Network Analysis Research Articles

Investigation of the Molecular Mechanism Underlying the Therapeutic Effect of Perilla frutescens L. Essential Oil on Acute Lung Injury Using Gas Chromatography Mass Spectrometry and Network Pharmacology.

The present study aimed to investigate the molecular mechanism through which Perilla essential oil treats acute lung injury (ALI) through network pharmacology, molecular docking, and in vitro assays. Relevant ALI targets of the active ingredients of Perilla essential oil were predicted using the SwissTargetPrediction database and meta TarFisher database. These ALI targets were then screened using GeneCards and DisGeNET, and differentially expressed ALI target genes were identified using the Gene Expression Omnibus (GEO) database. Next, key targets were enriched using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Protein-protein interaction network analysis was performed to obtain targets with the highest degree values for molecular docking with Perilla essential oil active ingredients. For in vitro experiments, lipopolysaccharide (LPS) was used to induce an ALI inflammation model using RAW264.7 cells. The model cells were then treated with Perilla essential oil to detect the protein expression levels of vascular endothelial factor (NO), tumor necrosis factor (TNF-α), and p65 nuclear transcription factor in them. Sixty-eight key targets of Perilla oil were identified for the treatment of ALI. These targets were found to be involved in biological processes related to peptides, response to lipopolysaccharides, the positive regulation of cytokine production, etc., using GO. The signaling pathways found to be associated with the targets included the AGE-RAGE signaling pathway in diabetic complications, the NF-kappa B signaling pathway, and small cell lung cancer and other inflammatory signaling pathways. The five key targets that showed good binding activity with Perilla oil active ingredients included TNF, RELA, PARP1, PTGS2, and IRAK4. In vitro assays showed that Perilla essential oil could significantly reduce NO and TNF-α levels and inhibit the phosphorylation of nuclear transcription factor P65, thus inhibiting the activation of NF-κB signaling pathway. Conclusion Perilla essential oil can play a role in the treatment of ALI by inhibiting the activation of the NF-κB signaling pathway and preventing an excessive inflammatory response. This study thus provides a reference for the in-depth study of the mechanisms through which Perilla essential oil treats ALI.

A domain-oriented approach to characterizing movement-evoked pain.

Movement-evoked pain (MEP) impacts a substantial proportion of US adults living with chronic pain. Evidence suggests that MEP is influenced by numerous biopsychosocial factors and mediated by mechanisms differing from those of spontaneous pain. However, both characteristic and mechanistic knowledge of MEP remain limited, hindering effective diagnosis and treatment. We asked (1) can chronic pain, functional, psychosocial, and behavioral measures be grouped into descriptive domains that characterize MEP? and (2) what relationships exist between biopsychosocial factors across multiple domains of MEP? We formed 6 characteristic domains from 46 MEP-related variables in a secondary analysis of data from 178 individuals (aged 45-85 years) with knee pain. Ratings of pain during 3 functional activities (ie, Balance, Walking, Chair Stand) were used as primary MEP variables. Pearson correlations were calculated to show linear relationships between all individual domain variables. Relationships between variables were further investigated through weighted correlation network analysis. We observed a unique combination of pain characteristics associated with MEP apart from general pain. Notably, minutes doing physical activity were inversely associated with multiple variables within 4 of the 6 domains. Weighted correlation network analysis largely supported our classification of MEP domains. Additional interdomain relationships were observed, with the strongest existing between MEP, Mechanical Pain, and Multiple Pain Characteristics and Symptoms. Additional relationships were observed both within and between other domains of the network. Our analyses bolster fundamental understanding of MEP by identifying relevant mechanistic domains and elucidating biopsychosocial and interdomain relationships.

