bluuebunny/crossref_metadata_2025_split huggingface dataset:
M1 recruitment during interleaved practice is important for encoding, not just consolidation, of novel skill memory
Authors: Kim Taewon , Kim Hakjoo , Philip Benjamin A. , Wright David L. 
Published: July 2023

ABSTRACTPrimary motor cortex (M1) plays a major role in motor memory acquisition and retention in humans, but its role in interleaved practice (as opposed to repetitive practice) remains unknown. We anticipated that the improved retention typically associated with interleaved practice depends on M1, and thus cathodal transcranial direct current (ctDCS) stimulation to M1 during training would disrupt this improved retention. The benefits of interleaved practice have been reported to occur from more effective consolidation, manifested as rapid skill memory stabilization followed by more long-term enhancement. While we observed the expected decline in retention performance following interleaved practice paired with ctDCS, this reduced retention resulted from more modest encoding of novel skill memory during acquisition rather than from disruption of offline consolidation processes. These data highlight the broad role played by motor cortex for both encoding and retention of novel skill memory.
Three-dimensional single-cell transcriptome imaging of thick tissues
Authors: Fang Rongxin , Halpern Aaron R. , Rahman Mohammed Mostafizur , Huang Zhengkai , Lei Zhiyun , Hell Sebastian J. , Dulac Catherine , Zhuang Xiaowei 
Published: July 2023

AbstractMultiplexed error-robust fluorescencein-situhybridization (MERFISH) allows genome-scale imaging of RNAs in individual cells in intact tissues. To date, MERFISH has been applied to image thin tissue samples of ∼10-µm thickness. Here, we present a thick-tissue three-dimensional (3D) MERFISH imaging method, which uses confocal microscopy for optical sectioning, deep learning for increasing imaging speed and quality, as well as sample preparation and imaging protocol optimized for image registration of thick samples. We demonstrated 3D MERFISH on mouse brain tissue sections of up to 200 µm thickness with high detection efficiency and accuracy. We anticipate that 3D thick-tissue MERFISH imaging will broaden the scope of questions that can be addressed by spatial genomics.
AlphaFold2 models of the active form of all 437 catalytically competent human protein kinase domains
Authors: Faezov Bulat , Dunbrack Roland L. 
Published: July 2023

AbstractHumans have 437 catalytically competent protein kinase domains with the typical kinase fold, similar to the structure of Protein Kinase A (PKA). Only 155 of these kinases are in the Protein Data Bank in their active form. The active form of a kinase must satisfy requirements for binding ATP, magnesium, and substrate. From structural bioinformatics analysis of 40 unique substrate-bound kinases, we derived several criteria for the active form of protein kinases. We include requirements on the DFG motif of the activation loop but also on the positions of the N-terminal and C-terminal segments of the activation loop that must be placed appropriately to bind substrate. Because the active form of catalytic kinases is needed for understanding substrate specificity and the effects of mutations on catalytic activity in cancer and other diseases, we used AlphaFold2 to produce models of all 437 human protein kinases in the active form. This was accomplished with templates in the active form from the PDB and shallow multiple sequence alignments of orthologs and close homologs of the query protein. We selected models for each kinase based on the pLDDT scores of the activation loop residues, demonstrating that the highest scoring models have the lowest or close to the lowest RMSD to 22 non-redundant substrate-bound structures in the PDB. A larger benchmark of all 130 active kinase structures with complete activation loops in the PDB shows that 80% of the highest-scoring AlphaFold2 models have RMSD < 1.0 Å and 90% have RMSD < 2.0 Å over the activation loop backbone atoms. Models for all 437 catalytic kinases are available athttp://dunbrack.fccc.edu/kincore/activemodels. We believe they may be useful for interpreting mutations leading to constitutive catalytic activity in cancer as well as for templates for modeling substrate and inhibitor binding for molecules which bind to the active state.
Mechanoreceptive Aβ primary afferents discriminate naturalistic social touch inputs at a functionally relevant time scale
Authors: Xu Shan , Hauser Steven C. , Nagi Saad S. , Jablonski James A. , Rezaei Merat , Jarocka Ewa , Marshall Andrew G. , Olausson Håkan , McIntyre Sarah , Gerling Gregory J. 
Published: July 2023

