bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Plantar Surface Shear Strain Methodology Utilising Digital Image Correlation
Authors: Crossland Sarah R. , Siddle Heidi J. , Culmer Peter , Brockett Claire L. 
Published: June 2022

AbstractThe increase in the global diabetic population is leading to an increase in associated complications such as diabetic foot ulceration (DFU), associated amputations, morbidity, which substantial treatment costs. Early identification of DFU risk is therefore of great benefit. International guidelines recommend off-loading is the most important intervention for healing and prevention of DFU, with current research focused on pressure measurement techniques. The contribution of strain to DFU formation is not well understood due to challenges in measurement. The limited data available in the literature suggest that plantar strain is involved in ulcer formation. As a consequence, there is a need for plantar strain measurement systems to advance understanding and inform clinical treatment. A method was developed to determine plantar strain based on a Digital Image Correlation (DIC) approach. A speckle pattern is applied to the plantar aspect of the foot using a low ink transference method. A raised walkway with transparent panels is combined with a calibrated camera to capture images of the plantar aspect throughout a single stance phase. Plantar strain is then determined using 2D DIC and custom analysis summarises these data into clinically relevant metrics. A feasibility study involving six healthy participants was used to assess the efficacy of this new technique. The feasibility study successfully captured plantar surface strain characteristics continuously throughout the stance phase for all participants. Peak mean and averaged mean strains varied in location between participants when mapped into anatomical regions of plantar interest, ranging from the calcaneus to the metatarsal heads and hallux. This method provides the ability to measure plantar skin strain for use in both research and clinical environments. It has the potential to inform improved understanding of the role of strain in DFU formation. Further studies using this technique can support these ambitions and help differentiate between healthy and abnormal plantar strain regimes.
Evaluating the Relationship between Neighborhood-Level Social Vulnerability and Patient Adherence to Ophthalmology Appointments
Authors: Scanzera Angelica C. , Kravets Sasha , Hallak Joelle A. , Musick Hugh , Krishnan Jerry A. , Paul Chan R.V. , Kim Sage J. 
Published: June 2022

AbstractObjectiveLittle is known about the association between neighborhood characteristics and non-adherence to attending scheduled ophthalmology appointments. The purpose of this study was to examine the association between neighborhood-level social vulnerability and adherence to scheduled ophthalmology appointments.DesignRetrospective cohort study.ParticipantsAdults aged 18 years and older with scheduled ophthalmology appointments between September 12, 2020, and February 8, 2021.MethodsA single-center study was conducted at the University of Illinois Chicago Illinois Eye and Ear Infirmary, an urban tertiary care referral center in Chicago, Illinois. Primary exposure is neighborhood-level Social Vulnerability Index (SVI), based on the patient’s address of residence. The SVI ranks (possible range 0 to 1) each census tract on 15 social factors into four related themes (socioeconomic status, household composition & disability, minority status & language, and housing type & transportation). Higher SVI rankings indicate higher levels of social vulnerability. The overall SVI ranking and rankings for each of the four themes were analyzed separately as the primary exposure of interest in multivariable logistic regression models that controlled for age, sex, status (new or established appointment), race, and distance from clinic.Main Outcome MeasureNon-adherence to attending scheduled ophthalmology appointments, defined as missing more than 25% of scheduled appointments.ResultsA total of 8,322 unique patients (41% non-Hispanic Black, 24% Hispanic, 22% non-Hispanic White) had scheduled appointments during the five-month study period (range 1 to 23 appointments). Of those, 28% of patients were non-adherent to appointments. In multivariable logistic regression models, non-adherence to appointments was associated with living in higher SVI ranking neighborhoods (socioeconomic status: (adjusted odds ratio [95% confidence interval]) 2.38 [1.94, 2.91]; household composition/disability: 1.51 [1.26, 1.81]; minority status/language: 2.03 [1.55, 2.68]; housing type/transportation: 1.41 [1.16, 1.73]; and overall SVI: 2.46 [1.99, 3.06]).ConclusionsNeighborhood-level measures of social vulnerability are associated with greater risk of non-adherence to scheduled ophthalmology appointments. Studies to better understand these neighborhood-level vulnerabilities are needed to inform the design and evaluation of multi-level (individual and neighborhood) strategies to reduce disparities in access to ophthalmology care.
Decoding functional cell–cell communication events by multi-view graph learning on spatial transcriptomics
Authors: Li Haochen , Ma Tianxing , Hao Minsheng , Guo Wenbo , Gu Jin , Wei Lei , Zhang Xuegong 
Published: June 2022

