bluuebunny/crossref_metadata_2025_split huggingface dataset:
Moving Beyond Processing and Analysis-Related Variation in Neuroscience
Authors: Li Xinhui , Esper Nathalia Bianchini , Ai Lei , Giavasis Steve , Jin Hecheng , Feczko Eric , Xu Ting , Clucas Jon , Franco Alexandre , Heinsfeld Anibal Sólon , Adebimpe Azeez , Vogelstein Joshua T. , Yan Chao-Gan , Esteban Oscar , Poldrack Russell A. , Craddock Cameron , Fair Damien , Satterthwaite Theodore , Kiar Gregory , Milham Michael P. 
Published: December 2021

AbstractWhen fields lack consensus standard methods and accessible ground truths, reproducibility can be more of an ideal than a reality. Such has been the case for functional neuroimaging, where there exists a sprawling space of tools and processing pipelines. We provide a critical evaluation of the impact of differences across five independently developed minimal preprocessing pipelines for functional MRI. We show that even when handling identical data, inter-pipeline agreement was only moderate, critically shedding light on a factor that limits cross-study reproducibility. We show that low inter-pipeline agreement mainly becomes appreciable when the reliability of the underlying data is high, which is increasingly the case as the field progresses. Crucially, we show that when inter-pipeline agreement is compromised, so too are the consistency of insights from brainwide association studies. We highlight the importance of comparing analytic configurations, as both widely discussed and commonly overlooked decisions can lead to marked variation.
A framework for defining livestock ecotypes based on ecological modelling and exploring genomic environmental adaptation: the example of Ethiopian village chicken
Authors: Vallejo-Trujillo Adriana , Kebede Adebabay , Lozano-Jaramillo Maria , Dessie Tadelle , Smith Jacqueline , Hanotte Olivier , Gheyas Almas 
Published: December 2021

AbstractIn evolutionary ecology, an ecotype is a population that is genetically adapted to specific environmental conditions. Environmental and genetic characterisation of livestock ecotypes can play a crucial role in conservation and breeding improvement, particularly to achieve climate resilience. However, livestock ecotypes are often arbitrarily defined without a detailed characterisation of their agro-ecologies. In this study, we employ a novel integrated approach, combining Ecological Niche Modelling (ENM) with genomics, to delineate ecotypes based on environmental characterisation of population habitats and unravel the signatures of adaptive selection in the ecotype genomes. The method was applied on 25 Ethiopian village chicken populations representing diverse agro-climatic conditions. ENM identified six key environmental drivers of adaptation and delineated 12 ecotypes. Within- ecotype selection signature analyses (using Hp and iHS methods) identified 1,056 candidate sweep regions (SRs) associated with diverse biological processes. A few biological pathways were shared amongst most ecotypes and the involved genes showed functions important for scavenging chickens, e.g. neuronal development/processes, immune response, vision development, and learning. Genotype-environment association using Redundancy Analysis (RDA) allowed for correlating ∼33% of the SRs with major environmental drivers. Inspection of some strong candidate genes from selection signature analysis and RDA showed highly relevant functions in relation to the major environmental drivers of corresponding ecotypes. This integrated approach offers a powerful tool to gain insight into the complex processes of adaptive evolution including the genotype x environment (GxE) interactions.
Efficiently, accurately, intelligently dissecting bamboo: characteristic of vascular bundle in Phyllostachys
Authors: Xu Haocheng , Zhang Ying , Wang Jiajun , Zhong Tuhua , Ma Xinxin , Li Jing , Wang Hankun 
Published: December 2021

