The role of transforming growth factor beta-1 protein in Escherichia coli secondary infection induced by H9N2 avian influenza virus in chickens.

The H9N2 subtype of avian influenza virus (AIV) is common in poultry production. It causes mild clinical signs but rarely leads to poultry mortalities. However, higher mortality can occur in chickens with co-infections, especially avian pathogenic Escherichia coli (APEC), which results in huge economic losses for the poultry industry. Unfortunately, the mechanism of co-infection remains unknown. Our previous studies screened several proteins associated with bacterial adhesion, including transforming growth factor beta-1 (TGF-ß1), integrins, cortactin, E-cadherin, vinculin, and fibromodulin. Herein, we investigated the contribution of TGF-ß1 to APEC adhesion after H9N2 infection. We first infected H9N2 and APEC in chicken, chicken embryo and DF-1 cells, and demonstrated that H9N2 infection promotes APEC adhesion to hosts in vitro and in vivo by plate count method. Through real-time fluorescence quantification and enzyme-linked immunosorbent assay, it was demonstrated that H9N2 infection not only increases TGF-ß1 expression but also its activity in a time-dependent manner. Then, through exogenous addition of TGF-ß1 and overexpression, we further demonstrated that TGF-ß1 can increase the adhesion of endothelial cells to DF-1 cells. Furthermore, the capacity of APEC adhesion to DF-1 cells was significantly decreased either by adding a TGF-ß1 receptor inhibitor or using small interfering RNAs to interfere with the expression of TGF-ß1. To sum up, H9N2 infection can promote the upregulation of TGF-ß1 and then increase the adhesion ability of APEC. Targeting TGF-ß1 and its associated pathway will provide valuable insights into the clinical treatment of E. coli secondary infection induced by H9N2 infection.

Comprehensive analysis of candidate signatures of long non-coding RNA LINC01116 and related protein-coding genes in patients with hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) is a long-term malignancy that causes high morbidities and mortalities worldwide. Notably, long non-coding RNAs (LncRNAs) have been identified as candidate targets for malignancy treatments. METHODS: LncRNA LINC01116 and its Pearson-correlated genes (PCGs) were identified and analyzed in HCC patients. The diagnostic and prognostic value of the lncRNA was evaluated using data from The Cancer Genome Atlas (TCGA). Further, we explored the target drugs of LINC01116 for clinical application. Relationships between immune infiltration and PCGs, methylation and PCGs were explored. The diagnostic potentials were then validated by Oncomine cohorts. RESULTS: LINC01116 and the PCG OLFML2B are differentially and highly expressed in tumor tissues (both P ≤ 0.050). We found that LINC01116, TMSB15A, PLAU, OLFML2B, and MRC2 have diagnostic potentials (all AUC ≥ 0.700, all P ≤ 0.050) while LINC01116 and TMSB15A have prognostic significance (both adjusted P ≤ 0.050). LINC01116 was enriched in the vascular endothelial growth factor (VEGF) receptor signaling pathway, mesenchyme morphogenesis, etc. After that, candidate target drugs with potential clinical significance were identified: Thiamine, Cromolyn, Rilmenidine, Chlorhexidine, Sulindac_sulfone, Chloropyrazine, and Meprylcaine. Analysis of immune infiltration revealed that MRC2, OLFML2B, PLAU, and TMSB15A are negatively associated with the purity but positively associated with the specific cell types (all P < 0.050). Analysis of promoter methylation demonstrated that MRC2, OLFML2B, and PLAU have differential and high methylation levels in primary tumors (all P < 0.050). Validation results of the differential expressions and diagnostic potential of OLFML2B (Oncomine) were consistent with those obtained in the TCGA cohort (P < 0.050, AUC > 0.700). CONCLUSIONS: Differentially expressed LINC01116 could be a candidate diagnostic and an independent prognostic signature in HCC. Besides, its target drugs may work for HCC therapy via the VEGF receptor signaling pathway. Differentially expressed OLFML2B could be a diagnostic signature involved in HCC via immune infiltrates.

Association between systemic inflammatory response index and left ventricular remodeling and systolic dysfunction in atrial fibrillation patients.

