bluuebunny/crossref_metadata_2025 huggingface dataset:
The Influence of Multiple Factors on Musicology Doctoral Students’ Academic Performance: An Empirical Study Based in China
Authors: Yan Tingyu , Yu Hong , Tang Jiajun
Published: November 2024

As doctoral education evolves globally, the focus intensifies on doctoral candidates’ academic performance and psychological well-being. Previous research has studied the effects of individual, societal, and environmental factors on students’ academic achievements. However, there is still a lack of investigation into how these factors interact, especially in the domains of arts. This study surveyed 213 Chinese musicology doctoral students and adopted Partial Least Squares Structural Equation Modeling (PLS-SEM) to evaluate how various factors affect academic and mental health outcomes. The analysis shows that factors including teacher support, student engagement, and well-being positively influence academic performance, while academic anxiety negatively impacts academic performance. Moreover, variables help diminish academic anxiety, encompassing self-efficacy, parental support, time management skills, and student engagement. Meanwhile, enhanced doctoral students’ well-being is related to robust teacher support, facilitating conditions, and active student engagement. Notably, students who experience academic anxiety about their studies generally have lower well-being. These findings indicate that alleviating academic anxiety, refining academic resources, and reinforcing mental health supports can foster academic and psychological outcomes for doctoral students. Our study contributes vital empirical data to developing higher education policies, benefiting doctoral students’ mental health and academic success.
School Connectedness and Academic Burnout in Middle School Students: A Multiple Serial Mediation Model
Authors: Zhao Hui , Han Mengjiao , Wang Zhenzhen , Liu Bangdan
Published: November 2024

Higher levels of school connectedness are associated with better study habits, but their relationship with academic burnout and the underlying mechanisms have not been revealed. We used a questionnaire to investigate the relationship between school connectedness and academic burnout and the mediating mechanisms of burnout in a sample of 394 Chinese middle school students, controlling for class, gender, and grade level. The results revealed that (1) school connectedness, autonomous motivation to learn, and core self-evaluations were significantly negatively related to academic burnout; and that (2) academic self-handicapping, core self-evaluations, and autonomous motivation to learn individually mediated the effects of school connectedness on academic burnout and mediated the effects of multiple factors. Therefore, educators should pay attention to the emotional needs of junior high school students, increase the level of school connectedness, consciously help students cultivate positive psychological factors such as autonomous motivation and core self-evaluations, reduce academic self-handicapping, increase their learning pleasure, and alleviate junior high school students’ academic burnout.
Exploring the Impact of After-Hours Work Connectivity on Employee Performance: Insights from a Job Crafting Perspective
Authors: Fan Chuanhao , Dong Tianfeng , Wang Jiaxin
Published: November 2024

With the leapfrog development of information and communication technology and the intensification of external competition among enterprises, after-hours work connectivity through communication devices has become a new norm in the workplace. While it offers certain conveniences, the constant connectivity it entails also imposes significant pressure on employees. How to comprehensively understand and rationally treat after-hours work connectivity has become an issue that organizations need to pay great attention to. Based on conservation of resources theory, this study analyzed 407 questionnaires to explore the “double-edged sword” effect of after-hours work connectivity on employee performance and analyzed the moderating effect of the psychological contract. The results indicate the following: (1) Proactive pathway: after-hours work connectivity promotes employees’ job crafting behaviors toward approach-oriented adjustments, thereby enhancing job performance. (2) Passive pathway: after-hours work connectivity encourages employees’ job crafting behaviors toward avoidance-oriented adjustments, leading to decreased job performance. (3) The psychological contract positively moderates the relationship between after-hours work connectivity and approach-oriented job crafting and negatively moderates the relationship between after-hours work connectivity and avoidance-oriented job crafting, regulating both the positive and negative coping pathways. The research findings contribute to assisting organizations in adopting a dialectical perspective towards and effectively utilizing after-hours work connectivity. This aids in achieving a balance between organizational effectiveness and employee well-being, seeking a mutually beneficial work paradigm, and providing managerial recommendations to promote sustainable organizational development.
Deformation Analysis and Reinforcement Effect Evaluation for the No. 65 Slope on the Shangsan Expressway Based on SBAS-InSAR
Authors: Bai Dongxin , Lu Guangyin , Hu Huihua , Lin Hang , Chen Changfu , Wang Xuan
Published: November 2024

The deformation of the No. 65 slope on the Shangsan Expressway poses a potential threat to road safety. In July 2021, the deformation rate of this slope accelerated significantly, leading to the implementation of reinforcement measures in 2022. To comprehensively analyze the historical deformation characteristics of the slope and evaluate the effectiveness of the reinforcement measures, this study employs Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) technology to calculate and analyze the historical deformation characteristics of the slope and the adjacent hillside for two periods: from 10 January 2018 to 22 August 2021, and from 3 September 2021 to 22 December 2023. The SBAS-InSAR monitoring results were compared with in situ data from borehole inclinometers to verify the reliability of the calculations. The SBAS-InSAR results indicate that before reinforcement, the slope exhibited slow movement; however, after the implementation of the reinforcement measures, the displacement significantly decreased, demonstrating the success and effectiveness of the interventions. The consistency between the SBAS-InSAR results, borehole inclinometer data, and surface observations confirms the substantial potential of SBAS-InSAR technology for slope engineering monitoring.
A Machine Learning Model Based on Thyroid US Radiomics to Discriminate Between Benign and Malignant Nodules
Authors: Guerrisi Antonino , Seri Elena , Dolcetti Vincenzo , Miseo Ludovica , Elia Fulvia , Lo Conte Gianmarco , Del Gaudio Giovanni , Pacini Patrizia , Barbato Angelo , David Emanuele , Cantisani Vito
Published: November 2024

