bluuebunny/crossref_metadata_2025 huggingface dataset:
Assessing climate change impacts on water availability in southern Portugal using a daily sequential soil-water budget model
Authors: Nunes Martins Tiago , Oliveira Manuel Mendes , Portela Maria Manuela , Leitão Teresa Eira
Published: May 2024

Climate change poses a significant threat to water resources in southern Portugal. To understand the potential impacts on surface and groundwater resources, this study employed a daily sequential soil-water budget model (BALSEQ) under two representative concentration pathway (RCP) scenarios, RCP 4.5 and 8.5, spanning the periods 2020–2060 and 2061–2100. An analysis of meteorological observations and EURO-CORDEX climate projections showed a decline in annual rainfall, particularly under RCP 8.5. Monthly rainfall patterns exhibited significant decreases occurring from March to June, while in December and January, rainfall is likely to increase in all RCP scenarios and respective time-windows. Potential evapotranspiration (PET) demonstrated an increase across all scenarios. BALSEQ model simulations showed a likely decrease in deep infiltration (Ip) and direct runoff (Ed) under both RCP scenarios. The river basins with the highest reductions in Ed and Ip are Mira, Barlavento, southern Guadiana, and Sotavento. For instance, Ed is projected to decrease by up to 87% in Guadiana (RCP 8.5 [2020–2060]). Similarly, Ip is projected to decrease by up to 60% in Sotavento (RCP 8.5 [2061–2100]). These findings highlight the need for adaptation and mitigation measures to preserve the region's water resources.
Construction of the water balance model for the Bontanga irrigation dam in Northern Ghana
Authors: Mwanga Eliafie , Shaibu Abdul-Ganiyu , Issaka Zakaria
Published: May 2024

Freshwater resources are essential for the sustenance of all living things, for crop production and socio-economic activities. The objective of this study was to construct a water balance model aimed at optimizing reservoir management by analyzing variations in water availability in the reservoir. This model will help dam operators to adopt water allocation strategies, timing of water releases and storage decisions. An echo sounder was used to measure the depth of water. Crop water requirements were computed using FAO CROPWAT 8 software, and the InVEST-SDR model was used to estimate sediments exported downstream of the watershed. Model construction utilized multiple linear regression, and the results were tested at a level of significance α = 0.05. Model performance was evaluated using a coefficient of determination (R2) and the ratio of the root mean square error to the standard deviation of measured data (RSR). The results revealed a coefficient of determination (R2) of 0.743 and a ratio of the root mean square error to the standard deviation of measured data (RSR) of 0.67. The constructed model will provide essential information to stakeholders on drought preparedness and mitigation, including water conservation measures and the management of water releases during critical periods.
Carbapenem-resistant Enterobacterales in wastewater resources and healthy carriers: A survey in Iran
Authors: Khavandi Shabnam , Habibzadeh Nasrin , Hasani Kamal , Sardari Mehran , Arzanlou Mohsen
Published: May 2024

The carbapenem-resistant Enterobacterales (CRE) pose a pressing public health concern. Here, we investigated the frequency of CRE bacteria, carbapenemase-encoding genes, and the molecular epidemiology of carbapenemase-resistant Escherichia coli in wastewater resources and healthy carriers in Iran. Out of 617 Enterobacterales bacteria, 24% were carbapenem-resistant. The prevalence of CRE bacteria in livestock and poultry wastewater at 34% and hospital wastewater at 33% was significantly higher (P ≤ 0.05) than those in healthy carriers and municipal wastewater at 22 and 17%, respectively. The overall colonization rate of CRE in healthy individuals was 22%. Regarding individual Enterobacterales species, the following percentages of isolates were found to be CRE: E. coli (18%), Citrobacter spp. (24%), Klebsiella pneumoniae (28%), Proteus spp. (40%), Enterobacter spp. (25%), Yersinia spp. (17%), Hafnia spp. (31%), Providencia spp. (21%), and Serratia spp. (36%). The blaOXA-48 gene was detected in 97% of CRE isolates, while the blaNDM and blaVIM genes were detected in 24 and 3% of isolates, respectively. The B2 phylogroup was the most prominent group identified in carbapenem-resistant E. coli isolates, accounting for 80% of isolates. High prevalence of CRE with transmissible carbapenemase genes among healthy people and wastewater in Iran underscores the need for assertive measures to prevent further dissemination.
Optimal scheduling of variable speed pumps with mixed integer linear programming
Authors: Janus Tomasz , Ulanicki Bogumil , Diao Kegong
Published: May 2024

