bluuebunny/crossref_metadata_2025 huggingface dataset:
İngiltere'de Özel Eğitim İhtiyacı Olan Türk Öğrencilerin Kaynaştırma Eğitimine İlişkin Ebeveyn Deneyimlerinin İncelenmesi
Authors: İnce Çakan Tansu
Published: May 2024

Bu nitel çalışma, İngiltere’de kaynaştırma sınıflarında eğitim gören özel eğitim gereksinimi (ÖEG) olan Türk öğrencilerin ebeveynlerinin deneyimlerini araştırmaktadır. Kaynaştırma eğitimine yönelik artan ilgiye rağmen, farklı ülkelerden gelen ebeveynlerin bu tür eğitimin etkililiği ve kalitesine ilişkin bakış açıları sınırlı ilgi görmüştür. Bu çalışma, kaynaştırma programların planlanması ve uygulanmasında farklı ülkelerden gelen ebeveynlerin deneyim ve algılarının dikkate alınmasının önemini vurgulamaktadır, çünkü onların bakış açıları kültürel olarak duyarlı kaynaştırma eğitiminin geliştirilmesine katkıda bulunmaktadır. Dört Türk ebeveyn, yarı yapılandırılmış görüşmelere katılmış ve çocuklarının İngiltere’de aldığı kaynaştırma eğitimiyle ilgili deneyimleri doğrultusunda beş tema ortaya çıkmıştır. Bulgular, İngiltere'de kaynaştırma eğitimiyle ilgili çeşitli deneyimlere işaret etmekte ve mevcut literatürdeki bazı bulguları doğrulamaktadır. Çalışma, İngiltere'de yaşamanın özel gereksinimli çocukların kaynaştırma eğitimi üzerinde hem olumlu hem de zorlayıcı etkileri olduğunu ve Türk ve İngiliz eğitim sistemleri arasındaki farklılıkların bazı zorluklar ortaya çıkardığını göstermektedir. Ayrıca, katılımcılar tarafından bildirildiği üzere, farklı etnik kökenlerden gelen bireylere yönelik profesyonellerin görüşleri İngiltere’de yaşayan Türk ebeveynlerin deneyimlerini etkilemiştir. Hepsi beraber ele alındığında, bu sonuçlar kapsayıcı eğitimde daha iyi uygulamaları teşvik etmek için faydalı hususları ortaya koymaktadır.
Advances of Oxidative Stress Impact in Periodontitis: Biomarkers and Effective Targeting Options
Authors: Pouliou Chrysi , Piperi Christina
Published: May 2024

:

Periodontitis is the most common inflammatory oral disease that affects
around 15% of adults and contributes to severe periodontal tissue destruction with subsequent
tooth loosening and loss. Among the main pathogenic mechanisms underlying periodontitis,
excessive reactive oxygen species production and oxidative stress play a predominant
role in inducing both local and systemic damage. Current therapeutic approaches
have expanded the conventional methods combined with herbal antioxidant
compounds to free radical-scavenging nanomaterials and infrared laser therapy, offering
promising pre-clinical evidence in periodontitis management. Herein, we review the
pathogenic mechanisms of reactive oxygen species tissue damage, along with recent advances
in oxidative stress biomarkers and novel targeting options.
Polyphyllin I Mitigated IL-1β-Induced Chondrocytes Damage through Downregulating TWIST1 Expression
Authors: Liu Feng , Han Bowen , Yang Deshun , Ji Xiaopeng , Yan Liangliang , Han Chaoyong
Published: May 2024

Background:

Osteoarthritis (OA) is a chronic joint disease characterized by
the degradation of articular cartilage. Polyphyllin I (PPI) has anti-inflammatory effects
in many diseases. However, the mechanism of PPI in OA remains unclear.

Methods:

HC-a cells treated with IL-1β were identified by immunofluorescence
staining and microscopic observation. The expression of collagen II and DAPI in HC-a
cells was detected by immunofluorescence. The effects of gradient concentration of
PPI on IL-1β-induced cell viability, apoptosis, senescence, and inflammatory factor
release were detected by MTT, flow cytometry, SA-β-Gal assay and ELISA,
respectively. Expressions of apoptosis-related genes, extracellular matrix (ECM)-
related genes, and TWIST1 were determined by qRT-PCR and western blot as
needed. The above-mentioned experiments were conducted again after TWIST1
overexpression in IL-1β-induced chondrocytes.

Results:

IL-1β reduced the number of chondrocytes and the density of collagen II. PPI
(0.25, 0.5, 1 μmol/L) had no effect on cell viability, but it dose-dependently elevated the
inhibition of cell viability regulated by IL-1β. The elevation of cell apoptosis,
senescence and expression of IL-6 and TNF-α were suppressed by PPI in a dosedependent
manner. Additionally, PPI reduced the expression of cleaved caspase-3,
bax, MMP-3, and MMP-13 and promoted the expression of collagen II. TWIST1
expression was diminished by PPI. TWIST1 overexpression reversed the abovementioned
effects of PPI on chondrocytes.

