bluuebunny/crossref_metadata_2025_split huggingface dataset:
Real-time imaging of traumatic brain injury using magnetic induction tomography
Authors: Jiao Yang , Zhang Tao , Fan Chao , Cao Haiyan , Chao Min , Han Liying , Zhang Weirui , Mao Lei , Liu Ruigang , Xu Canhua , Wang Liang 
Published: September 2022

Abstract
Early diagnosis of traumatic brain injury (TBI) is crucial for its prognosis; however, traditional computed tomography (CT) diagnostic methods rely on large medical devices with an associated lag time to receive results. In the present study, an improved magnetic induction tomography (MIT) data acquisition system was used to detect TBI in an animal model, distinguish the injury level, and locate the injured area. A pneumatically controlled cortical impactor was used to hammer the parietal lobe of anesthetized rabbits twice and three times under the same parameter mode to construct two different TBI rabbit models with significantly different degrees of damage (p = 0.0020). The MIT data acquisition system was used to record data and continuous monitoring for one hour without intervention. A target with increased conductivity is clearly observed in the reconstructed image. The position is relatively fixed and accurate, and the average positioning error of the image is 0.01372 m. The normalized mean reconstruction value of all images increased with time. The slope of the regression line of the normalized mean reconstruction value differed significantly between the two models (p < 0.0001). This indicates that in the animal model, MIT's unique features may facilitate the early diagnosis and localization of TBI and distinguish different degrees of injuries, thereby reducing the risk and mortality of associated complications.
A Detailed Study on Machine Learning Models with respect to wall-following Robots
Authors: Fatima Sana , Nasim syeda Faiza , Arif Fariha , Siddiqui Immad , Siddiqui Hamza , Arshad Maham 
Published: September 2022

Abstract
Machine learning, a class of artificial intelligence (AI), is widely used for big data analytics. It is now vastly used for accomplishing the Robot Navigation task by simply applying different algorithms. These algorithms convert user-generated commands into machine-understandable language. This is done by a wall-following control that is a robot’s movements in arbitrary directions while maintaining a specific distance from a particular wall. This paper illustrates two leading research contributions. Firstly, it discusses the significance of ML models in Robot navigations. Secondly, this paper comprises a detailed study and comparative analysis on the execution of different ML and Deep Learning algorithms using all three robot navigation formats (short, full, and simpler). In this paper, the evaluations and assessments of all the models are done by Monte-Carlo cross-validation.
Two Dimensional Model for Double-Sided Linear Permanent Magnet inner armature synchronous machine With Coreless Stator at on-Load in Different Patterns of Magnetization
Authors: Shirzad Ehsan 
Published: September 2022

Abstract
In this paper is presented a two-dimension analytical model for linear permanent magnet inner armature double sided synchronous motors (LPMIADSSMs). The flux density in all areas of the proposed machine is calculated based on the sub-domain method. According to this method the machine areas is divided into eleven sub-regions as first external, first mover, first PM, first air-gap, first winding, stator, second winding, second air gap, second PM, second external and second mover which sign as FE, FR, FP, FAG, FW, S, SW, SAG, SP, SE, SR. To find the flux density equations, it is mandatory to solve the extracted Maxwell equations and apply the boundary conditions between each two sub-regions, which lead to find the unknown coefficients for flux density in each sub-region. In addition, the influences of magnetization patterns, i.e. parallel, ideal Hal Bach, 2-segment Halbach and bar magnet in the shifting direction of the flux distribution is investigated. To validate the obtained results, the proposed model results are compared with those obtained from finite element method (FEM).
The 3D printed titanium mesh with high porosity has better repair effects than that with low porosity
Authors: Ma Rui , Liu Qian , Zhou Libo , Wang Lingxiao 
Published: September 2022

