bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cell-based therapies reverse the heart failure-altered right ventricular proteome
Authors: Makkaoui Nour , Prasad Vidhya , Bagchi Pritha , Carmona Tiffany , Li Ke , Latham Olivia , Zhang Yuanyuan , Lee Jingyun , Furdui Cristina , Maxwell Joshua 
Published: September 2024

Abstract

Background Congenital heart defects can lead to right ventricular (RV) pressure-overload and heart failure. Cell-based therapies, including mesenchymal stromal cells (MSCs) and c-kit positive cells (CPCs) have been studied clinically as options to restore heart function in disease states. Many studies have indicated these cells act through paracrine mechanisms to prevent apoptosis, promote cellular function, and regulate gene/protein expression. We aimed to determine the proteomic response of diseased hearts to cell therapyMethods We utilized an animal model of RV pressure overload created by banding the pulmonary artery (PAB). Two weeks post-banding, bone marrow-derived mesenchymal stromal cells (MSCs) and 3 populations of CPCs (nCPCs, cCPCs, ES-CPCs) were delivered to the RV free wall. RV function and cellular retention were measured for four weeks post-injection, at which point hearts were extracted and the RV was excised for liquid chromatography and tandem mass spectrometry. Resulting RV proteomes were compared and analyzed using systems biology and bioinformatics.Results Proteomic profiling identified 1156 total proteins from the RV, of which 5.97% were significantly changed after PAB. This disease-altered proteome was responsive to cellular therapy, with 72% of the PAB-altered proteome being fully or partially reversed by MSC therapy. This was followed by nCPCs (54%), ES-CPCs (52%), and cCPCs (39%). Systems biology and bioinformatics analysis showed MSC, nCPC, or ES-CPC cell therapy is associated with a decrease in predicted adverse cardiac effects. We also observed an effect of cell therapy on the non-altered RV proteome, however, this was associated with minor predicted pathological endpoints.Conclusions Our data indicate MSCs, ES-CPCs, and nCPCs significantly reverse the PAB-altered proteome towards a pre-disease state. These results indicate cell-based therapies show promise in improving RV function after pressure overload through partial restoration of the disease-altered cardiac proteome.
A Novel Algorithm to Detect and Prevent SQL Injection Attacks for Web Applications using Query Comparison Technique
Authors: Chowdhury Jayanto Kumar , Yadav Dilip Kumar , P.V.S Chandramouli 
Published: September 2024

Abstract

SQL Injection attacks (SQLiAs) have gained popularity among hackers since they can create massive impacts on digital platforms. SQLiAs may penetrate the security frameworks and can modify or destroy underlying databases. These attacks may steal valuable or/and confidential information from database-driven applications. It is therefore necessary to protect web applications from SQLiA attacks. Automatic SQLiAs detection and prevention mechanism is required to protect internet exposed applications from SQLiAs vulnerabilities. A novel algorithm is proposed based on query comparison logic to detect the SQL injection vulnerabilities in database-driven applications. This method compares the structure of design-time and run-time queries to identify the presence of SQL injection vulnerabilities. The proposed algorithm should be able to detect and prevent different types of SQL injection attacks like Boolean, tautology, piggybacked queries, illegal queries, union queries, stored procedure etc. This algorithm should be flexible enough so that developers can integrate it with the existing vulnerable web application and it works as a shield to protect the legacy web applications from SQL injection attacks. The proposed approach tested on GITHUB open source data set and the result is very satisfactory with an accuracy of 93% to 98%.
Design and Fabrication of Nanocomposite Filters for Dairy Industry Wastewater Treatment
Authors: Talafha Atheer , Abu-Dalo Muna , Albiss Borhan Aldeen , Al-Nabulsi Anas 
Published: September 2024

