bluuebunny/crossref_metadata_2025 huggingface dataset:
Algal Polysaccharides as Promising Anticancer Agents
Authors: Gomaa Mohamed
Published: October 2024

There is a growing demand for the development of new anticancer drugs
owing to the worldwide increase in cancer mortality. Algal polysaccharides, such as
fucoidan, alginate, laminarin, carrageenan, porphyran, ulvan and calcium spirulan, have
been recognized as natural products with potential good anticancer properties against a
variety of cancer cell lines in vitro and in vivo. Therefore, they can be used for the
development of natural anticancer drugs with fewer side effects than synthetic ones.
Additionally, algal polysaccharides can be used as an adjuvant treatment to mitigate
undesirable side effects and promote the anticancer properties of clinical anticancer
drugs. This chapter focuses on the recent anticancer properties of algal polysaccharides
from different algal groups as well as their mode of action.
Emodin: Anticancer Agent
Authors: Siddiqui Mohd Aftab , Rahman Mohammad Saidur , Islam Anas , Usmani Afreen , Ahmad Usama
Published: October 2024

Cancer is a serious health issue that remains a significant cause of mortality
around the world. Psychosocial support, surgery, radiation, and chemotherapy are
common cancer treatments. However, because of the rising rate of cancer-related
mortality and the adverse or toxic side effects of cancer chemotherapy and radiation
therapy, new anticancer compounds obtained from nature, particularly plants, are
currently being researched. Phytochemicals, which are naturally occurring plant
substances, are important sources for new drugs and cancer treatment. Phytochemicals
are selective in their actions, acting only on tumour cells and not on healthy cells.
These phytochemicals act by modulating molecular pathways involved in cancer
growth and progression. Anthraquinones are a class of phytochemicals that have a wide
range of biological functions as well as anticancer action. Emodin is a natural
anthraquinone derivative found in Rheum palmatum, Polygonum cuspidatum,
Polygonum multiflorum and among other commonly used Chinese medicinal plants.
Evidence indicates that emodin has a wide spectrum of pharmacological properties,
including hepatoprotective, antiinflammatory, antioxidant and antimicrobial activities.
Emodin has also been reported to have anticancer properties in a variety of
malignancies, including lung, liver, and pancreatic tumours. Anticancer properties of
emodin have been studied in a variety of biological pathways. This chapter aims to
comprehensively summarize the anti-proliferative and anti-carcinogenic properties of
emodin.
Nanotherapeutics as Antibacterial and Antiviral Agents: Approach beyond Antibiotics
Authors: Singh Raman , Gupta Vidushi , Nisha  , Singh Kuldeep
Published: October 2024

The field of nanotherapeutics has evolved over the last few decades, and the
scientific community has become increasingly interested in exploring and developing
versatile biomaterial nanosystems for clinical medicine. Antimicrobials, despite their
many advances, have been plagued by an ever-growing problem of antimicrobial
resistance. This threat has been labeled the “post-antibiotic era” by the WHO and other
organizations. Nanoparticles (NPs)-based therapeutics have recently emerged as new
tools for combating deadly bacterial infections. Traditional antimicrobials face
challenges, such as antibiotic resistance, which nanoparticle-based strategies can
overcome. This chapter discusses various nanotherapeutics and their essential roles in
antimicrobial therapy. This book chapter delves into the burgeoning field of
nanotherapeutics, focusing on their potential as innovative solutions to combat bacterial
and viral infections. With the escalating threat of antimicrobial resistance and the
ongoing challenge of emerging viral pathogens, traditional treatment modalities are
increasingly inadequate. Nanotechnology offers a promising avenue for the
development of novel antibacterial and antiviral agents, presenting unique advantages
such as enhanced drug delivery, improved bioavailability, and targeted action. The
chapter provides an overview of the mechanisms by which nanotherapeutics exert their
antimicrobial effects, including direct disruption of bacterial and viral structures,
inhibition of essential cellular processes, and modulation of host immune responses.
Various types of nanoparticles, such as liposomes, polymeric nanoparticles, and
metallic nanoparticles, are explored for their ability to encapsulate and deliver
antimicrobial agents to target sites with precision. Furthermore, the chapter discusses
the potential applications of nanotherapeutics in addressing key challenges associated
with conventional antibiotics and antiviral drugs, including drug resistance, adverse
effects, and limited efficacy. By leveraging the unique physicochemical properties of
nanoparticles, researchers aim to develop therapeutic strategies that minimize off-target
effects, reduce the likelihood of resistance development, and enhance patient outcomes.Despite the promising advancements in nanotherapeutics, several hurdles remain on the
path to clinical translation, including standardization of manufacturing processes,
evaluation of safety profiles, and regulatory approval. The chapter underscores the
importance of interdisciplinary collaboration among scientists, clinicians, and
regulatory agencies to overcome these challenges and realize the full potential of
nanotherapeutics in clinical practice.
Enzyme-Responsive Nanoparticles for Drug Delivery
Authors: Mathur Aakash , Singhal Jaya , Gupta Deepak , Saxena Reshu
Published: October 2024

