bluuebunny/crossref_metadata_2025 huggingface dataset:
Thermogenic Supplementation and Fat Loss in Resistance-Trained Males: A Randomized Controlled Trial
Authors: Colquhoun Ryan J. , Shelton Gretchen , Bove Daniel , Gai Chris , Martinez Nic , Beaugrand Stephen , Dankel Scott J. , Campbell Bill I.
Published: February 2025

As interest in weight management and metabolic health grows, thermogenic supplements have gained attention for their potential to enhance caloric expenditure and fat loss. This study aimed to investigate the effects of chronic thermogenic supplement ingestion on body composition and strength outcomes during an 8-week periodized resistance training program. Thirty-four resistance-trained males were randomized into thermogenic supplementation (TS) (n = 18) or placebo (n = 16) groups in a double-blind, placebo-controlled design. Participants consumed thermogenic or placebo capsules daily, with dosage adjusted midway through the intervention. Body composition was assessed using ultrasound-based body fat analysis, and strength was measured via bench press and back squat one-repetition maximum (1-RM) tests. Results indicated that TS experienced significantly greater reductions in fat mass (−0.65 kg vs. 0.12 kg, p = 0.029) and body fat percentage (−0.89% vs. −0.08%, p = 0.039) compared to the placebo. Both groups demonstrated significant and comparable improvements in squat (TS: 16.87 kg, placebo: 18.47 kg) and bench press strength (TS: 7.80 kg, placebo: 7.13 kg). These findings suggest that thermogenic supplement ingestion can enhance fat loss without impeding strength adaptations. Future research should explore the dose–response effects and applicability of thermogenics in different populations and over extended durations.
Fault Risk Assessment of Transmission Lines Under Extreme Weather Conditions Based on Genetic Algorithm Back-Propagation Neural Network
Authors: Li Jialu , Lei Ruilin , Gao Yongqiang , Lei Aoyu , Fan Junqiu , Mei Yong , Tao Wenwei , Wang Haohuai , Wang Linzi , Li Taiji , Zhao Qiansheng
Published: February 2025

In the context of global climate change environment, China’s power grid is faced with many extreme weather challenges, especially the southern China power grid region, which faces typhoons, torrential rain, high temperature, drought, frost and other disasters that greatly affect the safe and stable operation of the power system and the normal social order in this region. This study proposes a risk assessment model combining a genetic algorithm-optimized neural network (GA-BP) with GIS spatial analysis to evaluate transmission line faults under extreme weather in southern China. Experimental results demonstrate the model’s effectiveness in identifying high-risk regions, with significant correlations between extreme precipitation, prolonged drought, and circuit failures.
Influence of Climate and Solar Variability on Growth Rings of Araucaria angustifolia in Três Barras National Forest (Brazil)
Authors: Muraja Daniela Oliveira Silva , Klausner Virginia , Prestes Alan , da Silva Aline Conceição , Lemes Cecília Leite
Published: February 2025

This research applies continuous wavelet analysis and seasonal correlation analysis to tree-ring data from Três Barras National Forest (FLONA Três Barras), revealing diverse influences on growth, including climate, solar activity, and external factors. The methodology involved tree-ring collection and subsequent wavelet and seasonal analyses to unveil the non-stationary characteristics of and multifaceted influences on growth. Key findings include the subtle effects of El Niño events on tree-ring development, the sensitivity of Araucaria angustifolia to temperature changes, the significant influence of precipitation during drought periods, and the intricate relationship between tree growth and solar cycles. The El Niño–Southern Oscillation (ENSO) emerges as a primary climatic driver during specific intervals, with external factors (precipitation, temperature, and solar cycle–solar irradiance) influencing tree response between 1936 and 1989. Additionally, the seasonal correlation analysis highlighted the importance of sub-annual climate variability, capturing specific intervals, such as a 3-month season ending in March of the previous year, that significantly impacted tree-ring growth. The study underscores the importance of protecting the endangered Araucaria angustifolia for climatic studies and local communities. Historically, in Brazil, Araucaria angustifolia seeds played a vital role in sustaining indigenous populations, which in turn helped to disperse and propagate forests, creating anthropogenic landscapes that highlight the interconnected relationship between humans and the preservation of these forests.
Hopf Bifurcations in a Mathematical Model for Economic Growth, Corruption, and Unemployment: Computation of Economic Limit Cycles
Authors: Ifeacho Ogochukwu , González-Parra Gilberto
Published: February 2025

In this paper, we investigate the existence of Hopf bifurcations in a mathematical model that includes economic growth, corruption, and unemployment. The model links these social and economic factors to provide insights into the dynamics of the economy. The motivation for investigating the appearance of Hopf bifurcations is that economic cycles often occur in economics and play an important role. The mathematical model was presented before, but the important topic of the appearance of limit cycles was not investigated. The authors studied some of the effects of corruption on economic growth and unemployment. However, in our work, we focus on the existence of limit cycles. We used different bifurcation parameters to find the conditions for the appearance of Hopf bifurcations. We perform a variety of numerical simulations in which the system presents several Hopf bifurcations. The numerical simulations provide additional support for the theoretical results related to stability and Hopf bifurcations. Finally, we present a discussion and future directions for research.
The Bacterium P. aeruginosa Disperses Ordered Membrane Domains by Targeting Phase Boundaries
Authors: Stober Kai , Schwerdtfeger Fabian , Aigal Sahaja , Mely Yves , Römer Winfried
Published: February 2025

