bluuebunny/crossref_metadata_2025_split huggingface dataset:
Extending PROXIMAL to predict degradation pathways of phenolic compounds in the human gut microbiota
Authors: Balzerani Francesco , Blasco Telmo , Pérez-Burillo Sergio , Valcarcel Luis V. , Hassoun Soha , Planes Francisco J. 
Published: May 2024

AbstractDespite significant advances in reconstructing genome-scale metabolic networks, the understanding of cellular metabolism remains incomplete for many organisms. A promising approach for elucidating cellular metabolism is analysing the full scope of enzyme promiscuity, which exploits the capacity of enzymes to bind to non-annotated substrates and generate novel reactions. To guide time-consuming costly experimentation, different computational methods have been proposed for exploring enzyme promiscuity. One relevant algorithm is PROXIMAL, which strongly relies on KEGG to define generic reaction rules and link specific molecular substructures with associated chemical transformations. Here, we present a completely new pipeline, PROXIMAL2, which overcomes the dependency on KEGG data. In addition, PROXIMAL2 introduces two relevant improvements with respect to the former version: i) correct treatment of multi-step reactions and ii) tracking of electric charges in the transformations. We compare PROXIMAL and PROXIMAL2 in recovering annotated products from substrates in KEGG reactions, finding a highly significant improvement in the level of accuracy. We then applied PROXIMAL2 to predict degradation reactions of phenolic compounds in the human gut microbiota. The results were compared to RetroPath RL, a different and relevant enzyme promiscuity method. We found a significant overlap between these two methods but also complementary results, which open new research directions into this relevant question in nutrition.
Long-term intravital subcellular imaging with confocal scanning light-field microscopy
Authors: Lu Zhi , Zuo Siqing , Shi Minghui , Fan Jiaqi , Xie Jingyu , Xiao Guihua , Yu Li , Wu Jiamin , Dai Qionghai 
Published: May 2024

AbstractLong-term observation of subcellular dynamics in living organisms is limited by background fluorescence originating from tissue scattering or dense labeling. Existing confocal approaches face an inevitable tradeoff among parallelization, resolution and phototoxicity. Here we present confocal scanning light-field microscopy (csLFM), which integrates axially elongated line-confocal illumination with the rolling shutter in scanning light-field microscopy (sLFM). csLFM enables high-fidelity, high-speed, three-dimensional (3D) imaging at near-diffraction-limit resolution with both optical sectioning and low phototoxicity. By simultaneous 3D excitation and detection, the excitation intensity can be reduced below 1 mW mm−2, with 15-fold higher signal-to-background ratio over sLFM. We imaged subcellular dynamics over 25,000 timeframes in optically challenging environments in different species, such as migrasome delivery in mouse spleen, retractosome generation in mouse liver and 3D voltage imaging in Drosophila. Moreover, csLFM facilitates high-fidelity, large-scale neural recording with reduced crosstalk, leading to high orientation selectivity to visual stimuli, similar to two-photon microscopy, which aids understanding of neural coding mechanisms.
Multi-wall carbon Nanotube surface-based functional nanoparticles for stimuli-responsive dual pharmaceutical compound delivery
Authors: Nabitabar Masoumeh , Shaterian Maryam , Danafar Hossein , Enhessari Morteza 
Published: May 2024