AbstractA comprehensive understanding of vascular bundles is the key to elucidate the excellent intrinsic mechanical properties of bamboo. This research aims to investigate the gradient distribution of fiber volume fraction and the gradient changes in the shape of vascular bundles along the radial axis in Phyllostachys. We constructed a universal transfer-learning-based vascular bundle detection model with high precision of up to 96.97%, which can help to acquire the characteristics of vascular bundles quickly and accurately. The total number of vascular bundles, total fiber sheath area, the length, width and area of fiber sheath of individual vascular bundles within the entire cross-section were counted, and the results showed that these parameters had a strongly positive linear correlation with the outer circumference and wall thickness of bamboo culms, but the fiber volume fraction (around 25.5 %) and the length-to-width ratio of the vascular bundles (around 1.226) were relatively constant. Furthermore, we layered the cross section of bamboo according to the wall thickness finely and counted the characteristics of vascular bundle in each layer. The results showed that the radial distribution of fiber volume fraction decreased exponentially, the radial distribution of the length-to-width ratio of vascular bundle decreased quadratically, the radial distribution of the width of vascular bundle increased linearly. The trends of the gradient change in vascular bundle’s characteristics were found highly consistent among 29 bamboo species in Phyllostachys.One sentence summaryA universal vascular bundle detection model can efficiently dissect vascular bundles in Phyllostachys, and the radial gradient change of vascular bundles in cross-section are found highly consistent.
Foundation Model Enables Interpretable Open and Error-Tolerant Searching for Mass Spectrometry-Based Proteomics
Authors: Altenburg Tom , Muth Thilo , van Zalm Patrick , Steen Hanno , Renard Bernhard Y. 
Published: December 2021

AbstractMass spectrometry-based proteomics allows to study all proteins of a sample on a molecular level. However, mass spectra are noisy and contain complex patterns, making them inherently challenging to analyze with purely algorithmic approaches. In terms of the protein sequence landscape, most recent bottom-up MS-based proteomics studies consider either a diverse pool of post-translational modifications, employ large databases – as in metaproteomics or proteogenomics, study multiple isoforms of proteins, include unspecific cleavage sites or even combinations thereof. All this makes peptide and protein identifications challenging due to sheer size of the search space. To cope with this two-sided challenge, i.e. the complexity of real spectra and the search space size, we present a foundation model, called yHydra, that jointly embeds spectra and peptides. This allows us to implement various downstream tasks and search modes in Euclidean space. In particular, we implement an open search which allows to query multiple ten-thousands of spectra against millions of peptides. Furthermore, we implement an error-tolerant search for identifying additional proteoforms that are not included in off-the-shelf reference proteomes. Our foundation model provides meaningful embeddings, as we interpret learned peptide embeddings in comparison to the peptide’s physico-chemical properties. yHydra’s open search, assigns delta masses to each identification which allows to unrestrictedly characterize post-translational modifications. The error-tolerant mode of yHydra can be used as post-processing to existing search engines or as a standalone. yHydra is evaluated on several real life data sets for the identification of modified protein sequences and shows up to 25% increase in protein identification at constant false discovery rate compared to the current state-of-the-art.Availability(under MIT license)https://gitlab.com/dacs-hpi/yHydraContactbernhard.renard@hpi.de
The SPICA Coarse-Grained Force Field for Proteins and Peptides
Authors: Kawamoto Shuhei , Liu Huihui , Seo Sangjae , Miyazaki Yusuke , Dixit Mayank , DeVane Russell , MacDermaid Christopher , Fiorin Giacomo , Klein Michael L. , Shinoda Wataru 
Published: December 2021

ABSTRACTA coarse-grained (CG) model for peptides and proteins was developed as an extension of the SPICA (Surface Property fItting Coarse grAined) force field (FF). The model was designed to examine membrane proteins that are fully compatible with the lipid membranes of the SPICA FF. A preliminary version of this protein model was created using thermodynamic properties, including the surface tension and density in the SPICA (formerly called SDK) FF. In this study, we improved the CG protein model to facilitate molecular dynamics (MD) simulation with a reproduction of multiple properties from both experiments and all-atom (AA) simulations. The side chain analogs reproduced the transfer free energy profiles across the lipid membrane and demonstrated reasonable dimerization free energies in water compared to those from AA-MD. A series of peptides/proteins adsorbed or penetrated into the membrane simulated by the CG-MD correctly predicted the penetration depths and tilt angles of peripheral and transmembrane peptides/proteins comparable to those in the orientation of protein in membrane (OPM) database. In addition, the dimerization free energies of several transmembrane helices within a lipid bilayer were comparable to those from experimental estimation. Application studies on a series of membrane protein assemblies, scramblases, and poliovirus capsids demonstrated a good performance of the SPICA FF.
Redox-active secondary metabolites act as interspecies modulators of antibiotic resilience
Authors: Meirelles Lucas A. , Newman Dianne K. 
Published: December 2021