Various pathogens use receptors on the host’s plasma membrane for their cellular uptake. For the bacterium Pseudomonas aeruginosa, interactions between its lectin LecA and the host cell glycosphingolipid globotriaosylceramide (also known as Gb3) are crucial for its internalization via the so-called lipid zipper mechanism. In this study, we investigated the interactions of the P. aeruginosa strain PAO1 with phase-separated lipid bilayers containing Gb3. Surprisingly, bacteria are mostly bound to the interphase of liquid-ordered (Lo) and liquid-disordered (Ld) membrane domains. Simultaneously with the formation of bacterial aggregates and the accumulation of membrane lipids, the lipid bilayers were drastically reorganized and Lo domains were dissolved. Surprisingly, Gb3 was found to play a role in the localization of the bacterium at the interface, less so LecA. When microspheres were used as a minimal mimic of the bacterium, these beads also localized preferentially at the Lo–Ld phase boundaries, but in contrast to living bacteria, beads were unable to cause membrane reorganization and dissolution of the Lo domain, even when coated with LecA. Targeting phase boundaries as “weak points” in membranes and thereby reorganizing and destabilizing the host cell plasma membrane could be an attractive entry strategy for P. aeruginosa and many other bacteria and viruses.
Neutrophil- and Endothelial Cell-Derived Extracellular Microvesicles Are Promising Putative Biomarkers for Breast Cancer Diagnosis
Authors: Moreira Thayse Batista , Silvestrini Marina Malheiros Araújo , Gomes Ana Luiza de Freitas Magalhães , Rangel Kerstin Kapp , Costa Álvaro Percínio , Gomes Matheus Souza , do Amaral Laurence Rodrigues , Martins-Filho Olindo Assis , Salles Paulo Guilherme de Oliveira , Braga Letícia Conceição , Teixeira-Carvalho Andréa
Published: February 2025

Introduction: Breast cancer (BC) is a disease that affects about 2.2 million people worldwide. The prognosis and treatment of these patients depend on clinical and histopathologic staging, in which more aggressive cancers need a less conservative therapeutic approach. Previous studies showed that patients with BC have an increased frequency of systemic microvesicles (MVs) that are associated with invasion, progression, and metastasis, which can be used in liquid biopsy to predict the therapeutic response in individualized treatment. Objective: This study proposes the development of a minimally invasive BC diagnostic panel and follow-up biomarkers as a complementary method to screen patients. Methods: The quantification of circulating MVs in 48 healthy women and 100 BC patients who attended the Mário Penna Institute between 2019 and 2022 was performed by flow cytometry. In addition, the MVs of BC patients were analyzed before treatment and 6, 12, and 24 months post-treatment. Machine learning approaches were employed to determine the performance of MVs to identify BC and to propose BC classifier algorithms. Results: Patients with BC had more neutrophil- and endothelial cell-derived MVs than controls before treatment. After treatment, all MV populations were decreased compared to pre-treatment, but leukocyte- and erythrocyte-derived MVs were increased at 12 months after treatment, before decreasing again at 24 months. Conclusions: Performance analyses and machine learning approaches pointed out that MVs from neutrophils and endothelial cells are the best candidates for BC diagnostic biomarkers. Neutrophil- and endothelial cell-derived MVs are putative candidates for BC biomarkers to be employed as screening tests for BC diagnosis.
Multimodal Deep Learning Model for Cylindrical Grasp Prediction Using Surface Electromyography and Contextual Data During Reaching
Authors: Lázaro Raquel , Vergara Margarita , Morales Antonio , Mollineda Ramón A.
Published: February 2025

Grasping objects, from simple tasks to complex fine motor skills, is a key component of our daily activities. Our approach to facilitate the development of advanced prosthetics, robotic hands and human–machine interaction systems consists of collecting and combining surface electromyography (EMG) signals and contextual data of individuals performing manipulation tasks. In this context, the identification of patterns and prediction of hand grasp types is crucial, with cylindrical grasp being one of the most common and functional. Traditional approaches to grasp prediction often rely on unimodal data sources, limiting their ability to capture the complexity of real-world scenarios. In this work, grasp prediction models that integrate both EMG signals and contextual (task- and product-related) information have been explored to improve the prediction of cylindrical grasps during reaching movements. Three model architectures are presented: an EMG processing model based on convolutions that analyzes forearm surface EMG data, a fully connected model for processing contextual information, and a hybrid architecture combining both inputs resulting in a multimodal model. The results show that context has great predictive power. Variables such as object size and weight (product-related) were found to have a greater impact on model performance than task height (task-related). Combining EMG and product context yielded better results than using each data mode separately, confirming the importance of product context in improving EMG-based models of grasping.
Human-Computer Interaction Empowers Construction Safety Management: Breaking Through Difficulties to Achieving Innovative Leap
Authors: Peng Hao , Wang Xiaolin , Wu Han , Huang Bo
Published: February 2025