AbstractCarbon nanotubes (CNTs) have the potential to serve as delivery systems for medicinal substances and gene treatments, particularly in cancer treatment. Co-delivery of curcumin (CUR) and Methotrexate (MTX) has shown promise in cancer treatment, as it uses fewer drugs and has fewer side effects. This study used MTX-conjugated albumin (BSA)-based nanoparticles (BSA-MTX) to enhance and assess the efficiency of CUR. In-vitro cytotoxicity tests, DLS, TEM, FTIR, UV/Vis, SEM, and DSC studies assessed the formulations' physical and chemical properties. The Proteinase K enzyme was used to severe amidic linkages between MTX and BSA. The findings demonstrated the efficacy of using ƒ-MWCNT-CUR-BSA-MTX as a vehicle for efficient co-delivery of CUR and MTX in cancer treatment. The MTT colorimetric method was used to evaluate the effect of chemical and medicinal compounds. Cell division was studied using the MTT method to investigate the effect of pure MWCNT, pure CUR, MTX-BSA, and ƒ-MWCNT-CUR-MTX-BSA. Studies on cell lines have shown that the combination of curcumin and MTX with CNT can increase and improve the effectiveness of both drugs against cancer. A combination of drugs curcumin and methotrexate simultaneously had a synergistic effect on MCF-7 cells, which indicated that these drugs could potentially be used as a strategy for both prevention and treatment of breast cancer. Also, ƒ-MWCNT-CUR-MTX-BSA was found to have a significant effect on cancer treatment with minimal toxicity compared to pure curcumin, pure MTX-BSA, MTX, and ƒ-MWCNT alone. Unique properties such as a high ratio of specific surface area to volume, high chemical stability, chemical adsorption ability, high capacity of drug and biomolecules of carbon nanotubes, as well as multiple drug loading at the same time The combination of ƒ-MWCNT-CUR-BSA MTX significantly impacts cancer therapy), are desirable as an alternative option for targeted drug delivery and high therapeutic efficiency.
Evaluation of dental plaque reduction using microcurrent-emitting toothbrushes in orthodontic patients: a randomized, double-blind, crossover clinical trial
Authors: Kim Ji-Hoi , Yu Jae-Hun , Mangal Utkarsh , Liu Jing , Jung Hyo-Jung , Cha Jung-Yul 
Published: May 2024

AbstractThis study aimed to compare the effectiveness of microcurrent-emitting toothbrushes (MCTs) and ordinary toothbrushes in reducing the dental plaque index (PI) and dental caries activity among orthodontic patients. The evaluation was performed using a crossover study design involving 22 orthodontic patients randomly assigned to the MCT or ordinary toothbrush groups. The participants used the designated toothbrush for 4 weeks and had a 1-week wash-out time before crossover to the other toothbrush. PI (Attin’s index) and dental caries activity were measured at baseline and at the end of each 4-week period. Additionally, patients completed questionnaires to assess patient satisfaction for “freshness in mouth” and “cleansing degree.” The results showed that the MCT group had a significant reduction in PI (p = 0.009), whereas the ordinary toothbrush group did not (p = 0.595). There was no significant difference in the dental caries activity between the two groups (p > 0.05). Patient satisfaction assessment revealed that 65% patients in the MCT group had more than “fair” experience of freshness, in contrast to 50% of patients in the ordinary toothbrush group. Satisfaction with cleansing degree was similar in both groups. Overall, these findings suggest that MCTs are more effective in reducing dental PI than ordinary toothbrushes.
The effect of social network based motivational interviewing on health behaviors among infertile women with polycystic ovary syndrome: A randomized controlled trial
Authors: Hamzehgardeshi Zeinab , Elyasi Forouzan , Moosazadeh Mahmood , Ahmadi Imaneh , Jahanfar Shayesteh , Ahmadian Maryam , Ansari Fatemeh 
Published: May 2024

AbstractPolycystic ovary syndrome is one of the commonest and complex endocrine disorders in females of reproductive age. Attention to self-care behaviors such as health-promoting behaviors can improve physiological and psychological conditions in women with PCOS. This study aimed to determine the efficacy of Social Network-Based Motivational Interviewing on health-promoting behaviors and quality of life of infertile women with polycystic ovary syndrome. In this randomized controlled trial, 60 infertile women with polycystic ovary syndrome were randomly selected and assigned to the interventio (n = 30) or a control group (n = 30). Participants in the control group received routine care. Those in the intervention group received five motivational group sessions in WhatsApp, which were conducted in five groups of six participants each. The data related to health-promoting behaviors and quality of life were collected through an online questionnaire. Both groups were followed up immediately and 2 months after the intervention. Data collected in the two stages were analyzed using the paired-samples t-test, Chi-square, and repeated measures analysis. No significant difference was observed between the two groups before the intervention means health-promoting behaviors and quality of life scores (p>0.05). Immediately and two months after the intervention, the mean scores of health-promoting behaviors and their domains increased in the intervention group. This increase is statistically compared to the first test, and the scores obtained by the control group in the second (p< 0.001, ES = 1.5) and the third test (p< 0.001, ES= 1.3) were significant. The score of the quality of life variable increase was not statistically significant compared to the first test and also to the scores obtained by the control group. However According to the Generalized estimating equations (GEE) test, the changes in quality of life score between the two groups in the three stages of measurement are statistically significant. WhatsApp support increases the health-promoting self-care behaviors rate and has favorable effects on follow-up.Trial registration: Iranian Registry for Clinical Trial (the link to trial: https://www.irct.ir/trial/48089). Registered August 11 2020.
Research on safety condition assessment methodology for single tower steel box girder suspension bridges over the sea based on improved AHP-fuzzy comprehensive evaluation
Authors: Su Huifeng , Guo Cheng , Wang Ziyi , Han Tao , Kamanda David Bonfils , Su Fengzhao , Shang Liuhong 
Published: May 2024

