bluuebunny/crossref_metadata_2025 huggingface dataset:
The Relationships among Tree Mixture, Management Type, Stand Density and Diameter Increment in Kazdağı Fir (Abies nordmanniana subsp. equi-trojani [Asch. & Sint. ex Boiss] Coode & Cullen) Forests
Authors: Ozcelik Gokhan , Kara Ferhat
Published: November 2024

Tree mixture may increase stand productivity while forest tree density mostly negatively influence the tree growth. However, several research have indicated that the knowledge on the corelation between tree mixture and stand productivity is still limited. In this study, the relationships among tree mixture, stand type (i.e., even-aged versus uneven-aged), density and diameter increment of Kazdağı fir (Abies nordmanniana subsp. equi-trojani [Asch. & Sint. ex Boiss] Coode & Cullen) were examined. The research was conducted within the Ayancık Forest Management Directorate, Sinop Regional Directorate of Forestry. Four different stands were selected; a) uneven-aged fir stand, b) even-aged fir stand, c) uneven-aged mixed fir-beech stand, and d) even-aged mixed fir-beech stand. Five-year diameter increment in these four different stand types was determined and compared. Random effects regression analysis was utilized to examine the influence of the mixture and tree density on the diameter increment. Statistical relationships were found among tree mixture, stand density and the diameter increment (p<0.05). Moreover, diameter increment varied among the stand types
How Does Lavender Affect Lactic Acid Levels Increased With Exercise?
Authors: Naldan Hülya , Naldan Muhammet Emin , Taş Nurmuhammet , Akbulut Ömer
Published: November 2024

This study examines the effects of lavender plants on fatigue levels and performance. The research started by randomly dividing 60 participants aged 18-25 into study and control groups. The Wingate Anaerobic Test was applied to the participants and the study group was administered a sauna filled with lavender. Data were collected and analyzed by measuring blood lactate levels. In all physiological characteristics examined, the differences between the control group and the study group before the study were found to be statistically insignificant. In both the study group and the control group, except for diastolic blood pressure, changes in all physiological characteristics and blood values according to measurement times (0, 1, 5 and 15 min) were found to be very significant (p<0.001). When the control group and the study group were compared, significant differences were found between pulse values in the first minute (p=0.023), saturation in the fifth minute (p=0.020) and lactate averages (p=0.023). In particular, it was observed that the lactate average in the fifth minute was 1.64 units lower in the study group than in the control group. Blood sugar levels decreased gradually in both groups compared to the initial value. This feature decreased by 17.45 units in the control group and 9.30 units in the study group at minute 1 compared to the initial value. It can be said that the calmness provided by the lavender scent causes less blood sugar drops. Findings support lavender's fatigue-reducing effects and suggest it may reduce painful conditions. Our study shows that these effects occur because lavender reduces lactate levels. Additionally studies in the literature confirm these results. The mechanism of lavender explains that inhalation affects the limbic system and hypothalamus causing relaxation, decreased anxiety, increased attention and concentration. It has been emphasized that lavender inhalation is a safe option. The study states that the results of a more comprehensive study that includes a larger sample and gender differences are needed. However research points out the difficulty of finding sufficient participants. This study provides an essential contribution to the potential health benefits of lavender.
Green Synthesis of Smart Hydrogels via Radiation Crosslinking of Sodium Alginate and Citric Acid for pH-Sensitive Doxycycline Hyclate Release
Authors: Sütekin Semiha Duygu
Published: November 2024

Doxycycline hyclate (DH) is a second-generation tetracycline antibiotic with lower toxicity than its predecessors, used for bacterial infections and topically for mucosal and diabetic ulcers. Healthy skin's pH is mildly acidic (4.0-6.0), regulating bacterial flora and preventing infections. Wounds disrupt this pH, revealing the tissue's neutral pH of 7.4, necessitating pH-sensitive controlled drug release for effective chronic wound treatment. This study explores polysaccharide-based hydrogels synthesized by crosslinking sodium alginate/citric acid (NaAlg/CA) solutions using gamma radiation with varying citric acid concentrations for pH-sensitive DH release. The citric acid-modified polysaccharide hydrogels were created using a green method, free of additional chemicals. Citric acid significantly influenced swelling, critical for drug loading and release, with the highest swelling capacity (3500% mass) observed at a 5:1 NaAlg/CA ratio. Hydrogels were tested for pH-dependent swelling and DH drug release profiles at pH 5.5, 7.4, and 9.0. The results indicate that at pH 7.4, which replicates the pH of chronic wounds, the release of DH showed a prolonged profile up to 40 hours, distinct from the results at pH 5.5 and 9.0. These results highlight the capabilities of NaAlg/CA hydrogels created through gamma radiation, combining the biocompatibility and low toxicity of sodium alginate/citric acid, for efficient and sustainable drug delivery, especially valuable in acute wound care where pH-specific therapeutic effectiveness is essential.
Evaluation of the drinking water parameters in primary and secondary schools located in the Gaziantep Province Center
Authors: Petek Osman , Aydın Neriman
Published: November 2024

