bluuebunny/crossref_metadata_2025_split huggingface dataset:
Integration of advanced optimization algorithms into least-square support vector machine (LSSVM) for water quality index prediction
Authors: Chia See Leng , Chia Min Yan , Koo Chai Hoon , Huang Yuk Feng 
Published: September 2021

AbstractMachine learning models hybridized with optimization algorithms have been applied to many real-life applications, including the prediction of water quality. However, the emergence of newly developed advanced algorithms can provide new scopes and possibilities for further enhancements. In this study, the least-square support vector machine (LSSVM) integrated with advanced optimization algorithms is presented, for the first time, in the prediction of the water quality index (WQI) at the Klang River of Malaysia. Thereafter, the LSSVM model using RBF kernel was optimized using the hybrid particle swarm optimization and genetic algorithm (HPSOGA), whale optimization based on self-adapting parameter adjustment and mix mutation strategy (SMWOA) as well as ameliorative moth-flame optimization (AMFO) separately. It was found that the SMWOA-LSSVM model had the better performance for WQI prediction by having the best achievement root mean square error (RMSE), mean absolute error (MAE), coefficient of determination (R2) and mean absolute percentage error (MAPE). Comprehensive comparison was done using the global performance indicator (GPI), whereby the SMWOA-LSSVM had the highest average score of 0.31. This could be attributed to the internal architecture of the SMWOA, which was catered to avoid local optima within short optimization period.
Porous carbon aerogel derived from bacterial cellulose with prominent potential for efficient removal of antibiotics from the aquatic matrix
Authors: Wei Mengdan , Zheng Huabao , Zeng Tainan , Yang Jian , Fang Xiaobo , Zhang Cheng 
Published: September 2021

Abstract
The development of adsorption methods for the remediation of antibiotics pollution in water is hindered by the lack of high-performance sorbents. In this study, a nanofiber carbon aerogel was prepared using bacterial cellulose and its adsorption performances for three common antibiotics (norfloxacin, sulfamethoxazole, and chloramphenicol) in water were evaluated. The as-prepared nanofiber carbon aerogel showed a higher adsorption capacity toward target antibiotics compared to other adsorbents reported in the literature. The maximum adsorption capacities for norfloxacin, sulfamethoxazole, and chloramphenicol were 1,926, 1,264, and 525 mg/g, respectively at 298 K. Notably, the nanofiber carbon aerogel was able to adsorb 80% of the equilibrium adsorption capacity within 1 min and reach equilibrium within 15 min. After five regeneration cycles, the adsorption capacity still reached 1,166, 847, and 428 mg/g for norfloxacin, sulfamethoxazole, and chloramphenicol, respectively. The characterization results showed that the carbon aerogel exhibited a high specific surface area (1,505 m2/g) and a layered porous network structure. Furthermore, the mechanistic study reveals that the enhanced antibiotic adsorption by the as-prepared nanofiber carbon aerogel was attributed to the pore filling effect, hydrogen bonding, hydrophobic effect, electrostatic interaction, and π-π interactions. Overall, these results imply that low-cost and green nanofiber carbon aerogels may be promising adsorbents for the remediation of antibiotic-contaminated wastewater. The materials prepared from natural and readily available bacterial cellulose can adsorb antibiotics efficiently, which provides a reference for the development of adsorbent materials using natural substances.
Role of the Bone Marrow Microenvironment in Drug Resistance of
Hematological Malignances
Authors: Hosseini Alireza , Hamblin Michael R. , Mirzaei Hamed , Mirzaei Hamid R. 
Published: September 2021

Abstract:
The unique features of the tumor microenvironment (TME) govern the biological
properties of many cancers, including hematological malignancies. TME factors can
trigger an invasion and protect against drug cytotoxicity by inhibiting apoptosis and activating
specific signaling pathways (e.g. NF-ΚB). TME remodeling is facilitated due to
the high self-renewal ability of the bone marrow. Progressing tumor cells can alter some
extracellular matrix (ECM) components which act as a barrier to drug penetration in the
TME. The initial progression of the cell cycle is controlled by the MAPK pathway
(Raf/MEK/ERK) and Hippo pathway, while the final phase is regulated by the PI3K/Akt
/mTOR and WNT pathways. This review summarizes the main signaling pathways involved
in drug resistance (DR) and some mechanisms by which DR can occur in the bone
marrow. The relationship between autophagy, endoplasmic reticulum stress, and cellular
signaling pathways in DR and apoptosis is covered in the TME.
A Survey for Predicting ATP Binding Residues of Proteins Using
Machine Learning Methods
Authors: Yang Yu-He , Wang Jia-Shu , Yuan Shi-Shi , Liu Meng-Lu , Su Wei , Lin Hao , Zhang Zhao-Yue 
Published: September 2021

