bluuebunny/crossref_metadata_2025_split huggingface dataset:
Maternal obesity driven changes in collagen linearity of breast extracellular matrix induces invasive mammary epithelial cell phenotype
Authors: Amens Jensen N. , Bahçecioglu Gökhan , Dwyer Kiera , Yue Xiaoshan S. , Stack M. Sharon , Hilliard Tyvette S. , Zorlutuna Pinar 
Published: December 2022

AbstractObesity has been linked with numerous health issues as well as an increased risk of breast cancer. Although effects of direct obesity in patient outcomes is widely studied, effects of exposure to obesity-related systemic influencesin uterohas been overlooked. In this study, we investigated the effect of multigenerational obesity on epithelial cell migration and invasion using decellularized breast tissues explanted from normal female mouse pups from a diet induced multigenerational obesity mouse model. We first studied the effect of multigenerational diet on the mechanical properties, adipocyte size, and collagen structure of these mouse breast tissues, and then, examined the migration and invasion behavior of normal (KTB-21) and cancerous (MDA-MB-231) human mammary epithelial cells on the decellularized matrices from each diet group. Breast tissues of mice whose dams had been fed with high-fat diet exhibited larger adipocytes and thicker and curvier collagen fibers, but only slightly elevated elastic modulus and inflammatory cytokine levels. MDA-MB-231 cancer cell motility and invasion were significantly greater on the decellularized matrices from mice whose dams were fed with high-fat diet. A similar trend was observed with normal KTB-21 cells. Our results showed that the collagen curvature was the dominating factor on this enhanced motility and stretching the matrices to equalize the collagen fiber linearity of the matrices ameliorated the observed increase in cell migration and invasion in the mice that were exposed to a high-fat diet. Previous studies indicated an increase in serum leptin concentration for those children born to an obese mother. We generated extracellular matrices using primary fibroblasts exposed to various concentrations of leptin. This produced curvier ECM and increased breast cancer cell motility for cells seeded on the decellularized ECM generated with increasing leptin concentration. Our study shows that exposure to obesityin uterois influential in determining the extracellular matrix structure, and that the resultant changes in collagen curvature is a critical factor in regulating the migration and invasion of breast cancer cells.
Positive effects of projected climate change on post-disturbance forest regrowth rates in northeastern North American boreal forests
Authors: Danneyrolles Victor , Boucher Yan , Fournier Richard , Valeria Osvaldo 
Published: December 2022

AbstractForest anthropogenic and natural stand-replacing disturbances are increasing worldwide due to global change. Many uncertainties regarding the regeneration and growth of these young forests remain within the context of changing climate. In this study, we investigate the effects of climate, tree species composition, and other landscape-scale environmental variables upon boreal forest regrowth following clearcut logging in eastern Canada. Our main objective was to predict the effects of future climate changes upon post-logging forest height regrowth at a subcontinental scale using high spatial resolution remote sensing data. We modeled forest canopy height (estimated from airborne laser scanning [LiDAR] data over 20-m resolution virtual plots) as a function of time elapsed since the last clearcut along with climatic (i.e., temperature and moisture), tree species composition, and other environmental variables (e.g., topography and soil hydrology). Once trained and validated with ∼240,000 plots, the model that was developed in this study was used to predict potential post-logging canopy height regrowth at 20-m resolution across a 240,000 km2 area following scenarios depicting a range of projected changes in temperature and moisture across the region for 2041-2070. Our results predict an overall beneficial, but limited effect of projected climate changes upon forest regrowth rates in our study area. Stimulatory effects of projected climate change were more pronounced for conifer forests, with growth rates increasing between +5% and +50% over the study area, while mixed and broadleaved forests recorded changes that mostly ranged from -5% to +35%. Predicted increased regrowth rates were mainly associated with increased temperature, while changes in climate moisture had a minor effect. We conclude that such gains in regrowth rates may partially compensate for projected substantial increases in fire activity and other natural disturbances that are expected with climate change in these boreal forests.
Unclearing Microscopy
Authors: M’Saad Ons , Shribak Michael , Bewersdorf Joerg 
Published: December 2022

