bluuebunny/crossref_metadata_2025 huggingface dataset:
Impact of tele-exercise on quality of life, physical fitness, functional capacity and strength in different adult populations: a systematic review of clinical trials
Authors: Garrido Nuno Domingos , Reis Victor Machado , Vilaça-Alves José Manuel , Lucas Gabriela Chaves , Godinho Ismael Lima , Peixoto Rafael , Fucarino Alberto , Cantoia Manuela , Iuliano Enzo , De Giorgio Andrea , Fabbrizio Antonio , Suasa Martina , Zimatore Giovanna , Baldari Carlo , Macaluso Filippo
Published: January 2025

Introduction

This study aimed to review the impact of tele-exercise on different adult populations, comparing synchronous and asynchronous interventions and their effects on outcomes such as quality of life, physical fitness, functional capacity, strength, and pain.

Methods

Randomised clinical trials and quasi-experimental studies published between 2014 and 2024 were included, totalling 16 studies with 1,416 participants. The interventions varied between synchronous teleexercise (via videoconference) and asynchronous (via apps and recorded videos). The review followed the PRISMA guidelines, ensuring a systematic approach to study selection, data extraction, and bias assessment.

Results

The results indicate that tele-exercise, especially synchronous, has the potential to primarily improve physical fitness, functional capacity, and pain perception, being effective for the elderly and individuals with specific conditions such as multiple sclerosis and obesity.

Discussion

However, the methodological heterogeneity of the studies and the lack of consistent data limit the generalisation of the findings, highlighting the need for more high-quality research.

Systematic Review Registration

https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42024563241, PROSPERO (CRD42024563241).
Anodal tDCS and virtual reality gait rehabilitation in individuals with chronic stroke: a case series report
Authors: Marks Aracely , Oliveira Barbosa Shelley , Napoli Daniella , D'Andrea Susan E.
Published: January 2025

Background

Stroke is a principal cause of long-term disability worldwide, significantly impairing motor function, including gait and mobility. Conventional physical therapy, primarily focusing on repetitive, task-specific exercises, often falls short in addressing the complex rehabilitative needs of stroke survivors. Emerging technologies such as virtual reality (VR) and transcranial direct current stimulation (tDCS) have shown potential to enhance neuroplasticity and functional recovery, suggesting that their combined use could offer a novel pathway for stroke rehabilitation.

Objective

This study evaluated the efficacy of an integrated VR and tDCS treadmill training protocol in improving gait and mobility outcomes among individuals with chronic stroke.

Methods

Five chronic stroke patients were recruited for this study. Participants were randomly assigned to receive either anodal tDCS or sham stimulation in conjunction with VR treadmill training. The anodal stimulation was targeted at the ipsilesional motor cortex, specifically over the primary motor cortex (M1) area corresponding to the C3/C4 locations in the 10–20 EEG system. The intervention consisted of 10 30-min sessions over 2 weeks. Clinical assessments, including the Dynamic Gait Index (DGI), Berg Balance Scale (BBS), 10-meter Walk Test (10MWT), and the Timed Up and Go Test (TUG) were conducted pre-intervention, immediately post-intervention, and at a 2-week follow-up.

Results

All participants demonstrated improvements in the clinical measures post-intervention, irrespective of whether they received anodal tDCS or sham stimulation. Notably, clinically significant improvements, defined by an improvement greater or equal to the established minimal clinically important differences (MCIDs), were observed in DGI scores for four participants, suggesting enhanced gait functionality.

Conclusion

The combined VR and tDCS interventions promise to improve gait and mobility in chronic stroke survivors. While the observed improvements were not distinctly attributed to tDCS, the role of VR training was notably beneficial. These preliminary findings underscore the potential of integrating emerging technologies in stroke rehabilitation and highlight the need for future research with larger cohorts to explore the distinct contributions of each modality and validate this integrative approach.
Early Neurological Deterioration following acute stroke: association with reperfusion therapies and National Institutes Of Health Stroke Scale score
Authors: Yu Tony Bing , Lee Cameron , Mallah Mohammed , Belo Caroline Domingos , Uribe Mz Recaman Maria Lucia , Noui Yassine , Bayhonan Samantha , Sari Beatrix , Mah Yee-Haur
Published: January 2025

Early Neurological Deterioration (END) following acute stroke is associated with worse long-term functional outcomes. END is poorly defined and its relationship to reperfusion therapies is not fully understood. NIHSS is commonly used to risk-stratify and identify END following acute stroke however its relationship to END is relatively unexplored. The electronic health record of 933 stroke patients admitted to the Hyperacute Stroke Unit at King's College Hospital in 2022 were manually reviewed for END up to 14-days post stroke to: (1) characterize etiology and risk factors associated with END following acute stroke, and (2) evaluate the association between END, reperfusion therapy and NIHSS. Age, sex and co-morbidity were not associated with END, whereas reperfusion therapy was associated with greater END risk. Admission NIHSS was associated with END in those receiving conventional therapy alone, however, was not associated with END in those receiving reperfusion therapy. For those receiving IVT or EVT, the change in NIHSS at 24-hours was associated with END whereas admission NIHSS was not. In patients with a stable NIHSS 24-hours post stroke, there remained a greater than 10% risk of END. In conclusion, demographic factors and co-morbidity appear less important in determining END risk than stroke severity and treatment type. Admission NIHSS had limited association with END risk in those undergoing reperfusion therapy whereas the change in NIHSS at 24-hours was useful. NIHSS alone appears insufficient in its sensitivity to END to act as a risk-stratification tool, as significant END risk remains in those with stable or improving NIHSS.
Molecular investigation reveals three hemotropic mycoplasmas in cats and three tick species in China
Authors: Shi Hongfei , Li Guoguang , Li Dandan , Zhai Hongyue , Ji Shidong , Hu Yun , Wang Long , Yao Lunguang
Published: January 2025