Enzyme-responsive nanoparticles have emerged as a promising platform for
targeted drug delivery, offering unparalleled control over therapeutic release in
response to specific biological cues. This book chapter explores the design principles,
mechanisms of action, and biomedical applications of enzyme-responsive nanoparticles
in drug delivery. The chapter begins by elucidating the rationale behind the
development of enzyme-responsive nanoparticles, highlighting the importance of
precise drug release kinetics, site-specific targeting, and reduced off-target effects in
enhancing therapeutic efficacy. Key design considerations, including choice of enzyme
substrate, nanoparticle composition, and triggering mechanisms, are discussed in detail,
emphasizing the versatility and tunability of these nanosystems for diverse therapeutic
applications. Furthermore, the chapter delves into the underlying mechanisms
governing enzyme-triggered drug release from nanoparticles, such as enzymatic
cleavage, conformational changes, and degradation of nanoparticle matrices. Examples
of enzyme-responsive nanomaterials, including liposomes, polymeric nanoparticles,
and mesoporous silica nanoparticles, are presented, showcasing their ability to
selectively release therapeutic payloads in response to specific enzymatic stimuli, such
as proteases, phosphatases, and esterases. Moreover, the biomedical applications of
enzyme-responsive nanoparticles are comprehensively reviewed, encompassing
targeted cancer therapy, inflammation modulation, tissue engineering, and diagnostics.
Case studies illustrating the efficacy of enzyme-responsive nanocarriers in overcoming
biological barriers, improving drug bioavailability, and minimizing systemic toxicity
are highlighted, underscoring their translational potential in clinical settings. The
chapter concludes with a discussion of future perspectives and challenges in the field of
enzyme-responsive nanoparticles for drug delivery, including optimization of
nanoparticle stability, scalability of synthesis methods, and integration of imaging modalities for real-time monitoring of therapeutic responses. By harnessing the
catalytic power of enzymes to orchestrate precise drug release, enzyme-responsive
nanoparticles offer a paradigm shift in therapeutic precision, paving the way for
personalized and targeted treatments with enhanced therapeutic outcomes.
Anti-HIV Nanotherapeutics and their Challenges in the Future
Authors: Paramanick Debashish , Singh Vijay Kumar , Singh Veena Devi , Aalam Md. Aftab
Published: October 2024

The human immunodeficiency virus (HIV) affects the body's immune
system of the body in such a way that a minor infection, such as a cold, can become
severe. The treatment of HIV is challenging due to the virus's resistance. A high dose
of the drug is required to achieve viral load reduction. Current available antiretroviral
therapy can improve the health of HIV patients, although systemic viral load may
remain sequestered if the virus persists in anatomically privileged areas of the body.
Nanotechnology-based drug delivery techniques are being developed to target the virus
in various tissue compartments. Due to their durability, safety, multimodality, and
multifunctionality, nanomaterials are extensively used in biological applications.
However, unwanted interactions with plasma proteins in the systemic circulation,
failure to cross biological barriers, and nonspecific distribution throughout the body are
challenges. It is required to mitigate these challenges in the field of nanomedicine in
the near future. So, the main objective of this chapter is to compile information on
pathogenesis and their targets, as well as how anti-retroviral drugs improve efficacy in
treatment. This chapter will provide new insight intofinding nanotherapeutics for HIV.
Current Perspectives of Nanotherapeutics for the Treatment of Alzheimer’s Disease
Authors: Mishra Shruti , Senthilkumar Dharmaraj , Yadav Vivek Kumar
Published: October 2024

Alzheimer's disease (AD) is one of the most prevalent irreversible
neurodegenerative disorders, contributing to approximately 50-80% of all reported
cases worldwide. The majority of current treatment strategies for AD only provide
symptomatic treatment. The inability of existing medications to penetrate the bloodbrain barrier (BBB) is a major challenge in treating AD. The application of
nanotechnology in drug delivery systems is categorized by potential medicines
designed to penetrate the BBB and improve drug targeting for neurodegenerative
disorders (NDDs) treatment. Nanotechnology offers a wide range of nanoparticle-based
drug delivery systems with minimal systemic side effects. Nano-based gene delivery
vehicles and nanocarriers such as neurotrophic factors effectively improve neuronal
survival and synaptic connectivity. Thus, currently, they are being utilized as a popular
therapeutic against various neurodegenerative diseases. Recently, nanotechnology has
patented various novel nanostructures and developed several advanced formulations for
the management and prevention of NDDs. Therefore, to combat neurodegenerative
disorders, nanotechnology can be applied to neuroscience. Primary research on
employing nanoparticles (NPs) to manage Alzheimer's disease has shown promising
results, but additional studies are still required. In this chapter, we discuss the
pathogenesis and causes of AD and also outline the role of NPs in the brain's
microenvironment for treating Alzheimer's disease. Overall, this chapter focuses on
newly investigated NP systems that provide unique ways of understanding AD
pathophysiology and suggesting therapy to cure AD.
Nanotherapeutics in Skin Therapy
Authors: Chhabra Priyanka , Johari Akshara , Tripathy Divya Bajpai
Published: October 2024

