bluuebunny/crossref_metadata_2025 huggingface dataset:
Electron cryo-microscopy of Bacteriophage PR772 reveals the composition and structure of the elusive vertex complex and the capsid architecture
Authors: Reddy Hemanth. K. N. , Hajdu Janos , Carroni Marta , Svenda Martin
Published: May 2019

Bacteriophage PR772, a member of theTectiviridaefamily, has a 70-nm diameter icosahedral protein capsid that encapsulates a lipid membrane, dsDNA, and various internal proteins. An icosahedrally averaged CryoEM reconstruction of the wild-type virion and a localized reconstruction of the vertex region reveals the composition and the structure of the vertex complex along with new protein conformations that play a vital role in maintaining the capsid architecture of the virion. The overall resolution of the virion is 2.75 Å, while the resolution of the protein capsid is 2.3 Å. The conventional penta-symmetron formed by the capsomeres is replaced by a large vertex complex in the pseudo T=25 capsid. All the vertices contain the host-recognition protein, P5; two of these vertices show the presence of the receptor-binding protein, P2. The 3D structure of the vertex complex shows interactions with the viral membrane, indicating a possible mechanism for viral infection.
Weaker neural suppression in autism
Authors: Schallmo Michael-Paul , Kolodny Tamar , Kale Alexander M. , Millin Rachel , Flevaris Anastasia V. , Edden Richard A.E. , Gerdts Jennifer , Bernier Raphael A. , Murray Scott O.
Published: May 2019

Increased neural excitation resulting from weakened inhibition is a leading hypothesis for the pathophysiology of autism. However, experimental support in humans remains equivocal. Alternatively, modulatory processes that suppress neural responses but do not specifically rely on inhibition may be impacted in ASD. Leveraging well-characterized suppressive neural circuits in the visual system, we used behavioral and fMRI tasks to demonstrate a significant reduction in neural suppression in young adults with ASD compared to neurotypical controls. We further tested the mechanism of this suppression by measuring levels of the inhibitory neurotransmitter GABA, and found no differences in GABA between groups. We show how a computational model that incorporates divisive normalization, as well as narrower top-down gain (that could result, for example, from a narrower window of attention), can explain our observations and divergent previous findings. Thus, weaker neural suppression in ASD may be attributable to differences in top-down processing, but not to differences in GABA levels.
Personality and local brain structure: their shared genetic basis and reproducibility
Authors: Valk Sofie L. , Hoffstaedter Felix , Camilleri Julia A. , Kochunov Peter , Thomas Yeo B.T. , Eickhoff Simon B.
Published: May 2019

Local variation in cortical architecture is highly heritable and distinct genes are associated with specific cortical regions. Total surface area has been shown to be genetically correlated with complex cognitive capacities, suggesting cortical brain structure is a viable endophenotype linking genes to behavior. However, to what extend local brain structure has a genetic association with cognitive and emotional functioning is incompletely understood. Here, we study the genetic correlation between personality traits and local cortical structure in a large-scale twin sample (Human Connectome Project, n=1106, 22-37y). We found a genetic overlap between personality traits and local cortical structure in 10 of 17 observed phenotypic associations in predominantly frontal cortices. To evaluate the robustness of observed personality-brain associations we studied two independent age-matched samples (GSP: n=926, age=19-35y, eNKI: n=210, age: 19-39y). We observed anecdotal to moderate evidence for a successful replication of the negative association between surface area in medial prefrontal cortex and Neuroticism in both samples. Quantitative functional decoding indicated this region is implicated in emotional and socio-cognitive functional processes. In sum, our observations suggest that associations between local brain structure and personality are, in part, under genetic control. However, associations are weak and only the relation between frontal surface area and Neuroticism was consistently observed across three independent samples of young adults.
Intermittent theta burst stimulation at personalized targets reduces the functional connectivity of the default mode network in healthy subjects
Authors: Singh Aditya , Erwin-Grabner Tracy , Sutcliffe Grant , Paulus Walter , Dechent Peter , Antal Andrea , Goya-Maldonado Roberto
Published: May 2019

Understanding the mechanisms by which transcranial magnetic stimulation protocols exert changes in the default mode network (DMN) is paramount to develop therapeutically more effective approaches in the future. A full session (3000 pulses) of 10 Hz repetitive transcranial magnetic stimulation (HF-rTMS) reduces the functional connectivity (FC) of the DMN and the subgenual anterior cingulate cortex but current understanding of the effects of a single session of intermittent theta burst stimulation (iTBS) on the DMN in healthy subjects is limited. To reduce the effects of inter-individual variability in functional architectures, we used a novel personalized target selection approach based on each subject’s resting state fMRI for an unprecedented investigation into the effects of a single session (1800 pulses) of iTBS over the DMN in healthy controls. 26 healthy subjects participated in a double-blind, crossover, sham-controlled study. After iTBS to the personalized left dorsolateral prefrontal cortex (DLPFC) targets, we investigated the time lapse of effects in the DMN and its relationship to the harm avoidance (HA) personality trait measure (Temperament and Character Inventory/TCI). Approx. 25-30 minutes after stimulation, we observed reduced FC between the DMN and the rostral anterior cingulate cortex (rACC). About 45 minutes after stimulation the FC of rACC strongly decreased further, as did the FC of right anterior insula (rAI) with the DMN. We also report a positive correlation between the FC decrease in the rACC and the HA domain of TCI. Our results show how iTBS at personalized left-DLPFC targets reduces the FC between DMN and the rACC and rAI, regions typically described as nodes of the salience network. We find that HA scores can potentially predict iTBS response, as has been observed for HF-rTMS.
Visual epidural field potentials possess high functional specificity in single trials
Authors: Fischer Benjamin , Schander Andreas , Kreiter Andreas K. , Lang Walter , Wegener Detlef
Published: May 2019