This cross-sectional study aimed to assess the drinking water parameters in primary and secondary schools. A questionnaire encompassing the schools’ general characteristics and information about drinking water was administered to school administrators. Drinking water samples were taken from 60 schools to evaluate drinking water parameters. The data were analyzed using Chi-Square, Mann–Whitney U, and Kruskall–Wallis tests, T-test, and SPSS 22.0 software. Non-compliance with national legislation was observed in 16.7% of schools during drinking water analysis. The microbiological parameters exceeded the threshold values in 90% of the schools where the analysis results of the drinking water were deemed inadequate. The analysis yielded no discernible variations based on school district or type. Mains water was the primary drinking water source in 91.7% of schools. The rate was lower in rural schools compared to urban schools, with a difference of 85 and 95%, respectively. It was found that 41.7% of schools lacked canteens or the sale of packaged water. Consequently, the availability of tap water in schools falls short of the desired standard. It is imperative to investigate the factors leading to microbiological contamination in school drinking water and formulate short-, medium-, and long-term strategies to enhance its safety.
Short-term water demand prediction using stacking regression–based machine learning
Authors: Mohamed Hussain K. , Sivakumaran N. , Radhakrishnan T. K. , Swaminathan G. , Sankaranarayanan S.
Published: November 2024

Forecasting of water demand and equitable allocation of local water resources are used to reduce and eliminate water shortages and waste. The key emphasis of this research article is to estimate water demand using the prediction model for the Peroorkada urban water distribution network. The characteristics, such as head, pressure, and base demand, related to the water demand were the features of the prediction model. The prediction model has been developed using python. The water distribution network consists of 99 nodes. The demand graph for a time interval of 6 h has been plotted and predicted for all the nodes, and 24-h interval demand has been plotted for vulnerable nodes, which were determined by the sensor placement toolkit. This study included 13 machine learning algorithms, including three hybrid/stacked regression techniques. The least absolute shrinkage and selection operator-based stacking regressor model performs the best at demand prediction. Single prediction models were outperformed by stacking regressor models.
Modelling and set-point definition for the development of a joint control system of two interconnected wastewater treatment plants and its application in practice
Authors: Schütz Jan Tobias , Kleyböcker Anne , Larsen Sille Bendix , Kristensen Malene , Remy Christian , Miehe Ulf
Published: November 2024

The use of activated sludge models (ASMs) is a common way in the field of wastewater engineering in terms of plant design, development, optimization, and testing of stand-alone treatment plants. The focus of this study was the development of a joint control system (JCS) for a municipal wastewater treatment plant (mWWTP) and an upstream industrial wastewater treatment plant (iWWTP) to create synergies for saving aeration energy. Therefore, an ASM3 + BioP model of the mWWTP was developed to test different scenarios and to find the best set-points for the novel JCS. A predictive equation for the total nitrogen load (TN) coming from the iWWTP was developed based on real-time data. The predictive TN equation together with an optimized aeration strategy, based on the modelling results, was implemented as JCS. First results of the implementation of the JCS in the real environment showed an increase in energy efficiency for TN removal.
Recent Trends in Development of Novel Therapeutics for Modulation of 14-3-3 Protein-Protein Interactions in Diseases
Authors: Nazir Arshia
Published: November 2024

14-3-3s constitute a group of proteins belonging to the phosphoserine/phosphothreonine
family that are involved in the regulation of several physiological pathways by interacting
with several client proteins. All the eukaryotic cells are known to possess 14-3-3 isoforms. In addition,
14-3-3s isolated from different eukaryotic cells share high sequence homology with each
other. Seven isoforms (β, γ, ε, η, ζ, σ, and τ/θ) have been yet identified in mammals. These proteins
participate in several physiological processes by either stimulating or interfering with the enzymatic
activities of binding partners. These proteins take part in several human diseases upon dysregulation
which include cancer and neurodegenerative disorders. Recently, a number of evidences
suggest that the interaction of 14-3-3s with either oncogenic or pro-apoptotic proteins can
lead to cancer development in animals. In the case of neurodegenerative disorders, 14-3-3s interact
with Lewy bodies and neurofibrillary tangles in Parkinson’s and Alzheimer’s diseases, respectively.
The current review focuses on strategies to regulate 14-3-3s’ proteins in diseases. Potential
strategies to regulate 14-3-3 interactions in disease conditions include the use of small interfering
RNAs (siRNA), microRNA (miRNA), and modifications of 14-3-3s or their client proteins. In addition,
some peptides or chemicals can also serve as potential inhibitors of 14-3-3. However, optimization
of these therapeutic strategies is required for their practical implementations.
Overexpression of HIF2α Enhances the Angiogenesis-Promoting Effect of hUC-MSC-Derived Extracellular Vesicles by Stimulating miR-146a
Authors: Chen Yihui , Hong Shichai , Wang Zhefeng , Hong Xiang , Chen Gang , Huang Yulong , Lin Yue , Xie Xinsheng , Lin Chenwei , Lu Weifeng
Published: November 2024

Objective:

This study aimed to explore whether excessive HIF2α can amplify the impact
of human Umbilical Cord Mesenchymal Stem Cell-derived Extracellular Vesicles (hUC-MSC-
EVs) on endothelial cells.

