bluuebunny/crossref_metadata_2025_split huggingface dataset:
Blocking mineralocorticoid signaling with esaxerenone reduces atherosclerosis in ApoE KO mice without affecting blood pressure and glycolipid metabolism
Authors: Iwamoto Hideyuki , Sanada Junpei , Kimura Tomohiko , Shimoda Masashi , Iwamoto Yuichiro , Dan Kazunori , Fushimi Yoshiro , Katakura Yukino , Nogami Yuka , Shirakiya Yoshiko , Yamasaki Yuki , Nakanishi Shuhei , Mune Tomoatsu , Kaku Kohei , Kaneto Hideaki 
Published: October 2024

Abstract

Aims: Endothelial damage mediated by mineralocorticoid receptor (MR) is an important factor in the development of atherosclerosis. Esaxerenone is a highly selective drug that can specifically block MR activity. The aim of this study is to examine whether specific blocking of mineralocorticoid signaling with esaxerenone exerts favorable effects on the progression of atherosclerosis.
Methods: ApoE KO mice were used as a model of atherosclerosis. In addition to a non-diabetic model, we created a diabetic model using streptozotocin. These were divided into a control group and an esaxerenone group. Esaxerenone-containing diet was provided for 8 weeks starting at 10 weeks of age. Various metabolic markers and abdominal aortic mRNA expression were evaluated, and histological examination of the aortic arch and thoracic aorta was performed.
Results: In diabetic mice, plaque area in the aortic arch was significantly smaller in esaxerenone group compared to control group, although there were no differences in blood pressure, serum lipid levels between the two group. Inflammation-related genes, macrophage marker, cell adhesion factors and oxidative stress marker were all significantly lower in esaxerenone group.
Conclusions: Specific blocking of mineralocorticoid signaling with esaxerenone exerts favorable effects on the progression of atherosclerosis without influencing blood pressure and glucolipid metabolism.
Transperineal biopsy is associated with higher rates of Gleason grade group upgrading in prostate adenocarcinoma when compared with transrectal ultrasound biopsy
Authors: Reddy Paul W. , Keenan Robert A. , Crotty Tom , Galvin David , Swan Niall 
Published: October 2024

Abstract

Purpose:
Histopathological assessment of prostate biopsies (PBx) remains the mainstay of diagnosis in prostate cancer (PCa). The Gleason grade group score (GGG) is a critical parameter used for diagnosis, risk stratification and management in PCa. In our institution transperineal (TP) PBx has become the favoured biopsy method, largely due to its increased accuracy and lower risk of infection. Our review analysed the GGG concordance rates between PBx and radical prostatectomy (RP) specimens with a focus on biopsy method.
Method:
A total of 588 patients who underwent RP between January 2016 and December 2022 were included in our analysis. Clinicopathological data was collected from the laboratory information system. A chi-square and Mann-Whitney U test were used for categorical and continuous variables, respectively.
Results:
TRUS biopsy was performed in 79% of cases, while TP PBx was performed in 21%. Concordance between PBx and RP was observed in 58% of cases, with 22% being upgraded and 20% downgraded. Biopsy method, extra-prostatic extension and positive surgical margin status were all found to be significantly associated with GGG upgrading.
Conclusion:
TP biopsies is the favoured biopsy method in our institution and review reveals higher rates of GGG upgrading is associated with this approach. This presents a dilemma as TP PBx may compromise the precision of cancer grading in favour of reduced side effects. Ongoing monitoring of PBx and their outcomes is essential for optimal balance between diagnostic accuracy and procedure side effects.
Modelling and forecasting of monthly extreme temperature using MLE and L-moment estimation methods: Khyber Pakhtunkhwa, Pakistan
Authors: Alamzeb Khan , Jehangir Khan , Ahmed Karmaoui , Zardad Khan 
Published: October 2024

