bluuebunny/crossref_metadata_2025_split huggingface dataset:
Development of Crosspoint Modification for Isogeometric Analysis in AI
Authors: Verma Deepak 
Published: July 2023

Isogeometric Analysis (IGA) has emerged as a powerful computational method that seamlessly integrates computer-aided design (CAD) and finite element analysis (FEA). It provides an innovative approach for solving complex engineering problems by employing the same basis functions used in CAD representations, such as Non-Uniform Rational B-Splines (NURBS), to discretize the computational domain. However, one of the challenges in IGA is the occurrence of crosspoints, which are regions where multiple NURBS patches meet. This presents a novel development of a crosspoint modification technique for Isogeometric Analysis, leveraging the capabilities of Artificial Intelligence (AI) algorithms. The aim is to overcome the limitations posed by crosspoints and enhance the accuracy and efficiency of IGA simulations. It utilizes AI-based methods, such as deep learning and pattern recognition, to identify and modify the crosspoint regions in the NURBS-based representation. The AI model is trained on a large dataset of known crosspoint configurations and their corresponding modifications, enabling it to learn the underlying patterns and relationships between the geometry and the required modifications. This trained model is then employed to automatically identify and modify crosspoints in new IGA problems, streamlining the pre-processing stage and reducing human intervention. The crosspoint modification technique incorporates various strategies to ensure geometric continuity and smooth transition across the modified crosspoint regions. These strategies include local refinement of the NURBS control points, adaptively adjusting the degrees of the adjacent patches, and optimizing the blending functions in the crosspoint vicinity. Several numerical experiments and comparative studies are conducted. The results demonstrate that the crosspoint modification using AI significantly improves the accuracy of the IGA simulations, particularly in regions affected by crosspoints. Moreover, the computational efficiency is enhanced as the automated modification reduces the manual effort required for crosspoint handling.
This research contributes to the advancement of Isogeometric Analysis by introducing a novel AI-based crosspoint modification technique. By effectively addressing the challenges associated with crosspoints, the proposed method enhances the accuracy and efficiency of IGA simulations. The integration of AI algorithms with IGA holds great potential for future applications in various engineering disciplines, including structural analysis, fluid dynamics, and electromagnetics.
How is microbial biomass carbon affected by oil-pollution in soils? An alternative approach to its measure
Authors: Moradi Shokufeh , Sarikhani Mohammad Reza , Ale-Agha Ali Beheshti , Hasanpur Karim , Shiri Jalal 
Published: July 2023

Abstract
Oil pollution is one of the most critical environmental pollutions affecting soil's biological, physical, and chemical properties. There are several methods to measure MBC, the most important of which are chloroform fumigation extraction (CFE), chloroform fumigation incubation (CFI), and experimental methods based on substrate-induced respiration (SIR). Due to the presence of high oil content in the oil-polluted soil samples and high content of organic carbon (OC), the application of the CFE method has some limitations because tracking minor changes of MBC in a huge background of OC is not possible. The effect of three levels of oil pollution (L: low, M: moderate, and H: high) on MBC measured by CFI (MBC-CFI) and SIR (MBC-SIR) was investigated through an incubation experiment. Hence, 120 oil-contaminated soil samples were gathered from four selected locations of polluted sites in Naft-Shahr, Kermanshah, Iran. Four experimental formulas including MBC = 16.18×SIR + 5.11 (Eq. 1), MBC = SIR×30 (Eq. 2), MBC = SIR×25.3 (Eq. 3), and MBC = 40.04×SIR + 0.37 (Eq. 4) to estimate the amount of MBC-SIR were used. The results showed that there is a positive and significant correlation between two methods used in this study (r = 0.91, P < 0.01). In both methods, the MBC obtained in H soils was higher than in L and M soils. The values of MBC-CFI data ranged from 264.685 in L soils to 419.459 mgC 100g− 1 in H soils. Among the four used formulas in this study, the lowest amount of RMSE and SI was obtained for Eq. 4. The MBC-SIR measured by Eq. 4 ranged from 290.224 mgC 100g− 1 in L soils to 478.107 mgC 100g− 1 in H soils. According to this study's results, experimental methods based on SIR, especially Eq. 4 can also be used to estimate the amount of MBC in oil-contaminated soils. Moreover, in this study, multiple linear regression analysis and principal components analysis (PCA) was performed on data to get insight into the relation of bio-physical-chemical properties of soil, especially with MBC.
Effect of opioid-free anaesthesia with lidocaine on post-induction haemodynamic stability
Authors: Hu Yang , Cha Ning , Zhu Guo , Long Xiang , Jiang Jing , Zhang Qing , Qin Guan , GONG Yuan 
Published: July 2023

