bluuebunny/crossref_metadata_2025_split huggingface dataset:
Biomechanical Stimulation of Muscles Influences Bone Phenotype by Modulating Myokine Secretion
Authors: Suresh Kumar Harshini , Barnett Edwina N. , Kalaitzoglou Evangelia , Fowlkes John L. , Annamalai Ramkumar T. 
Published: October 2022

AbstractDiabetes is a chronic metabolic disorder that affects 422 million people worldwide and can lead to diabetic myopathy and bone diseases. The etiology of musculoskeletal complications in diabetes and the interplay between the muscular and osseous systems are poorly understood. Exercise training promises to prevent diabetic myopathy and diabetic bone disease and offer protective effects on muscle and bone. Although the muscle-bone interaction is largely biomechanical, the muscle secretome, specifically the myokines, has significant implications for bone biology. Here, we have developed an in vitro model to elucidate the effects of mechanical strain on myokine secretion and its impact on bone metabolism decoupled from physical stimuli. We developed modular bone constructs using crosslinked gelatin hydrogels which facilitated osteogenic differentiation of osteoprogenitor cells. Then muscle constructs were made from fibrin hydrogel, which enabled myoblast differentiation and formed mature myotubes. We investigated the myokine expression by the muscle constructs under strain regimens replicating endurance (END) and high-intensity interval training (HIIT) in hyperglycemic conditions. In monocultures, both regimens induced higher expression of Il15 and Igf1, while END supported more myoblasts differentiation and myotube maturation than HIIT. When cocultured with bone constructs, the HIIT regimen increased Glut4 expression in muscle contructs that END supporting higher glucose uptake. Likewise, the muscle constructs under the HIIT regimen promoted a healthier and matured bone phenotype than END. Interestingly, under static conditions, myostatin (Mstn) expression was significantly downregulated in muscle constructs cocultured with bone constructs compared to monocultures. Our in vivo analysis of the role of myostatin on bone structure and function also showed that myostatin knockout (GDF8-/-) enhanced muscle mass and moderately influenced bone phenotype in adult mice. Together, our in vitro coculture system allowed orthogonal manipulation of mechanical strain on muscle constructs while facilitating biochemical crosstalk between bone and muscle constructs. Such systems can provide an individualized microenvironment and allow decoupled biomechanical manipulation, which is unachievable using traditional models. In the long-term, these in-vitro systems will help identify molecular targets and develop engineered therapies for diabetic bone disease.
Iron Chelation Improves Ineffective Erythropoiesis and Iron Overload in Myelodysplastic Syndrome Mice
Authors: An Wenbin , Feola Maria , Aluri Srinivas , Ruiz-Martinez Marc , Shridharan Ashwin , Levy Maayan , Fibach Eitan , Zhu Xiaofan , Verma Amit , Ginzburg Yelena Z. 
Published: October 2022

ABSTRACTMyelodysplastic syndrome (MDS) is a heterogeneous group of bone marrow stem cell disorders characterized by ineffective hematopoiesis and cytopenias, most commonly anemia. Red cell transfusion therapy for anemia in MDS results in iron overload, correlating with reduced overall survival. Whether treatment of iron overload benefits MDS patients remains controversial. We evaluate underlying iron-related pathophysiology and the effect of iron chelation using deferiprone on erythropoiesis inNUP98-HOXD13transgenic mice, a highly penetrant well-established MDS mouse model. Our results characterize an iron overload phenotype with aberrant erythropoiesis in these mice which was reversed by deferiprone-treatment. Serum erythropoietin level decreased while erythroblast erythropoietin receptor expression increased in deferiprone-treated MDS mice. We demonstrate, for the first time, normalized expression of the iron chaperonesPcbp1andNco4and increased ferritin stores in late stage erythroblasts from deferiprone-treated MDS mice, evidence of aberrant iron trafficking in MDS erythroblasts. Importantly, erythroblast ferritin is increased in response to deferiprone, correlating with decreased erythroblast ROS. Finally, we confirmed increased expression of genes involved in iron uptake, sensing, and trafficking in stem and progenitor cells from MDS patients. Taken together, our findings provide evidence that erythroblast-specific iron metabolism is a novel potential therapeutic target to reverse ineffective erythropoiesis in MDS.BRIEF SUMMARYIneffective erythropoiesis in MDS mice correlates with aberrant iron trafficking within bone marrow erythroblasts, consistent with findings in MDS patient progenitors, reversed after iron chelation.
A Synthetic ERRα Agonist Induces an Acute Aerobic Exercise Response and Enhances Exercise Capacity
Authors: Billon Cyrielle , Sitaula Sadichha , Banerjee Subhashis , Welch Ryan , Elgendy Bahaa , Hegazy Lamees , Oh Tae Gyu , Kazantzis Melissa , Chatterjee Arindam , Chrivia John , Hayes Matthew E. , Xu Weiyi , Hamilton Angelica , Huss Janice M. , Zhang Lilei , Walker John K , Downes Michael , Evans Ronald M. , Burris Thomas P. 
Published: October 2022

