bluuebunny/crossref_metadata_2025 huggingface dataset:
Effects of Curcumin and Estrogen Receptor Alpha in Luminal Breast Cancer Cells
Authors: Palacios-Navarro Lorena , Crispin Leodan A. , Muñoz Juan P. , Calaf Gloria M.
Published: August 2024

This work examined the potential benefit of curcumin in breast cancer patients as a supplementary drug in ER-positive cancers. The results indicated that in the MCF-7 human breast cancer cell line, E2 and curcumin decreased cell proliferation and the colony-forming capacity and down-regulated protein expression as well as important molecules associated with cell proliferation, such as PCNA and estrogen receptor alpha; genes associated with the epithelial-mesenchymal transition, such as β-catenin, Vimentin, and E-cadherin; and molecules associated with apoptosis. Clinical studies in bioinformatics have indicated a positive correlation between ESR1 and either CCND1 or BCL2 gene expression in all breast cancer patients. Thus, curcumin could become a potential natural adjuvant treatment for patients with estrogen receptor alpha-positive breast cancer and those with resistance or a poor response to endocrine therapy since the reactivation of estrogen receptor alpha is inevitable.
Squamous Cell Carcinoma In Situ—The Importance of Early Diagnosis in Bowen Disease, Vulvar Intraepithelial Neoplasia, Penile Intraepithelial Neoplasia, and Erythroplasia of Queyrat
Authors: Scurtu Lucian G. , Scurtu Francesca , Dumitrescu Sebastian Catalin , Simionescu Olga
Published: August 2024

Cutaneous squamous cell carcinoma (cSCC) is the second-most-prevalent malignancy in humans. A delayed diagnosis of cSCC leads to heightened invasiveness and positive surgical margins. Bowen’s disease (BD) represents an early form of cSCC and presents as a small erythematous, photo-distributed, psoriasiform plaque. Although certain dermoscopy features in BD are quite characteristic, histopathology remains the gold standard for diagnosis and provides a severity-scoring system that assists in guiding appropriate treatment strategies. The classification of precancerous lesions of the vulva and penis has undergone multifarious transformations due to variations in clinical and histopathological characteristics. Presently, erythroplasia of Queyrat is categorized as a clinical variant of penile intraepithelial neoplasia (PeIN). The diagnoses of vulvar intraepithelial neoplasia (VIN) and PeIN present significant challenges and typically necessitate one or more biopsies, potentially guided by dermoscopy. Aceto-white testing demonstrates a notably high negative predictive value for genital precancerous lesions. Histopathological examination represents the gold-standard diagnosis in VIN and PeIN, while p16 and p53 immunostainings alongside HPV testing provide crucial diagnostic clues. The histopathologic features, degree of differentiation, and associations with lichen planus, lichen sclerosus, and HPV guide the selection of conservative treatments or surgical excision.
Perception and Acceptance of Shade Variances in the Smile
Authors: Wesselbaum Jana , Dirksen Dieter , Runte Christoph , Becker Alexander
Published: August 2024

(1) This study aimed to evaluate the influences of differences in denture teeth shade on harmony ratings and esthetic quality. Particular attention was paid to the question of how the overall variance of shade differences in the dental arch influences the perception of shade differences between adjacent teeth. (2) A total of 51 pictures of upper front teeth with standardized different colors of the left central incisor and different color variance of the dental arch were created. Eighty participants without dental knowledge and of different age, sex and educational level rated the pictures on a visual analogue scale from 0 (strongly disagree) to 100 (strongly agree) with regards to esthetic and color equality. (3) Results: The color differences between two teeth were judged in a negative linear correlation to the evaluation of color and esthetic quality. There was a sex- and education-specific difference in color and harmony ratings. In relation to the age of the participants, there was a significant difference in the color rating (p = 0.01) but not in the harmony rating (p = 0.27). Lower rating of color difference and harmony was found for a color difference in the dental arch up to ΔE = 3.1. In contrast, higher color differences resulted in higher ratings. (4) There is an influence of personal parameters on color perception. Color inhomogeneity in a dental arch leads to significant differences in color and harmony rating in a non-linear relation.
A Method for Locating Wideband Oscillation Disturbance Sources in Power Systems by Integrating TimesNet and Autoformer
Authors: Yan Huan , Tai Keqiang , Liu Mengchen , Wang Zhe , Yang Yunzhang , Zhou Xu , Zheng Zongsheng , Gao Shilin , Wang Yuhong
Published: August 2024

The large-scale integration of new energy generators into the power grid poses a potential threat to its stable operation due to broadband oscillations. The rapid and accurate localization of oscillation sources is fundamental for mitigating these risks. To enhance the interpretability and accuracy of broadband oscillation localization models, this paper proposes a broadband oscillation localization model based on deep learning, integrating TimesNet and Autoformer algorithms. This model utilizes transmission grid measurement sampling data as the input and employs a data-driven approach to establish the broadband oscillation localization model. TimesNet improves the model’s accuracy significantly by decomposing the measurement data into intra- and inter-period variations using dimensional elevation, tensor transformation, and fast Fourier transform. Autoformer enhances the ability to capture oscillation features through the Auto-Correlation mechanism. A typical high-proportion renewable energy system was constructed using CloudPSS to create a sample dataset. Simulation examples validated the proposed method, demonstrating it as a highly accurate solution for broadband oscillation source localization.
A Novel Ant Colony Algorithm for Optimizing 3D Printing Paths
Authors: Lin Xinghan , Huang Zhigang , Shi Wentian , Guo Keyou
Published: August 2024