AbstractIn order to propose a reliable method for assessing the safety condition for single-tower steel box girder Suspension bridges over the sea, a condition monitoring system is established by installing sensors on the bridge structure. The system is capable of gathering monitoring data that influence the safety status of the bridge. These include cable tension, load on the main tower and pylon, bearing displacement, wind direction, wind speed, and ambient temperature and humidity. Furthermore, an improved Analytic Hierarchy Process (AHP) algorithm is developed by integrating a hybrid triangular fuzzy number logic structure. This improvement, coupled with comprehensive fuzzy evaluation methods, improves the consistency, weight determination, and security evaluation capabilities of the AHP algorithm. Finally, taking the No.2 Channel Bridge as an example and based on the data collected by the health monitoring system, the application of the safety assessment method proposed in this paper provides favorable results in evaluating the overall safety status of the bridge in practical engineering applications. This provides a basis for management decisions by bridge maintenance departments. This project confirms that the research results can provide a reliable method for assessing the security status of relevant areas.
A new single switch universal supply voltage DC-DC converter for PV systems with MGWM-AFLC MPPT controller
Authors: Touti Ezzeddine , Rafikiran Shaik , Aoudia Mouloud , Alrougy Ibrahim Mohammed , Khan Baseem , Ali Ahmed 
Published: May 2024

AbstractThe present power generation government companies focus on Renewable Power Sources (RPS) because their features are zero carbon footprint, unlimited power source, fewer greenhouse pollutants, fewer output wastages, plus creatinga very healthy atmosphere. In this work, the sunlight source is utilized for the Photovoltaic (PV) standalone network. The merits of sunlight sources are very optimal human resources needed, unlimited natural sources, plus easy operation. However, the solar power resource is nonlinear fashion. As a result, the operating point of the sunlight network fluctuates concerning sunlight intensity. So, in this article, the Modified Grey Wolf Methodology with Adaptive Fuzzy Logic Controller (MGWM-AFLC) is introduced to maintain the operating point of the sunlight system at the global power point position of the PV array. This controller traces the MPP with very low fluctuations in the PV-produced voltage. The advantages of this proposed method arefewer sensing devices required, less difficulty in development, more useful for rapid changes inthe sunlight temperatures, simpler to realize operation, greater economic growth, plus highly useful for household applications. The sunlight set-up generation voltage is lowwhich is improved by introducing the new Wide Power Rating High Voltage DC-DC Boost Converter (WPRHVBC). The features of this WPRHV converter are low voltage strain on semiconductor devices, few passive elements are enough to develop the circuit, plus easy understanding.
Peripheral inflammatory response in people after acute ischaemic stroke and isolated spontaneous cervical artery dissection
Authors: Bauer Angelika , Boehme Christian , Mayer-Suess Lukas , Rudzki Dagmar , Knoflach Michael , Kiechl Stefan , Reindl Markus 
Published: May 2024