BACKGROUND: Cardiac remodeling and dysfunction can be caused by atrial fibrillation (AF). The aim of this research is to investigate the relationship between the systemic inflammatory response index (SIRI) and left ventricular (LV) remodeling and systolic function in individuals with AF. METHODS: 416 patients with AF who were admitted to the Second Department of Cardiology in the East Ward of the Qingdao Municipal Hospital between January 2020 and May 2022 were included in the present retrospective research. The relationship between SIRI and various cardiac parameters was analyzed. The patients' left atrial (LA) enlargement and left ventricular (LV) hypertrophy and systolic dysfunction were evaluated. SIRI was calculated by the formula: neutrophil × monocyte/lymphocyte. RESULTS: SIRI significantly correlated with LV end-diastolic diameter (LVDd), LV posterior wall thickness at end-diastole (LVPWTd), interventricular septal thickness at end-diastole (IVSTd), LV mass index (LVMI), LV ejection fraction (LVEF), LA diameter (LAD), C-reactive protein (CRP), and N-terminal pro-B-type natriuretic peptide (NT-proBNP) in patients with AF. In multivariate linear regression analyses, SIRI was discovered to be significantly related to LVMI (ln-transformed) (p = 0.025), LVEF (ln-transformed) (p = 0.005), and LAD (ln-transformed) (p = 0.007). In multivariate logistic regression, the highest quartile of SIRI (SIRI > 1.62) was significantly associated with LV hypertrophy (p = 0.026), impaired LV systolic function (p = 0.002), and LA enlargement (p = 0.025). CONCLUSIONS: SIRI was significantly associated with LV remodeling and systolic function impairment in patients with AF. SIRI may serve as a reliable and convenient inflammatory biomarker for detecting impaired cardiac structure and systolic function in patients with AF.

Method for Denoising the Vibration Signal of Rotating Machinery through VMD and MODWPT.

The vibration signals from rotating machinery are constantly mixed with other noises during the acquisition process, which has a negative impact on the accuracy of signal feature extraction. For vibration signals from rotating machinery, the conventional linear filtering-based denoising method is ineffective. To address this issue, this paper suggests an enhanced signal denoising method based on maximum overlap discrete wavelet packet transform (MODWPT) and variational mode decomposition (VMD). VMD decomposes the vibration signal of rotating machinery to produce a set of intrinsic mode functions (IMFs). By computing the composite weighted entropy (CWE), the phantom IMF component is then removed. In the end, the sensitive component is obtained by computing the value of the degree of difference (DID) after the high-frequency noise component has been decomposed through MODWPT. The denoised signal reconstructs the signal's intrinsic characteristics as well as the denoised high-frequency IMF component. This technique was used to analyze the simulated and real-world signals of gear faults and it was compared to wavelet threshold denoising (WTD), empirical mode decomposition reconstruction denoising (EMD-RD), and ensemble empirical mode decomposition wavelet threshold denoising (EEMD-WTD). The outcomes demonstrate that this method can accurately extract the signal feature information while filtering out the noise components in the signal.

Distinct diagnostic and prognostic values of Glypicans gene expression in patients with hepatocellular carcinoma.

BACKGROUD: In our current work, we aimed to investigate the expressions of glypican (GPC) family genes at the mRNA level and assess their prognostic significances in patients with hepatocellular carcinoma (HCC). METHODS: The pathological roles of GPC family genes were examined using bioinformatics analysis. The diagnostic values of GPC genes were explored with the Gene Expression Profiling Interactive Analysis. Moreover, the mRNA expression and prognostic values of GPC genes were assessed via the KM plotter database. RESULTS: Our data showed that the expression of GPC-3 was dramatically increased in the liver tumor tissue. Moreover, the expressions of the other five GPC family members were not significantly different between the tumor and normal liver tissues (P > 0.05). Furthermore, the up-regulation of GPC-1 at the mRNA level was dramatically correlated to the reduced overall survival (OS) for all HCC patients (hazard ratio = 2.03, 95% confidence intervals =1.44-2.87, P = 4.1e-05) compared with its low-expression group. Besides, the prognosis of the Caucasians was related to most GPC family genes, while the prognosis of the Asian race was only related to the expression of GPC-2. Besides, for pathological factors, including stage, grade, AJCC, and vascular invasion, the higher the pathological grade and vascular invasiveness, the lower the expression levels of GPC family genes (P < 0.05). Finally, the expression levels of GPC-1, 2, and 3 in the hepatitis group were related to the poor prognosis of HCC in the risk factor (alcohol consumption and hepatitis) subgroup (P < 0.05). CONCLUSIONS: Our findings indicated that GPC-3 was dysregulated in HCC compared with paracancerous tissues. The expression of GPC-1 could be used as a potent predictive index for the general prognosis of HCC. The pathology, patients, and risk factors might affect the prognostic value of GPC family genes in HCC.

