bluuebunny/crossref_metadata_2025 huggingface dataset:
Ownership of Cash Value Life Insurance among Rural Households: Utilization of Machine Learning Algorithms to Find Predictors
Authors: Heo Wookjae , Kwak Eun Jin , Grable John , Park Hye Jun
Published: August 2024

This study examines the determinants of life insurance ownership with a focus on rural areas and farming households in the United States. Utilizing data from online surveys conducted in 2019 and 2021, this paper explores how psychological factors, financial knowledge, and household characteristics influence life insurance ownership. Traditional indicators like wealth, income, and age were evaluated alongside less frequently discussed variables such as farm loans and rural residency. Machine learning techniques, including neural networks, Support Vector Machine modeling, Gradient Boosting, and logistic regression, were employed to identify the most robust predictors of life insurance demand. The findings reveal that farming-associated factors, particularly holding a farm loan and living in a farming household, significantly predict life insurance ownership. The study also highlights the complexity of life insurance demand, showing that financial education and management practices are critical determinants. This research underscores the need for tailored financial risk management strategies for rural and farming households and contributes to a nuanced understanding of life insurance demand in varying contexts.
On the Optimization of Kubernetes toward the Enhancement of Cloud Computing
Authors: Mondal Subrota Kumar , Zheng Zhen , Cheng Yuning
Published: August 2024

With the vigorous development of big data and cloud computing, containers are becoming the main platform for running applications due to their flexible and lightweight features. Using a container cluster management system can more effectively manage multiocean containers on multiple machine nodes, and Kubernetes has become a leader in container cluster management systems, with its powerful container orchestration capabilities. However, the current default Kubernetes components and settings have appeared to have a performance bottleneck and are not adaptable to complex usage environments. In particular, the issues are data distribution latency, inefficient cluster backup and restore leading to poor disaster recovery, poor rolling update leading to downtime, inefficiency in load balancing and handling requests, poor autoscaling and scheduling strategy leading to quality of service (QoS) violations and insufficient resource usage, and many others. Aiming at the insufficient performance of the default Kubernetes platform, this paper focuses on reducing the data distribution latency, improving the cluster backup and restore strategies toward better disaster recovery, optimizing zero-downtime rolling updates, incorporating better strategies for load balancing and handling requests, optimizing autoscaling, introducing better scheduling strategy, and so on. At the same time, the relevant experimental analysis is carried out. The experiment results show that compared with the default settings, the optimized Kubernetes platform can handle more than 2000 concurrent requests, reduce the CPU overhead by more than 1.5%, reduce the memory by more than 0.6%, reduce the average request time by an average of 7.6%, and reduce the number of request failures by at least 32.4%, achieving the expected effect.
Maximizing Computation Rate for Sustainable Wireless-Powered MEC Network: An Efficient Dynamic Task Offloading Algorithm with User Assistance
Authors: He Huaiwen , Huang Feng , Zhou Chenghao , Shen Hong , Yang Yihong
Published: August 2024

In the Internet of Things (IoT) era, Mobile Edge Computing (MEC) significantly enhances the efficiency of smart devices but is limited by battery life issues. Wireless Power Transfer (WPT) addresses this issue by providing a stable energy supply. However, effectively managing overall energy consumption remains a critical and under-addressed aspect for ensuring the network’s sustainable operation and growth. In this paper, we consider a WPT-MEC network with user cooperation to migrate the double near–far effect for the mobile node (MD) far from the base station. We formulate the problem of maximizing long-term computation rates under a power consumption constraint as a multi-stage stochastic optimization (MSSO) problem. This approach is tailored for a sustainable WPT-MEC network, considering the dynamic and varying MEC network environment, including randomness in task arrivals and fluctuating channels. We introduce a virtual queue to transform the time-average energy constraint into a queue stability problem. Using the Lyapunov optimization technique, we decouple the stochastic optimization problem into a deterministic problem for each time slot, which can be further transformed into a convex problem and solved efficiently. Our proposed algorithm works efficiently online without requiring further system information. Extensive simulation results demonstrate that our proposed algorithm outperforms baseline schemes, achieving approximately 4% enhancement while maintain the queues stability. Rigorous mathematical analysis and experimental results show that our algorithm achieves O(1/V),O(V) trade-off between computation rate and queue stability.
Multi-Layer Feature Restoration and Projection Model for Unsupervised Anomaly Detection
Authors: Cai Fuzhen , Xia Siyu
Published: August 2024

The anomaly detection of products is a classical problem in the field of computer vision. Image reconstruction-based methods have shown promising results in the field of abnormality detection. Most of the existing methods use convolutional neural networks to build encoding–decoding structures to do image restoration. However, the limited receptive field of convolutional neural networks makes the information considered in the image restoration process limited, and the downsampling in the encoder causes information loss, which is not conducive to performing fine-grained restoration of images. To solve this problem, we propose a multi-layer feature restoration and projection model (MLFRP), which enables the restoration process to be carried out on multi-scale feature maps through a block-level feature restoration module that fully considers the detail information and semantic information required for the restoration process. We conducted in-depth experiments on the MvtecAD anomaly detection benchmark dataset, which showed that our model outperforms current state-of-the-art anomaly detection methods.
Child Health Dataset Publishing and Mining Based on Differential Privacy Preservation
Authors: Li Wenyu , Wang Siqi , Wang Hongwei , Lu Yunlong
Published: August 2024