Conclusion:

PPI suppressed apoptosis, senescence, inflammation, and ECM
degradation of OA chondrocytes by downregulating the expression of TWIST1.
PPARs (Peroxisome Proliferator-activated Receptors) and Their Agonists in Alzheimer's Disease
Authors: Kumar Mohit , Sharma Anita Ashok , Datusalia Ashok Kumar , Khatik Gopal L.
Published: May 2024

:

Alzheimer's disease (AD) is a neurodegenerative disease leading to dementia because of
complex phathomechanisms like amyloid β (Aβ) aggregation, tau aggregates, and neurofibrillary
tangles. Peroxisome proliferator-activated receptor (PPAR) agonists have been reported recently
with neuroprotective and anti-inflammatory properties. PPARs belong to the superfamily of nuclear
hormone receptors and function as ligand-activated transcription factors. These have emerged as
crucial players in the pathogenesis of AD. This review presented the potential of PPARs and their
agonists in treating neurodegenerative diseases like AD.

:

PPARs regulate the expression of specific genes vital for synaptic function and neurotransmitter
release. PPAR agonists play a critical role in increasing the clearance of Aβ peptides by lowdensity
lipoprotein receptor-related protein 1 (LRP1) in the microvascular endothelial cells of the
human brain. Studies have shown that PPAR agonists reduce the level of APoE-mRNA, contributing
to the accumulation of Aβ plaques and up-regulation of PPAR. A knockout of miR-128 has
been found to inhibit AD-like cognitive decline, amyloid precursor protein (APP) amyloidogenic
processing, and inflammatory responses in AD.

:

PPARs are involved in the pathomechanism of AD, and therefore, PPAR agonists could be viable
options for controlling the neurodegenerative symptoms and may be useful in treating AD.
Stem Cell Markers in Neoplasms and their Relationship with Progression-free and Overall Survival in Patients with Recurrence
Authors: Eguiluz-Melendez Aldo , Rubio-Osornio Carmen , Rosiles-Abonce Artemio , Mendoza Cesar , Ramírez-Ordás Miryam , Rivera-Cañas Romina , Tena-Suck Martha , Gómez-Amador Juan Luis , Moreno-Jimenez Sergio
Published: May 2024

Background:

Gliomas account for 30% of primary brain tumors in adults, and despite
the scientific progress in the field, recurrence is prevalent. Glioma Stem Cells (GSCs) can generate
tumor cells in vivo and in vitro and they are associated with treatment resistance, tumor progression,
and recurrence. Furthermore, the expression of SOX transcription factors (SOX1, SOX2,
SOX9) in these cells is responsible for maintaining an oncogenic genotype and is associated with
an aggressive tumor phenotype. The relationship between SOX transcription factors and their prognostic
role in recurrent gliomas has not been described in detail. Therefore, we set out to describe
the relationship between SOX expression and Progression-free Survival (PFS) and Overall Survival
(OS) in patients with recurrent gliomas.

Methods:

In this observational study, we have retrospectively analyzed 69 patients, of which 20
met the inclusion criteria. The clinical, radiological, and histopathological findings have been described,
and survival analysis has been performed according to SOX expression for PFS and OS.

Results:

We found SOX1, SOX2, and SOX9 to show a non-statistically significant trend with increasing
histopathological grade, co-expressed with Ki67, a cell proliferation factor.

Conclusion:

There has been found an inversely proportional correlation between the degree of immunopositivity
of SOX1 and OS. A higher SOX1 immunopositivity could predict a worse clinical
prognosis. There has also been found an interaction between a pluripotent genotype (GSC) and
cell proliferation.
Smart Multifunctional Nanoparticles in Cancer Theranostics: Progress and Prospect
Authors: Karati Dipanjan , Mukherjee Swarupananda , Dutta Ayon , Ash Dipanjana , Ganguly Shayeri Chatterjee , Acharya Apurbaa , Basu Biswajit
Published: May 2024

Background:

Worldwide, cancer is the second most common cause of death. Chemotherapy
and other traditional cancer treatments have toxicities that affect normal cells in addition to
their intended targets, necessitating the development of novel approaches to enhance cell-specific
targeting.

Methods:

The present work summarizes the scientific information on nanoparticles in cancer
theranostics to provide a comprehensive insight into the preventive and therapeutic potential of nanoparticles
in cancer. Scopus, PubMed, Science Direct, and Google Scholar databases are searched
to collect all the recent (2015-2023) scientific information on smart multifunctional nanoparticles
using the terms nanotechnology, cancer theranostics, and polymer.

Results:

The use of nanomaterials as chemical biology tools in cancer theranostics has been thoroughly
investigated. They demonstrate expanded uses in terms of stability, biocompatibility, and
enhanced cell permeability, enabling precision targeting and ameliorating the drawbacks of conventional
cancer treatments. The nano platform presents a fascinating chance to acquire multifunctionality
and targeting techniques. The production of smart nanomaterials, specifically with regard to
the advent of nanotechnology, has revolutionized the diagnosis and treatment of cancer. The capability
of nanoparticles to functionalize with a variety of biosubstrates, including aptamers, antibodies,
DNA, and RNA, and their broad surface area allow them to encapsulate a huge number of molecules,
contributing to their theranostic effect. Comparatively speaking, economical, easily produced,
and less toxic nanomaterials formed from biological sources are thought to have benefits
over those made using conventional processes.

Conclusion:

The present study highlights the uses of several nanoparticles (NPs), and describes
numerous cancer theranostics methodologies. The benefits and difficulties preventing their adoption
in cancer treatment and diagnostic applications are also critically reviewed. The use of smart nanomaterials,
according to this review's findings, can considerably advance cancer theranostics and
open up new avenues for tumor detection and treatment.
A Comparative Analysis of Machine Learning Models for the Classification of Heart Failure Patients in the Intensive Care Unit
Authors: Gaudin Mateo , Kaur Swapandeep , Sharma Preeti , Kumar Rajeev
Published: May 2024

Background:

Heart failure is the leading cause of death globally over the last several
decades. This raises the necessity of timely, accurate, and prudent methods for establishing an
early diagnosis and implementing timely illness care.

