bluuebunny/crossref_metadata_2025_split huggingface dataset:
Predicting Drug-Target Affinity Based on Recurrent Neural Networks
and Graph Convolutional Neural Networks
Authors: Tian Qingyu , Ding Mao , Yang Hui , Yue Caibin , Zhong Yue , Du Zhenzhen , Liu Dayan , Liu Jiali , Deng Yufeng 
Published: February 2021

Background:
Drug development requires a lot of money and time, and the outcome of the challenge is unknown. So, there is an urgent need for researchers to find a new approach that can reduce costs. Therefore, the identification of drug-target interactions (DTIs) has been a critical step in the early stages of drug discovery. These computational methods aim to narrow the search space for novel DTIs and to elucidate the functional background of drugs. Most of the methods developed so far use binary classification to predict the presence or absence of interactions between the drug and the target. However, it is more informative, but also more challenging, to predict the strength of the binding between a drug and its target. If the strength is not strong enough, such a DTI may not be useful. Hence, the development of methods to predict drug-target affinity (DTA) is of significant importance.

Method:
We have improved the Graph DTA model from a dual-channel model to a triple-channel model. We interpreted the target/protein sequences as time series and extracted their features using the LSTM network. For the drug, we considered both the molecular structure and the local chemical background, retaining the four variant networks used in Graph DTA to extract the topological features of the drug and capturing the local chemical background of the atoms in the drug by using BiGRU. Thus, we obtained the latent features of the target and two latent features of the drug. The connection of these three feature vectors is then input into a 2-layer FC network, and a valuable binding affinity is output.

Result:
We use the Davis and Kiba datasets, using 80% of the data for training and 20% of the data for validation. Our model shows better performance by comparing it with the experimental results of Graph DTA.

Conclusion:
In this paper, we altered the Graph DTA model to predict drug-target affinity. It represents the drug as a graph, and extracts the two-dimensional drug information using a graph convolutional neural network. Simultaneously, the drug and protein targets are represented as a word vector, and the convolutional neural network is used to extract the time series information of the drug and the target. We demonstrate that our improved method has better performance than the original method. In particular, our model has better performance in the evaluation of benchmark databases.
Putative Roles of Astrocytes in General Anesthesia
Authors: Mulkey Daniel K. , Olsen Michelle L. , Ou Mengchan , Cleary Colin M. , Du Guizhi 
Published: February 2021

:
General anesthetics are a mainstay of modern medicine, and although much progress has been made towards identifying molecular targets of anesthetics and neural networks contributing to endpoints of general anesthesia, our understanding of how anesthetics work remains unclear. Reducing this knowledge gap is of fundamental importance to prevent unwanted and life-threatening side-effects associated with general anesthesia. General anesthetics are chemically diverse, yet they all have similar behavioral endpoints, and so for decades research has sought to identify a single underlying mechanism to explain how anesthetics work. However, this effort has given way to the ‘multiple target hypothesis’ as it has become clear that anesthetics target many cellular proteins including GABAA receptors, glutamate receptors, voltage-independent K+ channels and voltage-dependent K+, Ca2+ and Na+ channels, to name a few. Yet, despite evidence that astrocytes are capable of modulating multiple aspects of neural function and express many anesthetic target proteins, they have been largely ignored as potential targets of anesthesia. The purpose of this brief review is to highlight effects of anesthetic on astrocyte processes and identify potential roles of astrocytes in behavioral endpoints of anesthesia (hypnosis, amnesia, analgesia and immobilization).
Glutamate NMDA Receptor Antagonists with Relevance to Schizophrenia:
A Review of Zebrafish Behavioral Studies
Authors: Piato Angelo , Benvenutti Radharani , Gallas-Lopes Matheus , Marcon Matheus , Reschke Cristina R. , Herrmann Ana Paula 
Published: February 2021