Abstract
BACKGROUNDː Most studies on opioid-free anaesthesia have focused on postoperative pain control and opioid consumption, with less attention paid to haemodynamic stability. We aimed to determine whether opioid-free anaesthesia with lidocaine would provide better haemodynamic stability than general anaesthesia.
METHODSː This single-centre, parallel-group, randomised, double-blind, controlled trial included patients aged 18–50 years (American Society of Anesthesiologists Physical Status classes I–II) who underwent elective hysteroscopy. Patients were randomised into group S (general anaesthesia with sufentanil) or group L (opioid-free anaesthesia with lidocaine). All patients underwent the same anaesthetic induction and maintenance protocols. The primary outcome was the incidence of hypotension. Secondary outcomes included changes in the mean arterial pressure at different timepoints after anaesthesia induction, the incidence of bradycardia, and the average dose of rescue metaraminol. Intraoperative cardiac and respiratory events were recorded as safety events.
RESULTSː Opioid-free anaesthesia with lidocaine provided better post-induction haemodynamic stability than general anaesthesia. The incidence of hypotension in groups L and S was 15.56% (7/45) and 55.56% (25/45), respectively, and significant differences were observed in the changes in mean arterial pressure at T1, T2, T3, T4, and T5. The average dose of rescue metaraminol significantly differed between groups [mean (SD), 1.02 (2.96) mg vs. 4.21 (5.64) mg, P = 0.001]. The incidence of bradycardia significantly differed between groups [0% (0/45) vs. 44.44% (20/45), P < 0.001). No severe adverse effects were observed in any group.
CONCLUSIONː Opioid-free anaesthesia with lidocaine provides better post-induction haemodynamic stability than general anaesthesia, without any major adverse events.
TRIAL REGISTRATION: The trial was registered on January 15, 2022 in the Chinese Clinical Trial Registry (http://www.chictr.org.cn/showprojen.aspx?proj=149386), registration number ChiCTR2200055623.(15/01/2022)
Gedong-Dalem” pickles: the ethnogastronomy of the peranakan Chinese, in Bogor, West Java, Indonesia
Authors: Nikmatullah Muhamad , Rahayu Mulyati , Kiem Ary Prihardhyanto , Peniwidiyanti Peniwidiyanti , Kalima Titi ,   Oryzanti1 Parwa, Sujarwo Wawan 
Published: July 2023

Abstract

Indonesia has a variety of traditional culinary delights from the results of mixing between tribes in Indonesia, as well as with immigrants such as the Chinese. Bogor is one of the cities in West Java Province, Indonesia which is famous for its various traditional culinary influences from Chinese immigrants. Traditional culinary is a variety of foods related to an area and passed through generations, one of which is the Bogor typical Gedong-Dalem pickles. However, nowadays the original Gedong-Dalem pickles are barely found, because it is hard to get the ingredients. This can influence its original taste. In addition, competition in the modern culinary business is highly competitive, so traditional culinary culture can be pushed aside until it is extinct. This study aims to show the ethnogastronomic data and uniqueness of the Gedong-Dalem pickles in Bogor area, Indonesia. Data collection was carried out through open-ended semi-structured and unstructured interviews with respondents and key informants using a questionnaire and observation. Based on the results of the interviews, the Gedong-Dalem pickle is a culinary made from a mixture of various species of fruits or vegetables which was originally sold in Gedong-Dalem by the Chinese in Bogor. The ethnogastronomy of Gedong-Dalem pickles is the key to harmony between Chinese and Indonesian mixed ancestry. Ethnogastronomically, it is a culinary origin from Indonesia, not entirely from China. In other words, it is an authentic Indonesian cuisine.
miR-214-3p promotes the pathogenesis of Parkinson's disease by inhibiting autophagy
Authors: Dong Hui , Yan Jiahui , Huang Ping , Wang Xinyu , Zhang Ru , Zhang Caiyun , Wang Wenhui , Qian Wenxian , Zhou Jin , Zhao Yunli , Gao Jinghan , Zhang Mengmeng , Ma Xiuchang , Wang Zhizhong , Yi Changhua , Chen Wei 
Published: July 2023

