bluuebunny/crossref_metadata_2025_split huggingface dataset:
A multiresolution framework to characterize single-cell state landscapes
Authors: Mohammadi Shahin , Davila-Velderrain Jose , Kellis Manolis 
Published: August 2019

AbstractDissecting the cellular heterogeneity embedded in single-cell transcriptomic data is challenging. Although a large number of methods and approaches exist, robustly identifying underlying cell states and their associations is still a major challenge; given the nonexclusive and dynamic influence of multiple unknown sources of variability, the existence of state continuum at the time-scale of observation, and the inevitable snapshot nature of experiments. As a way to address some of these challenges, here we introduce ACTIONet, a comprehensive framework that combines archetypal analysis and network theory to provide a ready-to-use analytical approach for multiresolution single-cell state characterization. ACTIONet uses multilevel matrix decomposition and network reconstruction to simultaneously learn cell state patterns, quantify single-cell states, and reconstruct a reproducible structural representation of the transcriptional state space that is geometrically mapped to a color space. A color-enhanced quantitative view of cell states enables novel visualization, prediction, and annotation approaches. Using data from multiple tissues, organisms, and developmental conditions, we illustrate how ACTIONet facilitates the reconstruction and exploration of single-cell state landscapes.
Atrous Convolution with Transfer Learning for Skin Lesions Classification
Authors: Ratul Md. Aminur Rab , Mozaffari Mohammad Hamed , Parimbelli Enea , Lee WonSook 
Published: August 2019

AbstractSkin cancer is a crucial public health issue and by far the most usual kind of cancer specifically in the region of North America. It is estimated that in 2019, only because of melanoma nearly 7,230 people will die, and 192,310 cases of malignant melanoma will be diagnosed. Nonetheless, nearly all types of skin lesions can be treatable if they can be diagnosed at an earlier stage. The accurate prediction of skin lesions is a critically challenging task even for vastly experienced clinicians and dermatologist due to a little distinction between surrounding skin and lesions, visual resemblance between melanoma and other skin lesions, fuddled lesion border, etc. A well-grounded automated computer-aided skin lesions detection system can help clinicians immensely to prognosis malignant skin lesion in the earliest possible time. From the past few years, the emergence of machine learning and deep learning in the medical imaging has produced several image-based classification systems in the medical field and these systems perform better than traditional image processing classification methods. In this paper, we proposed a popular deep learning technique namely atrous or, dilated convolution for skin lesions classification, which is known to have enhanced accuracy with the same amount of computational cost compared to traditional CNN. To implement atrous convolution we choose the transfer learning technique with several popular deep learning architectures such as VGG16, VGG19, MobileNet, and InceptionV3. To train, validate, and test our proposed models we utilize HAM10000 dataset which contains total 10015 dermoscopic images of seven different skin lesions (melanoma, melanocytic nevi, Basal cell carcinoma, Benign keratosis-like lesions, Dermatofibroma, Vascular lesions, and Actinic keratoses). Four of our proposed dilated convolutional frameworks show promising outcome on overall accuracy and per-class accuracy. For example, overall test accuracy achieved 87.42%, 85.02%, 88.22%, and 89.81% on dilated VGG16, dilated VGG19, dilated MobileNet, and dilated IncaptionV3 respectively. These dilated convolutional models outperformed existing networks in both overall accuracy and individual class accuracy. Among all the architectures dilated InceptionV3 shows superior classification accuracy and dilated MobileNet is also achieving almost impressive classification accuracy like dilated InceptionV3 with the lightest computational complexities than all other proposed model. Compared to previous works done on skin lesions classification we have experimented one of the most complicated open-source datasets with class imbalances and achieved better accuracy (dilated inceptionv3) than any known methods to the best of our knowledge.
Long-Term Potentiation Induces Extrasynaptic Exocytosis of Glun2A-containing NMDA Receptors that is Mainly Controlled by SNAP23
Authors: Yu Xiaojun , Li Wei , Wang Tong 
Published: August 2019

