bluuebunny/crossref_metadata_2025_split huggingface dataset:
Box-Behnken design-based development of eco-friendly RP-HPLC analytical method for the quantification of erastin from the mesoporous silica nanoparticles
Authors: Gupta Ashutosh , P Rachana S , Moorkoth Sudheer , Dhas Namdev 
Published: July 2024

Abstract

The current work aims to optimize, stablish, validate a high-performance liquid chromatography (HPLC) method that possesses sufficient sensitivity and specificity to measure erastin (ERT) in mesoporous silica nanoparticles. The HPLC method was optimized using Design of Experiments (DoE) technique. The Box-Behnken design (BBD) was used and buffer ratio, injection volume, buffer pH, and flow rate were used as the independent factors. The dependent variables were retention time (Rt) of ERT, peak area of ERT, and tailing factor (Tf) of ERT. The optimized chromatographic condition were: buffer ration 80%, buffer pH 3.8 and flow rate 0.9 mL/min, and injection volume 8 µL. The established HPLC method was validated as per ICH Q2 (R1) recommendations. The established method showed the good linearity (R2 = 0.9991) having a range of 12–500 ng/mL and LOD and LOQ was 2.71 ng and 6.25 ng, respectively. The mesoporous silica nanoparticle (MSN) matrix did not affect the specificity of our validated RP-HPLC method of analysis for ERT. Analysing the formulation's surface morphology helped with the confirmation of the synthesized MSNs. The proposed RP-HPLC method was effectively used to calculated the medication loaded in the MSNs as well as to measure the amount of ERT entrapped. The % EE for ERT in MSNs was found to be 76.07% and % DL for ERT in MSNs was found to be 14%, respectively. The established HPLC method was found ecofriendly as per the AGREE analysis.
A Comparative Study of Histotripsy Parameters for the Treatment of Fibrotic ex-vivo Human Benign Prostatic Hyperplasia Tissue
Authors: Kumar Yashwanth Nanda , Singh Zorawar , Wang Yak-Nam , Kanabolo Diboro , Chen Lucas , Bruce Matthew , Vlaisavljevich Eli , True Lawrence , Maxwell Adam D. , Schade George R. 
Published: July 2024

Abstract

Histotripsy is a noninvasive focused ultrasound therapy that mechanically fractionates tissue to create well-defined lesions. In a previous clinical pilot trial to treat benign prostatic hyperplasia (BPH), histotripsy did not result in consistent objective improvements in symptoms, potentially because of the fibrotic and mechanically tough nature of this tissue. In this study, we aimed to identify the dosage required to homogenize BPH tissue by different histotripsy modalities, including boiling histotripsy (BH) and cavitation histotripsy (CH). A method for histotripsy lesion quantification via entropy (HLQE) analysis was developed and utilized to quantify lesion area of the respective treatments. These data were correlated to changes in mechanical stiffness measured by ultrasound shear-wave elastography before and after treatment with each parameter set and dose. Time points corresponding to histologically observed complete lesions were qualitatively evaluated and quantitatively measured. For the BH treatment, complete lesions occurred with >=30s treatment time, with a corresponding maximum reduction in stiffness of -90.9±7.2(s.d.)%. High pulse repetition frequency (PRF) CH achieved a similar reduction to that of BH at 288s (-91.6±6.0(s.d.)%), and low-PRF CH achieved a (-82.1±5.1(s.d.)%) reduction in stiffness at dose >=144s. Receiver operating characteristic curve analysis showed that a >~75% reduction in stiffness positively correlated with complete lesions observed histologically, and can provide an alternative metric to track treatment progression.
Physical Activity Combined with Tea Consumption could further Reduce All-cause Mortality: Results from the US National Health and Nutrition Examination Survey, 2009-2018
Authors: Hu Yiqun , Yang Luning , He Jinshen 
Published: July 2024

