bluuebunny/crossref_metadata_2025_split huggingface dataset:
Canine distemper in Nepal’s Annapurna Conservation Area - The implications of dog husbandry and human behaviour for wildlife disease
Authors: Ng Debby , Carver Scott , Gotame Mukhiya , Karmasharya Dibesh , Karmacharya Dikpal , Pradhan Saman Man , Rana Ajay N. , Johnson Christopher N. 
Published: July 2019

AbstractDogs are often commensal with human settlements. In areas where settlements are adjacent to wildlife habitat, the management of dogs can affect risk of spillover of disease to wildlife. We assess dog husbandry practices, and measure the prevalence of Canine Distemper Virus (CDV) in dogs, in 10 villages in Nepal’s Annapurna Conservation Area (ACA), an important region for Himalayan wildlife. A high proportion (58%) of owned dogs were allowed by their owners to roam freely, and many village dogs originated from urban areas outside the region. CDV antibodies, indicating past exposure, were detected in 70% of dogs, and 13% were positive for P-gene, suggesting current circulation of CDV. This is the first detection of canine distemper virus in a National Park in Nepal Himalaya. Dogs were generally in good condition, and none exhibited clinical signs of CDV infection, which suggests that infections were asymptomatic. CDV exposure varied with village location and age of dogs, but this variation was minor, consistent with high rates of movement of dogs across the region maintaining high seroprevalence. Residents reported the occurrence of several species of wild carnivores in or close to villages. These results suggest a high potential for transmission of CDV from village dogs to wild carnivores in ACA. We suggest that control of dog immigration, along with vaccination and neutering of dogs could mitigate the risk of CDV spillover into wild carnivore populations.
Photoswitchable microtubule inhibitors enabling robust, GFP-orthogonal optical control over the tubulin cytoskeleton
Authors: Gao Li , Kraus Yvonne , Wranik Maximilian , Weinert Tobias , Pritzl Stefanie D. , Meiring Joyce , Bingham Rebekkah , Olieric Natacha , Akhmanova Anna , Lohmüller Theobald , Steinmetz Michel O. , Thorn-Seshold Oliver 
Published: July 2019

ABSTRACTHere we present GFP-orthogonal optically controlled reagents for reliable and repetitive in cellulo modulation of microtubule dynamics and its dependent processes. Optically controlled reagents (“photopharmaceuticals”) have developed into powerful tools for high-spatiotemporal-precision control of endogenous biology, with numerous applications in neuroscience, embryology, and cytoskeleton research. However, the restricted chemical domain of photopharmaceutical scaffolds has constrained their properties and range of applications. Styrylbenzothiazoles are an as-yet unexplored scaffold for photopharmaceuticals, which we now rationally design to feature potent photocontrol, switching microtubule cytoskeleton function off and on according to illumination conditions. We show more broadly that this scaffold is exceptionally chemically and biochemically robust as well as substituent-tolerant, and offers particular advantages for intracellular biology through a range of desirable photopharmaceutical and drug-like properties not accessible to the current classes of photoswitches. We expect that these reagents will find powerful applications enabling robust, high precision, optically controlled cell biological experimentation in cytoskeleton research and beyond.
On Some Problems of Estimating Fundamental Niche from Physiological Data
Authors: Jesús Salvador Gutiérrez-Ruelas , Jiménez Laura , Quiroz-Reyes Ana Patricia , Sotelo-Pedroza Sabrina Cherizar , Jorge Soberon 
Published: July 2019

AbstractHutchinson proposed the idea of the fundamental niche, determined by physiological properties of a species, more than 50 years ago. The idea remains both central to ecological thinking and largely unexplored experimentally. In this note, we describe some problems of using physiological experiments databases to estimate fundamental niches, show some solutions, and the apply our solution to testing the prediction that fundamental niches contain realized niches, for some species of marine fishes and terrestrial beetles. Our results were concordant with Hutchinson’s predictions.
Functional significance and therapeutic potential of miR-15a mimic in pancreatic ductal adenocarcinoma
Authors: Guo Shixiang , Fesler Andrew , Huang Wenjie , Wang Yunchao , Yang Jiali , Wang Xianxing , Zheng Yao , Hwang Ga-Ram , Wang Huaizhi , Ju Jingfang 
Published: July 2019

