bluuebunny/crossref_metadata_2025 huggingface dataset:
Exploring the intersection of obesity and gender in COVID-19 outcomes in hospitalized Mexican patients: a comparative analysis of risk profiles using unsupervised machine learning
Authors: Nezhadmoghadam Fahimeh , Tamez-Peña José Gerardo , Martinez-Ledesma Emmanuel
Published: April 2024

Introduction

Obesity and gender play a critical role in shaping the outcomes of COVID-19 disease. These two factors have a dynamic relationship with each other, as well as other risk factors, which hinders interpretation of how they influence severity and disease progression. This work aimed to study differences in COVID-19 disease outcomes through analysis of risk profiles stratified by gender and obesity status.

Methods

This study employed an unsupervised clustering analysis, using Mexico’s national COVID-19 hospitalization dataset, which contains demographic information and health outcomes of patients hospitalized due to COVID-19. Patients were segmented into four groups by obesity and gender, with participants’ attributes and clinical outcome data described for each. Then, Consensus and PAM clustering methods were used to identify distinct risk profiles based on underlying patient characteristics. Risk profile discovery was completed on 70% of records, with the remaining 30% available for validation.

Results

Data from 88,536 hospitalized patients were analyzed. Obesity, regardless of gender, was linked with higher odds of hypertension, diabetes, cardiovascular diseases, pneumonia, and Intensive Care Unit (ICU) admissions. Men tended to have higher frequencies of ICU admissions and pneumonia and higher mortality rates than women. Within each of the four analysis groups (divided based on gender and obesity status), clustering analyses identified four to five distinct risk profiles. For example, among women with obesity, there were four profiles; those with a hypertensive profile were more likely to have pneumonia, and those with a diabetic profile were most likely to be admitted to the ICU.

Conclusion

Our analysis emphasizes the complex interplay between obesity, gender, and health outcomes in COVID-19 hospitalizations. The identified risk profiles highlight the need for personalized treatment strategies for COVID-19 patients and can assist in planning for patterns of deterioration in future waves of SARS-CoV-2 virus transmission. This research underscores the importance of tackling obesity as a major public health concern, given its interplay with many other health conditions, including infectious diseases such as COVID-19.
Association of socioeconomic position with sensory impairment among Chinese population: a nationally representative cohort and Mendelian randomization study
Authors: Wei Jin , Zhou Yifan , Abuduxukuer KaiweiSa , Dong Jialong , Wang Chuchu , Shi Wenming , Luo Jianfeng , Peng Qing , Song Yi
Published: April 2024

Aims

To investigate the association between socioeconomic position (SEP) and sensory impairments (SIs).

Methods

We used data from the China Health and Retirement Longitudinal Study (CHARLS) (2015). Logistic regressions estimated the odds ratio for associations of SEP with SIs. In addition, Mendelian randomization (MR) analysis was conducted to assess the causal relationship between them with the inverse variance weighting (IVW) estimator. MR-Egger, simple median, weighted median, maximum likelihood, and robust adjusted profile score were employed for sensitivity analyses.

Results

In the observational survey, we enrolled 19,690 individuals aged 45 and above. SEP was negatively associated with SIs. Adjusted odds of vision impairment were higher for illiterate (1.50; 95%CI: 1.19, 1.91), less than elementary school diploma (1.76; 95%CI: 1.39, 2.25), middle school diploma (1.53; 95%CI: 1.21, 1.93) and lower income (all p < 0.001). The odds of hearing impairment were significantly higher for people with less than a high school diploma than those with a college degree or higher diploma, for agricultural workers than non-agricultural workers, and for people in low-income families (p < 0.01). The MR analysis also showed that occupation was associated with HI (1.04, 95%CI: 1.01, 1.09, p < 0.05) using IVW.

Conclusion

We found that both observational and causal evidence supports the theory that SEP can result in SIs and that timely discovery, targeted management, and education can prevent SIs among middle-aged and older adults.
Effects of COVID-19-targeted non-pharmaceutical interventions on pediatric hospital admissions in North Italian hospitals, 2017 to 2022: a quasi-experimental study interrupted time-series analysis
Authors: Maglietta Giuseppe , Puntoni Matteo , Caminiti Caterina , Pession Andrea , Lanari Marcello , Caramelli Fabio , Marchetti Federico , De Fanti Alessandro , Iughetti Lorenzo , Biasucci Giacomo , Suppiej Agnese , Miceli Andrea , Ghizzi Chiara , Vergine Gianluca , Aricò Melodie , Stella Marcello , Esposito Susanna ,   Emilia-Romagna Paediatric COVID-19 network
Published: April 2024

Background

The use of Non-Pharmaceutical Interventions (NPIs), such as lockdowns, social distancing and school closures, against the COVID-19 epidemic is debated, particularly for the possible negative effects on vulnerable populations, including children and adolescents. This study therefore aimed to quantify the impact of NPIs on the trend of pediatric hospitalizations during 2 years of pandemic compared to the previous 3 years, also considering two pandemic phases according to the type of adopted NPIs.

