bluuebunny/crossref_metadata_2025_split huggingface dataset:
Clockwork Orangutan: microRNAs, thermoregulatory tradeoffs, and the evolution of brain size
Authors: Fromm Bastian , Sorger Thomas 
Published: May 2024

SUMMARYModels of brain size evolution have not accounted for the thermoregulatory adaptations underlying the 4-fold increase in brain metabolic rate (MR) in hominid apes. Like earlier increases in whole-bodyMR, the advent of placentation and permanent homeothermy, the divergence of Catarrhini coincided with an adaptive increase in the number of microRNA families (mirFam). We demonstrate in mammals that the size of the brain, the primary consumer of glucose, and the liver, the primary organ of gluconeogenesis, vary inversely relative to a thermogenic Core (kidney + heart + liver + brain). The cellularMR(cMR) of the liver, scaled in proportion tomirFam, varied inversely with body size and thecMRs of kidney, heart and brain. WithmirFamas a proxy for energy reliability, a logistic feedback model of relative brain size detected adaptation to a low-energy regime among the smallest primates and, among the largest primates, adaptation to the physiological limit on the rate of heat dissipation.
Using physiologically-based models to predictin vivoskeletal muscle energetics
Authors: Konno Ryan N. , Lichtwark Glen A. , Dick Taylor J. M. 
Published: May 2024

AbstractUnderstanding how muscles use energy is essential for elucidating the role of skeletal muscle in animal locomotion. Yet, experimental measures ofin vivomuscle energetics are challenging to obtain, so physiologically-based muscle models are often used to estimate energy use. These predictions of individual muscle energy expenditure are not often compared to indirect whole body measures of energetic cost. Here, we examined and illustrated the capability of physiologically-based muscle models to predictin vivomeasures of energy use. To improve model predictions and ensure a physiological basis for model parameters, we refined our model to include data from isolated muscle experiments. Simulations were performed to capture three different experimental protocols, which involved varying contraction frequency, duty cycle, and muscle fascicle length. Our results demonstrated that these models are able capture the general features of whole body energetics across contractile conditions, but tended to under predict the magnitude of energetic cost. Our analysis revealed that when predictingin vivoenergetic rates across contractile conditions, the model was most sensitive to the force-velocity parameters and the data informing the energetic rates when predictingin vivoenergetic rates across contractile conditions. This work highlights it is the mechanics of skeletal muscle contraction that govern muscle energy use.
Enhanced dynamic covalent chemistry for the controlled release of small molecules and biologics from a nanofibrous peptide hydrogel platform
Authors: Pogostin Brett H. , Wu Samuel X. , Swierczynski Michael J. , Pennington Christopher , Li Si-Yang , Vohidova Dilrasbonu , Seeley Erin H. , Agrawal Anushka , Tang Chaoyang , Cabler Jacob , Dey Arghadip , Veiseh Omid , Nuermberger Eric L. , Ball Zachary T. , Hartgerink Jeffrey D. , McHugh Kevin J. 
Published: May 2024

AbstractMaintaining safe and potent pharmaceutical drug levels is often challenging. Multidomain peptides (MDPs) assemble into supramolecular hydrogels with a well-defined, highly porous nanostructure that makes them attractive for drug delivery, yet their ability to extend release is typically limited by rapid drug diffusion. To overcome this challenge, we developed self-assembling boronate ester release (SABER) MDPs capable of engaging in dynamic covalent bonding with payloads containing boronic acids (BAs). As examples, we demonstrate that SABER hydrogels can prolong the release of five BA-containing small-molecule drugs as well as BA-modified insulin and antibodies. Pharmacokinetic studies revealed that SABER hydrogels extended the therapeutic effect of ganfeborole from days to weeks, preventingMycobacterium tuberculosisgrowth better than repeated oral administration in an infection model. Similarly, SABER hydrogels extended insulin activity, maintaining normoglycemia for six days in diabetic mice after a single injection. These results suggest that SABER hydrogels present broad potential for clinical translation.
Autophagy suppression in DNA damaged cells occurs through a newly identified p53-proteasome-LC3 axis
Authors: Lieu D’Feau J. , Crowder Molly K. , Kryza Jordan R. , Tamilselvam Batcha , Kaminski Paul J. , Kim Ik-Jung , Li Yingxing , Jeong Eunji , Enkhbaatar Michidmaa , Chen Henry , Son Sophia B. , Mok Hanlin , Bradley Kenneth A. , Phillips Heidi , Blanke Steven R. 
Published: May 2024

