Exogenous protectants alleviate ozone stress in Trifolium repens: Impacts on plant growth and endophytic fungi.

Industrialization-driven surface ozone (O3) pollution significantly impairs plant growth. This study evaluates the effectiveness of exogenous protectants [3 mg L⁻1 abscisic acid (ABA), 400 mg L⁻1 ethylenediurea (EDU), and 80 mg L⁻1 spermidine (Spd)] on Trifolium repens subjected to O3 stress in open-top chambers, focusing on plant growth and dynamics of culturable endophytic fungal communities. Results indicate that O3 exposure adversely affects photosynthesis, reducing root biomass and altering root structure, which further impacts the ability of plant to absorb essential nutrients such as potassium (K), magnesium (Mg), and zinc (Zn). Conversely, the application of ABA, EDU, and Spd significantly enhanced total biomass and chlorophyll content in T. repens. Specifically, ABA and Spd significantly improved root length, root surface area, and root volume, while EDU effectively reduced leaves' malondialdehyde levels, indicating decreased oxidative stress. Moreover, ABA and Spd treatments significantly increased leaf endophytic fungal diversity, while root fungal abundance declined. The relative abundance of Alternaria in leaves was substantially reduced by these treatments, which correlated with enhanced chlorophyll content and photosynthesis. Concurrently, EDU and Spd treatments increased the abundance of Plectosphaerella, enhance the absorption of K, Ca, and Mg. In roots, ABA treatment increased the abundance of Paecilomyces, while Spd treatment enhanced the presence of Stemphylium, linked to improved nitrogen (N), phosphorus (P), and K uptake. These findings suggest that specific symbiotic fungi mitigate O3-induced stress by enhancing nutrient absorption, promoting growth. This study highlights the potential of exogenous protectants to enhance plant resilience against O3 pollution through modulating interactions with endophytic fungal communities.

Identification of key immune-related genes and potential therapeutic drugs in diabetic nephropathy based on machine learning algorithms.

BACKGROUND: Diabetic nephropathy (DN) is a major contributor to chronic kidney disease. This study aims to identify immune biomarkers and potential therapeutic drugs in DN. METHODS: We analyzed two DN microarray datasets (GSE96804 and GSE30528) for differentially expressed genes (DEGs) using the Limma package, overlapping them with immune-related genes from ImmPort and InnateDB. LASSO regression, SVM-RFE, and random forest analysis identified four hub genes (EGF, PLTP, RGS2, PTGDS) as proficient predictors of DN. The model achieved an AUC of 0.995 and was validated on GSE142025. Single-cell RNA data (GSE183276) revealed increased hub gene expression in epithelial cells. CIBERSORT analysis showed differences in immune cell proportions between DN patients and controls, with the hub genes correlating positively with neutrophil infiltration. Molecular docking identified potential drugs: cysteamine, eltrombopag, and DMSO. And qPCR and western blot assays were used to confirm the expressions of the four hub genes. RESULTS: Analysis found 95 and 88 distinctively expressed immune genes in the two DN datasets, with 14 consistently differentially expressed immune-related genes. After machine learning algorithms, EGF, PLTP, RGS2, PTGDS were identified as the immune-related hub genes associated with DN. In addition, the mRNA and protein levels of them were obviously elevated in HK-2 cells treated with glucose for 24 h, as well as their mRNA expressions in kidney tissues of mice with DN. CONCLUSION: This study identified 4 hub immune-related genes (EGF, PLTP, RGS2, PTGDS), as well as their expression profiles and the correlation with immune cell infiltration in DN.

Effect of different techniques on removal of residual resin cement and marginal roughness of porcelain laminate veneers.