AbstractNMDA receptors (NMDAR) are key players in the initiation of synaptic plasticity that underlies learning and memory. Long-term potentiation (LTP) of synapses require an increased calcium current via NMDA channels to trigger modifications in postsynaptic density (PSD). It is generally believed that the amount of NMDARs on the postsynaptic surface remains stationary, whereas their subunit composition is dynamically fluctuated during this plasticity process. However, the molecular machinery underlying this subunit-specific regulation remains largely elusive. Here, by detecting the time-lapse changes of surface GluN2A and GluN2B subunit levels using biochemical approaches, surface immunostaining, live-imaging and super-resolution microscopy, we uncovered a transient increase of surface GluN2A-type NMDARs shortly after the induction of chemical long term potentiation (cLTP). These augmented sub-diffraction-limited GluN2A clusters predominantly exist in extrasynaptic domains. We also showed that the spine-enriched SNARE associated protein SNAP-23, and to a minor extent its homologue SNAP-25, control both the basal and regulated surface level of GluN2A receptors. Using a total internal reflection fluorescence microscopy (TIRFM) based live-imaging assay, we resolved and analyzed individual exocytic events of NMDARs in live neurons and found that cLTP raised the frequency of NMDAR exocytosis at extrasynaptic regions, without altering the duration or the package size of these events. Our study thereby provides direct evidence that synaptic plasticity controls the postsynaptic exocytosis machinery, which induces the insertion of more GluN2A receptors into the extrasynaptic area.Significance StatementMemory formation involves the long-term modification of synapses, which is called synaptic plasticity. In the postsynaptic density (PSD) of excited neurons, this modification process occurs on a minute timescale, initiated by the opening of NMDARs that trigger downstream cascades to fix the potentiation (LTP) at specific synapses for longer timescales. Here, using a novel live-imaging assay we resolved the dynamic delivery of NMDARs to the cell surface, and found that only the insertion frequency, not the duration of individual insertion or number of GluN2A subunits each of these NMDAR vesicles contains, was altered during the synaptic potentiation process. We also identified SNAP-23 as the key molecule mediating this activity dependent NMDAR surface delivery. This study provides a novel mechanism of how NMDARs are regulated in the short window to initiate the long-lasting synaptic modifications.
Novel Proteomic changes in Yeast Mitochondria provide insights into mitochondrial functioning upon over-expression of human p53
Authors: Redhu Archana Kumari , Bhat Jayadeva Paike 
Published: August 2019

AbstractCancer cells display enhanced glycolytic activity and impaired oxidative phosphorylation even in the presence of adequate oxygen (Warburg effect). Mitochondrial physiology is a promising hit target for anti-cancer therapy because of its key role in Warburg effect and activating apoptosis in mammalian as well as yeast cells. Over-expression of human p53 in S.cerevisiae leads to cell cycle arrest and apotosis. In the present work we show that how S.cerevisiae escapes from p53 induced apoptosis in fermentable carbon source, whereas in case of non-fermentable carbon source this phenomenon is not observed. To shed the light on this aspect we performed a quantitative proteomic analysis of yeast mitochondria isolated from the cells grown on sucrose (fermentation) and glycerol (respiration) with and without p53 over-expression. Through this approach, we identified a total dataset of 1120 proteins with 1% FDR, of which 239(133+106) proteins are differentially experssed in both conditions. Interestingly, we observed that after over-expression of p53 in sucrose grown yeast cells, a complete set of pentose phosphate pathway (PPP) enzymes is up-regulated in the mitochondria that leads to enhanced mitochondrial NADPH production and ROS quenching. Increased association of a hexose transporter (HXT6) and a hexokinase (HXK2) with the mitochondria of fermenting yeast cells upon over-expression of p53, may direct glucose towards PPP inside the mitochondria. In conclusion, our results provide the evidence that up-regulated PPP inside the mitochondria is a key to evade apoptosis by S.cerevisiae upon p53 over-expression.
Functional Anabolic Network Analysis of Human-associatedLactobacillusStrains
Authors: Moutinho Thomas J. , Neubert Benjamin C. , Jenior Matthew L. , Carey Maureen A. , Medlock Gregory L. , Kolling Glynis L. , Papin Jason A. 
Published: August 2019

