bluuebunny/crossref_metadata_2025 huggingface dataset:
Quantitative Analysis of Propofol Dosage in Cannabis Users: A Systematic Review and Meta-Analysis
Authors: Baker Maxwell B. , Binda Dhanesh D. , Nozari Ala , Kennedy Joseph M. , Dienes Erin , Baker William E.
Published: January 2025

Background: Rising cannabis use poses significant challenges in the administration of general anesthetics, particularly propofol, due to potential alterations in pharmacodynamics caused by tetrahydrocannabinol and its interactions with central nervous system receptors. This systematic review and meta-analysis aims to consolidate the existing literature to quantify propofol requirements in cannabis users, highlighting the complex relationship between cannabis use and anesthetic management. Methods: A systematic search of English-language literature was conducted to identify studies with data on propofol dosing in adult cannabis users. Propofol requirements were defined as the total intraoperative dose needed to achieve and maintain adequate sedation or anesthesia, assessed using parameters like monitoring and procedural tolerance. A random-effects model was used with DerSimonian–Laird estimations for pooled effect sizes and 95% confidence intervals. Heterogeneity was assessed using I2 and Cochran’s Q statistics, and sensitivity analysis was conducted by grouping publications by design, size, and quality. Results: Eight qualified studies were identified with 2268 patients included. Patients who used cannabis were typically younger and more likely to smoke tobacco than non-users. Propofol requirements were significantly higher in cannabis users, who required an average additional dose of 47.33 mg compared to non-users. Subgroup analyses revealed that cannabis users undergoing general anesthesia needed an additional 30.57 mg intraoperatively, while those undergoing sedation for endoscopic procedures required an additional 53.02 mg. Conclusions: These results underscore the need for personalized anesthetic plans to accommodate physiological variations in cannabis users. However, the lack of standardized definitions for propofol requirements and the heterogeneity across studies necessitate caution in interpretation. The observed increase in propofol requirements suggests altered central nervous system sensitivities and receptor changes in cannabis users, emphasizing the need for further research to establish clear definitions, elucidate underlying mechanisms, and refine clinical guidelines for anesthetic management in this population.
From Survival to Recovery: Understanding the Life Impact of an Acute Aortic Dissection Through Activity, Sleep, and Quality of Life
Authors: Bacour Nora , Grewal Simran , Theijsse Rutger T. , Klautz Robert J. M. , Grewal Nimrat
Published: January 2025

Background/Objectives: An acute aortic dissection (AAD) is a cardiovascular emergency with high mortality rates if left untreated. Survival has increased due to improvements in diagnosis and therapy. However, during their recovery, survivors frequently encounter major social, psychological, and physical challenges. This study aimed to evaluate the recovery experience of AAD survivors in The Netherlands. Insights on sleep quality, physical activity, and quality of life were collected from a unique nationwide cohort of AAD survivors recruited through the national patient support network ‘Stichting Aorta Dissectie Nederland’. Methods: This study was conducted among AAD survivors who were recruited through a national association for aortic dissection known as ‘Stichting Aorta Dissectie Nederland (SADN)’. The participants (n = 61) completed questionnaires assessing demographic data, physical activity, sleep quality, and health-related QoL. Results: The cohort had a mean age of 60.1 years, and 47.5% of the participants were female. The prevalence of sleep disruptions was high, as 55.7% of the people were categorized as bad sleepers (PSQI > 5). Poor sleep was associated with low physical activity and a higher BMI. The physical activity levels varied, with 47.5% reporting moderate activity levels and 44.3% reporting high activity levels. The QoL scores varied greatly among the participants, with significant impairment across all fields and reduced enthusiasm for daily activities. Poor sleepers reported significantly lower QoL (p < 0.001). Conclusions: Our study highlights significant gaps in post-AAD care, particularly addressing QoL, sleep, and physical activity. By acknowledging the multifaceted nature of recovery, healthcare providers can develop tailored interventions that empower survivors to achieve better quality of life.
Advancing Cardiovascular Diagnostics: The Expanding Role of CMR in Heart Failure and Cardiomyopathies
Authors: Parlati Antonio Luca Maria , Nardi Ermanno , Marzano Federica , Madaudo Cristina , Di Santo Mariafrancesca , Cotticelli Ciro , Agizza Simone , Abbellito Giuseppe Maria , Perrone Filardi Fabrizio , Del Giudice Mario , Annunziata Francesco Ruggiero , Martone Isabel , Prastaro Maria , Paolillo Stefania , Perrone Filardi Pasquale , Gargiulo Paola
Published: January 2025

Cardiovascular magnetic resonance (CMR) imaging has become a cornerstone in the diagnosis, risk stratification, and management of cardiovascular disease (CVD), particularly heart failure (HF) and cardiomyopathies. Renowned as the gold standard for non-invasive quantification of ventricular volumes and ejection fraction, CMR delivers superior spatial and temporal resolution with excellent tissue–blood contrast. Recent advancements, including T1, T2, and T2* mapping, extracellular volume quantification, and late gadolinium enhancement, enable precise tissue characterization, allowing early detection of myocardial changes such as fibrosis, edema, and infiltration. These features provide critical insights into the pathophysiological mechanisms underlying HF phenotypes and diverse cardiomyopathies, enhancing diagnostic accuracy and guiding therapeutic decisions. This review explores the expanding role of CMR in CV disease, highlighting its diagnostic value in HF and in several cardiomyopathies, as well as its contribution to improving patient outcomes through detailed tissue characterization and prognosis.
Topographic Pattern-Based Nomogram to Guide Keraring Implantation in Eyes with Mild to Moderate Keratoconus: Visual and Refractive Outcome
Authors: de Sanctis Ugo , Caselgrandi Paolo , Gennaro Carlo , Tosi Cecilia , Borrelli Enrico , Marolo Paola , Reibaldi Michele
Published: January 2025

