Search Results (89)

Aiming for convenience and the low cost of goods transfer between towns, this paper proposes a trade hub location and allocation method based on a novel artificial eagle-inspired optimization algorithm. Firstly, the trade hub location and allocation model is established, taking the total cost consisting of construction and transportation costs as the objective function. Then, to solve the nonlinear model, a novel artificial eagle optimization algorithm (AEOA) is proposed by simulating the collective migration behaviors of artificial eagles when facing a severe living environment. Three main strategies are designed to help the algorithm effectively explore the decision space: the situational awareness and analysis stage, the free exploration stage, and the flight formation integration stage. In the first stage, artificial eagles are endowed with intelligent thinking, thus generating new positions closer to the optimum by perceiving the current situation and updating their positions. In the free exploration stage, artificial eagles update their positions by drawing on the current optimal position, ensuring more suitable habitats can be found. Meanwhile, inspired by the consciousness of teamwork, a formation flying method based on distance information is introduced in the last stage to improve stability and success rate. Test results from the CEC2022 suite indicate that the AEOA can obtain better solutions for 11 functions out of all 12 functions compared with 8 other popular algorithms. Faster convergence speed and stronger stability of the AEOA are also proved by quantitative analysis. Finally, the trade hub location and allocation method is proposed by combining the optimization model and the AEOA. By solving two typical simulated cases, this method can select suitable hubs with lower construction costs and achieve reasonable allocation between hubs and the rest of the towns to reduce transportation costs. Thus, it is used to solve the trade hub location and allocation problem of Henan province in China to help the government make sound decisions. Full article

Background: Huang Qin Decoction (HQD) is a well-established Traditional Chinese Medicine (TCM) formulation recognized for its application in the treatment of colorectal cancer (CRC). However, the precise therapeutic mechanisms remain inadequately defined. Methods: This study integrates metabolomics from a mouse model and network pharmacology to screen potential targets and bio-active ingredients of HQD. The pharmacological activity of HQD for CRC was evidenced via single-cell RNA sequencing (scRNA-seq), molecular docking, and molecular dynamics simulations. Atomic force microscopy (AFM) assays and cellular experimental validation were used to confirm the relative mechanisms. Results: The metabolite profile undergoes significant alterations, with metabolic reprogramming evident during the malignant progression of CRC liver metastasis. Network pharmacology analysis identified that HQD regulates several metabolic pathways, including arginine biosynthesis, alanine, aspartate, and glutamate metabolism, nitrogen metabolism, phenylalanine metabolism, and linoleic acid metabolism, by targeting key proteins such as aspartate aminotransferase (GOT1), cytochrome P450 1A2 (CYP1A2), and carbonic anhydrase 2 (CA2). ScRNA-seq analysis indicated that HQD may enhance the functionality of cytotoxic T cells, thereby reversing the immunosuppressive microenvironment. Virtual verification revealed a strong binding affinity between the identified hub targets and active constituents of HQD, a finding subsequently corroborated by AFM assays. Cellular experiments confirmed that naringenin treatment inhibits the proliferation, migration, and invasion of CRC cells by downregulating GOT1 expression and disrupting glutamine metabolism. Conclusions: Computational prediction and in vitro validation reveal the active ingredients, potential targets, and molecular mechanisms of HQD against CRC liver metastasis, thereby providing a scientific foundation for the application of TCM in CRC treatment. Full article