Anisomeles indica (L.) Kuntze leaf essential oil ameliorates LPS-induced inflammation in RAW 264.7 cells: An integrated approach of network pharmacology and experimental validation

Anisomeles indica (L.) Kuntze (Lamiaceae), commonly called catmint, is an essential oil-bearing herb used in traditional systems of medicine against rheumatism, convulsions, inflammatory skin disorders, and epilepsy. However, the efficacy and mechanism of action of its essential oil against inflammatory conditions remain elusive. The current study aims at the chemical characterization of the essential oil of A. indica leaves (AILEO) and understanding the mechanism of its anti-inflammatory effects by an integrated approach of network pharmacology and in vitro assays. GC–MS analysis of AILEO revealed a total of 30 constituents representing 94.19 % of the total oil. The majority of the chemical groups include diterpene hydrocarbons with abietatriene (58.13 %) and abietadiene (7.18 %) as the major constituents. Out of 30 compounds, 20 passed the ADME screening and were considered as active constituents. A total of 524 compound targets, 409 anti-inflammation targets, and 88 compound-disease intersecting targets were obtained. Multi-level network analysis revealed that the pharmacological mechanisms of alleviation of inflammation by AILEO are due to its interaction with five core inflammatory targets such as PI3K, AKT1, MEK1, ERK1, and RXRA involved in the PI3K-AKT signaling pathway. AILEO did not exhibit any cytotoxic effect on RAW 264.7 cells, but it significantly inhibited nitric oxide (NO) production and reduced the levels of pro-inflammatory cytokines (TNF-α, IL-6, and IL-1β) in vitro assays. Further, AILEO enhanced the expression levels of endogenous antioxidant enzymes (CAT, SOD, GPx, and GSH) in comparison to the LPS-induced group. RT-qPCR analysis revealed that AILEO modulated the level of mRNA expression of all five core targets associated with the PI3K-AKT signaling pathway, which further supported the findings of network pharmacology. This study provides valuable insights into the intricate mechanisms by which AILEO exerts anti-inflammatory action indicating its pharmacological potential as a promising candidate for the treatment of disorders linked with inflammation.

Design and Analysis of Water Distribution System Network for a Rural Area of Gujarat State by Using EPANET

Abstract: This study presents the use of EPANET software in the design of the water distribution network for Vadi village in Umarpada District, Gujarat State. The major purpose of providing a good distribution network is to provide sufficient pressure at each point with less loss. A water distribution network consists of pipes, tanks etc. EPANET software is simulation tool which is used for efficient distribution of water supply. For the analysis of existing water distribution system various data are required like, Main water source, Population of the area, Demand for water, Requirement of the pumps, Distribution Network, and water tanks. The Google Earth Image of Vadi village is downloaded and the elevation of a node, length of pipe was recorded for nearly 112 junctions and 114 pipes.

Manipulating terahertz guided wave excitation with Fabry-Perot cavity–assisted metasurfaces

Metasurfaces are emerging as powerful tools for manipulating complex light fields, offering enhanced control in free space and on-chip waveguide applications. Their ability to customize refractive indices and dispersion properties opens up new possibilities in light guiding, yet their efficiency in exciting guided waves, particularly through metallic structures, is not fully explored. Here, we present a new method for exciting terahertz (THz) guided waves using Fabry-Perot (FP) cavity-assisted metasurfaces that enable spin-selective directional coupling and mode selection. Our design uses a substrate-free ridge silicon THz waveguide with air cladding and a supporting slab, incorporating placed metallic metasurfaces to exploit their unique interaction with the guided waves. With the silicon thin layer and air serving as an FP cavity, THz waves enter from the bottom of the device, thereby intensifying the impact of the metasurfaces. The inverse-structured complementary metasurface could enhance excitation performance. We demonstrate selective excitation of TE00 and TE10 modes with directional control, confirmed through simulations and experimental validations using a THz vector network analyzer (VNA) system. This work broadens the potential of metasurfaces for advanced THz waveguide technologies.

Rosmarinic acid alleviates septic acute respiratory distress syndrome in mice by suppressing the bronchial epithelial RAS-mediated ferroptosis