Background: To assess the outcome of Keraring (Mediphacos, Brazil) implantation according to a topographic pattern-based nomogram in eyes with mild to moderate keratoconus. Materials and Methods: A topographic pattern-based nomogram was used to guide Keraring selection in 47 consecutive eyes with stage I-II keratoconus (Amsler-Krumeich staging), which underwent femtosecond laser-assisted implantation at a single center. Electronic data of LogMar uncorrected distance visual acuity (UDVA) and corrected distance visual acuity (CDVA) manifest refraction and tomographic analysis (Pentacam HR, Oculus, Germany) measured preoperatively and at the last postoperative examination were retrospectively analyzed. Results: Mean follow-up was 18.8 months. (range 3–35). Mean UDVA improved (p < 0.001) from 0.87 ± 0.27 to 0.35 ± 0.21. UDVA increased on average by 5.13 lines. Mean CDVA improved from 0.21 ± 0.10 to 0.09. ± 0.07, and the proportion of eyes with CDVA ≥ 20/25 increased from 29.8% to 85.1% after surgery. No eyes lost lines of CDVA. The Alpins correction index of astigmatism was 0.77 and the mean refractive cylinder decreased from 4.99 ± 1.89 to −2.31 ± 1.47 D (p < 0.001). Mean and maximal keratometry was reduced on average by −2.10 ± 1.42 D and −3.02 ± 3.68 D, respectively (p < 0.001). The RMS of corneal high-order aberrations dropped from 3.296 ± 1.180 µm to 2.192 ± 0.919 µm, and that of vertical coma from −2.656 ± 1.189 µm to −1.427 ± 1.024 µm (p < 0.001). All topometric indices improved after surgery. Conclusions: Planning Keraring implantation using the topographic pattern-based nomogram is very effective and safe in eyes with mild to moderate keratoconus. Using that nomogram of UDVA and CDVA are clinically significant.
Psychophysiological Response Differences Between Advanced and Beginner Climbers and Fatigue Management
Authors: Padilla-Crespo Alejandro , Clemente-Suárez Vicente Javier , Bustamante-Sánchez Álvaro
Published: January 2025

Background/Objectives: Rock climbing is a multifaceted athletic activity that requires both psychological and physiological resilience. This study aimed to examine the differences in psychological factors and fatigue predictors between novice and advanced climbers, with a focus on the interplay between experience and performance. Methods: The study included 60 participants categorized based on climbing experience (novice or advanced). Psychological and physiological assessments were conducted, including heart rate variability (HRV), grip strength, rate of force development (RFD), subjective perceived stress (SPS), and anxiety levels using validated questionnaires. Results: Advanced climbers exhibited lower anxiety levels and better sympathetic modulation compared to novices. Significant differences in HRV parameters, grip strength, and RFD were observed, reflecting the impact of experience on physiological responses. Advanced climbers demonstrated notable strength decreases post-climbing, supporting the utility of a force sensor on a 20 mm edge for assessing forearm fatigue. Correlations between cortisol levels, anxiety, and self-confidence during climbing were also identified. Conclusions: The findings highlight the importance of psychological and physiological factors in climbing performance. Forearm fatigue emerged as a critical predictor, suggesting that portable force sensors can optimize training and injury prevention. Insights from this study may enhance training protocols and improve real-time performance monitoring in climbers.
Comprehensive Review of Environmental Surveillance for Azole-Resistant Aspergillus fumigatus: A Practical Roadmap for Hospital Clinicians and Infection Control Teams
Authors: Tashiro Masato , Nakano Yuichiro , Shirahige Tomoyuki , Kakiuchi Satoshi , Fujita Ayumi , Tanaka Takeshi , Takazono Takahiro , Izumikawa Koichi
Published: January 2025

As azole-resistant Aspergillus fumigatus emerges globally, healthcare facilities face mounting challenges in managing invasive aspergillosis. This review synthesizes worldwide azole resistance data to reveal profound regional variability, demonstrating that findings from other regions cannot be directly extrapolated to local settings. Consequently, hospital-level environmental surveillance is crucial for tailoring interventions to local epidemiology and detecting resistant strains in real-time. We outline practical approaches—encompassing sampling site prioritization, diagnostic workflows (culture-based and molecular), and PDCA-driven continuous improvement—so that even resource-limited facilities can manage resistant isolates more effectively. By linking real-time surveillance findings with clinical decisions, hospitals can tailor antifungal stewardship programs and swiftly adjust prophylaxis or treatment regimens. Our approach aims to enable accurate, ongoing evaluations of emerging resistance patterns, ensuring that institutions maintain efficient and adaptive programs. Ultimately, we advocate for sustained, collaborative efforts worldwide, where facilities adapt protocols to local conditions, share data through international networks, and contribute to a global knowledge base on resistance mechanisms. Through consistent application of these recommendations, healthcare systems can better preserve azole efficacy, safeguard immunocompromised populations, and refine infection control practices in the face of evolving challenges.
Exploring Psilocybe cubensis Strains: Cultivation Techniques, Psychoactive Compounds, Genetics and Research Gaps
Authors: Kurzbaum Eyal , Páleníček Tomáš , Shrchaton Amiel , Azerrad Sara , Dekel Yaron
Published: January 2025

