bluuebunny/crossref_metadata_2025_split huggingface dataset:
The prediction of PM2.5 concentration based on data decomposition and reconstruction algorithm and neural network model
Authors: Xiao Lushuang , Wang Guizhi 
Published: June 2022

Abstract
Since 2013, the concentration of PM2.5 in Beijing has been has dropped significantly, there is still there is still far from the World Health Organization’s revised 2021 target of 5µg/m 3 of the average annual concentration. We analyzed the monthly, quarterly and annual trends of PM2.5 concentrations in the Beijing, China, from 2014 to 2021 using independent T-test. In addition, we proposed a new combined PM2.5 concentration prediction model, which combines mode decomposition and reconstruction algorithm, convolutional neural network and long short-term memory neural networks. The results show that: (1) From 2016 to 2018, PM2.5 concentration in Beijing decreased at a fast pace, and then the decline entered a slow period. (2) The combination of the modal decomposition algorithm and neural network model can effectively process the PM2.5 concentration data with the characteristics of nonlinearity, instability and high complexity, and is more stable and generalizable. (3) The combination of convolutional neu-ral network and long short-term memory neural network model has a higher prediction accuracy than traditional neural network models. The research results are helpful to know the possible air pollution process in advance and take corresponding measures to reduce the harm caused by air pollution in the new stage of haze pollution.
Designing a decision aid of the Australian aspirin chemoprevention guidelines for colorectal cancer prevention
Authors: Milton Shakira , Macrae Finlay , McIntosh Jennifer G , Saya Sibel , Alphonse Pavithran , Yogaparan Thivagar , Karnchanachari Napin , Novy Kitty , Nguyen Peter , Lau Phyllis , Forbes Carmody , Cummings Kara-Lynne , Emery Jon David 
Published: June 2022

Abstract
Objectives
Australian guidelines recommend people aged 50 to 70-years-old, consider taking low-dose aspirin to reduce their risk of colorectal cancer. The aim was to design sex-specific decision aids (DAs) with clinician and consumer input including expected frequency trees (EFTs) to communicate risks and benefits of taking aspirin.
Methods
Semi-structured interviews were conducted with clinicians. Focus groups were conducted with consumers. The interview schedules covered ease of comprehension, design, potential effects on decision making, and approaches to implementation of the DAs. Thematic analysis was employed; independent coding by two researchers was inductive. Themes were developed through consensus between authors.
Results
Sixty-four clinician were interviewed over six-months in 2019. Twelve consumers, aged 50 to 70 years, participated in two focus groups in February and March 2020.
Genome-Wide CRISPR-Cas9 Screening and Identification of Potential
Genes Promoting Prostate Cancer Growth and Metastasis
Authors: Sun Fa , Jia Zhenyu , Zhu Jianguo , Wang Wei , Yuan Dongbo , Jiang Kehua , Li Ruidong , Qu Han , Jiang Fu-Neng , Zhong Wei-De 
Published: June 2022

Objective:
Identification and validation of genes that functionally account for the growth and metastasis of prostate cancer.

Methods:
DU145-KO cell line was constructed by transfecting DU145 cells with lentivirus packaged with the genome-wide knockout library. The DU145-KO cells were transplanted into the armpits of immunocompromised Nu/Nu mice, followed by the tissue collection from lung at week 3 (early lung tissue) or week 7 (late lung tissue with micro-metastasis), as well as from primary tumor site at week 7 (late primary tumor) after inoculation. Lung metastasis were retrieved at various time points for DNA sequencing analysis to identify enriched sgRNAs, thus candidate genes/miRNAs. Further bioinformatics analysis and limited functional validation studies were carried out.

Results:
DU145-KO cells promoted the formation of transplanted tumors in mice and promoted the growth and metastasis of primary tumors, compared to the controls (DU145-NC cells). The analysis of sequence data showed that the abundance of sgRNAs significantly changed in the primary tumor and micro-metastasis site. Fifteen target genes（C1QTNF9B, FAM229A, hsa-mir-3929, KRT23, TARS2, CRADD, GRIK4, PLA2G15, LOXL1, SLITRK6, CDC42EP5, SLC2A4, PTGDS, MYL9 and ACOX2 for the enriched sgRNAs have been selected for experimental validation, which showed that knockout of any of these genes led to enhanced potential of invasion and metastasis of DU145 cells.