Activating angiotensin-converting enzyme 2 (ACE2) is an important player in the pathogenesis of septic-related acute respiratory distress syndrome (ARDS). Rosmarinic acid (RA) as a prominent polyphenolic secondary metabolite derived from Rosmarinus officinalis modulates ACE2 in sepsis remains unclear, although its impact on ACE inhibition and septic-associated lung injury has been explored. The study investigated the ACE2 expression in lipopolysaccharide (LPS)-induced lungs in mice and BEAS2B cells. Additionally, molecular docking, protein–protein interaction (PPI) network analysis, and western blotting were employed to predict and evaluate the molecular mechanism of RA on LPS-induced ferroptosis in vivo and in vitro. LPS-induced glutathione peroxidase 4 (GPX4) downregulation, ACE/ACE2 imbalance, and alteration of frequency of breathing (BPM), minute volume (MV), and the expiratory flow at 50% expired volume (EF50) were reversed by captopril pretreatment in vitro and in vivo. RA notably inhibited the infiltration into the lungs of neutrophils and monocytes with increased amounts of GPX4 and ACE2 proteins, lung function improvement, and decreased inflammatory cytokines levels and ER stress in LPS-induced ARDS in mice. Molecular docking showed RA was able to interact with ACE and ACE2. Moreover, combined with different pharmacological inhibitors to block ACE and ferroptosis, RA still significantly inhibited inflammatory cytokines Interleukin-1ß (IL-1ß), tumor necrosis factor-α (TNF-α), and C-X-C motif chemokine 2 (CXCL2) levels, as well as improved lung function, and enhanced GPX4 expression. Particularly, the anti-ferroptosis effect of RA in LPS-induced septic ARDS is RAS-dependent.

MiR-497 target gene regulatory network in angiosarcoma.

Angiosarcoma is a vascular sarcoma that is highly aggressive and metastatic. Due to its rarity, treatment options for patients are limited, therefore more research is needed to identify possible therapeutic vulnerabilities. We previously found that conditional deletion of Dicer1 drives angiosarcoma development in mice. Given the role of DICER1 in canonical microRNA (miRNA) biogenesis, this suggests that miRNA loss is important in angiosarcoma development. After testing miRNAs previously suggested to have a tumor-suppressive role in angiosarcoma, microRNA-497-5p (miR-497) suppressed cell viability most significantly. We also found that miR-497 overexpression led to significantly reduced cell migration and tumor formation. To understand the mechanism of miR-497 in tumor suppression, we identified clinically relevant target genes using a combination of RNA-sequencing data in an angiosarcoma cell line, expression data from angiosarcoma patients, and target prediction algorithms. We validated miR-497 direct regulation of CCND2, CDK6, and VAT1. One of these genes, VAT1, is an understudied protein that has been suggested to promote cell migration and metastasis in other cancers. Indeed, we find that pharmacologic inhibition of VAT1 with the natural product Neocarzilin A reduces angiosarcoma migration. Implications: This work supports the potent tumor-suppressive abilities of miR-497 in angiosarcoma, providing evidence for its potential as a therapeutic, and provides insight into the mechanisms of tumor suppression through analysis of the target gene regulatory network of miR-497.

Exploration of the Changes in Facial Microbiota of Maskne Patients and Healthy Controls Before and After Wearing Masks Using 16S rRNA Analysis.

Whether in the field of medical care, or in people's daily life and health protection, the importance of masks has been paid more and more attention. Acne, the most common complication after wearing masks, which is also called maskne, has been successfully introduced into the common language as a common topic of dermatologist consultations. This study aims to study the changes of microflora in maskne patients and healthy controls before and after wearing masks. In the summer of 2023, we collected a total of 50 samples from 15 maskne patients and 10 healthy controls before and after wearing surgical masks for a long time. 16S ribosomal DNA sequencing and identification technology with V3-V4 variable region were adopted to explore the microbiome changes caused by mask wearing, analyze the changes in microbial diversity, and make interaction network. LDA effect size analysis was used to identify which bacteria showed significant changes in their relative abundance from phylum to genus. After wearing a mask, the microbiome of the maskne patients changed significantly more than that of the healthy controls, with both α diversity and β diversity lower than those of maskne patients before wearing masks and those of healthy controls after wearing masks. Co-occurrence network analysis showed that compared with other groups, the network of maskne patients after wearing masks for a long time had the lowest connectivity and complexity, but the highest clustering property, while the opposite was true for healthy controls. Many microbes that are potentially beneficial to the skin decreased significantly after wearing a mask. There was almost no difference in healthy controls before and after wearing a mask.