Effect of timing of surgical resection of primary hepatocellular carcinoma on survival outcomes in elderly patients and prediction of clinical models.

BACKGROUND: The effect of time delay from diagnosis to surgery on the prognosis of elderly patients with liver cancer is not well known. We investigated the effect of surgical timing on the prognosis of elderly hepatocellular carcinoma patients undergoing surgical resection and constructed a Nomogram model to predict the overall survival of patients. METHODS: A retrospective analysis was performed on elderly patients with primary liver cancer after hepatectomy from 2012 to 2018. The effect of surgical timing on the prognosis of elderly patients with liver cancer was analyzed using the cut-off times of 18 days, 30 days, and 60 days. Cox was used to analyze the independent influencing factors of overall survival in patients, and a prognostic model was constructed. RESULTS: A total of 232 elderly hepatocellular carcinoma patients who underwent hepatectomy were enrolled in this study. The cut-off times of 18, 30, and 60 days were used. The duration of surgery had no significant effect on overall survival. Body Mass Index, Child-Pugh classification, Tumor size Max, and Length of stay were independent influencing factors for overall survival in the elderly Liver cancer patients after surgery. These factors combined with Liver cirrhosis and Venous tumor emboli were incorporated into a Nomogram. The nomogram was validated using the clinical data of the study patients, and exhibited better prediction for 1-year, 3-year, and 5-year overall survival. CONCLUSIONS: We demonstrated that the operative time has no significant effect on delayed operation in the elderly patients with hepatocellular carcinoma, and a moderate delay may benefit some patients. The constructed Nomogram model is a good predictor of overall survival in elderly patients with hepatectomy.

Oncogene PLCE1 may be a diagnostic biomarker and prognostic biomarker by influencing cell cycle, proliferation, migration, and invasion ability in hepatocellular carcinoma cell lines.

Hepatocellular carcinoma (HCC) is a lethal malignancy worldwide. HCC has traits of late diagnosis and high recurrence. This study explored potential diagnosis and prognosis significance of phospholipase C epsilon 1 (PLCE1) in HCC. The messenger RNA (mRNA) levels and diagnostic value of PLCE1 were determined by real-time polymerase chain reaction and online databases GEPIA, oncomine, and GSE14520 data set. Survival analysis used the Kaplan-Meier Plotter website. Cell cycle, proliferation, migration, and invasion assays were performed with downregulated PLCE1 expression in HCC-M and HepG2 cell lines. PLCE1 was differentially expressed and highly expressed in tumors and had low expression in nontumor tissues (all p < .05). The diagnostic value of PLCE1 was validated with the datasets (all p < .01, all areas under curves > 0.7). PLCE1 mRNA expression was associated with the overall and relapse-free survival (both p < .05). Functional experiments indicated that downregulation of PLCE1 expression led to increased G1 stage in cell cycle and decreased cell proliferation, migration, and invasion compared with a negative control group (all p ≤ .05). The oncogene PLCE1 was differentially expressed in HCC and non-HCC tissues. It is a candidate for diagnosis and serves as prognosis biomarker. PLCE1 influenced survival by affecting the cell cycle, proliferation, migration, and invasion ability.

The diagnosis and prognosis values of WNT mRNA expression in colon adenocarcinoma.

WNT family genes have participated in the progression and development of many cancers, however, the association between colon adenocarcinoma (COAD) and WNTs have been rarely reported. This study investigated the significance of WNT genes expression in COAD from the standpoint of diagnosis and prognosis. The RNA-sequencing dataset of COAD was downloaded from The Cancer Genome Atlas and University of California, Santa Cruz Xena browser. The biology functions of WNT genes were investigated by biological analysis. Biological analysis of WNT family genes indicated that WNT genes were noticeably enriched in the complex process of WNT signaling pathway. The Pearson correlation analysis suggested WNT1 and WNT9B had a strong correlation. And receiver operating characteristic curves suggested that most of the genes could serve as a significant diagnostic makers in COAD (P < .05), especially WNT2 and WNT7B had high diagnostic values that the area under curve were 0.997 (95% confidence interval [0.994-1.000]) and 0.961 (95%CI [0.939-0.983]), respectively. And our multivariate survival analysis suggested the downregulated of WNT10B (P < .05) showed a favor prognosis in COAD overall survival. And the risk score model predicted that the upregulated expression of WNT10B might increase the risk of death. The very study we had conducted suggested that WNT genes had a certain connection with the diagnosis and prognosis of COAD. The messenger RNA expression of WNT2 and WNT7B might become potentially diagnostic biomarkers, and WNT10B might serve as an independent prognosis indicator for COAD.