AbstractTreatment of pancreatic ductal adenocarcinoma (PDAC) remains a clinical challenge. There is an urgent need to develop novel strategies to enhance survival and improve patient prognosis. microRNAs (miRNAs) play critical roles as oncogenes or tumor suppressors in the regulation of cancer development and progression. In this study, we demonstrate that low expression of miR-15a is associated with poor prognosis of PDAC patients. miR-15a expression is reduced in PDAC while closely related miR-16 expression remains relatively unchanged. miR-15a suppresses several important targets such as Wee1, Chk1, Yap-1, and BMI-1 causing cell cycle arrest and inhibiting cell proliferation. Ectopic expression of miR-15a sensitizes PDAC cells to gemcitabine reducing the IC50over 6.5-fold. To investigate the therapeutic potential of miR-15a, we used a modified miR-15a (5-FU-miR-15a) with uracil (U) residues in the guide strand replaced with 5-fluorouracil (5-FU). We demonstrated enhanced inhibition of PDAC cell proliferation by 5-FU-miR-15a compared to native miR-15a.In vivowe showed the therapeutic power of 5-FU-miR-15a alone or in combination with gemcitabine with near complete elimination of PDAC lung metastatic tumor growth. These results support the future development of 5-FU-miR-15a as a novel therapeutic agent as well as a prognostic biomarker in the clinical management of PDAC.
A Clinical Phenotyping Algorithm to Identify Cases of Chronic Obstructive Pulmonary Disease in Electronic Health Records
Authors: Martucci Victoria L. , Liu Nancy , Kerchberger V. Eric , Osterman Travis J. , Torstenson Eric , Richmond Bradley , Aldrich Melinda C. 
Published: July 2019

AbstractRationaleChronic obstructive pulmonary disease (COPD) is a leading cause of mortality in the United States. Electronic health records provide large-scale healthcare data for clinical research, but have been underutilized in COPD research due to challenges identifying these individuals, especially in the absence of pulmonary function testing data.ObjectivesTo develop an algorithm to electronically phenotype individuals with COPD at a large tertiary care center.MethodsWe identified individuals over 45 years of age at last clinic visit within Vanderbilt University Medical Center electronic health records. We tested phenotyping algorithms using combinations of both structured and unstructured text and examined the clinical characteristics of the resulting case sets.Measurement and Main ResultsA simple algorithm consisting of 3 International Classification of Disease codes for COPD achieved a sensitivity of 97.6%, a specificity of 76.0%, a positive predictive value of 57.1%, and a negative predictive value of 99.0%. A more complex algorithm consisting of both billing codes and a mention of oxygen on the problem list that achieved a positive predictive value of 86.5%. However, the association of known risk factors with chronic obstructive pulmonary disease was consistent in both algorithm sets, suggesting a simple code-only algorithm may suffice for many research applications.ConclusionsSimple code-only phenotyping algorithms for chronic obstructive pulmonary disease can identify case populations with epidemiologic and genetic profiles consistent with published literature. Implementation of this phenotyping algorithm will expand opportunities for clinical research and pragmatic trials for COPD.
Rapid degradation ofC. elegansproteins at single-cell resolution with a synthetic auxin
Authors: Martinez Michael A. Q. , Kinney Brian A. , Medwig-Kinney Taylor N. , Ashley Guinevere , Ragle James M. , Johnson Londen , Aguilera Joseph , Hammell Christopher M. , Ward Jordan D. , Matus David Q. 
Published: July 2019

