bluuebunny/crossref_metadata_2025_split huggingface dataset:
Machine learning, Water Quality Index, and GIS-based analysis of groundwater quality
Authors: Solangi Ghulam Shabir , Ali Zouhaib , Bilal Muhammad , Junaid Muhammad , Panhwar Sallahuddin , Keerio Hareef Ahmed , Sohu Iftikhar Hussain , Shahani Sheeraz Gul , Zaman Noor 
Published: January 2024

Abstract

Water is essential for life, as it supports bodily functions, nourishes crops, and maintains ecosystems. Drinking water is crucial for maintaining good health and can also contribute to economic development by reducing healthcare costs and improving productivity. In this study, we employed five different machine learning algorithms – logistic regression (LR), decision tree classifier (DTC), extreme gradient boosting (XGB), random forest (RF), and K-nearest neighbors (KNN) – to analyze the dataset, and their prediction performance were evaluated using four metrics: accuracy, precision, recall, and F1 score. Physiochemical parameters of 30 groundwater samples were analyzed to determine the Water Quality Index (WQI) of Pano Aqil city, Pakistan. The samples were categorized into the following four classes based on their WQI values: excellent water, good water, poor water, and unfit for drinking. The WQI scores showed that only 43.33% of the samples were deemed acceptable for drinking, indicating that the majority (56.67%) were unsuitable. The findings suggest that the DTC and XGB algorithms outperform all other algorithms, achieving overall accuracies of 100% each. In contrast, RF, KNN, and LR exhibit overall accuracies of 88, 75, and 50%, respectively. Researchers seeking to enhance water quality using machine learning can benefit from the models described in this study for water quality prediction.
Bio-copper nanoparticle-based superhydrophobic membranes for sustainable oil/water separation
Authors: Beagan A. , Chen C. , Mohamed M. E. 
Published: January 2024

Abstract
The effective separation of oil and water presents a significant global challenge due to the growing prevalence of industrial oily wastewater. In this investigation, a superhydrophobic (SP) coating based on bio-copper (Cu) was successfully created using the grape seed extract and applied onto a textile fabric (TF) to create a highly efficient membrane for oil–water (O–W) separation. The characteristics of the resulting bio-Cu nanoparticles, including surface area, morphology, and composition, were examined. The developed SP TF (STF) membrane, based on bio-Cu, underwent extensive analysis of its wettability, morphology, surface composition, oil absorption capacity, O–W separation performance, flux rate, mechanical stability, and chemical stability. The STF membrane exhibited excellent SP properties, with a high-water contact angle of 156° and a low water sliding angle of 2°, indicating its exceptional ability to repel water. Furthermore, the membrane demonstrated a remarkable oil absorption capacity, separation efficiency, and the flux rate toward three different oils (diesel, corn oil, and kerosene). It displayed good mechanical and chemical stability, with the ability to withstand abrasion and immersion in solutions of different pH values for varying exposure times. These findings highlight the potential of the bio-Cu-based STF membrane as an effective and durable solution for O–W separation applications.
Systematic Review on Herbal Preparations for Controlling Visceral
Hypersensitivity in Functional Gastrointestinal Disorders
Authors: Lashgari Naser-Aldin , Momeni Roudsari Nazanin , Momtaz Saeideh , Niazi Shahraki Faezeh , Zandi Nadia , Pazoki Benyamin , Farzaei Mohammad Hosein , Ghasemi Mehdi , Abdollahi Mohammad , Abdolghaffari Amir Hossein 
Published: January 2024

Background:
Visceral hypersensitivity (VH) is an overreaction of the gastrointestinal
(GI) tract to various stimuli and is characterized by hyperalgesia and/or allodynia. VH contributes
to the etiology of many GI dysfunctions, particularly irritable bowel syndrome (IBS). Although
the exact mechanisms underlying VH are yet to be found, inflammation and oxidative
stress, psychosocial factors, and sensorimotor alterations may play significant roles in it.

Objective:
In this review, we provide an overview of VH and its pathophysiological function in
GI disorders. Adverse effects of synthetic drugs may make herbal agents a good candidate for
pain management. Therefore, in this review, we will discuss the efficacy of herbal agents in the
management of VH with a focus on their anti-inflammatory and antioxidant potentials.