Background/Objectives: Thyroid nodules are a very common finding, mostly benign but sometimes malignant, and thus require accurate diagnosis. Ultrasound and fine needle biopsy are the most widely used and reliable diagnostic methods to date, but they are sometimes limited in addressing benign from malignant nodules, mainly with regard to ultrasound, by the operator’s experience. Radiomics, quantitative feature extraction from medical images and machine learning offer promising avenues to improve diagnosis. The aim of this work was to develop a machine learning model based on thyroid ultrasound images to classify nodules into benign and malignant classes. Methods: For this purpose, images of ultrasonography from 142 subjects were collected. Among these subjects, 40 patients (28.2%) belonged to the class “malignant” and 102 patients (71.8%) belonged to the class “benign”, according to histological diagnosis from fine-needle aspiration. This image set was used for the training, cross-validation and internal testing of three different machine learning models. A robust radiomic approach was applied, under the hypothesis that the radiomic feature could capture the disease heterogeneity among the two groups. Three models consisting of four ensembles of machine learning classifiers (random forests, support vector machines and k-nearest neighbor classifiers) were developed for the binary classification task of interest. The best performing model was then externally tested on a cohort of 21 new patients. Results: The best model (ensemble of random forest) showed Receiver Operating Characteristic-Area Under the Curve (ROC-AUC) (%) of 85 (majority vote), 83.7 ** (mean) [80.2–87.2], accuracy (%) of 83, 81.2 ** [77.1–85.2], sensitivity (%) of 70, 67.5 ** [64.3–70.7], specificity (%) of 88, 86.5 ** [82–91], positive predictive value (PPV) (%) of 70, 66.5 ** [57.9–75.1] and negative predictive value (NPV) (%) of 88, 87.1 ** [85.5–88.8] (* p < 0.05, ** p < 0.005) in the internal test cohort. It achieved an accuracy of 90.5%, a sensitivity of 100%, a specificity of 86.7%, a PPV of 75% and an NPV of 100% in the external testing cohort. Conclusions: The model constituted of four ensembles of random forest classifiers could identify all the malignant nodes and the consistent majority of benign in the external testing cohort.
p21Waf1/Cip1 Is a Novel Downstream Target of 40S Ribosomal S6 Kinase 2
Authors: Basu Alakananda , Xuan Zhenyu
Published: November 2024

Background/Objectives: The ribosomal S6 kinase 2 (S6K2) acts downstream of the mechanistic target of rapamycin complex 1 and is a homolog of S6K1 but little is known about its downstream effectors. The objective of this study was to use an unbiased transcriptome profiling to uncover how S6K2 promotes breast cancer cell survival. Methods: RNA-Seq analysis was performed to identify novel S6K2 targets. Cells were transfected with siRNAs or plasmids containing genes of interest. Western blot analyses were performed to quantify total and phosphorylated proteins. Apoptosis was monitored by treating cells with different concentrations of doxorubicin. Results: Silencing of S6K2, but not S6K1, decreased p21 in MCF-7 and T47D breast cancer cells. Knockdown of Akt1 but not Akt2 decreased p21 in MCF-7 cells whereas both Akt1 and Akt2 knockdown attenuated p21 in T47D cells. While Akt1 overexpression enhanced p21 and partially reversed the effect of S6K2 deficiency on p21 downregulation in MCF-7 cells, it had little effect in T47D cells. S6K2 knockdown increased JUN mRNA and knockdown of cJun enhanced p21. Low concentrations of doxorubicin increased, and high concentrations decreased p21 levels in T47D cells. Silencing of S6K2 or p21 sensitized T47D cells to doxorubicin via c-Jun N-terminal kinase (JNK)-mediated downregulation of Mcl-1. Conclusions: S6K2 knockdown enhanced doxorubicin-induced apoptosis by downregulating the cell cycle inhibitor p21 and the anti-apoptotic protein Mcl-1 via Akt and/or JNK.
The Role of Robotic Cystectomy in the Salvage and Palliative Setting: A Retrospective, Single-Center, Cohort Study
Authors: Brassetti Aldo , Cacciatore Loris , Proietti Flavia , Pallares-Méndez Rigoberto , Bove Alfredo Maria , Anceschi Umberto , Mastroianni Riccardo , Misuraca Leonardo , Tuderti Gabriele , Chiacchio Giuseppe , Ferriero Mariaconsiglia , Flammia Rocco Simone , Leonardo Costantino , Simone Giuseppe
Published: November 2024

