bluuebunny/crossref_metadata_2025_split huggingface dataset:
Translational Oncogenomics and Human Cancer Interactome Networks
Authors: Baianu I. 
Published: July 2019

AbstractAn overview of translational, human oncogenomics, transcriptomics and cancer interactomic networks is presented together with basic concepts and potential, new applications to Oncology and Integrative Cancer Biology. Novel translational oncogenomics research is rapidly expanding through the application of advanced technology, research findings and computational tools/models to both pharmaceutical and clinical problems. A self-contained presentation is adopted that covers both fundamental concepts and the most recent biomedical, as well as clinical, applications. Sample analyses in recent clinical studies have shown that gene expression data can be employed to distinguish between tumor types as well as to predict outcomes. Potentially important applications of such results are individualized human cancer therapies or, in general, ‘personalized medicine’. Several cancer detection techniques are currently under development both in the direction of improved detection sensitivity and increased time resolution of cellular events, with the limits of single molecule detection and picosecond time resolution already reached. The urgency for the complete mapping of a human cancer interactome with the help of such novel, high-efficiency / low-cost and ultra-sensitive techniques is also pointed out.
Soluble oligomerization provides a beneficial fitness effect on destabilizing mutations.
Authors: Bershtein Shimon , Shakhnovich Eugene 
Published: July 2019

AbstractProtein stability is widely recognized as a major evolutionary constraint. However, the relation between mutation-induced perturbations of protein stability and biological fitness has remained elusive. Here we explore this relation by introducing a selected set of mostly destabilizing mutations into an essential chromosomal gene of E.coli encoding dihydrofolate reductase (DHFR) to determine how changes in protein stability, activity and abundance affect fitness. Several mutant strains showed no growth while many exhibited fitness higher than wild type. Overexpression of chaperonins (GroEL/ES) buffered the effect of mutations by rescuing the lethal phenotypes and worsening better-fit strains. Changes in stability affect fitness by mediating the abundance of active and soluble proteins; DHFR of lethal strains aggregates, while destabilized DHFR of high fitness strains remains monomeric and soluble at 30oC and forms soluble oligomers at 42oC. These results suggest an evolutionary path where mutational destabilization is counterbalanced by specific oligomerization protecting proteins from aggregation.
Power-law behavior reveals phase transitions in landscape controls of fire regimes
Authors: McKenzie Donald , Kennedy Maureen 
Published: July 2019

AbstractIn low-severity fire regimes of the American West and elsewhere, landscape memory of fire events is registered in fire-scarred trees, with temporal record lengths often exceeding 200 years^1-5^. Understanding the environmental controls on historical wildfires, and how they changed across spatial scales, is difficult because there are no surviving explicit records of either weather or vegetation (fuels). We show how power laws associated with fire-event time series arise in limited domains of parameters that represent critical transitions in the controls on landscape fire. We used stochastic simulations iteratively with Monte Carlo inference to replicate the spatio-temporal structure of historical fire-scar records in forested watersheds of varying topographic complexity. We find that the balance between endogenous and exogenous controls on fire spread shifts with topographic complexity, where in the most complex landscapes the endogenous controls dominate and the pattern exhibits criticality. Comparison to an self-organized criticality (SOC) model^6,7^ shows that the latter mimics historical fire only in a limited domain of criticality, and is not an adequate mechanism to explain landscape fire dynamics, which are shaped by both endogenous and exogenous controls. Our results identify a continuous phase transition in landscape controls, marked by power laws, and provide an ecological analogue to critical behavior in physical and chemical systems^8-11^. This explicitly cross-scale analysis provides a paradigm for identifying critical thresholds in landscape dynamics that may be crossed in a rapidly changing climate.
Human Cancer Cells Express Slug-based Epithelial-Mesenchymal Transition Gene Signature Obtained in Vivo
Authors: Kandel Jessica , Anastassiou Dimitris , Rumjantseva Viktoria , Cheng Wei-yi , Huang Jianzhong , Canoll Peter , Yamashiro Darrell 
Published: July 2019