Semantic network analysis in consumer and marketing research: application areas in phygital contexts

Purpose Large-scale text-based data increasingly poses methodological challenges due to its size, scope and nature, requiring sophisticated methods for managing, visualizing, analyzing and interpreting such data. This paper aims to propose semantic network analysis (SemNA) as one possible solution to these challenges, showcasing its potential for consumer and marketing researchers through three application areas in phygital contexts. Design/methodology/approach This paper outlines three general application areas for SemNA in phygital contexts and presents specific use cases, data collection methodologies, analyses, findings and discussions for each application area. Findings The paper uncovers three application areas and use cases where SemNA holds promise for providing valuable insights and driving further adoption of the method: (1) Investigating phygital experiences and consumption phenomena; (2) Exploring phygital consumer and market discourse, trends and practices; and (3) Capturing phygital social constructs. Research limitations/implications The limitations section highlights the specific challenges of the qualitative, interpretivist approach to SemNA, along with general methodological constraints. Practical implications Practical implications highlight SemNA as a pragmatic tool for managers to analyze and visualize company-/brand-related data, supporting strategic decision-making in physical, digital and phygital spaces. Originality/value This paper contributes to the expanding body of computational, tool-based methods by providing an overview of application areas for the qualitative, interpretivist approach to SemNA in consumer and marketing research. It emphasizes the diversity of research contexts and data, where the boundaries between physical and digital spaces have become increasingly intertwined with physical and digital elements closely integrated – a phenomenon known as phygital.

A Study on Optimizing the Maximal Product in Cubic Fuzzy Graphs for Multifaceted Applications

Graphs in the field of science and technology make considerable use of theoretical concepts. When dealing with numerous links and circumstances in which there are varying degrees of ambiguity or robustness in the connections between aspects, rather than purely binary interactions, cubic fuzzy graphs (CFGs) are more adaptable and compatible than fuzzy graphs. To better represent the complexity of interactions or linkages in the real world, an emerging CFG can be very helpful in achieving better problem-solving abilities that specialize in domains like network analysis, the social sciences, information retrieval, and decision support systems. This idea can be used for a variety of uncertainty-related issues and assist decision-makers in selecting the best course of action through the use of a CFG. Enhancing the maximized network of three cubic fuzzy graphs’ decision-making efficiency was the ultimate objective of this study. We introduced the maximal product of three cubic fuzzy graphs to investigate how interval-valued fuzzy membership, fuzzy membership, and the miscellany of relations are all simultaneously supported through the aspect of degree and total degree of a vertex. Furthermore, the domination on the maximal product of three CFGs was illustrated to analyze the minimum domination number of the weighted CFG, and the proposed approach is illustrated with applications.

Inflammatory and neurodegenerative serum protein biomarkers increase sensitivity to detect clinical and radiographic disease activity in multiple sclerosis

The multifaceted nature of multiple sclerosis requires quantitative biomarkers that can provide insights related to diverse physiological pathways. To this end, proteomic analysis of deeply-phenotyped serum samples, biological pathway modeling, and network analysis were performed to elucidate inflammatory and neurodegenerative processes, identifying sensitive biomarkers of multiple sclerosis disease activity. Here, we evaluated the concentrations of > 1400 serum proteins in 630 samples from three multiple sclerosis cohorts for association with clinical and radiographic new disease activity. Twenty proteins were associated with increased clinical and radiographic multiple sclerosis disease activity for inclusion in a custom assay panel. Serum neurofilament light chain showed the strongest univariate correlation with gadolinium lesion activity, clinical relapse status, and annualized relapse rate. Multivariate modeling outperformed univariate for all endpoints. A comprehensive biomarker panel including the twenty proteins identified in this study could serve to characterize disease activity for a patient with multiple sclerosis.

Collective signalling is shaped by feedbacks between signaller variation, receiver perception and acoustic environment in a simulated communication network.