Psilocybe cubensis, a widely recognized psychoactive mushroom species, has played a significant role in both historical and modern therapeutic practices. This review explores the complex interplay between genetic diversity, strain variability and environmental factors that shape the biosynthesis of key psychoactive compounds, including psilocybin and psilocin. With many strains exhibiting substantial variability in their phenotypic characteristics and biochemical content, understanding and documenting this diversity is crucial for optimizing therapeutic applications. The review also highlights advances in cultivation techniques, such as submerged fermentation of the mycelium, and innovative analytical methodologies that have improved the precision of compound quantification and extraction. Although there is limited scientific information on P. cubensis due to nearly four decades of regulatory restrictions on psychedelic research, recent developments in genetic and biochemical studies are beginning to provide valuable insights into its therapeutic potential. Furthermore, this review emphasizes key knowledge gaps and offers insights into future research directions to advance the cultivation, scientific documentation of strain diversity, regulatory considerations and therapeutic use of P. cubensis.
Forecasting Follies: Machine Learning from Human Errors
Authors: Sun Li , Zhao Yongchen
Published: January 2025

Reliable inflation forecasts are essential for both business operations and macroeconomic policy making. This study explores the potential of using machine learning (ML) techniques to improve the accuracy of human forecasts of inflation. Specifically, we develop and examine ML-centered forecast adjustment procedures where advanced ML techniques are employed to predict and thus mitigate the errors of human forecasts, akin to how an AI-powered spell and grammar checker helps to prevent mistakes in human writing. Our empirical exercises demonstrate the benefits of several popular ML techniques, such as the elastic net, LASSO, and ridge regressions, and provide evidence of their ability to improve both our own benchmark inflation forecasts and those reported by the frequent participants in the US Survey of Professional Forecasters. The forecast adjustment procedures proposed in this paper are conceptually appealing, widely applicable, and empirically effective in reducing forecast bias and improving forecast accuracy.
Quantifying the Driving Forces of Water Conservation Using Geodetector with Optimized Parameters: A Case Study of the Yiluo River Basin
Authors: Li Kang , Qian Hui , Li Siqi , Cao Zhiming , Tian Panpan , Shi Xiaoxin , Chen Jie , Gao Yanyan
Published: January 2025

Accurately identifying the impact of different factors on water conservation is influenced by the spatial grid scale. However, existing studies on water conservation often overlook the Modifiable Areal Unit Problem (MAUP). MAUP is one of the key factors contributing to the uncertainty in spatial analysis results. The Qinling Mountains are a critical water conservation area, with the Yiluo River Basin (YLRB) as a key sub-basin. This study uses the Optimized Parameter GeoDetector (OPGD) model to analyze water conservation changes and influencing factors in the YLRB from 1990 to 2020. By optimizing spatial scale (2 km grid) and driving factor discretization, the OPGD model addresses spatial heterogeneity and the MAUP, enhancing analysis accuracy. Results show a fluctuating upward trend in water conservation depth, averaging 0.94 mm yearly, with a spatial decline from southwest to northeast. High–high and low–low clusters dominate the region, with some areas consistently showing high or low values. Key conservation zones expanded by 2748 km2, reflecting significant enhancement. Natural factors, particularly precipitation, predominantly influence water conservation, outweighing human activities. The interaction between precipitation and temperature notably affects dynamic changes, while human impacts, such as land use, play a secondary role. The findings suggest water management should prioritize climatic factors and integrate land-use policies to enhance conservation. The OPGD model’s application improves factor identification and supports targeted ecological and water management strategies.
Respiratory Muscle Dysfunction and Associated Risk Factors Following COVID-19-Related Hospitalisation
Authors: Verduri Alessia , Tonelli Roberto , Donatelli Pierluigi , Hewitt Jonathan , Guaraldi Giovanni , Milić Jovana , Ruggieri Valentina , Mussini Cristina , Clini Enrico , Beghè Bianca
Published: January 2025

