bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Comparative Study to Explore the Effect of Different Compounds in Immune Proteins of Human Beings Against Tuberculosis: An In-silico Approach
Authors: Tripathi Manish Kumar , Yasir Mohammad , Singh Pushpendra , Shrivastava Rahul 
Published: March 2019

Background:The lungs are directly exposed to pollutants, pathogens, allergens, and chemicals, which might lead to physiological disorders. During the Bhopal gas disaster, the lungs of the victims were exposed to various chemicals. Here, using molecular modelling studies, we describe the effects of these chemicals (Dimethyl urea, Trimethyl urea, Trimethyl isocyanurate, Alphanaphthol, Butylated hydroxytoluene and Carbaryl) on pulmonary immune proteins.Objective:In the current study, we performed molecular modelling methods like molecular docking and molecular dynamics simulation studies to identify the effects of hydrolytic products of MIC and dumped residues on the pulmonary immune proteins.Methods:Molecular docking studies of (Dimethyl urea, Trimethyl urea, Trimethyl isocyanurate, Alphanaphthol, Butylated hydroxytoluene and Carbaryl) on pulmonary immune proteins was performed using the Autodock 4.0 tool, and gromacs was used for the molecular dynamics simulation studies to get an insight into the possible mode of protein-ligand interactions. Further, in silico ADMET studies was performed using the TOPKAT protocol of discovery studio.Results:From docking studies, we found that surfactant protein-D is inhibited most by the chemicals alphanaphthol (dock score, -5.41Kcal/mole), butylated hydroxytoluene (dock score,-6.86 Kcal/mole), and carbaryl (dock score,-6.1 Kcal/mole). To test their stability, the obtained dock poses were placed in a lipid bilayer model system mimicking the pulmonary surface. Molecular dynamics simulations suggest a stable interaction between surfactant protein-D and carbaryl.Conclusion:This, study concludes that functioning of surfactant protein-D is directly or indirectly affected by the carbaryl chemical, which might account for the increased susceptibility of Bhopal gas disaster survivors to pulmonary tuberculosis.
Comprehensive Understanding of the Interaction Among Stress Hormones Signalling Pathways by Gene Co-expression Network
Authors: Mortezaeefar Maryam , Fotovat Reza , Shekari Farid , Sasani Shahryar 
Published: March 2019

Background:
Plants respond to various stresses at the same time. Recent studies show
that interactions of various phytohormones can play important roles in response to stresses.

Objective:
Although many studies have been done about the effects of the individual hormones,
little information exists about the crosstalk among the hormone signalling pathways in plants.

Methods:
In this work, the weighted gene co-expression network analysis method was used to
define modules containing genes with highly correlated expression patterns in response to abscisic
acid, jasmonic acid, and salicylic acid in Arabidopsis.

Results:
Results indicate that plant hormones cause major changes the expression profile and
control diverse cell functions, including response to environmental stresses and external factors,
cell cycle, and antioxidant activity. In addition, AtbHLH15 and HY5 transcription factors can
participate in phytochrome pathways in response to the phytohormones. It is probable that some
Type III WRKY transcription factors control the response to bacterium separately from the other
stresses. The E2Fa/DPa transcription factor also regulates the cell cycle.

Conclusion:
In general, many processes and pathways in plants may be regulated using a
combination of abscisic acid, jasmonic acid, and salicylic acid.
Systematic Comparisons of Positively Selected Genes between Gossypium arboreum and Gossypium raimondii Genomes
Authors: Guo Yue , Peng Zhen , Liu Jing , Yuan Na , Wang Zhen , Du Jianchang 
Published: March 2019