This paper focuses on the application of human–computer interaction technology in construction project safety management. Through bibliometric methods, we carried out an in-depth analysis of 286 relevant papers from Web of Science and Google Scholar from 2000 to 2024. The research results indicate that human–computer interaction technology has achieved remarkable development in four aspects: intelligent monitoring systems, risk assessment and management, ergonomics and cognitive psychology, as well as computer simulation and virtual reality. Meanwhile, this research has given rise to a series of new research topics, such as the safety operation decision-making method for intelligent construction machinery, the application of human action behavior recognition technology, and the application of Internet of Things technology in the safety control of smart construction sites. Additionally, future research modules have been identified, including personalized safety training, digital twin technology, and multimodal data analysis. This study not only summarizes the existing research achievements but also puts forward targeted suggestions for future development trends in the field of construction safety management from a practical perspective, aiming to promote the in-depth application and development of human–computer interaction technology in construction safety management.
Machine-Learning-Based Analysis of Internal Forces in Reinforced Concrete Conical and Cylindrical Tanks Under Hydrostatic Pressure Considering Material Nonlinearity
Authors: Haggag May , Ismail Mohamed K. , Elansary Ahmed
Published: February 2025

Reinforced concrete (RC) tanks are essential for storing liquids and bulk materials across various industries. However, simplified analytical methods fall short in providing an accurate analysis, while traditional methods, such as finite element modeling, can be computationally intensive and time-consuming, especially when dealing with nonlinear material properties and complex geometries, like conical and cylindrical shapes. This highlights the need for a more efficient and simplified analysis approach. Accordingly, the present paper introduces a machine learning (ML) framework as an effective predictive tool for RC conical and cylindrical tanks under hydrostatic pressure. Data from 320 RC conical and cylindrical water tanks, previously analyzed using finite element modeling, were used to train and test various ML models, considering geometrical and material nonlinearities. Four machine learning models—decision trees, random forests, gradient boosting, and extreme gradient boosting—were utilized to predict critical internal forces, including the maximum ring tension force, maximum meridional moment, and maximum meridional axial force. The accuracy of each model was evaluated using different statistical measures. To improve model interpretability and identify key predictors, feature importance techniques were employed to rank the significance of each input variable to the predictions. Furthermore, Accumulated Local Effects (ALE) plots were utilized to visualize the relationships between model inputs and outputs, providing a clearer understanding of the inner workings of the ML models. The combined use of feature importance and ALE plots enhances model transparency by illustrating how specific features contribute to the predictions, thereby supporting the informed application of ML in the structural design and analysis of RC tanks. Ultimately, the framework presented in this study aims to promote the practical application of machine learning in structural engineering, contributing to simpler, more efficient, and accurate analysis and design processes for RC water tanks.
Predicting Surgical Difficulty in Rectal Cancer Surgery: A Systematic Review of Artificial Intelligence Models Applied to Pre-Operative MRI
Authors: Hardacre Conor , Hibbs Thomas , Fok Matthew , Wiles Rebecca , Bashar Nada , Ahmed Shakil , Mascarenhas Saraiva Miguel , Zheng Yalin , Javed Muhammad Ahsan
Published: February 2025

Introduction: Following the rapid advances in minimally invasive surgery, there are a multitude of surgical modalities available for resecting rectal cancers. Robotic resections represent the current pinnacle of surgical approaches. Currently, decisions on the surgical modality depend on local resources and the expertise of the surgical team. Given limited access to robotic surgery, developing tools based on pre-operative data that can predict the difficulty of surgery would streamline the efficient utilisation of resources. This systematic review aims to appraise the existing literature on artificial intelligence (AI)-driven preoperative MRI analysis for surgical difficulty prediction to identify knowledge gaps and promising models warranting further clinical evaluation. Methods: A systematic review and narrative synthesis were undertaken in accordance with PRISMA and SWiM guidelines. Systematic searches were performed on Medline, Embase, and the CENTRAL Trials register. Studies published between 2012 and 2024 were included where AI was applied to preoperative MRI imaging of adult rectal cancer patients undergoing surgeries, of any approach, for the purpose of stratifying surgical difficulty. Data were extracted according to a pre-specified protocol to capture study characteristics and AI design; the objectives and performance outcome metrics were summarised. Results: Systematic database searches returned 568 articles, 40 ultimately included in this review. AI to support preoperative difficulty assessments were identified across eight domains (direct surgical difficulty grading, extramural vascular invasion (EMVI), lymph node metastasis (LNM), lymphovascular invasion (LVI), perineural invasion (PNI), T staging, and the requirement for multiple linear stapler firings. For each, at least one model was identified with very good performance (AUC scores of >0.80), with several showing excellent performance considerably above this threshold. Conclusions: AI tools applied to preoperative rectal MRI to support preoperative difficulty assessment for rectal cancer surgeries are emerging, with the progressing development and strong performance of many promising models. These warrant further clinical evaluation, which can aid personalised surgical approaches and ensure the adequate utilisation of limited resources.
Flow Cytometry for B-Cell Non-Hodgkin and Hodgkin Lymphomas
Authors: Gajzer David C. , Fromm Jonathan R.
Published: February 2025