Recordings of epidural field potentials (EFPs) allow to acquire neuronal activity over a large region of cortical tissue with minimal invasiveness. Because electrodes are placed on top of the dura and do not enter the neuronal tissue, EFPs offer intriguing options for both clinical and basic science research. On the other hand, EFPs represent the integrated activity of larger neuronal populations, possess a higher trial-by-trial variability, and a reduced signal-to-noise ratio due the additional barrier of the dura. It is thus unclear whether and to what extent EFPs have sufficient spatial selectivity to allow for conclusions about the underlying functional cortical architecture, and whether single EFP trials provide enough information on the short time scales relevant for many clinical and basic neuroscience purposes. We here use the high spatial resolution of primary visual cortex to address these issues and investigate the extent to which very short EFP traces allow reliable decoding of spatial information. We briefly presented different visual objects at one out of nine closely adjacent locations and recorded neuronal activity with a high-density, epidural multi-electrode array in three macaque monkeys. Using receiver-operating characteristics to identify most-informative data, machine-learning algorithms provided close-to-perfect classification rates for all 27 stimulus conditions. A binary classifier applying a simple max function on ROC-selected data further showed that single trials might be classified with 100% performance even without advanced offline classifiers. Thus, although highly variable, EFPs constitute an extremely valuable source of information and offer new perspectives for minimally invasive recording of large-scale networks.
Multiplex secretome engineering enhances recombinant protein production and purity
Authors: Kol Stefan , Ley Daniel , Wulff Tune , Decker Marianne , Arnsdorf Johnny , Gutierrez Jahir M. , Chiang Austin W.T. , Pedersen Lasse Ebdrup , Kildegaard Helene Faustrup , Lee Gyun Min , Lewis Nathan E.
Published: May 2019

Host cell proteins (HCPs) are process-related impurities generated during biotherapeutic protein production. HCPs can be problematic if they pose a significant metabolic demand, degrade product quality, or contaminate the final product. Here, we present an effort to create a “clean” Chinese hamster ovary (CHO) cell by disrupting multiple genes to eliminate HCPs. Using a model of CHO cell protein secretion, we predicted the elimination of unnecessary HCPs could have a non-negligible impact on protein production. We analyzed the total HCP content of 6-protein, 11-protein, and 14-protein knockout clones and characterized their growth in shake flasks and bioreactors. These cell lines exhibited a substantial reduction in total HCP content (40%-70%). We also observed higher productivity and improved growth characteristics, in specific clones. With the reduced HCP content, protein A and ion exchange chromatography more efficiently purified a monoclonal antibody (mAb) produced in these cells during a three-step purification process. Thus, substantial improvements can be made in protein titer and purity through large-scale HCP deletion, providing an avenue to increased quality and affordability of high-value biopharmaceuticals.
Sensory Processing and Categorization in Cortical and Deep Neural Networks
Authors: Pinotsis Dimitris A. , Siegel Markus , Miller Earl K.
Published: May 2019

Many recent advances in artificial intelligence (AI) are rooted in visual neuroscience. However, ideas from more complicated paradigms like decision-making are less used. Although automated decision-making systems are ubiquitous (driverless cars, pilot support systems, medical diagnosis algorithms etc.), achieving human-level performance in decision making tasks is still a challenge. At the same time, these tasks that are hard for AI are easy for humans. Thus, understanding human brain dynamics during these decision-making tasks and modeling them using deep neural networks could improve AI performance. Here we modelled some of the complex neural interactions during a sensorimotor decision making task. We investigated how brain dynamics flexibly represented and distinguished between sensory processing and categorization in two sensory domains: motion direction and color. We used two different approaches for understanding neural representations. We compared brain responses to 1) the geometry of a sensory or category domain (domain selectivity) and 2) predictions from deep neural networks (computation selectivity). Both approaches gave us similar results. This confirmed the validity of our analyses. Using the first approach, we found that neural representations changed depending on context. We then trained deep recurrent neural networks to perform the same tasks as the animals. Using the second approach, we found that computations in different brain areas also changed flexibly depending on context. Color computations appeared to rely more on sensory processing, while motion computations more on abstract categories. Overall, our results shed light to the biological basis of categorization and differences in selectivity and computations in different brain areas. They also suggest a way for studying sensory and categorical representations in the brain: compare brain responses to both a behavioral model and a deep neural network and test if they give similar results.
Genomics of clinal local adaptation inPinus sylvestrisunder continuous environmental and spatial genetic setting
Authors: Tyrmi Jaakko S. , Vuosku Jaana , Acosta Juan J. , Li Zhen , Sterck Lieven , Cervera Maria T. , Savolainen Outi , Pyhäjärvi Tanja
Published: May 2019

