andaedK-disrupted strain B50 cultures. Disruption offadD3[3aα-H-4α(3’-propanoate)-7aβ-methylhexahydro-1,5-indanedione (HIP)-coenzyme A ligase gene] in strain B50 resulted in apparent HIP accumulation in estrone-fed cultures, indicating the essential role offadD3in actinobacterial estrogen degradation. In addition, we detected a uniquemeta-cleavage product, 4,5-seco-estrogenic acid (C18), during actinobacterial estrogen degradation. Differentiating the estrogenic metabolite profile and degradation genes of actinobacteria and proteobacteria enables the cost-effective and time-saving identification of potential estrogen degraders in various ecosystems through liquid chromatography–mass spectrometry analysis and polymerase chain reaction–based functional assays.
Life-history predicts global population responses to the weather in the terrestrial mammals
Authors: Jackson John , Le Coeur Christie , Jones Owen R 
Published: April 2021

AbstractWith the looming threat of abrupt ecological disruption due to a changing climate, predicting which species are most vulnerable to environmental change is critical. The life-history of a species is an evolved response to its environmental context, and therefore a promising candidate for explaining differences in climate-change responses. However, we urgently need broad empirical assessments from across the worlds ecosystems to explore these predictions. Here, we use long-term abundance records from 157 species of terrestrial mammal and a two-step Bayesian meta-regression framework to investigate the link between annual weather anomalies, population growth rates, and species-level life-history. Overall, we found no consistent effect of temperature or precipitation anomalies on annual population growth rates. Furthermore, population responses to weather anomalies were not predicted by phylogenetic covariance, and instead there was variability in weather responses for populations within a species. Crucially, however, long-lived mammals with smaller litter sizes had responses with a reduced absolute magnitude compared to their shorter-living counterparts with larger litters. These results highlight the role of species-level life-history in driving responses to the environment.
Protein noise and distribution in a two-stage gene-expression model extended by an mRNA inactivation loop
Authors: Çelik Candan , Bokes Pavol , Singh Abhyudai 
Published: April 2021

AbstractChemical reaction networks involving molecular species at low copy numbers lead to stochasticity in protein levels in gene expression at the single-cell level. Mathematical modelling of this stochastic phenomenon enables us to elucidate the underlying molecular mechanisms quantitatively. Here we present a two-stage stochastic gene expression model that extends the standard model by an mRNA inactivation loop. The extended model exhibits smaller protein noise than the original two-stage model. Interestingly, the fractional reduction of noise is a non-monotonous function of protein stability, and can be substantial especially if the inactivated mRNA is stable. We complement the noise study by an extensive mathematical analysis of the joint steady-state distribution of active and inactive mRNA and protein species. We determine its generating function and derive a recursive formula for the protein distribution. The results of the analytical formula are cross-validated by kinetic Monte-Carlo simulation.
Incoherent modulation of bi-stable dynamics orchestrates the Mushroom and Isola bifurcations
Authors: Giri Amitava , Kar Sandip 
Published: April 2021

AbstractIn biological networks, steady state dynamics of cell-fate regulatory genes often exhibit Mushroom and Isola kind of bifurcations. How these complex bifurcations emerge for these complex networks, and what are the minimal network structures that can generate these bifurcations, remain elusive. Herein, by employing Waddington’s landscape theory and bifurcation analysis, we have shown that both Mushroom and Isola bifurcations can be realized with four minimal network motifs that are constituted by combining positive feedback motifs with different types of incoherent feedback motifs. Our study demonstrates that the intrinsic bi-stable dynamics due to the presence of the positive feedback motif can be fine-tuned by altering the extent of the incoherence of these proposed minimal networks to orchestrate these complex bifurcations. These modeling insights will be useful in identifying and analyzing possible network motifs that may give rise to either Mushroom or Isola bifurcation in other biological systems.
On the Reconstruction of Magnetic Resonance Current Density Images of the Human Brain: Pitfalls and Perspectives
Authors: Eroğlu Hasan H. , Puonti Oula , Göksu Cihan , Gregersen Fróði , Siebner Hartwig R. , Hanson Lars G. , Thielscher Axel 
Published: April 2021

