bluuebunny/crossref_metadata_2025_split huggingface dataset:
TheThermosynechococcusgenus: wide environmental distribution, but a highly conserved genomic core
Authors: Prondzinsky A. Paulina , Berkemer Sarah J. , Ward Lewis M. , McGlynn Shawn E. 
Published: October 2020

AbstractCyanobacteria thrive in very diverse environments. However, questions remain about possible growth limitations in ancient environmental conditions. As a single genus, theThermosynechococcusare cosmopolitan and live in chemically diverse habitats. To understand the genetic basis for this, we compared the protein coding component ofThermosynechococcusgenomes. Supplementing the known genetic diversity ofThermosynechococcus, we report draft metagenome-assembled genomes of twoThermosynechococcusrecovered from ferrous carbonate hot springs in Japan. We find that as a genus,Thermosynechococcusis genomically conserved, having a small pan-genome with few accessory genes per individual strain and only 14 putative orthologous protein groups appearing in allThermosynechococcusbut not in any other cyanobacteria in our analysis. Furthermore, by comparing orthologous protein groups, including an analysis of genes encoding proteins with an iron related function (uptake, storage or utilization), no clear differences in genetic content, or adaptive mechanisms could be detected between genus members, despite the range of environments they inhabit. Overall, our results highlight a seemingly innate ability forThermosynechococcusto inhabit diverse habitats without having undergone substantial genomic adaptation to accommodate this. The finding ofThermosynechococcusin both hot and high iron environments without adaptation recognizable from the perspective of the proteome has implications for understanding the basis of thermophily within this clade, and also for understanding the possible genetic basis for high iron tolerance in cyanobacteria on early Earth. The conserved core genome may be indicative of an allopatric lifestyle – or reduced genetic complexity of hot spring habitats relative to other environments.
Self-activation of Wnt signaling in pre-granulosa cells is required for ovarian folliculogenesis
Authors: Habara Okiko , Logan Catriona Y. , Kanai-Azuma Masami , Nusse Roeland , Takase Hinako M. 
Published: October 2020

SummaryIn mammalian ovaries, immature oocytes are reserved in primordial follicles. Precise control of primordial follicle activation (PFA) is a prerequisite for proper reproduction. Although Wnt signaling is thought to be involved in folliculogenesis, the timing and function of Wnt activity remain unclear. Here we show that canonical Wnt signaling is pivotal for the differentiation of pre-granulosa cells (pre-GCs) and subsequent oocyte maturation during PFA. We identified severalWntligands expressed in pre-GCs that cell-autonomously function via canonical Wnt activity. Inhibition of Wnt ligand secretion from pre-GCs/GCs led to infertility due to impaired pre-GC differentiation, whereas constitutive stabilization of β-catenin induced thickening of the pre-GCs. Our data support a two-step model of PFA in which self-activation of Wnt signaling promotes the transition of pre-GCs to GCs, and mature GCs then support oocyte reawakening. We anticipate that application of Wnt inhibitors or activators in vitro will lead to improved fertility treatments.
Inferring spatially transient gene expression pattern from spatial transcriptomic studies
Authors: Kueckelhaus Jan , von Ehr Jasmin , Ravi Vidhya M. , Will Paulina , Joseph Kevin , Beck Juergen , Hofmann Ulrich G. , Delev Daniel , Schnell Oliver , Heiland Dieter Henrik 
Published: October 2020

AbstractSpatial transcriptomic is a technology to provide deep transcriptomic profiling by preserving the spatial organization. Here, we present a framework for SPAtial Transcriptomic Analysis (SPATA,https://themilolab.github.io/SPATA), to provide a comprehensive characterization of spatially resolved gene expression, regional adaptation of transcriptional programs and transient dynamics along spatial trajectories.
The magnitude of airway remodelling is not altered by distinct allergic inflammatory responses in BALB/c vs C57BL/6 mice but matrix composition differs
Authors: Parkinson James E , Pearson Stella , Rückerl Dominik , Allen Judith E , Sutherland Tara E 
Published: October 2020