:
Schizophrenia pathophysiology is associated with hypofunction of glutamate NMDA
receptors (NMDAR) in GABAergic interneurons and dopaminergic hyperactivation in subcortical
brain areas. The administration of NMDAR antagonists is used as an animal model that replicates
behavioral phenotypes relevant to the positive, negative, and cognitive symptoms of schizophrenia.
Such models overwhelmingly rely on rodents, which may lead to species-specific biases and poor
translatability. Zebrafish, however, is increasingly used as a model organism to study evolutionarily
conserved aspects of behavior. We thus aimed to review and integrate the major findings reported in
the zebrafish literature regarding the behavioral effects of NMDAR antagonists with relevance to
schizophrenia. We identified 44 research articles that met our inclusion criteria from 590 studies
retrieved from MEDLINE (PubMed) and Web of Science databases. Dizocilpine (MK-801) and
ketamine were employed in 29 and 10 studies, respectively. The use of other NMDAR antagonists,
such as phencyclidine (PCP), APV, memantine, and tiletamine, was described in 6 studies. Frequently
reported findings are the social interaction and memory deficits induced by MK-801 and
circling behavior induced by ketamine. However, mixed results were described for several locomotor
and exploratory parameters in the novel tank and open tank tests. The present review integrates
the most relevant results while discussing variation in experimental design and methodological
procedures. We conclude that zebrafish is a suitable model organism to study drug-induced behavioral
phenotypes relevant to schizophrenia. However, more studies are necessary to further characterize
the major differences in behavior as compared to mammals.
MicroRNAs and Diabetes Mellitus Type 1
Authors: Rezaei Nima , Bahreini Farbod , Rayzan Elham 
Published: February 2021

:
Type 1 diabetes mellitus is a multifactorial, progressive, autoimmune disease with a strong genetic feature that can affect multiple organs, including kidney, eyes, and nerves. Early detection of type 1 diabetes can help critically to avoid serious damages to these organs. MicroRNAs are small RNA molecules that act in post-transcriptional gene regulation by attaching to the complementary sequence in the 3'-untranslated region of their target genes. Alterations in the expression of microRNA coding genes are extensively reported in several diseases such as type 1 diabetes. Presenting non-invasive biomarkers for early detection of type 1 diabetes by quantifying microRNAs gene expression level can be an influential step in biotechnology and medicine. This review discusses the area of microRNAs dysregulation in type 1 diabetes and affected molecular mechanisms involved in pancreatic islet cells formation and dysregulation in the expression of inflammatory elements as well as pro-inflammatory cytokines.
Involvement of YAP/TAZ Signaling Pathway in Anti-obesity Activity of Moringa oleifera Leaf Extract
Authors: Nurhayati Titing , Anton  , Setiawan Iwan , Tarawan Vita Murniati , Lesmana Ronny 
Published: February 2021

Introduction:
Obesity has become a pandemic chronic disease. The main principle of obesity
treatment is to regulate energy balance by reducing energy intake and increasing energy expenditure.
These target mechanisms have become the point of attention in herbal medicine studies. Several molecular
mechanisms of actions possessed by Moringa oleifera leaf extract (MLE) have been studied in
many experimental research works.

Objective:
In this mini-review, we encompass the mechanisms of MLE in demonstrating the antiobesity
activity, including the potential involvement of YAP/TAZ activity.

Methods:
Several major electronic databases, including PubMed, Google Scholar, and Scopus, were
used in selecting articles from the period between August 2011 and August 2020.

Results:
From 18 established pieces of literature, we demonstrated the anti-obesity activity of MLE in
detail. Several citations accompanied the results of these researched-based studies to explain and illustrate
the molecular mechanisms, including YAP/TAZ signaling pathway.

Conclusion:
MLE, through its phytochemistry contents, shows significant benefits in herbal medicine,
especially the anti-obesity activity. MLE potentially contributes to modify the lipid metabolism in
YAP/TAZ pathway. However, the study demonstrating this involvement has still not published. In the
future, more exploration may provide hope for its efficacy and safety as the therapeutic agent of obesity.
Risk Factors Identification and Prediction of Anemia among Women in Bangladesh using Machine Learning Techniques
Authors: Islam Md. Merajul , Rahman Md. Jahanur , Roy Dulal Chandra , Islam Md. Moidul , Tawabunnahar Most. , Ahmed N.A.M. Faisal , Maniruzzaman Md. 
Published: February 2021

