bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evaluating the Probiotic Potential of Lactic Acid Bacteria Isolated from Nipponia nippon Feces
Authors: Yang Lei , luo Jie , Zeng Yan , Zhang Baoyue , Wang Yang , Zhao Xiaoling , Lin Juchun , Li Haohuan , Xu Funeng , Zhang Wei , Fu Hualing , Amevor Felix Kwame , Liu Rui , Shu Gang 
Published: October 2024

Abstract

This study aims to identify an optimal lactic acid bacterial strain from the feces of healthy Nipponia nippon. From the fecal samples, twenty isolates were obtained. The isolates were subjected to biochemical identification, acid and bile tolerance tests, in vitro inhibition of pathogenic bacteria assays, cell surface hydrophobicity assessment, antibiotic susceptibility test, and hemolytic activity evaluation to determine their probiotic potential. The results indicated that six isolates (D1, D2, D6, E7, D8, D9) could survive in low acid and high bile salt conditions. Except for D8, all six isolates exhibited inhibitory activity against tested pathogens. Isolates D6 and E7 showed the least resistance to antibiotics, and only E7 demonstrated moderate hydrophobicity. The E7 strain was further studied in depth and identified as L. plantarum through 16srRNA sequencing. To assess its safety, mice were fed with the E7 strain, and the results showed no deaths or adverse effects on blood cellular components. Whole genome sequencing of Lactobacillus plantarum E7 using Nanopore PromrthION48 and the Illumina Novaseq revealed a ring chromosome and two ring plasmids. The chromosome encodes 3024 genes, some associated with cell adhesion, acid and bile salt tolerance, antioxidant enzymes, and secondary metabolites. Plasmids contained fewer coding genes. The VFDB database detected only a few virulence genes related to adherence, stress survival, exoenzyme production, immune modulation, and regulation factors. KEGG database analysis indicated that the genes of this bacterium are primarily involved in carbohydrate metabolism, amino acid metabolism, vitamin and cofactor metabolism, environmental information processing and genetic processing. This study lays a theoretical foundation for the clinical application and development of probiotics.
Alleviation of Myocardial Infarction by Hydrogen Sulfide-Releasing Nanoparticles: Mechanisms and Therapeutic Effects
Authors: Zhan Yujia , Zhao Xueshan , Bi Siwei , Liu Ruiqi , Ge Yuxuan , Gu Jun , Wang Yin 
Published: October 2024

Abstract

Myocardial infarction (MI), a common and severe disease threatening human health worldwide, results from ischemic and hypoxic-induced necrosis of cardiac tissue due to coronary artery obstruction or rupture. Hydrogen sulfide (H2S) is a gasotransmitter involved in various physiological and pathological processes. Exogenous supplementation of H2S is significantly beneficial for the treatment of MI. In this study, a novel H2S donor - zinc sulfide nanoparticles encapsulated in hyaluronic acid (HA@ZnS NPs), has been developed through a biomimetic mineralization process for the treatment of MI. HA@ZnS NPs can stably release H2S at the site of myocardial ischemic injury due to the acidic microenvironment. Compared to the MI group, the NP-treated group significantly improved cardiac function, including increased left ventricular ejection fraction and fractional shortening, as well as reduced end-systolic volume. Furthermore, the NPs significantly reduced the size of the myocardial infarction area, improved left ventricular remodeling, and exerted therapeutic effects by promoting angiogenesis and reducing apoptosis in cardiac tissue. In conclusion, HA@ZnS NPs demonstrate potential for treating MI through precise control of H2S release, providing valuable insights into new therapies for MI and laying the groundwork for the clinical application of H2S-releasing materials in the future.
Deep insight: An Efficient Hybrid Model for Oil Well Production Forecasting Using Spatio-Temporal Convolutional Networks and Kolmogorov-Arnold Networks
Authors: Hu Yandong , Xin Xiankang , Yu Gaoming , Deng Wu 
Published: October 2024