AbstractThe biological mechanisms underlying cancer cell motility and invasiveness remain unclear, although it has been hypothesized that they involve some type of epithelial-mesenchymal transition (EMT). Here we show that human cancer cells express in vivo a precise multi-cancer invasion-associated gene expression signature characterized by the prominent presence of collagen COL11A1 and thrombospondin THBS2. The signature is present in the expression of all solid tumor datasets that we analyzed and includes numerous EMT markers, among them the transcription factor Slug, fibronectin, and α SMA. Using xenograft models of human cancer cells in immunocompromised mice and profiling the harvested tumors separately with species specific probes, we found that human, but not mouse, cells express most of the genes of the signature and Slug is the only upregulated EMT-inducing transcription factor. Taken together with the presence of the signature in many publicly available datasets, our results suggest that this Slug based EMT signature is produced by the cancer cells themselves in multiple cancer types, including even nonepithelial cancers such as neuroblastoma. Furthermore, we found that the presence of the signature in human xenografted cells was associated with a downregulation of adipocyte markers in the mouse tissue adjacent to the invasive tumor, suggesting contextual microenvironmental interactions when the cancer cells encounter adipocytes, as previously reported. The known and consistent gene composition of this cancer EMT signature, particularly when combined with simultaneous analysis of the adjacent microenvironment, provides unique opportunities for shedding light on the underlying mechanisms of cancer invasiveness as well as identifying potential diagnostic markers and targets for metastasis-inhibiting therapeutics.
Synaptic state matching: a dynamical architecture for predictive internal representation and feature perception
Authors: Tavazoie Saeed 
Published: July 2019

AbstractHere we consider the possibility that a fundamental function of sensory cortex is the generation of an internal simulation of sensory environment in real-time. A logical elaboration of this idea leads to a dynamical neural architecture that oscillates between two fundamental network states, one driven by external input, and the other by recurrent synaptic drive in the absence of sensory input. Synaptic strength is modified by a proposed synaptic state matching (SSM) process that ensures equivalence of spike statistics between the two network states. Remarkably, SSM, operating locally at individual synapses, generates accurate and stable network-level predictive internal representations, enabling pattern completion and unsupervised feature detection from noisy sensory input. SSM is a biologically plausible substrate for learning and memory because it brings together sequence learning, feature detection, synaptic homeostasis, and network oscillations under a single parsimonious computational framework. Beyond its utility as a potential model of cortical computation, artificial networks based on this principle have remarkable capacity for internalizing dynamical systems, making them useful in a variety of application domains including time-series prediction and machine intelligence.
BioenergyProduction From Plant Biomass: Bioethanol From Concept To Reality
Authors: Khan Israr , Akhtar Muhammad Waheed 
Published: July 2019

AbstractNatural energy reserves like petrol and diesel etc are depleting. As such, it is of paramount importance to find alternative fuels. Solar energy is trapped as biomass in plants. Biomass provide an excellent reserve for trapping solar energy on field. Complex enzymatic machinery comprising of hydrolytic reactions and consolidated bioprocessing is needed to make viable bioenergy, mostly biofuels like bioethanol for locomotives, industries and general use in the future.
Statistical analysis of protein molecules
Authors: Shah Kushal 
Published: July 2019

AbstractIn this paper, entropy and auto-correlation values of main chain dihedral angles of 22,356 protein molecules are calculated and found to lie within a well-specified range for most proteins. Also, the entropy values obey a Gaussian distribution, which indicates that entropy plays a crucial role in evolution and conservation of protein tertiary structures. A comparison of the auto-correlation values of the dihedral angles of the entire protein molecule with those of the alpha helices and beta sheets indicates that random coils play an important role in determining the tertiary structure of protein molecules.
PrionOme: A database of prions and other sequences relevant to prion phenomena
Authors: Sowdhamini Ramanathan , Harrison Paul , Harbi Djamel , Parthiban Marimuthu , Gendoo Deena , Ehsani Sepehr , Kumar Manish , Schmitt-Ulms Gerold 
Published: July 2019