AbstractCell–cell communication events (CEs) are mediated by multiple ligand–receptor pairs. Usually only a particular subset of CEs directly works for a specific downstream response in a particular microenvironment. We name them as functional communication events (FCEs) of the target responses. Decoding the FCE-target gene relations is important for understanding the machanisms of many biological processes, but has been intractable due to the mixing of multiple factors and the lack of direct observations. We developed a method HoloNet for decoding FCEs using spatial transcriptomic data by integrating ligand–receptor pairs, cell-type spatial distribution and downstream gene expression into a deep learning model. We modeled CEs as a multiview network, developed an attention-based graph learning method to train the model for generating target gene expression with the CE networks, and decoded the FCEs for specific downstream genes by interpreting the trained model. We applied HoloNet on three Visium datasets of breast cancer or liver cancer. It revealed the communication landscapes in tumor microenvironments, and uncovered how various ligand–receptor signals and cell types affect specific biological processes. We also validated the stability of HoloNet in a Slideseq-v2 dataset. The experiments showed that HoloNet is a powerful tool on spatial transcriptomic data to help revealing specific cell–cell communications in a microenvironment that shape cellular phenotypes.
S373P Mutation Stabilizes the Receptor-binding Domain of Spike Protein in Omicron and Promotes Binding
Authors: Zheng Bin , Xiao Yuelong , Tong Bei , Mao Yutong , Ge Rui , Tian Fang , Dong Xianchi , Zheng Peng 
Published: June 2022

AbstractA cluster of several newly occurring mutations on Omicron are found at the β-core region of spike protein’s receptor-binding domain (RBD), where mutation rarely happened before. Notably, the binding of SARS-CoV-2 to human receptor ACE2 via RBD happens in a dynamic airway environment, where mechanical force caused by coughing or sneezing occurs and applies to the proteins. Thus, we used atomic force microscopy-based single-molecule force spectroscopy (AFM-SMFS) to measure the stability of RBDs and found that the mechanical stability of Omicron RBD increased by ~20% compared with the wild-type. Molecular dynamics simulations revealed that Omicron RBD showed more hydrogen bonds in the β-core region due to the closing of the α-helical motif caused primarily by mutation S373P, which was further confirmed experimentally. Moreover, the binding ability of Omicron to ACE2 is promoted with a stabilized RBD. This work reveals the effect of the highly conserved mutation S373P which is present in most Omicron subvariants, including BA.1-5, BQ. 1, XBB, and CH.1.1.
Extracting and characterizing protein-free megabasepair DNA for in vitro experiments
Authors: Holub Martin , Birnie Anthony , Japaridze Aleksandre , van der Torre Jaco , den Ridder Maxime , de Ram Carol , Pabst Martin , Dekker Cees 
Published: June 2022

AbstractChromosome structure and function is studied in cells using imaging and chromosome-conformation-based methods as well as in vitro with a range of single-molecule techniques. Here we present a method to obtain genome-size (megabasepair length) deproteinated DNA for in vitro studies, which provides DNA substrates that are two orders of magnitude longer than typically studied in single-molecule experiments. We isolated chromosomes from bacterial cells and enzymatically digested the native proteins. Mass spectrometry indicated that 97-100% of DNA-binding proteins are removed from the sample. Upon protein removal, we observed an increase in the radius of gyration of the DNA polymers, while quantification of the fluorescence intensities showed that the length of the DNA objects remained megabasepair sized. In first proof-of-concept experiments using these deproteinated long DNA molecules, we observed DNA compaction upon adding the DNA-binding protein Fis or PEG crowding agents and showed that it is possible to track the motion of a fluorescently labelled DNA locus. These results indicate the practical feasibility of a ‘genome-in-a-box’ approach to study chromosome organization from the bottom up.
Age-related Macular Degeneration patient deep phenotyping and whole genome sequencing analysis identifies coding variants linking small low-luminance visual deficit to fat storage defects
Authors: Kim Sehyun , Stockwell Amy , Qin Han , Gao Simon S. , Sagolla Meredith , Stoilov Ivaylo , Wuster Arthur , Lai Phillip , Yaspan Brian L. , Jeanne Marion 
Published: June 2022