Abstract

As global energy demand continues to grow, the oil and gas industry faces increasing pressure to optimize production and achieve sustainability. Accurate prediction of oil well production is essential for effective resource management and operational efficiency. However, traditional mathematical methods struggle with the complex nonlinear characteristics of production data, and while hybrid neural networks have shown promise, they often lack sensitivity to changes in production conditions and suffer from limited generalization due to their complex architectures and numerous parameters. To overcome these limitations, this study introduces a novel hybrid model that integrates Temporal Convolutional Networks (TCN) with Kolmogorov-Arnold Networks (KAN), optimized by Whale Optimization Algorithm (WOA). This approach significantly reduces parameter complexity while enhancing global optimization, resulting in improved model robustness and adaptability. TCN excels in capturing the spatio-temporal dynamics of fluid and reservoir properties, while KAN, with its strong nonlinear approximation capabilities, efficiently approximates functions with minimal hyperparameter tuning. Experiments conducted using data from the Volvo oil field (2008-2016) demonstrate that the WOA-TCN-KAN model outperforms other hybrid models in global search, spatio-temporal feature extraction, and nonlinear approximation, offering superior predictive accuracy and robustness in complex oil well production scenarios. This model provides strong support for improving operational efficiency in oil and gas reservoir development.
A comparative encapsulation behaviour analysis and biological studies of C- alkyl calix[4]resorcinarenes-4-hydroxybenzoic acid inclusion complexes
Authors: Kasi Sathiyaseelan , Albert Antony Muthu Prabhu 
Published: October 2024

Abstract

In this work, we are reported the comparative encapsulation behaviour analysis and biological applications of C-alkyl calix[4]resorcinarenes:4-hydroxybenzoic acid (C4RAs-4HBA) inclusion complexes. The solvent evaporation method was applied to prepare the solid C4RAs-4HBA (5a-5d) inclusion complexes. Phase solubility analysis and jobs plot method was used to identify the stoichiometric binding ratio, stability constant (K), complexation efficiency (CE) and type of phase solubility diagram formed between the aqueous solution of C4RAs (3a-3d) and 4HBA (compound 4). From the results of UV-Visible, fluorescence, 1H-NMR, 13C-NMR, PXRD and SEM imaging analysis was confirmed by formation of 1:1 ratio of C4RAs-4HBA inclusion complexes between C4RAs (3a-3d) and 4HBA (compound 4). In gas phase DFT/B3LYP 3-21G method of molecular modeling studies were applied to identify the more stable and reactive binding orientation (A or B) from the values of band gap energy, energy and complexation energy values. A redox a reaction of phosphomolybdate assay was used to find out the informations of total antioxidant capacity (TAC), % total antioxidant capacity (% TAC) and IC50 values. Kirby-Bauer antibacterial activity and Disc diffusion antifungal activity of C4RAs, 4HBA and their inclusion complexes were compared with the standard antibacterial (amikacin) and antifungal (nystain) drugs.
Physical and Social Health Needs of Postoperative Bariatric Surgery Patients: A Focus Group.
Authors: Glauser Angela C. , PT Robin L. Marcus , McGarrity Larissa A. , PT Anne Thackeray , Volckmann Eric T. , Terrill Alexandra L. 
Published: October 2024

Abstract

Purpose
This qualitative study explored the health needs of patients after undergoing bariatric surgery. The study specifically aimed to describe the unique physical, emotional, and social challenges patients face following surgery in order to inform the development of future obesity treatment programs.
Methods
A ninety-minute focus group was conducted using a semi-structured interview guide. Bariatric surgery patients were enrolled using purposive sampling. The mean number of months since surgery was 20.2 (SD 10.8). The mean age of participants was 53.3 (SD 9.8) years. The focus group was both audio and video recorded, transcribed, and analyzed using topic and analytical coding.
Results
Three main themes emerged revealing postoperative needs for 1) assistance with physical changes and reduced barriers to exercise, 2) reinforcement for healthy eating behaviors, and 3) emotional support from peers, family, and community.
Conclusions
Findings suggest that rehabilitation following bariatric surgery is complex in nature and patients may benefit from both pre- and post-surgery programs that address their unique needs. Weight maintenance and sustaining healthy behavior change post-surgery requires ongoing personal and professional assistance. Interventions should emphasize healthy eating practices, include practical exercise suggestions, and offer social and emotional support.
Research and Implementation of an Authentication System Fusing Physical Layer and Behavioural Fingerprinting for Power Systems
Authors: Chen Mu , Li Nige , Li Yong , Zhang Bo , Xiao Yongcai , Wang Tengyan , Lu Ziang 
Published: October 2024

