bluuebunny/crossref_metadata_2025_split huggingface dataset:
Clinical and Imaging Markers for the Prognosis of Acute Ischemic Stroke
Authors: Pei Chenyang , He Che , Li Han , Li Xiangying , Huang Weihui , Liu Jun , Yin Jianzhong 
Published: September 2023

Abstract
Significant differences in the outcomes observed in patients with acute ischemic stroke (AIS) have led to research investigations for identifying the predictors. In this retrospective study, we aimed to investigate the relationship of different clinical and imaging factors with the prognosis of AIS. All clinical and imaging metrics were compared between the good and poor prognosis groups according to the modified Rankin Scale (mRS) score at 90 days after discharge. Clinical factors included gender, age, NIHSS scores at admission, and other medical history risk factors. Imaging markers included the lesion’s size and location, diffusion, and perfusion metrics. A total of 89 patients with AIS were divided into the good (mRS score ≤ 2) and poor prognosis groups (mRS score ≥ 3). The two groups had significant differences in NIHSS scores, rCBF, rMK, and rMD (P < 0.05). Among them, rMK had the strongest correlation with the mRS score at 90 days after discharge (r = 0.545, P < 0.001). Perfusion and diffusion metrics, including CBF, MD and MK, could reflect the microstructure and blood flow characteristics of the lesion, which were the key factors for the salvage ability and prognosis of the infarction tissue.
Strain Rate Sensitive Polyampholyte Hydrogels Via Well Dispersed XLG Sheets
Authors: SU ESRA , Yelemessova Gaukhargul , Toleutay Gaukhar 
Published: September 2023

Abstract

The physical interactions between anionic and cationic monomers and the layered silicate clay mineral Laponite (XLG) have received great attention because of their potential implications for a variety of applications such as strain sensitive sensors, wearable electronics, drug delivery systems, and tissue engineering applications. A detailed investigation of the interaction between XLG and charged monomers is presented in this article. The study includes the observation of the changes in the viscosity of the solutions and the mechanical performance of the gels at various concentrations by adding XLG to the ionic monomer solution. The ionic interactions between XLG and the charged monomers, driven by electrostatic forces, play a crucial role in gelation and formation of a three-dimensional network, giving the structure strain rate sensitivity. In this way, the addition of XLG nanoparticles not only improves the mechanical properties of the gels, but also gives us information about the microstructure of the mechanical properties that change depending on the strain rate.
Sensor platform for assessment of water usage patterns in informal settlements
Authors: Rico Andres , Larson Kent , Gamboa Mayra 
Published: September 2023

Abstract
Rapid urbanization has intensified pressures on global water systems, particularly impacting informal settlements. Understanding water usage patterns within these settlements is of
importance for better addressing water scarcity issues. Current methods for gaining information about water within these settings tend to lack spatio-temporal granularity and miss complex patterns of behavior related to water usage. As a consequence, there is a shortage of the reliable quantitative measurements needed to improve water management processes and modeling. Here we introduce a low-cost sensing platform for water assessment in informal settlements. Households within these types of settlements, lacking water utility connections and piping, often use storage tanks and buckets to distribute, store, and consume water; hence, the platform consists of four distinct sensor modules that can be placed on these types of water infrastructure. Evaluated in controlled settings, the sensors prove to be reliable for measuring water quantity, quality, and usage. Field testing within an informal community in Mexico reveals that the system can comprehensively track multiple tank storage levels, assess water quality, and capture bucket usage patterns without disrupting a household's common activities or infrastructure. Our validation shows the technique's potential to improve water management in informal communities, while opening opportunities for enhancement of water-related research and policy making through combinations of top-down and bottom-up interventions.
Diagnostic value of carbohydrate antigen CA50, carbohydrate antigen 19-9 and α-fetoprotein in biliary tract cancer: A large-scale multicenter study
Authors: Wang Yong-Shuai , Wang Wei , Zhang Shen-Yu , Cai Wei , Song Hua-Chuan , Mei Tao , Wang Wei , Zhang Feng , Qi Fei-Yu , Zhang Sai , Liu Yan , Li Hao-Ran , Ji Peng , Gao Miao , Yao Hua-Chuan , Yao Huan-Zhang , Meng Fan , Lu Zheng , Wang Ji-Zhou , Liu Lian-Xin 
Published: September 2023

