bluuebunny/crossref_metadata_2025_split huggingface dataset:
Can a bulky glycocalyx promote catch bonding in early integrin adhesion? Perhaps a bit
Authors: Blanchard Aaron 
Published: March 2023

AbstractMany types of cancer overexpress bulky glycoproteins to form a thick glycocalyx layer. The glycocalyx physically separates the cell from its surroundings, but recent work has shown that the glycocalyx can paradoxically increase adhesion to soft tissues and therefore promote the metastasis of cancer cells. This surprising phenomenon occurs because the glycocalyx forces adhesion molecules (called integrins) on the cell’s surface into clusters. These integrin clusters have cooperative effects that allow them to form stronger adhesions to surrounding tissues than would be possible with equivalent numbers of un-clustered integrins. These cooperative mechanisms have been intensely scrutinized in recent years; a more nuanced understanding of the biophysical underpinnings of glycocalyx-mediated adhesion could uncover therapeutic targets, deepen our general understanding of cancer metastasis, and elucidate general biophysical processes that extend far beyond the realm of cancer research.This work examines the hypothesis that the glycocalyx has the additional effect of increasing mechanical tension experienced by clustered integrins. Integrins function as mechanosensors that undergo catch bonding – meaning the application of moderate tension increases integrin bond lifetime relative to the lifetime of integrins experiencing low tension. In this work, a three-state chemomechanical catch bond model of integrin tension is used to investigate catch bonding in the presence of a bulky glycocalyx.This modeling suggests that a bulky glycocalyx can lightly trigger catch bonding, increasing the bond lifetime of integrins at adhesion edges by up to 100%. The total number of integrin-ligand bonds within an adhesion is predicted to increase by up to ~60% for certain adhesion geometries. Catch bonding is predicted to decrease the activation energy of adhesion formation by ~1-4 kBT, which translates to a ~3-50× increase in the kinetic rate of adhesion nucleation. This work reveals that integrin mechanic and clustering likely both contribute to glycocalyx-mediated metastasis.Graphical Abstract
Respiration shapes sleep-oscillations and memory reactivation in humans
Authors: Schreiner Thomas , Petzka Marit , Staudigl Tobias , Staresina Bernhard P. 
Published: March 2023

AbstractThe beneficial effect of sleep on memory consolidation relies on the precise interplay of slow oscillations (SOs) and spindles. However, whether these rhythms are orchestrated by an underlying pacemaker has remained elusive. Here, we tested whether respiration, which has been shown to impact brain rhythms and cognition during wake, shapes memory reactivation by modulating sleep-related oscillations and their interplay in humans. We recorded scalp EEG and respiration throughout an experiment in which participants acquired associative memories before taking a nap. Our results reveal that respiration strongly modulates the emergence of sleep oscillations. Specifically, SOs, spindles as well as their interplay (i.e., coupled SO_spindle complexes) systematically increase towards inhalation peaks. Moreover, the strength of respiration-SO_spindle coupling is linked to the extent of memory reactivation during SO_spindles. Our results identify respiration as a potential pacemaker for memory consolidation in humans and highlight the critical role of brain-body interactions during sleep.
Statistical analyses of motion-corrupted MRI relaxometry data
Authors: Corbin Nadège , Oliveira Rita , Raynaud Quentin , Domenicantonio Giulia Di , Draganski Bogdan , Kherif Ferath , Callaghan Martina F. , Lutti Antoine 
Published: March 2023