Introduction: This article compares surgical and survival outcomes of robot-assisted and open radical cystectomy with cutaneous ureterostomy for the treatment of frail bladder cancer patients with limited life expectancy. Methods: The institutional database was searched for cystectomy cases with cutaneous ureterostomy, from 1 June 2016 to 31 August 2022. The study population was split into two groups, according to the surgical approach. The baseline characteristics and surgical outcomes were compared. Logistic regression analyses identified predictors of major bleeding events (hemoglobin loss ≥ 3.5 g/dL or blood transfusion) and re-operation within 30 days from surgery. The Kaplan–Meier method estimated the impact of the robotic approach on overall survival and Cox regression analysis assessed its predictors. Results: A total of 145 patients were included: 30% (n = 43) underwent robotic cystectomy. Patients’ characteristics and tumor stages distribution were comparable in the two groups but those receiving a minimally invasive treatment showed significantly reduced times to flatus, bowel and hospital discharge (all p < 0.001). Although operation times were longer in this cohort, major bleeding events (60% vs. 89%) and postoperative severe complications (0 vs. 8%) (both p < 0.001) were less frequent compared to the open approach. A logistic regression showed that robotic surgery independently predicted major bleeding events (OR: 0.26; 95%CI 0.09–0.72; p = 0.02) but not the need for re-intervention. A Kaplan–Meier analysis showed that robotic cystectomy was associated with a significant advantage in terms of overall survival (LogRank = 0.03), and this result was confirmed by Cox regression analysis (HR: 0.39; 95%CI 0.14–0.94; p = 0.04). Conclusions: Robotic cystectomy with cutaneous ureterostomy may represent a viable option to treat frail bladder cancer patients, as the minimally invasive approach reduces the risk of bleeding and serious complications and provides a prompt restoration of bowel function and a shorter hospital stay compared to open surgery.
Inflammation-Triggering Engineered Macrophages (MacTriggers) Enhance Reactivity of Immune Checkpoint Inhibitor Only in Tumor Tissues
Authors: Tanito Kenta , Nii Teruki , Wakuya Kanae , Hamabe Yusuke , Yoshimi Toma , Hosokawa Takanatsu , Kishimura Akihiro , Mori Takeshi , Katayama Yoshiki
Published: November 2024

Background: We have previously reported engineered macrophages (MacTriggers) that can accelerate the release of tumor necrosis factor-α in response to M2 polarization. MacTriggers are characterized by two original characteristics of macrophages: (1) migration to tumors; and (2) polarization to the M2 phenotype in tumors. Intravenously administered MacTriggers efficiently accumulated in the tumors and induced tumor-specific inflammation. This study reports a novel methodology for enhancing the anti-tumor effects of immune checkpoint inhibitors (ICIs). Results: In this study, we newly found that the intravenously administered MacTriggers in BALB/c mouse models upregulated the expression levels of immune checkpoint proteins, such as programmed cell death (PD)-1 in CD8+ T cells and PD-ligand 1 (PD-L1) in cancer cells and macrophages. Consequently, in two ICI-resistant tumor-inoculated mouse models, the combined administration of MacTrigger and anti-PD-1 antibody (aPD-1) synergistically inhibited tumor growth, whereas monotherapy with aPD-1 did not exhibit anti-tumor effects. This synergistic effect was mainly from aPD-1 enhancing the tumor-attacking ability of CD8+ T cells, which could infiltrate into the tumors following MacTrigger treatment. Importantly, no side effects were observed in normal tissues, particularly in the liver and spleen, indicating that the MacTriggers did not enhance the aPD-1 reactivity in normal tissues. This specificity was from the MacTriggers not polarizing to the M2 phenotype in normal tissues, thereby avoiding inflammation and increased PD-1/PD-L1 expression. MacTriggers could enhance aPD-1 reactivity only in tumors following tumor-specific inflammation induction. Conclusions: Our findings suggest that the MacTrigger and aPD-1 combination therapy is a novel approach for potentially overcoming the current low ICI response rates while avoiding side effects.
PRMT5/WDR77 Enhances the Proliferation of Squamous Cell Carcinoma via the ΔNp63α-p21 Axis
Authors: Liang Heng , Fisher Matthew L. , Wu Caizhi , Ballon Carlos , Sun Xueqin , Mills Alea A.
Published: November 2024

Protein arginine methyltransferase 5 (PRMT5) is a critical oncogenic factor in various cancers, and its inhibition has shown promise in suppressing tumor growth. However, the role of PRMT5 in squamous cell carcinoma (SCC) remains largely unexplored. In this study, we analyzed SCC patient data from The Cancer Genome Atlas (TCGA) and the Cancer Dependency Map (DepMap) to investigate the relationship between PRMT5 and SCC proliferation. We employed competition-based cell proliferation assays, 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl-2H-tetrazolium bromide (MTT) assays, flow cytometry, and in vivo mouse modeling to examine the regulatory roles of PRMT5 and its binding partner WDR77 (WD repeat domain 77). We identified downstream targets, including the p63 isoform ΔNp63α and the cyclin-dependent kinase inhibitor p21, through single-cell RNA-seq, RT-qPCR, and Western blot analyses. Our findings demonstrate that upregulation of PRMT5 and WDR77 correlates with the poor survival of head and neck squamous cell carcinoma (HNSCC) patients. PRMT5/WDR77 regulates the HNSCC-specific transcriptome and facilitates SCC proliferation by promoting cell cycle progression. The PRMT5 and WDR77 stabilize the ΔNp63α Protein, which in turn, inhibits p21. Moreover, depletion of PRMT5 and WDR77 repress SCC in vivo. This study reveals for the first time that PRMT5 and WDR77 synergize to promote SCC proliferation via the ΔNp63α-p21 axis, highlighting a novel therapeutic target for SCC.
Extracellular Vesicle microRNAs as Possible Liquid Biopsy Markers in HNSCC—A Longitudinal, Monocentric Study
Authors: Apeltrath Carla , Simon Frank , Riders Armands , Rudack Claudia , Oberste Maximilian
Published: November 2024