AbstractMembers of theLactobacillusgenus are frequently utilized in the probiotic industry with many species conferring demonstrated health benefits; however, these effects are largely strain-dependent. We designed a method called PROTEAN (Probabilistic Reconstruction Of constituent Anabolic Networks) to computationally analyze the genomic annotations and predicted metabolic production capabilities of 144 strains across 16 species ofLactobacillusisolated from human intestinal, oral, and vaginal body sites. Using PROTEAN we conducted a genome-scale metabolic network comparison between strains, revealing that metabolic capabilities differ by isolation site. Notably, PROTEAN does not require a well-curated genome-scale metabolic network reconstruction to provide biological insights. We found that predicted metabolic capabilities of lactobacilli isolated from the vaginal microbiota cluster separately from intestinal and oral isolates, and we also uncovered an overlap in the predicted metabolic production capabilities of intestinal and oral isolates. Using machine learning, we determined the most informative metabolic products driving the difference between predicted metabolic capabilities of intestinal, oral, and vaginal isolates. Notably, intestinal and oral isolates were predicted to have a higher likelihood of producing D-alanine, D/L-serine, and L-proline, while the vaginal isolates were distinguished by a higher predicted likelihood of producing L-arginine, citrulline, and D/L-lactate. We found the distinguishing products to be consistent with published experimental literature. This study showcases a systematic technique, PROTEAN, for comparing the predicted functional metabolic output of microbes using genome-scale metabolic network analysis and computational modeling and provides unique insight into human-associatedLactobacillusbiology.ImportanceTheLactobacillusgenus has been shown to be important for human health. Lactobacilli have been isolated from human intestinal, oral, and vaginal sites. Members of the genus contribute significantly to the maintenance of vaginal health by providing colonization resistance to invading pathogens. A wide variety of clinical studies have indicated thatLactobacillus-based probiotics confer health benefits for several gut- and immune-associated diseases. Microbes interact with the human body in several ways, including the production of metabolites that influence physiology or other surrounding microbes. We have conducted a strain-level genome-scale metabolic network reconstruction analysis of human-associatedLactobacillusstrains, revealing that predicted metabolic capabilities differ when comparing intestinal/oral isolate to vaginal isolates. The technique we present here allows for direct interpretation of discriminating features between the experimental groups.
High-throughput multi-parallel enteropathogen quantification via nano-liter qPCR
Authors: Grembi Jessica A. , Mayer-Blackwell Koshlan , Luby Stephen P. , Spormann Alfred M. 
Published: August 2019

AbstractQuantitative molecular diagnostic methods, such as qPCR, can effectively detect pathogen-specific nucleic acid sequences. However, costs associated with multi-pathogen quantitative molecular diagnostics hinder their widespread use. Nano-liter qPCR (nL-qPCR) is a miniaturized tool for quantification of multiple targets in large numbers of samples based on assay parallelization on a single chip, with potentially significant cost-savings due to rapid throughput and reduced reagent volumes. We evaluated a suite of novel and published assays to detect 17 enteric pathogens using a commercially available nL-qPCR technology. Assay efficiencies ranged from 88-98% (mean 91%) and were reproducible across four operators at two separate facilities. When applied to complex fecal material, assays were sensitive and selective (99.8% of DNA amplified were genes from the target organism). Detection limits were 1-2 orders of magnitude higher for nL-qPCR than an existing enteric TaqMan Array Card (TAC), due to nanofluidic volumes. Compared to the TAC, nL-qPCR displayed 97% (95% CI 0.96, 0.98) negative percent agreement and 63% (95% CI 0.60, 0.66) overall positive percent agreement. Positive percent agreement was 90% for target concentrations above the nL-qPCR detection limits. nL-qPCR assays showed an underestimation bias of 0.34 log10copies/gram of stool [IQR -0.41, -0.28] compared with the enteric TAC. Higher detection limits, inherent to nL-qPCR, do not hinder detection of clinically relevant pathogen concentrations. With 12 times higher throughput for a sixth of the per-sample cost of the enteric TAC, the nL-qPCR chip described here is a viable alternative for enteropathogen quantification for studies where other technologies are cost-prohibitive.
Single-cell analysis of intestinal immune cells during helminth infection
Authors: Ferrer-Font Laura , Mehta Palak , Harmos Phoebe , Schmidt Alfonso , Price Kylie M , Hermans Ian F , Ronchese Franca , Le Gros Graham , Mayer Johannes U 
Published: August 2019