Communication takes place within a network of multiple signallers and receivers. Social network analysis provides tools to quantify how an individual's social positioning affects group dynamics and the subsequent biological consequences. However, network analysis is rarely applied to animal communication, likely due to the logistical difficulties of monitoring natural communication networks. We generated a simulated communication network to investigate how variation in individual communication behaviours generates network effects, and how this communication network's structure feeds back to affect future signalling interactions. We simulated competitive acoustic signalling interactions among chorusing individuals and varied several parameters related to communication and chorus size to examine their effects on calling output and social connections. Larger choruses had higher noise levels, and this reduced network density and altered the relationships between individual traits and communication network position. Hearing sensitivity interacted with chorus size to affect both individuals' positions in the network and the acoustic output of the chorus. Physical proximity to competitors influenced signalling, but a distinctive communication network structure emerged when signal active space was limited. Our model raises novel predictions about communication networks that could be tested experimentally and identifies aspects of information processing in complex environments that remain to be investigated. This article is part of the theme issue 'The power of sound: unravelling how acoustic communication shapes group dynamics'.

Comprehensive comparative analysis of the periodontal pathogen Porphyromonas gingivalis: exploring the pan-genome, the reconstruction of the gene regulatory network and genome-scale metabolic network.

Porphyromonas gingivalis is a nonmotile, obligate anaerobic, Gram-negative bacterium known for its association with periodontal disease and its involvement in systemic diseases such as atherosclerosis, cardiovascular disease, colon cancer and Alzheimer's disease. This bacterium produces several virulence factors, including capsules, fimbriae, lipopolysaccharides, proteolytic enzymes and hemagglutinins. A comparative genomic analysis revealed the open pangenome of P. gingivalis and identified complete type IV secretion systems (T4SS) in strain KCOM2805 and almost complete type VI secretion systems (T6SS) in strains KCOM2798 and ATCC49417, which is a new discovery as previous studies did not find the proteins involved in secretion systems IV and VI. Conservation of some virulence factors between different strains was observed, regardless of their genetic diversity and origin. In addition, we performed for the first time a reconstruction analysis of the gene regulatory network (GRN), identifying transcription factors and proteins involved in the regulatory mechanisms of bacterial pathogenesis. In particular, QseB regulates the expression of hemagglutinin and arginine deaminase, while Rex may suppress the release of gingipain through interactions with PorV and the formatum/nitrate transporter. Our study highlights the central role of conserved virulence factors and regulatory pathways, particularly QseB and Rex, in P. gingivalis and provides insights into potential therapeutic targets.

Integrated multi-omics investigation revealed the importance of phenylpropanoid metabolism in the defense response of Lilium regale Wilson to Fusarium wilt

Abstract Lilies (genus: Lilium) play a significant role in the global cut-flower industry, but they are highly susceptible to Fusarium wilt caused by Fusarium oxysporum. However, Lilium regale, a wild lily species, exhibits remarkable resistance to F. oxysporum. To investigate the quantitative resistance of L. regale to Fusarium wilt, a comprehensive multi-omics analysis was conducted. Upon inoculation with F. oxysporum, L. regale roots showed a significant accumulation of phenylpropane metabolites, including lignin precursors, flavonoids, and hydroxycinnamic acids. These findings were consistent with the up-regulated expression of phenylpropanoid biosynthesis-related genes encoding various enzymes, as revealed by transcriptomics and proteomics analyses. Furthermore, metabolomics and proteomics data demonstrated differential activation of monoterpenoid and isoquinoline alkaloid biosynthesis. Colorimetry and high-performance liquid chromatography analyses revealed significantly higher levels of total flavonoids, lignin, ferulic acid, phlorizin, and quercetin contents in L. regale scales compared to susceptible lily ‘Siberia’ scales during F. oxysporum infection. These phenylpropanes exhibited inhibitory effects on F. oxysporum growth and suppressed the expression of pathogenicity-related genes. Transcriptional regulatory network analysis suggested that ethylene-responsive transcription factors (ERFs) may positively regulate phenylpropanoid biosynthesis. Therefore, LrERF4 was cloned and transiently overexpressed in the Fusarium wilt-susceptible Oriental hybrid lily, ‘Siberia’. The overexpression of LrERF4 resulted in increased levels of total flavonoids, lignin, ferulic acid, phlorizin, and quercetin, while the silencing of LrERF4 in L. regale through RNAi had opposite effect. In conclusion, phenylpropanoid metabolism plays a crucial role in the defense response of L. regale against Fusarium wilt, with LrERF4 acting as a positive regulator of phenylpropane biosynthesis.