Methods

This is a multicenter, quasi-experimental before-after study conducted in 12 hospitals of the Emilia-Romagna Region, Northern Italy, with NPI implementation as the intervention event. The 3 years preceding the beginning of NPI implementation (in March 2020) constituted the pre-pandemic phase. The subsequent 2 years were further subdivided into a school closure phase (up to September 2020) and a subsequent mitigation measures phase with less stringent restrictions. School closure was chosen as delimitation as it particularly concerns young people. Interrupted Time Series (ITS) regression analysis was applied to calculate Hospitalization Rate Ratios (HRR) on the diagnostic categories exhibiting the greatest variation. ITS allows the estimation of changes attributable to an intervention, both in terms of immediate (level change) and sustained (slope change) effects, while accounting for pre-intervention secular trends.

Results

Overall, in the 60 months of the study there were 84,368 cases. Compared to the pre-pandemic years, statistically significant 35 and 19% decreases in hospitalizations were observed during school closure and in the following mitigation measures phase, respectively. The greatest reduction was recorded for “Respiratory Diseases,” whereas the “Mental Disorders” category exhibited a significant increase during mitigation measures. ITS analysis confirms a high reduction of level change during school closure for Respiratory Diseases (HRR 0.19, 95%CI 0.08–0.47) and a similar but smaller significant reduction when mitigation measures were enacted. Level change for Mental Disorders significantly decreased during school closure (HRR 0.50, 95%CI 0.30–0.82) but increased during mitigation measures by 28% (HRR 1.28, 95%CI 0.98–1.69).

Conclusion

Our findings provide information on the impact of COVID-19 NPIs which may inform public health policies in future health crises, plan effective control and preventative interventions and target resources where needed.
On composite sampling for monitoring generic and antibiotic-resistant coliforms in irrigation ponds
Authors: Stocker Matthew Daniel , Smith Jaclyn Elizabeth , Pachepsky Yakov
Published: April 2024

The presence of fecal bacteria in irrigation waters is well documented in causing human and animal illnesses, with the potential for antibiotic-resistant pathogens to increase the seriousness of these infections. Approaches to sampling fecal and antibiotic-resistant bacteria (ARB) in irrigation waters used in raw food production require standardization to quantify and discern potential spatiotemporal trends in antibiotic-resistant bacteria. Composite sampling is widely used to reduce the cost and time of processing samples while estimating spatial or temporal variation in contaminant concentrations. The objectives of this work were to evaluate the spatial variation in generic and ARB in several irrigation ponds and assess the effectiveness of composite sampling in estimating the average of individual samples. In a grid-like fashion, five irrigation ponds were sampled for generic and antibiotic-resistant E. coli and total coliforms using the Colilert Quanti-Tray/2000 system with and without tetracycline and cefotaxime added. Individual samples were composited in sample sets including all samples, only bank samples, and only interior samples. Coefficients of variations in general were high (> 100%) for generic bacteria and higher for ARB (140%−290%). Concentrations of all measured bacteria were lower in the pond interior locations than the banks. The percentage of tetracycline-resistant E. coli varied among ponds from averages of 0% to 23%. No cefotaxime-resistant E. coli were detected in any of the ponds whereas cefotaxime-resistant total coliforms were detected at each site. The average percentage of cefotaxime-resistant total coliforms varied from 1.1 to 13.8% among ponds. E. coli concentrations in composite samples did not significantly differ from either the mean or median of the individual sample sets in 89% and 83% of cases, respectively, indicating composite sampling to be effective in capturing spatial variation of both generic and ARB. Results of this work can be used to aid in the development of better strategies for surveilling antibiotic resistance in aquatic environments.
Performance and healthcare analysis in elite sports teams using artificial intelligence: a scoping review
Authors: Munoz-Macho A. A. , Domínguez-Morales M. J. , Sevillano-Ramos J. L.
Published: April 2024

Introduction

In competitive sports, teams are increasingly relying on advanced systems for improved performance and results. This study reviews the literature on the role of artificial intelligence (AI) in managing these complexities and encouraging a system thinking shift. It found various AI applications, including performance enhancement, healthcare, technical and tactical support, talent identification, game prediction, business growth, and AI testing innovations. The main goal of the study was to assess research supporting performance and healthcare.

Methods

Systematic searches were conducted on databases such as Pubmed, Web of Sciences, and Scopus to find articles using AI to understand or improve sports team performance. Thirty-two studies were selected for review.

Results

The analysis shows that, of the thirty-two articles reviewed, fifteen focused on performance and seventeen on healthcare. Football (Soccer) was the most researched sport, making up 67% of studies. The revised studies comprised 2,823 professional athletes, with a gender split of 65.36% male and 34.64% female. Identified AI and non-AI methods mainly included Tree-based techniques (36%), Ada/XGBoost (19%), Neural Networks (9%), K-Nearest Neighbours (9%), Classical Regression Techniques (9%), and Support Vector Machines (6%).

Conclusions

This study highlights the increasing use of AI in managing sports-related healthcare and performance complexities. These findings aim to assist researchers, practitioners, and policymakers in developing practical applications and exploring future complex systems dynamics.
Euthanasia and Physician-Assisted Suicide in People With an Accumulation of Health Problems Related to Old Age: A Cross-Sectional Questionnaire Study Among Physicians in the Netherlands
Authors: Kraak-Steenken Frédérique W. M. , Renckens Sophie C. , Pasman H. Roeline W. , Bosma Fenne , van der Heide Agnes , Onwuteaka-Philipsen Bregje D.
Published: April 2024

Objectives: We explored characteristics of people with an accumulation of health problems related to old age requesting euthanasia or physician-assisted suicide (EAS) and identified characteristics associated with granting EAS requests.