The advancement of 3D printing technology has enabled the fabrication of intricate structures, yet the complexity of the print head’s motion path significantly hampers production efficiency. Addressing the challenges posed by the dataset of section points in 3D-printed workpieces, this study introduces an innovative ant colony optimization algorithm tailored to enhance the print head’s trajectory. By framing the optimization of the motion path as a Traveling Salesman Problem (TSP), the research employs a custom-designed K-means clustering algorithm to categorize the dataset into distinct clusters. This clustering algorithm partitions each printing point into different subsets based on density, optimizes these subsets through improved K-means clustering computations, and then aggregates the results to classify the entire dataset. Subsequently, the ant colony algorithm arranges the printing sequence of these clusters based on the cluster centers, followed by computing the shortest path within each cluster. To form a cohesive motion trajectory, the nearest nodes between adjacent clusters are linked, culminating in a globally optimal solution. Comparative experiments repeatedly demonstrate significant enhancements in the print head’s motion path, leading to marked improvements in printing efficiency.
A Novel Linear-Based Closed-Loop Control and Analysis of Solid-State Transformer
Authors: Cavdar Metin , Ozcira Ozkilic Selin
Published: August 2024

In this paper, a new linear-based closed-loop control method for a Solid-State Transformer (SST) has been proposed. In this new control method, individual current and voltage loops for each of the power conversion stages (AC-DC, DC-DC, DC-AC) are implemented. The feedback between the input and output control signals for each loop is achieved through the voltage on the DC link capacitors and the current transferred between the converters. This enables the SST to be controlled easily in a linear-based closed-loop manner without the need for complex computations. In order to evaluate the performance analysis of the proposed control system, a simulation of an SST with approximately 10 kVA apparent power was performed. Based on the obtained simulation results, the response time of the proposed control method for dynamic load variations was proved to be in the range of 40 milliseconds, and it has been observed that this method allows electrical power to be transferred from the load to the grid. The power factor value of SST under inductive load is measured to be approximately 99%, and the overall system efficiency is 96% and above, indicating that this proposed new control method has very high performance.
The Supplementary Damping Method for CLCC HVDC Based on Projective Control Theory
Authors: Zhao Feifei , Xie Zhenjian , Zhang Wenjia , Qi Wanchun , Cai Hui , Xu Sixuan , Han Xingning , Wang Quanquan
Published: August 2024

This paper proposes a design method for an additional damping reduced-order controller based on the projective control theorem. Improvements are made to the projective theorem to achieve additional damping control through Controllable-Line-Commutated Converter (CLCC)-based High Voltage Direct Current (HVDC), which suppresses low-frequency oscillations. Using small disturbance identification techniques, the system’s linear model is first identified, and the state feedback control law of the system is then determined using the state-space pole assignment control method. Then, by retaining the dominant oscillation modes of the closed-loop system through the improved projective theorem, the state feedback is converted into output feedback. Ultimately, the sixth-order state feedback controller is reduced to a second-order one and applied in the CLCC HVDC additional damping strategy to suppress low-frequency oscillations. Simulation results based on the electromagnetic transient simulation software PSCAD demonstrate that the designed CLCC HVDC additional damping reduced-order projective control exhibits good suppression performance, strong robustness, and low order, which are of significant importance for engineering practice.
Resource-Saving Overcurrent Protection
Authors: Issabekov Dauren Dzhambulovich , Kislov Aleksandr Petrovich , Markovskiy Vadim Pavlovich , Zhumataev Nurlybek Shakaevich , Zhumadirova Aliya Kairullovna , Narynbayev Damir Serikovich
Published: August 2024

Construction of relay protections of electrical installations without the use of bulky metal- and insulation-intensive measuring current transformers (CTs) was repeatedly discussed at Conferences of the International Council on Large Electric Systems (CIGRE) as a challenge for the electric power industry. In the article, the authors present resource-saving reed switch current protection for 6–10-kV electrical installations connected to switchgear cells, which is an alternative to traditional protections. The scientific novelty of the work lies in (a) reed switch protection design on the basis of measuring the magnetic induction in different modes and at different points inside a cell, and we prove that inductance values are sufficient to detect phase short-circuits in electrical installations fed from this cell and derive the dependence of the induction on the position of an inductance coil inside the cell; (b) proven possibility of using the simplest formula of the Biot–Savart law for the calculations if the experimentally obtained coefficients are introduced into it; (c) development of a technique for calculating the parameters of the overcurrent protection based on reed switches. Experimental results are presented in graphical form and clearly show the points of EMS maxima and minima. Settings for resource-saving current protection are selected and a feasibility study of the effectiveness of resource-saving overcurrent protection is carried out. A technical and economical assessment of the efficiency of the suggested overcurrent protection is conducted.
The Impact of Limiting Reactive Power Flows on Active Power Losses in Lighting Installations
Authors: Kurkowski Marek , Popławski Tomasz , Zajkowski Maciej , Sołjan Zbigniew
Published: August 2024