Abstract
Background
Most patients with insufficient bone mass suffer from severe horizontal or vertical bone defects in oral implant surgery. The purpose of this study was to compare the bone regeneration effects of titanium mesh with different porosity in the treatment of bone defects.
Methods
Nine beagle dogs were equally divided into three groups. Three months after the extraction of the first to fourth premolars of the mandible, three bone defects were randomly selected in the mandible. Bone particles and three kinds of 3D printed titanium nets with different porosity (low porosity group, 55%; medium porosity group, 62%; and high porosity group, 68%) were replanted in situ. Beagle dogs were killed 4, 8, and 12 weeks after surgery. Formalin fixed specimens were embedded in acrylic resin. The specimens were stained with micro CT and hard tissue grinding.
Results
microCT analysis showed that the trabecular thickness, trabecular number, and bone volume fraction of the high porosity group were higher than those of the other two groups. Moreover, the trabecular separation of the high porosity group decreased slightly at any time and was lower than that of the medium porosity and low porosity groups. Histological staining analysis showed that the trabecular number in the high porosity group was higher than in the other two groups at 8 and 12 weeks, and the bone volume fraction was higher than that in the other two groups at 12 weeks. Moreover, the TB. Thmp was higher than that of the LP group at 12 weeks and the trabecular separation was lower in the high porosity group at 4 and 8 weeks. The differences were statistically significant (P < 0.05).
Conclusions
3D printed titanium mesh with high porosity in a certain range may have more advantages than titanium mesh with low porosity in repairing large bone defects.
Treatment of Ischemic Stroke with Wenyang Huayu Formula: network pharmacology analysis and experimental validation
Authors: Ma Wei , Yang Yi-Bao , Xie Ting-Ting , Li Xiangling , Mo Xue-Ni 
Published: September 2022

Abstract
Objective
To explore the mechanism of Wenyang Huayu Formula in the treatment of ischemic stroke based on network pharmacology, molecular docking and experimental verification.
Methods
The chemical components and potential targets in Wenyang Huayu Formula were obtained by network pharmacology, and the targets related to the pathological process of cerebral ischemia-reperfusion were obtained, and the "drug-component-target-disease" was drawn by Cytoscape software,protein interaction network map was drawn based on STRING database.Gene enrichment analysis was using the Metascape database, and the Autodock vina software was using for molecular docking to determine the pathways and targets of Wenyang Huayu Formula, which were verified by vivo experiments in rats.
Results
277 drug targets and 3777 disease targets of Wenyang Huayu Formula were retrieved. The core components were Quercetin, kaempferol, luteolin, etc., and the core targets were AKT1, TP53, IL6, CASP3, IL1β, etc.Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analysis yielded 222 entries, involving Cellular senescence, TNF signaling pathway, Toll-like receptor signaling pathway, etc. Molecular docking results showed that the core component and the core protein had good binding energy. Vivo experiments results shown that: Stigmasterol, C-Homoerythrinan, luteolin and other components in Wenyang Huayu Formula may act on targets such as IL-6, IL-1β and TNF-α through the TLR4/NF-κB signaling pathway, and play roles in neural protection, reduce reperfusion injury, inhibit apoptosis, anti-inflammatory and other effects.
Conclusion
The mechanism of ischemic stroke by Wenyang Huayu Formula was the result of multi-component, multi-target and multi-channel interaction, and its mean mechanism may inhibit cell apoptosis, reduce inflammation and promote blood vessels through the TLR4/NF-κB signaling pathway.
Neuromuscular activation of the quadriceps femoris, including the vastus intermedius, during isokinetic knee extensions
Authors: Akima Hiroshi , Maeda Kazuhiro , Shima Norihiro 
Published: September 2022

Abstract
The purpose of this study was to compare the neuromuscular activation patterns of the individual muscles of the quadriceps femoris (QF), including the vastus intermedius (VI), during isokinetic concentric (CON) and eccentric (ECC) contractions. Thirteen healthy men performed maximum isokinetic CON and ECC knee extensions at angular velocities of 30, 90, and 120°/sec at knee joint angles from 80° to 180° (180° = full extension). The surface electromyographic (EMG) activities of the four individual muscles of the QF were recorded. The root mean squares of the EMG signals were normalized by the root mean square (nRMS) during CON contraction at 30°/sec. To investigate the nRMS changes, we classified the range of motion into four subcategories for each CON and ECC contraction. The nRMS of the VI was significantly higher in the flexed position during CON and ECC contractions at all velocities, and gradually decreased toward the extended positions regardless of the type of muscle contraction or angular velocity. These results suggest that the QF undergoes neuromuscular activation in a joint angle-dependent manner. In particular, the VI may contribute greatly during flexed contractions, independent of the type of contraction and angular velocity.
Effects of preoperative immunonutrition with surgical site infection after radical cystectomy and ileal conduit for muscle invasive bladder cancer
Authors: Takeuchi Hiroki , Nakata Wataru , Matsuse Miwa , Tsujimura Go , Tsujimoto Yuichi , Tsujihata Masao , Saijo Takeshi , Ryomoto Kayoko , Momoki Chika , Habu Daiki 
Published: September 2022