Abstract:
Protein-ligand interactions are necessary for majority protein functions. Adenosine-
5’-triphosphate (ATP) is one such ligand that plays vital role as a coenzyme in
providing energy for cellular activities, catalyzing biological reaction and signaling.
Knowing ATP binding residues of proteins is helpful for annotation of protein function
and drug design. However, due to the huge amounts of protein sequences influx into databases
in the post-genome era, experimentally identifying ATP binding residues is costineffective
and time-consuming. To address this problem, computational methods have
been developed to predict ATP binding residues. In this review, we briefly summarized
the application of machine learning methods in detecting ATP binding residues of proteins.
We expect this review will be helpful for further research.
Anti-Proliferative Potential of Fluorinated Curcumin Analogues:
Experimental and Computational Analysis and Review of the Literature
Authors: Hatamipour Mahdi , Hadizadeh Farzin , Jaafari Mahmoud Reza , Khashyarmanesh Zahra , Sathyapalan Thozhukat , Sahebkar Amirhossein 
Published: September 2021

Background:
Curcuminoids, flavoring, and coloring agents in food have potent
antioxidant, anti-tumor activity, and anti-inflammatory effects. However, they are rapidly
metabolized to lesser active metabolites. Therefore, various studies have been conducted
to synthesize new and stable curcumin analogues with enhanced therapeutic activity.

Methods:
Fluorinated curcumin compounds (2a-2f) were synthesized by Knoevenagel
condensation between fluorobenzaldehydes (1a-1f) with curcumin. Fluorinated demethoxycurcumin
(3a) was synthesized by condensation between demethoxycurcumin and
3,4-difluorobenzaldehyde (1f). The structures of these compounds were confirmed by FTIR,
1H-NMR, 13C-NMR, 19FNMR, and mass spectroscopy. Antiproliferative activities of
these synthetic compounds were evaluated against breast cancer cells (4T1), melanoma
cancer cells (B16F10), and normal cell lines (NIH 3T3) using MTT assay. The interaction
of curcumin, 2f and 3a with several proteins (1HCL, 2ZOQ, 3D94, 5EW3, 4WA9,
1XKK, 6CCY) was investigated. The structural preservation of the epidermal growth factor
receptor (EGFR) was investigated by molecular dynamics simulation.

Results:
The spectroscopic data obtained confirmed the proposed structure of fluorinated
analogues. The results showed that compounds 2f and 3a inhibited cancer cells proliferation
significantly more than other compounds. Compounds 2f and 3a showed the highest
affinity and lowest binding energy with EGFR. The binding energies were -7.8, -10, and -
9.8 kcal/mol for curcumin, 2f and 3a with EGFR, respectively. The molecular docking results
demonstrated that compounds 2f and 3a were firmly bound in a complex with EGFR
via the formation of a hydrogen bond.

Conclusion:
In summary, we found that fluorinated demethoxycurcumin and fluorinated
curcumin induces cancer cell death and binds to EGFR with high affinity.
Therapeutic Targeting of Inflammatory Pathways with Emphasis on
NLRP3 Inflammasomes by Natural Products: A Novel Approach for
the Treatment of Inflammatory Eye Diseases
Authors: Soliman Amro M. , Sim Ru Hui , Das Srijit , Mahakkanukrauh Pasuk 
Published: September 2021

Abstract:
There is an increase in the incidence of inflammatory eye diseases worldwide.
Several dysregulated inflammatory pathways, including the NOD-like receptor protein 3
(NLRP3) inflammasome, have been reported to contribute significantly to the pathogenesis
and progression of ophthalmic diseases. Although the available allopathic/ conventional
medicine has demonstrated effectiveness in managing eye diseases, there is an ongoing
global demand for alternative therapeutics with minimal adverse drug reactions,
easy availability, increase in patient compliance, and better disease outcomes. Therefore,
several studies are investigating the utilization of natural products and herbal formulations
in impeding inflammatory pathways, including the NLRP3 inflammasome, in order to
prevent or manage eye diseases. In the present review, we highlight the recently reported
inflammatory pathways with special emphasis on NLRP3 Inflammasomes involved in the
development of eye diseases. Furthermore, we present a variety of natural products and
phytochemicals that were reported to interfere with these pathways and their underlying
mechanisms of action. These natural products represent potential therapeutic applications
for the treatment of several inflammatory eye diseases.
Role of Adenosine Receptors in Rare Neurodegenerative Diseases with
Motor Symptoms
Authors: Beltran-Beltran Vicent , Benetó Noelia , Lapeña-Luzón Tamara , Rodríguez Laura R. , Pallardó Federico V. , Gonzalez-Cabo Pilar 
Published: September 2021

