bluuebunny/crossref_metadata_2025_split huggingface dataset:
O Cuidado de Enfermagem a criança com transtorno do espectro autista: um desafio no cotidiano
Authors: De Brito Ribas Lara , Alves Manoela 
Published: June 2020

O trabalho trata do cuidado de enfermagem a criança autista. Tendo por objetivos:descrever o cuidado de enfermagem a criança autista e analisar o cuidado deenfermagem a criança autista. Trata-se de uma revisão bibliográfica, através de estudoscientíficos, nas bases de dados mais relevantes como: Scielo (Scientific ElectronicLibrary Online) e BIREME. Foram encontrados inicialmente 1.278 artigos queenvolviam o tema de autismo. Após aplicar os DECS (cuidados de enfermagem,transtorno do espectro autista, autismo), filtrou-se 8 artigos que abordavam a temática,no idioma Português e no período de 2014-2019. Após avaliação dos títulos,encontraram-se o total de 6 artigos, com a leitura minuciosa dos artigos foram excluídoso total de 3 artigos, resultando em somente 3 artigos que abordavam a temática doscuidados de enfermagem ao autismo infantil Os dados demonstram um grande déficitsobre a temática. A prática assistencial do enfermeiro frente à criança autista, ainda éum tabu para muitos profissionais, o que decorre da falta de estudos científicos queabordem o assunto. Conclui-se, que há a necessidade de que a temática seja ministradana graduação, a fim de que sejam produzidos estudos que capacitem os profissionaisenfermeiros, proporcionando uma assistência qualificada.
Palavras chave: Autismo; Criança; Cuidado de enfermagem.
An Insight into Oligopeptide Transporter 3 (OPT3) Family Proteins
Authors: Kurt Fırat 
Published: June 2020

Background:
OPT3s are involved in the transport of Fe from xylem to phloem, in loading
Fe into phloem, and in the transmission of shoot-to-root iron signaling. Yet, apart from Arabidopsis,
little is known about these transporters’functions in other plant species.

Objective:
OPT3 proteins of several plant species were characterized using bioinformatical tools.
Also, a probable Fe chelating protein, GSH, was used in docking analyses to shed light on the interactions
of ligand binding sites of OPT3s.

Methods:
The multiple sequence alignment (MSA) analysis, protein secondary and tertiary structure
analyses, molecular phylogeny analysis, transcription factor binding site analyses, co-expression
and docking analyses were performed using up-to-date bioinformatical tools.

Results:
All OPT3s in this study appear to be transmembrane proteins. They appear to have broad
roles and substrate specificities in different metabolic processes. OPT3 gene structures were highly
conserved. Promoter analysis showed that bZIP, WRKY, Dof and AT-Hook Transcription factors
(TFs) may regulate the expression of OPT3 genes. Consequently, they seemed to be taking part in
both biotic and abiotic stress responses as well as growth and developmental processes.

Conclusion:
The results showed that OPT3 proteins are involved in ROS regulation, plant stress responses,
and basal pathogen resistance. They have species-specific roles in biological processes.
Lastly, the transport of iron through OPT3s may occur with GSH according to the binding affinity
results of the docking analyses.
Unmasking the Many Faces of Giloy (Tinospora cordifolia L.): A Fresh Look on its Phytochemical and Medicinal Properties
Authors: Verma Deepak Kumar , G. Kimmy , Kumar Pradyuman , El-Shazly Mohamed 
Published: June 2020

Background:
Plants have been used to treat health disorders and prevent diseases since antiquity in all
civilizations including the Indian and Chinse. Giloy (Tinospora cordifolia L.) is one of the most important medicinal
plants in Indian folk medicine and is commonly known as the “Heart-leaved Moonseed” or “Guduchi”.
Giloy is a perennial shrubby creeper of the Menispermaceae family. It is native to the tropical areas of India, Sri
Lanka, Myanmar, Sothern Eastern Asia, Africa, and Australia. It attracted attention in the last few decades because
its roots, stems, and leaves are used in folk medicine treating several disorders.

Methods:
To reveal its potential, we reviewed the literature on this plant over the last five decades using several
search engines.