With the emergence and development of application requirements such as data analysis and publishing, it is particularly important to use differential privacy protection technology to provide more reliable, secure, and compliant datasets for research in the field of children’s health. This paper focuses on the differential privacy protection of the ultrasound examination health dataset of adolescents in southern Texas from three aspects: differential privacy protection with output perturbation on basic statistics, publication of differential privacy marginal histogram and synthesized data, and a machine learning differential privacy learning algorithm. Firstly, differential privacy protection results with output perturbation show that Laplace and Gaussian mechanisms for numerical data, as well as the exponential mechanism for non-numerical data, can achieve the goal of protecting privacy. The exponential mechanism provides higher privacy protection. Secondly, a differential privacy marginal histogram with four attributes can be obtained with an appropriate privacy budget that approximates the marginal histogram of the original data. In order to publish synthetic data, we construct a synthetic query to obtain the corresponding differential privacy histogram for two attributes. Further, a synthetic dataset can be constructed by following the data distribution of the original dataset and the quality of the synthetic data publication can also be evaluated by the mean square error and error rate. Finally, consider a differential privacy logistic regression model under machine learning to predict whether children have fatty liver in binary classification tasks. The experimental results show that the model combined with quadratic perturbation has better accuracy and privacy protection. This paper can provide differential privacy protection models under different demands, which provides important data release and analysis options for data managers and research organizations, in addition to enriching the research on child health data releasing and mining.
A Novel Radial Basis and Sigmoid Neural Network Combination to Solve the Human Immunodeficiency Virus System in Cancer Patients
Authors: Sabir Zulqurnain , Dirani Sahar , Bou Saleh Sara , Mabsout Mohamad Khaled , Arbi Adnène
Published: August 2024

The purpose of this work is to design a novel process based on the deep neural network (DNN) process to solve the dynamical human immunodeficiency virus (HIV-1) infection system in cancer patients (HIV-1-ISCP). The dual hidden layer neural network structure using the combination of a radial basis and sigmoid function with twenty and forty neurons is presented for the solution of the nonlinear HIV-1-ISCP. The mathematical form of the model is divided into three classes named cancer population cells (T), healthy cells (H), and infected HIV (I) cells. The validity of the designed novel scheme is proven through the comparison of the results. The optimization is performed using a competent scale conjugate gradient procedure, the correctness of the proposed numerical approach is observed through the reference results, and negligible values of the absolute error are around 10−3 to 10−4. The database numerical solutions are achieved from the Runge–Kutta numerical scheme, and are used further to reduce the mean square error by taking 72% of the data for training, while 14% of the data is taken for testing and substantiations. To authenticate the credibility of this novel procedure, graphical plots using different performances are derived.
Evaluation of the Impact of Stress Distribution on Polyurethane Trileaflet Heart Valve Leaflets in the Open Configuration by Employing Numerical Simulation
Authors: Masheane Lebohang Reginald , du Preez Willie , Combrinck Jacques
Published: August 2024

It is costly and time-consuming to design and manufacture functional polyurethane heart valve prototypes, to evaluate and comprehend their hemodynamic behaviour. To enhance the rapid and effective design of replacement heart valves, to meet the minimum criteria of FDA and ISO regulations and specifications, and to reduce the length of required clinical testing, computational fluid dynamics (CFD) and finite element analysis (FEA) were used. The results revealed that when the flexibility of the stent was taken into consideration with a uniform leaflet thickness, stress concentration regions that were present close to the commissural attachment were greatly diminished. Furthermore, it was found that the stress on the leaflets was directly impacted by the effect of reducing the post height on both rigid and flexible stents. When varying the leaflet thickness was considered, the high-stress distribution close to the commissures appeared to reduce at thicker leaflet regions. However, thicker leaflets may result in a stiffer valve with a corresponding increase in pressure drop. It was concluded that a leaflet with predefined varying thickness may be a better option.
The Influence of Circulating Immune Cell and CA125 Dynamics on Neoadjuvant Therapy Selection for Advanced Ovarian Cancer
Authors: Lazar Alexandra , Popa Ana Maria , Orlov-Slavu Cristina , Cotan Horia-Teodor , Iaciu Cristian Ion , Olaru Cristina Mihaela , Schreiner Oliver Daniel , Ciobanu Romeo Cristian , Nitipir Cornelia
Published: August 2024

Background and Objectives: Ovarian cancer, including tubal and peritoneal cancer, is the third most common gynecological cancer and the leading cause of death from gynecological malignancies in developed countries. This study explores the prognostic value of the neutrophil-to-lymphocyte ratio (NLR) in determining the optimal duration of neoadjuvant chemotherapy (NACT) for advanced ovarian cancer. It also investigates the correlation between NLR dynamics and the KELIM score, a chemosensitivity marker, to enhance individualized therapeutic strategies. Materials and Methods: A total of 79 patients underwent NACT followed by interval debulking surgery (IDS) or palliative care. The data collected included demographic information, tumor characteristics, treatment modalities, and laboratory parameters. The baseline NLR (NLR-T0) and post-therapeutic NLR (NLR-T1) were calculated, and their variation (NLR∆) was analyzed. The KELIM score was determined using CA-125 values. Results: Patients with a high baseline NLR (≥2.5) had significantly worse progression-free survival (PFS) and overall survival (OS) compared to those with a low NLR (<2.5). A negative NLR∆ was associated with poorer PFS and OS. The KELIM score indicated a more effective treatment response, with higher scores correlating with better outcomes. The majority of patients achieved R0 resection, and those with favorable KELIM scores showed improved survival rates. Conclusions: The NLR is a valuable prognostic marker for assessing treatment response and guiding NACT duration in advanced ovarian cancer.
Renal Angiomyolipoma with Tumor Thrombus in the Inferior Vena Cava and Right Atrium Accompanied by Renal Cell Carcinoma: A Case Report
Authors: Shu Fan , Hao Yichang , Yan Ye , Lu Min , Ma Lulin , Deng Shaohui , Ge Liyuan , Zhang Shudong
Published: August 2024