Methods:
Data were extracted from clinical and animal studies published in English between
2004 and June, 2020, which were collected from PubMed, Google Scholar, Scopus, and
Cochrane Library.

Results:
Overall, Radix, Melissia, Glycyrrhizae, Mentha, and Liquorice were the most efficient
herbals for VH management in IBS and dyspepsia, predominantly through modulation of the
mRNA expression of transient receptor potential vanilloid type-1 (TRPV1) and suppression of 5-
hydroxytryptamine 3 (5-HT3) or the serotonin receptors.

Conclusion:
Considering the positive effects of herbal formulations in VH management, further
research on novel herbal and/or herbal/chemical preparations is warranted.
A Novel Methylation-based Model for Prognostic Prediction in Lung Adenocarcinoma
Authors: Li Manyuan , Deng Xufeng , Zhou Dong , Liu Xiaoqing , Dai Jigang , Liu Quanxing 
Published: January 2024

Objective:Specific methylation sites have shown promise in the early diagnosis of lung adenocarcinoma (LUAD). However, their utility in predicting LUAD prognosis remains unclear. This study aimed to construct a reliable methylation-based predictor for accurately predicting the prognosis of LUAD patients.Method:DNA methylation data and survival data from LUAD patients were obtained from the TCGA and a GEO series. A DNA methylation-based signature was developed using univariate least absolute shrinkage and selection operators and multivariate Cox regression models.Result:Eight CpG sites were identified and validated as optimal prognostic signatures for the overall survival of LUAD patients. Receiver operating characteristic analysis demonstrated the high predictive ability of the eight-site methylation signature combined with clinical factors for overall survival.Conclusion:This research successfully identified a novel eight-site methylation signature for predicting the overall survival of LUAD patients through bioinformatic integrated analysis of gene methylation markers used in the early diagnosis of lung cancer.
Exploring the Role of Non-synonymous and Deleterious Variants
Identified in Colorectal Cancer: A Multi-dimensional Computational
Scrutiny of Exomes
Authors: Karunakaran Chandrashekar , Niranjan Vidya , Setlur Anagha S. , Pradeep Dhanya , Kumar Jitendra 
Published: January 2024

Introduction:
Colorectal cancers are the world’s third most commonly diagnosed type
of cancer. Currently, there are several diagnostic and treatment options to combat it. However, a
delay in detection of the disease is life-threatening. Additionally, a thorough analysis of the exomes
of cancers reveals potential variation data that can be used for early disease prognosis.

Methods:
By utilizing a comprehensive computational investigation, the present study aimed to reveal
mutations that could potentially predispose to colorectal cancer. Ten colorectal cancer exomes
were retrieved. Quality control assessments were performed using FastQC and MultiQC,
gapped alignment to the human reference genome (hg19) using Bowtie2 and calling the germline
variants using Haplotype caller in the GATK pipeline. The variants were filtered and annotated using
SIFT and PolyPhen2 successfully categorized the mutations into synonymous, non-synonymous,
start loss and stop gain mutations as well as marked them as possibly damaging, probably
damaging and benign. This mutational profile helped in shortlisting frequently occurring mutations
and associated genes, for which the downstream multi-dimensional expression analyses were
carried out.

Results:
Our work involved prioritizing the non-synonymous, deleterious SNPs since these polymorphisms
bring about a functional alteration to the phenotype. The top variations associated with
their genes with the highest frequency of occurrence included LGALS8, CTSB, RAD17, CPNE1,
OPRM1, SEMA4D, MUC4, PDE4DIP, ELN and ADRA1A. An in-depth multi-dimensional downstream
analysis of all these genes in terms of gene expression profiling and analysis and differential
gene expression with regard to various cancer types revealed CTSB and CPNE1 as highly expressed
and overregulated genes in colorectal cancer.