Prognostic value of Glypican family genes in early-stage pancreatic ductal adenocarcinoma after pancreaticoduodenectomy and possible mechanisms.

BACKGROUND: This study explored the prognostic significance of Glypican (GPC) family genes in patients with pancreatic ductal adenocarcinoma (PDAC) after pancreaticoduodenectomy using data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). METHODS: A total of 112 PDAC patients from TCGA and 48 patients from GEO were included in the analysis. The relationship between overall survival and the expression of GPC family genes as well as basic clinical characteristics was analyzed using the Kaplan-Meier method with the log-rank test. Joint effects survival analysis was performed to further examine the relationship between GPC genes and prognosis. A prognosis nomogram was established based on clinical characteristics and prognosis-related genes. Prognosis-related genes were investigated by genome-wide co-expression analysis and gene set enrichment analysis (GSEA) was carried out to identify potential mechanisms of these genes affecting prognosis. RESULTS: In TCGA database, high expression of GPC2, GPC3, and GPC5 was significantly associated with favorable survival (log-rank P = 0.031, 0.021, and 0.028, respectively; adjusted P value = 0.005, 0.022, and 0.020, respectively), and joint effects analysis of these genes was effective for prognosis prediction. The prognosis nomogram was applied to predict the survival probability using the total scores calculated. Genome-wide co-expression and GSEA analysis suggested that the GPC2 may affect prognosis through sequence-specific DNA binding, protein transport, cell differentiation and oncogenic signatures (KRAS, RAF, STK33, and VEGFA). GPC3 may be related to cell adhesion, angiogenesis, inflammatory response, signaling pathways like Ras, Rap1, PI3K-Akt, chemokine, GPCR, and signatures like cyclin D1, p53, PTEN. GPC5 may be involved in transcription factor complex, TFRC1, oncogenic signatures (HOXA9 and BMI1), gene methylation, phospholipid metabolic process, glycerophospholipid metabolism, cell cycle, and EGFR pathway. CONCLUSION: GPC2, GPC3, and GPC5 expression may serve as prognostic indicators in PDAC, and combination of these genes showed a higher efficiency for prognosis prediction.

Diagnostic and prognostic significance of mRNA expressions of apolipoprotein A and C family genes in hepatitis B virus-related hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) is among the most common and lethal malignancies worldwide. Apolipoproteins (APOs) have been reported increasingly for their relationships with tumors. We aim at exploring the potential relationships of apolipoprotein A (APOA) and apolipoprotein C (APOC) family members with HCC. METHODS: A data set, containing 212 hepatitis B virus-related HCC patients, was used for analysis. The diagnostic and prognostic ability of APOA and APOC family genes was figured out. Risk score models and nomograms were developed for the HCC prognosis prediction. Moreover, molecular mechanism exploration were identified biological processes and metabolic pathways of these genes involved in. Validation analysis was carried out using online website. RESULTS: APOA1, APOC1, APOC3, and APOC4 showed robust diagnosis significance (all P < 0.05). APOA4, APOC3, and APOC4 were associated with the overall survival (OS) while APOA4 and APOC4 were linked to recurrence-free survival (RFS, all P ≤ 0.05). Risk score models and nomograms had the advantage of predicting OS and RFS for HCC. Molecular mechanism exploration indicated that these genes were involved in the steroid metabolic process, the PPAR signaling pathway, and fatty acid metabolism. Besides that, validation analysis revealed that APOC1 and APOC4 had an association with OS; and APOC3 was associated with OS and RFS (all P ≤ 0.05). CONCLUSIONS: APOA1, APOC1, APOC3, and APOC4 are likely to be potential diagnostic biomarkers and APOC3 and APOC4 are likely to be potential prognostic biomarkers for hepatitis B virus-related HCC. They may be involved in the steroid metabolic process, PPAR signaling pathway, and fatty acid metabolism.