Multi-parametric flow cytometry is a powerful diagnostic tool that permits rapid assessment of cellular antigen expression to quickly provide immunophenotypic information suitable for disease classification. This chapter describes the classification of B-cell non-Hodgkin lymphoma (B-NHL) by flow cytometry suitable for the clinical and research environment. In addition to describing the immunophenotypic patterns of the most common B-NHL (including examples of common B-NHL), the effect of anti-CD19, -CD20, and -CD38 therapies on the evaluation of flow cytometric data is also discussed. Over the last 15 years, our laboratory has developed flow cytometry combinations that can immunophenotype classic Hodgkin lymphoma (CHL), nodular lymphocyte predominant Hodgkin lymphoma (NLPHL), and T-cell/histocyte-rich large B-cell lymphoma (THRLBCL) and the use of these assays will be presented. The CHL assay combination is also particularly well suited to immunophenotype primary mediastinal large B-cell lymphoma (PMLBCL) and our experience immunophenotyping PMLBCL by flow cytometry will be discussed. Finally, an approach to the evaluation of the reactive infiltrate of CHL, NLPHL, and THRLBCL that can provide diagnostic information will also be provided.
Multi-Center Benchmarking of a Commercially Available Artificial Intelligence Algorithm for Prostate Imaging Reporting and Data System (PI-RADS) Score Assignment and Lesion Detection in Prostate MRI
Authors: Oerther Benedict , Engel Hannes , Wilpert Caroline , Nedelcu Andrea , Sigle August , Grimm Robert , von Busch Heinrich , Schlett Christopher L. , Bamberg Fabian , Benndorf Matthias , Herrmann Judith , Nikolaou Konstantin , Amend Bastian , Bolenz Christian , Kloth Christopher , Beer Meinrad , Vogele Daniel
Published: February 2025

Background: The increase in multiparametric magnetic resonance imaging (mpMRI) examinations as a fundamental tool in prostate cancer (PCa) diagnostics raises the need for supportive computer-aided imaging analysis. Therefore, we evaluated the performance of a commercially available AI-based algorithm for prostate cancer detection and classification in a multi-center setting. Methods: Representative patients with 3T mpMRI between 2017 and 2022 at three different university hospitals were selected. Exams were read according to the PI-RADSv2.1 protocol and then assessed by an AI algorithm. Diagnostic accuracy for PCa of both human and AI readings were calculated using MR-guided ultrasound fusion biopsy as the gold standard. Results: Analysis of 91 patients resulted in 138 target lesions. Median patient age was 67 years (range: 49–82), median PSA at the time of the MRI exam was 8.4 ng/mL (range: 1.47–73.7). Sensitivity and specificity for clinically significant prostate cancer (csPCa, defined as ISUP ≥ 2) were 92%/64% for radiologists vs. 91%/57% for AI detection on patient level and 90%/70% vs. 81%/78% on lesion level, respectively (cut-off PI-RADS ≥ 4). Two cases of csPCa were missed by the AI on patient-level, resulting in a negative predictive value (NPV) of 0.88 at a cut-off of PI-RADS ≥ 3. Conclusions: AI-augmented lesion detection and scoring proved to be a robust tool in a multi-center setting with sensitivity comparable to the radiologists, even outperforming human reader specificity on both patient and lesion levels at a threshold of PI-RADS ≥3 and a threshold of PI-RADS ≥ 4 on lesion level. In anticipation of refinements of the algorithm and upon further validation, AI-detection could be implemented in the clinical workflow prior to human reading to exclude PCa, thereby drastically improving reading efficiency.
An Evaluation of Serum miRNA in Renal Cell Carcinoma: A Systematic Review
Authors: Cochetti Giovanni , Guadagni Liliana , Paladini Alessio , Russo Miriam , La Mura Raffaele , Vitale Andrea , Saqer Eleonora , Mangione Paolo , Esposito Riccardo , Gioè Manfredi , Pastore Francesca , De Angelis Lorenzo , Ricci Federico , Vannuccini Giacomo , Mearini Ettore
Published: February 2025

Background: In recent years, research has highlighted the importance of microRNAs (miRNAs) in the context of oncological diseases, including renal cell carcinoma (RCC). The aim of this systematic review of the literature was to analyze the main serum miRNAs involved in RCC and their potential diagnostic power. Methods: This systematic review was performed following the PROSPERO protocol CRD42024550709. Literature search strategies were developed composing strings with text words related to serum miRNA in RCC for PubMed, EMBASE and Clinicaltrial.gov. The studies enrolling adult populations with RCC and healthy controls measuring circulating miRNAs were included. Results: We found 500 records, and 26 papers were included after screening. Four studies found that miR-210, the most investigated miRNA, was overexpressed in RCC patients compared to controls, while one reported no statistical difference. The expression of some miRNAs was consistently lower in cases compared to healthy controls, such as miR-1-3p and miR-129-5p, while others (miR-221, miR-222, miR-224-5p and miR-1233) were consistently upregulated. Conclusions: Circulating miRNAs represent a promising avenue for the non-invasive diagnosis of RCC. Future research should focus on standardization, validation in larger cohorts and the development of multi-marker diagnostic panels to address these current limitations and pave the way for miRNA-based diagnostics in RCC.
Advances and Challenges in Catalyst Dense-Phase Packing Technology: A Review
Authors: Xu Zhiqiang , Liu Wenming , Yu Zhengyong , Liu Xuedong
Published: February 2025