Methods: We conducted a cross-sectional questionnaire study among Dutch physicians on characteristics of these people requesting EAS (n = 123). Associations between characteristics and granting a request were assessed using logistic regression analyses.

Results: People requesting EAS were predominantly >80 years old (82.4%), female (70.0%), widow/widower (71.7%), (partially) care-dependent (76.7%), and had a life expectancy >12 months (68.6%). The most prevalent health problems were osteoarthritis (70.4%) and impaired vision and hearing (53.0% and 40.9%). The most cited reasons to request EAS were physical deterioration (68.6%) and dependence (61.2%). 44.7% of requests were granted. Granting a request was positively associated with care dependence, disability/immobility, impaired vision, osteoporosis, loss of control, suffering without prospect of improvement and a treatment relationship with the physician >12 months.

Conclusion: Enhanced understanding of people with an accumulation of health problems related to old age requesting EAS can contribute to the ongoing debate on the permissibility of EAS in people without life-threatening conditions.
Effective and safe provocation test for wheat-dependent exercise-induced anaphylaxis (WDEIA) in adults results of testing on 33 cases
Authors: Sugiyama Akiko , Fukushima Takehito , Okabe Koki , Shimada Kiyotaka , Kojima Kaoru , Shigeoka Yuko , Honjo Satoshi , Kishikawa Reiko
Published: April 2024

Background: Wheat-dependent exercise-induced anaphylaxis (WDEIA) is induced not by the intake of wheat-based food alone, but by the combination of exercise stress and such intake. Provocation tests have been reported to be useful for the diagnosis of this condition, but they are not always accurate. Furthermore, provocation tests are associated with the risk of anaphylactic shock, so safer testing is required.

Subjects and methods: Thirty-three patients (mean age 35.5 ± 16.0 years) who underwent provocation tests from April 2019 to July 2023 were included in this study. We investigated associations of their provocation test results with their medical history, blood test results before the provocation tests, exercise load at the time of the test, and severity of the induced symptoms.

Results: Symptoms were induced and the diagnosis of WDEIA was made in 28 cases, while 2 cases were confirmed not to have WDEIA. Overall, 25 of the 28 positive cases had symptoms induced by an exercise load greater than 70% of the heart rate calculated by the Karvonen formula, 7 of which required Non-Steroidal Anti-Inflammatory Drugs (NSAIDs) loading to induce symptoms. None of the patients with negative wheat-specific IgE titers and positive gluten and/or ω-5 gliadin ones required NSAIDs loading. No patients required the administration of adrenaline.

Conclusion: Wheat-specific IgE as well as gluten and ω-5 gliadin antibody titers are associated with WDEIA symptom severity. Exercise loading with a target heart rate of 70%–90% of that calculated by the Karvonen formula is safe and useful for diagnosis this condition.
Integrated Spatial Kinematics–Dynamics Model Predictive Control for Collision-Free Autonomous Vehicle Tracking
Authors: Yang Weishan , Su Yixin , Chen Yuepeng , Lian Cheng
Published: April 2024

The development of intelligent transportation technology has provided a significant impetus for autonomous driving technology. Currently, autonomous vehicles based on Model Predictive Control (MPC) employ motion control strategies based on sampling time, which fail to fully utilize the spatial information of obstacles. To address this issue, this paper proposes a dual-layer MPC vehicle collision-free trajectory tracking control strategy that integrates spatial kinematics and vehicle dynamics. To fully utilize the spatial information of obstacles, we designed a vehicle model based on spatial kinematics, enabling the upper-layer MPC to plan collision avoidance trajectories based on distance sampling. To improve the accuracy and safety of trajectory tracking, we designed an 8-degree-of-freedom vehicle dynamic model. This allows the lower-layer MPC to consider lateral stability and roll stability during trajectory tracking. In collision avoidance trajectory tracking experiments using three scenarios, compared to two advanced time-based algorithms, the trajectories planned by the proposed algorithm in this paper exhibited predictability. The proposed algorithm can initiate collision avoidance at predetermined positions and can avoid collisions in predetermined directions, with all state variables within safe ranges. In terms of time efficiency, it also outperformed the comparative algorithms.
Antibacterial Activity of Oregano (Origanum vulgare L.) Essential Oil Vapors against Microbial Contaminants of Food-Contact Surfaces
Authors: Pinto Loris , Cervellieri Salvatore , Netti Thomas , Lippolis Vincenzo , Baruzzi Federico
Published: April 2024

The antimicrobial effect of eight essential oils’ vapors against pathogens and spoilage bacteria was assayed. Oreganum vulgare L. essential oil (OVO) showed a broad antibacterial effect, with Minimum Inhibitory Concentration (MIC) values ranging from 94 to 754 µg cm−3 air, depending on the bacterial species. Then, gaseous OVO was used for the treatment of stainless steel, polypropylene, and glass surfaces contaminated with four bacterial pathogens at 6–7 log cfu coupon−1. No viable cells were found after OVO treatment on all food-contact surfaces contaminated with all pathogens, with the exception of Sta. aureus DSM 799 on the glass surface. The antimicrobial activity of OVO after the addition of beef extract as a soiling agent reduced the Sta. aureus DSM 799 viable cell count by more than 5 log cfu coupon−1 on polypropylene and glass, while no viable cells were found in the case of stainless steel. HS-GC-MS analysis of the headspace of the boxes used for the antibacterial assay revealed 14 different volatile compounds with α-Pinene (62–63%), and p-Cymene (21%) as the main terpenes. In conclusion, gaseous OVO could be used for the microbial decontamination of food-contact surfaces, although its efficacy needs to be evaluated since it depends on several parameters such as target microorganisms, food-contact material, temperature, time of contact, and relative humidity.
Leveraging IoT Harmonization: An Efficacious NB-IoT Relay for Integrating 6LoWPAN Devices into Legacy IPv4 Networks
Authors: Saavedra Edgar , Santamaria Asuncion , del Campo Guillermo , Gomez Igor
Published: April 2024