Background: Biomarkers for HNSCC are still lacking. Biomolecules obtained via liquid biopsy are being investigated for diagnosis, prognosis, and therapy monitoring, including extracellular vesicles (EVs) and EV-cargo, e.g., proteins, RNA, and microRNA. This study aims to understand localization-dependent EV-microRNA expression in blood sera, their dynamics over time (12 months FU), and insights into their potential in diagnostics and therapy monitoring. Methods: Via liquid biopsy, blood serum was taken from 50 patients with HNSCC and 16 controls. Extracellular vesicles were isolated from serum by precipitation, and the contained microRNA-21, -1246, -200c, -let-7a, -181a, and -26a were amplified by reverse transcription and determined with real-time PCR. Expression ratios (HNSCC to healthy controls) were collated with the patients’ clinical parameters. A second liquid biopsy was carried out avg. 12 months later in the tumor aftercare. A sub-analysis with the Oropharynx subsite was implemented. Results: EV-mir-21, -let-7a, and -181a were 2.5–3-fold higher expressed in HPV/p16+ than in HPV/p16- HNSCC. Different expressions of EV-mir-181a and -26a could be demonstrated depending on the therapy modality. Conclusions: EV-microRNA could be a promising biomarker in the diagnosis and therapy monitoring of HNSCC. A systematic comparison of EV- and tissue microRNA expression in different HNSCC-subsites is needed.
Semaglutide Ameliorates Diabetic Neuropathic Pain by Inhibiting Neuroinflammation in the Spinal Cord
Authors: Lee Sing-Ong , Kuthati Yaswanth , Huang Wei-Hsiu , Wong Chih-Shung
Published: November 2024

Glucagon-like peptide 1 (GLP-1) receptor agonists are frequently used to treat type 2 diabetes and obesity. Despite the development of several drugs for neuropathic pain management, their poor efficacy, tolerance, addiction potential, and side effects limit their usage. Teneligliptin, a DPP-4 inhibitor, has been shown to reduce spinal astrocyte activation and neuropathic pain caused by partial sciatic nerve transection. Additionally, we showed its capacity to improve the analgesic effects of morphine and reduce analgesic tolerance. Recent studies indicate that GLP-1 synthesized in the brain activates GLP-1 receptor signaling pathways, essential for neuroprotection and anti-inflammatory effects. Multiple in vitro and in vivo studies using preclinical models of neurodegenerative disorders have shown the anti-inflammatory properties associated with glucagon-like peptide-1 receptor (GLP-1R) activation. This study aimed to investigate the mechanism of antinociception and the effects of the GLP-1 agonist semaglutide (SEMA) on diabetic neuropathic pain in diabetic rats. Methods: Male Wistar rats, each weighing between 300 and 350 g, were categorized into four groups: one non-diabetic sham group and three diabetic groups. The diabetic group received a single intraperitoneal injection of streptozotocin (STZ) at a dosage of 60 mg/kg to induce diabetic neuropathy. After 4 weeks of STZ injection, one diabetic group was given saline (vehicle), and the other two were treated with either 1× SEMA (1.44 mg/kg, orally) or 2× SEMA (2.88 mg/kg, orally). Following a 4-week course of oral drug treatment, behavioral, biochemical, and immunohistochemical analyses were carried out. The mechanical allodynia, thermal hyperalgesia, blood glucose, advanced glycation end products (AGEs), plasma HbA1C, and spinal inflammatory markers were evaluated. Results: SEMA treatment significantly reduced both allodynia and hyperalgesia in the diabetic group. SEMA therapy had a limited impact on body weight restoration and blood glucose reduction. In diabetic rats, SEMA lowered the amounts of pro-inflammatory cytokines in the spinal cord and dorsal horn. It also lowered the activation of microglia and astrocytes in the dorsal horn. SEMA significantly reduced HbA1c and AGE levels in diabetic rats compared to the sham control group. Conclusions: These results indicate SEMA’s neuroprotective benefits against diabetic neuropathic pain, most likely by reducing inflammation and oxidative stress by inhibiting astrocyte and microglial activity. Our findings suggest that we can repurpose GLP-1 agonists as potent anti-hyperalgesic and anti-inflammatory drugs to treat neuropathic pain without serious side effects.
In Vitro Models of Diabetes: Focus on Diabetic Retinopathy
Authors: Galgani Giulia , Bray Giorgia , Martelli Alma , Calderone Vincenzo , Citi Valentina
Published: November 2024