Results:
Giloy is recommended in diabetes, stomachache, jaundice, urinary problems, skin ailments, and prolonged
diarrhea and dysentery. The medicinal properties of T. cordifolia extracts were attributed to its phytochemical
content including steroids, alkaloids, diterpenoid lactones, and glycosides.

Conclusion:
In this review, we summarized the phytochemical content of T. cordifolia and its medicinal properties
with special emphasis on its antioxidant, anti-inflammatory, and cytotoxic activities. We aimed to provide
natural product researchers with a full picture of the potential applications of this plant in the development of food
additives and nutraceuticals.
Recent Achievement in the Synthesis of Benzo[b]furans
Authors: Duc Dau Xuan 
Published: June 2020

Background:Benzo[b]furan derivatives are oxygen-containing heterocyclic compounds consisting of fused benzene and furan rings and are present in a large number of natural and non-natural compounds. This class of compounds has a wide spectrum of biological activities, such as antiarrhythmic, anticancer, inflammatory, antioxidant, antimicrobial, and antiviral. Furthermore, benzo[b]furan derivatives have also been applied in various areas, such as organic electroluminescence device materials and organic dyes, photosensitizing material, organic synthesis as building blocks or intermediates.:Because of a broad range of applicability, the synthesis of benzo[b]furan derivative has drawn great attention of chemists and many studies on the synthesis of this class of compounds have been reported recently. This review will give an overview of benzo[b]furan preparation based on studies dating back to the year 2012.Objective:In this review, recent development in the synthesis of benzo[b]furans are discussed. There has been increasingly new methodologies for the construction of benzo[b]furans skeleton to improve efficiency or develop environmentally friendly procedures. In some studies, reaction mechanisms were also outlined.Conclusion:Many methods for the synthesis of benzo[b]furans have been reported recently. Most of them involve cyclization or cycloisomerization processes. Unquestionably, more imaginative strategies for the construction of benzo[b]furan skeleton will be established in the near future. Application of known methods to natural products or drug synthesis, on industrial scale for the synthesis of economically or medicinally important benzo[ b]furans will probably be paid attention to.
Pharmacological Effects of Secondary Bile Acid Microparticles in Diabetic Murine Model
Authors: Mooranian Armin , Zamani Nassim , Kovacevic Bozica , Ionescu Corina Mihaela , Luna Giuseppe , Mikov Momir , Goločorbin-Kon Svetlana , Stojanovic Goran , Kojic Sanja , Al-Salami Hani 
Published: June 2020

Aim:
Examine bile acids effects in Type 2 diabetes.

Background:
In recent studies, the bile acid ursodeoxycholic acid (UDCA) has shown potent anti-inflammatory effects in
obese patients while in type 2 diabetics (T2D) levels of the pro-inflammatory bile acid lithocholic acid were increased,
and levels of the anti-inflammatory bile acid chenodeoxycholic acid were decreased, in plasma.

Objective:
Hence, this study aimed to examine applications of novel UDCA nanoparticles in diabetes.

Methods:
Diabetic balb/c adult mice were divided into three equal groups and gavaged daily with either empty microcapsules, free UDCA, or microencapsulated UDCA over two weeks. Their blood, tissues, urine, and faeces were collected for
blood glucose, inflammation, and bile acid analyses.
UDCA resulted in modulatory effects on bile acids profile without antidiabetic effects suggesting that bile acid modulation was not directly linked to diabetes treatment.

Results:
UDCA resulted in modulatory effects on bile acids profile without antidiabetic effects suggesting that bile acid
modulation was not directly linked to diabetes treatment.

Conclusion:
Bile acids modulated the bile profile without affecting blood glucose levels.
Ld/Mm+ Simulation of Some Aristolochic and Humic Acids Species Coupled
in Periodic Box with Water
Authors: Petrescu Alina-Maria , Putz Mihai Viorel , Ifrim Feng Chen , Ilia Gheorghe , Paunescu Virgil 
Published: June 2020

Background:
This study is one of the dynamics molecular docking that presents the interactions
between a molecular model of the mixture of humic acid structure and 18 aristolochic acids structures, from
PubChem database in a water box that simulates the environment reactions.