ABSTRACTMacroautophagy is thought to have a critical role in shaping and refining cellular proteostasis in eukaryotic cells recovering from DNA damage. Here, we report a mechanism by which autophagy is suppressed in cells exposed to bacterial toxin-, chemical-, or radiation-mediated sources of genotoxicity. Autophagy suppression is directly linked to cellular responses to DNA damage, and specifically the stabilization of the tumor suppressor p53, which is both required and sufficient for regulating the ubiquitination and proteasome-dependent reduction in cellular pools of microtubule-associated protein 1 light chain 3 (LC3A/B), a key precursor of autophagosome biogenesis and maturation, in both epithelial cells and anex vivoorganoid model. Our data indicate that suppression of autophagy, through a newly identified p53-proteasome-LC3 axis, is a conserved cellular response to multiple sources of genotoxicity. Such a mechanism could potentially be important for realigning proteostasis in cells undergoing DNA damage repair.
Cardiac hemodynamics computational modeling including chordae tendineae, papillaries, and valves dynamics
Authors: Crispino Andrea , Bennati Lorenzo , Vergara Christian 
Published: May 2024

AbstractIn the context of dynamic image-based computational fluid dynamics (DIB-CFD) modeling of cardiac system, the role of sub-valvular apparatus (chordae tendineae and papillary muscles) and the effects of different mitral valve (MV) opening/closure dynamics, have not been systemically determined. To provide a partial filling of this gap, in this study we performed DIB-CFD numerical experiments in the left ventricle, left atrium and aortic root, with the aim of highlighting the influence on the numerical results of two specific modeling scenarios: i) the presence of the sub-valvular apparatus, consisting of chordae tendineae and papillary muscles; ii) different MV dynamics models accounting for different use of leaflet reconstruction from imaging.This is performed for one healthy and one MV regurgitant subjects. Specifically, a systolic wall motion is reconstructed from time-resolved Cine-MRI images and imposed as boundary condition for the CFD numerical simulation.Analyzing the numerical results, we found that sub-valvular apparatus do not affect the global fluid dynamics quantities, although it creates local variations, such as the developing of vortexes or flow disturbances, which lead to different stress distributions on cardiac structures.Moreover, different MV dynamics are considered starting from Cine-MRI MV segmentation at different temporal configurations, and then they are compared and managed numerically through a resistive approach. The obtained results highlight the importance of including a sophisticated diastolic model of MV dynamics, which accounts for MV geometries during diastasis and A-wave, in terms of describing the disturbed flow and ventricular turbulence.Statements and DeclarationsThe authors have no relevant financial or non-financial interests to disclose.
Exploring changes in social spider DNA methylation profiles when succumbing to infection in CpG, CHG, and CHH contexts
Authors: Fisher David N. , Bechsgaard Jesper , Bilde Trine 
Published: May 2024

AbstractLiving at high density and with low genetic diversity are factors that should both increase the susceptibility of organisms to disease. Therefore, group living organisms, especially those that are inbred, should be especially vulnerable to infection and therefore have particular strategies to cope with infection. Phenotypic plasticity, underpinned by epigenetic changes, could allow group living organisms to rapidly respond to infection challenges. To explore the potential role of epigenetic modifications in the immune response to a group-living species with low genetic diversity, we compared the genome-wide DNA methylation profiles of five colonies of social spiders (Stegodyphus dumicola) in their natural habitat in Namibia at the point just before they succumbed to infection to a point at least six months previously where they were presumably healthier. We found increases in genome- and chromosome-wide methylation levels in the CpG, CHG, and CHH contexts, although the genome-wide changes were not clearly different from zero. These changes were most prominent in the CHG context, especially at a narrow region of chromosome 13, hinting at an as-of-yet unsuspected role of this DNA methylation context in phenotypic plasticity. However, there were few clear patterns of differential methylation at the base level, and genes with a known immune function in spiders had mean methylation changes close to zero. Our results suggest that DNA methylation may change with infection at large genomic scales, but that this type of epigenetic change is not necessarily integral to the immune response of social spiders.
Estimating full-field displacement in biological images using deep learning
Authors: Warsop Solomon J. E. T. , Caixeiro Soraya , Bischoff Marcus , Kursawe Jochen , Bruce Graham D. , Wijesinghe Philip 
Published: May 2024