AbstractInterpersonal touch is an important part of our social and emotional interactions. How these physical, skin-to-skin touch expressions are processed in the peripheral nervous system is not well understood. From single-unit microneurography recordings in humans, we evaluated the capacity of six subtypes of cutaneous afferents to differentiate perceptually distinct social touch expressions. By leveraging conventional statistical analyses and classification analyses using convolutional neural networks and support vector machines, we found that single units of multiple Aβ subtypes, especially slowly adapting type II (SA-II) and fast adapting hair follicle afferents (HFA), can reliably differentiate the skin contact of those expressions at accuracies similar to those perceptually. Rapidly adapting field (Field) afferents exhibit lower accuracies, whereas C-tactile (CT), fast adapting Pacinian corpuscles (FA-II), and muscle spindle (MS) afferents can barely differentiate the expressions, despite responding to the stimuli. We then identified the most informative firing patterns of SA-II and HFA afferents’ spike trains, which indicate that an average duration of 3-4 s of firing provides sufficient discriminative information. Those two subtypes also exhibit robust tolerance to shifts in spike-timing of up to 10 ms. A greater shift in spike-timing, however, drastically compromises an afferent’s discrimination capacity, and can change a firing pattern’s envelope to resemble that of another expression. Altogether, the findings indicate that SA-II and HFA afferents differentiate the skin contact of social touch at time scales relevant for such interactions, which is 1-2 orders of magnitude longer than those relevant for discriminating non-social touch inputs.
Growth directions and stiffness across cell layers determine whether tissues stay smooth or buckle
Authors: Yadav Avilash S. , Hong Lilan , Klees Patrick M. , Kiss Annamaria , Petit Manuel , He Xi , Barrios Iselle M. , Heeney Michelle , Galang Anabella Maria D. , Smith Richard S. , Boudaoud Arezki , Roeder Adrienne H.K. 
Published: July 2023

AbstractFrom smooth to buckled, nature exhibits organs of various shapes and forms. How cellular growth patterns produce smooth organ shapes such as leaves and sepals remains unclear. Here we show that unidirectional growth and comparable stiffness across both epidermal layers of Arabidopsis sepals are essential for smoothness. We identified a mutant with ectopicASYMMETRIC LEAVES 2(AS2) expression on the outer epidermis. Our analysis reveals that ectopicAS2expression causes outer epidermal buckling at early stages of sepal development, due to conflicting growth directions and unequal epidermal stiffnesses. Aligning growth direction and increasing stiffness of the outer epidermis restores smoothness. Furthermore, buckling influences auxin efflux transporter protein PIN-FORMED 1 polarity to generate outgrowth in the later stages, suggesting that buckling is sufficient to initiate outgrowths. Our findings suggest that in addition to molecular cues influencing tissue mechanics, tissue mechanics can also modulate molecular signals, giving rise to well-defined shapes.One-Sentence SummaryTheasymmetric leaves 2-7Dmutant sepals buckle due to discoordination of growth between the two epidermal layers.
Ocular dominance columns in mouse visual cortex
Authors: Goltstein Pieter M. , Laubender David , Bonhoeffer Tobias , Hübener Mark 
Published: July 2023

AbstractThe columnar organization of response properties is a fundamental feature of the mammalian visual cortex. However, columns have not been observed universally across all mammalian species. Here, we report the discovery of ocular dominance columns in mouse visual cortex. Our observation in this minute cortical area sets a new boundary condition for models explaining the emergence of columnar organizations in the neocortex.
Landing the ‘Tiger of Rivers’: Understanding Recreational Angling of Mahseers in India using YouTube Videos
Authors: Das Prantik , Binoy V.V. 
Published: July 2023