Methods:

In this study, we created HIF2α-overexpressing hUC-MSC-EVs and compared their
pro-angiogenic effects with control EVs on Human Umbilical Vein Endothelial Cells (HUVECs).
MTT assay and Edu staining were used to detect the viability and proliferation ability of HUVECs,
and Transwell and tube formation assays were used to detect cell migration and tube formation
ability. qPCR assay was used to detect the expression of cellular angiogenic markers. Subsequently,
miRNAs that might be regulated by HIF2α were predicted by bioinformatics analysis,
and qPCR was used to detect the relative expression of miRNAs in HUVECs treated with hUC-MSC-
EV, which over-expresses HIF2α. Subsequently, miR-146a inhibitors were used to investigate
the role of miR-146a in mediating the pro-angiogenic effect of HIF2α on HUVECs by detecting
cell viability, proliferation, migration, tube-forming ability, and expression of angiogenic markers.
Finally, AKT/ERK phosphorylation and Spred1 expression were detected using Western blotting.

Results:

Our findings have indicated that overexpression of HIF2α significantly enhances the ability
of hUC-MSC-EVs to stimulate proliferation, migration, and tube formation in HUVECs, as demonstrated
by MTT/Edu staining, Transwell assay, and tube formation assay results, respectively.
Mechanistically, excessive HIF2α has been found to induce the expression of miR-146a in HUVECs
and the overexpression of a miR-146a inhibitor to negate the influence of excessive HIF2α
on hUC-MSC-EV-induced activity in HUVECs.

Conclusion:

The overexpression of HIF2α is an effective strategy for enhancing the pro-angiogenic
function of hUC-MSC-EVs.
Thrombectomy Failure and Associated Factors for Large-Vessel
Occlusion Stroke
Authors: Rilianto Beny , Kurniawan Ricky Gusanto , Prasetyo Bambang Tri , Rajab Nurfadilah M. , Arham Abrar
Published: November 2024

Background:

Ischemic stroke due to Large Vessel Occlusion (LVO) represents a critical
and time-sensitive neurological emergency. Advancements in imaging technology and endovascular
therapies have transformed the management of LVO. Nonetheless, thrombectomy failure
diminishes the chances of patients achieving a favorable clinical outcome.

Objective:

We aimed to determine the factors influencing recanalization failure in order to optimize
thrombectomy therapy along with enhancing patient outcomes.

Methods:

A retrospective analysis was performed employing consecutive LVO patients who underwent
Endovascular Thrombectomy (EVT) in a tertiary comprehensive stroke center between
January 2020 and June 2024. Recanalization failure (mTICI 0-2a) following thrombectomy was assessed
using the Kolmogorov-Smirnov test, χ2 test, Fisher’s exact test, and multivariable logistic
regression to identify the related factors.

Results:

A total of 82 EVT patients were analyzed. The mean age was 58.20 years and 70.73% of
the patients were male. The rate of recanalization failure was 61%. Multivariable logistic regression
analysis with age-sex adjusted factors has revealed hypertension [aOR: 5.31 (95% CI:
1.23-22.77); p =0.025] and no IVT [aOR: 2.75 (95% CI: 1.06-7.14); p =0.037] to be independent
predictors of recanalization failure in this study.

Conclusion:

Hypertension and the absence of prior intravenous thrombolysis have been found to
be significant contributing factors to the high rate of thrombectomy failure in large-vessel occlusion.
Transforming Alzheimer’s Digital Caregiving through Large Language Models
Authors: Kim Sujin , Han Dong Y. , Bae Jihye
Published: November 2024

Introduction/Objective:

Alzheimer's Disease and Related Dementias (AD/ADRD) present
significant caregiving challenges, with increasing burdens on informal caregivers. This study
examines the potential of AI-driven Large Language Models (LLMs) in developing digital caregiving
strategies for AD/ADRD. The objectives include analyzing existing caregiving education materials
(CEMs) and mobile application descriptions (MADs) and aligning key caregiving tasks with
digital functions across different stages of disease progression.

Methods:

We analyzed 38 CEMs from the National Library of Medicine’s MedlinePlus, along
with associated hyperlinked web resources, and 57 MADs focused on AD digital caregiving. Using
ChatGPT 3.5, essential caregiving tasks were extracted and matched with digital functionalities
suitable for each stage of AD progression, while also highlighting digital literacy requirements
for caregivers.

Results:

The analysis categorizes AD caregiving into 4 stages-Pre-Clinical, Mild, Moderate, and
Severe-identifying key tasks, such as behavior monitoring, daily assistance, direct supervision,
and ensuring a safe environment. These tasks were supported by digital aids, including memory-
enhancing apps, Global Positioning System (GPS) tracking, voice-controlled devices, and advanced
GPS tracking for comprehensive care. Additionally, 6 essential digital literacy skills for
AD/ADRD caregiving were identified: basic digital skills, communication, information management,
safety and privacy, healthcare knowledge, and caregiver coordination, highlighting the need
for tailored training.

Conclusion:

The findings advocate for an LLM-driven strategy in designing digital caregiving interventions,
particularly emphasizing a novel paradigm in AD/ADRD support, offering adaptive
assistance that evolves with caregivers' needs, thereby enhancing their shared decision-making
and patient care capabilities.
Impact of the COVID-19 Pandemic on People with Dementia and their Caregivers: A Multiphase Observational Study from India
Authors: Arshad Faheem , Hurzuk Saadiya , Tiwari Megha , Varghese Feba , Hoskeri Rakshith Maneshwar , Paplikar Avanthi , Goyal Sheetal , Dhiren Shah Rutul , Ganeshbhai Patel Vishal , Ansari Mohammed Farhan , Komaravolu Shashidhar , Kammammettu Chandrashekar , Thomas Priya Treesa , Rao Girish Nagaraja , Alladi Suvarna
Published: November 2024

Introduction:

The COVID-19 pandemic has had multifaceted and enduring impacts on
people with dementia and their caregivers; however, our understanding of the long-term outcomes
remains limited. We aimed to explore the long-term effects of the COVID-19 pandemic on cognitive
symptoms and vaccination rates in people living with dementia.