Abstract

With the rapid growth of resource integration in modern power systems, these resources are diverse, large-scale, and situated in complex and open physical environments, making them relatively vulnerable to cyber-attacks due to weaker security measures. To address this challenge, this paper proposes an identity authentication architecture system that integrates software and hardware. In the software fingerprint section, we extract packet characteristics and statistical features through network probing, and combine them with time difference sequence features obtained from side-channel monitoring to generate the software fingerprint of the power smart terminal by direct concatenation. This method incorporates various characteristic information, enhancing the recognition accuracy of the fingerprint features. In the hardware fingerprint section, we generate hardware fingerprints by extracting the preamble signal and performing statistical feature analysis. Finally, using an ensemble learning method, we integrate the software and hardware fingerprints to generate device fingerprint features. This approach effectively addresses the security authentication issue of power equipment based on High-Level Power Line Communication (HPLC), achieving a recognition rate of over 95% under most machine learning classification methods.
Predicting software defects: a comprehensive analysis of machine learning approaches
Authors: Sistaninezhad Masoud , Rajebi Saman , Pouramirarsalani Shahrzad , Pakzad Sajjad , Asadi Houshyar , Pedrammehr Siamak 
Published: October 2024

Abstract

In software development, achieving flawless software is essential for maintaining quality and reducing testing costs. Predicting software defects is a crucial aspect of enhancing software quality. This paper explores various techniques, including feature selection, principal component analysis, and fisher discriminant ratio, utilizing well-known machine learning algorithms on the publicly available JM1 dataset, addressing the gap in the current literature. support vector machine, multi-layer perceptron, K-nearest neighbor, Naïve Bayes, and decision tree algorithms are utilized along with the K-Fold approach for class label classification. Additionally, a binary genetic algorithm with a support vector machine classifier is employed for feature selection, and a particle swarm optimization algorithm is used to determine optimal fisher discriminant ratio coefficients. Model performance is evaluated according to accuracy, sensitivity, specificity, F-measure, precision, and a confusion matrix. The findings indicate that all machine learning models perform well with different processing techniques. However, the support vector machine algorithm, when combined with optimal fisher discriminant ratio coefficients, achieved the highest accuracy at 88.2% and excelled in specificity at 99.6%. The K-nearest neighbor classifier with selected features attained the highest scores in precision, sensitivity, and F-measure. Other classification algorithms did not surpass these models in any performance metrics.
Mapping Seismic Vulnerability index on Durban using the spectral ratio Local site effects using Ambient noise Measurements for Durban
Authors: Manzunzu Brassnavy , Midzi Vunganai , Zulu Brian , Mulabisana Thifhelimbilu , Pule Tebogo 
Published: October 2024

Abstract

Ambient noise vibrations are widely used in the field of geotechnical earthquake engineering for site response analysis. Though generally weak, these vibrations are available anywhere and anytime and are an ideal source of energy for conducting seismic surveys. The use of horizontal to vertical spectral ratio (H/V) from ambient noise records, to characterise local site effects is now an established technique. This technique can be applied to estimate predominant frequencies, amplitude ratios and seismic vulnerability index of an area. Ninety sites were selected in Durban (KwaZulu-Natal Province) for ambient vibration measurements and H/V analysis. The analysis of recorded waveforms resulted in the determination of predominant frequencies as well as the amplitude ratios that can be assumed to be equivalent to amplification factors, allowing the city to be divided into zones of differing site effects. The results showed predominant frequencies ranging between 0.78 and 36.8 Hz and peak amplitude ratios in the interval 1.3 to 30.0. The predominant frequency and amplitude ratio results were then used to estimate a seismic vulnerability index, which was observed to vary from 0.2 to 87.3. The city was then successfully divided into three zones according to the obtained vulnerability index values. High vulnerability index values were found to correlate with coastal areas, thus indicating areas that are likely to suffer significant amplification of earthquake ground motion. These coastal areas are associated with thick sediments and alluvial plains, conditions which have been shown in many studies to have a significant impact on ground motion resulting in amplification. Building structures with natural frequencies close to the site predominant frequencies in these areas will experience large resonance effects. This study can be considered as a first step towards the microzonation of the city of Durban.
Rapeseed Protein Isolate in High-Fat Diet-Induced Obesity Reduction: A Study on Amino Acids and Their Biological Effects
Authors: Xu Feiran , Tang Juan , Ji Tong , Wang Yu , Tao Xuan , Xiong Zheng , Zhang Bao , Wang Zhigao 
Published: October 2024