Background:Anemia is a major public health problem with raising prevalence worldwide, including Bangladesh.Objectives:To identify the risk factors of anemia among women in Bangladesh and its prediction using Machine Learning (ML) based techniques.Methods:The anemia dataset, comprising of 3,020 respondents, was extracted from the Bangladesh Demographic and Health Survey (BDHS). Two feature selection techniques as Logistic Regression (LR) and Random Forest (RF), have been utilized to determine the risk factors of anemia. Additionally, eight ML-based techniques, namely LR, Linear Discriminant Analysis (LDA), K-Nearest Neighborhood (KNN), Support Vector Machine (SVM), Quadratic Discriminant Analysis (QDA), Neural Network (NN), Classification And Regression Tree (CART), and RF have also been utilized to predict anemia disease among women in Bangladesh. Classification accuracy and Area Under the Curve (AUC) are used to evaluate the performances of these classifiers.Results:LR and RF-based feature selection results indicate that out of 15 factors, 13 for LR and 14 factors for RF appear to be significant risk factors for anemia among women. All predictive models provide the highest classification accuracy and AUC of 74.10-81.29% and 0.744-0.819 under RF features. However, the combination of RF-based feature selection along with RF-based classifier gives the highest classification accuracy (81.29%) and AUC (0.819).Conclusion:Out of the eight predictive models, RF-RF based combination model shows the best performance for the prediction of anemia. This study suggests policymakers to make appropriate decisions to control the anemia using RF-RF combination to save time and reduce the cost for Bangladeshi women.
Effect of Solvent Type, Extraction Temperature, Agitation Speed and Microwave
Power on Phenolic Compound Extraction and Antioxidant Activity
of Apricot Kernels ((Prunus armeniaca L.)
Authors: Teffane Mohand , Boudries Hafid , Bey Mostapha Bachir , Kadi Ahcene , Boukhalfa Farid 
Published: February 2021

Background:
Prunus armeniaca L. is widely cultivated around the world. High consumption
of its fruit produces a large quantity of the apricot kernel. The valorization of this byproduct
in terms of polyphenol compounds seems to be important.

Objective:
The aim of the present study is to investigate the best conditions of phenolic compound
extraction from apricot kernels in order to determine the effects of different parameters, namely
time, stirring speed, solvent type, temperature, and microwave power, on polyphenol yield.

Methods:
In this study, the effect of many parameters, such as the type of solvent (ethanol,
methanol, acetone and water), the acetone concentration (40-70%, v/v), the extraction time, power
of the microwave (100-900 W) and stirring speed on the extraction of Total Phenolic Content (TPC)
from apricot kernels was studied, using the approach of single factor experiments.

Results:
The importance of agitation speed was determined for polyphenol compound extraction
from apricot kernels besides time, temperature and microwave power, whereas the linear agitation
in the water bath had no significant effect on the extraction of phenolic compounds. The best extraction
conditions were 60% acetone, 300 W of microwave power for 5 min of extraction time,
which gave a high TPC of 249.44 ±15.83 mg GAE/g DW. All the extraction conditions showed a
significant effect (p <0.05) on the TPC. The antioxidant capacity (DPPH-RSA) of the extract was
positively correlated with TPC in all tested methods.

Conclusion:
It can be concluded that the importance of agitation speed was determined for the extraction
of phenolic compounds from apricot kernels by maceration. However, the linear agitation
in the water bath had no significant effect on the extraction. Apricot kernel seems to be a good
source of polyphenols compared to other sources mentioned in the previous studies present in literature.
Antioxidant Properties and Polyphenol Screening of the Leaves of Native
Hungarian Oak (Quercus) Species
Authors: Hofmann Tamás , Visi-Rajczi Eszter , Albert Levente 
Published: February 2021

Abstract:
Due to their ecological significance and timber value, Quercus species are especially important
in Hungary. Nevertheless, the leaves of these species lack a dedicated utilization field and
are considered a waste biomass.

Materials and Methods:
The present study comprehensively analyses three selected oak species
(Q. petraea, Q. pubescens, Q. cerris) native to Hungary to assess their antioxidant capacity (FRAP,
ABTS, DPPH) and provide information on their polyphenol pool using state-of-the-art liquid chromatographic/
tandem mass spectrometric technique. To the best of our knowledge, no such investigation
has yet been conducted for the assigned species.