Abstract
Background
Radical cystectomy and ileal conduit have a high incidence of surgical site infection. In this study, we evaluated the effects of preoperative immunonutrition on its incidence following these procedures.
Methods
We retrospectively enrolled 86 patients who underwent radical cystectomy and ileal conduit at our hospital between 2014 October and 2021 July. They were sequentially divided into the Immunonutrition group (n = 43) and Control group (n = 43). Patients in the Immunonutrition group drank 4 packs of IMPACT (Nestle, Japan) per day for 5 days before surgery. IMPACT contains arginine and eicosapentaenoic acid. We compared levels of plasma arginine and eicosapentaenoic acid before and after surgery and the rate of surgical site infection between the groups. Factors related to surgical site infection were analyzed using univariate and multivariable logistic regression analysis.
Results
No statistically significant differences were observed in patient characteristics between the groups except for surgical operative method (p < 0.001) and transfusion (p = 0.009). Levels of plasma arginine and eicosapentaenoic acid were significantly increased the day before surgery in the immunonutrition group (p < 0.001). However, the levels of plasma arginine on the day after surgery did not vary significantly between the groups. The incidence of surgical site infection was significantly lower in the immunonutrition group (p = 0.014). Multivariate analyses showed a significant association of surgical site infection with immunonutrition (OR = 0.14, CI 0.03–0.72, p = 0.019) and with ASA classification (OR = 4.76, CI 1.23–18.40, p = 0.024).
Conclusions
Preoperative immunonutrition significantly reduced the incidence of surgical site infection following radical cystectomy and ileal conduit.
Apelin-13 Alleviates Hexavalent Chromium-Induced Myocardial Injury by Inhibiting ROS-mediated Oxidative Damage and Regulating Multiple Signals
Authors: Zhang Pu , Fu Rong , Liu Hengshu , Li Wang , Zhang Yingying , Song Na , Liu Hui , Yao Na , Xue Jianfeng , Yin Luhua , Chao Cui 
Published: September 2022

Abstract
Background
Hexavalent chromium (Cr (VI)) from environmental pollution shows severe toxicity towards human organs by causing oxidative damage. Apelin-13 may inhibit oxidative damage by blocking ROS accumulation and regulating multiple signals.
Methods
However, whether apelin-13 can attenuate Cr (VI)-induced toxicity has not been explored. Herein, the protective effect and molecular mechanism of apelin-13 against K2Cr2O7-induced cardiotoxicity in vitro and in vivo were evaluated.
Results
Apelin-13 significantly inhibited K2Cr2O7-induced H9c2 cytotoxicity and apoptosis, followed by the attenuated PARP cleavage and caspase activation. Further investigation revealed that apelin-13 co-treatment effectively suppressed K2Cr2O7-induced oxidative damage by inhibiting ROS accumulation. Moreover, apelin-13 co-treatment dramatically normalized MAPKs and PI3K/AKT pathways in K2Cr2O7-treated H9c2 cells. Importantly, apelin-13 administration in vivo effectively attenuated myocardial fibrosis, improved angiogenesis, and inhibited myocardial abnormal proliferation and apoptosis.
Conclusions
Ultimately, it alleviated K2Cr2O7-induced myocardial injury in rats.Taken together, our findings validated the strategy of the use of apelin-13 to effectively combat Cr (VI)-induced myocardial injury.
Electrochemical Detection of Some Water Soluble and Fat Soluble Vitamins by Using Bare Pencil Graphite Electrode
Authors: ÖZÇİL İHSAN EROL , SARUHAN TOLGA , ADUN PERİHAN 
Published: September 2022