AbstractConsistent noise variance across data points (i.e. homoscedasticity) is required to ensure the validity of statistical analyses of MRI data conducted using linear regression methods. However, head motion leads to degradation of image quality, introducing noise heteroscedasticity into ordinary-least square analyses. The recently introduced QUIQI method restores noise homoscedasticity by means of weighted least square analyses in which the weights, specific for each dataset of an analysis, are computed from an index of motion-induced image quality degradation. QUIQI was first demonstrated in the context of brain maps of the MRI parameter R2*, which were computed from a single set of images with variable echo time. Here, we extend this framework to quantitative maps of the MRI parameters R1, R2*, and MTsat, which are computed from multiple sets of images. QUIQI allows for optimization of the noise model by using metrics quantifying heteroscedasticity and free energy. QUIQI restores homoscedasticity more effectively than insertion of an image quality index in the analysis design and yields higher sensitivity than simply removing the datasets most corrupted by head motion from the analysis. In sum, QUIQI provides an optimal approach to group-wise analyses of a range of quantitative MRI parameter maps that is robust to inherent homoscedasticity.
General and specific patterns of cortical gene expression as spatial correlates of complex cognitive functioning
Authors: Moodie Joanna E. , Harris Sarah E. , Harris Mathew A. , Buchanan Colin R. , Davies Gail , Taylor Adele , Redmond Paul , Liewald David , del C Valdés Hernández Maria , Shenkin Susan , Russ Tom C. , Maniega Susana Muñoz , Luciano Michelle , Corley Janie , Stolicyn Aleks , Shen Xueyi , Steele Douglas , Waiter Gordon , Sandu-Giuraniuc Anca , Bastin Mark E. , Wardlaw Joanna M. , McIntosh Andrew , Whalley Heather , Tucker-Drob Elliot M. , Deary Ian J. , Cox Simon R. 
Published: March 2023

AbstractGene expression varies across the brain. This spatial patterning denotes specialised support for particular brain functions. However, the way that a given gene’s expression fluctuates across the brain may be governed by general rules. Quantifying patterns of spatial covariation across genes would offer insights into the molecular characteristics of brain areas supporting, for example, complex cognitive functions. Here, we use principal component analysis to separate general and unique gene regulatory associations with cortical substrates of cognition. We find that the region-to-region variation in cortical expression profiles of 8235 genes covaries across two major principal components : gene ontology analysis suggests these dimensions are characterised by downregulation and upregulation of cell-signalling/modification and transcription factors. We validate these patterns out-of-sample and across different data processing choices. Brain regions more strongly implicated in general cognitive functioning (g; 3 cohorts, total meta-analyticN =39,519) tend to be more balanced between downregulation and upregulation of both major components (indicated by regional component scores). We then identify a further 41 genes as candidate cortical spatial correlates ofg, beyond the patterning of the two major components (|β| range = 0.15 to 0.53). Many of these genes have been previously associated with clinical neurodegenerative and psychiatric disorders, or with other health-related phenotypes. The results provide insights into the cortical organisation of gene expression and its association with individual differences in cognitive functioning.
TorchLens: A Python package for extracting and visualizing hidden activations of PyTorch models
Authors: Taylor JohnMark , Kriegeskorte Nikolaus 
Published: March 2023

AbstractDeep neural network models (DNNs) are essential to modern AI and provide powerful models of information processing in biological neural networks. Researchers in both neuroscience and engineering are pursuing a better understanding of the internal representations and operations that undergird the successes and failures of DNNs. Neuroscientists additionally evaluate DNNs as models of brain computation by comparing their internal representations to those found in brains. It is therefore essential to have a method to easily and exhaustively extract and characterize the results of the internal operations of any DNN. Many models are implemented in PyTorch, the leading framework for building DNN models. Here we introduceTorchLens, a new open-source Python package for extracting and characterizing hidden-layer activations in PyTorch models. Uniquely among existing approaches to this problem,TorchLenshas the following features: (1) it exhaustively extracts the results of all intermediate operations, not just those associated with PyTorch module objects, yielding a full record of every step in the model’s computational graph, (2) it provides an intuitive visualization of the model’s complete computational graph along with metadata about each computational step in a model’s forward pass for further analysis, (3) it contains a built-in validation procedure to algorithmically verify the accuracy of all saved hidden-layer activations, and (4) the approach it uses can be automatically applied to any PyTorch model with no modifications, including models with conditional (if-then) logic in their forward pass, recurrent models, branching models where layer outputs are fed into multiple subsequent layers in parallel, and models with internally generated tensors (e.g., injections of noise). Furthermore, usingTorchLensrequires minimal additional code, making it easy to incorporate into existing pipelines for model development and analysis, and useful as a pedagogical aid when teaching deep learning concepts. We hope this contribution will help researchers in AI and neuroscience understand the internal representations of DNNs.
Reconstructing prehistoric viral genomes from Neanderthal sequencing data
Authors: Ferreira Renata C. , Alves Gustavo V. , Ramon Marcello , Antoneli Fernando , Briones Marcelo R. S. 
Published: March 2023

