bluuebunny/crossref_metadata_2025_split huggingface dataset:
Natural Bioactive Compounds as Anti-aging Agents: Current and Future
Perspectives
Authors: Sahoo Purbasha , Vyas Manish , Sahu Sanjeev Kumar 
Published: June 2024

Abstract:
Aging is a natural biological process that occurs due to various factors like unhealthy
diet, environmental factors, genetic factors, and lack of moisture. This process leads to the loss of
skin elasticity, also known as sagging. It happens due to the gradual decline of collagen type VII
(Col-7) and fibril, which slows down the connection between the dermis and epidermis layers,
causing the skin to look aged externally. There are several theories of aging, such as the free radical theory, membrane theory, DNA or genetic theory, neuroendocrine theory, telomerase theory,
mitochondrial decline theory, and Hayflick limit theory. According to WHO, by 2030, one in six
individuals worldwide will be 60 years or older. There are synthetic compounds available in the
market for anti-aging purposes, but they pose various side effects. Natural products play an essential role in managing aging, and anti-aging phytoconstituents are mostly found in plant parts like
fruits, stems, roots, and other plant sources that have no side effects. This review focuses on various anti-aging agents derived from plants and other natural sources.
The Low Tumorigenic Risk and Subtypes of Cardiomyocytes Derived from Human-induced Pluripotent Stem Cells
Authors: Lu Jizhen , Zhang Lu , Cao Hongxia , Ma Xiaoxue , Bai Zhihui , Zhu Hanyu , Qi Yiyao , Zhang Shoumei , Zhang Peng , He Zhiying , Yang Huangtian , Liu Zhongmin , Jia Wenwen 
Published: June 2024

Background:
Clinical application of human induced pluripotent stem cell-derived cardiomyocytes
(hiPSC-CMs) is a promising approach for the treatment of heart diseases. However,
the tumorigenicity of hiPSC-CMs remains a concern for their clinical applications and the composition
of the hiPSC-CM subtypes need to be clearly identified.

Methods:
In the present study, hiPSC-CMs were induced from hiPSCs via modulation of Wnt signaling
followed by glucose deprivation purification. The structure, function, subpopulation composition,
and tumorigenic risk of hiPSC-CMs were evaluated by single-cell RNA sequencing (scRNAseq),
whole exome sequencing (WES), and integrated molecular biology, cell biology, electrophysiology,
and/or animal experiments.

Results:
The high purity of hiPSC-CMs, determined by flow cytometry analysis, was generated.
ScRNAseq analysis of differentiation day (D) 25 hiPSC-CMs did not identify the transcripts representative
of undifferentiated hiPSCs. WES analysis showed a few newly acquired confidently
identified mutations and no mutations in tumor susceptibility genes. Further, no tumor formation
was observed after transplanting hiPSC-CMs into NOD-SCID mice for 3 months. Moreover, D25
hiPSC-CMs were composed of subtypes of ventricular-like cells (23.19%) and atrial-like cells
(66.45%) in different cell cycle stages or mature levels, based on the scRNAseq analysis. Furthermore,
a subpopulation of more mature ventricular cells (3.21%) was identified, which displayed
significantly up-regulated signaling pathways related to myocardial contraction and action potentials.
Additionally, a subpopulation of cardiomyocytes in an early differentiation stage (3.44%) experiencing
nutrient stress-induced injury and heading toward apoptosis was observed.

Conclusions:
This study confirmed the biological safety of hiPSC-CMs and described the composition
and expression profile of cardiac subtypes in hiPSC-CMs which provide standards for quality
control and theoretical supports for the translational applications of hiPSC-CMs.
The Overweight Prediction Model in the Risk Factor-based Adolescents Using a Web-based Online Application
Authors: Yuniarti Elsyie , Masrul Masrul , Sulastri Delmi , Elfitri Ikhwana , Lipoeto Nur Indrawati , Machmud Rizanda , Afrizal Afrizal , Symond Denas 
Published: June 2024

Background
The overweight prevalence rate in Indonesian adolescents has kept increasing. Basic Health Research in Indonesia recorded the overweight prevalence and obese nutritional status (BMI/Age) in adolescents at 18.1%. The overweight nutritional status (BMI/Age) in 2010-2013 among adolescents at the age of 16-18 was 1.4% in 2010 and increased to 7.3% in 2013.