ABSTRACTAs developmental biologists in the age of genome editing, we now have access to an ever-increasing array of tools to manipulate endogenous gene expression. The auxin-inducible degradation system, allows for spatial and temporal control of protein degradation, functioning through the activity of a hormone-inducibleArabidopsisF-box protein, transport inhibitor response 1 (TIR1). In the presence of auxin, TIR1 serves as a substrate recognition component of the E3 ubiquitin ligase complex SKP1-CUL1-F-box (SCF), ubiquitinating auxin-inducible degron (AID)-tagged proteins for proteasomal degradation. Here, we optimize theCaenorhabditis elegansAID method, utilizing 1-naphthaleneacetic acid (NAA), an indole-free synthetic analog of the natural auxin indole-3-acetic acid (IAA). We take advantage of the photostability of NAA to demonstrate via quantitative high-resolution microscopy that rapid degradation of target proteins can be detected in single cells within 30 minutes of exposure. Additionally, we show that NAA works robustly in both standard growth media and physiological buffer. We also demonstrate that K-NAA, the water-soluble, potassium salt of NAA, can be combined with microfluidics for targeted protein degradation inC. eleganslarvae. We provide insight into how the AID system functions inC. elegansby determining that TIR1 interacts withC. elegansSKR-1/2, CUL-1, and RBX-1 to degrade target proteins. Finally, we present highly penetrant defects from NAA-mediated degradation of the Ftz-F1 nuclear hormone receptor, NHR-25, duringC. elegansuterine-vulval development. Together, this work provides a conceptual improvement to the AID system for dissecting gene function at the single-cell level duringC. elegansdevelopment.
High resolution structure of a partially folded insulin aggregation intermediate
Authors: Ratha Bhisma N , Kar Rajiv K , Brender Jeffrey R , Sahoo Bankanidhi , Kalita Sujan , Bhunia Anirban 
Published: July 2019

AbstractInsulin has long served as a model for protein aggregation, both because of the importance of aggregation in insulin manufacture and because the structural biology of insulin has been extensively characterized. Despite intensive study, details about the initial triggers for aggregation have remained elusive at the molecular level. We show here that at acidic pH, the aggregation of insulin is likely initiated by a partially folded monomeric intermediate whose concentration is controlled by an off-pathway micellar species. High resolution structures of the partially folded intermediate show that it is coarsely similar to the initial monomeric structure but differs in subtle details – the A chain helices on the receptor interface are more disordered and the B chain helix moves away from C-terminal A chain helix. The result of these movements is the creation of a hydrophobic cavity in the center of the protein that may serve as nucleation site for oligomer formation. Knowledge of this transition may aid in the engineering of insulin variants that retain the favorable pharamacokinetic properties of monomeric insulin but are more resistant to aggregation.
Adding Extra Knowledge in Scalable Learning of Sparse Differential Gaussian Graphical Models
Authors: Sekhon Arshdeep , Wang Beilun , Qi Yanjun 
Published: July 2019

AbstractWe focus on integrating different types of extra knowledge (other than the observed samples) for estimating the sparse structure change between two p-dimensional Gaussian Graphical Models (i.e. differential GGMs). Previous differential GGM estimators either fail to include additional knowledge or cannot scale up to a high-dimensional (large p) situation. This paper proposes a novel method KDiffNet that incorporates Additional Knowledge in identifying Differential Networks via an Elementary Estimator. We design a novel hybrid norm as a superposition of two structured norms guided by the extra edge information and the additional node group knowledge. KDiffNet is solved through a fast parallel proximal algorithm, enabling it to work in large-scale settings. KDiffNet can incorporate various combinations of existing knowledge without re-designing the optimization. Through rigorous statistical analysis we show that, while considering more evidence, KDiffNet achieves the same convergence rate as the state-of-the-art. Empirically on multiple synthetic datasets and one real-world fMRI brain data, KDiffNet significantly outperforms the cutting edge baselines with regard to the prediction performance, while achieving the same level of time cost or less.
AnIn silicoAlgorithm for Identifying Amino Acids that Stabilize Oligomeric Membrane-Toxin Pores through Electrostatic Interactions
Authors: Desikan Rajat , Maiti Prabal K. , Ayappa K. Ganapathy 
Published: July 2019