This review comprehensively focuses on catalyst dense-phase packing technology. It provides a systematic review of its principles, characteristics, and applications across diverse fields. A detailed comparison between dense-phase packing and traditional packing methods is presented, along with an in-depth analysis of its application status in petrochemical, fine-chemical, and other industries. The innovative trends of this technology in packing equipment and processes, as well as the challenges and countermeasures in its application, are thoroughly discussed. The aim is to offer a comprehensive and profound reference for relevant research and industrial practices, guiding future development in this crucial area of chemical engineering.
Age-Related Neurodegenerative Diseases: A Stem Cell’s Perspective
Authors: Calvo Belén , Schembri-Wismayer Pierre , Durán-Alonso María Beatriz
Published: February 2025

Neurodegenerative diseases encompass a number of very heterogeneous disorders, primarily characterized by neuronal loss and a concomitant decline in neurological function. Examples of this type of clinical condition are Alzheimer’s Disease, Parkinson’s Disease, Huntington’s Disease and Amyotrophic Lateral Sclerosis. Age has been identified as a major risk in the etiology of these disorders, which explains their increased incidence in developed countries. Unfortunately, despite continued and intensive efforts, no cure has yet been found for any of these diseases; reliable markers that allow for an early diagnosis of the disease and the identification of key molecular events leading to disease onset and progression are lacking. Altered adult neurogenesis appears to precede the appearance of severe symptoms. Given the scarcity of human samples and the considerable differences with model species, increasingly complex human stem-cell-based models are being developed. These are shedding light on the molecular alterations that contribute to disease development, facilitating the identification of new clinical targets and providing a screening platform for the testing of candidate drugs. Moreover, the secretome and other promising features of these cell types are being explored, to use them as replacement cells of high plasticity or as co-adjuvant therapy in combinatorial treatments.
Preliminary Experience with Transdermal Preoperative Hormonal Treatment Before Severe Hypospadias Repair: Synergy Between Pediatric Surgeons and Endocrinologists
Authors: Lucaccioni Laura , Ghidini Filippo , Repetto Paolo , Spampinato Grazia , Insalaco Anna , Vandelli Sara , Trevisani Viola , Iughetti Lorenzo , Ceccarelli Pier Luca
Published: February 2025

Objectives: The preoperative hormonal treatment (PHT) in eligible patients has the potential to become an asset for the treatment of severe hypospadias. The aim of the paper is to report the preliminary results on tolerability and efficacy of tailored transdermal PHT with testosterone before primary hypospadias repair, resulting by the joint activity between pediatric surgeons and endocrinologists. Methods: A retrospective study collected all the patients affected by severe hypospadias, with a glans width (GW) < 14 mm and/or a penile ventral curvature > 30°, treated with preoperative transdermal testosterone gel 2% at a standard dose of 2 mg/day after pediatric endocrinologist evaluation, from December 2020 to February 2024. Increases in GWs and penile lengths (PLs), together with adverse events and the rate of surgical complications, were reported. Results: During the period, ten patients were included and received transdermal PHT for 43 (±15) days on average. The treatment with PHT stopped 52 (±23) days before surgery. PL increased 0.76 (±0.27) cm (+37%) on average, and GW increased 0.42 (±0.26) cm (+40%). No adverse events were described. Three surgical complications were reported with an overall rate of 30%. Conclusions: Transdermal PHT was well-tolerated and showed a positive impact on the treatment of severe hypospadias. Future investigations might confirm these findings.
Prevalence, Socio-Demographic Characteristics, and Co-Morbidities of Autism Spectrum Disorder in US Children: Insights from the 2020–2021 National Survey of Children’s Health
Authors: Salehi Mona , Jaka Sanobar , Lotfi Aida , Ahmad Arham , Saeidi Mahdieh , Gunturu Sasidhar
Published: February 2025

Background: The primary goal of our study is to assess the national US prevalence of autism spectrum disorder (ASD), along with its socio-demographic characteristics, severity, and co-occurring medical and psychiatric disorders, using data from the 2020–2021 National Survey of Children’s Health (NSCH). Methods: We analyzed 2020–2021 NSCH data to estimate the prevalence of ever-diagnosed and current ASD among 79,182 children and adolescents (3–17 years). Univariate and multivariate regression models were used to examine associations between medical and psychiatric co-morbidities, socio-demographic factors, and ASD severity. Results: Adolescents (11–17 years) and males were more likely to have ASD, with males comprising 78.7% of the ASD group. The mean age of the sample was 10.1 ± 4.6 years, and 3.2% had an ASD diagnosis. Children from lower-income households and those with caregivers who completed only a high school education were more likely to have ASD. Nearly 96.4% of children with ASD had at least one co-morbid condition. The most common neuropsychiatric co-morbidities were developmental delay (64%), behavioral and conduct problems (57.8%), and anxiety disorder (45.7%), while the most common medical conditions were allergies (32.4%), genetic disorders (26.2%), and asthma (12.6%). Gender disparities in ASD presentation were evident that females with ASD were more likely to experience vision problems, cerebral palsy, epilepsy, depression, and intellectual disability but had lower odds of ADHD and anxiety problems. Greater ASD severity was linked to higher odds of intellectual disability (OR: 5.8, p < 0.001), developmental delay (OR: 5.0, p < 0.001), epilepsy, Down syndrome (OR: 3.4, p < 0.001), vision problems (OR: 2.5, p < 0.001), and genetic disorders (OR: 2.3, p < 0.001). Conclusions: This study provides updated prevalence estimates of ASD and highlights the high burden of co-morbidities, emphasizing the need for comprehensive, multidisciplinary approaches in ASD management. Additionally, our findings emphasize gender differences in ASD presentation, which should be considered in future research and clinical practice to ensure more tailored diagnostic and intervention strategies.
Uncovering the Evolutionary History in Lineage of Caribbean Octocorals: Phylogenomics Reveals Unrecognized Diversity in Eunicea
Authors: Sarmiento Adriana , Calixto-Botía Iván , Julio-Rodríguez Tatiana , Quattrini Andrea M. , Sánchez Juan A.
Published: February 2025