Methods:

This study was conducted as a part of a longitudinal study design in two specialized hospitals
in South India. In this study, patients with dementia and their caregivers assessed in earlier
phases (‘period of lockdown with phased relaxations - phase-I’ and ‘cluster of cases transmission
phase - phase-II’) were telephonically interviewed. We adopted a quantitative approach to understand
disease progression during the three-year course of the pandemic. Changes in cognition and
disease severity were measured using the Clinical Dementia Rating (CDR) scale. In brief, semistructured
interviews were carried out with caregivers of people with dementia to gain insights into
vaccination rates. Data obtained from the current study (phase III) were compared against phase
I data, which served as the baseline. Among the 72 participants contacted in the current phase, 59
(81·9%) could be reevaluated for dementia severity and vaccination status, whereas 13 (18·0%)
had died. Among the 59 participants, 33 (55·9%) had severe dementia (CDR 3). This is in contrast
to phases I and II, when 17·6% and 19·2% of the participants, respectively, were classified as
CDR 3.

Results:

A significant difference in dementia severity between the two phases (phases I and III)
was observed. In addition, we observed vaccination hesitancy among caregivers of patients with
dementia. This study would provide valuable insights into the long-term impact of the COVID-19
pandemic on the cognitive outcomes and vaccination status of patients with dementia.

Conclusion:

This overall longitudinal study has compared dementia severity between different
phases throughout the pandemic, with implications for future studies to tailor home-based support
and healthcare interventions in order to meet these evolving needs.
Antivirals to Treat COVID-19
Authors: Bhattacharyya Sayan
Published: November 2024

Introduction: COVID -19, caused by the novel coronavirus or SARS-CoV2,
has claimed thousands of lives across the world as well as in India as of now. There are
many antivirals available to treat COVID-19 at present. Some of them are safe and
effective, while many others have been banned by the World Health Organization.
Hence, it is very important for clinicians and nurses to know accurately and precisely
about the safe and effective antivirals to treat COVID-19. Materials and methods: The
purpose of this chapter is to address the issues with available antivirals, their modes of
action, adverse effects, and drug interactions. Literature search has been carried out
meticulously. Conclusion: Many options are available for treating COVID-19, but
treatment needs to be tailored according to the situation.
Ribosomally Synthesized Bacteriocins as Potent Anti-infective Agents, Their Medical and Pharmaceutical Applications
Authors: Daba Ghoson M. , Elnahas Marwa O. , Elkhateeb Waill A.
Published: November 2024

The development of multidrug-resistant bacteria (MDRB) and the
emergence of new lethal diseases have raised the need for potent anti-infective agents
with different killing action mechanisms that contribute to treating and/or supporting
the currently used drugs. For this purpose, bacteriocins are considered excellent
candidates with promising potential. Bacteriocins are ribosomally synthesized
antimicrobial peptides that are produced by many bacterial genera. They are
characterized by high thermal stability, being active over a wide pH range, and having
specificity against selected bacterial strains by employing specific receptors on their
cell membrane, which encourages bacteriocins to use in clinical applications as support
and/or alternatives currently used antibiotics. Interestingly, bacteriocins have many
advantages over antibiotics, such as the relative difficulty of developing resistance
compared to broad-spectrum antibiotics. Moreover, due to their simple biosynthetic
mechanisms, bacteriocins can be easily bioengineered, which improves their activity or
specificity against selected microorganisms. Additionally, bacteriocins originating from
lactic acid bacteria have the extra safety advantage because many LAB and their
products are classified by the American Food and Drug Administration (FDA) to be
generally recognized as safe (GRAS). Bacteriocins have promising pharmaceutical
potentials as anti-infective agents, anti-MDRB agents, antileishmanial, and antiviral
agents. Moreover, bacteriocins have been used to treat many ulcers, tumors, and
cancers. In this chapter, we highlight the importance of bacteriocins as anti-infective
agents, describing their common action mechanisms and recent clinical and
therapeutical applications of bacteriocins. Finally, prospects in this field are discussed
to discover and develop more diverse and efficient bacteriocins with potent antiinfective activities.
Epidemiology of Coronavirus
Authors: Badar Mohammad Sufian , Hafeez Ibtesaam , Nawaz Imtshan , Badar Mohammad Rehan , Saba Sadia
Published: November 2024