Conclusion:
Genome-wide CRISPR-Cas9 knockout screening technology combined with high-throughput sequencing analysis identified genes that potentially relate to prostate tumor invasion and metastasis. Analysis of these genes provided insights into biological pathways relevant to the disease and disclosed innovative markers for diagnosis or prognosis as well as potential targets for therapy.
In silico Prediction and Pharmacokinetic Studies on Glucosinolates as a
Potential Drug and Key Inhibitor Molecule for Lanosterol-14α-
demethylase: A Fungal Membrane Biosynthesis Enzyme
Authors: Singh Gurpreet 
Published: June 2022

Background:
Glucosinolates (β-thioglucoside-N-hydroxysulfates) are a water-soluble organic
anion with sulfur- and nitrogen-containing glycosides which are found in abundance in Cruciferous
plants. Ergosterol (ERG13) lanosterol-14α-demethylase protein has been targeted for inhibition
studies as a key regulator enzyme of fungal membrane biosynthesis.

Objectives:
To understand the molecular mechanism of inhibition of Ergosterol (ERG13) lanosterol-
14α-demethylase by various phytochemicals from brassicales, i.e., glucosinolates and their potential
role as putative drug molecules.

Methodology:
In this study, in silico analyses were performed to predict the molecular basis of various
glucosinolates as a potential inhibitor of lanosterol-14α-demethylase protein, which is a key regulator
of fungal membrane biosynthesis and its pharmacodynamics and toxicity profile. 3d structures of various
glucosinolates were retrieved from PubChem, and the target protein, lanosterol-14α-demethylase
(Pdb ID- 4lxj), was retrieved from the RCSB protein data bank. Molecular docking and interactions
were carried out using the PyRx software using the AutoDOCK toolbar with default parameters. Dru-
LiTo, ORISIS web servers were used to predict various drug likeliness predictions and Lipinski’s Rule
of 5, whereas admetSAR was used for prediction of toxicity, and PASS Program was used to study the
antifungal and antimicrobial properties of these compounds.

Results:
This study shows that among the different compounds screened, gluconasturtiin, Glucotropaeolin,
and Indolylmethyl-Glucosinolate showed the highest binding energies of -8.7 kcal/mol, -8.5
kcal/mol, and -8.3 kcal/mol with the lanosterol-14α-demethylase, respectively. Further all the compounds
follow the Lipinski’s rule as well as they are found to be non-carcinogenic and non-cytotoxic
in nature. These compounds also show antifungal properties.

Conclusion:
This study thus reveals that various glucosinolates interact with the ERG13 enzyme at
various amino acid positions, which behaves as a catalytic site, thus indicates the probable mechanism
of inactivation, and subsequently, these can be used as potential drug molecules. In vitro studies can be
taken to further examine the utility of these compounds as antifungal agents.
Synthetic Procedures to Access 2-Guanidinobenzazoles of Biological Interest
Authors: Cruz Alejandro , Rosales-Hernández Martha C. , Mendieta-Wejebe Jessica E. , Tamay-Cach Feliciano 
Published: June 2022