Mixed integer linear programming (MILP) has been gaining traction as a method for solving optimal pump scheduling problems in water distribution networks (WDNs). However, inclusion of variable speed pumps (VSPs) in MILP pump scheduling frameworks has not been given adequate treatment. This article addresses this gap by describing a methodology for formulating and solving optimal pump scheduling problems with VSPs using MILP and piece-linear approximations of network components. The methodology proceeds in four steps: (a) WDN simulation with initial pump schedule(s), (b) approximation of network components, including VSP, using linear and piece-linear functions around the chosen operating points, (c) formulation of a fully parameterised mixed integer linear programme, and (d) solution of the optimisation problem and WDN simulation with optimal pump schedule(s). The methodology is coded in MATLAB/OCTAVE and Python and is publicly available on GitHub. It was applied to solve a pump scheduling problem on a two variable speed pump single-tank network that allows the reader to easily understand how the methodology works and how it is applied in practice. The results show that the formulation is robust and the optimiser is able to return a globally optimal solution for a range of operating points.
Enhanced removal of nano-oil droplets utilizing polysilicate aluminum ferric (PSAF): Leveraging bridging and non-polar surface advantages
Authors: Liu Yadan , Zhou Yanjun , Su Hui , Gu Chao , Shangguan Botao , Yan Zhiyang , Qin Jinyi
Published: May 2024

Hydraulic oil leaks during mechanical maintenance, resulting in flushing wastewater contaminated with dispersed nano-oil droplets. In this study, 75 mg L−1 of polysilicate aluminum ferric (PSAF) was stirred at 350 rpm and the optimal chemical oxygen demand (COD) removal was 71%. The increase of PSAF led to more hydrolysis of Fe, and 1,175 cm−1 hydroxyl bridged with negative oil droplets. At the same molar concentration, PSAF hydrolyzes cationic metals more rapidly than polymeric aluminum chloride (PAC). PSAF forms flocs of smaller complex structures with greater bridging. The Al–O and Si–O peaks occurred at 611 and 1,138 cm−1, indicating the formation of Si–O–Fe and Si–O–Al bonds on the flocs surface. Higher stirring speeds did not change the free energy of the flocs surface γTot, mainly because the decrease in the van der Waals force (γLW) offset the increase of Lewis acid–base force (γAB). Preserving the non-polar surface, in summary, owing to its bridging abilities and affinity for non-polar surfaces, PSAF demonstrates superior efficiency over PAC in capturing and removing oil droplets.
Synthesis, Characterization, and Antimicrobial Evaluation of Schiff Base-mixed
Ligand Complexes with Divalent Metal Ions Derived from Amoxicillin and
Vanillin/Nicotinamide
Authors: Bahry Manhel R. , Al-Noor Taghreed H. , Fardous Ali M. , Heydari Ahmad R. , Abdou Aly , Fayez Shaimaa , El-Shazly Mohamed , Saleh Na'il
Published: May 2024

Introduction:

This study focuses on the development of novel antimicrobial agents. A Schiff base
ligand, 6-(2-(4-hydroxy-3-methoxybenzylideneamino)-2-(4-hydroxyphenyl)acetamido)-3,3-dimethyl-7-oxo-
4-thia-1-azabicyclo [3.2.0] heptane-2-carboxylic acid, synthesized through the condensation of amoxicillin
and vanillin in methanol, served as the foundation. Polydentate mixed ligand complexes were then formed by
reacting the Schiff base with metal ions (Fe(II), Co(II), Ni(II), Cu(II), and Zn(II)) and nicotinamide in specific
ratios.

Methods:

Characterization involved various techniques, such as 1H-NMR, FT-IR, UV-Vis, and elemental
analysis for the ligand, and Atomic Absorption, FT-IR, UV-Vis, magnetic susceptibility, and conductance
measurements for the Schiff base-metal ion complexes.

Results:

Quantum chemical features of both ligands and metal complexes were computed, refining their electronic
and molecular structures theoretically. Antimicrobial activity against Staphylococcus aureus, Escherichia
coli, Klebsiella pneumoniae, Salmonella typhi, Acinetobacter baumannii, and Pseudomonas aeruginosa
was assessed for the starting materials, ligands, and synthesized complexes, revealing significant effects on
certain species. In-silico binding modes with Escherichia coli (PDB ID: 5iq9) were determined through molecular
docking.

Conclusion:

This study underscores the potential applications of the Schiff base ligands and their metal complexes
in developing new antimicrobial agents.
Curcumin in Cancer Prevention: Insights from Clinical Trials and Strategies to
Enhance Bioavailability
Authors: Alam Shabaz , Lee Jaewon , Sahebkar Amirhossein
Published: May 2024

Cancer remains a leading cause of death worldwide, and current cancer drugs often have high costs
and undesirable side effects. Additionally, the development of drug resistance can reduce their effectiveness
over time. Natural products have gained attention as potential sources for the treatment and prevention of various
diseases. Curcumin, an extract from turmeric (Curcuma longa), is a natural phenolic compound with diverse
pharmacological properties, including antioxidant, anti-inflammatory, antiviral, antibacterial, antifungal,
antiprotozoal, antidiabetic, antivenom, antiulcer, anticarcinogenic, antimutagenic, anticoagulant, and antifertility
activities. Given the increasing interest in curcumin for cancer prevention, this review aims to comprehensively
examine clinical trials investigating the use of curcumin in different types of cancer. Additionally, effective
techniques and approaches to enhance the bioavailability of curcumin are discussed and summarized. This
review article provides insights into the properties of curcumin and its potential as a future anticancer drug.
hdWGCNA and Cellular Communication Identify Active NK Cell
Subtypes in Alzheimer's Disease and Screen for Diagnostic Markers
through Machine Learning
Authors: Song Guobin , Wu Haoyang , Chen Haiqing , Zhang Shengke , Hu Qingwen , Lai Haotian , Fuller Claire , Yang Guanhu , Chi Hao
Published: May 2024

Background:

Alzheimer's disease (AD) is a recognized complex and severe neurodegenerative
disorder, presenting a significant challenge to global health. Its hallmark pathological
features include the deposition of β-amyloid plaques and the formation of neurofibrillary tangles.
Given this context, it becomes imperative to develop an early and accurate biomarker model for
AD diagnosis, employing machine learning and bioinformatics analysis.