ABSTRACTRepetitive physical exercise induces physiological adaptations in skeletal muscle that improves exercise performance and is effective for the prevention and treatment of several diseases. Here we report the identification of a synthetic agonist for the orphan nuclear receptor ERRα (estrogen receptor-related receptor α), SLU-PP-332, that activates an acute aerobic exercise genetic program in skeletal muscle in an ERRα-dependent manner. SLU-PP-332 increases mitochondrial function and cellular respiration consistent with induction of this genetic program. When administered to mice, SLU-PP-332 increased the type IIa oxidative skeletal muscle fibers and enhanced exercise endurance. These data indicate the feasibility of targeting ERRα for development of compounds that act as exercise mimetics that may be effective in treatment of numerous metabolic disorders and to improve muscle function in the aging.
Artificial Intelligence Guided Discovery of Gastric Cancer Continuum
Authors: Vo Daniella , Ghosh Pradipta , Sahoo Debashis 
Published: October 2022

ABSTRACTBackgroundDetailed understanding of pre, early and late neoplastic states in gastric cancer helps develop better models of risk of progression to Gastric Cancers (GCs) and medical treatment to intercept such progression.MethodsWe built a Boolean Implication network of gastric cancer and deployed machine learning algorithms to develop predictive models of known pre-neoplastic states, e.g., atrophic gastritis, intestinal metaplasia (IM) and low-to high-grade intestinal neoplasia (L/HGIN), and GC. Our approach exploits the presence of asymmetric Boolean Implication relationships that are likely to be invariant across almost all gastric cancer datasets. Invariant asymmetric Boolean Implication relationships can decipher fundamental time series underlying the biological data. Pursuing this method, we developed a healthy mucosa →GC continuum model based on this approach.ResultsOur model performed better against publicly available models for distinguishing healthy versus GC samples. Although not trained on IM and L/HGIN datasets, the model could identify the risk of progression to GC via the metaplasia →dysplasia →neoplasia cascade in patient samples. The model could rank all publicly available mouse models for their ability to best recapitulate the gene expression patterns during human GC initiation and progression.ConclusionsA Boolean implication network enabled the identification of hitherto undefined continuum states during GC initiation. The developed model could now serve as a starting point for rationalizing candidate therapeutic targets to intercept GC progression.MINI-ABSTRACTWe developed predictive models of early and late neoplastic states in gastric cancer and identified gene clusters that are up/down-regulated at various points along the gastric cancer disease continuum.
Non-Gaussian Normative Modelling With Hierarchical Bayesian Regression
Authors: de Boer Augustijn A.A. , Bayer Johanna M. M. , Kia Seyed Mostafa , Rutherford Saige , Zabihi Mariam , Fraza Charlotte , Barkema Pieter , Westlye Lars T. , Andreassen Ole A. , Hinne Max , Beckmann Christian F. , Marquand Andre 
Published: October 2022