AbstractBackgroundThe basis of Age-related macular degeneration (AMD) genetic risk has been well documented; however, few studies have looked at genetic biomarkers of disease progression or treatment response within advanced AMD patients. Here we report the first genome-wide analysis of genetic determinants of low-luminance vision deficit (LLD), which is seen as predictive of visual acuity loss and anti-VEGF treatment response in neovascular AMD patients.MethodsAMD patients were separated into small- and large-LLD groups for comparison and whole genome sequencing was performed. Genetic determinants of LLD were assessed by common and rare variant genetic analysis. Follow-up functional analysis of rare coding variants identified by the burden test was then performed in vitro.ResultsWe identified four coding variants in the CIDEC gene. These rare variants were only present in patients with a small LLD, which has been previously shown to indicate better prognosis and better treatment response. Our in vitro functional characterization of these CIDEC alleles revealed that all decrease the binding affinity between CIDEC and the lipid droplet fusion effectors PLIN1, RAB8A and AS160. The rare CIDEC alleles all cause a hypomorphic defect in lipid droplet fusion and enlargement, resulting in a decreased fat storage capability in adipocytes.ConclusionsAs we did not detect CIDEC expression in the ocular tissue affected by AMD, our results suggest that the CIDEC variants do not play a direct role in the eye and influence low-luminance vision deficit via an indirect and systemic effect related to fat storage capacity.FundingNo external funding was received for this work.
Metabolic influence of core ciliates within the rumen microbiome
Authors: Andersen Thea O. , Altshuler Ianina , de Leon Arturo V.P. , Walter Juline , McGovern Emily , Keogh Kate , Martin Cécile , Bernard Laurence , Morgavi Diego P. , Park Tansol , Li Zongjun , Jiang Yu , Firkins Jeffrey L. , Yu Zhongtang , Hvidsten Torgeir R. , Waters Sinead M. , Popova Milka , Arntzen Magnus Ø. , Hagen Live H. , Pope Phillip B. 
Published: June 2022

ABSTRACTProtozoa comprise a major fraction of the microbial biomass in the rumen microbiome, of which the entodiniomorphs (order:Entodiniomorphida) and holotrichs (order:Vestibuliferida) are consistently observed to be dominant across a diverse genetic and geographical range of ruminant hosts. Despite the apparent core role that protozoal species exert, their major biological and metabolic contributions to rumen function remain largely undescribedin vivo. Here, we have leveraged (meta)genome-centric metaproteomes from rumen fluid samples originating from both cattle and goats fed diets with varying inclusion levels of lipids and starch, to detail the specific metabolic niches that protozoa occupy in the context of their microbial co-habitants. Initial proteome estimations via total protein counts and label-free quantification highlight that entodiniomorph speciesEntodiniumandEpidiniumas well as the holotrichsDasytrichaandIsotrichacomprise an extensive fraction of the total rumen metaproteome. Proteomic detection of protozoal metabolism such as hydrogenases (Dasytricha, Isotricha, Epidinium, Enoploplastron), carbohydrate-active enzymes (Epidinium, Diplodinium, Enoploplastron, Polyplastron), microbial predation (Entodinium) and volatile fatty acid production (EntodiniumandEpidinium) was observed at increased levels in high methane-emitting animals. Despite certain protozoal species having well-established reputations for digesting starch, they were unexpectedly less detectable in low methane emitting-animals fed high starch diets, which were instead dominated by propionate/succinate-producing bacterial populations suspected of being resistant to predation irrespective of host. Finally, we reaffirmed our abovementioned observations in geographically independent datasets, thus illuminating the substantial metabolic influence that under-explored eukaryotic populations have in the rumen, with greater implications for both digestion and methane metabolism.
The Saccharina latissima microbiome: algal tissue matters more than region, season, and physiology
Authors: Burgunter-Delamare Bertille , Rousvoal Sylvie , Legeay Erwan , Tanguy Gwenn , Fredriksen Stein , Boyen Catherine , Dittami Simon M. 
Published: June 2022