Methods:

In this study, single-cell data analysis was employed to identify cellular subtypes that exhibited
significant differences between the diseased and control groups. Following the identification
of NK cells, hdWGCNA analysis and cellular communication analysis were conducted to pinpoint
NK cell subset with the most robust communication effects. Subsequently, three machine
learning algorithms-LASSO, Random Forest, and SVM-RFE-were employed to jointly screen for
NK cell subset modular genes highly associated with AD. A logistic regression diagnostic model
was then designed based on these characterized genes. Additionally, a protein-protein interaction
(PPI) networks of model genes was established. Furthermore, unsupervised cluster analysis was
conducted to classify AD subtypes based on the model genes, followed by the analysis of immune
infiltration in the different subtypes. Finally, Spearman correlation coefficient analysis was utilized
to explore the correlation between model genes and immune cells, as well as inflammatory
factors.

Results:

We have successfully identified three genes (RPLP2, RPSA, and RPL18A) that exhibit a
high association with AD. The nomogram based on these genes provides practical assistance in diagnosing
and predicting patients' outcomes. The interconnected genes screened through PPI are intricately
linked to ribosome metabolism and the COVID-19 pathway. Utilizing the expression of
modular genes, unsupervised cluster analysis unveiled three distinct AD subtypes. Particularly
noteworthy is subtype C3, characterized by high expression, which correlates with immune cell infiltration
and elevated levels of inflammatory factors. Hence, it can be inferred that the establishment
of an immune environment in AD patients is closely intertwined with the heightened expression
of model genes.

Conclusion:

This study has not only established a valuable diagnostic model for AD patients but
has also delved deeply into the pivotal role of model genes in shaping the immune environment of
individuals with AD. These findings offer crucial insights into early AD diagnosis and patient management
strategies.
Management of Unilateral Impacted Maxillary Permanent Canine: A Case Report
Authors: Halim Himawan , Halim Ivan A.
Published: May 2024

Introduction

The management of maxillary canine is very complex because it must be carefully planned and carried out as a team. The handling of impacted canine cases must be seen from a clinical and radiological point of view. Maxillary canine impaction can be caused by a lack of space or inadequate seed placement. The time to treat canine impaction is usually between the ages of 11 and 14.

Objective

The aim of this case report was to describe the management of an impacted maxillary left canine of a teenage girl. Successful treatment requires complete diagnostics, such as radiographs, good teamwork, and precise treatment planning of the dental team.

Case Report

An 11-year-old female patient with class I molar relationship, bimaxillary protrusive, and impacted left upper canine visited the clinic for orthodontic treatment. Extraction of four first premolars (bicuspids) was carried out, and exposure by the periodontist was completed on the maxillary left canine for the installation of a traction device (gold chain traction).

Conclusion

The appropriate timing, treatment plan, and proper surgical exposure preparation in handling this case produced optimal and ideal results.
High-Performance Cobalt Chalcogenides for Oxygen Reduction Reaction
Authors: Hazarika Kumar Kashyap , Goswami Chiranjita , Bharali Pankaj
Published: May 2024

:

The oxygen reduction reaction (ORR) is vital to numerous energy conversion technologies, such as fuel cells and metal-air batteries. Moreover, to
enhance the overall efficacy and durability of these devices, it is crucial to develop catalysts that are both effective and economical. Among the
many explored catalyst materials, cobalt chalcogenides have attracted considerable interest due to their unique properties and exceptional ORR
performance. This review focuses on the synthesis methods, structural characteristics, and electrochemical performance of high-performance cobalt
chalcogenides as catalysts for the ORR. In addition, the influence of various synthetic parameters on the catalytic activity and stability of cobalt
chalcogenides is investigated. Also addressed are the effects of defects, doping, and surface modification on the ORR performance of cobalt
chalcogenides. In addition, the use of cobalt chalcogenides in practical fuel cell devices is discussed, along with their outstanding performance as
ORR catalysts in both acidic and alkaline environments. The durability and long-term stability of cobalt chalcogenides under severe operating
conditions are evaluated, indicating their potential commercial applications. Finally, the field of cobalt chalcogenides for ORR challenges and
prospects are outlined. This review proposes strategies for further enhancing their catalytic activity, selectivity, and durability, such as interface
engineering and synergistic combinations with other catalyst materials. For researchers working on the development of next-generation ORR
catalysts and the practical implementation of cobalt chalcogenides for sustainable energy applications, the insights garnered from this review are
invaluable.
The Multigenerational Legacy of Diabetes and Illness Perception: Influence on Older Adult’s Stigma
Authors: Scollan-Koliopoulos Melissa , Naturale Donna , Mahurter Brynn , Curren Sara , Koliopoulos Ryan J.
Published: May 2024