Abstract

Current pharmacological treatments have not been effective in achieving sustainable and long-term weight loss. Studies have shown that reducing dietary fat alone is not sufficient to prevent weight gain and obesity. Proteins are used to change diet and cause weight loss. Rapeseed plant protein is a high-quality protein, and RPI provides all essential amino acids needed for proper nutrition. However, the suitability of RPI as a dietary protein source for weight loss and its potential effects on plasma amino acid levels in lower floating cells and the induction of satiety in lower floating cells remains unknown. Therefore, we analyzed the amino acid composition of rapeseed protein isolate (RPI) and evaluated its effect on high-fat diet-induced obesity using in vivo and in vitro models. The RPI group exhibited elevated levels of anti-obesity amino acids in the plasma compared to the CS and SPI groups, leading to reduced food intake, weight gain, Lee index, white adipose tissue weight, improved serum lipid profiles, and beneficial alterations in the intestinal microbiota of obese rats. Molecular analyses elucidated RPI’s role in metabolic signaling, revealing its activation of Mammalian Target of Rapamycin/p70S6K (mTOR/p70S6K) pathway, inhibition of AMP-activated protein kinase (AMPK) and Acetyl-CoA carboxylase (ACC) phosphorylation, and modulation of the melanocortin system by increasing α-Melanocyte-Stimulating Hormone (α-MSH) and Melanocortin 4 Receptor (MC4R) levels in paraventricular nucleus neurons. These findings suggest that RPI could potentially reduce obesity through amino acid-mediated inhibition, appetite suppression, and increased metabolism.
Development and validation of a novel endoplasmic reticulum stress-related lncRNA signature in laryngeal squamous cell carcinoma
Authors: Pan Xiazhi , Liu Duanshali , Xie Yingli , Li Beicheng , Zhang Shanshan , Li Gege , Li Xiaohan , Zheng Qiuchen , Zhao Kai , Liu Mingbo 
Published: October 2024

Abstract

Background Endoplasmic reticulum stress (ERS) is an intracellular process in which improperly folded proteins lead to a cellular stress response. Such responses serve to protect cells from damage and are tightly bound to the development and advancement of various tumors. How endoplasmic reticulum stress contributes to the onset and progression of laryngeal squamous cell carcinoma remains unclear. Our research aimed to find an ERS signature to forecast the prognosis of laryngeal squamous cell carcinoma and to investigate its potential biological functions.
Method LSCC sample data obtained from The Cancer Genome Atlas (TCGA) database were co-expressed with ERS- related genes, and then a prognostic signature on the basis of endoplasmic reticulum stress- related lncRNAs (ERS-related lncRNAs) was constructed by differential analysis and Cox regression analysis. Survival analysis, TMB, consensus cluster analysis, drug sensitivity analysis, immune analysis and clinical drug prediction were carried out on the model. Finally, the function of LHX1-DT was verified by in vitro experiments.
Results From the TCGA-LSCC cohort, 35 significantly different ERS-related lncRNAs were identified. Then, a prognostic signature consisting of three lncRNAs (AC110611.2, LHX1-DT, and AL157373.2) was identified. Kaplan-Meier analysis demonstrated the predictive ability of the model for overall survival. Calibration curves and receiver operating characteristic curves were validated and showed high predictive accuracy. Ultimately, the experimental results verified the expression of LHX1-DT in LSCC.
Conclusion Our work built an ERS-related risk signature, providing a useful exegesis for LSCC prognosis prediction.
A Case Report of Acute Fatty Liver of Pregnancy
Authors: Liao Wei , Luo Qian , Wang LiFei , Liu RuiQian 
Published: October 2024

