bluuebunny/crossref_metadata_2025_split huggingface dataset:
Accurate 3-gene-signature for early diagnosis of liposarcoma progression
Authors: Serguienko Anastassia , Braadland Peder , Meza-Zepeda Leonardo A. , Bjerkehagen Bodil , Myklebost Ola 
Published: March 2020

Abstract
Background
Well- and dedifferentiated liposarcoma (WD/DDLPS) are rare mesenchymal malignant tumors that account for 20% of all sarcomas in adults. The WD form is a low-grade malignancy with a favourable prognosis which may progress to DDLPS, a high-grade aggressive counterpart. WDLPS is referred to as atypical lipomatous tumour (ALT) when localised in extremities, due to its better prognosis. Currently the final differential diagnosis to distinguish between more aggressive and less aggressive form is based on post-surgical histological examination and no molecular biomarkers for early detection are available.

Methods
Quantitative polymerase chain reaction (qPCR) analysis of 11 metabolic genes involved in general and adipose tissue-specific metabolism, was performed on ALT (= 8), WDLPS (= 9) and DDLPS (= 20) samples. Subsequent statistical analysis was carried out to determine genes that most accurately can predict DDLPS differential diagnosis. Selected genes were further validated in a separate cohort by qPCR and the data statistically analysed. Deep sequencing was performed on DDLPS specimen from the metastatic patient and on five random WDLPS specimens.

Results
We established a three-gene signature based on PNPLA2, LIPE and PLIN1, which identified DDLPS with 100% sensitivity and 90% specificity, even in specimens from the WD component of DDLPS tumors. Interestingly, the PNPLA2 gene is deleted in 45% of DDLPS samples analyzed under TCGA project, and the deletion is associated with significantly lower PNPLA2 expression level. However, other mechanisms causing loss or downregulation of the expression of these three genes may be involved. Moreover, the significantly lower level of PNPLA2 is associated with R1 surgical margins, compare to R0 margins, which suggests the more invasive tumor phenotype in the absence of PNPLA2.

Conclusions
The identified metabolic signature allows highly accurate differential diagnosis between WD- and DDLPS even in samples containing lipid droplets, a marker of differentiation, which makes it very suitable for the use on biopsies. In respect to the pathogenesis of the disease, our results give a new insight into possible molecular mechanisms involved and support the recent observation that deletion of PNPLA2 is a novel factor in liposarcoma progression.
Minimal residual ordinal loss hashing with an adaptive optimization mechanism
Authors: Wang Zhen , Sun Fuzhen , Zhang Longbo , Liu Pingping 
Published: March 2020

AbstractThe binary coding technique has been widely used in approximate nearest neighbors (ANN) search tasks. Traditional hashing algorithms treat binary bits equally, which usually causes an ambiguous ranking. To solve this issue, we propose an innovative bitwise weight method dubbed minimal residual ordinal loss hashing (MROLH). Different from a two-step mechanism, MROLH simultaneously learns binary codes and bitwise weights by a feedback mechanism. When the algorithm converges, the binary codes and bitwise weights can be well adaptive to each other. Furthermore, we establish the ordinal relation preserving constraint based on quartic samples to enhance the power of preserving relative similarity. To decrease the training complexity, we utilize a tensor ordinal graph to represent quartic ordinal relation, and the original objective function is approximated by the one based on triplet samples. In this paper, we also assign different weight values to training samples. During the training procedure, the weight of each data is initialized to the same value, and we iteratively boost the weight of the data whose relative similarity is not well preserved. As a result, we can minimize the residual ordinal loss. Experimental results on three large-scale ANN search benchmark datasets, i.e., SIFT1M, GIST1M, and Cifar10, show that the proposed method MROLH achieves a superior ANN search performance in both the Hamming space and the weighted Hamming space over the sate-of-the-art approaches.
Protocol for a systematic review and meta-analysis on the effect of hippotherapy and related equine-assisted therapies on motor capabilities in children with cerebral palsy
Authors: Häusler Martin , Heussen Nicole 
Published: March 2020

Abstract
Background
Equine-assisted treatments of the motor system appear to have an effect on the neuromuscular system and aim to improve the pathological condition of children with cerebral palsy. Hippotherapy is a distinct form of equine-assisted therapy where certified physiotherapists use the horse as a dynamic tool in a medical treatment setting. The objective of the proposed review is to summarize and critically appraise the evidence on the effect of equine-assisted treatments on motor capabilities of children with cerebral palsy.