Nanotherapeutics has emerged from nanotechnology applications and has a
wide range of utilities in the medical field. Nanotherapeutics made a revolutionary
change in healthcare and provided a vision to augment diagnostics and treatment
solutions by managing the release of contained bioactive compounds. It has gained
much research interest in today’s modern world due to its implications in drug delivery
and genes, which overcome lacunae prevailing in the existing therapeutic sphere by the
use of engineered nanostructures and nanodevices. The interaction of nanostructures
with the skin tissue at the subatomic level has significant applications in the diagnosis
and treatment of dermatological conditions, especially wound healing and
cosmeceutical treatment. Nanotherapies and diagnostics have the potential to improve
treatment effectiveness while reducing or eliminating toxicity problems. This book
chapter provides an overview of the latest advancements and applications of
nanotherapeutics in skin therapy. Nanoparticles, owing to their unique physicochemical
properties, have shown immense potential in enhancing drug delivery, improving skin
penetration, and targeting specific cellular and molecular pathways implicated in
various skin conditions. Key topics covered include the design and synthesis of
nanoparticles for skin delivery, including liposomes, polymeric nanoparticles, solid
lipid nanoparticles, and nanoemulsions. These nanocarriers can encapsulate a wide
range of therapeutic agents, including anti-inflammatory drugs, antimicrobials,
antioxidants, and gene-based therapies, enabling precise and controlled release at the
site of action.
Multifaceted Applications of Nanoparticle Functionalized Graphene
Authors: Sengupta Poulomi , Patel Siddhant B.
Published: October 2024

Recently, graphene sheets have attracted a huge awareness for their special
optical, mechanical, magnetic, electronic, and thermal characteristics. This has been
possible due to the thin yet robust two-dimensional structural arrangement. The special
properties may further be enhanced by smart chemical modifications on the twodimensional structure. Meanwhile, nanoparticles also have come up as an emerging
platform for their size, shape, surface area, optoelectronic properties and flexibility in
functionalization. To utilize the advantages of both worlds, the scientific community
has combined graphene with metallic nanoparticles. This event has brought about
extreme enhancements in the above properties. Both inorganic and organic
nanoparticles have been attached to the graphene surface. However, the attachment of
metallic nanoparticles has increased their applications in developing sensors and
catalysts. In this literature review, we want to concentrate on synthesizing and
functionalizing graphene with different metallic nanoparticles. At the same time, we
would discuss their applications in various fields.
Stanene, Mxene and Transition Metal Chalcogenides
Authors: Pathak Rakshit , Punetha Mayank , Kumar Rajesh , Tamta Anshu
Published: October 2024

In recent years, there has been a notable surge of interest in Stanene,
MXene, and Transition Metal Chalcogenides. The chapter offers a comprehensive
exploration of these cutting-edge 2D materials and their multifaceted applications.
Stanene, with its remarkable quantum effects and physicochemical properties, holds
promise for the future of nanoelectronics and optoelectronics. Similarly, MXene and
Transition Metal Chalcogenides exhibit exceptional characteristics that make them
indispensable in various fields, from theranostics to sensor nano-systems and
spintronics. Practical applications often hinge on the successful manipulation of
molecules through quantum dynamics, but limited synthesis methods for 2D materials
pose challenges in this regard. The chapter delves into the structures, synthesis
techniques, and applications associated with these materials, providing a
comprehensive overview of their potential and current advancements. While a
substantial portion of research on these materials has remained theoretical, the chapter
underscores the pressing need for increased experimental endeavours. It serves as an
invaluable resource for researchers, scientists, and professionals interested in
harnessing the unique properties of Stanene, MXene, and Transition Metal
Chalcogenides across a spectrum of innovative applications.
SOCIAL MEDIA SPAM DETECTION USING DIFFERENT TEXT FEATURE SELECTION TECHNIQUE AND MACHINE LEARNING
Authors:   Sage University, India, Sharma Anubha , Ramaiya Manoj ,   Sage University, India
Published: October 2024

The messaging systems and social media is popular and has essential contributions to our social and professional life. Similarly, Spam is a part of the messaging system and social media. In social media, spam is found in various places (i.e. in posts, in comments, in reviews, and in chatting). Social media Spam is aimed to influence the user’s decision, point of view, and credibility of the service or brand. Therefore, social spam detection is essential. However, using the social media data a number of contributions are available in literature, but a fewer amount of work is available for social media spam detection. In this paper, we proposed a social media spam detection technique using machine learning and text feature extraction techniques. In this context first, a review on social media spam detection techniques has been carried out. Using this review, we extract the different machine learning techniques used, techniques of text feature selection, and experimental datasets used. In this review, we found that the spam messages with the URLs are more critical and harmful. Next step, we design a theoretical model for social media spam detection, which includes text feature selection techniques (i.e. TF-IDF, POS, and Information Gain) and their combinations (POS+TF-IDF and POS+IG). These features are used with Support Vector Machine (SVM), Artificial Neural Network, and Naïve Bayes classifier for training. Experimental analysis with dataset available in Kaggle we found that hybrid features is more effective for accurate classification as compared to individual features. Additionally, we found for classification the SVM and ANN are more accurate as compared to the Bayes classifier.
A NOVEL ARCHITECTURE OF INTELLIGENT DECISION MODEL FOR EFFICIENT RESOURCE ALLOCATION IN 5G BROADBAND COMMUNICATION NETWORKS
Authors:   Sri Eshwar College of Engineering, India, J Logeshwaran , T Kiruthiga ,   Vetri Vinayaha College of Engineering and Technology, India, Lloret Jaime ,   Universitat Politecnica de Valencia, Spain
Published: October 2024

