bluuebunny/crossref_metadata_2025_split huggingface dataset:
The association between Lipid accumulation products and Migraine Risk : results from the 1999-2004 NHANES analysis
Authors: Yang Shiqiang , Liu Yanwei , Wang Shiqiang , Peng Hua , Zhou Hu , Hui Xuhui , Yang Anqiang 
Published: January 2025

Abstract

Background:Lipid accumulation Products(LAP) is a novel indicator of obesity. Migraine is a debilitating neurological disorder associated with severe pain. The relationship between LAP and migraine is unclear. This study used the National Health and Nutrition Examination Survey (NHANES) database from 1999-2004 to explore the relationship between Lipid accumulation products and migraine.
Methods: This study used data from adults in NHANES from 1999 to 2004 for analysis. Logistic multiple regression analysis and restricted cubic spline (RCS) models were used in the study to elucidate the relationship between LAP and migraine. Subgroup analyses and sensitivity analyses were performed to validate the results.
Results: Eventually 5660 participants entered the final analysis. 1129 (19.9%) cases reported having migraine or severe headaches. Based on the results of weighted Logistic analyses, a nonlinear relationship of type U between LAP and migraine was observed. When LAP was used as a continuous variable, its ratio OR= 1.001, 95% CI: 1 to 1.002, p = 0.191. LAP tertiles were grouped. Both the T1 group with lower LAP (OR = 1.16, 95% CI: 1.02-1.29, p = 0.011) and the T3 group with higher LAP (OR = 1.29, 95% CI: 1.12-1.59, p = 0.008) had a higher incidence of migraines compared to the medium group(T2). Results remained stable in models adjusted for multiple covariates.
Conclusion: The study demonstrated a U-shaped like non-linear relationship between LAP and the occurrence of migraine.Lower and higher LAP were positively associated with elevated migraine occurrence. These findings are noteworthy for migraine prevention.
Application of next-generation sequencing-based technologies for the identification of cereal-based allergens
Authors: Tang Yuxin , Kang Wenhan , Wu Shaozong , Lei Hongtao , Yu Ning , Chen Ying 
Published: January 2025

Abstract

Cereal allergy has a high prevalence and incidence of sensitization worldwide, posing a serious safety risk to cereal-allergic populations. Multiple cereal allergens are often present in foods, and the complex matrix of cereal allergen-containing foods can easily affect identification. At the same time, processed foods are susceptible to contamination with trace amounts of cereal allergens such as wheat and buckwheat. Therefore, it is imperative to accurately identify multiple cereal allergens in foods. It has been shown that next-generation sequencing technologies can identify multiple species components at once and quantify species components relative to each other by relative abundance. In summary, four cereal allergens, including barley, wheat, buckwheat and sweet buckwheat were identified in the study using next-generation sequencing technology. The results showed that: ① this method can simultaneously identify wheat, barley, buckwheat, and sweet buckwheat allergens in the samples and determine the high or low content of the target allergens in the samples; ② the detection limit is as low as 0.1%; ③ is suitable for the detection of commercially available food products contain cereal allergens. In conclusion, this method provides solid and robust technical support for detecting cereal-like allergens in foods, reducing the possibility of exposure to target allergens.
A Simulation Environment for Robot-Assisted Endovascular Interventions
Authors: Pescio Matteo , Li Chenhao , Kundrat Dennis , Casadio Maura , Dagnino Giulio 
Published: January 2025

