bluuebunny/crossref_metadata_2025_split huggingface dataset:
Tetrafunctionalized Azocalix[4]resorcinarene Dye: A Chromogenic Supramolecule Used for the Selective Liquid-Liquid Extraction and Spectrophotometric Determination of Cu(II)
Authors: Kanaiya Parin H. , Jain Vinod K. 
Published: October 2024

Background:
The detection and extraction of trace metal ions, particularly copper(II), are
critical for environmental monitoring and industrial processes. Calixresorcinarene, with its unique
cavity structure, offers excellent platforms for designing selective chemosensors and extractants.
Functionalization of calixresorcinarene with azo groups can enhance their chromogenic properties,
enabling both extraction and detection in a single step.

Objective:
This study aimed to evaluate its (Azocalix[4]resorcinaren) efficacy as a selective
chemosensor for the liquid-liquid extraction and spectrophotometric determination of Cu(II) ions.

Methods:
Application in Extraction and Detection: The ability of the dye to selectively extract
Cu(II) ions from aqueous solutions was investigated via liquid-liquid extraction experiments. The
dye-Cu(II) complex formation was monitored by UV-Vis spectrophotometry, with systematic optimization
of experimental conditions, including pH, solvent system, and extraction duration.

Results:
The synthesized azocalix[4]resorcinarene dye exhibited a pronounced selectivity towards
Cu(II) ions, forming a stable, colored complex. The complexation induced a distinct bathochromic
shift in the absorption spectrum, allowing for precise spectrophotometric detection. Optimal extraction
was achieved at a specific pH and solvent combination, with the method demonstrating a low
detection limit and high sensitivity. The dye showed minimal interference from other metal ions,
confirming its selectivity for Cu(II).

Conclusion:
The tetrafunctionalized azocalix[4]resorcinarene dye is a highly effective chromogenic
agent for the selective extraction and detection of Cu(II) ions. Its robust performance in both extraction
efficiency and spectrophotometric detection underscores its potential utility in environmental
analysis and industrial applications where trace metal detection is crucial.
PEGylated Titanium Dioxide Nanoparticle-bound Doxorubicin and Paclitaxel Drugs Affect Prostate Cancer Cells and Alter the Expression of DUSP Family Genes
Authors: Tuncbilek Zuhal , Cakmak Nese Keklikcioglu , Tas Ayca , Ayan Durmus , Silig Yavuz 
Published: October 2024

Background:
Prostate cancer (PC) is among the cancer types with high incidence and mortality. New
and effective strategies are being sought for the treatment of deadly cancers, such as PC. In this context, the use
of nanocarrier systems containing titanium dioxide (TiO2) can improve treatment outcomes and increase the effectiveness
of anticancer drugs.

Objective:
This study aimed to evaluate the cytotoxic activity of doxorubicin (DOX) and paclitaxel (PTX) drugs
on the PC cell line by attaching them to PEGylated TiO2 nanoparticles and to examine their effect on the expression
levels of dual-specificity phosphatase (DUSP) genes.

Methods:
Free DOX and PTX drugs, DOX and PTX compounds bound to the pegylated TiO2 system were applied
to DU-145 cells, a PC cell line, under in vitro conditions, and MTT analysis was performed. Additionally,
the IC50 values of these compounds were analyzed. In addition, the expression levels of DUSP1, DUSP2, DUSP4,
DUSP6, and DUSP10 genes were measured using RT-PCR. Additionally, bioinformatics and molecular docking
analyses were performed on DUSP proteins.

Results:
The cytotoxic activity of PTX compound bound to PEGylated TiO2 was found to be higher than that of
DOX compound bound to PEGylated TiO2. Additionally, when the expression levels were compared to the control
group, the expression levels of DUSPs were found to be lower in the drugs of the drug carrier systems.