Background: Renal angiomyolipoma (AML) without local invasion is generally considered benign. However, it may extend to the renal sinus, even the renal vein, or the inferior vena cava (IVC). In patients with non-tuberous sclerosis complex, coexistence of renal cell carcinoma (RCC) and renal AML is uncommon. Case presentation: A 72-year-old woman was incidentally found to have a solitary right renal mass with an IVC thrombus extending into the right atrium during a routine health checkup. Robot-assisted laparoscopic radical nephrectomy and thrombectomy were successfully performed through adequate preoperative examination and preparation. Two tumor lesions were found and pathologically confirmed as renal AML and RCC, and the tumor thrombus was derived from the renal AML. During the one-year follow-up period, no signs of recurrence or metastatic disease were observed. Conclusions: Renal AML with a tumor thrombus in the IVC and right atrium accompanied by RCC may occur, although rarely. In clinical practice, if preoperative manifestations differ from those of common diseases, rare diseases must be considered to avoid missed diagnoses. In addition, adequate examination and multidisciplinary discussions before making a diagnosis are necessary. For a level 4 tumor thrombus with no infringement of the venous wall, adoption of robot-assisted minimally invasive surgery, without extracorporeal circulation technology, is feasible.
Lung Ultrasound Efficacy in Monitoring Post-SARS-CoV-2 Pneumonia and Inflammatory Biomarkers in Pediatric Patients
Authors: Chelcea Ramona , Dediu Mihaela , Dabica Diana , Laitin Sorina Maria Denisa , Ciuca Ioana Mihaiela
Published: August 2024

Background and Objectives: Recognizing the crucial gaps in our understanding of pediatric pneumonia post-SARS-CoV-2 infection, this study aimed to assess the relationship between Pediatric Pneumonia Ultrasound Scores (PedPne) and inflammatory biomarkers. The primary objective of this study is to evaluate the predictive value of PedPne in comparison with inflammatory biomarkers (IL-6 and dNLR) for the development of pneumonia in pediatric patients following SARS-CoV-2 infection. Materials and Methods: This longitudinal observational study collected data from pediatric patients diagnosed with pneumonia after an acute SARS-CoV2 infection. The study focused on analyzing changes in PedPne scores and inflammatory markers such as IL-6 and dNLR from initial admission to follow-up at 7 days. Statistical analysis involved calculating the sensitivity, specificity, and Area Under the Curve (AUC) for each biomarker, alongside regression analysis to determine their hazard ratios for predicting pneumonia development. Results: The analysis identified significant cutoff values for dNLR at 1.88 (sensitivity 77.0%, specificity 85.7%, AUC 0.802, p < 0.001), IL-6 at 6.1 pg/mL (sensitivity 70.3%, specificity 92.9%, AUC 0.869, p < 0.001), and PedPne score at 3.3 (sensitivity 75.7%, specificity 78.6%, AUC 0.794, p < 0.001). Conversely, NLR showed lower diagnostic performance (AUC 0.485, p = 0.327). Regression analysis further highlighted the strong predictive power of these markers, with IL-6 showing a fourfold increase in pneumonia risk (HR = 4.25, CI: 2.07–9.53, p < 0.001), dNLR indicating more than a twofold increase (HR = 2.53, CI: 1.19–6.97, p = 0.006), and PedPne score associated with more than a doubling of the risk (HR = 2.60, CI: 1.33–5.18, p < 0.001). Conclusions: The study conclusively demonstrated that both PedPne ultrasound scores and specific inflammatory biomarkers such as dNLR and IL-6 are significant predictors of pneumonia development in pediatric patients post-COVID-19 infection. These findings advocate for the integration of these biomarkers in routine clinical assessments to enhance the diagnostic accuracy and management of pneumonia in children following SARS-CoV-2 infection.
Current Status and Future Directions of Bone Trauma Surgery
Authors: Dumic-Cule Ivo
Published: August 2024

The ever-evolving field of bone trauma surgery and bone regeneration is characterized by continuous transformation due to advancements in medical technology, enhancements in surgical techniques, and a deeper understanding of biological interactions underlying the processes of bone healing and regeneration [...]
Competence of Combined Low Dose of Human Chorionic Gonadotropin (HCG) and Clomiphene Citrate (CC) Versus Continued CC during Ovulation Induction in Women with CC-Resistant Polycystic Ovarian Syndrome: A Randomized Controlled Trial
Authors: Thabet Mahmoud , Abdelhafez Mohamed Sayed , Elshamy Maged Ragheb , Albahlol Ibrahim A. , Fayala Emad , Wageeh Alaa , El-Zayadi Ahmed Abdelhamid , Bahgat Nagwan Ahmed , Mohammed Shereen M. , Mohamed Alhussein Ahmed , Awad Mahmoud Mohamed , El-Menayyer Ahmed , El-Sherbiny Mohamed , Elsherbini Dalia Mahmoud Abdelmonem , Albarakati Rayan G. , Alshaikh Ahmed Baker A. , Edris Fawaz E. , Bushaqer Nayla Jamal , Salama Youstina Georges Makarious , Abdel-razik Mahmoud Mohamed
Published: August 2024