Objective
This study aims to establish a prediction model for overweight adolescents based on their risk factors to prevent an early overweight.

Methods
The samples were 300 students from 5 high schools in Padang City, Indonesia. This study applied mixed methods and used a logistic regression test to comprehend the determinant variables in establishing the prediction model and conducting the application tests.

Results
The research shows the result that these adolescents had the risk factors, namely excessive consumption of carbohydrates and fats, the amount of vegetable consumption was <3 portions/day, physical activity time was <15 minutes/day, and a low level of health knowledge. It was predicted that the odds of being overweight were 82.31%, with accuracy at 95.0%, sensitivity at 93.33%, and specificity at 95.71%. The result showed application design validation by experts at 0.96 and validation of application construction and content by experts at 0.84. The teachers’ response practicality was 92.22%, adolescents’ response practicality was 85.45%, and adolescents’ response effectiveness was 85.05.

Conclusion
The most dominant risk factors are fat consumption, carbohydrate consumption, amount of vegetable consumption, duration of physical activities, and level of health knowledge that can be considered to prevent overweight in adolescents.
Extracts from Artemisia annua Alleviates Myocardial Remodeling through
TGF-β1/Smad2/3 Pathway and NLRP3 Inflammasome
Authors: Ma Zizhe , Bai Zhenzhou , Li Bohan , Zhang Yue , Liu Wei 
Published: June 2024

Background and Objectives:
Artemisinin and its derivatives, the well-known anti-malarial drugs extracted from traditional Chinese medicine, have been implicated in treating
fibrotic diseases. However, whether artemisinin affects cardiac fibrosis in the pathogenesis of heart failure is still unknown. This study aimed to
evaluate the possible effects of artemisinin on cardiac function and myocardial fibrosis in the heart failure model and to explore the underlying
mechanisms.

Methods:
Isoproterenol was injected subcutaneously for induction of the cardiac fibrosis model. Proteomic analysis was performed after 4 four weeks of
artemisinin treatment. Echocardiography was used to evaluate cardiac function and structure. Hematoxylin and eosin (H&E) staining, as well as
Masson staining, were performed for histopathology. The α-SMA, collagen I, and III expression in the myocardium was detected by
Immunohistochemical staining. The ratio of heart weight (HW) to body weight (HW/BW, mg/kg) and the ratio of heart weight to tibia length
(HW/TL, mg/mm) were calculated as indicators for cardiac remodeling. Brain natriuretic peptide (BNP) levels were quantified in rat plasma using
enzyme-linked immunosorbent assay (ELISA). In contrast, the protein levels of TGF-β1, p-Smad2/3, and Smad2/3 were assessed in myocardium
and fibroblasts via western blot analysis. RT-qPCR analysis of Col-I, Col-III, α-SMA, NLRP3, Caspase-1, IL-1β, and IL-18 was performed in the
heart.

Results:
Proteomic analysis identified 227 differentially expressed proteins (DEPs), including 119 upregulated and 108 downregulated proteins. These
proteins were identified as the core proteins targeted by artemisinin for improving myocardial remodeling. GO annotation of the DEPs indicated
that the DEPs were mainly associated with biological processes such as TGF-β and NLRP3 inflammasome regulation. In the in vivo study of an
isoproterenol-induced SD rat cardiac remodeling model, we found that artemisinin administration significantly ameliorated cardiac dysfunction and
reduced collagen production by suppressing TGFβ-1/Smads signaling and inhibiting NLRP3 inflammasome activation. As manifested by
downregulating the expression of α-SMA, Col-I, and Col-III, NLRP3, IL-1β, IL-18, Caspase-1 mRNA, and TGF-β1, p-SMAD 2/3 protein in the
myocardium. Similar beneficial effects of artemisinin were consistently observed in TGF-β1 treated primary cardiac fibroblasts.

Conclusions:
Artemisinin relieves myocardial remodeling through TGF-β1/Smad2/3 pathway and NLRP3 inflammasome.
A Novel Swarm Optimization Method to Address Coverage Connectivity
Problem in Wireless Sensor Networks
Authors: Sunkavalli Jaya Prakash , Ramesh Mona , Ramalingam Rajakumar , Ravi Vinayakumar , Alahmadi Tahani Jaser 
Published: June 2024

Background:
Over the last decade, Wireless Sensor Networks (WSNs) have found applications
across various domains, such as mines, agricultural sectors, healthcare, etc. These networks
consist of multiple sensor nodes responsible for collecting and relaying data to a central
gateway. Consequently, the integration of sensor devices bears the potential to influence the operational
effectiveness of these systems.