STATEMENT OF PROBLEM: A consensus regarding how to effectively remove residual resin cement and polish the restoration margin during the cementation of porcelain laminate veneers (PLVs) is lacking. PURPOSE: The purpose of this in vitro study was to evaluate the effect of different cleaning and polishing techniques on the removal of residual resin cement and margin surface roughness of PLVs. MATERIAL AND METHODS: PLVs were bonded to prepared buccal surfaces of extracted human premolars. All specimens were randomly divided by using a random number table into 8 groups (n=6): curette (C); brush (B); curette + polisher (CP); curette + rotary instrument (CR); curette + rotary instrument + polisher (CRP); brush + polisher (BP); brush + rotary instrument (BR); brush + rotary instrument + polisher (BRP). The relative amount of residual cement along the PLV margins were observed with a stereomicroscope and evaluated with a software program of Image J. The surface roughness and 3-dimensional (3D) morphology of the restoration margins were evaluated with a 3D topography scanner. Scanning electron microscopy (SEM) was used to detect the microscopic morphological characteristics of the restoration margins. Statistical analysis was performed by 2-way analysis of variance (α=.05). RESULTS: Different techniques were associated with significantly different efficiencies in terms of removing residual cement and the surface roughness at the restoration margins (P<.001). The lowest relative amount of residual cement, as well as the lowest surface roughness, was detected in the BRP group (P<.001). SEM observation indicated that the BRP technique also maintained the integrity of the cement layer. CONCLUSIONS: The removal of excess cement before polymerization using a brush, followed by sequential polishing with high-speed rotary instruments and low-speed polishers represents an effective technique in the removal of residual cement and smoothing the restoration margin without impairing the integrity of the bonded interface.

Mandarin fish von Hippel-Lindau protein regulates the NF-κB signaling pathway via interaction with IκB to promote fish ranavirus replication.

The von Hippel-Lindau tumor suppressor protein (VHL), an E3 ubiquitin ligase, functions as a critical regulator of the oxygen-sensing pathway for targeting hypoxia-inducible factors. Recent evidence suggests that mammalian VHL may also be critical to the NF-κB signaling pathway, although the specific molecular mechanisms remain unclear. Herein, the roles of mandarin fish ( Siniperca chuatsi) VHL ( scVHL) in the NF-κB signaling pathway and mandarin fish ranavirus (MRV) replication were explored. The transcription of scVHL was induced by immune stimulation and MRV infection, indicating a potential role in innate immunity. Dual-luciferase reporter gene assays and reverse transcription quantitative PCR (RT-qPCR) results demonstrated that scVHL evoked and positively regulated the NF-κB signaling pathway. Treatment with NF-κB signaling pathway inhibitors indicated that the role of scVHL may be mediated through scIKKα, scIKKß, scIκBα, or scp65. Co-immunoprecipitation (Co-IP) analysis identified scIκBα as a novel target protein of scVHL. Moreover, scVHL targeted scIκBα to catalyze the formation of K63-linked polyubiquitin chains to activate the NF-κB signaling pathway. Following MRV infection, NF-κB signaling remained activated, which, in turn, promoted MRV replication. These findings suggest that scVHL not only positively regulates NF-κB but also significantly enhances MRV replication. This study reveals a novel function of scVHL in NF-κB signaling and viral infection in fish.

piRNA-disease association prediction based on multi-channel graph variational autoencoder.

Piwi-interacting RNA (piRNA) is a type of non-coding small RNA that is highly expressed in mammalian testis. PiRNA has been implicated in various human diseases, but the experimental validation of piRNA-disease associations is costly and time-consuming. In this article, a novel computational method for predicting piRNA-disease associations using a multi-channel graph variational autoencoder (MC-GVAE) is proposed. This method integrates four types of similarity networks for piRNAs and diseases, which are derived from piRNA sequences, disease semantics, piRNA Gaussian Interaction Profile (GIP) kernel, and disease GIP kernel, respectively. These networks are modeled by a graph VAE framework, which can learn low-dimensional and informative feature representations for piRNAs and diseases. Then, a multi-channel method is used to fuse the feature representations from different networks. Finally, a three-layer neural network classifier is applied to predict the potential associations between piRNAs and diseases. The method was evaluated on a benchmark dataset containing 5,002 experimentally validated associations with 4,350 piRNAs and 21 diseases, constructed from the piRDisease v1.0 database. It achieved state-of-the-art performance, with an average AUC value of 0.9310 and an AUPR value of 0.9247 under five-fold cross-validation. This demonstrates the method's effectiveness and superiority in piRNA-disease association prediction.