Abstract

Purpose
Cardiovascular diseases are the leading cause of mortality globally. Advances in interventional radiology and endovascular devices have made endovascular procedures effective alternatives to traditional open surgery, leading to their routine application in clinical practice. Within this framework, novel technologies, including robotic platforms and navigation software, have been developed to assist clinicians in executing endovascular interventions with improved dexterity, enhanced guidance, and superior clinical training, ultimately yielding better patient outcomes.
Methods
This study aims to develop a model-based simulation environment within the SOFA Framework, to enable shape and force sensing for endovascular robotic procedures. The vascular catheter was modeled using beam theory and realistic interactions between the catheter and vascular models were established using the Finite Element Method (FEM) with both linear elastic and nonlinear hyper-elastic models. Experiments measured contact forces and positional changes during catheter insertion, comparing anatomical deformations with simulation results.
Results
Experimental tests validated the simulated force and displacement measurements. The catheter contact force showed an absolute error of 0.0371 N (30.45%). Catheter tip displacement averaged 3.1 mm, and the proximal segment’s Fréchet distance averaged 3.6 mm. For the anatomical model, the Elastic FEM model performed best, with deformation measurement errors of 34%, 19%, and 59% across three different force scenarios.
Conclusion
The results indicate that the integration of advanced physical modeling, realistic human-robot interactions, and enhanced computational capabilities will facilitate the development of innovative solutions, enabling clinicians to achieve greater accuracy and reliability in minimally invasive surgical (MIS) applications, particularly in endovascular interventions.
Key Determinants of Nutritional Status Among Children Under Five in Uganda: Insights from the 2016 Demographic and Health Survey
Authors: Aboda Carol , Semakula Henry Musoke , Wasswa Hannington , Nakibuule Betty 
Published: January 2025

Abstract

Background: Despite concerted efforts by the Ugandan government to combat child malnutrition, it remains a persistent and significant public health challenge. The persistence of child malnutrition in Uganda is attributed to deep-rooted factors which have not been adequately examined. Using data from the 2016 Uganda Demographic and Health Survey (UDHS), this study analyzes the determinants of nutritional status among children under five, focusing on stunting, wasting, and underweight as key indicators.
Methods:This study focused on 4324 children under five. The UDHS dataset used in this study was the Kids Recode file. Stunting, wasting and underweight were the dependent variables whose z-scores, where categorized based on WHO growth standards. The independent variables extracted included characteristics of the child, mother and household. Descriptive analysis was performed to generate summarized statistics, while inferential statistics by way of bivariate analysis were performed to assess the association between the outcome and the independent variables using the chi-square test, and multivariable logistic regression modelling to determine the magnitude of the associations after controlling for other covariates. All analyses considered the survey sampling design and sampling weights, and were conducted in Stata version 18.
Results: Children whose mothers attained a university level education had 330% higher odds of being stunted. Children whose mothers were Anglican had 160% higher odds of being underweight. Children who were given fortified baby food had higher odds (15.6 times) of being stunted. The odds of children being underweight increased by 350% if they resided in North Buganda. Children whose households had refrigerators, had higher odds (4.0 times) of being underweight. The odds of children being wasted reduced between 40% and 60% if they were fed with eggs, potatoes, cassava, or other tubers.
Conclusions: The results highlight areas of intervention that can reduce child malnutrition in Uganda and these include: promoting family-friendly policies, such as maternity leave and breastfeeding support in workplaces; caregivers should be educated on how to properly use fortified baby foods as part of a balanced diet; nutrition programs should promote the inclusion of eggs, tubers, as part of a balanced diet.
Assessment of Urban Fire Risk Coverage and Accessibility through a Network and Spatial GIS Analysis of the Distribution of Fire Stations Case Study ( Irbid City – Jordan)
Authors: Gharaibeh Sora 
Published: January 2025

Abstract

This research addresses the growing demand for enhanced urban fire risk management in Irbid city, Jordan, which has seen significant population growth due to rural-urban migration and the influx of refugees from Syria. As urban expansion heightens fire risks, effective spatial planning for emergency response infrastructure becomes crucial. The study proposes a comprehensive model for urban fire risk mapping at the city scale, employing an integrated approach that combines Geographic Information Systems (GIS) Network Analysis, GIS Spatial Analysis, and Simple Additive Weighting (SAW). These methodologies are applied to evaluate and optimize the spatial distribution of fire stations across Irbid. The model incorporates six key components critical to fire risk assessment: population density, historical fire incident data, land-use patterns, adjacency of buildings, vertical building density, and accessibility. By leveraging these variables, the model aims to provide a nuanced analysis of urban fire risks. It also addresses limitations related to time constraints, challenges in accessing high-quality data, and difficulties in accurately representing population density variations across small geographical distances. The findings of the study, based on a classification system dividing the city into nine fire risk categories, suggest that new fire stations should be strategically located in densely built-up, central areas, rather than in peripheral zones. This spatial prioritization is designed to enhance emergency response coverage and mitigate fire hazards more effectively. The research contributes to urban planning by offering a data-driven framework that supports decision-makers in optimizing fire station placement, thereby improving overall fire risk management in Irbid.
Risk prediction of postoperative renal dysfunction based on preoperative lipid profiles in renal transplant recipients: A retrospective cohort study
Authors: Zhang Hong , Zhang Haoxiang , Li Ronghua , Zhuo Lin , Liu Ling , Tan Ling , Li Rongrong , Zhang Sai 
Published: January 2025