To date, the primary hemoplasmas that infect cats include Mycoplasma haemofelis, ‘Candidatus Mycoplasma haemominutum’, and ‘Candidatus Mycoplasma turicensis’. In addition, other hemoplasmas Mycoplasma species have also been identified in cats. In central China, no infections or potential vectors with hemotropic mycoplasmas have been recorded in cats. To elucidate the prevalence of hemotropic mycoplasmas in both cats and parasitic ticks, this study investigated the occurrence of hemotropic mycoplasma infections in ticks and cats. A total of 78 blood samples were collected from both anemic and healthy cats, along with 284 ticks from the cats’ body surfaces and 356 ticks found in the surrounding environment. Following the morphological and molecular identification of ticks, all samples were screened for pathogens using PCR detection and sequence analysis. The results indicated the presence of 392 Haemaphysalis longicornis, 152 Rhipicephalus microplus, and 76 Rhipicephalus sanguineus sensu lato in cats and their surrounding environment. Molecular detection revealed the amplification of 156 ‘Ca. M. haemominutum’, 96 ‘Candidatus Mycoplasma haemobos’, 41 M. haemofelis, and 64 Rickettsia felis-positive amplicons from both cats and ticks. Notably, when comparing the infection rates of ‘Ca. M. haemobos’ in the environment group, no significant differences were observed in the infection rates among the three tick species from anemic or healthy cats (p > 0.05, α = 0.05). Furthermore, sequence analysis of ‘Ca. M. haemobos’ indicated two novel sequence types that were most closely related to an isolate from buffalo in China. In conclusion, in this study, in addition to ‘Ca. M. haemominutum’ and M. haemofelis, ‘Ca. M. haemobos’ was first detected in cats. ‘Ca. M. haemominutum’ appears to be associated with anemic syndrome in cats, while further research is needed to explore the relationship between ‘Ca. M. haemobos’ and clinical signs in felines. Additionally, these three hemotropic mycoplasmas were also found in three species of ticks, and transmission experiments are required to investigate the capacity of these ticks to transmit hemoplasmas Mycoplasma among animals.
Improved Results Over Time With Bridge-to-Lung Transplantation: A 10-Year Experience of a Single High-Volume Center
Authors: Kim Gyungah , Ahn Jee Hwan , Shim Tae Sun , Kang Pil-Je , Lee Geun Dong , Choi Sehoon , Kim Won , Jung Sung-Ho , Kim Dong Kwan , Park Seung-Il , Hong Sang-Bum
Published: January 2025

When donor scarcity limits timely lung transplantation (LTx), extracorporeal membrane oxygenation (ECMO) as a bridge to transplantation (BTT) can prolong survival and delay deconditioning until the donor lungs become available. We reviewed 10-year BTT experiences of a single high-volume center, where 99 (59%) were on ECMO BTT among 169 eligible adult LTx cases. Both 28-day and 2-year survivals did not differ between BTT and non-BTT. The BTT data was then divided into two periods, delineated by the most recent 3 years. The clinical outcomes of the earlier period (“Period 1”) and the later period (“Period 2”) were compared, and mortality within 28 days of LTx was significantly lower in Period 2 (n = 1, 1.7%) than in Period 1 (n = 6, 14.6%, p < 0.01). Improved survival was observed in the subgroup with BTT duration of 14 days or more. Taken together, more experiences in BTT and improved competence may contribute to better survival after LTx, especially in patients receiving ECMO for 14 days or more.
Utilizing Noseband Sensor Technology to Evaluate Rumination Time as a Predictor of Feeding and Locomotion Behaviors in Dairy Cows
Authors: Antanaitis Ramūnas , Džermeikaitė Karina , Krištolaitytė Justina , Arlauskaitė Samanta , Girdauskaitė Akvilė , Tolkačiovaitė Kotryna , Juodžentytė Renalda , Palubinskas Giedrius , Labokojytė Aistė , Šertvytytė Greta , Lembovičiūtė Gabija , Baumgartner Walter
Published: January 2025