Understanding the consequences of local adaptation at the genomic diversity is a central goal in evolutionary genetics of natural populations. In species with large continuous geographical distributions the phenotypic signal of local adaptation is frequently clear, but the genetic background often remains elusive. We examined the patterns of genetic diversity inPinus sylvestris, a keystone species in many Eurasian ecosystems with a huge distribution range and decades of forestry research showing that it is locally adapted to the vast range of environmental conditions. MakingP. sylvestrisan even more attractive subject of local adaptation study, population structure has been shown to be weak previously and in this study. However, little is known about the molecular genetic basis of adaptation, as the massive size of gymnosperm genomes has prevented large scale genomic surveys. We generated a both geographically and genomically extensive dataset using a targeted sequencing approach. By applying divergence-based and landscape genomics methods we found that several coding loci contribute to local adaptation. We also discovered a very large (ca. 300 Mbp) putative inversion with a signal of local adaptation, which to our knowledge is the first such discovery in conifers. Our results call for more detailed analysis of structural variation in relation to genomic basis of local adaptation, emphasize the lack of large effect loci contributing to local adaptation in the coding regions and thus point out to the need for more attention towards multi-locus analysis of polygenic adaptation.
Analysis of leaf microbiome composition of near-isogenic maize lines differing in broad-spectrum disease resistance
Authors: Wagner Maggie R. , Busby Posy E. , Balint-Kurti Peter
Published: May 2019

Plant genotype strongly affects disease resistance, and also influences the composition of the leaf microbiome. However, these processes have not been studied and linked in the microevolutionary context of breeding for improved disease resistance. We hypothesized that broad-spectrum disease resistance alleles also affect colonization by non-pathogenic symbionts.

Quantitative trait loci (QTL) conferring resistance to multiple fungal pathogens were introgressed into a disease-susceptible maize inbred line. Bacterial and fungal leaf microbiomes of the resulting near-isogenic lines were compared to the microbiome of the disease-susceptible parent line at two timepoints in multiple fields.

Introgression of QTL from disease-resistant lines strongly shifted the relative abundance of diverse fungal and bacterial taxa in both 3-week-old and 7-week-old plants. Nevertheless, the effects on overall community structure and diversity were minor and varied among fields and years. Contrary to our expectations, host genotype effects were not any stronger in fields with high disease pressure than in uninfected fields, and microbiome succession over time was similar in heavily infected plants and uninfected plants.

These results show that introgressed QTL can greatly improve broad-spectrum disease resistance while having only limited and inconsistent pleiotropic effects on the leaf microbiome in maize.
Optimal Recovery of Missing Values for Non-negative Matrix Factorization
Authors: Chen Rebecca , Varshney Lav R.
Published: May 2019

We extend the approximation-theoretic technique of optimal recovery to the setting of imputing missing values in clustered data, specifically for non-negative matrix factorization (NMF), and develop an implementable algorithm. Under certain geometric conditions, we prove tight upper bounds on NMF relative error, which is the first bound of this type for missing values. We also give probabilistic bounds for the same geometric assumptions. Experiments on image data and biological data show that this theoretically-grounded technique performs as well as or better than other imputation techniques that account for local structure.
Early Ictal Recruitment of Midline Thalamus in Mesial Temporal Lobe Epilepsy
Authors: Romeo Andrew , Issa Roach Alexandra T. , Toth Emilia , Chaitanya G. , Ilyas Adeel , Riley Kristen O. , Pati Sandipan
Published: May 2019

The causal role of midline thalamus in the initiation and early organization of mesial temporal lobe seizures is studied. Three patients undergoing stereoelectroencephalography were enrolled for the placement of an additional depth electrode targeting the midline thalamus. The midline thalamus was recruited in all three patients at varying points of seizure initiation (0-13 seconds) and early propagation (9-60 seconds). Stimulation of either thalamus or hippocampus induced similar habitual seizures. Seizure-induced in the hippocampus rapidly recruited the thalamus. Evoked potentials demonstrated stronger connectivity from the hippocampus to the thalamus than in the opposite direction. The midline thalamus can be within the seizure initiation and symptomatogenic circuits.
SELVa: Simulator of Evolution with Landscape Variation
Authors: Nabieva Elena , Bazykin Georgii A.
Published: May 2019

Organisms evolve to increase their fitness, a process that may be described as climbing the fitness landscape. However, the fitness landscape of an individual site, i.e., the vector of fitness values corresponding to different variants at this site, can change with time due to changes in the environment or substitutions at other epistatically interacting sites. We present SELVa, the Simulator of Evolution with Landscape Variation, aimed at modeling the substitution process under a changing single position fitness landscape in a set of evolving lineages forming a phylogeny of arbitrary shape. Written in Java and distributed as an executable jar file, SELVa provides a flexible framework that allows the user to choose from a number of implemented rules governing landscape change.

