bluuebunny/crossref_metadata_2025_split huggingface dataset:
SIX1: A Prognostic Biomarker in Uterine Corpus Endometrial Carcinoma
Authors: Chen Guohua , Zhao Quangang , Yang Xin , Wang Taiyong , Yuan Shuhong , Meng Qi 
Published: April 2022

Background:
Uterine Corpus Endometrial Carcinoma (UCEC) is a common malignancy
of the female genital tract. The sine oculis homeobox homolog 1 (SIX1) protein has been documented
to be important for tumor progression. However, little is known about the relationship
between SIX1 and the pathogenesis of UCEC.

Objective:
This study aimed to assess the prognostic value of biomarker SIX1 in UCEC by analyzing
clinical traits, immune infiltration, and gene set enrichment analysis.

Method:
The Wilcoxon signed-rank test and logistic regression were used to analyze the relationship
between clinicopathological characteristics and SIX1. The Kaplan-Meier method was used to
assess the relationship between clinicopathological characteristics and prognosis verified by immunohistochemistry
(IHC). Then gene set enrichment analysis (GSEA) was performed to explore
signaling pathways correlated with SIX1 expression in UCEC. Finally, the TIMER2 database was
used to analyze the correlation between SIX1 and immune infiltration, and the effect of SIX1 expression
on immune cells was calculated with the CIBERSORT algorithm.

Results:
We found that the expression of SIX1 in UCEC was up-regulated and correlated with a
poor prognosis. Analysis showed that the expression of SIX1 was related to various clinical features
and was an independent prognostic factor of UCEC. Enrichment analysis showed that SIX1
promoted the occurrence and development of UCEC by regulating multiple signaling pathways.
The results of immune infiltration analysis showed that SIX1 has a complex correlation with
immune infiltration.

Conclusion:
Our findings indicate that SIX1 is a promising biomarker for predicting the prognosis
of UCEC and is a potential therapeutic target.
Developing a Genetic Biomarker-based Diagnostic Model for Major
Depressive Disorder using Random Forests and Artificial Neural Networks
Authors: Xie Zhongwen , Gu Wei , Ming Tinghong 
Published: April 2022

Background:
The clinical diagnosis of major depressive disorder (MDD) mainly relies
on subjective assessment of depression-like behaviors and clinical examination. In the present
study, we aimed to develop a novel diagnostic model for specially predicting MDD.

Methods:
The human brain GSE102556 DataSet and the blood GSE98793 and GSE76826 Data
Sets were downloaded from the Gene Expression Omnibus (GEO) database. We used a novel algorithm,
random forest (RF) plus artificial neural network (ANN), to examine gene biomarkers and
establish a diagnostic model of MDD.

Results:
Through the “limma” package in the R language, 2653 differentially expressed genes
(DEGs) were identified in the GSE102556 DataSet, and 1786 DEGs were identified in the
GSE98793 DataSet, and a total of 100 shared DEGs. We applied GSE98793 TrainData 1 to an RF
algorithm and thereby successfully selected 28 genes as biomarkers. Furthermore, 28 biomarkers
were verified by GSE98793 TestData 1, and the performance of these biomarkers was found to be
perfect. In addition, we further used an ANN algorithm to optimize the weight of each gene and
employed GSE98793 TrainData 2 to build an ANN model through the neural net package by R
language. Based on this algorithm, GSE98793 TestData 2 and independent blood GSE76826 were
verified to correlate with MDD, with AUCs of 0.903 and 0.917, respectively.

Conclusion:
To the best of our knowledge, this is the first time that the classifier constructed via
DEG biomarkers has been used as an endophenotype for MDD clinical diagnosis. Our results may
provide a new entry point for the diagnosis, treatment, outcome prediction, prognosis and recurrence
of MDD.
Comprehensive Characterization of RNA-Binding Proteins in Colon
Adenocarcinoma Identifies a Novel Prognostic Signature for Predicting
Clinical Outcomes and Immunotherapy Responses Based on Machine
Learning
Authors: Ren Jie , Wang Changmiao , Miao Ye , Yuan Qihang , Wang Chao , Feng Xiaoshi 
Published: April 2022

Background:
RNA-binding proteins (RBPs) are crucial factors that function in the posttranscriptional
modification process and are significant in cancer.

Objective:
This research aimed for a multigene signature to predict the prognosis and immunotherapy
response of patients with colon adenocarcinoma (COAD) based on the expression profile of
RNA-binding proteins (RBPs).