Use of Genome-Scale Integrated Analysis to Identify Key Genes and Potential Molecular Mechanisms in Recurrence of Lower-Grade Brain Glioma.

BACKGROUND The aim of this study was to identify gene signals for lower-grade glioma (LGG) and to assess their potential as recurrence biomarkers. MATERIAL AND METHODS An LGG-related mRNA sequencing dataset was downloaded from The Cancer Genome Atlas (TCGA) Informix. Multiple bioinformatics analysis methods were used to identify key genes and potential molecular mechanisms in recurrence of LGG. RESULTS A total of 326 differentially-expressed genes (DEGs), were identified from 511 primary LGG tumor and 18 recurrent samples. Gene ontology (GO) analysis revealed that the DEGs were implicated in cell differentiation, neuron differentiation, negative regulation of neuron differentiation, and cell proliferation in the forebrain. The Kyoto Encyclopedia of Genes and Genomes (KEGG) database suggests that DEGs are associated with proteoglycans in cancer, the Wnt signaling pathway, ECM-receptor interaction, the PI3K-Akt signaling pathway, transcriptional deregulation in cancer, and the Hippo signaling pathway. The hub DEGs in the protein-protein interaction network are apolipoprotein A2 (APOA2), collagen type III alpha 1 chain (COL3A1), collagen type I alpha 1 chain (COL1A1), tyrosinase (TYR), collagen type I alpha 2 chain (COL1A2), neurotensin (NTS), collagen type V alpha 1 chain (COL5A1), poly(A) polymerase beta (PAPOLB), insulin-like growth factor 2 mRNA-binding protein 1 (IGF2BP1), and anomalous homeobox (ANHX). GSEA revealed that the following biological processes may associated with LGG recurrence: cell cycle, DNA replication and repair, regulation of apoptosis, neuronal differentiation, and Wnt signaling pathway. CONCLUSIONS Our study demonstrated that hub DEGs may assist in the molecular understanding of LGG recurrence. These findings still need further molecular studies to identify the assignment of DEGs in LGG.

Identification of Potential Prognostic Long Non-Coding RNA Biomarkers for Predicting Survival in Patients with Hepatocellular Carcinoma.

BACKGROUND/AIMS: The aim of the current study was to identify potential prognostic long non-coding RNA (lncRNA) biomarkers for predicting survival in patients with hepatocellular carcinoma (HCC) using The Cancer Genome Atlas (TCGA) dataset and bioinformatics analysis. METHODS: RNA sequencing and clinical data of HCC patients from TCGA were used for prognostic association assessment by univariate Cox analysis. A prognostic signature was built using stepwise multivariable Cox analysis, and a comprehensive analysis was performed to evaluate its prognostic value. The prognostic signature was further evaluated by functional assessment and bioinformatics analysis. RESULTS: Thirteen differentially expressed lncRNAs (DELs) were identified and used to construct a single prognostic signature. Patients with high risk scores showed a significantly increased risk of death (adjusted P < 0.0001, adjusted hazard ratio = 3.522, 95% confidence interval = 2.307-5.376). In the time-dependent receiver operating characteristic analysis, the prognostic signature performed well for HCC survival prediction with an area under curve of 0.809, 0.782 and 0.79 for 1-, 3- and 5-year survival, respectively. Comprehensive survival analysis of the 13-DEL prognostic signature suggested that it serves as an independent factor in HCC, showing a better performance for prognosis prediction than traditional clinical indicators. Functional assessment and bioinformatics analysis suggested that the prognostic signature was associated with the cell cycle and peroxisome proliferator-activated receptor signaling pathway. CONCLUSIONS: The novel lncRNA expression signature identified in the present study may be a potential biomarker for predicting the prognosis of HCC patients.

Prognostic Value of Dynactin mRNA Expression in Cutaneous Melanoma.