Methods
We will identify trials through systematic searches of PubMed, Embase, Web of Science, and the Cochrane Central Register of Controlled Trials (CENTRAL). Quality assessment of retrieved articles will be conducted using the criteria outlined in the revised tool to assess risk of bias in randomized trials (RoB 2.0) or the ROBINS-I tool (Risk Of Bias In Non-randomized Studies - of interventions), respectively. Quantitative data synthesis will be performed if treatments, participants, and the underlying clinical question are homogenous and provide adequate outcome data for meta-analysis. Otherwise, data will be synthesized, using the narrative synthesis approach.

Conclusion
This review will provide a critical summary of the evidence regarding the impact of equine-assisted treatments on motor capabilities of children with cerebral palsy. The result from this review will help to inform healthcare practitioners and policymakers on the additional effect of equine-assisted treatments on reducing the burden of cerebral palsy among children.

Systematic review registration
This systematic review protocol is registered with the International Prospective Register of Systematic Reviews (PROSPERO). Registration number: CRD42018096403. This protocol was prepared using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Protocols checklist (PRISMA-P).
Ground states for planar axially Schrödinger–Newton system with an exponential critical growth
Authors: Wang Wenbo , Li Quanqing , Li Yongkun 
Published: March 2020

AbstractIn this paper, we study the following planar Schrödinger–Newton system: $$ \left \{ \textstyle\begin{array}{l} -\Delta u+ V(x)u+\lambda\phi u= f(x,u)\quad \textrm{in } \mathbb{R}^{2},\\ \Delta\phi=u^{2}\quad\textrm{in } \mathbb{R}^{2}, \end{array}\displaystyle \right . $${−Δu+V(x)u+λϕu=f(x,u)in R2,Δϕ=u2in R2, where V, f are axially symmetric about x, V is positive, and f is super-linear at zero and exponential critical at infinity. Using a weaker condition $$ \biggl[\frac{f(x,u)}{u^{3}}-\frac{f(x,tu)}{(tu)^{3}} \biggr]\operatorname {sign}(1-t)+ \theta V(x)\frac{ \vert 1-t^{2} \vert }{(tu)^{2}}\geq0,\quad \forall x\in \mathbb{R}^{2}, t>0, u\neq0 $$[f(x,u)u3−f(x,tu)(tu)3]sign(1−t)+θV(x)|1−t2|(tu)2≥0,∀x∈R2,t>0,u≠0 with $\theta\in[0,1)$θ∈[0,1) instead of the Nehari type monotonic condition on $\frac{f(x,u)}{|u|^{3}}$f(x,u)|u|3, we obtain a ground state solution of the above problem via variational methods.
Sufficient conditions for regular solvability of an arbitrary order operator-differential equation with initial-boundary conditions
Authors: Faried Nashat , Ahmed Abdel Baset I. , Labeeb Mohamed A. 
Published: March 2020

AbstractOn this paper, for an arbitrary order operator-differential equation with the weight $e^{\frac{-\alpha t}{2}}, \alpha \in (-\infty ,+ \infty )$e−αt2,α∈(−∞,+∞), in the space $W^{n+m}_{2}(R_{+};H)$W2n+m(R+;H), we attain sufficient conditions for the well-posedness of a regular solvable of the boundary value problem. These conditions are provided only by the operator coefficients of the investigated equation where the leading part of the equation has multiple characteristics. We prove the connection between the lower bound of the spectrum of the higher-order differential operator in the main part and the exponential weight and also obtain estimations of the norms of operator intermediate derivatives. We apply the results of this paper to a mixed problem for higher-order partial differential equations (HOPDs).
ConvLSTMConv network: a deep learning approach for sentiment analysis in cloud computing
Authors: Ghorbani Mohsen , Bahaghighat Mahdi , Xin Qin , Özen Figen 
Published: March 2020