Abstract

Extreme Events Analysis (EEA) is an essential tool for the designing and policy-making of rare events occurrence and infrastructure epically in Climate Change (CC). The results of EEA can be used to predict the magnitude and frequency of extreme environmental events in the future like temperature, droughts, rainfalls, floods, high winds and storms etc. EEA of extreme temperature based on Maximum Likelihood Estimation (MLE) and L-MOM Estimation Method has been carried out in this study. Both methods are used on two sets of data, collected from (Peshawar and Risalpur) of monthly mean (minimum) temperature data, maintained by Pakistan Metrological Office, Islamabad from the period of 1951 to 2018 and 1954 to 2018 respectively. Numerous tests are applied for initial fundamental assumptions i.e. stationarity, randomness, independence and homogeneity. Data from both the sites satisfied the said tests. For best fitted and robust estimation of parameters of the distribution, well-known goodness of fit tests i.e. Chi-square fit, Anderson-Darling test and Kolmogorov Smirnov method are used. Model is based on the model selection, the Generalized Extreme Value (GEV) distribution appeared to provide better results than other models used for the same purpose. In this study, quantile estimates for return ranging from 5 to 100 years have also been examined. Return periods and non-exceedance probabilities are used to generate quantitative estimations. The investigation shows that quantitative estimates or design prices based on the L - MOM estimating approach are lower than those based on maximum likelihood estimation (MLE) with equal return durations and non-exceedance probabilities. In such cases, Maximum Likelihood Estimation (MLE) is applied. As a result, it may be advised that the data produced from various methods and procedures should be compared during the design and policy planning phase for extreme temperature events. Furthermore, the results of such investigations can be utilized to choose improved design criteria for temperature policy management, notable measures for the prevention of extreme temperature events.
Fabrication and characterization of Polysulphanilic acid/Borate glass Composites as Anticorrosion Coat for Mild steel in Acidic medium
Authors: Ibrahim M. S. , Azooz M. A. , El-Deeb M. M. , Fathi A. M. , Kamal Emad H M , El-Salam H. M. Abd 
Published: October 2024

Abstract

Polymer-glass matrix composite exhibits excellent performance as scale inhibitors and anticorrosive coatings.Polysulphanilic acid borate glass composites were chemically performed using potassium dichromate (PDC) as an oxidant in an acidic medium at room temperature. The prepared polymer composites are characterized by IR spectroscopy, XRD and SEM. The interaction between polymer and borate glass is mainly via H-bonding and electrostatic attraction. The efficiency of all the synthesized polymeric samples as anticorrosive coating on mild steel in acidic mediumwas performed by using electrochemical techniques and well compared. The morphology of the coated samples after 7 days of immersion in 1.0 M HCl and the polarization and impedance results confirmed that the composite containing glass borate with0 % CuO (Graft100) represented the best coat with an efficiency of 94.6 %.
Concordance of three different methods to obtain samples for culture in reverse total shoulder arthroplasty. A prospective study.
Authors: Torrens Carlos , Companys Raquel , Suárez-López Amaya , Pérez-Prieto Daniel , Santana Fernando , Alier Albert 
Published: October 2024

Abstract

Purpose
The objective of this study was to analyze the concordance of the results obtained when culturing samples that are obtained with three different methods.
Methods
Prospective study that includes primary Reverse shoulder arthroplasties. From all the patients, 9 cultures were obtained. There were 3 cultures obtained from skin at the beginning of surgery, 3 from the tissue around the insertion of the long biceps on the glenoid side and 3 from the tissue around the greater tuberosity on the humeral side. At each location one culture was obtained from a swab, another one was obtained from the instruments on the table, and another one was obtained from a newly-opened set of instruments.
Results
There were 87 patients included, leaving 783 culture samples for the analysis. Of those 783 samples, 69 turned to be positive: 57 were positive for C. acnes, 5 for S. epidermidis, 4 for other coagulase-negative staphylococcus and 3 were positive for other indolent microorganisms. Comparing the results obtained with the three different methods, the kappa coefficient for all positive cultures was 0.1894 for cultures taken from skin, 0.4891 for cultures from the glenoid and 0.5456 for cultures from the greater tuberosity. Therefore, the kappa coefficient obtained for the three different locations ranged from poor to moderate.
Conclusion
The samples obtained with swab, tissue cultures taken with the instruments of the table and tissue cultures taken with new sets of instruments lead to different culture results in shoulder arthroplasty.
Cognitive decline is correlated with frailty in community-dwelling older adults
Authors: Chen Yi-Chun , Wu Yah-Yuan , Lee Chia-Ju , Hsu Chih-Cheng , Chung Ren-Hua , Hsiung Chao A. , Liu Tung-Hsia , Chen Wei J. , Liu Yu-Li 
Published: October 2024