There is not enough information regarding the impact of stigma associated with a. diagnosis of diabetes in aging older adults. Perceptions of diabetes are passed down generationally and may be influenced by mainstream societal perceptions at the time the perception is shaped. This is known as a multigenerational legacy of diabetes for those with whom the perceptions are shaped within families when a hereditarily predisposed condition occurs. In this study, participants over the age of (n = 88) 60 years old were administered measures of illness perception with social stigma items added to the social consequences domain. Participants were also administered the recollections of diabetes experiences survey developed to measure the multigenerational legacy of diabetes. Hierarchical multiple regression analysis was used to test hypotheses. The results showed that those who anticipate the same complications, especially lower extremity amputations, and who have threatening illness perceptions, are likely to have stigma regarding diabetes (R2 = 0.092, F (2,84), p = 0.02). In this model, a threatening illness perception, (β = -0.20, p = 0.05). Findings of this study conclude that if an individual with diabetes has an anticipation of developing similar complications to that of a family member who had diabetes before them, they will be more likely to endorse perceptions of stigma. This is especially true if they have a threatening illness perception of diabetes, and if the complication was lower extremity amputation. Clinical implications include a need to anticipate stigma and provide psychoeducation during healthcare interactions.
Requirements for and Barriers to Rehabilitation Services for Children With Disabilities in Middle- and High-Income Countries: Scoping Review
Authors: Xie Yijun , Wu Jing , Li Yao , Liu Hui , Peng Yanyan , Zhou Ping , Sun Yizhou , Kang Luyan , Jiang Chenghua , Wu Hengjing
Published: May 2024

Background

The rehabilitation of children with disabilities has received considerable attention from the United Nations. However, the state of rehabilitation services for children with disabilities worldwide remains far from optimistic, even in economically affluent middle- and high-income countries.

Objective

This scoping review aimed to identify the rehabilitation needs of children with disabilities and their barriers to rehabilitation services in middle- and high-income countries.

Methods

A systematic search was conducted using MEDLINE and Web of Science for papers published from January 2013 to December 2023. Studies were included if they were peer-reviewed, full-text articles related to children with disabilities, reporting on their access to rehabilitation services, and conducted in countries classified by the World Bank 2023 as middle- and high-income economies. Exclusion criteria included duplicates, unavailable full texts, and studies without distinct outcomes. A total of 27 studies were selected following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, focusing on children, their families, or service providers.

Results

The suitability, availability, and affordability of rehabilitation services were identified as the major needs and barriers for children with disabilities in middle- and high-income countries. This included communication barriers, a need for more personnel and facilities, and the stagnation and inadequacy of economic subsidies.

Conclusions

Middle- and high-income countries have relatively well-established rehabilitation infrastructure and support systems. They are nevertheless insufficient for meeting the needs of children with disabilities. More attention should be paid to these issues to improve the well-being of children with disabilities. The data provided by this review can help raise awareness of rehabilitation needs and barriers at the policy level.
Can an Online Course, Life101: Mental and Physical Self-Care, Improve the Well-Being of College Students?
Authors: Jafari Mahtab
Published: May 2024

The COVID-19 pandemic has had a significant impact on the mental health of college students worldwide. As colleges shifted to online instruction, students faced disruptions and increased stressors, leading to a decline in mental health that appears to continue in the postpandemic era. To alleviate this problem, academic institutions have implemented various interventions to address mental health issues; however, many of these interventions focus on a single approach and lack diverse delivery methods. This viewpoint introduces the concept of a multimodal self-care online course, Life101: Mental and Physical Self-Care, and discusses the potential effectiveness of such an intervention in improving students’ well-being. The course combines evidence-based interventions and incorporates interactive lectures, workshops, and guest speakers. Pre- and postcourse surveys were conducted over a span of 4 academic terms to evaluate the impact of this course on the well-being and self-care practices of students. The survey data suggest positive outcomes in students taking Life101, including the adoption of healthier habits, reduced stress levels, and increased knowledge and practice of self-care techniques. Life101 represents a novel multimodality intervention to address the epidemic of mental health issues faced by students today. By implementing similar evidence-based multimodal didactic curricula across campuses, academic institutions may be able to better equip students to navigate challenges and promote their overall well-being.
Long-Term Emotional Impact of the COVID-19 Pandemic and Barriers and Facilitators to Digital Mental Health Tools in Long-Term Care Workers: Qualitative Study (Preprint)
Authors: González-Spinoglio Leticia , Monistrol-Mula Anna , Vindrola-Padros Cecilia , Aguilar-Ortiz Salvatore , Carreras Bernat , Haro Josep Maria , Felez-Nobrega Mireia
Published: May 2024

BACKGROUND

The overall pandemic created enormous pressure on long-term care workers (LTCWs), making them particularly vulnerable to mental disorders. Despite this, most of the available evidence on professional well-being during COVID-19 has exclusively focused on frontline health care workers.

OBJECTIVE

This study aimed to identify the long-term psychological needs of LTCWs derived from the COVID-19 pandemic and to explore barriers and facilitators related to digital mental health tools. This is part of a project that seeks to develop a digital mental health intervention to reduce psychological distress in this population group.