Abstract

The dairy industry produces a significant volume of effluents that contain various pollutants, which causes environmental issues. In this study, the fabrication and performance of nanocomposite filters including activated carbon (AC), calcium alginate (CA), and nanosilica were investigated for the treatment of dairy industry wastewater. This nanocomposite filled a major gap in the use of nanocomposite for dairy wastewater treatment in a simple, cost-effective, and environmentally friendly approach. The nanoparticles were synthesized using sand extraction in an environmentally friendly approach with a size of 30–45 nm. Several techniques such as X-ray fluorescence (XRF), X-ray diffraction (XRD), ultraviolet-visible spectroscopy (UV-VIS), Fourier transform infrared spectroscopy (FTIR), and scanning electron microscopy (SEM) were used to characterize the materials. Furthermore, the nanocomposite filter performance and efficiency in removing chemical oxygen demand (COD) were assessed through batch experiments. Batch experiments were used to investigate optimum conditions such as the contact time, pH, and nanosilica dosage. The results showed that the nanocomposite filters effectively treat the dairy wastewater, where the percentage of COD removal reached 99.7%. However, the adsorption isotherm, kinetic, and thermodynamic studies were carried out and the best-fitted models of isotherm, and kinetic models were Langmuir, and pseudo-second-order reaction, respectively. The thermodynamic reaction of this study is related to being endothermic. Results were discussed to reveal that the integration of the Water-Food-Environment (WEFE) NEXUS was successfully achieved.
Heterogeneous effects of Agricultural insurance on Agricultural Green development: Evidence from Sub national economies of India
Authors: Malik Mohd , Tiwari Ashu , Hemat Waheedullah 
Published: September 2024

Abstract

The current paper aims to assess the relative competitiveness of agricultural green development across 27 Indian states and explore the factors influencing this development. Given India's significant role as a global producer of various crops such as rice, wheat, sugarcane, cotton, and pulses, and with approximately 43.96 percent of the labor force engaged in agriculture, the sector's performance is crucial for achieving Sustainable Development Goals (SDGs). The analysis of the green development index reveals that states like Uttar Pradesh demonstrate higher green competitiveness, attributed to factors such as irrigation infrastructure and a higher proportion of insured farmland. Conversely, states like Himachal Pradesh, Uttarakhand, and Punjab exhibit lower levels of green competitiveness due to their elevated consumption of fertilizers and pesticides. To understand the determinants of agricultural green development competitiveness, Quantile regression has been employed. The findings highlight a positive relationship between agricultural green development (the endogenous variable) and several explanatory factors. These include the extent of land insured, per capita power availability, the presence of bank branches in rural areas, and an increase in crop intensity. Furthermore, employing the Dumitrescu and Hurlin (2012) panel Granger causality test reveals that economic growth at the state level in India precedes and influences agricultural green development. This suggests a dynamic relationship wherein economic progress fosters advancements in agricultural sustainability.
Transcriptome profiles of leaves and roots of Brassica napus L. in response to antimony stress
Authors: Liu Xianjun , You Liang , Yu Wencong , Yuan Yuhui , Zhang Wei , Yan Mingli , Zheng Yu , Duan Renyan , Meng Guiyuan , Chen Yong , Liu Zhongsong , Xiang Guohong 
Published: September 2024

Abstract

Antimony (Sb), a non-essential heavy metal, exerts severe toxic effects on the growth and development of plants. This study investigated the response of Brassica napus to 75 mg/L Sb(III) stress under hydroponic conditions, focusing on Sb accumulation, physiological indexes, and transcriptome sequencing. Sb accumulation in six B. napus varieties ranged from 199.73 to 561.42 mg/kg. Enzymatic activities (SOD, POD, CAT) and MDA content showed initial increases followed by declines under varying Sb treatments. Transcriptomic analysis identified 8,802 genes in root tissues and 13,612 genes in leaf tissues responsive to Sb stress, predominantly involved in oxidative stress responses, glutathione metabolism, plant hormone signaling, ABC transporters, and MAPK pathways. Upregulation of antioxidant-related genes like GPX2, APX2, PER34, and GSTU4 in root tissues correlated with physiological index changes, while photosynthesis-related genes were largely downregulated in leaf tissues. This study provides crucial insights into B. napus's response mechanisms to Sb stress and highlights its potential for phytoremediation efforts.
Impact of finger–ball slip on baseball pitching performance
Authors: Yamaguchi Takeshi , Suzuki Souta , Suzuki Shinnosuke , Nishi Toshiaki , Fukuda Takehiro , Nasu Daiki 
Published: September 2024

