bluuebunny/crossref_metadata_2025_split huggingface dataset:
Photothermal and radiotherapy with alginate-coated gold nanoparticles for breast cancer treatment
Authors: Ghaffarlou Mohammadreza , Rashidzadeh Hamid , Mohammadi Ali , Mousazadeh Navid , Barsbay Murat , Sharafi Ali , Gharbavi Mahmoud , Danafar Hossein , Javani Siamak 
Published: June 2024

AbstractRadiation therapy and phototherapy are commonly used cancer treatments that offer advantages such as a low risk of adverse effects and the ability to target cancer cells while sparing healthy tissue. A promising strategy for cancer treatment involves using nanoparticles (NPs) in combination with radiation and photothermal therapy to target cancer cells and improve treatment efficacy. The synthesis of gold NPs (AuNPs) for use in biomedical applications has traditionally involved toxic reducing agents. Here we harnessed dopamine (DA)-conjugated alginate (Alg) for the facile and green synthesis of Au NPs (Au@Alg-DA NPs). Alg-DA conjugate reduced Au ions, simultaneously stabilized the resulting AuNPs, and prevented aggregation, resulting in particles with a narrow size distribution and improved stability. Injectable Au@Alg-DA NPs significantly promoted ROS generation in 4T1 breast cancer cells when exposed to X-rays. In addition, their administration raised the temperature under a light excitation of 808 nm, thus helping to destroy cancer cells more effectively. Importantly, no substantial cytotoxicity was detected in our Au@Alg-DA NPs. Taken together, our work provides a promising route to obtain an injectable combined radio enhancer and photothermally active nanosystem for further potential clinic translation.
Effects of multimodal explanations for autonomous driving on driving performance, cognitive load, expertise, confidence, and trust
Authors: Kaufman Robert , Costa Jean , Kimani Everlyne 
Published: June 2024

AbstractAdvances in autonomous driving provide an opportunity for AI-assisted driving instruction that directly addresses the critical need for human driving improvement. How should an AI instructor convey information to promote learning? In a pre-post experiment (n = 41), we tested the impact of an AI Coach’s explanatory communications modeled after performance driving expert instructions. Participants were divided into four (4) groups to assess two (2) dimensions of the AI coach’s explanations: information type (‘what’ and ‘why’-type explanations) and presentation modality (auditory and visual). We compare how different explanatory techniques impact driving performance, cognitive load, confidence, expertise, and trust via observational learning. Through interview, we delineate participant learning processes. Results show AI coaching can effectively teach performance driving skills to novices. We find the type and modality of information influences performance outcomes. Differences in how successfully participants learned are attributed to how information directs attention, mitigates uncertainty, and influences overload experienced by participants. Results suggest efficient, modality-appropriate explanations should be opted for when designing effective HMI communications that can instruct without overwhelming. Further, results support the need to align communications with human learning and cognitive processes. We provide eight design implications for future autonomous vehicle HMI and AI coach design.
Multi-stage framework for optimal incorporating of inverter based distributed generator into distribution networks
Authors: Hamza Shrouk A. , Yousef Mariem Y. , Ali A. A. , Masry Said M. El , Mosa Magdi A. 
Published: June 2024

AbstractRecently, hydrogen-based distributed generators (DG) have gained significant attention for modern energy generation systems. These modem DGs are typically outfitted with power electronics converters, resulting in harmonic pollution. Furthermore, increasing the growth of modern nonlinear loads may result in exceeding the harmonic beyond the permitted level. This research proposes a framework for optimal incorporation of inverter-based distributed generation (a fuel cell connected to an AC distribution system) for minimizing power losses, enhancing the voltage profile, and limiting both total and individual harmonic distortion according to the IEEE-519 standard. In addition, for accounting system sustainability, the proposed framework considers load variation and the expected rise in demand. Therefore, the suggested framework comprises three stages, which include fundamental and harmonic power flow analysis. The first stage identifies the optimal size and location of the DG in relation to the base load operating condition. While, with the optimal DG of the first stage, the amount of harmonic pollution may violate the limits during a high level of nonlinear load penetration, as a result, the second stage resizes the DG, considering the connection bus of the first stage, to mitigate the harmonics and optimize the system at a higher level of nonlinear load penetration. Both the first and second stages are performed off-line, while the third stage optimizes the system operation during run time according to loading conditions, harmonic pollution, and the available DG capacity of the previous stages. DG’s harmonic spectrum is represented according to recently issued IEEE 1547-2018 for permissible DG’s current distortion limits. The suggested approach is applied and evaluated using an IEEE 33-bus distribution system for various combinations of linear and nonlinear loads. For run-time operation throughout the day, the presented framework reduces the energy losses from 5.281 to 2.452 MWh/day (about 53.57% energy savings). This saving is associated with voltage profile enhancement without violating the permissible standard levels of harmonics and other system constraints.
A Siamese deep learning framework for efficient hardware Trojan detection using power side-channel data
Authors: Nasr Abdurrahman , Mohamed Khalil , Elshenawy Ayman , Zaki Mohamed 
Published: June 2024