The objective of the study was to examine the relationship between rumination time and various parameters related to eating and locomotion, including other chews, eating chews, eating time, drinking gulps, bolus counts, chews per minute, activity, and activity change, utilizing RumiWatch technology. The RumiWatch noseband sensor (RWS; ITIN + HOCH GmbH, Feeding Technology, Liestal, Switzerland) was utilized to record time and frequency related to rumination, eating, and movement behaviors. The RumiWatch system (RWS) was put into operation from 1 June 2023 to 30 June 2023. The first two weeks, from 1 June to 14 June 2023 at 7 a.m., served as a period for the cows to acclimate to the RWS, acting as an adjustment phase. Monitoring activities with the RWS commenced on 7 a.m. and lasted until the end of the month, 30 June 2023, with data being recorded daily on an hourly basis. Our findings indicate a significant negative correlation between rumination time and other activity time (r = −0.50), which represents the duration cows allocate to behaviors outside of eating, chewing cud, or distinct movement activities. Additionally, a significant negative correlation was observed between rumination time and eating time (r = −0.54). Furthermore, we observed strong positive correlations with rumination chews (r = 0.84) and bolus (r = 0.75). A weaker positive correlation was found with chews per minute (r = 0.29), while no significant correlation was detected with drinking gulps (r = 0.10). Based on our findings, we recommend the implementation of the RumiWatch System for monitoring rumination and feeding behaviors in lactating dairy cattle. This technology provides valuable insights into cow health and welfare, enabling early detection of potential health issues and improving herd management practices.
A Model for Diagnosing Mild Nutrient Stress in Facility-Grown Tomatoes Throughout the Entire Growth Cycle
Authors: Yuan Yunpeng , Sun Guoxiang , Chen Guangyu , Zhang Qihua , Liang Lingwei
Published: January 2025

The effective diagnosis of mild nutrient stress across the complete growth cycle of facility-grown tomatoes is challenging. This study proposes a deep learning framework based on CNN + LSTM, using canopy near-infrared spectroscopy from different growth stages of tomatoes as input, to diagnose mild stress of nitrogen (N), potassium (K), and calcium (Ca) throughout the entire growth cycle of facility-grown tomatoes. The study compares the diagnostic performance of Random Forest (RF), Support Vector Machine (SVM), Partial Least Squares (PLS), Convolutional Neural Networks (CNNs), and CNN + Long Short-Term Memory (LSTM) models for detecting mild nutrient stress in facility-grown tomatoes. Firstly, the preprocessing method of spectral characteristic bands combined with Savitzky-Golay (SG) + Standard Normal Variate (SNV) was determined. Subsequently, all sample data were divided into six groups: N-deficient, K-deficient, Ca-deficient, N-excess, K-excess, and Ca-excess. The aforementioned models were then used for classification prediction. The results show that RF and CNN + LSTM models demonstrated good predictive performance. Specifically, RF achieved accuracy rates of 70.14%, 90.81%, 88.59%, and 85.37% in the classification tasks of Ca-deficient, N-excess, K-excess, and Ca-excess, respectively. The CNN + LSTM model achieved accuracy rates of 93.33%, 63.33%, 99.2%, 83.33%, and 98.52% in the classification tasks of K-deficient, Ca-deficient, N-excess, K-excess, and Ca-excess, respectively. Finally, in the Leave-One-Group-Out Validation (LOGOV) for validating the model’s generalisation performance, RF performed better in the N-deficient, K-deficient, and Ca-deficient tasks, achieving diagnostic accuracy rates of 80.19%, 81.43%, and 77.02%, respectively. The CNN + LSTM model showed a diagnostic accuracy rate of 66.72% in the N-excess classification task. The study concludes that, given complete training data, the CNN + LSTM model can effectively diagnose mild nutrient stress (N, K, and Ca) in facility-grown tomatoes in most scenarios.
Heatmap Regression-Based Context-Aware Learning for Tillage Boundary Detection
Authors: Ham Gyu-Sung , Oh Kanghan
Published: January 2025

In agricultural automation, autonomous tractors play a crucial role in enhancing farming efficiency, particularly through the navigation and identification of tillage boundaries. Traditional approaches rely on machine vision techniques to identify paths by distinguishing between tilled and untilled soil areas. Although recent advancements in convolutional neural networks (CNNs) have shown promising results in agricultural automation, they still face challenges in fully capturing the global context of tillage boundaries. This limitation stems mainly from CNNs’ small receptive fields, which often limit the network’s capacity to capture broader contextual information in agricultural landscapes, potentially causing inaccuracies in boundary detection. These methods rely significantly on local feature analysis and necessitate complex, computationally intensive heuristic post-processing to enhance detected tillage lines, thus limiting their real-time application efficacy. We propose a line-context-aware learning method that combines a heatmap regression with a transformer to more effectively learn and extract global contextual features. The proposed end-to-end method streamlines detection, enhancing real-time agricultural applications and improving the accuracy and reliability of autonomous tractor navigation and operation. The proposed method was evaluated on a custom dataset, demonstrating competitive performance in accurately detecting tillage boundaries and proving its capability to handle the intricate details and variations present in agricultural landscapes.
The Application of Machine Learning to Model the Impacts of Extreme Climatic Events on the Productivity of Dwarf Green Coconut Trees in the Eastern Amazon
Authors: Nery Maryelle Kleyce M. , Fernandes Gabriel S. T. , Pinto João V. de N. , Rua Matheus L. , Santos Miguel Gabriel M. , Ribeiro Luis Roberto T. , Navarro Leandro M. , de Souza Paulo Jorge O. P. , Rolim Glauco de S.
Published: January 2025