AbstractSingle cell isolation from helminth infected intestines has been notoriously difficult, due to the strong anti-parasite type 2 immune responses that drive mucus production, tissue remodeling and immune cell infiltration. Through the systematic optimization of a standard intestinal digestion protocol, we were able to isolate millions of immune cells from heavily infected tissues. Using this protocol, we validated many hallmarks of anti-parasite immunity and analyzed immune cells from the lamina propria and granulomas during helminth development, as well as acute and chronic worm infection.
Wild songbirds exhibit consistent individual differences in inter-specific social behaviour
Authors: Hillemann F. , Cole E. F. , Farine D. R. , Sheldon B. C. 
Published: August 2019

ABSTRACTNatural populations and communities consist of individuals that differ in their phenotypes. There is increasing evidence in community ecology that consistent intraspecific variation in behaviour changes the outcome of ecological interactions.Differences in intra- and inter-specific interactions are expected to play a major role in determining patterns of species coexistence and community structure. However, the question of whether individuals vary in their propensity to associate with heterospecifics has been neglected.We used social network analysis to characterise pattern of heterospecific associations in wild mixed-species flocks of songbirds, and assessed whether individuals adopt consistent social strategies in their broader, heterospecific, social environment. We quantified heterospecific foraging associations using data from a large automatically monitored PIT-tagged population of birds, involving more than 300 000 observations of flock membership, collected over three winters, for two tit species (Paridae), blue tits, Cyanistes caeruleus, and great tits, Parus major.We assessed individual consistency in interspecific social preferences over both short-term (week-to-week) and longer-term (year-to-year) timescales for a total of 4610 individuals, and found that blue tits and great tits exhibited marked and consistent intraspecific differences in heterospecific social phenotypes in terms of both absolute and relative number of associates. Further, we found that these consistent differences were significantly greater than expected from spatial and temporal differences in population densities.Heterospecific associations represent a major component of the social environment for many species, and our results show that individuals vary consistently in their social decisions with respect to heterospecifics. These findings provide support for the notion that intraspecific trait variation contributes to patterns at community and ecosystem levels.
Interleukin-4 signaling plays a major role in urogenital schistosomiasis-associated bladder pathogenesis
Authors: Mbanefo Evaristus C. , Fu Chi-Ling , Ho Christina P. , Le Loc , Ishida Kenji , H. Hsieh Michael 
Published: August 2019

AbstractIL-4 is crucial in many helminth infections, but its role in urogenital schistosomiasis, infection withSchistosoma haematobiumworms, remains poorly understood due to a historical lack of animal models. The bladder pathology of urogenital schistosomiasis is caused by immune responses to eggs deposited in the bladder wall. A range of pathology occurs, including urothelial hyperplasia and cancer, but associated mechanisms and links to IL-4 are largely unknown. We modeled urogenital schistosomiasis by injecting the bladder walls of IL-4 receptor-alpha knockout(Il4ra−/−) and wild type mice withS. haematobiumeggs. Readouts included bladder histology andex vivoassessments of urothelial proliferation, cell cycle and ploidy status. We also quantified the effects of exogenous IL-4 on urothelial cell proliferationin vitro, including cell cycle status and phosphorylation patterns of major downstream regulators in the IL-4 signaling pathway. There was a significant decrease in the intensity of granulomatous responses to bladder-wall injectedS. haematobiumeggs inIl4ra−/−versus wild type mice.S. haematobiumegg injection triggered significant urothelial proliferation, including evidence of urothelial hyperdiploidy and cell cycle skewing in wild type but notIl4ra−/−mice. Urothelial exposure to IL-4in vitroled to cell cycle polarization and increased phosphorylation of AKT. Our results show IL-4 signaling is required for key pathogenic features of urogenital schistosomiasis, and that particular aspects of this signaling pathway may exert these effects directly on the urothelium. These findings point to potential mechanisms by which urogenital schistosomiasis promotes bladder carcinogenesis.
Protein-surfactant-polysaccharide nanoparticles increase the catalytic activity of an engineered β-lactamase maltose-activated switch enzyme
Authors: Fuenzalida J.P. , Xiong T. , Moerschbacher B. M. , Ostermeier Marc , Goycoolea F.M. 
Published: August 2019