AbstractAllergic airway inflammation is heterogenous with variability in immune phenotypes observed across asthmatic patients. Inflammation has been thought to directly contribute to airway remodelling in asthma, but clinical data suggests that neutralising type 2 cytokines does not necessarily alter disease pathogenesis. Here, we utilised C57BL/6 and BALB/c mice to investigate the development of allergic airway inflammation and remodelling. Exposure to an allergen cocktail for up to 8 weeks led to type 2 and type 17 inflammation, characterized by airway eosinophilia and neutrophilia and increased expression of chitinase-like proteins in both C75BL/6 and BALB/c mice. However, BALB/c mice developed much greater inflammatory responses than C57BL/6 mice, effects possibly explained by a failure to induce pathways that regulate and maintain T cell activation in C57BL/6 mice, as shown by whole lung RNA transcript analysis. Allergen administration resulted in a similar degree of airway remodelling between mouse strains but with differences in collagen subtype composition. Increased collagen III was observed around the airways of C57BL/6 but not BALB/c mice while allergen-induced loss of basement membrane collagen IV was only observed in BALB/c mice. This study highlights a model of type 2/type 17 airway inflammation in mice whereby development of airway remodelling can occur in both BALB/c and C57BL/6 mice despite differences in immune response dynamics between strains. Importantly, compositional changes in the ECM between genetic strains of mice may help us better understand the relationships between lung function, remodelling and airway inflammation.
Experience-dependent alteration of mnemonic representation in early visual cortex and intraparietal sulcus
Authors: Jia Ke , Li Ya , Gong Mengyuan , Huang Hui , Wang Yonghui , Li Sheng 
Published: October 2020

AbstractThe ability to discriminate between stimuli relies on a chain of neural operations associated with perception, memory and decision-making. Accumulating studies show learning-dependent plasticity in perception or decision-making, yet whether perceptual learning modifies mnemonic processing remains unclear. Here, we trained participants on an orientation discrimination task, while using fMRI and TMS to separately examine training-induced changes in working memory (WM) representation. Although fMRI decoding revealed orientation-specific neural patterns during delay period in early visual cortex (V1) before, but not after, training, neurodisruption of V1 during delay period led to behavioral deficit in both phases. In contrast, both fMRI decoding and disruptive effect of TMS showed that intraparietal sulcus (IPS) represent WM content after, but not before, training. These results suggest that sensory engagement for WM is relatively independent of training but the coding format may be altered, whereas the involvement of parietal area in WM depends on training.
DSTG: Deconvoluting Spatial Transcriptomics Data through Graph-based Artificial Intelligence
Authors: Su Jing , Song Qianqian 
Published: October 2020

AbstractRecent development of spatial transcriptomics (ST) is capable of associating spatial information at different spots in the tissue section with RNA abundance of cells within each spot, which is particularly important to understand tissue cytoarchitectures and functions. However, for such ST data, since a spot is usually larger than an individual cell, gene expressions measured at each spot are from a mixture of cells with heterogenous cell types. Therefore, ST data at each spot needs to be disentangled so as to reveal the cell compositions at that spatial spot. In this study, we propose a novel method, named DSTG, to accurately deconvolute the observed gene expressions at each spot and recover its cell constitutions, thus achieve high-level segmentation and reveal spatial architecture of cellular heterogeneity within tissues. DSTG not only demonstrates superior performance on synthetic spatial data generated from different protocols, but also effectively identifies spatial compositions of cells in mouse cortex layer, hippocampus slice, and pancreatic tumor tissues. In conclusion, DSTG accurately uncovers the cell states and subpopulations based on spatial localization.
Improving power while controlling the false discovery rate when only a subset of peptides are relevant
Authors: Lin Andy , Plubell Deanna L. , Keich Uri , Noble William S. 
Published: October 2020