More than 600 million people have contracted the COVID-19, and a
substantial level of fatalities have occurred on a global scale. The pandemic has grown
to pose a serious risk to humankind. Gaining knowledge about the dynamics of virus
transmission and clinical manifestation, as well as possible causes of severe illness and
mortality, requires an understanding of coronavirus epidemiology. To create global
health policies that work, it is imperative to understand these elements. It is believed
that bats are the original host of the coronavirus that causes severe acute respiratory
syndrome. The most prevalent means of transmission is through airborne droplets.
Other potential routes of infection include the fecal-oral pathway, sexual transmission,
the vertical chain, and so forth. The incubation period of COVID-19 is two to fourteen
days, during which asymptomatic carriers may spread the virus to other people. From
mild symptoms like fever, coughing, and fatigue to life-threatening illness necessitating
hospitalization, COVID-19 respiratory illness can range widely in severity. The
impacts of the disease are more likely to affect the elderly and people with underlying
medical disorders including Type 2 diabetes, obesity, or chronic heart disease. New
strains of SARS-CoV-2 have evolved as the pandemic has expanded, wreaking havoc
on countries with weak healthcare systems and low incomes. Social isolation, the use
of masks, and vaccination campaigns have all helped reduce the spread of the virus.
Challenges Posed by COVID-19
Authors: Badar Mohammad Sufian , Ali Waseem , Ansari Onaiza , Malik Asrar Ahmad , Sheikh Javaid Ahmad , Mursaleen Anam
Published: November 2024

SARS-CoV-2, the viral inciting agent of one of the deadliest pulmonary
infections known as novel Coronavirus Disease (COVID-19) has resulted in millions of
deaths. With the first incidence being reported in the city of Wuhan, China, in
December 2019 and dealing with a pathogen capable of quick as well as easy
transmissibility, undefined symptoms, non-availability of therapeutics and
acclimatization/adaptation to COVID-19 scenario can be acknowledged as the phase I
challenges faced by the world. The novel and enduring COVID-19 pandemic that the
world has been witnessing for the past few years has advanced to the huge and
exhaustive phase II challenges that encompass the implementation of one of the longest
complete global shutdowns, unusual practice of work-from-home practices, immense
pressure on the healthcare sector, suspension of daily activities, majorly closing of
schools and colleges, no social gatherings, the urgency to develop anti-COVID
therapeutic/vaccine, lack of awareness/negligence, antimicrobial resistance and
emergence of variants that fuelled the spread of the infection. Despite the combined
efforts that might have flattened the curve of the infection, it remains a major trigger
for rolling out post-COVID challenges, being a serious concern for every facet of the
society that includes continuous deterioration of mental health, financial instability, and
fear of death. This chapter focuses on addressing the challenges and threats that
prevailed during and post-COVID period. Additionally, it also summarizes strategies to
combat the setbacks posed by SARS-CoV-2 infection.
AI-Based Diagnosis of Novel Coronavirus Using Radiograph Images
Authors: Badar Mohammad Sufian , Idris Aisha , Khan Areeba , Mustafa Md , Asaf Farheen
Published: November 2024

The therapeutic value of artificial intelligence (ML) in the diagnosis of viral
illnesses has been illustrated by the outbreak of COVID-19. This chapter digs into the
modern uses of Artificial Intelligence and Machine Learning (ML) algorithms for
COVID-19 diagnosis, with a focus on chest imaging procedures like as CT and X-rays.
Additionally, we explored ML's strengths, such as its capacity to analyze enormous
datasets and detect patterns in medical imagery. But there are still issues to deal with,
like the scarcity of data, privacy issues, and machine learning's incapacity to evaluate
the severity of health conditions. However, several machine learning methods, such as
decision trees, random forests, and convolutional neural networks, are reviewed in this
research concerning COVID-19 diagnosis. Subsequently, we highlight the efficacy of
several models in COVID-19 screening, such as XGBoost and Truncated Inception
Net. Moreover, the chapter discusses potential strategies for machine learning in
COVID-19 diagnosis, emphasizing the crucial role of collaboration among data
scientists and healthcare experts. It is imperative to confront data bias and incorporate
more comprehensive patient data than just chest imaging. All things considered,
machine learning presents a potential pathway toward quick and precise COVID-19
diagnosis; nonetheless, conquering existing obstacles is necessary for ML to be widely
used in healthcare institutions.
Dye Decolorization by Immobilized Recombinant rDyP and Turnover Capacity of rDyP
Authors: Shoda Makoto
Published: November 2024

For an efficient application of the soluble recombinant enzyme of rDyP,
immobilization of the enzyme was caried out to enhance and stabilize catalytic
efficiency of rDyP. Although several conventional immobilization methods have been
attempted for rDyP, no methods have been successful. Therefore, new catalysts
developed for exhaust gas removal were employed. They were silica-based
mesocellular foams and two silica-based porous materials, FSM-16 and AISBA-15,
which were chemically synthesized. Immobilization of rDyP on them was carried out
and immobilization efficiency was assessed. The overall efficiency was defined as
adsorption efficiency x activity efficiency to find the maximum efficiency. The
efficiency of rDyP immobilized on FSM-16 and AISBA-15 was maximum at pH 5 and
pH 4, respectively. FSM-16 showed advantages over AISBA-15 in terms of stronger
affinity for rDyP due to its anionic surface and much lower leaching of rDyP from
FSM-16. When the rDyP immobilized on FSM-16, an anthraquinone dye, RBBR, was
decolorized in repeated-batch mode, and eight sequential batches were possible, while
rDyP immobilized on AISBA-15 enabled only two batches.
For evaluation of the practical potential of rDyP, the turnover capacity of rDyP was
introduced. In order to minimize H2O2
inactivation for rDyP activity, four H2O2
supply
methods were attempted and the turnover capacity of each method was compared. The
continuous fed-batch supply of H2O2
and the stepwise fed-batch supply of the dye gave
the maximum turnover capacity of 20.4. At this turnover capacity, one liter of crude
rDyP solution containing 5,000 U could decolorize up to 102 g dye in 10h.
The impact of digital transformation on the accounting system effectiveness
Authors:   Applied College, Imam Mohammad Ibn Saud Islamic University, Riyadh, Saudi Arabia, Alotaibi Khaleed Omair
Published: November 2024