The coconut crop (Cocos nucifera L.) is essential in humid tropical regions, contributing to the economy and food security. However, its perennial nature makes it sensitive to climate variability, particularly extreme events that affect productivity. This study evaluated the impacts of extreme climatic events on the productivity of dwarf green coconut in northeastern Pará, analyzing rainy (PC—December to July) and less rainy (PMC—August to November) periods between 2015 and 2023. Meteorological and experimental data were used, including extreme climate variables such as maximum temperature (HT) and precipitation (HEP), defined by the 90th percentiles, and low precipitation (LP, 10th percentile). Predictive models, such as Multiple Linear Regression (MLR) and Random Forest (RF), were developed. RF showed better performance, with an RMSE equivalent to 20% of the average productivity, while that of MLR exceeded 50%. However, RF struggled with generalization in the test set, likely due to overfitting. The inclusion of lagged productivity (productivity t-1) highlighted its significant influence. During the PC, extreme high precipitation (HEP) events and excessive water surplus (HE) occurring after the fifth month of inflorescence development contributed to increased productivity, whereas during the PMC, low-precipitation (LP) events led to productivity reductions. Notably, under certain circumstances, elevated precipitation can mitigate the negative impacts of low water availability. These findings underscore the need for adaptive management strategies to mitigate climatic impacts and promote stability in dwarf green coconut production.
Semi-Supervised Chinese Word Segmentation in Geological Domain Using Pseudo-Lexicon and Self-Training Strategy
Authors: Wan Bo , Tan Zhuo , Chu Deping , Dai Yan , Fang Fang , Wu Yan
Published: January 2025

Chinese word segmentation (CWS), which involves splitting the sequence of Chinese characters into words, is a key task in natural language processing (NLP) for Chinese. However, the complexity and flexibility of geologic terms require that domain-specific knowledge be utilized in CWS for geoscience domains. Previous studies have identified several challenges that have an impact on CWS in the geoscience domain, including the absence of abundant labeled data and difficult-to-delineate complex geological word boundaries. To solve these problems, a novel semi-supervised deep learning framework, GeoCWS, is developed for CWS in the geoscience domain. The framework is designed with domain-enhanced features and an uncertainty-aware self-training strategy. First, n-grams are automatically constructed from the input text as a pseudo-lexicon. Then, a backbone model is suggested that learns domain-enhanced features by introducing a pseudo-lexicon-based memory mechanism to delineate complex geological word boundaries based on BERT. Next, the backbone model is fine-tuned with a small amount of labeled data to obtain the teacher model. Finally, we design a self-training strategy with joint confidence and uncertainty awareness to improve the generalization ability of the backbone model to unlabeled data. Our method outperformed the state-of-the-art baseline methods in extensive experiments, and ablation experiments verified the effectiveness of the proposed backbone model and self-training strategy.
Bayesian Growth Curve Modelling of Student Academic Trajectories: The Impact of Individual-Level Characteristics and Implications for Education Policy
Authors: Mosia Moeketsi , Egara Felix O. , Nannim Fadip , Basitere Moses
Published: January 2025

This study examined the factors influencing student academic performance in the Bachelor of Science (BSc) Actuarial Science programme, focusing on Grade 12 mathematics marks, admission point (AP) scores, socioeconomic background, and progression rates. The purpose of this research was to identify the predictors of academic success and the disparities in performance related to socioeconomic factors. Data were obtained from 770 student records, with particular emphasis on admission point (AP) scores, Grade 12 mathematics marks, and progression rates over time. Bayesian hierarchical modelling was applied to analyse how these factors contribute to the students’ academic trajectories. The results revealed a strong correlation between Grade 12 mathematics marks and university success in Actuarial Science. Furthermore, students from lower SES backgrounds tended to perform less favourably than their peers, suggesting persistent disparities in academic achievement. Non-academic factors, such as personal motivation and external support systems, played a crucial role in student performance. This study concludes by recommending that universities adopt more holistic support strategies, incorporating both academic and non-academic interventions, to address the diverse needs of students in rigorous academic programmes like Actuarial Science. Educational policymakers are urged to revise admission policies and enhance support structures to foster equity and academic excellence.
On Ulam Stability of the Davison Functional Equation in m-Banach Spaces
Authors: El-hady El-sayed , Brzdęk Janusz
Published: January 2025

We prove new Ulam stability results for the Davison functional equation, in the class of mappings h from a ring F into an m-Banach space. In this way, we complement several earlier outcomes, by extending them to the case of m-normed spaces. Our proofs are based on an earlier Ulam stability result obtained for some functional equation in a single variable.
Biaxial Resistance of Pre-Engineered Beam Hangers in Glulam
Authors: Ganjali Houman , Tong Fei , Tannert Thomas
Published: January 2025

In timber construction, Glulam post-and-beam systems are commonly used to transfer vertical loads to the foundation. In such systems, the connections play a critical role in structural performance. Pre-engineered connectors, which facilitate fast and efficient assembly, are typically designed to resist only vertical shear loads. However, during seismic and wind events, post-and-beam systems deform horizontally, and axial forces develop at the connections. In this research, the performance of RICON and MEGANT pre-engineered connectors was studied under biaxial loading involving concurrent shear and axial forces. A total of 12 full-scale tests on Glulam frame segments were conducted. Neither type of connector experienced any resistance loss under concurrent shear loads equal to the factored shear resistance and axial loads equal to 5% of the factored shear resistance. The axial load-carrying capacity of the RICON and MEGANT connectors was up to 124% and 97% of their factored shear resistance, respectively. The global failure of all the studied connectors demonstrated both ductility and residual deformation capacity. These results provide valuable information for engineers designing Glulam post-and-beam systems in seismic regions.
Anthocyanin-Binding Affinity and Non-Covalent Interactions with IIS-Pathway-Related Protein Through Molecular Docking
Authors: Haroon  , Khan Zahid , Javaid Wasim , Xing Lian-Xi
Published: January 2025