The evolutionary history of the Caribbean candelabrum octocorals from the genus Eunicea (Plexauridae: Octocorallia) remains unknown despite their high diversity and abundance in reef environments. Understanding the evolutionary relationships between and within the Eunicea species is critical to accurately measuring the group diversity. Furthermore, this group has a high potential for cryptic diversity and new species, particularly given the rich morphological variability. Conventional molecular markers, however, have not provided a precise positioning for the species inside the genus. Here, we provide the first phylogenomic reconstruction of these candelabrum octocorals employing NextRAD, a reduced-representation sequencing technique, to generate thousands of SNPs. We include 15 morphospecies sampled between valid and new species throughout the Caribbean. At large, the phylogeny is well supported and resolved. In total, 13 species-level clades are discernible, including two lineages with demonstrated genetic and morphological variation that are considered and described as two new species, Eunicea criptica sp. nov. and E. colombiensis sp. nov., both previously assigned as E. clavigera and the second as the “thick morphotype”, thereby increasing the diversity of the group. Understanding the magnitude of species diversity within Eunicea is essential for directing conservation initiatives and clarifying the biological processes in reef ecosystems.
18F-Fluorodeoxyglucose Imaging for Assessing Cardiovascular Inflammation
Authors: Tamaki Nagara , Aikawa Tadao , Manabe Osamu
Published: February 2025

Cardiovascular inflammation has recently emerged as a critical issue across various cardiovascular diseases. Various non-invasive imaging modalities are applied for assessing cardiovascular inflammation. Positron emission tomography (PET) using 18F-fluorodeoxyglucose (FDG) is a valuable non-invasive imaging tool for identifying active cardiovascular inflammation. It is utilized in evaluating conditions, such as cardiac sarcoidosis, endocarditis, vasculitis, and unstable atherosclerosis. Furthermore, management of cardiovascular complications after aggressive cancer therapy has increasingly been required in cancer patients. FDG PET is considered a suitable approach not only for the assessment of tumor responses to cancer therapy, but also for early and accurate detection of cardiovascular complications. This review highlights the clinical value of FDG PET under appropriate patient preparation. The future perspectives of new molecular imaging tools for assessing active cardiovascular inflammation have been described.
Twenty Years of Kaniadakis Entropy: Current Trends and Future Perspectives
Authors: Hristopulos Dionissios T. , da Silva Sérgio Luiz E. F. , Scarfone Antonio M.
Published: February 2025

Napier’s number e=2 [...]
Environmental Heterogeneity Drives Secondary Metabolite Diversity from Mesquite Pods in Semiarid Regions
Authors: Esparza-Orozco Alfredo , Carranza-Becerra Liliana , Delgadillo-Ruiz Lucía , Bollaín y Goytia Juan José , Gaytán-Saldaña Norma Angélica , Mandujano-García Cruz Daniel , Delgadillo-Ruiz Eladio , Michel-López Claudia Yared , Huerta-García Josefina , Valladares-Carranza Benjamín , Valtierra-Marín Héctor Emmanuel
Published: February 2025

Secondary metabolites (SM) in plants play crucial pharmacological, ecological, and nutritional roles for humans, wildlife, and livestock. Environmental Heterogeneity (EH) encompasses the variability of biotic and abiotic factors that influence biological responses of plant species. Advancements in remote sensing have enhanced the ability to assess plant functional traits more affordably and comprehensively by integrating spectral reflectance data with detailed plant metabolomics. However, studies investigating the relationship between EH—quantified using Rao’s Q heterogeneity index from remote sensing data—and SM diversity remain limited. Here, we present the first report demonstrating that the biotic component of EH, measured as Rao’s Q, is positively associated with SM diversity in mesquite pod extracts—higher Rao’s Q values correspond to greater SM diversity. Generalized additive models (GAMs) revealed that Rao’s Q contributed the most explanatory power, accounting for 21.2% of the deviance, compared to pod weight (13.7%) and pod length (2.03%). However, only the relationship between Rao’s Q and SM diversity was statistically significant (p = 0.029). The Rao’s Q index derived from remote sensing serves as a scalable proxy for identifying SM hotspots, facilitating the targeted discovery of regions with high pharmacological or nutritional value.
Tailoring Gamification in a Science Course to Enhance Intrinsic Motivation in Preservice Primary Teachers
Authors: Jiménez-Valverde Gregorio , Fabre-Mitjans Noëlle , Heras-Paniagua Carlos , Guimerà-Ballesta Gerard
Published: February 2025

