bluuebunny/crossref_metadata_2025 huggingface dataset:
EEG analysis of speaking and quiet states during different emotional music stimuli
Authors: Lin Xianwei , Wu Xinyue , Wang Zefeng , Cai Zhengting , Zhang Zihan , Xie Guangdong , Hu Lianxin , Peyrodie Laurent
Published: February 2025

Introduction

Music has a profound impact on human emotions, capable of eliciting a wide range of emotional responses, a phenomenon that has been effectively harnessed in the field of music therapy. Given the close relationship between music and language, researchers have begun to explore how music influences brain activity and cognitive processes by integrating artificial intelligence with advancements in neuroscience.

Methods

In this study, a total of 120 subjects were recruited, all of whom were students aged between 19 and 26 years. Each subject is required to listen to six 1-minute music segments expressing different emotions and speak at the 40-second mark. In terms of constructing the classification model, this study compares the classification performance of deep neural networks with other machine learning algorithms.

Results

The differences in EEG signals between different emotions during speech are more pronounced compared to those in a quiet state. In the classification of EEG signals for speaking and quiet states, using deep neural network algorithms can achieve accuracies of 95.84% and 96.55%, respectively.

Discussion

Under the stimulation of music with different emotions, there are certain differences in EEG between speaking and resting states. In the construction of EEG classification models, the classification performance of deep neural network algorithms is superior to other machine learning algorithms.
Clinicopathological and molecular characterization of astrocytoma
Authors: Wu Xiaoyan , Peng Wenfeng , Zhang Xu , Tang Tao , Deng Ling , Xu Yuxia , Liu Xiaoyun , Wang Fang , Peng Wujian , Huang Jianrong , Zhong Xiaoni
Published: February 2025

Introduction

Astrocytoma is a rare tumour of the central nervous system that often manifests with non-specific clinical symptoms and lacks distinct histological features. There is a pressing need for further understanding of the clinicopathological and molecular characteristics of astrocytoma. Identifying mutant genes can aid in reliable and early diagnosis, as well as provide insights for the development of targeted therapies.

Methods

This study aims to investigate the clinicopathologic and molecular characteristics of astroblastoma. A total of four patients diagnosed with astroblastoma were included in the analysis. Clinical features, histological findings, and immunohistochemistry results were reviewed and analyzed. Genetic alterations were identified using fluorescence in situ hybridization (FISH) and next-generation sequencing (NGS), followed by patient follow-up.

Results

The study included four female patients, ranging in age from 8 to 44 years. One patient had a tumour in the right parietal lobe, while the other three had tumours in the spinal cord. Histology is usually characterized by pseudorosettes of astroblasts and hyalinization of blood vessels. These tumors showed a growth pattern similar to traditional intracranial astroblastoma, and the histological manifestations of the four patients were all high-grade, showing features of high-density areas of tumor cells or necrosis. Immunohistochemical staining revealed that all four patients expressed OLIG2, EMA, and vimentin, while three patients also expressed GFAP and S-100. The Ki-67 positivity index was approximately 15% in three cases and 10% in one case. Fluorescence in situ hybridization (FISH) using break-apart probes showed EWRS1 breaks in three patients and MN1 breaks in one. Further DNA or RNA-targeted biallelic sequencing identified an EWSR1(Exon1-7)-BEND2(Exon2-14) fusion in case 1, and an EWSR1(Exon1-7)-BEND2(Intergenic) fusion in case 2. In case 3, an EWSR1(Exon1-7)-NUDT10(Intergenic) fusion was present, and in case 4, an MN1(Exon1)-BEND2(Exon2) fusion was identified. The EWSR1-NUDT10 gene fusion is a new fusion type in astroblastoma. The patients were followed up for 76.5, 17.6, 33.7, and 61.3 months, respectively. Three cases experienced tumour recurrences at the spinal cord site, with multiple recurrences in case 4.

Discussion

Our study unveiled the distinctive clinicopathological and molecular mutational characteristics of astrocytoma, while also identifying rare mutated genes. Additionally, the detection of MN1 or EWSR1 gene fusion through FISH or next-generation sequencing can provide valuable insights into the molecular mechanisms and aid in the differential diagnosis of astrocytoma.
Spicy food intake and overweight/obesity in rural Southwest China: findings from a cross-sectional study
Authors: Xiong Huali , Zhao Peng , Ma Fengxun , Tang Dayi , Liu Daiqiang
Published: February 2025

Background

Spicy food is an essential part of the culinary culture in rural southwest China, while little is known about the association between spicy food intake and overweight/obesity. This study was undertaken to explore the association between spicy food intake and overweight/obesity by a cross-sectional study.

Method

We enrolled 2,995 individuals aged 30–79 years living in Rongchang, Chongqing municipality, southwest China from The China Multi-Ethnic Cohort Study, which was deemed to be the largest cohort study in southwest China. A multivariable-adjusted logistic regression model was applied to estimate the association between spicy food intake and overweight/obesity. Additionally, subgroup and sensitivity analyses were performed to verify the stability of the results.