Diabetic retinopathy is a major eye complication in patients with diabetes mellitus, and it is the leading cause of blindness and visual impairment in the world. Chronic hyperglycemia induces endothelial damage with consequent vascular lesions, resulting in global vasculitis, which affects the small vessels of the retina. These vascular lesions cause ischemic conditions in certain areas of the retina, with a consequent increase in the release of pro-angiogenic mediators. In addition to pharmacological interventions for controlling the blood glycaemic level, the main strategies for treating diabetic retinopathy are the intravitreal injections of drugs, surgical treatments, and vitrectomies. The complexity of diabetic retinopathy is due to its close interactions with different cell types (endothelial cells, astrocytes, and Müller cells). The evaluation of the efficacy of novel pharmacological strategies is mainly performed through in vivo models. However, the use of different animal species leads to heterogenic results and ethical concerns. For these reasons, the development of new and reliable in vitro models, such as cell co-cultures and eye organoids, represents an urgent need in this area of research. This review features an overview of the in vitro models used to date and highlights the advances in technology used to study this pathology.
Structural and Functional Insights into Dishevelled-Mediated Wnt Signaling
Authors: Wang Lei , Zhu Rui , Wen Zehua , Fan Hua-Jun Shawn , Norwood-Jackson Teresa , Jathan Danielle , Lee Ho-Jin
Published: November 2024

Dishevelled (DVL) proteins precisely control Wnt signaling pathways with many effectors. While substantial research has advanced our understanding of DVL’s role in Wnt pathways, key questions regarding its regulatory mechanisms and interactions remain unresolved. Herein, we present the recent advances and perspectives on how DVL regulates signaling. The experimentally determined conserved domain structures of DVL in conjunction with AlphaFold-predicted structures are used to understand the DVL’s role in Wnt signaling regulation. We also summarize the role of DVL in various diseases and provide insights into further directions for research on the DVL-mediated signaling mechanisms. These findings underscore the importance of DVL as a pharmaceutical target or biological marker in diseases, offering exciting potential for future biomedical applications.
Oxidative Stress and Antioxidant Strategies: Relationships and Cellular Pathways for Human Health
Authors: Remigante Alessia , Morabito Rossana
Published: November 2024

Chronic diseases and aging have increased significantly in recent decades [...]
Species Distribution Modeling of Ixodes ricinus (Linnaeus, 1758) Under Current and Future Climates, with a Special Focus on Latvia and Ukraine
Authors: Tytar Volodymyr , Kozynenko Iryna , Pupins Mihails , Škute Arturs , Čeirāns Andris , Georges Jean-Yves , Nekrasova Oksana
Published: November 2024

This study assesses the impact of climate change on the distribution of Ixodes ricinus, which transmits Lyme disease, a growing public health concern. Utilizing ensemble models from the R package ‘flexsdm’ and climate data from WorldClim, ENVIREM, and CliMond, we project habitat suitability changes for the focus species. The models, validated against Lyme disease incidence rates, predict a 1.5-fold increase in suitable habitats in Latvia, contrasted with a 4.5-fold decrease in suitable habitats within Ukraine over the coming decades. SHAP values are analyzed to determine the most influential climatic features affecting tick distribution, providing insights for future vector control and disease prevention strategies. The optimal bioclimatic environment for I. ricinus seems to be an intricate balance of moderate temperatures, high humidity, and sufficient rainfall (bio7, 14, 18, 29). Also, radiation during the wettest quarter (bio24) significantly influences tick distribution in northern countries. This implies an increased presence of ticks in Scandinavian countries, Baltic states, etc. These findings largely coincide with our projections regarding bioclimatic suitability for ticks in Latvia and Ukraine. These shifts reflect broader patterns of vector redistribution driven by global warming, highlighting the urgent need to adapt public health planning to the evolving landscape of vector-borne diseases under climate change.
Stainless Steel Deposits on an Aluminum Support Used in the Construction of Packaging and Food Transport Containers
Authors: Radu Steluța , Toma Stefan Lucian
Published: November 2024

A series of chemical elements from the chemical composition of the packs of liquid food products migrate inside them or they combine with other chemical elements existing in the food, resulting in chemical compounds that worsen the quality of the food. In the present paper, layers of food stainless steel were deposited using thermal arc spraying on an aluminum alloy substrate to stop the migration of aluminum ions inside liquid food products. The physical-chemical and mechanical properties of the protection system: stainless steel layer used in the food industry (suggestively called: food-grade stainless steel)—aluminum substrate were investigated, and then the organoleptic properties of the food liquids that came into contact with the deposit were evaluated. It was found that food-gradestainless steel deposits have low porosity (3.8%) and relatively high adhesion and hardness, which allows complete isolation of the substrate material. The investigations carried out on the properties of food liquids that come into contact with the stainless steel deposit revealed the fact that it perfectly seals the aluminum start. The food-grade stainless steel coating (80T) was much better and safer for preserving dairy products maintaining a constant acidity up to 17 degrees Thorner, wines (with an average acidity of 3.5–4 degrees), juices (with natural pigments), and oils (with a good absorbance level correlated with clarity). This aspect suggests that the created system can be successfully used to manufacture containers for the transport of liquid products.
Pediatric Bone Tumors: Location and Age Distribution of 420 Cases
Authors: Breden Sebastian , Stephan Maximilian , Hinterwimmer Florian , Consalvo Sarah , Lenze Ulrich , von Eisenhart-Rothe Rüdiger , Mogler Carolin , Gersing Alexandra S. , Knebel Carolin
Published: November 2024