Abstract

Background
Renal dysfunction is a frequent complication after kidney transplantation, leading to poor prognosis and increased mortality. Abnormal blood lipids are closely related to renal dysfunction, yet their associations and mechanisms among renal transplant recipients remain unclear. This study aimed to establish an effective risk prediction model for renal dysfunction among RTRs based on abnormal lipid profiles using machine learning.
Methods
This retrospective cohort study recruited a cohort of 345 RTRs and followed up for one year after renal transplantation. Patients' demographic and clinical characteristics, including blood lipids, were retrieved from the electronic medical record system and analyzed using machine learning. Renal dysfunction was defined as estimated glomerular filtration rate (eGFR) < 60 mL/min /1.73 m2. The cohort was randomly split into training (n = 276) and validation (n = 69) groups at a 4:1 ratio. Predictors of renal dysfunction were determined using three ML models: RandomForest, XGBoost, and LightGBM.
Results
During the one-year follow-up, 193 (55.9%) patients had renal dysfunction. A total of 20 demographic and clinical variables were selected to screen for significant predictors of renal dysfunction, and five were retained, including age, gender, HDL-C, non-HDL-C, and LDL-C, based on which a nomogram was developed. The nomogram showed good diagnostic performance with an area under the curve (AUC) of 0.87 in the training group and 0.81 in the validation group.
Conclusions
Our study showed that preoperative lipid profiles predicted postoperative renal function among RTRs, based on which we developed a risk prediction model. The model can quickly identify high-risk RTRs with renal dysfunction, which is crucial for optimizing patient management and improving the prognosis.
Sensor with strong solid emission for fluorescence colormetric detection of 1, 4-dioxane in Water and vapor based on the Keto-Enol isomerisation
Authors: Wang Jing , Zong Zi-Ao , Huang Shi-Fu , Muddassir Mohd. , Xing Zhi-Yong , Li Na-Na , Jiang Wen Qiong 
Published: January 2025

Abstract

In this work, an easy prepared solid fluorescent sensor 3-(benzo[d]thiazol-2-yl)-1-hydroxy-4-oxo-3,4-dihydrophthalazine-6-carboxylic acid (BPCA) was designed and synthesized and the structure was proved by IR, UV-Vis, NMR, HRMS and elemental analysis, which displayed high selectivity and sensitivity for fluorescence colormetric from green to blue sensing 1, 4-dioxane in water, and the detection limit was obtained 0.009% and the stability constant was 7.4×104 M. Also, sensor BPCA was applied for the real-time monitoring 1, 4-dioxane vapor with apparent fluorescent color change from green to blue. The mild and specific chemical interaction between sensor BPCA and 1, 4-dioxane molecule allowed the sensor as portable chips to respond 1, 4-dioxane vapor with good selectivity over other common VOCs at room temperature. Also, the sensing mechanism based on the 1, 4-dioxane-induced keto-enol tautomerization of the phthalazine moiety was found and supported by DFT calculations.
Statistical Characteristics of K6 as an Explanatory Variable in the United States and China
Authors: stern steven , lu xin 
Published: January 2025

Abstract

We consider many ways to use K6 as an explanatory variable in equations for marriage and employment. We find that a) it is inappropriate transform K6 into a binary variable; b) it is inappropriate to add the K6variables into a single sum of Lykert scales; c) there are serious issues associated with using each of the K6 variables separately; and d) each possible way to use K6 has critical issues making its use problematic.
Pilonadal disease: Rationale for the original method of radical surgery
Authors: Sergatskiy K. I. , Aljabr M. , Nikolskiy V. I. , Romanova V. S. 
Published: January 2025