Results:
According to the results, the antioxidant capacity of the three species’ leaves are roughly
equal. Altogether, 109 compounds have been tentatively identified and described, including phenolic
acid derivatives, tannins, flavonoid glycosides, and catechins. Compared to other oak leaf samples
and other types of plant tissues, the investigated samples contained a large number (24) of acylated
polyphenols.

Conclusion:
The recent findings on the excellent antioxidant and antibacterial properties of acylated
polyphenols suggest that the investigated samples could also be beneficial to human health, requiring
further analysis.
Drug-induced Neuropsychiatric Adverse Events Using Post-Marketing
Surveillance
Authors: Hosohata Keiko , Wakabayashi Tomohito , Nakatsuji Takahiro , Kambara Hiroko , Niinomi Iku , Oyama Saki , Inada Ayaka , Ueno Sayaka , Uchida Mayako , Iwanaga Kazunori , Iida Tatsuya 
Published: February 2021

Background:
Several studies reported that abnormal behavior was noted in pediatric patients
receiving several drugs, including neuraminidase inhibitors (NIs). However, the information on
drugs associated with abnormal behavior in a real-world setting remains limited. The purpose of this
study was to clarify the drugs associated with abnormal behavior using a spontaneous reporting system
database.

Methods:
We performed a retrospective pharmacovigilance disproportionality analysis using the Japanese
Adverse Drug Event Report database. Adverse event reports submitted to the Pharmaceuticals
and Medical Devices Agency were analyzed, and the reporting odds ratio at 95% confidence interval
were calculated.

Results:
A total of 1,144 reports of abnormal behavior were identified. The signals were detected
through the association of 4 neuraminidase inhibitors (oseltamivir, zanamivir, laninamivir, and peramivir)
with the abnormal behaviour. These signals were stronger for oseltamivir than other neuraminidase
inhibitors. The signals were also detected for acetaminophen and montelukast.

Conclusion:
Our results should be able to raise physicians’ awareness of drugs associated with abnormal
behavior, but further investigation of these medications is warranted.
Uncovering the Key miRNAs and Targets of the Liuwei Dihuang Pill in Diabetic
Nephropathy-Related Osteoporosis based on Weighted Gene Co-Expression
Network and Network Pharmacology Analysis
Authors: Liu Ming Ming , Lv Nan Ning , Geng Rui , Hua Zhen , Ma Yong , Huang Gui Cheng , Cheng Jian , Xu Hai Yan 
Published: February 2021

Background:
Diabetic nephropathy-related osteoporosis (DNOP) is the most common
comorbid bone metabolic disorder associated with diabetes mellitus (DM). The Liuwei Dihuang
Pill (LWD) is a traditional Chinese herbal medicine widely used to treat diabetic complications, including
diabetic nephropathy (DN). This study aimed to identify the biomarkers of the mechanisms
of DNOP in LWD with systems biology approaches.

Methods:
Herein, we performed an integrated analysis of the GSE51674 and GSE63446 datasets
from the GEO database via weighted gene co-expression network and network pharmacology
(WGCNA) analysis. In addition, a network pharmacology approach, including bioactive compounds,
was used with oral bioavailability (OB) and drug-likeness (DL) evaluation. Next, target
prediction, functional enrichment analysis, network analysis, and virtual docking were used to investigate
the mechanisms of LWD in DNOP.

Results :
WGCNA successfully identified 63 DNOP-related miRNAs. Among them, miR-574 was
significantly upregulated in DN and OP samples. A total of 117 targets of 22 components associated
with LWD in DNOP were obtained. The cellular response to nitrogen compounds, the AGERAGE
signaling pathway in diabetic complications, and the MAPK signaling pathway were related
to the main targets. Network analysis showed that kaempferol and quercetin were the most significant
components. MAPK1 was identified as a potential target of miR-574 and the hub genes in
the protein-protein interaction (PPI) network. The docking models demonstrated that kaempferol
and quercetin had a strong binding affinity for Asp 167 of MAPK1.