Background:Studies of Positively Selected Genes (PSGs) in microorganisms and mammals have provided insights into the dynamics of genome evolution and the genetic basis of differences between species by using whole genome-wide scans. Systematic investigations and comparisons of PSGs in plants, however, are still limited.Objective:A systematic comparison of PSGs between the genomes of two cotton species, Gossypium arboreum (G. arboreum) and G. raimondii, will give the key answer for revealing molecular evolutionary differences in plants.Methods:Genome sequences of G. arboreum and G. raimondii were compared, including Whole Genome Duplication (WGD) events and genomic features such as gene number, gene length, codon bias index, evolutionary rate, number of expressed genes, and retention of duplicated copies.Results:Unlike the PSGs in G. raimondii, G. arboreum comprised more PSGs, smaller gene size and fewer expressed gene. In addition, the PSGs evolved at a higher rate of synonymous substitutions, but were subjected to lower selection pressure. The PSGs in G. arboreum were also retained with a lower number of duplicate gene copies than G. raimondii after a single WGD event involving Gossypium.Conclusion:These data indicate that PSGs in G. arboreum and G. raimondii differ not only in Ka/Ks, but also in their evolutionary, structural, and expression properties, indicating that divergence of G. arboreum and G. raimondii was associated with differences in PSGs in terms of evolutionary rates, gene length, expression patterns, and WGD retention in Gossypium.
Predicting Drug-target Interactions via FM-DNN Learning
Authors: Wang Jihong , Wang Hao , Wang Xiaodan , Chang Huiyou 
Published: March 2019

Background:
Identifying Drug-Target Interactions (DTIs) is a major challenge for
current drug discovery and drug repositioning. Compared to traditional experimental approaches,
in silico methods are fast and inexpensive. With the increase in open-access experimental data,
numerous computational methods have been applied to predict DTIs.

Methods:
In this study, we propose an end-to-end learning model of Factorization Machine and
Deep Neural Network (FM-DNN), which emphasizes both low-order (first or second order) and
high-order (higher than second order) feature interactions without any feature engineering other
than raw features. This approach combines the power of FM and DNN learning for feature
learning in a new neural network architecture.

Results:
The experimental DTI basic features include drug characteristics (609), target
characteristics (1819), plus drug ID, target ID, total 2430. We compare 8 models such as SVM,
GBDT, WIDE-DEEP etc, the FM-DNN algorithm model obtains the best results of AUC(0.8866)
and AUPR(0.8281).

Conclusion:
Feature engineering is a job that requires expert knowledge, it is often difficult and
time-consuming to achieve good results. FM-DNN can auto learn a lower-order expression by FM
and a high-order expression by DNN.FM-DNN model has outstanding advantages over other
commonly used models.
Active Tip Fins for Box Wing Aircraft
Authors: Paul Jemitola O. , Gabriel Okafor E. , Abbe Godwin 
Published: March 2019

Background:
Induced drag accounts for significant percentage of cruise and total aircraft
drag. In agreement with Prandtl’s theorem, the ideal arrangement for minimum induced drag is a
closed biplane design. Past studies have implemented fixed tip fins for closed biplane design, with
the reduction of induced drag associated with fixed tip fin found to be less than optimal. A review of
patents related to the box-wing aircraft was carried out.

Methods:
In an attempt to further reduce the induced drag for box wing aircraft, this study proposed
the implementation of Active Tip Fins (ATF) for aircraft design. Athena Vortex Lattice (AVL)
software was used to simulate the induced drag associated with AFT in comparison with that of a
fixed tip fin.

Results:
From the result, the ATF design shows a superior induced drag reduction.

Conclusion:
ATF design is a novel concept that has the potential of improving box wing aircraft
performance.
Analysis of Crime Rates of Different States in India Using Apache Pig in HDFS Environment
Authors: Gupta Yogesh K. , Barhaiya Gunjan 
Published: March 2019

Background:
In this astronomically immense world tremendous amount of data engendering
in every minute from the different domain which is referred to Big Data. In the last few
years the data is incrementing day by day across the world. This Research fixates on the analysis of
malefaction rates of 5 different states year wise, all the analysis is done utilizing Apache Pig.

Methods:
The goal of the work is to analyze the astronomically immense malefaction data and find
the estimate number of malefaction transpires in sundry states. This is done in Apache pig environment
utilizing “Pig Latin” as language. A short code is indicted in Pig Latin which is utilized to
load and process the data into Map reduce environment, afterwards the result are obtained with the
detail of minimum and maximum mapper and reducer timing.