Introduction. Considering the dissatisfaction with the results of existing methods for treating the pilonadal disease, the search for the most effective methods of radical surgery is currently ongoing.Aim. To evaluate the feasibility of using in patients with chronic epithelial coccygeal tract an original method of radical treatment, consisting of excision of the substrate of the disease, plastic surgery of the sacrococcygeal fascia and suturing of the soft tissue defect with vertical polyspaste sutures.Materials and methods. Main group: 34 patients who underwent an original method of radical surgical treatment. Comparison group: 34 patients who underwent traditional radical excision of the disease substrate.Results. In the main group, less severe pain was recorded (p < 0.05) on days 1–6 after surgery. In terms of the total number of complications, a significant difference in results was demonstrated with a predominance of the indicator in patients in the comparison group (χ2 = 12.324; p = 0.0004). A significant difference (p < 0.05) was also obtained in the healing time of surgical wounds, with the lowest values in patients after the original surgical technique.Discussion. The study demonstrated an alternative technique, the implementation of which resulted in a significant reduction in the number of wound complications, severity of pain in the intervention area, average wound healing time, and also noted better quality of life indicators compared to patients who underwent traditional surgery.Conclusions. The implementation of an original method of radical surgical treatment of the epithelial coccygeal tract can reliably reduce the severity of pain on days 1–6 of the postoperative period, reduce the number of early postoperative complications by 38.23%, and also reduce the average wound healing time by 16 days compared with similar indicators after traditional radical excision of the pilonidal sinus.
A Promising Druggable Target for Translational Therapy of Ovarian Cancer: A Molecular Profiling of Therapeutic Innovations, Extracellular Vesicle Acquired Resistance, and Signaling Pathways
Authors: Mustafa Mohd , Abbas Kashif , Ahmad Waleem , Ahmad Rizwan , Islam Sidra , Khan Hamda , . Moinuddin , Hassan Md Imtaiyaz , Parveen Shazia , Habib Safia 
Published: January 2025

Abstract:
Ovarian cancer (OC) ranks as the fifth leading cause of cancer-related deaths
in the United States, posing a significant threat to female health. Late-stage diagnoses,
driven by elusive symptoms often masquerading as gastrointestinal issues, contribute to
a concerning 70% of cases being identified in advanced stages. While early-stage OC
brags a 90% cure rate, progression involving pelvic organs or extending beyond the peritoneal
cavity drastically diminishes it. Overcoming chemoresistance and metastasis requires
a deep understanding of the associated progression mechanisms for innovative
therapies. Extracellular vesicles (EVs), containing proteins, RNAs, DNAs, and metabolites,
have surged in recent years, significantly impacting tumor progression, recurrence,
immune evasion, and metastasis associated with the ovarian tumor microenvironment.
Recent research unveils organ-specific metastatic patterns in OC, providing insights into
tumor cell interactions and signaling crosstalk with stromal cells. The review explores
the role of EVs behind OC cell metastasis and chemoresistance. Furthermore, the article
delves into the role of EVs in the tumor microenvironment, immune evasion, and as biomarkers
in context to OC, offering promising therapeutic strategies to enhance survival
rates for OC patients. Lastly, the article focuses on an overview of PI3K/AKT/mTOR,
MAPK/ERK, and VEGFR signaling pathways in the pathophysiology of ovarian cancer.
Computational Model to Predict Potential Therapeutic Targets Employing Generative Adversarial Networks for Analysis of Proteins Involved in Mycobacterium fortuitum Biofilm Formation
Authors: Ghai Shan , Shrivastava Rahul , Jain Shruti 
Published: January 2025