Conclusion:
Accordingly, it was predicted that the PEGylated TiO2 nano-based carrier could be effective in
PC.
In Silico and ADMET Studies of Spiro-Quinazoline Compounds as Acetylcholine Esterase Inhibitors Against Alzheimer’s Disease
Authors: Aljuaid Abdulelah , Abdulaziz Osama , Allahyani Mamdouh , Almehmadi Mazen , Alzahrani Abdullah Yahya  Abdullah , Verma Shivani , Yusuf Mohd , Asif Mohammad 
Published: October 2024

Background:
Alzheimer's disease (AD) is a prevalent neurodegenerative condition characterized
by progressive cognitive decline and memory impairment resulting from the degeneration
and death of brain neurons. Acetylcholinesterase (AChE) inhibitors are used in primary pharmacotherapy
for numerous neurodegenerative conditions, providing their capacity to modulate acetylcholine
levels crucial for cognitive function. Recently, quinazoline derivatives have emerged as a
compelling model for neurodegenerative disease treatment, showcasing promising pharmacological
features. Their unique structural features and pharmacokinetic profiles have sparked interest in their
potential efficacy and safety across diverse neurodegenerative disorders. The exposure of quinazoline
derivatives as a potential therapeutic way underscores the imperative for continued research exploration.
Their multifaceted mechanisms of action and ability to target various pathways implicated
in neurodegeneration offer exciting prospects for developing novel, effective, and well-tolerated
treatments. Further investigations into their pharmacological activities and precise therapeutic roles
are essential to advance our understanding of neurodegenerative disease pathophysiology and promote
the development of modern therapeutic strategies to address this critical medical challenge.

Methods:
Quinazoline derivatives have gained eminent acetylcholinesterase (AChE) inhibitory activity.
Their ability to effectively modulate AChE activity makes them promising candidates for
treating neurological disorders, particularly Alzheimer's disease (AD). Their intricate molecular
structures confer selectivity and affinity for AChE, offering potential for the development of novel
therapeutic agents targeting cholinergic pathways. Hence, in this study, we designed, synthesized,
and characterized a series of spiro[cycloalakane-1,2'-quinazoline derivatives (1-6) to assess their
possible AChE inhibiting ability using docking into the active sites.

Results:
The AChE inhibitory potential of spiro[cycloalkane-1,2'-quinazoline derivatives (1-6) was
explored via docking studies of the AChE active site. The findings revealed significant inhibitory
activity and highlighted the promising nature of these derivatives.

Conclusion:
The synthesized spiro[cycloalkane-1,2'-quinazoline derivatives (1-6) exhibited their
notable potential as AChE inhibitors. The observed significant inhibitory activity suggested that these
derivatives warrant further exploration as candidates for developing therapeutic agents in AChE
inhibitory pathways. This study emphasizes the relevance of quinazoline derivatives in searching for
novel treatments for neurological disorders, particularly associated with cholinergic dysfunction,
and they could be a useful alternative therapeutic agent.
Appropriate Selection of Frequency Range and Damping Ratio to Reduce the Resonance Effect, Lower Power Consumption, and Improve the Accuracy of the Capacitive Accelerometer
Authors: Ghemari Zine , Belkhiri Salah , Saad Salah 
Published: October 2024

Introduction:
In this work, we explored the capacitive accelerometer in depth by highlighting
its advantages over other accelerometers. However, a major challenge associated with using
capacitive accelerometers lies in choosing the appropriate frequency range.

Method:
Incorrect selection of the frequency range can cause several problems. It can decrease the
accuracy of the accelerometer, increase the measurement error, and increase power consumption.
To overcome these challenges, we undertook detailed modeling of the physical behaviour of the capacitive
accelerometer. This modeling takes into account the mechanical and electrical properties of
the sensor, including its mass, its rigidity, and the characteristics of its capacitive circuit. By simulating
the developed model, we analyzed how the accelerometer reacts to different frequencies of
vibratory movements.

Result:
This analysis led to the extraction of an important mathematical relationship that links the
natural frequency of the accelerometer to the frequency of the vibratory movements to which it is
subjected. Using this mathematical relationship, we determined the optimal frequency range for capacitive
accelerometer operation. This precise determination of the frequency range makes it possible
to significantly reduce the measurement error by avoiding resonance regimes and ensuring that
the sensor operates in its maximum precision zone.