ABSTRACTMagnetic resonance current density imaging (MRCDI) of the human brain aims to reconstruct the current density distribution caused by transcranial electric stimulation from MR-based measurements of the current-induced magnetic fields. The reconstruction problem is challenging due to a low signal-to-noise ratio and a limited volume coverage of the MR-based measurements, the lack of data from the scalp and skull regions and because MRCDI is only sensitive to the component of the current-induced magnetic field parallel to the scanner field. Most existing reconstruction approaches have been validated using simulation studies and measurements in phantoms with simplified geometries. Only one reconstruction method, the projected current density algorithm, has been applied to human in-vivo data so far, however resulting in blurred current density estimates even when applied to noise-free simulated data.We analyze the underlying causes for the limited performance of the projected current density algorithm when applied to human brain data. In addition, we compare it with an approach that relies on the optimization of the conductivities of a small number of tissue compartments of anatomically detailed head models reconstructed from structural MR data. Both for simulated ground truth data and human in-vivo MRCDI data, our results indicate that the estimation of current densities benefits more from using a personalized volume conductor model than from applying the projected current density algorithm. In particular, we introduce a hierarchical statistical testing approach as a principled way to test and compare the quality of reconstructed current density images that accounts for the limited signal-to-noise ratio of the human in-vivo MRCDI data and the fact that the ground truth of the current density is unknown for measured data. Our results indicate that the statistical testing approach constitutes a valuable framework for the further development of accurate volume conductor models of the head. Our findings also highlight the importance of tailoring the reconstruction approaches to the quality and specific properties of the available data.
Acoustic properties across the human skull
Authors: Riis Thomas , Webb Taylor , Kubanek Jan 
Published: April 2021

AbstractTranscranial ultrasound is emerging as a noninvasive tool for targeted treatments of brain disorders. Transcranial ultrasound has been used for remotely mediated surgeries, transient opening of the blood-brain barrier, local drug delivery, and neuromodulation. However, all applications have been limited by the severe attenuation and phase distortion of ultrasound by the skull. Here, we characterized the dependence of the aberrations on specific anatomical segments of the skull. In particular, we measured ultrasound propagation properties throughout the perimeter of intact human skulls at 500 kHz. We found that the parietal bone provides substantially higher transmission (average pressure transmission 31±7%) and smaller phase distortion (242±44 degrees) than frontal (13±2%, 425±47 degrees) and occipital bone regions (16±4%, 416±35 degrees). In addition, we found that across skull regions, transmission strongly anti-correlated (R= −0.79) and phase distortion correlated (R= 0.85) with skull thickness. This information guides the design, positioning, and skull correction functionality of next-generation devices for effective, safe, and reproducible transcranial focused ultrasound therapies.
Ubiquitination of G3BP1 mediates stress granule disassembly in a stress-specific manner
Authors: Gwon Youngdae , Maxwell Brian A. , Kolaitis Regina-Maria. , Zhang Peipei , Kim Hong Joo , Taylor J. Paul 
Published: April 2021

AbstractStress granules are dynamic, reversible condensates composed of RNA and protein that assemble in response to a variety of stressors and are normally disassembled after stress is removed. Whereas the composition of stress granules and the mechanisms underlying their assembly have been extensively studied, far less is known about the mechanisms that govern disassembly. Impaired disassembly has been implicated in some diseases. Here we report that stress granule disassembly is context-dependent and, in the setting of heat shock, requires ubiquitination of G3BP1, the central protein within the stress granule RNA-protein network. Ubiquitinated G3BP1 interacts with the ER-resident protein FAF2, which engages the ubiquitin-dependent segregase p97/VCP. Targeting G3BP1 enables the stress granule-specific interaction network to fall below the percolation threshold for phase separation, which causes disassembly.One Sentence SummaryUbiquitination of G3BP1 mediates FAF2- and p97/VCP-dependent disassembly of heat-induced stress granules
Ubiquitination is essential for recovery of cellular activities following heat shock
Authors: Maxwell Brian A. , Gwon Youngdae , Mishra Ashutosh , Peng Junmin , Zhang Ke , Kim Hong Joo , Taylor J. Paul 
Published: April 2021