ABSTRACTSaccharina latissima is a canopy-forming species of brown algae and, as such, is considered an ecosystem engineer. Several populations of this alga are exploited worldwide, and a decrease in the abundance of S. latissima at its southern distributional range limits has been observed. Despite its economic and ecological interest, only a few data are available on the composition of microbiota associated with S. latissima and its role in algal physiology. We studied the whole bacterial community composition associated with S. latissima samples from three locations (Brittany, Helgoland, and Skagerrak) by 16S metabarcoding analyses at different scales: algal blade part, regions, season, and physiologic state.We have shown that the difference in bacterial composition is driven by factors of decreasing importance: (i) the algal tissues (apex/meristem), (ii) the geographical area, (iii) the seasons, and (iv) the algal host’s condition (healthy vs. symptoms). Overall, Alphaproteobacteria, Gammaproteobacteria, and Bacteroidota dominated the general bacterial communities. Almost all individuals hosted bacteria of the genus Granulosicoccus, accounting for 12% of the total sequences, and eight additional core genera were identified. Our results also highlight a microbial signature characteristic for algae in poor health independent of the disease symptoms. Thus, our study provides a comprehensive overview of the S. latissima microbiome, forming a basis for understanding holobiont functioning.
When do bursts matter in the motor cortex? Investigating changes in the intermittencies of beta rhythms associated with movement states
Authors: West Timothy O. , Duchet Benoit , Farmer Simon F. , Friston Karl J. , Cagnan Hayriye 
Published: June 2022

AbstractTime series of brain activity recorded from different anatomical regions and in different behavioural states and pathologies can be summarised by the power spectrum. Recently, attention has shifted to characterising the properties of changing temporal dynamics in rhythmic neural activity. Here, we present evidence from electrocorticography recordings made from the motor cortex to show that, dependent on the specific motor context, the statistics of temporal transients in beta frequency (14-30 Hz) rhythms (i.e., bursts) can significantly add to the description of states such rest, movement preparation, movement execution, and movement imagery. We show that the statistics of burst duration and amplitude can significantly improve the classification of motor states and that burst features reflect nonlinearities not detectable in the power spectrum, with states increasing in order of nonlinearity from movement execution to movement preparation to rest. Further, we provide mechanistic explanations for these features by fitting models of the motor cortical microcircuit to the empirical data and investigate how dynamical instabilities interact with noise to generate burst dynamics. Finally, we examine how beta bursting in motor cortex may influence the integration of exogenous inputs to the cortex and suggest that properties of spontaneous activity cannot be reliably used to infer the response of the cortex to external inputs. These findings have significance for the classification of motor states, for instance in novel brain-computer interfaces. Critically, we increase the understanding of how transient brain rhythms may contribute to cortical processing, which in turn, may inform novel approaches for its modulation with brain stimulation.
Contributions of Bayesian and Discriminative Models to Active Visual Perception across Saccades
Authors: Subramanian Divya , Pearson John , Sommer Marc A. 
Published: June 2022

SummaryThe brain interprets sensory inputs to guide behavior, but behavior disrupts sensory inputs. In primates, saccadic eye movements displace visual images on the retina and yet the brain perceives visual stability, a process called active vision. We studied whether active vision is Bayesian. Humans and monkeys reported whether an image moved during saccades. We tested whether they used prior expectations to account for sensory uncertainty in a Bayesian manner. For continuous judgments, subjects were Bayesian. For categorical judgments, they were anti-Bayesian for uncertainty due to external, image noise but Bayesian for uncertainty due to internal, motor-driven noise. A discriminative learning model explained the anti-Bayesian effect. Therefore, active vision uses both Bayesian and discriminative models depending on task requirements (continuous vs. categorical) and the source of uncertainty (image noise vs. motor-driven noise), suggesting that active perceptual mechanisms are governed by the interaction of both models.
Kiaa1024L/Minar2 is essential for hearing by regulating cholesterol distribution in hair bundles
Authors: Gao Ge , Guo Shuyu , Zhang Quan , Zhang Hefei , Zhang Cuizhen , Peng Gang 
Published: June 2022

