bluuebunny/crossref_metadata_2025_split huggingface dataset:
A twelve-country population-based psychometric validation study of the Arabic version of the Social Pain Questionnaire (SPQ)
Authors: Fekih-Romdhane Feten , Alhuwailah Amthal , Sakr Fouad , Chaibi Leila Sarra , Helmy Mai , Shuwiekh Hanaa Ahmed Mohamed , Boudouda Nedjem Eddine , Zarrouq Btissame , Naser Abdallah Y , Jebreen Kamel , Roubi Mohammed Lakhdar , Hassan Bassam Abdul Rasool , Merdad Nisma , Amin Rizwana , Nawajah Inad , Mohammed Ali Haider , Farhan Sinan Subhi , AlAni Omar Abdulwahid , Cheour Majda , Dabbous Mariam , Malaeb Diana , Obeid Sahar , Hallit Souheil 
Published: June 2024

Abstract

Background: To our knowledge, there is currently no valid instrument available in the Arabic language to measure the social pain construct. In addition, we could find no previous studies that evaluated social pain in Arabic-speaking individuals of Arab origin. This is a clear gap, especially given the evidence that emotional responses to social rejection vary across cultures. The present study aims to examine the psychometric properties of an Arabic translation of the Social Pain Questionnaire (SPQ) in Arabic-speaking adults from the general population of different Arab countries.
Methods: A cross-sectional web-based study was carried-out from February to April 2024 in 12 Arab countries: Algeria, Bahrain, Egypt, Iraq, Jordan, Kingdom of Saudi Arabia, Kuwait, Lebanon, Morocco, Oman, Palestine, Tunisia. A total of 8408 adults from the general population filled the survey, with a mean age of 24.70 ± 8.44 years and 74.5% females.
Results: Our findings showed that all 10 items of the Arabic version loaded on one factor and provided a good fit to the data in the present sample. Both the Cronbach's alpha and McDonald’s Omega were greater than 0.9, indicating excellent internal reliability. Multi-level CFA showed that the Arabic version of the SPQ was invariant between adult sex-groups and across countries. Convergent and divergent validity of the scale were evidenced through significant positive correlations between social pain and measures of anxiety, depression, and psychotic experiences severity. In addition, SPQ scores negatively correlated with self-esteem levels.
Conclusion: The Arabic translated version of the SPQ was found to be valid, reliable and suitable for use among Arabic-speaking adults from the general population. The Arabic validated SPQ may help shed light on social pain as an important emotional experience that can “hurt” and have serious health effects just as much as physical pain.
Impact Analysis of Natural Herb on Streptozotocin-Induced Diabetic Rats using Machine Learning Method
Authors: Ray Paramita , Susmita  
Published: June 2024

Abstract

Diabetes mellitus (DM) is a chronic metabolic disorder affecting millions globally. Effective management of DM is crucial to mitigate its complications. Natural herbs, including turmeric (Curcuma longa), aloe vera, and basil (Ocimum basilicum), are known for their medicinal properties and have been explored for their potential benefits in diabetes management. Objective of the paper is to evaluate the impact of the herbal treatment on Fasting Blood Glucose (FBG), Urea, Creatinine levels and Blood Urea Nitrogen (BUN) levels and employ machine learning models to predict and analyze the effectiveness of different doses of the herbal treatment. In this study, we divided our work into two phases. Firstly, we performed the experiment with adult Wistar albino rats and rats were made diabetic through intraperitoneal injection of freshly prepared streptozotocin (STZ). The diabetic rats were split into an untreated control group and treated test groups. The treated groups received varying doses of an aqueous solution of natural herbs (turmeric, aloe vera, and basil) administered orally through gavage for 21 days. In second phase, experimental data were collected and analyzed to detect the impact of natural herbs on diabetic rats. The paper proposes an algorithm that integrates the Bayesian Structural Time Series (BSTS) model with the Dynamic Time Warping (DTW) method. The Bayesian Structural Time Series (BSTS) model has been used as a baseline to determine the impact of natural herbs on specific health metrics such as Fasting Blood Glucose (FBG), Urea, Creatinine, and Blood Urea Nitrogen (BUN) levels. The DTW algorithm has been used in conjunction with the BSTS model to enhance performance. This combination of BSTS and DTW aims to provide a more comprehensive analysis of the effects of natural herbs on the health metrics of diabetic rats, highlighting the potential therapeutic benefits of these herbs in managing diabetes. Significant reduction (p=0.001) in FBG levels, Urea, Creatinine and BUN levels indicates the potential of this herbal combination in managing blood sugar levels. These findings suggest that the combined herbal preparation has a beneficial effect on the treatment of diabetes mellitus.
Hydromorphological shifts in the Yamuna River: Post-barrage impacts and water management implications
Authors: Mohanty Maithili , Tare Vinod 
Published: June 2024