AbstractThe systemic inflammatory response following acute ischaemic stroke remains incompletely understood. We characterised the circulating inflammatory profile in 173 acute ischaemic stroke patients by measuring 65 cytokines and chemokines in plasma. Participants were grouped based on their inflammatory response, determined by high-sensitivity C-reactive protein levels in the acute phase. We compared stroke patients’ profiles with 42 people experiencing spontaneous cervical artery dissection without stroke. Furthermore, variations in cytokine levels among stroke aetiologies were analysed. Follow-up samples were collected in a subgroup of ischaemic stroke patients at three and twelve months. Ischaemic stroke patients had elevated plasma levels of HGF and SDF-1α, and lower IL-4 levels, compared to spontaneous cervical artery dissection patients without stroke. Aetiology-subgroup analysis revealed reduced levels of nine cytokines/chemokines (HGF, SDF-1α, IL-2R, CD30, TNF-RII, IL-16, MIF, APRIL, SCF), and elevated levels of IL-4 and MIP-1β, in spontaneous cervical artery dissection (with or without ischaemic stroke as levels were comparable between both groups) compared to other aetiologies. The majority of cytokine/chemokine levels remained stable across the study period. Our research indicates that stroke due to large artery atherosclerosis, cardioembolism, and small vessel occlusion triggers a stronger inflammatory response than spontaneous cervical artery dissection.
Enhancing grid resiliency in distributed energy systems through a comprehensive review and comparative analysis of islanding detection methods
Authors: Kulkarni Mangesh S , Mishra Sachin , Sudabattula Suresh Kumar , Sharma Naveen Kumar , Basha D. Baba , Bajaj Mohit , Tuka Milkias Berhanu 
Published: May 2024

AbstractReduction of fossil fuel usage, clean energy supply, and dependability are all major benefits of integrating distributed energy resources (DER) with electrical utility grid (UG). Nevertheless, there are difficulties with this integration, most notably accidental islanding that puts worker and equipment safety at risk. Islanding detection methods (IDMs) play a critical role in resolving this problem. All IDMs are thoroughly evaluated in this work, which divides them into two categories: local approaches that rely on distributed generation (DG) side monitoring and remote approaches that make use of communication infrastructure. The study offers a comparative evaluation to help choose the most efficient and applicable IDM, supporting well-informed decision-making for the safe and dependable operation of distributed energy systems within electrical distribution networks. IDMs are evaluated based on NDZ outcomes, detection duration, power quality impact, multi-DG operation, suitability, X/R ratio reliance, and efficient functioning.
From density functional theory to machine learning predictive models for electrical properties of spinel oxides
Authors: Elbaz Yuval , Caspary Toroker Maytal 
Published: May 2024

AbstractThis work focuses on predicting and characterizing the electronic conductivity of spinel oxides, which are promising materials for energy storage devices and for the oxygen evolution and oxygen reduction reactions due to their attractive properties and abundance of transition metals that can act as active sites for catalysis. To this end, a new database was developed from first principles, including band structure and conductivity properties of spinel oxides, and machine learning algorithms were trained on this database to predict electronic conductivity and band gaps based solely on the compositions. The models developed in this study are scaled from the quantum level up to a continuum conductivity model. The relatively small database used in this study allowed for accurate predictions of band gap and conductivity. By altering the composition of spinel oxides, the model was able to predict high conductivity for spinels with high nickel content and to match experimental trends for manganese cobalt spinels. The ability to predict material properties is especially important in energy conversion devices such as batteries and supercapacitors where redox reactions take place.
Advanced stability analysis of a fractional delay differential system with stochastic phenomena using spectral collocation method
Authors: Xie Mengqi , Khan Sami Ullah , Sumelka Wojciech , Alamri Atif M. , AlQahtani Salman A. 
Published: May 2024

AbstractIn recent years, there has been a growing interest in incorporating fractional calculus into stochastic delay systems due to its ability to model complex phenomena with uncertainties and memory effects. The fractional stochastic delay differential equations are conventional in modeling such complex dynamical systems around various applied fields. The present study addresses a novel spectral approach to demonstrate the stability behavior and numerical solution of the systems characterized by stochasticity along with fractional derivatives and time delay. By bridging the gap between fractional calculus, stochastic processes, and spectral analysis, this work contributes to the field of fractional dynamics and enriches the toolbox of analytical tools available for investigating the stability of systems with delays and uncertainties. To illustrate the practical implications and validate the theoretical findings of our approach, some numerical simulations are presented.
LncRNA TUG1 mediates microglial inflammatory activation by regulating glucose metabolic reprogramming
Authors: He Chunxiang , Li Ze , Yu Wenjing , Luo Rongsiqing , Zhou Jinyong , He Jiawei , Chen Qi , Song Zhenyan , Cheng Shaowu 
Published: May 2024

