bluuebunny/crossref_metadata_2025_split huggingface dataset:
Interpretable deep learning approach for extracting cognitive features from hand-drawn images of intersecting pentagons in older adults
Authors: Tasaki Shinya , Kim Namhee , Truty Tim , Zhang Ada , Buchman Aron S , Lamar Melissa , Bennett David A. 
Published: April 2023

AbstractHand drawing involves multiple neural systems for planning and precise control of sequential movements, making it a valuable cognitive test for older adults. However, conventional visual assessment of drawings may not capture intricate nuances that could help track cognitive states. To address this issue, we utilized a deep-learning model, PentaMind, to examine cognition-related features from hand-drawn images of intersecting pentagons. PentaMind, trained on 13,777 images from 3,111 participants in three aging cohorts, explained 23.3% of the variance in global cognitive scores, a comprehensive hour-long cognitive battery. The model’s performance, which was 1.92 times more accurate than conventional visual assessment, significantly improved the detection of cognitive decline. The improvement in accuracy was due to capturing additional drawing features that we found to be associated with motor impairments and cerebrovascular pathologies. By systematically modifying the input images, we discovered several important drawing attributes for cognition, including line waviness. Our results demonstrate that hand-drawn images can provide rich cognitive information, enabling rapid assessment of cognitive decline and suggesting potential clinical implications in dementia.
Gene regulatory network inference with popInfer reveals dynamic regulation of hematopoietic stem cell quiescence upon diet restriction and aging
Authors: Rommelfanger Megan K. , Behrends Marthe , Chen Yulin , Martinez Jonathan , Bens Martin , Xiong Lingyun , Rudolph K. Lenhard , MacLean Adam L. 
Published: April 2023

AbstractInference of gene regulatory networks (GRNs) can reveal cell state transitions from single-cell genomics data. However, obstacles to temporal inference from snapshot data are difficult to overcome. Single-nuclei multiomics data offer means to bridge this gap and derive temporal information from snapshot data using joint measurements of gene expression and chromatin accessibility in the same single cells. We developed popInfer to infer networks that characterize lineage-specific dynamic cell state transitions from joint gene expression and chromatin accessibility data. Benchmarking against alternative methods for GRN inference, we showed that popInfer achieves higher accuracy in the GRNs inferred. popInfer was applied to study single-cell multiomics data characterizing hematopoietic stem cells (HSCs) and the transition from HSC to a multipotent progenitor cell state during murine hematopoiesis across age and dietary conditions. From networks predicted by popInfer, we discovered gene interactions controlling entry to/exit from HSC quiescence that are perturbed in response to diet or aging.
Matrisome AnalyzeR: A suite of tools to annotate and quantify ECM molecules in big datasets across organisms
Authors: Petrov Petar B. , Considine James M. , Izzi Valerio , Naba Alexandra 
Published: April 2023

ABSTRACTThe extracellular matrix (ECM) is a complex meshwork of proteins that forms the scaffold of all tissues in multicellular organisms. It plays critical roles in all aspects of life: from orchestrating cell migration during development, to supporting tissue repair. It also plays critical roles in the etiology or progression of diseases. To study this compartment, we defined the compendium of all genes encoding ECM and ECM-associated proteins for multiple organisms. We termed this compendium the “matrisome” and further classified matrisome components into different structural or functional categories. This nomenclature is now largely adopted by the research community to annotate -omics datasets and has contributed to advance both fundamental and translational ECM research. Here, we report the development of Matrisome AnalyzeR, a suite of tools including a web-based application (https://sites.google.com/uic.edu/matrisome/tools/matrisome-analyzer) and an R package (https://github.com/Matrisome/MatrisomeAnalyzeR). The web application can be used by anyone interested in annotating, classifying, and tabulating matrisome molecules in large datasets without requiring programming knowledge. The companion R package is available to more experienced users, interested in processing larger datasets or in additional data visualization options.SUMMARY STATEMENTMatrisome AnalyzeR is a suite of tools, including a web-based app and an R package, designed to facilitate the annotation and quantification of extracellular matrix components in big datasets.
Partitioning to ordered membrane domains regulates the kinetics of secretory traffic
Authors: Castello-Serrano Ivan , Heberle Fred A. , Diaz-Rohrer Barbara , Ippolito Rossana , Shurer Carolyn R. , Lujan Pablo , Campelo Felix , Levental Kandice R. , Levental Ilya 
Published: April 2023