This study examines the intrinsic motivation of preservice primary teachers in a science education course designed with player-type personalization in gamification strategies. Using a mixed-methods approach, a one-group post-test-only design was combined with qualitative analysis. Game elements were personalized based on the HEXAD user typologies, aligning with Self-Determination Theory to support autonomy, competence, and relatedness. Quantitative data from the Intrinsic Motivation Inventory revealed high median scores across these psychological needs, suggesting that customization fostered deeper engagement. Key elements included cooperative challenges, branching narratives, and flexible participation pathways. Qualitative findings reinforced these results, highlighting students’ increased sense of agency, social connection, and investment in learning. The structured integration of narrative played a crucial role in contextualizing academic tasks, transforming the learning process into an immersive experience. Overall, the findings indicate that well-designed, personalized gamification strategies effectively bolster preservice teachers’ intrinsic motivation in this science education course. By demonstrating how player-type personalization optimizes motivation in gamified teacher education, this study contributes to the growing body of research on tailored gamification.
Optimization Study of Air-Based Cooling Photovoltaic Roofs: Experimental and Numerical Analysis
Authors: He Yi , Xue Yibing , Zhang Yingge
Published: February 2025

The rapid growth of photovoltaic (PV) installed capacity has driven advancements in photovoltaic technology, such as integrating PV panels into building envelopes. Temperature increases are known to negatively impact PV panel performance. This study investigates and optimizes the design of air-based cooling systems for PV roofs using experimental and numerical analyses, leveraging free natural convection for cooling. Experimental measurements included air inlet/outlet, PV panel, and roof surface temperatures. The primary parameters examined in Computational Fluid Dynamics (CFD) for the numerical study were the heights and widths of the air channels between the panels and the rooftop, with heights ranging from 25 mm to 75 mm and widths varying from 200 mm to 400 mm. There are good agreements between the numerical results and experimental measurements after model validation. The results reveal significant temperature non-uniformity across the surface of the PV panels, with a maximum temperature difference of 16.50 °C. The shading effect of the PV panels resulted in an average reduction in roof surface temperature by 12.90 °C. Parametric studies showed that changes in height had a more pronounced effect on cooling than in width. The optimal design was identified with a channel size of 75 mm × 400 mm, resulting in the lowest average PV panel temperature of 65.21 °C and enhanced temperature uniformity, with maximum efficiency reaching 11.54%.
Giant Bird Tracks (Family Gastornithidae) from the Paleogene Chuckanut Formation, Northwest Washington, USA, with a Review of Gastornis Distribution
Authors: Mustoe George E.
Published: February 2025

Giant Paleogene groundbirds named Gastornis have long been known from Europe, with similar fossils from North America being placed in the genus Diatryma. A more recent discovery in China is evidence that these birds had wide geographic distribution. The name Gastornis is now generally considered to be the name that has historical precedence. Historically, Gastornis has been interpreted as being a fierce predator, but anatomical and isotopic evidence suggests that the giant birds were herbivores. Gastornithid tracks preserved in Lower Eocene fluvial sediments of the Chuckanut Formation in northwest Washington State, USA, support the herbivore interpretation. These tridactyl footprints preserve broad triangular toenails rather than talons. The Chuckanut Formation gastornithid tracks have been given the ichnotaxonomic name Rivavipes giganteus Mustoe et al. (2012). In 2024, two important new discoveries were made. These are a trackway that preserves three adult tracks, and two tracks left by a gastornithid chick.The adult bird trackway has stride and pace distances that are consistent with the short lower limb bones (tarsometatarsals) observed in Gastornis skeletal remains. The reproductive strategies of gastornithids remain enigmatic; the evidence consists of numerous egg shell fragments found at sites in France and the newly discovered Chuckanut tracks.
The Origin of Amerindians: A Case Study of Secluded Colombian Chimila, Wiwa, and Wayúu Ethnic Groups and Their Trans-Pacific Gene Flow
Authors: Arnaiz-Villena Antonio , Lledo Tomás , Silvera-Redondo Carlos , Juarez Ignacio , Vaquero-Yuste Christian , Martin-Villa José Manuel , Suarez-Trujillo Fabio
Published: February 2025