AbstractMegafish mahseers popularly known as the ‘tiger of rivers’, are the dream catch of recreational anglers in India. The present study explored the Recreational Angling (RA) videos of five mahseer speciesTor khudree(deccan mahseer),T. putitora(golden mahseer),T. remadevii(humpback mahseer),T. mosal(mosal mahseer) andNeolissochilus hexagonolepis(chocolate mahseer) recorded from India and uploaded on the social media platform YouTube from January 2010 to October 2022. We did not come across any RA videos ofT. mosalandT. remadeviion YouTube hence further analyses were carried out on the remaining three focal species. No seasonality was observed in the frequency of RA videos uploaded on YouTube andT. khudreeattracted the highest number of views per video. Catch and Release (C&R), an ethical RA practice was noticeably low in the case ofN. hexagonolepis. The size of the catch was found to be positively associated with the social engagement received by the RA videos of all the three mahseer species focused. Angler and angling-related remarks and words associated with the emotion ‘trust’ dominated the comments received by the videos. The results are discussed in light of the trending discourses on developing social media data as a complementary tool for monitoring and managing RA and conserving fish.
Collaborative network analysis for the interpretation of transcriptomics data in rare diseases, an application to Huntington’s disease
Authors: Ozisik Ozan , Kara Nazli Sila , Abbassi-Daloii Tooba , Térézol Morgane , Queralt-Rosinach Núria , Jacobsen Annika , Sezerman Osman Ugur , Roos Marco , Evelo Chris T. , Baudot Anaïs , Ehrhart Friederike , Mina Eleni 
Published: July 2023

AbstractBackgroundRare diseases may affect the quality of life of patients and in some cases be life-threatening. Therapeutic opportunities are often limited, in part because of the lack of understanding of the molecular mechanisms that can cause disease. This can be ascribed to the low prevalence of rare diseases and therefore the lower sample sizes available for research. A way to overcome this is to integrate experimental rare disease data with prior knowledge using network-based methods. Taking this one step further, we hypothesized that combining and analyzing the results from multiple network-based methods could provide data-driven hypotheses of pathogenicity mechanisms from multiple perspectives.ResultsWe analyzed a Huntington’s disease (HD) transcriptomics dataset using six network-based methods in a collaborative way. These methods either inherently reported enriched annotation terms or their results were fed into enrichment analyses. The resulting significantly enriched Reactome pathways were then summarized using the ontological hierarchy which allowed the integration and interpretation of outputs from multiple methods. Among the resulting enriched pathways, there are pathways that have been shown previously to be involved in HD and pathways whose direct contribution to disease pathogenesis remains unclear and requires further investigation.ConclusionsIn summary, our study shows that collaborative network analysis approaches are well-suited to study rare diseases, as they provide hypotheses for pathogenic mechanisms from multiple perspectives. Applying different methods to the same case study can uncover different disease mechanisms that would not be apparent with the application of a single method.
Dendritic Cells Overcome Cre/Lox Induced Gene Deficiency by Siphoning Material From Neighboring Cells Using Intracellular Monitoring—a Novel Mechanism of Antigen Acquisition
Authors: Herbst Christopher H. , Bouteau Aurélie , Menykő Evelin J. , Qin Zhen , Su Qingtai , Buelvas Dunia M. , Gyenge Ervin , Mabbott Neil A. , Igyártó Botond Z. 
Published: July 2023

ABSTRACTMacrophages and dendritic cells (DCs) in peripheral tissue interact closely with their local microenvironment by scavenging protein and nucleic acids released by neighboring cells. Material transfer between cell types is necessary for pathogen detection and antigen presentation, but thought to be relatively limited in scale. Recent reports, however, demonstrate that the quantity of transferred material can be quite large when DCs are in direct contact with live cells. This observation may be problematic for conditional gene deletion models that assume gene products will remain in the cell they are produced in. Here, we investigate whether conditional gene deletions induced by the widely used Cre/Lox system can be overcome at the protein level in DCs. Of concern, using the human Langerin Cre mouse model, we find that epidermal Langerhans cells and CD11b+CD103+ mesenteric DCs can overcome gene deletion if the deleted gene is expressed by neighboring cells. Surprisingly, we also find that the mechanism of material transfer does not resemble known mechanisms of antigen uptake, is dependent on extra- and intracellular calcium, PI3K, and scavenger receptors, and mediates a majority of material transfer to DCs. We term this novel processintracellular monitoring,and find that it is specific to DCs, but occurs in all murine DC subsets tested, as well as in human DCs. Transferred material is successfully presented and cross presented on MHC-II and MHC-I, and occurs between allogeneic donor and acceptors cells—implicating this widespread and unique process in immunosurveillance and organ transplantation.ONE SENTENCE SUMMARYDendritic cells maintain RNA and protein levels for conditionally deleted genes by siphoning material from neighboring cells using a novel mechanism.
Matrix confinement modulates 3D spheroid sorting and burst-like collective migration
Authors: Cai Grace , Li Xinzhi , Lin Shan-Shan , Chen Samuel J. , Rodgers Nicole C. , Koning Katherine M. , Bi Dapeng , Liu Allen P. 
Published: July 2023