Objective:

This study aims to develop and validate a classification model for the patients admitted
to the Intensive Care Unit (ICU) with heart failure, using various machine learning models applied
to the MIMIC (Medical Information Mart for Intensive Care)-III database.

Method:

A retrospective cohort study was conducted using data extracted from the MIMIC-III
database. Machine learning models: Logistic Regression, K-Nearest Neighbor (KNN), Random
Forest, Decision Tree, Naïve Bayes, AdaBoost, and XGBoost were utilized to construct the predictive
model. The dataset has been preprocessed in two different manners. The study included
1,177 patients with heart failure, selected according to specific inclusion/exclusion criteria and
admitted to the ICU.

Result:

At the end of the study, the most effective model for predicting patients who survived was
Logistic Regression, with an accuracy of 0.9025, sensitivity of 0.9763, precision of 0.9196, and
F1-score of 0.9471.

Conclusion:

Classification of the patients into those who survived or could not survive due to
heart failure was the primary measure, with various clinical and demographic variables used as
predictors.
Impact of Deep Learning on Natural Language Processing
Authors: Singh Arun Kumar , Tripathi Ashish , Saxena Sandeep , Choudhary Pushpa , Singh Mahesh Kumar , Singh Arjun
Published: May 2024

In the era of digitalization, electronic gadgets such as Google Translate, Siri,
and Alexa have at least one characteristic: They are all the products of natural language
processing (NLP). “Natural Language” refers to a human language used for daily
communication, such as English, Hindi, Bengali, etc. Natural languages, as opposed to
artificial languages such as computer languages and mathematical nomenclature, have
evolved as they have been transmitted from generation to generation and are
challenging to explain with clear limits in the first instance. In natural language
processing, artificial intelligence (Singh et al., 2021), linguistics, information
processing, and cognitive science are all related fields (NLP). NLP aims to use
intelligent computer techniques to process human language. However, NLP
technologies such as voice recognition, language comprehension, and machine
translation exist. With such limited obvious exclusions, machine learning algorithms in
NLP sometimes lacked sufficient capacity to consume massive amounts of training
data. In addition, the algorithms, techniques, and infrastructural facilities lack enough
strength. Humans design features in traditional machine learning, and feature engineering is a
limitation that requires significant human expertise. Simultaneously, the accompanying
superficial algorithms lack depiction capability and, as a result, the ability to generate
layers of duplicatable concepts that would naturally separate intricate aspects in
forming visible linguistic data. Deep learning overcomes the challenges mentioned
earlier by using deep, layered modelling architectures, often using neural networks and
the corresponding full-stack learning methods.
Deep learning has recently enhanced natural language processing by using artificial
neural networks based on biological brain systems and Backpropagation. Deep learning
approaches that use several processing layers to develop hierarchy data representations have produced cutting-edge results in various areas. This chapter introduces natural language processing (NLP) as an AI component. The history of NLP is next.
Distributed language representations are the core of NLP's profound learning
revolution. After the survey, the boundaries of deep learning for NLP are investigated.
The paper proposes five NLP scientific fields.
Powering User Interface Design of Tourism Recommendation System with AI and ML
Authors: Shelke P. M. , Dedgaonkar Suruchi , Bhimanpallewar R. N.
Published: May 2024

The term “User Experience” (UX) refers to all elements of a customer's
relationship with a company, including its services, products, and overall customer
experience. Meeting the specific consumer demands and knowing their behavioral
patterns are the most important criteria for an efficient UX.
The backend that selects what to recommend and the frontend that gives the
recommendation are the two essential components of recommendation systems (RS).
An RS's user interface must deliver recommendations in a way that allows users to
anticipate taking action on them. A user interface is required to provide the
recommendations. When creating a recommender's user interface, the designers must
make several decisions. Understandability, transparency, assessability, trust, and
timeliness are five elements that the designer must address.
When it comes to organizing a trip, people are becoming increasingly accustomed to
using modern technology. Users are provided with a large quantity of data, which they
must evaluate in order to choose the offerings that are interesting or appropriate for
them. A customized tourist attractions recommender system is thought to be the most
efficient way for visitors to find tourist attractions. The recommender system compares
the acquired data to comparable and dissimilar data from other sources to provide a list
of recommended tourist sites. These systems, which assist people in finding what they need on the internet, have been
a huge success, and they wouldn't be conceivable without an excellent user interface.
Data can now be easily segmented based on demographics, habits, trends, and a variety
of other factors, thanks to the application of machine learning and AI. The main
concept is to provide each user with better strategic decisions to their preferences based
on their prior travel data and behavior. In this way, every facet of human behavior that
these systems supply and explore is then fed into algorithms, which develop
meaningful patterns. These patterns are then expressed through an interface and then
transformed into useful products and services that help businesses improve their user
experience. Both AI and machine learning are extremely compatible and friendly with UX; they all
follow the same concepts and aims. However, there are many challenges to their
implementation. AI/ML engineers and UX designers should collaborate on a shared
platform to create a blueprint for a fantastic UX experience. The mix of qualitative and
quantitative data is crucial if AI and machine learning connect with UX. There is no
other technology that can improve UX as much as AI.
Insights into Deep Learning and Non-Deep Learning Techniques for Code Clone Detection
Authors: Kunjir Ajinkya
Published: May 2024