Objective:
The major objective was to identify what happens in this procedure(LD/MM+) with the coupled
species.

Method:
LD/MM+ SIMULATION ( Langevin dynamics simulation)

Results:
The R-Squared statistic indicates that the model as fitted by MLR , explains 90.9437% of the variability in Volume.

Conclusion:
The interactions of these acids, the types of forces, and the way that these molecules can get
closer to each other, in terms of total energy density, while identifying the specificities vis-à-vis of wateraromaticity or water-reactivity behaviors.
Hydrogel as a Novel Drug Delivery System: Recent Advancements and Patents
Authors: Singh Ruchi , Goel Surya , Sharma Pankaj Kumar , Agarwal Abhinav 
Published: June 2020

Background:
A semisolid gel-like preparation constitutes with the cross-linked polymers,
which may easily swell in the presence of water and incorporate the amount of drug substance
known as ‘Hydrogel.’

Objective:
To prepare the review on the hydrogels, leading ennoblements, classification, mechanism,
recent patents, and evaluation parameters.

Methods:
This review accrued by taking the help of online and offline journals, books, and other
sources. This field includes new developments in the field of inventions in the novel drug delivery of
hydrogels.

Results:
The impact of the formulation of hydrogels is attracting the focus of the researchers expeditiously
because of their nature, three-dimensional structure, compatibility with the other excipients
was found enormously useful in the biomedical applications and pharmaceutical industries, less time
consuming, better sustained and prolonged the effect. Currently, hydrogels are growing expeditiously
for the intensive work done by the use of natural, synthetic, and semi-synthetic polymers for the
transformation of hydrophobic and hydrophilic drugs into hydrogels as compared to develop the
conventional gels.

Conclusion:
The journey of hydrogel goes through with the numerous inventions research papers,
reports, publications, and many other sources. The development arouses with the hydrogels in the use
of wound dressing, making diapers, contact lens, etc. Nowadays, it is pivotally growing in the field
of tissue engineering scaffolds, preparation of hydrophobic drugs into hydrogels, which is a critical
challenge in prompt conditions.
Electrical Conductivity and Wettability of Nanofluids Prepared by Nanocomposite of MWCNTs and Dialkyl Pentasulfide
Authors: Wang Yong , Guan Jiju , Wang Jia , Feng Bohua , Xu Xuefeng 
Published: June 2020

Background:
Multi-walled carbon nanotubes (MWCNTs) were filled with dialkyl pentasulfide
(DPS) to prepare MWCNTs-DPS composite (nanocomposite) additives for use in nanofluid-
based machining.

Methods:
The nanocomposite was prepared by employing a liquid phase wet chemistry method, and
was then added in pure water with a surfactant to form the nanofluids. The present study comprehensively
reveals the effects of additive concentration, acid treatment time, testing temperature and electrowetting
conditions on the electrical conductivity and wettability of nanofluids.

Results:
The nanocomposite was successfully produced with a maximum filling rate of 27.4%. Its
additives displayed an optimal performance at a concentration of about 0.1%. Consequently, the
electrical conductivity and wettability of the nanofluids were increased by over 13.7% and 6.35%,
respectively in comparison with individual MWCNTs additives. Under the electro-wettability conditions,
the wetting performance of the nanofluids produced by the nanocomposite increased with the
increase in charging voltage. Moreover, due to higher conductivity and greater charge capacity, the
nanofluids with a higher additive concentration displayed better wetting performance.

Conclusion:
The modification and filling enhanced properties such as the surface activity, electrical
conductivity and capacitance of the MWCNTs, thereby improving the performance.
Detection of Hepatitis B Virus-associated Hepatocellular Carcinoma Disease Using Hybrid Hierarchical k-Means Clustering and SVM Algorithm
Authors: Muflikhah Lailil , Widodo Nashi , Mahmudy Wayan Firdaus , Solimun  
Published: June 2020

Background:
Hepatocellular carcinoma (HCC) is a serious disease and is the third main
cause of death in the world. Hepatitis B virus infection can lead to HCC. The virus introduces
genetic material into the host, damages DNA, and interferes with the activity of the apoptotic and
tumor suppressors to trigger the formation of an oncogene. However, most of these cases are
discovered after cancer enters stage three or four.