Background/Objectives: One of the most important diagnostic tools in bone tumors is X-rays. Preliminary and, in the case of some benign lesions, definitive diagnoses are formed using this basic tool. Part of the decision making in this stage is based on statistical probability using the patient’s age, as well as the incidence and predilection sites of different entities. The information used today is based on older and fragmented data. To verify the underlying principles, we retrospectively evaluated all bone tumors in children and adolescents treated by our tertiary center in the last 20 years. Methods: For this retrospective study, patients under the age of 18 years suffering from histopathologically verified bone tumors were evaluated. Data were retrieved from our local musculoskeletal tumor database. Results: We were able to include 420 children treated for bone tumors in our tertiary center. The cohort consisted of 335 benign and 85 malignant lesions. The most common lesions were 137 osteochondromas; the malignant tumors consisted mainly of osteosarcomas (53) and Ewing’s sarcomas (28). The primary predilection sites were the metaphyses of long bones. Conclusions: We were able to confirm and supplement the fragmentary data of these rare diseases using our own cohort.
Explainable and Interpretable Model for the Early Detection of Brain Stroke Using Optimized Boosting Algorithms
Authors: Dubey Yogita , Tarte Yashraj , Talatule Nikhil , Damahe Khushal , Palsodkar Prachi , Fulzele Punit
Published: November 2024

Background/Objectives: Stroke stands as a prominent global health issue, causing con-siderable mortality and debilitation. It arises when cerebral blood flow is compromised, leading to irreversible brain cell damage or death. Leveraging the power of machine learning, this paper presents a systematic approach to predict stroke patient survival based on a comprehensive set of factors. These factors include demographic attributes, medical history, lifestyle elements, and physiological metrics. Method: An effective random sampling method is proposed to handle the highly biased data of stroke. The stroke pre-diction using optimized boosting machine learning algorithms is supported with explainable AI using LIME and SHAP. This enables the models to discern intricate data patterns and establish correlations between selected features and patient survival. Results: The performance of three boosting algorithms is studied for stroke prediction, which include Gradient Boosting (GB), AdaBoost (ADB), and XGBoost (XGB) with XGB achieved the best outcome overall with a training accuracy of 96.97% and testing accuracy of 92.13%. Conclusions: Through this approach, the study seeks to uncover actionable insights to guide healthcare practitioners in devising personalized treatment strategies for stroke patients.
Diagnostic Applications of AI in Sports: A Comprehensive Review of Injury Risk Prediction Methods
Authors: Musat Carmina Liana , Mereuta Claudiu , Nechita Aurel , Tutunaru Dana , Voipan Andreea Elena , Voipan Daniel , Mereuta Elena , Gurau Tudor Vladimir , Gurău Gabriela , Nechita Luiza Camelia
Published: November 2024

This review provides a comprehensive analysis of the transformative role of artificial intelligence (AI) in predicting and preventing sports injuries across various disciplines. By exploring the application of machine learning (ML) and deep learning (DL) techniques, such as random forests (RFs), convolutional neural networks (CNNs), and artificial neural networks (ANNs), this review highlights AI’s ability to analyze complex datasets, detect patterns, and generate predictive insights that enhance injury prevention strategies. AI models improve the accuracy and reliability of injury risk assessments by tailoring prevention strategies to individual athlete profiles and processing real-time data. A literature review was conducted through searches in PubMed, Google Scholar, Science Direct, and Web of Science, focusing on studies from 2014 to 2024 and using keywords such as ‘artificial intelligence’, ‘machine learning’, ‘sports injury’, and ‘risk prediction’. While AI’s predictive power supports both team and individual sports, its effectiveness varies based on the unique data requirements and injury risks of each, with team sports presenting additional complexity in data integration and injury tracking across multiple players. This review also addresses critical issues such as data quality, ethical concerns, privacy, and the need for transparency in AI applications. By shifting the focus from reactive to proactive injury management, AI technologies contribute to enhanced athlete safety, optimized performance, and reduced human error in medical decisions. As AI continues to evolve, its potential to revolutionize sports injury prediction and prevention promises further advancements in athlete health and performance while addressing current challenges.
Quantitative Evaluation of Enamel Thickness in Maxillary Central Incisors in Different Age Groups Utilizing Cone Beam Computed Tomography a Retrospective Analysis
Authors: Jánosi Kinga Mária , Cerghizan Diana , Mureșan Izabella Éva , Kovács Alpár , Szász Andrea , Markovics Emese Rita , Mártha Krisztina Ildikó , Pop Silvia Izabella
Published: November 2024