AbstractMicroglia are natural immune cells in the central nervous system, and the activation of microglia is accompanied by a reprogramming of glucose metabolism. In our study, we investigated the role of long non-coding RNA taurine-upregulated gene 1 (TUG1) in regulating microglial glucose metabolism reprogramming and activation. BV2 cells were treated with Lipopolysaccharides (LPS)/Interferon-γ (IFN-γ) to establish a microglial activation model. The glycolysis inhibitor 2-Deoxy-D-glucose (2-DG) was used as a control. The expression levels of TUG1 mRNA and proinflammatory cytokines such as Interleukin-1β (IL-1β), Interleukin -6, and Tumor Necrosis Factor-α mRNA and anti-inflammatory cytokines such as IL-4, Arginase 1(Arg1), CD206, and Ym1 were detected by RT-qPCR. TUG1 was silenced using TUG1 siRNA and knocked out using CRISPR/Cas9. The mRNA and protein expression levels of key enzymes involved in glucose metabolism, such as Hexokinase2, Glyceraldehyde-3-phosphate dehydrogenase (GAPDH), Lactate dehydrogenase, Glucose 6 phosphate dehydrogenase, and Pyruvate dehydrogenase (PDH), were determined by RT-qPCR and Western blotting. The glycolytic rate of microglial cells was measured using Seahorse. Differential metabolites were determined by metabolomics, and pathway enrichment was performed using these differential metabolites. Our findings revealed that the expression of TUG1 was elevated in proinflammatory-activated microglia and positively correlated with the levels of inflammatory factors. The expression of anti-inflammatory cytokines such as IL-4, Arg1, CD206, and Ym1 were decreased when induced with LPS/IFN-γ. However, this decrease was reversed by the treatment with 2-DG. Silencing of GAPDH led to an increase in the expression of TUG1 and inflammatory factors. TUG1 knockout (TUG1KO) inhibited the expression of glycolytic key enzymes and promoted the expression of oxidative phosphorylation key enzymes, shifting the metabolic profile of activated microglia from glycolysis to oxidative phosphorylation. Additionally, TUG1KO reduced the accumulation of metabolites, facilitating the restoration of the tricarboxylic acid cycle and enhancing oxidative phosphorylation in microglia. Furthermore, the downregulation of TUG1 was found to reduce the expression of both proinflammatory and anti-inflammatory cytokines under normal conditions. Interestingly, when induced with LPS/IFN-γ, TUG1 downregulation showed a potentially beneficial effect on microglia in terms of inflammation. Downregulation of TUG1 expression inhibits glycolysis and facilitates the shift of microglial glucose metabolism from glycolysis to oxidative phosphorylation, promoting their transformation towards an anti-inflammatory phenotype and exerting anti-inflammatory effects in BV2.
Assimilation of PSO and SVR into an improved ARIMA model for monthly precipitation forecasting
Authors: Parviz Laleh , Ghorbanpour Mansour 
Published: May 2024

AbstractPrecipitation due to its complex nature requires a comprehensive model for forecasting purposes and the efficiency of improved ARIMA (IARIMA) forecasts has been proved relative to the conventional models. This study used two procedures in the structure of IARIMA to obtain accurate monthly precipitation forecasts in four stations located in northern Iran; Bandar Anzali, Rasht, Ramsar, and Babolsar. The first procedure applied support vector regression (SVR) for modeling the statistical characteristics and monthly precipitation of each class, IARIMA-SVR, which improved the evaluation metrics so that the decrease of Theil's coefficient and average relative variance in all stations was 21.14% and 17.06%, respectively. Two approaches are defined in the second procedure which includes a forecast combination (C) scheme, IARIMA-C-particle swarm optimization (PSO), and artificial intelligence technique. Generally, most of the time, IARIMA-C-PSO relative to the other approach, exhibited acceptable results and the accuracy improvement was greater than zero at all stations. Comparing the two procedures, it is found that the capability of IARIMA-C-PSO is higher concerning the IARIMA-SVR, so the decrease in the normalized mean squared error value from IARIMA to IARIMA-SVR and IARIMA-C-PSO is 36.72% and 39.92%, respectively for all stations. The residual predictive deviation (RPD) of IARIMA-C-PSO for all stations is greater than 2, which indicates the high performance of the model. With a comprehensive investigation, the performance of Bandar Anzali station is better than the other stations. By developing an improved ARIMA model, one can achieve a high performance in structure identifying and forecasting of monthly time series which is one of the issues of interest and importance.