bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mitochondrial electron transport chain, ceramide and Coenzyme Q are linked in a pathway that drives insulin resistance in skeletal muscle
Authors: Diaz-Vegas Alexis , Madsen Soren , Cooke Kristen C. , Carroll Luke , Khor Jasmine X. Y. , Turner Nigel , Lim Xin Ying , Astore Miro A. , Morris Jonathan , Don Anthony , Garfield Amanda , Zarini Simona , Zemski Berry Karin A. , Ryan Andrew , Bergman Bryan C. , Brozinick Joseph T. , James David E. , Burchfield James G. 
Published: March 2023

SummaryInsulin resistance (IR) is a complex metabolic disorder that underlies several human diseases, including type 2 diabetes and cardiovascular disease. Despite extensive research, the precise mechanisms underlying IR development remain poorly understood. Here, we provide new insights into the mechanistic connections between cellular alterations associated with IR, including increased ceramides, deficiency of coenzyme Q (CoQ), mitochondrial dysfunction, and oxidative stress. We demonstrate that elevated levels of ceramide in the mitochondria of skeletal muscle cells results in CoQ depletion and loss of mitochondrial respiratory chain components, leading to mitochondrial dysfunction and IR. Further, decreasing mitochondrial ceramide levels in vitro and in animal models (under chow and high fat diet) increased CoQ levels and was protective against IR. CoQ supplementation also rescued ceramide-associated IR. Examination of the mitochondrial proteome from human muscle biopsies revealed a strong correlation between the respirasome system and mitochondrial ceramide as key determinants of insulin sensitivity. Our findings highlight the mitochondrial Ceramide-CoQ-respiratory chain nexus as a potential foundation of an IR pathway that may also play a critical role in other conditions associated with ceramide accumulation and mitochondrial dysfunction, such as heart failure, cancer, and aging. These insights may have important clinical implications for the development of novel therapeutic strategies for the treatment of IR and related metabolic disorders.
Predominant myosin super-relaxed state in canine myocardium with naturally occurring dilated cardiomyopathy
Authors: Ochala Julien , Lewis Christopher T. A. , Beck Thomas , Iwamoto Hiroyuki , Hessel Anthony L. , Campbell Kenneth S. , Pyle W. Glen 
Published: March 2023

AbstractDilated cardiomyopathy (DCM) is a naturally occurring heart failure condition in humans and dogs, notably characterized by a reduced contractility and ejection fraction. As the identification of its underlying cellular and molecular mechanisms remain incomplete, the aim of the present study was to assess whether the molecular motor myosin and its known relaxed conformational states are altered in DCM. For that, we dissected and skinned thin cardiac strips from left ventricle obtained from six DCM Doberman Pinschers and six non-failing controls (NF). We then used a combination of Mant-ATP chase experiments and X-ray diffraction to assess both energetic and structural changes of myosin. Using the Mant-ATP chase protocol, we observed that in DCM dogs, the amount of myosin molecules in the ATP-conserving conformational state also known as super-relaxed (SRX), is significantly increased when compared with NF dogs. This alteration can be rescued by applying EMD-57033, a small molecule activating myosin. Conversely, with X-ray diffraction, we found that in DCM dogs, there is a higher proportion of myosin heads in the vicinity of actin when compared with NF dogs (1,0 to 1,1 intensity ratio). Hence, we observed an uncoupling between energetic (Mant-ATP chase) and structural (X-ray diffraction) data. Taken together, these results may indicate that in the heart of Doberman Pinschers with DCM, myosin molecules are potentially stuck in a non-sequestered but ATP-conserving SRX state, that can be counterbalanced by EMD-57033 demonstrating the potential for a myosin-centered pharmacological treatment of DCM.New & noteworthyThe key finding of the present study is that, in left ventricles of dogs with a naturally occurring dilated cardiomyopathy, relaxed myosin molecules favor a non-sequestered super-relaxed state potentially impairing sarcomeric contractility. This alteration is rescuable by applying a small molecule activating myosin known as EMD-57033.
Repeated unilateral injections of botulinum toxin in masticatory muscles in adult rats do not amplify condylar and alveolar bone loss nor modify the volume of the hypertrophic bone proliferation at enthesis
Authors: Dechaufour Pierre , Libouban Hélène , Chappard Daniel , Kün-Darbois Jean-Daniel 
Published: March 2023