Background and Objectives: Polycystic ovarian syndrome (PCOS) is a widespread endocrine disorder affecting 5–18% of females in their childbearing age. The aim of this study is to assess the efficacy of combining a low dosage of human chorionic gonadotropin (HCG) along with clomiphene citrate (CC) for stimulating ovulation in infertile women diagnosed with CC-resistant PCOS. Materials and Methods: A randomized controlled trial was carried out on 300 infertile CC-resistant PCOS women. All participants were assigned to two groups: the CC-HCG group and the CC-Placebo group. Subjects in the CC-HCG group were given CC (150 mg/day for 5 days starting on the 2nd day of the cycle) and HCG (200 IU/day SC starting on the 7th day of the cycle). Subjects in the CC-Placebo group were given CC and a placebo. The number of ovarian follicles > 18 mm, cycle cancellation rate, endometrial thickness, ovulation rate, clinical pregnancy rate, and occurrence of early ovarian hyper-stimulation syndrome were all outcome variables in the primary research. Results: Data from 138 individuals in the CC-HCG group and 131 participants in the CC-Placebo group were subjected to final analysis. In comparison to the CC-Placebo group, the cycle cancellation rate in the CC-HCG group was considerably lower. The CC-HCG group exhibited a substantial increase in ovarian follicles reaching > 18 mm, endometrial thickness, and ovulation rate. The clinical pregnancy rate was higher in the CC-HCG group (7.2% vs. 2.3%; CC-HCG vs. CC-Placebo). Upon adjusting for BMI and age, the findings of our study revealed that individuals in the CC-HCG group who had serum prolactin levels below 20 (ng/mL), secondary infertility, infertility duration less than 4 years, baseline LH/FSH ratios below 1.5, and serum AMH levels more than 4 (ng/mL) had a higher likelihood of achieving pregnancy. In the CC-Placebo group, there was a greater prediction of clinical pregnancy for those with serum AMH (<4), primary infertility, serum prolactin ≤ 20 (ng/mL), baseline LH/FSH < 1.5, and infertility duration < 4 years. Conclusions: The use of a small dose of HCG along with CC appeared to be an effective treatment in reducing cycle cancelation, improving the clinical pregnancy rate and ovulation rate in CC-resistant PCOS patients. The trial was registered with Clinical Trials.gov, identifier NCT02436226
Exploring the Overlooked Depression, Anxiety, Insomnia and Fibromyalgia Syndrome Burden in Arab Women with Type 2 Diabetes: New Avenues for Chronic Disease Management
Authors: Gammoh Omar , Alqudah Abdelrahim , Alswidan Maysa , Abu Shwiemeh Lamia , Abu Shaikh Hanan , Massad Talal , Al-Jabari Sereene , Al-Shudifat Abdel-Ellah , Alsheyyab Jafar , Binsaleh Ammena Y. , Shilbayeh Sireen Abdul Rahim , Aljabali Alaa A. A.
Published: August 2024

Background and Objectives: Although physical health is always studied for women with diabetes, the mental health aspect is generally overlooked for this chronic disease. The present study aimed to examine the prevalence of psychosomatic symptoms, namely, fibromyalgia syndrome, depression, anxiety, and insomnia, and how these symptoms related to the medications used in a cohort of women diagnosed with type 2 diabetes (DM) in Jordan. Materials and Methods: This cross-sectional study recruited women diagnosed with type 2 diabetes, and validated scales (PSRS, PHQ-9, GAD-7, and ISI-A) for fibromyalgia syndrome, depression, anxiety, and insomnia were used. The associations between the different medications used and the dependent variables were examined using four separate multivariate logistic regression models. Results: Data were analyzed from 213 participants. Of them, 27.2% met the threshold for fibromyalgia syndrome diagnosis, 38% met the threshold for severe depression, 36.2% met the threshold for severe anxiety, and 39.9% met the threshold for severe insomnia. Fibromyalgia syndrome symptoms were significantly associated with glimepiride (OR = 1.92, CI = 1.00–3.68), β-blockers (OR = 2.21, CI = 1.03–4.70), diuretics (OR = 3.13, CI = 1.26–7.78), herbal remedies (OR = 2.12, CI = 0.98–4.55), and prescriptions for centrally acting medication (OR = 2.78, CI = 1.24–6.29). Significant associations were found between depression and diuretics (OR = 2.62, CI = 1.05–6.67), over-the-counter nonsteroidal anti-inflammatory drugs (NSAIDs) (OR = 3.49, CI = 1.69–7.23), and herbal remedies (OR = 5.07, CI = 2.40–10.69). In addition, anxiety was significantly related to diuretics (OR = 2.48, CI = 1.02–6.02), and OTC NSAIDs (OR = 2.60, CI = 1.29–5.21). Significant associations were evident between insomnia and β-blockers (OR = 3.23, CI = 1.51–6.95), acetaminophen (OR = 2.09, CI = 1.06–4.08), NSAIDs (OR = 4.61, CI = 2.18–9.76), and herbal remedies (OR = 5.95, CI = 2.71–13.07). Conclusions: Medications are associated with high burden of fibromyalgia syndrome, depression, anxiety, and insomnia. These findings underscore the importance of revising and optimizing the pharmacotherapy of these vulnerable patients, performing close mental health monitoring and the implementation of non-pharmacological interventions by integrating mental health services for women with chronic diseases such as diabetes.
Elucidating the Mechanism of Electro-Adsorption on Electrically Conductive Ultrafiltration Membranes via Modified Poisson-Boltzmann Equation
Authors: Usman Muhammad , Vahedi Shahrokh , Glass Sarah , Filiz Volkan , Ernst Mathias
Published: August 2024