Abstract:
Benzazoles (Bz) and derivatives are interesting molecules in medicinal chemistry.
Several of these compounds display diverse biological activities; some are still used in clinical
applications. In this way, synthetic chemists are interested in developing new procedures
to access compounds with the guanidine moiety as 2-aminobenzimidazole (2ABI), Astemizole
(antihistaminic), Albendazole (anthelmintic) and Carbendazim (fungicide). The guanidine
group, considered a super base bonded to a benzoxazole ring, results in the 2-guanidinobenzazoles
(2GBZs), which could modify the biological activity of these heterocycles. On
these bases, we prepared this review article, which covers chemical aspects of 2-guanidinobenzoazoles
as potential therapeutic agents and summarizes the current knowledge on the
mechanism of pharmacological activities such as cytotoxic, inhibition of cell proliferation via
angiogenesis and apoptosis. Specifically, it highlights the most recent results of synthetic approaches
to 2GBZs with variety of modifications and functionalization with aromatic, carbohydrate,
and amino-acid moieties as illustrated on 28 schemes and is concluded with 141
references. Additionally, the format of this interesting review is exclusively designed on specifically
classified category of chemical reactions with primary precursors such as o-substituted
anilines and 2-aminobenzazoles (2ABZs). This will constitute the important goals and
novelty of this paper to facilitate synthetic chemists in the investigation about development
of new pharmacophores.
An Overview of Palladium-Catalyzed Fabrication of Some Heterocyclic
Frameworks
Authors: Devi Ahanthem Priyanca , Ameta Keshav Lalit , Penoni Andrea , Akhmetova Vnira R. , Pawar Rajendra P. , Fatimah Is 
Published: June 2022

Abstract:
Heterocycles are the largest family of organic compounds due to their wide applications as therapeutic agents, synthetic intermediates, scaffolds, building blocks or fine chemicals. Heterocyclic compounds are continuously used in material science, biotechnology, pharmaceutical and agrochemical industries. In the past few years, the use of transition metal complexes especially palladium as a heterogeneous catalyst has become a trend for the synthesis of various organic compounds. Pd-catalyzed reactions have proven to be effective ways for synthesising a variety of heterocyclic compounds, which are a popular class of molecules in chemical study. Hence, in this review we have discussed the palladium catalyzed synthesis of various heterocyclic compounds i,e. furan, indole, quinoline, coumarin and some other heterocycle derivatives.
Construction and Investigation of circRNA-associated ceRNA Regulatory
Network in Molecular Subtypes of Breast Cancer
Authors: Luo Jiesi , Zhong Yinming , Pan Sicen , Zhi Shunji , Li Yue , Xiu Zhiping , Wei Changran 
Published: June 2022

Background:
Circular RNAs (circRNAs) act as competing endogenous RNAs (ceRNAs)
that indirectly regulate gene expression and function by binding microRNAs (miRNAs). A
growing body of evidence indicates that the ceRNA networks can be used as an effective method
to investigate cancer; however, the construction and analysis of ceRNA networks, especially
circRNA-miRNA-mRNA regulatory network, in different subtypes of breast cancer have not been
previously performed.

Objectives:
The current study provides a potential application of the ceRNA network within BC
subtypes and may offer new targets for their diagnosis, therapy and prognosis.

Methods:
First, the expression profiles of circRNA, miRNA, and mRNA were downloaded from
the GEO database, differentially expressed genes were obtained using GEO2R, and a ceRNA network
was constructed based on circRNA-miRNA pairs and miRNA-mRNA pairs, consisted of 10
circRNAs, 25 miRNAs and 39 mRNAs. Further studies of BC subtypes based on TCGA datasets
were also performed to validate the effect of a novel ceRNA network.

Results and Discussion:
Then, the related genes in the regulatory network were analyzed by GO
functional annotation and KEGG pathway enrichment. The analysis showed that targeted genes
were enriched in 97 GO terms and 25 KEGG pathways, involved in the molecular typing of breast
cancer. Meanwhile, Kaplan-Meier analysis revealed that three key genes (MKI67, DEF8, and
GFRA1) were significantly associated with BC tumor differentiation and prognosis.

Conclusion:
The current study provides a potential application of ceRNA network within BC subtypes, and may offer new targets for their diagnosis, therapy and prognosis.
Co-culture of Liver Parenchymal Cells with Non-parenchymal Cells Under 2D and 3D Culture Systems; A Review
Authors: Farzaneh Zahra , Khojastehpour Fatemeh , Keivan Mona , Farzaneh Maryam 
Published: June 2022