Road lighting is one of the most important services provided by public entities. Entities providing such a service are interested in providing it with the lowest possible financial outlays. When planning modernization, unfortunately, one forgets about hidden operating costs, which are caused by, among others, the flow of reactive energy in the circuit. The use of modern light sources also involves the use of electronic systems in their accessories, which makes these electrical energy receivers capacitive. This is due to the lack of use of individual compensation systems in the luminaires themselves. Due to the above, the costs of capacitive reactive energy flow also increase. Newly designed road lighting installations, as well as modernized ones, are equipped with electronic systems enabling their effective control. The operation of such systems also causes fluctuations in the reactive power value, which must be compensated. Commonly used compensation choke systems also introduce additional active power losses, which makes the expected savings lower than expected. In the article, the authors presented selected results of measurements of the electrical parameters of LED luminaires, carried out both in the laboratory and in used road lighting circuits. The determined amounts of active power losses caused by the installation and operation of additional equipment in the road lighting installation, such as compensating chokes, are presented. The calculations were made based on the example of a selected fragment of the audit of this installation. On this basis, modernization was carried out and measurements of current electricity quality parameters were carried out.
Optimizing Virtual Power Plant Management: A Novel MILP Algorithm to Minimize Levelized Cost of Energy, Technical Losses, and Greenhouse Gas Emissions
Authors: Aoun Alain , Adda Mehdi , Ilinca Adrian , Ghandour Mazen , Ibrahim Hussein
Published: August 2024

The modern energy landscape is undergoing a significant transformation towards cleaner, decentralized energy sources. This change is driven by environmental and sustainability needs, causing traditional centralized electric grids, which rely heavily on fossil fuels, to be replaced by a diverse range of decentralized distributed energy resources. Virtual power plants (VPPs) have surfaced as a flexible solution in this transition. A VPP’s primary role is to optimize energy production, storage, and distribution by coordinating output from various connected sources. Relying on advanced communication and control systems, a VPP can balance supply and demand in real time, offer ancillary services, and support grid stability. However, aligning VPPs’ economic and operational practices with broader environmental goals and policies is a challenging yet crucial aspect. This article introduces a new VPP management and optimization algorithm designed for quick and intelligent decision-making, aiming for the lowest levelized cost of energy (LCOE), minimum grid technical losses, and greenhouse gas (GHG) emissions. The algorithm’s effectiveness is confirmed using the IEEE 33-bus grid with 10 different distributed power generators. Simulation results show the algorithm’s responsiveness to complex variables found in practical scenarios, finding the optimal combination of available energy resources. This minimizes the LCOE, technical losses, and GHG emissions in less than 0.08 s, achieving a total LCOE reduction of 16% from the baseline. This work contributes to the development of intelligent energy management systems, aiding the transition towards a more resilient and sustainable energy infrastructure.
Design of Optimal Pitch Controller for Wind Turbines Based on Back-Propagation Neural Network
Authors: Qin Shengsheng , Cao Zhipeng , Wang Feng , Ngu Sze Song , Kho Lee Chin , Cai Hui
Published: August 2024

To ensure the stable operation of a wind turbine generator system when the wind speed exceeds the rated value and address the issue of excessive rotor speed during high wind speeds, this paper proposes a novel variable pitch controller strategy based on a back-propagation neural network and optimal control theory to solve this problem. Firstly, a mathematical model for the wind turbine is established and linearized. Then, each optimal sub-controller is designed for different wind speed conditions by optimal theory. Subsequently, a back-propagation neural network is utilized to learn the variation pattern of controller parameters with respect to wind speed. Finally, real-time changes in wind speed are applied to evaluate and adjust controller parameters using the trained back-propagation neural network. The model is simulated in MATLAB 2019b, real-time data are observed, and the control effect is compared with that of a Takagi–Sugeno optimal controller, firefly algorithm optimal controller and fuzzy controller. The simulation results show that the rotor speed overshoot of the optimal controller under the step wind speed is the smallest, only 0.05 rad/s. Under other wind speed conditions, the rotor speed range fluctuates around 4.35 rad/s, and the fluctuation size is less than 0.2 rad/s, which is much smaller than the fluctuation range of other controllers. It can be seen that the back-propagation optimal controller can ensure the stability of the rotor speed above the rated wind speed. At the same time, it has better control accuracy compared to other controllers.
Non-Exhaust Particulate Emissions from Road Transport Vehicles
Authors: Costagliola Maria Antonietta , Marchitto Luca , Giuzio Rocco , Casadei Simone , Rossi Tommaso , Lixi Simone , Faedo Davide
Published: August 2024