:
The approval of istradefylline, an adenosine 2A receptor (A2AR) antagonist, as an addon
treatment in adult patients with Parkinson’s disease by the Food and Drug Administration (FDA)
and European Medicines Agency (EMA), is the latest proof of the importance of the adenosinergic
system in the nervous system. Adenosine is an endogenous purine nucleoside with a role as a modulator
of both neurotransmission and the inflammatory response. As such, the expression pattern of
the 4 adenosine receptors (A1R, A2AR, A2BR and A3R) and the extracellular adenosine levels
have attracted great interest in the pathogenesis and possible treatment of rare neurodegenerative
diseases with motor symptoms. These include Huntington’s Disease (HD), Amyotrophic Lateral
Sclerosis (ALS), Multiple Sclerosis (MS), Restless Legs Syndrome (RLS) and Machado-Joseph
Disease (MJD, also known as spinocerebellar ataxia type 3, SCA3). In this review, we shall focus
on the role of the different adenosine receptor subtypes in the development and possible treatment
of the aforementioned rare neurodegenerative diseases with motor symptoms using the currently
available data. The last section discusses the possibility of a role for the adenosine receptors in the
treatment of other rare diseases based on the available molecular pathology knowledge.
CD155: A Key Receptor Playing Diversified Roles
Authors: Nandi Shyam Sundar , Gohil Trupti , Sawant Sonali Ankush , Lambe Upendra Pradeep , Ghosh Sudip , Jana Snehasis 
Published: September 2021

:
Cluster of differentiation (CD155), formerly identified as poliovirus receptor
(PVR) and later as immunoglobulin molecule, is involved in cell adhesion, proliferation,
invasion and migration. It is a surface protein expressed mostly on normal and
transformed malignant cells. The expression of the receptor varies based on the origin of
tissue. The expression of the protein is determined by factors involved in the sonic
hedgehog pathway, Ras-MEK-ERK pathway and during stressful conditions like DNA
damage response. The protein uses an alternate splicing mechanism, producing four
isoforms, two being soluble (CD155β and CD155γ) and two being transmembrane
protein (CD155α and CD155δ). Apart from being a viral receptor, researchers have
identified CD155 to play important roles in cancer research and the cell signaling field.
The receptor is recognized as a biomarker for identifying cancerous tissue. The receptor
interacts with molecules involved in the cells’ defense mechanism. The immunesurveillance
role of CD155 is being deciphered to understand the mechanistic approach
it utilizes as an onco-immunologic molecule. CD155 is a non-MHC-I ligand which helps
in identifying non-self to NK cells via an inhibitory TIGIT ligand. The TIGIT–CD155
pathway is a novel MHC-I-independent education mechanism for cell tolerance and
activation of NK cells. The receptor also has a role in metastasis of cancer and
transendothelial mechanism. In this review, the authors discuss the virus-host interaction
that occurs via a single transmembrane receptor, the poliovirus infection pathway, which
is being exploited as a therapeutic pathway. The oncolytic virotherapy is now a
promising modality for curing cancer.
Network Pharmacology Analysis of Molecular Mechanism of Curcuma longa L.
Extracts Regulating Glioma Immune Inflammatory Factors: Implications for
Precise Cancer Treatment
Authors: Li Hui , Li Yongwei 
Published: September 2021

Introduction: :
Curcuma longa L. has been associated with different antioxidant, antiinflammatory,
bactericidal and anticancer effects, but the mechanisms of the effects are not yet
clearly understood. This study aimed to investigate the key targets and the effect of potential molecular
mechanisms of Curcuma longa L. extracts on glioma using different network pharmacology
analysis approaches.