Background/Objectives: Oral squamous cell carcinoma (OSCC) is the most prevalent malignancy of the oral cavity and is frequently diagnosed at an advanced stage, resulting in poor prognosis and limited treatment options. Identifying reliable biomarkers that can predict tumor progression and serve as therapeutic targets remains an urgent clinical need. Methods: To identify key molecular drivers in OSCC, we performed an integrative bioinformatics analysis of five OSCC-related microarray datasets from the Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) were identified and subjected to functional enrichment, protein–protein interaction (PPI) network construction, and hub gene ranking using Cytoscape. Candidate genes were further validated using TCGA, UALCAN, and the Human Protein Atlas. In vitro functional assays were performed to evaluate the effect of TK1 knockdown on cell migration. Results: A total of 138 common DEGs were identified across datasets. GO enrichment revealed that these genes were associated with cell proliferation, extracellular matrix organization, and metastasis-related processes. Thymidine kinase 1 (TK1) was identified as a key hub gene and found to be consistently overexpressed in OSCC tissues. Kaplan–Meier analysis showed that high TK1 expression correlated with poor overall survival in head and neck cancer. TK1 knockdown in OSCC cell lines significantly impaired cell migration and wound-healing ability. Conclusions: Our findings suggest that TK1 plays an active role in promoting OSCC progression and may serve as a prognostic biomarker and potential therapeutic target for metastatic OSCC. Full article

Background: The rise in antimicrobial-resistant (AMR) strains of Neisseria gonorrhoeae is internationally recognised as a critical public health concern, with limited treatment options available. The urgency of this issue prompted the European Centre for Disease Prevention and Control to establish ‘EURO-GASP’ to monitor trends in resistance and address developments. Comprehensive data on AMR strains in people living with HIV (PLHIV) is limited, especially in Cyprus. Objectives: To analyse trends in rates of resistant N. gonorrhoeae infections and identify any correlations between patient factors that may contribute to such in PLHIV in The Republic of Cyprus. Methods: We conducted a retrospective chart review study on N. gonorrhoea resistance among PLHIV from the Gregorios HIV reference clinic in Larnaca, Cyprus, between 2015 and 2023. Antimicrobial susceptibility was assessed via disc diffusion or gradient strip method on GC II agar against a non-homogenous panel of antibiotic preparations, based on standard laboratory practice variation. Demographic and clinical data, including antibiograms, treatments and test of cure, were recorded. Statistical analysis was performed using Stata v16, with significance set at p < 0.05. The study received approval from the Cyprus National Bioethics Committee. Results: A total of 45 isolates from 39 patients were analysed, with 62% of these demonstrating resistance to at least one antibiotic. Resistance rates were not shown to change over time. We identified a statistically significant linear association between a person having a history of an STI and the number of antibiotics which the isolate is resistant to (β = 1.2; p: 0.004). Notably, a single isolate demonstrated resistance to ceftriaxone, the first-line treatment currently recommended in both Europe and the United States. This finding is particularly alarming given the critical role of ceftriaxone in the management of gonorrhoea. Conclusions: Whilst there has been no increase in resistance rates over time, the detection of ceftriaxone-resistant N. gonorrhoeae is a significant public health concern. Given that having a history of an STI makes a person more likely to develop a resistant infection, PLHIV or those who engage in risky sexual behaviours are particularly vulnerable. There is a pressing need to enhance surveillance and implement routine susceptibility testing in Cyprus, given the country’s role as a major international hub for travel and migration. Molecular analysis can further improve our understanding. Additionally, the global public health community must urgently prioritise the development of novel therapeutic agents for the treatment of gonorrhoea. Full article

Rabbit meat constitutes a high-protein, low-fat nutritional resource demonstrating rising consumption, particularly within the Asia-Pacific region. Consequently, muscle growth and developmental pattern in meat rabbits represent critical economic considerations. To elucidate the primary signaling pathways governing muscle development, we first performed comparative body weight analyses between two rabbit breeds exhibiting divergent growth rates: the fast-growing Checkered Giant (Ju) and slow-growing Sichuan Ma rabbit. Subsequent, post-natal qualities of thigh and longissimus dorsi muscle fiber were quantified across three developmental phases (28, 56, and 84 days post-natal). The results showed the body weight of Ju rabbit was significantly higher than that of Ma rabbit beyond 3 weeks post-natal (p < 0.05), while Ma rabbit exhibited larger muscle fiber areas in both tissues at 56 days (p < 0.05). The transcriptome analysis showed that 284 and 305 differentially expressed genes (DEGs) (|log2FC| > 1, padj < 0.05) were identified in thigh muscle and longissimus dorsi muscle, respectively. GO (Gene Ontology) analysis of DEGs indicated DEGs in the thigh muscle were enriched in these terms related to biological processes of muscle cell migration and smooth muscle cell migration, cellular components of sarcomere, myofibril, and actin filament bundle, while DEGs in longissimus dorsi muscle were enriched in these terms associated with biological processes of muscle cell migration, smooth muscle cell migration and muscle structure development, cellular component of actin cytoskeleton, contractile fiber, myofibril, myosin complex and molecular function of actin filament binding. Integrated GO, KEGG and PPI analyses of co-expressive DEGs implicated the HIF-1 signaling pathway and Glycolysis/Gluconeogenesis in muscular development. Different expression of energy metabolism hub-genes might be the primary reason for interbreed muscle developmental disparities. Full article