Background/Objectives: The Human Leukocyte Antigen (HLA) system is composed of a set of genes that codify glycoproteins presenting antigenic proteins to clonotypic T cell receptors in order to start the immune response. Class I and Class II classical loci exhibit high allelic diversity; some of them (or their specific combinations that form haplotypes) are quasi-specific or highly frequent in certain populations and thus are useful for population genetic studies. In this study, an HLA genetic comparison of Chimila, Wayúu, Wiwa, and Barranquilla Colombian nonrelated healthy individuals was carried out together with other populations from all over the world to trace their genetic origin, obtain a virtual transplantation list, and inform future epidemiology studies. Methods: HLA-A, -B, -DRB1, and -DQB1 alleles were sequenced using the PCR-SSOP–Luminex method to analyze the HLA genetic profile of each individual. The data obtained were subsequently processed with standard software to obtain HLA alleles, haplotype frequencies, and genetic distances compared with data from global populations to generate relatedness dendrograms and carry out a correspondence analysis. Results: The results obtained place the Chimila, Wayúu, and Wiwa populations phylogenetically close to the other North and South Amerindian populations included in this study. Amerindians are genetically separated from the rest of the world’s populations. Chimila, Wayúu, and Wiwa present unique extended HLA haplotypes and specific alleles, such as HLA-B*48 or HLA-A*24:01, shared with Oceanian populations. Conclusions: These genetic results and anthropological data support prehistorical trans-Pacific (bidirectional) contacts that contributed to the settlement of America and also suggest that the effects of ancient European gene flow cannot be discarded.
Synergistic Regulation at Physiological, Transcriptional, and Metabolic Levels in Dendrobium huoshanense Plants Under Combined Drought and High-Temperature Stress
Authors: Zhang Xingen , Li Guohui , Wei Peipei , Du Binbin , Liu Shifan , Dai Jun
Published: February 2025

Background: With global warming and climate change, the occurrence of abiotic stresses has become increasingly prevalent. Drought often occurs with high temperatures, especially in arid and semi-arid regions. However, the molecular mechanisms of plants responding to combined drought and high-temperature stress remains unclear. Results: Through integrative physiological, transcriptomic, and metabolomic analyses, we systematically investigated the adaptive mechanisms of Dendrobium huoshanense under combined drought and high-temperature stress. Our findings revealed that combined drought and high-temperature stress led to significant reductions in photosynthetic efficiency and increased oxidative damage in Dendrobium huoshanense, with high-temperature stress being the primary contributor to these adverse effects. The joint analysis shows that three core pathways—signal transduction, lipid metabolism, and secondary metabolite biosynthesis—were identified as critical for antioxidant defense and stress adaptation. Conclusions: These findings not only deepen our understanding of plant responses to combined drought and high-temperature stress but also provide new directions for future research on the cultivation and resistance improvement of Dendrobium huoshanense.
Healthcare Professionals’ Perceptions and Experiences of Ageism: A Qualitative Study
Authors: Kim Jiyoun
Published: February 2025

This study focused on the experiences and perceptions of geriatric healthcare professionals. The research aimed to identify ageism, examine the influencing factors, explore the desired attitudes of geriatric healthcare professionals, and identify institutional changes required for age-integrated efforts and strategies to eliminate these barriers. Interviews with two physicians and eight nurses were conducted in South Korea from August to November 2023, with each session lasting about 1 h, and the transcripts were analyzed using the grounded theory by Strauss and Corbin. The analysis yielded 11 categories, 20 subcategories, and 120 concepts. The central phenomenon was “Ageism that is conducted implicitly and covertly”. Causal conditions affecting the development of ageism were “Difficulties related to the perceived characteristics of older adults” and “Extra burden for older patients and their families”. Contextual conditions were “Provider’s aging anxiety” and “Personal experience about older patients”, and interventional conditions were “Insufficient regular education aimed at ageism prevention” and “Insufficient staffing and resources”. The action/interaction strategies were “Not perceived as a critical issue” and “Perception that it is difficult to change”. After a thorough analysis and materializing of these concepts, the following prevention measures were proposed: “Need for regular education regarding the care of older patients (including ageism) in the nursing educational curriculum” and the “Need for sufficient staffing and resources”. According to the results of this study, medical professionals must satisfy the healthcare needs of the elderly by understanding the proper aging process and tailoring their approach to the specific characteristics of older individuals. To achieve this, organizations should provide adequate resources and personnel.
Monitoring Antibiotic Resistance in Wastewater: Findings from Three Treatment Plants in Sicily, Italy
Authors: Magnano San Lio Roberta , Maugeri Andrea , Barchitta Martina , Favara Giuliana , La Rosa Maria Clara , La Mastra Claudia , Agodi Antonella
Published: February 2025

Antimicrobial resistance (AMR) poses a global public health threat. Wastewater analysis provides valuable insights into antimicrobial resistance genes (ARGs), identifying sources and trends and evaluating AMR control measures. Between February 2022 and March 2023, pre-treatment urban wastewater samples were collected weekly from treatment plants in Pantano D’Arci, Siracusa, and Giarre (Sicily, Italy). Monthly composite DNA extracts were prepared by combining weekly subsamples from each site, yielding 42 composite samples—14 from each treatment plant. Real-time PCR analysis targeted specific ARGs, including blaSHV, erm(A), erm(B), blaOXA, blaNDM, blaVIM, blaTEM, and blaCTX-M. The preliminary findings revealed that blaERM-B, blaOXA, blaTEM, and blaCTX-M were present in all samples, with erm(B) (median value: 8.51; range: 1.67–30.93), blaSHV (0.78; 0.00–6.36), and blaTEM (0.72; 0.34–4.30) showing the highest relative abundance. These results underscore the importance of integrating ARG data with broader research to understand the persistence and proliferation mechanisms of ARGs in wastewater environments. Future studies should employ metagenomic analyses to profile resistomes in urban, hospital, agricultural, and farm wastewater. Comparing these profiles will help identify contamination pathways and inform the development of targeted ARG surveillance programs. Monitoring shifts in ARG abundance could signal cross-sectoral contamination, enabling more effective AMR control strategies.