Objective:
This study concentrates on scrutinizing coverage and connectivity within a WSN deployed
for monitoring purposes. This research delves into determining the most efficient deployment
pattern requiring the minimum number of sensors.

Methods:
For attaining thorough coverage and uninterrupted connectivity, adopting a nondeterministic
strategy in sensor deployment is crucial. This study utilizes a model inspired by the
salp swarm optimization method, a technique rooted in swarm-based optimization principles. In
this methodology, clusters are defined as groups of sensor nodes meeting connection criteria and
ensuring adequate coverage. Adequacy is achieved when at least one of these nodes transmits monitored
data to the central hub.

Results:
The results offer compelling evidence that the discrete salp swarm optimization algorithm
is better than state-of-the-art algorithms. The results are interpreted in three different metrics,
namely the number of deployed sensors, total computational time, and the ratio between potential
sensors available and the number of sensors deployed to cover the region. As a result, on average,
the proposed model achieved an overall 87% of coverage and connectivity that are simulated with
different iteration numbers on a 50X50 grid. For the 100X100 grid, a total of 89% of coverage and
connectivity among sensors were achieved.

Conclusion:
The application of the discrete salp swarm optimization model presents a promising
approach to addressing the coverage connectivity problem in WSNs. Through the utilization of
salp-inspired behaviors, this model effectively optimizes network coverage while ensuring robust
connectivity, thus enhancing the overall performance and reliability of WSNs. By harnessing the
collective intelligence of salp swarms, the proposed algorithm demonstrates superior convergence
speed and solution quality compared to traditional methods.
Perspectives of Medical Students and Developers Regarding Virtual Reality, Augmented Reality, Mixed Reality, and 3D Printing Technologies: Survey Study
Authors: Yun Young Hyun , Shin Dong Hoon , Choi Hyung Jin 
Published: June 2024

Background
Emerging technologies, such as virtual reality (VR), augmented reality (AR), mixed reality (MR), and 3D printing (3DP), have transformative potential in education and health care. However, complete integration has not yet been achieved, and routine use is limited. There may exist gaps in the perspectives of these technologies between users and developers, and improvement may be necessary in developing such technologies.

Objective
The purpose of this study was to investigate the gaps in perspectives between medical students and developers in medical education regarding satisfaction and anticipated future use of VR, AR, MR, and 3DP technologies, as well as developers’ perspectives on their advantages and current challenges.

Methods
This retrospective survey study was conducted during a 4-hour elective course over a period of 4 weeks. In this course, computed tomography scans of congenital heart disease patients, medical image processing software, head-mounted displays, and a virtual table were used. Student pre- and postsurveys and the developer survey included demographic and other characteristics, satisfaction, and anticipated future use of VR, AR, MR, and 3DP technologies. The advantages and current challenges of these technologies were only assessed in the developer survey.

Results
The study enrolled 41 participants, including 15 first-year medical students and 26 software and content developers. Students were more satisfied than developers across AR, VR, and 3DP in terms of overall satisfaction (VR and AR: P<.001; 3DP: P=.002), esthetics (VR: all P<.001; AR: vividness, P=.006 and design, P<.001; 3DP: vividness, P=.001 and design, P=.002), and continuous use intention (VR: repetition, P=.04 and continuous use, P=.02). Particularly in VR, satisfaction with reality was higher among students than among developers (real world, P=.006). Developers anticipated future use of MR for educating medical students and residents, individual and collaborative surgical planning, and performing surgery on patients. In contrast, students anticipated future use of VR primarily for student education, 3DP for resident education and individual surgical planning, and AR for collaborative surgical planning and performing surgery on patients. Developers perceived the inherent capabilities of VR, AR, and MR technologies as strengths, with hardware performance identified as a drawback. For 3DP, the possibility of customized product manufacturing was seen as an advantage, while cost was seen as a disadvantage.