Abstract

The study aimed to comprehensively assess the separate and combined effects of physical activity (PA) and tea consumption on all-cause mortality among 21,350 participants from The National Health and Nutrition Examination Survey (NHANES) between 2009 and 2018. PA and tea consumption were evaluated through self-reported questionnaires and dietary recall interviews at baseline, with mortality data obtained from the National Death Index. Cox regression analyses yielded hazard ratios (HR) and 95% confidence intervals (CI). Results indicated that both tea consumption and PA independently reduced all-cause mortality. In the physically active group, tea consumption further decreased mortality risk, while this effect was not significant in the inactive group. Jointly, the highest tea consumers who exercised the most exhibited the lowest mortality risk compared to non-tea drinkers who exercised the least. These findings underscore the potential benefits of regular tea consumption and PA in promoting longevity and reducing premature death risks.
Mechanism of electrochemical discharge machining on film cooling holes with thermal barrier coatings
Authors: Zhang Ajian , Chen Xiaokang , Ma Tongyi , Zhu Qianlong , Zhou Jianping , Wang Bingbing , Ma Ning , Liu Hai , Chen Yulong 
Published: July 2024

Abstract

This paper investigates the electrochemical discharge machining (ECDM) mechanism to address the susceptibility of coatings to cracking, delamination, microcracks, and recast layers during the machining of film cooling holes with thermal barrier coatings. By using NaOH as the working fluid and enhancing chip removal through electrode rotation, this study investigates the machining state transition laws, material removal mechanisms, and post-processing workpiece surface integrity in ECDM of film cooling holes with thermal barrier coatings. The results indicate that only the electrochemical discharge effect is active during the ECDM of the ceramic layer, with material removal primarily dependent on rapid thermal cycling and electrochemical discharge. In contrast, for metal substrates, both electrochemical and electrical discharge machining occur, involving electrochemical and thermal effects. This study provides valuable insights for the efficient and high-quality production of film cooling holes with thermal barrier coatings.
Enhancing Water Deficit Stress Tolerance in Wheat: Synergistic Effects of Silicon Nanoparticles and Plant Growth-Promoting Bacteria
Authors: Davoudi Faezeh , Jalali Mahboobeh , Valizadeh-Rad Keyvan , Etesami Hasan 
Published: July 2024

Abstract

Water deficit stress significantly reduces grain yield in bread wheat, requiring improved tolerance in cultivars. Despite recent breeding advancements, enhancing tolerance remains crucial. Plant growth-promoting bacteria (PGPB) and silicon (Si) independently boost drought resistance through different mechanisms, but their combined effects are understudied. This research explored the combined impacts of silicon dioxide nanoparticles (SiO2 NPs) and native PGPB on wheat's morphophysiological and nutritional responses under water deficit stress. The study tested various SiO2 NP concentrations (control, soil application of 100 and 200 mg/kg, and foliar application of 200 mg/kg) and PGPB strains (no bacterium, Pseudomonas fluorescens p-187, and Pseudomonas putida p-168). Results showed that SiO2 NPs significantly improved wheat tolerance to water stress, increasing shoot dry weight by 4.40 g/pot with 100 mg/kg Si-NPs and Pseudomonas fluorescens p-187 compared to the control, and root dry weight by 1.05 g/pot with foliar application of 200 mg/kg Si-NPs and Pseudomonas putida p-168. SiO2 NPs and PGPB also boosted N, P, K, and Si concentrations in wheat shoots, reduced malondialdehyde content, and increased superoxide dismutase and glutathione peroxidase activities. The best performance was achieved with 200 mg/kg Si-NPs and Pseudomonas fluorescens p-187. The study confirms that combining Si sources with PGPB effectively enhances wheat's drought tolerance. This synergistic approach offers an environmentally sustainable strategy to bolster crop resilience against water deficit stress, ensuring better wheat yield in drought-prone conditions.
Superiority Of Suture Endobutton Augmentation In Type 2b Clavicle Fractures Fixatıon Using Locking Plate
Authors: Yağar Hilal , Çağlar Ceyhun , Asfuroğlu Zeynel Mert , Aydın Murat 
Published: July 2024