As part of the Zero Pollution Action Plan of the Green Deal, the European Commission has set the goal of reducing the number of premature deaths caused by fine particulate matter (PM2.5) by at least 55% by 2030, compared to 2005 levels. To achieve this, the European Commission aims to introduce stricter limits. In urban areas, road transport is a significant source of PM emissions. Vehicle PM originates from engine exhaust and from tire, brake and road wear, as well as from road dust resuspension. In recent decades, the application of stringent emission limits on vehicle exhaust has led to the adoption of technologies capable of strongly reducing PM emissions at the tailpipe. Further, the progressive electrification of vehicle fleets will lead to near-zero exhaust PM emissions. On the other hand, non-exhaust PM emissions have increased in recent years following the proliferation of sport utility vehicles (SUVs), whose numbers have jumped nearly tenfold globally, and electric vehicles, as these vehicles tend to be heavier than corresponding conventional and older internal combustion engine light-duty vehicles. This shift has resulted in a more modest reduction in PM10 and PM2.5 emissions from the transport sector compared to other pollutants (−49% and −55%, respectively, from 1990 to 2020). This report aims to provide an up-to-date overview of non-exhaust PM characterization, drawing insights from the recent scientific literature to address this critical environmental and public health challenge.
Estimation of the Aboveground Carbon Storage of Dendrocalamus giganteus Based on Spaceborne Lidar Co-Kriging
Authors: Yang Huanfen , Qin Zhen , Shu Qingtai , Xi Lei , Xia Cuifen , Wu Zaikun , Wang Mingxing , Duan Dandan
Published: August 2024

Bamboo forests, as some of the integral components of forest ecosystems, have emerged as focal points in forestry research due to their rapid growth and substantial carbon sequestration capacities. In this paper, satellite-borne lidar data from GEDI and ICESat-2/ATLAS are utilized as the main information sources, with Landsat 9 and DEM data as covariates, combined with 51 pieces of ground-measured data. Using random forest regression (RFR), boosted regression tree (BRT), k-nearest neighbor (KNN), Cubist, extreme gradient boosting (XGBoost), and Stacking-ridge regression (RR) machine learning methods, an aboveground carbon (AGC) storage model was constructed at a regional scale. The model evaluation indices were the coefficient of determination (R2), root mean square error (RMSE), and overall estimation accuracy (P). The results showed that (1) The best-fit semivariogram models for cdem, fdem, fndvi, pdem, and andvi were Gaussian models, while those for h1b7, h2b7, h3b7, and h4b7 were spherical models; (2) According to Pearson correlation analysis, the AGC of Dendrocalamus giganteus showed an extremely significant correlation (p < 0.01) with cdem and pdem from GEDI, and also showed an extremely significant correlation with andvi, h1b7, h2b7, h3b7, and h4b7 from ICESat-2/ATLAS; moreover, AGC showed a significant correlation (0.01 < p < 0.05) with fdem and fndvi from GEDI; (3) The estimation accuracy of the GEDI model was superior to that of the ICESat-2/ATLAS model; additionally, the estimation accuracy of the Stacking-RR model, which integrates GEDI and ICESat-2/ATLAS (R2 = 0.92, RMSE = 5.73 Mg/ha, p = 86.19%), was better than that of any single model (XGBoost, RFR, BRT, KNN, Cubist); (4) Based on the Stacking-RR model, the estimated AGC of Dendrocalamus giganteus within the study area was 1.02 × 107 Mg. The average AGC was 43.61 Mg/ha, with a maximum value of 76.43 Mg/ha and a minimum value of 15.52 Mg/ha. This achievement can serve as a reference for estimating other bamboo species using GEDI and ICESat-2/ATLAS remote sensing technologies and provide decision support for the scientific operation and management of Dendrocalamus giganteus.
Quantifying Regulating Ecosystem Services of Urban Trees: A Case Study of a Green Space at Chungnam National University Using i-Tree Eco
Authors: Hintural Wencelito Palis , Jeon Hee Jeong , Kim Seo Young , Go San , Park Byung Bae
Published: August 2024

Urban green spaces (UGSs) provide numerous ecosystem services (ESs) that are essential to the well-being of the residents. However, these services are often neglected in regional urban development and spatial planning. This study quantified the ESs of a 10.25 ha UGS at Chungnam National University, Daejeon, Republic of Korea, comprising 27 species with 287 tree individuals, using i-Tree Eco. Key regulating ESs investigated included air pollution removal, carbon storage and sequestration, oxygen production, energy use reduction, avoidance of surface runoff, and replacement and functional values. Results revealed significant annual environmental benefits: 131 kg air pollutants removed (USD 3739.01 or ₩5.16 M), 1.76 Mg carbon sequestered, which is equivalent to 0.18 Mg CO2 ha−1 yr−1 (USD 289.85 or ₩0.40 M), 2.42 Mg oxygen produced, energy savings (including carbon offset) valued at USD 391.29 (₩0.54 M), and 203 m3 reduction in surface runoff (USD 413.09 or ₩0.57 M). The annual total benefits of these urban trees amounted to USD 4833.86 (₩6.67 M), USD 16.83/tree, or USD 0.089/capita. Additionally, these trees had replacement and functional values estimated at USD 311,115.17 (₩429.3 M). The study underscores that species selection and abundance of urban trees are fundamental for maximizing the ES delivery in urban areas, highlighting the role of UGSs in ecological and economical sustainability in cities. These insights are valuable for urban planners and policymakers to optimize benefits of UGSs in cities.
Arbuscular Mycorrhiza Fungi Alleviate the Allelopathic Effects of Invasive Nicotiana glauca on the Growth of Acacia gerrardii Seedlings
Authors: Adam Abdelmalik M. , Alshahrani Thobayet S. , Alqarawi Abdulaziz A. , Abd-ElGawad Ahmed M. , Ahmed Eljaily M. , Sorrori Salah N.
Published: August 2024