A source code clone is a type of bad smell caused by pieces of code that
have the same functional semantics, but the syntactical representation varies. In the
past few years, there have been several studies about code clone detection, steered by
numerous machine learning models, software techniques and other mathematical
measures. This paper aims to conduct an impartial comparative study of the existing
literature on Deep Learning and Non-Deep Learning techniques. Due to the lack of
work in studying the previous and the current state-of-the-art tools in code clone
detection, there is no concrete evidence found to underpin the use of Deep Learning
approaches in clone detection, except for a preference from the evolutionary point of
view. We will address and investigate a few research questions related to the intentions
of using DL techniques for code clone detection compared to those of non-DL
approaches (Based on –token, text, AST, metrics, and others). Furthermore, we will
discuss the challenges faced in the Deep Learning implementation for clone detection
and their potential resolutions if feasible. This review would help the audience
understand how different approaches aid the clone detection process along with their
performance measures, limitations, issues, and challenges.
Role of Artificial Intelligence (AI) in Solid Waste Management: A Synopsis
Authors: Bhattacharjee Pankaj , More Ashok B.
Published: May 2024

Rapid urbanisation and subsequent growth in population have brought about
a worldwide spike in the production of municipal solid waste. Poor management skills
in the collection of waste and the improper allocation of transporting vehicles due to
lack of technology usage, also, insufficient funds and inappropriate management of
human resources have contributed towards making Municipal Solid Waste
Management (MSWM) which is a big challenge nowadays, especially in developing
countries. Scientists and researchers have been working towards developing cuttingedge technology in order to address this issue. Modern Artificial Intelligence (AI)
technologies are being studied for their potential usefulness in the Solid Waste
Management (SWM) industry. Waste management as a whole, including collection,
transportation, and sorting, may benefit substantially from the intelligent use of AI
algorithms. This article provides a brief overview of the way in which Machine
Learning (ML) algorithms are used in MSWM across the whole process, from the
initial creation of waste through its collection, transportation, and ultimate disposal.
Cyber-Physical System: Advances and Applications in Cyber Security
Authors: Rajendran Sindhu , S.P. Shilpa , L. Sai Priya , N. Ramavenkateswaran
Published: May 2024

A cyber-physical system is a computer system that operates or monitors a
mechanism using computer-based algorithms. Due to the rapid evolution of CPS in
today's world, a greater range of services and applications involving e-Health, smart
homes, e-Commerce, and industry automation may be easily realized, affecting
numerous parts of people's lives. Smart grid, autonomous underwater, and UAVs, gas
and oil pipeline monitoring and control, smart factory and manufacturing, pollution
control, and HEVs are among the most prominent applications in this domain.
However, interconnecting the cyber and physical worlds introduces new security
threats. Security attacks can result in trouble to essential infrastructure and business
continuity, including production-performance deterioration, severe commercial risks,
unavailability of critical services, and regulatory violations. Cybersecurity attacks are
one of the most serious dangers to CPS due to the system's complexity and
interdependencies, owing to which risk management is difficult considering recent
attack trends. The first section of the manuscript discusses the evolution of CPS and its
wide range of applications in different areas, followed by in-depth insights into the
industrial sector. Types of cyber and physical threats, as well as examples, various
system components, related algorithms and models, attack characteristics, and defense
measures, are explained. Current study classifications are assessed and summarized
using various system modeling and analytic approaches along with the benefits and
drawbacks of various techniques. The chapter is concluded by stating future research
topics on secure CPS and potential solutions. 4 Cyber-physical systems -Advances and
Applications Rajendran et al.
Journey from Data Warehouse to Data Lake
Authors: Rani Geeta , Kaur Puninder , Sharma Avinash
Published: May 2024

With the increase in high volume, velocity, and variety of data, the
traditional data analysis approaches are not adequate to handle diverse analysis
challenges. Traditionally, a data warehouse is being used which is an integrated
repository from various sources used for management and decision-making in business.
Data is already in a transformed and structured format stored in a costly but reliable
storage device. The data warehouse does not include all the data that may be not
required at the time of construction of the data warehouse. With the advent of big data
and to handle the data silos problem, the concept of Data Lake is introduced to handle
data analysis. Data lakes have not replaced the data warehouse but rather complement
it. In this chapter, firstly Data Lake is introduced and compared with predecessor
technologies, then various tools and techniques are discussed to implement Data Lake.
Rare Earth Glass Spectroscopy and Fiber Lasers
Authors: Walsh B.M.
Published: May 2024

The ability to make new materials is often key to major progress in fundamental physics and numerous applications. This is the focus of our research. Therefore, we have synthesized a novel glass compositions doped with erbium. Glasses based on antimony oxide (Sb2O3) make one of the major classes of heavy metal oxide glasses, which have specific properties such as low phonon energy, a high non-linearity associated with a high refractive index, good mechanical properties, and better stability than that fluoride and tellurite glasses. They present the advantage to be easy to elaborate at a low price compared to single crystals. It is also possible to modulate the optical properties by moderating their chemical composition. We have demonstrated favorable spectroscopic properties in these Er antimonate glasses which compared with Er silica glass. We will present the data, and these glasses are able to accommodate other rare earth ions offering thereby a potential for developing new laser materials.
Prospective Potential Applications and Emerging Tendencies in Rare Earth Materials
Authors: Ramakrishna Reddy R.
Published: May 2024