AbstractHardware Trojans (HTs) are hidden threats embedded in the circuitry of integrated circuits (ICs), enabling unauthorized access, data theft, operational disruptions, or even physical harm. Detecting Hardware Trojans (HTD) is paramount for ensuring IC security. This paper introduces a novel Siamese neural network (SNN) framework for non-destructive HTD. The proposed framework can detect HTs by processing power side-channel signals without the need for a golden model of the IC. To obtain the best results, different neural network models such as Convolutional Neural Network (CNN), Gated Recurrent Unit (GRU), and Long Short-Term Memory (LSTM) are integrated individually with SNN. These models are trained on the extracted features from the Trojan Power & EM Side-Channel dataset. The results show that the Siamese LSTM model achieved the highest accuracy of 86.78%, followed by the Siamese GRU model with 83.59% accuracy and the Siamese CNN model with 73.54% accuracy. The comparison shows that of the proposed Siamese LSTM is a promising new approach for HTD and outperform the state-of-the-art methods.
Thymoquinone attenuates diabetes-induced hepatic damage in rat via regulation of oxidative/nitrosative stress, apoptosis, and inflammatory cascade with molecular docking approach
Authors: Hafez Mona H. , Ez Elarab Samar M. , Tohamy Hossam G. , El-Far Ali H. 
Published: June 2024

AbstractDiabetes mellitus (DM) is a complex metabolic condition that causes organ dysfunction. The current experiment sought to determine the effect of thymoquinone (TQ) on hyperglycemia, hyperlipidemia, oxidative/nitrosative stress, inflammation, and apoptosis in diabetic rats prompted by streptozotocin (STZ) (55 mg/kg body weight i/p). The animals were allocated into control, TQ (50 mg/kg B.W. orally administered for 4 succeeding weeks), Diabetic, and Diabetic + TQ groups. This study confirmed that TQ preserves the levels of insulin, fasting blood glucose, HOMA β-cell indices, HbA1c %, body weight, and lipid profile substantially relative to the DC group. Furthermore, hepatic antioxidant (CAT, GSH, and T-SOD) values were reduced. Conversely, the enzymatic activity of liver functions (AST, ALT, ALP, cytochrome P450, and hepatic glucose-6-phosphatase), lipid peroxidation (MDA), pro-inflammatory cytokines (IL-1β, TNF-α, and IL-6), nitric oxide (NO) and inflammatory marker (CRP) enhanced with STZ administration, which is substantially restored after TQ treatment. Relative to the diabetic rats, TQ reestablished the hepatic architectural changes and collagen fibers. Additionally, TQ downregulated the intensity of the immunohistochemical staining of pro-apoptotic marker (caspase-3), p53, and tumor necrosis factor-alpha (TNF-α) proteins in hepatic tissues. Furthermore, TQ displayed abilities to interact and inhibit the binding site of caspase-3, interleukin-6 receptor, interleukin-1 receptor type 1, TNF receptor superfamily member 1A, and TNF receptor superfamily member 1B in rats following the molecular docking modeling. All these data re-establish the liver functions, antioxidant enzymes, anti-inflammatory markers, and anti-apoptotic proteins impacts of TQ in STZ-induced DM rats. Founded on these outcomes, the experiment proposes that TQ is a novel natural supplement with various clinical applications, including managing DM, which in turn is recommended to play a pivotal role in preventing the progression of diabetes mellitus.
Yttrium oxide nanoparticles ameliorates calcium hydroxide and calcium titanate nanoparticles induced genomic DNA and mitochondrial damage, ROS generation and inflammation
Authors: Mohamed Hanan R. H. , Farouk Ahmed H. , Elbasiouni Salma H. , Nasif Kirolls A. , Safwat Gehan 
Published: June 2024