The burgeoning complexity and heterogeneity of IoT networks, coupled with their rapid growth, constant evolution, and new players, present significant challenges in terms of connectivity, interoperability, management, and usability. These networks, composed of a diverse array of devices, technologies and the like, demand innovative solutions to bridge the gaps between different IoT technologies and communication protocols. This article presents a simple, yet efficacious communication Relay to address one of these critical gaps. This Relay uses NB-IoT to ease the integration of 6LoWPAN-based IoT devices (IPv6) into the public legacy Internet (IPv4). This device translates 6LoWPAN, IPv6 CoAP messages into Internet-standard REST requests, so that appropriate handling of devices’ data be achieved in several stages. Thus, the Relay establishes two branches of communications: (i) the local network where the 6LoWPAN gateway is placed, and (ii) the public NB-IoT network. User interaction and data analysis are achieved by virtue of Home Assistant, where former 6LoWPAN devices are now discovered and shown as proper Home Assistant entities thanks to the Relay’s ease of integration into the open-source platform. This novel approach not only ensures efficient data and network management, but it also meets the urgent necessity for advanced solutions in enhancing actual IoT interconnectivity and monitoring. The unprecedented pace at which IoT devices, players and different networks have been proliferating in recent times is not compatible with countless manufacturer-dependent platforms, applications, and proprietary protocols that the IoT field has been leading with so far, almost from its beginnings.
Protocol for the Development of Automatic Multisensory Systems to Analyze Human Activity for Functional Evaluation: Application to the EYEFUL System
Authors: Obeso-Benítez Paula , Pérez-de-Heredia-Torres Marta , Huertas-Hoyas Elisabet , Sánchez-Herrera-Baeza Patricia , Máximo-Bocanegra Nuria , Serrada-Tejeda Sergio , Marron-Romera Marta , Macias-Guarasa Javier , Losada-Gutierrez Cristina , Palazuelos-Cagigas Sira E. , Martin-Sanchez Jose L. , Martínez-Piédrola Rosa M.
Published: April 2024

The EYEFUL system represents a pioneering initiative designed to leverage multisensory systems for the automatic evaluation of functional ability and determination of dependency status in people performing activities of daily living. This interdisciplinary effort, bridging the gap between engineering and health sciences, aims to overcome the limitations of current evaluation tools, which often lack objectivity and fail to capture the full range of functional capacity. Until now, it has been derived from subjective reports and observational methods. By integrating wearable sensors and environmental technologies, EYEFUL offers an innovative approach to quantitatively assess an individual’s ability to perform activities of daily living, providing a more accurate and unbiased evaluation of functionality and personal independence. This paper describes the protocol planned for the development of the EYEFUL system, from the initial design of the methodology to the deployment of multisensory systems and the subsequent clinical validation process. The implications of this research are far-reaching, offering the potential to improve clinical evaluations of functional ability and ultimately improve the quality of life of people with varying levels of dependency. With its emphasis on technological innovation and interdisciplinary collaboration, the EYEFUL system sets a new standard for objective evaluation, highlighting the critical role of advanced screening technologies in addressing the challenges of modern healthcare. We expect that the publication of the protocol will help similar initiatives by providing a structured approach and rigorous validation process.
Phytochemical Profiles and Anti-Glioma Activity of Bearberry Arctostaphylos uva-ursi (L.) Spreng. Leaf Extracts
Authors: Sugier Piotr , Jakubowicz-Gil Joanna , Zając Adrian , Sugier Danuta , Wójcik Małgorzata , Czarnecka Joanna , Krawczyk Rafał , Urban Danuta , Sęczyk Łukasz
Published: April 2024

The use of diversified raw materials and various extractant types is justified because the varied chemical composition of extracts obtained via extraction determines their biological activity. Therefore, the objective of this study was (i) to characterize the chemical profile of two types of bearberry extracts (70% ethanolic and water) and (ii) to investigate the biological activity of the analyzed extracts through an assessment of their possible proapoptotic effects on glioma cell lines. The HPLC-UV analysis of individual compounds was performed for the determination of the phytochemical profile of the bearberry extracts, and their total phenolic content (TPC) and total flavonoid content (TFC) were determined spectrophotometrically. The induction of apoptosis, autophagy, and necrosis in anaplastic astrocytoma MOGGCCM and human glioblastoma LN229 cell lines were investigated. The results indicated that the ethanolic (Et) and aqueous (Aq) extracts had different chemical profiles. The TPC in the Et was ca. 60% higher than in the Aq. Similarly, the TFC and methylarbutin (mARB) concentrations were significantly higher in the Et. On the other hand, the concentration of hydroquinone (HQ) was ca. 70% and that of corilagin (COR) was ca. 100% higher in the Aq. In turn, the presence of ursolic acid (UA) and oleanolic acid (OA) was confirmed solely in the Et. In contrast to Aq, Et demonstrated high proapoptotic activity. At the concentration of 2 µL/mL, the level of apoptosis varied between 14.7% and 26% in the case of the MOGGCCM cells and between 12.3% and 33.3% in the case of the LN229 cell line. The knowledge and information obtained in this study indicate a need for further research on the anticancer effect of the studied bearberry phytochemicals on the MOGGCCM and LN229 cell lines and for the elucidation of their molecular anticancer mechanisms.
Enhancing Food Integrity through Artificial Intelligence and Machine Learning: A Comprehensive Review
Authors: Gbashi Sefater , Njobeh Patrick Berka
Published: April 2024