ABSTRACTBacterial opportunistic pathogens make a wide range of secondary metabolites both in the natural environment and when causing infections, yet how these molecules mediate microbial interactions and their consequences for antibiotic treatment are still poorly understood. Here, we explore the role of two redox-active secondary metabolites, pyocyanin and toxoflavin, as interspecies modulators of antibiotic resilience. We find that these molecules dramatically change susceptibility levels of diverse bacteria to clinical antibiotics. Pyocyanin is made by Pseudomonas aeruginosa, while toxoflavin is made by Burkholderia gladioli, organisms that infect cystic fibrosis and other immunocompromised patients. Both molecules alter the susceptibility profile of pathogenic species within the “Burkholderia cepacia complex” to different antibiotics, either antagonizing or potentiating their effects, depending on the drug’s class. Defense responses regulated by the redox-sensitive transcription factor SoxR potentiate the antagonistic effects these metabolites have against fluoroquinolones, and the presence of genes encoding SoxR and the efflux systems it regulates can be used to predict how these metabolites will affect antibiotic susceptibility of different bacteria. Finally, we demonstrate that inclusion of secondary metabolites in standard protocols used to assess antibiotic resistance can dramatically alter the results, motivating the development of new tests for more accurate clinical assessment.
Serum Amyloid A promotes Acetaminophen-induced liver injury by damaging sinusoidal endothelial cell and exacerbating platelet aggregation in liver
Authors: You Kai , Wang Yan , Chen Xiaoxia , Yang Zhen , Chen Yan , Tan Shenglin , Tao Jiawang , Getachew Anteneh , Pan Tingcai , Xu Yingying , Zhuang Yuanqi , Yang Fan , Lin Xianhua , Li Yinxiong 
Published: December 2021

AbstractBackgroundAcetaminophen (APAP) is the most commonly used non-prescription antipyretic and analgesic drugs. Overuse of APAP can cause hepatotoxicity. Liver sinusoidal endothelial cells (LSECs) damage is an important early event in APAP-induced liver injury. Serum amyloid A (SAA) is an acute phase protein that mainly produced by hepatocytes, and promotes endothelial dysfunction via a pro-inflammatory and pro-thrombotic effect in atherosclerosis and renal disease. However, the role of SAA in APAP-induced liver injury remains unclear.MethodsIn this study, we used neutralizing antibody (anti-SAA) or antagonistic small peptide derived from sequence of human SAA1/2 (SAA-pep) to block the functional activity of Saa1/2 in mouse serum. Immunohistochemistry staining, Evans blue and platelet adhesion assays were performed to examine the liver damage, the integrity of sinusoidal endothelium and platelets accumulation in APAP-induce liver injury.ResultsOur study showed that in the early stage of APAP-induced acute liver injury in mice, the intrahepatic and serum Saa1/2 levels were significantly increased within 24 hours, and then gradually reduced to normal level from 3 days. Neutralization of Saa1/2 by antibodies or peptides effectively prevented the destruction of hepatic sinusoids, reduced the intrahepatic hemorrhage and platelet accumulation in liver, as well as increased the survival rate of mice treated with lethal dose of APAP. In vitro experiments showed that Saa1/2 aggravated LSECs death induced by APAP. Moreover, Saa1/2 promoted platelets adhesion on LSECs via Tlr2/Vcam-1 axis.ConclusionOur findings suggest that Saa1/2 promotes APAP-induced liver injury by damaged LSECs and exacerbated platelets aggregation. This study provides a potential target for intervention of acute liver injury/failure caused by hepatotoxic drugs such as APAP.
Bacterial community response to species overrepresentation or omission is strongly influenced by life in spatially structured habitats
Authors: Kleyer Hannah , Tecon Robin , Or Dani 
Published: December 2021