AbstractDNA viruses that produce persistent infections have been proposed as potential causes for the extinction of Neanderthals and therefore, the identification of viral genome remnants in Neanderthal sequence reads is an initial step to address this hypothesis. Here, as proof of concept, we searched for viral remnants in sequence reads of Neanderthal genome data by mapping to adenovirus, herpesvirus and papillomavirus, which are double stranded DNA viruses that may establish lifelong latency and can, produce persistent infections. The reconstructed ancient viral genomes of adenovirus, herpesvirus and papillomavirus revealed conserved segments, with nucleotide identity to extant viral genomes, and variable regions in coding regions with substantial divergence to extant close relatives. Sequence reads mapped to extant viral genomes showed deamination patterns of ancient DNA and that these ancient viral genomes showed divergence consistent with the age of these samples (≈50,000 years) and viral evolutionary rates (10-5to 10-8substitutions/site/year). Analysis of random effects shows that the Neanderthal mapping to genomes of extant persistent viruses is above the expected by random similarities of short reads. Also, negative control with a nonpersistent DNA virus does not yield statistically significant assemblies. This work demonstrates the feasibility of identifying viral genome remnants in archaeological samples with signal-to-noise assessment.
Expanding the Characterization of Microbial Ecosystems using DIA-PASEF Metaproteomics
Authors: Gómez-Varela David , Xian Feng , Grundtner Sabrina , Sondermann Julia Regina , Carta Giacomo , Schmidt Manuela 
Published: March 2023

AbstractMetaproteomics is gaining momentum in microbiome research due to the multi-dimensional information it provides. However, current approaches have reached their detection limits. We present a highly-sensitive metaproteomic workflow using the extra information captured by Parallel Accumulation-Serial Fragmentation (PASEF) technology. The comparison of different acquisition modes and data analysis software packages showed that DIA-PASEF and DIA-NN doubled protein identifications of mouse gut microbiota and, importantly, also of the host proteome. DIA-PASEF significantly improved peptide detection reproducibility and quantification accuracy, which resulted in more than twofold identified taxa, reaching depths comparable to metagenomic studies. Consequently, DIA-PASEF exhibited improved coverage of functional networks revealing 131 additional pathways compared to DDA-PASEF. We applied our optimized workflow to a pre-clinical mouse model of chronic pain, in which we deciphered novel host-microbiome interactions. In summary, we present here a metaproteomic approach that paves the way for increasing the functional characterization of microbiome ecosystems and is applicable to diverse fields of biological research.
Aedes aegyptigut transcriptomes respond differently to microbiome transplants from field-caught or laboratory-reared mosquitoes
Authors: Hegde Shivanand , Brettell Laura E. , Quek Shannon , Etebari Kayvan , Saldaña Miguel A. , Asgari Sassan , Coon Kerri L. , Heinz Eva , Hughes Grant L. 
Published: March 2023

AbstractThe mosquito microbiome is critical for host development and plays a major role in many aspects of mosquito biology. While the microbiome is commonly dominated by a small number of genera, there is considerable variation in composition among mosquito species, life stages, and geography. How the host controls and is affected by this variation is unclear. Using microbiome transplant experiments, we asked whether there were differences in transcriptional responses when mosquitoes of different species were used as microbiome donors. We used microbiomes from four different donor species spanning the phylogenetic breadth of the Culicidae, collected either from the laboratory or field. We found that when recipients received a microbiome from a donor reared in the laboratory, the response was remarkably similar regardless of donor species. However, when the donor had been collected from the field, far more genes were differentially expressed. We also found that while the transplant procedure did have some effect on the host transcriptome, this is likely to have had a limited effect on mosquito fitness. Overall, our results highlight the possibility that variation in mosquito microbiome communities are associated with variability in host-microbiome interactions and further demonstrate the utility of the microbiome transplantation technique.
Loss Of function of Male-Specific Lethal 3 (Msl3) Does Not Affect Spermatogenesis in Rodents
Authors: Mitchell T.A. , Lin J.M. , Hicks S.M. , James J.R. , Rangan P. , Forni P.E. 
Published: March 2023