AbstractThe standard proteomics database search strategy involves searching spectra against a peptide database and estimating the false discovery rate (FDR) of the resulting set of peptide-spectrum matches. One assumption of this protocol is that all the peptides in the database are relevant to the hypothesis being investigated. However, in settings where researchers are interested in a subset of peptides, alternative search and FDR control strategies are needed. Recently, two methods were proposed to address this problem: subset-search and all-sub. We show that both methods fail to control the FDR. For subset-search, this failure is due to the presence of “neighbor” peptides, which are defined as irrelevant peptides with a similar precursor mass and fragmentation spectrum as a relevant peptide. Not considering neighbors compromises the FDR estimate because a spectrum generated by an irrelevant peptide can incorrectly match well to a relevant peptide. Therefore, we have developed a new method, “filter then subsetneighbor search” (FSNS), that accounts for neighbor peptides. We show evidence that FSNS properly controls the FDR when neighbors are present and that FSNS outperforms group-FDR, the only other method able to control the FDR relative to a subset of relevant peptides.
Deep learning model fitting for diffusion-relaxometry: a comparative study
Authors: Grussu Francesco , Battiston Marco , Palombo Marco , Schneider Torben , Gandini Wheeler-Kingshott Claudia A. M. , Alexander Daniel C. 
Published: October 2020

AbstractQuantitative Magnetic Resonance Imaging (qMRI) signal model fitting is traditionally performed via non-linear least square (NLLS) estimation. NLLS is slow and its performance can be affected by the presence of different local minima in the fitting objective function. Recently, machine learning techniques, including deep neural networks (DNNs), have been proposed as robust alternatives to NLLS. Here we present a deep learning implementation of qMRI model fitting, which uses DNNs to perform the inversion of the forward signal model. We compare two DNN training strategies, based on two alternative definitions of the loss function, since at present it is not known which definition leads to the most accurate, precise and robust parameter estimation. In strategy 1 we define the loss as thel2-norm of tissue parameter prediction errors, while in strategy 2 as thel2-norm of MRI signal prediction errors. We compare the two approaches on synthetic and 3Tin vivosaturation inversion recovery (SIR) diffusion-weighted (DW) MRI data, using a model for joint diffusion-T1 mapping. Strategy 1 leads to lower tissue parameter root mean squared errors (RMSEs) when realistic noise distributions are considered (e.g. Rician vs Gaussian). However, strategy 2 offers lower signal reconstruction RMSE, and allows training to be performed on both synthetic and actualin vivoMRI measurements. In conclusion, both strategies are valid choices for DNN-based fitting. Strategy 2 is more practical, as it does not require pre-computation of reference tissue parameters, but may lead to worse parameter estimation.
Hippocampal replay of experience at real-world speeds
Authors: Denovellis Eric L. , Gillespie Anna K. , Coulter Michael E. , Sosa Marielena , Chung Jason E. , Eden Uri T. , Frank Loren M. 
Published: October 2020

AbstractRepresentations related to past experiences play a critical role in memory and decision-making processes. The rat hippocampus expresses these types of representations during sharp-wave ripple (SWR) events, and previous work identified a minority of SWRs that contain “replay” of spatial trajectories at ~20x the movement speed of the animal. Efforts to understand replay typically make multiple assumptions about which events to examine and what sorts of representations constitute replay. We therefore lack a clear understanding of both the prevalence and the range of representational dynamics associated with replay. Here we develop a state space model that uses a combination of movement dynamics of different speeds to capture the spatial content and time evolution of replay during SWRs. Using this model, we find that the large majority of replay events contain spatially coherent, interpretable content. Furthermore, many events progress at real-world, rather than accelerated, movement speeds, consistent with actual experiences.
HOXA9 promotes MYC-mediated leukemogenesis by maintaining gene expression for multiple anti-apoptotic pathways
Authors: Miyamoto Ryo , Kanai Akinori , Okuda Hiroshi , Takahashi Satoshi , Matsui Hirotaka , Inaba Toshiya , Yokoyama Akihiko 
Published: October 2020