ABSTRACT
The study analyzes the hydromorphological impacts of barrage construction and operation on the Yamuna River over 25 years, employing the River Flow Health Index (RFHI). The RFHI methodology includes segregating flow data into different periods, identifying key parameters, assessing flow alterations, and developing an index from 0 to 1. Results indicate moderate alterations in the flow regime, with RFHI of 0.379 and 0.328 for different periods. Geomorphological analysis revealed variations in river sinuosity, peaking at 1.232 in 1999 before reducing to 1.206 by 2018, and braid-channel ratio decreasing from 1.864 in 1999 to 1.508 in 2018. Channel width narrowed in 1999 to 0.082 km and slightly expanded to 0.093 km by 2018. The channel area reduced from 6.418 km² in 1993 to 5.632 km² in 2018, with the bar area significantly decreasing and bar density dropping from 3.28 to 0.83, indicating changes in the channel belt. Construction phases showed increased fluvial bars and channel multiplicity and decreased channel area and width. Post-Hathnikund barrage, withdrawals during lean seasons left the channel dry, as seen in 2003, 2008, and 2013. These findings emphasize integrated river basin management to harmonize development with ecological impacts.
Full-length 16S rRNA gene sequencing reveals the operating mode and chlorination-aggravated SWRO biofouling at a nuclear power plant
Authors: Ren Kaijia , Ming Hongxia , Liu Siyu , Lang Xianlong , Jin Yuan , Fan Jingfeng 
Published: June 2024

ABSTRACT

Reverse osmosis (RO) membrane fouling and biological contamination problems faced by seawater desalination systems are microbiologically related. We used full-length 16S rRNA gene sequencing to assess the bacterial community structure and chlorine-resistant bacteria (CRB) associated with biofilm growth in different treatment processes under the winter mode of a chlorinated seawater desalination system in China. At the outset of the winter mode, certain CRB, such as Acinetobacter, Pseudomonas, and Bacillus held sway over the bacterial community structure, playing a pivotal role in biofouling. At the mode's end, Deinococcus and Paracoccus predominated, with Pseudomonas and Roseovarius following suit, while certain CRB genera still maintained their dominance. RO and chlorination are pivotal factors in shaping the bacterial community structure and diversity, and increases in total heterotrophic bacterial counts and community diversity in safety filters may adversely affect the effectiveness of subsequent RO systems. Besides, the bacterial diversity and culturable biomass in the water produced by the RO system remain high, and some conditionally pathogenic CRBs pose a certain microbial risk as a source of drinking water. Targeted removal of these CRBs will be an important area of research for advancing control over membrane clogging and ensuring water quality safety in the future.
Purification of acidic wastewater containing Cd(II) using a red mud–loess mixture: Column test, breakthrough curve, and speciation of Cd
Authors: Lu Yisi , Liu Xiaofeng , Zhang Hao , Li Jiashi 
Published: June 2024

ABSTRACT

In this study, the safety of a red mud–loess mixture (RM–L) for the remediation of groundwater polluted by acid mine drainage (AMD) containing Cd(II) in mining areas was systematically analyzed and clarified. The effects of the initial concentration, flow rate, and packing height on the breakthrough performance and longevity of RM–L as a permeable reactive barrier (PRB) packing material were explored by column tests. The results show that the breakthrough time, saturation time, and adsorption capacity of Cd(II) in RM–L increased with decreasing initial concentration and flow rate, as well as increasing packing height. Moreover, RM–L had a long-term effective acid buffering capacity for acidic wastewater containing Cd(II). An increase in the packing height led to a longer longevity of the PRB than the theoretical value. In addition, the speciation of Cd on RM–L was dominated by carbonate form and iron–manganese oxide form. The surface of the RM–L particles evolved from a dense lamellar structure to small globular clusters after purifying the acidic wastewater containing Cd(II), due to the corrosion of H+ and the reoccupation and coverage by increasingly enriched adsorbates and precipitates of heavy metal ions.
Methicillin-Resistant Staphylococcus aureus Infection and its Health
Perspective: A Review
Authors: Thomas Abisha , Palathoti Nagarjuna , Azam Mohammed Afzal 
Published: June 2024

Background::
Methicillin-resistant Staphylococcus aureus (MRSA) is a potential
threat globally since it is associated with high morbidity and mortality. In addition, the ability of
MRSA to develop resistance and adapt to various environments makes it exceptional from other
bacterial strains. Effective management is best determined by the site of infection.