Abstract
Vitamins are a group of organic compounds needed in small quantities by the body to perform its essential functions like growing, regulating metabolism and maintain a healty immune system. In recent years, substantial efforts have been focused on development of simplified, fast and cost-effective approaches for vitamin analysis. Aim of this study was electrochemical detection of some water and fat-soluble vitamins individualy and simultaneously by using bare pencil graphite electrode (PGE). Vitamins of C, B1, B6, B12, A, D3, and E were selected and electrochemically analyzed in pharmaceutical preparates. Simultaneous analysis of water-soluble vitamins by using DPV with PGE can be promising technique for the determination of vitamin C and B6 or vitamin B1, B12 and B6. In the case of fat-soluble vitamins, resolution between vitamin D3 and E was not satisfactory. However, vitamin A and D or vitamin A and E could be detected in a single run. Limit of detection of the selected vitamins were quite low (4-548 µg/ml).
MoMaf1 mediates vegetative growth, conidiogenesis, and pathogenicity in the rice blast fungus Magnaporthe oryzae
Authors: Qian Bin , Guo Lingyuan , Song Chi , Ji Hong 
Published: September 2022

Abstract
In eukaryotes, Maf1 is an essential and specific negative regulator of RNA polymerase (Pol) III. Pol III, which synthesizes transfer RNAs (tRNAs), is suppressed by Maf1 under conditions of nutrient starvation or environmental stress. Here, we identified M. oryzae MoMaf1, a homolog of ScMaf1 in budding yeast. A heterogeneous complementation assay revealed that MoMaf1 fully restored growth defects in the ΔScmaf1 mutant under SDS stress. Disrupting MoMAF1 elevated the tRNA content and increased sensitivity to cell wall agents. Moreover, the ΔMomaf1 mutant exhibited reduced vegetative growth, conidiogenesis, and pathogenicity. Interestingly, we found that MoMaf1 undergoes nuclear–cytoplasmic shuffling, through which MoMaf1 accumulates in nuclei under nutrient deficiency or upon the interaction of M. oryzae with rice. Therefore, this study helps to elucidate the pathogenic molecular mechanism of M. oryzae.
Restricted prognostic value of tumor size in gastric cancer: A retrospective cohort study based on SEER database
Authors: Xiao Jian , Shen Kuan , Fan Hao , Wang Gang , Liu Kanghui , Wang Yuanhang , Ma Xiang , Ni Peidong , Xu Zekuan , Yang Li 
Published: September 2022

Abstract
Background: Although tumor size (Ts) is regarded as the “T” stage of the Tumor-Node-Metastasis (TNM) staging system for many solid tumors, the prognostic impact in gastric cancer (GC) remains uncertain and conflicting.
Methods: We enrolled 6960 eligible cases from the Surveillance, Epidemiology, and End Results (SEER) database. The X-tile program was used to select the best cutoff value of Ts. Then the Kaplan-Meier method and the Cox proportional hazards model were applied to examine the efficacy of Ts on prognostic prediction for overall survival (OS) and gastric cancer-specific survival (GCSS). The presence of nonlinear association was determined by restricted cubic splines (RCS).
Results: Ts was divided into three groups: small size (≤ 2.5 cm), medium size (2.6-5.2 cm), and large size (≥ 5.3 cm). After adjusting by covariates, Ts larger than 2.5 cm predicted a worse prognosis; however, no survival difference on OS was suggested between the medium and large groups. Similarly, according to the adjusted RCS models, for tumors larger than 3.9 cm, large tumor size showed no significant differences on OS and GCSS with those smaller. However, the stratified analyses proposed the usage of the 3-way cut of Ts in prognostic prediction for patients with both inadequate lymphadenectomy and negative lymph node metastasis.
Conclusions: Ts as a prognostic predictor may not have good clinical applicability in GC. Otherwise, it is recommended for patients with both insufficient examination of lymph nodes and stage N0 disease.
Identification of Prognosis Signature and Analysis of the Immune Microenvironment in Gastric Cancer Based on ALKBH5
Authors: Ji Tiannan , Gao Xiaohui , Li Dan , Huai Siyuan , Chi Yajing , An Xian , Ji Wenyu , Yang Siming , Li Jianxiong 
Published: September 2022