Background: Studies have highlighted long-term respiratory muscle dysfunction in COVID-19 survivors, although the underlying risk factors remain unclear. This single-centre study assessed respiratory muscle function and individual associated factors at follow-up in patients hospitalised with COVID-19 and related acute respiratory failure. Methods: Data were collected for consecutive patients, aged ≥ 18 years, at the post-COVID outpatient service of Hospital Policlinico in Modena (Italy) in the time frame of 3 to 6 months after discharge. Data were analysed using single and multiple logistic regression models. Correlations among MIP/MEP, hand-grip values, and lung function were further explored. Results: Out of 223 patients (mean age 67 years, 69% male) 121 (54.3%) exhibited MIP or MEP dysfunction, which was found to be associated with the use of non-invasive ventilation (aOR = 1.91 [1.07–3.49], p = 0.04) and female gender (aOR = 1.76 [1.09–4.16], p = 0.03) as independent risk factors. A positive correlation was observed between MIP dysfunction and hand-grip strength (p = 0.03 and 0.01), whereas both MIP and MEP were significantly associated with FEV1, FVC, TLC, and DLCO. Conclusions: Respiratory muscle dysfunction is consistently prevalent and parallels peripheral muscle weakness and the lung function level in patients at follow-up after severe COVID-19. The need for non-invasive ventilation during the acute phase and female gender might represent risk factors. MIP/MEP assessment should be recommended to observe respiratory muscle dysfunction in severe post-COVID survivors.
An Innovative Approach of Using a Bio-Based Polyurethane Elastomer to Overcome the “Magic Triangle” in Tires
Authors: Wang Xin , Yin Dexian , Chen Zhi , Zhao Xiuying , Ye Xin , Hu Shikai
Published: January 2025

Rubber tires are fundamental components of modern society and industrial operations, holding an irreplaceable position in the global manufacturing and transportation sectors. The potential for traditional rubber tires to enhance performance is gradually approaching its limits, rendering it challenging to further improve low rolling resistance, high wet-skid resistance, and high wear resistance (called “magic triangle”). Moreover, the reliance on petroleum resources for rubber hinders the sustainable development of rubber tires. In this work, a series of novel polyurethane (PU) elastomers with potential applications in high-performance automotive tires were synthesized by CO2-based poly(propylene carbonate) diol and bio-based poly(propylene oxide) glycol (PO3G). The comprehensive influences of PO3G on the thermal, mechanical, rolling resistance, and wear properties of the elastomers were systematically investigated. The results illustrated that increasing the PO3G content significantly enhanced the wear resistance by 98.43% and the wet-skid resistance by 73.21% and reduced the rolling resistance by 15.38% of the elastomers compared to commercial green tires (HT166). The rational design strategy of PU elastomers not only effectively addresses the “magic triangle” challenge in the tire industry but leverages CO2 to contribute to the sustainable development of the automotive sector.
Design Method of a Cylindrical Skiving Tool for Internal Gear with Circular Arcs
Authors: Guo Erkuo , Chen Mingfeng , Pan Xuechao , Yuan Yayun , Qiao Hua
Published: January 2025

Gear skiving is a highly productive method for manufacturing gears, especially internal gears. Circular arc internal gears are important parts of Rotary Vector (RV) reducers and harmonic reducers. This study presents the implementation of the gear skiving technique using a cylindrical tool to enhance the precision and efficiency of machining circular arc internal gears. By establishing the mathematical model for skiving a circular arc internal gear based on the conjugation theory of two surfaces, the barrel-shaped conjugate surface was solved by deducing gear meshing equations. A design method is proposed for a cylindrical skiving tool by utilizing the barrel-shaped conjugate surface with an off-center tool position along the axis. The cutting edge of the tool rake face was then obtained through cubic spline interpolation from the conjugate surface. The influence of the tool rake face offsets on the cutting rake angle and clearance angle is also discussed by defining the normal cutting plane of the tool. The correctness of the proposed cylindrical skiving tool was validated through simulation and actual skiving experiments. The experimental results demonstrated that the tooth profile error of the gear fell within ±0.004 mm, thereby satisfying the accuracy requirement for pin wheel housing gears. These research findings can contribute to advancements in novel cylindrical skiving tools.
Numerical Modeling and Optimization of Nomex Honeycomb Core Milling: Influence of Longitudinal and Longitudinal–Torsional Ultrasonic Vibrations
Authors: Zarrouk Tarik , Nouari Mohammed , Bouali Hicham
Published: January 2025

Nomex honeycomb structures (NHCs) have currently experienced significant development, mainly in the aeronautics, aerospace, marine, and automotive sectors. This expansion raises noteworthy challenges related to the improvement of machining excellence, necessitating the use of particular cutting tools and adapted techniques. With this in mind, experimental studies were conducted to analyze the specificities of Nomex honeycomb cores milling by integrating longitudinal ultrasonic vibrations along the cutting tool rotation axis (UCK). However, the high tool speed and the unreachability of the tool-workpiece interface complicate the direct observation of the cutting process. To overcome these challenges, a 3D numerical model was developed to simulate the milling of composite honeycomb structures by integrating longitudinal and longitudinal–torsional ultrasonic vibrations. This model was developed by Abaqus/Explicit software, version 2017. The obtained results indicate that the integration of longitudinal–torsional vibrations allows a reduction in cutting forces by up to 28%, a reduction in the accumulation of material in front of the cutting tool, with a maximum reduction of 30%, and an improvement in the quality of the machined surface.
Resource Allocation Optimization Model for Computing Continuum
Authors: Mihaiu Mihaela , Mocanu Bogdan-Costel , Negru Cătălin , Petrescu-Niță Alina , Pop Florin
Published: January 2025