Results

A total of 81.67% of participants had the habit of consuming spicy food. The overall prevalence of overweight/obesity was 57.53%. Spicy food intake (OR = 2.913, 95%CI: 1.319–6.434) and frequency of spicy food intake (OR = 1.300, 95%CI: 1.164–1.452) were positively associated with overweight/obesity. Compared with the participants who never consumed spicy food, after adjusting for confounding factors, the adjusted ORs (95% CIs) in frequency of spicy food intake in 1–2 days/week, 3–5 days/week, 6–7 days/week subgroups were 3.985 (1.855–8.560), 4.381 (2.011–9.543), 6.515 (3.101–13.686), respectively. Subgroup analyses stratified by gender and age group, as well as sensitivity analyses, have consistently revealed a similar association between spicy food intake/the frequency of spicy food intake and overweight/obesity.

Conclusion

This study could provide additional evidence for overweight and the obesity epidemic among rural adults in southwest China. Reducing spicy food intake might benefit from weight management.
Quantifying the spatial patterns of retinal ganglion cell loss and progression in optic neuropathy by applying a deep learning variational autoencoder approach to optical coherence tomography
Authors: Wang Jui-Kai , Johnson Brett A. , Chen Zhi , Zhang Honghai , Szanto David , Woods Brian , Wall Michael , Kwon Young H. , Linton Edward F. , Pouw Andrew , Kupersmith Mark J. , Garvin Mona K. , Kardon Randy H.
Published: February 2025

Introduction

Glaucoma, optic neuritis (ON), and non-arteritic anterior ischemic optic neuropathy (NAION) produce distinct patterns of retinal ganglion cell (RGC) damage. We propose a booster Variational Autoencoder (bVAE) to capture spatial variations in RGC loss and generate latent space (LS) montage maps that visualize different degrees and spatial patterns of optic nerve bundle injury. Furthermore, the bVAE model is capable of tracking the spatial pattern of RGC thinning over time and classifying the underlying cause.

Methods

The bVAE model consists of an encoder, a display decoder, and a booster decoder. The encoder decomposes input ganglion cell layer (GCL) thickness maps into two display latent variables (dLVs) and eight booster latent variables (bLVs). The dLVs capture primary spatial patterns of RGC thinning, while the display decoder reconstructs the GCL map and creates the LS montage map. The bLVs add finer spatial details, improving reconstruction accuracy. XGBoost was used to analyze the dLVs and bLVs, estimating normal/abnormal GCL thinning and classifying diseases (glaucoma, ON, and NAION). A total of 10,701 OCT macular scans from 822 subjects were included in this study.

Results

Incorporating bLVs improved reconstruction accuracy, with the image-based root-mean-square error (RMSE) between input and reconstructed GCL thickness maps decreasing from 5.55 ± 2.29 µm (two dLVs only) to 4.02 ± 1.61 µm (two dLVs and eight bLVs). However, the image-based structural similarity index (SSIM) remained similar (0.91 ± 0.04), indicating that just two dLVs effectively capture the main GCL spatial patterns. For classification, the XGBoost model achieved an AUC of 0.98 for identifying abnormal spatial patterns of GCL thinning over time using the dLVs. Disease classification yielded AUCs of 0.95 for glaucoma, 0.84 for ON, and 0.93 for NAION, with bLVs further increasing the AUCs to 0.96 for glaucoma, 0.93 for ON, and 0.99 for NAION.

Conclusion

This study presents a novel approach to visualizing and quantifying GCL thinning patterns in optic neuropathies using the bVAE model. The combination of dLVs and bLVs enhances the model’s ability to capture key spatial features and predict disease progression. Future work will focus on integrating additional image modalities to further refine the model’s diagnostic capabilities.
An analysis of the burden of migraine and tension-type headache across the global, China, the United States, India and Japan
Authors: Xu Rongjiang , Zhang Ruonan , Dong Liang , Xu Xiaonuo , Fan Xiaoping , Zhou Jiying
Published: February 2025

Background

Recurrent headaches in headache disorders adversely impact quality of life and job. Migraines and tension-type headache TTH) are the most common primary headaches and a prominent cause of disability globally. However, few research compare headache illness burden in China, India, the United States (US), and Japan.

Methods

Global and Chinese, the US, Indian, and Japanese migraine and TTH incidence, prevalence, and disability-adjusted life years were taken from the GBD database for 1990–2021. The data is studied utilizing decomposition analysis, health inequality research, joinpoint regression model, and Bayesian Average Annual Percentage Change (BAPC) model.

Results

The study found that migraine mostly affects women aged 15–49, while TTH are evenly distributed across gender and age. The worldwide average annual percentage change (AAPC) in disease-adjusted life years (DALYs) for migraine and TTH from 1990 to 2021 was 0.0357, a statistically significant trend (p < 0.001), as determined using joinpoint analysis. China exhibited the quickest rise in migraine and TTH incidence and prevalence, as well as the age-standardized rate (ASR) of DALYs, of the four nations analyzed. The US had the highest value of these indicators. Forecasting models reveal that without policy action, migraine prevalence will grow but TTH prevalence would stay unchanged. Decomposition research showed that population expansion is the major cause of migraines and TTH, which will be slightly alleviated by population aging. Health disparities across economic growth areas lessened between 1990 and 2021, according to the report.

Conclusion

Globally and in China, migraine and TTH incidence and burden have increased since 1990. Migraines are becoming more common in young and middle-aged women, so headache treatment professionals should invest more in patient education to raise awareness and improve self-management to reduce disease burden and medical costs.
Prevalence of myopia and refractive parameters among children and adolescents in Hi-tech District of Chengdu City
Authors: Wang Xiaoqin , Zeng Liuzhi , Xian Yiping , Xin Mei , Shan Qingqing , Li Weiye , Lv Lixia , Liu Yifeng , Zhang Rui , Song Kejian , Tian Xixi , Guo Han , Yan Changjiang , Li Chunyan , Luo Xueni , Luo Honglin , Yang Ling , Luo Jun , Chen Zejun
Published: February 2025

Objective

To analyze the prevalence of myopia among children and adolescents in Chengdu from 2021 to 2023, providing insights for myopia prevention and control.