Methods:
COAD samples retrieved from the TCGA and GEO datasets were utilized for a training
dataset and a validation dataset. Totally, 14 shared RBP genes with prognostic significance were
identified. Non-negative matrix factorization clusters defined by these RBPs could stratify COAD
patients into two molecular subtypes. Cox regression analysis and identification of 8-gene signature
categorized COAD patients into high- and low-risk populations with significantly different
prognosis and immunotherapy responses.

Results:
Our prediction signature was superior to another five well-established prediction models.
A nomogram was generated to quantificationally predict the overall survival (OS) rate, validated
by calibration curves. Our findings also indicated that high-risk populations possessed an enhanced
immune evasion capacity and low-risk populations might benefit immunotherapy, especially for
the joint combination of PD-1 and CTLA4 immunosuppressants. DHX15 and LARS2 were detected
with significantly different expressions in both datasets, which were further confirmed by qRTPCR
and immunohistochemical staining.

Conclusion:
Our observations supported an eight-RBP-related signature that could be applied for
survival prediction and immunotherapy response of patients with COAD.
Effect of Atorvastatin on Single Oral Pharmacokinetics and Safety of Daclatasvir in
Rats: Emphasis on P-glycoprotein and Cytochrome P450
Authors: Elbadawy Heba A. , Wahdan Sara A. , El-Demerdash Ebtehal 
Published: April 2022

Objective:
This study aimed to investigate the effect of atorvastatin on daclatasvir oral pharmacokinetics
and safety and assess the possible underlining mechanisms by targeting P-glycoprotein (P-gp) and cytochrome P450
(CYP3A4).

Methods:
The transport of daclatasvir, as well as the standard rhodamine 123 by P-gp across the rat intestine, was
studied in vitro using the non-everted sac method. To assess the pharmacokinetic profile of daclatasvir in vivo, rats
were divided into three groups receiving either saline, standard P-gp inhibitor verapamil (25 mg/kg), or atorvastatin
(10 mg/kg), 2 hrs prior to a single dose of daclatasvir (7 mg/kg). In addition, the markers of liver and kidney functions
and muscle rhabdomyolysis were assessed. Further, histopathological examination of liver and kidney tissue
and assessment of CYP3A4 level was done.

Results:
The inhibitory effect of atorvastatin on Pgp activity and expression was manifested by increased serosal
transport of the standard rhodamine 123, as well as daclatasvir. In vivo, Cmax (peak plasma concentration) and area
under the curve (AUC (0‐t)) of daclatasvir after atorvastatin treatment increased compared to the vehicle group but
not in a significant manner. On the other hand, atorvastatin caused a significant increase in the clearance of daclatasvir.
Concomitant administration of atorvastatin with daclatasvir significantly decreased CYP3A4 content compared
to the control group. The combination also showed increased liver enzymes and some pathological alterations in the
liver.

Conclusion:
Atorvastatin has a significant effect on P-gp mediated intestinal transport of daclatasvir; however, it did
not affect the systemic bioavailability of a single oral dose of daclatasvir.
The Identification and Analysis of MicroRNAs Combined Biomarkers for
Hepatocellular Carcinoma Diagnosis
Authors: Shi Yi , Men Jingrui , Sun Hongliang , Tan Jianjun 
Published: April 2022

Background:
Hepatocellular carcinoma (HCC) is a common malignant tumor with high
morbidity and mortality globally. Compared with traditional diagnostic methods, microRNAs (miRNAs)
are novel biomarkers with higher accuracy.

Objective:
We aimed to identify combinatorial biomarkers of miRNAs to construct a classification
model for the diagnosis of HCC.

Method:
The mature miRNA expression profile data of six cancers (liver, lung, gastric, breast, prostate,
and colon) were retrieved from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus
(GEO) database with accession number GSE36915, GSE29250, GSE99417, GSE41970,
GSE64333 and GSE35982. The messenger RNA (mRNA) expression profile data of these six cancers
were obtained from TCGA. Three R software packages, student’s t-test, and a normalized foldchange
method were utilized to identify HCC-specific differentially expressed miRNAs (DEMs).
Using all combinations of obtained HCC-specific DEMs as input features, we constructed a classification
model by support vector machine searching for the optimal combination. Furthermore, target
genes prediction was conducted on the miRWalk 2.0 website to obtain differentially expressed
mRNAs (DEmRNAs), and KEGG pathway enrichment was analyzed on the DAVID website.