Results:
The data is visualized into graphs to make analysis to analyze the variation of malefaction
rates in distinct states. After analyzing the malefaction against women, murder cases are very high
in 2006-2010 as compared to other year groups whereas abducting and rape cases incremented perpetually
from 2001 to 2014 respectively. Similarly all the reports regarding to different malefaction
rates are visualized above by utilizing graphs.

Conclusion:
Various results are found with sundry queries and everything is represented graphically
for better understanding and comparison. This avails us to find which state is affected by which
crime. The expeditiousness of Apache pig can additionally be optically discerned as this immensely
colossal crime data processed in short time with precision.
Development of an In situ Gel Polymer Composite for Local and Sustained Delivery of Drugs in Vaginal Cavity
Authors: Boregowda Sateesha S. , Maggidi Sadanand R. , Jayaramu Rajamma A. , Puttegowda Nethravathi , Parbin Nikhat 
Published: March 2019

Objective:
The present research work is aimed at the development of an in situ gel polymer
composite to provide local and sustained delivery of therapeutic agents in the vaginal cavity. Administration
of medicated gel into a vaginal cavity is very complicated, inconvenient and needs expert assistance.
There is a chance of expulsion of liquid formulation from site of application, leads to poor therapeutic
efficacy. The effective drug delivery system for the vaginal cavity should be of liquid for application
and gel to reside in the cavity.

Methods:
In situ gel composed of chitosan (0.8%) cross-linked with β-glycerol phosphate (15%) and
glutaraldehyde treated guar gum (0.2%) was developed. Gel was characterized for in situ gelling properties.
In vitro drug release pattern of the gel was tested on a nutrient agar medium containing attenuated
E. coli and B. Subtilis. In vitro diffusion pattern of gel was tested using KC-diffusion cell with
Simulated Vaginal Fluid (SVF) (pH 4.2) as the diffusion medium.

Results:
In situ gel exhibited sharpest sol-gel transition at 35±2°C, at pH 5.4 in 62±1.31sec. The viscosity
of polymer composite is 51.25±3.68 CPs at 20±2°C and 328.56±4.16 CPs at 35±2°C. The gelation
time of gel was found to be decreasing as the concentration of cross-linking agent β-GP increased.
Formulations exhibited a shear thinning property. Drug release from this polymeric composite was
found to be highly linear and follows non-fickian diffusion mechanism.

Conclusion:
This advanced thermosensitive in situ gel is convenient to apply and reside in the vaginal
cavity for a prolonged period of time. The gel is mucoadhesive, biodegradable and suitable for controlled
drug delivery in the cavity.
Development and Evaluation of Particulate Microcarriers of Adapalene as a Topical Delivery System
Authors: Jain Divya D. , Desai Namita D. 
Published: March 2019

Background:
Adapalene is a promising third generation retinoid used in the topical treatment
of acne vulgaris. However, the major drawback associated with conventional topical therapy of
Adapalene is the ‘retinoid reaction’ which is dose-dependent and characterized by erythema, scaling
and burning sensation at the application sites. Microparticulate drug delivery can play a major role in
reducing side effects and providing better patient compliance due to targeted delivery.

Methods:
Adapalene microparticles were prepared using quasi emulsion solvent diffusion method. The
effects of formulation variables including polymer ratios, amounts of emulsifier, drug loading and process
variables such as stirring time and speed on the physical characteristics of microparticles were investigated.
The developed microparticles were characterized by DSC and SEM. Adapalene microparticles
were incorporated into Carbopol 971 NF gel for ease of topical delivery.

Results:
Adapalene microparticulate topical gel showed sustained drug release over 8 hours in in vitro
studies. The amount of drug retained in the rat skin during ex vivo studies was higher in the microparticulate
topical gel (227.43 ± 0.83 µg/cm2) as compared to the marketed formulation (81.4 ±
1.11 µg/cm2) after 8 hours indicating localized and sustained drug action that can be useful in treating
acne vulgaris. The safety of optimized Adapalene gel determined by skin irritation studies performed on
Sprague Dawley rats showed no irritation potential.