AbstractThe rapid development of social media, and special websites with critical reviews of products have created a huge collection of resources for customers all over the world. These data may contain a lot of information including product reviews, predicting market changes, and the polarity of opinions. Machine learning and deep learning algorithms provide the necessary tools for intelligence analysis in these challenges. In current competitive markets, it is essential to understand opinions, and sentiments of reviewers by extracting and analyzing their features. Besides, processing and analyzing this volume of data in the cloud can increase the cost of the system, strongly. Fewer dependencies on expensive hardware, storage space, and related software can be provided through cloud computing and Natural Language Processing (NLP). In our work, we propose an integrated architecture of Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) network to identify the polarity of words on the Google cloud and performing computations on Google Colaboratory. Our proposed model based on deep learning algorithms with word embedding technique learns features through a CNN layer, and these features are fed directly into a bidirectional LSTM layer to capture long-term feature dependencies. Then, they can be reused from a CNN layer to provide abstract features before final dense layers. The main goal for this work is to provide an appropriate solution for analyzing sentiments and classification of the opinions into positive and negative classes. Our implementations show that found on the proposed model, the accuracy of more than 89.02% is achievable.
Predictable modulation of cancer treatment outcomes by the gut microbiota
Authors: Heshiki Yoshitaro , Vazquez-Uribe Ruben , Li Jin , Ni Yueqiong , Quainoo Scott , Imamovic Lejla , Li Jun , Sørensen Maria , Chow Billy K. C. , Weiss Glen J. , Xu Aimin , Sommer Morten O. A. , Panagiotou Gianni 
Published: March 2020

AbstractThe gut microbiota has the potential to influence the efficacy of cancer therapy. Here, we investigated the contribution of the intestinal microbiome on treatment outcomes in a heterogeneous cohort that included multiple cancer types to identify microbes with a global impact on immune response. Human gut metagenomic analysis revealed that responder patients had significantly higher microbial diversity and different microbiota compositions compared to non-responders. A machine-learning model was developed and validated in an independent cohort to predict treatment outcomes based on gut microbiota composition and functional repertoires of responders and non-responders. Specific species, Bacteroides ovatus and Bacteroides xylanisolvens, were positively correlated with treatment outcomes. Oral gavage of these responder bacteria significantly increased the efficacy of erlotinib and induced the expression of CXCL9 and IFN-γ in a murine lung cancer model. These data suggest a predictable impact of specific constituents of the microbiota on tumor growth and cancer treatment outcomes with implications for both prognosis and therapy.
Meta-analysis of human prefrontal cortex reveals activation of GFAP and decline of synaptic transmission in the aging brain
Authors: Wruck Wasco , Adjaye James 
Published: March 2020

AbstractDespite ongoing research efforts, mechanisms of brain aging are still enigmatic and need to be elucidated for a better understanding of age-associated cognitive decline. The aim of this study is to investigate aging in the prefrontal cortex region of human brain in a meta-analysis of transcriptome datasets. We analyzed 591 gene expression datasets pertaining to female and male human prefrontal cortex biopsies of distinct ages. We used hierarchical clustering and principal component analysis (PCA) to determine the influence of sex and age on global transcriptome levels. In sex-specific analysis we identified genes correlating with age and differentially expressed between groups of young, middle-aged and aged. Pathways and gene ontologies (GOs) over-represented in the resulting gene sets were calculated. Potential causal relationships between genes and between GOs were explored employing the Granger test of gene expression time series over the range of ages. The most outstanding results were the age-related decline of synaptic transmission and activated expression of glial fibrillary acidic protein (GFAP) in both sexes. We found an antagonistic relationship between calcium/calmodulin dependent protein kinase IV (CAMK4) and GFAP which may include regulatory mechanisms involving cAMP responsive element binding protein (CREB) and mitogen-activated protein kinase (MAPK, alias ERK). Common to both sexes was a decline in synaptic transmission, neurogenesis and an increased base-level of inflammatory and immune-related processes. Furthermore, we detected differences in dendritic spine morphogenesis, catecholamine signaling and cellular responses to external stimuli, particularly to metal (Zinc and cadmium) ions which were higher in female brains.
Market disputes and government intervention: an explanatory framework of risk transformation
Authors: Xiang Jinglin 
Published: March 2020