Methods

This study was a school-based cross-sectional study in children and adolescents aged 3–18 years in Hi-tech District of Chengdu City. All the students underwent comprehensive ocular measurement, including uncorrected binocular visual acuity (VA), spherical equivalent error (SER) with noncycloplegic autorefraction, corneal radius (CR), and axial length (AL).

Results

Over the three-year study period from 2021 to 2023, the overall prevalence of myopia was 38.15%, with annual rates of 38.74% in 2021, 38.67% in 2022, and 37.03% in 2023. The prevalence and severity of myopia increased significantly with age (P < 0.001). The prevalence was consistently higher among girls (P < 0.001) with 40.17% in 2021, 39.43% in 2022, and 38.33% in 2023 compared to 37.03%, 38.05% and 35.85% among boys in the years, respectively. The myopia prevalence increased with school level (P < 0.001). Mild myopia was the most common (24.47%), followed by moderate (10.77%) and severe myopia (2.91%). The mean SER were −1.72 ± 1.57 D in 2021, −1.32 ± 1.51 D in 2022, and −1.42 ± 1.36 D in 2023 (P < 0.001). AL was stable across most age groups, with mean AL across the overall sample of 23.80 ± 1.02 mm in 2021, 23.79 ± 1.04 mm in 2022, and 23.81 ± 1.04 mm in 2023.

Conclusion

Myopic prevalence among children and adolescents in Hi-tech District of Chengdu City decreased from 2021 to 2023. The prevalence increased with age and school level, indicating a need for targeted interventions. Significant changes in spherical equivalent refraction and AL emphasize the importance of early intervention and regular monitoring of myopia for an effective management.
Leveraging AI to automate detection and quantification of extrachromosomal DNA to decode drug responses
Authors: Goble Kohen , Mehta Aarav , Guilbaud Damien , Fessler Jacob , Chen Jingting , Nenad William , Ford Christina G. , Cope Oliver , Cheng Darby , Dennis William , Gurumurthy Nithya , Wang Yue , Shukla Kriti , Brunk Elizabeth
Published: February 2025

Introduction

Traditional drug discovery efforts primarily target rapid, reversible protein-mediated adaptations to counteract cancer cell resistance. However, cancer cells also utilize DNA-based strategies, often perceived as slow, irreversible changes like point mutations or drug-resistant clone selection. Extrachromosomal DNA (ecDNA), in contrast, represents a rapid, reversible, and predictable DNA alteration critical for cancer’s adaptive response.

Methods

In this study, we developed a novel post-processing pipeline for automated detection and quantification of ecDNA in metaphase Fluorescence in situ Hybridization (FISH) images, leveraging the Microscopy Image Analyzer (MIA) tool. This pipeline is tailored to monitor ecDNA dynamics during drug treatment.

Results

Our approach effectively quantified ecDNA changes, providing a robust framework for analyzing the adaptive responses of cancer cells under therapeutic pressure.

Discussion

The pipeline not only serves as a valuable resource for automating ecDNA detection in metaphase FISH images but also highlights the role of ecDNA in facilitating swift and reversible adaptation to epigenetic remodeling agents such as JQ1.
Adaptive spatial-channel feature fusion and self-calibrated convolution for early maize seedlings counting in UAV images
Authors: Sun Zhenyuan , Yang Zhi , Ding Yimin , Sun Boyan , Li Saiju , Guo Zhen , Zhu Lei
Published: February 2025

Accurate counting of crop plants is essential for agricultural science, particularly for yield forecasting, field management, and experimental studies. Traditional methods are labor-intensive and prone to errors. Unmanned Aerial Vehicle (UAV) technology offers a promising alternative; however, varying UAV altitudes can impact image quality, leading to blurred features and reduced accuracy in early maize seedling counts. To address these challenges, we developed RC-Dino, a deep learning methodology based on DINO, specifically designed to enhance the precision of seedling counts from UAV-acquired images. RC-Dino introduces two innovative components: a novel self-calibrating convolutional layer named RSCconv and an adaptive spatial feature fusion module called ASCFF. The RSCconv layer improves the representation of early maize seedlings compared to non-seedling elements within feature maps by calibrating spatial domain features. The ASCFF module enhances the discriminability of early maize seedlings by adaptively fusing feature maps extracted from different layers of the backbone network. Additionally, transfer learning was employed to integrate pre-trained weights with RSCconv, facilitating faster convergence and improved accuracy. The efficacy of our approach was validated using the Early Maize Seedlings Dataset (EMSD), comprising 1,233 annotated images of early maize seedlings, totaling 83,404 individual annotations. Testing on this dataset demonstrated that RC-Dino outperformed existing models, including DINO, Faster R-CNN, RetinaNet, YOLOX, and Deformable DETR. Specifically, RC-Dino achieved improvements of 16.29% in Average Precision (AP) and 8.19% in Recall compared to the DINO model. Our method also exhibited superior coefficient of determination (R²) values across different datasets for seedling counting. By integrating RSCconv and ASCFF into other detection frameworks such as Faster R-CNN, RetinaNet, and Deformable DETR, we observed enhanced detection and counting accuracy, further validating the effectiveness of our proposed method. These advancements make RC-Dino particularly suitable for accurate early maize seedling counting in the field. The source code for RSCconv and ASCFF is publicly available at https://github.com/collapser-AI/RC-Dino, promoting further research and practical applications.
Tomato mitogen-activated protein kinase: mechanisms of adaptation in response to biotic and abiotic stresses
Authors: Shi Yumei , Zhang Zhifang , Yan Zhenghao , Chu Honglong , Luo Changxin
Published: February 2025

