bluuebunny/crossref_metadata_2025_split huggingface dataset:
Risks Associated with Vortioxetine in the Established Therapeutic Indication
Authors: Verma Akansha , Kumar Anoop 
Published: August 2020

Background:
Vortioxetine is approved for the treatment of Major Depressive Disorder
(MDD). However, the safety of this drug in a large group of populations is still unclear. Thus, we
have tried to analyze the risk profile of vortioxetine.

Material and Methods:
The data related to the risk profile of vortioxetine has been extracted from
Pub-Med from January 2014 to May 2019. The adverse drug reactions (ADRs) have been categorized
into listed and unlisted categories as per the Summary of product characteristics (SmPC) of
the innovator. Further, unlisted ADRs have been analyzed as per Naranjo Scale.

Results:
Galactorrhea, hyperprolactinemia, glycolimia, exacerbation of anxiety, weight gain, edema,
excessive itching, petechiae, and ecchymoses have been observed with the use of vortioxetine
and falls under the unlisted category. Further, the causality assessment results have shown a probable
relation between vortioxetine and galactorrhea, hyperprolactinemia, edema, excessive itching,
ecchymoses, and petechiae. Weight gain, glycolimia and exacerbation of anxiety have a possible relationship
with vortioxetine. The common ADRs observed with the use of vortioxetine are nausea,
diarrhea, constipation, vomiting, pruritus, including pruritus generalized, abnormal dreams, and
dizziness.

Conclusion:
In conclusion, more data is required to establish a strong relationship between vortioxetine
and reported unlisted ADRs.
Withdrawal Notice: Anti-cancer Effect of Urginea Maritima Bulb Extract In Vitro through Cell Cycle Arrest and Induction of Apoptosis in Human Breast Cancer Cell Lines
Authors: Saket Khadije , Salari Roshanak , Saburi Ehsan , Yousefi Mahdi , Khodadoust Mohammad Ali , Hadi Mahdieh , afshari Jalil Tavakol 
Published: August 2020

The article has been withdrawn by agreement between the editors and publisher of Current Drug Discovery Technologies. The
authors are not responding to the editor’s requests to provide the language-edited version.

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

The Bentham Editorial Policy on Article Withdrawal can be found at https://benthamscience.com/editorial-policies-main.php

Bentham Science Disclaimer:
It is a condition of publication that manuscripts submitted to this journal have not been published and will not be simultaneously
submitted or published elsewhere. Furthermore, any data, illustration, structure or table that has been published elsewhere
must be reported, and copyright permission for reproduction must be obtained. Plagiarism is strictly forbidden, and by submitting
the article for publication the authors agree that the publishers have the legal right to take appropriate action against the
authors, if plagiarism or fabricated information is discovered. By submitting a manuscript, the authors agree that the copyright
of their article is transferred to the publishers if and when the article is accepted for publication.
In Silico Based Structural and Fingerprint Analysis of Structurally Diverse AT1 inhibitors
Authors: Moorthy Narayana Subbiah Hari Narayana 
Published: August 2020

Background and Objective:
The development of pharmacologically active molecules
for the treatment of hypertension and other cardiovascular diseases are important nowadays. In the
present investigation, computational techniques have been implemented on Angiotensin II Type 1
(AT1) antagonists to develop better predictive models.

Methods:
Quantitative Structure Activity Relationship (QSAR) and structural patterns/fragments
analyses were performed using physicochemical descriptors and MACCS Fingerprints calculaced
from AT1 inhibitors collected from the literature.

Results:
The significant models developed have been validated by Leave One Out (LOO) and test
set methods, which exhibit considerable Q2 values (>0.65 for the training set and >0.5 for the test
set) and the R2pred values for the models are also >0.5. The applicability of the contributed descriptors
in these models revealed that the chlorine atom, dipole moment, hydrogen bond donor atoms
and electrostatic potential are negatively contributing, and the presence of bond between
heavy atoms and the carbon atom connected with small side chain and topological polar vdW surface
area are favorable for the AT1 antagonistic activity. The MACCS Fingerprints showed that the
presence of atoms (kind of heavy atoms), such as N, O, and S, connected with other heteroatoms or carbon
or any other atoms, through single or double bonds are predominantly present in highly active molecules.
The presence of halogens, long chain alkanes, halogenated alkanes, and sulfur atoms attached with
nitrogen through any atoms are responsible for decreased AT1 antagonistic activity.