Identification of diagnostic biomarkers of rheumatoid arthritis based on machine learning-assisted comprehensive bioinformatics and its correlation with immune cells.

Background: Rheumatoid arthritis (RA) is a chronic systemic autoimmune disease characterized by inflammatory cell infiltration, which can lead to chronic disability, joint destruction and loss of function. At present, the pathogenesis of RA is still unclear. The purpose of this study is to explore the potential biomarkers and immune molecular mechanisms of rheumatoid arthritis through machine learning-assisted bioinformatics analysis, in order to provide reference for the early diagnosis and treatment of RA disease. Methods: RA gene chips were screened from the public gene GEO database, and batch correction of different groups of RA gene chips was performed using Strawberry Perl. DEGs were obtained using the limma package of R software, and functional enrichment analysis such as gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), disease ontology (DO), and gene set (GSEA) were performed. Three machine learning methods, least absolute shrinkage and selection operator regression (LASSO), support vector machine recursive feature elimination (SVM-RFE) and random forest tree (Random Forest), were used to identify potential biomarkers of RA. The validation group data set was used to verify and further confirm its expression and diagnostic value. In addition, CIBERSORT algorithm was used to evaluate the infiltration of immune cells in RA and control samples, and the correlation between confirmed RA diagnostic biomarkers and immune cells was analyzed. Results: Through feature screening, 79 key DEGs were obtained, mainly involving virus response, Parkinson's pathway, dermatitis and cell junction components. A total of 29 hub genes were screened by LASSO regression, 34 hub genes were screened by SVM-RFE, and 39 hub genes were screened by Random Forest. Combined with the three algorithms, a total of 12 hub genes were obtained. Through the expression and diagnostic value verification in the validation group data set, 7 genes that can be used as diagnostic biomarkers for RA were preliminarily confirmed. At the same time, the correlation analysis of immune cells found that γδT cells, CD4+ memory activated T cells, activated dendritic cells and other immune cells were positively correlated with multiple RA diagnostic biomarkers, CD4+ naive T cells, regulatory T cells and other immune cells were negatively correlated with multiple RA diagnostic biomarkers. Conclusions: The results of novel characteristic gene analysis of RA showed that KYNU, EVI2A, CD52, C1QB, BATF, AIM2 and NDC80 had good diagnostic and clinical value for the diagnosis of RA, and were closely related to immune cells. Therefore, these seven DEGs may become new diagnostic markers and immunotherapy markers for RA.

The feedback loop between MTA1 and MTA3/TRIM21 modulates stemness of breast cancer in response to estrogen.

The metastasis-associated protein (MTA) family plays a crucial role in the development of breast cancer, a common malignancy with a high incidence rate among women. However, the mechanism by which each member of the MTA family contributes to breast cancer progression is poorly understood. In this study, we aimed to investigate the roles of MTA1, MTA3, and tripartite motif-containing 21 (TRIM21) in the proliferation, invasion, epithelial-mesenchymal transition (EMT), and stem cell-like properties of breast cancer cells in vivo and in vitro. The molecular mechanisms of the feedback loop between MTA1 and MTA3/TRIM21 regulated by estrogen were explored using Chromatin immunoprecipitation (ChIP), luciferase reporter, immunoprecipitation (IP), and ubiquitination assays. These findings demonstrated that MTA1 acts as a driver to promote the progression of breast cancer by repressing the transcription of tumor suppressor genes, including TRIM21 and MTA3. Conversely, MTA3 inhibited MTA1 transcription and TRIM21 regulated MTA1 protein stability in breast cancer. Estrogen disrupted the balance between MTA1 and MTA3, as well as between MTA1 and TRIM21, thereby affecting stemness and the EMT processes in breast cancer. These findings suggest that MTA1 plays a vital role in stem cell fate and the hierarchical regulatory network of EMT through negative feedback loops with MTA3 or TRIM21 in response to estrogen, supporting MTA1, MTA3, and TRIM21 as potential prognostic biomarkers and MTA1 as a treatment target for future breast cancer therapies.

An Insulin-Modified pH-Responsive Nanopipette Based on Ion Current Rectification.