Millions of young Africans earn a variety of qualifications annually, yet the majority return without prospects for employment. This challenge has become a catalyst for inequality, poverty, crime involvement, and international migration. Empirical discourse points to education—such as a pedagogy that is chiefly theory-oriented rather than aligned with a knowledge economy, mismatched skills, and irrelevant qualifications—as constraints that contribute to the unemployment of the continent’s vibrant young graduates. Amidst this surging issue, the call for transformation in higher learning has never been clearer. Focusing on rural landscapes, this case study analysed the contextual employability potential of graduates pursuing an entrepreneurial university trajectory in Africa, illustrating why the paradigm should be implemented. The findings, based on qualitative data collected using a semi-structured questionnaire through one-on-one and remote approaches from stakeholders in universities across five African countries, highlight three dimensions central to this pathway. These include (1) curriculum alignment to advance cutting-edge qualifications and skill development that resonate with industrial demand and local economic priorities; (2) stakeholder embeddings in which universities strive to partner with local organisations and established alumni to provide mentorship, job leads, and referrals; and (3) innovation hubs that offer a variety of entrepreneurial support, real-world experience, and Indigenous entrepreneurship practices, leading to unique new ventures and employment opportunities. Implementing this strategy will enable rural-based universities in Africa to innovate in promoting graduate employability, socioeconomic advancements, and sustainable development, ultimately shaping a brighter future for the continent. Further studies could test the assumptions for broader application using statistical analysis. Full article

Hepatocellular carcinoma (HCC) is a deadly cancer with limited treatment options for patients at advanced stages. It is urgent to develop reliable prognostic risk models and identify more biomarkers to improve the clinical outcomes of patients with HCC. Disulfidptosis is a newly discovered form of regulated cell death (RCD), and research on the comprehensive roles of disulfidptosis-related genes (DRGs) in HCC prognosis and development remains limited. In this paper, we systematically analyzed the expression levels and prognostic profiles of 26 DRGs in HCC samples from The Cancer Genome Atlas (TCGA) cohort and developed a prognostic risk model using seven hub DRGs. The independent prognostic value of the risk model was further validated in the external cohort. The overall survival of patients with HCC in the low-risk group was significantly longer than that of those in the high-risk group. Subsequently, the protein level of CD2-associated protein (CD2AP) was found to be highly expressed in HCC clinical tissues and associated with the severity of HCC. In vitro experiments demonstrated that the down-regulation of CD2AP attenuated the proliferation, migration, invasion, and epithelial–mesenchymal transition (EMT) abilities of HCC cells. Taken together, our study revealed that the DRG CD2AP may serve as a potential biomarker for HCC and offer support for prognosis prediction of patients with HCC. Full article