Conclusion:
The results have provided additional information on the structural patterns of the
compounds based on its MACCS Fingerprints, which may be used for further characterization and
design of novel AT1 inhibitors.
Identification of Flavonoids by LC-MS/MS in Leaves Extract From Protium heptaphyllum(Aubl.) March and Antioxidant Activity in Mice
Authors: Patias Naiéle Sartori , Gindri Sinhorin Valéria Dornelles , de Moura Fernando Rafael , da Cunha Ana Paula Simóes , da Silva Lima Ritane Rose , da Costa Thaniara Barbosa , da Costa Romeu José , Cavalheiro Larissa , de Campos Bicudo Rogério , Sinhorin Adilson Paulo 
Published: August 2020

Background:
Protium heptaphyllum (Aubl.) March resin is accepted as an analgesic,
healing, expectorant, anti-inflammatory, antinociceptive and gastroprotective agent. However,
there are no specific studies on leaves of this plant.

Objective:
This study identified the chemical composition and biological activity of crude ethanolic
extract (EE) and ethyl acetate (EA) fraction from P. heptaphyllum.

Methods:
Mice were intoxicated with acetaminophen (PCM; 250 mg kg-1), and subsequently treated
with EE and EA (100 mg kg-1) for 7 days via gavage. Plasma analysis and evaluation of liver
and kidney homogenates of the animals were performed.

Results:
The extract and fraction showed the presence of phenols and flavonoids. Three main
flavonoids were identified by HPLC-UV, LC-MS/MS fractionation, quercetin-3-β-D-glycoside,
myricetin and quercetin. For total antioxidant potential tests, EE presented EC50 of 75 mg kg-1 and
100 μg mL-1 for EA. ALT, AST and ALP enzymes activity increased in the PCM-exposed plasma,
but EA decreased these activities at control levels for ALT and AST. Animal glycemic levels decreased
with EE and EA, which may be due to a possible hypoglycemic effect of the plant. In the
liver tissue, SOD was unchanged, CAT, GSH and ASA decreased in the PCM group, but EA was
able to reverse these effects. TBARS and PC were reduced by both treatments. In the renal tissue,
EA fraction recovered the GST activity, GSH levels were restored by EE and EA and PC was reduced
by treatments.

Conclusion:
This antioxidant effect may be due to the presence of the flavonoids identified, which
are already well known for their antioxidant properties.
Insight on Ameliorative Role of Selenium Nanoparticles and Niacin in Wound Healing on Adult Female Albino Mice
Authors: Emam Marwa , Keshta Akaber T. , Mohamed Yasser M.A. , Attia Yasser A. 
Published: August 2020

Background:
Wound healing is a complex process necessary for repairing damaged
tissues and preventing infection. Selenium nanoparticles (Se NPs) were known due to
their antioxidant and antimicrobial effects, also niacin has angiogenesis and antioxidant effects
that are important in wound healing.

Objective:
The present study was conducted to investigate the effect of Se NPs and niacin in
reducing and accelerating the wound healing time in mice.

Methods:
A simple wet chemical method has been modified to synthesize Se NPs in order to
investigate their effect and niacin on reducing the wound healing in 80 adult female albino
mice (250 mm2 full thickness open excision wound) that were divided into eight groups (10
mice/each). After 30-days, the mice were sacrificed, blood and tissue samples were taken for
analysis.

Results:
The results showed that the percentage of wound area had been significantly reduced
in Se NPs and niacin treated groups compared to the positive control. The level of
Vascular Endothelial cell Growth Factor and Collagenase I in Se NPs and niacin groups significantly
exceed those of other groups while Nitric Oxide (NO) was significantly decreased
in treated groups. Liver and kidney functions showed the lower toxicity effect of Se NPs and
niacin. Skin tissue showed the wound healing effect of Se NPs and niacin by regenerating
skin layer compared to the positive group.