Anthocyanins compounds, including cyanidin, malvidin, pelargonidin, peonidin, and petunidin, have demonstrated remarkable anti-aging and insulin-sensitizing properties through their interactions with proteins associated with the insulin/insulin-like growth factor signaling (IIS) pathway in Reticulitermes chinensis, employing advanced molecular docking techniques to elucidate strong binding affinities between specific anthocyanins and key proteins such as Pdk1, EIF4E, and Tsc2 in R. chinensis, suggesting a potential mechanism for their anti-aging effects. These findings not only provide critical insights into the therapeutic potential of anthocyanins for mitigating insulin resistance and promoting longevity, but also highlight the efficacy of in silico molecular docking as a predictive tool for small-molecule–protein interactions. Our research opens new avenues for the development of innovative therapeutic strategies targeting age-related diseases. However, further investigations, including a comprehensive chromosomal analysis and in vivo studies, are essential in order to fully elucidate the molecular mechanism underlying these interactions and their physiological implications. The detailed characterization of anthocyanin-binding affinities and their interactions with key regulatory genes presents exciting opportunities for advancement in molecular medicine, pharmacology, and the development of novel nutraceuticals.
Heart Rate Variability-Based Stress Detection and Fall Risk Monitoring During Daily Activities: A Machine Learning Approach
Authors: Messaoud Ines Belhaj , Thamsuwan Ornwipa
Published: January 2025

Impaired balance and mental stress are significant health concerns, particularly among older adults. This study investigated the relationship between the heart rate variability and fall risk during daily activities among individuals over 40 years old. This aimed to explore the potential of the heart rate variability as an indicator of stress and balance loss. Data were collected from 14 healthy participants who wore a Polar H10 heart rate monitor and performed Berg Balance Scale activities as part of an assessment of functional balance. Machine learning techniques applied to the collected data included two phases: unsupervised clustering and supervised classification. K-means clustering identified three distinct physiological states based on HRV features, such as the high-frequency band power and the root mean square of successive differences between normal heartbeats, suggesting patterns that may reflect stress levels. In the second phase, integrating the cluster labels obtained from the first phase together with HRV features into machine learning models for fall risk classification, we found that Gradient Boosting performed the best, achieving an accuracy of 95.45%, a precision of 93.10% and a recall of 85.71%. This study demonstrates the feasibility of using the heart rate variability and machine learning to monitor physiological responses associated with stress and fall risks. By highlighting this potential biomarker of autonomic health, the findings contribute to developing real-time monitoring systems that could support fall prevention efforts in everyday settings for older adults.
A Bibliometric Review of COVID-19 Vaccines and Their Side Effects: Trends and Global Perspectives
Authors: Benites Santiago , Díaz Félix , Liza Rafael , Sánchez Luis , Rivera Luis
Published: January 2025

This bibliometric review analyzes global research on COVID-19 vaccine side effects, focusing on publication trends, collaborations, and key topic areas. Using VOSviewer and Bibliometrix for data analysis and visualization, this study examines 1353 unique papers indexed in Scopus and Web of Science (2020–2024). The results indicate a significant increase in publications in 2021 and 2022, with the United States, China, and Europe contributing the most. While many studies focused on common side effects, such as headache, fatigue, and injection-site pain, rare but serious adverse events, such as myocarditis, thrombocytopenia, Guillain–Barré syndrome, pericarditis, and thrombosis, were also reported. However, regions with limited research infrastructure, particularly in developing countries, remain underrepresented despite the critical need for vaccine safety studies in these areas. Additionally, journals such as Vaccines, Vaccine, and Human Vaccines and Immunotherapeutics, all ranked Q1, dominate the publication volume, ensuring wide dissemination through open-access availability. This analysis also highlights global collaboration networks, identifying key authors and regions with high levels of co-authorship. Thematic mapping distinguishes niche topics focused on rare and severe side effects from driving topics addressing more common reactions. This review, therefore, underscores the importance of scaling up research efforts in underrepresented regions and strengthening global collaborations to ensure effective pharmacovigilance. Finally, future research should prioritize the long-term, ongoing monitoring of side effects and address disparities in scientific output, particularly in developing countries where vaccine safety data are urgently needed.
Zoom-in Dermoscopy for Facial Tumors
Authors: D’Onghia Martina , Falcinelli Francesca , Barbarossa Lorenzo , Pinto Alberto , Cartocci Alessandra , Tognetti Linda , Rubegni Giovanni , Batsikosta Anastasia , Rubegni Pietro , Cinotti Elisa
Published: January 2025