In today's rapidly changing digital landscape, most businesses in various industries have embraced digital transformation to improve their operations and efficiency. The accounting industry also has opportunities to enhance the effectiveness of its systems with new technologies. This study introduces a new framework called the Digital Transformation Framework for Accounting System Effectiveness (DTFASE), developed using design science research. The framework consists of five main stages: assessment and planning, implementation and integration, operationalization and monitoring, continuous improvement, and evaluation and reporting. Its purpose is to guide organizations in systematically transforming their accounting systems to boost overall effectiveness. By using this framework, organizations can fully leverage digital technologies to optimize their accounting processes.
Digital Teaching and Learning Media for Nursing and Health Care Courses in Germany: Protocol for a Scoping Review
Authors: Vogel Jann Niklas , Letzin Jaqueline , Schmidt Stefan
Published: November 2024

Background

In Germany, digital transformation and legal regulations are leading to the need to integrate digital technologies into the nursing profession. In addition, to nursing practice, they are also being incorporated into nursing training. Despite comprehensive regulations regarding the use of digital teaching and learning media in nursing education, their specific applicability and implementation vary.

Objective

This study aims to map evidence and identify the main concepts, theories, sources, and knowledge gaps in the use of digital teaching and learning formats in nursing and health care education in Germany.

Methods

The study is planned as a scoping review. The reporting of the study is based on the PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) 2020 guidelines. The sources of information for the review include six bibliographic databases (MEDLINE via PubMed, Cochrane Library, Web of Science Core Collection, ERIC, PROSPERO, and APA PsycInfo). The search results will be presented in accordance with the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) checklist. The eligibility of studies is based on the population, concept, and context criteria: (1) learners of nursing and health care professions, (2) digital teaching and learning formats, and (3) forms of implementation in Germany since 2007.

Results

The literature search is planned for January 2025. The selection of titles, the coding of the data, and the data analysis are expected to be completed by March 2025.

Conclusions

In Germany, there is a growing interest in integrating digital teaching and learning formats into nursing and health care education. Our scoping review will map applications of digital teaching and learning media in the education of nursing and health care professions in Germany. In this way, the scoping review provides relevant impulses for fields of application and design aspects of digital teaching or learning media for nursing and health care education.

International Registered Report Identifier (IRRID)

PRR1-10.2196/60427
Improving Self-Efficacy, Quality of Life, and Glycemic Control in Adolescents With Type 1 Diabetes: Randomized Controlled Trial for the Evaluation of the Family-Centered Empowerment Model
Authors: Alzawahreh Salah , Ozturk Candan
Published: November 2024

Background

Poor glycemic management in adolescents with type 1 diabetes mellitus (T1DM) increases complications. Enhanced control is associated with other factors, such as cultural, socioeconomic, and health care system disparities specific to the Middle East, which can greatly influence individuals’ ability to get and use health care services as well as their reaction to treatment approaches.

Objective

This study aims to evaluate the impact of the family-centered empowerment model on Jordanian adolescents with T1DM, focusing on their glycosylated hemoglobin levels, self-efficacy, and quality of life (QOL).

Methods

A randomized controlled trial involved 68 adolescents with T1DM visiting Jordanian Royal Medical Services’ clinics. Two sets of participant groups were created: control (n=34) and intervention (n=34). Participants were randomly assigned to either the intervention group, receiving the family-centered empowerment model intervention, or the control group, receiving standard care. Data were collected through face-to-face interviews and medical records.

Results

From April to October 2023, a total of 68 adolescents with T1DM participated in the study at the Jordanian Royal Medical Services. QOL had significant improvement among 13 (38%) of the 34 participants in the intervention group, and the program significantly improved moderate self-efficacy levels in 12 (35%) patients (P<.001). In addition, the average glycosylated hemoglobin levels dropped from 11.25% to 10.23% (P<.001). Additionally, improvements were seen in stress management, communication, and treatment adherence, with a substantial decrease in treatment obstacles. The intervention was successful in improving both clinical and psychosocial outcomes, as evidenced by the fact that the control group showed no noticeable improvements in these parameters.

Conclusions

The study suggests that patients with T1DM should receive continuous care education sessions, including self-care training, to improve their health. Nurses should also incorporate this training into treatment plans and educational programs for adolescents to enhance their QOL.

Trial Registration

ClinicalTrials.gov NCT06694467; https://clinicaltrials.gov/study/NCT06694467
Continuous Glucose Monitoring Among Patients With Type 1 Diabetes in Rwanda (CAPT1D) Phase I: Prospective Observational Feasibility Study
Authors: Baker Jason , Cappon Giacomo , Habineza Jean Claude , Basch Corey H , Mey Steven , Malkin-Washeim Diana L , Schuetz Christian , Simon Pierre Niyonsenga , Uwingabire Etienne , Mukamazimpaka Alvera , Mbonyi Paul , Narayanan Sandhya
Published: November 2024

Background

The development of minimally invasive continuous glucose monitoring systems (CGMs) has transformed diabetes management. CGMs have shown clinical significance by improving time in the euglycemic range, decreasing rates of hypoglycemia, and improving hemoglobin A1c (HbA1c). In Rwanda, CGMs are currently not routinely used, and no clinical studies of CGM use were identified in the literature.