Conclusion:
Se NPs and niacin play an important role in accelerating and reducing the time
of wound healing while they were antagonistic to each other.
Study of Antioxidant, Antiproliferative and DNA Damage Protecting Activities of Cinnamomum cassia Extracts Obtained by Sequential Extraction
Authors: Rad Sima Kianpour , Movafagh Abolfazl 
Published: August 2020

Background:
Cinnamomum cassia (C. cassia) is an evergreen tree in China and Southern
and Eastern Asia. In traditional medicine, cinnamon is widely used due to its many bioactivity
effects.

Objective:
The present novel study aims to evaluate and make a comparison of antioxidant and antiproliferative
activities of different extractions of C. cassia bark using seven solvents having different
polarities. Solvents polarity gradients start with the solvent of lower polarity, n-hexane, and
end with water as the highest polar solvent. Among the extracts, acetone extract contains the highest
phenolic and flavonoid contents; therefore, it is assessed for the ability to protect DNA from
damage.

Methods:
The extracts are evaluated for total phenolic, flavonoid contents and antioxidant activities,
using FRAP, DPPH, superoxide, and hydroxyl and nitric oxide radicals scavenging assays.
DNA damage protecting activity of the acetone extract is studied with the comet assay. Each of the
extracts is studied for its antiproliferative effect against, MCF-7, MDA-MB-231(breast cancer), and
HT29 (colon cancer), using MTT assay.

Results:
The acetone extract exhibited the highest FRAP value, phenolic and flavonoids contents
when compared to the other extracts and could protect 45% mouse fibroblast cell line (3T3-L1)
from DNA damage at 30 μg/ml. The lowest IC50 value in DPPH, superoxide, and hydroxyl radicals
scavenging was noticed in the ethyl acetate extract. IC50 value obtained for the hexane extract was
the lowest compared to the other extracts in scavenging nitric oxide radicals. The hexane extract
showed the highest antiproliferative effect against cancer cells followed by the chloroform extract.
The ethyl acetate extract inhibited the proliferation of only MCF-7 by IC50 of 100 μg/ml, while the
other extracts exhibited no IC50 in all the cancer cells.

Conclusions:
C. cassia showed promising antioxidant and anticancer activities with significant
DNA damage protecting effect.
Effect of Different Dentifrices, Bleaching with 35% Hydrogen Peroxide, and Red Wine on Surface Color and Roughness of Bovine Enamel
Authors: Garcia Raíssa Manoel , Vieira-Junior Waldemir Francisco , Theobaldo Jéssica Dias , Pini Núbia Inocencya Pavesi , Ambrosano Glaucia Maria Bovi , Aguiar Flávio Henrique Baggio , Leite Lima Débora Alves Nunes 
Published: August 2020

Objective:
To evaluate color and roughness of bovine enamel exposed to dentifrices,
dental bleaching with 35% hydrogen peroxide (HP), and erosion/staining by red wine.

Methods:
Bovine enamel blocks were exposed to: artificial saliva (control), Oral-B Pro-Health (stannous
fluoride with sodium fluoride, SF), Sensodyne Repair & Protect (bioactive glass, BG), Colgate
Pro-Relief (arginine and calcium carbonate, AR), or Chitodent (chitosan, CHI). After toothpaste
exposure, half (n=12) of the samples were bleached (35% HP), and the other half were not
(n=12). The color (CIE L*a* b*, ΔE), surface roughness (Ra), and scanning electron microscopy
were evaluated. Color and roughness were assessed at baseline, post-dentifrice and/or -dental
bleaching, and after red wine. The data were subjected to analysis of variance (ANOVA) (ΔE) for
repeated measures (Ra), followed by Tukey´s test. The L*, a*, and b* values were analyzed by generalized
linear models (a=0.05).

Results:
The HP promoted an increase in Ra values; however, the SF, BG, and AR did not enable
this alteration. After red wine, all groups apart from SF (unbleached) showed increases in Ra values;
SF and AR promoted decreases in L* values; AR demonstrated higher ΔE values, differing
from the control; and CHI decreased the L* variation in the unbleached group.