Abstract
Background
N6-methyladenosine(m6A) RNA regulators play important roles in cancers, but the functions and mechanism of them have not been demonstrated clearly in gastric cancer (GC).
Methods
In this study, the GC samples with clinical information and RNA transcriptome were downloaded from TCGA database. The different expression genes were compared by absolute value and median ± standard deviation (sd). Samples with complete information were randomly divided into training dataset and test datasets. The differential expression genes (DEGs) between ALKBH5-low and ALKBH5-high subgroups were identified in training dataset and constructed a risk model by Cox and LASSO regression. The model was testified in test datasets, the overall survival (OS) was compared with Kaplan-Meier method and immune cells infiltration was calculated by CIBERSORT algorithm in the low-risk and high-risk subgroups based on the model.
Results
ALKBH5 was the only one regulator whose expression was lower in tumor samples than that in normal samples, there was the same phenomenon in GEO dataset GSE29998. Low expression of ALKBH5 led to poor overall survival of GC patients and seemed to be an independent protective factor. The model based on ALKBH5 regulated genes was validated in both two datasets (training/test) and it displayed potential capacity to predict clinical prognosis. Gene Ontology (GO) analysis implied that the DEGs were involved in immune response, CIBERSORT results indicated that ALKBH5 and its related genes could alter the immune microenvironment of GC.
Conclusions
In this study we found that ALKBH5 might be a suppressor of GC, ALKBH5 and its related genes were latent biomarkers and immunotherapy targets.
The anti-tumor effect of a novel agent MCL/ACT001 in pancreatic ductal adenocarcinoma
Authors: Yang Juan , Li Yin , Han Xiao , Pei Xiaolin , Lin Zhoujun , Li Chenggang 
Published: September 2022

Abstract
Purpose
Pancreatic ductal adenocarcinoma (PDAC) is a major challenge in cancer therapy, there are more than four hundred thousand deaths a year and the 5-year survival rate less than 10%. The incidence continues to rise. Treatment with classic drugs offers limited therapeutic benefits. The aim of this study was to investigate a new agent ACT001, the active metabolite is Micheliolide (MCL), study the mechanism and effect in vitro and in vivo against PDAC.
Methods
MTT assay, wound healing assay and flow cytometry were used to assess the effects of MCL/ACT001 in vitro. DCFH-DA assay was to assess ROS accumulation. Western blotting, Immunohistochemical staining and TUNEL assay were also conducted to determine the mechanisms. PANC-1-Luc cells and bioluminescent reporter imaging were used to assess anti-tumor effect of ACT001 using a GSC orthotopic xenograft model in vivo.
Results
MCL/ACT001 inhibited cell growth in PDAC in a dose-dependent manner significantly, induced cell apoptosis, cell migration and reactive oxygen species (ROS) accumulation in vitro. In vivo, ACT001 (400 mg/kg/day) inhibited PDAC tumor growth in orthotopic xenograft mice. We verified that EGFR, Akt were overexpressed in PDAC cells and patient tumors markedly. Mechanism investigations revealed that MCL exerted its anti-tumor activity via regulation of EGFR-Akt-Bim signaling pathway thus inducing Bim expression both in vitro and in vivo.
Conclusion
MCL/ACT001 is a highly promising agent in the treatment of PDAC patients.
SML-AutoML: A Smart Meta-Learning Automated Machine Learning Framework
Authors: Gomaa Ibrahim , Zidane Ali , Mokhtar Hoda M. O. , El-Tazi Neamat 
Published: September 2022

Abstract

Machine Learning (ML) and Automated Machine Learning (Auto-ML) had attracted more attention and interest in industrial applications in recent years. Machine learning pipeline includes repetitive tasks such as data pre-processing, feature engineering, model selection and hyper-parameter optimization. Building a machine learning model requires extensive time for development, stress-testing, and multiple experiments. Besides, building a model with a small search space of pipeline steps with multiple algorithms and hyper-parameters takes hours. Hence, Auto-ML has been widely adapted to save time and efforts on such tasks. Nevertheless, there are many limitations in the existing Auto-ML frameworks. Most of the existing Auto-ML pipeline frameworks focus only on a part of the ML pipeline which does not always result in the optimum overall pipeline for the given dataset. Moreover, several Auto-ML pipeline frameworks ignore integrating meta-learning, thus they recommend a well-performing pipeline for a single task and not a global and generic optimal pipeline. Thus, for new tasks they must search for a new pipeline. Furthermore, although there are Auto-ML frameworks that consider the complete pipeline but imbalanced datasets did not receive much attention from the proposed Auto-ML frameworks. To tackle these challenges, we propose a new efficient Auto-ML framework that is equipped with a meta learning mechanism for automated algorithm selection which also handles imbalanced datasets efficiently. This paper also demonstrates how the proposed framework outperforms the-state-of-the-art frameworks.