Abstract

Background
Aging impacts both mental and physical health. The relationship between cognitive decline and frailty in aged individuals remains unclear. This study aimed to elucidate the correlation between cognitive and physical decline in elders, identify contributing factors, and explore potential blood biomarkers associated with these conditions.
Methods
Three groups at average aged of 65 (288 subjects), aged of 71 (196 subjects), and aged of 79 (80 subjects) were selected from the cohort of the Healthy Aging Longitudinal Study in Taiwan (HALST) database. Variables included global cognitive function, assessed by the Mini-Mental State Examination (MMSE), Fried frailty phenotype, and plasma tumor necrosis factor receptor-1 (TNFR1) were included. Statistical analyses utilized multiple regression analysis of variance, accounting for potential confounding variables.
Results
We found a gradual MMSE decline from average age of 65 to age of 79, which correlated with an increase in total frailty rating scores, especially in the components of exhaustion, slow walking speed, and weak grip strength (p ≦ 0.008). In addition, higher frailty scores were strongly associated with elevated plasma TNFR1 levels, particularly in components such as low physical activity, and weak grip strength (p ≦ 0.008).
Conclusion
Cognitive decline correlates with increase in frailty during aging process. Plasma TNFR1 emerges as a valuable indicator for identifying frailty in individuals.
Optimized fractional-order PID (FOPID) controller for two-wheeled self-balancing robots(TWSBR) using Multi-strategy improved Beluga Whale optimization algorithm(MSBWO)
Authors: ZHANG HUAQIANG , Nor Norzalilah Mohamad 
Published: October 2024

Abstract

In recent years, fractional-order controllers have seen a rise in popularity. These controllers provide researchers with increased flexibility in design, with intelligent optimization algorithms playing a critical role in parameter tuning. This study employs FOPID controllers for the control of a TWSBR. To ensure optimal performance, all controllers are optimized using intelligent algorithms. FOPID controllers introduce two additional parameters, $\lambda$ and $\mu$, resulting in a total of five parameters to optimize. The performance of each algorithm is influenced not only by its distinct structure but also by the specific characteristics of the optimization problem. Therefore, this paper introduces a Multi-strategy Improved Beluga Whale Optimization (MSBWO) algorithm and conducts a comprehensive performance evaluation. The parameters of the FOPID controller are fine-tuned using various popular algorithms, and the resultant system performances are compared. The results indicate that the FOPID controller, when optimized by MSBWO, outperforms other algorithms and consistently surpasses the performance of the integer-order PID controller under identical conditions.
Mathematics Subject Classification (2020) 93C10 · 93C40 · 49M37 · 26A33
Exploring Multi-Temporal Scale Co-Location of Childhood Respiratory Disease Incidents in Nanning City: A Guide to Geographically and Temporally Weighted Colocation Quotients
Authors: Li Ling , Cheng Jianquan , Mai Xiongfa , Duan Lian , Mo Liping , Tan Jie 
Published: October 2024

Abstract

Background
The incidence of disease data occurring in close spatial and temporal proximity are likely to exhibit unobserved effects. Investigating the spatial and temporal associations among various categories of childhood respiratory diseases is a crucial for modelling of demographic, environmental, and behavioral factors influencing these diseases. Traditional spatial statistical methods that do not account for associations among incident categories risk producing spurious findings.
Methods
This paper presents a practical approach for effectively handling spatio-temporal incident disease data, with a particular emphasis on optimizing sample size, addressing class imbalance, and examining temporal effects within the framework of Geographically and Temporally Weighted Co-Location Quotient (GTWCLQ) analysis. We apply this approach to investigate the patterns of childhood respiratory diseases in Nanning City, using data at both monthly and daily scales from December 2016.
Results
By utilizing datasets spanning different time scales, we discern the spatio-temporal association patterns of childhood respiratory diseases and compare disparities across these temporal scales. Our findings reveal a higher aggregation of childhood respiratory diseases in Nanning City on a daily scale, particularly on days with poor air quality, compared to days with good air quality. Moreover, the experimental results show that temporal resolution can affect the intensity of the co-occurrence pattern, while duration influences its frequency, and starting time affects both intensity and frequency.
Conclusion
Our findings demonstrate the utility of this practical guide in managing sample size and class imbalance within GTWCLQ analysis, establishing it as a valuable tool for exploring multi-scale spatio-temporal co-location patterns. Furthermore, this study enhances our understanding of the spatio-temporal distribution of childhood respiratory diseases, providing insights that can aid in identifying and mitigating potential underlying causes, which is of considerable significance for GIS-based health analysis and decision-making.
Efficiency detection technology for carrier communication model using instantaneous active power synchronization principle
Authors: YANG Lei 
Published: October 2024