Electrically conductive membranes (ECMs) were prepared by coating porous ethylenediamine-modified polyacrylonitrile (PAN-EDA) UF membranes with an ultrathin layer of platinum (Pt) nanoparticles through magnetron sputtering. These ECMs were used in electrofiltration to study the removal of brilliant blue dye from an aqueous solution under positive electrical potentials (0–2.5 V). Negative electrical potentials (−1.0–−2.5 V) were also investigated to regenerate the membrane by desorbing the dye from the ECM surface. At +0 V, the EC PAN-EDA membrane adsorbed the dye due to its intrinsic positive charge. Application of −2.0 V resulted in a maximum of 39% desorption of the dye. A modified Poisson-Boltzmann (MPB) model showed that −2.0 V created a repulsive force within the first 24 nm of the membrane matrix, which had a minimal effect on dye ions adsorbed deeper within the membrane, thus limiting the electro-desorption efficiency to 39%. Moreover, increasing positive potentials from +0.5 V to +2.5 V led to increased dye electro-adsorption by 9.5 times, from 132 mg/m2 to 1112 mg/m2 at pH 8 (equivalent to the membrane’s isoelectric point). The MBP simulations demonstrated that increasing electro-adsorption loadings are related to increasing attractive force, indicating electro-adsorption induced by attractive force is the dominant mechanism and the role of other mechanisms (e.g., electrochemical oxidation) is excluded. At pH 5, electro-adsorption further increased to 1390 mg/m2, likely due to the additional positive charge of the membrane (zeta potential = 9.2 mV) compared to pH 8. At pH 8, complete desorption of the dye from the ECM surface was achieved with a significant repulsive force at −2.0 V. However, as pH decreased from 8 to 5, the desorption efficiency decreased by 3.9% due to the membrane’s positive charge. These findings help elucidate the mechanisms of electro-adsorption and desorption on ECMs using dye as a model for organic compounds like humic acids.
Fufang Muji Granules Ameliorate Liver Fibrosis by Reducing Oxidative Stress and Inflammation, Inhibiting Apoptosis, and Modulating Overall Metabolism
Authors: Men Lei , Gu Zhihong , Wang Enhua , Li Jiwen , Li Zhongyu , Li Keke , Li Chunbin , Gong Xiaojie
Published: August 2024

Fufang Muji granules (FMGs) are a prominent modern prescription Chinese patent formulation derived from the Muji decoction. Utilized in clinical practice for nearly four decades, FMGs have demonstrated efficacy in treating liver diseases. However, the precise mechanism of action remains unclear. This study investigates the hepatoprotective effects of FMGs against liver fibrosis in rats based on untargeted metabolomics and elucidates their underlying mechanisms. A comprehensive model of liver fibrosis was established with 30% CCl4 (2 mL/kg) injected intraperitoneally, and a fat and sugar diet combined with high temperatures and humidity. Rats were orally administered FMGs (3.12 g/kg/d) once daily for six weeks. FMG administration resulted in improved liver fibrosis and attenuated hepatic oxidative stress and apoptosis. Furthermore, FMGs inhibited hepatic stellate cell activation and modulated transforming growth factor β1/Smad signaling. Additionally, FMG treatment influenced the expression levels of interleukin-6, interleukin-1β, and tumour necrosis factor alpha in the injured liver. Metabolic pathways involving taurine and hypotaurine metabolism, as well as primary bile acid biosynthesis, were identified as mechanisms of action for FMGs. Immunohistochemistry, quantitative reverse transcription polymerase chain reaction (RT-qPCR), and quantitative analysis also revealed that FMGs regulated taurine and hypotaurine metabolism and bile acid metabolism. These findings provide a valuable understanding of the role of FMGs in liver fibrosis management.
Simulation and Experimental Study on Stress Relaxation Response of Polycrystalline γ-TiAl Alloy under Nanoindentation Based on Molecular Dynamics
Authors: Li Junye , Wang Chunyu , Liu Jianhe , Dong Xiwei , Zhao Jinghe , Chen Ying
Published: August 2024

This study employed nano-indentation technology, molecular dynamics simulation, and experimental investigation to examine the stress relaxation behaviour of a polycrystalline γ-TiAl alloy. The simulation enabled the generation of a load-time curve, the visualisation of internal defect evolution, and the mapping of stress distribution across each grain during the stress relaxation stage. The findings indicate that the load remains stable following an initial decline, thereby elucidating the underlying mechanism of load change during stress relaxation. Furthermore, a nano-indentation test was conducted on the alloy, providing insight into the load variation and stress relaxation behaviour under different loading conditions. By comparing the simulation and experimental results, this study aims to guide the theoretical research and practical application of γ-TiAl alloys.
Comprehensive Review on Research Status and Progress in Precision Grinding and Machining of BK7 Glasses
Authors: Yang Dayong , Zhang Zhiyang , Wei Furui , Li Shuping , Liu Min , Lu Yuwei
Published: August 2024

