bluuebunny/crossref_metadata_2025_split huggingface dataset:
Activating a collaborative innate-adaptive immune response to control breast and ovarian cancer metastasis
Authors: Sun Lijuan , Kees Tim , Almeida Ana Santos , Liu Bodu , He Xue-Yan , Ng David , Spector David , McNeish Iain A. , Gimotty Phyllis , Adams Sylvia , Egeblad Mikala 
Published: July 2020

AbstractMany cancers recruit monocytes/macrophages and polarize them into tumor-associated macrophages (TAMs). TAMs promote tumor growth and metastasis and inhibit cytotoxic T cells. Yet, macrophages can also kill cancer cells after polarization bye.g., lipopolysaccharide (LPS, a bacteria-derived toll-like receptor 4 [TLR4] agonist) and interferon gamma (IFNγ). They do so via nitric oxide (NO), generated by inducible NO synthase (iNOS). Altering the polarization of macrophages could therefore be a strategy for controlling cancer. Here, we show that monophosphoryl lipid A (MPLA, a derivative of LPS) with IFNγ activated macrophages isolated from metastatic pleural effusions of breast cancer patients to kill the corresponding patients’ cancer cellsin vitro. Importantly, intratumoral injection of MPLA with IFNγ not only controlled local tumor growth but also reduced metastasis in mouse models of luminal and triple negative breast cancers. Furthermore, intraperitoneal administration of MPLA with IFNγ reprogrammed peritoneal macrophages, suppressed metastasis, and enhanced the response to chemotherapy in the ID8-p53−/−ovarian carcinoma mouse model. The combined MPLA+IFNγ treatment reprogrammed the immunosuppressive microenvironment to be immunostimulatory by recruiting leukocytes, stimulating type I interferon signaling, decreasing tumor-associated (CD206+) macrophages, increasing tumoricidal (iNOS+) macrophages, and activating cytotoxic T cells through macrophage-secreted interleukin 12 (IL-12) and tumor necrosis factor α (TNFα). Both macrophages and T cells were critical for the anti-metastatic effects of MPLA+IFNγ. MPLA and IFNγ are already used individually in clinical practice, so our strategy to engage the anti-tumor immune response, which requires no knowledge of unique tumor antigens, may be ready for near-future clinical testing.
FEATS: Feature selection based clustering of single-cell RNA-seq data
Authors: Vans Edwin , Patil Ashwini , Sharma Alok 
Published: July 2020

ABSTRACTAdvances in next-generation sequencing (NGS) have made it possible to carry out transcriptomic studies at single-cell resolution and generate vast amounts of single-cell RNA-seq data rapidly. Thus, tools to analyze this data need to evolve as well to improve accuracy and efficiency. We present FEATS, a python software package that performs clustering on single-cell RNA-seq data. FEATS is capable of performing multiple tasks such as estimating the number of clusters, conducting outlier detection, and integrating data from various experiments. We develop a univariate feature selection based approach for clustering, which involves the selection of top informative features to improve clustering performance. This is motivated by the fact that cell types are often manually determined using the expression of only a few known marker genes. On a variety of single-cell RNA-seq datasets, FEATS gives superior performance compared to the current tools, in terms of adjusted rand index (ARI) and estimating the number of clusters. In addition to cluster estimation, FEATS also performs outlier detection and data integration while giving an excellent computational performance. Thus, FEATS is a comprehensive clustering tool capable of addressing the challenges during the clustering of single-cell RNA-seq data. The installation instructions and documentation of FEATS is available athttps://edwinv87.github.io/feats/.
Environmental controls and habitat connectivity of phototrophic microbial mats and bacterioplankton communities in an Antarctic freshwater system
Authors: Ramoneda J. , Hawes I. , Pascual-García A. , Mackey T.J. , Sumner D.Y. , Jungblut A.D. 
Published: July 2020