Abstract

In order to improve the efficiency detection ability of carrier communication model, this study designed a carrier communication model efficiency detection method based on the instantaneous active power synchronization principle. Based on the instantaneous active power synchronization principle, a new carrier communication model was designed, which includes data information sender, data information attenuator, communication load simulator, communication line noise simulator and data receiving end. The data parameters of carrier communication include carrier frequency, data rate, modulation mode, carrier bandwidth, noise and interference, communication distance, communication rate and communication quality, etc. The efficiency detection ability of carrier communication model is greatly improved by genetic algorithm. Through experiments, the detection efficiency of this research method is more than 90%, which greatly improves the efficiency detection ability of carrier communication model.
Assessment and quantification of average soil erosion using RUSLE and geospatial modeling for sustainable Land management over Melka-Sedi Catchment, Ethiopia.
Authors: Abera Bereket 
Published: October 2024

Abstract

Soil erosion is a significant worldwide threat, with far-reaching adverse effects on the environment. The general objective of this study is to assess the spatial average soil loss, identify high-risk areas, and visually represent variation of soil loss from Melka-sedi catchment employing Revised Universal Soil Loss Equation (RUSLE) and geospatial modeling. RUSLE computes average soil erosion based on five significant factors: rainfall erosivity, topography, cover management, soil erodibility, and support and management activities. The spatial distribution of all factors and the final RUSLE estimations were performed using the ArcGIS workspace. The results of this study indicated that the annual soil loss from the catchment ranged from 0 to 4,742 tons ha− 1 year− 1. The area was categorized into five subclasses of soil loss severity zones: high, sub-high, moderate, sub-low, and low. Most of the land, 209,561.24 hectares (77.25%), falls into the low erosion category, while 36,093.65 hectares (13.05%) are classified as sub-low erosion, 13,992.43 hectares (5.15%) are considered moderate erosion, 7,363.25 hectares (2.71%) as sub-high erosion, and 4,249.98 hectares (1.56%) as high erosion. Overall, the total annual soil loss throughout the study area was 1,098,931.5 tons. More than 4% of the land within a catchment requires urgent conservation activities. It is concluded that significant soil erosion is found in the catchment, and it is recommended to prioritize erosion-affected areas in the catchment and apply conservation practices to achieve sustainable watershed management within the catchment. This study provides useful information for directing actions to reduce erosion, prevent significant land degradation, and achieve sustainable land management.
Predicting MOOC Dropout Using Ensemble Models Based on RNN and GRU
Authors: Talebi Kowsar , Torabi Zeinab , Daneshpour Negin 
Published: October 2024

Abstract

Nowadays, dropout prediction in Massive Open Online Courses (MOOCs) has become a popular field in educational data mining. In order to predict early dropouts with high accuracy, this research introduces a model for data pre-processing. In addition, since our data consist of time series, Recurrent Neural Networks (RNNs) and Gated Recurrent Units (GRUs) are used. The study proposes six ensemble models named Adaboost RNN, Voting RNN, Bagging RNN, Adaboost GRU, Voting GRU, and Bagging GRU to improve the accuracy of dropout prediction. The models were trained and evaluated using KDD Cup 2015 data set. Results show that the ensemble models outperform both RNN and GRU models individually, with Bagging GRU achieving an accuracy of 91.73% and improving precision, recall, and F-score as well. The findings suggest that deep learning techniques such as RNN and GRU can be effective tools for predicting MOOC dropout rates, and that ensemble models can further enhance their predictive power.
The Analytical Performance Evaluation of Routine Clinical Chemistry Parameters by Six Sigma Approach: An Effective Tool for Laboratory Quality Management
Authors: Rasheed Asma , Sharif Sadia , Humayun Lubna , Javaid Faiza , Agha Muhammad Afaaq , Ilyas Anam , Tahir Naeem  
Published: October 2024