Abstract:Hepatocytes are the major parenchymal cells (PC) in the liver and present an important role in liver metabolism. Hepatocytes are considered a gold standard tool for drug toxicity/screening or liver disease modeling. However, the maturation and functions of hepatocytes are lost under routine 2- dimensional (2D) culture conditions. Recent studies revealed that the interactions between hepatocytes and non-parenchyma cells (NPC) under 3D culture conditions can be an alternative option for optimizing hepatocyte maturation. Co-culture of hepatocytes with NPC simplifies the in-vitro liver disease models of fibrosis, steatosis and non-alcoholic fatty liver disease (NAFLD), cholestasis, and viral hepatitis. This review described the co-culture of liver PC with NPC under 2D and 3D culture systems.
Management of A Bad Split Complication: A Systematic Review
Authors: Afifah Naaila , Maulina Tantry , Yuza Abel Tasman 
Published: June 2022

Introduction:
Bad split is one of the well-known intra-operative complications that occur during the bilateral sagittal split osteotomy (BSSO) procedure, which is a rehabilitation procedure for patients with mandibular deformities. The prevention of further post-surgery complications required sufficient management of bad split complications.

Objective:
This study aimed to analyze the management of bad split complications during a BSSO procedure.

Methods:
The literature review was conducted in the form of library research in the field of bad split complications' management by a BSSO based on the Preferred Reporting Items for Systematic Reviews (PRISMA). Related studies were found through using a manual search using Pubmed, ScienceDirect, Ebscohost, Scopus, Medline, Embase, and Web of Science, among other search engines. The inception of incorporation standards, the process of data extraction, and the determination of the risk of bias were carried out by the authors. The process of data screening was conducted by applying the inclusion and exclusion criteria.

Results:
This paper systematically reviewed seven related studies, four of which were case series and two of which were cross-sectional. The utilization of additional osteosynthetic plates was revealed throughout the extraction process as the most acquainted course of action to manage the bad split complications during the BSSO procedure.

Conclusion:
The osteosynthetic plate and miniplate application with bicortical or monocortical screws were exposed as the most used treatment for bad split complications.
IoT-Enabled Energy-efficient Multipath Power Control for Underwater
Sensor Networks
Authors: Shaker Reddy Pundru Chandra , Sucharitha Yadala 
Published: June 2022

Aims & Background:
Energy saving or accurate information transmission within resource limits were major challenges for IoT Underwater Sensing Networks (IoT-UWSNs) on the Internet. Conventional transfer methods increase the cost of communications, leading to bottlenecks or compromising the reliability of information supply. Several routing techniques were suggested using UWSN to ensure uniform transmission of information or reduce communication latency while preserving a data battery (to avoid an empty hole in the network).

Objectives & Methodology:
In this article, adaptable power networking methods based on the Fastest Route Fist (FRF) method and a smaller amount of the business unit method are presented to solve the problems mentioned above. Both Back Laminated Inter Energy Management One (FLMPC-One) networking method, that employs 2-hop neighborhood knowledge, with the Laminated Inter Energy Management Two (FLMPC-Two) networking procedure, which employs 3-hop neighborhood data, were combined to create such innovative technologies (to shortest path selection). Variable Session Portion (SP) and Information Speed (IS) were also considered to ensure that the suggested method is flexible.

Results & Conclusions:
These findings show that the suggested methods, Shortest Path First without 3-hop Relatives Data (SPF-Three) or Broadness Initial Searching for Shortest Route. Breadth First Search to 3-hop Relatives Data (BFS-Three) was successfully developed (BFS-SPF-Three). These suggested methods are successful in respect of minimal Electric Cost (EC) and Reduced Transmission Drop Rates (RTDR) given a small number of operational sites at a reasonable latency, according to the simulated findings.
High Free Volume Polymeric Membranes for CO2 Capture: Stateof-
the-art
Authors: Wan Ruilin , Ma Yulei , Wei Jing , Guo Hongfang , Fan Jianan , Qin Zikang , Dai Zhongde 
Published: June 2022