AbstractFreshwater ecosystems are considered hotspots of biodiversity in Antarctic polar deserts. Anticipated warming is expected to change the hydrology of these systems due to increased meltwater and reduction of ice cover, with implications for environmental conditions and physical connectivity between habitats. Using 16S rRNA sequencing, we evaluated the structure of microbial mat and planktonic communities within a connected watershed in the McMurdo Wright Valley, Antarctica to determine the roles of connectivity and habitat conditions in controlling microbial assemblage composition. We examined benthic and planktonic samples from glacial Lake Brownworth, the perennially ice-covered Lake Vanda, and the Onyx River, which connects the two. In Lake Vanda, we found distinct microbial assemblages occupying sub-habitats at different lake depths, while the communities from Lake Brownworth and Onyx River were structurally similar between them. Despite the higher connectivity between bacterial communities in the shallow parts of the system, environmental filtering dominated over dispersal in driving bacterial community structure. Functional metagenomics predictions identified genes related to degradation of halogenated aromatic compounds in surface microbial mats exposed to changes in water regimes, which progressively disappeared with increasing depth. Shifting environmental conditions due to increasing connectivity, rather than dispersal, may become the dominant drivers of bacterial diversity and functioning in Antarctic freshwater ecosystems.
Peptide Gaussian accelerated molecular dynamics (Pep-GaMD): Enhanced sampling and free energy and kinetics calculations of peptide binding
Authors: Wang Jinan , Miao Yinglong 
Published: July 2020

AbstractPeptides mediate up to 40% of known protein-protein interactions in higher eukaryotes and play an important role in cellular signaling. However, it is challenging to simulate both binding and unbinding of peptides and calculate peptide binding free energies through conventional molecular dynamics, due to long biological timescales and extremely high flexibility of the peptides. Based on the Gaussian accelerated molecular dynamics (GaMD) enhanced sampling technique, we have developed a new computational method “Pep-GaMD”, which selectively boosts essential potential energy of the peptide in order to effectively model its high flexibility. In addition, another boost potential is applied to the remaining potential energy of the entire system in a dual-boost algorithm. Pep-GaMD has been demonstrated on binding of three model peptides to the SH3 domains. Independent 1 μs dual-boost Pep-GaMD simulations have captured repetitive peptide dissociation and binding events, which enable us to calculate peptide binding thermodynamics and kinetics. The calculated binding free energies and kinetic rate constants agreed very well with available experimental data. Furthermore, the all-atom Pep-GaMD simulations have provided important insights into the mechanism of peptide binding to proteins that involves long-range electrostatic interactions and mainly conformational selection. In summary, Pep-GaMD provides a highly efficient, easy-to-use approach for unconstrained enhanced sampling and calculations of peptide binding free energies and kinetics.Significance StatementWe have developed a new computational method “Pep-GaMD” for enhanced sampling of peptide-protein interactions based on the Gaussian accelerated molecular dynamics (GaMD) technique. Pep-GaMD works by selectively boosting the essential potential energy of the peptide to effectively model its high flexibility. In addition, another boost potential can be applied to the remaining potential energy of the entire system in a dual-boost algorithm. Pep-GaMD has been demonstrated on binding of three model peptides to the SH3 domains. Dual-boost Pep-GaMD has captured repetitive peptide dissociation and binding events within significantly shorter simulation time (microsecond) than conventional molecular dynamics. Compared with previous enhanced sampling methods, Pep-GaMD is easier to use and more efficient for unconstrained enhanced sampling of peptide binding and unbinding, which provides a novel physics-based approach to calculating peptide binding free energies and kinetics.
Cancer Risk and the Somatic Cell Lineage Tree
Authors: Derényi Imre , Demeter Márton C. , Szöllősi Gergely J. 
Published: July 2020