METHODS

We performed a qualitative study with a rapid research approach. Participants were LTCWs of the autonomous community of Catalonia. We conducted 30 semistructured interviews between April and September 2022. We used a qualitative content analysis method with an inductive-deductive approach.

RESULTS

The period of the pandemic with the highest mental health burden was the COVID-19 outbreak, with almost all workers having experienced some form of emotional distress. Emotional distress persisted over time in more than half of the participants, with fatigue and nervousness being the main emotions expressed at the time of the interview. High workload, the feeling that pandemic times are not over, and poor working conditions that have remained since then have been the most frequently expressed determinants of such emotions. Potential barriers and facilitators to engagement with digital tools were also identified in terms of previous experience and beliefs of the target population, possibilities for the integration of a digital tool into daily life, preferences regarding the level of guidance, the possibility of social connectedness through the tool, and privacy and confidentiality. The identified factors may become especially relevant in the context of the pandemic remission phase.

CONCLUSIONS

More than 2 years after the pandemic outbreak, emotional distress is still relevant. The persistent burden of psychological distress points to a need for institutions to take action to improve working conditions and promote employees’ well-being. Considering factors that act as barriers and facilitators for the use of digital mental health tools, it is important to develop tailored tools that could offer valuable support to this population during and after a pandemic.
Effectiveness of mHealth Apps for Maternal Health Care Delivery: Systematic Review of Systematic Reviews (Preprint)
Authors: Ameyaw Edward Kwabena , Amoah Padmore Adusei , Ezezika Obidimma
Published: May 2024

BACKGROUND

Globally, the use of mobile health (mHealth) apps or interventions has increased. Robust synthesis of existing systematic reviews on mHealth apps may offer useful insights to guide maternal health clinicians and policy makers.

OBJECTIVE

This systematic review aims to assess the effectiveness or impact of mHealth apps on maternal health care delivery globally.

METHODS

We systematically searched Scopus, Web of Science (Core Collection), MEDLINE or PubMed, CINAHL, and Cochrane Database of Systematic Reviews using a predeveloped search strategy. The quality of the reviews was independently assessed by 3 reviewers, while study selection was done by 2 independent raters. We presented a narrative synthesis of the findings, highlighting the specific mHealth apps, where they are implemented, and their effectiveness or outcomes toward various maternal conditions.

RESULTS

A total of 2527 documents were retrieved, out of which 16 documents were included in the review. Most mHealth apps were implemented by sending SMS text messages with mobile phones. mHealth interventions were most effective in 5 areas: maternal anxiety and depression, diabetes in pregnancy, gestational weight management, maternal health care use, behavioral modification toward smoking cessation, and controlling substance use during pregnancy. We noted that mHealth interventions for maternal health care are skewed toward high-income countries (13/16, 81%).

CONCLUSIONS

The effectiveness of mHealth apps for maternity health care has drawn attention in research and practice recently. The study showed that research on mHealth apps and their use dominate in high-income countries. As a result, it is imperative that low- and middle-income countries intensify their commitment to these apps for maternal health care, in terms of use and research.

CLINICALTRIAL

PROSPERO CRD42022365179; https://tinyurl.com/e5yxyx77
Causal Inference for Hypertension Prediction (Preprint)
Authors: Gong Ke , Chen Yifan , Song Xinyue , Fu Zhizhong , Ding Xiaorong
Published: May 2024

BACKGROUND

Hypertension is a leading cause of cardiovascular disease and premature death worldwide and it puts a heavy burden on the healthcare system. It is, therefore, very important to detect and evaluate hypertension and related cardiovascular events so as for early prevention, detection and management. Hypertension can be evaluated in real time with wearable noninvasive cardiac signals, such as electrocardiogram (ECG) and photoplethysmogram (PPG). Most previous studies predicted hypertension from ECG and PPG signals with extracted features that are correlated with hypertension. However, correlation is sometimes unreliable and may be affected by confounding factors.

OBJECTIVE

In this study, we explored the feasibility of predicting the risk of hypertension using causal inference methods. Additionally, we paid special attention to and verified the reliability and effectiveness of causality compared to correlation.

METHODS

Firstly, we constructed causal graphs by the Greedy Equivalence Search algorithm, and then applied causal strategies to obtain the optimal causal graph. Finally, we used machine learning classification algorithms to achieve hypertension prediction.

RESULTS

The machine learning classification models achieve great classification performance, with accuracy being 0.89, precision being 0.92, recall being 0.82, and F1-score being 0.87, which outperformed the correlation-based hypertension detection.

CONCLUSIONS

The results indicate that the causal inference-based approach can potentially clarify the mechanism of hypertension detec-tion with noninvasive signal and effectively detect hyperten-sion. In addition, the results also reveal that causality is more reliable and effective compared to correlation.
Establishment of the visualization platform for ADR query and analysis: an example of severe skin adverse reactions caused by sulfonylureas (Preprint)
Authors: Cheng Shuqiao , Yu Hui-Min , Huang Ya-Min , Xiao Jian , Zhang Lu , Huang Hangxing , Huang Ling , Li Jing-Yang
Published: May 2024

BACKGROUND

Driven by the need of medical staff and general public to collect and review adverse drug reactions (ADRs) of interest, we introduced and validated a visualization platform for querying and analyzing data from the FDA Adverse Event Reporting System (FAERS). A case study of the association between sulfonylureas and serious skin adverse reactions was conducted to validate platform usability.