Availability

https://github.com/bazykinlab/SELVa
StereoMate: 3D Stereological Automated Analysis of Biological Structures
Authors: West Steven J. , Bonboire Damien , Bennett David L
Published: May 2019

Tissue clearing methods offer great promise to understand tissue organisation, but also present serious technical challenges. Generating high quality tissue labelling, developing tools for demonstrably reliable and accurate extraction, and eliminating baises through stereological technique, will establish a high standard for 3D quantitative data from cleared tissue. These challenges are met with StereoMate, an open-source image analysis framework for immunofluorescent labelling in cleared tissue. The platform facilitates the development of image segmentation protocols with rigorous validation, and extraction of object-level data in an automated and stereological manner. Mouse dorsal root ganglion neurones were assessed to validate this platform, which revealed a profound loss and shift in neurone size, and loss of axonal input and synaptic terminations within the spinal dorsal horn following their injury. In conclusion, the StereoMate platform provides a general-purpose automated stereological analysis platform to generate rich and unbiased object-level datasets from immunofluorescent data.
GSAn: an alternative to enrichment analysis for annotating gene sets
Authors: Ayllon-Benitez Aaron , Bourqui Romain , Thébaut Patricia , Mougin Fleur
Published: May 2019

The revolution in new sequencing technologies, by strongly improving the production of omics data, is greatly leading to new understandings of the relations between genotype and phenotype. To interpret and analyze these massive data that are grouped according to a phenotype of interest, methods based on statistical enrichment became a standard in biology. However, these methods synthesize the biological information by a priori selecting the over-represented terms and may suffer from focusing on the most studied genes that represent a limited coverage of annotated genes within the gene set.

To address these limitations, we developed GSAn, a novel gene set annotation Web server that uses semantic similarity measures to reduce a priori Gene Ontology annotation terms. The originality of this new approach is to identify the best compromise between the number of retained annotation terms that has to be drastically reduced and the number of related genes that has to be as large as possible. Moreover, GSAn offers interactive visualization facilities dedicated to the multi-scale analysis of gene set annotations. GSAn is available at: https://gsan.labri.fr.
Rapid adaptive evolution of scale-eating kinematics to a novel ecological niche
Authors: St. John Michelle E. , Holzman Roi , Martin Christopher H.
Published: May 2019

The origins of novel trophic specialization, in which organisms begin to exploit novel resources for the first time, may be explained by shifts in behavior such as foraging preferences or feeding kinematics. One way to investigate the behavioral mechanisms underlying ecological novelty is by comparing prey capture kinematics between groups. In this study, we investigated the contribution of kinematics to the origins of a novel ecological niche for scale-eating within a microendemic adaptive radiation of pupfishes on San Salvador Island, Bahamas. We compared prey capture kinematics across three species of pupfish while consuming shrimp and scales in the lab and found that scale-eating pupfish exhibited peak gape sizes that were twice as large as all other groups, but also attacked prey with a more obtuse angle between their lower jaw and suspensorium. We then investigated how this variation in feeding kinematics could explain scale-biting performance by measuring the surface area removed per strike from standardized gelatin cubes. We found that a combination of larger peak gape and more obtuse lower jaw and suspensorium angles resulted in 67% more surface area removed per strike, indicating that scale-eaters may reside on a performance optimum for scale-biting. We also measured feeding kinematics of F1 hybrids to test whether feeding performance could contribute to reproductive isolation between species and found that F1 hybrid kinematics and performance more closely resembled those of generalists, suggesting that they may have low fitness in the scale-eating niche. Ultimately, our results suggest that the evolution of strike kinematics in this radiation is an adaptation to the novel niche of scale-eating.
Overt attention towards appetitive cues enhances their subjective value, independent of orbitofrontal cortex activity
Authors: McGinty Vincent B.
Published: May 2019

Neural representations of value underlie many behaviors that are crucial for survival. Previously, we found that value representations in primate orbitofrontal cortex (OFC) are modulated by attention, specifically, by overt shifts of gaze towards or away from reward-associated visual cues (McGinty et al., 2016). Here, we investigate the influence of overt attention on behavior, by asking how gaze shifts correlate with reward anticipatory responses, and whether activity in OFC mediates this correlation. Macaque monkeys viewed Pavlovian-conditioned appetitive cues on a visual display, while the fraction of time they spent looking towards or away from the cues was measured using an eye tracker. Also measured during cue presentation were the monkeys’ reward anticipation, indicated by conditioned licking responses (CRs), and single neuron activity in OFC. In general, gaze allocation predicted subsequent licking responses: the longer the monkeys spent looking at a cue at a given time point in a trial, the more likely they were to produce an anticipatory CR later in that trial, as if the subjective value of the cue were increased. To address neural mechanisms, mediation analysis measured the extent to which the gaze-CR correlation could be statistically explained by the concurrently recorded firing of single OFC neurons. The resulting mediation effects were indistinguishable from chance. Therefore, while overt attention may increase the subjective value of reward-associated cues (as revealed by anticipatory behaviors), the underlying mechanism remains unknown, as does the functional significance of gaze-driven modulation of OFC value signals.
A humanness dimension to visual object coding in the brain
Authors: Contini Erika W. , Goddard Erin , Grootswagers Tijl , Williams Mark , Carlson Thomas
Published: May 2019