Abstract

Objective: Report on a rare pregnancy complication.
Background: Acute fatty liver of pregnancy (AFLP) is one of the most common causes of acute liver failure during pregnancy, although its incidence is low. The primary pathological change is diffuse microvesicular steatosis of hepatocytes. The manifestations of AFLP are nonspecific, and its diagnosis typically relies on clinical symptoms, laboratory findings, and the Swansea criteria as an auxiliary diagnostic tool. Early diagnosis and timely termination of pregnancy are crucial measures to improve outcomes.
Case Description: A 23-year-old woman, at 38+5 weeks of gestation, G1P0, presented with a 10-day history of abdominal distension, nausea, vomiting, and constipation, with only the ability to consume small amounts of liquid food. The patient reported a long-term preference for carbonated beverages and an aversion to drinking plain water. Upon admission, physical examination revealed severe jaundice of the skin and sclera. Laboratory tests indicated elevated liver enzymes, increased total bilirubin, abnormal kidney function, and coagulopathy. Abdominal ultrasound revealed abnormalities. The patient’s Swansea score was 6, leading to a diagnosis of AFLP, and an emergency cesarean section was performed. The patient’s liver enzymes improved within a day post-surgery, but persistent coagulopathy postoperatively led to the development of an abdominal subcutaneous hematoma. After treatment with clotting factor supplementation, coagulation function gradually improved within four days.
Conclusion: Early detection and timely termination of pregnancy can improve outcomes in cases of AFLP. Post-cesarean section, vigilance is required for persistent coagulopathy, which may lead to the development of abdominal subcutaneous hematomas.
Thermodynamics and effectiveness of biomolecules and electron-acceptors in an ecologically engineered wetland – Implications for the design and optimisation
Authors: Hansen Robert Neill , Vuuren Mariette Jansen van , Oberholster Paul 
Published: October 2024

Abstract

In this study redox models were developed for each of the three sample sites to calculate the most effective biomolecule-electron acceptor pairs as a function of pH. The study effectively demonstrated the importance of considering biomolecular substrates available in ecologically engineered wetland systems in conjunction with the specific electron acceptors and redox reaction products in optimising specific wetland functions e.g., denitrification. The study indicated that the pH of the wetland water column and soil pore water is an important factor in controlling which biomolecules are most effectively oxidised by which specific electron donors. The pH intersect point can be calculated and observed on Eh-pH diagrams of the electron acceptors oxidising the various biomolecules input into the model and of biomolecules reducing various electron acceptors input into the model. Wetland water quality monitoring data thus is important in managing ecologically engineered wetlands, so the correct biomolecular substrates are added to optimise specific redox reactions e.g., denitrification. The model also indicated that Fe(OH)3 as an electron acceptor is more or less effective depending on the reaction products of the reaction e.g., magnetite, more effective, or Fe2+, less effective. This observation indicates that the effectiveness of the various redox reaction in ecologically engineered wetland systems may be highly dependent on the specific reaction products that form from these reactions. This implies a foreknowledge of the products that could form in redox reactions in specific engineered wetlands, underlining the importance of geochemical modelling in the design and optimisation of ecologically engineered wetland systems.
Effect of high-purity Ag@ ZnO Core shell nanoparticles synthesized by pulse laser ablation technique: Evaluation of Skin cancer cells
Authors: Khudhair Ali A. , Mazhir Sabah N. , Hammed Mohammed 
Published: October 2024

Abstract

Silver and zinc oxide nanoparticles with a core-shell structure were synthesized using pulsed laser ablation (Nd: YAG laser) in deionized water, a straightforward method requiring minimal lab conditions. The optical properties and energy gap were assessed via UV-visible spectroscopy. Transmission electron microscopy identified the core-shell structure, spherical shape, and size (52 nm). Atomic force microscopy revealed semi-smooth surface roughness, while field emission scanning electron microscopy confirmed a homogeneous surface. X-ray diffraction provided ideal peak patterns for crystal size calculations. Energy-dispersive X-ray spectroscopy (EDX) showed a higher ZnO content compared to Ag, indicating an effective coating of silver by zinc oxide to reduce toxicity. The high purity of the samples (only Ag and ZnO nanoparticles) ensured accurate property determination and biological effect assessment. The study leverages the anti-skin cancer properties of both nanoparticles: Ag nanoparticles, with their small size and large surface area, interact effectively with cancer cells but have high toxicity, which is mitigated by the ZnO coating. ZnO also contributes to anti-cancer activity by generating reactive oxygen species that disrupt cell membranes. Zeta potential analysis indicated a moderate electrostatic equilibrium with a value of -15.2 mV for the core-shell nanoparticles. MTT assay results on A375 skin cancer cell lines confirmed that these nanoparticles are effective at certain concentrations, showing minimal effect on normal cells, suggesting their potential as a drug for skin cancer.