ABSTRACTThe organelles of eukaryotic cells maintain distinct protein and lipid compositions required for their specific functions. The mechanisms by which many of these components are sorted to their specific locations remain unknown. While some motifs mediating subcellular protein localization have been identified, many membrane proteins and most membrane lipids lack known sorting determinants. A putative mechanism for sorting of membrane components is based on membrane domains known as lipid rafts, which are laterally segregated nanoscopic assemblies of specific lipids and proteins. To assess the role of such domains in the secretory pathway, we applied a robust tool for synchronized secretory protein traffic (RUSH,RetentionUsingSelectiveHooks) to protein constructs with defined affinity for raft phases. These constructs consist solely of single-pass transmembrane domains (TMDs) and, lacking other sorting determinants, constitute probes for membrane domain-mediated trafficking. We find that while raft affinity can be sufficient for steady-state PM localization, it is not sufficient for rapid exit from the endoplasmic reticulum (ER), which is instead mediated by a short cytosolic peptide motif. In contrast, we find that Golgi exit kinetics are highly dependent on raft affinity, with raft preferring probes exiting Golgi ∼2.5-fold faster than probes with minimal raft affinity. We rationalize these observations with a kinetic model of secretory trafficking, wherein Golgi export can be facilitated by protein association with raft domains. These observations support a role for raft-like membrane domains in the secretory pathway and establish an experimental paradigm for dissecting its underlying machinery.
Single-cell analysis reveals distinct fibroblast plasticity during tenocyte regeneration in zebrafish
Authors: Rajan Arsheen M. , Rosin Nicole L. , Labit Elodie , Biernaskie Jeff , Liao Shan , Huang Peng 
Published: April 2023

ABSTRACTDespite their importance in tissue maintenance and repair, fibroblast diversity and plasticity remain poorly understood. Using single-cell RNA sequencing, we uncover distinct sclerotome-derived fibroblast populations in zebrafish, including progenitor-like perivascular/interstitial fibroblasts, and specialized fibroblasts such as tenocytes. To determine fibroblast plasticityin vivo, we develop a laser-induced tendon ablation and regeneration model. Lineage tracing reveals that laser-ablated tenocytes are quickly regenerated by preexisting fibroblasts. By combining single-cell clonal analysis and live imaging, we demonstrate that perivascular/interstitial fibroblasts actively migrate to the injury site, where they proliferate and give rise to new tenocytes. By contrast, perivascular fibroblast-derived pericytes or specialized fibroblasts, including tenocytes, exhibit no regenerative plasticity. Interestingly, active Hedgehog (Hh) signaling is required for the proliferation of activated fibroblasts to ensure efficient tenocyte regeneration. Together, our work highlights the functional diversity of fibroblasts and establishes perivascular/interstitial fibroblasts as tenocyte progenitors that promote tendon regeneration in a Hh signaling-dependent manner.TEASERPerivascular/interstitial fibroblasts function as plastic progenitors during tenocyte regeneration.
The condition for dynamic stability in humans walking with feedback control
Authors: Reimann Hendrik , Bruijn Sjoerd M. 
Published: April 2023

