bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evaluation of peripheral perfusion index and heart rate variability as early predictors for intradialytic hypotension in critically ill patients.
Authors: Shaban Mohamed , Hasanin Ahmed , El-adawy Akram , Mostafa Hanan , Fathy Shymaa , Abdelreheem Hossam M , Lotfy Ahmed , Abougabal Ayman , Mohamed Hassan , Mukhtar Ahmed 
Published: August 2019

Abstract
Background
Intradialytic hypotension is a serious complication during renal replacement therapy in critically ill patients. Early prediction of intradialytic hypotension could allow adequate prophylactic measures. In this study we evaluated the ability of peripheral perfusion index (PPI) and heart rate variability (HRV) to predict intradialytic hypotension.
Methods
A prospective observational study included 36 critically ill patients with acute kidney injury during their first session of intermittent hemodialysis. In addition to basic vital signs, PPI was measured using Radical-7 (Masimo) device. Electrical cardiometry (ICON) device was used for measuring cardiac output, systemic vascular resistance, and HRV. All hemodynamic values were recorded at the following time points: 30 minutes before the hemodialysis session, 15 minutes before the start of hemodialysis session, every 5 minutes during the session, and 15 minutes after the conclusion of the session. The ability of all variables to predict intradialytic hypotension was assessed through area under receiver operating characteristic (AUROC) curve calculation.
Results
Twenty-three patients (64%) had intradialytic hypotension. Patients with pulmonary oedema showed higher risk for development of intradialytic hypotension {Odds ratio (95% CI): 13.75(1.4-136)}. Each of baseline HRV, and baseline PPI showed good predictive properties for intradialytic hypotension {AUROC (95% CI): 0.761(0.59-0.88)}, and 0.721(0.547-0.857)} respectively.
Conclusions
Each of low PPI, low HRV, and the presence of pulmonary oedema are good predictors of intradialytic hypotension.
Low health literacy levels in patients with chronic retinal disease
Authors: Jandorf Sofie , Nielsen Marie Krogh , Sørensen Kristine , Sørensen Torben Lykke 
Published: August 2019

Abstract
Background

A patient’s health literacy is fundamental for navigating the health system and managing disease. This study aimed to compare the health literacy levels of patients with chronic retinal disease in Denmark.

Methods

This cross-sectional questionnaire study used the validated HLS-EU-Q16 questionnaire to determine the health literacy of 225 patients with age-related macular degeneration (AMD), diabetic macular edema (DME) or retinal vein occlusion (RVO), receiving intravitreal treatment at the retinal clinic, Zealand University Hospital, Denmark. Patients were consecutively included as participants for the study. All patients had the option of having the survey read aloud to them.

Results

Health literacy levels between the patient groups did not differ significantly, however, the proportion of patients with poor health literacy was high—65% of AMD patients, 73% of DME patients, and 63% of patients with RVO.

Conclusions

Low health literacy of patients with retinal disease signify a need for more health literacy research in the field of retinal diseases, to secure that patients have the timely and appropriate knowledge and competencies to manage their condition.
Expression patterns of two pal genes of Pleurotus ostreatus across developmental stages and under heat stress
Authors: Hou Ludan , Wang Lining , Wu Xiangli , Gao Wei , Zhang Jinxia , Huang Chenyang 
Published: August 2019

Abstract
Background: Phenylalanine ammonia-lyase (PAL, EC 4.3.1.24) is the first key enzyme in the phenylpropanoid pathway. The pal gene has been widely studied in plants and participates in plant growth, development and defense systems. However, in Pleurotus ostreatus, the biological functions of pal during organismal development and exposure to abiotic stress have not been reported.
Results: In this study, we cloned and characterized the pal1 (2232 bp) and pal2 (2244 bp) genes from the basidiomycete Pleurotus ostreatus CCMSSC 00389. The pal1 and pal2 genes are interrupted by 6 and 10 introns, respectively, and encode proteins of 743 and 747 amino acids, respectively. Furthermore, prokaryotic expression experiments showed that PAL enzymes catalyzed the conversion of L-phenylalanine to trans-cinnamic acid. The function of pal1 and pal2 was determined by constructing overexpression (OE) and RNA interference (RNAi) strains. The results showed that the two pal genes had similar expression patterns during different developmental stages. The expression of pal genes was higher in the reproductive growth stage than in the vegetative growth stage. And the interference of pal1 and pal2 delayed the formation of primordia. The results of heat stress assays showed that the RNAi-pal1 strains had enhanced mycelial tolerance to high temperature, while the RNAi-pal2 strains had enhanced mycelial resistance to H2O2.
Conclusions: These results indicate that two pal genes may play a similar role in the development of P. ostreatus fruiting bodies, but may alleviate stress through different regulatory pathways under heat stress.
Symbiotic bacteria motivate the foraging decision and promote fecundity and survival of Bactrocera dorsalis (Diptera: Tephritidae)
Authors: Author) Mazarin Akami(Former Corresponding , Ren Xue-Ming , Qi Xuewei , Mansour Abdelaziz , Gao Bingli , Cao Shuai , Author) Chang-Ying Niu(New Corresponding 
Published: August 2019