Herein, we examined the transformative potential of artificial intelligence (AI) and machine learning (ML) as new fronts in addressing some of the pertinent challenges posed by food integrity to human and animal health. In recent times, AI and ML, along with other Industry 4.0 technologies such as big data, blockchain, virtual reality, and the internet of things (IoT), have found profound applications within nearly all dimensions of the food industry with a key focus on enhancing food safety and quality and improving the resilience of the food supply chain. This paper provides an accessible scrutiny of these technologies (in particular, AI and ML) in relation to food integrity and gives a summary of their current advancements and applications within the field. Key areas of emphasis include the application of AI and ML in quality control and inspection, food fraud detection, process control, risk assessments, prediction, and management, and supply chain traceability, amongst other critical issues addressed. Based on the literature reviewed herein, the utilization of AI and ML in the food industry has unequivocally led to improved standards of food integrity and consequently enhanced public health and consumer trust, as well as boosting the resilience of the food supply chain. While these applications demonstrate significant promise, the paper also acknowledges some of the challenges associated with the domain-specific implementation of AI in the field of food integrity. The paper further examines the prospects and orientations, underscoring the significance of overcoming the obstacles in order to fully harness the capabilities of AI and ML in safeguarding the integrity of the food system.
Ensemble Empirical Mode Decomposition Granger Causality Test Dynamic Graph Attention Transformer Network: Integrating Transformer and Graph Neural Network Models for Multi-Sensor Cross-Temporal Granularity Water Demand Forecasting
Authors: Wu Wenhong , Kang Yunkai
Published: April 2024

Accurate water demand forecasting is crucial for optimizing the strategies across multiple water sources. This paper proposes the Ensemble Empirical Mode Decomposition Granger causality test Dynamic Graph Attention Transformer Network (EG-DGATN) for multi-sensor cross-temporal granularity water demand forecasting, which combines the Transformer and Graph Neural Networks. It employs the EEMD–Granger test to delineate the interconnections among sensors and extracts the spatiotemporal features within the causal domain by stacking dynamical graph spatiotemporal attention layers. The experimental results demonstrate that compared to baseline models, the EG-DGATN improves the MAPE metrics by 2.12%, 4.33%, and 6.32% in forecasting intervals of 15 min, 45 min, and 90 min, respectively. The model achieves an R2 score of 0.97, indicating outstanding predictive accuracy and exceptional explanatory power for the target variable. This research highlights significant potential applications in predictive tasks within smart water management systems.
Investigation of Steep Waste Dump Slope Stability of Iron Ore Mine—A Case Study
Authors: Yang Zhongao , Liu Xin , Qian Weimin , Ding Xiaohua , Ao Zhongchen , Zhang Zhiyuan , Jiskani Izhar Mithal , Tian Ya , Xing Bokang , Wahab Abdoul
Published: April 2024

Using a combination of experimental and numerical methods, this study examines the stability of the slope of Waste Dump#1 in Ziluoyi Iron Mine. We conducted direct shear tests on soil samples taken from the waste dump, which provided important insights into slope stability. The tests identified key mechanical parameters, including an average cohesion of 4.80 kPa and an internal friction angle of 25.63°. By implementing GEO-SLOPE software, we could determine that the slope stability factor is 1.047, which is far from the required safety standards. To address this issue, we proposed an appropriate rectification strategy including the construction of safety platforms and reconfiguration of the slope structure. This approach effectively improved the slope stability factor to 1.219 and met the safety criteria. In addition, particle flow code (PFC) simulations were methodically performed to model the slope morphology and particle displacement before and after rectification. The obtained results revealed a remarkable reduction in sliding areas and particle displacement post-rectification, enhancing mine safety and efficiency. Our findings provide valuable insights into the application of combined experimental and numerical methods to assess and improve slope stability in open-pit mines, which will substantially contribute to the field of geotechnical engineering and mining safety.
Bergman Space Properties of Fractional Derivatives of the Cauchy Transform of a Certain Self-Similar Measure
Authors: Wang Songran , Wang Zhimin
Published: April 2024

Let μ be a self-similar measure with compact support K. The Hausdorff dimension of K is α. The Cauchy transform of μ is denoted by F(z). For 0<β<1, we define the function F[β], which compares with the fractional derivative of F of order β. Let Φ(z)=F(1/z),|z|<1. In this paper, we prove that Φ[β] belongs to Ap for 0<p<1/(β+1), and (Φ′)[β] belongs to Ap for 1≤p<1/β≤1/(2−α), where Ap is the Bergman space. At the same time, we give a value distribution property of F, which is similar to the big Picard theorem.
Postnatal Growth and Development of the Rumen: Integrating Physiological and Molecular Insights
Authors: Pokhrel Binod , Jiang Honglin
Published: April 2024