AbstractObjectivesBotulinum toxin (BTX) induces muscle paralysis. It is used in human in masticatory muscles injections performed often repeatedly. A single BTX injection in masticatory muscles in animal induces mandibular bone loss (alveolar and condylar) with a muscle enthesis hypertrophic metaplasia. Our aim was to evaluate mandibular bone changes after unilateral repeated injections of BTX in temporal and masseter muscles in adult rats.Materials and MethodsMature male rats were randomized into 3 groups: one, two or three injections. Each injection was performed 4 weeks after the prior injection. Each rat received injections in right masseter and temporalis muscles. The left side was the control side. Microcomputed tomography was used to perform 2D and 3D analyses.ResultsBone loss was evidenced on the right sides of alveolar and condylar bone. Alveolar bone volume increased in both control left side and injected right side whereas condylar bone volume remained constant in all groups, for both left and right sides. Enthesis bone hypertrophic metaplasias were evidenced on the BTX injected sides without any modification with the number of injections.ConclusionsBTX repeated injections in masticatory muscles lead to major mandibular condylar and alveolar bone loss that does not worsen. They lead to the occurrence of an enthesis bone proliferation that is not dependent on the number of injections.Clinical relevanceThese results are an argument for the safety of BTX injections in masticatory muscles in human.
Estimating the Lambda measure in multiple-merger coalescents
Authors: Miró Pina Verónica , Joly Émilien , Siri-Jégousse Arno 
Published: March 2023

AbstractMultiple-merger coalescents, also known as Λ-coalescents, have been used to describe the genealogy of populations that have a skewed offspring distribution or that undergo strong selection. Inferring the characteristic measure Λ, which describes the rates of the multiple-merger events, is key to understand these processes. So far, most inference methods only work for some particular families of Λ-coalescents that are described by only one parameter, but not for more general models. This article is devoted to the construction of a non-parametric estimator of the density of Λ that is based on the observation at a single time of the so-called Site Frequency Spectrum (SFS), which describes the allelic frequencies in a present population sample. First, we produce estimates of the multiple-merger rates by solving a linear system, whose coefficients are obtained by appropriately subsampling the SFS. Then, we use a technique that aggregates the information extracted from the previous step through a kernel type of re-construction to give a non-parametric estimation of the measure Λ. We give a consistency result of this estimator under mild conditions on the behavior of Λ around 0. We also show some numerical examples of how our method performs.
A spatial approach to jointly estimate Wright’s neighborhood size and long-term effective population size
Authors: Hancock Zachary B. , Toczydlowski Rachel H. , Bradburd Gideon S. 
Published: March 2023

AbstractSpatially continuous patterns of genetic differentiation, which are common in nature, are often poorly described by existing population genetic theory or methods that assume panmixia or discrete, clearly definable populations. There is therefore a need for statistical approaches in population genetics that can accommodate continuous geographic structure, and that ideally use georeferenced individuals as the unit of analysis, rather than populations or subpopulations. In addition, researchers are often interested describing the diversity of a population distributed continuously in space, and this diversity is intimately linked to the dispersal potential of the organism. A statistical model that leverages information from patterns of isolation-by-distance to jointly infer parameters that control local demography (such as Wright’s neighborhood size), and the long-term effective size (Ne) of a population would be useful. Here, we introduce such a model that uses individual-level pairwise genetic and geographic distances to infer Wright’s neighborhood size and long-termNe. We demonstrate the utility of our model by applying it to complex, forward-time demographic simulations as well as an empirical dataset of the Red Sea clownfish (Amphiprion bicinctus). The model performed well on simulated data relative to alternative approaches and produced reasonable empirical results given the natural history of clownfish. The resulting inferences provide important insights into the population genetic dynamics of spatially structure populations.
plasma: Partial LeAst Squares for Multiomics Analysis
Authors: Yamaguchi Kyoko , Abdelbaky Salma , Yu Lianbo , Oakes Christopher C. , Abruzzo Lynne V. , Coombes Kevin R. 
Published: March 2023