Conclusion:
Additionally, this approach helps improve overall measurement accuracy and minimize
sensor power consumption by avoiding inefficient operating conditions.
Key LncRNAs Associated with Distant Metastasis in Breast Cancer: A System Biology Analysis
Authors: Mohammadi Shakila , Dehghani-Samani Mina , Firouzi-Farsani Khatereh , Dibaj Mohsen , Zhaeentan Shahrzad 
Published: October 2024

Introduction:
Breast cancer (BC) is the most prevalent cancer among women globally.
Metastasis is the leading cause of mortality in most cancers. Early BC detection before metastasis
can enhance survival rates. Understanding BC metastasis mechanisms could aid in developing
metastasis-specific treatments.

Method:
The role of long non-coding RNAs (lncRNA) in cancer progression is recognized, yet
the importance of specific lncRNAs in BC, despite potential alterations, remains inadequately
explored. We utilized bioinformatics tools to identify novel lncRNAs dysregulated in metastasis.
To achieve this objective, the gene expression profile of GSE102484, encompassing metastatic
and non-metastatic BC tissue samples, was analyzed using the limma package in R with cut-off
criteria set at an adjusted p-value < 0.005 and |fold change (FC)| ≥ 0.5. We used WGCNA analysis
to find co-expression genes for lncRNAs. Then, we identified hub genes and performed pathway
enrichment to better understand the results. Considering the defined criteria, eight novels of
dysregulated lncRNAs and top 10 miRNAs were identified.

Result:
Dysregulated lncRNAs are found in yellow, green, brown, purple, and turquoise co-expression
modules from WGCNA analysis. Enrichment analysis of these co-expressed modules
revealed relevant pathways to metastasis, such as epithelial-to-mesenchymal transition and integrin
cell-surface interactions, as well as regulation of HIF1-alpha. In addition, SDPR, TGFB1I1,
ILF3, KIF4A, and COL5A1 were identified as hub genes. Based on DElncRNA-miRNADEmRNA
connections and co-expression, we ultimately constructed lncRNA-associated ceRNA
axes.

Conclusion:
The current study may identify novel lncRNAs implicated in BC metastasis; still,
additional research is required to determine the potential functions of these lncRNAs in BC metastasis.
Jamming Attacks Detection Based on IGWO for Optimization of Fast Correlation-Based Feature extraction in Wireless Communication
Authors: Ameen Zinah Jaffar Mohammed , Naman Hala A. , Mahmood Alza Abduljabbar 
Published: October 2024

Background:
Wireless networks are essential communication technologies that prevent
cable installation prices and burdens. Because of this technology's pervasive usage, wireless
network safety is a significant problem. Owing to distributed and open wireless medium
aspects, attackers might use different jamming methods to exploit physical and MAC layer
protocol vulnerabilities. In addition, jamming attacks require to be accurately grouped so that
suitable countermeasures can be considered. Given the potential severity of such attacks, precisely
identifying and classifying them is critical for implementing effective responses. The
motivation for this paper is the need to improve the detection and categorization of jamming
signals using modern machine learning algorithms, consequently enhancing wireless network
security and reliability.

Objective:
In this paper, we compare some machine learning models' efficiency for diagnosing
jamming signals.

Methods:
Such algorithms refer to support vector machine (SVM) and k-nearest neighbors
(KNN). We checked the signal features that recognize jamming signals. After the jamming attack
model, the developed grey wolf optimizer version known as IGWO (improved grey wolf
optimizer) has been discussed for feature extraction of software usability. Four separate metrics
were employed as features to detect jamming attacks in order to evaluate the machine learning
models. This novel feature extraction method is crucial for improving the accuracy of jamming
detection.

Results:
The measurements of these parameters were gathered through a simulation of a real
setting. And generated a large dataset using these parameters.

Conclusion:
The simulation results illustrate that the KNN algorithm based on jamming detection
could diagnose jammers having a minimal likelihood of false alarms and a high level of
accuracy.
User Perceptions of Wearability of Knitted Sensor Garments for Long-Term Monitoring of Breathing Health: Thematic Analysis of Focus Groups and a Questionnaire Survey
Authors: Fobelets Kristel , Mohanty Nikita , Thielemans Mara , Thielemans Lieze , Lake-Thompson Gillian , Liu Meijing , Jopling Kate , Yang Kai 
Published: October 2024

Background
Long-term unobtrusive monitoring of breathing patterns can potentially give a more realistic insight into the respiratory health of people with asthma or chronic obstructive pulmonary disease than brief tests performed in medical environments. However, it is uncertain whether users would be willing to wear these sensor garments long term.