AbstractPrions are units of propagation of an altered state of a protein or proteins. Prions can propagate from cell to cell, and from organism to organism, through cooption of other protein copies. Prions contain no necessary nucleic acids, and are important both as both pathogenic agents, and as a potential force in epigenetic phenomena. The original prions were derived from a misfolded form of the mammalian Prion Protein PrP. Infection by these prions causes neurodegenerative diseases. Other prions cause non-Mendelian inheritance in budding yeast, and sometimes act as diseases of yeast. We have compiled a database of >2000 prion-related sequences, called the PrionOme. The database comprises seven PrionOme classification categories: prionogenic sequences (i.e., sequences that can make prions), ‘prionoids’ (i.e., phenomena that have some prion characteristics), orthologs, paralogs, pseudogenes, prion interactors, and prion-like molecules. Database entries list: supporting information for PrionOme classifications, prion-determinant areas (where relevant), and disordered and compositionally-biased regions. Also included are original references for the PrionOme classifications, transcripts and genomic coordinates, and structural data (including comparative models). We provide database usage examples for both vertebrate and fungal prion contexts. As development of this resource is on-going, we will be very happy to receive and act on any constructive comments from peer scientists in the areas of prion biology and protein misfolding, either by email or using the feedback form provided on the PrionOme website. We hope that this database will be a valuable experimental aid and reference resource. It is freely available at: http://libaio.biol.mcgill.ca/prion.
Isoglitter
Authors: Bucknum Michael , Castro Eduardo , Wen Bin 
Published: July 2019

AbstractDescribed herein is a novel crystalline pattern in space group Ammm, that is a model of a C allotrope. This so-called isoglitter structure-type is a model of a graphite-diamond hybrid. A DFT geometry optimization and band structure calculation indicates that the lattice is metallic in a C realization.
Antidepressant suppression of REM and spindle sleep impairs hippocampus-dependent learning and memory but fosters striatal-dependent strategies
Authors: Watts Alain , Gritton Howard , Sweigart Jamie , Poe Gina 
Published: July 2019

AbstractREM sleep enhances hippocampus-dependent associative memory but has little impact on striatal-dependent procedural learning. Antidepressant medications like desipramine (DMI) inhibit rapid-eye-movement (REM) sleep but it is little understood how antidepressant treatments affect learning. We found that DMI strongly suppressed REM sleep in rats for several hours and impaired reconsolidation of a familiar maze and consolidation of moved baited positions (reversal learning) in a sleep-dependent fashion. Unexpectedly, DMI also reduced the spindle-rich transition-to-REM sleep state (TR) and spatial memory changes were more related to TR than to REM sleep. Working memory was unaffected, but overnight reference memory was significantly impaired and subjects increased reliance on non-hippocampal strategies. Procedural memory performance was positively correlated with increases in non-REM sleep after DMI serving to offset memory declines, partially preserving performance. Our results suggest that familiar memories are re-consolidated during REM sleep, reversal memories consolidated during TR, and procedural memories consolidated during non-REM sleep.
Slug-based epithelial-mesenchymal transition gene signature is associated with prolonged time to recurrence in glioblastoma
Authors: Cheng Wei-Yi , Kandel Jessica , Yamashiro Darrell , Canoll Peter , Anastassiou Dimitris 
Published: July 2019

Abstract
Background
We previously identified a precise stage-associated gene expression signature of coordinately expressed genes, including the transcription factor Slug (SNAI2) and other epithelial mesenchymal transition (EMT) markers, present in samples from publicly available gene expression datasets in multiple cancer types. The expression levels of the co-expressed genes vary in a continuous and coordinate manner across the samples, ranging from absence of expression to strong co-expression of all genes. These data suggest that tumor cells may pass through an EMT like process of mesenchymal transition to varying degrees.Findings Here we show that this signature in glioblastoma multiforme (GBM) is associated with time to recurrence following initial treatment. By analyzing data from The Cancer Genome Atlas (TCGA), we found that GBM patients who responded to therapy and had long time to recurrence had low levels of the signature in their tumor samples (P = 3x10^-7^). We also found that the signature is strongly correlated in gliomas with the putative stem cell marker CD44, and is highly enriched among the differentially expressed genes in glioblastomas vs. lower grade gliomas.