The properties of nanopipettes largely rely on the materials introduced onto their inner walls, which allow for a vast extension of their sensing capabilities. The challenge of simultaneously enhancing the sensitivity and selectivity of nanopipettes for pH sensing remains, hindering their practical applications. Herein, we report insulin-modified nanopipettes with excellent pH response performances, which were prepared by introducing insulin onto their inner walls via a two-step reaction involving silanization and amidation. The pH response intensity based on ion current rectification was significantly enhanced by approximately 4.29 times when utilizing insulin-modified nanopipettes compared with bare ones, demonstrating a linear response within the pH range of 2.50 to 7.80. In addition, insulin-modified nanopipettes featured good reversibility and selectivity. The modification processes were monitored using the I-V curves, and the relevant mechanisms were discussed. The effects of solution pH and insulin concentration on the modification results were investigated to achieve optimal insulin introduction. This study showed that the pH response behavior of nanopipettes can be greatly improved by introducing versatile molecules onto the inner walls, thereby contributing to the development and utilization of pH-responsive nanopipettes.

Exhaustive State-to-State Cross Sections and Rate Coefficients for Inelastic N2-N2 Collisions using QCT Combined with Neural Network Models.

Using the quasi-classical trajectory method, we systematically studied the state-to-state vibrational relaxation process of N2(v1) + N2(v2) collisions over a wide temperature range (5000-30,000 K). Different temperature dependencies of the single- and multiquantum VV and VT events in various (v1,v2) collisions are captured, with the dominant channel being related to the initial vibrational energy levels (vmax = 50). At a specified relative translational energy, there is a monotonic relationship of the VT cross sections with the vibrational energy level, particularly in high-energy collisions. Additionally, we constructed well-trained neural network models (R-values reaching 0.99) using limited quasi-classical trajectory (QCT) data sets, which can be used to predict the state-to-state cross sections and rate coefficients of the VV processes N2(v1) + N2(v2) → N2(v1 - Δv) + N2(v2 + Δv) and VT processes N2(v1) + N2(v2) → N2(v1 - Δv) + N2(v2) (Δv = ±1, ±2, ±3) for collisions with arbitrary initial vibrational states. This work not only significantly reduces computational resources but also serves as a reference for the study of the state-to-state dynamics of all four-atom collision systems in hypersonic flows.

Four new lycoctonine-type C19-diterpenoid alkaloids from the whole plants of Delphinium kamaonense.

Four new lycoctonine-type C19-diterpenoid alkaloids kamaonensines H-K (1-4) have been isolated from the whole plants of Delphinium kamaonense, together with 12 known compounds (5-16). Interestingly, kamaonensines 1-3 contained a rare nitrone (immine N-oxide) moiety, respectively. Their structures were established by spectroscopic analyses. The active evaluation of compounds (1-16) by LPS induced RAW 264.7 macrophages showed that compounds 4 and 8 displayed strong anti-inflammatory activities. While compounds 11 and 12 also showed strong cytotoxicities by the RAW 264.7 cell viability assay.

Targeted delivery of TGF-ß mRNA to lung parenchyma using one-component ionizable amphiphilic Janus Dendrimers.

Current clinical strategies for the delivery of pulmonary therapeutics to the lung are primarily targeted to the upper portions of the airways. However, targeted delivery to the lower regions of the lung is necessary for the treatment of parenchymal lung injury and disease. Here, we have developed an mRNA therapeutic for the lower lung using one-component Ionizable Amphiphilic Janus Dendrimers (IAJDs) as a delivery vehicle. We deliver an anti-inflammatory cytokine mRNA, transforming growth factor-beta (TGF-ß), to produce transient protein expression in the lower regions of the lung. This study highlights IAJD's potential for precise, effective, and safe delivery of TGF-ß mRNA to the lung. This delivery system offers a promising approach for targeting therapeutics to the specific tissues, a strategy necessary to fill the current clinical gap in treating parenchymal lung injury and disease.

Aerosol exposure at air-liquid-interface (AE-ALI) in vitro toxicity system characterisation: Particle deposition and the importance of air control responses.