Plants live under various biotic and abiotic stress conditions, and to cope with the adversity and severity of these conditions, they have developed well-established resistance mechanisms. These mechanisms begin with the perception of stimuli, followed by molecular, biochemical, and physiological adaptive measures. Tomato (Solanum lycopersicum) is a globally significant vegetable crop that experiences several biotic and abiotic stress events that can adversely impact its quality and production. Mitogen-activated protein kinases (MAPKs) in tomato plants have crucial functions of mediating responses to environmental cues, internal signals, defense mechanisms, cellular processes, and plant development and growth. MAPK cascades respond to various environmental stress factors by modulating associated gene expression, influencing plant hormone synthesis, and facilitating interactions with other environmental stressors. Here, we review the evolutionary relationships of 16 tomato SlMAPK family members and emphasize on recent studies describing the regulatory functions of tomato SlMAPKs in both abiotic and biotic stress conditions. This review could enhance our comprehension of the MAPK regulatory network in biotic and abiotic stress conditions and provide theoretical support for breeding tomatoes with agronomic traits of excellent stress resistance.
Exploring urban–rural inequities in older adults life expectancy: a case study in Zhejiang, China for health equity
Authors: Chen Yongguo , Fan Xiaoting , Shen Shusheng , Chen Yong , Pan Zhiwei , Chen Zixuan , Zhong Haoqiang , Li Menglong
Published: February 2025

This study investigates the inequities in life expectancy among individuals aged 65 and above in urban and rural areas of Zhejiang Province, China, with a primary focus on promoting health equity among the older adults population. The objective is to analyze the trends and factors contributing to the urban–rural gap in life expectancy and to propose strategies for reducing this disparity. Data from the 2010 and 2020 statistical records and census data were analyzed using cohort life tables and gray correlation analysis. Results indicate an overall increase in life expectancy among the older adults, with a more pronounced improvement in rural areas, thereby narrowing the urban–rural gap from 1.53 years in 2010 to 1 year in 2020. Income inequality emerges as the primary factor influencing life expectancy, followed by educational attainment, with variations across different age groups and gender. This underscores the importance of tailored interventions that consider the specific needs of older adults individuals in diverse geographical areas and age brackets to extend life expectancy and promote health equity. By tackling these unfair differences, health equity can be ensured and the overall well-being of the older population in both urban and rural areas can be improved.
Quantifying hope: an EU perspective of rare disease therapeutic space and market dynamics
Authors: Cacoub Emmanuelle , Lefebvre Nathalie Barreto , Milunov Dimitrije , Sarkar Manish , Saha Soham
Published: February 2025

Rare diseases, affecting millions globally, pose a significant healthcare burden despite impacting a small population. While approximately 70% of all rare diseases are genetic and often begin in childhood, diagnosis remains slow and only 5% have approved treatments. The UN emphasizes improved access to primary care (diagnostic and potentially therapeutic) for these patients and their families. Next-generation sequencing (NGS) offers hope for earlier and more accurate diagnoses, potentially leading to preventative measures and targeted therapies. In here, we explore the therapeutic landscape for rare diseases, analyzing drugs in development and those already approved by the European Medicines Agency (EMA). We differentiate between orphan drugs with market exclusivity and repurposed existing drugs, both crucial for patients. By analyzing market size, segmentation, and publicly available data, this comprehensive study aims to pave the way for improved understanding of the treatment landscape and a wider knowledge accessibility for rare disease patients.
Deep learning and explainable AI for classification of potato leaf diseases
Authors: Alhammad Sarah M. , Khafaga Doaa Sami , El-hady Walaa M. , Samy Farid M. , Hosny Khalid M.
Published: February 2025

The accurate classification of potato leaf diseases plays a pivotal role in ensuring the health and productivity of crops. This study presents a unified approach for addressing this challenge by leveraging the power of Explainable AI (XAI) and transfer learning within a deep Learning framework. In this research, we propose a transfer learning-based deep learning model that is tailored for potato leaf disease classification. Transfer learning enables the model to benefit from pre-trained neural network architectures and weights, enhancing its ability to learn meaningful representations from limited labeled data. Additionally, Explainable AI techniques are integrated into the model to provide interpretable insights into its decision-making process, contributing to its transparency and usability. We used a publicly available potato leaf disease dataset to train the model. The results obtained are 97% for validation accuracy and 98% for testing accuracy. This study applies gradient-weighted class activation mapping (Grad-CAM) to enhance model interpretability. This interpretability is vital for improving predictive performance, fostering trust, and ensuring seamless integration into agricultural practices.
Softer, Safer, Smarter: Robotic Hands Inspired by Nature
Authors: Terrile Silvia , Lee Loong Yi
Published: February 2025