BACKGROUND Dynactin (DCTN) is a multi-subunit protein encoded by DCTN genes for 6 subunits. In different diseases the DCTN genes may have different roles; therefore, we investigated the prognostic potential of DCTN mRNA expression in cutaneous melanoma (CM). MATERIAL AND METHODS Data for DCTN mRNA expression in CM patients were obtained from the OncoLnc database, which contains updated gene expression data for 459 CM patients based on the Cancer Genome Atlas. Kaplan-Meier analysis and a Cox regression model were used to determine overall survival (OS) with calculation of hazard ratios (HRs) and 95% confidence intervals (CIs). RESULTS The multivariate survival analysis showed that individually low expression of DCTN1, DCTN2, and DCTN5 and high expression of DCTN6 were associated with favorable OS (adjusted P=0.008, HR=0.676, 95% CI=0.506-0.903; adjusted P=0.004, HR=0.648, 95% CI=0.485-0.867; adjusted P=0.011, HR=0.686, 95% CI=0.514-0.916; and adjusted P=0.018, HR=0.706, 95% CI=0.530-0.942, respectively). In a joint-effects analysis, combinations of low expression of DCTN1, DCTN2, and DCTN5 and high expression of DCTN6 were found to be more highly correlated with favorable OS (all P<0.05). CONCLUSIONS Our findings suggest that downregulated DCTN1, DCTN2, and DCTN5 and upregulated DCTN6 mRNA expression in CM are associated with favorable prognosis and may represent potential prognostic biomarkers. Moreover, use of the 4 genes in combination can improve the sensitivity for predicting OS in CM patients.

Distinct Diagnostic and Prognostic Values of Kinesin Family Member Genes Expression in Patients with Breast Cancer.

BACKGROUND This study investigated the diagnostic and prognostic values of kinesin superfamily proteins (KIFs) in breast cancer (BC) patients. MATERIAL AND METHODS All data were obtained from the Cancer Genome Atlas. DESeq was run to test for differentially expressed KIF genes. Patients were divided into high- and low-expression groups according to the median expression values of each KIF genes. Survival data were calculated using the Cox proportional hazard model. Comprehensive survival analysis was performed to evaluate the prognostic value of the prognostic signature. Gene set enrichment analysis (GSEA) was conducted to identify associated gene ontology and KEGG pathways. RESULTS Bioinformatics analysis showed that all KIF genes were significantly enriched during DNA replication and the cell cycle, and co-expressed with each other. Thirteen KIF genes were differentially expressed in cancer and adjacent tissues, and high levels of KIF15, KIF20A, KIF23, KIF2C and KIF4A genes were significantly correlated with poor overall survival (OS). GSEA showed that BC patients with high expression of KIF15, KIF20A, KIF23, KIF2C and KIF4A were enriched in the cell cycle process, P53 regulation pathway and mismatch repair. Combinations of low expression of KIF15, KIF20A, KIF23, KIF2C and KIF4A were more highly correlated with favorable OS. Nomograms showed that the KIF4A risk score provided the maximum number of risk points (range 0-100), whereas other genes made a lower contribution. CONCLUSIONS We conclude that 13 KIF genes are differentially expressed in BC tumor tissues, and KIF15, KIF20A, KIF23, KIF2C and KIF4A are associated with prognostic factors in BC.

An Energy-Saving and Efficient Deployment Strategy for Heterogeneous Wireless Sensor Networks Based on Improved Seagull Optimization Algorithm.

The Internet of Things technology provides convenience for data acquisition in environmental monitoring and environmental protection and can also avoid invasive damage caused by traditional data acquisition methods. An adaptive cooperative optimization seagull algorithm for optimal coverage of heterogeneous sensor networks is proposed in order to address the issue of coverage blind zone and coverage redundancy in the initial random deployment of heterogeneous sensor network nodes in the sensing layer of the Internet of Things. Calculate the individual fitness value according to the total number of nodes, coverage radius, and area edge length, select the initial population, and aim at the maximum coverage rate to determine the position of the current optimal solution. After continuous updating, when the number of iterations is maximum, the global output is output. The optimal solution is the node's mobile position. A scaling factor is introduced to dynamically adjust the relative displacement between the current seagull individual and the optimal individual, which improves the exploration and development ability of the algorithm. Finally, the optimal seagull individual position is fine-tuned by random opposite learning, leading the whole seagull to move to the correct position in the given search space, improving the ability to jump out of the local optimum, and further increasing the optimization accuracy. The experimental simulation results demonstrate that, compared with the coverage and network energy consumption of the PSO algorithm, the GWO algorithm, and the basic SOA algorithm, the coverage of the PSO-SOA algorithm proposed in this paper is 6.1%, 4.8%, and 1.2% higher than them, respectively, and the energy consumption of the network is reduced by 86.8%, 68.4%, and 52.6%, respectively. The optimal deployment method based on the adaptive cooperative optimization seagull algorithm can improve the network coverage and reduce the network cost, and effectively avoid the coverage blind zone and coverage redundancy in the network.