Conclusion:
This study demonstrated that miR-574 may play important roles in DNOP, and the
therapeutic effects of kaempferol and quercetin on LWD in DNOP might be mediated by miR-574
by targeting MAPK1. Our results provide new perspectives for further studies on the anti-DNOP
mechanism of LWD.
Oral Health Knowledge, Behaviour, and Access to Dental Care in Visually Impaired Individuals in Jordan: A Case-Control Study
Authors: Alshatrat Sabha , Bakri Isra AL , Omari Wael AL , Tabnjh Abedelmalek 
Published: February 2021

Aim:
The study aimed to assess oral health knowledge, dental behaviors, and use of dental services in individuals with vision impairment in Jordan and identify barriers that affect their access to dental care in comparison with individuals without vision impairment.

Materials and Methods:
A case-control study was carried out among 399 parents/caregivers of individuals with vision impairment and individuals without vision impairment, which involved the completion of a self-designed questionnaire. A closed-ended, validated self-designed questionnaire was distributed. The questionnaire included questions addressing participants’ oral health knowledge, oral health behaviour, dental service use and barriers to accessing dental care. Data were analyzed using SPSS® software Version 22 with a 0.05 level of significance. A Chi-square test and contingency-table analysis were performed on the data.

Results:
Individuals with vision impairment in Jordan were significantly less knowledgeable about different oral health aspects than sighted counterparts. In addition, individuals with vision impairment used toothbrush, dental floss, and mouth rinse less frequently. They also visited dentists less regularly and mostly when only feeling pain. Limited access to dental services was observed among individuals with vision impairment compared to sighted individuals. Barriers, including embarrassment (22%), lack of knowledge of how to treat people with disabilities among dentists (12.5%), and inadequate facilities (13.7%), were significantly (P<0.05) more likely to be reported by visually impaired participants than the controls.

Conclusion:
Visually impaired individuals and their families should be given appropriate education about oral health care by oral health professionals to reduce the risk of having dental problems and oral disease and enhance their quality of life. Furthermore, recognizing the challenges in accessing dental care for this population could help oral health professionals to minimize these difficulties.
Porosity Pattern of 3D Chitosan/Bioactive Glass Tissue Engineering Scaffolds Prepared for Bone Regeneration
Authors: Hammad Hoda G.H. , Salama Miral Nagy F. 
Published: February 2021

Aim:
The study was conducted to investigate the obtained external and internal porosity and the pore-interconnectivity of specific fabricated bioactive composite tissue engineering scaffolds for bone regeneration in dental applications.

Materials and Methods:
In this study, the bioactive glass [M] was elaborated as a quaternary system to be incorporated into the chitosan [C] scaffold preparation on a magnetic stirrer to provide bioactivity and better strength properties for the attempted composite scaffolds [C/ M] of variable compositions. The homogenous chitosan/bioactive glass mix was poured into tailor-made cylindrical molds [10cm×10cm]; a freeze-dryer program was used for the creation of uniform and interconnected macropores for all prepared chitosan-based scaffolds. The morphology of fabricated chitosan [C] and chitosan-bioactive glass [C/ M] composite scaffolds was studied by a scanning electron microscope [SEM] and a mercury porosimeter. In addition, the in-vitro biodegradation rate of all elaborated scaffolds was reported after immersing the prepared scaffolds in a simulated body fluid [SBF] solution. Furthermore, for every prepared scaffold composition, characterization was performed for phase identification, microstructure, porosity, bioactivity, and mechanical properties using an X-ray diffraction analysis [XRD], an X-ray Fourier transfer infrared spectroscopy [FTIR], a mercury porosimetry, a scanning electron microscopy [SEM] coupled to an energy-dispersive X-ray spectrometry [EDS] and a universal testing machine, respectively.

Results:
All the prepared porous chitosan-based composite materials showed pore sizes suitable for osteoblasts seeding, with relatively larger pore sizes for the C scaffolds.

Conclusion:
The smart blending of the prepared bioactive glass [M] with the chitosan matrix offered some advantages, such as the formation of an apatite layer for cell adhesion upon the scaffold surfaces, the reasonable decrease in scaffold pore size, and the relative increase in compressive strength that were enhanced by the incorporation of [M]. Therefore, the morphology, microstructure, and mechanical behavior of the elaborated stress loaded biocomposite tissue engineering scaffolds seem highly dependent on their critical contented bioactive glass.