Abstract
Background
To date, carbohydrate antigen 19 − 9 (CA19-9) and carcinoembryonic antigen (CEA) have been widely used for the screening, diagnosis and prediction of biliary tract cancer (BTC) patients. However, few studies with large sample sizes of carbohydrate Antigen 50 (CA50) were reported in BTC patients and combined CA50, CA19-9 and α-fetoprotein (AFP) to build a clinical diagnostic model to provide a new screening and diagnosis method.
Methods
Here, we designed a cross-sectional study and analyzed data for patients with BTC, hepatocellular carcinoma (HCC), combined hepatocellular-cholangiocarcinoma (CHC), and benign biliary-liver diseases (BBD) and healthy people (HP) from two Chinese hospitals diagnosed between January 2017 and December 2022. Receiver operating characteristic (ROC) curves and decision curve analysis (DCA) were used to evaluate the diagnostic efficacy and clinical usefulness.
Results
A total of 1121 patients were included in this study (673 in the training cohort and 448 in the validation cohort): among them, 458 with BTC were included in the experimental group, and 178 with HCC, 23 with CHC, 242 with BBD, and 220 with HP were included in the control group, respectively. ROC curves by combining CA50, CA19-9 and AFP showed that, the AUC value of the diagnostic MODEL 1 was 0.885 (95% CI 0.856–0.885, specificity 93.9%, and sensitivity 74.3% in the training cohort; 0.879 (0.841–0.917, 92.8% and 75.9%) in the validation cohort. In addition, comparing iCCA and HCC (235 in the training cohort, 157 in the validation cohort), the AUC values of the diagnostic MODEL 2 was 0.893 (95% CI 0.853–0.933, specificity 96%, and sensitivity 68.6%) in the training cohort; 0.872 (95% CI 0.818–0.927, 94.2%, and 64.6%) in the validation cohort.
Conclusion
The model combining CA50, CA19-9, and AFP not only has good diagnostic value for BTC, but also has good diagnostic value for distinguishing iCCA and HCC.
Investigation of laser wavelength effect on the ablation of enamel and dentin using femtosecond laser pulses
Authors: Rapp Ludovic , Madden Steve , Brand Julia , Maximova Ksenia , Walsh Laurence J. , Spallek Heiko , Zuaiter Omar , Habeb Alaa , Hirst Timothy R. , Rode Andrei V. 
Published: September 2023

Abstract
We investigated the effect of femtosecond (fs) laser ablation of enamel and dentin for different pulse wavelengths: infrared (1030 nm), green (515 nm), and ultra-violet (343 nm) and for different pulse separations to determine the optimal irradiation conditions for the precise removal of dental hard tissues with the absence of structural and compositional damage. The ablation rates and efficiencies were established for all three laser wavelengths for both enamel and dentin at room temperature without using any irrigation or cooling system, and the surfaces were assessed with optical and scanning electron microscopy, optical profilometry, and Raman spectroscopy. We demonstrated that 515 nm fs irradiation provides the highest rate and efficiency for ablation, followed by infrared. Finally, we explored the temperature variations inside the dental pulp during the laser procedures for all three wavelengths and showed that the maximum increase at the optimum conditions for both infrared and green irradiations was 5.5˚C, within the acceptable limit of temperature increase during conventional dental treatments. Ultra-violet irradiation significantly increased the internal temperature of the teeth, well above the acceptable limit, and caused severe damage to tooth structures. Thus, ultra-violet is not a compatible laser wavelength for femtosecond teeth ablation.
A Multi-scale Combined Prediction on Tourist Flow: Does Internet Big Data Matter？
Authors: Liu Jinpei , Zhao Xiaoman , Chen Yi , Dai Yujie 
Published: September 2023