Abstract
Background

The gut bacteria of tephritid fruit flies play prominent roles in nutrition, reproduction, maintenance and ecological adaptations of the host. Here, we adopted an approach based on direct observation of symbiotic or axenic flies feeding on dishes seeded with drops of full diet (containing all amino acids) or full diet supplemented with bacteria at similar concentrations to explore the effects of intestinal bacteria on foraging decision and fitness of Bactrocera dorsalis.

Results

The results show that intestinal probiotics elicit beneficial foraging decision and enhance the female reproduction fitness and survival of B. dorsalis (symbiotic and axenic), yet preferences for probiotic diets were significantly higher in axenic flies to which they responded faster compared to full diet. Moreover, females fed diet supplemented with Pantoea dispersa and Enterobacter cloacae laid more eggs but had shorter lifespan while female fed Enterococcus faecalis and Klebsiella oxytoca enriched diets lived longer but had lower fecundity compared to the positive control. Conversely, flies fed sugar diet (negative control) were not able to produce eggs, but lived longer than those from the positive control.

Conclusions

These results suggest that intestinal bacteria can drive the foraging decision in a way which promotes the reproduction and survival of B. dorsalis. Our data highlight the potentials of gut bacterial isolates to control the foraging behavior of the fly and c empower the sterile insect technique (SIT) program through the mass rearing.
ANÁLISE FITOQUÍMICA E MICROBIOLÓGICA DE AMOSTRAS DE PIMENTA-ROSA OBTIDAS DE PROPRIEDADES FAMILIARES DA REGIÃO NORTE DO ESPÍRITO SANTO
Authors: Píccolo Maria Da Penha 
Published: August 2019

A pimenta-rosa ou aroeira Schinus terebinthifolius Raddi é uma especiaria de grande valor de mercado nacional e internacional associado às suas aplicações nas indústrias alimentícia, farmacêutica e de cosméticos. No estado do Espírito Santo a produção concentra-se na região litorânea, sendo São Mateus um polo de produção, processamento e escoamento. Objetivou-se avaliar características de qualidade de pimenta-rosa produzida em São Mateus-ES. Frutos in natura e desidratados foram submetidos a análises fitoquímicas e microbiológicas. Constatou-se presença dos metabólitos secundários fenóis, taninos, glicosídeos/saponinas e flavonoides além de um baixo índice de contaminação microbiana. Em nenhuma das amostras foi constatada a presença de Salmonella sp. Esses resultados reforçam o potencial dessa espécie para uso como condimento, medicinal e farmacêutico. A qualidade da matéria-prima deve ser considerada para obtenção de produtos derivados de boa qualidade. Assim, o cultivo de acordo com as Boas Práticas Agrícolas (BPA) e Boas Práticas de Fabricação (BPF) pode contribuir para a sustentabilidade do agronegócio pimenta-rosa na região norte do Estado do Espírito Santo.
Fa‘āliyah Ta‘zīz Dawr al-Qānūn li Taṭwīr Qiṭā‘ al-Ḥalāl wa Taḥwīl Mukhrajātihi ilā Sūq al-‘Amal
Authors: Ahmed Ahmed Salem 
Published: August 2019