AbstractHOXA9 is often highly expressed in leukemias. However, its precise roles in leukemogenesis remain elusive. Here, we show that HOXA9 maintains gene expression for multiple anti-apoptotic pathways to promote leukemogenesis. InMLL-rearranged leukemia, MLL fusion directly activates the expression of MYC and HOXA9. Combined expression of MYC and HOXA9 induced leukemia, whereas single gene transduction of either did not, indicating a synergy between MYC and HOXA9. HOXA9 sustained expression of the genes implicated to the hematopoietic precursor identity when expressed in hematopoietic precursors, but did not reactivate it once silenced. Among the HOXA9 target genes,BCL2andSOX4synergistically induced leukemia withMYC. Not only BCL2, but also SOX4 suppressed apoptosis, indicating that multiple anti-apoptotic pathways underlie cooperative leukemogenesis by HOXA9 and MYC. These results demonstrate that HOXA9 is a key transcriptional maintenance factor which promotes MYC-mediated leukemogenesis, potentially explaining why HOXA9 is highly expressed in many leukemias.
Girdin regulates dendrite morphogenesis and cilium position in two specialized sensory neuron types inC. elegans
Authors: Nechipurenko Inna , Lavrentyeva Sofia , Sengupta Piali 
Published: October 2020

ABSTRACTPrimary cilia are located at the dendritic tips of sensory neurons and house the molecular machinery necessary for detection and transduction of sensory stimuli. The mechanisms that coordinate dendrite extension with cilium position during sensory neuron development are not well understood. Here, we show that GRDN-1, theCaenorhabditis elegansortholog of the highly conserved scaffold and signaling protein Girdin/GIV, regulates both cilium position and dendrite extension in the postembryonic AQR and PQR gas-sensing neurons. Mutations ingrdn-1disrupt dendrite outgrowth and mislocalize cilia to the soma or proximal axonal segments in AQR, and to a lesser extent, in PQR. GRDN-1 is localized to the basal body and regulates localization of HMR-1/Cadherin to the distal AQR dendrite. However, loss of HMR-1 and/or SAX-7/LICAM, molecules previously implicated in sensory dendrite development inC. elegans, do not alter AQR dendrite morphology or cilium position. We demonstrate that GRDN-1 localization in AQR is regulated by UNC-116/Kinesin-1, and that correspondingly,unc-116mutants exhibit severe AQR dendrite outgrowth and cilium positioning defects. In contrast, GRDN-1 and cilium localization in PQR is modulated by LIN-44/Wnt signaling. Together, these findings identify upstream regulators of GRDN-1, and describe new cellspecific roles for this multifunctional protein in sensory dendrite development.
Multidimensional face representation in deep convolutional neural network reveals the mechanism underlying AI racism
Authors: Tian Jinhua , Xie Hailun , Hu Siyuan , Liu Jia 
Published: October 2020

AbstractThe increasingly popular application of AI runs the risks of amplifying social bias, such as classifying non-white faces to animals. Recent research has attributed the bias largely to data for training. However, the underlying mechanism is little known, and therefore strategies to rectify the bias are unresolved. Here we examined a typical deep convolutional neural network (DCNN), VGG-Face, which was trained with a face dataset consisting of more white faces than black and Asian faces. The transfer learning result showed significantly better performance in identifying white faces, just like the well-known social bias in human, the other-race effect (ORE). To test whether the effect resulted from the imbalance of face images, we retrained the VGG-Face with a dataset containing more Asian faces, and found a reverse ORE that the newly-trained VGG-Face preferred Asian faces over white faces in identification accuracy. In addition, when the number of Asian faces and white faces were matched in the dataset, the DCNN did not show any bias. To further examine how imbalanced image input led to the ORE, we performed the representational similarity analysis on VGG-Face’s activation. We found that when the dataset contained more white faces, the representation of white faces was more distinct, indexed by smaller ingroup similarity and larger representational Euclidean distance. That is, white faces were scattered more sparsely in the representational face space of the VGG-Face than the other faces. Importantly, the distinctiveness of faces was positively correlated with the identification accuracy, which explained the ORE observed in the VGG-Face. In sum, our study revealed the mechanism underlying the ORE in DCNNs, which provides a novel approach of study AI ethics. In addition, the face multidimensional representation theory discovered in human was found also applicable to DCNNs, advocating future studies to apply more cognitive theories to understand DCNN’s behavior.
The collapse of the spindle following ablation in S. pombe is mediated by microtubules and the motor protein dynein
Authors: Zareiesfandabadi Parsa , Elting Mary Williard 
Published: October 2020