Objectives::
This study aims to summarize and assess the epidemiology of MRSA, resistance,
detection of MRSA in humans, animals, and food products, treatment employed, and combination
therapy.

Methods::
For the present review, we collected data from PubMed, Embase, Web of Science,
BioMed Central, Medline, Encyclopedia of Life Sciences, Scopus, Cochrane Library, and ScienceDirect
that report the epidemiology of MRSA, drug resistance in MRSA, spread of MRSA
infection, diagnosis of infection, existing and emerging remedies of MRSA infections. Collected
data were analyzed and represented in this article with the help of Figures and Tables.

Results::
S. aureus resistance to vancomycin is because of genetic adaptation and also due to the widespread and indiscriminate use of antibiotics in the treatment of MRSA infection. Specifically, infections related to vancomycin-resistant S. aureus are life-threatening and difficult to treat. MRSA epidemiology with the recognition of community-acquired-MRSA transmission between livestock and humans is also reported and is alarming. Multiple studies suggested that early detection of MRSA colonization and elimination of carriage can help reduce the risk of subsequent infection. Specifically, PCR-based screening from different body sites offers the highest overall sensitivity for the detection of MRSA carriage.

Conclusion::
Screening novel mutants and methods of transmission in each environment will
assist in managing MRSA. Further, effective MRSA control in all clinical setups is required with
the avoidance of uncontrolled antibiotic usage.
Emerging Insights into the PI3K/AKT/mTOR Signaling Pathway and Non-Coding RNA-mediated Drug Resistance in Glioblastoma
Authors: Afrashteh Mina , Rahmati-yamchi Mohammad , Shimia Mohammad , Yousefi Bahman , Majidinia Maryam 
Published: June 2024

Abstract:
Glioblastoma multiforme [GBM] is a highly aggressive grade IV central
nervous system tumor with a dismal prognosis. Factors such as late detection,
treatment limitations due to its aggressive nature, and, notably, drug resistance
significantly affect clinical outcomes. Despite the effectiveness of Temozolomide
[TMZ], a potent chemotherapy agent, the development of drug resistance remains a
major challenge. Given the poor survival rates and chemoresistance, there is an
urgent need for novel treatment strategies. Non-coding RNAs, particularly microRNAs
[miRNAs], offer a promising approach to GBM diagnosis and treatment. These small
non-coding RNAs play crucial roles in tumor progression, either suppressing or
promoting oncogenic characteristics. The phosphoinositide-3 kinase [PI3K]/AKT/
mTOR pathway, which regulates essential biological processes like proliferation and
survival, is a key target of miRNAs in cancer. Studies have underscored the
significance of PI3K/AKT/mTOR signaling in drug resistance development and its
interplay with non-coding RNAs as mediators of tumorigenesis. This review aims to
outline the involvement of PI3K/AKT/mTOR signaling in miRNA modulation and
strategies to overcome chemoresistance in GBM.
A Comprehensive Review on Deep Learning Techniques in Alzheimer’s Disease Diagnosis
Authors: Mahavar Anjali , Patel Atul , Patel Ashish 
Published: June 2024

:
Alzheimer's Disease (AD) is a serious neurological illness that causes memory loss gradually
by destroying brain cells. This deadly brain illness primarily strikes the elderly, impairing
their cognitive and bodily abilities until brain shrinkage occurs. Modern techniques are required
for an accurate diagnosis of AD. Machine learning has gained attraction in the medical field as a
means of determining a person's risk of developing AD in its early stages. One of the most advanced
soft computing neural network-based Deep Learning (DL) methodologies has garnered significant
interest among researchers in automating early-stage AD diagnosis. Hence, a comprehensive
review is necessary to gain insights into DL techniques for the advancement of more effective
methods for diagnosing AD.

:
This review explores multiple biomarkers associated with Alzheimer's Disease (AD) and various
DL methodologies, including Deep Neural Networks (DNN), Convolutional Neural Networks
(CNN), Recurrent Neural Networks (RNN), The k-nearest-neighbor (k-NN), Deep Boltzmann
Machines (DBM), and Deep Belief Networks (DBN), which have been employed for automating
the early diagnosis of AD. Moreover, the unique contributions of this review include the classification
of ATN biomarkers for Alzheimer's Disease (AD), systemic description of diverse DL algorithms
for early AD assessment, along with a discussion of widely utilized online datasets such as
ADNI, OASIS, etc. Additionally, this review provides perspectives on future trends derived from
critical evaluation of each variant of DL techniques across different modalities, dataset sources,
AUC values, and accuracies.
Pediatric Surgical Outcomes of Persistent Fetal Vasculature: A Five-Year Retrospective Study at a Tertiary Eye Center in Kazakhstan
Authors: Orazbekov Lukpan , Sadyk Aida , Ruslanuly Kairat 
Published: June 2024

Objective
To present the surgical outcomes of Persistent Fetal Vasculature (PFV) in a pediatric cohort over five years at the main referral tertiary eye care center in Kazakhstan.