AbstractThe spatial resolution and contrast sensitivity of the human eye is limited, restricting our ability to directly see subcellular structures. We report a new principle for unaided eye cellular visualization in a method we call Unclearing Microscopy. By expanding cells and tissue >8,000 volumetrically and opaquing their bulk with light-scattering molecules of sufficient density, cell microstructure can now be discerned with a contrast visible to the unaided eye. We further inspect uncleared samples with transmitted light microscopy modalities and prove that 3D ultrastructural features, previously accessible only with super-resolution fluorescence or electron microscopy methods, can now be visualized with simple magnification optics alone.
Prediction and Curation of Missing Biomedical Identifier Mappings with Biomappings
Authors: Hoyt Charles Tapley , Hoyt Amelia L. , Gyori Benjamin M. 
Published: December 2022

AbstractMotivationBiomedical identifier resources (ontologies, taxonomies, controlled vocabularies) commonly overlap in scope and contain equivalent entries under different identifiers. Maintaining mappings for these relationships is crucial for interoperability and the integration of data and knowledge. However, there are substantial gaps in available mappings motivating their semi-automated curation.ResultsBiomappings implements a curation cycle workflow for missing mappings which combines automated prediction with human-in-the-loop curation. It supports multiple prediction approaches and provides a web-based user interface for reviewing predicted mappings for correctness, combined with automated consistency checking. Predicted and curated mappings are made available in public, version-controlled resource files on GitHub. Biomappings currently makes available 8,560 curated mappings and 41,178 predicted ones, providing previously missing mappings between widely used resources covering small molecules, cell lines, diseases and other concepts. We demonstrate the value of Biomappings on case studies involving predicting and curating missing mappings among cancer cell lines as well as small molecules tested in clinical trials. We also present how previously missing mappings curated using Biomappings were contributed back to multiple widely used community ontologies.AvailabilityThe data and code are available under the CC0 and MIT licenses athttps://github.com/biopragmatics/biomappings.Contactbenjamin_gyori@hms.harvard.edu
Probing Conformational Landscapes and Mechanisms of Allosteric Communication in the Functional States of the ABL Kinase Domain Using Multiscale Simulations and Network-Based Mutational Profiling of Allosteric Residue Potentials
Authors: Krishnan Keerthi , Tian Hao , Tao Peng , Verkhivker Gennady M. 
Published: December 2022

AbstractIn the current study, multiscale simulation approaches and dynamic network methods are employed to examine the dynamic and energetic details of conformational landscapes and allosteric interactions in the ABL kinase domain that determine the kinase functions. Using a plethora of synergistic computational approaches, we elucidate how conformational transitions between the active and inactive ABL states can employ allosteric regulatory switches to modulate the intramolecular communication networks between the ATP site, the substrate binding region, and the allosteric binding pocket. A perturbation-based network approach that implements mutational profiling of allosteric residue propensities and communications in the ABL states is proposed. Consistent with the biophysical experiments, the results reveal functionally significant shifts of the allosteric interaction networks in which preferential communication paths between the ATP binding site and substrate regions in the active ABL state become suppressed in the closed inactive ABL form, which in turn features favorable allosteric couplings between the ATP site and the allosteric binding pocket. By integrating the results of atomistic simulations with dimensionality reduction methods and Markov state models we analyze the mechanistic role of the macrostates and characterize kinetic transitions between the ABL conformational states. Using network-based mutational scanning of allosteric residue propensities, this study provides a comprehensive computational analysis of the long-range communications in the ABL kinase domain and identifies conserved regulatory hotspots that modulate kinase activity and allosteric cross-talk between the allosteric pocket, ATP binding site and substrate binding regions.
Machine learning assisted ligand binding energy prediction forin silicogenerated glycosyl hydrolase enzyme combinatorial mutant library
Authors: Guranovic Igor , Kumar Mohit , Bandi Chandra K. , Chundawat Shishir P. S. 
Published: December 2022