BK7 glass, with its outstanding mechanical strength and optical performance, plays a crucial role in many cutting-edge technological fields and has become an indispensable and important material. These fields have extremely high requirements for the surface quality of BK7 glass, and any small defects or losses may affect its optical performance and stability. However, as a hard and brittle material, the processing of BK7 glass is extremely challenging, requiring precise control of machining parameters to avoid material fracture or excessive defects. Therefore, how to obtain the required surface quality with lower cost machining techniques has always been the focus of researchers. This article introduces the properties, application background, machining methods, material removal mechanism, and surface and subsurface damage of optical glass BK7 material. Finally, scientific predictions and prospects are made for future development trends and directions for improvement of BK7 glass machining.
Hybrid Fibers with Subwavelength-Scale Liquid Core for Highly Sensitive Sensing and Enhanced Nonlinearity
Authors: Wang Caoyuan , Yu Ruowei , Ye Yucheng , Xiong Cong , Ahmed Khan Khushik Muhammad Hanif , Xiao Limin
Published: August 2024

Interest grows in designing silicon-on-insulator slot waveguides to trap optical fields in subwavelength-scale slots and developing their optofluidic devices. However, it is worth noting that the inherent limitations of the waveguide structures may result in high optical losses and short optical paths, which challenge the device’s performance in optofluidics. Incorporating the planar silicon-based slot waveguide concept into a silica-based hollow-core fiber can provide a perfect solution to realize an efficient optofluidic waveguide. Here, we propose a subwavelength-scale liquid-core hybrid fiber (LCHF), where the core is filled with carbon disulfide and surrounded by a silicon ring in a silica background. The waveguide properties and the Stimulated Raman Scattering (SRS) effect in the LCHF are investigated. The fraction of power inside the core of 56.3% allows for improved sensitivity in optical sensing, while the modal Raman gain of 23.60 m−1·W−1 is two times larger than that generated around a nanofiber with the interaction between the evanescent optical field and the surrounding Raman media benzene-methanol, which enables a significant low-threshold SRS effect. Moreover, this in-fiber structure features compactness, robustness, flexibility, ease of implementation in both trace sample consumption and reasonable liquid filling duration, as well as compatibility with optical fiber systems. The detailed analyses of the properties and utilizations of the LCHF suggest a promising in-fiber optofluidic platform, which provides a novel insight into optofluidic devices, optical sensing, nonlinear optics, etc.
Alteration in the Morphological and Transcriptomic Profiles of Acinetobacter baumannii after Exposure to Colistin
Authors: Yoon Eun-Jeong , Mo Jun Won , Kim Jee-woong , Jeong Min Chul , Yoo Jung Sik
Published: August 2024

Acinetobacter baumannii is often highly resistant to multiple antimicrobials, posing a risk of treatment failure, and colistin is a “last resort” for treatment of the bacterial infection. However, colistin resistance is easily developed when the bacteria are exposed to the drug, and a comprehensive analysis of colistin-mediated changes in colistin-susceptible and -resistant A. baumannii is needed. In this study, using an isogenic pair of colistin-susceptible and -resistant A. baumannii isolates, alterations in morphologic and transcriptomic characteristics associated with colistin resistance were revealed. Whole-genome sequencing showed that the resistant isolate harbored a PmrBL208F mutation conferring colistin resistance, and all other single-nucleotide alterations were located in intergenic regions. Using scanning electron microscopy, it was determined that the colistin-resistant mutant had a shorter cell length than the parental isolate, and filamented cells were found when both isolates were exposed to the inhibitory concentration of colistin. When the isolates were treated with inhibitory concentrations of colistin, more than 80% of the genes were upregulated, including genes associated with antioxidative stress response pathways. The results elucidate the morphological difference between the colistin-susceptible and -resistant isolates and different colistin-mediated responses in A. baumannii isolates depending on their susceptibility to this drug.
Enhancing Antibiotic Efficacy and Combating Biofilm Formation: Evaluating the Synergistic Potential of Origanum vulgare Essential Oil against Multidrug-Resistant Gram-Negative Bacteria
Authors: Saoudi Bilal , Bariz Karim , Saci Sarah , Belounis Yousra , Ait Issad Hakima , Abbaci Mohamed , Mustapha Mohamed Abou , Nabti El-Hafid , Alenazy Rawaf , Alhussaini Mohammed Sanad , Alyahya Abdulrahman A. I. , Alqasmi Mohammed , Alhumaidi Maryam S. , Almufarriji Fawaz M. , Houali Karim
Published: August 2024