Background/Objectives: Facial lesions, including lentigo maligna and lentigo maligna melanoma (LM/LMM), both malignant, present significant diagnostic challenges due to their clinical similarity to benign conditions. Although standard dermoscopy is a well-established tool for diagnosis, its inability to reveal cellular-level details highlights the necessity of new magnified techniques. This study aimed to assess the role of standard dermoscopy, high-magnification dermoscopy, and fluorescence-advanced videodermatoscopy (FAV) in diagnosing LM/LMM and differentiating them from benign facial lesions. Methods: This retrospective, observational, multicenter study evaluated 85 patients with facial skin lesions (including LM, LMM, basal-cell carcinoma, solar lentigo, seborrheic keratosis, actinic keratosis, and nevi) who underwent dermatological examination for skin tumor screening. Standard dermoscopy at 30× magnification (D30), high-magnification dermoscopy at 150× magnification (D150), and FAV examination were performed. Dermoscopic images were retrospectively evaluated for the presence of fifteen 30× and twenty-one 150× dermoscopic features, and their frequency was calculated. To compare D30 with D150 and D150 with FAV, the Gwet AC1 concordance index and the correct classification rate (CCR) were estimated. Results: Among 85 facial lesions analyzed, LM/LMM exhibited distinctive dermoscopic features at D30, including a blue–white veil (38.9% vs. 1.7%, p < 0.001), regression structures (55.6% vs. 21.7%, p = 0.013), irregular dots or globules (50.0% vs. 10%, p = 0.001), angulated lines (72.2% vs. 6.7%, p < 0.001), an annular granular pattern (61.1% vs. 20%, p = 0.002), asymmetrical pigmented follicular openings (100.0% vs. 21.7%; p < 0.001), and follicular obliteration (27.8% vs. 3.3%). At D150, roundish melanocytes (87.5% vs. 18.2%, p < 0.001) and melanophages (43.8% vs. 14.5%, p = 0.019) were predominant. FAV examination identified large dendritic cells, isolated melanocytes, and free melanin in LM/LMM (all p < 0.001) with high concordance to D150. Conclusions: Integrating D30, D150, and FAV into clinical practice may enhance diagnostic precision for facial lesions by combining macroscopic and cellular insights, thereby reducing unnecessary biopsies. However, future studies are essential to confirm these results.
Ultra-High Contrast (UHC) MRI of the Brain, Spinal Cord and Optic Nerves in Multiple Sclerosis Using Directly Acquired and Synthetic Bipolar Filter (BLAIR) Images
Authors: Condron Paul , Cornfeld Daniel M. , Bydder Mark , Kwon Eryn E. , Whitehead Karen , Pravatà Emanuele , Danesh-Meyer Helen , Shi Catherine , Emsden Taylor C. , Newburn Gil , Scadeng Miriam , Holdsworth Samantha J. , Bydder Graeme M.
Published: January 2025

In this educational review, the basic physics underlying the use of ultra-high contrast (UHC) bipolar filter (BLAIR) sequences, including divided subtracted inversion recovery (dSIR), is explained. These sequences can increase the contrast produced by small changes in T1 by a factor of ten or more compared with conventional IR sequences. In illustrative cases, the sequences were used in multiple sclerosis (MS) patients during relapse and remission and were compared with positionally matched conventional (T2-weighted spin echo, T2-FLAIR) images. Well-defined focal lesions were seen with dSIR sequences in areas where little or no change was seen with conventional sequences. In addition, widespread abnormalities affecting almost all of the white matter of the brain were seen during relapses when there were no corresponding abnormalities seen on conventional sequences (the whiteout sign). Grayout signs, in which there is a loss of contrast in gray matter or between gray matter and CSF, were also seen, as well as high signal boundaries around lesions. Disruption of the usual high signal boundary between white and gray matter was seen in leucocortical lesions. Lesions in the spinal cord were better seen or only seen with dSIR sequences. Generalized change was observed in the optic nerve with the dSIR sequence in a case of optic neuritis. UHC BLAIR sequences may be of considerable value for recognition of abnormalities in clinical practice and in research studies on MS.
An In-Vitro Investigation into the Fracture Resistance of Prefabricated and Custom-Made Zirconia Crowns for Permanent Molars in Children
Authors: Bani-Hani Thikrayat , Al-Fodeh Rami S. , Al-Wahadni Ahed M. , Abu-Alhaija Elham S. , Al-Hakam Mahmoud
Published: January 2025

Background: Recently, the demand for esthetic restorations has grown dramatically and extended into the pediatric population. The prefabricated zirconia crowns (PZCs) and custom-made zirconia crowns (CZCs) are new esthetic options in pediatric dentistry. However, they are still inadequately tested for use in children. Aim: To determine the fracture resistance and failure mode of the PZC in comparison to the CZC. Materials and Methods: In this in-vitro study, thirty cobalt-chromium dies were fabricated by scanning the negative replica of a prefabricated lower first permanent molar zirconia crown. CZCs were designed and milled using two different zirconia brands: Ceramill Zolid-FX (FX) and the Highly-Translucent (HT) zirconia. Dies were randomly assigned to receive either a PZC or a CZC (n = 10 in each group). All crowns were cemented on their respective dies using glass ionomer cement. Following artificial aging, all specimens were loaded to failure. Fracture mode analysis was performed. One-way ANOVA and Bonferroni post-hoc test were used for multiple comparisons across the groups. The significant level was set at p ≤ 0.05. Results: HT zirconia had a significantly higher fracture load compared to other groups (p < 0.05). The mean fracture resistance values were: (3087 ± 385) N for HT zirconia, (2633 ± 300) N for PZCs, and (2483 ± 381) N for FX, with no statistically significant difference in fracture strengths between PZCs and FX. Conclusions: HT zirconia crowns showed the highest fracture resistance amongst all groups. The fracture loads of tested crowns exceeded the maximum posterior biteforce. When placed in permanent molars, PZC are expected to perform well under masticatory forces in children.
Variable-Speed Hydropower Control and Ancillary Services: A Remedy for Enhancing Grid Stability and Flexibility
Authors: Cebeci Cagatay , Parker Max , Recalde-Camacho Luis , Campos-Gaona David , Anaya-Lara Olimpo
Published: January 2025