Background/Objectives: The presence of enamel on the tooth surface is crucial for the long-term success of minimally invasive adhesive restorations such as dental veneers. Our study aims to evaluate the enamel thickness in the incisal, middle, and cervical portions of the labial surface of the upper central incisors using cone beam computed tomography (CBCT). This imaging method provides detailed and accurate three-dimensional images with a low radiation dose, allowing an accurate assessment of enamel thickness. The analysis aims to identify variations in enamel thickness depending on the age and different levels of the labial tooth surface. Methods: 800 CBCT scans performed for diagnostic or therapeutic purposes on patients aged 18–60 years were analyzed. The data were gathered from the imaging archives of private practitioners from Targu Mures and the “George Emil Palade” University of Medicine, Pharmacy, Science, and Technology of Targu Mures. Enamel thickness measurements were conducted using the OnDemand3D Communicator CBCT evaluation program, with subsequent statistical analysis performed using GraphPad Instat Prism software. Results: Results showed significant variation in enamel thickness between the incisal, middle, and cervical segments of the labial surface of the upper central incisors. A decrease in enamel thickness with age has been observed. In patients aged 18–40, mean values of enamel thickness 1 mm and 3 mm above the cementoenamel junction (CEJ) were 0.48 ± 0.092, respectively, 0.819 ± 0.158. In patients over 40, the mean values were 0.454 ± 0.116 and 0.751 ± 0.067 at 1 mm, respectively, 3 mm above the CEJ. Statistically significant differences were found between the two age groups at 1 mm and 3 mm above the CEJ, with p < 0.0001 and p = 0.0214. Conclusions: A statistically significant decrease can be observed in enamel thickness in almost the entire labial surface of the upper central incisors with aging. The varied thickness of the enamel at different tooth levels requires individualized planning for each patient to maximize the long-term aesthetic and functional results.
Prospective Validation and Usability Evaluation of a Mobile Diagnostic App for Obstructive Sleep Apnea
Authors: Amorim Pedro , Ferreira-Santos Daniela , Drummond Marta , Rodrigues Pedro Pereira
Published: November 2024

Background/Objectives: Obstructive sleep apnea (OSA) classification relies on polysomnography (PSG) results. Current guidelines recommend the development of clinical prediction algorithms in screening prior to PSG. A recent intuitive and user-friendly tool (OSABayes), based on a Bayesian network model using six clinical variables, has been proposed to quantify the probability of OSA. Our aims are (1) to validate OSABayes prospectively, (2) to build a smartphone app based on the proposed model, and (3) to evaluate app usability. Methods: We prospectively included adult patients suspected of OSA, without suspicion of other sleep disorders, who underwent level I or III diagnostic PSG. Apnea–hypopnea index (AHI) and OSABayes probabilities were obtained and compared using the area under the ROC curve (AUC [95%CI]) for OSA diagnosis (AHI ≥ 5/h) and higher severity levels (AHI ≥ 15/h) prediction. We built the OSABayes app on ‘App Inventor 2’, and the usability was assessed with a cognitive walkthrough method and a general evaluation. Results: 216 subjects were included in the validation cohort, performing PSG levels I (34%) and III (66%). OSABayes presented an AUC of 83.6% [77.3–90.0%] for OSA diagnosis and 76.3% [69.9–82.7%] for moderate/severe OSA prediction, showing good response for both types of PSG. The OSABayes smartphone application allows one to calculate the probability of having OSA and consult information about OSA and the tool. In the usability evaluation, 96% of the proposed tasks were carried out. Conclusions: These results show the good discrimination power of OSABayes and validate its applicability in identifying patients with a high pre-test probability of OSA. The tool is available as an online form and as a smartphone app, allowing a quick and accessible calculation of OSA probability.
Glial Fibrillary Acidic Protein’s Usefulness as an Astrocyte Biomarker Using the Fully Automated LUMIPULSE® System
Authors: Kamada Jo , Hamanaka Tomohiro , Oshimo Aya , Sato Hideo , Nishii Tomonori , Fujita Marika , Makiguchi Yoshiharu , Tanaka Miki , Aoyagi Katsumi , Nojima Hisashi
Published: November 2024

Background: Glial fibrillary acidic protein (GFAP) is an important biomarker for neuroinflammatory conditions. Recently, advancements in the treatment of neurological diseases have highlighted the increasing importance of biomarkers, creating a demand for accurate and simple measurement systems for GFAP levels, which are essential for both research and clinical applications. This study presents the development and validation of a novel fully automated immunoassay for the quantitative determination of GFAP levels in biological samples. Methods: We examined the analytical performance of the GFAP assay on the LUMIPULSE platform. The assay’s parameters, including antibody concentrations, incubation times, and detection methods, were optimized to enhance sensitivity and specificity. GFAP levels were measured in 396 serum or plasma samples, comprising both healthy controls and patients with neurodegenerative diseases. Results: In the analytical performance studies, intra- and inter-assay coefficients of variation (CV) were below 5%, indicating high reproducibility. Additionally, the assay demonstrated good linearity over the measurement range. The limit of quantification (LoQ) for this assay was 6.0 pg/mL, which is sufficient for measuring specimens from healthy controls. In clinical validation studies, GFAP levels were significantly elevated in patients with neurodegenerative diseases compared to healthy controls. Conclusions: This automated GFAP assay provides a robust and reliable tool for GFAP measurement, facilitating further research into GFAP’s role in neurological disorders and potentially aiding in the diagnosis and monitoring of these conditions.
Audiovestibular Dysfunction Related to Anti-Phospholipid Syndrome: A Systematic Review
Authors: Chen Jiann-Jy , Hsu Chih-Wei , Chen Yen-Wen , Chen Tien-Yu , Zeng Bing-Yan , Tseng Ping-Tao
Published: November 2024