Rare Earth Elements (REE) remain underappreciated despite their numerous applications. High-temperature superconductors, phosphors (for energy-saving lamps, flat-screen monitors, and flat-screen televisions), rechargeable batteries (home and automotive), magnetic resonance image scanning systems, superconductors, laser technology, and very strong permanent magnets all rely on them (used for instance, in wind turbines and hard-disk drives). The article provides a brief overview of the various applications of REES. Medical imaging and therapy using rare earth doped lasers: potential environmental effects. New methods for isolating specific rare earth elements have been highlighted in applications as diverse as metallurgy and recycling.
Mérnöktanár-képzés – Modellalkotás, szakmai szókincsfejlesztés, tantárgyi kapcsolatok
Authors: Nagyné Kondor Rita
Published: May 2024

Vocational Teacher Training Programmes provide teachers of Vocational Education and Training schools. University of Debrecen Faculty of Engineering offers Vocational Teacher Training in five specializations, in form of cooperative training. The company specialists participating in the training teach prospective vocational teachers with modern professional knowledge. The aim of this article is to summarize the pedagogical experiences of the prospective vocational teachers, based on the content analysis of their lesson plans. The investigation focuses on prospective vocational teachers’ examples of modeling, professional vocabulary development and connections between subjects from their practical pedagogical training in Vocational Education and Training schools.
Multilingual Selves and Motivations for Learning Languages other than English in Asian Contexts
Authors: Manan Syed Abdul
Published: May 2024

This book focuses on individuals learning languages other than English in a range of under-researched Asian contexts. The chapters explore learners’ motivational trajectories, multilingual identities and conceptualisations of the ‘ideal multilingual self’.
Spanish and Catalan Versions of the eHealth Literacy Questionnaire: Translation, Cross-Cultural Adaptation, and Validation Study
Authors: Hernández Encuentra Eulàlia , Robles Noemí , Angulo-Brunet Ariadna , Cullen David , del Arco Ignacio
Published: May 2024

Background

The rise of digital health services, especially following the outbreak of COVID-19, has led to a need for health literacy policies that respond to people’s needs. Spain is a country with a highly developed digital health infrastructure, but there are currently no tools available to measure digital health literacy fully. A well-thought-through questionnaire with strong psychometric properties such as the eHealth Literacy Questionnaire (eHLQ) is important to assess people’s eHealth literacy levels, especially in the context of a fast-growing field such as digital health.

Objective

This study aims to adapt the eHLQ and gather evidence of its psychometric quality in 2 of Spain’s official languages: Spanish and Catalan.

Methods

A systematic cultural adaptation process was followed. Data from Spanish-speaking (n=400) and Catalan-speaking (n=400) people were collected. Confirmatory factor analysis was used to confirm the previously established factor structure. For reliability, the Cronbach α and categorical ω were obtained for every subscale. Evidence of convergent and discriminant validity was provided through the correlation with the total score of the eHealth Literacy Scale. Evidence based on relations to other variables was evaluated by examining extreme values for educational level, socioeconomic level, and use of technology variables.

Results

Regarding the confirmatory factor analysis, the 7-factor correlated model and the 7 one-factor models had adequate goodness-of-fit indexes for both Spanish and Catalan. Moreover, measurement invariance was established between the Spanish and Catalan versions. Reliability estimates were considered adequate as all the scales in both versions had values of >0.80. For convergent and discriminant validity evidence, the eHealth Literacy Scale showed moderate correlation with eHLQ scales in both versions (Spanish: range 0.57-0.76 and P<.001; Catalan: range 0.41-0.64 and P<.001). According to the relationship with external variables, all the eHLQ scales in both languages could discriminate between the maximum and minimum categories in level of education, socioeconomic level, and level of technology use.

Conclusions

The Spanish and Catalan versions of the eHLQ appear to be psychometrically sound questionnaires for assessing digital health literacy. They could both be useful tools in Spain and Catalonia for researchers, policy makers, and health service managers to explore people’s needs, skills, and competencies and provide interesting insights into their interactions and engagement regarding their own experiences with digital health services, especially in the context of digital health growth in Spain.
Research on AEB-P Control Strategy Considering Braking Process Comfort
Authors: Yang Peng , Lu Ying , Chen Ye
Published: May 2024

A control approach for the pedestrian-oriented automobile automatic emergency braking system (AEB-P) that takes driving comfort into account is suggested in an effort to further optimize the AEB-P system's control algorithm. Firstly, for the AEB-P assessment standard of C-NCAP, a braking safety distance model that takes the driver's comfort into account during braking is created. The next step was to construct a hierarchical controller using PID and MPC principles. Lastly, CarSim and Matlab/Simulink are used to build and validate the test scenarios and control methods. The simulation results demonstrate that both ride comfort and driving safety can be guaranteed by the suggested control technique.
Challenges and Solutions for Ride-Hailing Motorbike Drivers in Vietnam: An Analysis of Working Conditions and Health
Authors: Chi Do Thi Lan , Mai Le Thanh , Anh Le Hoang , Anh Do Thi Minh , Dung Pham Thi Thuy
Published: May 2024