AbstractNormative modelling is an emerging technique for parsing heterogeneity in clinical cohorts. This can be implemented in practice using hierarchical Bayesian regression, which provides an elegant probabilistic solution to handle site variation in a federated learning framework. However, applications of this method to date have employed a Gaussian assumption, which may be restrictive in some applications. We have extended the hierarchical Bayesian regression framework to flexibly model non-Gaussian data with heteroskdastic skewness and kurtosis. To this end, we employ a flexible distribution from the sinh-arcsinh (SHASH) family, and introduce a novel reparameterisation and a Markov chain Monte Carlo sampling approach to perform inference in this model. Using a large neuroimaging dataset collected at 82 different sites, we show that the results achieved with this extension are equivalent or better than a warped Bayesian linear regression baseline model on most datasets, whilst providing better control over the parameters governing the shape of distributions that approach is able to model. We also demonstrate that the attained flexibility is useful for accurately modelling highly nonlinear relationships between aging and imaging derived phenotypes, which shows that the extension is important for pushing the field of normative modelling forward. All methods described here are available in the open-sourcepcntoolkit.HighlightsWe extended the Hierarchical Bayesian Regression framework for normative modellingOur extension allows modelling data with heteroskedastic skewness and kurtosisWe developed a reparameterization of the SHASH distribution, suitable for samplingWe provide the first implementation of the SHASH distribution in a fully Bayesian frameworkResults show that the extension outperforms current methods on various measures
Zebrafish screen of high-confidence effector genes at insomnia GWAS loci implicates conserved regulators of sleep-wake behaviors
Authors: Zimmerman Amber J. , Doldur-Balli Fusun , Keenan Brendan T. , Shetty Zoe Y. , Palermo Justin , Chesi Alessandra , Sonti Shilpa , Pahl Matthew C. , Brown Elizabeth B. , Pippin James A. , Wells Andrew D. , Veatch Olivia J. , Mazzotti Diego R. , Krishnan Anitra , Gehrman Phillip R. , Keene Alex C. , Grant Struan F.A. , Pack Allan I. 
Published: October 2022

AbstractRecent large-scale human genome-wide association studies (GWAS) for insomnia have identified more than 200 significant loci. The functional relevance of these loci to the pathogenesis of insomnia is largely unknown. GWAS signals are typically non-coding variants, which are often arbitrarily annotated to the nearest protein-coding gene; however, due to 3D chromatin structure, variants can interact with more distal genes driving their function. The distal gene may, therefore, represent the true causal gene influencing the phenotype. By integrating our high-resolution chromatin interaction maps from neural progenitor cells with phenotypic data from aDrosophilaRNAi screen, we prioritized candidate genes that we hypothesized would have deep phylogenetic conservation of sleep function. To determine the conservation of these candidate genes in the context of vertebrate sleep and their relevance to insomnia-like behaviors, we performed CRISPR-Cas9 mutagenesis in larval zebrafish for six highly conserved candidate genes and examined sleep-wake behaviors using automated video-tracking. CRISPR mutation of zebrafish orthologs ofMEIS1andSKIV2Lproduced insomnia-like behaviors, while mutation ofARFGAP2impaired activity and development in our larval zebrafish model, demonstrating the importance of performing functional validation of GWAS-implicated effector genes to reveal genes influencing disease-relevant mechanisms.
Plant–hummingbird pollination networks exhibit minimal rewiring after experimental removal of a locally abundant plant species
Authors: Leimberger Kara G. , Hadley Adam S. , Betts Matthew G. 
Published: October 2022