AbstractThe walking human body is mechanically unstable. Loss of stability and falling is more likely in certain groups of people, such as older adults or people with neuromotor impairments, as well as in certain situations, such as when experiencing conflicting or distracting sensory inputs. Stability during walking is often characterized biomechanically, by measures based on body dynamics and the base of support.Neural control of upright stability, on the other hand, does not factor into commonly used stability measures. Here we analyze stability of human walking accounting for both biomechanics and neural control, using a modeling approach. We define a walking system as a combination of biomechanics, using the well known inverted pendulum model, and neural control, using a proportional-derivative controller for foot placement based on the state of the center of mass at midstance. We analyze this system formally and show that for any choice of system parameters there is always one periodic orbit. We then determine when this periodic orbit is stable, i.e. how the neural control gain values have to be chosen for stable walking. Following the formal analysis, we use this model to make predictions about neural control gains and compare these predictions with the literature and existing experimental data. The model predicts that control gains should increase with decreasing cadence. This finding appears in agreement with literature showing stronger effects of visual or vestibular manipulations at different walking speeds.Author summaryThe walking human body is mechanically unstable and humans frequently lose upright stability and fall while walking. Stability of human walking is usually analyzed from a biomechanical perspective. We argue that sensorimotor control is an essential aspect of walking stability. We model a walking system as a combination of inverted pendulum biomechanics and a neural feedback controller for foot placement and analyze the properties of this hybrid dynamical system. We find that there is always exactly one periodic orbit and derive a criterion for the asymptotic stability of this periodic orbit. This analytic criterion allows us to characterize the region in the parameter space where the walking system is stable. We use these theoretical results to analyze stability of human walking depending on different sensorimotor control gains. The model predicts that control gains should be larger for slower-paced walking, which is partially consistent with the available experimental data.
Intermediate antiparallel beta structure in amyloid plaques revealed by infrared spectroscopic imaging
Authors: Holcombe Brooke , Foes Abigail , Banerjee Siddhartha , Yeh Kevin , Wang Shih-Hsiu J. , Bhargava Rohit , Ghosh Ayanjeet 
Published: April 2023

AbstractAggregation of amyloid beta (Aβ) peptides into extracellular plaques is a hallmark of the molecular pathology of Alzheimer’s disease (AD). Amyloid aggregates have been extensively studied in-vitro, and it is well known that mature amyloid fibrils contain an ordered parallel β structure. The structural evolution from unaggregated peptide to fibrils can be mediated through intermediate structures that deviate significantly from mature fibrils, such as antiparallel β-sheets. However, it is currently unknown if these intermediate structures exist in plaques, which limits the translation of findings from in-vitro structural characterizations of amyloid aggregates to AD. This arises from the inability to extend common structural biology techniques to ex-vivo tissue measurements. Here we report the use of infrared (IR) imaging, wherein we can spatially localize plaques and probe their protein structural distributions with the molecular sensitivity of IR spectroscopy. Analyzing individual plaques in AD tissues, we demonstrate that fibrillar amyloid plaques exhibit antiparallel β-sheet signatures, thus providing a direct connection between in-vitro structures and amyloid aggregates in AD brain. We further validate results with IR imaging of in-vitro aggregates and show that antiparallel β-sheet structure is a distinct structural facet of amyloid fibrils.
Complete Genome Sequences and Characteristics of Seven Novel Mycobacteriophages
Authors: Weiss Skylar M , Happy Kezia K , Baliraine Faith W , Beach Abigail K , Brobston Sean M , Martinez Claire P , Menard Kaitlyn J , Orton Savannah M , Salazar Angela L , Frederick Gregory D , Baliraine Frederick N 
Published: April 2023

ABSTRACTFull genome sequences of seven mycobacteriophages isolated from environmental soil samples are presented. These bacteriophages, with their respective cluster or subclusters, are Duplo (A2), Dynamo (P1), Gilberta (A11), MaCh (A11), Nikao (K1), Phloss (N), and Skinny (M1). All were temperate Siphoviridae, with genome sizes ranging from 43,107–82,071 bp.
MACI: A machine learning-based approach to identify drug classes of antibiotic resistance genes from metagenomic data
Authors: Chowdhury Rohit Roy , Dhar Jesmita , Robinson Stephy Mol , Lahiri Abhishake , Paul Sandip , Basak Kausik , Banerjee Rachana 
Published: April 2023