Abstract
This article proposes a multi-scale combination prediction method for tourism traffic driven by internet big data. Firstly, process data on tourist traffic, Baidu index, and online reviews. Use Principal Component Analysis (PCA) to reduce the dimensionality of Baidu Index, and then use Snownlp to calculate the emotional value of each online comment. Secondly, a mixed multi-scale decomposition method is used to decompose tourism traffic and processed data, and sample entropy is used to reconstruct the decomposition results into high-frequency, low-frequency, and trend components. Thirdly, LSTM, BPNN, and SVR are used to predict high-frequency, low-frequency, and trend components, respectively, to obtain the predicted values under the three decomposition paths. The optimal weighted combination is used to obtain the final prediction result. Finally, the empirical analysis of tourism flow in Jiuzhaigou Valley,the result shows that the Internet big data can significantly improve the prediction effect of tourism flow.
Osteocalcin and Chinese visceral adiposity index are associated with the risk of atherosclerotic cardiovascular disease and arterial stiffness in patients with type 2 diabetes mellitus：a case control study
Authors: Gong Caixia , Chen Chongyang , Zhao Yangting , Wang Yawen , Li Kai , Lv Xiaoyu , Liu Jingfang 
Published: September 2023

Abstract
Background
Current risk assessments for atherosclerotic cardiovascular disease (ASCVD) in patients with type 2 diabetes mellitus (T2DM) are limit. Recent evidence strongly supports a close correlation between serum osteocalcin, the Chinese visceral adiposity index (CVAI), and T2DM, and cardiovascular events. However, their association with ASCVD risk in patients with T2DM remains unknown, and their impact on arterial stiffness also remains unclear.
Methods
An analysis of 646 T2DM patients aged 18 and older was conducted in this cross-sectional study. The ASCVD risk was assessed using the China-PAR equation, with patients categorized into low- or medium-high-risk groups. Osteocalcin was detected through electrochemical luminescence, whereas arterial stiffness was defined using ankle-brachial index and brachial-ankle pulse wave velocity. Logistic regression analysis was conducted to examine the correlation between serum osteocalcin levels, CVAI, ASCVD risk, and arterial stiffness.
Results
Osteocalcin levels were significantly lower in men patients with T2DM in the medium-high-risk ASCVD group compared to the low-risk ASCVD group, whereas CVAI levels was significantly higher in women patients with T2DM in the medium-high-risk ASCVD group than the low-risk ASCVD group. Logistic regression analysis identified osteocalcin and CVAI as independent risk factors for both medium-high-risk ASCVD (osteocalcin: men, OR,0.958, 95%CI 0.923, 0.99, women, OR, 0.788, 95%CI 0.645, 0.96, respectively)(CVAI: men, OR,1.010, 95%CI 1.00, 1.02, women, OR,1.084, 95%CI 1.00, 1.17, respectively) and arterial stiffness (osteocalcin: men, OR, 0.958, 95%CI 0.92, 1.00, women, OR, 0.925, 95%CI 0.86, 0.99, respectively)(CVAI: men, OR,1.011, 95%CI 1.003, 1.02, women, OR,1.0217, 95%CI 1.00, 1.03, respectively) in both men and women patients with T2DM. Combining osteocalcin levels and CVAI improved the prediction accuracy of arterial stiffness in men patients with T2DM (difference of AUC (Model 4 vs. Model 1):1.4%). All P-values were < 0.05.
Conclusion
Osteocalcin levels and CVAI are independent risk factors for ASCVD risk and arterial stiffness in T2DM. Combining osteocalcin and CVAI can enhance the early detection of atherosclerosis through men patients with T2DM.
Identification of Potential Acetylcholinesterase (AChE) inhibitors from Vitis vinifera: A Case study of Alzheimer’s Disease (AD)
Authors: Sofela Salimat O. , Ibrahim Abdulwasiu , Bodun Damilola S. , Nwankwo Daniel O. , Mafimisebi Mojirade , Abdulrasheed Buhari , Balogun Toheeb , Opeyemi Isaac 
Published: September 2023

Abstract

Alzheimer’s disease (AD) is the most prevalent neurodegenerative disease that affects people aged 60 years and above. Yet, the discovery of potent therapeutic agents against this disease has no utmost progress and a number of drug candidates could not make it out of the clinical trials at varied stages. At the same time, the currently available anti-cholinesterase for the treatment of AD can only improve the clinical symptoms while the recently approved immunotherapy agent “remains questionable. Thus, the need for novel therapeutic agents with the potential to treat the aetiology of the disease. Herein, this study sought to examine the potential of a number of bioactive compounds derived fromVitis viniferaas a promising agent against AChE. Using a computational approach via molecular docking 23 bioactive agents were screened against AChE and the compounds with a binding score below that of the standard ligand were further subjected to drug-likeness and pharmacokinetic screening. Eight of the studied agents optimally saturated the active pocket of the AChE, forming principal interactions with a number of amino acids at its active pocket and among these compounds only rutin failed the drug-likeness test by violating four parameters while all showed moderate pharmacokinetics features. A number ofVitis vinifera-derived bioactive compounds show excellent inhibitory potential against AChE and moderate pharmacokinetic features when compared to the reference ligand (tacrine). These compounds are therefore proposed as novel AChE inhibitors for the treatment of AD and wet-lab analysis is necessary to affirm their potency.
Acarbose reduces Pseudomonas aeruginosa respiratory tract infection in type 2 diabetic mice
Authors: Liu Lin , Fan Haiyang , Li Liang , Fan Yunping 
Published: September 2023