In the digital age, ride-hailing motorbike services have become an indispensable part of the urban transportation system in Vietnam, attracting thousands of workers with their flexibility and income potential. However, occupation also poses numerous health and safety challenges. The job requires long working hours, exposure to harsh weather conditions, and highly competitive pressure, leading to physical and mental health issues such as muscle pain, fatigue, and stress. This research article employs a survey method to collect data from ride-hailing motorbike drivers to analyze the labor burdens they endure. Based on the findings, the study suggests solutions such as improving working conditions, developing health support programs, and implementing more flexible policies to enhance the quality of life and job satisfaction among workers, thereby contributing to the sustainable development of the industry in Vietnam.
ACUTE ORAL TOXICITY OF TOFACITINIB CITRATE IN WISTAR RATS: IMPLICATIONS FOR NOVEL MOUTH DISSOLVING FORMULATIONS
Authors: RAYKAR MEGHANA , VELRAJ MALARKODI
Published: May 2024

Objective: Tofacitinib citrate is a commonly used therapeutic agent for various diseases. Mouth-dissolving formulations provide potential benefits for patient compliance. This study aims to evaluate the acute oral toxicity of tofacitinib citrate in these formulations to ensure their safety and efficacy.
Methods: This study aimed to assess the acute oral toxicity of tofacitinib citrate in mouth-dissolving formulations and evaluate its effects on food and water consumption, hematological and biochemical parameters, and organ histopathology. Male and female Wistar rats were divided into four groups. The control group received distilled water, while the treated groups were orally administered tofacitinib citrate at 5 mg/kg, 100 mg/kg, and 300 mg/kg. Observations were made over 14 d, assessing general appearance, behavior, food and water consumption, and mortality. Hematological and biochemical analyses and histopathological examinations were conducted on vital organs.
Results: In acute toxicity studies, Wistar rats showed no toxicity at up to 300 mg/kg tofacitinib citrate. Compared to controls, food/water intake and hematological, biochemical, and histopathological parameters of major organs remained unchanged, indicating no systemic effects and affirming the compound's safety in mouth-dissolving formulations.
Conclusion: Tofacitinib citrate in mouth-dissolving formulations demonstrated a favorable safety profile with no acute oral toxicity. Normal consumption, unchanged parameters, and no organ abnormalities support its safety. Further investigation is required to assess chronic toxicity and long-term safety.
EFFECT OF POLYMER CONCENTRATION AND SURFACTANTS ON PHYSICAL CHARACTERISTICS, DRUG RELEASE AND ANTIOXIDANT ACTIVITY OF GLUTATHIONE-KAPPA CARRAGEENAN NANOSPHERES
Authors: NAILUFA YUYUN , WIDJAJA BAMBANG
Published: May 2024

Objective: Glutathione is one of the antioxidants widely used as an antiaging and skin lightener. Glutathione at a dose of 250 mg/d orally proved useful as an antiaging. At the same time, glutathione topical night cream is effective at a dose of 0.1% for the skin of Indonesian women. Glutathione is one of the antioxidants that has easily oxidized properties in storage. Research purpose to optimize the concentration of kappa carrageenan polymer and surfactan to obtain the optimal physical characteristics of nanosphere system analyzed based on size, PDI, yield, drug loading, entrapment efficiency, dissolution and antioxidant activity.
Methods: The most commonly used method of making nanospheres is ionotropic gelation because it has proven effective, easy, and easy to apply. Ionotropic gelation is depend on the tendency of polyelectrolytes to cross connect to develop hydrogel beads often called gelispheres in the existence of counter ions. Nanospheres were prepared by aerosolization ionotropic gelation technique followed by freeze-drying. This method uses carrageenan polymers of 0.5% and 1.0% with the addition of surfactant as a stabilizer. Evaluation parameters are particle size, entrapment efficiency, drug loading, drug release and antioxidant activity.
Results: The results of the nanospheres obtained were tested physically and drug activity. Nanospheres successfully formed, with size 382.67±52.24 nm, F2 325.20±4.62 nm, F3 495.39±30.61 nm, and F4 409.80±4.11 nm. The greater the polymer concentration, the greater the value of entrapment efficiency and drug content in the nanosphere. The morphology of the nanosphere is quite good, spherical, with a smooth surface. The release profile shows that glutathione release is quite good but takes a long time, namely F1 73.91±2.17%, F2 75.91±2.76%, F3 78.56±2.82%, and F4 79.56±1.34% in 480 min or 8 h. Antioxidant activity of glutathione-Kappa carrageenan nanospheres with the DPPH method showed that nanospheres have medium or medium category antioxidant activity.
Conclusion: The most optimal formula is F4 with 1% kappa-carrageenan concentration and 0.6% KCl.
DESIGN AND OPTIMIZATION OF ESCITALOPRAM OXALATE ORAL DISSOLVING FILMS BY RESPONSE SURFACE METHODOLOGY
Authors: BABU CHENNUPATI VENU , MURTHY KOLAPALLI VENKATA RAMANA
Published: May 2024