Abstract

Parkinson's disease (PD) is the second most common neurodegenerative disease in the world. To date, there is still no effective treatment regimen for PD, which has prodromal stage, de novo stage (early stage) and advanced stage. Early diagnosis and intervention are paramount to prevent progression of this disease. We previously found that miR-214-3p was significantly up-regulated in the serums of prodromal and early PD patients. In this study, we confirmed that miR-214-3p was up-regulated in both MPP+-induced PD cell model and MPTP-induced PD mouse. Overexpression of miR-214-3p inhibited the cell activity and autophagy, and promoted apoptosis of dopaminergic neurons in vitro and in vivo, and aggravated the disease symptoms of animal model. Knockdown of miR-214-3p was able to restore the inhibition of autophagy and cell viability in both cell and animal model. Overexpression of autophagy-related gene 3 (ATG3) partially reversed the inhibition of autophagy and cell viability caused by overexpression of miR-214-3p in PD cell model. ATG3 is a member of the autophagy-related gene family and autophagy is involved in the pathological process of PD. BiBiServ2 website prediction showed that miR-214-3p could directly target ATG3. The western blot results showed that the protein expression of ATG3 could be down-regulated by miR-214-3p. Therefore, miR-214-3p may inhibit autophagy and activity of dopaminergic neurons and promote apoptosis by regulating the expression of ATG3. Our study provides a putative biomarkers and potential drug targets for early PD, which has important theoretical significance and clinical value.
Prognostic value of metabolic parameters of baseline PET/CT in patients with double expression types of diffuse large B-cell lymphoma
Authors: Zhao Jincheng , Teng Yue , Jiang Chong , Chen Man , Xu Jingyan 
Published: July 2023

Abstract
Objectives To explore the value of baseline PET/CT parameters for predicting prognosis in patients with double expression lymphoma (DEL). Methods We retrospectively analyzed the clinical and [18F]FDG PET/CT imaging data of 118 patients diagnosed with DLBCL by pathological examination at two independent medical centers from October 2015 to September 2022. We used receiver operating characteristic (ROC) curve analysis to determine the optimal threshold for the maximum standardized uptake value (SUVmax), the total metabolic tumor volume (TMTV), and the total lesion glycolysis (TLG) in predicting overall survival (OS) rate. Kaplan-Meier survival analysis, univariate and multivariate analyses were performed to predict OS rate, construct a survival prediction model, plot a calibration curve for the model, a time-dependent area under the ROC curve (tdAUC), and a decision curve analysis (DCA) curve, and calculate the C-index of the model. Results The area under the curve (AUC) of the ROC curve for TMTV was 0.705, with corresponding cutoff values of 230.9 cm3. In multivariate analysis, Eastern Cooperative Oncology Group performance status (ECOG PS) (HR=3.989, P=0.002) and TMTV (HR=4.042, P<0.008) were identified as independent predictors of OS. A combined model of ECOG PS and TMTV was found to be superior to IPI in predicting OS. Conclusions TMTV, a metabolic index, and ECOG PS, a clinical risk factor, are independent predictors of OS in patients with DEL, and their combination can provide more accurate prognostic predictions.
The metabolic functional feature of gut microbiota in Mongolian patients with type 2 diabetes
Authors: Liu Yanchao , Gao Yumin , Zhao Lingyan , Pang Hui , Jiao Yang , Wang Mingxiao 
Published: July 2023

Abstract

The accumulating evidence substantiates the indispensable role of gut microbiota in modulating the pathogenesis of type 2 diabetes. Uncovering the intricacies of the mechanism is imperative in aiding disease control efforts. Revealing key bacterial species, their metabolites and/or metabolic pathways from the vast array of gut microorganisms can significantly contribute to precise treatment of the disease. With a high prevalence of type 2 diabetes in Inner Mongolia, China, the Mongolian population was selected as subjects to investigate the relationship between gut microbiota and the disease. We recruited Volunteers of Mongolian with type 2 diabetes and control group and detected their fecal samples by metagenomic analysis and untargeted metabolomics analysis. The findings suggest that Firmicutes and Bacteroidetes phyla are the predominant gut microorganisms that exert significant influence on the pathogenesis of type 2 diabetes in Mongolian population. In the disease group, despite an increase in the quantity of most gut microbial metabolic enzymes, there was a concomitant weakening of gut metabolic function, suggesting that the gut microbiota may be in a compensatory state during the disease stage. The beta-Tocotrienol may serve as a pivotal gut metabolite produced by gut microorganisms and a potential biomarker for type 2 disease. The metabolic pathway of Ubiquinone and other terpenoid-quinone biosynthesis could be the crucial mechanism through which the gut microbiota regulates type 2 diabetes. Additionally, certain Clostridium gut species may play a pivotal role in the progression of the disease.
Nanobiopsy investigation of the subcellular mtDNA heteroplasmy in human tissues
Authors: Bury Alexander Gerard , Vincent Amy E. , Pyle Angela , Actis Paolo , Hudson Gavin 
Published: July 2023