AbstractCalcium hydroxide (Ca(OH)2NPs), calcium titanate (CaTiO3NPs) and yttrium oxide (Y2O3NPs) nanoparticles are prevalent in many industries, including food and medicine, but their small size raises concerns about potential cellular damage and genotoxic effects. However, there are very limited studies available on their genotoxic effects. Hence, this was done to investigate the effects of multiple administration of Ca(OH)2NPs, CaTiO3NPs or/and Y2O3NPs on genomic DNA stability, mitochondrial membrane potential integrity and inflammation induction in mouse brain tissues. Mice were orally administered Ca(OH)2NPs, CaTiO3NPs or/and Y2O3NPs at a dose level of 50 mg/kg b.w three times a week for 2 weeks. Genomic DNA integrity was studied using Comet assay and the level of reactive oxygen species (ROS) within brain cells was analyzed using 2,7 dichlorofluorescein diacetate dye. The expression level of Presenilin-1, tumor necrosis factor-alpha (TNF-α) and Interleukin-6 (IL-6) genes and the integrity of the mitochondrial membrane potential were also detected. Oral administration of Ca(OH)2NPs caused the highest damage to genomic DNA and mitochondrial membrane potential, less genomic DNA and mitochondrial damage was induced by CaTiO3NPs administration while administration of Y2O3NPs did not cause any remarkable change in the integrity of genomic DNA and mitochondrial membrane potential. Highest ROS generation and upregulation of presenilin-1, TNF-α and IL-6 genes were also observed within the brain cells of mice administrated Ca(OH)2NPs but Y2O3NPs administration almost caused no changes in ROS generation and genes expression compared to the negative control. Administration of CaTiO3NPs alone slightly increased ROS generation and the expression level of TNF-α and IL-6 genes. Moreover, no remarkable changes in the integrity of genomic DNA and mitochondrial DNA potential, ROS level and the expression level of presenilin-1, TNF-α and IL-6 genes were noticed after simultaneous coadministration of Y2O3NPs with Ca(OH)2NPs and CaTiO3NPs. Coadministration of Y2O3NPs with Ca(OH)2NPs and CaTiO3NPs mitigated Ca(OH)2NPs and CaTiO3NPs induced ROS generation, genomic DNA damage and inflammation along with restoring the integrity of mitochondrial membrane potential through Y2O3NPs scavenging free radicals ability. Therefore, further studies are recommended to study the possibility of using Y2O3NPs to alleviate Ca(OH)2NPs and CaTiO3NPs induced genotoxic effects.
Neuroinflammation is dependent on sex and ovarian hormone presence following acute woodsmoke exposure
Authors: Wardhani Kartika , Yazzie Sydnee , Edeh Onamma , Grimes Martha , Dixson Connor , Jacquez Quiteria , Zychowski Katherine E. 
Published: June 2024

AbstractWoodsmoke (WS) exposure is associated with significant health-related sequelae. Different populations can potentially exhibit varying susceptibility, based on endocrine phenotypes, to WS and investigating neurological impacts following inhaled WS is a growing area of research. In this study, a whole-body inhalation chamber was used to expose both male and female C57BL/6 mice (n = 8 per group) to either control filtered air (FA) or acute WS (0.861 ± 0.210 mg/m3) for 4 h/d for 2 days. Neuroinflammatory and lipid-based biological markers were then assessed. In a second set of studies, female mice were divided into two groups: one group was ovariectomized (OVX) to simulate an ovarian hormone-deficient state (surgical menopause), and the other underwent Sham surgery as controls, to mechanistically assess the impact of ovarian hormone presence on neuroinflammation following FA and acute WS exposure to simulate an acute wildfire episode. There was a statistically significant impact of sex (P ≤ 0.05) and statistically significant interactions between sex and treatment in IL-1β, CXCL-1, TGF-β, and IL-6 brain relative gene expression. Hippocampal and cortex genes also exhibited significant changes in acute WS-exposed Sham and OVX mice, particularly in TGF-β (hippocampus) and CCL-2 and CXCL-1 (cortex). Cortex GFAP optical density (OD) showed a notable elevation in male mice exposed to acute WS, compared to the control FA. Sham and OVX females demonstrated differential GFAP expression, depending on brain region. Overall, targeted lipidomics in phosphatidylcholine (PC) and phosphatidylethanolamine (PE) serum and brain lipids demonstrated more significant changes between control FA and acute WS exposure in female mice, compared to males. In summary, male and female mice show distinct neuroinflammatory markers in response to acute WS exposure. Furthermore, ovarian hormone deficiency may impact the neuroinflammatory response following an acute WS event.
Synergistic effect of Salvadora persica and chitosan nanoparticles against oropharyngeal microorganisms
Authors: Balto Hanan , Bekhit Mounir Salim , Auda Sayed H. , Elansary Afaf , Bhat Ramesa Shafi , Marraiki Najat , Al-Hadlaq Solaiman 
Published: June 2024