AbstractMsl3 is a member of the chromatin-associated male-specific lethal MSL complex which is responsible for the transcriptional upregulation of genes on the X chromosome in males Drosophila. Although the dosage complex operates differently in mammals, the Msl3 gene is conserved from flies to humans.Msl3 is required for meiotic entry during Drosophila oogenesis. Recent reports indicate that also in primates, Msl3 is expressed in undifferentiated germline cells before meiotic entry. However, if Msl3 plays a role in the meiotic entry of mammals has yet to be explored. To study this, we used mouse spermatogenesis as a study model. Analyses of single cells RNA-seq data revealed that, in mice, Msl3 is mostly expressed in meiotic cells.To test the role of Msl3 in meiosis, we used a male germline-specific Stra8-iCre driver and a newly generated Msl3floxconditional knock-out mouse line. Msl3 conditional loss-of-function in spermatogonia did not cause spermatogenesis defects or changes in the expression of genes related to meiosis. Our data suggest that, in mice, Msl3 exhibits delayed expression compared to Drosophila and primates, and loss-of-function mutations disrupting the chromodomain of Msl3 alone do not impede meiotic entry in rodents.
Simple and highly efficient detection of PSD95 using a nanobody and its recombinant minibody derivative
Authors: Kilisch Markus , Gere-Becker Maja , Wüstefeld Liane , Bonnas Christel , Crauel Alexander , Mechmershausen Maja , Martens Henrik , Götzke Hansjörg , Opazo Felipe , Frey Steffen 
Published: March 2023

AbstractThe post-synaptic density protein 95 (PSD95) is a crucial scaffolding protein participating in the organization and regulation of synapses. PSD95 interacts with numerous molecules, including neurotransmitter receptors and ion channels. The functional dysregulation of PSD95 as well as its abundance and localization has been implicated with several neurological disorders, making it an attractive target to develop strategies able to monitor PSD95 accurately for diagnostics and therapeutics. This study characterizes a novel camelid single-domain antibody (nanobody) that binds strongly and with high specificity to rat, mouse and human PSD95. This nanobody allows for a more precise detection and better quantification of PSD95 in various biological samples. We expect that the flexibility and unique performance of this thoroughly characterized affinity tool will help to further understand the role of PSD95 in normal and diseased neuronal synapses.
Effect of predicting familiar melodies on alpha power
Authors: Ito Shuma , Matsunaga Kazuki , Chanpornpakdi Ingon , Tanaka Toshihisa 
Published: March 2023

AbstractThe processing of music and language share similar characteristics. Previous studies indicated that the similarity between language and melody was observed in event-related potentials to the deviation of a word and tone, respectively. We focused on a language study that demonstrated strong suppression of the alpha power in the presence of easily predictable words. Motivated by the physiological similarity between language and music, this study hypothesized that predictable music might suppress the alpha power. We measured electroencephalogram (EEG) signals while a melody followed by silence was presented for a participant who imagined the melody during the silent part of the music. The participants scored the melody’s familiarity to quantify the ease of prediction and imagination. We observed similarity to language processing. For familiar melodies, alpha power suppression was observed in the left frontal and left central regions. Further, we observed Bereitschaftspotential (a negative slope) in both familiar and unfamiliar conditions before the silent interval. Moreover, a network analysis revealed that information flow from the right sensory-motor cortex to the right auditory cortex in the beta band was stronger for familiar music than for unfamiliar music. Considering the previous findings that motor preparation and execution suppress the alpha power in the left frontal and left central regions, the alpha band suppression under music prediction suggests a motor interaction during music processing in the prediction of melodies.
ADAM17 targeting by human cytomegalovirus remodels the cell surface proteome to simultaneously regulate multiple immune pathways
Authors: Rubina Anzelika , Patel Mihil , Nightingale Katie , Potts Martin , Fielding Ceri A. , Kollnberger Simon , Lau Betty , Ladell Kristin , Miners Kelly L. , Nichols Jenna , Nobre Luis , Roberts Dawn , Trinca Terrence M. , Twohig Jason P. , Vlahava Virginia-Maria , Davison Andrew J. , Price David A. , Tomasec Peter , Wilkinson Gavin W.G. , Weekes Michael P. , Stanton Richard J. , Wang Eddie C.Y. 
Published: March 2023