Objective:
Early detection of HCC through machine learning algorithm approach using data set:
DNA sequence of HBx HepB virus.

Methods:
The research method used is the development of a Support Vector Machine classifier
algorithm for carcinoma detection. The large data volume and unbalance data distribution in class
can decrease the accuracy rate and sensitivity. Therefore, this paper proposed a hybrid of
Hierarchical k-Means clustering and SVM algorithms to detect HCC disease using HBx DNA
sequences. In this method, the SVM algorithm was applied in each cluster using the Hierarchical k-
Means method.

Results:
The experimental result showed an accuracy rate of 97.18%, a sensitivity of 98.9%, and
AUC of 0.918. This means the performance was increased to 9.52%, 95.3%, and 0.4 above the
conventional SVM method.

Conclusion:
Detection of HCC can be applied using the SVM algorithm based on clustering. The
proposed method, by hybrid hierarchical k-Means and SVM, increased the performance of
classification results for the detection.
Morphological and Physical Characteristic of Stone Mastic Asphalt Mixture Incorporating Nano Silica
Authors: Masri Khairil A. , Jaya Ramadhansyah Putra , Arshad Ahmad K. , Mahmud Mohd Zul H. 
Published: June 2020

Introduction:
Asphalt binder plays an important role in contributing to the good performance of asphalt mixture. However, the interlocking structure of asphalt binder is delicate and sensitive due to surrounding temperature and moisture.

Methods:
Previously, asphalt binder usually modified with polymer modifier. But, this type of modifier has low temperature susceptibility. To overcome this, nanomaterial is introduced to enhance the performance of virgin asphalt binder. Among the crucial evaluation of nano-modification is to evaluate its microstructural changes through morphological property evaluation. The addition of nanomaterial then will significantly improve the inner structure of asphalt binder and reduce the effect of those problems.

Aim:
Thus, the aim of this study was to assess the morphological properties of nanosilica modified asphalt binder to determine the inner structured properties of modified specimen.

Results:
Among the morphological tests conducted for asphalt binder in this study were Scanning Electron Microscope (SEM), X-Ray Diffraction (XRD) and Atomic Force Microscope (AFM). From SEM image analysis and XRD evaluation, the existence of Nanosilica (NS) inside the asphalt binder was well dispersed and from these two tests, the existence of NS inside asphalt binder was verified. From AFM results, most of NS-MB images before and after ageing conditions displayed the typical bee structure (Catana Phase).

Conclusion:
It was also concluded that the addition of NS in asphalt binder improved its surface stiffness. The overall surface stiffness of the asphalt binder after aging was increased and the surface became more solid.
State of the Art Contemporary Prefabricated Fiber-Reinforced Posts
Authors: Elsubeihi Emad S. , Aljafarawi Tareq , Elsubeihi Heba E. 
Published: June 2020

Background:
There is an increased interest in investigating and use of prefabricated fiber-reinforced posts by scientists and clinicians in the restoration of endodontically treated teeth.

Objective:

The objective of this narrative review was to summarize the composition of contemporary prefabricated fiber-reinforced posts and elucidate its effect on the different properties of these posts.

Methods:

PubMed/Medline, Scopus, and Google Scholar were searched from January 1990 to December 2019 for English Language articles describing the composition and properties of prefabricated fiber-reinforced posts. First, the search strategy was established for Medline / PubMed using the following terms ((Fiber post[All Fields] OR (fiber reinforced post[All Fields] AND composition[All Fields] AND (“matrix”[MeSH Terms] OR (“fiber”[All Fields] AND “properties”[All Fields] AND “epoxy”[All Fields]) OR “dimethacrylate”[All Fields]) AND NOT (CAD CAM[All Fields])). The search strategy was then adapted for Scopus and Google Scholar databases to identify eligible studies.

Results:

The current state of the art of prefabricated fiber-reinforced posts revealed a myriad of products with different formulations which are reflected on the mechanical and handling characteristics of the different posts available in the market. More recent research and development efforts attempted to address issues related to the improved transmission of polymerization light through the post to the most apical end of the restoration inside the root canal. Others focused on the development of new matrix materials for fiber-reinforced posts.