<p><em>Ḥalāl</em> concept correlation with the industry and trade has shown a new matter leads to discovering other sciences to find the scientific basis for the Islamic principle that governs these matters, especially in the natural and economic sciences, but the different philosophy between Islamic science and those sciences led to the dichotomy of research between the laboratories and jurisprudence groups. In spite of the high value of the output of both of them, but they are unable to translate it and linked it with the labor market, here where the researcher has felt the law role importance and its ability to coordinate these efforts and codify them as a reference in the <em>ḥalāl</em> standard application and settlement of its disputes, which show the law-science creativity in <em>ḥalāl</em> sector, by pointing the legalization importance and its direct connection with the rights and duties of those connected with the <em>ḥalāl</em> sector.</p>
Preparation of Chitosan/Alginate-ellagic Acid Sustained-release Microspheres and their Inhibition of Preadipocyte Adipogenic Differentiation
Authors: Ding Chengshi , Bi Haidan , Wang Deya , Kang Meiling , Tian Zhongjing , Zhang Yingxia , Wang Hongkai , Zhu Tianshun , Ma Jing 
Published: August 2019

Objective:
In this study, chitosan/alginate-ellagic acid sustained-release microspheres were
prepared, and the effect of sustained-release microspheres on preadipocyte adipogenic differentiation
was analyzed.

Methods:
Chitosan/alginate-ellagic acid microspheres were prepared and identified by scanning electron
microscopy (SEM) and infrared spectroscopy (IR). The drug release rates were measured at pH
6.8, 7.0, 7.2, 7.4 to determine sustained release of ellagic acid from microspheres. The effects of 0.1, 1,
10 mg/L chitosan/alginate-ellagic acid microsphere on 3T3-F442A preadipocyte proliferation were determined
by Methyl thiazolyl tetrazolium assay (MTT), and cell morphology was checked by hematoxylin/
eosin staining (HE staining). The effect of chitosan/alginate-ellagic acid microspheres on
preadipocyte adipogenic differentiation was also determined by Oil red O staining, and lipogenesis was
measured by isopropanol extraction. The molecular mechanism was investigated by detecting the
mRNA expression of CCAAT/enhancer binding protein alpha (C/EBPα) and peroxisome proliferatorsactivated
receptor gamma (PPARγ).

Results:
Chitosan/alginate-ellagic acid sustained-release microspheres were successfully prepared, and
the inhibition of proliferation and adipogenic differentiation of preadipocytes was found to be dosedependent.
The mechanism of differentiation inhibition was found to be closely related to the expression
of transcription factor C/EBPα and PPARγ.

Conclusion:
Chitosan/alginate can be used as a good material to prepare ellagic acid sustained-release
microspheres, and these microspheres can be used for treating the obesity.
iMethylK-PseAAC: Improving Accuracy of Lysine Methylation Sites Identification by Incorporating Statistical Moments and Position Relative Features into General PseAAC via Chou’s 5-steps Rule
Authors: Ilyas Sarah , Hussain Waqar , Ashraf Adeel , Khan Yaser Daanial , Khan Sher Afzal , Chou Kuo- Chen 
Published: August 2019

Background:Methylation is one of the most important post-translational modifications in the human body which usually arises on lysine among.the most intensely modified residues. It performs a dynamic role in numerous biological procedures, such as regulation of gene expression, regulation of protein function and RNA processing. Therefore, to identify lysine methylation sites is an important challenge as some experimental procedures are time-consuming.Objective:Herein, we propose a computational predictor named iMethylK-PseAAC to identify lysine methylation sites.Methods:Firstly, we constructed feature vectors based on PseAAC using position and composition relative features and statistical moments. A neural network is trained based on the extracted features. The performance of the proposed method is then validated using cross-validation and jackknife testing.Results:The objective evaluation of the predictor showed accuracy of 96.7% for self-consistency, 91.61% for 10-fold cross-validation and 93.42% for jackknife testing.Conclusion:It is concluded that iMethylK-PseAAC outperforms the counterparts to identify lysine methylation sites such as iMethyl-PseACC, BPB-PPMS and PMeS.
A Review of PCSK9 Inhibitors and their Effects on Cardiovascular Diseases
Authors: Chen Bo , Shi Xin , Cui Yanping , Hou Aiping , Zhao Pengjun 
Published: August 2019

Background:
Cardiovascular diseases remain the leading cause of morbidity and mortality in
the world, with elevated Low-Density Lipoprotein-Cholesterol (LDL-C) levels as the major risk factor.
Lower levels of LDL-C can effectively reduce the risk of cardiovascular diseases. Proprotein convertase
subtilisin/kexin type 9 (PCSK9) plays an important role in regulating the degradation of hepatic LDL
receptors that remove LDL-C from the circulation. PCSK9 inhibitors are a new class of agents that are
becoming increasingly important in the treatment to reduce LDL-C levels. Two PCSK9 inhibitors, alirocumab
and evolocumab, have been approved to treat hypercholesterolemia and are available in the
United States and the European Union. Through the inhibition of PCSK9 and increased recycling of
LDL receptors, serum LDL-C levels can be significantly reduced.