Multidrug-resistant (MDR) Gram-negative bacteria remain a global public health issue due to the barrier imposed by their outer membrane and their propensity to form biofilms. It is becoming imperative to develop new antibacterial strategies. In this context, this study aims to evaluate the antibacterial efficacy of Origanum vulgare essential oil (OEO), alone and in combination with antibiotics, as well as its antibiofilm action against multidrug-resistant Gram-negative strains. OEO components were identified by gas chromatography-mass spectrometry (GC-MS), and antibacterial activity was assessed using the agar diffusion test and the microdilution method. Interactions between OEO and antibiotics were examined using the checkerboard method, while antibiofilm activity was analyzed using the crystal violet assay. Chemical analysis revealed that carvacrol was the major compound in OEO (61.51%). This essential oil demonstrated activity against all the tested strains, with inhibition zone diameters (IZDs) reaching 32.3 ± 1.5 mm. The combination of OEO with different antibiotics produced synergistic and additive effects, leading to a reduction of up to 98.44% in minimum inhibitory concentrations (MICs). In addition, this essential oil demonstrated an ability to inhibit and even eradicate biofilm formation. These results suggest that OEO could be exploited in the development of new molecules, combining its metabolites with antibiotics.
Comparative Analysis of Commercially Available Flavor Oil Sausages and Smoked Sausages
Authors: Zhao Penghui , An Yongqiang , Dong Zijie , Sun Xiaoxue , Zhang Wanli , Wang Heng , Yang Bing , Yan Jing , Fang Bing , Ren Fazheng , Chen Lishui
Published: August 2024

This study utilized gas chromatography-ion mobility spectrometry (GC-IMS) to analyze the volatile flavor compounds present in various commercially available sausages. Additionally, it conducted a comparative assessment of the distinctions among different samples by integrating sensory evaluation with textural and physicochemical parameters. The results of the GC-IMS analysis showed that a total of 65 volatile compounds were detected in the four samples, including 12 hydrocarbons, 11 alcohols, 10 ketones, 9 aldehydes, 12 esters, and 1 acids. Fingerprinting combined with principal component analysis (PCA) showed that the volatiles of different brands of sausages were significantly different (p < 0.05). The volatiles of S1 and S4 were more similar and significantly different from the other two samples (p < 0.05). Among them, there were 14 key volatile substances in the four samples, of which 3-hydroxy-2-butanone and diallyl sulfide were common to all four sausages. Combined textural and sensory evaluations revealed that smoked sausages exhibited superior characteristics in resilience, cohesiveness, springiness, gumminess, and chewiness. Additionally, smoked sausages were found to be more attractive in color, moderately spicy, and salty, while having a lower fat content. In conclusion, smoked sausages are preferred by consumers over flavored oil sausages.
Synthetic and Natural Antifungal Substances in Cereal Grain Protection: A Review of Bright and Dark Sides
Authors: Szczygieł Tomasz , Koziróg Anna , Otlewska Anna
Published: August 2024

Molds pose a severe challenge to agriculture because they cause very large crop losses. For this reason, synthetic fungicides have been used for a long time. Without adequate protection against pests and various pathogens, crop losses could be as high as 30–40%. However, concerns mainly about the environmental impact of synthetic antifungals and human health risk have prompted a search for natural alternatives. But do natural remedies only have advantages? This article reviews the current state of knowledge on the use of antifungal substances in agriculture to protect seeds against phytopathogens. The advantages and disadvantages of using both synthetic and natural fungicides to protect cereal grains were discussed, indicating specific examples and mechanisms of action. The possibilities of an integrated control approach, combining cultural, biological, and chemical methods are described, constituting a holistic strategy for sustainable mold management in the grain industry.
Coupling Electro-Fenton and Electrocoagulation of Aluminum–Air Batteries for Enhanced Tetracycline Degradation: Improving Hydrogen Peroxide and Power Generation
Authors: Zhou Zhenghan , Wei Wei , Wu Houfan , Gong Haoyang , Zhou Kai , Zheng Qiyuan , Liu Shaogen , Gui Ling , Jiang Zhongqi , Zhu Shuguang
Published: August 2024

Electro-Fenton (EF) technology has shown great potential in environmental remediation. However, developing efficient heterogeneous EF catalysts and understanding the relevant reaction mechanisms for pollutant degradation remain challenging. We propose a new system that combines aluminum–air battery electrocoagulation (EC) with EF. The system utilizes dual electron reduction of O2 to generate H2O2 in situ on the air cathodes of aluminum–air batteries and the formation of primary cells to produce electricity. Tetracycline (TC) is degraded by ·OH produced by the Fenton reaction. Under optimal conditions, the system exhibits excellent TC degradation efficiency and higher H2O2 production. The TC removal rate by the reaction system using a graphite cathode reached nearly 100% within 4 h, whereas the H2O2 yield reached 127.07 mg/L within 24 h. The experimental results show that the novel EF and EC composite system of aluminum–air batteries, through the electroflocculation mechanism and ·OH and EF reactions, with EC as the main factor, generates multiple •OH radicals that interact to efficiently remove TC. This work provides novel and important insights into EF technology, as well as new strategies for TC removal.
Degradation Acyclovir Using Sodium Hypochlorite: Focus on Byproducts Analysis, Optimal Conditions and Wastewater Application
Authors: Medici Antonio , De Nisco Mauro , Luongo Giovanni , Di Fabio Giovanni , Brigante Marcello , Zarrelli Armando
Published: August 2024