Intelligent Decision Model for efficient resource allocation in 5G broadband communication networks is essential for ensuring the most efficient use of available resources. This model considers several factors, such as traffic demand, network topology, and radio access technology, to make the most efficient decisions about resource allocation. It is based on intelligent algorithms and advanced analytics, which allow the network to quickly and accurately identify the optimal resource allocation for a given situation. This model can reduce costs, improve network performance, and increase customer satisfaction. In addition, the Intelligent Decision Model can help operators reduce the complexity and cost of managing a 5G network. The intelligent decision model for efficient resource allocation in 5G broadband communication networks is based on a combination of artificial intelligence (AI) and optimization techniques. The proposed decision models can use AI to identify patterns in traffic and user behavior. In contrast, the proposed can use optimization techniques to maximize resource utilization and reduce latency in the network. This model can also leverage predictive analytics and machine learning algorithms to determine the most efficient allocation of resources. Additionally, the proposed model can use AI to detect and mitigate potential security threats and malicious activities in the network. the proposed IDM has reached 91.85% of accuracy, 90.05% of precision, 90.96% of recall and 91.33% of F1-score.
Naloxone Coprescribing and the Prevention of Opioid Overdoses: Quasi-Experimental Metacognitive Assessment of a Novel Education Initiative
Authors: Enich Michael , Morton Cory , Jermyn Richard
Published: October 2024

Background

Critical evaluation of naloxone coprescription academic detailing programs has been positive, but little research has focused on how participant thinking changes during academic detailing.

Objective

The dual purposes of this study were to (1) present a metacognitive evaluation of a naloxone coprescription academic detailing intervention and (2) describe the application of a metacognitive evaluation for future medical education interventions.

Methods

Data were obtained from a pre-post knowledge assessment of a web-based, self-paced intervention designed to increase knowledge of clinical and organizational best practices for the coprescription of naloxone. To assess metacognition, items were designed with confidence-weighted true-false scoring. Multiple metacognitive scores were calculated: 3 content knowledge scores and 5 confidence-weighted true-false scores. Statistical analysis examined whether there were significant differences in scores before and after intervention. Analysis of overall content knowledge showed significant improvement at posttest.

Results

There was a significant positive increase in absolute accuracy of participant confidence judgments, confidence in correct probability, and confidence in incorrect probability (all P values were <.05). Overall, results suggest an improvement in content knowledge scores after intervention and, metacognitively, suggest that individuals were more confident in their answer choices, regardless of correctness.

Conclusions

Implications include the potential application of metacognitive evaluations to assess nuances in learner performance during academic detailing interventions and as a feedback mechanism to reinforce learning and guide curricular design.
Accuracy of Machine Learning in Detecting Pediatric Epileptic Seizures: Systematic Review and Meta-Analysis
Authors: Zou Zhuan , Chen Bin , Xiao Dongqiong , Tang Fajuan , Li Xihong
Published: October 2024

Background

Real-time monitoring of pediatric epileptic seizures poses a significant challenge in clinical practice. In recent years, machine learning (ML) has attracted substantial attention from researchers for diagnosing and treating neurological diseases, leading to its application for detecting pediatric epileptic seizures. However, systematic evidence substantiating its feasibility remains limited.

Objective

This systematic review aimed to consolidate the existing evidence regarding the effectiveness of ML in monitoring pediatric epileptic seizures with an effort to provide an evidence-based foundation for the development and enhancement of intelligent tools in the future.

Methods

We conducted a systematic search of the PubMed, Cochrane, Embase, and Web of Science databases for original studies focused on the detection of pediatric epileptic seizures using ML, with a cutoff date of August 27, 2023. The risk of bias in eligible studies was assessed using the QUADAS-2 (Quality Assessment of Diagnostic Accuracy Studies–2). Meta-analyses were performed to evaluate the C-index and the diagnostic 4-grid table, using a bivariate mixed-effects model for the latter. We also examined publication bias for the C-index by using funnel plots and the Egger test.

Results

This systematic review included 28 original studies, with 15 studies on ML and 13 on deep learning (DL). All these models were based on electroencephalography data of children. The pooled C-index, sensitivity, specificity, and accuracy of ML in the training set were 0.76 (95% CI 0.69-0.82), 0.77 (95% CI 0.73-0.80), 0.74 (95% CI 0.70-0.77), and 0.75 (95% CI 0.72-0.77), respectively. In the validation set, the pooled C-index, sensitivity, specificity, and accuracy of ML were 0.73 (95% CI 0.67-0.79), 0.88 (95% CI 0.83-0.91), 0.83 (95% CI 0.71-0.90), and 0.78 (95% CI 0.73-0.82), respectively. Meanwhile, the pooled C-index of DL in the validation set was 0.91 (95% CI 0.88-0.94), with sensitivity, specificity, and accuracy being 0.89 (95% CI 0.85-0.91), 0.91 (95% CI 0.88-0.93), and 0.89 (95% CI 0.86-0.92), respectively.

Conclusions

Our systematic review demonstrates promising accuracy of artificial intelligence methods in epilepsy detection. DL appears to offer higher detection accuracy than ML. These findings support the development of DL-based early-warning tools in future research.