Abstract
Background
Type 2 diabetes mellitus (T2DM) is widely prevalent worldwide, and respiratory tract infections have become the primary cause of death in T2DM patients who develop concurrent infections. Among these, Pseudomonas aeruginosa infection has been found to exhibit a high mortality rate and poor prognosis and is frequently observed in bacterial infections that are concurrent with COVID-19. Studies have suggested that acarbose can be used to treat T2DM and reduce inflammation. Our objective was to explore the effect of acarbose on P. aeruginosa respiratory tract infection in T2DM individuals and elucidate its underlying mechanism.
Methods
High-fat diet (HFD) induction and P. aeruginosa inhalation were used to establish a respiratory tract infection model in T2DM mice. The effect and mechanism of acarbose administered by gavage on P. aeruginosa respiratory tract infection were investigated in T2DM and nondiabetic mice using survival curves, pathological examination, and transcriptomics.
Results
We found that P. aeruginosa respiratory tract infection was more severe in T2DM mice than in nondiabetic individuals, which could be attributed to the activation of the NF-κB and TREM-1 signaling pathways. When acarbose alleviated P. aeruginosa respiratory tract infection in T2DM mice, both HIF-1α and NF-κB signaling pathways were inhibited. Furthermore, inhibition of the calcium ion signaling pathway and NF-κB signaling pathway contributed to the attenuation of P. aeruginosa respiratory tract infection by acarbose in nondiabetic mice.
Conclusions
This study confirmed the attenuating effect of acarbose on P. aeruginosa respiratory tract infections in T2DM and nondiabetic mice and investigated its mechanism, providing novel support for its clinical application in related diseases.
Feasibility Study of PERCIST In The Efficacy Evaluation of [ 18 F] -PSMA-1007 PET/CT In Patients With Prostate Cancer Receiving Systematic Treatment
Authors: Li Yunxuan , Wang Zhuonan , Li Yan , Zheng Anqi , Gao Jungang , Dong Weixuan , Duan Xiaoyi 
Published: September 2023

Abstract
Purpose
Positron Emission Tomography (PET) Response Criteria in Solid Tumors (PERCIST) is a tumor efficacy evaluation standard developed for 2-deoxy-2-[18F]fluoro-D-glucose ([18F]-FDG) PET/CT, We applied this standard to [18F]-coagulate specific membrane antigen-1007 (PSMA) PET/CT in patients with prostate cancer, the standardized uptake value corrected for lean body mass (SUL)was used as metabolic parameter. We compared the consistency between the efficacy evaluation of SUL and prostate specific antigen (PSA), and analyzed the effect of prostate cancer-related clinical factors on consistency. Finally, we attempted to apply the new PSMA efficacy evaluation criteria in 2021 Consensus Statements to this study.
Procedures
: We enrolled 41 men with prostate cancer, who underwent [18F] -PSMA-1007 PET/CT before and after therapy with radiation, androgen deprivation, or chemotherapy, quantitative analysis of positive lesions (at most 5 lesions in a single examination), obtain metabolic parameters,including Summed SULmax,Summed SULmean, Summed SULpeak, whole-body PSMA tumor volume (PSMA-TV), whole-body total lesion PSMA (TL-PSMA). The efficacy of the enrolled patients was evaluated according to PERCIST criteria, Kappa consistency test was carried out between the evaluation results of different parameters and the changes of serum PSA. Logistics regression was used to analyze the impact of clinical factors related to prostate cancer on the efficacy evaluation of PSMA. The new disease progression criteria in 2021 Consensus Statements are used to evaluate efficacy.
Result
41 patients received systematic treatment, 6 patients achieved complete response(CR) to biochemical indicators PSA, 20 patients partial response(PR), 6 patients stable disease(SD), 9 patients progressive disease(PD), Summed SULmax (22/41, Kappa 0.306), Summed SULmean (23/41, Kappa 0.342), Summed SULpeak (23/41, Kappa 0.381), PSMA-TV (22/41, Kappa 0.331), TL-PSMA(26/41, Kappa 0.431). Logistic regression analysis showed that clinical factors associated with prostate cancer(including PSA level, Gleason score, metastatic status, and sensitivity to hormone therapy) did not affect the consistency of PSMA PET/CT metabolic parameters with PSA assessment(P > 0.05). The progress criteria in 2021 consensus statements changed the outcome of the metabolic parameters assessment in 2 patients.
Conclusions
SUL metabolic parameters were consistent with PSA in the efficacy assessment of [18F]-PSMA PET/CT, and were not affected by clinical factors related to prostate cancer, the PERCIST standard can be used in PSMA imaging. Progress criteria in 2021 Consensus Statements could improve consistency between PSMA metabolic parameters and PSA assessment in some patients.
Li adsorption and diffusion on the surfaces of molybdenum dichalcogenides MoX 2 (X=S, Se, Te) monolayers for lithium-ion batteries application: A DFT study
Authors: BOUNBAA Malak , KHUILI Mohamed , FAZOUAN Nejma , ATMANI El Houssine , Allaoui Isam , Houmad Mohamed 
Published: September 2023