Objective
Our objective was to explore whether users would wear ordinary looking knitted garments with unobtrusive knitted-in breathing sensors long term to monitor their lung health and under what conditions.

Methods
Multiple knitted breathing sensor garments, developed and fabricated by the research team, were presented during a demonstration. Participants were encouraged to touch and feel the garments and ask questions. This was followed by two semistructured, independently led focus groups with a total of 16 adults, of whom 4 had asthma. The focus group conversations were recorded and transcribed. Thematic analysis was carried out by three independent researchers in 3 phases consisting of familiarization with the data, independent coding, and overarching theme definition. Participants also completed a web-based questionnaire to probe opinion about wearability and functionality of the garments. Quantitative analysis of the sensors’ performance was mapped to participants’ garment preference to support the feasibility of the technology for long-term wear.

Results
Key points extracted from the qualitative data were (1) garments are more likely to be worn if medically prescribed, (2) a cotton vest worn as underwear was preferred, and (3) a breathing crisis warning system was seen as a promising application. The qualitative analysis showed a preference for a loose-fitting garment style with short sleeves (13/16 participants), 11 out of 16 would also wear snug fitting garments and none of the participants would wear tight-fitting garments over a long period of time. In total, 10 out of 16 participants would wear the snug fitting knitted garment for the whole day and 13 out of 16 would be happy to wear it only during the night if not too hot. The sensitivity demands on the knitted wearable sensors can be aligned with most users’ garment preferences (snug fit).

Conclusions
There is an overall positive opinion about wearing a knitted sensor garment over a long period of time for monitoring respiratory health. The knit cannot be tight but a snugly fitted vest as underwear in a breathable material is acceptable for most participants. These requirements can be fulfilled with the proposed garments. Participants with asthma supported using it as a sensor garment connected to an asthma attack alert system.
Predictive Models for Sustained, Uncontrolled Hypertension and Hypertensive Crisis Based on Electronic Health Record Data: Algorithm Development and Validation
Authors: Nguyen Hieu Minh , Anderson William , Chou Shih-Hsiung , McWilliams Andrew , Zhao Jing , Pajewski Nicholas , Taylor Yhenneko 
Published: October 2024

Abstract

Background
Assessing disease progression among patients with uncontrolled hypertension is important for identifying opportunities for intervention.

Objective
We aim to develop and validate 2 models, one to predict sustained, uncontrolled hypertension (≥2 blood pressure [BP] readings ≥140/90 mm Hg or ≥1 BP reading ≥180/120 mm Hg) and one to predict hypertensive crisis (≥1 BP reading ≥180/120 mm Hg) within 1 year of an index visit (outpatient or ambulatory encounter in which an uncontrolled BP reading was recorded).

Methods
Data from 142,897 patients with uncontrolled hypertension within Atrium Health Greater Charlotte in 2018 were used. Electronic health record–based predictors were based on the 1-year period before a patient’s index visit. The dataset was randomly split (80:20) into a training set and a validation set. In total, 4 machine learning frameworks were considered: L2-regularized logistic regression, multilayer perceptron, gradient boosting machines, and random forest. Model selection was performed with 10-fold cross-validation. The final models were assessed on discrimination (C-statistic), calibration (eg, integrated calibration index), and net benefit (with decision curve analysis). Additionally, internal-external cross-validation was performed at the county level to assess performance with new populations and summarized using random-effect meta-analyses.

Results
In internal validation, the C-statistic and integrated calibration index were 0.72 (95% CI 0.71‐0.72) and 0.015 (95% CI 0.012‐0.020) for the sustained, uncontrolled hypertension model, and 0.81 (95% CI 0.79‐0.82) and 0.009 (95% CI 0.007‐0.011) for the hypertensive crisis model. The models had higher net benefit than the default policies (ie, treat-all and treat-none) across different decision thresholds. In internal-external cross-validation, the pooled performance was consistent with internal validation results; in particular, the pooled C-statistics were 0.70 (95% CI 0.69‐0.71) and 0.79 (95% CI 0.78‐0.81) for the sustained, uncontrolled hypertension model and hypertensive crisis model, respectively.