Background/Objectives: Lipid metabolism plays a crucial role in uterine corpus endometrial carcinoma (UCEC); however, its specific mechanisms remain to be fully elucidated. This study aimed to construct a lipid-metabolism-related prognostic model and explore its association with the tumor immune microenvironment. Methods: A total of 552 UCEC and 35 normal tissue samples from The Cancer Genome Atlas (TCGA) database were analyzed to identify differentially expressed lipid-metabolism-related genes (DE-LMRGs). A prognostic risk model was established using univariate Cox analysis, least absolute shrinkage and selection operator (LASSO) regression, and multivariate Cox regression, and its clinical utility was assessed through nomogram construction. Functional enrichment analysis was performed to explore the biological pathways involved. Tumor immune infiltration patterns were evaluated using single-sample Gene Set Enrichment Analysis (ssGSEA), Estimation of Stromal and Immune Cells in Malignant Tumors using Expression Data (ESTIMATE), and Tumor Immune Dysfunction and Exclusion (TIDE) algorithms. Results: Multivariate analysis indicated that the prognostic model had robust predictive value, with AUCs of 0.701, 0.746, and 0.790 for 1-, 3-, and 5-year overall survival predictions. High-risk patients exhibited a suppressed immune microenvironment characterized by reduced immune cell infiltration, lower tumor mutation burden (TMB), and elevated TIDE scores, suggesting potential resistance to immunotherapy. Furthermore, LIPG was identified as a key hub gene through the intersection of nine machine learning algorithms, demonstrating strong associations with both cancer progression and immune infiltration. Functional validation using Cell Counting Kit-8 (CCK-8), wound healing, and transwell migration assays following small interfering RNA (siRNA) transfection demonstrated that LIPG promotes UCEC cell proliferation and migration in vitro. Conclusions: These findings highlight the critical role of lipid metabolism in UCEC progression and immune modulation, with LIPG emerging as a potential prognostic biomarker. The identified lipid-metabolism-related gene signature may provide new insights into tumor microenvironment interactions. Full article

Background/Objectives: Periostracum Cicadae (PC) is commonly used to treat chronic atrophic gastritis (CAG), but its underlying mechanisms are unclear. We investigated the therapeutic effects, active ingredients and molecular mechanisms of PC on CAG. Methods: We analyzed the components in the serum extract of PC by UHPLC-Q-Orbitrap-MS/MS. Then, we used rat and cell models to assess the impact of PC on CAG and employed network pharmacology and bioinformatics to predict key targets and active ingredients. Finally, we confirmed hub targets through experiments and molecular docking. Results: A total of 22 components were identified in the PC extract-containing serum using UHPLC-Q-Orbitrap MS/MS. Network pharmacology combined with molecular docking revealed that the protective effect was primarily mediated by three compounds: (Z)-akuammidine, chicoric acid, and columbianadin. And we revealed that c-Fos/c-Jun signaling pathways were crucial in therapy. PC extract-containing serum inhibited the vitality, migration, invasion, and multiplication of MC cells (model cells for CAG), induced apoptosis, and caused G0/G1 phase cell cycle arrest. The expression level of tumor necrosis factor-alpha (TNF-α), interleukin-6 (IL-6), interleukin-1 beta (IL-1β) and gastrin 17 (G17) in the serum of CAG rats increased, while the expression level of pepsinogen I (PG I) and pepsinogen II (PG II) decreased. After 12 weeks of PC administration, these conditions were significantly improved. PC not only reduced the levels of antigen KI-67 (Ki67) and tumor protein p53 (P53) but also enhanced SRY-box Transcription Factor (SOX2). Simultaneously, PC down-regulated the expression of N-cadherin and Vimentin while up-regulating that of E-cadherin. Conclusions: PC inhibited epithelial–mesenchymal transition (EMT) via the c-Fos/c-Jun signaling pathway, thereby providing therapeutic benefits for CAG. Our study elucidates the mechanisms and material basis of PC in treating CAG, providing experimental evidence to support its clinical application. Full article