ABSTRACTMutualistic relationships, such as those between plants and pollinators, may be vulnerable to the local extinctions predicted under global environmental change. However, network theory predicts that plant–pollinator networks can withstand species loss if pollinators switch to alternative floral resources (rewiring). Whether rewiring occurs following species loss in natural communities is poorly known because replicated species exclusions are difficult to implement at appropriate spatial scales.We experimentally removed a hummingbird-pollinated plant,Heliconia tortuosa, from within tropical forest fragments to investigate how hummingbirds respond to temporary loss of an abundant resource. Under therewiring hypothesis, we expected that niche expansions would decrease ecological specialization and reorganize the network structure (i.e., pairwise interactions).We employed a replicated Before-After-Control-Impact experimental design and quantified plant–hummingbird interactions using two parallel sampling methods: observations of hummingbirds visiting focal plants (‘camera networks’, created from >19,000 observation hours) and pollen collected from individual hummingbirds (‘pollen networks’, created from >300 pollen samples). To assess hummingbird rewiring, we quantified ecological specialization at the individual, species, and network levels and calculated the amount of network-level interaction turnover (i.e., gain/loss of pairwise interactions). Leveraging our parallel network datasets, we also explored how sampling method influences apparent specialization.H. tortuosaremoval caused some reorganization of pairwise interactions but did not prompt large changes in specialization, despite the large magnitude of our manipulation (on average, >100 inflorescences removed in treatment areas of >1 ha). Although some individual hummingbirds sampled through time showed modest increases in niche breadth followingHeliconiaremoval (relative to birds that did not experience resource loss), these changes were not reflected in species- and network-level specialization metrics. We also found that camera networks were more specialized than pollen networks, and that correlation between sampling methods was low.Our results suggest that animals may not necessarily shift to alternative resources after losing an abundant food resource, even in species thought to be highly opportunistic foragers such as hummingbirds. Given that rewiring contributes to theoretical predictions of network stability, future studies should investigate why pollinators might not expand their diets after a local resource extinction.
Predicting Anti-Cancer Drug Combination Responses with a Temporal Cell State Network Model
Authors: Sarmah Deepraj , Meredith Wesley O , Weber Ian , Price Madison R , Birtwistle Marc R 
Published: October 2022

AbstractCancer chemotherapy combines multiple drugs, but predicting the effects of drug combinations on cancer cell proliferation remains challenging. We hypothesized that by combining knowledge of single drug dose responses and cell state transition network dynamics, we could predict how a population of cancer cells will respond to drug combinations. We tested this hypothesis here using three targeted inhibitors of different cell cycle states in two different cell lines. We formulated a Markov model to capture temporal cell state transitions between different cell cycle phases, with single drug data constraining how drug doses affect transition rates. This model was able to predict the landscape of all three different pairwise drug combinations across all dose ranges for both cell lines with no additional data. This work shows how currently available or attainable information could be combined to predict how cancer cell populations respond to drug combinations.
Spatial metabolomics for symbiotic marine invertebrates
Authors: Chan Wing Yan , Rudd David , van Oppen Madeleine J. H. 
Published: October 2022

AbstractMicrobial symbionts frequently localize within specific body structures or cell types of their multicellular hosts. This spatiotemporal niche is critical to host health, nutrient exchange and fitness. Measuring host-microbe metabolite exchange has conventionally relied on tissue homogenates, eliminating dimensionality and dampening analytical sensitivity. We have developed a mass spectrometry imaging (MSI) workflow for a soft- and hard-bodied cnidarian animal capable of revealing the host and symbiont metabolome in situ, without the need for a priori isotopic labelling or skeleton decalcification. The MSI method provides critical functional insights that cannot be gleaned from bulk tissue analyses or other presently available spatial methods. We show that cnidarian hosts may regulate microalgal symbionts acquisition and rejection through specific ceramides distributed throughout the tissue lining the gastrovascular cavity; once resident, symbionts reside in light-exposed tentacles to generate photosynthate. These spatial patterns reveal how symbiont identity can drive host metabolism.
Origin and dynamics of Mycobacterium tuberculosis subpopulations that predictably generate drug tolerance and resistance
Authors: Sebastian Jees , Thomas Anooja , Levine Carly , Shrestha Riju , Levy Shawn , Safi Hassan , Pentakota Sri Ram , Kumar Pradeep , Alland David 
Published: October 2022