Neuroimaging studies investigating human object recognition have largely focused on a relatively small number of object categories, in particular, faces, bodies, scenes, and vehicles. More recent studies have taken a broader focus, investigating hypothesised dichotomies, for example animate versus inanimate, and continuous feature dimensions, such as biologically similarity. These studies typically have used stimuli that are clearly identified as animate or inanimate, neglecting objects that may not fit into this dichotomy. We generated a novel stimulus set including standard objects and objects that blur the animate-inanimate dichotomy, for example robots and toy animals. We used MEG time-series decoding to study the brain’s emerging representation of these objects. Our analysis examined contemporary models of object coding such as dichotomous animacy, as well as several new higher order models that take into account an object’s capacity for agency (i.e. its ability to move voluntarily) and capacity to experience the world. We show that early brain responses are best accounted for by low-level visual similarity of the objects; and shortly thereafter, higher order models of agency/experience best explained the brain’s representation of the stimuli. Strikingly, a model of human-similarity provided the best account for the brain’s representation after an initial perceptual processing phase. Our findings provide evidence for a new dimension of object coding in the human brain – one that has a “human-centric” focus.
Genome-wide heritability analysis of severe malaria susceptibility and resistance reveals evidence of polygenic inheritance
Authors: Damena Delesa , Chimusa Emile R.
Published: May 2019

Objective

Estimating SNP-heritability (h2g) of severe malaria/resistance and its distribution across the genome might shed new light in to the underlying biology.

Method

We investigated h2g of severe malaria susceptibility and resistance from genome-wide association study (GWAS) dataset (sample size =11, 657). We partitioned the h2g in to chromosomes, allele frequencies and annotations. We further examined none-cell type specific and cell type specific enrichments from GWAS-summary statistics.

Results

We estimated the h2g of severe malaria at 0.21 (se=0.05, p=2.7×10−5), 0.20 (se =0.05, p=7.5×10−5) and 0.17 (se =0.05, p= 7.2×10−4) in Gambian, Kenyan and Malawi populations, respectively. The h2g attributed to the GWAS significant SNPs and the well-known sickle cell (HbS) variant was approximately 0.07 and 0.03, respectively. We prepared African population reference panel and obtained comparable h2g estimate (0.21 (se = 0.02, p< 1×10−5)) from GWAS-summary statistics meta-analysed across the three populations. Partitioning analysis from raw genotype data showed significant enrichment of h2g in protein coding genic SNPs while summary statistics analysis suggests pattern of enrichment in multiple categories.

Conclusion

We report for the first time that the heritability of malaria susceptibility and resistance is largely ascribed by common SNPs and the causal variants are overrepresented in protein coding regions of the genome. Overall, our results suggest that malaria susceptibility and resistance is a polygenic trait. Further studies with larger sample sizes are needed to better understand the underpinning genetics of resistance and susceptibility to severe malaria.
Cytometric fingerprints of gut microbiota predict Crohn’s disease state
Authors: Rubbens Peter , Props Ruben , Kerckhof Frederiek-Maarten , Boon Nico , Waegeman Willem
Published: May 2019

Variations in the gut microbiome have been associated with changes in health state such as Crohn’s disease. Most surveys characterize the microbiome through analysis of the 16S rRNA gene. An alternative technology that can be used is flow cytometry. In this report we analyzed a disease cohort that has been characterized by both technologies. Changes in microbial community structure are reflected in both types of data. We demonstrate that cytometric fingerprints can be used as a diagnostic tool in order to classify samples according to Crohn’s disease state. These results highlight the potential of flow cytometry to perform rapid diagnostics of microbiome-associated diseases.
The effect of network thresholding and weighting on structural brain networks in the UK Biobank
Authors: Buchanan Colin R. , Bastin Mark E. , Ritchie Stuart J. , Liewald David C. , Madole James , Tucker-Drob Elliot M. , Deary Ian J. , Cox Simon R.
Published: May 2019