Migratory fish often encounter hypoxic zones during migration, which can lead to varying degrees of hypoxic stress. This issue has become increasingly severe due to human activities and climate change, which have resulted in the expansion of hypoxic zones in aquatic environments. However, there is limited research on how these species respond to hypoxic stress and subsequent recovery. In this study, we used Eleutheronema tetradactylum, a well-recognized migratory and economically valuable fish species, as a model organism. Histological analysis revealed extensive neuronal damage during hypoxia exposure, with limited recovery observed even after 12 h of reoxygenation. Differential gene expression analysis highlighted progressive alterations in genes associated with stress response, neuroactive ligand interactions, and cellular repair mechanisms. Time-series analysis of differentially expressed genes (DEGs) identified critical expression profiles throughout the hypoxia-recovery process and revealed hub genes for each stage. Furthermore, dynamic changes in miRNA expression and proteomic profiles indicated active regulation of several key biological pathways, including MAPK, HIF-1, and ECM-receptor interactions. Through miRNA-mRNA-protein correlation analysis, we propose a model that predicts key regulatory pathways and critical miRNA-mRNA-protein interactions across the various stages of hypoxia-recovery in the brain of E. tetradactylum. This study presents the first integrated analysis of miRNA, mRNA, and protein throughout the entire hypoxia-recovery process in fish brains. The molecular interactions and regulatory pathways identified in this model could serve as valuable biomarkers for future research on hypoxia-recovery mechanisms in fish. Full article

Exposure to air pollution, especially fine particulate matter (PM2.5), is closely linked to various adverse health effects, particularly in the respiratory system. The present study was designed to investigate the lncRNA–mRNA interactions in PM2.5-induced lung cell injury using weighted gene co-expression network analysis (WGCNA). We downloaded the gene expression data of GSE138870 from the Gene Expression Omnibus (GEO) database and screened for differentially expressed lncRNAs and mRNAs. We constructed co-expression modules with WGCNA. Furthermore, functional enrichment analysis was also performed. We also constructed lncRNA–mRNA co-expression networks and lncRNA–mRNA-pathway networks to identify key regulatory relationships. The results revealed several modules significantly correlated with PM2.5-induced lung injury, such as the turquoise and blue modules. Genes within these modules were enriched in pathways related to signal transduction, metabolism, and cancer. Hub lncRNAs in the turquoise module, including LOC100129034 and CROCCP2, were found to be co-expressed with mRNAs involved in apoptosis and proliferation regulation. In the blue module, lnc-CLVS2-2 and GARS1-DT were connected to genes related to cell migration, invasion, and lung injury. These findings contribute novel perspectives to the molecular mechanisms involved in PM2.5-induced lung injury and suggest that WGCNA could be a valuable tool for predicting and understanding this disease process. Full article

The Chinese sturgeon (Acipenser sinensis) is an ancient, complex autooctoploid fish species that is currently facing conservation challenges throughout its distribution. To comprehensively characterize the expression profiles of genes and their associated biological functions across different tissues, we performed a transcriptome-scale gene expression analysis, focusing on housekeeping genes (HKGs), tissue-specific genes (TSGs), and co-expressed gene modules in various tissues. We collected eleven tissues to establish a transcriptomic repository, including data from Pacific Biosciences isoform sequencing (PacBio Iso-seq) and RNA sequencing (RNA-seq), and then obtained 25,434 full-length transcripts, with lengths from 307 to 9515 bp and an N50 of 3195 bp. Additionally, 20,887 transcripts were effectively identified and classified as known homologous genes. We also identified 787 HKGs, and the number of TSGs varied from 25 in the liver to 2073 in the brain. TSG functions were mainly enriched in certain signaling pathways involved in specific physiological processes, such as voltage-gated potassium channel activity, nervous system development, glial cell differentiation in the brain, and leukocyte transendothelial migration in the spleen and pronephros. Meanwhile, HKGs were highly enriched in some pathways involved in ribosome biogenesis, proteasome core complex, spliceosome activation, elongation factor activity, and translation initiation factor activity, which have been strongly implicated in fundamental biological tissue functions. We also predicted five modules, with eight hub genes in the brown module, most of which (such as rps3a, rps7, rps23, rpl11, rpl17, rpl27, and rpl28) were linked to ribosome biogenesis. Our results offer insights into ribosomal proteins that are indispensable in ribosome biogenesis and protein synthesis, which are crucial in various cell developmental processes and neural development of Chinese sturgeon. Overall, these findings will not only advance the understanding of fundamental biological functions in Chinese sturgeon but also supply a valuable genetic resource for characterizing this extremely important species. Full article