Experimental systems allowing aerosol exposure (AE) of cell cultures at the air-liquid-interface (ALI) are increasingly being used to assess the toxicity of inhaled contaminants as they are more biomimetic than standard methods using submerged cultures, however, they require detailed characterisation before use. An AE-ALI system combining aerosol generation with a CULTEX® exposure chamber was characterised with respect to particle deposition and the cellular effects of filtered air (typical control) exposures. The effect of system parameters (electrostatic precipitator voltage, air flowrate to cells and insert size) on deposition efficiency and spatial distribution were investigated using ICP-MS and laser ablation ICP-MS, for an aerosol of CeO2 nanoparticles. Deposition varied with conditions, but appropriate choice of operating parameters produced broadly uniform deposition at suitable levels. The impact of air exposure duration on alveolar cells (A549) and primary small airway epithelial cells (SAECs) was explored with respect to LDH release and expression of selected genes. Results indicated that air exposures could have a significant impact on cells (e.g., cytotoxicity and expression of genes, including CXCL1, HMOX1, and SPP1) at relatively short durations (from 10 mins) and that SAECs were more sensitive. These findings indicate that detailed system characterisation is essential to ensure meaningful results.

A review on improving the sensitivity and color stability of naturally sourced pH-sensitive indicator films.

Naturally sourced pH-sensitive indicator films are of interest for real-time monitoring of food freshness through color changes because of their safety. Therefore, natural pigments for indicator films are required. However, pigment stability is affected by environmental factors, which can in turn affect the sensitivity and color stability of the pH-sensitive indicator film. First, natural pigments (anthocyanin, betalain, curcumin, alizarin, and shikonin) commonly used in pH-sensitive indicator films are presented. Subsequently, the mechanisms behind the change in pigment color under different pH environments and their applications in monitoring food freshness are also described. Third, influence factors, such as the sources, types, and pH sensitivity of pigments, as well as environmental parameters (light, temperature, humidity, and oxygen) of sensitivity and color stability, are analyzed. Finally, methods for improving the pH-sensitive indicator film are explored, encapsulation of natural pigments, incorporation of a hydrophobic film-forming matrix or function material, and protective layer have been shown to enhance the color stability of indicator films, the addition of copigments or mental ions, blending of different natural pigments, and the utilization of electrospinning have been proved to increase the color sensitivity of indicator films. This review could provide theoretical support for the development of naturally sourced pH-sensitive indicator films with high stability and sensitivity and facilitate the development in the field of monitoring food freshness.

Quantitative assessment of intertarget position variations based on 4D-CT and 4D-CBCT simulations in single-isocenter multitarget lung stereotactic body radiation therapy.

BACKGROUND: In single-isocenter multitarget stereotactic body radiotherapy (SBRT), geometric miss risks arise from uncertainties in intertarget position. However, its assessment is inadequate, and may be interfered by the reconstructed tumor position errors (RPEs) during simulated CT and cone beam CT (CBCT) acquisition. This study aimed to quantify intertarget position variations and assess factors influencing it. METHODS: We analyzed data from 14 patients with 100 tumor pairs treated with single-isocenter SBRT. Intertarget position variation was measured using 4D-CT simulation to assess the intertarget position variations (ΔD) during routine treatment process. Additionally, a homologous 4D-CBCT simulation provided RPE-free comparison to determine the impact of RPEs, and isolating purely tumor motion induced ΔD to evaluate potential contributing factors. RESULTS: The median ΔD was 4.3 mm (4D-CT) and 3.4 mm (4D-CBCT). Variations exceeding 5 mm and 10 mm were observed in 31.1% and 5.5% (4D-CT) and 20.4% and 3.4% (4D-CBCT) of fractions, respectively. RPEs necessitated an additional 1-2 mm safety margin. Intertarget distance and breathing amplitude variability showed weak correlations with variation (Rs = 0.33 and 0.31). The ΔD differed significantly by locations (upper vs. lower lobe and right vs. Left lung). Notably, left lung tumor pairs exhibited the highest risk. CONCLUSIONS: This study provide a reliable way to assess intertarget position variation by using both 4D-CT and 4D-CBCT simulation. Consequently, single-isocenter SBRT for multiple lung tumors carries high risk of geometric miss. Tumor motion and RPE constitute a substantial portion of intertarget position variation, requiring correspondent strategies to minimize the intertarget uncertainties.