OBJECTIVE

To build a visualization platform for querying and analyzing data from the FDA Adverse Event Reporting System (FAERS), facilitating the collection and review of adverse drug reactions (ADRs) of interest.

METHODS

We performed appropriate data acquisition, cleaning and subsequent platform interface and functional development of available data. In order to evaluate the usability of the platform, we focused on a case study involving serious skin adverse reactions caused by sulfonylureas.

RESULTS

We developed a visualization platform for adverse reaction query and analysis based on FAERS data. The platform consists of five components, including the login page, multi-condition query, drug and adverse reaction query, primary ID query and data download interface. The high usability of the platform was verified by demonstrating the signal mining results of serious skin adverse reactions caused by sulfonylureas and visualizing information.

CONCLUSIONS

The visualization platform and verification cases constructed in this study provide a suitable framework and method for drug safety research, which is expected to promote the development of pharmacovigilance.
AutoRD: An Automatic and End-to-End System for Rare Disease Knowledge Graph Construction Based on Ontology-enhanced Large Language Models (Preprint)
Authors: Cao Lang , Sun Jimeng , Cross Adam
Published: May 2024

BACKGROUND

Rare diseases affect millions worldwide but often face limited research focus due to their low prevalence. This results in prolonged diagnoses and a lack of approved therapies. Recent advancements in Large Language Models (LLMs) have shown promise in automating the extraction of medical information, offering potential to improve rare disease diagnosis and management.

OBJECTIVE

Our objective is to create an end-to-end system called AutoRD, which automates extracting information from medical text about rare diseases. We conducted various experiments to evaluate the performance of AutoRD and highlighted its strengths and limitations in this paper.

METHODS

AutoRD is a pipeline system involving data preprocessing, entity extraction, relation extraction, entity calibration, and knowledge graph construction. We implement this using large language models and medical knowledge graphs developed from open-source medical ontologies. We quantitatively evaluate our system on entity extraction, relation extraction, and the performance of knowledge graph construction.

RESULTS

AutoRD achieves an average of entity F1 score and relation F1 score of 47.3%, a 14.4% improvement compared to the base LLM. In detail, AutoRD achieves an overall entity extraction F1 score of 56.1% (‘rare_disease’: 83.5%, disease: 35.8%, ‘symptom_and_sign’: 46.1%, anaphor: 67.5%) and an overall relation extraction F1 score of 38.6% (‘produces’: 34.7%, ‘increases_risk_of’: 12.4%, ‘is_a’: 37.4%, ‘is_acronym’: 44.1%, ‘is_synonym’: 16.3%, ‘anaphora’: 57.5%). The qualitative experiment also demonstrates that the constructed knowledge graph’s performance is respectable.

CONCLUSIONS

AutoRD is an automated end-to-end system for extracting rare disease information from text to build knowledge graphs. It uses ontology-enhanced LLMs for a robust medical knowledge base. The superior performance of AutoRD is validated by experimental evaluations, demonstrating the potential of LLMs in healthcare.

CLINICALTRIAL
User engagement with DiabeteWise: Forging a novel, unbiased, person-centered pathway to diabetes access and uptake (Preprint)
Authors: Wong Jessie , Addala ananta , Alamarie Selma , Hanes Sarah , Krugman Sara , Naranjo Diana , Nelmes Sierra , Rose Kyle Jacques , Schneider-Utaka Aika , Tanenbaum Molly , Hood Korey
Published: May 2024

BACKGROUND

Despite shown benefits of diabetes technologies for people living with diabetes, barriers to device education and uptake can prevent the realization of these potential benefits. DiabetesWise is an unbranded, data-driven online resource that tailors device recommendations based on preferences and priorities of people with insulin-requiring diabetes.

OBJECTIVE

To examine engagement with DiabetesWise and its correlates.

METHODS

A sample of 458 participants (Mage=37.1, SD=9.73; 66% female; 81% type 1 diabetes) with minimal diabetes device use at enrollment were invited to use DiabetesWise. Their website activity was tracked, and they completed online surveys. Chi-square and t-tests evaluated correlates of engagement.

RESULTS

Most participants logged into DiabetesWise at least once (69%), which was associated with increased likelihood of starting a new device within 6 months (13.7% vs. 1.5%, p=.005). Logging in was also associated with being female, having public/no insurance, having lower income, and receiving care in a private practice/community health setting. Nearly 38% logged in multiple times, which was more common for participants receiving diabetes care through primary care. Most who logged in used the Check Up tool to assess current device needs and preferences (85%), of whom 74% were using meter and injections. Most Check Up recommendations were for meter and pump (63%), followed by sensor and pump (35%), then sensors with smart pump (2%). Cost was the most frequent priority for device decisions (51%). Nearly half the participants who completed the Check Up reported at least moderate diabetes distress (41%).