Abstract

Purpose
Instability in distal clavicle fractures with impaired integrity of the CC ligament poses a serious risk for nonunion, necessitating surgical intervention. Despite a consensus on the need for surgery in cases of unstable distal clavicle fractures, various surgical techniques are available. Aim of this study is to evaluate the radiological and functional outcomes of CC augmentation using the suture endobutton technique for Neer type 2b clavicle fractures.
Methods
42 patients who met the criteria for this retrospective study divided into two groups; Group 1 (locking plate with CC augmentation) and Group 2 (locking plate without CC augmentation). Demographic data, the Constant–Murley scores(CS), union time, range of motion, complications, and implant failures during the follow-up period were recorded.
Results
13 (31.0%) patients were female and 29 (69.0%) were male.The mean age was 40.5 ± 11.5 years. Significant differences were found in union time (week) (t(40) = − 2.11, p = 0.04) and the 6th-month CS (t(40) = 4.19, P = 0.01). No significant difference was observed in postoperative complications between the groups (p > 0.05).
Conclusion
CC augmentation with a suture endobutton in type 2b distal clavicle fractures, resulted in more favorable short-term functional and radiological outcomes.
Multi-omics integration and immune profiling identify possible causal networks leading to uterine microbiome dysbiosis in dairy cows that develop metritis
Authors: Casaro S. , Prim J. G. , Gonzalez T. D. , Cunha F. , Silva A. C. M. , Yu H. , Bisinotto R. S. , Chebel R. C. , Santos J. E. P. , Nelson C. D. , Jeon S. J. , Bicalho R. C. , Driver J. P. , Galvão Klibs N. 
Published: July 2024

Abstract

Background
Cows that develop metritis experience dysbiosis of their uterine microbiome, where opportunistic pathogens overtake uterine commensals. Whether opportunistic pathogens thrive and cause metritis may be determined by how efficiently the immune system responds to these pathogens. Nonetheless, periparturient cows experience immune dysregulation, which seems to be intensified by prepartum obesity and lipid mobilization Herein, Bayesian networks were applied to investigate the directional correlations between prepartum body weight (BW), BW loss, pre- and postpartum systemic immune profiling and plasma metabolome, and postpartum uterine metabolome and microbiome.
Results
According to the directionality network, greater prepartum BW led to greater BW loss, which led to an increase in plasma fatty acids at parturition, indicating that heavier cows were in lower energy balance than lighter cows. Greater prepartum BW also led to an increase in prepartum systemic cellular death, which led to an increase in systemic inflammation, immune activation, and metabolomic changes associated with oxidative stress prepartum and at parturition, which indicates a positive directional correlation between BW and systemic inflammation. These changes led to an increase in polymorphonuclear cell extravasation postpartum, which led to an increase in uterine metabolomic changes associated with tissue damage, suggesting that excessive polymorphonuclear cell migration to the uterus leads to excessive endometrial damage. These changes led to an increase in pathogenic bacteria in cows that developed metritis, suggesting that excessive tissue damage may disrupt physical barriers or increase substrate availability for bacterial growth.
Conclusions
This work provides robust mechanistic hypotheses for how prepartum body weight impacts peripartum immune and metabolic profiles, leading to uterine opportunistic pathogens overgrowth and metritis development.
A generic detailed multibody thoracic spine and ribcage model
Authors: Shayestehpour Hamed , Tørholm Søren , Damsgaard Michael , Lund Morten , Wong Christian , Rasmussen John 
Published: July 2024

Abstract

A reliable and comprehensive multibody musculoskeletal model of the thoracic spine and ribcage can offer valuable insight into the biomechanics behind healthy and curved spines. In this study, we developed a generic rigid-body thoracic spine and ribcage model, which is kinematically determinate and controlled by spine posture. A newly devised averaging constraint was implemented to model the individual ribs and the sternum kinematics. The rib motion validation confirmed adjacent ribs’ movement against measured data in different tasks. We simulated 39 adolescent idiopathic scoliosis subjects aged 7–17 years with the average (SD) Cobb angle of 15.2 (8.4) deg. The average errors of multiple scoliosis metrics were less than 4 degrees for angle parameters, 5 mm for displacement parameters, and 3 percent for the ratio parameter. This generic model is simple to use and can simulate a large range-of-motion of daily living activities (e.g., spinal articulation and breathing) and capture pathological deformities conforming to experimentally observed deformations with proper accuracy. It is available to the public in a GitHub repository and will be made available also in the AnyBody Managed Model Repository.
High-speed 4D computed tomography for uncovering the dynamics of oil uptake in deep-fried food products
Authors: Verboven Pieter , Verma Ujjwal , Riley Isabella , Lukic Bratislav , Broche Ludovic , Delcour Jan , Nicolaï Bart 
Published: July 2024