Objective:
This review will describe the chemistry, pharmacokinetics, and pharmacodynamics of
PCSK9 inhibitors and their clinical effects.
Bothrops alternatus Snake Venom Induces Cytokine Expression and Oxidative Stress on Renal Function
Authors: Júnior F.A. Nogueira , Jorge A.R. Coelho , Marinho A.D. , Silveira J.A. de Moraes , Alves N.T. Queiroz , Costa P.H. Sá , e Silva P.L. Braga , Chaves-Filho A.J. Maia , Lima D.B. , Sampaio T.L. , Morais G.B. de , Evangelista J.S. Azul Monteiro , Martins A.M. Costa , Júnior R.S. Ferreira , Macedo D.S. , Jorge R.J. Bezerra , Monteiro H.S. Azul 
Published: August 2019

Background:Envenomation caused by Bothrops alternatus is common in Southern Brazil. Acute Kidney Injury occurs after Bothrops snakebite and more information is necessaryrequired to understand its mechanism.Objective:The objective was to evaluate the effect of Bothrops alternatus venom (BaV) on renal cells and rat isolated kidney function.Methods:Wistar rats (n = 6, weighing 260-320 g) were perfused with a Krebs-Henseleit solution containing 6 g 100 mL-1 of bovine serum albumin. After 30 minutes, the kidneys were perfused with BaV to a final concentration of 1 and 3 μgmL-1; and subsequently were evaluated for Perfusion Pressure (PP), Renal Vascular Resistance (RVR), Urinary Flow (UF), Glomerular Filtration Rate (GFR), and percentage of electrolyte tubular transport. Renal histological analysis, cytokine release, oxidative stress and cytotoxicity in renal proximal tubular cells were assessed.Results:BaV reduced PP, RVR, GFR, UF, total and proximal sodium transport (%TNa+), and chloride (%TCl-) in the isolated kidney perfusion model. Histological analysis of perfused kidneys disclosed the presence of proteinaceous material in the glomeruli and renal tubules, vacuolar tubular epithelial cell degeneration, Bowman's capsule degeneration, swelling of glomerular epithelial cells, glomerular atrophy and degeneration, and the presence of intratubular protein. Cytokine release (TNF-α, IL-1β, IL-10) and oxidative stress were increased in the kidneys. The viability of LLC-MK2 cells (IC50: 221.3 μg/mL) was decreased by BaV and necrosis was involved in cell death.Conclusion:These findings indicate that BaV modifies functional parameters in an isolated perfused kidney model and has cytotoxic effects on renal lineage cells.
Dermal Delivery of Meloxicam Nanosuspensions based Gel: Optimization with Box Behnken Design Experiment Approach: Ex Vivo and In Vivo Study
Authors: Pathan Inayat B. , Sakhare Mahesh , Ambekar Wahid , Setty Chitral M. 
Published: August 2019

Background:
Transdermal delivery of meloxicam is advantageous than the oral route in
the treatment of pain management.

Objective:
The goal of the present study is to formulate and evaluate meloxicam (MX) loaded
nanosuspensions based gel for transdermal application.

Methods:
The formulation parameters were optimized using Box Behnken design (BBD) taking
three independent variables and three responses. Formulations were evaluated for particle size
(nm), polydispersity index (PDI), zeta potential (mV), ex vivo permeation, in vivo study, morphology,
FTIR, skin irritation and, stability study. Optimized formulation having Poloxamer 188 (0.4
mg), PVP K30 (0.5 mg) and sonication time (60 min.) demonstrated smaller particle size (159.2 ±
3.5 nm), low PDI (0.120 ± 0.01) and higher zeta potential value (-29 ± 4mV).

Results:
In the ex vivo study, MX-NG showed a significant increase (p<0.05) in the flux (24.40 ±
2.6 μg/cm2/h) of meloxicam through the human cadaver skin as compared to other formulations. In
the in- vivo study, MX-NG showed a significant (p<0.05) increase in anti-inflammatory activity as
compared to marketed gel.