Conclusion:
Microparticles can provide promising carrier systems to deliver Adapalene, improving patient
compliance due to enhanced skin deposition, localized and sustained action with reduced associated
irritant effects.
Synthesis, In vitro and In silico Studies of Benzothiazole Azo-Ester Derivatives as Anti-TB Agents
Authors: Bhat Mahesh , Belagali Shiddappa L. 
Published: March 2019

Introduction:A new series of benzothiazole azo-ester derivatives was synthesized by using Steglish esterification reaction.Methods:All the synthesized compounds were screened for their anti-TB activities by in vitro microplate Alamar Blue assay method against M. tuberculosis (H37RV strain). All the compounds showed activities and their MIC values were over the range of 1.6 µg/mL to 50 µg/mL. The compounds 4d and 4j showed superior activity with MIC 1.6 µg/mL compared to the standard drug Streptomycin (MIC 6.25 µg/mL), Pyrazinamide (MIC 3.125 µg/mL) and Ciprofloxacin (MIC 3.125 µg/mL).Results:Molecular docking study was carried out with enoyl acyl carrier reductase (InhA) of M. tuberculosis and decaprenyl phosphoryl-D-ribose oxidase (DprE1).Conclusion:These studies showed that these compounds have more interaction with InhA protein whereas some compounds could not be docked into DprE1.
Development of Usnic Acid Embedded Eudragit Microspheres for Alleviation of Nosocomial Infections
Authors: Pandey Shraddha , Misra Shashi K. , Sharma Nisha 
Published: March 2019

Background:
Usnic Acid has been progressively reported in the literature as one of the chiefly
significant lichen metabolites exemplified by an ample diversity of applications such as antimicrobial, antifungal,
antiviral, antiprotozoal agents, etc. Herein, we shed a light on nosocomial infections and formulated
topical microspheres loaded with Usnic acid for improved antimicrobial activity. Recent patents and
novel researches were referred to pursue the present work.

Methods:
Usnic acid embedded Eudragit microspheres were designed applying solvent evaporation method,
investigated for topography and drug-polymer compatibility studies. Dialysis bag method was utilized
for studying drug release kinetics. In vitro antibacterial assay was carried out against the virulent bacterial
strain of Staphylococcus aureus using the disc diffusion method.

Results:
Topography studies revealed the formation of regular, micro-sized, smooth surface microspheres.
Well defined and specific structural peaks were obtained from FTIR and TGA studies, revealing drugpolymer
compatibility. The dissolution profile suggested Korsmeyer Peppas kinetic and Fickian kind of
diffusion from microspheres. The pre-eminent activity of formulated microspheres was visualized from the
disc diffusion study against Staphylococcus aureus.

Conclusion:
The strong biological activity of Usnic acid –loaded Eudragit RS and Eudragit RL microspheres
provides a promising application for corresponding material as a bactericidal agent for the
alleviation of nosocomial infection. Findings paid attention to the potential of usnic acid microspheres for
effective treatment of dermal and nosocomial infections caused by S. aureus.
Synergistic Effects of Essential Oils of Ammoides verticillata and Satureja candidissima Against Many Pathogenic Microorganisms
Authors: Benyoucef Fatima , Dib Mohammed El Amine , Tabti Boufeldja , Zoheir Arrar , Costa Jean , Muselli Alain 
Published: March 2019

Background:
Antibiotic resistance is today one of the most serious threats to global health, food
security and development. Due to the growing number of infections, treatment becomes more difficult, if
not impossible, because of the loss of antibiotic efficacy.

Objective:
In the present investigation, the chemical composition of essential oils of Ammoides verticillata
and Satureja candidissima and their synergistic effects on antimicrobial activities were investigated.

Methods:
The chemical composition of the essential oil was analyzed by Gas Chromatography (GC) and
Gas Chromatography-Mass Spectroscopy (GC/MS). The antimicrobial activity of the essential oils was investigated
using dilution-agar method against nine bacterial strains three Gram-negative Escherichia coli
(ATCC 25922), Pseudomonas aeruginosa (ATCC 27853) and Salmonella typhi (ATCC 14028), and six
Gram-positive: Staphylococcus aureus (ATCC 43300,) Clostridium sporogenes (ATCC 19404), Bacillus
subtilis (ATCC 6633), Enterococcus faecalis (ATCC 7314), Lactobacillus rhamnosus (ATCC 53103) and
Bacillus cereus (ATCC 14579).