Trial Registration

PROSPERO CRD42023467260; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023467260
Relationship Between Depression and Falls Among Nursing Home Residents: Integrative Review
Authors: Matos Queirós Alcina , von Gunten Armin , Rosselet Amoussou Joëlle , Lima Andreia Maria , Martins Maria Manuela , Verloo Henk
Published: October 2024

Background

Depression is a highly prevalent psychopathological condition among older adults, particularly those institutionalized in nursing homes (NHs). Unfortunately, it is poorly identified and diagnosed. NH residents are twice as likely to fall as community-dwelling older adults. There is a need for more knowledge about the mechanisms and relationships between depression and falls.

Objective

This study aims to identify, analyze, and synthesize research on the relationships between depression and falls among NH residents.

Methods

A literature search was conducted in October 2023 in the following bibliographic databases: MEDLINE ALL Ovid, Embase, CINAHL with Full Text EBSCO, APA PsycInfo Ovid, Web of Science Core Collection, the Cochrane Database of Systematic Reviews Wiley, and ProQuest Dissertations & Theses A&I. Clinical trials were searched for in the Cochrane Central Register of Controlled Trials Wiley, ClinicalTrials.gov, and the World Health Organization International Clinical Trials Registry Platform. Additional searches were performed using Google Scholar, the DART-Europe E-theses Portal, and backward citation tracking. The Newcastle-Ottawa Scale and the Appraisal tool for Cross-Sectional Studies were used to evaluate study quality.

Results

The review included 7 quantitative studies published in 7 different countries from 3 continents; of these, 6 (86%) were cross-sectional studies, and 1 (14%) was a prospective cohort study. Results suggested high frequencies of depressive symptoms and falls among older adults living in NHs, and depressive symptoms were considered a risk factor for falls. The 15-item and 10-item versions of the Geriatric Depression Scale were the most commonly used measurement tools, followed by the Cornell Scale for Depression in Dementia and the Resident Assessment Instrument-Minimum Data Set 2.0. The prevalence of depression was heterogeneous, varying from 21.5% to 47.7% of NH residents. The studies used heterogeneous descriptions of a fall, and some considered the risk of falls, recurrent fallers, and near falls in their data. The prevalence of fallers was disparate, varying from 17.2% to 63.1%. Of the 7 retained studies, 6 (86%) reported a relationship between depression and falls or the risk of falls. Among the 19 other risk factors identified in the review as being associated with falls among NH residents were a history of falls in the last 180 days, >1 fall in the past 12 months, and respiratory illnesses.

Conclusions

There is a paucity of research examining falls among older adults with depressive symptoms in NHs. These findings should alert nurses to the need to consider depression as a risk factor in their work to prevent falls. More research is needed to gain a comprehensive understanding of fall risk among NH residents with depressive symptoms.

International Registered Report Identifier (IRRID)

RR2-10.2196/46995
Unveiling the Influence of AI on Advancements in Respiratory Care: Narrative Review
Authors: Alqahtani Mohammed M , Alanazi Abdullah M M , Algarni Saleh S , Aljohani Hassan , Alenezi Faraj K , F Alotaibi Tareq , Alotaibi Mansour , K Alqahtani Mobarak , Alahmari Mushabbab , S Alwadeai Khalid , M Alghamdi Saeed , Almeshari Mohammed A , Alshammari Turki Faleh , Mumenah Noora , Al Harbi Ebtihal , Al Nufaiei Ziyad F , Alhuthail Eyas , Alzahrani Esam , Alahmadi Husam , Alarifi Abdulaziz , Zaidan Amal , T Ismaeil Taha
Published: October 2024

Background

Artificial intelligence is experiencing rapid growth, with continual innovation and advancements in the health care field.

Objective

This study aims to evaluate the application of artificial intelligence technologies across various domains of respiratory care.

Methods

We conducted a narrative review to examine the latest advancements in the use of artificial intelligence in the field of respiratory care. The search was independently conducted by respiratory care experts, each focusing on their respective scope of practice and area of interest.

Results

This review illuminates the diverse applications of artificial intelligence, highlighting its use in areas associated with respiratory care. Artificial intelligence is harnessed across various areas in this field, including pulmonary diagnostics, respiratory care research, critical care or mechanical ventilation, pulmonary rehabilitation, telehealth, public health or health promotion, sleep clinics, home care, smoking or vaping behavior, and neonates and pediatrics. With its multifaceted utility, artificial intelligence can enhance the field of respiratory care, potentially leading to superior health outcomes for individuals under this extensive umbrella.

Conclusions

As artificial intelligence advances, elevating academic standards in the respiratory care profession becomes imperative, allowing practitioners to contribute to research and understand artificial intelligence’s impact on respiratory care. The permanent integration of artificial intelligence into respiratory care creates the need for respiratory therapists to positively influence its progression. By participating in artificial intelligence development, respiratory therapists can augment their clinical capabilities, knowledge, and patient outcomes.
Home Transcutaneous Electrical Stimulation Rehabilitation Program for Patients With Ankylosing Spondylitis: Crossover Trial (Preprint)
Authors: Lin Yu-Chih , Wu Chen-Ching , Sung Wan-Yu , Yen Jeng-Hsien , Lin Yi-Ching
Published: October 2024

BACKGROUND

Maintaining physical function and preserving spinal flexibility have been challenging in managing ankylosing spondylitis (AS). Most rehabilitation programs, including manual therapy, massage, hydrotherapy, and acupuncture, cannot be performed at home. The effect of transcutaneous electrical nerve stimulation (TENS) was validated in treating AS, but no home TENS system has explored its efficacy to date.