Objective: To develop and optimise the oral dissolving films of escitalopram oxalate by response surface methodology.
Methods: Oral dissolving film compositions were optimized by central composite design. The films are prepared by solvent casting method. Initially, different polymers were screened and based on the results polyvinyl alcohol was selected as polymer, propylene glycol was selected as plasticizer. Concentration of polymer and concentration of plasticizer were fixed as independent variables; tensile strength, percent elongation, elastic modulus and amount dissolved up to 5 min (%D5 min) were taken as responses.
Results: The prepared films exhibited good surface characteristics. The thickness, uniformity of weight, surface pH and drug content are within acceptable range. The mechanical properties like tensile strength, folding endurance, percent elongation and elastic modulus were determined. The statistical analysis showed that polymer concentration has a positive effect on disintegration time and the plasticizer concentration has a significant effect on folding endurance. The prepared film relesases nearly 95% at the end of 5 min. The design space was used to optimize the quantities of polymer and plasticizer. The comparison of checkpoint experiment batch responses are corelating with the predicted responses.
Conclusion: Escitalopram oxalate oral dissolving films was successfully designed and optimized by response surface method. It was concluded that the prepared films exhibit good mechanical properties and maximum release within 10 min.
THE APPLICATION OF BIOANALYTICAL METHOD OF TAMOXIFEN AND ITS ACTIVE METABOLITES FOR THERAPEUTIC DRUG MONITORING IN BREAST CANCER PATIENTS: A REVIEW
Authors: IKHSAN MUHAMMAD , HARAHAP YAHDIANA
Published: May 2024

Breast cancer is the most common cancer around the world and in Indonesia. The most widely used agent for breast cancer treatment is tamoxifen, with a fixed dose of 20 mg per day. Tamoxifen is metabolized by cytochrome P450 3A4 (CYP3A4) and 2D6 (CYP2D6) to endoxifen and 4-hydroxytamoxifen, which have 30-to 100-fold more potent antiestrogenic activity than tamoxifen. High variations of CYP3A4 and CYP2D6 genes can lead to interpatient variability in its metabolites concentration. The dose can be increased to 40 or 60 mg per day based on individual needs. Therapeutic drug monitoring (TDM) is required to measure the concentration of tamoxifen and its metabolites to decide the individualized dose. The measurement of drug levels should use a sensitive, selective, accurate, precise, and reliable bioanalytical method. Various bioanalytical methods have been developed in several matrices: urine, scalp hair, serum, plasma, dried blood spot (DBS), and volumetric absorptive microsampling (VAMS) samples, with different sample preparations, and frequently using liquid chromatography-tandem mass spectrometry (LC-MS/MS). The bioanalytical method of tamoxifen and its metabolites in the DBS sample was more suitable in the TDM application due to the low invasive sampling technique, more stable sample, and rapid sample preparation. Therefore, it is more time-and cost-efficient than the other methods.
FORMULATION OF NANOPARTICLE CONTAINING KENIKIR LEAF ETHANOL EXTRACTS (COSMOS CAUDATUS KUNTH.) AND ANTIDIABETIC ACTIVITY IN RATS
Authors: WIJAYA DINA PERMATA , HERLINA  , AZIZAN HAQ RADEN AYU AULYA
Published: May 2024

Objective: This study aimed to formulate the ethanol extract of kenikir leaf into nanoparticles. The ethanol extract of kenikir leaves loading into nanoparticles can enhanced the stability and effectiveness of antidiabetic activity.
Methods: The nanoparticles were prepared using the ionic gelation method with chitosan and variation in sodium tripolyphosphate. The nanoparticle formula was characterized by efficiency encapsulation using spectrophotometry methods and particle size, zeta potential, and polydispersity index using dynamic light scattering (DLS). An antidiabetic activity test was initiated by inducing a high-fat and fructose diet. The parameters tested were decreasing blood glucose levels in rats.
Results: The result of the characterization of the nanoparticle was the percent of efficiency encapsulation, particle size, PDI, zeta potential, and pH were carried out to get the best formula. The best formula obtained was the percent of efficiency encapsulation of 96.20±0.0278%, the particle size of 144.6±7.800 nm, zeta potential of+15.32±0.9550 mEv, PDI of 0.48±0.070, and pH of 4.255±0.0035. The decrease in blood glucose levels in the nanoparticles of kenikir leaves extract was not significantly (p>0.05) different from the positive group (metformin) compared to the kenikir leaves extract, which decreased not really significantly.
Conclusion: Nanoparticle containing kenikir leaf ethanol extract successfully prepared into nanoparticles and the potential to increase antidiabetic activity.
STUDY OF THE INHIBITORY EFFECTS OF VITAMIN E DERIVATIVES ON MITOCHONDRIAL COMPLEX II SUBUNIT USING MOLECULAR DOCKING
Authors: KARTIKA IRMA RATNA , ERNAWATI TENI , JUSMAN Sri WIDIA A. , SADIKIN MOHAMAD
Published: May 2024

Objective: The goal of this study was to create vitamin E derivatives and explore their potential anticancer properties using a computational approach.
Methods: The Steglich method was used for the synthesis of the vitamin E-fatty acid (pentanoic acid, heptanoic acid, and octanoic acid) derivatives, with N,N'-dicyclohexylcarbodiimide (DCC) and 4-dimethylaminopyridine (DMAP) as the catalysts. The structure of the synthesized products was determined by ultraviolet-visible (UV-Vis) spectroscopy, fourier transform infrared (FTIR) spectroscopy, and liquid chromatography-mass spectrometry (LC-MS). Molecular docking was carried out on the succinate dehydrogenase (SDH) enzyme using AutoDockTools.
Results: α–Tocopherol pentanoate (α–TP), α–tocopherol heptanoate (α–TH), and α–tocopherol octanoate (α–TO) were the three vitamin E derivatives synthesized in this study. Based on the results of molecular docking, the novel compounds (α–TP, α–TH, and α–TO) generated bond energies of-10.57,-9.61, and-9.20 kcal/mol, respectively.
Conclusion: All newly synthesized compounds exhibited lower binding affinity values than α–tocopherol (α–T). This confirms that these compounds might not provide greater advantages than α-tocopherol in terms of inhibitory effects on mitochondrial complex II (CII).
DESIGN FOR THE COLON CANCER INHIBITORS TARGETING THYMIDYLATE KINASE BY USING INSILICO STUDIES
Authors: BAQI MOHD ABDUL , JAYANTHI KOPPULA , RAJESHKUMAR RAMAN
Published: May 2024