AbstractRecent growth in the number and applications of high-throughput “omics” technologies has created a need for better methods to integrate multiomics data. Much progress has been made in developing unsupervised methods, but supervised methods have lagged behind. We present a novel algorithm,plasma, to learn models to predict time-to-event outcomes from multiomics data sets. Plasma uses two layers of existing partial least squares algorithms to first select components that covary with the outcome and then construct a joint Cox proportional hazards model. We applyplasmato the stomach adenocarcinoma (STAD) data from The Cancer Genome Atlas. We validate the model both by splitting the STAD data into training and test sets and by applying it to the subset of esophageal cancer (ESCA) containing adenocarcinomas. We use the other half of the ESCA data, which contains squamous cell carcinomas dissimilar to STAD, as a negative control. Our model successfully separates both the STAD test set (p = 2.73 × 10−8) and the independent ESCA validation data (p= 0.025) into high risk and low risk patients. It does not separate the negative control data set (ESCA squamous cell carcinomas,p= 0.57). The performance of the joint multiomics model is superior to that of the individually trained models. It is also superior to the performance of an unsupervised method (Multi Omics Factor Analysis; MOFA) that finds latent factors to be used as putative predictors in a post-hoc survival analysis. Many of the factors that contribute strongly to theplasmamodel can be justified from the biological literature.SignificanceTo fill the unmet need for supervised multiomics methods, we introduceplasma, an algorithm based on partial least squares that integrates multiomics features into biologically relevant “components” that can predict patient outcomes.Availability and ImplementationTheplasmaR package can be obtained from The Comprehensive R Archive Network (CRAN) athttps://CRAN.R-project.org/package=plasma. The latest version of the package can always be obtained from R-Forge athttps://r-forge.r-project.org/R/?group_id=1746. Source code and data for the analysis presented here can be obtained from GitLab, athttps://gitlab.com/krcoombes/plasma.ContactEmail:kcoombes@augusta.eduSupplementary InformationSupplementary material is available from the journal web site.
Including biotic interactions in species distribution models improves the understanding of species niche: a case of study with the brown bear in Europe
Authors: Lucas Pablo M. , Thuiller Wilfried , Talluto Matthew V. , Polaina Ester , Albrecht Jörg , Selva Nuria , Barba Marta De , Maiorano Luigi , Penteriani Vincenzo , Guéguen Maya , Balkenhol Niko , Dutta Trishna , Fedorca Ancuta , Frank Shane C. , Zedrosser Andreas , Afonso-Jordana Ivan , Ambarlı Hüseyin , Ballesteros Fernando , Bashta Andriy-Taras , Bilgin Cemal Can , Bogdanović Neda , Bojārs Edgars , Bojarska Katarzyna , Bragalanti Natalia , Brøseth Henrik , Chynoweth Mark W. , Ćirović Duško , Ciucci Paolo , Corradini Andrea , Angelis Daniele De , Hernando Miguel de Gabriel , Domokos Csaba , Dutsov Aleksander , Ertürk Alper , Filacorda Stefano , Frangini Lorenzo , Groff Claudio , Heikkinen Samuli , Hoxha Bledi , Huber Djuro , Huitu Otso , Ionescu Georgeta , Ionescu Ovidiu , Jerina Klemen , Jurj Ramon , Karamanlidis Alexandros A. , Kindberg Jonas , Kojola Ilpo , López-Bao José Vicente , Männil Peep , Melovski Dime , Mertzanis Yorgos , Molinari Paolo , Molinari-Jobin Anja , Mustoni Andrea , Naves Javier , Ogurtsov Sergey , Özüt Deniz , Palazón Santiago , Pedrotti Luca , Perović Aleksandar , Piminov Vladimir N. , Pop Ioan-Mihai , Popa Marius , Psaralexi Maria , Quenette Pierre-Yves , Rauer Georg , Reljic Slaven , Revilla Eloy , Saarma Urmas , Saveljev Alexander P. , Sayar Ali Onur , Şekercioğlu Cagan H. , Sergiel Agnieszka , Sîrbu George , Skrbinšek Tomaž , Skuban Michaela , Soyumert Anil , Stojanov Aleksandar , Tammeleht Egle , Tirronen Konstantin , Trajçe Aleksandër , Trbojević Igor , Trbojević Tijana , Zięba Filip , Zlatanova Diana , Zwijacz-Kozica Tomasz , Pollock Laura J. 
Published: March 2023

ABSTRACTBiotic interactions are expected to influence species’ responses to climate change, but they are usually not included when predicting future range shifts. We assessed the importance of biotic interactions to understand future consequences of climate and land use change for biodiversity using as a model system the brown bear (Ursus arctos) in Europe. By including biotic interactions using the spatial variation of energy contribution and habitat models of each food species, we showed that the use of biotic factors considerably improves our understanding of the distribution of brown bears. Predicted future range shifts, which included changes in the distribution of food species, varied greatly when considering various scenarios of change in biotic factors, warning about future indirect climate change effects. Our study confirmed that advancing our understanding of ecological networks of species interactions will improve future scenarios of biodiversity change, which is key for conserving biodiversity and ecosystem services.
Spatial Transcriptomic Cell-type Deconvolution Using Graph Neural Networks
Authors: Li Yawei , Luo Yuan 
Published: March 2023