A greenhouse experiment was conducted to determine the potential of arbuscular mycorrhizal fungi (AMF) to mitigate the allelopathic effects of invasive Nicotiana glauca on the growth of Acacia gerrardii seedlings. Aqueous extracts from N. glauca leaves and flowers (at concentrations of 20, 60, and 100 g/L) and AMF treatment (±AMF) were applied to A. gerrardii seedlings arranged in a factorial experiment with four replicates. After 6 months, vegetative (plant fresh and dry weight, height, leaf number area), physiological (photosynthesis, stomatal conductance, transpiration rate), chlorophyll a and b, proline, and root (length, surface area, diameter, volume, tip number) parameters as well as root distribution in five root diameter classes (0–5 mm, in 1 mm increments) were examined. The presence of AMF increased the seedling growth parameters. The 20 g/L treatment stimulated most of the vegetative growth, root, chlorophyll, and photosynthesis parameters at both inoculant levels for all extract types and concentrations, and the 100 g/L treatment inhibited seedling growth whether inoculated with AMF or not. This decline was alleviated in AMF-treated seedlings. For both extract sources, root length decreased as extract concentration increased, and roots <1 mm accounted for the greatest proportion of total root length, surface area, and tip number, with higher values observed in AMF-treated seedlings compared to their untreated counterparts. Further research is required at the field level to identify AMF strains and their interaction effects in alleviating the allelopathic impact of N. glauca on A. gerrardii seedling growth.
Predicting the Population Size and Potential Habitat Distribution of Moschus berezovskii in Chongqing Based on the MaxEnt Model
Authors: Liu Qing , Liu Huilin , Cui Xiaojuan , Peng Jianjun , Wang Xia , Shen Ling , Zhang Minqiang , Chen Lixia , Li Xin
Published: August 2024

The forest musk deer (Moschus berezovskii) is a national Class I protected wild animal in China, and the IUCN Red list classifies it as globally endangered. It has significant value in traditional Chinese medicine and spices. However, wild M. berezovskii has faced a severe population decline due to human hunting, habitat loss, and fragmentation. Thus, studying its population size and distribution pattern is of great importance to develop effective conservation measures. Here, we determined the optimal MaxEnt model and used stratified sampling and the fecal pile counting method to predict the population size and potential habitat distribution of wild M. berezovskii in Chongqing using 133 species distribution points and 28 environmental variables. The results were as follows: (1) When the optimal model parameters were RM = 3.5 and FC = LQHPT, it had high model prediction accuracy (AUC = 0.909 ± 0.010, TSS = 0.663). (2) Under various climatic, topographic, vegetation, and anthropogenic disturbance scenarios, M. berezovskii was primarily distributed in northern, eastern, southwestern regions of Chongqing, covering an area of approximately 5562.80 km2. (3) The key environmental factors affecting the potential habitat distribution of M. berezovskii were elevation (36.5%), normalized difference vegetation index (NDVI, 16.6%), slope (11.8%), and land-use type (7.6%), whereas climate and anthropogenic disturbance factors had relatively little influence. (4) A population estimation for M. berezovskii identified approximately 928 ± 109 individuals in Chongqing. We recommend prioritizing the preservation of high-altitude habitats and native vegetation to mitigate human interference and minimize road damage. In summary, our results can enhance the understanding of M. berezovskii distribution and provide a basis for effective conservation and management initiatives.
Hazardous Chemical Laboratory Fire Risk Assessment Based on ANP and 3D Risk Matrix
Authors: Qi Changmao , Zou Qifeng , Cao Yu , Ma Mingyuan
Published: August 2024

The laboratory is a high-risk place for scientific research and learning, and there are many risk factors and great potential for harm. Hazardous chemicals are important to consider and are the key objects to monitor in a laboratory. In recent years, hazardous chemical fire accidents have occurred in laboratories in various industries, bringing painful lessons and making it urgent to strengthen the safety management of hazardous laboratory chemicals. In this study, a semi-quantitative comprehensive risk assessment model for hazardous chemical laboratory fires was constructed by combining the bowtie model, three-dimensional risk matrix, and analytic network process (ANP). This study applied this method to the management of hazardous chemicals at the TRT Research Institute; evaluated the probability, severity, and preventive components of the corresponding indicators by constructing different index systems; and calculated the evaluation results using the weight of each index. The evaluation results show that the comprehensive likelihood level is 2, the comprehensive severity level is 3, the comprehensive preventive level is 3, and the final calculated comprehensive risk level is tolerable (II). Based on the results of the risk assessment, the corresponding control measures that can reduce the fire risk of hazardous chemicals in the laboratory are proposed according to the actual situation at the TRT Research Institute.
Meta-Genomic Analysis of Different Bacteria and Their Genomes Found in Raw Buffalo Milk Obtained in Various Farms Using Different Milking Methods
Authors: Li Ling , Miao Wenhao , Li Zhipeng , Huang Li , Hau Enghuan , Khan Muhammad Farhan , Liu Qingyou , Zeng Qingkun , Cui Kuiqing
Published: August 2024