Abstract

This study aimed to investigate the finger-ball slip distance in baseball pitching under different finger–ball friction conditions and to demonstrate how slippage affects pitching performance. 6 experienced pitchers were instructed to throw 4-seam fastballs at approximately 130 km/h toward a target behind the home base. The finger–ball friction conditions varied and included no application, water application, rosin powder application, and pine resin application. The finger-ball slip distance was estimated from images of the fingertips and ball during the ball release process captured by a high-speed camera (2000 frames/s). The sliding distance was significantly affected by the finger–ball friction condition. In the ball release process, except for the water application condition, the ball was released by hooking the fingertips on the seam, and the ball slid against the fingers. However, in the water application condition, slippage occurred throughout the ball release process. The slip distance was negatively correlated with the ball speed and ball spin rate and positively correlated with the horizontal and vertical ball arrival locations. Our findings will provide new insights into the understanding of how a ball is released in baseball pitching under different friction conditions and will lead to improvements in pitching performance.
Organic inputs and L-phenylalanine amino acid impacts on yield and essential oil compounds of sage (Salvia officinalis L.) under different soil moisture conditions
Authors: Hasanabadi Safoura , Ardakani M. Reza , Pirbalouti Abdollah Ghasemi , Paknejad Farzad , Habibi Davoud 
Published: September 2024

Abstract

To distinguish the impacts of soil moisture conditions and the foliar spraying with an amino acid as affected by two organic inputs on the dry matter yield and volatile oil of sage (Salvia officinalis L.) at the early flowering stage, a field experiment was done according to a split-plot in time and place design in West of Iran in two experimental years. Experimental treatments were two irrigation frequency levels [optimum or irrigation at field capacity (F.C.) and reduced irrigation or irrigation at 50% F.C.] as the main plot, and in subplots: organic inputsin three levels including control (without amendment), arbuscular mycorrhizal fugi (AMF), and cow dung manure, and also the foliar spraying of L-phenylalanine amino acid at four levels: negative control (non-spraying), positive control (with distilled water as solvent), and foliar spraying with 25 and 50% L-phenylalanine. Results indicated that the basic compounds of the volatile oil from sage were oxygenated monoterpenes, including 1,8-cineole, camphor, α-thujone, and β-thujone. Generally, the highest values of these oxygenated monoterpenes were obtained from optimum irrigation and foliar spraying with amino acids (50% L-phenylalanine) under an organic farming system, which significantly influenced the quantity and quality of the biologically active compound of sage. In addition, the highest value of dry matter yield (972.97 g m− 2) was observed in the second experimental year in the interaction of 50% L-phenylalanine × 100% F.C. × cow dung manure, and also 943.52 g m− 2, was seen in the first year in the 50% L-phenylalanine × 100% F.C. × mycorrhizal symbiosis. Generally, the foliar spray of amino acids under organic inputs (AMF and cow dung manure), and their interaction could ameliorate the dry matter yield and essential oil compounds of sage in environmentally friendly agriculture conditions.
Escin induces PANoptosis of Pancreatic ductal adenocarcinoma in tumor microenvironment by targeting PTGS2
Authors: Zhang Qian , Wang Yulong , Hu Wensi , Liu Ju , chen Zhao , Tian Hu , Tian Hui 
Published: September 2024

Abstract

Background
Pancreatic ductal adenocarcinoma (PDAC) is known as the “King of Cancer” and has a low survival rate. The occurrence and development of PDAC are complex biological processes. Tumor microenvironment (TME) surrounding pancreatic cancer cells is a key determinant of tumor growth, metastatic potential, and treatment resistance. These PDAC complex properties indicate that a single pathway cannot inhibit tumor growth.
Purpose
Escin, a natural triterpene saponin extracted from plants, has been demonstrated to exert anticancer effects in various cancer cell models. In current study, we aim to investigate the effects of Escin on PDAC in TME and explore its potential molecular mechanisms.
Methods and Results
We evaluated cell migration, invasion, clonogenicity, and cell cycle of PDAC, and found that it has anti-PDAC effects compared with Gemcitabine. To understand the mechanism of Escin, we found that Escin can induce PANoptosis of PDAC in the tumor microenvironment, increase the release of reactive oxygen species(ROS), and change the mitochondrial membrane potential. To further illustrate the mechanism, we used bioinformatics analysis and found that PTGS2 is one of the targets of Escin treated PDAC, and high expression of PTGS2 is associated with poor prognosis. To further explore the downstream of PTGS2, we used Celecoxib for comparison. Our results suggest that both Escin and Celecoxib can inhibit the expression of PTGS2. Additionally, the anti-PDAC effect is related to the PTGS2/STAT3/ERK signaling axis.
Conclusions
Escin can inhibit PDAC growth, block cell cycle and promote PANoptosis. These biological processes may be related to the release of ROS, changes of mitochondrial membrane potential, and downregulation of the PTGS2/STAT3/ERK pathways.
A Comprehensive Comparative Study of Individual ML Models and Ensemble Strategies for Network Intrusion Detection Systems
Authors: Bibers Ismail , Arreche Osvaldo , Abdallah Mustafa 
Published: September 2024