The rumen plays an essential role in the physiology and production of agriculturally important ruminants such as cattle. Functions of the rumen include fermentation, absorption, metabolism, and protection. Cattle are, however, not born with a functional rumen, and the rumen undergoes considerable changes in size, histology, physiology, and transcriptome from birth to adulthood. In this review, we discuss these changes in detail, the factors that affect these changes, and the potential molecular and cellular mechanisms that mediate these changes. The introduction of solid feed to the rumen is essential for rumen growth and functional development in post-weaning calves. Increasing evidence suggests that solid feed stimulates rumen growth and functional development through butyric acid and other volatile fatty acids (VFAs) produced by microbial fermentation of feed in the rumen and that VFAs stimulate rumen growth and functional development through hormones such as insulin and insulin-like growth factor I (IGF-I) or through direct actions on energy production, chromatin modification, and gene expression. Given the role of the rumen in ruminant physiology and performance, it is important to further study the cellular, molecular, genomic, and epigenomic mechanisms that control rumen growth and development in postnatal ruminants. A better understanding of these mechanisms could lead to the development of novel strategies to enhance the growth and development of the rumen and thereby the productivity and health of cattle and other agriculturally important ruminants.
Multiomics Picture of Obesity in Young Adults
Authors: Kiseleva Olga I. , Pyatnitskiy Mikhail A. , Arzumanian Viktoriia A. , Kurbatov Ilya Y. , Ilinsky Valery V. , Ilgisonis Ekaterina V. , Plotnikova Oksana A. , Sharafetdinov Khaider K. , Tutelyan Victor A. , Nikityuk Dmitry B. , Ponomarenko Elena A. , Poverennaya Ekaterina V.
Published: April 2024

Obesity is a socially significant disease that is characterized by a disproportionate accumulation of fat. It is also associated with chronic inflammation, cancer, diabetes, and other comorbidities. Investigating biomarkers and pathological processes linked to obesity is especially vital for young individuals, given their increased potential for lifestyle modifications. By comparing the genetic, proteomic, and metabolomic profiles of individuals categorized as underweight, normal, overweight, and obese, we aimed to determine which omics layer most accurately reflects the phenotypic changes in an organism that result from obesity. We profiled blood plasma samples by employing three omics methodologies. The untargeted GC×GC–MS metabolomics approach identified 313 metabolites. To augment the metabolomic dataset, we integrated a label-free HPLC–MS/MS proteomics method, leading to the identification of 708 proteins. The genomic layer encompassed the genotyping of 647,250 SNPs. Utilizing omics data, we trained sparse Partial Least Squares models to predict body mass index. Molecular features exhibiting frequently non-zero coefficients were selected as potential biomarkers, and we further explored enriched biological pathways. Proteomics was the most effective in single-omics analyses, with a median absolute error (MAE) of 5.44 ± 0.31 kg/m2, incorporating an average of 24 proteins per model. Metabolomics showed slightly lower performance (MAE = 6.06 ± 0.33 kg/m2), followed by genomics (MAE = 6.20 ± 0.34 kg/m2). As expected, multiomic models demonstrated better accuracy, particularly the combination of proteomics and metabolomics (MAE = 4.77 ± 0.33 kg/m2), while including genomics data did not enhance the results. This manuscript is the first multiomics study of obesity in a gender-balanced cohort of young adults profiled by genomic, proteomic, and metabolomic methods. The comprehensive approach provides novel insights into the molecular mechanisms of obesity, opening avenues for more targeted interventions.
Radiolabelled FGF-2 for Imaging Activated Fibroblasts in the Tumor Micro-Environment
Authors: Bentivoglio Valeria , Galli Filippo , Varani Michela , Ranieri Danilo , Nayak Pallavi , D’Elia Annunziata , Soluri Andrea , Massari Roberto , Lauri Chiara , Signore Alberto
Published: April 2024

Tumor associated fibroblasts (TAFs) play a key role in tumor growth and metastatization. TAFs overexpress different biomarkers that are usually expressed at low levels in physiological conditions. Among them are the fibroblast growth factor receptors (FGFRs) that bind the fibroblast growth factors (FGFs). In particular, the overexpression of FGFR-2c in tumors has been associated with advanced clinical stages and increased metastatization. Here, we developed a non-invasive tool to evaluate, in vivo, the expression of FGFR-2c in metastatic cancer. This is based on 99mTc-labelled FGF-2. Methods: 99mTc-FGF-2 was tested in vitro and in vivo in mice bearing allografts of sarcoma cells. Images of 99mTc-FGF-2 were acquired using a new portable high-resolution ultra-sensitive gamma camera for small animal imaging. Results: FGF-2 was labeled with high specific activity but low labelling efficiency, thus requiring post-labeling purification by gel-filtration chromatography. In vitro binding to 2C human keratinocytes showed a Kd of 3.36 × 10−9 M. In mice bearing J774A.1 cell allografts, we observed high and rapid tumor uptake of 99mTc-FGF-2 with a high Tumor/Blood ratio at 24 h post-injection (26.1 %ID/g and 12.9 %ID) with low kidney activity and moderate liver activity. Conclusions: we labeled FGF-2 with 99mTc and showed nanomolar Kd in vitro with human keratinocytes expressing FGF-2 receptors. In mice, 99mTc-FGF-2 rapidly and efficiently accumulated in tumors expressing FGF-2 receptors. This new radiopharmaceutical could be used in humans to image TAFs.
Antiproliferative Activity of N-Acylhydrazone Derivative on Hepatocellular Carcinoma Cells Involves Transcriptional Regulation of Genes Required for G2/M Transition
Authors: Andrade Amanda Aparecida Ribeiro , Pauli Fernanda , Pressete Carolina Girotto , Zavan Bruno , Hanemann João Adolfo Costa , Miyazawa Marta , Fonseca Rafael , Caixeta Ester Siqueira , Nacif Julia Louise Moreira , Aissa Alexandre Ferro , Barreiro Eliezer J. , Ionta Marisa
Published: April 2024