Background: Anti-phospholipid syndrome (APS) has emerged as a significant issue in autoimmune diseases over recent decades. Its hallmark feature is thromboembolic events, potentially affecting any vascularized area including the microcirculation of the inner ear. Since the first case report of APS-related audiovestibular dysfunction described in 1993, numerous reports have explored the association between APS-related antibodies and audiovestibular dysfunction. These studies indicate a higher prevalence of APS-related antibodies in patients with sensorineural hearing loss compared to healthy controls. Unlike other idiopathic hearing loss disorders, audiovestibular dysfunction associated with APS may respond to appropriate treatments, highlighting the importance of timely recognition by clinicians to potentially achieve favorable outcomes. Therefore, this systematic review aims to consolidate current evidence on the characteristics, pathophysiology, assessment, and management of audiovestibular dysfunction linked to APS. Methods: This systematic review utilized electronic searches of the PubMed, Embase, ClinicalKey, Web of Science, and ScienceDirect online platforms. The initial search was performed on 27 January 2024, with the final update search completed on 20 June 2024. Results: Based on theoretical pathophysiology, anticoagulation emerges as a pivotal treatment strategy. Additionally, drawing from our preliminary data, we propose a modified protocol combining anticoagulants, steroids, and non-invasive brain stimulation to offer clinicians a novel therapeutic approach for managing these symptoms. Conclusions: Clinicians are encouraged to remain vigilant about the possibility of APS and its complex audiovestibular manifestations, as prompt intervention could stabilize audiovestibular function effectively.
Influence of the Inclusion of Off-Nadir Images on UAV-Photogrammetry Projects from Nadir Images and AGL (Above Ground Level) or AMSL (Above Mean Sea Level) Flights
Authors: Agüera-Vega Francisco , Ferrer-González Ezequiel , Martínez-Carricondo Patricio , Sánchez-Hermosilla Julián , Carvajal-Ramírez Fernando
Published: November 2024

UAV-SfM techniques are in constant development to address the challenges of accurate and precise mapping in terrains with complex morphologies. In contrast with the traditional photogrammetric processes, where only nadir images were considered, the combination of those with oblique imagery, also called off-nadir, has emerged as an optimal solution to achieve higher accuracy in these kinds of landscapes. UAV flights at a constant height above ground level (AGL) have also been considered a possible alternative to improve the resulting 3D point clouds compared to those obtained from constant height above mean sea level (AMSL) flights. The aim of this study is to evaluate the effect of incorporating oblique images as well as the type of flight on the accuracy and precision of the point clouds generated through UAV-SfM workflows for terrains with complex geometries. For that purpose, 58 scenarios with different camera angles and flight patterns for the oblique images were considered, 29 for each type of flight (AMSL and AGL). The 3D point cloud derived from each of the 58 scenarios was compared with a reference 3D point cloud acquired with a terrestrial laser scanner (TLS). The results obtained confirmed that both incorporating oblique images and using AGL flight mode have a positive effect on the mapping. Combination of nadir image blocks, obtained from an AGL crosshatch flight plan, with supplemental oblique images collected with a camera angle of between 20° and 35° yielded the best accuracy and precision records.
Accurate Prediction of 327 Rice Variety Growth Period Based on Unmanned Aerial Vehicle Multispectral Remote Sensing
Authors: Qiu Zixuan , Liu Hao , Wang Lu , Shao Shuaibo , Chen Can , Liu Zijia , Liang Song , Wang Cai , Cao Bing
Published: November 2024

Most rice growth stage predictions are currently based on a few rice varieties for prediction method studies, primarily using linear regression, machine learning, and other methods to build growth stage prediction models that tend to have poor generalization ability, low accuracy, and face various challenges. In this study, multispectral images of rice at various growth stages were captured using an unmanned aerial vehicle, and single-plant rice silhouettes were identified for 327 rice varieties by establishing a deep-learning algorithm. A growth stage prediction method was established for the 327 rice varieties based on the normalized vegetation index combined with cubic polynomial regression equations to simulate their growth changes, and it was first proposed that the growth stages of different rice varieties were inferred by analyzing the normalized difference vegetation index growth rate. Overall, the single-plant rice contour recognition model showed good contour recognition ability for different rice varieties, with most of the prediction accuracies in the range of 0.75–0.93. The accuracy of the rice growth stage prediction model in recognizing different rice varieties also showed some variation, with the root mean square error between 0.506 and 3.373 days, the relative root mean square error between 2.555% and 14.660%, the Bias between1.126 and 2.358 days, and the relative Bias between 0.787% and 9.397%; therefore, the growth stage prediction model of rice varieties can be used to effectively improve the prediction accuracy of the growth stage periods of rice.
Teachers’ Mixed Implementation of Mindset Mathematics Practices During and After a Novel Approach to Teacher Learning
Authors: Leshin Miriam , LaMar Tanya , Boaler Jo
Published: November 2024

Supporting teachers to transfer their learnings from innovative professional development settings to the classroom is challenging. In this paper, we investigate a novel approach to teacher learning, in which teachers from seven US districts taught in a mathematics summer camp using a research-based curriculum centered on student reasoning and mindset messages. We examined the practices teachers did and did not implement in their camp and school-year classrooms, as well as the possible reasons for the greater or lesser changes in practice. Through analysis of classroom video, teacher artifacts, and teacher interviews, we found that teachers implemented several important practices in both camp and school-year classrooms, namely posing open tasks, giving students ample time to collaborate, and asking questions that pushed students to reason. Interview analysis revealed that the act of centering students’ reasoning and witnessing their subsequent engagement seemed to motivate teacher uptake of these practices. At the same time, however, teachers less frequently integrated mindset messaging directly into their teaching and gave space for the exploration of students’ mistakes and struggles. These findings suggest implications for innovative professional development efforts outside of the school year, as well as incremental approaches.