ABSTRACTPore forming toxins (PFTs) are a class of proteins which have specifically evolved to form unregulated pores in target plasma membranes, and represent the single largest class of bacterial virulence factors. With increasingly prevalent antibiotic-resistant bacterial strains, next generation therapies are being developed to target bacterial PFTs rather than the pathogens themselves. However, structure-based design of inhibitors that could block pore formation are hampered by a paucity of structural information about pore intermediates. On similar lines, observations of the inter-subunit interfaces in fully-formed pore complexes to identify druggable residues, whose interactions could potentially be blocked to hamper pore formation or destabilize pore assemblies, are often limited because of the presence of a large number of protein-protein interaction sites across pore inter-subunit interfaces. Narrowing down the list of plausible target residues requires a quantitative assessment of their contributions towards pore stability, which cannot be gleaned from a single, static, crystal or cryo-EM pore structure. We overcome this limitation by developing anin silicoscreening algorithm that employs fully atomistic molecular dynamics simulations coupled with knowledge-based screening to identify residues engaged in persistent and stabilizing electrostatic interactions across inter-subunit interfaces in membrane-inserted PFT pores. Application of this algorithm to prototypicalα-PFT (cytolysin A) andβ-PFT (α-hemolysin) pores yielded a small predicted subset of highly interacting residues, blocking of which could destabilize pore complexes as shown in previous mutagenesis experiments for some of these predicted residues. The algorithm also yielded a novel set of residues in both cytolysin A andα-hemolysin pores for which no mutagenesis and stability data exists to the best of our knowledge, and therefore could serve as hitherto un-recognised potential targets for PFT inhibitors. The algorithm worked equally well for bothαandβ-PFT pores, and could thus be potentially applicable to all pores with known structures to generate a database of pore-destabilizing mutations, which could then serve as a starting point for experimental validation and structure-based PFT-inhibitor design.
The Aging Microenvironment Shapes Alveolar Macrophage Identity in Aging
Authors: McQuattie-Pimentel Alexandra C. , Ren Ziyou , Joshi Nikita , Watanabe Satoshi , Stoeger Thomas , Chi Monica , Lu Ziyan , Sichizya Lango , Piseaux Raul , Chen Ching-I , Soberanes Saul , Reyfman Paul A. , Walter James M. , Anekalla Kishore R. , Davis Jennifer M. , Helmin Kathryn A. , Runyan Constance E. , Abdala-Valencia Hiam , Nam Kiwon , Meliton Angelo Y. , Winter Deborah R. , Morimoto Richard I. , Mutlu Gökhan M. , Bharat Ankit , Perlman Harris , Gottardi Cara J. , Ridge Karen M. , Chandel Navdeep S. , Sznajder Jacob I. , Balch William E. , Singer Benjamin D. , Misharin Alexander V. , Budinger GR Scott 
Published: July 2019

AbstractA dysfunctional response to inhaled pathogens and toxins drives a substantial portion of the susceptibility to acute and chronic lung disease in the elderly. We used transcriptomic profiling combined with genetic lineage tracing, heterochronic adoptive transfer, parabiosis and treatment with metformin to show that the lung microenvironment defines the phenotype of long-lived alveolar macrophages during aging. While tissue-resident alveolar macrophages persist in the lung without input from monocytes over the lifespan, severe lung injury results in their replacement with monocyte-derived alveolar macrophages. These monocyte-derived alveolar macrophages are also shaped by the microenvironment both during aging and in response to a subsequent environmental challenge to become transcriptionally and functionally similar to tissue-resident alveolar macrophages. These findings show that changes in alveolar macrophage phenotypes during injury and aging are not cell autonomous but instead are shaped by changes in the aging lung microenvironment.
Tyrosine-based Signals Regulate the assembly of Daple•PARD3 Complex at Cell-cell Junctions during Polarized Planar Cell Migration
Authors: Ear Jason , Saklecha Anokhi , Rajapakse Navin , Choi Julie , Ghassemian Majid , Kufareva Irina , Ghosh Pradipta 
Published: July 2019

SummaryPolarized distribution of organelles and molecules inside a cell is vital for a range of cellular processes and its loss is frequently encountered in disease. Polarization during planar cell migration is a special condition in which cellular orientation is triggered by cell-cell contact. Here, we demonstrate that the multi-modular signaling scaffold Daple (CCDC88C) is a component of cell junctions in epithelial cells which serves like a cellular ‘compass’ for establishing and maintaining contact-triggered planar polarityviaits interaction with the polarity regulator PARD3, which has been implicated in both apical-basal and planar polarity. This interaction, mediated by Daple’s PDZ-binding motif (PBM) and the third PDZ domain of PARD3, is fine-tuned by two tyrosine phosphoevents on Daple’s PBM that are known to be triggered by a multitude of receptor and non-receptor tyrosine kinases, such as Src. Hypophosphorylation strengthens the interaction, whereas hyperphosphorylation disrupts it. These findings reveal an unexpected role of Daple within the planar cell polarity pathway as a platform for signal integration and gradient sensing for tyrosine-based signals.
Transcriptome analysis of apple leaves infected by the rust fungus Gymnosporangium yamadae at two sporulation stages (spermogonia and aecia) reveals specific host responses, rust pathogenesis-related genes and a shift in the phyllosphere fungal community composition
Authors: Tao Si-Qi , Auer Lucas , Morin Emmanuelle , Liang Ying-Mei , Duplessis Sébastien 
Published: July 2019