Liver cancer is the second leading cause of cancer-related death in males. It is estimated that approximately one million deaths will occur by 2030 due to hepatic cancer. Hepatocellular carcinoma (HCC) is the most prevalent primary liver cancer subtype and is commonly diagnosed at an advanced stage. The drug arsenal used in systemic therapy for HCC is very limited. Multikinase inhibitors sorafenib (Nexavar®) and lenvatinib (Lenvima®) have been used as first-line drugs with modest therapeutic effects. In this scenario, it is imperative to search for new therapeutic strategies for HCC. Herein, the antiproliferative activity of N-acylhydrazone derivatives was evaluated on HCC cells (HepG2 and Hep3B), which were chemically planned on the ALL-993 scaffold, a potent inhibitor of vascular endothelial growth factor 2 (VEGFR2). The substances efficiently reduced the viability of HCC cells, and the LASSBio-2052 derivative was the most effective. Further, we demonstrated that LASSBio-2052 treatment induced FOXM1 downregulation, which compromises the transcriptional activation of genes required for G2/M transition, such as AURKA and AURKB, PLK1, and CDK1. In addition, LASSBio-2052 significantly reduced CCNB1 and CCND1 expression in HCC cells. Our findings indicate that LASSBio-2052 is a promising prototype for further in vivo studies.
Improved Evidence Fusion Theory for the Safety Assessment of Prestressed Concrete Bridges
Authors: Shu Jiangpeng , Ma Haibo , Ding Wei , Jin Zhenfen
Published: April 2024

The safety condition assessment of prestressed concrete bridges is currently subject to great uncertainty due to the subjectivity of data collection and data types. This study proposes an improved evidence fusion method, improving the conventional Dempster–Shafer fusion method to reduce assessment inaccuracies caused by data uncertainty. Firstly, the uncertain analytic hierarchy process was applied to construct a three-level safety assessment model for 15 different indicators with their initial weights. Secondly, the fuzzy matter element theory was proposed to obtain basic probability assignments required for the evidence fusion. Finally, an improved evidence fusion method was proposed based on the evidence credibility and preprocessing corrections for highly conflicting evidence. In this study, a prestressed concrete bridge in eastern China was used as a case study to perform a comprehensive safety assessment and verify the effectiveness and practicality of the proposed method. The assessment results demonstrate that the improved fusion method in this study can deal with conflicting evidence better than existing fusion methods. Compared with conventional fuzzy AHP method, it has greater sensitivity to certain indicators with severe damages, which prevents those indicators from being overshadowed by other well-performing ones in the overall assessment.
Recent Advances in Pathology of Intrahepatic Cholangiocarcinoma
Authors: Choi Joon Hyuk , Thung Swan N.
Published: April 2024

Intrahepatic cholangiocarcinoma (ICCA) is a malignant epithelial neoplasm characterized by biliary differentiation within the liver. ICCA is molecularly heterogeneous and exhibits a broad spectrum of histopathological features. It is a highly aggressive carcinoma with high mortality and poor survival rates. ICCAs are classified into two main subtypes: the small-duct type and large-duct types. These two tumor types have different cell origins and clinicopathological features. ICCAs are characterized by numerous molecular alterations, including mutations in KRAS, TP53, IDH1/2, ARID1A, BAP1, BRAF, SAMD4, and EGFR, and FGFR2 fusion. Two main molecular subtypes—inflammation and proliferation—have been proposed. Recent advances in high-throughput assays using next-generation sequencing have improved our understanding of ICCA pathogenesis and molecular genetics. The diagnosis of ICCA poses a significant challenge for pathologists because of its varied morphologies and phenotypes. Accurate diagnosis of ICCA is essential for effective patient management and prognostic determination. This article provides an updated overview of ICCA pathology, focusing particularly on molecular features, histological subtypes, and diagnostic approaches.
The Prevalence of Orthostatic Hypotension in Cancer Patients
Authors: Iwański Mateusz A. , Sokołowska Aldona , Sokołowski Andrzej , Wojdyła Roman , Styczkiewicz Katarzyna
Published: April 2024

Background: Orthostatic hypotension (OH) is associated with a higher risk of mortality in the general population; however, it has not been studied in the cancer population. This study aimed to assess the prevalence of OH in cancer patients compared to that in the noncancer population. Methods: A total of 411 patients (mean age 63.5 ± 10.6 years) were recruited: patients with active cancer (n = 223) and patients hospitalised for other reasons, but without a cancer diagnosis (n = 188). Medical histories were collected and an orthostatic challenge test was performed. OH was defined as a blood pressure (BP) decrease upon standing of ≥20 mmHg for the systolic or ≥10 mmHg for the diastolic BP after 1 or 3 min; or a systolic BP decrease <90 mmHg. Results: The prevalence of OH in the subjects with cancer was significantly higher than in the subjects without cancer (28.7% vs. 16.5%, respectively, p = 0.003). OH was the most common in the lung cancer patients (57.5%). In a single-variable analysis, the predictors of OH were cancer presence, age ≥ 65 years, and body mass index (BMI) ≥ 30 kg/m2. In the multivariable model, the strongest independent predictor of OH was cancer status, which doubled the risk of OH, and BMI ≥ 30 kg/m2 and diabetes. Conclusions: Cancer patients are characterised by a high prevalence of OH. In this population, the recommendation of routine orthostatic challenge tests should be considered.
Kahweol Inhibits Pro-Inflammatory Cytokines and Chemokines in Tumor Necrosis Factor-α/Interferon-γ-Stimulated Human Keratinocyte HaCaT Cells
Authors: Kwon Ye Jin , Kwon Hyun Hee , Leem Jaechan , Jang Yoon Young
Published: April 2024