Results:
The optimal combination consisted of four miRNAs (hsa-miR-130a-3p, hsa-miR-450b-5p,
hsa-miR-136-5p, and hsa-miR-24-1-5p), of which the last one has not been currently reported to be
relevant to HCC. The target genes of hsa-miR-24-1-5p (CDC7, ACACA, CTNNA1, and NF2) were
involved in the cell cycle, AMPK signaling pathway, Hippo signaling pathway, and insulin signaling
pathway, which affect the proliferation, metastasis, and apoptosis of cancer cells. Moreover, the area
under the receiver operating characteristic curves of the four miRNAs were all higher than 0.85.

Conclusion:
These results suggest that the miRNAs combined biomarkers were reliable for the diagnosis
of HCC. Hsa-miR-24-1-5p was a novel biomarker for HCC diagnosis identified in this study.
Modified Drug Delivery Systems for Veterinary Use: Pharmaceutical Development and Applications
Authors: Souto Eliana B. , Santini Antonello , Barbosa Catarina I. , Baldim Iara , Campos Joana R. , Fernandes Ana R. , Mazzola Priscila G. , Andreani Tatiana , Dias Isabel R. , Durazzo Alessandra , Lucarini Massimo , Atanasov Atanas G. , Silva Amélia M. 
Published: April 2022

Abstract:Scientific research in the field of veterinary pharmacology has provided new opportunities for the development of modified release dosage forms, with the aim to improve therapeutic efficacy and reduce animal stress. The formulation of classical drug molecules with advanced biomaterials has become a new approach to increase drug bioavailability and thereby improve the therapeutic outcome. The main reasons for the development of modified drug delivery systems for animal use are the need of reducing the animal stress caused by its handling and administration of the drug and of reducing the cost in financial and chronological terms. This review discusses the most common delivery systems used in veterinary, and the difficulties encountered in innovating therapeutic options in the field.
Distance-based Support Vector Machine to Predict DNA N6-
methyladenine Modification
Authors: Zhang Haoyu , Zou Quan , Ju Ying , Song Chenggang , Chen Dong 
Published: April 2022

Background:
DNA N6-methyladenine plays an important role in the restriction-modification
system to isolate invasion from adventive DNA. The shortcomings of the high time consumption and
high costs of experimental methods have been exposed, and some computational methods have
emerged. The support vector machine theory has received extensive attention in the bioinformatics field
due to its solid theoretical foundation and many good characteristics.

Objective:
General machine learning methods include an important step of extracting features. The research
has omitted this step and replaced with easy-to-obtain sequence distances matrix to obtain better
results.

Method:
First sequence alignment technology was used to achieve the similarity matrix. Then, a novel
transformation turned the similarity matrix into a distance matrix. Next, the similarity-distance matrix
was made positive semi-definite so that it can be used in the kernel matrix. Finally, the LIBSVM software
was applied to solve the support vector machine.

Results:
The five-fold cross-validation of this model on rice and mouse data has achieved excellent accuracy
rates of 92.04% and 96.51%, respectively. This shows that the DB-SVM method has obvious
advantages over traditional machine learning methods. Meanwhile, this model achieved 0.943,0.982 and
0.818 accuracy; 0.944, 0.982, and 0.838 Matthews correlation coefficient; and 0.942, 0.982 and 0.840
F1 scores for the rice, M. musculus and cross-species genome datasets, respectively.

Conclusion:
These outcomes show that this model outperforms the iIM-CNN and csDMA in the prediction
of DNA 6mA modification, which is the latest research finding on DNA 6mA.
Temozolomide Resistance: A Multifarious Review on Mechanisms Beyond
O-6-Methylguanine-DNA Methyltransferase
Authors: Rao Vanishree , Kumar Gautam , Vibhavari R.J.A. , Nandakumar Krishnadas , Thorat Nanasaheb D. , Chamallamudi Mallikarjuna Rao , Kumar Nitesh 
Published: April 2022

Background:
Chemotherapy with the oral alkylating agent temozolomide still prevails as a
linchpin in the therapeutic regimen of glioblastoma alongside radiotherapy. Because of the
impoverished prognosis and sparse chemotherapeutic medicaments associated with glioblastoma, the
burgeoning resistance to temozolomide has made the whole condition almost irremediable.