Conclusion:
Our work provides insights into the various alterations that might possibly lead to colorectal
cancer and suggests the possibility of utilizing the most important genes identified for wetlab
experimentation.
The Role of Cytokines in Activation of Tumour-promoting Pathways and
Emergence of Cancer Drug Resistance
Authors: Shirbhate Ekta , Singh Vaibhav , Kore Rakesh , Vishwakarma Subham , Veerasamy Ravichandran , Tiwari Amit K. , Rajak Harish 
Published: January 2024

Abstract:
Scientists are constantly researching and launching potential chemotherapeutic agents
as an irreplaceable weapon to fight the battle against cancer. Despite remarkable advancement
over the past several decades to wipe out cancer through early diagnosis, proper prevention, and
timely treatment, cancer is not ready to give up and leave the battleground. It continuously tries to
find some other way to give a tough fight for its survival, either by escaping from the effect of chemotherapeutic
drugs or utilising its own chemical messengers like cytokines to ensure resistance.
Cytokines play a significant role in cancer cell growth and progression, and the present article
highlights their substantial contribution to mechanisms of resistance toward therapeutic drugs.
Multiple clinical studies have even described the importance of specific cytokines released from
cancer cells as well as stromal cells in conferring resistance. Herein, we discuss the different mechanism
behind drug resistance and the crosstalk between tumor development and cytokines release
and their contribution to showing resistance towards chemotherapeutics. As a part of this review,
different approaches to cytokines profile have been identified and employed to successfully target
new evolving mechanisms of resistance and their possible treatment options.
Resistance Training Reduces Blood Pressure: Putative Molecular
Mechanisms
Authors: Ferreira Mendes Bruno , Improta-Caria Alex Cleber , Diniz e Magalhães Caique Olegário , Dias Peixoto Marco Fabricio , Cardoso Cassilhas Ricardo , de Oliveira Edilamar Menezes , De Sousa Ricardo Augusto Leoni 
Published: January 2024

Abstract:
Arterial hypertension is a multifactorial clinical condition characterized by higher blood pressure levels. The
main treatment for controlling high blood pressure consists of drug therapy, but the scientific literature has
been pointing to the efficiency of aerobic and resistance exercises acting in a therapeutic and/or preventive
way to reduce and control the blood pressure levels. Resistance training is characterized by sets and repetitions
on a given muscle segment that uses overload, such as machine weights, bars, and dumbbells. As it successfully
affects a number of variables associated to practitioners' functional and physiological features as well as
emotional and social variables, resistance training has been a crucial part of physical exercise programs. Several
reports highlight the various adaptive responses it provides, with a focus on the improvement in strength,
balance, and muscular endurance that enables a more active and healthy lifestyle. Resistance training programs
that are acute, sub-chronic, or chronic can help people with varying ages, conditions, and pathologies reduce
their arterial hypertension. However, molecular mechanisms associated with resistance training to reduce
blood pressure still need to be better understood. Thus, we aimed to understand the main effects of resistance
training on blood pressure as well as the associated molecular mechanisms.
Machine Learning in Magnetic Resonance Images of Glioblastoma: A Review
Authors: Waldo-Benítez Georgina , Padierna Luis Carlos , Cerón Pablo , Sosa Modesto A. 
Published: January 2024

Background::
The purpose of this work was to identify which Glioblastoma (GBM) problems can be handled by Magnetic Resonance Imaging (MRI) and
Machine Learning (ML) techniques. Results, limitations, and trends through a review of the scientific literature in the last 5 years were performed.
Google Scholar, PubMed, Elsevier databases, and forward and backward citations were used for searching articles applying ML techniques in
GBM. The 50 most relevant papers fulfilling the selection criteria were deeply analyzed. The PRISMA statement was followed to structure our
report.

Methods::
A partial taxonomy of the GBM problems tackled with ML methods was formulated with 15 subcategories grouped into four categories: extraction
of characteristics from tumoral regions, differentiation, characterization, and problems based on genetics.

Results::
The dominant techniques in solving these problems are: Radiomics for feature extraction, Least Absolute Shrinkage and Selection Operator for
feature selection, Support Vector Machines and Random Forest for classification, and Convolutional Neural Networks for characterization. A
noticeable trend is that the application of Deep Learning on GBM problems is growing exponentially. The main limitations of ML methods are
their interpretability and generalization.