Conclusion:
Dentifrices did not interfere with the bleaching efficacy of 35% HP. However, dentifrices
acted as a preventive agent against surface alteration from dental bleaching (BG, SF, and
AR) or red wine (SF). Dentifrices can decrease (CHI) or increase (AR and SF) staining by red
wine.
Medical Comorbidity in Elderly Schizophrenic Patients: A Preliminary Study in Iran
Authors: Shafti Saeed Shoja , Memarie Alireza , Rezaie Masomeh , Rahimi Behjat 
Published: August 2020

Background:
While comorbidity between mental disorders and physical illnesses is the
rule rather than an exception, appraising the impact of comorbidity is challenging due to lack of
consensus about how to define and measure the concept of comorbidity.

Objective:
The aim of the present evaluation was to appraise the prevalence and features of medical
comorbidities among a group of native elderly schizophrenic patients.

Methods:
Geriatric unit of Razi psychiatric hospital was selected as the field of investigation and
168 elderly schizophrenic patients (≥65 years old), including 101 males and 67 females, who have
been hospitalized there as chronic cases, were chosen as an accessible sample, and were surveyed
with respect to existing comorbid medical disorders. Psychiatric diagnosis was based on ‘Diagnostic
and Statistical Manual of Mental Disorders’, 5th edition (DSM-5), and the medical diagnosis was
based on ‘International Classification of Diseases’, 10th edition.

Results:
As shown by the results, 89% (n=151) of elderly schizophrenic patients had some kind of
registered physical co-morbidity, which was more significant than the frequency of medical comorbidities
among native senior citizens. Amongst the listed co-morbidities, falls, hypertension and
osteoarthritis were the most prevalent comorbidities with a frequency of around 48.8%, 44.6% and
39.2%, respectively. Hypertension, renal disease and malnutrition were significantly more prevalent
among male patients (p<0.0000, p<0.0045 and p< 0.0018, respectively) and hyponatremia, aspiration/
asphyxiation and seizure were meaningfully more prevalent among female patients (p<0.0075,
p<0.0000 and p<0.0009, respectively). As stated by the findings and in comparison with the native
seniors, while diabetes, renal diseases and malnutrition were significantly more frequent, coronary
artery disease, gastrointestinal disorder and osteoarthritis were significantly less frequent in the existing
sample of elderly schizophrenic patients.

Conclusion:
In comparison with the native senior people, the rate of medical comorbidities, particularly
diabetes, renal diseases and malnutrition, was significantly higher in elderly schizophrenic
patients, a significant difference, was observed regarding physical comorbidities between male and
female patients, which demands further methodical and gender-based studies for defining more
appropriate care.
A New Approach for EOQ Calculation Using Modified Opportunity Cost
Authors: Singh Juhi , Mittal Mandeep , Pareek Sarla 
Published: August 2020

Introduction:
Optimal inventory levels are necessary for a firm to avoid shortage/excess of an item. Shortage of
an item leads to stock out conditions which results in loss of profit. When items are correlated with each other, stock out
condition of one item may result in non purchase of its associated items also which, in turn, further brings down the profit.
In this paper, this loss in profit is used to modify opportunity cost of an item resulting in its modified EOQ.

Method:
One illustrative example has been discussed which incorporates purchase dependencies in retail multi-item inventory management. The model discussed in this research paper will be motivational for researchers and inventory managers
and provides a method for incorporating correlation among items while managing inventory.

Result:
The EOQs of items are estimated both by using traditional method and then by using modified opportunity cost
(modeled as loss profit). Results show that in frequent item set A, B, D, EOQs of all three items increased when correlation among them is considered resulting in increase in profit.

Conclusion:
One of the major focus areas of inventory management is to determine when and how much quantity of items
needs to be ordered so that total inventory cost can be minimized and profit of a firm can be maximized. However, while
calculating the true value of an item and the profit it brings to the firm, it is very essential to analyze its effect on the sale
of other items. Asso-ciation rule mining provides a way to correlate items by calculating support and confidence factor.