Methods
A retrospective analysis was performed on the medical records of 23 pediatric patients (24 eyes) under 18 years old who were treated for PFV at the Kazakh Eye Research Institute between 2017 and 2021. Clinical presentations of PFV, types of surgery performed, and postoperative functional outcomes were analyzed.

Results
The average age at the time of surgery was 4.49 ± 4.24 years, ranging from 5 months to 16 years, with 39.1% boys and 60.9% girls. The anterior, posterior, and mixed forms of PFV were observed in 12.5%, 4.2%, and 83.3% of cases, respectively. PFV was most commonly accompanied by cataracts (95.8%), followed by strabismus (33.3%), microphthalmia (25%), and both nystagmus and microcornea (16.7% each). There was a significant overall improvement in visual acuity, from 2.24 ± 0.26 to 1.11 ± 0.66 logMAR (p < 0.001).

Conclusion
The findings of this study confirm that timely surgery leads to improved anatomical and functional outcomes in PFV, influenced by a range of factors, both evident and less apparent.
Potential Herbal Therapy in Dermatology: A Review of Malaysian Medicinal Plants
Authors: Zulkepli Nuraina Izzati , Osman Nurul Izzati 
Published: June 2024

:
Dermatology is a medical aspect that revolves around the diseases of the skin. The incorporation
of medicinal plants in the treatment of skin diseases has been widely used since ancient
days. Malaysia is blessed with various plant species and rich biodiversity with tropical weather yearround.
With the emerging use of medicinal plants in dermatology, more studies on their potential
therapeutic effects need to be reviewed thoroughly. Thus, the purpose of this work is to critically
review relevant publications on related pharmacological activities and potential use of Malaysian
plants for dermatological purposes. The articles that were found related to the research field were
retrieved from several online databases like PubMed, Google Scholar, Scopus, Hindawi, and
ScienceDirect published from 2016 to 2022. The pharmacological activities that were commonly
associated with the treatment of skin diseases include anti-inflammatory, antioxidant, antibacterial,
and wound healing. Various phytochemical compounds such as flavonoids, alkaloids, phenols,
tannins, and vitamins were found to contribute to the therapeutic potential of plant extracts against
skin diseases. In conclusion, the understanding of the plant’s pharmacological activities is important
to evaluate its therapeutic potential to be used against specific skin diseases. More reliable references
are required to ensure safety and efficacy of medicinal plants in dermatology.
A Clustering Analysis of Lebanese Adaptive Driving Behaviors in Response to Road Complexity
Authors: Kobeissy Farah , Faddoul Rafic , Carnis Laurent , Raphael Wassim 
Published: June 2024

Aims
This study aims to investigate adaptive driving behaviors in response to road complexity in Lebanon, emphasizing how multifaceted factors influence these adaptations.

Background
Lebanon faces major road safety challenges due to its deteriorating infrastructure and diverse socio-economic conditions. Addressing these issues, the research examines the interaction between infrastructure, vehicle conditions, and road user adaptation, with the objective of informing more effective safety strategies.

Objective
This study aimsto explore adaptive driving behaviors among Lebanese drivers across different environmental complexities and the influence of demographic and socio-economic factors on these behaviors.

Methods
Through a comprehensive survey among a representative sample, drivers were segmented into three clusters using the K-Prototypes algorithm to assess self-reported driving speeds, the impact of road elements on behavior, and the role of various factors on driving patterns.

Results
The Clustering analysis identified three distinct groups, each exhibiting unique adaptive driving behaviors: Cluster 1 consists of mature, conservative drivers; Cluster 2 includes predominantly young, cautious female drivers; and Cluster 3 comprises younger male drivers with riskier behaviors. These findings illustrate significant behavioral variations and highlight the influence of demographic profiles on driving behavior.