Whole-brain structural networks can be constructed using diffusion MRI and probabilistic tractography. However, measurement noise and the probabilistic nature of the tracking procedure result in an unknown proportion of spurious white matter connections. Faithful disentanglement of spurious and genuine connections is hindered by a lack of comprehensive anatomical information at the network-level. Therefore, network thresholding methods are widely used to remove ostensibly false connections, but it is not yet clear how different thresholding strategies affect basic network properties and their associations with meaningful demographic variables, such as age. In a sample of 3,153 generally healthy volunteers from the UK Biobank Imaging Study (aged 44—77 years), we constructed 85 × 85 node whole-brain structural networks and applied two principled network thresholding approaches (consistency and proportional thresholding). These were applied over a broad range of threshold levels across six alternative network weightings (streamline count, fractional anisotropy, mean diffusivity and three novel weightings from neurite orientation dispersion and density imaging) and for four common network measures (mean edge weight, characteristic path length, network efficiency and network clustering coefficient). We compared network measures against age associations and found that the most commonly-used level of proportional-thresholding from the literature (retaining 68.7% of all possible connections) yielded significantly weaker age-associations (0.070 ≤ |β| ≤ 0.406) than the consistency-based approach which retained only 30% of connections (0.140 ≤ |β| ≤ 0.409). However, we determined that the stringency of the threshold was a stronger determinant of the network-age association than the choice of threshold method and the two thresholding approaches identified a highly overlapping set of connections (ICC = 0.84) when matched at a plausible level of network sparsity (70%). Generally, more stringent thresholding resulted in more age-sensitive network measures in five of the six network weightings, except at the highest levels of sparsity (>90%), where crucial connections were then removed. At two commonly-used threshold levels, the age-associations of the connections that were discarded (mean β ≤ |0.068|) were significantly smaller in magnitude than the corresponding age-associations of the connections that were retained (mean β ≤ |0.219|, p < 0.001, uncorrected). Given histological evidence of widespread degeneration of structural brain connectivity with increasing age, these results indicate that stringent thresholding methods may be most accurate in identifying true white matter connections.
Targeted brain tumor radiotherapy using an Auger emitter
Authors: Pirovano Giacomo , Jannetti Stephen A. , Carter Lukas M. , Sadique Ahmad , Kossatz Susanne , Guru Navjot , De Souza Franca Paula Demetrio , Maeda Masatomo , Zeglis Brian M. , Lewis Jason S. , Humm John L. , Reiner Thomas
Published: May 2019

Glioblastoma multiforme is a highly aggressive form of brain cancer whose location, tendency to infiltrate healthy surrounding tissue, and heterogeneity significantly limit survival, with scant progress having been made in recent decades.123I-MAPi (Iodine-123 Meitner-Auger PARP1 inhibitor) is a precise therapeutic tool composed of a PARP1 inhibitor radiolabeled with an Auger- and gamma-emitting iodine isotope. Here, the PARP inhibitor, which binds to the DNA repair enzyme PARP1, specifically targets cancer cells, sparing healthy tissue, and carries a radioactive payload within reach of the cancer cells’ DNA. The high relative biological efficacy of Auger electrons within their short range of action is leveraged to inflict DNA damage and cell death with high precision. The gamma ray emission of123I-MAPi allows for the imaging of tumor progression and therapy response, and for patient dosimetry calculation. Here we demonstrated the efficacy and specificity of this small molecule radiotheranostic in a complex preclinical model.In vitroandin vivostudies demonstrate high tumor uptake and a prolonged survival in mice treated with123I-MAPi when compared to vehicle controls. Different methods of drug delivery were investigated to develop this technology for clinical applications, including convection enhanced delivery (CED) and intrathecal injection. Taken together, these results represent the first full characterization of an Auger-emitting PARP inhibitor, demonstrate a survival benefit in mouse models of GBM, and confirm the high potential of123I-MAPi for clinical translation.

One Sentence Summary

A novel PARP1-targeted Auger radiotherapeutic shows translational potential as a theranostic tool for imaging and killing cancer cells, resulting in tumor delineation and prolonged survival in a glioblastoma model.
Connecting Concepts in the Brain by Mapping Cortical Representations of Semantic Relations
Authors: Zhang Yizhen , Han Kuan , Worth Robert , Liu Zhongming
Published: May 2019

In the brain, the semantic system is thought to store concepts. However, little is known about how it connects different concepts and infers semantic relations. To address this question, we collected hours of functional magnetic resonance imaging data from human subjects listening to natural stories. We developed a predictive model of the voxel-wise response and further applied it to thousands of new words. Our results suggest that both semantic categories and relations are represented by spatially overlapping cortical patterns, instead of anatomically segregated regions. Semantic relations that reflect conceptual progression from concreteness to abstractness are represented by cortical patterns of activation in the default mode network and deactivation in the frontoparietal attention network. We conclude that the human brain uses distributed networks to encode not only concepts but also relationships between concepts. In particular, the default mode network plays a central role in semantic processing for abstraction of concepts.
Long non-coding RNAGRASLNDenhances chondrogenesis via suppression of interferon type II signaling pathway
Authors: Huynh Nguyen P.T. , Gloss Catherine C. , Lorentz Jeremiah , Tang Ruhang , Brunger Jonathan M. , McAlinden Audrey , Zhang Bo , Guilak Farshid
Published: May 2019