Milking methods have significant impacts on the microbiological composition, which could affect the quality of raw buffalo milk. Hence, the current study was conducted on the impact of milking methods on microorganisms in buffalo tank raw milk from 15 farms in Guangxi, China. The farms were divided into two groups based on the milking method: mechanical milking (MM, n = 6) and hand milking (HM, n = 9). Somatic cell counts, bacterial cell counts and nutrients of the raw buffalo milk samples were analyzed. The comparison of raw buffalo milk samples was analyzed using metagenomic sequencing to detect any differences between the two groups. There was no significant difference in the basic nutritional compositions and somatic cell count of raw buffalo milk between the two milking methods. However, the HM samples had significantly higher bacterial counts and diversity compared to the MM samples. The results showed that Staphylococcus spp., Klebsiella spp., Streptococcus spp., and Pseudomonas spp. were the major microbes present in canned raw buffalo milk. However, the differences between the two milking methods were the relative abundance of core microorganisms and their potential mastitis-causing genera, including the content of antibiotic-resistance genes and virulence genes. Our study revealed that Staphylococcus spp. and Streptococcus spp. were significantly more abundant in the MM group, while Klebsiella spp. was more abundant in the HM group. Regardless of the milking method used, Pseudomonas spp. was identified as the primary genus contributing to antibiotic resistance and virulence genes in canned raw buffalo milk. These findings affirm that there are differences in the microbial and genomic levels in canned raw milk. To prove the functional roles of the discovered genes and how these genes affect milk quality, further research and experimental validation are necessary.
The Mobility of Identity: The Cosmopolitan Vision in Chang-rae Lee’s A Gesture Life
Authors: Xu Jiameng
Published: August 2024

Chang-rae Lee, a contemporary Korean-American writer, is renowned in the literary world for his rich imagination, delicate emotional expression, unique transcultural perspective and idiosyncratic narrative technique. He is one of the representatives who succeeds in transcending the classical paradigm of ethnic literature. Cosmopolitanism stems from ancient Greek philosophy, further developing in the age of Enlightenment and thriving in the era of globalization. Taking close reading as the primary methodology and cosmopolitanism as the major theoretical framework, this research attempts to provide a multi-dimensional, interdisciplinary and in-depth interpretation of Lee’s A Gesture Life, and finds that Lee has expressed his ideal vision that rejects the essentialist paradigm of unchanging cultural identity and upholds cosmopolitanism which embraces cultural diversity and heterogeneity. Additionally, through the depiction of cosmopolitan community, Lee has expressed his expectation for peaceful coexistence, communal solidarity, and mutual assistance among various ethnicities, and he has visualized a picture that different ethnic groups engage in transcultural communication in a harmonious way. In conclusion, A Gesture Life has widened the boundaries of Korean-American literature, and the cosmopolitan vision in the text has contributed to the development and prosperity of American ethnic literature.
Comprehensive Review of Chronic Stress Pathways and the Efficacy of Behavioral Stress Reduction Programs (BSRPs) in Managing Diseases
Authors: Shchaslyvyi Aladdin Y. , Antonenko Svitlana V. , Telegeev Gennadiy D.
Published: August 2024

The connection between chronic psychological stress and the onset of various diseases, including diabetes, HIV, cancer, and cardiovascular conditions, is well documented. This review synthesizes current research on the neurological, immune, hormonal, and genetic pathways through which stress influences disease progression, affecting multiple body systems: nervous, immune, cardiovascular, respiratory, reproductive, musculoskeletal, and integumentary. Central to this review is an evaluation of 16 Behavioral Stress Reduction Programs (BSRPs) across over 200 studies, assessing their effectiveness in mitigating stress-related health outcomes. While our findings suggest that BSRPs have the potential to enhance the effectiveness of medical therapies and reverse disease progression, the variability in study designs, sample sizes, and methodologies raises questions about the generalizability and robustness of these results. Future research should focus on long-term, large-scale studies with rigorous methodologies to validate the effectiveness of BSRPs.
Food Banks as a “Treasure Trove”: Users’ Experiences of a Western Australian Food Relief Organization
Authors: Marshall Ned , Bendotti Carolyn , Charlesworth Jessica , Mullan Barbara , Maxwell-Smith Chloe
Published: August 2024

Food banks are providing crucial relief as food insecurity increases worldwide. While these services are essential for vulnerable populations, there is variability in foods available and users may experience poor nutritional quality, and an overabundance of discretionary foods, contributing to public health risks including overnutrition and obesity. Understanding how customers perceive food availability, variety, and quality is important to inform relief services and health interventions. This study reports the findings of a convergent parallel mixed-methods investigation of user experiences and perceptions of food availability, variety, and quality at a major food bank in Western Australia. Food bank customers (N = 207) at a food bank branch and mobile van locations completed a survey, with an option to complete a subsequent semi-structured interview (n = 15). Approximately 80% of the survey sample had low (48%) or very low (30%) food security, half of the sample had been using the food bank for longer than 6 months, and 77% reported the food bank as their first choice for food. Three-quarters (77%) reported financial barriers to a balanced diet in the past twelve months and described how limited availability and variety complicated shopping. Interviewees explained complex perceptions of these issues, including favouring healthy food while considering discretionary food as a “luxury” that enhanced their quality of life. Our findings suggest that food bank users experience barriers to maintaining a balanced diet, encounter variable supplies of healthy and nutritious foods, and have concerns about the impacts of frequent discretionary food consumption. These findings have implications for public health promotion.
Navigating Real-World Randomized Clinical Trials: The ‘Parents as Teachers’ Experience
Authors: LeCroy Craig W. , Sullins Carolyn
Published: August 2024