AbstractInitial responses to tuberculosis treatment are poor predictors of final therapeutic outcomes in drug-susceptible disease suggesting that treatment success depends on features that are hidden within a small minority of the overall infecting Mycobacterium tuberculosis (Mtb) population. We developed a multi-transwell robotic system to perform numerous parallel cultures of genetically barcoded Mtb exposed to steady-state concentrations of rifampicin to uncover these difficult to eliminate minority populations. We found that tolerance repeatedly emerged from at least two subpopulations of barcoded cells, one that could not grow on solid agar media and a second that could form colonies, but whose kill curves diverged from the general bacterial population within 4 and 16 days of drug exposure, respectively. These tolerant subpopulations reproducibly passed through a phase characterized by multiple unfixed resistance mutations followed by emergent drug resistance in some cultures. Barcodes associated with drug resistance identified an especially privileged subpopulation that was rarely eliminated despite 20 days of drug treatment even in cultures that did not contain any drug resistant mutants. The association of this evolutionary scenario with a defined subset of barcodes across multiple independent cultures suggested a transiently heritable phenotype, and indeed glpK phase variation mutants were associated with up to 16 % of the resistant cultures. Drug tolerance and resistance were eliminated in ΔruvA mutant consistent with the importance of bacterial stress responses. This work provides a window into the origin and dynamics of bacterial drug tolerant subpopulations whose elimination may be critical to developing rapid and resistance free cures.ImportanceTuberculosis is unusual among bacterial diseases in that treatments which can rapidly resolve symptoms do not predictably lead to a durable cure unless treatment is continued for months after all clinical and microbiological signs of disease have been eradicated. Using a novel steady-state antibiotic exposure system combined with chromosomal barcoding, we identified small hidden Mycobacterium tuberculosis subpopulations that repeatedly enter into a state of drug tolerance with a predisposition to develop fixed drug resistance after first developing a cloud of unfixed resistance mutations. The existence of these difficult to eradicate subpopulations may explain the need for extended treatment regimen for tuberculosis. Their identification provides opportunities to test genetic and therapeutic approaches that may result in shorter and more effective TB treatments.
Circularization of rv0678 for genotypic bedaquiline resistance testing of Mycobacterium tuberculosis
Authors: Limberis Jason D , Nalyvayko Alina , Ernst Joel D , Metcalfe John Z 
Published: October 2022

AbstractCircular DNA offers benefits over linear DNA in diagnostic and field assays, but currently, circular DNA generation is lengthy, inefficient, highly dependent on the length and sequence of DNA, and can result in unwanted chimeras. We present streamlined methods for generating PCR-targeted circular DNA from a 700bp amplicon of rv0678, the high GC content (65%) gene implicated in Mycobacterium tuberculosis bedaquiline resistance, and demonstrate that these methods work as desired. We employ self-circularization with and without splints, a Gibson cloning-based approach, and novel two novel methods for generating pseudocircular DNA. The circular DNA can be used as a template for rolling circle PCR followed by long-read sequencing, allowing for the error correction of sequence data, and improving the confidence in the drug resistance determination and strain identification; and ultimately improving patient treatment.
The natural history of homonymous hemianopia revisited
Authors: Saionz Elizabeth L. , Cavanaugh Matthew R. , Johnson Brent A. , Harrington Donald , Aguirre Geoffrey K. , Huxlin Krystel R. 
Published: October 2022

AbstractObjectiveTo re-evaluate the longitudinal progression of stroke-induced homonymous visual field defects using strictly automated perimetry (Zeiss Humphrey Systems), rigorous inclusion/exclusion criteria, and quantitative analyses.MethodsA retrospective chart review of stroke patients diagnosed with “homonymous hemianopia”, who underwent monocular Humphrey visual field (HVF) perimetry using the 24-2 SITA standard pattern from 2011-2019, was conducted at a large US academic medical center. Reliable tests (<20% fixation losses, false positives, and false negatives) were identified and analyzed with generalized estimating equations to extract temporal trends in perimetric mean deviation (PMD) and deficit area.ResultsOf 532 patients with “homonymous hemianopia”, sequential, reliable HVFs were only available for 36 patients in the right eye, and 30 patients in the left eye, ranging from 7 days to 58 months post-stroke. Both PMD and deficit area improved early, within the first 3 months post-stroke; however, this was followed by a subsequent decline in performance >1 year post-stroke. Changes were similar between eyes.ConclusionWe discovered that a large portion of occipital stroke patients do not receive comprehensive ophthalmologic follow-up and, even then, only a fraction of HVFs performed are reliable enough for rigorous analysis. Nonetheless, reliable HVFs in such patients confirmed early visual improvement after stroke, consistent with prior reports. However, in contrast with prior, qualitative reports, there was no stability of the deficit beyond 6 months post-stroke; instead, gradual worsening erased the initial spontaneous improvement, especially >1 year post-stroke.