Conclusion:
Thus, it is concluded that the developed meloxicam loaded nanosuspensions based
gel showed maximum therapeutic effects in rats.
Classification and Analysis of Static Metric Based Antipattern Detection in Service Computing
Authors: Saluja Shivani , Batra Usha 
Published: August 2019

Background:
Design Pattern is regarded as an essential component for enhancement of
system design which can further improve the reusability and maintainability whereas antipattern degrades
the quality of the program. Antipatterns are sub-optimal implementation choices which initially
appears to be a good concept but later on leads to low code maintainability and higher maintenance
costs.

Objective:
The identification of antipatterns which lead to performance degradation plays an important
role in the reduction of expensive work and cost involved in maintenance, redesign, reimplementation,
and redeployment. The main motivation is to refactor the source code in order to reduce
maintenance efforts. Antipatterns impact reliability, testability and maintainability, but they
still lack clear identification because of different interpretations and definition of each antipattern.
There is a need for a benchmark to analyze the result generated by antipatterns.

Methods:
Static and dynamic analysis individually do not suffice for antipattern .A hybrid approach
is proposed by combining rule based static analysis with dynamic run time analysis. Before applying
the hybrid approach a simple manual validation was done to exclude the type of input which had
the least probability of containing antipattern. The approach aims at optimizing the results by inclusion
of response time metric measure which can be evaluated at runtime execution of the web service.

Results and Conclusion:
: The paper focusses on detection of antipatterns from web services based
on code level and interface level static metrics .Only a brief overview of dynamic approach for detection
is proposed. The future scope of this paper will focus on detection of antipattern based on
more number of dynamic metrics and also a comparative analysis of the results generated from static,
dynamic and hybrid approach.
Enhancing Resiliency Feature in Smart Grids through a Deep Learning Based Prediction Model
Authors: Khediri Abderrazak , Laouar Mohamed Ridda , Eom Sean B. 
Published: August 2019

Background:
Enhancing the resiliency of electric power grids is becoming a crucial issue
due to the outages that have recently occurred. One solution could be the prediction of imminent failure
that is engendered by line contingency or grid disturbances. Therefore, a number of researchers
have initiated investigations to generate techniques for predicting outages. However, extended
blackouts can still occur due to the frailty of distribution power grids.

Objective:
This paper implements a proactive prediction model based on deep-belief networks to
predict the imminent outages using previous historical blackouts, trigger alarms, and suggest solutions
for blackouts. These actions can prevent outages, stop cascading failures and diminish the
resulting economic losses.

Methods:
The proposed model is divided into three phases: A, B and C. The first phase (A) represents
the initial segment that collects and extracts data and trains the deep belief network using the collected
data. Phase B defines the Power outage threshold and determines whether the grid is in a
normal state. Phase C involves detecting potential unsafe events, triggering alarms and proposing
emergency action plans for restoration.

Results:
Different machine learning and deep learning algorithms are used in our experiments to
validate our proposition, such as Random forest, Bayesian nets and others. Deep belief Networks
can achieve 97.30% accuracy and 97.06% precision.

Conclusion:
The obtained findings demonstrate that the proposed model would be convenient
for blackouts’ prediction and that the deep-belief network represents a powerful deep learning
tool that can offer plausible results.
An Efficient Computational Model for Assessing the Stability Characteristics of Electro-active Natural Bio-resources
Authors: Jhawar Divyanshu , Sharma Pranshu , Sharma Abhishek , Srinivasan Kathiravan , Chen Bor-Yann 
Published: August 2019

Background:
The properties of the natural bio-sensors as the fuel after treatment, is beneficial
and considered as the most environmental friendly alternative. The microbial fuel cell will help
in the bio electricity generation. To use them first, it is important to know the stability and the characteristics
of such organic compound. The research presents the computational methods of assessment
of stability and characteristics analysis of organic herbs, Syzygium and Citrus.

Objective:
MFC has a very vast research area and many scientists are rigorously working on MFCs.
Here, we have explained research work related to what we have presented in the paper.

Methods:
To compute the stability of these microbial fuel cells, we have used two different methods
on each herb, Structural Similarity Index Method (SSIM) and Graph Comparison using their Coordinates
(GCC).

Results:
This research work provides the results of convergence towards the stability of herbs. Further,
this section also presents the performance characteristics of the software algorithms and their
comparative results to verify the outcomes of the herb characteristics using both methods.

Conclusion:
The proposed work is efficient in finding stability of MFCs on the selected herbs. The
approach should work fine on other herbs as well. Machine Learning could have been much useful
for this purpose if the availability of the data would have been much high.