Discussion:
In inventory management system, for increasing the profit of a firm, EOQs of items need to be calculated in
order to avoid shortage or excess of inventory. For explaining the approach a very small database is taken consisting of only 5 items and 10 transactions therefore the increase in profit is minimal however, when this approach applies on real database consisting of thousands of items and transactions, the increase in profit will be significant.
Door Knob Security
Authors: Kumar Mohit , Goel Kushagra , Kandpal Rakshit , Jain Sanchit , Saxena Shikha , Sharmila  
Published: August 2020

Introduction:
This paper deals with research on the security of houses that are vulnerable to door locking
systems. Usually, doors are locked with keys whether computerized keys or man-made locks. But the key unlocking
system is vulnerable as keys can be lost or stolen and might be duplicated.

Method:
This methodology works using the Morse code that is delivered to the person standing outside the door to get
in. The Morse code is generated randomly from software so the code can’t be duplicated.

Result:
The project was done to accomplish the goal of security on the door lock. The student worked on the project individually with assistance from the professor, whenever necessary. The project could potentially be a group project for
two or more students, allowing each student to focus on a particular aspect of the project, such as hardware or soft-ware.

Conclusion:
Most of the documentation accessed online was missing configuration steps and all of them were using a
button to regenerate a secret code. The documents do not cover all potential issues which were addressed.

Discussion:
Artificial Intelligence will be added so that the door-knob mecha-nism will not work if anyone member is
already inside. The mechanism will be made access remotely in case the owner allows someone but the owner is not
present there at that moment.
Energy Adaptive and Max-Min based BFS Model for Route Optimization
in Sensor Network
Authors: Juneja Kapil 
Published: August 2020

Background:
The restricted energy and network life is a critical issue in the real-time sensor network. The occurrence of low-energy and faulty intermediate nodes can increase communication failure. The number of intermediate
nodes affects the number of re-transmission, communication-failures, and increases the energy consumption on the routing
path. The existing protocols take the greedy decision on all possible intermediate nodes collectively by considering one or
more parameters.

Objective:
This work divides the distance between the source and destination into coverage-specific zones for restricting
the hop-count. Now each zone is processed individually and collectively for generating the energy effective and failure
preventive route.

Methods:
In this paper, the energy and coverage weighted BFS (Best First Model) algorithm is presented for route optimization in the sensor network. The max-min BFS is implied on sensor nodes of each zone and identified as the most reliable
and effective intermediate node. The individual and composite weighted rules are applied to energy and distance parameters. This new routing protocol discovered the energy-adaptive route.

Results:
The proposed model is simulated on a randomly distributed network, and the analysis is done in terms of network
life, energy consumption, hop count, and the number of route switching parameters. The comparative analysis is done
against the MCP, MT-MR, Greedy, and other state-of-art routing protocols.

Conclusion:
The comparative results validate the significance of the proposed routing protocol in terms of energy effectiveness, lesser route switching, and improved the network life.
SVM Kernel and Genetic Feature Selection Based Automated Diagnosis of Breast Cancer
Authors: Singh Indu , Garg Shashank , Arora Shivam , Arora Nikhil , Agrawal Kripali 
Published: August 2020

Background:
Breast cancer is the development of a malignant tumor in the breast of human beings (especially
females). If not detected at the initial stages, it can substantially lead to an inoperable construct. It is a reason for majority
of cancer-related deaths throughout the world.

Objectives:
The main aim of our study is to diagnose the breast cancer at early stage so that required treatment can be
provided for survival. The tumor is classified as malignant or benign accurately at early stage using a novel approach that
includes an ensemble of Genetic Algorithm for feature selection and kernel selection for SVM-Classifier.

Methods:
The proposed GA-SVM (Genetic Algorithm – Support Vector Machine) algorithm in this paper optimally
selects the most appropriate features for training with the SVM classifier. Genetic Programming is used to select the
features and the kernel for the SVM classifier. Genetic Algorithm operates by exploring the optimal layout of features for
breast cancer, thus, subjugating the problems faced in exponentially immense feature space.

Results:
The proposed approach accounts for a mean accuracy of 98.82% by using the Wisconsin Diagnostic Breast
Cancer (WDBC) dataset available on UCI with the training and testing ratio being 50:50 respectively.

Conclusion:
The results prove that our proposed model outperforms the previously designed models for breast cancer
diagnosis. The outcome assures that the GA-SVM model may be used as an effective tool in assisting the doctors for
treating the patients. Alternatively, it may be utilized as an alternate opinion in their eventual diagnosis.