ABSTRACTThe estimation of full-field displacement between biological image frames or in videos is important for quantitative analyses of motion, dynamics and biophysics. However, the often weak signals, poor biological contrast and many noise processes typical to microscopy make this a formidable challenge for many contemporary methods. Here, we present a deep-learning method, termed Displacement Estimation FOR Microscopy (DEFORM-Net), that outperforms traditional digital image correlation and optical flow methods, as well as recent learned approaches, offering simultaneous high accuracy, spatial sampling and speed. DEFORM-Net is experimentally unsupervised, relying on displacement simulation based on a random fractal Perlin-noise process and optimised training loss functions, without the need for experimental ground truth. We demonstrate its performance on real biological videos of beating neonatal mouse cardiomyocytes and pulsed contractions inDrosophilapupae, and in various microscopy modalities. We provide DEFORM-Net as open source, including inference in the ImageJ/FIJI platform, for rapid evaluation, which will empower new quantitative applications in biology and medicine.
Analyzing high-throughput assay data to advance the rapid screening of environmental chemicals for human reproductive toxicity
Authors: Varshavsky Julia R. , Lam Juleen , Cooper Courtney , Allard Patrick , Fung Jennifer , Oke Ashwini , Kumar Ravinder , Robinson Joshua F. , Woodruff Tracey J. 
Published: May 2024

AbstractWhile high-throughput (HTP) assays have been proposed as platforms to rapidly assess reproductive toxicity, there is currently a lack of established assays that specifically address germline development/function and fertility. We assessed the applicability domains of yeast (S. cerevisiae)and nematode(C. elegans)HTP assays in toxicity screening of 124 environmental chemicals, determining their agreement in identifying toxicants and their concordance with reproductive toxicityin vivo. We integrated data generated in the two models and compared results using a streamlined, semi-automated benchmark dose (BMD) modeling approach. We then extracted and modeled relevant mammalianin vivodata available for the matching chemicals included in the Toxicological Reference Database (ToxRefDB). We ranked potencies of common compounds using the BMD and evaluated correlation between the datasets using Pearson and Spearman correlation coefficients. We found moderate to good correlation across the three data sets, with r = 0.48 (95% CI: 0.28–1.00, p<0.001) and rs= 0.40 (p=0.002) for the parametric and rank order correlations between the HTP BMDs; r = 0.95 (95% CI: 0.76–1.00, p=0.0005) and rs= 0.89 (p=0.006) between the yeast assay and ToxRefDB BMDs; and r = 0.81 (95% CI: 0.28–1.00, p=0.014) and rs= 0.75 (p=0.033) between the worm assay and ToxRefDB BMDs. Our findings underscore the potential of these HTP assays to identify environmental chemicals that exhibit reproductive toxicity. Integrating these HTP datasets into mammalianin vivoprediction models using machine learning methods could further enhance the predictive value of these assays in future rapid screening efforts.
Characterizing the Role of EndocarpAandBCells Layers During Pod (silique) Development in Brassicaceae
Authors: Nichol Justin B. , Samuel Marcus A. 
Published: May 2024

AbstractThe process of silique dehiscence is essential for proper dispersal of seeds at the end of a plant’s lifecycle. Current research focuses on genetic manipulation to mitigate this process and enhance shatter tolerance in crop plants, which has significant economic implications. In this study, we have conducted a time-course analysis of cell patterning and development in valve tissues ofArabidopsis thalianaand closely related Triangle of U species from Brassicaceae. The goal was to decipher the detailed temporal developmental patterns of the endocarp a and b cell layers of the valve, specifically their degradation and lignification respectively. Additionally, we propose a new classification system for the lignification of the endocarp a cell layer: L1 indicates the cell closest to the replum, with L2 and L3 representing the second and third cells, respectively, each numerical increment indicating lignified cells farther from the replum. Our findings provide a foundational framework absent in current literature, serving as an effective blueprint for future genomic work aimed at modifying valve structures to enhance agronomic traits, such as reducing fiber (lignin) or increasing shatter tolerance.
Automatic segmentation of medial temporal lobe subregions in multi-scanner, multi-modality MRI of variable quality
Authors: Li Yue , Xie Long , Khandelwal Pulkit , Wisse Laura E. M. , Brown Christopher A. , Prabhakaran Karthik , Tisdall M. Dylan , Mechanic-Hamilton Dawn , Detre John A. , Das Sandhitsu R. , Wolk David A. , Yushkevich Paul A. 
Published: May 2024