The Parents as Teachers Randomized Controlled Trial (PAT RCT) Case Study investigates the multifaceted impact of implementing the PAT RCT in Arizona, U.S.A., shedding light on both the positive and negative effects. There has been a recent focus on improving the implementation of RCTs in community settings, as this issue has not been fully addressed. This research presents a case study examining the implementation of a community-based RCT in home visitation. This study also addresses the strategies that can be employed to mitigate some of the challenges in the implementation of an RCT, offering valuable insights for future RCTs in the domain of home visiting. The PAT program, aimed at providing parent education and family engagement for children from birth to kindergarten, encompasses a range of services, including personal visits, group connections, child screenings, and community resource linkages. The Parents as Teachers Randomized Controlled Trial (PAT RCT) directly promotes health by educating parents about health and wellness as well as providing early child screenings and heath referrals, all of which enhance health outcomes through timely interventions and improved parental practices. Lessons from the study also aim to improve the implementation of future health-related RCTs, ensuring effective delivery and impactful results.
Technological Advances in the Diagnosis of Cardiovascular Disease: A Public Health Strategy
Authors: Restrepo Tique Maria , Araque Oscar , Sanchez-Echeverri Luz Adriana
Published: August 2024

This article reviews technological advances and global trends in the diagnosis, treatment, and monitoring of cardiovascular diseases. A bibliometric analysis was conducted using the SCOPUS database, following PRISMA-ScR guidelines, to identify relevant publications on technologies applied in the diagnosis and treatment of cardiovascular diseases. An increase in scientific output since 2018 was observed, reflecting a growing interest in the technologies available for the treatment of cardiovascular diseases, with terms such as “telemedicine”, “artificial intelligence”, “image analysis”, and “cardiovascular disease” standing out as some of the most commonly used terms in reference to CVDs. Significant trends were identified, such as the use of artificial intelligence in precision medicine and machine learning algorithms to analyse data and predict cardiovascular risk, as well as advances in image analysis and 3D printing. Highlighting the role of artificial intelligence in the diagnosis and continuous monitoring of cardiovascular diseases, showing its potential to improve prognosis and reduce the incidence of acute cardiovascular events, this study presents the integration of traditional cardiology methods with digital health technologies—through a transdisciplinary approach—as a new direction in cardiovascular health, emphasising individualised care and improved clinical outcomes. These advances have great potential to impact healthcare, and as this field expands, it is crucial to understand the current research landscape and direction in order to take advantage of each technological advancement for improving the diagnosis, treatment, and quality of life of cardiovascular patients. It is concluded that the integration of these technologies into clinical practice has important implications for public health. Early detection and personalised treatment of cardiovascular diseases (CVDs) can significantly reduce the morbidity and mortality associated with these diseases. In addition, the optimisation of public health resources through telemedicine and telecare can improve access to quality care. The implementation of these technologies can be a crucial step towards reducing the global burden of cardiovascular diseases.
Enhancing Value-at-Risk with Credible Expected Risk Models
Authors: Syuhada Khreshna , Puspitasari Rizka , Arnawa I Kadek Darma , Mufaridho Lailatul , Elonasari Elonasari , Jannah Miftahul , Rohmawati Aniq
Published: August 2024

Accurate risk assessment is crucial for predicting potential financial losses. This paper introduces an innovative approach by employing expected risk models that utilize risk samples to capture comprehensive risk characteristics. The innovation lies in the integration of classical credibility theory with expected risk models, enhancing their stability and precision. In this study, two distinct expected risk models were developed, referred to as Model Type I and Model Type II. The Type I model involves independent and identically distributed random samples, while the Type II model incorporates time-varying stochastic processes, including heteroscedastic models like GARCH(p,q). However, these models often exhibit high variability and instability, which can undermine their effectiveness. To mitigate these issues, we applied classical credibility theory, resulting in credible expected risk models. These enhanced models aim to improve the accuracy of Value-at-Risk (VaR) forecasts, a key risk measure defined as the maximum potential loss over a specified period at a given confidence level. The credible expected risk models, referred to as CreVaR, provide more stable and precise VaR forecasts by incorporating credibility adjustments. The effectiveness of these models is evaluated through two complementary approaches: coverage probability, which assesses the accuracy of risk predictions; and scoring functions, which offer a more nuanced evaluation of prediction accuracy by comparing predicted risks with actual observed outcomes. Scoring functions are essential in further assessing the reliability of CreVaR forecasts by quantifying how closely the forecasts align with the actual data, thereby providing a more comprehensive measure of predictive performance. Our findings demonstrate that the CreVaR risk measure delivers more reliable and stable risk forecasts compared to conventional methods. This research contributes to quantitative risk management by offering a robust approach to financial risk prediction, thereby supporting better decision making for companies and financial institutions.
Dried Blood Spot Metabolome Features of Ischemic–Hypoxic Encephalopathy: A Neonatal Rat Model
Authors: Eldarov Chupalav , Starodubtseva Natalia , Shevtsova Yulia , Goryunov Kirill , Ionov Oleg , Frankevich Vladimir , Plotnikov Egor , Sukhikh Gennady , Zorov Dmitry , Silachev Denis
Published: August 2024