All the cells of a multicellular organism are the product of cell divisions that trace out a single binary tree, the so-called cell lineage tree. Because cell divisions are accompanied by replication errors, the shape of the cell lineage tree is one of the key determinants of how somatic evolution, which can potentially lead to cancer, proceeds. Cancer initiation usually requires the accumulation of a certain number of driver mutations. By mapping the accumulation of driver mutations into a graph theoretical problem, we show that in leading order of the mutation rate the probability of collecting a given number of driver mutations depends only on the distribution of the lineage lengths (irrespective of any other details of the cell lineage tree), and we derive a simple analytical formula for this probability. Our results are crucial in understanding how natural selection can shape the cell lineage trees of multicellular organisms in order to reduce their lifetime risk of cancer. In particular, our results highlight the significance of the longest cell lineages. Our analytical formula also provides a tool to quantify cancer susceptibility in theoretical models of tissue development and maintenance, as well as for empirical data on cell linage trees.Significance StatementA series of cell divisions starting from a single cell produce and maintain tissues of multicellular organisms. Somatic evolution, including the development of cancer, takes place along thecell lineage treetraced out by these cell divisions. A fundamental question in cancer research is how the lifetime risk of cancer depends on the properties of an arbitrary cell lineage tree. Here we show that for small mutation rates (which is the case in reality) the distribution of the lineage lengths alone determines cancer risk, and that this risk can be described by a simple analytical formula. Our results have far-reaching implications not only for cancer research, but also for evolutionary biology in general.
A CRISPR-based genome-wide screen for adipogenesis reveals new insights into mitotic expansion and lipogenesis
Authors: Turn Rachel E. , Hilgendorf Keren I. , Johnson Carl T. , Han Kyuho , Rabiee Atefeh , Demeter Janos , Aziz-Zanjani Mohammad Ovais , Domizi Pablo , Cheng Ran , Zhu Yingdi , Jiang Zewen , Svensson Katrin J. , Bassik Michael C. , Jackson Peter K. 
Published: July 2020

SummaryIn response to excess nutrients, white adipose tissue expands by both generating new adipocytes and by upregulating lipogenesis in existing adipocytes. Here, we performed a genome-wide functional genomics screen to identify regulators of adipogenesis in the mouse 3T3-L1 preadipocyte model. The pooled screening strategy utilized FACS to isolate populations based on lipid content by gating for fluorescence intensity of the lipophilic, green fluorescent BODIPY dye. Additionally, the approach categorized if genes functioned during mitotic expansion or lipogenesis. Cellular mechanisms regulating the rate of protein translation and protein stability were found critical for adipogenesis and lipogenesis. These protein-directed mechanisms were further supported by proteomic analyses, which demonstrated that essential changes in protein abundance driving 3T3-L1 adipogenesis were not driven by transcription. We exemplify this theme by showing that the hypusination pathway, a conserved regulator of translation initiation, is critical to translate adipogenic inducers of mitotic expansion and that the neddylation/ubiquitin pathway modulates insulin sensitivity to regulate lipogenesis.
Transient receptor potential canonical 5 (TRPC5) mediates inflammatory mechanical pain
Authors: Sadler Katelyn E. , Moehring Francie , Shiers Stephanie I. , Laskowski Lauren J. , Mikesell Alexander R. , Plautz Zakary R. , Mecca Christina M. , Dussor Gregory , Price Theodore J. , McCorvy John D. , Stucky Cheryl L. 
Published: July 2020

AbstractPersistent tactile pain is a poorly managed symptom of inflammatory and neuropathic injury. To develop therapies for this maladaptive sensation, the underlying molecular mediators must be identified. Using knockout mice and pharmacological inhibitors, we identified transient receptor canonical 5 (TRPC5) as a key contributor to the persistent tactile pain that occurs in many inflammatory and neuropathic preclinical rodent models. TRPC5 inhibition was effective in injuries associated with elevated levels of the bioactive phospholipid lysophosphatidylcholine (LPC). Exogenous application of LPC induced TRPC5-dependent behavioral mechanical allodynia, neuronal mechanical hypersensitivity, and spontaneous pain.In vitro, LPC activated both homomeric mouse and human TRPC5 channels, which upon examination of human dorsal root ganglia tissue, were expressed in 75% of human sensory neurons. Based on these results, TRPC5 inhibitors should be pursued as personalized therapy for spontaneous and tactile pain in conditions where elevated LPC is a biomarker.
Structural basis of αE-catenin–F-actin catch bond behavior
Authors: Xu Xiao-Ping , Pokutta Sabine , Torres Miguel , Swift Mark F. , Hanein Dorit , Volkmann Niels , Weis William I. 
Published: July 2020