The cycle of violence: effects of violence experience, behavior, and attitudes on adolescents’ peer rejection networks

Previous research on adolescent peer networks has mainly focused on friendship networks and their association with violence, but very limited research is available on peer rejection networks. This lack of knowledge hinders the effectiveness of preventing peer rejection and its negative effects. Based on the theory of the cycle of violence, the present study examines the extent to which parental physical abuse experiences, aggressive behavior toward peers and acceptance of violence are related to peer rejection networks at school. Social network analysis with a stochastic actor-oriented model of longitudinal data collected from high school students (Wave 1, n = 620; Wave 2, n = 590) confirms that adolescents who frequently use aggression toward their peers are more likely to be rejected, especially if those adolescents have experienced abuse. Similarly, peers are more likely to reject adolescents with high levels of accepting violence. The results also show that aggression toward peers generally tends to decrease over time but not for adolescents who reject a larger number of students. For students who reject many peers, aggression frequency increases. From the perspective of resilience theory, peer rejection, when combined with aggression toward peers and acceptance of violence, particularly in female adolescents, creates a significant risk factor for socio-emotional development. Therefore, tackling violence attitudes, experiences and behavior in the school environment and at home is crucial in overcoming the cycle of violence.

Identification of Ion Channel-Related Genes as Diagnostic Markers and Potential Therapeutic Targets for Osteoarthritis Through Bioinformatics and Machine Learning-based approaches

ABSTRACT Background Osteoarthritis (OA) is a debilitating joint disorder characterized by the progressive degeneration of articular cartilage. Although the role of ion channels in OA pathogenesis is increasingly recognized, diagnostic markers and targeted therapies remain limited. Methods In this study, we analyzed the GSE48556 dataset to identify differentially expressed ion channel-related genes (DEGs) in OA and normal controls. We employed machine learning algorithms, least absolute shrinkage and selection operator(LASSO), and support vector machine recursive feature elimination(SVM-RFE) to select potential diagnostic markers. Then the gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) were performed to explore the potential diagnostic markers’ involvement in biological pathways. Finally, weighted gene co-expression network analysis (WGCNA) was used to identify key genes associated with OA. Results We identified a total of 47 DEGs, with the majority involved in transient receptor potential (TRP) pathways. Seven genes (CHRNA4, GABRE, HTR3B, KCNG2, KCNJ2, LRRC8C, and TRPM5) were identified as the best characteristic genes for distinguishing OA from healthy samples. We performed clustering analysis and identified two distinct subtypes of OA, C1, and C2, with differential gene expression and immune cell infiltration profiles. Then we identified three key genes (PPP1R3D, ZNF101, and LOC651309) associated with OA. We constructed a prediction model using these genes and validated it using the GSE46750 dataset, demonstrating reasonable accuracy and specificity. Conclusions Our findings provide novel insights into the role of ion channel-related genes in OA pathogenesis and offer potential diagnostic markers and therapeutic targets for the treatment of OA.

Programmed Cell Death-Related Gene Signature Associated with Prognosis and Immune Infiltration and the Roles of HMOX1 in the Proliferation and Apoptosis were Investigated in Uveal Melanoma.