Variable-Speed Hydropower Plants (VSHP) are becoming more promising for stabilising power grids with the increasing integration of renewable energy sources. This research focuses on improving fault ride-through capabilities and delivering efficient ancillary services for VSHPs to support the grid by developing a comprehensive control strategy. The control system proposed integrates a machine-side controller, a Frequency Support Controller (FSC), a Virtual Synchronous Machine (VSM), a Vector Current Controller (VCC) for the grid-side converter, a turbine governor for regulating turbine speed, and a DC-link controller. PID with an anti-windup scheme and a Model Predictive Controller (MPC) were employed for the turbine governor. The MPC turbine governor results demonstrate the potential of advanced control methods for enhanced performance of the VSHP. A benchmarking between the MPC and the PID governor was made. The benchmarking results have reported that the MPC can achieve reference tracking improvements up to 99.42%. Tests on a diverse set of grid scenarios were conducted, and the graphical results showed significant improvements in mitigating the frequency drops through the effective governor response. The synthetic inertia provision is swift, completing within seconds of a frequency drop. Compared to the fixed-speed approach, the VSHP improves the grid’s overall stability by minimising frequency dipping and achieving steady-state recovery remarkably faster. The fixed-speed approach only begins to recover minutes after the VSHP reaches the settling time. By effectively providing critical ancillary services such as frequency support, synthetic inertia, and smooth fault ride-through capability, the VSHP can become a transformative solution for future power grids, which are estimated to be more reliant on renewable energy sources.
Strategic Dynamics and Decision-Making Models in the Maritime Trade of Biofuels in Spain: Insights into Port Operations and Energy Transition Policies
Authors: González-Cancelas Nicoletta , Vaca-Cabrero Javier , Camarero-Orive Alberto , Álvarez Garzón Diego Alfonso
Published: January 2025

This study examines the maritime trade of biofuels in Spain, focusing on its contribution to the global energy transition and sustainable development. Using data from Spain’s 28 port authorities, the research identifies key trends, trade dynamics, and port-specific roles. This study reveals that Spain is a net biofuel exporter, maintaining a positive balance of 5.20 million tons throughout the study period. Export volumes peaked in 2021 at 1.63 million tons, while imports have shown steady growth over the past seven years. Barcelona and Bilbao emerge as strategic ports with robust connections to the Netherlands, Italy, and Belgium, reinforcing Spain’s role in the international biofuel market. This study incorporates hierarchical decision models, including classification trees, to analyze sustainability and efficiency factors in biofuel trade. These models unveil key interactions between variables such as cargo type, origin country, and port characteristics, offering actionable strategies to optimize port operations and enhance Spain’s standing in the global biofuels sector. This research highlights the importance of sustainable port infrastructure and international collaboration to strengthen Spain’s position as a pivotal player in the global energy transition.
A Lightweight Stepwise SCMA Codebook Design Scheme for AWGN Channels
Authors: Hua Min , Meng Shuo , Juan Yue , Bian Borui , Liu Xiaoming
Published: January 2025

Forests play a critical role in maintaining global ecological balance, regulating climate, and supporting biodiversity. Effective forest management and monitoring relies on the deployment of large-scale wireless sensor networks (WSNs) for real-time data collection, enabling the protection of ecosystems and the early detection of environmental changes. However, such massive deployments pose serious challenges with increasingly scarce radio resources. Sparse code multiple access (SCMA), a non-orthogonal multiple access (NOMA) technique, has been identified as a promising solution for facilitating wireless communications among numerous distributed sensors in large-scale WSNs with improved spectral efficiency. This is essential for application scenarios involving a substantial number of terminal devices, including forest monitoring and management. Codebook design is a critical issue for SCMA systems. It is closely related to the detection performance at the receiver, which in turn has a direct effect on the communication coverage or quality of service (QoS) for the terminal devices. This paper investigates the symbol error rate (SER) performance of SCMA systems over AWGN channels and derives its theoretical upper bound. The optimization objectives for each stage of codebook design are mathematically analyzed for a single resource element (RE), a single device, and multi-device, multi-RE scenarios. On this basis, a lightweight stepwise codebook design scheme is proposed in this paper. Simulation results demonstrate that the proposed codebooks can maintain fairness among devices while guaranteeing detection performance.
Recent Insights on the Role of Nuclear Receptors in Alzheimer’s Disease: Mechanisms and Therapeutic Application
Authors: Shan Xiaoxiao , Li Dawei , Yin Huihui , Tao Wenwen , Zhou Lele , Gao Yu , Xing Chengjie , Zhang Caiyun
Published: January 2025