Methods:
The components of Curcuma longa were extracted by gas chromatography-mass spectrometry
(GC-MS), and the active components related to the occurrence and development of glioma
were determined by traditional Chinese medicine systems pharmacology database and analysis platform
(TCMSP) database, and the same targets of the active components and glioma were screened
by network pharmacology approach. Then, the protein’s function and regulatory pathway of the
common targets were analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes
(KEGG) pathway enrichment analyses. The protein’s action and regulatory pathway of the
common targets were analyzed with the Cytoscape package using the Search Tool for the Retrieval
of Interacting Genes/Proteins (STRING) database to construct the target interaction network through
which the key targets were identified.

Results :
GC-MS combined with TCMSP database was used to identify the active components related
to the occurrence and development of glioma in Curcuma longa. Finally, we identified the active
components 1-(1,5-Dimethyl-4-hexenyl)-4-methyl benzene and Zingiberene. At the same time,
190 target genes of Curcuma longa extracts on glioma were obtained using the Venn diagram. The
results of GO analysis showed that the biological processes involved included a response to stimulation,
metabolic process, inflammatory process, cell differentiation, and regulation of biological processes.
KEGG analysis showed that the PI3K-Akt signaling pathway, MAPK signaling pathway,
Th17 cell differentiation, and proteoglycan pathway might be involved in cancer. Further analyses
showed that the IL-17 signaling pathway and Interleukin-4 and interleukin-13 signaling were involved
in the inflammatory pathway. The analysis of key nodes showed that GSK3B, MAPK14,
HSP90AA1, MAPK3 and MAPK8 were IL-17 signaling pathways, while HIF1A and JAK3 were
Interleukin-4 and interleukin-13 signaling pathways.

Conclusion:
Curcuma longa extracts can regulate the occurrence and development of glioma by
regulating the immune-inflammatory responses.
A Novel Multicolor-thresholding Auto-detection Method to Detect the Location
and Severity of Inflammation in Confirmed SARS-COV-2 Cases using
Chest X-Ray Images
Authors: Abbas Mohamed A. , Alqahtani Mohammed S. , Alqahtani Ali M. , Alshahrani Mohammad Y. , Alkulib Abdulhadi J. , Alelyani Magbool A. , Almarhaby Awad M. 
Published: September 2021

Objectives:
Since late 2019, Coronavirus Disease 2019 (COVID-19) has spread around
the world. It has been determined that the disease is very contagious and can cause acute respiratory
distress (ARD). Medical imaging has the potential to help identify, detect, and quantify the severity
of this infection. This work seeks to develop a novel auto-detection technique for verified
COVID-19 cases that can detect aberrant alterations in traditional X-ray pictures.

Methods:
Nineteen separately colored layers were created from X-ray scans of patients diagnosed
with COVID-19. Each layer represents objects that have a similar contrast and can be represented
by a single color. In a single layer, objects with similar contrasts are formed. A single color image
was created by extracting all the objects from all the layers. The prototype model could recognize a
wide range of abnormal changes in the image texture based on color differentiation. This was true
even when the contrast values of the detected unclear abnormalities varied slightly.

Results:
The results indicate that the proposed novel method is 91% accurate in detecting and grading
COVID-19 lung infections compared to the opinions of three experienced radiologists evaluating
chest X-ray images. Additionally, the method can be used to determine the infection site and
severity of the disease by categorizing X-rays into five severity levels.

Conclusion:
By comparing affected tissue to healthy tissue, the proposed COVID-19 auto-detection
method can identify locations and indicate the severity of the disease, as well as predict where
the disease may spread.
Pre- and post- Covid-19 Outreach Experiences at Marshall University Libraries
Authors: Mollette Sarah , Johnson Kelli 
Published: September 2021

This article will provide insight into how MU Libraries’ cross-departmental system has evolved over the years, and how the recent finalization of their Outreach Plan led to a successful transition to online outreach during the COVID pandemic. Specifically, the authors will address: the history of library outreach at the university; the formation of the Outreach Librarian position; the audit the Outreach librarian performed on the library’s practices; the creation of an Outreach committee and subsequent Outreach Plan guide; and, how the library adapted their approach during the Covid-19 pandemic of 2020.
Willingness to Share Wearable Device Data for Research Among Mechanical Turk Workers: Web-Based Survey Study
Authors: Taylor Casey Overby , Flaks-Manov Natalie , Ramesh Shankar , Choe Eun Kyoung 
Published: September 2021

Background
Wearable devices that are used for observational research and clinical trials hold promise for collecting data from study participants in a convenient, scalable way that is more likely to reach a broad and diverse population than traditional research approaches. Amazon Mechanical Turk (MTurk) is a potential resource that researchers can use to recruit individuals into studies that use data from wearable devices.