Conclusion
The research underscores the necessity of a nuanced road safety strategy that acknowledges the diverse adaptive behaviors of Lebanese drivers It recommends specific policy adjustments, such as differentiated speed limits and targeted educational programs, to cater to the distinct needs of each driver cluster. Further research is suggested to continuously refine and customize road safety measures, accommodating the complex driving environment in Lebanon.
Enhanced Oral Bioavailability and Stability Studies of Loratadine Tablets Based on Solid Dispersion of Modified Ziziphus spina-christi Gum
Authors: Alwossabi Ameen M. , Elamin Eltayeb S. , Ahmed Elhadi M.M. , Ismail Eman A. , Ashour Ahmed , Osman Wadah , Sherif Asmaa E. , Mira Amira , Bafail Rawan , Andijani Yusra Saleh , Ibrahim Sabrin R.M. , Mohamed Gamal A. , Abdelrahman Mohammed 
Published: June 2024

Background:
Solid dispersion is a common technique used for solubility enhancement of
poorly soluble drugs.

Objective:
In this study, loratadine (LOR), a class II biopharmaceutical classification system (BCS),
was formulated as solid dispersion tablets using modified Ziziphus spina-christi gum (MZG) as a
carrier.

Methods:
The solvent evaporation method was used for LOR-MZG solid dispersion (SD) preparation.
A variety of tests were conducted to characterize and optimize the formulation. Solubility,
Fourier transform infrared (FTIR) analysis, Differential Scanning Calorimetry (DSC), X-Ray Diffraction
(X-RD), and Scanning Electron Micrograph (SEM) of solid dispersions were carried out.
Accelerated stability testing and pharmacokinetic studies of formulated tablets were also performed
using albino Wistar rats.

Results:
Solid dispersion improved the solubility of LOR by 51 folds. FTIR spectra excluded drugpolymer
interactions, and results obtained by DSC, X-RD, and SEM proved the transition from the
crystalline to the amorphous state. The stability of LOR-MZG solid dispersion tablets was found to
be better when the Alu-Alu package was used. The pharmacokinetics of LOR-MZG compared to
MZG-free loratadine tablets (LOR pure) and commercial loratadine tablets (LOR-TM) following
oral administration revealed that about 6 folds and 10 folds bioavailability were achieved with
LOR-MZG compared to LOR pure and LOR-TM, respectively.

Conclusion:
Such promising results encourage more studies on MZG to be used for improving the
aqueous solubility and bioavailability of a wide range of poorly soluble drugs.
Multi-target Phenylpropanoids Against Epilepsy
Authors: Rodrigues Teresa Carolliny Moreira Lustoza , Dias Arthur Lins , dos Santos Aline Matilde Ferreira , Monteiro Alex France Messias , Oliveira Mayara Cecile Nascimento , Pires Hugo Fernandes Oliveira , de Sousa Natália Ferreira , da Silva Stiebbe Salvadori Mirian Graciela , Scotti Marcus Tullius , Scotti Luciana 
Published: June 2024

:
Epilepsy is a neurological disease with no defined cause, characterized by recurrent epilep-
tic seizures. These occur due to the dysregulation of excitatory and inhibitory neurotransmitters in the
central nervous system (CNS). Psychopharmaceuticals have undesirable side effects; many patients
require more than one pharmacotherapy to control crises. With this in mind, this work emphasizes the
discovery of new substances from natural products that can combat epileptic seizures. Using in silico
techniques, this review aims to evaluate the antiepileptic and multi-target activity of phenylpropanoid
derivatives. Initially, ligand-based virtual screening models (LBVS) were performed with 468 phe-
nylpropanoid compounds to predict biological activities. The LBVS were developed for the targets al-
pha-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA), voltage-gated calcium channel T-
type (CaV), gamma-aminobutyric acid A (GABAA), gamma-aminobutyric acid transporter type 1
(GAT-1), voltage-gated potassium channel of the Q family (KCNQ), voltage-gated sodium channel
(NaV), and N-methyl D-aspartate (NMDA). The compounds that had good results in the LBVS were
analyzed for the absorption, distribution, metabolism, excretion, and toxicity (ADMET) parameters,
and later, the best molecules were evaluated in the molecular docking consensus. The TR430 com-
pound showed the best results in pharmacokinetic parameters; its oral absorption was 99.03%, it did
not violate any Lipinski rule, it showed good bioavailability, and no cytotoxicity was observed either
from the molecule or from the metabolites in the evaluated parameters. TR430 was able to bind with
GABAA (activation) and AMPA (inhibition) targets and demonstrated good binding energy and sig-
nificant interactions with both targets. The studied compound showed to be a promising molecule with
a possible multi-target activity in both fundamental pharmacological targets for the treatment of epi-
lepsy.