AbstractMolecular docking is a computational method used to predict the preferred binding orientation of one molecule to another when bound to each other to form an energetically stable complex. This approach has been widely used for early-stage small-molecule drug design as well as identifying suitable protein-based macromolecule residues for mutagenesis. Estimating binding free energy, based on docking interactions of protein to its ligand based on an appropriate scoring function is often critical for protein mutagenesis studies to improve the activity or alter the specificity of targeted enzymes. However, calculating docking free energy for a large number of protein mutants is computationally challenging and time-consuming. Here, we showcase an end-to-end computational workflow for predicting the binding energy of pNP-Xylose substrate docked within the substrate binding site for a large library of combinatorial mutants of an alpha-L-fucosidase (TmAfc, PDB ID-2ZWY) belonging toThermotoga maritimaglycosyl hydrolase (GH) family 29. Briefly,in silicocombinatorial mutagenesis was performed for the top conserved residues inTmAfc as determined by running multiple sequence alignment against all GH29 family enzyme sequences downloaded from an in-house developed Carbohydrate-Active enZyme (CAZy) database retriever program. The binding energy was calculated through Autodock Vina with pNP-Xylose ligand docking with energy minimizedTmAfc mutants, and the data was then used to train a neural network model which was also validated for model predictions using data from Autodock Vina. The current workflow can be adopted for any family of CAZymes to rapidly identify the effect of different mutations within the active site on substrate binding free energy to identify suitable targets for mutagenesis. We anticipate that this workflow could also serve as the starting point for performing more sophisticated and computationally intensive binding free energy calculations to identify targets for mutagenesis and hence optimize use of wet lab resources.
Evaluation of sex and age effects of fiber damage before permeabilization on mitochondrial respiration
Authors: Campbell Matthew D. , Marcinek David J. 
Published: December 2022

AbstractThe use of permeabilized muscle fibers (PMF) has emerged as a gold standard for assessing skeletal muscle mitochondrial function. PMF provide an intermediate approach between in vivo strategies and isolated mitochondria that allows the mitochondria to be maintained in close to their native morphology in the myofiber while allowing greater control of substrate and inhibitor concentrations. However, like mitochondrial isolation, the primary drawback to PMF is disruption of the cellular environment during the muscle biopsy and preparation. Despite all the benefits of permeabilized muscle fibers in evaluating mitochondrial respiration and dynamics one of the major drawbacks is increased variability introduced during a muscle biopsy as well as intrinsic variation that exists due to sex and age. This study was designed to evaluate how age, sex, and biopsy preparations affect mitochondrial respiration in extensor digitorum longus, soleus, and gastrocnemius muscle of mice. Here we detail a modified approach to skeletal muscle biopsy of the gastrocnemius muscle of mice focused on maintenance of intact fibers that results in greater overall respiration compared to cut fibers. The improved respiration of intact fibers is sex specific as are some of the changes in mitochondrial respiration with age. This study shows the need for standard practices when measuring mitochondrial respiration in permeabilized muscle and provides a protocol to control for variation introduced during a typical mouse muscle biopsy.
Dynamic Data Independent Acquisition Mass Spectrometry with Real-Time Retrospective Alignment
Authors: Heil Lilian R , Remes Philip M , Canterbury Jesse D , Yip Ping , Barshop William D , Wu Christine C , MacCoss Michael J 
Published: December 2022

AbstractWe report a data independent acquisition (DIA) strategy that dynamically adjusts the tandem mass spectrometry (MS/MS) windows during the chromatographic separation. The method focuses MS/MS acquisition on the most relevant mass range at each point in time – improving the quantitative sensitivity by increasing the time spent on each DIA window. We demonstrate an improved lower limit of quantification, on average, without sacrificing the number of peptides detected.
miR-29 is an important driver of aging-related phenotypes
Authors: Swahari Vijay , Nakamura Ayumi , Hollville Emilie , Hung Yu-Han , Kanke Matt , Kurtz C. Lisa , Caravia Xurde M. , He Shenghui , Krishnamurthy Janakiraman , Kapoor Sahil , Prasad Varun , Flowers Cornelius , Beck Matt , Baran-Gale Jeanette , Sharpless Norman , López-Otín Carlos , Sethupathy Praveen , Deshmukh Mohanish 
Published: December 2022