Background: Clinical laboratories errors can impose serious adverse effects on patient management. Clinical laboratories can evaluate their analytical performance by effective quality management tool i.e. Six Sigma metrics.Objectives: To evaluate the analytical performance of routine chemistry parameters by Six Sigma approach.Methods: Cross sectional study carried out from July 2022 till February 2024 in the Chemical Pathology section of University of Lahore Diagnostic Lab and Research Center, Lahore. Analytical performance of nineteen routine chemistry parameters were evaluated by using the external and internal quality control material. Only those parameters were selected who enrolled in External Quality Assurance Scheme. Inclusion criteria for IQC following West gard rule +/- 2 SD while for EQAS results follow +/- 2 Z score. Sample size for 19 parameters analyzed in EQAS from July 2022 till December 2023 was 342. 2700 IQC samples were analyzed from August 2023 till February 2024. All control values were entered in Microsoft Excel 2013 and calculated manually by conventional equations.Results: Most of our laboratory parameters showed satisfactory analytical performance in between 3-6 when evaluated by six sigma metrics.Conclusion: Control frequency for parameters showed score > 6 can be reduce for saving laboratory resources whereas parameters with sigma score around 3 needs more vigilant monitoring. Health care and laboratory outcome need high quality results to improve patient health. Six sigma tool allows laboratory to identify the right method, right rule, run controls at right frequency to enable the right patient outcome.
Stormwater runoff volume reduction and pollutant removal efficiency via bioretention cell using rock wool as the media
Authors: Qiu Rongting , Wang Jianlong , Qiu Zhiming , Wang Shiping , Yang Tao , Sun Jian , Tu Nannan 
Published: October 2024

ABSTRACT
Bioretention cells have been widely used in stormwater management. Media plays an important role in stormwater runoff volume reduction and pollutant removal. A novel bioretention media of rock wool has been proposed, and its effect on stormwater runoff volume reduction was investigated via a laboratory-scale experiment. The results showed that compared with the conventional bioretention (CB) using medium sand as media, the volume capture ratio of annual rainfall (VCRAR) of the rock wool bioretention (RWB) was 2.66–5.5% higher, and the peak flow reduction rate was 2.97–11.32% higher. The removal efficiency of the RWB on COD, NH4+ -N, TN, and TP were 25–30%, 10–31%, 20–40%, and 5–14% higher than the CB, respectively. The removal efficiency of the RWB on both Pb and Zn was &gt;99%. The microbial high-throughput sequencing results showed that the RWB can provide a better breeding environment for Bacteroides and Actinobacteria, which is conducive for the removal of pollutants. The RWB had a better stormwater runoff volume reduction rate and pollutant removal efficiency than the CB, therefore, it could be used as a better media for bioretention cells to improve stormwater management efficiency by using rock wool, obtained from construction waste, as the media.
Methylene blue adsorption by chemical-activated Trichanthera gigantea leaf
Authors: Fakunmoju Azeezat Ayoku , Azaman Fazureen , Ali Asmadi , Hamzah Sofiah 
Published: October 2024

ABSTRACT

This study investigated the potential of NaOH-treated Trichanthera gigantea leaf (TGL) powder as a sustainable, low-cost biosorbent for methylene blue (MB) removal from wastewater. Characterization using scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), Brunauer–Emmett–Teller, and energy-dispersive X-ray spectroscopy (EDX) techniques confirmed favorable morphology, identifying micropores, suitable functional groups, notable surface area, pore volume, and elemental diversity. Batch experiments systematically investigated the influence of operational parameters, including contact time, initial MB concentration (5–35 mg/L), pH (2–10), and biosorbent dosage (2–10 g/L) on adsorption performance. The Langmuir isotherm model best represented the experimental data (R² values of 0.993 and 0.9725), indicating favorable adsorption (RL &lt; 1) and maximum MB adsorption capacities of 0.822 and 0.330 mg/g for treated and untreated TGL, respectively. Statistical analysis (ANOVA) results further identified the most significant factors influencing MB biosorption. These findings highlight the potential of NaOH-treated TGL powder as an effective and eco-friendly solution for removing MB dye from industrial effluents, contributing to sustainable wastewater treatment and environmental protection.