Ni/Cu Dual-Catalyzed Propargylation for the Stereodivergent Synthesis of Methohexital.

The development of efficient methodologies for the controlled manufacture of specific stereoisomers bearing quaternary stereocenters has prompted advances in a variety of scientific disciplines including pharmaceutical chemistry, materials science, and chemical biology. However, complete control of the absolute and relative stereochemical configurations of alkyne derivatives remains an unmet synthetic challenge. Herein, a Ni/Cu dual-catalyzed asymmetric propargylic substitution reaction is presented to produce propargylated products with all-carbon quaternary stereocenters in high yields with significant diastereo- and enantioselectivities (up to >20:1 dr, >99% ee). The synthesis of all stereochemical variants of methohexital, a widely used sedative-hypnotic drug, exemplifies the efficacy of dual-catalyzed stereodivergent propargylation.

Distribution and dynamic changes of Huanglongbing pathogen in its insect vector Diaphorina citri.

The Asian citrus psyllid (ACP) Diaphorina citri Kuwayama is the leading vector of Candidatus Liberibacter asiaticus (CLas), the causative agent of citrus Huanglongbing (HLB) disease. The distribution and dynamics of CLas within ACP are critical to understanding how the transmission, spread and infection of CLas occurs within its host vector in nature. In this study, the distribution and titer changes of CLas in various tissues of ACP 5th instar nymphs and adults were examined by fluorescence in situ hybridization (FISH) and real-time quantitative PCR (qPCR) techniques. Results demonstrated that 100% of ACP 5th instar nymphs and adults were infected with CLas following feeding on infected plants, and that CLas had widespread distribution in most of the tissues of ACP. The titers of CLas within the midgut, salivary glands and hemolymph tissues were the highest in both 5th instar nymphs and adults. When compared with adults, the titers of CLas in these three tissues of 5th instar nymphs were significantly higher, while in the mycetome, ovary and testes they were significantly lower than those of adults. FISH visualization further confirmed these findings. Dynamic analysis of CLas demonstrated that it was present across all the developmental ages of ACP adults. There was a discernible upward trend in the presence of CLas with advancing age in most tissues of ACP adults, including the midgut, hemolymph, salivary glands, foot, head, cuticula and muscle. Our findings have significant implications for the comprehensive understanding of the transmission, dissemination and infestation of CLas, which is of much importance for developing novel strategies to halt the spread of CLas, and therefore contribute to the efficient prevention and control of HLB.

Estimation of invasive coronary perfusion pressure using electrocardiogram and Photoplethysmography in a porcine model of cardiac arrest.

BACKGROUND: Coronary perfusion pressure (CPP) indicates spontaneous return of circulation and is recommended for high-quality cardiopulmonary resuscitation (CPR). This study aimed to investigate a method for non-invasive estimation of CPP using electrocardiography (ECG) and photoplethysmography (PPG) during CPR. METHODS: Nine pigs were used in this study. ECG, PPG, invasive arterial blood pressure (ABP), and right atrial pressure (RAP) signals were simultaneously recorded. The CPPs were estimated using three datasets: (a) ECG, (b) PPG, and (c) ECG and PPG, and were compared with invasively measured CPPs. Four machine-learning algorithms, namely support vector regression, random forest (RF), K-nearest neighbor, and gradient-boosted regression tree, were used for estimation of CPP. RESULTS: The RF model with a combined ECG and PPG dataset achieved better estimation of CPP than the other algorithms. Specifically, the mean absolute error was 4.49 mmHg, the root mean square error was 6.15 mm Hg, and the adjusted R2 was 0.75. A strong correlation was found between the non-invasive estimation and invasive measurement of CPP (r = 0.88), which supported our hypothesis that machine-learning-based analysis of ECG and PPG parameters can provide a non-invasive estimation of CPP for CPR. CONCLUSIONS: This study proposes a novel estimation of CPP using ECG and PPG with machine-learning-based algorithms. Non-invasively estimated CPP showed a high correlation with invasively measured CPP and may serve as an easy-to-use physiological indicator for high-quality CPR treatment.