CONCLUSIONS

DiabetesWise is an innovative, unbiased pathway to promote diabetes device education and awareness. Highest initial engagement was observed among people with fewer resources; repeated use was observed among those receiving diabetes care through primary care. DiabetesWise may help offset disparities in diabetes technology access and uptake.
Integrating Human-Smartphone Interactions and Actigraphy in Digital Phenotyping: Exploring Social-Physical Coherence in Relation to Obesity and Depression (Preprint)
Authors: Lin Yu-Hsuan , Lin Chen , Chuang Hai-Hua , Chang Hsiang-Chih , Chen I-Ming , Chen Tien-Yu
Published: May 2024

UNSTRUCTURED

Introduction: The interrelationship between physical and social activities plays a crucial role in influencing health outcomes, particularly in populations with obesity and depression. This study aims to develop the "social-physical coherence" method for measuring the alignment between physical and social activities, investigating its association with obesity and depression.
Methods: The research encompassed 135 participants (average age: 43.8±12.3 years; 65.2% female), including individuals with a history of major depression, those with obesity, and health-care professionals participating in a workplace health program. Body Mass Index (BMI) and the Patient Health Questionnaire-9 (PHQ-9) scale were employed to determine obesity and depression levels, respectively. Activity data were collected over a minimum of four weeks using wrist actigraphy devices and the Rhythm app, yielding 3,973 person-days of data. The Rhythm app tracked human-smartphone interactions and computed rest-activity rhythm (RAR) patterns, including interdaily stability (IS), from both standard actigraphy and app-derived data, thus offering two distinct RAR measurements. Social-physical coherence was assessed by combining physical activity data from actigraphy with social activity data derived from human-smartphone interactions.
Results: Findings demonstrated a significant positive correlation between social-physical coherence and IS, particularly significant in app-derived IS (ISapp) over a period of 1-6 weeks. Analysis of the relationship with BMI revealed a significant negative correlation for both social-physical coherence and ISapp within the first 2-4 weeks, whereas no notable correlation was found with actigraphy-based IS (ISact). Regarding depressive symptom scores, a borderline-significant negative correlation was observed with ISact when examining data from the first 1, 3, 4, or 5 weeks (P=.054 to .062). No significant correlation was found between social-physical coherence or ISapp and PHQ-9 scores across all timeframes studied.
Conclusions: This study leveraging digital phenotyping through actigraphy and human-smartphone interactions, reveals an inverse relationship between social-physical coherence and obesity, and a more complex association with depression.
Evaluating the effectiveness of mobile applications on medication adherence for chronic conditions: Systematic Review and Meta-analysis (Preprint)
Authors: Lanke Vaidehee , Trimm Kevin , Habib Bettina , Tamblyn Robyn
Published: May 2024

BACKGROUND

Medication adherence is crucial in managing chronic conditions, yet only 50% of chronically ill patients take medications as prescribed, leading to poor health outcomes. Mobile applications include a variety of possible features that have the potential to support and improve medication adherence.

OBJECTIVE

The purpose of this systematic review was to evaluate the effectiveness of mobile applications in promoting medication adherence for patients managing chronic conditions.

METHODS

MEDLINE (Ovid), Embase (Ovid) and Cochrane Central Register of Controlled Trials databases were searched for randomized controlled trails (RCTs) evaluating the effectiveness of mobile app interventions in improving medication adherence in patients with chronic conditions. Meta-analyses were performed on medication adherence scores, categorized by adherence measurement scale, and bias assessment was conducted using the Cochrane Risk of Bias tool.

RESULTS

This review included 14 RCTs published between 2014 to 2022, with sample sizes between 57 to 412 participants and the length of interventions ranging from 30 days to 12 months. A range of patient populations were evaluated in the included studies, including those with Parkinson’s disease, coronary heart disease, psoriasis, and hypertension, with the latter being the most common. All 14 studies reported that app interventions improved medication adherence and 10 RCTs demonstrated statistically significant improvement in medication adherence. Three separate sets of meta-analyses and difference in difference analyses were conducted on studies, categorized by the 3 scales used in individual studies: the 8-item Morisky Medication Adherence Scale, 4-item Morisky Medication Adherence Scale and percentage adherence scale. Each set of analyses demonstrated that app-based interventions improved medication adherence.

CONCLUSIONS

From the studies included in this review, mobile apps, designed for a range of conditions with a range of features, can improve medication adherence and may be a tool to successfully manage chronic conditions.

CLINICALTRIAL

PROSPERO International Prospective Register of Systematic Reviews CRD42023488188
AI Patient Actor: A Large-Language-Model-Based App for Medical Training (Preprint)
Authors: Thesen Thomas , Alilonu Nsomma , Stone Simon
Published: May 2024