Objective: Thymidylate Kinase (TMK) plays a crucial role in bacterial DNA synthesis by catalyzing the phosphorylation of Deoxythymidine Monophosphate (dTMP) to form Deoxythymidine Diphosphate (dTDP). Consequently, this enzyme emerges as a promising target for developing novel anti-cancer drugs. However, no anti-cancer drugs have been reported for this target until now.
Methods: Ligands obtained from Benzylidene derivatives were examined for their potency by using molecular docking by glide module, Qikprop screening of Absorption, Distribution, Metabolism, and Excretion (ADME) study, and prime Molecular Mechanics in Generalized Bond Surface Area study (MM-GBSA) by binding free energy. Hereafter, a Molecular Dynamic (MD) simulation was performed at 100 ns to assess the stability of the potential ligand as a Human TMK (HaTMK) inhibitor.
Results: These ten molecules showed good binding affinity and hydrogen and hydrophobic bond interactions with Arg150, Phe42, and Phe72 in the HaTMK enzyme (PDB id: 1E2D). Among them, trichloro-6-(((4-hydroxyphenyl)imino)methyl)phenol molecule had a high XP-docking score of (−7.87 kcal/mol), based on extra-precision data. Prime MM-GBSA studies also showed promising binding affinities i.e., ΔBind (-34.59 kcal/mol), ΔLipo (-13.92 kcal/mol), and ΔVdW (-34.42 kcal/mol). Arg76 and Phe72 residues maintained constant interactions with the ligand during Molecular Dynamics (MD) simulation. This ligand showed a potential binding affinity for the TMK target.
Conclusion: The trichloro-6-(((4-hydroxyphenyl)imino)methyl)phenol ligand has active sites, namely benzene ring, benzylidene, and oxygen group, which actively participate in interaction with the protein of HaTMK, thus indicating good potential activity as the inhibitor of HaTMK to treat colon cancer.
DEVELOPMENT AND OPTIMIZATION OF RABEPRAZOLE CHRONO-MODULATED DRUG DELIVERY SYSTEMS
Authors: KURAPATI PHANEENDRA , CHINNI SANTHIVARDHAN
Published: May 2024

Objective: Development and optimization of chrono-modulated pulsatile drug delivery systems (CPDDS) loaded with Rabeprazole for treating nocturnal acid breakthrough in ulcer patients was set as the major objective of this work.
Methods: CPDDS were developed to provide drug release as two pulses with predetermined gap. Separate microparticles for delayed instant release (DIR) and delayed extended-release (DER) were formulated. Through the optimization of several formulation and process parameters, ER microparticles were created as matrix microspheres. Central composite design was used to understand how the factors affected the responses. The optimized ER microspheres and plain drug were separately subjected to enteric coating to obtain DER and DIR portion microparticles, respectively.
Results: With the exception of stirring speed's impact on drug release, every other factor was found to have a significant influence (p<0.05) on every response. The mechanism underlying the Rabeprazole's delayed prolonged release was explained by the SEM images. The microspheres made with Eudragit RSPO at 0.72 g and polyethylene oxide at 0.5 g for 1 g of Rabeprazole at 400 rpm were shown to be the optimal formulation based on the graphical optimization results. After being coated with a terminal enteric coating, this formulation showed delayed release for a duration of 6 h.
Conclusion: After oral administration of equal doses of DIR microcapsules along with the optimized DER microspheres could release Rabeprazole effectively as two different pulses at the desired time intervals.
ENHANCING NOSE- TO- BRAIN DELIVERY OF PIRIBEDIL: DEVELOPMENT OF A NANOSUSPENSION DISPERSED IN NASAL IN-SITU GELLING SYSTEM
Authors: BHARGAVI CHEKKILLA , RAGHUVEER PATHURI
Published: May 2024

Objective: This study focuses on improving the delivery of Piribedil, a poorly soluble drug, to the brain through the nasal route using a nanosuspension in a nasal in-situ gel.
Methods: The nanosuspension was prepared using the sonoprecipitation method. Quality-by-Design (QbD) principles were used to optimize both the formulation and process parameters. The optimal process parameters were determined as sonication time (7.09 min), sonication amplitude (83.44%), and infusion rate (2.41 mL/min) with a desirability value of 0.970.
Results: The nanosuspension exhibited an average particle size ranging from 46.7 nm to 50.1 nm, and polydispersity index values between 0.393 and 0.425. Zeta potential values ranged from -33.78 ± 1.86 mV to -35.06 ± 2.12 mV, indicating favorable stability. FTIR studies revealed molecular interactions between Piribedil and stabilizers. XRPD and DSC analyses showed the transition from a crystalline to an amorphous state in the nanosuspension. Dissolution studies demonstrated significantly accelerated dissolution for the Piribedil nanosuspension, attributed to its nanosize and improved wettability. Stability assessments confirmed the robustness of the nanosuspension.
Conclusion: This innovative approach offers potential solutions for drug solubility challenges and blood-brain barrier penetration, holding promise for effective brain-targeted treatments.