AbstractApple rust disease caused by Gymnosporangium yamadae is one of the major threats to apple orchards. In this study, dual RNA-seq analysis was conducted to simultaneously monitor gene expression profiles of G. yamadae and infected apple leaves during the formation of rust spermogonia and aecia. The molecular mechanisms underlying this compatible interaction at 10 and 30 days post inoculation (dpi) indicate a significant reaction from the host plant and comprise detoxication pathways at the earliest stage and the induction of secondary metabolism related pathways at 30dpi. Such host reactions have been previously reported in other rust pathosystems and may represent a general reaction to rust infection. G. yamadae transcript profiling indicates a conserved genetic program in spermogonia and aecia that is shared with other rust fungi, whereas secretome prediction reveals the presence of specific secreted candidate effector proteins expressed during apple infection. Unexpectedly, the survey of fungal unigenes in the transcriptome assemblies of inoculated and mock-inoculated apple leaves reveals that G. yamadae infection modifies the fungal community composition in the apple phyllosphere at 30 dpi. Collectively, our results provide novel insights into the compatible apple-apple rust interaction and advance the knowledge of this heteroecious demicyclic rust fungus.
High Resolution Imaging Mass Spectrometry of Bacterial Microcolonies at Ecological Scales
Authors: de Cassia Pessotti Rita , Hansen Bridget L. , Zacharia Vineetha M. , Polyakov Daniel , Traxler Matthew F. 
Published: July 2019

AbstractMicrobes interact with the world around them at the chemical level. However, directly examining the chemical exchange between microbes, and microbes and their environment, at ecological scales,i.e.the scale of a single bacterial cell or small groups of cells, remains a key challenge. Here we address this obstacle by presenting a methodology that enablesMatrix-assistedlaserdesorption/ionization (MALDI)imagingmassspectrometry (IMS) of bacterial microcolonies. By combining optimized sample preparation with sub-atmospheric pressure MALDI, we demonstrate that chemical output from groups of as few as ~50 cells can be visualized with MALDI-IMS. Application of this methodology toBacillus subtilisandStreptomyces coelicolorrevealed heterogeneity in chemical output across microcolonies, and asymmetrical metabolite production when cells grew within physiological gradients produced byMedicago sativaroots. Taken together, these results indicate that MALDI-IMS can readily visualize metabolites made by very small assemblages of bacterial cells, and that even these small groups of cells can differentially produce metabolites in response to local chemical gradients.
Response to CAR T cell therapy can be explained by ecological cell dynamics and stochastic extinction events
Authors: Kimmel Gregory J. , Locke Frederick L. , Altrock Philipp M. 
Published: July 2019

ABSTRACTChimeric antigen receptor (CAR) T cell therapy is a remarkably effective immunotherapy that relies on in vivo expansion of engineered CAR T cells, after lymphodepletion by chemotherapy. The laws underlying this expansion and subsequent tumor eradication remain unknown. Still, about 60% of CAR T-treated patients are likely to progress; their tumors are not eradicated. Here we seek to understand and disentangle the multiple processes that contribute to CAR expansion and tumor eradication. We developed a mathematical model of T cell-tumor cell interactions, and demonstrate that CAR T cell expansion is shaped by immune reconstitution dynamics after lymphodepletion and predator prey-like dynamics. Our cell population model was parameterized using patient population-level data over time and recapitulates progression free survival. As an intrinsic property, we find that tumor eradication is a stochastic event. Our cell population-based approach renders CAR T cell therapy as an ecological dynamic process that drives tumors toward an extinction vortex. Even if a clinical event, such as progression, is likely, its timing can be highly variable. We predict how clinical interventions that increase CAR T memory populations could improve the likelihood of tumor eradication and improve progression free survival. Our model can be leveraged to propose new CAR composition and dosing strategies, assess the need for multiple doses, and identify patient populations most likely to benefit from CAR T with or without additional interventions.