Conclusion:

A review of the literature revealed that currently available prefabricated fiber-reinforced posts consist of a heterogeneous group of materials which can have a significant effect on the behavior of posts. Understanding different formulations will help clinicians in scrutinizing the vast literature available on prefabricated fiber-reinforced posts. This, in turn, will help them make an informed decision when selecting materials for the restoration of endodontically treated teeth.
Inflammation Biomarkers in Psychiatry
Authors: Evrensel Alper , Tarhan Nevzat 
Published: June 2020

Introduction:
There has long been a need for diagnostic, theragnostic, and prognostic
biomarkers for psychiatric disorders. Biomarkers help in reducing ambiguity and arbitrariness and
increase objectivity. In this context, many candidates for hormonal, immunological, serological, and
neuroimaging markers have been proposed, but none of these marker candidates alone nor a biomarker
panel has been approved for any disease. The fact that almost all psychiatric disorders are
heterogeneous makes this process challenging. However, strong biomarker candidates have been
identified, especially in light of the large number of clinical and preclinical studies conducted within
the last five years.

Objective:
The aim of this article was to compile and discuss the current information on immune
biomarkers in major psychiatric disorders, such as schizophrenia, depression, bipolar disorder, and
anxiety disorders.

Methods:
In this study, respected scientific databases were searched using key terms related to the
subject, and the related literature was examined in detail.

Results:
There are many relationships between psychiatric disorders and immune system parameters.
Evidence also suggests that neuroinflammation is involved in the etiopathogenesis of psychiatric
disorders. Markers, such as proinflammatory cytokines, tumor necrosis factor alpha, and C-reactive
protein have been associated with psychiatric disorders in numerous studies.

Conclusions:
The neuroinflammation hypothesis has an important place in the etiopathogenesis of
psychiatric disorders. Uncertainty remains as to whether neuroinflammation is a cause or consequence
of psychiatric disorders. Some researchers have indicated that intestinal microbiota composition
disorders and dysbiosis are sources of neuroinflammation. Immune marker studies are of
great importance in terms of eliminating this uncertainty and overcoming diagnostic and treatment
difficulties in the clinic. In this review, biomarker studies on psychiatric disorders were examined
from the viewpoint of the immune system and discussed in light of the current studies.
Time Series Features Extraction and Forecast from Multi-feature Stocks with Hybrid Deep Neural Networks
Authors: Xu Ye , Yuan Xun 
Published: June 2020

Background:
Forecasting of time series stock data is important in financial related works. Stock data usually have multifeatures such as opening price, closing price and so on. The traditional forecast methods, however, is mainly applied to
one feature – closing price, or a few, like four or five features. The massive information hidden in the multi-feature data is
not thoroughly discovered and used.

Objective:
Find a method to make used of all information of multi-features and get a forecast model.

Method:
LSTM based models are introduced in this paper. For comparison, three models are used and they are single
LSTM model, hybrid model of LSTM-CNN, and traditional ARIMA model.

Results:
Experiments with different models are performed on stock data with 50 and 230 features, respectively. Results
show that MSE of single LSTM model is 2.4% lower than ARIMA model and MSE of LSTM-CNN model is 12.57%
lower than that of single LSTM model on 50 features data. On 230 features data, LSTM-CNN model is found to be improved by 23.41% in forecast accuracy.

Conclusion:
In this paper, we use three different models – ARIMA, single LSTM and LSTM-CNN hybrid model – to
forecast rise and fall of multi-features stock data. It’s found that single LSTM model is better than traditional ARIMA
model on the average, and LSTM-CNN hybrid model is better than single LSTM model on 50-feature stock data. What’s
more, we use LSTM-CNN model to perform experiments on stock data with 50 and 230 features, respectively. And is
found that results of the same model on 230 features data is better than that on 50 features data. It’s proved in our work
that the LSTM-CNN hybrid model is better than other models and experiments on stock data with more features could result in better outcomes. We’ll do more works on hybrid models next.