The exponential growth of Internet of Things (IoT) devices has led to massive volumes of data, challenging traditional centralized processing paradigms. The cloud–edge continuum computing model has emerged as a promising solution to address this challenge, offering a distributed approach to data processing and management and improved performances in terms of the overhead and latency of the communication network. In this paper, we present a novel resource allocation optimization solution in cloud–edge continuum architectures designed to support multiple heterogeneous mobile clients that run a set of applications in a 5G-enabled environment. Our approach is structured across three layers, mist, edge, and cloud, and introduces a set of innovative resource allocation models that addresses the limitations of the traditional bin-packing optimization problem in IoT systems. The proposed solution integrates task offloading and resource allocation strategies designed to optimize energy consumption while ensuring compliance with Service Level Agreements (SLAs) by minimizing resource consumption. The evaluation of our proposed solution shows a longer period of active time for edge servers because of the lower energy consumption. These results indicate that the proposed solution is viable and a sustainability model that prioritizes energy efficiency in alignment with current climate concerns.
A Green Supplier Selection Through an MCDM Based Framework Under Fuzzy Environment
Authors: Lin Ting-Yu , Hung Kuo-Chen , Jablonsky Josef , Lin Kuo-Ping
Published: January 2025

Uncertainty exists in reality decision-making problems. Therefore, fuzzy theories, fuzzy intervals, intuitionistic fuzzy, and Z-numbers have been proposed and successfully applied to multi-criteria decision-making (MCDM). However, since the information presented in the Z-numbers method is the subjective opinion of the decision-maker, the problem of overestimating or underestimating the reliability of the information may occur in both individual and group decision-making. The Extended Z-numbers (ZE-numbers) method was proposed in 2021 to solve this problem; hence, the decision-making process no longer relies on subjective opinions only but seeks external experts related to the problem to further vote on the evaluation value given by the internal decision-maker, in order to modify the information’s reliability, and thus to obtain a more realistic result. This paper combines the ZE-numbers method with the improved Elimination et Choix Traduisant la Realite II (ELECTRE II) proposed in 2022 and proposes a new MCDM method based on ZE-numbers, named ZE-ELECTRE II. The green supplier selection problem was used as an illustrative example. Meanwhile, the close analysis in this paper examines two primary dimensions of variability: (1) simulation of external expert voting situations to analyze the variations in information reliability and decision-making results and to cross-compare them with other MCDM methods; (2) investigation of the impact of internal preferences, as reflected through systematic adjustments to the weights of the evaluation criteria. The results show that uncertainty of information, reliability, and the perspectives of different decision-makers and expert groups can be considered through ZE-numbers. The proposed ZE-ELECTRE II is applicable to group decision-making, validates the robustness of the process, and is suitable for dynamic decision-making under varying decision-maker preferences. Furthermore, using the ZE-numbers along with the MCDM method can obtain more flexibility and more reliable results.
The Finite Coarse Shape Paths
Authors: Jelić Ivan , Mirošević Ivančica
Published: January 2025

In this paper, we introduce the notions of finite coarse shape path and finite coarse shape path connectedness of a topological space. We prove that the solenoid Σ(pn), which is known to be coarse shape path connected but not shape path connected, is not finite coarse shape path connected either. Furthermore, we show that every finite coarse shape path induces an isomorphism between finite coarse shape groups of the topological space at different base points, with some interesting and useful properties. We also show that finite coarse shape groups of the same space, in general, depend on the choice of a base point. Hence, the pointed finite coarse shape type of X,x, in general, depends on the choice of the point x. Finally, we prove that if X is a finite coarse shape path connected paracompact locally compact space, then the pointed finite coarse shape type of X,x does not depend on the choice of the point x.
Sustainability, Accuracy, Fairness, and Explainability (SAFE) Machine Learning in Quantitative Trading
Authors: Dung Phan Tien , Giudici Paolo
Published: January 2025

The paper investigates the application of advanced machine learning (ML) methodologies, with a particular emphasis on state-of-the-art deep learning models, to predict financial market dynamics and maximize profitability through algorithmic trading strategies. The study compares the predictive capabilities and behavioral characteristics of traditional machine learning approaches, such as logistic regression and support vector machines, with those of highly sophisticated deep learning architectures, including Recurrent Neural Networks (RNNs), Long Short-Term Memory (LSTM) networks, and Gated Recurrent Units (GRUs). The findings underscore the fundamental distinctions between these methodologies, with deeply trained models exhibiting markedly different predictive behaviors and performance, particularly in capturing complex temporal patterns within financial data. A cornerstone of the paper is the introduction and rigorous analysis of a framework to evaluate models, by means of the SAFE framework (Sustainability, Accuracy, Fairness, and Explainability). The framework is designed to address the opacity of black-box ML models by systematically evaluating their behavior across a set of critical dimensions. It also demonstrates how models’ predictive outputs align with the observed data, thereby reinforcing their reliability and robustness. The paper leverages historical stock price data from International Business Machines Corporation (IBM). The dataset is partitioned into a training phase during which the models are calibrated, and a validation phase, used to evaluate the predictive performance of the generated trading signals. The study addresses two primary machine learning tasks: regression and classification. Classical models are utilized for classification tasks, with their outputs directly interpreted as trading signals, while advanced deep learning models are employed for regression, with predictions of future stock prices further processed into actionable trading strategies. To evaluate the effectiveness of each strategy, rigorous backtesting is conducted, incorporating visual representations such as equity curves to assess profitability and key risk metrics like maximum drawdown for risk management. Supplementary performance indicators, including hit rates and the incidence of false positions, are analyzed alongside the equity curves to provide a holistic assessment of each model’s performance. This comprehensive evaluation not only highlights the superiority of cutting-edge deep learning models in predicting financial market trends but also demonstrates the pivotal role of the SAFE framework in ensuring that machine learning models remain trustworthy, interpretable, and aligned with ethical considerations.
Preoperative Osteoporosis Treatment Reduces Stress Shielding in Total Hip Arthroplasty
Authors: Kanabuchi Ryuichi , Mori Yu , Baba Kazuyoshi , Tanaka Hidetatsu , Kuriyama Yasuaki , Fukuchi Hideki , Kawamata Hiroki , Aizawa Toshimi
Published: January 2025