AbstractBackgroundVolumetry of subregions in the medial temporal lobe (MTL) computed from automatic segmentation in MRI can track neurodegeneration in Alzheimer’s disease. However, image quality may vary in MRI. Poor quality MR images can lead to unreliable segmentation of MTL subregions. Considering that different MRI contrast mechanisms and field strengths (jointly referred to as “modalities” here) offer distinct advantages in imaging different parts of the MTL, we developed a muti-modality segmentation model using both 7 tesla (7T) and 3 tesla (3T) structural MRI to obtain robust segmentation in poorquality images.MethodMRI modalities including 3T T1-weighted, 3T T2-weighted, 7T T1-weighted and 7T T2-weighted (7T-T2w) of 197 participants were collected from a longitudinal aging study at the Penn Alzheimer’s Disease Research Center. Among them, 7T-T2w was used as the primary modality, and all other modalities were rigidly registered to the 7T-T2w. A model derived from nnU-Net took these registered modalities as input and outputted subregion segmentation in 7T-T2w space. 7T-T2w images most of which had high quality from 25 selected training participants were manually segmented to train the multi-modality model. Modality augmentation, which randomly replaced certain modalities with Gaussian noise, was applied during training to guide the model to extract information from all modalities. To compare our proposed model with a baseline single-modality model in the full dataset with mixed high/poor image quality, we evaluated the ability of derived volume/thickness measures to discriminate Amyloid+ mild cognitive impairment (A+MCI) and Amyloid-cognitively unimpaired (A-CU) groups, as well as the stability of these measurements in longitudinal data.ResultsThe multi-modality model delivered good performance regardless of 7T-T2w quality, while the single-modality model under-segmented subregions in poor-quality images. The multi-modality model generally demonstrated stronger discrimination of A+MCI versus A-CU. Intra-class correlation and Bland-Altman plots demonstrate that the multi-modality model had higher longitudinal segmentation consistency in all subregions while the single-modality model had low consistency in poor-quality images.ConclusionThe multi-modality MRI segmentation model provides an improved biomarker for neurodegeneration in the MTL that is robust to image quality. It also provides a framework for other studies which may benefit from multimodal imaging.
Heterotrimeric Collagen Helix with High Specificity of Assembly Results in a Rapid Rate of Folding
Authors: Cole Carson C. , Walker Douglas R. , Hulgan Sarah A.H. , Pogostin Brett H. , Swain Joseph W.R. , Miller Mitchell D. , Xu Weijun , Duella Ryan , Misiura Mikita , Wang Xu , Kolomeisky Anatoly B. , Phillips George N. , Hartgerink Jeffrey D. 
Published: May 2024

AbstractThe most abundant natural collagens form heterotrimeric triple helices. Synthetic mimics of collagen heterotrimers have been found to fold slowly, even compared to the already slow rates of homotrimeric helices. These prolonged folding rates are not understood and have not been studied. This work compares three heterotrimeric collagen mimics’ stabilities, specificities and folding rates. One of these was designed through a computational-assisted approach, resulting in a well-controlled composition and register, in addition to providing increased amino acid diversity and excellent specificity. The crystal structure of this heterotrimer elucidates the composition, register and geometry of pairwise cation-π and axial and lateral salt bridges. Complementary experimental methods of circular dichroism and NMR suggest the folding paradigm is frustrated by unproductive, competing heterotrimer species and these species must completely unwind to the monomeric state before refolding into the thermodynamically favored assembly. This collagen heterotrimer, which displays the best reported thermal specificity, was also found to fold much faster (hours vs days) than comparable, well-designed systems. The heterotrimeric collagen folding rate was observed to be both concentration and temperature-independent, suggesting a complex, multi-step mechanism. These results suggest heterotrimer folding kinetics are dominated by frustration of the energy landscape caused by competing triple helices.
Evaluation of altered cell-cell communication between glia and neurons in the hippocampus of 3xTg-AD mice at two time points
Authors: Soelter Tabea M. , Howton Timothy C. , Wilk Elizabeth J. , Whitlock Jordan H. , Clark Amanda D. , Birnbaum Allison , Patterson Dalton C. , Cortes Constanza J. , Lasseigne Brittany N. 
Published: May 2024