Long non-coding RNAs (lncRNAs) play critical roles in regulating gene expression and cellular processes; however, their roles in musculoskeletal development, disease, and regeneration remain poorly understood. Here, we identified a novel lncRNA, Glycosaminoglycan Regulatory ASsociated Long Non-coDing RNA (GRASLND) as a regulator of mesenchymal stem cell (MSC) chondrogenesis, and we investigated its basic molecular mechanism and its potential application towards regenerative medicine.GRASLND,a primate-specific lncRNA, is upregulated during MSC chondrogenesis and appears to act directly downstream of SRY-Box 9 (SOX9), but not Transforming Growth Factor Beta 3 (TGF-β3). Utilizing the established model of pellet formation for MSC chondrogenesis, we showed that the silencing ofGRASLNDresulted in lower accumulation of cartilage-like extracellular matrix, whileGRASLNDoverexpression, either via transgene ectopic expression or by endogenous activation via CRISPR, significantly enhanced cartilage matrix production.GRASLNDacts to inhibit interferon gamma (IFN-γ) by binding to Eukaryotic Initiation Factor-2 Kinase EIF2AK2. We further demonstrated thatGRASLNDexhibits a protective effect in engineered cartilage against interferon type II across different sources of chondroprogenitor cells. Our results indicate an important role ofGRASLNDin regulating stem cell chondrogenesis, as well as its therapeutic potential in the treatment of cartilage-related diseases, such as osteoarthritis.

Significance

Long non-coding RNAs (lncRNAs) play critical roles in gene regulation and cellular physiology; however, the role of lncRNAs in controlling stem cell chondrogenesis remains to be determined. Here, we utilized next generation sequencing of adult stem cell chondrogenesis to identify a set of potential lncRNA candidates involved in this process. We identified lncRNA Glycosaminoglycan Regulatory ASsociated Long Non-coDing RNA (GRASLND) and characterized its molecular mechanism of action. We described a novel role ofGRASLNDin positive regulation of chondrogenesis via its inhibition of type II interferon. Importantly, we showed that overexpression ofGRASLNDaugments stem cell chondrogenesis, providing a promising approach to enhancing stem cell chondrogenesis and cartilage regeneration.
Time-dependent Canonical Correlation Analysis for Multilevel Time Series
Authors: Cao Xuefei , Ke Jun , Sandstede Björn , Luo Xi
Published: May 2019

Canonical Correlation Analysis is a technique in multivariate data analysis for finding linear projections that maximize the correlation between two groups of variables. The correlations are typically defined without accounting for the serial correlations between observations, a typical setting for time series data. To understand the coupling dynamics and temporal variations between the two time-varying sources, we introduce the time-dependent canonical correlation analysis (TDCCA), a method for inferring time-dependent canonical vectors from multilevel time series data. A convex formulation of the problem is proposed, which leverages the singular value decomposition (SVD) characterization of all solutions of the CCA problem. We use simulated datasets to validate the proposed algorithm. Moreover, we propose a novel measure, canonical correlation variation as another way to assess the dynamic pattern of brain connections and we apply it to a real resting state fMRI dataset to study the aging effects on brain connectivity. Additionally, we explore our proposed method in a task-related fMRI to detect the temporal dynamics due to different motor tasks. We show that, compared to extant methods, the TDCCA-based approach not only detect temporal changes but also improves feature extraction. Together, this paper contributes broadly to new computational methodologies in understanding multilevel time series.
TheC. elegansTubby homolog dynamically modulates olfactory cilia membrane morphogenesis and phospholipid composition
Authors: DiTirro Danielle , Philbrook Alison , Rubino Kendrick , Sengupta Piali
Published: May 2019

Plasticity in sensory signaling is partly mediated via regulated trafficking of signaling molecules to and from primary cilia. Tubby-related proteins regulate ciliary protein transport; however, their roles in remodeling of cilia properties are not fully understood. We find that theC. elegansTUB-1 Tubby homolog regulates membrane morphogenesis and signaling protein transport in specialized sensory cilia. In particular, TUB-1 is essential for sensory signaling-dependent reshaping of olfactory cilia morphology. We show that compromised sensory signaling alters cilia membrane phosphoinositide composition via TUB-1-dependent trafficking of a PIP5 kinase. TUB-1 regulates localization of this lipid kinase at the cilia base in part via localization of the AP-2 adaptor complex subunit DPY-23. Our results describe new functions for Tubby proteins in the dynamic regulation of cilia membrane lipid composition, morphology, and signaling protein content, and suggest that this conserved family of proteins plays a critical role in mediating cilia structural and functional plasticity.
Global mistranslation facilitates sampling of beneficial mutations under stress
Authors: Samhita Laasya , Raval Parth K , Agashe Deepa
Published: May 2019