Conclusions
An electronic health record–based model predicted hypertensive crisis reasonably well in internal and internal-external validations. The model can potentially be used to support population health surveillance and hypertension management. Further studies are needed to improve the ability to predict sustained, uncontrolled hypertension.
Promoting Digital Health Data Literacy: The Datum Project
Authors: Powell Daniel , Asad Laiba , Zavaglia Elissa , Ferrari Manuela 
Published: October 2024

Abstract
With the increased use of digital health innovations in Canadian health care, educating health care users, professionals, and researchers on the ethical challenges and privacy implications of these tools is essential. The Datum project, funded by the Fondation Barreau du Quebec, was created to help these actors better understand legal and ethical issues regarding the collection, use, and disclosure of digital health data for the purposes of scientific research, thereby enhancing literacy around data privacy. The project consists of a multimedia website divided into legislation and policy documents and narrative-based video content. Users can access the core legislation and policies governing the collection and use of health care data geared toward researchers and health practitioners. Users can also view the narrative-based video content explaining key concepts related to digital health data. The Datum project makes an original contribution to the field of law and ethics in health science research by using novel approaches, such as learning health systems and data banks, to improve equity in health care delivery and by generating multimedia content aimed at encouraging health care users to become better consumers and supporting the collective use of their data. The Datum project also promotes digital literacy as a digital communication tool, which has the significant potential to improve health outcomes, bridge the digital divide, and reduce health inequities.
La gran empresa panificadora en Colombia: Un análisis de su utilidad contable y residual (2017-2021)
Authors: Rivera Godoy Jorge Alberto 
Published: October 2024

El objetivo de esta investigación es analizar la utilidad contable y residual para conocer el desempeño financiero de la gran empresa panificadora en Colombia en el periodo 2017-2021, siguiendo como metodología el análisis de tendencias de indicadores que miden su eficiencia en el uso de activos, la eficacia en el control de costos y gastos y la efectividad en el logro de utilidades, y cotejándolos con los indicadores de la empresa afín en Europa. Se encuentra que la gran empresa panificadora colombiana logra rendimientos sobre el patrimonio cada año con la misma orientación del margen de utilidad neta, pero menos semejante a su rotación de activos y apalancamiento financiero; resultados semejantes se presentaron en la empresa europea, aunque con valores superiores, salvo el multiplicador financiero. Además, la gran empresa panificadora colombiana creó en promedio un porcentaje de utilidad residual, al igual que su homóloga europea, pero superada por esta última. La desventaja con respecto a la empresa europea se debe a su menor eficiencia y eficacia, y al uso de recursos financieros a mayor costo. La investigación podría extenderse para grupos homogéneos en edad, fases de su ciclo de vida, estructura legal y comercio internacional.
The Impact of Restaurant’s Online Food Delivery (OFD) Service Quality on Customers’ Repurchase Intention: A Conceptual Framework
Authors: Mohamad Khan Noor Rita , Ibrahim Muhammad Azman , Mohd Ruslan Rafiatul Adlin , Abd Hamid Nor Harlina , Abdullah Mohamad Fariz 
Published: October 2024

The outbreak of the COVID-19 pandemic in 2020 had a profound impact on the food service industry, forcing many restaurants and eateries to pivot towards online food delivery (OFD) services to survive. This shift, driven by restrictions on dining-in, has persisted even as dine-in services resumed, positioning OFD as an integral part of restaurant operations. This paper explores the impact of service quality in OFD, proposing a conceptual framework that links service quality dimensions—such as delivery speed, order accuracy, customer service, and platform usability—to the customer’s repurchase intention of food from the restaurant via its OFD services. By addressing these dimensions, restaurants can enhance customer satisfaction, leading to improved financial outcomes. This study aims to provide actionable insights for restaurant operators and contribute to the existing literature on service quality within the OFD sector.