Background: While miRNAs are increasingly recognized for their role in tumorigenesis, their involvement in head and neck cancer (HNC) remains insufficiently explored. Additionally, the carcinogenic mechanisms of areca nut, a major habitual carcinogen in Southeast Asia, are not well understood. Methods and results: This study adopts a systematic approach to identify miRNA profiles associated with areca nut-induced HNC. Using miRNA microarray analysis, we identified 292 miRNAs dysregulated in areca nut-treated HNC cells, with 136 upregulated and 156 downregulated. Bioinformatic analysis of the TCGA-HNSC dataset uncovered a set of 692 miRNAs relevant to HNC development, comprising 449 overexpressed and 243 underexpressed in tumor tissues. Integrating these datasets, we defined a signature of 84 miRNAs, including 39 oncogenic miRNAs (OncomiRs) and 45 tumor-suppressive miRNAs (TsmiRs), highlighting their pivotal role in areca nut-induced carcinogenesis. MultiMiR analysis identified 740 genes cross-regulated by eight hub TsmiRs, significantly impacting key cancer-related pathways (p53, PI3K-AKT, MAPK, and Ras) and critical oncogenic processes. Moreover, we validated miR-499a-5p as a vital regulator, demonstrating its ability to mitigate areca nut-induced cancer progression by reducing cell migration, invasion, and chemoresistance. Conclusions: Thus, this miRNA signature addresses a crucial gap in understanding the molecular underpinnings of areca nut-induced carcinogenesis and offers a promising platform for clinical applications in risk assessment, diagnosis, and prognosis of areca nut-associated malignancies. Full article

Ras homolog family member A (RhoA) acts as a signaling hub in many cellular processes, including cytoskeletal dynamics, division, migration, and adhesion. RhoA activity is tightly spatiotemporally controlled, but whether downstream effectors share these activation dynamics is unknown. We developed a novel single-color FRET biosensor to measure Rho-associated kinase (ROCK) activity with high spatiotemporal resolution in live cells. We report the validation of the Rho-Kinase Activity Reporter (RhoKAR) biosensor. RhoKAR activation was specific to ROCK activity and was insensitive to PKA activity. We then assessed the mechanisms of ROCK activation in mouse fibroblasts. Increasing intracellular calcium with ionomycin increased RhoKAR activity and depleting intracellular calcium with EGTA decreased RhoKAR activity. We also investigated the signaling intermediates in this process. Blocking calmodulin or CaMKII prevented calcium-dependent activation of ROCK. These results indicate that ROCK activity is increased by calcium in fibroblasts and that this activation occurs downstream of CaM/CaMKII. Full article

Pancreatic ductal adenocarcinoma (PDAC) has earned a notorious reputation as one of the most formidable and deadliest malignant tumors. Within the tumor microenvironment, cancer cells have acquired the capability to maintain incessant expansion and increased proliferation in response to hypoxia via metabolic reconfiguration, leading to elevated levels of lactate within the tumor surroundings. However, there have been limited studies specifically investigating the association between hypoxia and lactic acid metabolism-related lactylation in PDAC. In this study, multiple machine learning approaches, including LASSO regression analysis, XGBoost, and Random Forest, were employed to identify hub genes and construct a prognostic risk signature. The implementation of the CERES score and single-cell analysis was used to discern a prospective therapeutic target for the management of PDAC. CCK8 assay, colony formation assays, transwell, and wound-healing assays were used to explore both the proliferation and migration of PDAC cells affected by CENPA. In conclusion, we discovered two distinct subtypes characterized by their unique hypoxia and lactylation profiles and developed a risk score to evaluate prognosis, as well as response to immunotherapy and chemotherapy, in PDAC patients. Furthermore, we indicated that CENPA may serve as a promising therapeutic target for PDAC. Full article