Background: Total hip arthroplasty (THA) is a widely used surgical intervention for hip osteoarthritis (HOA), with a rising demand driven by an aging population. Osteoporosis is associated with increased risks of bone loss and implant loosening after THA. While medications such as bisphosphonates and denosumab have shown promise in mitigating these risks, the impact of preoperative osteoporosis treatment on postoperative outcomes remains unclear. This study investigates the effect of preoperative osteoporosis treatment intervention on stress shielding and clinical outcomes in THA patients. Methods: This retrospective study included 107 patients who underwent cementless THA between April 2019 and March 2022. Patients under 60 years old, with a follow-up period of less than one year, or with prior hip surgery were excluded. Participants were divided into two groups: a treatment group receiving osteoporosis medication preoperatively and a non-treatment group. The outcomes assessed included preoperative bone metabolism markers, Bombelli classification, stress shielding grade, and clinical scores. Statistical analysis was performed using the Mann–Whitney U test and Chi-squared test, with significance set at p < 0.05. Results: The preoperative osteoporosis treatment intervention rate was 28.9%. Stress shielding grades were significantly lower in the treatment group (p = 0.001). However, no significant differences were observed in clinical scores one year postoperatively. Conclusion: Preoperative osteoporosis treatment significantly reduced stress shielding incidence, potentially influencing long-term outcomes by preventing bone atrophy-related pain and fractures. Preoperative bone density assessment and osteoporosis treatment intervention are recommended to improve THA outcomes. Larger studies are needed for further validation.
Effect of Four Different Initial Drying Temperatures on Biochemical Profile and Volatilome of Black Tea
Authors: Shu Zaifa , Zhou Huijuan , Chen Limin , Wang Yuhua , Ji Qingyong , He Weizhong
Published: January 2025

Background: Black tea processing conditions significantly affect the final taste and flavor profiles, so researchers are now focusing on developing equipment and improving the appropriate processing conditions of major black tea varieties. Methods: Here, we tested the effect of four different initial drying temperatures, i.e., R65 (65 °C), R85 (85 °C), R105 (105 °C), and R125 (125 °C), on the sensory and biochemical profiles and volatilome of the black tea variety “Lishui wild” (LWV). Results: Our results indicate that both 85 and 105 °C are better than 65 and 125 °C for initial drying for 20 min. R105 had the highest sensory evaluation scores due to better shape, aroma, taste, leaf base, thearubigins, theanine, caffeine, and ratio of theaflavins + thearubigins to theaflavins. Both R85 and R105 had higher catechins than R65 and R125. The LWV volatilome consisted of esters (19.89%), terpenoids (18.95%), ketones (11.3%), heterocyclic compounds (9.99%), and alcohols (8.59%). In general, acids, aldehydes, amines, aromatics, ethers, hydrocarbons, phenols, sulfur compounds, and terpenoids accumulated in higher amounts in R85 and R105. The highly accumulated compounds in R105 were associated with green, fruity, sweet, woody, floral, hawthorn, mild, nutty, powdery, rose, and rosy flavors. The main pathways affected are secondary metabolites, sesquiterpenoid and triterpenoid biosynthesis, glycerolipid metabolism, zeatin biosynthesis, phenylpropanoid biosynthesis, ABC transport, glutathione metabolism, etc. Therefore, R105 can be used to achieve the optimal taste, flavor, and aroma of LWV. Conclusions: Overall, the presented data can be used by the tea industry for processing black tea with the most optimum volatile substances, catechins, theanine, amino acids, and other compounds.
Exploring Knowledge, Attitudes, and Behaviors Toward Antibiotics Use Among Adolescents in Southern Italy
Authors: Angelillo Silvia , Paduano Giovanna , Sansone Vincenza , De Filippis Anna , Finamore Emiliana , Pelullo Concetta Paola , Di Giuseppe Gabriella
Published: January 2025

Background: This study explored knowledge, attitudes, and behaviors regarding antibiotics among adolescents. Methods: The cross-sectional study was conducted from February to April 2024. Results: Overall, 65.2% of adolescents believed that antibiotics should only be used when prescribed, this was more likely among women and those who needed additional information regarding antibiotics. Women and adolescents without a parent with a chronic disease, who believed that it is not possible to stop antibiotics when symptoms improve and who disagreed that antibiotics are faster treatment for flu were more likely to prefer prescribed antibiotics. Antibiotic use without a medical prescription was reported by 37.4% of participants, and this was more likely among men and adolescents who had a parent with a chronic disease, who needed additional information regarding antibiotics, and who disagreed that antibiotics should only be used when prescribed. Adolescents who are afraid that antimicrobial resistance (AMR) may affect their health, who received previous information about AMR, who know that antibiotics are not useful for viral infection treatment, and who need additional information regarding antibiotics, were more likely to believe that it is important to talk about AMR at school. Conclusions: Interventions on AMR and antibiotic use among adolescents are needed.
Mutational Analysis Supports Three-Hairpin Model of Attenuator for Transcription Regulation of ilvBNC Operon in Corynebacterium glutamicum
Authors: Ryabchenko Ludmila E. , Titov Igor I. , Leonova Tatyana E. , Kalinina Tatyana I. , Gerasimova Tatyana V. , Sheremetieva Marina E. , Kolchanov Nikolay A. , Khlebodarova Tamara M. , Yanenko Alexander S.
Published: January 2025