AbstractAging is a consequence of complex molecular changes, but the roles of individual microRNAs (miRNAs) in aging remain unclear. One of the few miRNAs that are upregulated during both normal and premature aging is miR-29. We confirmed this finding in our study in both mouse and monkey models. Follow-up analysis of the transcriptomic changes during normal aging revealed that miR-29 is among the top miRNAs predicted to drive the aging-related gene expression changes. We also showed that partial loss of miR-29 extends the lifespan ofZmpste24-/-mice, an established model of progeria, which indicates that miR-29 is functionally important in this accelerated aging model. To examine whether miR-29 upregulation alone is sufficient to promote aging-related phenotypesin vivo, we generated mice in which miR-29 can be conditionally overexpressed (miR-29TG). We found that miR-29 overexpression in mice is sufficient to drive aging-related phenotypes including alopecia, kyphosis, osteoporosis, senescence, and leads to early lethality. Transcriptomic analysis of both young miR-29TG and old WT mice revealed shared downregulation of genes enriched in extracellular matrix and fatty acid metabolism, and shared upregulation of genes in pathways linked to inflammation. Together, these results highlight the functional importance of miR-29 in controlling a gene expression program that drives agingrelated phenotypes.
Circulation of Fluconazole-ResistantC. albicans, C. aurisandC. parapsilosisBloodstream Isolates Carrying Y132F, K143R or T220L Erg11p Substitutions in Colombia
Authors: Ceballos-Garzon Andres , Peñuela Ana , Valderrama-Beltrán Sandra , Vargas-Casanova Yerly , Ariza Beatriz , Parra-Giraldo Claudia M. 
Published: December 2022

AbstractAlthoughCandidaspp., is a common cause of bloodstream infections and is often associated with high mortality rates, its resistance to antifungal drugs, and the molecular mechanisms involved have been poorly studied in Colombia. Here, 123 bloodstream isolates ofCandidaspp. were collected. MALDI-TOF MS identification and fluconazole (FLC) susceptibility patterns were assessed on all isolates. Subsequently, sequencing ofERG11, TAC1orMRR1, and efflux pumps were performed for resistant isolates. Out of 123 clinical strains,C. albicansaccounted for 37.4%, followed byC. tropicalis26.8%,C. parapsilosis19.5%,C. auris8.1%,C. glabrata4.1%,C. krusei2.4% andC. lusitaniae1.6%. Resistance to FLC reached 18%. Erg11 amino acid substitutions associated with FLC-resistance (Y132F, K143R or T220L) were found in 58% of 19 FLC-resistant isolates. Furthermore, novel mutations were found in all genes studied. Regarding efflux pumps, 42% of 19 FLC-resistantCandidaspp strains showed significant efflux activity. Finally, six of the 19 FLC-resistant isolates neither harbored resistance-associated mutations nor showed efflux pump activity. AlthoughC. albicansremain the most predominant species, non-C. albicansspecies comprise a high proportion (62.6%). Among FLC-resistant species,C. auris(70%) andC. parapsilosis(25%) displayed the highest percentages of resistance. In 68% of FLC-resistant isolates, a mechanism that could explain their phenotype was found (e.g. mutations, flux pump activity or both). We provide evidence that endemic isolates harbor amino acid substitutions related with resistance to one of the most used molecules in the hospital setting, with Y132F being the most frequently detected one.
Identifying patients requiring treatment for depression in the postpartum period from common electronic medical record data available antepartum using machine learning
Authors: Wakefield Colin , Frasch Martin G. 
Published: December 2022

ObjectiveDepression requiring treatment in the postpartum period (PPD) significantly impacts maternal and neonatal health. While preventive management of depression in pregnancy has been shown to decrease the negative effects, current methods for identifying at-risk patients are insufficient. Given the complexity of the diagnosis and interplay of clinical/demographic factors, we tested if machine learning (ML) techniques can accurately identify patients at risk of PPD.Study DesignThis is a retrospective cohort study of the NIH Nulliparous Pregnancy Outcomes Study (nuMoM2b) which enrolled 10,038 nulliparous people. The primary outcome was PPD. We constructed and optimized four ML models using distributed random forest modeling based on the nuMoM2b dataset. Model 1 utilized only readily obtainable sociodemographic data. Model 2 added maternal pre-pregnancy mental health data. Model 3 utilized recursive feature elimination to construct a parsimonious model. Model 4 further titrated the input data to exclude pre-pregnancy mental health variables.ResultsOf 8454 births, 338 (4%) were complicated by PPD. Model 3 was the highest performing, demonstrating the area under the receiver operating characteristics curve (AUC) of 0.91(±0.02). Models 1-3 identified the 9 variables most predictive of depression hierarchically ranging from BMI (highest), prior depression, age, income, medications, education, past medical history, race, and prior anxiety (lowest). In model 4, the AUC remained at 0.80(±0.04).ConclusionsCounterintuitively, the presence of pre-pregnancy mental health conditions is not the most predictive factor of PPD. Furthermore, PPD can be predicted with high accuracy for individual patients using antepartum information commonly found in the EMR.
Sexual dimorphism of the synovial transcriptome underpins greater PTOA disease severity in male mice following joint injury
Authors: Bergman Rachel F. , Lammlin Lindsey , Junginger Lucas , Farrell Easton , Goldman Sam , Darcy Rose , Rasner Cody , Obeidat Alia M. , Malfait Anne-Marie , Miller Rachel E. , Maerz Tristan 
Published: December 2022