Results:
The essential oil of A. verticillata was characterized principally by carvacrol (44,3%), Limonene
(19,3%) and p-cymene (19,2%). The constituents identified of S. candidissima essential oil were principally
oxygenated monoterpenes represented by pulegone (70,4%). The essential oil of A. verticillata had a
good antimicrobial activity against four bacterial strains (Escherichia coli, Salmonella typhi, Lactobacillus
rhamnosus and Bacillus cereus) with MIC and MBC values between 0.2-0.4 µl/ml and 0.2-6.2 µl/ml, respectively.
While, S. candidissima essential oil had moderate antimicrobial activities against all strains
with MIC and MBC values between 1.5-6.2 µl/ml and 6.2-12.5 µl/ml, respectively. The results of antimicrobial
activity of essential oils blend presented higher antimicrobial activity against all tested bacteria
with MIC and MBC values between 0.3-1.5 µl/ml and 0.4-6.2 µl/ml, respectively.

Conclusion:
The essential oils blend presented high antimicrobial activity compared to virgin oils. This
activity can be due to the association of active compounds such as carvacrol and pulegone. These findings
provide a new source of drugs that may help in therapy to lead to the development of a new treatment
based on a combination of these essential oils against gram-negative and gram-positive bacteria that continue
to pose a threat to public health.
Real-Time Detection of Road Lane-Lines for Autonomous Driving
Authors: Farag Wael 
Published: March 2019

Background:
Enabling fast and reliable lane-lines detection and tracking for advanced
driving assistance systems and self-driving cars.

Methods:
The proposed technique is mainly a pipeline of computer vision algorithms that augment
each other and take in raw RGB images to produce the required lane-line segments that represent the
boundary of the road for the car. The main emphasis of the proposed technique in on simplicity and
fast computation capability so that it can be embedded in affordable CPUs that are employed by
ADAS systems.

Results:
Each used algorithm is described in details, implemented and its performance is evaluated
using actual road images and videos captured by the front mounted camera of the car. The whole
pipeline performance is also tested and evaluated on real videos.

Conclusion:
The evaluation of the proposed technique shows that it reliably detects and tracks road
boundaries under various conditions.
Test Case Prioritization Using Bat Algorithm
Authors: Bajaj Anu , Sangwan Om P. 
Published: March 2019

Background:
Regression testing is very important stage of software maintenance and
evolution phase. The software keeps on updating and to preserve the software quality, it needs to be
retested every time it is updated. Due to limited resources, complete testing of the software becomes
tedious task. The probable solution to this problem is to execute those test cases first that are more
important prior to less important test cases.

Objective:
Optimization methods need to be acquired for efficient test case prioritization in minimum
time, while maintaining the quality of the software. Various nature-inspired algorithms like
genetic algorithm, particle swarm optimization and ant colony optimization, etc. have been applied
for prioritizing test cases. In this paper, we have applied a relatively new nature-inspired optimization
method, namely, Bat algorithm that utilizes the echolocation, loudness and pulse emission rate
of bats in prioritizing the test cases.

Methods:
The proposed algorithm is experimented on sample case study of timetable management
system and evaluated with the help of popular evaluation metric Average Percentage of Fault Detection.

Results:
Results have been compared with the baseline approaches i.e. untreated, random and reverse
prioritization and well-established optimization method i.e. genetic algorithm and we have
found a considerable increase in the value of evaluation metric.

Conclusion:
This preliminary study shows that the bat algorithm have great potential to solve test
case prioritization problems.
Withdrawn: Diabetes Mellitus Prognosis Using Fuzzy Logic and Neural Networks Case Study: Alexandria Vascular Center (AVC)
Authors: Amer Abeer A. , Ismail Soha M. 
Published: March 2019

The following article has been withdrawn on the request of the author of the journal Recent Advances in Computer
Science and Communications (Recent Patents on Computer Science):;.

Title:
Diabetes Mellitus Prognosis Using Fuzzy Logic and Neural Networks Case Study: Alexandria Vascular Center (AVC)

Authors:
Abeer A. Amer and Soha M. Ismail*

Bentham Science apologizes to the readers of the journal for any inconvenience this may cause.

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