AbstractSpatially resolved transcriptomics performs high-throughput measurement of transcriptomes while preserving spatial information about the cellular organizations. However, many spatially resolved transcriptomic technologies can only distinguish spots consisting of a mixture of cells instead of working at single-cell resolution. Here, we present STdGCN, a graph neural network model designed for cell type deconvolution of spatial transcriptomic (ST) data that can leverage abundant single-cell RNA sequencing (scRNA-seq) data as reference. STdGCN is the first model incorporating the expression profiles from single cell data as well as the spatial localization information from the ST data for cell type deconvolution. Extensive benchmarking experiments on multiple ST datasets showed that STdGCN outperformed 14 published state-of-the-art models. Applied to a human breast cancer Visium dataset, STdGCN discerned spatial distributions between stroma, lymphocytes and cancer cells for tumor microenvironment dissection. In a human heart ST dataset, STdGCN detected the changes of potential endothelial-cardiomyocyte communications during tissue development.
Development and Evaluation of a Machine Learning Recursive Partitioning Decision Tree Algorithm to Optimize Urinalysis Parameters to Predict Urine Culture Positivity
Authors: Seheult Jansen N. , Stram Michelle N. , Contis Lydia , Pontzer Raymond E. , Hardy Stephanie , Wertz William , Baxter Carla M. , Ondras Michael , Kip Paula L. , Snyder Graham M. , Pasculle A. William 
Published: March 2023

ABSTRACTPittUDT, a recursive partitioning decision tree algorithm for predicting urine culture (UC) positivity based on macroscopic and microscopic urinalysis (UA) parameters, may significantly decrease the number of unnecessary UC. The reflex algorithm derivation included 38,361 paired UA and UC cases; the average patient age was 57.4 years and 70% of samples were from female patients. Receiver operating characteristic (ROC) analysis identified urine WBCs, leukocyte esterase, and bacteria as the best predictors of UC positivity, with area under the ROC curve of 0.79, 0.78, and 0.77, respectively. The test data comprised 9,773 cases, of which 2,571 (26.3%) had a positive UC result. Using the held-out test data set, the PittUDT algorithm met the pre-specified targets of a 30-60% total negative proportion (true negative plus false negative predictions) with a negative predictive value above 90%. These data show that a rule-based algorithm trained on UA data has adequate predictive ability for triaging urine specimens by identifying low risk urine specimens, which are unlikely to grow pathogenic organisms, with a false-negative proportion under 5%. Our study demonstrates the feasibility and performance of using a supervised machine learning approach to develop a human readable machine learning model to optimize UA parameters in a reflex protocol that can be deployed across multiple hospital sites and settings. Our work supports a UA reflex to UC protocol that has the capacity to optimize UA parameters to predict UC positivity and improve antimicrobial stewardship and UC utilization, a potential avenue for cost savings.
Augmentation of a neuroprotective myeloid state by hematopoietic cell transplantation
Authors: Mader Marius Marc-Daniel , Napole Alan , Wu Danwei , Shibuya Yohei , Scavetti Alexa , Foltz Aulden , Atkins Micaiah , Hahn Oliver , Yoo Yongjin , Danziger Ron , Tan Christina , Wyss-Coray Tony , Steinman Lawrence , Wernig Marius 
Published: March 2023

SummaryMultiple sclerosis (MS) is an autoimmune disease associated with inflammatory demyelination in the central nervous system (CNS). Autologous hematopoietic cell transplantation (HCT) is under investigation as a promising therapy for treatment-refractory MS. Here we identify a reactive myeloid state in chronic experimental autoimmune encephalitis (EAE) mice and MS patients that is surprisingly associated with neuroprotection and immune suppression. HCT in EAE mice leads to an enhancement of this myeloid state, as well as clinical improvement, reduction of demyelinated lesions, suppression of cytotoxic T cells, and amelioration of reactive astrogliosis reflected in reduced expression of EAE- associated gene signatures in oligodendrocytes and astrocytes. Further enhancement of myeloid cell incorporation into the CNS following a modified HCT protocol results in an even more consistent therapeutic effect corroborated by additional amplification of HCT-induced transcriptional changes, underlining myeloid-derived beneficial effects in the chronic phase of EAE. Replacement or manipulation of CNS myeloid cells thus represents an intriguing therapeutic direction for inflammatory demyelinating disease.
Enzymatic Hydroxylation of Aliphatic C-H Bonds by a Mn/Fe Cofactor
Authors: Powell Magan M. , Rao Guodong , Britt R. David , Rittle Jonathan 
Published: March 2023