Conclusions
This study elucidated the different perspectives between medical students and developers regarding 3D technologies, highlighting the discrepancy in potential applications and challenges within the medical field. These findings will guide the integration of 3D technologies in education and health care to fulfill the needs and goals of both medical students and developers.
Entity and Relation Linking for Knowledge Graph Question Answering Using Gradual Searching
Authors: Adila Alfa Krisnadhi  , Mohammad Yani  , Indra Budi  
Published: June 2024

Knowledge graph question answering (KGQA) systems have an important role in retrieving data from a knowledge graph (KG). With the system, regular users can access data from a KG without the need to construct a formal SPARQL query. KGQA systems receive a natural language question (NLQ) and translate it into a SPARQL query through three main tasks, namely, entity and relation detection, entity and relation linking, and query construction. However, the translation is not trivial due to lexical gaps and entity ambiguity that may occur during entity or relation linking. This research proposed an approach based on multiclass classification of NLQ whose entity occurrences are detected into categories based on KG relations to address the lexical gap challenge. Next, to solve the entity ambiguity challenge, this research proposed a three-stage searching procedure to determine appropriate KG entities associated with the NLQ entities, given the correspondence between the NLQ and a particular KG relation. This three-stage searching consisted of text-based searching, vector-based searching, and entity and relation pairing. The proposed approach was evaluated on the SimpleQuestions and LC-QuAD 2.0 datasets. The experiments demonstrated that the proposed approach outperformed the state-of-the-art baseline. For the relation linking task, the proposed approach reached 89.87% and 74.83% recall for the SimpleQuestions and LC-QuAD 2.0, respectively. This approach also achieved 91.74% and 61.96% recall on the entity linking tasks for the SimpleQuestions and LC-QuAD 2.0, respectively.
Is machine learning “revolutionising” the Arts?
Authors: Ploin Anne 
Published: June 2024

Although the Arts have a long history of incorporating technology––analogue and digital, emerging and retro––into artistic practice, artists have generally been considered automation-proof. Until recently––as recent successes in machine learning (ML) research in the past ten years have given rise to a new wave of interest in the complete automatability of creativity, a final frontier for a maximalist vision for AI-driven automation. Narratives featuring fully autonomous algorithmic “artists” fuelled the hype surrounding machine learning. But what has been happening on the ground in the arts?
Apical Hypertrophic Cardiomyopathy: A Special Entity.
Authors: Adhikaree Ajay , KC Man Bahadur , Malla Rabi 
Published: June 2024

Introduction: Apical Hypertrophic Cardiomyopathy (AHCM) is a unique variant with distinct clinical presentation, genetics, treatment, complications and outcome. Case: A 52 year non-hypertensive Asian male presented with exertional shortness of breath for two years without chest pain, palpitation or syncope. The apex beat was heaving. Electrocardiogram revealed non q wave deep symmetrical T wave inversion in anterolateral leads and echocardiography demonstrated hypertrophied apical septum. Coronary angiogram showed normal coronaries with typical “Ace of Spade” configuration during ventriculography. Conclusion: Characterization of various forms of hypertrophic cardiomyopathy is essential for management purpose as apical hypertrophic cardiomyopathy usually have benign course.
Implementasi SMOTE dan Support Vector Machine Pada Klasifikasi Data Tidak Seimbang Metilasi Arginin
Authors: Lumbanraja Favorisen Rosyking , Gaol Ester Caroline Lumban , Shofiana Dewi Asiah , Junaidi Akmal 
Published: June 2024

Imbalanced data is one of the crucial problems in machine learning and data mining which may provide low accuracy in minority classes and makes the classification method not fully optimized. The Arginine Methylation dataset for example, gives a large amount of imbalanced data. Methylation is one of the post-translational modification processes that occurs in arginine protein which affects signal transduction and RNA binding inside cytoplasms. Therefore, it is essential to handle imbalanced data for classification. Synthetic Minority Oversampling Technique (SMOTE) is an algorithm for solving imbalanced data in classification using the concept of k-nearest neighbors. Support Vector Machine (SVM) is a supervised learning method which splits datasets using hyperplane and maximize margin distance. In this research, the arginine methylation dataset is divided into three experimental data, which consists of training data, testing data, and independen data. Data processing goes through a series of steps; data pre-processing (clean redundance data), feature extraction (generates 159 feature dimensions), SMOTE and SVM modeling, and classification testing using 10-fold cross-validation and confusion matrix. The accuracy of training data is 100% in RBF kernel, whereas testing data gives a low accuracy of 65,90% in linear kernel. Independen data have decent accuracy in linear kernel by 98,50% percentage.
Feline aortic thromboembolism with and without congestive heart failure did not exhibit hypercoagulability using a novel viscoelastic coagulation monitor
Authors: Moses Ivan A. , Hallowell Theresa C. , Johnson Justine A. 
Published: June 2024

Abstract

OBJECTIVE
To demonstrate hypercoagulability with a benchtop viscoelastic monitor in cats with congestive heart failure (CHF) and/or aortic thromboembolism (ATE) compared to controls.