Robot arms can be found in many factories around the world. From the tiniest chip in a phone to the body of a car, robots are responsible for moving things around thousands of times a day. However, robots find themselves a bit stuck when dealing with more natural objects, such as fruits or vegetables. Their rigid bodies feel out of place amongst all the squishiness and different shapes and sizes of nature. One way to help solve that is by making robots softer. Soft grippers allow robots to delicately touch the world around them, grabbing fragile objects almost as easily as humans do. Many robots made of soft materials, called soft robots, are inspired by nature to help them interact with their environments. With hands made of softer materials, these robots are ready to help us not just in factories, but also in our daily lives. How are soft grippers created? What do they look like? In this article, we will explore the captivating realm of soft grippers!
Incidence of seed-borne fungi of stored sunflower seeds (Helianthus annuus) in Tanzania and their influence on seed viability and vigor
Authors: Selemani Siwajali , Madege Richard , Nzogela Yasinta
Published: February 2025

Understanding the impact of seed-borne fungi on seed quality is crucial for improving sunflower productivity. This study was conducted to investigate the incidence of seed-borne fungi in stored sunflower seeds under ambient conditions and their effects on seed viability and vigor. Certified seeds, quality-declared seeds (QDS), and farmer-saved seeds (FSS) were stored for 6 months, with monthly sampling to evaluate fungal infection percentage (FIP), germination percentage (G), and seedling vigor index (SVI). Key findings include the identification of fungal species: Aspergillus flavus, A. niger, Alternaria padwickii, A. zinniae, Botrytis cinerea, Curvularia lunata, Fusarium vericillioides, and Rhizopus arrihizus. The highest incidence of F. vericillioides (14.39%) and B. cinerea (14.28%) occurred in FSS, while the lowest incidence of A. zinniae (1.83%) was recorded in QDS. Total fungal infection was highest in FSS (73.11%) compared to QDS (66.94%) and certified seeds (67.06%). Seed quality parameters showed a clear trend: QDS exhibited the highest G (81.56%), with certified seeds following closely (81.33%). The highest SVI was recorded in certified seeds (96.76), with QDS showing a similar result (95.69). In contrast, FSS showed the lowest G% (60.67) and SVI (65.98). Seeds with minimal fungal infection consistently demonstrated higher G% and SVI. These results highlight the detrimental impact of fungal infections on seed vigor and viability. This study is the first in Tanzania to report and quantify the incidence of seed-borne fungi in stored sunflower seeds, providing critical insights for improving seed management practices and sunflower production.
Comparing traditional surveys and web-scraped data to understand the pigeon racing industry in Southern California
Authors: Pitesky Maurice , Isa Malekah , Rivera Charlene , Streba Elise , Gendreau Joseph D.
Published: February 2025

Recent outbreaks of virulent Newcastle disease (vND) in domestic poultry in Southern California have raised questions as to the source(s) and the mode(s) of transmission. While pigeons have been found to be capable of transmitting a variant of Newcastle disease virus (NDV) known as Pigeon paramyxovirus-1 (PPMV-1) to other avian species including poultry, the potential geographic distribution and scope of transmission from racing pigeons to other domestic poultry in Southern California is poorly understood. In order to better understand the potential risk of transmission of vND from racing pigeons to domestic poultry, an extension-initiated survey was conducted in addition to social-media based analysis of racing pigeon activity associated with postings on a web-based popular classified advertisement (CAW) in Southern California. Likely due to the insularity of the pigeon racing industry in Southern California, only 1 survey response was completed. However, monitoring results from the CAW demonstrated a much higher level of social media activity associated with racing pigeon sales in Southern California. Specifically, 191 unique posts associated with pigeon sales were flagged between 12/21/2020 and 1/21/2021 demonstrating the potential for the analysis of social media as an extension-based tool. Data from the CAW showed that the majority of pigeon related posts and sales came from both the Inland Empire region of Southern California and San Diego county which overlapped with the established vND control zone. From an extension perspective, while traditional-based surveys can still provide valuable information, web-scraping of social media can provide a continuous source of spatio-temporal data that can facilitate extension-based observations and analysis among hard to reach stakeholder groups.
Comparative anti-methanogenic ability of green algae (C. reinhardtii) with/without nanoparticles: in vitro gas and methane production
Authors: Palangi Valiollah , Kaya Adem , Macit Muhlis , Nadaroglu Hayrunnisa , Ünlü Hayrullah Bora , Kaya Ali , Fekri Ashkan , Mammadov Ayaz , Lackner Maximilian
Published: February 2025

Introduction

The purpose of this study was to investigate how in vitro gas production (GP) and ruminal fermentation characteristics were affected by increasing concentrations of green algae plant (C. reinhardtii) extracts in combination with nanoparticles MgO and MgS.

Methods

A solution containing 0.1 M MgCl2 was prepared in 300 mL for the green production of MgCl nanoparticles. The mixture was refluxed for two hours at 85°C using a reflux condenser after 10 mL of pomegranate plant extract was added. The green algal plant (C. reinhardtii), which has many non-toxic antioxidants, was used as a carbon source to produce carbon quantum dots (CQD). Chemical analysis was conducted in accordance with AOAC (2005) recommendations. Rumen fluid from recently slaughtered calves is used to produce in vitro gas immediately following slaughter. Analysis of variance (ANOVA) was performed on the obtained data from the in vitro study in a completely randomized design using the mixed model of SAS (version 9.4; Inc., Cary NC, USA).