Objective

This study aims to determine the impact and feasibility of real-time CGM use among people living with type 1 diabetes (T1D) in Rwanda through assessment of sensor use, time in range, rates of hypoglycemia and hyperglycemia, HbA1c, and rates of diabetes-related hospitalizations over time.

Methods

The Continuous Glucose Monitoring Among Patients with Type 1 Diabetes in Rwanda (CAPT1D) study is a single-arm, prospective observational study conducted at the Rwandan Diabetes Association clinic in Kigali, Rwanda, aiming to assess the impact and feasibility of CGM use in Rwanda. A cohort of 50 participants diagnosed with T1D were enrolled. Participants were at least 21 years old, undergoing multiple daily insulin therapy, and not currently pregnant. Phase I of the study was conducted over 12 months, using the Dexcom G6 CGM. Phase II and Phase III extended CGM use for an additional 6 months respectively, using the next-generation Dexcom G7 CGM. Here, we report the quantitative results of the Phase I study.

Results

Participants used the sensor for >80% of the time throughout the study period. A significant increase in time in range was observed within 3 months and sustained over 12 months. HbA1c decreased significantly in 3 months and stayed lower throughout the 12-month period. Mean HbA1c levels decreased by 2.8% at 6 months (P<.001) and 3.2% at 12 months (P<.001). A total of 12 diabetes-related hospitalizations were reported during the study period. No cases of diabetic ketoacidosis or episodes of severe hypoglycemia occurred.

Conclusions

Significant and meaningful improvements in key glycemic indices indicate the potential feasibility and impact of a CGM among people living with T1D in Rwanda. Future studies could be designed to include pre- and postintervention analysis to determine the effectiveness in terms of complications and costs.
Applications of Augmented Reality for Prehospital Emergency Care: Systematic Review of Randomized Controlled Trials
Authors: Harari Rayan E , Schulwolf Sara L , Borges Paulo , Salmani Hamid , Hosseini Farhang , Bailey Shannon K T , Quach Brian , Nohelty Eric , Park Sandra , Verma Yash , Goralnick Eric , Goldberg Scott A , Shokoohi Hamid , Dias Roger D , Eyre Andrew
Published: November 2024

Background

Delivering high-quality prehospital emergency care remains challenging, especially in resource-limited settings where real-time clinical decision support is limited. Augmented reality (AR) has emerged as a promising health care technology, offering potential solutions to enhance decision-making, care processes, and emergency medical service (EMS) training.

Objective

This systematic review assesses the effectiveness of AR in improving clinical decision-making, care delivery, and educational outcomes for EMS providers.

Methods

We searched databases including PubMed, Cochrane CENTRAL, Web of Science, Institute of Electrical and Electronics Engineers (IEEE), Embase, PsycInfo, and Association for Computing Machinery (ACM). Studies were selected based on their focus on AR in prehospital care. A total of 14 randomized controlled trials were selected from an initial screening of 2081 manuscripts. Included studies focused on AR use by EMS personnel, examining clinical and educational impacts. Data such as study demographics, intervention type, outcomes, and methodologies were extracted using a standardized form. Primary outcomes assessed included clinical task accuracy, response times, and training efficacy. A narrative synthesis was conducted, and bias was evaluated using Cochrane’s risk of bias tool. Improvements in AR-assisted interventions and their limitations were analyzed.

Results

AR significantly improved clinical decision-making accuracy and EMS training outcomes, reducing response times in simulations and real-world applications. However, small sample sizes and challenges in integrating AR into workflows limit the generalizability of the findings.

Conclusions

AR holds promise for transforming prehospital care by enhancing real-time decision-making and EMS training. Future research should address technological integration and scalability to fully realize AR’s potential in EMS.
Exploring risk factors related to low calf circumference older adults with multimorbidity: From individual-centered perspective (Preprint)
Authors: Peng Xilin , Zhou Ruihao , Chen Xudong , Shi Fanfan , Zhu Tao , Chen Guo
Published: November 2024

BACKGROUND

As the global population continues to age, the prevalence of sarcopenia is gradually increasing, and the loss of skeletal muscle mass is one of the manifestations of sarcopenia. Low calf circumference is often used as a predictor of poor skeletal muscle mass or sarcopenia. The older adults usually have a combination of multiple chronic diseases. There is a lack of evidence to explore the risk factors for low calf circumference with multimorbidity in Chinese community-dwelling older adults.

OBJECTIVE

This study aimed to explore the risk factors and potential categories in low calf circumference with multimorbidity older adult patients from an individual-centered perspective.

METHODS

We selected 15,874 participants from the Chinese Longitudinal Healthy Longevity Survey in 2018 and screened for low calf circumference older adult patients. The "individual-centered" Latent class analysis to classify potential multimorbidity groups. Applying elastic net to screen the reliable risk variables, multiple logistic regression was used to explore the risk factors in low calf circumference with multimorbidity.