Objective:
The present review highlights the possible mechanisms of drug resistance following
chemotherapy with temozolomide.

Method:
The review summarizes the recent developments, as published in articles from Scopus,
PubMed, and Web of Science search engines.

Description:
One of the prime resistance mediators, O‑6‑methylguanine‑DNA methyltransferase, upon
activation, removes temozolomide-induced methyl adducts bound to DNA and reinstates genomic
integrity. In the bargain, neoteric advances in the conception of temozolomide resistance have opened
the door to explore several potential mediators like indirect DNA repair systems, efflux mechanisms,
epigenetic modulation, microenvironmental influences, and autophagy-apoptosis processes that
constantly lead to the failure of chemotherapy.

Conclusion:
This review sheds light on recent discoveries, proposed theories, and clinical developments
in the field of temozolomide resistance to summarize the complex and intriguing involvement of
oncobiological pathways.
Circularly Polarized Triangular Patch Antenna
Authors: Toktas Abdurrahim 
Published: April 2022

Background:
Circularly polarized (CP) antenna is an effective choice for wireless systems
due to its insensitivity to the orientations of electromagnetic waves.

Objective:
A novel CP triangular patch antenna (CPTA) system is designed for ultra-wideband
(UWB) applications.

Methods:
The CPTA, with a total size of 40.6 x 40.9 x 1.6 mm3, comprises a triangular patch positioned
on the aperture of a V-shaped ground plane and a feeding network that powers the two corners
of the patch. The network consists of a T-shaped divider with a 50 Ohm microstrip transmission line
(MTL) and two 100 Ohm MTLs, and two matching strips are inserted at the end of the MTLs.

Results:
The antenna system shows UWB performance for both impedance bandwidth (IM-BW) of
4-11 GHz and axial ratio bandwidth (AR-BW) of 3.5-8.0 GHz. A detailed review is further carried
out to manifest the superiority of CPTA over the state-of-the-art technology.

Conclusion:
It thus provides compatible IM-BW and AR-BW for UWB operations due to its optimal
compact design.
Rubbery Polyhydroxyesters based on Polyethylene Glycol Diglycidyl Ether:
Reaction and Vitrimer-like Behavior Catalyzed by Tin Octoate
Authors: Cunha Rodrigo H. , Nele Marcio , Dias Marcos L. , Cunha R. 
Published: April 2022

Background:
Polyhydroxyesters prepared from epoxy and organic acids are vitrimers that can rearrange their topology from exchange reactions enhanced by catalysts, forming crosslinked net-works that can be deformed and remolded.

Objectives:
In this work, the curing kinetics and thermal properties of polyhydroxyesters vitrimers based on polyethylene glycol diglycidyl ether (PEGDGE), citric acid (CA), and sebacic acid (SA) in the presence and absence of tin octoate (Sn(Oct)2) were investigated.

Methods:
Differential scanning calorimetry (DSC) non-isothermal experiments and Ozawa models were used for the curing kinetic studies, and thermogravimetry analysis (TGA) and thermomechanical analyses (TMA) were employed to investigate the thermal behavior of the networks.

Results:
The highest curing enthalpy of these exothermic reactions was observed in the binary system PEGDGE:CA without catalyst (326 J/g). The addition of Sn increases the reaction enthalpy for formu-lations with SA and decreases it for formulations rich in CA. The lowest activation energy was shown for the formulation PEGDGE:CA = 3:2 containing 1 mol% of Sn (56 kJ/mol). The polyhydroxyesters presented Tg ranging from -24 to -48 °C, and the Tg decreased when the proportion of SA was in-creased in the formulation. The thermal stability was increased when the SA content increased and de-creased when the content of Sn increased from 1 to 5 mol%.

Conclusion:
Esterification of PEGDGE and organic acids (SA and CA) occurs even in the absence of catalyst, producing rubbery polyesters, but the use of Sn(Oct)2 decreases the curing time. Ternary net-works of polyhydroxyesters containing Sn showed a discontinuity in the thermal expansion around 180°C attributed to exchange reactions, similarly to what was theorized for this class of vitrimer material.
Analytical Methods and GAPI Assessment Used for the Determination of
Toxic Metals in Commercial Cosmetic Products: A Review
Authors: Abbas Ruba Fahmi , Waheb Ali Amer 
Published: April 2022

Background:
The toxic metal content of cosmetics causes worry because of the daily and repeated use of these products, which are placed over thin and sensitive areas of the skin such as the face, eyelids, and lips.