OBJECTIVE

This study aims to evaluate the efficacy of a home TENS system with a novel treatment program for patients with AS.

METHODS

The modified WeHeal TS-200 TENS and galvanic response system provided home-based TENS treatment for patients with AS. Patients were divided into a 2-month course group and a 1-month course group. After the first treatment course, patients went through a washout period for the same duration of their treatment course. Participants could decide whether to accept the second course of treatment. The Bath Ankylosing Spondylitis Disease Activity Index (BASDAI), Bath Ankylosing Spondylitis Functional Index (BASFI), Schober test, finger-to-floor flexion test, enthesis score, cytokines, chemokines, inflammatory factors, and immunoglobulins were measured to evaluate its efficacy. The clinical trial protocol (1096607481) received approval from the Ministry of Health and Welfare in Taiwan.

RESULTS

A total of 9 patients (5 in a 2-month course group and 4 in a 1-month course group) completed the first treatment course, and 5 patients (4 in a 2-month course group and 1 in a 1-month course group) completed the sequential treatment course. The weighted results showed that patients reported an improving BASFI score (mean difference –0.9, SD 1.7; P=.03) after treatment. Looking into the trajectories, declined BASFI and BASDAI scores were noticed during treatments; this score increased during the washout period. There were improving trends in the Schober test (mean difference 1.9, SD 4.9; P=.11) and finger-to-floor flexion test (mean difference –0.6, SD 9.5; P=.79), but the results were not statistically significant. The response of cytokines, chemokines, inflammatory factors, and immunoglobulins before and after treatment did not show a consistent trend, and all results were not statistically significant (all P>.05).

CONCLUSIONS

The home TENS device demonstrated a potential role in AS management. It may improve accessibility and adherence for patients with AS and provide remote monitoring for clinicians. Further research can compare the effectiveness of electrotherapy at home or in a medical setting and focus on integrating the home TENS system and exercise program to enhance patients’ physical functions and spinal flexibility.
Interrelationships Among Individual Factors, Family Factors, and Quality of Life in Older Chinese Adults: Cross-Sectional Study Using Structural Equation Modeling (Preprint)
Authors: Wu Yuting , Gong Cong , Pi Lifang , Zheng Meixin , Liu Weifang , Wang Yamei
Published: October 2024

BACKGROUND

China's rapidly aging population necessitates effective strategies for ensuring older adults' quality of life (QOL). While individual factors (IF) and family factors (FF) are known to influence QOL, existing research often examines these factors in isolation or focuses on specific subpopulations, overlooking potential interactions and mediating pathways.

OBJECTIVE

This study aims to examine both direct and indirect pathways connecting IF and FF to older adults’ QOL, focusing on the mediating roles of health risks (HR) and health care service demand (HSD).

METHODS

This study uses structural equation modeling (SEM) to analyze cross-sectional data from 8600 older participants in the 2015 China Health and Retirement Longitudinal Study (CHARLS), a nationally representative study using a multistage probability proportional to size sampling method.

RESULTS

Among the 8600 participants, the majority (5586/8502, 65.7%) were aged 60-70 years, with a near-equal distribution of males and females at around 50%. The average PCS score was 76.77, while the MCS score averaged 59.70. Both IF (β=0.165, P<.001) and FF (β=0.189, P<.001) had a direct positive effect on QOL. Furthermore, the indirect effects of IF (β=0.186, P<.001) and FF (β=0.211, P<.001) through HR and HSD were also significant. In the direct model, IF and FF had a greater impact on MCS (β=0.841) than on PCS (β=0.639). However, after including the 2 mediating factors, HR and HSD, the influence of IF and FF on MCS (β=0.739) became consistent with that on PCS (β=0.728). Subgroup analyses revealed that the direct effect of IF on QOL was significant in the 60-70 age group (β=0.151, P<.001) but not in those over 70 years old (β=0.122, P=.074). Comorbidity status significantly influenced the pathway from HR to HSD, with older adults having 2 or more chronic diseases (β=0.363) showing a greater impact compared to those with fewer than 2 chronic diseases (β=0.358).

CONCLUSIONS

Both IF (education, per capita disposable income, and endowment insurance) and FF (satisfaction with a spouse and children) directly impact the QOL in older people. Meanwhile, IF and FF have equal influence on QOL through the mediating role of HR and HSD. Recognizing the interplay among these factors is crucial for targeted interventions to enhance the well-being of older adults in China.

CLINICALTRIAL
The effectiveness of virtual reality technology interventions on cognitive function, depression, and quality of life in clinical populations: A systematic review and meta-analysis of randomized controlled trials (Preprint)
Authors: Du Qiujing , Wei Yuhan , Liu Changqing , Zhang Qi , Gong Xiaotong , Yang Jiaju , Li Qijie , Li Ka
Published: October 2024

BACKGROUND

Virtual reality technology has garnered extensive utilization within the domain of cognitive rehabilitation and has shown promise in ameliorating mental health conditions and augmenting the quality of life for clinical populations, but the research results are inconsistent, and the overall effectiveness is inconclusive.

OBJECTIVE

We aimed to assess virtual reality interventions' impact on cognitive function, depression, and quality of life in clinical populations.