AbstractWhile it is known that cells with differential adhesion tend to segregate and preferentially sort, the physical forces governing sorting and invasion in heterogeneous tumors remain poorly understood. To investigate this, we tune matrix confinement, mimicking changes in the stiffness and confinement of the tumor microenvironment, to explore how physical confinement influences individual and collective cell migration in 3D spheroids. High levels of confinement lead to cell sorting while reducing matrix confinement triggers the collective fluidization of cell motion. Cell sorting, which depends on cell-cell adhesion, is crucial to this phenomenon. Burst-like migration does not occur for spheroids that have not undergone sorting, regardless of the degree of matrix confinement. Using computational Self-Propelled Voronoi modeling, we show that spheroid sorting and invasion into the matrix depend on the balance between cell-generated forces and matrix resistance. The findings support a model where matrix confinement modulates 3D spheroid sorting and unjamming in an adhesion-dependent manner, providing insights into the mechanisms of cell sorting and migration in the primary tumor and toward distant metastatic sites.
Bilingual Language Model for Protein Sequence and Structure
Authors: Heinzinger Michael , Weissenow Konstantin , Sanchez Joaquin Gomez , Henkel Adrian , Mirdita Milot , Steinegger Martin , Rost Burkhard 
Published: July 2023

AbstractAdapting large language models (LLMs) to protein sequences spawned the development of powerful protein language models (pLMs). Concurrently, AlphaFold2 broke through in protein structure prediction. Now we can systematically and comprehensively explore the dual nature of proteins that act and exist as three-dimensional (3D) machines and evolve as linear strings of one-dimensional (1D) sequences. Here, we leverage pLMs to simultaneously model both modalities by combining 1D sequences with 3D structure in a single model. We encode protein structures as token sequences using the 3Di-alphabet introduced by the 3D-alignment methodFoldseek. This new foundation pLM extracts the features and patterns of the resulting “structure-sequence” representation. Toward this end, we built a non-redundant dataset from AlphaFoldDB and fine-tuned an existing pLM (ProtT5) to translate between 3Di and amino acid sequences. As a proof-of-concept for our novel approach, dubbed Protein structure-sequence T5 (ProstT5), we showed improved performance for subsequent prediction tasks, and for “inverse folding”, namely the generation of novel protein sequences adopting a given structural scaffold (“fold”). Our work showcased the potential of pLMs to tap into the information-rich protein structure revolution fueled by AlphaFold2.ProstT5paves the way to develop new tools integrating the vast resource of 3D predictions, and opens new research avenues in the post-AlphaFold2 era. Our model is freely available for all athttps://github.com/mheinzinger/ProstT5.
Deep learning-based cell profiling based on neuronal morphology
Authors: Liu Qiang , Nicholls Francesca , Rowland Helen A. , Dangla-Valls Adrià , Li Shuhan , Zhang Yi , Kalinowski Piotr , Ribe Elena , Ifkovits Jamie L. , Kumar Sanjay , Nguyen Cuong Q. , Nevado-Holgado Alejo , Buckley Noel J. , Kormilitzin Andrey 
Published: July 2023

AbstractTreatment of neurons with β-amyloid peptide (Aβ1-42) has been widely used as a model to interrogate the cellular and molecular mechanisms underlying Alzheimer’s disease, and as an assay system to identify drugs that reverse or block disease phenotype. Prior studies have largely relied on high content imaging (HCI) to extract cellular features such as neurite length or branching, but these have not offered a robust/comprehensive means of relating readout to Aβ1-42concentrations. Here, we use a deep learning-based cell profiling technique to directly measure the impact of Aβ1-42on primary murine cortical neurons. The deep learning model achieved approximately 80% accuracy, compared to 54% for the cell phenotypic feature-based approach. The deep learning model could distinguish subtle neuronal morphological changes induced by a range of Aβ1-42concentration. When tested on a separate dataset, the accuracy remained comparable and dropped by only 2%. Our study demonstrates that deep learning-based cell profiling is superior to HCI-based feature extraction on neuronal morphology and it provides an alternative to a dose/response curve, where the modality of the response does not have to be pre-determined. Moreover, this approach could form the basis of a screening tool that can be applied to any cellular model where appropriate phenotypic markers based on genotypes and/or pathological insults are available.
Natural Product Screen Identifies Asiatic Acid Targeting Mutant p53
Authors: Swargiary Geeta , Jamal Qazi S , Ojha Shreesh , Jha Niraj Kumar , Singh Keshav K , Mani Shalini 
Published: July 2023