In recent years, the environmental impact of pharmaceutical residues has emerged as a pressing global concern, catalyzed by their widespread usage and persistence in aquatic ecosystems. Among these pharmaceuticals, acyclovir (ACV) stands out due to its extensive prescription during medical treatments for herpes simplex virus, chickenpox, and shingles, as well as its heightened usage amidst the COVID-19 pandemic. ACV is excreted largely unchanged by the human body, leading to significant environmental release through wastewater effluents. The urgency of addressing ACV’s environmental impact lies in its potential to persist in water bodies and affect aquatic life. This persistence underscores the critical need for effective degradation strategies that can mitigate its presence in aquatic systems. This study focuses on employing sodium hypochlorite as an oxidative agent for the degradation of ACV, leveraging its common use in wastewater treatment plants. Our research aims to explore the kinetics of ACV degradation, identify and characterize its degradation byproducts, and optimize the conditions under which complete degradation can be achieved. By assessing the efficiency of sodium hypochlorite in real wastewater samples, this study seeks to provide practical insights into mitigating ACV contamination in aquatic environments. The novelty of this research lies in its comprehensive approach to understanding the degradation pathways of ACV and evaluating the feasibility of using sodium hypochlorite as a sustainable solution in wastewater treatment. By addressing the environmental concerns associated with ACV and offering practical solutions, this study contributes to the broader goal of sustainable pharmaceutical waste management and environmental stewardship.
Recent Advances and New Insights in Genome Analysis and Transcriptomic Approaches to Reveal Enzymes Associated with the Biosynthesis of Dendrobine-Type Sesquiterpenoid Alkaloids (DTSAs) from the Last Decade
Authors: Qian Xu , Sarsaiya Surendra , Dong Yuanyuan , Yu Tuifan , Chen Jishuang
Published: August 2024

Dendrobium species, which are perennial herbs widely distributed in tropical and subtropical regions, are notable for their therapeutic properties attributed to various bioactive compounds, including dendrobine-type sesquiterpenoid alkaloids (DTSAs). The objective of this review article is to provide a comprehensive overview of recent advances in the biosynthesis of DTSAs, including their extraction from Dendrobium species and endophytes, elucidation of associated genes through genomic and transcriptomic sequencing in both Dendrobium spp. and endophytes, exploration of the biosynthetic pathways of DTSAs, and drawing conclusions and outlining future perspectives in this field. Alkaloids, predominantly nitrogen-containing compounds found in medicinal orchids, include over 140 types discovered across more than 50 species. DTSAs, identified in 37 picrotoxane alkaloids, have a distinctive five-membered nitrogen heterocyclic ring. This review highlights endophytic fungi as alternative sources of DTSAs, emphasizing their potential in pharmaceutical applications when plant-derived compounds are scarce or complex. Genomic and transcriptomic sequencing of Dendrobium spp. and their endophytes has identified key genes involved in DTSAs biosynthesis, elucidating pathways such as the mevalonate (MVA) and 2-C-methyl-D-erythritol 4-phosphate (MEP) pathways. Genes encoding enzymes, such as acetyl-CoA C-acetyltransferase and diphosphomevalonate decarboxylase, are positively associated with dendrobine production. Despite significant advancements, the complexity of terpenoid biosynthesis in different subcellular compartments remains a challenge. Future research should focus on leveraging high-quality genomic data and omics technologies to further understand and manipulate the biosynthetic pathways of DTSAs and enhance their medicinal use.
Nicotinamide Riboside: What It Takes to Incorporate It into RNA
Authors: Wenzek Felix , Biallas Alexander , Müller Sabine
Published: August 2024

Nicotinamide is an important functional compound and, in the form of nicotinamide adenine dinucleotide (NAD), is used as a co-factor by protein-based enzymes to catalyze redox reactions. In the context of the RNA world hypothesis, it is therefore reasonable to assume that ancestral ribozymes could have used co-factors such as NAD or its simpler analog nicotinamide riboside (NAR) to catalyze redox reactions. The only described example of such an engineered ribozyme uses a nicotinamide moiety bound to the ribozyme through non-covalent interactions. Covalent attachment of NAR to RNA could be advantageous, but the demonstration of such scenarios to date has suffered from the chemical instability of both NAR and its reduced form, NARH, making their use in oligonucleotide synthesis less straightforward. Here, we review the literature describing the chemical properties of the oxidized and reduced species of NAR, their synthesis, and previous attempts to incorporate either species into RNA. We discuss how to overcome the stability problem and succeed in generating RNA structures incorporating NAR.
Density Functional Theory-Based Indicators to Estimate the Corrosion Potentials of Zinc Alloys in Chlorine-, Oxidizing-, and Sulfur-Harsh Environments
Authors: Mukhametov Azamat , Samikov Insaf , Korznikova Elena A. , Kistanov Andrey A.
Published: August 2024

Nowadays, biodegradable metals and alloys, as well as their corrosion behavior, are of particular interest. The corrosion process of metals and alloys under various harsh conditions can be studied via the investigation of corrosion atom adsorption on metal surfaces. This can be performed using density functional theory-based simulations. Importantly, comprehensive analytical data obtained in simulations including parameters such as adsorption energy, the amount of charge transferred, atomic coordinates, etc., can be utilized in machine learning models to predict corrosion behavior, adsorption ability, catalytic activity, etc., of metals and alloys. In this work, data on the corrosion indicators of Zn surfaces in Cl-, S-, and O-rich harsh environments are collected. A dataset containing adsorption height, adsorption energy, partial density of states, work function values, and electronic charges of individual atoms is presented. In addition, based on these corrosion descriptors, it is found that a Cl-rich environment is less harmful for different Zn surfaces compared to an O-rich environment, and more harmful compared to a S-rich environment.