Objective
This study aimed to explore the characteristics of wearable device users on MTurk that are associated with a willingness to share wearable device data for research. We also aimed to determine whether compensation was a factor that influenced the willingness to share such data.

Methods
This was a secondary analysis of a cross-sectional survey study of MTurk workers who use wearable devices for health monitoring. A 19-question web-based survey was administered from March 1 to April 5, 2018, to participants aged ≥18 years by using the MTurk platform. In order to identify characteristics that were associated with a willingness to share wearable device data, we performed logistic regression and decision tree analyses.

Results
A total of 935 MTurk workers who use wearable devices completed the survey. The majority of respondents indicated a willingness to share their wearable device data (615/935, 65.8%), and the majority of these respondents were willing to share their data if they received compensation (518/615, 84.2%). The findings from our logistic regression analyses indicated that Indian nationality (odds ratio [OR] 2.74, 95% CI 1.48-4.01, P=.007), higher annual income (OR 2.46, 95% CI 1.26-3.67, P=.02), over 6 months of using a wearable device (OR 1.75, 95% CI 1.21-2.29, P=.006), and the use of heartbeat and pulse tracking monitoring devices (OR 1.60, 95% CI 0.14-2.07, P=.01) are significant parameters that influence the willingness to share data. The only factor associated with a willingness to share data if compensation is provided was Indian nationality (OR 0.47, 95% CI 0.24-0.9, P=.02). The findings from our decision tree analyses indicated that the three leading parameters associated with a willingness to share data were the duration of wearable device use, nationality, and income.

Conclusions
Most wearable device users indicated a willingness to share their data for research use (with or without compensation; 615/935, 65.8%). The probability of having a willingness to share these data was higher among individuals who had used a wearable for more than 6 months, were of Indian nationality, or were of American (United States of America) nationality and had an annual income of more than US $20,000. Individuals of Indian nationality who were willing to share their data expected compensation significantly less often than individuals of American nationality (P=.02).
Peer Support Specialists’ Perspectives of a Standard Online Research Ethics Training: Qualitative Study
Authors: Fortuna Karen L , Marceau Skyla R , Kadakia Arya , Pratt Sarah I , Varney Joy , Walker Robert , Myers Amanda L , Thompson Shavon , Carter Katina , Greene Kaycie , Pringle Willie 
Published: September 2021

Background
Certified peer support specialists (CPS) have a mental health condition and are trained and certified by their respective state to offer Medicaid reimbursable peer support services. CPS are increasingly involved as partners in research studies. However, most research ethics training in the protection of human subjects is designed for people who, unlike CPS, have had exposure to prior formal research training.

Objective
The aim of this study is to explore the perspectives of CPS in completing the Collaborative Institutional Training Initiative Social and Behavioral Responsible Conduct of Research online training.

Methods
A total of 5 CPS were recruited using a convenience sample framework through the parent study, a patient-centered outcomes research study that examined the comparative effectiveness of two chronic health disease management programs for people with serious mental illness. Participants independently completed the Collaborative Institutional Training Initiative Social and Behavioral Responsible Conduct of Research online training. All participants completed 15 online modules in approximately 7-9 hours and also filled out a self-report measure of executive functioning (the Adult Executive Functioning Inventory [ADEXI]). Qualitative data were collected from a 1-hour focus group and qualitative analysis was informed by the grounded theory approach. The codebook consisted of codes inductively derived from the data. Codes were independently assigned to text, grouped, and checked for themes. Thematic analysis was used to organize themes.

Results
Passing scores for each module ranged from 81%-89%, with an average of 85.4% and a median of 86%. The two themes that emerged from the focus group were the following: comprehension (barrier) and opportunity (facilitator). Participants had a mean score of 27.4 on the ADEXI.

Conclusions
The CPS perceived the research ethics online training as an opportunity to share their lived experience expertise to enhance current research efforts by nonpeer scientists. Although the CPS completed the online research ethics training, the findings indicate CPS experienced difficulty with comprehension of the research ethics online training materials. Adaptations may be needed to facilitate uptake of research ethics online training by CPS and create a workforce of CPS to offer their lived experience expertise alongside peer and nonpeer researchers.