The ilvBNC operon in Corynebacterium glutamicum encodes key enzymes for the biosynthesis of branched-chain amino acids (L-isoleucine, L-leucine, and L-valine). This operon has been studied for quite a long time, and it is assumed that three hairpin mRNA structures can be formed in its regulatory region; however, their functionality and role in the attenuation mechanism of the ilvBNC operon are not completely clear. In the present work, we performed a mutational analysis of mRNA secondary structures in the regulatory region of the C. glutamicum ilvBNC operon, which allowed us to propose a model of the regulation of its transcription involving three mRNA hairpins that essentially act as a transcription terminator, an antiterminator, and an antiantiterminator. In this work, we proved the existence of a transcription terminator in this operon and experimentally confirmed the effectiveness of its influence on the expression of the ilvBNC operon, AHAS enzyme activity, and valine production. We demonstrated the unique functional features of this attenuator, which, due to the overlapping of the terminator and antiterminator hairpins, is capable of rapid low-energy transitions between them without the complete disruption of the hairpin structures.
Enhanced Coercivity and Tb Distribution Optimization of Sintered Nd-Fe-B Magnets by TbF3 Grain Boundary Diffusion Facilitated by Ga
Authors: Wang Ling , Li Wenjiao , Wang Xiaopeng , Deng Zejun , Gao Shujuan
Published: January 2025

The grain boundary diffusion process employing a mixed diffusion source, comprising heavy rare-earth elements and low-melting metals, significantly enhances the coercivity (Hcj) of sintered Nd-Fe-B magnets. In the present study, Tb and Ga were deposited onto the surface of Nd-Fe-B magnets to serve as a diffusion source for improving hard magnetic properties. The effects of varying deposition sequences of Tb and Ga on the magnetic properties and microstructure of the magnets were analyzed. The findings demonstrate that TbF3 grain boundary diffusion facilitated by Ga effectively increases the efficiency of Tb substitution, leading to enhanced coercivity. When Tb and Ga are deposited simultaneously, coercivity shows a notable improvement of 53.15% compared to the untreated magnet, with no reduction in remanence. Additionally, thermal stability is enhanced, resulting in superior overall magnetic properties. Microstructural analysis reveals that Ga promotes the diffusion of Tb into the magnet. In the magnet where Tb and Ga are co-deposited, the formation of a thinner and more uniform (Nd,Tb)2Fe14B shell–core structure, along with the greater infiltration depth of Tb, leads to a broader distribution of core–shell structures within the magnet. This effectively increases the anisotropy fields (HA) of the main phase grains, preventing the nucleation of antiferromagnetic domains at the edges of main-phase grains, thereby enhancing coercivity. Furthermore, the corrosion resistance of the magnet subjected to mixed diffusion is improved. This study provides a foundation for producing highly efficient magnets with a lower content of heavy rare-earth elements. The simplicity and flexibility of the process make it highly suitable for industrial applications.
Ultra-Processed Food Consumption and Metabolic-Dysfunction-Associated Steatotic Liver Disease (MASLD): A Longitudinal and Sustainable Analysis
Authors: García Silvia , Monserrat-Mesquida Margalida , Ugarriza Lucía , Casares Miguel , Gómez Cristina , Mateos David , Angullo-Martínez Escarlata , Tur Josep A. , Bouzas Cristina
Published: January 2025

Background: The rising prevalence of metabolic-dysfunction-associated steatotic liver disease (MASLD) is a significant health challenge, and the consumption of ultra-processed foods (UPFs) could play a key role. Aim: The aim is assess the impact of UPF consumption changes on the development and progression of MASLD in adults. Design: This is a longitudinal study to assess how changes in UPF consumption affect liver fat and MASLD parameters over 6 months in 70 participants. Methods: Dietary intake was assessed using a validated food frequency questionnaire, and foods were classified according to the NOVA system. Participants were divided into three groups based on UPF consumption changes: maximum (T1), medium (T2), and minimum reduction (T3). Fatty liver parameters were assessed with magnetic resonance imaging and ultrasonography. Mediterranean diet (Med-diet) adherence and sociodemographic parameters were also recorded. The General Linear Model was used to determine relationships between UPF consumption, fatty liver disease parameters, and diet. Results: Participants in T1 experienced a 7.7% reduction in intrahepatic fat content (IFC) compared to 2.6% in T3. T1 showed increased Med-diet adherence and decreased meat and sweets consumption. The energy intake decreased by 605.3 kcal/day in T1, while T3 showed an increase of 209.5 kcal/day. Conclusions: Reducing UPF consumption leads to a decrease in IFC, associated with high Med-diet adherence and low calorie intake. Adopting these dietary patterns aligns with global sustainability goals and could further benefit MASLD patients by addressing environmental challenges alongside improving liver health.
Dietary Habits, Obesity, and Bariatric Surgery: A Review of Impact and Interventions
Authors: Maxim Mădălina , Soroceanu Radu Petru , Vlăsceanu Vlad Ionuț , Platon Răzvan Liviu , Toader Mihaela , Miler Ancuța Andreea , Onofriescu Alina , Abdulan Irina Mihaela , Ciuntu Bogdan-Mihnea , Balan Gheorghe , Trofin Felicia , Timofte Daniel Vasile
Published: January 2025