AbstractThis article examines the government intervention in market governance, that is, why a local government that claims to be a rule maker or market regulator would intervene deeply in transaction disputes between market players. Based on the institutional analysis in the fields of sociology and economics, the author constructs a theoretical framework of risk transformation to study the case of a loan dispute at the Wenzhou Private Lending Service Center. The study shows that there are two aspects in the process of government intervention in transaction disputes: the transformation of economic risk into political risk and the government’s response to risk transformation. The completeness of law, the relationship between government and market players, and the ability of the government to withdraw from society are the three structural factors that affect risk transformation. Facing risk transformation, the greater the potential political risk perceived by the government, the more likely it is to intervene in transaction disputes. This paper provides a new analytical approach for studying the role of government in market transition and the social construction of market institutions.
Diversity in optical coherence tomography normative databases: moving beyond race
Authors: Mehta Nihaal , Waheed Nadia K. 
Published: March 2020

AbstractNormative databases of optical coherence tomography (OCT) metrics, such as retinal nerve fiber layer (RNFL) and macular thickness, are critical to clinical use of OCT imaging. In order to accurately represent the range of normal variation in patient populations, these normative databases must themselves be adequately diverse. Thus far, diversity in OCT normative databases has largely been defined as racial diversity. However, this has largely been based on self-reported “race,” which is inconsistent and generally not scientifically rigorous as a form of categorization. Moreover, there is a great deal of variation even within any single racial group, suggesting that other drivers of variation, such as geography or socioeconomic status, may be more important metrics for diversity. Finally, race itself is a proxy for the biological variation that must be represented in such samples, and as such racial diversity does not itself inherently equate to adequate biologic diversity. As clinical use of OCT continues to grow, including to international settings, it is increasingly important that normative databases built into OCT systems accurately represent the populations to which they are applied. Race is not an ideal sole or even primary means of assessing sample diversity in this context. In future normative OCT database construction, other forms of diversity should be considered.
Views of primary care physicians and rheumatologists regarding screening and treatment of hyperlipidemia among patients with rheumatoid arthritis
Authors: Navarro-Millán Iris , Cornelius-Schecter Anna , O’Beirne Ronan J. , Morris Melanie S. , Lui Geyanne E. , Goodman Susan M. , Cherrington Andrea L. , Fraenkel Liana , Curtis Jeffrey R. , Safford Monika M. 
Published: March 2020

Abstract
Background
Despite high risk for cardiovascular disease (CVD) mortality, screening and treatment of hyperlipidemia in patients with rheumatoid arthritis (RA) is suboptimal. We asked primary care physicians (PCPs) and rheumatologists to identify barriers to screening and treatment for hyperlipidemia among patients with RA.

Methods
We recruited rheumatologists and PCPs nationally to participate in separate moderated structured group teleconference discussions using the nominal group technique. Participants in each group generated lists of barriers to screening and treatment for hyperlipidemia in patients with RA, then each selected the three most important barriers from this list. The resulting barriers were organized into physician-, patient- and system-level barriers, informed by the socioecological framework.

Results
Twenty-seven rheumatologists participated in a total of 3 groups (group size ranged from 7 to 11) and twenty PCPs participated in a total of 3 groups (group size ranged from 4 to 9). Rheumatologists prioritized physician level barriers (e.g. ‘ownership’ of hyperlipidemia screening and treatment), whereas PCPs prioritized patient-level barriers (e.g. complexity of RA and its treatments).

Conclusion
Rheumatologists were conflicted about whether treatment of CVD risk among patients with RA should fall within the role of the rheumatologist or the PCP. All participating PCPs agreed that CVD risk reduction was within their role. Factors that influenced PCPs’ decisions for screening and treatment for CVD risk in patients with RA were mainly related to their concern about how treatment for CVD risk could influence RA symptomatology (myalgia from statins) or how inflammation from RA and RA medications influences lipid profiles.
Radiant heating rapidly increases litter flammability through impacts on fuel moisture
Authors: Kreye Jesse K. , Kane Jeffrey M. , Varner J. Morgan , Hiers J. Kevin 
Published: March 2020