Abstract

Mitochondrial function is critical to continued cellular vitality and is an important contributor to a growing number of human diseases. Mitochondrial dysfunction is typically heterogeneous, mediated through the clonal expansion of mitochondrial DNA (mtDNA) variants in a subset of cells in a given tissue. To date, our understanding of the dynamics of clonal expansion of mtDNA variants has been technically limited to the single cell-level. Here, we report the use of nanobiopsy for subcellular sampling from human tissue, combined with next-generation sequencing to assess subcellular mtDNA mutation load in human tissue from mitochondrial disease patients. The ability to map mitochondrial mutation loads within individual cells of diseased tissue samples will further our understanding of mitochondrial genetic diseases.
Comprehensive Analysis of Expression and prognostic values of Annexin family genes in breast cancer
Authors: Fathi Afshin , Valizadeh Mehdi , Mansoori Behzad , Soozangar Narges , Hosseini-Asl Saied 
Published: July 2023

Abstract
Background
Breast cancer is the most commonly diagnosed cancer among women and remains the leading cause of cancer-related deaths worldwide. Annexins are a family of calcium-binding proteins that have been linked to cancer progression and metastasis, but their role in breast cancer remains uncertain.
Methods
In this study, we investigated the mRNA expression, clinical parameters, genetic alterations, and prognostic value of all ANXA members in breast cancer using multiple online open-access databases including ONCOMINE, UALCAN, bc-GenExMiner, Kaplan-Meier plotter, THPA (The Human Protein Atlas), Metascape, GeneMANIA, TIMER, STRING, and Enrichr.
Results
Our findings revealed that the expression of ANXA1/2/3/5/6/8/11 was significantly lower, while ANXA9 was upregulated in breast cancer tissues compared to normal tissues. Furthermore, we found that elevated expression of ANXA6/7/9/11 was linked to favorable overall survival, while ANXA8/9/10/13 was associated with longer relapse-free survival. We also discovered that 48% of BC patients had genetic mutations of ANXA family members. Finally, we found significant correlations among the expression of different annexin family members and the infiltration of six types of immune cells in the tumor microenvironment.
Conclusions
Our results highlight the significant role of ANXAs in breast cancer progression and prognosis. ANXAs could serve as potential therapeutic targets and prognostic biomarkers in breast cancer. These findings may provide valuable insights into the development of more effective treatments for breast cancer patients.
Uterine Artery Doppler Ultrasound for Predicting Preeclampsia During Pregnancy: A Meta-analysis
Authors: Cao Li , He Biyuan , Zhou Yuqing , Chen Tiantian , Gao Yihui , Yao Bingyi 
Published: July 2023

Abstract
Background
Accurate prediction of preeclampsia can improve maternal outcomes. However, the utility of uterine artery Doppler imaging in the prediction of preeclampsia remains unclear. To investigate the accuracy of uterine artery Doppler ultrasound parameters in predicting preeclampsia during pregnancy.
Methods
We searched databases for studies using uterine artery Doppler imaging to predict preeclampsia from inception to March 23, 2023. The main outcome was preeclampsia. We assessed study bias using QUADAS-2.
Results
Of 40 studies, 19 used the pulsatility index (PI) to predict preeclampsia, with sensitivity 0.05 (95% CI 0.02–0.08) and specificity 0.44 (95% CI 0.28–0.61). Nine studies used the resistance index (RI), with sensitivity 0.13 (95% CI 0.05–0.27) and specificity 0.31 (95% CI 0.07–0.63). Three studies used the systolic/diastolic (S/D) ratio, with sensitivity 0.50 (95% CI 0.30–0.67) and specificity 0.86 (95% CI 0.68–0.95). Nine studies used notching, with sensitivity 0.20 (95% CI 0.09–0.35) and specificity 0.60 (95% CI 0.23–0.90).
Conclusions
Uterine artery Doppler parameters predicted preeclampsia differently. PI and RI had low sensitivity and specificity. S/D ratio had high sensitivity and specificity, useful for predicting preeclampsia. Notching had low sensitivity and high specificity. Uterine artery Doppler alone has limited use in predicting preeclampsia.
Distinctive Molecular and Metabolic Profiles of
Chemically Synthesized Psilocybin and Psychedelic Mushroom Extract
Authors: Shahar Orr , Botvinnik Alexander , Shwartz Amit , Lerer Elad , Buko Alex , Hamid Ethan , Kahn Dani , Guralnick Miles , Blakolmer Karin , Wolf Gilly , Lerer Leonard , Lerer Bernard , Lifschytz Tzuri 
Published: July 2023