METHODS
97 cats were enrolled throughout this prospective observational cohort study from September 2022 through October 2023. Cats were grouped by diagnosis of CHF, ATE, ATE plus CHF, or controls. Enrollment required diagnosis of heart disease and no previous antithrombotic therapy. The results of viscoelastic testing with the benchtop viscoelastic coagulation monitor (VCM Vet [VCM]; Entegrion) were compared between groups using factorial analysis of variance.

RESULTS
Cats with heart disease had significantly higher clot times when compared to controls (control: mean, 285.3 [SD, 172.6]; CHF: mean, 391.7 [SD, 106.8]; ATE: mean, 415.9 [SD, 109.2]; and ATE plus CHF: mean, 368.6 [SD, 232.6]). Heart disease cats were noted to have significantly lower 45-minute lysis index values (control: median, 100 [range, 93 to 100]; CHF: median, 99 [range, 89 to 100]; ATE: median, 98 [range, 88 to 100]; and ATE plus CHF: range, 98 [91 to 100]). Age was a covariate to this variable, and when applied to analysis, statistical significance was lost. No significant difference in any other variables were noted.

CLINICAL RELEVANCE
The hypercoagulability of ATE and CHF cats was not detected by the VCM. Further research with other coagulation monitors is required in this population.
Incidence and type of voluntary reported perianesthetic medication errors in community veterinary clinics in Calgary, Canada
Authors: Pinho Renata H. , Tscheng Dorothy , Cheema Jagjit S. , Pang Daniel S. J. 
Published: June 2024

Abstract

OBJECTIVE
To collect medication error (ME) data during the perianesthetic period from small animal clinics.

SAMPLE
6 small animal general practice veterinary clinics.

METHODS
Small animal general practice veterinary clinics were recruited in this prospective observational study, with staff given a presentation on medical errors and instructed on how to submit medication error reports to an online reporting system. Errors were classified according to type and timing.

RESULTS
A total of 2,728 general anesthesia or sedation procedures were performed, with 49 ME reports submitted. One duplicated report of the same error was excluded, resulting in a ME rate of 1.8%. Most reports (69% [33/48]) were near misses. The remaining 31% were MEs that reached the patient but did not cause harm. Wrong dose errors were the most common type (63% [30/48]), of which 80% (24/30) were calculation errors. Premedication/sedation and maintenance were the most reported stages, at 47% (20/43) and 23% (10/43), respectively. None of the MEs reported resulted in an adverse event, with an approximately 2:1 ratio of near-miss to no-harm MEs. The observed patterns of MEs reported, including type and timing, represent a target for further education.

CLINICAL RELEVANCE
These results quantify the ME rate in general practice veterinary clinics, providing an initial benchmark for MEs during the perianesthetic period.
Cooperative Societies as a Sustainable Legislative Aspect of the Establishment of a Dispersed Hotel
Authors: Pavić Lazar , Vizjak Katja 
Published: June 2024

Abstract
Dispersed hotels, characterized by their decentralized accommodation facilities integrated into existing structures of historical or cultural significance, have emerged as a sustainable alternative to traditional centralized hotels. This study explores the role of cooperative societies as a legislative and organizational framework for establishing and managing dispersed hotels. Utilizing a mixed-methods approach, the research analyzes case studies from Europe where cooperative models have successfully facilitated the integration of dispersed hotels into local communities, ensuring economic and cultural sustainability in Slovenia. The findings indicate that cooperative societies enable effective resource sharing, community engagement, and equitable distribution of economic benefits, which are essential for the long-term sustainability of dispersed hotels. Legislative support in the form of favorable policies and financial incentives has been identified as critical in fostering these cooperative initiatives. The study suggests that cooperative societies not only enhance the operational sustainability of dispersed hotels but also contribute to the conservation of cultural heritage and the stimulation of local economies. The results advocate for policymakers to consider cooperative models in tourism development strategies, emphasizing their potential to transform local communities and promote sustainable tourism practices.