Conclusion::
The diagnosis, treatment, and characterization of GBM have advanced with the aid of ML methods and MRI data, and this improvement is
expected to continue. ML methods are effective in solving GBM-related problems with different precisions, Overall Survival being the hardest
problem to solve with accuracies ranging from 57%-71%, and GBM differentiation the one with the highest accuracy ranging from 80%-97%.
Automated Diagnosis of Bone Metastasis by Classifying Bone Scintigrams Using
a Self-defined Deep Learning Model
Authors: Wang Yubo , Lin Qiang , Zhao Shaofang , Zeng Xianwu , Zheng Bowen , Cao Yongchun , Man Zhengxing 
Published: January 2024

Background::
Patients with cancer can develop bone metastasis when a solid tumor invades the bone, which is the third most commonly affected site by
metastatic cancer, after the lung and liver. The early detection of bone metastases is crucial for making appropriate treatment decisions and
increasing survival rates. Deep learning, a mainstream branch of machine learning, has rapidly become an effective approach to analyzing medical
images.

Objective::
To automatically diagnose bone metastasis with bone scintigraphy, in this work, we proposed to cast the bone metastasis diagnosis problem into
automated image classification by developing a deep learning-based automated classification model.

Methods::
A self-defined convolutional neural network consisting of a feature extraction sub-network and feature classification sub-network was proposed to
automatically detect lung cancer bone metastasis, with a feature extraction sub-network extracting hierarchal features from SPECT bone
scintigrams and feature classification sub-network classifying high-level features into two categories (i.e., images with metastasis and without
metastasis).

Results::
Using clinical data of SPECT bone scintigrams, the proposed model was evaluated to examine its detection accuracy. The best performance was
achieved if the two images (i.e., anterior and posterior scans) acquired from each patient were fused using pixel-wise addition operation on the
bladder-excluded images, obtaining the best scores of 0.8038, 0.8051, 0.8039, 0.8039, 0.8036, and 0.8489 for accuracy, precision, recall,
specificity, F-1 score, and AUC value, respectively.

Conclusion::
The proposed two-class classification network can predict whether an image contains lung cancer bone metastasis with the best performance as
compared to existing classical deep learning models. The high accumulation of 99mTc MDP in the urinary bladder has a negative impact on
automated diagnosis of bone metastasis. It is recommended to remove the urinary bladder before automated analysis.
A Comprehensive Review on Potential Chemical and Herbal Permeation
Enhancers Used in Transdermal Drug Delivery Systems
Authors: Raghav Rajat Singh , Verma Sushma , Monika  
Published: January 2024

Abstract:
Using skin patches to deliver drugs is dependable and doesn't have the same issues as
permeation enhancers, which help drugs get through the skin but struggle because of the skin's natural
barrier. Strategies are required to increase topical bioavailability to enhance drug absorption.
Natural compounds offer a promising solution by temporarily reducing skin barrier resistance and
improving drug absorption. Natural substances allow a wider variety of medications to be distributed
through the stratum corneum, offering a dependable approach to enhancing transdermal drug delivery.
Natural substances have distinct advantages as permeability enhancers. They are pharmacologically
effective and safe, inactive, non-allergenic, and non-irritating. These characteristics ensure
their suitability for use without causing adverse effects. Natural compounds are readily available
and well tolerated by the body. Studies investigating the structure-activity relationship of natural
chemicals have demonstrated significant enhancer effects. By understanding the connection between
chemical composition and enhancer activity, researchers can identify effective natural compounds
for improving drug penetration. In conclusion, current research focuses on utilizing natural
compounds as permeability enhancers in transdermal therapy systems. These substances offer safety,
non-toxicity, pharmacological inactivity, and non-irritation. Through structure-activity relationship
investigations, promising advancements have been made in enhancing drug delivery. Using
natural compounds holds enormous potential for improving the penetration of trans-dermally delivered
medications.
A Systemic Review on Nutraceutical Supplements used in the
Management of Osteoarthritis
Authors: Nooreen Zulfa , Wal Pranay , Summaiyya Fariha 
Published: January 2024

Abstract:
Osteoarthritis (OA) is a progressive degenerative joint disease. It basically impairs
the structural integrity of articulate cartilage and imbalances the catabolic and anabolic signals
in the joint. A degenerative disease is characterized by swelling, pain, and joint stiffness. The
treatment and management of osteoarthritis are based on analgesic and anti-inflammatory
agents, whereas the exact cause of OA is not known yet. The negative effects of synthetic medications
have led to a daily rise in the usage of nutraceuticals and dietary supplements. Clinicians
are aware of these treatments, and they also recommend nutraceuticals in addition to the currently
preferred therapy. Many in-vitro and in-vivo experiments have been performed in past
years to evaluate the function of these on osteoarthritis.