Hypoxic–ischemic encephalopathy (HIE) is a severe neurological disorder caused by perinatal asphyxia with significant consequences. Early recognition and intervention are crucial, with therapeutic hypothermia (TH) being the primary treatment, but its efficacy depends on early initiation of treatment. Accurately assessing the HIE severity in neonatal care poses challenges, but omics approaches have made significant contribution to understanding its complex pathophysiology. Our study further explores the impact of HIE on the blood metabolome over time and investigated changes associated with hypothermia’s therapeutic effects. Using a rat model of hypoxic–ischemic brain injury, we comprehensively analyzed dried blood spot samples for fat-soluble compounds using HPLC-MS. Our research shows significant changes in the blood metabolome after HIE, with a particularly rapid recovery of lipid metabolism observed. Significant changes in lipid metabolites were observed after 3 h of HIE, including increases in ceramides, carnitines, certain fatty acids, phosphocholines, and phosphoethanolamines, while sphingomyelins and N-acylethanolamines (NAEs) decreased (p < 0.05). Furthermore, NAEs were found to be significant features in the OPLS-DA model for HIE diagnosis, with an area under the curve of 0.812. TH showed a notable association with decreased concentrations of ceramides. Enrichment analysis further corroborated these observations, showing modulation in several key metabolic pathways, including arachidonic acid oxylipin metabolism, eicosanoid metabolism via lipooxygenases, and leukotriene C4 synthesis deficiency. Our study reveals dynamic changes in the blood metabolome after HIE and the therapeutic effects of hypothermia, which improves our understanding of the pathophysiology of HIE and could lead to the development of new rapid diagnostic approaches for neonatal HIE.
Drug Repurposing for COVID-19 by Constructing a Comorbidity Network with Central Nervous System Disorders
Authors: Qian Jing , Yang Bin , Wang Shuo , Yuan Su , Zhu Wenjing , Zhou Ziyun , Zhang Yujuan , Hu Guang
Published: August 2024

In the post-COVID-19 era, treatment options for potential SARS-CoV-2 outbreaks remain limited. An increased incidence of central nervous system (CNS) disorders has been observed in long-term COVID-19 patients. Understanding the shared molecular mechanisms between these conditions may provide new insights for developing effective therapies. This study developed an integrative drug-repurposing framework for COVID-19, leveraging comorbidity data with CNS disorders, network-based modular analysis, and dynamic perturbation analysis to identify potential drug targets and candidates against SARS-CoV-2. We constructed a comorbidity network based on the literature and data collection, including COVID-19-related proteins and genes associated with Alzheimer’s disease, Parkinson’s disease, multiple sclerosis, and autism spectrum disorder. Functional module detection and annotation identified a module primarily involved in protein synthesis as a key target module, utilizing connectivity map drug perturbation data. Through the construction of a weighted drug–target network and dynamic network-based drug-repurposing analysis, ubiquitin–carboxy-terminal hydrolase L1 emerged as a potential drug target. Molecular dynamics simulations suggested pregnenolone and BRD-K87426499 as two drug candidates for COVID-19. This study introduces a dynamic-perturbation-network-based drug-repurposing approach to identify COVID-19 drug targets and candidates by incorporating the comorbidity conditions of CNS disorders.
Activation of the G Protein-Coupled Bile Acid Receptor TGR5 Modulates the HCP5/miR-139-5p/DDIT4 Axis to Antagonize Cervical Cancer Progression
Authors: Su Jia , Zhao Yiqi , Chen Wei-Dong , Wang Yan-Dong
Published: August 2024

A growing body of evidence indicates that the G protein-coupled bile acid receptor, TGR5, plays a critical role in multiple physiological processes ranging from metabolic disorders to cancers. However, the biological functions of TGR5 in cervical cancer (CC) have not been elucidated. Here, using TGR5 knockout mice, we found that a deficiency of TGR5 leads to greater sensitivity to the progression of cervical inflammation. Activation of TGR5 by its specific ligands significantly attenuated the malignant behavior of CC cells. In addition, we found that TGR5 can negatively modulate the expression of lncRNA HCP5 by blocking its transcription activation when mediated by p65. HCP5 was highly expressed in CC tissues, which was positively correlated with the poor prognosis of CC patients. HCP5 knockdown notably restrained CC cell proliferation, colony formation, and migration in vitro, and inhibited tumor growth in vivo. Furthermore, HCP5 can function as the molecular sponge for miR-139-5p to upregulate DNA damage-induced transcript 4 (DDIT4) in CC cells. Murine xenograft studies demonstrated that TGR5 suppressed the tumor formation of CC cells and downregulated HCP5 and DDIT4 while increasing miR-139-5p in the xenografts. Taken together, these findings, for the first time, indicate that TGR5 inhibits CC progression by regulating the HCP5/miR-139-5p/DDIT4 axis, suggesting that it may represent a novel and potent target for CC treatment.