Nuclear receptors (NRs) are ligand-activated transcription factors that regulate a broad array of biological processes, including inflammation, lipid metabolism, cell proliferation, and apoptosis. Among the diverse family of NRs, peroxisome proliferator-activated receptors (PPARs), estrogen receptor (ER), liver X receptor (LXR), farnesoid X receptor (FXR), retinoid X receptor (RXR), and aryl hydrocarbon receptor (AhR) have garnered significant attention for their roles in neurodegenerative diseases, particularly Alzheimer’s disease (AD). NRs influence the pathophysiology of AD through mechanisms such as modulation of amyloid-beta (Aβ) deposition, regulation of inflammatory pathways, and improvement of neuronal function. However, the dual role of NRs in AD progression, where some receptors may exacerbate the disease while others offer therapeutic potential, presents a critical challenge for their application in AD treatment. This review explores the functional diversity of NRs, highlighting their involvement in AD-related processes and discussing the therapeutic prospects of NR-targeting strategies. Furthermore, the key challenges, including the necessity for the precise identification of beneficial NRs, detailed structural analysis through molecular dynamics simulations, and further investigation of NR mechanisms in AD, such as tau pathology and autophagy, are also discussed. Collectively, continued research is essential to clarify the role of NRs in AD, ultimately facilitating their potential use in the diagnosis, prevention, and treatment of AD.
The Role of Genetic, Environmental, and Dietary Factors in Alzheimer’s Disease: A Narrative Review
Authors: Mertaş Beyza , Boşgelmez İ. İpek
Published: January 2025

Alzheimer’s disease (AD) is one of the most common and severe forms of dementia and neurodegenerative disease. As life expectancy increases in line with developments in medicine, the elderly population is projected to increase in the next few decades; therefore, an increase in the prevalence of some diseases, such as AD, is also expected. As a result, until a radical treatment becomes available, AD is expected to be more frequently recorded as one of the top causes of death worldwide. Given the current lack of a cure for AD, and the only treatments available being ones that alleviate major symptoms, the identification of contributing factors that influence disease incidence is crucial. In this context, genetic and/or epigenetic factors, mainly environmental, disease-related, dietary, or combinations/interactions of these factors, are assessed. In this review, we conducted a literature search focusing on environmental factors such as air pollution, toxic elements, pesticides, and infectious agents, as well as dietary factors including various diets, vitamin D deficiency, social factors (e.g., tobacco and alcohol use), and variables that are affected by both environmental and genetic factors, such as dietary behavior and gut microbiota. We also evaluated studies on the beneficial effects of antibiotics and diets, such as the Mediterranean-DASH Intervention for Neurodegenerative Delay (MIND) and Mediterranean diets.
Myopericarditis and Pericardial Effusion as the Initial Presentation of Systemic Lupus Erythematosus in a Patient with Sickle Cell Trait: A Case Report
Authors: Rojas-Cadena Marlon , Rodríguez-Arcentales Felipe , Narváez-Cajas Jose , Arias-Intriago Marlon , Morales Orbe Karen , Izquierdo-Condoy Juan S.
Published: January 2025

Background: Systemic lupus erythematosus (SLE) is a chronic autoimmune disease with rare but severe cardiac manifestations, including myocarditis and pericarditis. The coexistence of SLE with sickle cell trait (SCT), an inherited hemoglobinopathy prevalent among individuals of African descent, is exceptionally rare and presents significant diagnostic challenges due to overlapping clinical features. Objective: To describe the case of an Afro-Ecuadorian male with SLE and sickle cell trait who developed an uncommon presentation of myopericarditis and pericardial effusion. Case report: A 48-year-old African American male with no prior medical history presented with persistent fever, polyarticular arthralgias, and pleuritic chest pain. Investigations revealed sickle cell trait (SCT) and myopericarditis with pericardial effusion, marking the initial manifestation of SLE. Diagnostic delays occurred due to overlapping symptoms and a family history of sickle cell disease. Laboratory findings showed elevated hemoglobin S (<50%), positive ANA (1:1280, coarse speckled pattern), and anti-Smith/RNP antibodies, meeting EULAR/ACR 2019 criteria for SLE. Cardiac MRI confirmed myopericarditis. Treatment with pulse methylprednisolone, oral prednisone, and mycophenolate mofetil resulted in clinical improvement, with stable disease control on immunomodulatory therapy during follow-up. Conclusions: This case highlights the diagnostic complexity of SLE in patients with SCT, particularly when presenting with myopericarditis as the initial manifestation. It emphasizes the importance of a comprehensive diagnostic approach and timely initiation of immunosuppressive therapy to optimize clinical outcomes. This report broadens the understanding of overlapping syndromes involving SLE and SCT.
The Need for a Quality Strategy in Metal Additive Manufacturing Technology
Authors: Sithole Cindy , Jalalian Athena , Hoekstra Sipke , Gibson Ian
Published: January 2025

This study investigates the need for a quality strategy in metal additive manufacturing (AM) technology effective for batch production. We carried out two surveys aimed at gathering data from industry experts to understand the challenges and the requirements of quality strategies in metal AM. Survey 1 investigated general quality aspects in metal technology, revealing key areas where quality strategies are required, such as process control, material consistency, and post-processing. It also highlighted challenges that directly impact part quality, including process variability, material inconsistencies, and surface finish issues. Survey 2, focused on batch production, showed that 75% of participants strongly agreed with the need for a specific quality strategy to address challenges specific to metal AM. The respondents highlighted critical processes requiring quality strategies, including powder quality, process optimisation, and defect detection, while identifying ongoing issues with process variability and material inconsistency. Both surveys indicate a need for a standardised and effective quality strategy to enhance production consistency, efficiency, and regulatory compliance. Regardless of a limited sample size of 59 respondents, these results emphasise the need for improved quality strategies in metal AM to reduce defects effectively, meet customer expectations, and ensure scalable production. This study provides insights into the strategic development of quality strategies significant for advancing metal AM technology.