METHODS

An exhaustive search was systematically performed across multiple databases, including EMBASE, PubMed, Medline, Cochrane Library, and Web of Science, spanning from their commencement until July 2023. The Cochrane tool for evaluating bias risk in randomized controlled trials was employed to appraise the methodological rigor of the studies incorporated in the analysis. Review Manager 5.3 was utilized to conduct the integration of effect sizes. Subgroup analyses were employed to probe potential sources of heterogeneity, while sensitivity analyses were executed to evaluate the robustness of the overall effect.

RESULTS

The review encompassed thirteen randomized controlled trials encompassing a total of 513 participants. The outcomes of the meta-analysis indicated that interventions utilizing virtual reality technology could exhibit a statistically significant enhancement in cognitive function(SMD = 0.61, 95% CI [0.25 ∼0.97], p= 0.0010), but not depression(SMD = -0.04, 95% CI [-0.39 ∼0.31], p = 0.82) and quality of life (SMD = 0.06, 95% CI [−0.21 ∼0.33], p = 0.67) within clinical populations. The sensitivity analysis demonstrated the robustness of the results for all three outcomes.

CONCLUSIONS

Virtual reality technology interventions are innovative strategies to improve nursing clinical practice, which could enhance the cognitive function of clinical populations, but may have no significant effect on their depression and quality of life.

CLINICALTRIAL

PROSPERO CRD42023445000
Implementation and Evaluation of a Sangyan digital health intervention to enhance knowledge related to COVID-19 and other health conditions (Preprint)
Authors: Joshi Ashish , Bhatt Ashruti , Mohan Surapaneni Krishna , Malhotra Gunjan , Oliveira Doilyn , Revathi Saravanavel Kalpana , Grover Ashoo
Published: October 2024

BACKGROUND

The spread of misinformation during the COVID 19 Pandemic has highlighted the importance of evidence-based information. The Sangyan podcast promotes evidence-based knowledge on health-related issues in multiple languages in a simple, cost - effective, and concise manner. This provides individuals to access to the appropriate information in an accessible manner.

OBJECTIVE

The study's goal is to assess user preferences for health information on digital health interventions to address COVID-19 misinformation.

METHODS

The study design was Quasi- experimental study, prior to introducing the Sangyan podcast, participants' socio-demographic information was collected, and health literacy was assessed using the REALM scale. Participants were interviewed after listening to the podcast about its usability, and they completed the System Usability Scale (SUS) and the Client Satisfaction Questionnaire. Data was collected from a total of 500 participants, 250 each from RHTC and PMCH&RI. The participants were over the age of 18 when they were included. Descriptive and bivariate analysis was performed.

RESULTS

Forty-eight percent (n=240) of respondents were from rural areas whereas forty-four percent (n=203) were from urban areas and had never used or heard of podcasts before. The findings revealed that the participant age groups and the overall Score System Usability System (SUS) were significant (p-value <0.05).

CONCLUSIONS

The study reveals that Sangyan Podcast transmits information to diverse individuals as it is multi-lingual and was found useful among individuals.
Comparing AI-Generated and Clinician-Created Personalized Self-Management Guidance for Knee Osteoarthritis Patients: A Blinded Observational Study (Preprint)
Authors: Du Kai , Li Ao , Zuo Qi-Heng , Zhang Chen-Yu , Guo Ren , Chen Ping , Du Wei-Shuai , Li Shu-Ming
Published: October 2024

BACKGROUND

Background: Personalized education is crucial for effective knee osteoarthritis (OA) management, but providing it remains challenging due to imbalanced patient-provider ratio and limited resources. This study explores the potential of GPT-4, a large language model, in generating tailored self-management guidance and compares its performance with physician-provided advice.

OBJECTIVE

Objective：This study aims to evaluate the effectiveness of GPT-4 in generating personalized education materials for patients with knee osteoarthritis (OA) and compare it with experienced clinicians. Specifically, the comparison is made in terms of efficiency, readability, accuracy, personalization, comprehensiveness, and safety. By leveraging patient data from previous trials, it is evaluated whether AI can improve the quality and accuracy of patient education and evaluate its potential in improving patient care and outcomes.

METHODS

Methods: A two-phase, blinded, observational study was conducted using patient data from a previous trial. In phase one, two experienced orthopedic specialists created personalized education materials. In phase two, the same data were input into GPT-4 by a physician to generate content. Materials were evaluated for efficiency (words per minute), readability (Flesch-Kincaid Grade Level, Gunning Fog Index, Coleman-Liau Index, and SMOG Index), accuracy, personality, comprehensiveness, and safety.

RESULTS

Results: GPT-4 demonstrated higher efficiency than clinicians (median 530.03 vs. 37.29 WPM, P < 0.001). GPT-4 content exhibited superior readability on the Flesch-Kincaid grade level, Gunning Fog Index, and SMOG Index (P < 0.001). Expert evaluations revealed that GPT-4 outperformed clinicians in accuracy (5.307 ± 1.731 vs. 4.76 ± 1.098, P = 0.047), personality (54.32 ± 6.212 vs. 33.2 ± 5.395, P < 0.001), comprehensiveness (51.74 ± 6.471 vs. 35.26 ± 6.657, P < 0.001), and safety (median 61 vs. 50, P < 0.001).