AbstractHerbal medicine combined with nanoparticles has caught much interest in clinical dental practice, yet the incorporation of chitosan with Salvadora persica (S. persica) extract as an oral care product has not been explored. The aim of this study was to evaluate the combined effectiveness of Salvadora persica(S. persica) and Chitosan nanoparticles (ChNPs) against oropharyngeal microorganisms. Agar well diffusion, minimum inhibitory concentration, and minimal lethal concentration assays were used to assess the antimicrobial activity of different concentrations of ethanolic extracts of S. persica and ChNPs against selected fungal strains, Gram-positive, and Gram-negative bacteria. A mixture of 10% S. persica and 0.5% ChNPs was prepared (SChNPs) and its synergistic effect against the tested microbes was evaluated. Furthermore, the strain that was considered most sensitive was subjected to a 24-h treatment with SChNPs mixture; and examined using SEM, FT-IR and GC–MS analysis. S. persica extract and ChNPs exhibited concentration-dependent antimicrobial activities against all tested strains. S. persica extract and ChNPs at 10% were most effective against S. pneumoni, K. pneumoni, and C. albicans. SEM images confirmed the synergistic effect of the SChNPs mixture, revealing S. pneumonia cells with increased irregularity and higher cell lysis compared to the individual solutions. GC–MS and FT-IR analysis of SChNPs showed many active antimicrobial phytocompounds and some additional peaks, respectively. The synergy of the mixture of SChNPs in the form of mouth-rinsing solutions can be a promising approach for the control of oropharyngeal microbes that are implicated in viral secondary bacterial infections.
Geographical adaptability for optimizing the recommendation of soybean cultivars in the Brazilian Cerrado
Authors: Corbellini Marcos , Bobek Daniel Vicente , de Toledo José Francisco Ferraz , Ferreira Lenio Urzeda , Santana Dthenifer Cordeiro , Gilio Thiago Alexandre Santana , Teodoro Larissa Pereira Ribeiro , Teodoro Paulo Eduardo , Tardin Flavio Dessaune 
Published: June 2024

AbstractYield multi-location trials associated to geostatistical techniques with environmental covariables can provide a better understanding of G x E interactions and, consequently, adaptation limits of soybean cultivars. Thus, the main objective of this study is understanding the environmental covariables effects on soybean adaptation, as well as predicting the adaptation of soybean under environmental variations and then recommend each soybean cultivar to favorable environments aiming maximize the average yield. The trials were carried out in randomized block design (RBD) with three replicates over three years, in 28 locations. Thirty-two genotypes (commercial and pre-commercial) representing different maturity groups (7.5–8.5) were evaluated in each trial were covering the Edaphoclimatic Region (REC) 401, 402 and 403. The covariables adopted as environmental descriptors were accumulated rainfall, minimum temperature, mean temperature, maximum temperature, photoperiod, relative humidity, soil clay content, soil water avaibility and altitude. After fitting means through Mixed Linear Model, the Regression-Kriging procedure was applied to spacialize the grain yield using environmental covariables as predictors. The covariables explained 32.54% of the GxE interaction, being the soil water avaibility the most important to the adaptation of soybean cultivars, contributing with 7.80%. Yield maps of each cultivar were obtained and, hence, the yield maximization map based on cultivar recommendation was elaborated.
The GEA pipeline for characterizing Escherichia coli and Salmonella genomes
Authors: Dickey Aaron M. , Schmidt John W. , Bono James L. , Guragain Manita 
Published: June 2024