Mistranslation is typically deleterious, but can sometimes be beneficial. Although a specific mistranslated protein can confer a short-term benefit in a particular environment, the prevalence of high global mistranslation rates remains puzzling given the large overall cost. Here, we show that generalized mistranslation enhances earlyE. colisurvival under various forms of DNA damage, because it leads to early activation of the DNA damage-induced SOS response. Mistranslating cells therefore maintain larger populations, facilitating later sampling of critical beneficial mutations. Thus, under DNA damage, both basal and induced mistranslation (through genetic or environmental means) increase the number of genetically resistant and phenotypically persistent cells. Surprisingly, mistranslation also increases survival at high temperature. This wide-ranging stress resistance relies on Lon protease, which is revealed as a key effector that induces the SOS response in addition to alleviating proteotoxic stress. The new links between error-prone protein synthesis, DNA damage, and generalised stress resistance indicate surprising coordination between intracellular stress responses, and suggest a novel hypothesis to explain high global mistranslation rates.
Aurora A promotes chromosome congression by activating the condensin-dependent pool of KIF4A
Authors: Poser Elena , Caous Renaud , Gruneberg Ulrike , Barr Francis A.
Published: May 2019

Aurora kinases create phosphorylation gradients within the spindle during prometaphase and anaphase. These locally regulate factors that promote spindle organisation, chromosome condensation and movement, and cytokinesis. We show that one such factor is the kinesin KIF4A, which is present along the chromosome axes throughout mitosis and the central spindle in anaphase. These two pools of KIF4A depend on condensin I and PRC1, respectively. Previous work has shown KIF4A is activated by Aurora B at the anaphase central spindle. However, whether or not chromosome-associated KIF4A bound to condensin I is regulated by Aurora kinases remain unclear. To determine the roles of the two different pools of KIF4A, we generated specific point mutants that are unable to interact with either condensin I or PRC1, or are deficient for Aurora kinase regulation. By analysing these mutants, we show that Aurora kinases phosphorylate the condensin I dependent pool of KIF4A and thus actively promote chromosome congression from the spindle poles to the metaphase plate.
Exploring multiple sensory systems in ovipositors ofDrosophila suzukiiand related species with different egg-laying behaviour
Authors: Crava Cristina Maria , Romani Roberto , Zanini Damiano , Amati Simone , Sollai Giorgia , Crnjar Roberto , Haase Albrecht , Paoli Marco , Rossi-Stacconi Marco Valerio , Rota-Stabelli Omar , Tait Gabriella , Anfora Gianfranco
Published: May 2019

Drosophila suzukiiis an invasive agricultural pest species that lays eggs in fruit during ripening, while most closely relatedDrosophilaspecies use rotten matter as oviposition substrates. This behaviour is allowed by an enlarged and serrated ovipositor that can pierce intact fruit skin.D. suzukiicombines multiple sensory systems (mechanosensation, olfaction, and taste) to select oviposition sites. Here, we test the hypothesis that theD. suzukiiovipositor is involved in these sensory modalities. We first investigate the ovipositor gene expression using a comparative framework of fourDrosophilaspecies with gradual changes in ovipositor morphology to identify evolutionary adaptations specific toD. suzukii. Results show transcription of chemoreceptors and mechanoreceptors in the four species, with a common core of sensory receptors expressed in all of them. Then, we demonstrate that sensory structures present in the distal tip of theD. suzukiiovipositor are mechanosensory-like sensilla, and that the degenerin/epithelial sodium channelppkis expressed in homologous structures inDrosophila melanogaster. Our results suggest theD. suzukiiovipositor playing a role in mechanosensation, which might be shared with otherDrosophilaspecies.
Clinical characteristics of sarcoidosis patients with systemic sclerosis‐specific autoantibody: Possible involvement of thymus and activation‐regulated chemokine and a review of the published works
Authors: Ueda‐Hayakawa Ikuko , Nguyen Chuyen Thi Hong , Kishimoto Izumi , Ly Nhung Thi My , Okamoto Hiroyuki
Published: May 2019

Sarcoidosis and systemic sclerosis (SSc) are both multisystem disorders of unknown etiology. Some cases having both sarcoidosis and SSc have been reported previously. The present study was to investigate clinical features in sarcoidosis patients who possessed SSc‐specific autoantibody. The pathophysiology of each disease, including shared pathways leading to the development of both conditions, is reviewed in addition to previous reports of patients with concomitant SSc and sarcoidosis. SSc‐specific autoantibodies including anticentromere antibody (ACA), anti‐topoisomerase I antibody, anti‐RNA polymerase III antibody and anti‐U1RNP antibody were examined in sarcoidosis patients. Complete medical histories, clinical examinations and laboratory tests were conducted for all patients. For reviewing previously published reports, all cases were retrieved through a PubMed search. ACA was most frequently observed in sarcoidosis patients. Plaques and papules were the most frequent as the cutaneous sarcoidosis lesions. Soluble interleukin‐2 receptor was elevated in most of the cases (6/8, 75%), and thymus and activation‐regulated chemokine (TARC) was elevated in all cases (6/6, 100%). Together with our two cases (cases 1 and 3), a review of previously reported cases of sarcoidosis patients concomitant with SSc showed high frequency of ACA and plaques as cutaneous lesions. We suppose that TARC may play some roles in the production of SSc‐specific autoantibodies and development of concomitance with SSc in sarcoidosis, although the mechanisms remain unknown.