Abstract

The escalating frequency of intrusions in networked systems has spurred the exploration of new research avenues in devising artificial intelligence (AI) techniques for intrusion detection systems (IDS). Various AI techniques have been used to automate network intrusion detection tasks, yet each model possesses distinct strengths and weaknesses. Selecting the optimal model for a given dataset can pose a challenge, necessitating the exploration of ensemble methods to enhance generalization and applicability in network intrusion detection. This paper addresses this gap by conducting a comprehensive evaluation of diverse individual models and both simple and advanced ensemble methods for network IDS. We introduce an ensemble learning framework tailored for assessing individual models and ensemble methods in network intrusion detection tasks. Our framework encompasses the loading of input datasets, training of individual models and ensemble methods, and the generation of evaluation metrics. Furthermore, we incorporate all features across individual models and ensemble techniques. The study presents results for our framework, encompassing 14 methods, including various bagging, stacking, blending, and boosting techniques applied to multiple base learners such as decision trees, neural networks, and among others. We evaluate the framework using two distinct network intrusion datasets, RoEduNet-SIMARGL2021 and CICIDS-2017, each possessing unique characteristics. Additionally, we categorize AI models based on their performances on our evaluation metrics and via their confusion matrices. Our assessment demonstrates the efficacy of learning across most setups explored in this study. Furthermore, we contribute to the community by releasing our source codes, providing a foundational ensemble learning framework for network intrusion detection.
Comparative Study of Midterm Outcomes between Roux-en-Y Gastric Bypass (RYGB), Diverted One-Anastomosis Gastric Bypass (D-OAGB), and One Anastomosis Gastric Bypass (OAGB)
Authors: Masry Mohamed El , Rahman Islam Abdul , Elshal Mohamed , Maher Ahmed 
Published: September 2024

Abstract

Purpose
Diverted one anastomosis gastric bypass (D-OAGB) is a new procedure that entails performing Roux-en-Y diversion during OAGB to preclude post-OAGB bile reflux. This study aimed to compare the mid-term outcomes of Roux-en-Y gastric bypass (RYGB) and OAGB versus D-OAGB.
Methods
This is a retrospective study that encompassed the analysis of data from patients undergoing bypass surgeries from 2015 to May 2021. The patients’ data until 2 years of follow-up were compared.
Results
This study included 140 patients who underwent OAGB (n = 64), RYGB (n = 24), and D-OAGB (n = 52). In the OAGB, RYGB, and D-OAGB groups, complication rates were 3.1%, 8.3%, and 5.8%, respectively. At the 3-month and 6-month follow-ups, the OAGB and D-OAGB groups showed statistically significant higher percentage of excess weight loss (EWL%). Otherwise, the weight measures and weight loss outcome were comparable among the three groups in the other follow-up visits (p > 0.05). There was a significantly lower number of gastroesophageal reflux disease (GERD) remission cases and a higher number of de novo GERD cases in the OAGB group.
Conclusion
D-OAGB demonstrated favorable outcomes, including lower early adverse events and superior weight loss results in the first 6 months post-surgery when compared to RYGB. The D-OAGB group also showed higher rates of GERD remission and lower de novo GERD occurrence than OAGB. Further research is warranted to validate these findings and expand our understanding of this innovative surgical approach.
Factors influencing walking practice among urban residents before and after the COVID-19 pandemic
Authors: Park Jeongsun , Shon Changwoo 
Published: September 2024