Conclusions
Our results suggest that long delay before tumor recurrence is associated with absence of the mesenchymal transition signature, raising the possibility that inhibiting this transition might improve the durability of therapy in glioma patients.
A similarity criterion for forest growth curves
Authors: Alexandrov Georgii , Golitsyn Georgy 
Published: July 2019

AbstractComparison of forest growth curves has led many to the conclusion that there is a similarity between forest stands growing in different conditions. Here we treat the same subject from the viewpoint of similarity theory. Our goal is to form a dimensionless ratio of biophysical entities that could parameterize the diversity of forest growth curves. (Such ratios are called similarity criteria.) Pursuing this goal, we focus on the analogy between tree crown growth and atomic explosion. A blast wave is formed when the rate of energy release is much higher than the rate of energy dissipation. The difference between the rates of energy release and dissipation is the essence of this phenomenon. The essential feature of crown growth is the difference between the rates of non-structural carbohydrate supply and demand. Since the rate of supply is much higher than the rate of demand, the flow of non-structural carbohydrates achieves the tips of branches and enables the radial growth of crown. Proceeding from these ideas, we derived the similarity criterion which supposedly captures the “essence of growth” that emerges from the geometric similarity of tree crowns.
Food Physical Chemistry and Biophysical Chemistry
Authors: Baianu I.C. 
Published: July 2019

AbstractFood Physical Chemistry is considered to be a branch of Food Chemistry^1,2^ concerned with the study of both physical and chemical interactions in foods in terms of physical and chemical principles applied to food systems, as well as the applications of physical/chemical techniques and instrumentation for the study of foods^3,4,5,6^. This field encompasses the "physiochemical principles of the reactions and conversions that occur during the manufacture, handling, and storage of foods"^7^. Two rapidly growing, related areas are Food Biotechnology and Food Biophysical Chemistry.
Variability of Mauna Loa melt inclusions
Authors: Armienti Pietro , Gasperini Daniela 
Published: July 2019

AbstractA major element of variability of olivine melt inclusions in Mauna Loa lavas is here proved to be strictly related to olivine crystallization at inclusion walls, at low pressure and decreasing temperature.In so doing it is probably worth it to interpret trace elements and isotope variability in these olivine trapped liquids as the effect of disequilibrium (isotope) fractionation. In this respect, the accurate analytical work performed by Sobolev et al. (2011) does not document the presence of a heterogeneous source, rather representing a tool to explore poorly documented aspects of magmatic crystallization that are controlled by the kinetics of liquid-solid phase transition.
Trans-Disciplinary Protein Binding Of Drug: Docking Approach
Authors: Ajeet Ajeet 
Published: July 2019

AbstractThe purpose of present work is to introduce the binding of existing drugs to the trans-disciplinary protein with the help of docking procedures. Docking procedures allows virtually screening a database of compounds and predict the strongest binder based on various scoring functions. This work has been performed with the help of Molegro Virtual docker, in which two drugs are docked with their corresponding and non-corresponding (trans-disciplinary) protein. Results reveals that the protein-ligand interaction energy, hydrogen bond energy and MolDock scores provided by molegro virtual docker, between legands (Levodopa and Acyclovir) and trans-disciplinary proteins have been equivalent or even better than that of between legands and corresponding proteins.
Determinative atom model and the nature of chemical bond
Authors: Hu Wanchung 
Published: July 2019

AbstractQuantum mechanics including Schrodinger and Dirac’s equations are used to describe the atom model. However, the basic assumption assuming electron energy can be described by E=h’w is wrong. If E=h’w, then the total energy of the electron will be E=rmv^2 in contrary to E=rmc^2 from special relativity. Here, I propose a new atom model integrating frame-dragging force, centrifugal force, electrostatic force, and magnetic force. In this new model, the proton group and neutron group in atomic nucleus are rotating in different direction. Thus, they provide equal and opposite frame-dragging force for orbiting electrons. The electrons are orbiting in the equator plane of nucleus. There is no net force or net acceleration for electrons to allow electrons for stable orbiting. 1.Electrostatic force from protons balances centrifugal force. 2. Electrostatic force from paired electron itself balances magnetic force from spinning electrons. 3. No net frame-dragging force from proton group and neutron group. In addition, by using De Brodglie’s matter wave and standing wave concept, we can explain the atomic magic number 2,8,8,18,18,32,32. The electron is basically a particle, but it moves like a wave. By using this atom model, we can explain the chemical structure and the nature of chemical bond formation.
Ultrasonically sculpted virtual relay lens for in situ microimaging
Authors: Scopelliti Matteo Giuseppe , Chamanzar Maysamreza 
Published: July 2019