AbstractHuman cytomegalovirus (HCMV) is a major human pathogen whose life-long persistence is enabled by its remarkable capacity to systematically subvert host immune defences. In exploring the finding that HCMV infection upregulates tumor necrosis factor receptor 2 (TNFR2), a ligand for the pro-inflammatory anti-viral cytokine TNFa, we discovered the underlying mechanism was due to targeting of the protease, A Disintegrin And Metalloproteinase 17 (ADAM17). ADAM17 is the prototype ‘sheddase’, a family of proteases that cleaves other membrane-bound proteins to release biologically active ectodomains into the supernatant. HCMV impaired ADAM17 surface expression through the action of two virally-encoded proteins in itsUL/b’ region, UL148 and UL148D. Proteomic plasma membrane profiling of cells infected with a HCMV double deletion mutant for UL148 and UL148D with restored ADAM17 expression, combined with ADAM17 functional blockade, showed that HCMV stabilized the surface expression of 114 proteins (p<0.05) in an ADAM17-dependent fashion. These included known substrates of ADAM17 with established immunological functions such as TNFR2 and Jagged1, but also numerous novel host and viral targets, such as Nectin1, UL8 and UL144. Regulation of TNFα-induced cytokine responses and NK inhibition during HCMV infection were dependent on this impairment of ADAM17. We therefore identify a viral immunoregulatory mechanism in which targeting a single sheddase enables broad regulation of multiple critical surface receptors, revealing a paradigm for viral-encoded immunomodulation.Significance statementHuman cytomegalovirus (HCMV) is an important pathogen, being the commonest infectious cause of brain damage to babies and the primary reason for hospital readmissions in transplant recipients. Even though HCMV induces the strongest immune responses by any human pathogen, it evades host defences and persists for life. This study describes a novel immunoregulatory strategy through which HCMV modulates multiple immune pathways simultaneously, by targeting a single host protein. HCMV UL148 and UL148D impair the maturation of the sheddase, A Disintegrin And Metalloproteinase 17, profoundly altering surface expression of numerous immunoregulatory proteins. This is the first description of viral genes targeting this pathway. Our findings may be relevant for future viral therapies and understanding the impact of HCMV in developmental biology.
Estrogen therapy induces receptor-dependent DNA damage enhanced by PARP inhibition in ER+ breast cancer
Authors: Traphagen Nicole A. , Schwartz Gary N. , Tau Steven , Jiang Amanda , Hosford Sarah R. , Goen Abigail E. , Roberts Alyssa M. , Romo Bianca A. , Johnson Anneka L. , Duffy Emily-Claire K. , Demidenko Eugene , Heverly Paul , Mosesson Yaron , Soucy Shannon M. , Kolling Fred , Miller Todd W. 
Published: March 2023

AbstractPurposeClinical evidence indicates that treatment with estrogens elicits anti-cancer effects in ∼30% of patients with advanced endocrine-resistant estrogen receptor alpha (ER)-positive breast cancer. Despite the proven efficacy of estrogen therapy, its mechanism of action is unclear and this treatment remains under-utilized. Mechanistic understanding may offer strategies to enhance therapeutic efficacy.Experimental DesignWe performed genome-wide CRISPR/Cas9 screening and transcriptomic profiling in long-term estrogen-deprived (LTED) ER+ breast cancer cells to identify pathways required for therapeutic response to the estrogen 17β-estradiol (E2). We validated findings in cell lines, patient-derived xenografts (PDXs), and patient samples, and developed a novel combination treatment through testing in cell lines and PDX models.ResultsCells treated with E2 exhibited replication-dependent markers of DNA damage and the DNA damage response prior to apoptosis. Such DNA damage was partially driven by the formation of DNA:RNA hybrids (R-loops). Pharmacological suppression of the DNA damage response via poly(ADP-ribose) polymerase (PARP) inhibition with olaparib enhanced E2-induced DNA damage. PARP inhibition synergized with E2 to suppress growth and prevent tumor recurrence inBRCA1/2-mutant andBRCA1/2-wild-type cell line and PDX models.ConclusionsE2-induced ER activity drives DNA damage and growth inhibition in endocrine-resistant breast cancer cells. Inhibition of the DNA damage response using drugs such as PARP inhibitors can enhance therapeutic response to E2. These findings warrant clinical exploration of the combination of E2 with DNA damage response inhibitors in advanced ER+ breast cancer, and suggest that PARP inhibitors may synergize with therapeutics that exacerbate transcriptional stress.