AbstractBackgroundLitter is the predominant fuel that drives surface fire behavior in most fire-prone forest and woodland ecosystems. The flammability of litter is driven by fuel characteristics, environmental factors, and the interactive effects of the two. Solar radiation can influence litter flammability through its effect on fuel moisture and temperature. The direct influence of radiative heating on flammability, however, is poorly understood and the interactive effects of forest structure, composition, fuels, and micrometeorology may have fine-scale ecological consequences in fire-dependent ecosystems.ResultsIn this study, we measured laboratory flammability of two dominant southeastern USA litter fuels—Pinus palustrisMill. andQuercus stellataWangenh.—and evaluated the interactive effects of fuel moisture and infrared radiation. Heating of litter fuels increased their flammability primarily through enhanced litter drying. Heated litter quickly became more flammable than unheated litter when fuels were undergoing drying after saturation, a result of more rapid moisture loss. Litter mass did not change the effect of heating on drying rates, but heavier fuels burned with greater flammability.ConclusionsInteractions among surface fuels, overstory structure, and solar heating may be important in understanding fine-scale heterogeneity in both fire behavior and effects, with strong implications toward increasing the effectiveness of prescribed burning.
Numerical study of thermal radiation and mass transfer effects on free convection flow over a moving vertical porous plate using cubic B-spline collocation method
Authors: Abu zeid M. , Ali Khalid K. , Shaalan M. A. , Raslan K. R. 
Published: March 2020

Abstract
In this paper, we present a numerical method based on cubic B-spline function for studying the effects of thermal radiation and mass transfer on free convection flow over a moving vertical porous plate. Similarity transformations reduced the governing partial differential equations of the fluid flow to a system of nonlinear ordinary differential equations which are solved numerically using a cubic B-spline collocation method. The effects of various physical parameters on the velocity, temperature, and concentration distributions are shown graphically, and the numerical values of physical quantities like skin friction, Nusselt number, and Sherwood number for various parameters are presented in tabular form and discussed.
Secure Hash Algorithm-2 formed on DNA
Authors: Nassr Dieaa I. 
Published: March 2020

Abstract
We present a new version of the Secure Hash Algorithm-2 (SHA-2) formed on artificial sequences of deoxyribonucleic acid (DNA). This article is the first attempt to present the implementation of SHA-2 using DNA data processing. We called the new version DNSHA-2. We present new operations on an artificial DNA sequence, such as (1) $\bar {R}^{k}(\alpha)$

R

̄

k

(
α
)
and $\bar {L}^{k}(\alpha)$

L

̄

k

(
α
)
to mimic the right and left shift by k bits, respectively; (2) $\bar {S}^{k}(\alpha)$

S

̄

k

(
α
)
to mimic the right rotation by k bits; and (3) DNA-nucleotide addition (mod 264) to mimic word-wise addition (mod 264). We also show, in particular, how to carry out the different steps of SHA-512 on an artificial DNA sequence. At the same time, the proposed nucleotide operations can be used to mimic any hash algorithm of its bitwise operations similar to bitwise operations specified in SHA-2. The proposed hash has the following features: (1) it can be applied to all data, such as text, video, and image; (2) it has the same security level of SHA-2; and (3) it can be performed in a biological environment or on DNA computers.
Generalized mixed equilibrium problems and quasi- ϕ-asymptotically nonexpansive multivalued mappings in Banach spaces
Authors: Ali Bashir , Umar Lawal , Harbau M. H. 
Published: March 2020

Abstract
In this paper, we introduce two iterative algorithms for finding a common element of the set of fixed points of a quasi- ϕ-asymptotically nonexpansive multivalued mapping and the sets of solutions of generalized mixed equilibrium problem in Banach space. Then, we prove strong and weak convergence of the sequences to element in the mentioned set. Our results generalize and improve recent results announced by many authors.
Existence of mild solutions to semilinear fractional differential inclusion with deviated advanced nonlocal conditions
Authors: Herzallah Mohamed A. E. , Radwan Ashraf H. A. 
Published: March 2020

AbstractThis paper is devoted to study the existence of at least one continuous mild solution to semilinear fractional differential inclusion with deviated-advanced nonlocal conditions. We develop the results obtained, by exchanging the deviated-advanced nonlocal condition to an integral form. Our results will be accomplished by using the nonlinear Leray-Schauder’s alternative fixed point theorem. The main results are well illustrated with the aid of an example.