Results and Discussion

The variance analysis results and the average values of the chemical compositions were significantly influenced by the extracts (all p < 0.0001). In this line, the values of net gas, pH, OMD, ME, NEl, and ME were found to be the highest for Algae + 50 MgO and the lowest for Algae + 50 MgS, respectively (all p < 0.0001). These promising results imply that extracts from C. Reinhardtii may be able to mitigate the adverse consequences of rumen fermentation. To precisely ascertain the impact particular Rhodophyta on greenhouse gas emissions, additional investigation is needed.
Comparing Open and Robotic Unilateral Transversus Abdominis Release in Incisional Hernias With a Lateral Component: A Single Center Retrospective Study
Authors: Van Hoef Stijn , Eker Hasan H. , Berrevoet Frederik , Allaeys Mathias
Published: February 2025

Introduction

Lateral hernias are often more challenging to correct when compared to midline defects, due to the anatomic boundaries of the bony pelvis, retroperitoneum, and costal margin. With the insurgence of robot assisted abdominal wall surgery, these defects have been found more manageable through a minimal invasive repair. In this study, we aim to present our short-term results of incisional hernia repair with a lateral component requiring a unilateral transversus abdominis release, through open surgery versus robot assisted.

Methods

A retrospective analysis was performed of our robotic and open abdominal wall repairs of lateral hernias, where a unilateral transversus abdominis release was performed, between January 2017 and December 2023. Patient, hernia and perioperative details are reported.

Results

54 patients in the open group versus 10 patients in the robotic group were included. Hernia width and hernia surface area were higher in the open group, but not significant. Operation time was similar between open and robotic procedures. In-hospital complications, surgical site infection and clinical seroma rate during the first 30 postoperative days were similar in both groups. There was a clear difference in length of stay, in favor of the robotic group.

Discussion

In our limited series, a robotic approach seems safe and feasible when faced with large lateral hernias. Short-term results show a shorter length of stay using the robotic approach, with no significant difference in short term complications, specifically SSI-rate. However, conclusions are limited due to the low number of patients and additional studies should be performed to account for long term recurrence and increase included patient number.
Intelligent Multi-Fault Diagnosis for a Simplified Aircraft Fuel System
Authors: Li Jiajin , King Steve , Jennions Ian
Published: February 2025

Machine learning (ML) techniques are increasingly used to diagnose faults in aerospace applications, but diagnosing multiple faults in aircraft fuel systems (AFSs) remains challenging due to complex component interactions. This paper evaluates the accuracy and introduces an innovative approach to quantify and compare the interpretability of four ML classification methods—artificial neural networks (ANNs), support vector machines (SVMs), decision trees (DTs), and logistic regressions (LRs)—for diagnosing fault combinations present in AFSs. While the ANN achieved the highest diagnostic accuracy at 90%, surpassing other methods, its interpretability was limited. By contrast, the decision tree model showed an 82% consistency between global explanations and engineering insights, highlighting its advantage in interpretability despite the lower accuracy. Interpretability was assessed using two widely accepted tools, LIME and SHAP, alongside engineering understanding. These findings underscore a trade-off between prediction accuracy and interpretability, which is critical for trust in ML applications in aerospace. Although an ANN can deliver high diagnostic accuracy, a decision tree offers more transparent results, facilitating better alignment with engineering expectations even at a slight cost to accuracy.
A Novel Model for Noninvasive Haemoglobin Detection Based on Visibility Network and Clustering Network for Multi-Wavelength PPG Signals
Authors: Liu Lei , Wang Ziyi , Zhang Xiaohan , Zhuang Yan , Liang Yongbo
Published: February 2025

Non-invasive haemoglobin (Hb) testing devices enable large-scale haemoglobin screening, but their accuracy is not comparable to traditional blood tests. To this end, this paper aims to design a non-invasive haemoglobin testing device and propose a classification-regression prediction framework for non-invasive testing of haemoglobin using visibility graphs (VG) with network clustering of multi-sample pulse-wave-weighted undirected graphs as the features to optimize the detection accuracy of non-invasive haemoglobin measurements. Different prediction methods were compared by analyzing 608 segments of multiwavelength fingertip PPG signal data from 152 volunteers and analyzing and comparing the data and methods. The results showed that the classification using NVG with complex network clustering as features in the interval classification model was the best, with its classification accuracy (acc) of 93.35% and model accuracy of 88.28%. Among the regression models, the classification regression stack: SVM-Light Gradient Boosting Machine (LGBM) was the most effective, with a Mean Absolute Error (MAE) of 6.67 g/L, a Root Mean Square Error (RMSE) of 8.21 g/L, and an R-Square (R2) of 0.64. The results of this study indicate that the use of complex network technology in non-invasive haemoglobin detection can effectively improve its accuracy, and the detector designed in this study is promising to carry out a more accurate large-scale haemoglobin screening.
A Safety and Efficacy Study of a Synthetic Biolubricant in an Equine Model of Post-Traumatic Osteoarthritis
Authors: Luedke Lauren K. , Seabaugh Kathryn A. , Cooper Benjamin G. , Snyder Brian D. , Wimmer Markus A. , McIlwraith C. Wayne , Barrett Myra F. , Kawcak Christopher E. , Grinstaff Mark W. , Goodrich Laurie R.
Published: February 2025