ABSTRACTObjectiveTo elucidate sex differences in synovitis, mechanical sensitization, structural damage, bone remodeling, and the synovial transcriptome in the anterior cruciate ligament rupture (ACLR) mouse model of post-traumatic osteoarthritis (PTOA).MethodsMale and female 12-week-old C57Bl/6 mice were randomized to noninvasive ACLR or sham (n=9/sex/group/timepoint). Knee hyperalgesia, mechanical allodynia, and intra-articular MMP activity (via intravital imaging) were measured longitudinally. Trabecular and subchondral bone remodeling and osteophyte formation were assessed by μCT. Histological scoring of PTOA and synovitis and anti-MMP13 immunostaining was performed. NaV1.8-Cre;tdTomato mice were used to document localization and sprouting of nociceptors. Bulk RNAseq of synovium in sham, 7d, and 28d post-ACLR, and contralateral joints (n=6) assessed injury-induced and sex-dependent synovial gene expression.ResultsMale mice exhibited worse joint damage at 7d and 28d and worse synovitis at 28d, accompanied by greater MMP activity, knee hyperalgesia, and mechanical allodynia. Females had catabolic responses in trabecular and subchondral bone after injury, whereas males exhibited greater osteophyte formation and sclerotic remodeling of trabecular and subchondral bone. NaV1.8+ nociceptor sprouting in subchondral bone and medial synovium was induced by injury and comparable between sexes. RNAseq of synovium demonstrated that both sexes had similar injury-induced gene expression at 7d, but only female mice exhibited synovial inflammatory resolution by 28d, whereas males had persistent pro-inflammatory, pro-fibrotic, pro-neurogenic, and pro-angiogenic gene expression.ConclusionWorse overall joint pathology and pain behavior in male mice was associated with persistent activation of synovial inflammatory, fibrotic, and neuroangiogenic processes, implicating persistent synovitis in driving sex differences in murine PTOA.
Modeling Mechanical Feedback Mechanisms in a Multiscale Sliding Filament Model of Lymphatic Muscle Pumping
Authors: Xie Peter Y. , Morris Christopher J. , Bertram Christopher , Zaweija David , Moore James E. 
Published: December 2022

AbstractThe lymphatic system maintains bodily fluid balance by returning interstitial fluid to the venous system. Flow can occur through a combination of extrinsic pumping, due to forces from surrounding tissues, and intrinsic pumping involving contractions of muscle in the lymphatic vessel walls. Lymph transport is important not only for fluid homeostasis, but also for immune function, as lymph is a carrier for immune cells. Lymphatic muscle cells exhibit cardiac-like phasic contractions to generate flow and smooth-muscle-like tonic contractions to regulate flow. Lymphatic vessels therefore act as both active pumps and conduits. Lymphatic vessels are sensitive to mechanical stimuli, including flow-induced shear stresses and pressure-induced vessel stretch. These forces modulate biochemical pathways, leading to changes in intracellular calcium and interaction with regulatory and contractile proteins. In a multiscale computational model of phasic and tonic contractions in lymphatic muscle coupled to a lumped-parameter model of lymphatic pumping, we tested different models of the mechanical feedback mechanisms exhibited by lymphatics in experiments. Models were validated using flow and pressure experiments not used in the models’ construction. The final model shows that with flow-induced shear stress modulation, there is a small change in flow rate but an increase in muscle efficiency. A better understanding of the mechanobiology of lymphatic contractions can help guide future lymphatic vessel experiments, providing a basis for developing better treatments for lymphatic dysfunction.