ABSTRACTCell-cell and cell-matrix junctions transmit mechanical forces during tissue morphogenesis and homeostasis. α-Catenin links cell-cell adhesion complexes to the actin cytoskeleton, and mechanical load strengthens its binding to F-actin in a direction-sensitive manner. This so-called catch bond behavior is described by a model in which force promotes a transition between weak and strong actin-bound states. We describe the cryo-electron microscopy structure of the F-actin-bound αE-catenin actin-binding domain, which in solution forms a 5-helix bundle. Upon binding to actin, the first helix of the bundle dissociates and the remaining four helices and connecting loops rearrange to form the interface with actin. Deletion of the N-terminal helix produces strong actin binding in the absence of force. Our analysis explains how mechanical force applied to αE-catenin or its homolog vinculin favors the strongly bound state, and the dependence of catch bond strength on the direction of applied force.
Persistent intestinal abnormalities and symptoms in cystic fibrosis: The underpinning mechanisms impacting gut health and motility. Protocol for a systematic review
Authors: Marsh R.J. , Ng C. , Major G. , Rivett D.W. , Smyth A. , van der Gast C.J. 
Published: July 2020

AbstractBackgroundPatients with cystic fibrosis (CF) are characterised by abnormalities of the intestinal tract relating to gut motility and physiological issues, with daily symptoms of disease including abdominal pain, flatulence, bloating, and constipation. With improvements in respiratory outcomes, a shift in disease manifestations has highlighted the prevalence of the gastrointestinal-related problems associated with CF, yet most therapies currently in clinical use for the gut symptoms of CF have been repurposed from other disease indications and have not been developed with a knowledge of the mechanisms underpinning gastrointestinal disease in CF. Increased attention towards the role of intestinal inflammation and microbial dysbiosis in the CF population warrants a comprehensive knowledge of these aspects alongside the increased luminal fat content, dysmotility, and small intestinal bacterial overgrowth (SIBO) resultant of the primary consequences of CFTR dysfunction (disrupted fluid secretion and pancreatic insufficiency), and how they contribute towards the intestinal complications of CF disease.Methods and Study DesignWe will conduct a systematic review to comprehensively address our current understanding of the primary consequences of CFTR dysfunction, and their subsequent secondary effects that contribute towards the disruption of gut motility, health, and associated symptoms in the CF intestine. Databases searched will include PubMed, CINAHL, MEDLINE and the Cochrane library from 1939 until a specified date of last search, alongside clinical trial databases for ongoing studies. Search strategies will include various terminology that relates to the primary mechanistic defects of CF, postulated secondary effects of such defects, and symptoms experienced in patients. A full search strategy is outlined in appendix B. One reviewer will apply an inclusion criterion to obtained abstracts. Following agreement from a second reviewer, full-text articles will be sought, and data will be extracted from relevant articles. Disagreements will be resolved with a third reviewer. The quality of data will be assessed by the GRADE criteria. Data will be used to present a narrative, and where possible, quantitative synthesis.DiscussionThis systematic review will discuss our current understanding of the underpinning mechanisms of the persisting abnormalities in gut health and motility within CF, addressing potential intricate relationships that further contribute to disease progression within the intestinal tract. Furthermore, we will identify current gaps in the literature to propose directions for future research. A comprehensive understanding of these aspects in relation to intestinal abnormalities will aid future clinical directions.
Modelling theWolbachiaIncompatible Insect Technique: strategies for effective mosquito population elimination
Authors: Pagendam D.E. , Trewin B.J. , Snoad N. , Ritchie S.A. , Hoffmann A.A. , Staunton K.M. , Paton C. , Beebe N. 
Published: July 2020

AbstractTheWolbachiaIncompatible Insect Technique (IIT) shows promise as a method for eliminating invasive mosquitoes such asAedes aegypti(Linnaeus)(Diptera: Culicidae) and reducing the incidence of vector-borne diseases such as dengue, chikungunya and Zika. Successful implementation of this biological control strategy relies on high-fidelity separation of male from female insects in mass production systems for inundative release into landscapes. Processes for sex-separating mosquitoes are typically error prone, laborious and IIT programs run the risk of releasingWolbachiainfected females and replacing wild mosquito populations. We introduce a simple Markov Population Process (MPP) model for studying mosquito populations subjected to aWolbachia-IIT program which exhibit an unstable equilibrium threshold. The model is used to study,in silico, scenarios that are likely to yield a successful elimination result. Our results suggest that elimination is best achieved by releasing males at rates that adapt to the ever-decreasing wild population, thus reducing the risk of releasingWolbachia-infected females while reducing costs. While very high-fidelity sex-separation is required to avoid establishment, release programs tend to be robust to the release of a small number ofWolbachia-infected females. These findings will inform and enhance the next generation ofWolbachia-IIT control strategies that are already showing great promise in field trials.
Development of a severity of disease score and classification model by machine learning for hospitalized COVID-19 patients
Authors: Marcos Miguel , Belhassen-García Moncef , Sánchez-Puente Antonio , Sampedro-Gomez Jesús , Azibeiro Raúl , Dorado-Díaz P-Ignacio , Marcano-Millán Edgar , García-Vidal Carolina , Moreiro-Barroso Maria-Teresa , Cubino-Bóveda Noelia , Pérez-García María-Luisa , Rodríguez-Alonso Beatriz , Encinas-Sánchez Daniel , Peña-Balbuena Sonia , Sobejano-Fuertes Eduardo , Inés Sandra , Carbonell Cristina , Lopez-Parra Miriam , Andrade-Meira Fernanda , López-Bernús Amparo , Lorenzo Catalina , Carpio Adela , Polo-San-Ricardo David , Sánchez-Hernández Miguel-Vicente , Borrás Rafael , Sagredo-Meneses Víctor , Sanchez Pedro-L , Soriano Alex , Martín-Oterino José-Ángel 
Published: July 2020