AbstractSalmonella enterica and Escherichia coli are major food-borne human pathogens, and their genomes are routinely sequenced for clinical surveillance. Computational pipelines designed for analyzing pathogen genomes should both utilize the most current information from annotation databases and increase the coverage of these databases over time. We report the development of the GEA pipeline to analyze large batches of E. coli and S. enterica genomes. The GEA pipeline takes as input paired Illumina raw reads files which are then assembled followed by annotation. Alternatively, assemblies can be provided as input and directly annotated. The pipeline provides predictive genome annotations for E. coli and S. enterica with a focus on the Center for Genomic Epidemiology tools. Annotation results are provided as a tab delimited text file. The GEA pipeline is designed for large-scale E. coli and S. enterica genome assembly and characterization using the Center for Genomic Epidemiology command-line tools and high-performance computing. Large scale annotation is demonstrated by an analysis of more than 14,000 Salmonella genome assemblies. Testing the GEA pipeline on E. coli raw reads demonstrates reproducibility across multiple compute environments and computational usage is optimized on high performance computers.
Synergistic effects of boron and saponin in mitigating salinity stress to enhance sweet potato growth
Authors: Younis Uzma , Danish Subhan , Datta Rahul , Al Obaid Sami , Ansari Mohammad Javed 
Published: June 2024

AbstractSalinity stress significantly hinders plant growth by disrupting osmotic balance and inhibiting nutrient uptake, leading to reduced biomass and stunted development. Using saponin (SAP) and boron (B) can effectively overcome this issue. Boron decreases salinity stress by stabilizing cell walls and membranes, regulating ion balance, activating antioxidant enzymes, and enhancing water uptake. SAP are bioactive compounds that have the potential to alleviate salinity stress by improving nutrient uptake, modulating plant hormone levels, promoting root growth, and stimulating antioxidant activity. That’s why the current study was planned to use a combination of SAP and boron as amendments to mitigate salinity stress in sweet potatoes. Four levels of SAP (0%, 0.1%, 0.15%, and 0.20%) and B (control, 5, 10, and 20 mg/L B) were applied in 4 replications following a completely randomized design. Results illustrated that 0.15% SAP with 20 mg/L B caused significant enhancement in sweet potato vine length (13.12%), vine weight (12.86%), root weight (8.31%), over control under salinity stress. A significant improvement in sweet potato chlorophyll a (9.84%), chlorophyll b (20.20%), total chlorophyll (13.94%), photosynthetic rate (17.69%), transpiration rate (16.03%), and stomatal conductance (17.59%) contrast to control under salinity stress prove the effectiveness of 0.15% SAP + 20 mg/L B treatment. In conclusion, 0.15% SAP + 20 mg/L B is recommended to mitigate salinity stress in sweet potatoes.
Associations of mixed metal exposure with chronic kidney disease from NHANES 2011–2018
Authors: Shi Xiaoru , Wang Xiao , Zhang Jia , Dang Ying , Ouyang Changping , Pan Jinhua , Yang Aimin , Hu Xiaobin 
Published: June 2024

AbstractMetals have been proved to be one of risk factors for chronic kidney disease (CKD) and diabetes, but the effect of mixed metal co-exposure and potential interaction between metals are still unclear. We assessed the urine and whole blood levels of cadmium (Cd), manganese (Mn), lead (Pb), mercury (Hg), and renal function in 3080 adults from National Health and Nutrition Survey (NHANES) (2011–2018) to explore the effect of mixed metal exposure on CKD especially in people with type 2 diabetes mellitus (T2DM). Weighted quantile sum regression model and Bayesian Kernel Machine Regression model were used to evaluate the overall exposure impact of metal mixture and potential interaction between metals. The results showed that the exposure to mixed metals was significantly associated with an increased risk of CKD in blood glucose stratification, with the risk of CKD being 1.58 (1.26,1.99) times in urine and 1.67 (1.19,2.34) times in whole blood higher in individuals exposed to high concentrations of the metal mixture compared to those exposed to low concentrations. The effect of urine metal mixture was elevated magnitude in stratified analysis. There were interactions between urine Pb and Cd, Pb and Mn, Pb and Hg, Cd and Mn, Cd and Hg, and blood Pb and Hg, Mn and Cd, Mn and Pb, Mn and Hg on the risk of CKD in patients with T2DM and no significant interaction between metals was observed in non-diabetics. In summary, mixed metal exposure increased the risk of CKD in patients with T2DM, and there were complex interactions between metals. More in-depth studies are needed to explore the mechanism and demonstrate the causal relationship.