A microtubule-based machine called the mitotic spindle segregates chromosomes when eukaryotic cells divide. In the fission yeastS. pombe, which undergoes closed mitosis, the spindle forms a single bundle of microtubules inside the nucleus. During elongation, the spindle extends via antiparallel microtubule sliding by molecular motors. These extensile forces from the spindle are thought to resist compressive forces from the nucleus. We probe the mechanism and maintenance of this force balance via laser ablation of spindles at various stages of mitosis. We find that spindle pole bodies collapse toward each other following ablation, but spindle geometry is often rescued, allowing spindles to resume elongation. While this basic behavior has been previously observed, many questions remain about this phenomenon’s dynamics, mechanics, and molecular requirements. In this work, we find that previously hypothesized viscoelastic relaxation of the nucleus cannot fully explain spindle shortening in response to laser ablation. Instead, spindle collapse requires microtubule dynamics and is powered at least partly by the minus-end directed motor protein dynein. These results suggest a role for dynein in redundantly supporting force balance and bipolarity in theS. pombespindle.STATEMENT OF SIGNIFICANCES. pombeserves as an important model organism for understanding cell division. Its structurally simple mitotic spindle is especially suited for mechanical perturbation. SinceS. pombeundergoes a process of closed cell division, without breakdown of the nuclear envelope, force may be exerted between its nuclear envelope and spindle. Here, we mechanically sever spindles via laser ablation to probe this force balance. Following ablation,S. pombespindle fragments collapse toward each other. We find that, contrary to prior expectations, forces from the chromosomes and nuclear envelope are not responsible for this collapse. Instead, it is microtubule-dependent, and is powered at least in part by the minus-end directed microtubule motor protein dynein.
The molecular basis ofAcinetobacter baumanniicadmium toxicity and resistance
Authors: Alquethamy Saleh F. , Adams Felise G. , Maharjan Ram , Delgado Natasha N. , Zang Maoge , Paton James C. , Hassan Karl A. , Paulsen Ian T. , McDevitt Christopher A. , Cain Amy K. , Eijkelkamp Bart A. 
Published: October 2020

ABSTRACTAcinetobacterspecies are ubiquitous Gram-negative bacteria that can be found in water, soil and as commensals of the human skin. The successful inhabitation ofAcinetobacterspecies in diverse environments is primarily attributable to the expression of an arsenal of stress resistance determinants, which includes an extensive repertoire of metal ion efflux systems. Although metal ion homeostasis in the hospital pathogenAcinetobacter baumanniiis known to contribute to pathogenesis, insights into its metal ion transporters for environmental persistence are lacking. Here, we studied the impact of cadmium stress onA. baumannii. Our functional genomics and independent mutant analyses revealed a primary role for CzcE, a member of the cation diffusion facilitator (CDF) superfamily, in resisting cadmium stress. Further, we show that the CzcCBA heavy metal efflux system also contributes to cadmium efflux. Analysis of theA. baumanniimetallome under cadmium stress showed zinc depletion and copper enrichment, which are likely to influence cellular fitness. Overall, this work expands our understanding of the role of membrane transporters inA. baumanniimetal ion homeostasis.IMPORTANCECadmium toxicity is a widespread problem, yet the interaction of this heavy metal with biological systems is poorly understood. Some microbes have evolved traits to proactively counteract cadmium toxicity, which includesAcinetobacter baumannii. Here we show thatA. baumanniiutilises a dedicated cadmium efflux protein in concert with a system that is primarily attuned to zinc efflux, to efficiently overcome cadmium stress. The molecular characterization ofA. baumanniiunder cadmium stress revealed how active cadmium efflux plays a key role in preventing the dysregulation of bacterial metal ion homeostasis, which appeared to be the primary means by which cadmium exerts toxicity upon the bacterium.