AbstractUnbiased genetic screens implicated a number of uncharacterized genes in hearing loss, suggesting some biological processes required for auditory function remain unexplored. Loss of Kiaa1024L/Minar2, a previously understudied gene, caused deafness in mice, but how it functioned in hearing was unclear. Here we show that disruption of kiaa1024L/minar2 causes hearing loss in the zebrafish. Defects in mechanotransduction, longer and thinner hair bundles, and enlarged apical lysosomes in hair cells are observed in kiaa1024L/minar2 mutant. In cultured cells, Kiaa1024L/Minar2 is mainly localized to lysosomes and its overexpression recruits cholesterol and increases cholesterol labeling. Strikingly, an accessible pool of cholesterol is highly enriched in the hair bundle membrane, and loss of kiaa1024L/minar2 reduces cholesterol localization to the hair bundles. Decreasing cholesterol levels aggravates, while increasing cholesterol levels rescues hair cell defects in kiaa1024L/minar2 mutant. Therefore cholesterol plays an essential role in the hair bundles, and Kiaa1024L/Minar2 regulates cholesterol distribution and homeostasis to ensure normal hearing.
WiNGS: Widely integrated NGS platform for federated genome analysis
Authors: Chizari Haleh , Sattanathan Nishkala , Ardeshirdavani Amin , Shabani Nasim , Huremagic Benjamin , Vermeesch Joris Robert , Moreau Yves , Vandeweyer Geert 
Published: June 2022

AbstractNext-generation sequencing (NGS) has been increasingly used in a wide range of research communities and in routine clinical practice and leads to an ever increasing amount of sequencing data. Sequencing data comes with, several challenges such as sharing, storing, integrating, analyzing, and interpretion. The management of the expanding amount of data is challenging and, especially for human omics data, privacy protection is crucial. Unraveling the causes of rare diseases is critically dependent on data sharing, but progress is hampered by regulations and privacy concerns. To overcome the concerns associated with centralized human genomic data storage, we developed a federated analysis platform, referred to as Widely Integrated NGS (WiNGS). The presented approach enables datasharing and combined data-analysis of omics data across a consortium without a centralized data store. Moreover, the platform incorporates extensive variant interpretation tools from genotype to phenotype for the diagnosis of rare developmental disorders.
Non-cell-adhesive hydrogel promotes formation of human blastoids from primed human pluripotent stem cells
Authors: Imamura Satoshi , Wen Xiaopeng , Terada Shiho , Yamamoto Akihisa , Mutsuda-Zapater Kaori , Sawada Kyoko , Yoshimoto Koki , Tanaka Motomu , Kamei Ken-ichiro 
Published: June 2022

AbstractArtificial human blastoids are used to investigate early embryo development, pregnancy failures, and birth deficiencies, previously impossible without human embryos. Recent methods generating blastoids used human naive pluripotent stem cells, which are prone to genomic instability duringin vitroculturing. Here, we introduce a simple, robust, and scalable method for generating human blastoids from more stable, primed human pluripotent stem cells (hPSC). Using a non-cell-adhesive hydrogel, hPSC aggregates formed an asymmetric blastoid structure with a cellular distribution similar to that of a human blastocyst, within vitroimplantation capability. Single-cell RNA-seq followed by cellular trajectory analysis revealed that hydrogel promoted differentiation to tri-lineage cells associated with a blastocyst. This model will allow studies on the underlying mechanisms of human pre- and postimplantation processes, consider elaborating on the potential implications of the model on assistive reproductive technology.One Sentence SummaryNo more than 125 characters and spaces.