Post-traumatic osteoarthritis (PTOA) is a common cause of lameness in the horse. There is no cure, therefore treatments are aimed at reducing pain and improving the joint environment by modifying inflammatory pathways or by viscosupplementation. Here, we report the safety and efficacy of the biolubricant (poly(2-methacryloyloxyethyl phosphorylcholine; pMPC) to mitigate the physical, gross, histological, and biochemical effects of arthritis. We created an osteochondral fragment in the middle carpal joint of one limb in 16 horses to induce PTOA; the contralateral limb served as a sham-operated joint. Two weeks postoperative, half (n = 8) of the horses received a single injection of pMPC in the PTOA joint, while the other half received saline. All sham-operated joints (n = 16) received saline. We conducted clinical evaluations weekly while synovial fluid biomarkers were measured biweekly during the 70-day study period. Subsequently, we performed postmortem gross and histologic analyses. Horses in which PTOA joints were treated with pMPC exhibited mild increases in clinical data, including lameness, effusion, and flexion scores. Similarly, synovial cell count, total protein, and prostaglandin E2 values were higher for pMPC-treated joints. Radiographic changes included significantly higher osteophyte scores in pMPC-treated joints at the terminal timepoint. The biolubricant may demonstrate some chondroprotective effects with lower total erosion scores and higher cartilage glycosaminoglycan content. In summary, when pMPC is administered to PTOA joints, the biolubricant induces a mild inflammatory response but may offer some chondroprotective effects in horses.
Oxazolone-Induced Immune Response in Atopic Dermatitis Using a Goat Model and Exploration of the Therapeutic Potential of Pomegranate Peel Extract
Authors: Elfadadny Ahmed , Samir Haney , Mandour Ahmed S. , Ragab Rokaia F. , Elshafey Besheer G. , Alanazi Fawaz E. , Hetta Helal F. , Alharbi Ahmad A. , Albalawi Abdullah S. , Aljameel Suhailah S. , Alwaili Maha Abdullah , Nageeb Wedad M. , Emam Mahmoud H.
Published: February 2025

Atopic dermatitis (AD) remains a challenging condition, necessitating effective models for investigation and therapeutic exploration. In this study, we employed a goat skin model to assess the immune response triggered by topical oxazolone (OX) application. The OX simulates a Th2-driven immune reaction typified by elevated Th2 cytokine (IL-4 and IL-13) expression and the infiltration of mononuclear cells magnified by the presence of CD3+ and CD4+ T-cells in the epidermal and dermal layers. Additionally, the application of pomegranate peel extract (PPE) demonstrated a mitigating effect on OX-induced skin alterations, suggesting potential therapeutic benefits. This study underscores the value of goats as a reliable and accessible model for studying AD in humans and/or large animals. While the therapeutic potential of PPE dosage requires further exploration.
Effects of Exercise Speed and Circle Diameter on Markers of Bone and Joint Health in Juvenile Sheep as an Equine Model
Authors: Harbowy Renee M. , Nielsen Brian D. , Colbath Aimee C. , Robison Cara I. , Buskirk Daniel D. , Logan Alyssa A.
Published: February 2025

Though circular exercise is commonly used in equestrian disciplines, it may be at the detriment of horses’ musculoskeletal system. To investigate the effects of circular exercise on bone and joint health, 42 lambs were randomly assigned to a non-exercised control, straight-line, small circle, or large circle exercise regime at a slow (1.3 m/s) or fast (2.0 m/s) speed for 12 wk. Blood samples were taken biweekly. Animals were humanely euthanized upon study completion, and the fused third and fourth metacarpals were collected for biomechanical testing and bone density analysis. Fast groups were found to have more bone formation and less resorption activity than slow groups as evidenced by serum biomarker concentrations (p < 0.05). Sheep in the large fast group tended to have greater flexural rigidity and fracture force for the outside leg compared to the inside leg (p < 0.1). Sheep in the small slow group tended to have increased bone mineral density of the outside leg compared to the inside leg, whereas the opposite occurred in the large slow group (p < 0.1). These results provide further evidence for potential asymmetric musculoskeletal adaptations to circular exercise while emphasizing the importance of speed as a positive influence on bone metabolism and strength.
Revitalizing Recovery: Unveiling the Potential of Apigenin and Related Flavonoids in Long COVID-19 Therapy Through Molecular Dynamics Simulation
Authors: Muchtaridi Muchtaridi , Prasetiawati Riska , Alawiah Siti Ajah , Salsabila Shela , Fakih Taufik Muhammad , Nuwarda Rina Fajri , Ikram Nur Kusaira Khairul
Published: February 2025

Long COVID-19, also known as post-acute sequelae of SARS-CoV-2 infection (PASC), involves symptoms or effects that persist for more than 4 weeks after the initial SARS-CoV-2 infection. One contributing factor to this condition is the disruption in the expression of the antioxidant enzyme Nuclear Factor Erythroid-2 (Nrf2) induced by the COVID-19 infection. Apigenin and related flavonoids, known for their diverse pharmacological activities, including potent antioxidant properties, have emerged as promising candidates for Long COVID-19 therapy. These compounds, particularly apigenin, are recognized for their ability to modulate oxidative stress and inflammation, making them potential activators of the Nrf2 pathway. This study aims to predict the activity of apigenin and its related flavonoids as Nrf2 activators using molecular modeling and molecular dynamics (MD) techniques, providing insights into their therapeutic potential in managing Long COVID-19. The findings from the molecular modeling analysis indicate that apigenin has a favorable affinity, with a free energy value (ΔG) of −6.40 kcal/mol. Additionally, MD simulation results demonstrate the strong stability of the Keap1-apigenin complex, with an average Root Mean Square Deviation (RMSD) value below 0.20 nm and the lowest average Root Mean Square Fluctuation (RMSF) value of 0.86 nm. Using the Molecular Mechanics/Generalized Born Surface Area (MM-GBSA) calculation method, the binding affinity of the Keap1-apigenin complex yields a lower free energy value (ΔG) of −67.039 kJ/mol, consistent with the molecular modeling results. Apigenin also exhibits the ability to inhibit the binding of Nrf2 to the hydrophobic surface of Keap1, with a total energy value of 993.266 kcal/mol and binding affinity value of −1.162 kJ/mol through peptide−receptor docking. In conclusion, the comprehensive results suggest that apigenin has the potential to be a lead compound for developing Nrf2 activators specifically designed for Long COVID-19 therapy.
Eccentric Wear Mechanism and Centralizer Layout Design in 3D Curved Wellbores
Authors: Feng Ziming , Guo Botao , Cai Zhihui , Yuan Heng
Published: February 2025