AbstractAlzheimer’s disease (AD) is the most common form of dementia and is characterized by progressive memory loss and cognitive decline, affecting behavior, speech, and motor abilities. The neuropathology of AD includes the formation of extracellular amyloid-β plaque and intracellular neurofibrillary tangles of phosphorylated tau, along with neuronal loss. While neuronal loss is an AD hallmark, cell-cell communication between neuronal and non-neuronal cell populations maintains neuronal health and brain homeostasis. To study changes in cellcell communication during disease progression, we performed snRNA-sequencing of the hippocampus from female 3xTg-AD and wild-type littermates at 6 and 12 months. We inferred differential cell-cell communication between 3xTg-AD and wild-type mice across time points and between senders (astrocytes, microglia, oligodendrocytes, and OPCs) and receivers (excitatory and inhibitory neurons) of interest. We also assessed the downstream effects of altered glia-neuron communication using pseudobulk differential gene expression, functional enrichment, and gene regulatory analyses. We found that glia-neuron communication is increasingly dysregulated in 12-month 3xTg-AD mice. We also identified 23 AD-associated ligand-receptor pairs that are upregulated in the 12-month-old 3xTg-AD hippocampus. Our results suggest increased AD association of interactions originating from microglia. Signaling mediators were not significantly differentially expressed but showed altered gene regulation and TF activity. Our findings indicate that altered glia-neuron communication is increasingly dysregulated and affects the gene regulatory mechanisms in neurons of 12-month-old 3xTg-AD mice.
Comparative and population genomics analyses of eared pheasants inhabiting highly varying altitudes
Authors: Wu Siwen , Wang Kun , Ge Xuehai , Yuan Sisi , Wu Dong-Dong , Ge Changrong , Jia Junjing , Su Zhengchang , Dou Tengfei 
Published: May 2024

AbstractOxygen pressure varies dramatically with altitudes on Earth; however, humans and animals thrive at almost all altitudes. To better understand genetic basis underlying adaptation of closely related species to varying altitudes, we annotated and compared the genome of a white eared pheasant (WT) (Crossoptilon crossoptilon) inhabiting high altitudes and the genome of a brown eared pheasant (BR) (C. mantchuricum) inhabiting low altitudes, and found that the WT genome harbors 967 more genes but 457 fewer pseudogenes than the BR genome. Moreover, we compared genetic variations in populations of WT and BR as well as of blue eared pheasants (BL) (C. auritum) inhabiting intermediate altitudes, and identified thousands of selective sweeps in each species. Intriguingly, the unique genes and pseudogenes in the two genomes converge on the same set of altitude adaptation-related pathways of four functional categories as genes in selective sweeps in each species. Thus, these species appear to adapt to highly varying altitudes by diverging selection on the same traits via loss-of-function mutations and fine-tuning genes in common pathways.
Structural characterization and AlphaFold modeling of human T cell receptor recognition of NRAS cancer neoantigens
Authors: Wu Daichao , Yin Rui , Chen Guodong , Ribeiro-Filho Helder V. , Cheung Melyssa , Robbins Paul F. , Mariuzza Roy A. , Pierce Brian G. 
Published: May 2024

AbstractT cell receptors (TCRs) that recognize cancer neoantigens are important for anti-cancer immune responses and immunotherapy. Understanding the structural basis of TCR recognition of neoantigens provides insights into their exquisite specificity and can enable design of optimized TCRs. We determined crystal structures of a human TCR in complex with NRAS Q61K and Q61R neoantigen peptides and HLA-A1 MHC, revealing the molecular underpinnings for dual recognition and specificity versus wild-type NRAS peptide. We then used multiple versions of AlphaFold to model the corresponding complex structures, given the challenge of immune recognition for such methods. Interestingly, one implementation of AlphaFold2 (TCRmodel2) was able to generate accurate models of the complexes, while AlphaFold3 also showed strong performance, although success was lower for other complexes. This study provides insights into TCR recognition of a shared cancer neoantigen, as well as the utility and practical considerations for using AlphaFold to model TCR–peptide–MHC complexes.