Abstract

Background
Walking is vital for urban residents' health, but the COVID-19 pandemic has significantly altered daily life and walking practices. This study examinedthe factors influencing walking practices before and after COVID-19 at individual and community levels to understand the pandemic's impact on health behaviors and inform future public health strategies.
Methods
Secondary data from Korea's Community Health Survey (2018–2021) were analyzed, focusing on adults aged 19 and older in Busan Metropolitan City. Multilevel regression analysis was conducted on a total of 54,092 participants, and IBM SPSS Statistics 27.0 was used for statistical analysis. For the multilevel regression analysis, individual-level factors included demographic and social characteristics, health behavior, and subjective perceptions of the community. Community-level factors included urban parks, pedestrian paths, vehicular roads, public and private sports facilities, traditional markets, and social network difficulty.
Results
At the individual level, walking decreased among women and overall from 0.98 (95% CI: 0.97–0.99) before COVID-19 to 0.92 (95% CI: 0.91–0.93) after COVID-19 but increased among those aged 65 and older from 0.96 (95% CI: 0.94–0.99) to 1.05 (95% CI: 1.02–1.08). Subjective health status declined from 1.10 (95% CI: 1.08–1.12) to 1.05 (95% CI: 1.03–1.07). Obesity (OR=0.98, 95% CI: 0.96–1.00) and depression (OR=0.93, 95% CI: 0.90–0.96) were associated with lower walking, while individuals with one chronic disease (OR=1.04, 95% CI: 1.02–1.06) and smokers (OR=1.07, 95% CI: 1.04–1.09) walked more. Neighbors’ trust (OR=1.04, 95% CI: 1.02–1.06) and neighborhood safety (OR=1.03, 95% CI: 1.00–1.06) positively influenced walking. At the community level, walking increased with more pedestrian paths before and after COVID-19. Traditional markets positively influenced walking before the pandemic (OR=1.01, 95% CI: 1.00–1.01. Social network difficulties were influenced bylower walking (OR=0.84, 95% CI: 0.77–0.93).
Conclusions
The study reveals significant changes in walking practices before and after COVID-19, influenced by individual factors such as sex, age, health status, and community factors like pedestrian paths, traditional markets, and social network difficulties. These insights highlight the need for targeted public health strategies to promote physical activity during global health crises.
A Reinforcement learning-Based GWO-RNN approach for Energy Efficiency in Data Centers by Minimizing Virtual Machine Migration
Authors: Parsafar Parsa 
Published: September 2024

Abstract

In the era of exponential data growth, data centers play a critical role in providing reliable and efficient computing resources. However, the energy consumption of these facilities has become a significant concern, driving the need for innovative solutions to enhance energy efficiency. This paper presents a novel approach to minimizing virtual machine (VM) migrations in data centers, thereby reducing energy consumption. Our model leverages a Recurrent Neural Network (RNN) optimized with a Grey Wolf Optimizer (GWO) to predict energy consumption and preemptively manage workloads. By incorporating this RNN, our model effectively anticipates the energy consumption of future, leading to make the best decision to migrate the VM or not. Furthermore, energy consumption is monitored in real-time to identify overloading and underloading of VMs. The reinforcement GWO-RNN framework adapts dynamically to changing workloads, ensuring optimal resource allocation and reducing the frequency of energy-intensive VM migrations. Experimental results demonstrate a significant reduction in energy consumption and improved efficiency in data center operations, showcasing the potential of this approach for sustainable computing.
Electrode-electrolyte interactions on oxide surfaces: the crucial role of surface redox chemistry
Authors: Mom Rik V. , Deka Nipon , Bernsmeier Denis , Jones Travis , Irtem Erdem , Trzesniowski Hanna , Louisia Sheena , Kolmeier Kees E. , Gorgoi Mihaela , Zeller Patrick 
Published: September 2024

Abstract

The electric double layer (EDL) formed by ions at the electrode-electrolyte interface is a fundamental component of any electrochemical system, ranging from batteries to fuel cells and electrolyzers1. At the atomic level, the behavior of the EDL varies greatly with the choice of electrode, electrolyte, and conditions2,3. However, it is thought to follow one general rule analogous to a capacitor4,5: low electrode potentials lead to a negative electrode surface charge which attracts cations to the EDL, whereas high potentials lead to a positive surface charge and anion attraction. Here, we show that this most basic rule does not apply for the oxide-electrolyte interface. Using an interface-sensitive X-ray absorption spectroscopy (XAS) approach, we show that increasing the electrode potential attracts cations and repels anions at the IrO2-electrolyte interface. We show that this behavior is driven by the surface redox chemistry of the oxide, which dictates the surface charge of the electrode by modulating the surface electrophilicity. Our findings rationalize the cation-dependent performance trends observed for oxide electrodes6–9, paving the way to exploit them in electrolyte engineering.