AbstractNovel methodologies are now essential for identification of antibiotic resistant pathogens in order to resist them. Here, we are presenting a model, MACI (Machine learning-based Antibiotic resistance gene-specific drug Class Identification) that can take metagenomic fragments as input and predict the drug class of antibiotic resistant genes. We trained the model to learn underlying patterns of genes using the Comprehensive Antibiotic Resistance Database. It comprises of 116 drug classes with a total of 2960 representative sequences. Among these 116 drug classes, we found 22 categories (contributing approximately 85% of the overall sequence-data) surpassed other 94 drug classes based on the number of fragments. The model showed an average precision of 0.83 and a recall of 0.81 for these 22 drug classes. Moreover, the model predicted multidrug resistant classes with higher performance score (precision and recall: 0.9 and 0.88 respectively) compared to single drug resistant categories (0.77 and 0.75). Post to this, we analysed these 22 drug classes to find out class-specific overlapping patterns of nucleotides that led to accurate classification. This way, we found five drug classes viz. “carbapenem;cephalosporin;penam”, “cephalosporin”, “cephamycin”, “cephalosporin;monobactam;penam;penem”, and “fluoroquinolone”. Additionally, the positions of these significant patterns corroborated with the functional domains of majority of antibiotic resistance genes in that drug class, indicating their biological importance. These class-specific patterns play a pivotal role in rapid identification of some drug classes comprising antibiotic resistance genes. Further analysis showed that bacterial species, containing these five-drug classes, were found to have well-known multidrug resistance property.
Exhaustive benchmarking ofde novoassembly methods for eukaryotic genomes
Authors: Southwood Dean , Rane Rahul V , Lee Siu Fai , Oakeshott John G , Ranganathan Shoba 
Published: April 2023

AbstractThe assembly of reference-quality, chromosome-resolution genomes for both model and novel eukaryotic organisms is an increasingly achievable task for single research teams. However, the overwhelming abundance of sequencing technologies, assembly algorithms, and post-assembly processing tools currently available means that there is no clear consensus on a best-practice computational protocol for eukaryoticde novogenome assembly. Here, we provide a comprehensive benchmark of 28 state-of-the-art assembly and polishing packages, in various combinations, when assembling two eukaryotic genomes using both next-generation (Illumina HiSeq) and third-generation (Oxford Nanopore and PacBio CLR) sequencing data, at both controlled and open levels of sequencing coverage. Recommendations are made for the most effective tools for each sequencing technology and the best performing combinations of methods, evaluated against common assessment metrics such as contiguity, computational performance, gene completeness, and reference reconstruction, across both organisms and across sequencing coverage depth.
Cardiac age prediction using graph neural networks
Authors: Inácio Marco H. de A. , Shah Mit , Jafari Mina , Shehata Nairouz , Meng Qingjie , Bai Wenjia , Gandy Axel , Glocker Ben , O’Regan Declan P. 
Published: April 2023

AbstractThe function of the human heart is characterised by complex patterns of motion that change throughout our lifespan due to accumulated damage across biological scales. Understanding the drivers of cardiac ageing is key to developing strategies for attenuating age-related processes. The motion of the surface of the heart can be conceived as a graph of connected points in space moving through time. Here we develop a generalisable framework for modelling three-dimensional motion as a graph and apply it to a task of predicting biological age. Using sequences of segmented cardiac imaging from 5064 participants in UK Biobank we train a graph neural network (GNN) to learn motion traits that predict healthy ageing. The GNN outperformed (mean absolute error, MAE = 4.74 years) a comparator dense neural network and boosting methods (MAE = 4.90 years and 5.08 years, respectively). We produce human-intelligible explanations of the predictions and using the trained model we also assess the effect of hypertension on biological age. This work shows how graph representations of complex motion can efficiently predict biologically meaningful outcomes.
Diagnosing diastolic dysfunction using explainable advanced electrocardiography
Authors: McColl Hayden , Chowdhury Sabbab , Schlegel Todd T , Maanja Maren , Yang Kevin , Lindow Thomas , Price Michelle , Fulthorp Elias , Lal Sean , McGrady Michele , Kozor Rebecca , Ugander Martin 
Published: April 2023