Abstract:
Carbon dioxide (CO2) capture has been widely accepted to be a prerequisite
strategy to mitigate the increase of CO2 concentration in the atmosphere. Membrane separation
has been envisaged to be one of the most promising technologies for CO2 capture
due to its small footprint, simple up- and down-scaling, and low impact on the environment.
Owing to their extraordinary high CO2 permeability and moderate CO2 selectivity
over other gases, high free volume polymeric membrane materials have been intensively
studied for CO2 capture. In the past few years, abundant high free volume polymers have
been developed and big progress has been made in this field. Therefore, in this review,
starting from CO2 emissions and sources, followed by CO2 transport mechanisms in polymeric
membranes, this paper emphasizes reviewing recent research progress in high
free volume membrane materials, collecting and analyzing CO2 separation data, as well
as discussing the challenges of high free volume polymeric membranes. Furthermore,
perspectives on future directions of high free volume polymeric membranes were also
proposed.
Translation and Validation Study of the French Version of the eHealth Literacy Scale: Web-Based Survey on a Student Population
Authors: Chaniaud Noémie , Sagnier Camille , Loup-Escande Emilie 
Published: June 2022

Background
eHealth literacy is emerging as a crucial concept for promoting patient self-management in an overloaded hospital system. However, to the best of our knowledge, no tool currently exists to measure the level of eHealth literacy among French-speaking people. The eHealth Literacy Scale (eHEALS) is an easy-to-administer 8-item questionnaire (5-point Likert scale, ranging from strongly disagree to strongly agree) that has already been translated into many languages. Currently, it is the most cited questionnaire in the literature.

Objective
The aim of this study was to translate eHEALS to French and validate the French version of eHEALS (F-eHEALS).

Methods
The validation of the F-eHEALS scale followed the 5 steps of the transcultural validation method: double reverse translation, validation by a committee of experts (n=4), pretest measurement to check the clarity of the items (n=22), administration of the scale in French via a web-based quantitative study combined with two other questionnaires (Health Literacy Survey-Europe–16 and Patient Activation Measure–13; N=328 students), and finally test-retest (n=78) to check the temporal stability of the measurements obtained from the scale.

Results
The results obtained for the measurement of factor structure, internal consistency, and temporal stability (intraclass correlation coefficient=0.84; 95% CI 0.76-0.9; F77,77=6.416; P<.001) prove the validity and fidelity of the proposed scale. The internal consistency of F-eHEALS was estimated by Cronbach α of .89. The factor analysis with varimax rotation used to validate the construct showed a 2-factor scale. The effect of the construct was analyzed using 3 hypotheses related to the theory. The F-eHEALS score was correlated with the Health Literacy Survey-Europe–16 score (r=0.34; P<.001) and the Patient Activation Measure–13 score (r=0.31; P<.001).

Conclusions
F-eHEALS is consistent with the original version. It presents adequate levels of validity and fidelity. This 2D scale will need to be generalized to other populations in a French-speaking context. Finally, a version taking into account collaborative applications (ie, Health 2.0; eg, Digital Health Literacy Instrument scale) should be considered on the basis of this study.
Predicting Risk of Hypoglycemia in Patients With Type 2 Diabetes by Electronic Health Record–Based Machine Learning: Development and Validation
Authors: Yang Hao , Li Jiaxi , Liu Siru , Yang Xiaoling , Liu Jialin 
Published: June 2022

Background
Hypoglycemia is a common adverse event in the treatment of diabetes. To efficiently cope with hypoglycemia, effective hypoglycemia prediction models need to be developed.

Objective
The aim of this study was to develop and validate machine learning models to predict the risk of hypoglycemia in adult patients with type 2 diabetes.

Methods
We used the electronic health records of all adult patients with type 2 diabetes admitted to West China Hospital between November 2019 and December 2021. The prediction model was developed based on XGBoost and natural language processing. F1 score, area under the receiver operating characteristic curve (AUC), and decision curve analysis (DCA) were used as the main criteria to evaluate model performance.

Results
We included 29,843 patients with type 2 diabetes, of whom 2804 patients (9.4%) developed hypoglycemia. In this study, the embedding machine learning model (XGBoost3) showed the best performance among all the models. The AUC and the accuracy of XGBoost are 0.82 and 0.93, respectively. The XGboost3 was also superior to other models in DCA.

Conclusions
The Paragraph Vector–Distributed Memory model can effectively extract features and improve the performance of the XGBoost model, which can then effectively predict hypoglycemia in patients with type 2 diabetes.