In deep oil and gas wells, sucker rod strings (SRS) frequently experience breakage and eccentric wear problems. To address this engineering challenge, this study establishes a new coupled three-dimensional (3D) mechanical-mathematical model for sucker rod strings in 3D curved wellbores. The model comprehensively considers well trajectory, rod string structure, and external excitation, analysing the influences of elastic force, inertial force, and friction force on the sucker rod micro-elements. The formulated differential equations are discretised using the central difference method to obtain the configuration of each point on SRS and the 3D distribution of stress and strain, thereby determining the eccentric wear points between the rod and tube. A numerical solution program was developed and successfully applied in the Daqing oilfield. Results from two case studies demonstrate significant improvements: for A1# well, the system efficiency increased from 16% to 20%, while for A2# well, the pump efficiency improved from 39.8% to 58.9% and system efficiency from 33.4% to 35%. The model overcomes previous limitations by considering rod torque, 3D curved tubing spatial coordinates, tubing non-anchoring effects, and forced buckling influence, providing a theoretical basis for dynamic calculations of sucker rod pumping systems in 3D curved wells.
Impact of Texture Feature Count on the Accuracy of Osteoporotic Change Detection in Computed Tomography Images of Trabecular Bone Tissue
Authors: Dzierżak Róża
Published: February 2025

The aim of this study is to compare the classification accuracy depending on the number of texture features used. This study used 400 computed tomography (CT) images of trabecular spinal tissue from 100 patients belonging to two groups (50 control patients and 50 patients diagnosed with osteoporosis). The descriptors of texture features were based on a gray level histogram, gradient matrix, RL matrix, event matrix, an autoregressive model, and wavelet transformation. From the 290 obtained texture features, the features with fixed values were eliminated and structured according to the feature importance ranking. The classification performance was assessed using 267, 200, 150, 100, 50, 20, and 10 texture features to build classifiers. The classifiers applied in this study included Naive Bayes, Multilayer Perceptron, Hoeffding Tree, K-nearest neighbors, and Random Forest. The following indicators were used to assess the quality of the classifiers: accuracy, sensitivity, specificity, precision, negative predictive value, Matthews correlation coefficient, and F1 score. The highest performance was achieved by the K-Nearest Neighbors (K = 1) and Multilayer Perceptron classifiers. KNN demonstrated the best results with 50 features, attaining a highest F1 score of 96.79% and accuracy (ACC) of 96.75%. MLP achieved its optimal performance with 100 features, reaching an accuracy and F1 score of 96.50%. This demonstrates that building a classifier using a larger number of features, without a selection process, allows us to achieve high classification effectiveness and holds significant diagnostic value.
Evaluation of Permeability, Safety, and Stability of Nanosized Ketoprofen Co-Spray-Dried with Mannitol for Carrier-Free Pulmonary Systems
Authors: Banat Heba , Gróf Ilona , Deli Mária A. , Ambrus Rita , Csóka Ildikó
Published: February 2025

Pulmonary drug delivery presents a promising approach for managing respiratory diseases, enabling localized drug deposition and minimizing systemic side effects. Building upon previous research, this study investigates the cytotoxicity, permeability, and stability of a novel carrier-free dry powder inhaler (DPI) formulation comprising nanosized ketoprofen (KTP) and mannitol (MNT). The formulation was prepared using wet media milling to produce KTP-nanosuspensions, followed by spray drying to achieve combined powders suitable for inhalation. Cell viability and permeability were conducted in both alveolar (A549) and bronchial (CFBE) models. Stability was assessed after storage in hydroxypropyl methylcellulose (HPMC) capsules under stress conditions (40 °C, 75% RH), as per ICH guidelines. KTP showed good penetration through both models, with lower permeability through the CFBE barrier. The MNT-containing sample (F1) increased permeability by 1.4-fold in A549. All formulations had no effect on cell barrier integrity or viability after the impedance test, confirming their safety. During stability assessment, the particle size remained consistent, and the partially amorphous state of KTP was retained over time. However, moisture absorption induced surface roughening and partial agglomeration, leading to reduced fine particle fraction (FPF) and emitted fraction (EF). Despite these changes, the mass median aerodynamic diameter (MMAD) remained stable, confirming the formulation’s continued applicability for pulmonary delivery. Future research should focus on optimizing excipient content, alternative capsule materials, and storage conditions to mitigate moisture-related issues. Hence, the findings demonstrate that the developed ketoprofen–mannitol DPI retains its quality and performance characteristics over an extended period, making it a viable option for pulmonary drug delivery.