AbstractEukaryotic cells respond to stress via adaptive programs that include reversible shutdown of key cellular processes, the formation of stress granules, and a global increase in ubiquitination. The primary function of this ubiquitination is generally considered to be tagging damaged or misfolded proteins for degradation. Here we show that different types of stress generate distinct ubiquitination patterns. For heat stress, ubiquitination correlates with cellular activities that are downregulated during stress, including nucleocytoplasmic transport and translation, as well as with stress granule constituents. Ubiquitination is not required for the shutdown of these processes or for stress granule formation, but is essential for resumption of cellular activities and for stress granule disassembly. These findings indicate that stress-induced ubiquitination primes the cell for recovery following heat stress.One Sentence SummaryStress-induced ubiquitination is essential for recovery of cellular activities following heat stress.
Disbalance of the intestinal epithelial cell turnover and apoptosis in a rat model of sporadic Alzheimer’s disease
Authors: Homolak Jan , Perhoc Ana Babic , Knezovic Ana , Barilar Jelena Osmanovic , Koc Fatma , Stanton Catherine , Ross R. Paul , Salkovic-Petrisic Melita 
Published: April 2021

AbstractBackgroundDyshomeostasis of the gastrointestinal (GI) system is investigated as a potential contributor to metabolic dysfunction, systemic and neuro-inflammation recognized as important pathophysiological drivers of neurodegeneration. Gastrointestinal redox dyshomeostasis and dysfunctional brain-gut incretin axis have been reported in the rat model of insulin-resistant brain state (IRBS)-driven neurodegeneration induced by intracerebroventricular administration of streptozotocin (STZ-icv). The aim was to assess i) whether GI oxidative stress is accompanied by structural and functional changes of the epithelial barrier; ii) whether the brain glucose-dependent insulinotropic polypeptide receptor (GIP-R) is also involved in redox regulation of the gut; and iii) whether the STZ-icv brain-gut axis is resistant to pharmacological inhibition of the brain GIP-R.MethodsForty three-month-old male Wistar rats were treated with 3mg/kg STZ-icv or vehicle. One month later the animals were randomized to receive either saline or 85 μg/kg GIP-R inhibitor [Pro3]-GIP intracerebroventricularly and sacrificed 30 minutes later. Thiobarbituric acid reactive substances (TBARS) were measured in plasma and duodenum. Duodenal sections were subjected to morphometric analysis. Caspase-3 expression and activation were analyzed by western blot and spatial signal analysis was done by multiplex fluorescent signal amplification (MFSA). Data were analyzed by linear and linear mixed modeling, and exploration was done by principal component analysis.ResultsInhibition of the brain GIP-R decreased plasma TBARS in the controls and the STZ-icv animals and increased duodenal TBARS only in the controls. Acute inhibition of brain GIP-R affects duodenal epithelial cell, but not villus structure, while all morphometric parameters were altered in the STZ-icv-treated animals. Morphometric changes in the STZ-icv animals were accompanied by reduced levels of activated and total regulator of apoptosis – caspase-3. Acute inhibition of brain GIP-R inactivated duodenal apoptosis at the level of caspase-3 activation.ConclusionsBrain GIP-R is involved in the regulation of the systemic and duodenal redox homeostasis and epithelial function. Duodenal oxidative stress in the STZ-icv rats is accompanied by the resistance of the brain-gut GIP axis and morphological changes indicative of abnormal epithelial cell turnover and dysfunctional GI barrier. Dysfunction of the brain-gut incretin axis might be an important etiopathogenetic factor in neurodegeneration and a potential pharmacological target.