Eating behavior encompasses the psychological, physiological, and environmental factors influencing food intake. Dysregulation in eating behavior, such as emotional eating, binge eating, or loss of satiety signals, contributes to excessive caloric intake and weight gain. These behaviors are often linked to hormonal imbalances, stress, or genetic predisposition. Obesity is a chronic, multifactorial disease characterized by excessive body fat accumulation, with a body mass index (BMI) ≥ 30 kg/m2 often used for diagnosis. It is associated with significant morbidity, including type 2 diabetes, cardiovascular disease, and obstructive sleep apnea. Pathophysiological mechanisms underlying obesity include insulin resistance, leptin dysregulation, and altered gut microbiota, which perpetuate metabolic derangements. Lifestyle interventions remain first-line treatment, but sustained weight loss is challenging for many patients. Bariatric surgery is a therapeutic option for individuals with severe obesity (BMI ≥ 40 kg/m2 or ≥35 kg/m2 with comorbidities) who have failed conservative management. Procedures such as Roux-en-Y gastric bypass and sleeve gastrectomy alter gastrointestinal anatomy, promoting weight loss through restriction, malabsorption, and hormonal modulation (e.g., increased GLP-1 secretion). Bariatric surgery improves obesity-related comorbidities and enhances quality of life. However, it requires lifelong medical follow-up to address potential nutritional deficiencies and ensure sustainable outcomes.
HDAC/σ1R Dual-Ligand as a Targeted Melanoma Therapeutic
Authors: Leotta Claudia Giovanna , Barbaraci Carla , Fiorito Jole , Coco Alessandro , di Giacomo Viviana , Amata Emanuele , Marrazzo Agostino , Pitari Giovanni Mario
Published: January 2025

Background: In melanoma, multiligand drug strategies to disrupt cancer-associated epigenetic alterations and angiogenesis are particularly promising. Here, a novel dual-ligand with a single shared pharmacophore capable of simultaneously targeting histone deacetylases (HDACs) and sigma receptors (σRs) was synthesized and subjected to phenotypic in vitro screening. Methods: Tumor cell proliferation and spreading were investigated using immortalized human cancer and normal cell lines. Angiogenesis was also evaluated in mouse endothelial cells using a tube formation assay. Results: The dual-ligand compound exhibited superior potency in suppressing both uveal and cutaneous melanoma cell viability compared to other cancer cell types or normal cells. Melanoma selectivity reflected inhibition of the HDAC-dependent epigenetic regulation of tumor proliferative kinetics, without involvement of σR signaling. In contrast, the bifunctional compound inhibited the formation of capillary-like structures, formed by endothelial cells, and tumor cell spreading through the specific regulation of σ1R signaling, but not HDAC activity. Conclusions: Together, the present findings suggest that dual-targeted HDAC/σ1R ligands might efficiently and simultaneously disrupt tumor growth, dissemination and angiogenesis in melanoma, a strategy amenable to future clinical applications in precision cancer treatment.
Exploring the Genetic Potential for Multi-Resistance to Rust and Other Coffee Phytopathogens in Breeding Programs
Authors: Mariz Bruna Lopes , Caixeta Eveline Teixeira , Resende Marcos Deon Vilela de , Oliveira Antônio Carlos Baião de , Almeida Dênia Pires de , Alves Danúbia Rodrigues
Published: January 2025

The application of marker-assisted selection in coffee breeding programs accelerates the identification and concentration of target alleles, being essential for developing cultivars resistant to multiple diseases. In this study, a population was developed from artificial crossings between Timor Hybrid and Tupi Amarelo, with the aim of promoting the pyramiding of resistance genes to the main diseases and pests of Coffea arabica: coffee leaf rust (CLR), coffee berry disease (CBD), cercospora, and leaf miner. Resistance was confirmed by nine molecular markers at loci associated with CLR (genes SH3, CC-NBS-LRR, RLK, QTL-GL2, and GL5) and with CBD (gene Ck-1). The resistance to CLR, cercospora, and leaf miner was evaluated using phenotypic diagrammatic scales. Mixed models estimated population superiority in 16 morphoagronomic traits over four agricultural years. The introgression of resistance alleles to CLR and CBD was identified in 98.6% of the population, with 29% showing pyramiding of five resistance genes. These pyramiding genotypes showed 100% resistance to the leaf miner and 90% to cercospora. The traits were grouped into univariate, bivariate, and trivariate repeatability models, with 11 significant ones. These results are indicative of genetic variability to be explored in the development of cultivars with multiple resistances and high agronomic potential.