:
The collection of articles was published on search engines like PubMed, Scopus, Google Scholar,
ResearchGate, and ScienceDirect. The evaluation covers every potential nutraceutical utilized
in osteoarthritis, together with its supporting data and mode of action.

:
The present review discusses nutraceuticals, including devil’s claw, vitamin D, boswellic acid,
capsaicin, ginger, curcumin, krill oil, ginger, and avocado/soybean unsaponifiable.
Resistensi Pemilih Perempuan Terhadap Caleg Perempuan Di Kota Banjar Pada Pemilu Legislatif Periode 2014-2019
Authors: Widiastuti Wiwi , Yuliawati Fitriyani 
Published: January 2024

Penelitian ini Menarik untuk diteliti melihat data jumlah anggota Legislatif di Kota Banjar yang berbanding 1:25 antara anggota legislatif perempuan dan anggota legislatif laki-laki. data tersebut menunjukkan bahwa tingkat partisipasi pemilih yang memilih anggota dewan perempuan sangat rendah sehingga ada indikasi terjadi resistensi terhadap anggota dewan perempuan. indikasi ini kami khususkan pada pemilih perempuan karena perempuan dengan jumlah 70.998 jiwa atau lebih dari setengan pemilih yang terdaftar tidak menghasilkan anggota dewan perempuanÂ yang memenuhi kuota 30% Keterwakilan Perempuan. penelitian ini menggunakan teori Resistensi Keterwakilan Perempuan dan Teori Perwakilan Politik, Lembaga Politik dan Kuota 30%. penelitian ini menggunakan metodologi survey dengan metode Slovin dalam pemilihan Sampel. Hasil penelitian ini membuktikan bahwa terjadi resistensi pada pemilih perempuan karena dari jumlah total pemilih perempuan yang berhasil di wawancarai membuktikan bahwa 86% pemilih perempuan yang datang ke TPS memilih calon legislatif perempuan tetapi yang benar-benar berencana memilih hanya 6% saja. meskipun 40% dari total pemilih perempuan memilih calon legislatif ternyata suara tersebut tersebar di lebih dari 70 calon tetap legislatif perempuan. faktanya 34% yang memilih calon perempuan di legislatif memilih secara acak karena berharap akan membawa perubahan sehingga memang tidak paham secara jelas visi misi calon karena kurangnya sosialisasi calon sebelum pemilihan umum legislatif.Â Kata Kunci: Resistensi Pemilih Perempuan, Caleg Perempuan
Capacity and Adequacy: Explicating Voting Behavior in A Multilevel and Concurrent Local Election
Authors: Sobari Wawan 
Published: January 2024

This qualitative case study explores voting behavior in a multilevel (municipality and province) and concurrent local election in the Municipality of Malang. Previous researches on concurrent local election in Indonesia revealed a number of relevant factors elucidating votersâ€™ choices, namely vote-buying (Fossati et al., 2016), social identity (Kristianus, 2016), intensity of meeting with candidates (Ramadhany, 2017), and the blater character of incumbent (friendly and close to commoners) (Sobari, 2018).Â The study extends previous findings through exposure to voting behavior that the capacity to vote and the adequacy of information about candidates are two converging factors explaining similarities and differences in the considerations for voting. The capacity demonstrates ability in making electoral decision, mainly referring to rational choice arguments. It is supported by the adequacy of information about the profile of candidates for mayors and governors along with their proposed vision, missions and programs. On the contrary, the lack of knowledge about candidates' profiles and their platforms contribute to the emergence of trivial voters who simply exercised their voting rights (alakadarnya) or without adequate consideration, especially in selecting candidates for governor. Furthermore, this research echoes Mondak and Huckfeldtâ€™s study (2006) that information about candidateâ€™s integrity is a rational argument for electoral decision, especially in the 2018 Local Election of Malang.Â Key words: local election, multilevel and concurrent, integrity, malang, indonesia.