Objective:
Toxic metals like Fe, Cr, Hg, Cu, Cd, Ni, and As are determined in various types of cosmetics such as colour cosmetics, hair cosmetics, body and face care products, and herbal cosmetics. Last studies estimate that in commercial cosmetics toxic metals might present in amounts making a risk to human health.

Methods:
Many analysis methods used for determining toxic metals in cosmetics were established. The instruments involving FAAS, ICP-AES, ICP–MS, Hydride generation, Cold vapor, and CE spectrometers with many novel methods were described in this review. Green analytical methods should be developed for determining toxic metals in cosmetics and particularly during the preparation of analytical cosmetic samples.

Results:
The most tools used for assessing analytical protocols related to green analytical chemistry are GAPI (Green Analytical Procedure Index). GAPI gives good information on the safety of analytical chemistry procedures, depending on the five pentagrams shaped with three color symbols that can be used (green, yellow, and red) referring to low, medium to high impact, respectively.

Conclusion:
This review offers an overview, analytical chemistry methods and instruments used for the estimation of toxic metals in cosmetics and their GAPI assessment.
Vesicular Approach Review on Nanocarriers bearing Curcumin and Applications
Authors: Upadhyay Prashant , Singh Deepak , Upadhyay Sukirti 
Published: April 2022

Abstract:
Phytoconstituents have been used to treat a variety of human diseases for a long time, but their use in pharmaceuticals is limited because of their low aqueous solubility. Researchers have created vesicular systems to address many of the issues associated with the bioavailability and therapeutic efficacy of poorly water-soluble drugs and target the drug to the desired location in the body. Several vesicular nanocarrier systems have been developed. Review contrasts various vesicular drug delivery systems, including liposomes, sphingosomes, emulsomes, niosomes, ethosomes, virosomes, phytosomes, aquasomes, proniosomes, transfersomes, pharmacosomes. Vesicular drug delivery systems have caused a scientific revolution, which has resulted in the development of novel dosage forms. This review aims to illustrate the applications, advantages, and disadvantages of the vesicular approach as nanocarriers bearing curcumin and widely used in gene delivery, tumor-targeting to the brain, oral formulations, and resolving various problems associated with drug stability and permeability issues. Nanocarriers also has wide application as green nanocomposites and for antitubercular drugs depending on their physical properties.
Drug Delivery Platforms Containing Thermoresponsive Polymers and
Mucoadhesive Cellulose Derivatives: A Review of Patents
Authors: da Silva Jéssica Bassi , dos Santos Rafaela Said , Vecchi Camila Felix , Bruschi Marcos Luciano 
Published: April 2022

Abstract:
Nowadays, the development of mucoadhesive systems for drug delivery has gained keen
interest, with enormous potential in applications through different routes. Mucoadhesion characterizes
an attractive interaction between the pharmaceutical dosage form and the mucosal surface. Many polymers
have shown the ability to interact with mucus, increasing the residence time of local and/or systemic
administered preparations, such as tablets, patches, semi-solids, and micro and nanoparticles.
Cellulose is the most abundant polymer on the earth. It is widely used in the pharmaceutical industry
as an inert pharmaceutical ingredient, mainly in its covalently modified forms: methylcellulose, ethylcellulose,
hydroxyethyl cellulose, hydroxypropyl cellulose, hydroxypropyl methylcellulose, and carboxymethylcellulose
salts. Aiming to overcome the drawbacks of oral, ocular, nasal, vaginal, and rectal
routes and thereby maintaining patient compliance, innovative polymer blends have gained the interest
of the pharmaceutical industry. Combining mucoadhesive and thermoresponsive polymers allows
for simultaneous in situ gelation and mucoadhesion, thus enhancing the retention of the system at
the site of administration and drug availability. Thermoresponsive polymers have the ability to change
physicochemical properties triggered by temperature, which is particularly interesting considering the
physiological temperature. The present review provides an analysis of the main characteristics and applications
of cellulose derivatives as mucoadhesive polymers and their use in blends together with
thermoresponsive polymers, aiming at platforms for drug delivery. Patents were reviewed, categorized,
and discussed, focusing on the applications and pharmaceutical dosage forms using this innovative
strategy. This review manuscript also provides a detailed introduction to the topic and a perspective
on further developments.