AbstractBACKGROUND AND AIMSDiastolic dysfunction of the left ventricle is a precursor to heart failure with preserved ejection fraction (HFpEF). Detection by electrocardiography (ECG) when asymptomatic (stage B heart failure) would be valuable. We hypothesised that an explainable advanced ECG (A-ECG) score derived from standard 12-lead ECG could accurately diagnose diastolic dysfunction.METHODSIncluded patients had undergone resting 12-lead ECG and echocardiography demonstrating normal systolic function, with at most mild valve disease, and either the presence (n=150) or absence (n=264) of grade II or III diastolic dysfunction. Stepwise multivariable logistic regression was used to generate an A-ECG score that was crossvalidated using bootstrapping.RESULTSA 6-measure A-ECG score was able to identify diastolic dysfunction with an area under the receiver operating characteristics curve [95% confidence interval] of 0.91 [0.88-0.94], sensitivity 83 [76-91]%, specificity 87 [77-92]%, positive predictive value 78 [69-85]%, negative predictive value 90 [86-94]%, positive likelihood ratio 6.38 [3.30-11.38] and inverse negative likelihood ratio 5.12 [3.21-10.22].CONCLUSIONSStandard 12-lead ECG can be used to accurately identify diastolic dysfunction by echocardiography via A-ECG. This may have clinical utility for early identification of patients who may benefit from further cardiac assessment and risk factor management to prevent progression to symptomatic heart failure.
Repeatability and agreement of central corneal thickness measurements with a new handheld non-contact pachymeter
Authors: Lawrenson John G , Gill Simranjit , Masuid Isra , Rashid Fardip 
Published: April 2023

AbstractPurposeTo compare the repeatability of central corneal thickness (CCT) measurements taken with a new hand-held pachymeter (Occuity PM1 Pachymeter) and to assess its agreement with ultrasound biometry and two commercially available optical biometers in participants with normal eyes.MethodsThree consecutive CCT measurements of the right eye of 105 participants with normal corneas were acquired by the PM1 pachymeter, Lenstar LS900 and Oculus Pentacam HR in a random order. This was followed by three measurements with a hand-held ultrasound pachymeter (UP) (Pachmate-2). Repeatability and the repeatability limit were calculated with each device and Bland-Altman limits of agreement (LoA) were determined for the PM1 pachymeter compared to the other devices.ResultsThe mean CCT (±SD) was 551.04±33.43 μm, 558.62±31.46 μm, 549.41±31.00 μm, and 539.73±29.50 μm for the PM1 pachymeter, UP, Lenstar and Pentacam, respectively. The repeatability limits (expressed as the within subject SD for repeat measurements) were 14.02, 13.68, 4.99 and 9.90 μm respectively. The closest agreement was between the PM1 and Lenstar (mean difference = 1.63 μm with LoA 10.72 μm below and 13.97 μm above the readings obtained with the Lenstar. The PM1 underestimated CCT compared to UP (mean difference = 7.58 μm, LoA 24.63 μm below and 9.47 μm above UP. The agreement was lowest between the PM1 and Pentacam (mean difference= -11.30 μm, LoA between 4.29 μm and 26.89 μm).ConclusionsThe PM1 pachymeter shows excellent precision for CCT measurements across a range of corneal thicknesses in normal eyes and provides a safe and easy to use alternative to ultrasound pachymetry.Key pointsMeasurement of central corneal thickness (CCT) is an important clinical measurement in the diagnosis and management of glaucoma and certain corneal dystrophies, it also provides useful information prior to refractive surgeryThe Occuity PM1 pachymeter is a new hand-held non-contact perimeter that uses confocal technology to measure CCT. The device showed excellent precision for CCT measurements across a range of corneal thicknesses in normal eyesThe PM1 pachymeter provides a safe and easy to use alternative to ultrasound pachymetry that could facilitate an increased uptake of pachymetry in routine optometric practice