Atopic dermatitis (AD), marked by intense itching and eczema-like lesions, is a globally increasing chronic skin inflammation. Kahweol, a diterpene that naturally occurs in coffee beans, boasts anti-inflammatory, antioxidative, and anti-cancer properties. This research explores the anti-inflammatory action of kahweol on HaCaT human keratinocytes stimulated by tumor necrosis factor-α (TNF-α) and interferon-γ (IFN-γ), focusing on key signal transduction pathways. Our results demonstrate that kahweol markedly reduces the production of IL-1β, IL-6, C-X-C motif chemokine ligand 8, and macrophage-derived chemokine in TNF-α/IFN-γ-activated HaCaT cells. Furthermore, it curtails the phosphorylation of key proteins in the mitogen-activated protein kinase (MAPK) pathways, including c-Jun N-terminal kinase, extracellular signal-regulated kinase, and p38. Additionally, kahweol impedes the phosphorylation and nuclear translocation of the NF-κB p65 subunit and constrains its DNA-binding capability. It also hampers the phosphorylation, nuclear translocation, and DNA-binding activities of signal transducer and activator of transcription 1 (STAT1) and STAT3. Collectively, these findings suggest that kahweol hinders the generation of cytokines and chemokines in inflamed keratinocytes by inhibiting the MAPK, NF-κB, and STAT cascades. These insights position kahweol as a promising agent for dermatological interventions, especially in managing inflammatory skin conditions such as AD.
Visualising the Complexity of Drought: A Network Analysis Based on the Water Resilience Assessment Framework and the Actor-Relational Approach
Authors: Vercruysse Joachim , Deruyter Greet , De Sutter Renaat , Boelens Luuk
Published: April 2024

This paper discusses the increasing severity of droughts due to climate change. It emphasises the complexity of defining drought and the diverse perspectives among stakeholders. Lots of stakeholders with unclear responsibilities are involved, which can lead to uncertainty and indecisiveness in addressing the issue. To tackle this, the present paper proposes a methodology to dissect drought systems and reveal the intricate relationships between their components. This approach combines a comprehensive definition of drought with the “Water Resilience Assessment Framework” and an “Actor-Relational Approach”, visualised through network analysis. The methodology was applied to a case study situated in the Leie Basin of Flanders, Belgium. By employing this strategy, policymakers and mediators can gain a deeper understanding of drought, identify its root causes, and prioritise necessary changes for more effective drought and water management.
Deep Learning Prediction of Axillary Lymph Node Metastasis in Breast Cancer Patients Using Clinical Implication-Applied Preprocessed CT Images
Authors: Park Tae Yong , Kwon Lyo Min , Hyeon Jini , Cho Bum-Joo , Kim Bum Jun
Published: April 2024

Background: Accurate detection of axillary lymph node (ALN) metastases in breast cancer is crucial for clinical staging and treatment planning. This study aims to develop a deep learning model using clinical implication-applied preprocessed computed tomography (CT) images to enhance the prediction of ALN metastasis in breast cancer patients. Methods: A total of 1128 axial CT images of ALN (538 malignant and 590 benign lymph nodes) were collected from 523 breast cancer patients who underwent preoperative CT scans between January 2012 and July 2022 at Hallym University Medical Center. To develop an optimal deep learning model for distinguishing metastatic ALN from benign ALN, a CT image preprocessing protocol with clinical implications and two different cropping methods (fixed size crop [FSC] method and adjustable square crop [ASC] method) were employed. The images were analyzed using three different convolutional neural network (CNN) architectures (ResNet, DenseNet, and EfficientNet). Ensemble methods involving and combining the selection of the two best-performing CNN architectures from each cropping method were applied to generate the final result. Results: For the two different cropping methods, DenseNet consistently outperformed ResNet and EfficientNet. The area under the receiver operating characteristic curve (AUROC) for DenseNet, using the FSC and ASC methods, was 0.934 and 0.939, respectively. The ensemble model, which combines the performance of the DenseNet121 architecture for both cropping methods, delivered outstanding results with an AUROC of 0.968, an accuracy of 0.938, a sensitivity of 0.980, and a specificity of 0.903. Furthermore, distinct trends observed in gradient-weighted class activation mapping images with the two cropping methods suggest that our deep learning model not only evaluates the lymph node itself, but also distinguishes subtler changes in lymph node margin and adjacent soft tissue, which often elude human interpretation. Conclusions: This research demonstrates the promising performance of a deep learning model in accurately detecting malignant ALNs in breast cancer patients using CT images. The integration of clinical considerations into image processing and the utilization of ensemble methods further improved diagnostic precision.