AbstractWe demonstrate in situ non-invasive relay imaging through a medium without inserting physical optical components. We show that a virtual optical graded-index (GRIN) lens can be sculpted in the medium using in situ reconfigurable ultrasonic interference patterns to relay images through the medium. Ultrasonic wave patterns change the local density of the medium to sculpt a graded refractive index pattern normal to the direction of light propagation, which modulates the phase front of light, causing it to focus within the medium and effectively creating a virtual relay lens. We demonstrate the in situ relay imaging and resolving of small features (22 µm) through a turbid medium (optical thickness = 5.7 times the scattering mean free path), which is normally opaque. The focal distance and the numerical aperture of the sculpted optical GRIN lens can be tuned by changing the ultrasonic wave parameters. As an example, we experimentally demonstrate that the axial focal distance can be continuously scanned over a depth of 5.4 mm in the modulated medium and that the numerical aperture can be tuned up to 21.5%. The interaction of ultrasonic waves and light can be mediated through different physical media, including turbid media, such as biological tissue, in which the ultrasonically sculpted GRIN lens can be used for relaying images of the underlying structures through the turbid medium, thus providing a potential alternative to implanting invasive endoscopes.
Autophagosome accumulation-mediated ATP energy deprivation induced by penfluridol triggers nonapoptotic cell death of lung cancer via activating unfolded protein response
Authors: Hung Wen-Yueh , Chang Jer-Hwa , Cheng Yu , Cheng Guo-Zhou , Huang Hsiang-Ching , Hsiao Michael , Chung Chi-Li , Lee Wei-Jiunn , Chien Ming-Hsien 
Published: July 2019

AbstractAnticancer chemotherapeutic drugs mainly trigger apoptosis induction to eliminate malignant cells. However, many cancer cells are chemoresistant because of defective apoptosis induction. Targeting the autophagic pathway is currently regarded as an alternative strategy for cancer drug discovery. Penfluridol, an antipsychotic drug, has been reported to exert oncostatic effects, but the effect of penfluridol on lung cancer remains unknown. Herein, the antitumor activity of penfluridol was determined in vitro in non-small-cell lung cancer (NSCLC) cell lines using MTS, plate clonogenic, and transwell migration assays and in vivo in an orthotopic xenograft model. Flow cytometry, holotomographic microscopy, immunofluorescence, and immunohistochemistry were employed to determine the cell-death phenotype induced by penfluridol in vitro and in vivo. Western blotting and genetic knockdown by small interfering RNA were performed to explore the underlying mechanisms involved in penfluridol-mediated cell death. We uncovered that penfluridol inhibited the viability and motility of NSCLC cells in vitro and in vivo. Penfluridol induced nonapoptotic cell death by blocking autophagic flux and inducing accumulation of autophagosome-related protein, light chain 3 (LC3) B-II, in HCC827 and A549 NSCLC cells, and in an A549 orthotopic xenograft tumor model. Autophagosome accumulation-induced cell viability inhibition by penfluridol was mainly attributed to ATP energy deprivation. Moreover, we observed that patients with lung tumors expressing high LC3B had longer overall and disease-free survival times. Mechanistically, upregulation of endoplasmic reticulum (ER) stress-induced unfolded protein response (UPR) pathways and activation of p38 mitogen-activated protein kinase (MAPK) were critical for penfluridol-induced autophagosome accumulation. Our findings identify that penfluridol acts as an inducer of ER stress and p38 MAPK activation, which led to UPR-mediated nonapoptotic cell death via autophagosome accumulation-caused energy loss. Penfluridol is clinically used for schizophrenia, and our study results strongly support penfluridol as a repurposed drug for treating NSCLC.