UNSTRUCTURED

Standardized Patient (SP) simulations are integral but resource-intensive components of medical education, aimed at developing clinical interviewing and diagnostic skills. The nature of in-person SP encounters poses challenges in scalability and access. We introduce a web-based application leveraging a Large-Language Model (LLM) to simulate physician-patient interactions, thereby offering a scalable, cost-effective alternative for practicing clinical skills while receiving personalized formative feedback. The AI Patient Actor utilizes GPT-4o to create responsive, contextually appropriate simulated patient interactions based on expert-created clinical case scenarios. Python 3.10 and Streamlit provide the development framework, while LangChain optimizes prompt and case file processing. Whisper-3 speech recognition and synthesis enables multi-language vocal interaction. Formative feedback is generated immediately during the simulations, based on established medical education rubrics. The application delivers a conversational simulation environment where students can practice and refine interviewing and diagnostic skills. It minimizes resource constraints of traditional SP methods while enabling more equitable access across medical institutions. The design safeguards against the generation of erroneous medical advice by relying on expert-created case content. LLM-powered simulations present a new frontier for medical training in clinical communication and reasoning. The application stands out for its low operational costs, scalability, and multi-language capabilities, enhancing global accessibility. Continuing to evaluate the models’ fidelity, bias, and performance across different languages is pivotal to ensure its robustness and effectiveness in medical education.
Assessing the Quality of Content Related to Osteonecrosis of the Femoral Head on YouTube: A Quantitative Analysis (Preprint)
Authors: Fu Weili , Hu Yunan , Zhang Lei , Fan Lei
Published: May 2024

BACKGROUND

Osteonecrosis of the femoral head (ONFH) is a debilitating condition that can lead to chronic pain, joint destruction, and disability. YouTube has become a popular platform for people to seek and share health-related content, but the lack of regulation and oversight has raised concerns about the accuracy and reliability of the information presented.

OBJECTIVE

To evaluate the Quality of Content Related to Osteonecrosis of the Femoral Head on YouTube

METHODS

The videos were assessed for quality using internationally recognized medical information evaluation scores, including the DISCERN score, the Journal of the American Medical Association score (JAMA score), and the Global Quality Scale score (GQS). The completeness of each video content was evaluated based on a content score, which is adapted from clinical practice guidelines.

RESULTS

A total of 68 videos met eligibility criteria. According to the DISCERN score, 41 (60.3%) videos were classified as very poor to poor. The average DISCERN score, JAMA score, GQS, and content score of the included videos were 36 (SD, 9.38), 1.97 (SD, 0.8), 2.09 (SD, 0.95), and 4.62 (SD, 3.47), respectively. The results showed no significant differences in the basic video characteristics, such as duration, likes, dislikes and comments for videos from various sources. Videos uploaded by foundation/medical organizations obtained the highest scores on all four scales (P＜0.001). The correlation analysis showed that DISCERN score was significantly and positively correlated with JAMA score, GQS, and content score, demonstrating the reliability of the assessment results.

CONCLUSIONS

Our study highlighted that the overall quality of YouTube videos pertaining to ONFH is poor, with many lacking in accuracy, clarity, and usefulness. However, videos uploaded by foundation/medical organizations consistently demonstrated high-quality standards. Much work needs to be done to ensure that patients have access to accurate and informative information about ONFH, leading to improved disease management and health literacy.
Correction: Experiences of Using Digital Mindfulness-Based Interventions: Rapid Scoping Review and Thematic Synthesis (Preprint)
Authors: Osborne Emma Louise , Ainsworth Ben , Hooper Nic , Atkinson Melissa Jayne
Published: May 2024

UNSTRUCTURED
Monitoring the world’s largest and fastest vaccine rollout: developing information systems to track COVID-19 vaccination worldwide (Preprint)
Authors: Brooks Donald Joseph , Kim Carolyn Inae , Mboussou Franck Fortuné , Danovaro-Holliday M. Carolina
Published: May 2024

BACKGROUND

The COVID-19 vaccine rollout presented all immunization information systems (IIS) with challenging demands – requiring in-depth vaccine implementation data at all health system levels in real-time. The system development approaches taken by countries were heterogeneous, with some countries opting to adapt existing systems and others implementing new ones.

OBJECTIVE

Using data reported by Member States to the World Health Organization (WHO), develop a global understanding of a) the types of IIS to monitor COVID-19 vaccination implemented in 2021 and b) the approaches taken by countries to develop these systems.

METHODS

A descriptive analysis of data reported through a supplemental questionnaire of the WHO/UNICEF Joint Reporting Form for Immunization, collecting data for 2021 on a) the use of and developmental approaches taken for seven IIS functions, and b) on modifications needed to digital health frameworks to permit COVID-19 vaccination monitoring.

RESULTS

188 of 194 WHO Member States reported data. For each of the seven IIS functions explored, greater than 85% of responding countries reported that the system was in place for COVID-19 vaccines. In total, two in three (68%) countries reported establishing at least one new system, ranging from 72% in high-income countries (HIC) to 61% in low-income countries (LICs). Concurrently, many countries adapted existing systems to include COVID-19 vaccines, notably those for stock management and safety surveillance. Overall, 55% of countries reported adapting at least one system already in place to COVID-19 vaccines, with 62% of HICs reporting this compared to ~53% for other income groups. On digital health frameworks, 31% of responding countries reported needing to adapt them in relation to COVID-19 vaccination systems, mostly HICs.

CONCLUSIONS

Nearly all countries have adapted existing and / or developed new IIS to monitor COVID-19 vaccination. The approaches varied, notably by income group. Reflection is needed on how to sustain investments made in IIS during the pandemic. Continued support for IIS is critical, given their essential role in program monitoring and performance.