Uveal melanoma (UVM) is the most common primary ocular malignancy, with a wide range of symptoms and outcomes. The programmed cell death (PCD) plays an important role in tumor development, diagnosis, and prognosis. There is still no research on the relationship between PCD-related genes and UVM. A novel PCD-associated prognostic model is urgently needed to improve treatment strategies. We aim to screen PCD-related prognostic signature and investigate its proliferation ability and apoptosis in UVM cells. The clinical information and RNA-seq data of the UVM patients were collected from the TCGA cohort. All the patients were classified using consensus clustering by the selected PCD-related genes. After univariate Cox regression and PPI network analysis, the prognostic PCD-related genes were then submitted to the LASSO regression analysis to build a prognostic model. The level of immune infiltration of 8-PCD signature in high- and low-risk patients was analyzed using xCell. The prediction on chemotherapy and immunotherapy response in UVM patients was assessed by GDSC and TIDE algorithm. CCK-8, western blot and Annexin V-FITC/PI staining were used to explore the roles of HMOX1 in UVM cells. A total of 8-PCD signature was constructed and the risk score of the PCD signature was negatively correlated with the overall survival, indicating strong predictive ability and independent prognostic value. The risk score was positively correlated with CD8 Tcm, CD8 Tem and Th2 cells. Immune cells in high-risk group had poorer overall survival. The drug sensitivity demonstrated that cisplatin might impact the progression of UVM and better immunotherapy responsiveness in the high-risk group. Finally, Overespression HMOX1 (OE-HMOX1) decreased the cell viability and induced apoptosis in UVM cells. Recuse experiment results showed that ferrostatin-1 (fer-1) protected MP65 cells from apoptosis and necrosis caused by OE-HMOX1. The PCD signature may have a significant role in the tumor microenvironment, clinicopathological characteristics, prognosis and drug sensitivity. More importantly, HMOX1 depletion greatly induced tumor cell growth and inhibited cell apoptosis and fer-1 protected UVM cells from apoptosis and necrosis induced by OE-HMOX1. This work provides a foundation for effective therapeutic strategy in tumour treatment.

Response of photosynthetic characteristics and antioxidant system in the leaves of safflower to NaCl and NaHCO3.

Compared with NaCl, NaHCO3 caused more serious oxidative damage and photosynthesis inhibition in safflower by down-regulating the expression of related genes. Salt-alkali stress is one of the important factors that limit plant growth. NaCl and sodium bicarbonate (NaHCO3) are neutral and alkaline salts, respectively. This study investigated the physiological characteristics and molecular responses of safflower (Carthamus tinctorius L.) leaves treated with 200mmolL-1 of NaCl or NaHCO3. The plants treated with NaCl treatment were less effective at inhibiting the growth of safflower, but increased the content of malondialdehyde (MDA) in leaves. Meanwhile, safflower alleviated stress damage by increasing proline (Pro), soluble protein (SP), and soluble sugar (SS). Both fresh weight and dry weight of safflower was severely decreased when it was subjected to NaHCO3 stress, and there was a significant increase in the permeability of cell membranes and the contents of osmotic regulatory substances. An enrichment analysis of the differentially expressed genes (DEGs) using Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes identified significant enrichment of photosynthesis and pathways related to oxidative stress. Furthermore, a weighted gene co-expression network analysis (WGCNA) showed that the darkgreen module had the highest correlation with photosynthesis and oxidative stress traits. Large numbers of transcription factors, primarily from the MYB, GRAS, WRKY, and C2H2 families, were predicted from the genes within the darkgreen module. An analysis of physiological indicators and DEGs, it was found that under saline-alkali stress, genes related to chlorophyll synthesis enzymes were downregulated, while those related to degradation were upregulated, resulting in inhibited chlorophyll biosynthesis and decreased chlorophyll content. Additionally, NaCl and NaHCO3 stress downregulated the expression of genes related to the Calvin cycle, photosynthetic antenna proteins, and the activity of photosynthetic reaction centers to varying degrees, hindering the photosynthetic electron transfer process, suppressing photosynthesis, with NaHCO3 stress causing more pronounced adverse effects. In terms of oxidative stress, the level of reactive oxygen species (ROS) did not change significantly under the NaCl treatment, but the contents of hydrogen peroxide and the rate of production of superoxide anions increased significantly under NaHCO3 stress. In addition, treatment with NaCl upregulated the levels of expression of the key genes for superoxide dismutase (SOD), catalase (CAT), peroxidase (POD), the ascorbate-glutathione cycle, and the thioredoxin-peroxiredoxin pathway, and increased the activity of these enzymes, thus, reducing oxidative damage. Similarly, NaHCO3 stress increased the activities of SOD, CAT, and POD and the content of ascorbic acid and initiated the glutathione-S-transferase pathway to remove excess ROS but suppressed the regeneration of glutathione and the activity of peroxiredoxin. Overall, both neutral and alkaline salts inhibited the photosynthetic process of safflower, although alkaline salt caused a higher level of stress than neutral salt. Safflower alleviated the oxidative damage induced by stress by regulating its antioxidant system.