RESULTS

A collection of 7956 older individuals was eligible for the research, with age over 90 years accounting for 49.77%, the prevalence of low calf circumference occurred in 66.68%, 27.22% with multimorbidity in low calf circumference. Between 65 and 89 years of age, the prevalence of multimorbidity increased with age. However, the majority of older adults are in reasonably good health after the age of 90. Five multimorbidity groups were identified by latent class analysis: multisystem morbidity diseases (3.60%), arthritis-rheumatism or rheumatoid diseases (18.47%), diabetes-hypertension diseases (15.23%), respiratory-heart diseases (16.02%), and cardiovascular diseases (46.68%). Through 12 variables screened by elastic net, multiple logistic regression showed different significant impaction to multimorbidity groups, including demographic background, behavioural characteristics, and physical and mental health factors. In particular, older patients who self-report poor health grading and live in urban areas need more attention.

CONCLUSIONS

Our results revealed that low calf circumference is a common phenomenon among older adults in the community-dwelling older adults, and combined multimorbidity is also a large group. In the low calf circumference older adult population, the proportion of multimorbidity does not simply increase with age. Multimorbidity in low calf circumference has been identified in five potential groups. Different groups have distinctive risk factors. Public health authorities should pay attention to the low calf circumference in older adult patients with multimorbidity, carrying out targeted interventions and enhancing health outcomes.
Effects of Sound Interventions on the Mental Stress Response in Adults: A Scoping Review (Preprint)
Authors: Saskovets Marina , Saponkova Irina , Liang Zilu
Published: November 2024

BACKGROUND

This scoping review explores the effects of various sound interventions, including music, natural sounds, and speech, on stress response in adults.

OBJECTIVE

The review identifies key therapeutic factors, including sound type, individual listener characteristics, and environmental factors. As part of our review, we synthesize evidence of the body's response to sound interventions and highlight current research gaps.

METHODS

A systematic search was conducted using databases such as PubMed, Web of Science, Scopus, and PsycINFO, focusing on studies from 1990 to the present. Eligible studies included randomized controlled trials, clinical trials, and laboratory experiments that measured stress through physiological markers (e.g., heart rate variability, cortisol) and self-reports. Data from 34 studies were included, and thematic analysis was conducted to categorize the factors influencing the effectiveness of sound interventions.

RESULTS

Findings suggest that music, especially classical and self-selected pieces, effectively reduces physiological stress markers, including heart rate variability, blood pressure, and cortisol levels. Non-musical sounds, such as nature sounds and calming voices, also demonstrate stress-relief potential, though research in this area is less comprehensive. While most sound interventions demonstrated positive effects, some studies reported adverse responses, suggesting that sound can induce stress as much as mitigate it. The outcomes were significantly affected by context factors, such as personal preferences, delivery methods, cultural context, etc., which emphasizes the importance of personalized interventions.

CONCLUSIONS

Sound interventions offer promising non-invasive methods for stress reduction. This review suggests a future focus on addressing the gaps in research on non-musical sound interventions and further investigation of the neural mechanisms underlying stress responses to sound.

INTERNATIONAL REGISTERED REPORT

RR2-10.2196/54030
The Applications of Large Language Models in Mental Health: A Scoping Review (Preprint)
Authors: Jin Yu , Liu Jiayi , Li Pan , Wang Baosen , Yan Yangxinyu , Zhang Huilin , Ni Chenhao , Wang Jing , Li Yi , Bu Yajun , Wang Yuanyuan
Published: November 2024

BACKGROUND

Mental health is emerging as an increasingly prevalent public issue, particularly within low- and middle-income nations. There is an urgent need in mental health for efficient detection methods, effective treatments, affordable privacy-focused healthcare solutions, and increased access to specialized psychiatrists. The emergence and rapid development of large language models (LLMs) have been leveraged to address these mental health demands. However, a comprehensive review summarizing the applications, processes, and performance of LLMs in mental health has been lacking up until now.

OBJECTIVE

To summarize the applications of LLMs in mental health, encompassing trends, research areas, performance comparisons, and prospective future directions.

METHODS

A scoping review was conducted to map the landscape of LLM applications in mental health, including trends, application domains, comparative performances, and future trajectories. We conducted a search across seven electronic databases, including Web of Science, PubMed, Cochrane Library, IEEE Xplore, Weipu, CNKI, and WanFang, from January 1, 2019, to August 31, 2024. Subsequent data-charting of eligible articles extracted relevant information on application aspects and performance metrics.

RESULTS

A total of 95 articles were included, drawn from 4,544 studies, employing LLMs for mental health tasks. The applications were categorized into three key areas: screening and detection of mental disorders (n = 67), support for clinical treatments and interventions (n = 31), and assisting in mental health counseling and education (n = 11). The majority of studies utilized LLMs for depression detection and classification (34·7%), clinical treatment support and intervention (14·7%), and suicide risk prediction (12·6%). In comparison with non-transformer models and human experts, LLMs demonstrate superior capabilities in information acquisition and analysis, generating natural-language responses, and addressing complex reasoning problems. Assessments of LLM performances indicate that the majority of LLMs exhibit efficiency and promise in addressing mental health tasks.

CONCLUSIONS

This scoping review synthesizes the applications, processes, and performances of LLMs within the mental health field. These findings highlight the substantial potential of LLMs to augment mental health research, diagnostics, and intervention strategies, underscoring the imperative for ongoing development and ethical deliberation in clinical settings.