AbstractBACKGROUNDEfficient and early triage of hospitalized Covid-19 patients to detect those with higher risk of severe disease is essential for appropriate case management.METHODSWe trained, validated, and externally tested a machine-learning model to early identify patients who will die or require mechanical ventilation during hospitalization from clinical and laboratory features obtained at admission. A development cohort with 918 Covid-19 patients was used for training and internal validation, and 352 patients from another hospital were used for external testing. Performance of the model was evaluated by calculating the area under the receiver-operating-characteristic curve (AUC), sensitivity and specificity.RESULTSA total of 363 of 918 (39.5%) and 128 of 352 (36.4%) Covid-19 patients from the development and external testing cohort, respectively, required mechanical ventilation or died during hospitalization. In the development cohort, the model obtained an AUC of 0.85 (95% confidence interval [CI], 0.82 to 0.87) for predicting severity of disease progression. Variables ranked according to their contribution to the model were the peripheral blood oxygen saturation (SpO2)/fraction of inspired oxygen (FiO2) ratio, age, estimated glomerular filtration rate, procalcitonin, C-reactive protein, updated Charlson comorbidity index and lymphocytes. In the external testing cohort, the model performed an AUC of 0.83 (95% CI, 0.81 to 0.85). This model is deployed in an open source calculator, in which Covid-19 patients at admission are individually stratified as being at high or non-high risk for severe disease progression.CONCLUSIONSThis machine-learning model, applied at hospital admission, predicts risk of severe disease progression in Covid-19 patients.
MIND diet associated with later onset of Parkinson’s disease
Authors: Metcalfe-Roach A , Yu AC , Golz E , Sundvick K , Cirstea MS , Kliger D , Foulger LH , Mackenzie M , Finlay BB , Appel-Cresswell S 
Published: July 2020

ABSTRACTBackgroundThe MIND diet has been linked with prevention of Alzheimer’s disease and cognitive decline but has not been fully assessed in the context of Parkinson’s disease (PD).ObjectiveTo determine whether MIND diet adherence is associated with the age of Parkinson’s disease onset in a manner superior to that of the Mediterranean diet.MethodsFood Frequency Questionnaires from 167 participants with PD and 119 controls were scored for MIND and two versions of Mediterranean diet adherence. Scores were compared between sex and disease subgroups, and PD diet adherence was correlated with age of onset using univariate and multivariate linear models.ResultsThe female subgroup adhered more closely to the MIND diet than the males, and diet scores were not modified by disease status. Later age of onset correlated most strongly with MIND diet adherence in the female subgroup, corresponding to differences of up to 17.4 years (p<0.001) between low and high dietary tertiles. Greek Mediterranean adherence was also significantly associated with later PD onset across all models (p=0.05-0.03). Conversely, only Greek Mediterranean adherence remained correlated with later onset across all models in men, with differences of up to 8.4 years (p=0.002).ConclusionsThis cross-sectional study finds a strong correlation of age of onset of PD with dietary habits, suggesting that nutritional strategies may be an effective tool to delay PD onset. Further studies may help to elucidate potential nutrition-related sex-specific pathophysiological mechanisms and differential prevalence rates in PD.