Abstract:
A planktonic population of bacteria can form a biofilm by adhesion and colonization.
Proteins known as “adhesins” can bind to certain environmental structures,
such as sugars, which will cause the bacteria to attach to the substrate. Quorum sensing
is used to establish the population is dense enough to form a biofilm. This paper presents
a comprehensive overview of our investigation into these processes, specifically focusing
on Mycobacterium fortuitum, an emerging pathogen of increasing clinical relevance.
In our study, we detailed the methodology employed for the proteomic analysis
of M. fortuitum, as well as our innovative application of Generative Adversarial Networks
(GANs). These advanced computational tools allow us to analyze complex data
sets and identify patterns that might otherwise remain obscured. With a particular focus
on the effectiveness of GAN, the identified proteins and their potential roles in the context
of M. fortuitum's pathogenesis were discussed. The insights gained from this study
can significantly contribute to our understanding of this emerging pathogen and pave the
way for developing targeted interventions, potentially leading to improved diagnostic
tools and more effective therapeutic strategies against M. fortuitum infection. The authors
can achieve 95.43% accuracy for the generator and 87.89% for the discriminator.
The model was validated by considering different Machine learning algorithms, reinforcing
that integrating computational techniques with microbiological investigations can
significantly enhance our understanding of emerging pathogens. Overall, this study emphasizes
the importance of exploring the molecular mechanisms behind biofilm formation
and pathogenicity, providing a foundation for future research that could lead to innovative
solutions in combating infections caused by M. fortuitum and other similar pathogens.
Experimental Evidence of the Benefits of Acupuncture/Electroacupuncture for Acute Lung Injury/ Acute Respiratory Distress Syndrome: A Literature Review of Rodent Studies
Authors: Zeng Lin , Yan Jiangtian 
Published: January 2025

Abstract:
Acute lung injury (ALI) and acute respiratory distress syndrome (ARDS)
encompass various etiologies and are distinguished by the onset of acute pulmonary
inflammation and heightened permeability of the pulmonary vasculature, often leading
to substantial morbidity and frequent mortality. There is a scarcity of viable approaches
for treating effectively. In recent decades, acupuncture has been proven to be antiinflammatory.
This review aims to provide a comprehensive summary of the previously
documented mechanisms underlying the beneficial effects of acupuncture in
ALI/ARDS, including inhibiting excessive oxidative stress, alleviating pulmonary
inflammatory response, suppressing programmed cell death, and protecting the
alveolar-capillary membrane. Collectively, these findings indicate that acupuncture
yields therapeutic benefits for ALI/ARDS.
Cu@DPP-SPION: A Novel and Versatile Catalyst for the Synthesis of Thioxo-Tetrahydropyrimidine Derivatives under Mild Reaction Conditions
Authors: Ghasemi Nastaran , Moradi Shahram , Mahdavi Mohammad , Iraji Aida 
Published: January 2025

Introduction:
The development of efficient and sustainable catalytic methodolo-gies has garnered considerable attention in contemporary organic synthesis.

Methods:
Herein, we present a novel approach employing the Cu@DPP-SPION catalyst for the synthesis of ethyl 4-(aryl)-6-methyl-2-thioxo-1,2,3,4-tetrahydropyrimidine-5-carboxylate derivatives. This versatile catalytic system incorporates copper nanoparticles supported on 4-(1H-imidazo[4,5-f][1,10]phenanthrolin-2-yl)benzoic acid-functionalized superparamagnetic iron oxide nanoparticles (SPIONs). The catalyst was meticulously characterized through scanning electron microscopy (SEM), transmission electron microscopy (TEM), dynamic light scattering (DLS), Fourier-transform infrared spectroscopy (FTIR), energy dispersive spectroscopy (EDS), and inductively coupled plasma (ICP) analysis. The catalytic process, exemplified by the synthesis of heterocyclic compounds, demonstrated high isolated yields, attesting to the robust performance of the catalyst.

Results:
Furthermore, the reusability of the catalyst was validated through five consecutive reactions without a notable decrease in yield, while structural stability was confirmed by SEM analysis. The methodology combines green reaction conditions, room temperature operation, and facile magnetic catalyst separation, underscoring its potential for sustainable synthesis.

Conclusion:
This work highlights the promise of the Cu@DPP-SPION catalyst as an innova-tive tool in heterogeneous catalysis and its role in advancing efficient and environmentally conscious synthetic methodologies.