Abstract
Psilocybin, a naturally occurring, tryptamine alkaloid prodrug, is currently being investigated for the treatment of a range of psychiatric disorders. Preclinical reports suggest that the biological effects of psilocybin-containing mushroom extract or “full spectrum” (psychedelic) mushroom extract (PME), may differ from those of chemically synthesized psilocybin (PSIL). We compared the effects of PME to those of PSIL on the head twitch response (HTR), neuroplasticity-related synaptic proteins and frontal cortex metabolomic profiles in male C57Bl/6j mice. HTR measurement showed similar effects of PSIL and PME over 20 minutes. Brain specimens (frontal cortex, hippocampus, amygdala, striatum) were assayed for the synaptic proteins, GAP43, PSD95, synaptophysin and SV2A, using western blots. These proteins are indicators of synaptic plasticity. Three days after treatment, there was minimal increase in synaptic proteins. After 11 days, nested analysis of variance (ANOVA) showed a significant increase in each of the 4 proteins over all brain areas studied for PME versus vehicle control, while significant PSIL effects were observed only in the hippocampus and amygdala and were limited to PSD95 and SV2A. Metabolomic analyses of the pre-frontal cortex were performed by untargeted polar metabolomics utilizing capillary electrophoresis – Fourier transform mass spectrometry (CE-FTMS) and showed a differential metabolic separation between PME and vehicle groups. The purines guanosine, hypoxanthine and inosine, associated with oxidative stress and energy production pathways, showed a progressive decline from VEH to PSIL to PME. In conclusion, our synaptic protein findings suggest that PME has a more potent and prolonged effect on synaptic plasticity than PSIL. Our metabolomics data support a gradient of effects from inert vehicle via chemical psilocybin to PME further supporting differential effects. Further studies are needed to confirm and extend these findings and to identify the molecules that may be responsible for the enhanced effects of PME as compared to psilocybin alone.
Advancements in Deep Learning for Accurate Classification of Grape Leaves and Diagnosis of Grape Diseases
Authors: Kunduracıoğlu İsmail , Pacal Ishak 
Published: July 2023

Abstract
Plant diseases are a major factor contributing to agricultural production losses, necessitating effective disease detection and classification methods. Traditional manual approaches heavily rely on expert knowledge, which can introduce biases. However, advancements in computing and image processing have opened up possibilities for leveraging these technologies to assist non-experts in managing plant diseases. Particularly, deep learning techniques have shown remarkable success in assessing and classifying plant health based on digital images. This paper focuses on fine-tuning state-of-the-art pre-trained convolutional neural network (CNN) models and vision transformer models for the detection and diagnosis of grape leaves and diseases using digital images.The experiments were conducted using two datasets: PlantVillage, which encompasses four classes of grape diseases (Black Rot, Leaf Blight, Healthy, and Esca leaves), and Grapevine, which includes five classes for leaf recognition (Ak, Alaidris, Buzgulu, Dimnit, and Nazli). The results of the experiments, involving a total of 14 models based on six well-known CNN architectures and 17 models based on five widely recognized vision transformer architectures, demonstrated the capability of deep learning techniques in accurately distinguishing between grape diseases and recognizing grape leaves. Notably, four CNN models and four vision transformer models achieved 100% accuracy on the test data from the PlantVillage dataset, while one CNN model and one vision transformer model achieved 100% accuracy on the Grapevine dataset. Among the models tested, the Swinv2-Base model stood out by achieving 100% accuracy on both the PlantVillage and Grapevine datasets. The proposed deep learning-based approach is believed to have the potential to enhance crop productivity through early detection of grape diseases. Additionally, it is expected to offer a fresh perspective to the agricultural sector by providing insights into the characterization of various grape varieties.