AbstractVariations in type and strength of interspecific interactions in natural bacterial communities (e.g., synergistic to inhibitory) affect species composition and community functioning. The extent of interspecific interactions is often modulated by environmental factors that constrain diffusion pathways and cell mobility and limit community spatial arrangement. We studied how spatially structured habitats affect interspecific interactions and influence the resulting bacterial community composition. We used a bacterial community made of 11 well-characterized species that grew in porous habitats (comprised of glass beads) under controlled hydration conditions or in liquid habitats. We manipulated the initial community composition by overrepresenting or removing selected members, and observed community composition over time. Life in porous media reduced the number and strength of interspecific interactions compared to mixed liquid culture, likely due to spatial niche partitioning in porous habitats. The community converged to similar species composition irrespective of the initial species mix, however, the dominant bacterial species was markedly different between liquid culture and structured porous habitats. Moreover, differences in water saturation levels of the porous medium affected community assembly highlighting the need to account for habitat structure and physical conditions to better understand and interpret assembly of bacterial communities. We point at the modulation of bacterial interactions due to spatial structuring as a potential mechanism for promoting community stability and species coexistence, as observed in various natural environments such as soil or human gut.ImportanceBacteria live as complex multispecies communities essential for healthy and functioning ecosystems ranging from soil to the human gut. The bacterial species that form these communities can have positive or negative impact on each other, promoting or inhibiting each other’s growth. Yet, the factors controlling the balance of such interactions in nature, and how these influence the community, are not fully understood. Here, we show that bacterial interactions are modified by life in spatially structured bacterial habitats. These conditions exert important control over the resulting bacterial community regardless of initial species composition. The study demonstrates limitations of inferences from bacterial communities grown in liquid culture relative to behaviour in structured natural habitats such as soil.
Dynamic utilization of low-molecular-weight organic substrates across a microbial growth rate gradient
Authors: Cyle K. Taylor , Klein Annaleise R. , Aristilde Ludmilla , Martínez Carmen Enid 
Published: December 2021

AbstractConstantly in flux, low-molecular-weight organic substances (LMWOSs) are at the nexus between microorganisms, plant roots, detritus, and the soil mineral matrix. Nominal oxidation state of carbon (NOSC) has been put forward as one way to parameterize microbial uptake rates of LMWOSs and efficiency of carbon incorporation into new biomass. In this study, we employed an ecophysiological approach to test these proposed relationships using targeted exometabolomics (1H-NMR, HR-LCMS) coupled with stable isotope (13C) probing. We assessed the role of compound class and oxidation state on uptake kinetics and substrate-specific carbon use efficiency (SUE) during the growth of three model soil microorganisms (Penicillium spinulosum,Paraburkholderia solitsugae,andRalstonia pickettii) in media containing 34 common LMWOSs. Microbial isolates were chosen to span a gradient in growth rate (0.046-0.316 hr−1) and differ phylogenetically (a fungal isolate and two bacterial isolates). Clustered, co-utilization of LMWOSs occured for all three organisms, but temporal cluster separation was most apparent forP. solitsugae. Potential trends (p <0.05) for early utilization of more oxidized substrates were present for the two bacterial isolates (P. solitsugaeandR. pickettii), but high variability (R2> 0.15) and a small effect of NOSC indicate these are not useful relationships for prediction. The SUEs ranged from 0.16-0.99 and the hypothesized inverse relationship between NOSC and SUE was not observed. Thus, our results do not provide compelling support for NOSC as a predictive tool, implying that metabolic strategies of organisms may be more important than chemical identity in determining LMWOS cycling in soils.ImportanceCommunity-level observations from soils indicate that low-molecular-weight compounds of higher oxidation state tend to be depleted from soil solution faster and incorporated less efficiently into microbial biomass under oxic conditions. Here, we tested hypothetical relationships between substrate chemical characteristics and the order of substrate utilization by aerobic heterotrophs at the population-level in culture, using two bacterial isolates (Ralstonia pickettiiandParaburkholderia solitsugae) and one fungal isolate from soil (Penicillium spinulosum). We found weak relationships indicating earlier uptake of more oxidized substrates by the two bacterial isolates but no relationship for the fungal isolate. We found no relationship between substrate identity and substrate use efficiency. Our findings indicate that substrate chemical characteristics have limited utility for modeling the depletion of low-molecular-weight organics from soil solution and incorporation into biomass over broader phylogenetic gradients.
Structural basis of dynamic P5CS filaments
Authors: Zhong Jiale , Guo Chen-Jun , Zhou Xian , Chang Chia-Chun , Yin Boqi , Zhang Tianyi , Hu Huan-Huan , Lu Guang-Ming , Liu Ji-Long 
Published: December 2021