AbstractManganese cofactors activate strong chemical bonds in many essential enzymes. Yet very few manganese-dependent enzymes are known to functionalize ubiquitous carbon-hydrogen (C-H) bonds, and those that catalyze this important reaction display limited intrinsic reactivity. Herein, we report that the 2-aminoisobutyric acid hydroxylase fromRhodococcus wratislaviensisrequires manganese to functionalize a C-H bond possessing a bond dissociation enthalpy (BDE) exceeding 100 kcal/mol. Structural and spectroscopic studies of this enzyme reveal a redox-active, heterobimetallic manganese-iron active site that utilizes a manganese ion at the locus for O2activation and substrate coordination. Accordingly, this enzyme represents the first documented Mn-dependent monooxygenase in biology. Related proteins are widespread in microorganisms suggesting that many uncharacterized monooxygenases may utilize manganese-containing cofactors to accomplish diverse biological tasks.
Determinants of Disordered Protein Co-Assembly Into Discrete Condensed Phases
Authors: Welles Rachel M. , Sojitra Kandarp A. , Garabedian Mikael V. , Xia Boao , Wang Wentao , Guan Muyang , Regy Roshan M. , Gallagher Elizabeth R. , Hammer Daniel A. , Mittal Jeetain , Good Matthew C. 
Published: March 2023

AbstractCells harbor numerous mesoscale membraneless compartments that house specific biochemical processes and perform distinct cellular functions. These protein and RNA-rich bodies are thought to form through multivalent interactions among proteins and nucleic acids resulting in demixing via liquid-liquid phase separation (LLPS). Proteins harboring intrinsically disordered regions (IDRs) predominate in membraneless organelles. However, it is not known whether IDR sequence alone can dictate the formation of distinct condensed phases. We identified a pair of IDRs capable of forming spatially distinct condensates when expressed in cells. When reconstituted in vitro, these model proteins do not co-partition, suggesting condensation specificity is encoded directly in the polypeptide sequences. Through computational modeling and mutagenesis, we identified the amino acids and chain properties governing homotypic and heterotypic interactions that direct selective condensation. These results form the basis of physicochemical principles that may direct subcellular organization of IDRs into specific condensates and reveal an IDR code that can guide construction of orthogonal membraneless compartments.
High ResolutionSalmonellaSubtyping by the MLSTnext Method
Authors: Ma Zhihai , Gharizadeh Baback , Huang Steven , Jia Mo , Wu Florence , Wang Chunlin 
Published: March 2023

AbstractThe food industry needs a straightforward, efficient, widely applicable and cost-efficient method to not only detect, but also determine serovar and potential sources of multiple strains in food and environment. While Whole Genome Sequencing (WGS) can generate complete genomic profile of food pathogens, it is a laborious, time-consuming, and expensive method that necessitates pure isolates. As a result, it is unsuitable for samples with complex background, limiting its widespread application by food industry. However, traditional multilocus sequence typing (MLST) approaches do not provide sufficient single nucleotide polymorphism (SNP) information to effectively track- and-trace sources of contamination. In contrast, ChapterDx MLSTnext-NGS (next-generation sequencing)Salmonellaassay amplifies and sequences 47 polymorphic loci, evenly spanning theSalmonella entericagenome. As demonstrated in this study, the ChapterDx MLSTnext-NGSSalmonellacan identify serovar with high resolution, distinguishing between various strains of the same serovar and resolve co-presence of different strains in a single sample. Additionally, this assay can analyze up to thousand samples in a single sequencing run within 22 hours, making it a highly efficient and scalable method for the food industry. Moreover, the cost per sample of the ChapterDx MLSTnext-NGSSalmonellaassay is comparable to that of quantitative Polymerase Chain Reaction (qPCR), making it an affordable option. The assay uses ChapterDx amplification technology, allowing for the amplification of all 47 loci in a single-tube, single-step PCR reaction. This makes it one of the simplest NGS applications available. In summary, ChapterDx MLSTnext-NGSSalmonellaassay can be implemented in many diagnostic laboratories to address increasingly complex food safety issues.