CONCLUSIONS

Conclusion: GPT-4 shows promise in generating high-quality, personalized patient education for knee OA, surpassing human experts. This study provides novel evidence for the potential of AI in enabling precise and intelligent patient education. Further research is needed to validate the findings in larger populations and assess the impact on patient outcomes.
Rancang Bangun Sistem Monitoring PLTS Menggunakan Board Sonoff melalui Smartphone Android
Authors: Rangkuti Syahban , Firmansyah Eliyana , Munandar Liman Khoeri
Published: October 2024

Pembangkit Listrik Tenaga Surya merupakan salah satu sumber energi listrik alternatif terbarukan. Pembangkit listrik tenaga surya yang dirancang bangun dilengkapi dengan sistem monitoring dan kendali automatic transfer switch (ATS) dari jarak jauh melalui aplikasi android eWeLink dengan perangkat utama untuk sistem kendalinya menggunakan board Sonoff. Board Sonoff telah dilengkapi fitur untuk kendali jarak jauh yang dapat terintegrasi melalui jaringan internet. Sistem monitoring pembangkit listrik tenaga surya yang akan dibuat terdiri dari monitoring daya, arus, tegangan, dan kalkulasi kWh yang telah digunakan. Sistem monitoring  ini mampu dioperasikan dari jarak jauh melalui perangkat smartphone dengan menggunakan koneksi internet. Pembangkit listrik tenaga surya yang dibuat dilengkapi perangkat pelacak matahari (solar tracker)  dengan konsep single axis yang dapat mengarahkan panel surya secara otomatis mengikuti pergerakan matahari dari timur ke barat dengan tujuan agar panel surya selalu tegak lurus dengan matahari sehingga daya listrik yang dihasilkan oleh panel surya (solar Panel)  lebih maksimal. Sistem ini menggunakan panel surya 10WP, solar charger controller (SCC), baterai, inverter, Sonoff Pow R2, relay, time delay relay (TDR), MCB 1 Fasa, modul solar tracker, dan aktuator linear. Secara keseluruhan sistem monitoring yang dibuat dapat membantu memudahkan pengguna saat melakukan monitoring pembangkit listrik tenaga surya dari jarak jauh, serta dapat memaksimalkan perolehan daya panel surya dengan penggunaan solar tracker. Pada baterai 12V 16Ah dengan DoD 70% serta rugi daya sebesar 20% maka dapat waktu yang dibutuhkan untuk mengisi baterai adalah sekitar 6,8 Jam. Semakin tinggi intensitas cahaya maka semakin besar daya listrik yang dihasilkan oleh solar panel.
Metrics to Increase Data Usage Understanding and Transparency
Authors: Esteva Maria , Freeze Joshua , Carson James , Jansen Craig
Published: October 2024

Data metrics are essential to assess the impact of data repositories' holdings and to understand the research practices of the community that they serve. These metrics are useful for reporting to funders, to inform community engagement strategies, and to direct and sustain repository services. In turn, communicating these metrics to the user community conveys transparency and elicits their trust in data sharing. However, because data metrics are time-sensitive and context-dependent, tracking, interpreting, and communicating them is challenging. In this work we introduce data usage analyses including benchmarking and grouping, developed to better assess the impact of the DesignSafe Data Depot, a natural hazards data repository. Make Data Count compliant metrics are analysed in relation to research methods, sub-disciplines, natural hazard types, and time, to learn what data is being used, what influences data usage, and to establish realistic usage expectations. Results are interpreted in relation to the research and publication practices of the community and to natural hazard events. In addition, we introduce strategies to clearly communicate dataset metrics to users.
Direito da pessoa imputada ao anonimato digital
Authors: Sarkis Jamilla Monteiro
Published: October 2024

Based on the need to expand, in the virtual age, the list of fundamental rights available to the accused person in the same proportion that procedural practices that use technological resources are extended to their disadvantage, the article proposes to answer the following question: would the accused person have the right to digital anonymity? Without disregarding the need for state intervention when used in the practice of criminal offences, the paper methodologically proposes an interdisciplinary bibliographical review to conceptualize anti-forensic techniques as important tools for protecting the right of the accused person not to produce digital evidence against them, highlighting anonymity as one of its most effective tools and defending the relevance of its legal protection in the cyber age.
Variações na aplicação dos acordos de não persecução penal em Maracanaú/CE: um estudo de caso sobre a dosimetria da pena de prestação pecuniária
Authors: Santiago Nestor Eduardo Araruna , Soares Filho Sidney , Rocha Leitão Iuri
Published: October 2024

This work examines the application of the Criminal Non-Prosecution Agreements (ANPPs) carried out in the Municipality of Maracanaú between 01/01/2022 and 12/31/2022, aiming to identify whether there is equality in the application of the monetary benefit sanction. The impact of Law no. 13,964/19, which introduced the Criminal Non-Persecution Agreement (ANPP) and allowed monetary benefits in criminal agreements, allowing discretion in negotiations, but without establishing fixed criteria for its application. The empirical research was conducted in 2022 at the criminal prosecutor's offices in Maracanaú-CE and involved data collection and subsequent comparison and analysis. The results indicate discrepancies in the use of ANPPs between ministerial units and, in certain cases, significant differences in the values ​​stipulated in the pecuniary benefit, raising questions about compliance with the principle of equality. A concrete dysfunctionality of negotiated criminal justice and, more broadly, of the Brazilian criminal prosecution system was revealed.