Abstract

Oil acts as a high-temperature heating medium while also contributing to the organoleptic properties in energy dense deep-fried foods. The amount of oil absorbed is associated with the rapid structural deformation of food during deep-frying, creating pathways for oil to enter the internal microstructure. Here, we describe a 4D imaging system (three spatial dimensions and time) that uses fast synchrotron radiation tomography for in-situ visualization of the highly dynamic deep-frying and post-frying cooling processes. We use dynamic imaging and 3D quantification to show that the continuously evolving connectivity of the heterogeneous porous microstructure in a wheat flour-based dough is altered by the deformations induced during and after deep-frying. The resulting pore network integrity, more than porosity, significantly impacts the rate of oil uptake and its distribution. The findings also suggest that a two-stage deep-frying operation at different temperatures can help reduce oil content while achieving a desired crust.
ArmanEmo: A Persian Dataset for Text-based Emotion Detection
Authors: Mirzaee Hossein , Peymanfard Javad , Moshtaghin Hamid Habibzadeh , Zeinali Hossein 
Published: July 2024

Abstract

With the recent proliferation of open textual data on social media platforms, Emotion Detection (ED) from Text has received more attention over the past years. It has many applications, especially for businesses and online service providers, where emotion detection techniques can help them make informed commercial decisions by analyzing customers/users' feelings towards their products and services. In this study, we introduce ArmanEmo, a human-labeled emotion dataset of more than 7000 Persian sentences labeled for seven categories. The dataset has been collected from different resources, including Twitter, Instagram, and Digikala comments. Labels are based on Ekman's six basic emotions (Anger, Fear, Happiness, Hatred, Sadness, Wonder) and another category (Other) to consider any other emotion not included in Ekman's model. Along with the dataset, we have provided several baseline models for emotion classification focusing on the state-of-the-art transformer-based language models. Our best model achieves a macro-averaged F1 score of 75.39 percent across our test dataset. Moreover, we also conduct transfer learning experiments to compare our proposed dataset's generalization against other Persian emotion datasets. Results of these experiments suggest that our dataset has superior generalizability among the existing Persian emotion datasets. ArmanEmo is publicly available for non-commercial use at \url{https://github.com/Arman-Rayan-Sharif/arman-text-emotion}.
Paternal Preconception Donepezil Exposure Enhances Learning in Offspring
Authors: Fan Guangyuan , Pan Tao , Ji Xingyu , Jiang Changyou , Wang Feifei , Liu Xing , Ma Lan , Le Qiumin 
Published: July 2024

Abstract

Background
Recent research has indicated that parental use of central nervous system-targeting medications during periconceptional periods may affect offspring across various developmental and behavioral domains. The present study sought to investigate the potential influence of paternal use of donepezil, a specific reversible central acetylcholinesterase inhibitor that activates the cholinergic system to promote cognition, on offspring.
Results
In this study, male rats were bred after 21 days of oral donepezil administration at a dose of 4 mg/kg to generate F1 offspring. Both male and female F₁ offspring displayed enhanced performance in learning and short-term memory tests, including novel object recognition, Y maze, and operant learning. Transcriptomic analysis revealed notable alterations in genes associated with the extracellular matrix in the hippocampal tissue of the F1 generation. Integration with genes related to intelligence identified potential core genes that may be involved in the observed behavioral enhancements.
Conclusions
These findings indicate that prolonged paternal exposure to donepezil may enhance the learning and memory abilities of offspring, possibly by targeting nonneural, extracellular regions. Further research is required to fully elucidate any potential transgenerational effects.
CCD-YOLO: An Accurate and Fast Algorithm for Steel Surface Defect Detection
Authors: Wang Dingran , Wang Hong 
Published: July 2024

Abstract

A variety of surface defects can be created in steel during manufacturing and transportation, which can reduce the strength of the steel and shorten the service life of the workpiece. Therefore, surface defect detection is a key link to ensure the quality of industrial production. However, traditional surface defect detection methods have the disadvantages of low accuracy and slow speed. Therefore, we propose a steel surface defect detection model CCD-YOLO based on YOLOv5. Firstly, we replace the C3 module in the backbone of YOLOv5 with the C2f module to obtain more gradient flow information while maintaining lightweight. Secondly, we insert a flexible and lightweight CA attention mechanism into the backbone to help the model accurately locate and identify objects of interest. Finally, we use decoupled heads to separate the regression and classification tasks, which improves detection accuracy. Finally, a large number of experimental results show that CCD-YOLO achieves an accuracy of 72.9% mAP on the NEU-DET dataset, which is 4.3% better than YOLOv5 and 1.1% higher than YOLOv8. The model has good comprehensive performance in steel surface defect detection.
AuCePt porous hollow cascade nanozymes targeted delivery of disulfiram for alleviating hepatic insulin resistance
Authors: Shen Huawei , Fu Yafei , Liu Feifei , Zhang Wanliang , Yuan Yin , Yang Gangyi , Yang Mengliu , Li Ling 
Published: July 2024