Visualization and Analysis of Mapping Knowledge Domain of Fluid Flow Related to Microfluidic Chip.

Microfluidic chips are important tools to study the microscopic flow of fluid. To better understand the research clues and development trends related to microfluidic chips, a bibliometric analysis of microfluidic chips was conducted based on 1115 paper records retrieved from the Web of Science Core Collection database. CiteSpace and VOSviewer software were used to analyze the distribution of annual paper quantity, country/region distribution, subject distribution, institution distribution, major source journals distribution, highly cited papers, coauthor cooperation relationship, research knowledge domain, research focuses, and research frontiers, and a knowledge domain map was drawn. The results show that the number of papers published on microfluidic chips increased from 2010 to 2023, among which China, the United States, Iran, Canada, and Japan were the most active countries in this field. The United States was the most influential country. Nanoscience, energy, and chemical industry and multidisciplinary materials science were the main fields of microfluidic chip research. Lab on a Chip, Microfluidics and Nanofluidics, and Journal of Petroleum Science and Engineering were the main sources of papers published. The fabrication of chips, as well as their applications in porous media flow and multiphase flow, is the main knowledge domain of microfluidic chips. Micromodeling, fluid displacement, wettability, and multiphase flow are the research focuses in this field currently. The research frontiers in this field are enhanced oil recovery, interfacial tension, and stability.

Laser Precise Synthesis of Oxidation-Free High-Entropy Alloy Nanoparticle Libraries.

High-entropy alloy nanoparticles (HEA-NPs) show exceptional properties and great potential as a new generation of functional materials, yet a universal and facile synthetic strategy in air toward nonoxidized and precisely controlled composition remains a huge challenge. Here we provide a laser scribing method to prepare single-phase solid solution HEA-NPs libraries in air with tunable composition at the atomic level, taking advantage of the laser-induced metastable thermodynamics and substrate-assisted confinement effect. The three-dimensional porous graphene substrate functions as a microreactor during the fast heating/cooling process, which is conductive to the generation of the pure alloy phase by effectively blocking the binding of oxygen and metals, but is also beneficial for realizing accurate composition control via microstructure confinement-endowed favorable vapor pressure. Furthermore, by combining an active learning approach based on an adaptive design strategy, we discover an optimal composition of quinary HEA-NP catalysts with an ultralow overpotential for Li-CO2 batteries. This method provides a simple, fast, and universal in-air route toward the controllable synthesis of HEA-NPs, potentially integrated with machine learning to accelerate the research on HEAs.

Terpinen-4-ol Improves Lipopolysaccharide-Induced Macrophage Inflammation by Regulating Glutamine Metabolism.

Terpinen-4-ol (T-4-O) is an important component of tea tree oil and has anti-inflammatory effects. Currently, there are very few studies on the mechanisms by which T-4-O improves lipopolysaccharide (LPS)-induced macrophage inflammation. In this study, LPS-stimulated mouse RAW264.7 macrophages were used as a model to analyze the effects of T-4-O on macrophage inflammatory factors and related metabolic pathways in an inflammatory environment. The results showed that T-4-O significantly decreased the expression levels of inflammatory cytokines induced by LPS. Cellular metabolism results showed that T-4-O significantly decreased the ratio of the extracellular acidification rate and oxygen consumption rate. Non-targeted metabolomics results showed that T-4-O mainly affected glutamine and glutamate metabolism and glycine, serine, and threonine metabolic pathways. qPCR results showed that T-4-O increased the transcript levels of GLS and GDH and promoted glutamine catabolism. Western blotting results showed that T-4-O inhibited the mTOR and IκB, thereby decreasing NF-κB activity. The overall results showed that T-4-O inhibited mTOR phosphorylation to promote glutamine metabolism and increased cell oxidative phosphorylation levels, thereby inhibiting the expression of LPS-induced inflammatory cytokines.