AbstractMutations in p53 are common in different cancer types and are reported to protect cancer via different mechanisms. R175H, R248Q, and R273H are the hotspot mutations of p53 and are suggested to increase aerobic glycolysis in cancer cells. Cancer cells rely mostly upon aerobic glycolysis, so it will be interesting to target these three p53 mutants for designing alternative cancer therapy. The class of compounds studied for their potential to target energy metabolism of cancer cells is called mitocans. The current study is an approach to explore if these selected 3 mutants of p53 may act as suitable target(s) for natural mitocans. Hereby, we selected 60 phytocompounds altogether fromAndrographis paniculataandCentella asiaticaand docked against all three p53 mutants, using Autodock vina. 11 compounds were sorted based on their binding energies and drug-like properties, and toxicity levels prediction showed asiatic acid to be the most significant. As asiatic acid was observed to significantly bind with R248Q only, R248Q-Asiatic acid was identified for molecular dynamics simulation using GROMACS which showed significant interactions. In conclusion, mutant R248Q was observed to be the best target for asiatic acid, though additionalin-vitroexperiments are important to validate the findings of this study.
The Role of Rivers as Geographical Barriers in Shaping Genetic Differentiation and Diversity of Neotropical Primates
Authors: Helenbrook William D. , Valdez Jose 
Published: July 2023

ABSTRACTWe quantitatively tested the riverine barrier hypothesis and its influence on biogeographical distributions and molecular variation in New World monkeys (Parvorder: Platyrrhini). Using mitochondrial markers (cytochrome oxidase subunit II and cytochrome b), we analyzed taxonomic differences and the effects of geographical barriers on molecular patterns across Central and South America. Nearly 80% of described species are separated by geographical barriers. River width exhibited a positive correlation with molecular dissimilarity in adjacent taxa for both molecular markers. Streamflow also showed a positive association, although not statistically significant, likely due to limited sample size. Several presently described taxa were not supported based solely on these molecular phylogenetic markers, includingSaimiri,Mico,Cebus,Sapajus, andCherecebus. These taxonomic issues are far more common where river barriers do not exist. In conclusion, we found a significant correlation between river width and molecular divergence in adjacent taxa, indicating that wider rivers were associated with greater molecular dissimilarity for two commonly used mitochondrial genes. Species boundaries were predominantly found at river interfaces, and in the absence of discernable geological barriers, adjoining species were more likely to exhibit molecular similarity. Our findings suggest that both river and mountain barriers significantly restrict gene flow for the majority of neotropical taxa, with geological formation of river barriers coinciding with estimated speciation events. Additionally, river width proves to be a valuable tool for estimating molecular divergence in adjacent taxa, particularly in regions with limited sampling.
Allostery in Protein Tyrosine Phosphatases is Enabled by Divergent Dynamics
Authors: Welsh Colin L. , Madan Lalima K. 
Published: July 2023

AbstractDynamics-driven allostery provides important insights into the working mechanics of proteins, especially enzymes. In this study we employ this paradigm to answer a basic question: in enzyme superfamilies where the catalytic mechanism, active sites and protein fold are conserved, what accounts for the difference in the catalytic prowess of the individual members? We show that when subtle changes in sequence do not translate to changes in structure, they do translate to changes in dynamics. We use sequentially diverse PTP1B, TbPTP1, and YopH as the representatives of the conserved Protein Tyrosine Phosphatase (PTP) superfamily. Using amino acid network analysis of group behavior (community analysis) and influential node dominance on networks (eigenvector centrality), we explain the dynamic basis of catalytic variations seen between the three proteins. Importantly, we explain how a dynamics-based blueprint makes PTP1B amenable to allosteric control and how the same is abstracted in TbPTP1 and YopH.