Abstract
In this work, we study some of the most high performance electrode materials for lithium-ion batteries. These comprise molybdenum dichalcogenide MoX2 (molybdenum disulfide MoS2, molybdenum diselenide MoSe2, molybdenum ditelluride MoTe2). Using first principal calculations, structural and electronic proprieties of 2D material MoX2 are determinate. The stability estimation by cohesive energy, formation energy, adsorption, theoretical capacity and path diffusion of Lithium are calculated. Our study findings suggest that the adsorption of Li on various sites on the surface of the MoX2 monolayer maintains its semiconductor behavior, and MoX2 demonstrates negative adsorption energies for Li-ion. All of this indicates that the MoX2 is well suited as an anode material for lithium-ion batteries. Our research can offer new ideas for experimental and theoretical design and new anode materials for lithium-ion batteries (LIB).
Homogenous Ensemble Boosting Approach to Improve the Consistency in the Accuracy of Text Data Classification
Authors: Azam Muhammad , Sabah Fahad , Raheem Abdul , Ahmad Nadeem , Irfan Danish , Sarwar Raheem 
Published: September 2023

Abstract
The rapid growth of the internet in recent years has produced an enormous amount of data. The significant chunk of this data is unstructured. This unstructured data requires critical analysis and modelling to become useful for decision making. Due to the wild spread of internet across the globe, several applications are being developed every day. These applications have direct interaction with end-users, and users can provide their opinions, sentiments, reviews etc. about the products, services, events, etc. These sentiments, reviews and opinions are very useful for individuals, organizations, businesses, and governments for future decision making. Surveys from last few years confer those online opinions have more prominent financial effect compared to traditional media advertisement. The significant task of sentiment analysis is used to locate the useful information from the client sentiment. While this substance is intended to be valuable, most of this client produced content requires using the data mining methods and sentiment analysis. However, a few difficulties are confronting sentiment analysis. Sentiment analysis includes the applications of natural language processing and text analysis methods to recognize and separate the useful information from text data. Machine learning techniques are widely used for sentiment classification. In this paper, we provide a deep understanding of different machine learning systems for sentiment classification. An extensive study of homogenous ensemble-based machine learning techniques in the domain of sentiment classification has been carried out to enhance the efficiency and consistency by implementing various learning algorithms to gain better accuracy that can be attained from any of the individual learning algorithms. Our methodology in this paper is to explore the whole process from data preprocessing to classification accuracy. Various preprocessing steps are applied to selected text data to prepare data for classification. Many classification models (NB, NNET, KNN, RPART, SVM, LDA, CTREE) are explored from a different family of classifiers for classification purpose. Lastly, homogeneous ensemble techniques (Boosting (GBM) and Bagging (RF)) are used and compared with individual classifiers. And results obtained shows that Boosting ensemble model is more consistent and accurate than all other discussed models.