Abstract

As the pathophysiological basis of type 2 diabetes mellitus (T2DM), insulin resistance (IR) is closely related to oxidative stress (OS) and inflammation, while nanozymes have a good therapeutic effect on inflammation and OS by scavenging reactive oxygen species (ROS). Hence, AuCePt porous hollow cascade nanozymes (AuCePt PHNs) are designed by integrating the dominant enzymatic activities of three metallic materials, which exhibit superior superoxide dismutase/catalase-like activities, and high drug loading capacity. In vitro experiments proved that AuCePt PHNs can ultra-efficiently scavenge endogenous and exogenous ROS. Moreover, AuCePt PHNs modified with lactobionic acid (LA) and loaded with disulfiram (DSF), named as AuCePt PHNs-LA@DSF, can significantly improve glucose uptake and glycogen synthesis in IR hepatocytes by regulating the insulin signaling pathways (IRS-1/AKT) and gluconeogenesis signaling pathways (FOXO-1/PEPCK). Intravenous administration of AuCePt PHNs-LA@DSF not only showed high liver targeting efficiency, but also reduced body weight and blood glucose and improved IR and lipid accumulation in high-fat diet-induced obese mice and diabetic ob/ob mice. This research elucidates the intrinsic activity of AuCePt PHNs for cascade scavenging of ROS, and reveals the potential effect of AuCePt PHNs-LA@DSF in T2DM treatment.
Machine learning-based diagnostic prediction of minimal change disease: model development study
Authors: Noda Ryunosuke , Ichikawa Daisuke , Shibagaki Yugo 
Published: July 2024

Abstract

Minimal change disease (MCD) is a common cause of nephrotic syndrome. Due to its rapid progression, early detection is essential; however, definitive diagnosis requires invasive kidney biopsy. This study aims to develop non-invasive predictive models for diagnosing MCD by machine learning. We retrospectively collected data on demographic characteristics, blood tests, and urine tests from patients with nephrotic syndrome who underwent kidney biopsy. We applied four machine learning algorithms—TabPFN, LightGBM, Random Forest, and Artificial Neural Network—and logistic regression. We compared their performance using stratified 5-repeated 5-fold cross-validation for the area under the receiver operating characteristic curve (AUROC) and the area under the precision-recall curve (AUPRC). Variable importance was evaluated using the SHapley Additive exPlanations (SHAP) method. A total of 248 patients were included, with 82 cases (33%) were diagnosed with MCD. TabPFN demonstrated the best performance with an AUROC of 0.915 (95% CI 0.896–0.932) and an AUPRC of 0.840 (95% CI 0.807–0.872). The SHAP methods identified C3, total cholesterol, and urine red blood cells as key predictors for TabPFN, consistent with previous reports. Machine learning models could be valuable non-invasive diagnostic tools for MCD.
Performance Analysis of Enhanced Downlink Transmission in MIMO-NOMA Networks under Rician Fading Channels
Authors: Ahmmed Rubab , Kabir Md. Humayun , Tarfi Kasira-Tut , Kabir Md. Alomgir 
Published: July 2024

Abstract

This paper investigates downlink transmission in multiple-input multiple-output (MIMO) non-orthogonal multiple access (NOMA) networks under Rician fading channels. An analytical framework for user signal-to-interference-plus-noise ratio (SINR) and bit error rate (BER) is developed. Numerical results are given to show that the outage probability is significantly decreased with higher transmit power, especially for cell-edge users, since NOMA is a good power allocation scheme. Furthermore, at higher SINR, the Bit-Error-Rate (BER) is reduced for all users, though such a user located far from the transmitter sees improved performance. This shows that MIMO NOMA presents an inter-user interference mitigation technique, and the closer users will benefit most. Overall, in comparison with SIMO NOMA, the MIMO NOMA will have better performance in either outage or BER reduction because of multi-antenna.