ABSTRACTWe present polysaccharide-based nanoparticles able to associate and increase the catalytic activity of the maltose-binding MBP317-347 switch enzyme. Fluorescence quenching and molecular docking studies along with the partial resistance to increasing pH and ionic strength indicate that the increase in enzymatic activity is due to a specific interaction between the maltose binding pocket on MBP317-347 and alginate exposed on the surface of the nanoparticles. Finally, we show that the hybrid self co-assembled particles increase the half-life of MBP317-347 over six-fold at 37°C, thus reflecting their potential use as a macromolecular drug delivery system.
Inhibition of Microbial Beta-Glucuronidase Does Not Prevent Breast Carcinogenesis in the Polyoma Middle T Mouse
Authors: Beck Amanda P. , Li Hao , Ervin Samantha M. , Redinbo Matthew R. , Mani Sridhar 
Published: August 2019

AbstractPurposeTo demonstrate whether inhibition of intestinal microbial beta (β)-glucuronidase (BGUS) abrogates tumor formation in a MMTV-PyMT mouse breast cancer model.MethodsFemale MMTV-PyMT heterozygote mice (4 weeks old) were randomized to oral gavage with vehicle or UNC10201652 (20 μg/day), a microbial BGUS inhibitor, for 9 weeks. The entire animal carcass was assessed for tumor deposits by histology and immunohistochemical staining for tumor (Ki67, PCNA) and breast specific (ER, PR, Cyclin D1, aSMA, Integrin β1) markers.ResultsThe MMTV-PyMT breast pathology in our study simulates prior published reports of tumor incidence and aggressiveness. There was no significant difference in the tumor histology, number of tumors (lesions), and patterns of spread of tumors in the UNC10201652 versus the vehicle treated mice. Similarly, there were no significant differences in the semi-quantitative scores for expression of ER, PR, Ki67, PCNA, or Integrin β1. There were also no major differences seen in qualitative screening of Cyclin D1 and aSMA.ConclusionsMMTV-PyMT mice administered UNC10201652, when compared to vehicle treated mice, show a similar abundance of breast tumor (and tumor initiating) lesions ranging from hyperplasia to frank carcinoma. There is a trend, however small, that the incidence of hyperplastic and adenomas may be decreased in UNC10201652 treated mice. Further refined dosing strategies in MMTV-PyMT are planned to clarify its biological significance. To our knowledge this is the first report of use of any BGUS inhibitor in chemoprevention of breast tumors using a genetic model simulating human breast cancer.
Natural variation in the Arabidopsis AGO2 gene is associated with susceptibility to potato virus X
Authors: Brosseau Chantal , Adurogbangba Ayooluwa , Roussin-Léveillée Charles , Zhao Zhenxing , Biga Sébastien , Moffett Peter 
Published: August 2019

AbstractRNA silencing functions as an anti-viral defence in plants through the action of DICER-like (DCL) and ARGONAUTE (AGO) proteins. However, there are few known examples of functional variation in RNA silencing components. The AGO2 protein is important for antiviral defense against multiple viruses and has been shown to be a major limiting factor to infection by potato virus X (PVX) of Arabidopsis thaliana but not Nicotiana benthamiana. We show that the AGO2 proteins from these two plants have differential activity against PVX, suggesting that variation in AGO2 is important in plant-virus interactions. Consistent with this, we find that the Arabidopsis thaliana AGO2 gene shows a high incidence of polymorphisms between accessions, with evidence of selective pressure. AGO2 protein variants can be assigned to two groups, in near equal frequency, based on an amino acid change and small deletions in the protein N-terminus. Inoculation of a large number of Arabidopsis accessions shows strong correlation between these alleles and resistance or susceptibility to PVX. These observations were validated using genetic and transgenic complementation analysis, which showed that one type of AGO2 variant is specifically affected in its antiviral activity, without interfering with other AGO2-associated functions such as anti-bacterial resistance or DNA methylation. Our results demonstrate a novel type of genetically-encoded virus resistance and suggest that plant-virus interactions have influenced natural variation in RNA silencing components.