Connections between soil microbes, land use and European climate: Insights for management practices

Soil microbial biomass and activity strongly depend on land use, vegetation cover, climate, and soil physicochemical properties. In most cases, this dependence was assessed by one-to-one correlations while by employing network analysis, information about network robustness and the balance between stochasticity and determinism controlling connectivity, was revealed. In this study, we further elaborated on the hypothesis of Smith et al. (2021) that cropland soils depended more on climate variables and therefore are more vulnerable to climate change. We used the same dataset with that of Smith et al. (2021) that contains seasonal microbial, climate and soil variables collected from 881 soil points representing the main land uses in Europe: forests, grassland, cropland. We examined complete (both direct and indirect relationships) and incomplete networks (only direct relationships) and recorded higher robustness in the former. Partial Least Square results showed that on average more than 45% of microbial attributes' variability was predicted by climate and habitat drivers denoting medium to strong effect of habitat filtering. Network architecture slightly affected by season or land use type; it followed the core/periphery structure with positive and negative interactions and no hub nodes. Microbial attributes (biomass, activity and their ratio) mostly belong to core block together with Soil Organic Carbon (SOC), while climate and soil variables to periphery block with the exception of cropland networks, denoting the higher dependence between microbial and climate variables in these latter. All complete networks appeared robust except for cropland and forest in summer, a finding that disagrees with our initial hypothesis about cropland. Networks' connectivity was controlled stronger by stochasticity in forest than in croplands. The lack of human interventions in forest soils increase habitat homogeneity enhancing the influence of stochastic agents such as microbial unlimited dispersal and/or stochastic extinction. The increased stochasticity implies the necessity for proactive management actions.

Weighted gene co-expression network analysis reveals hub genes regulating response to salt stress in peanut

Peanut (Arachis hypogaea L.) is an important oilseed crop worldwide. However, soil salinization becomes one of the main limiting factors of peanut production. Therefore, developing salt-tolerant varieties and understanding the molecular mechanisms of salt tolerance is important to protect peanut yield in saline areas. In this study, we selected four peanut varieties with contrasting response to salt challenges with T1 and T2 being tolerance and S1 and S2 being susceptible. High-throughput RNA sequencing resulted in more than 314.63 Gb of clean data from 48 samples. We identified 12,057 new genes, 7,971of which have functional annotations. KEGG pathway enrichment analysis of uniquely expressed genes in salt-tolerant peanut revealed that upregulated genes in the root are involved in the MAPK signaling pathway, fatty acid degradation, glycolysis/gluconeogenesis, and upregulated genes in the shoot were involved in plant hormone signal transduction and the MAPK signaling pathway. Na+ content, K+ content, K+/ Na+, and dry mass were measured in root and shoot tissues, and two gene co-expression networks were constructed based on weighted gene co-expression network analysis (WGCNA) in root and shoot. In this study, four key modules that are highly related to peanut salt tolerance in root and shoot were identified, plant hormone signal transduction, phenylpropanoid biosynthesis, starch and sucrose metabolism, flavonoid biosynthesis, carbon metabolism were identified as the key biological processes and metabolic pathways for improving peanut salt tolerance. The hub genes include genes encoding ion transport (such as HAK8, CNGCs, NHX, NCL1) protein, aquaporin protein, CIPK11 (CBL-interacting serine/threonine-protein kinase 11), LEA5 (late embryogenesis abundant protein), POD3 (peroxidase 3), transcription factor, and MAPKKK3. There were some new salt-tolerant genes identified in peanut, including cytochrome P450, vinorine synthase, sugar transport protein 13, NPF 4.5, IAA14, zinc finger CCCH domain-containing protein 62, beta-amylase, fatty acyl-CoA reductase 3, MLO-like protein 6, G-type lectin S-receptor-like serine/threonine-protein kinase, and kinesin-like protein KIN-7B. The identification of key modules, biological pathways, and hub genes in this study enhances our understanding of the molecular mechanisms underlying salt tolerance in peanuts. This knowledge lays a theoretical foundation for improving and innovating salt-tolerant peanut germplasm.