AbstractThe bifunctional enzyme Δ1-pyrroline-5-carboxylate synthase (P5CS) is central to the synthesis of proline and ornithine. Pathogenic mutations in P5CS gene (ALDH18A1) lead to neurocutaneous syndrome and skin relaxation connective tissue disease in humans, and P5CS deficiency seriously damages the ability to resist adversity in plants, which has an essential role in agriculture and human health. Recently, P5CS has been demonstrated forming the cytoophidium in vivo and filaments in vitro. However, the underlying mechanism for the function of P5CS filamentation and catalyze the synthesis of P5C is hardly accessible without structural basis. Here, we have succeeded in determining the full-length structures of Drosophila P5CS filament in three states at resolution from 3.1 to 4.3 Å under cryo-electron microscopy, we observed the distinct ligand-binding states and conformational changes for GK and GPR domain separately. These structures show the distinctive spiral filament is assembled by P5CS tetramers and stabilized by multiple interfaces. Point mutations that deplete such interactions disturb P5CS filamentation and greatly reduce the activity. Our findings reveal a previously undescribed mechanism that filamentation is crucial for the coordination between GK and GPR domains, and provide insights into structural basis for catalysis function of P5CS filament.
Sex Differences in Affective States and Association with Voluntary Ethanol Intake in Sprague Dawley Rats
Authors: Quadir SG , Arleth GM , Jahad JV , Sanchez M Echeveste , Herman MA 
Published: December 2021

ABSTRACTAlcohol use disorders (AUDs) are a major problem across the United States. While AUD remains a complex human condition, it is difficult to isolate the directionality of anxiety and ethanol (EtOH) drinking from outside influences. The present study sought to investigate the relationship between affective states and EtOH intake using male and female Sprague Dawley rats. Using complementary tests of anxiety- and depressive-like behavior, we found sex- and test-specific differences in basal affective behavior such that females displayed enhanced anxiety-like behavior in the Splash Test and males displayed enhanced anxiety-like behavior in the Novelty Suppressed Feeding Test. Although there were no sex differences in EtOH intake and no correlation between anxiety-like behavior and subsequent EtOH intake, we did find that depressive-like behavior predicted future EtOH intake in females rats only. In addition, we observed an increase in depressive-like behavior is male rats in both the water and EtOH drinking groups. Furthermore, anxiety-like behavior, but not depressive-like behavior predicted subsequent EtOH intake in female rats. Lastly, we found a history of EtOH intake decreased pain thresholds in male and female rats. Together, these experiments provide important information on the complex interaction between negative affect and alcohol intake and how these two contexts reciprocally do, or do not, influence each other in a sex-specific manner.
U-CIE [/juː ‘siː/]: Color encoding of high-dimensional data
Authors: Koutrouli Mikaela , Morris John H. , Jensen Lars J. 
Published: December 2021

ABSTRACTData visualization is essential to discover patterns and anomalies in large high-dimensional datasets. New dimensionality reduction techniques have thus been developed for visualizing omics data, in particular from single-cell studies. However, jointly showing several types of data, e.g. single-cell expression and gene networks, remains a challenge. Here, we present ‘U-CIE, a visualization method that encodes arbitrary high-dimensional data as colors using a combination of dimensionality reduction and the CIELAB color space to retain the original structure to the extent possible. U-CIE first uses UMAP to reduce high-dimensional data to three dimensions, partially preserving distances between entities. Next, it embeds the resulting three-dimensional representation within the CIELAB color space. This color model was designed to be perceptually uniform, meaning that the Euclidean distance between any two points should correspond to their relative perceptual difference. Therefore, the combination of UMAP and CIELAB thus results in a color encoding that captures much of the structure of the original high-dimensional data. We illustrate its broad applicability by visualizing single-cell data on a protein network and metagenomic data on a world map and on scatter plots.