Mechanisms and regulations of ferroptosis.

Regulation of cell mortality for disease treatment has been the focus of research. Ferroptosis is an iron-dependent regulated cell death whose mechanism has been extensively studied since its discovery. A large number of studies have shown that regulation of ferroptosis brings new strategies for the treatment of various benign and malignant diseases. Iron excess and lipid peroxidation are its primary metabolic features. Therefore, genes involved in iron metabolism and lipid metabolism can regulate iron overload and lipid peroxidation through direct or indirect pathways, thereby regulating ferroptosis. In addition, glutathione (GSH) is the body's primary non-enzymatic antioxidants and plays a pivotal role in the struggle against lipid peroxidation. GSH functions as an auxiliary substance for glutathione peroxidase 4 (GPX4) to convert toxic lipid peroxides to their corresponding alcohols. Here, we reviewed the researches on the mechanism of ferroptosis in recent years, and comprehensively analyzed the mechanism and regulatory process of ferroptosis from iron metabolism and lipid metabolism, and then described in detail the metabolism of GPX4 and the main non-enzymatic antioxidant GSH in vivo.

RAD51AP1 as an Immune-Related Prognostic Biomarker and Therapeutic Response Predictor in Hepatocellular Carcinoma.

Background: RAD51 associated protein 1 (RAD51AP1) is shown to regulate cell proliferation and cancer progression. However, the immune-infiltrating correlation and the therapeutics guidance of RAD51AP1 in hepatocellular carcinoma (HCC) still need further investigation. Methods: In this study, comprehensive bioinformatic analysis of RAD51AP1 on differential expression, clinicopathologic correlation, prognostic value, and function enrichment were performed in The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO; GSE14520 and GSE76427), and International Cancer Genome Consortium (ICGC) datasets. Besides, the Guangxi cohort containing 50 pairs HCC and adjacent non-cancerous samples from First Affiliated Hospital of Guangxi Medical University was served as validation cohort. Moreover, we explored the predictive value of RAD51AP1 to therapeutics response and its underlying correlation with HCC immunoinfiltration. Results: RAD51AP1 was significantly overexpressed in HCC tissues and had a high diagnostic value of HCC. The shorter survival time and poorer clinical features were showed when RAD51AP1 upregulated, and then a nomogram featuring RAD51AP1 expression and other clinicopathologic factors was established to predict prognosis. In CIBERSORT analysis, higher T cells follicular helper but lower T cells CD4+ memory resting infiltration levels were exhibited when RAD51AP1 upregulated. The ssGSEA analysis demonstrated that high-RAD51AP1 expression subgroup had higher macrophages, Th2 and Treg cells infiltration levels, but lower type II IFN response function. Furthermore, high-RAD51AP1 expression subgroup exhibited the upregulated expression levels of immune-related checkpoint genes, but lower IPS and TIDE scores which suggested a possibly better immunotherapy response. The drug sensitivity analysis showed the high-expression subgroup may be more susceptible to Bexarotene, Doxorubicin, Gemcitabine and Tipifarnib. Conclusion: Taken together, RAD51AP1 is a potential diagnostic and prognostic biomarker. It may be related to the immunosuppressive microenvironment and could be an underlying HCC treatment strategy. However, the conclusions still require further validation studies.

Identification and validation of candidate clinical signatures of apolipoprotein L isoforms in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is a lethal malignancy worldwide with an increasing number of new cases each year. Apolipoprotein (APOL) isoforms have been explored for their associations with HCC.The GSE14520 cohort was used for training data; The Cancer Genome Atlas (TCGA) database was used for validated data. Diagnostic, prognostic significance and mechanisms were explored using these cohorts. Risk score models and nomograms were constructed using prognosis-related isoforms and clinical factors for survival prediction. Oncomine and HCCDB databases were further used for validation of diagnostic, prognostic significance. APOL1, 3, and 6 were differentially expressed in two cohorts (all P ≤ 0.05). APOL1 and APOL6 had diagnostic capacity whereas APOL3 and APOL6 had prognostic capacity in two cohorts (areas under curves [AUCs] > 0.7, P ≤ 0.05). Mechanism studies demonstrated that APOL3 and APOL6 might be involved in humoral chemokine signaling pathways (all P ≤ 0.05). Risk score models and nomograms were constructed and validated for survival prediction of HCC. Moreover, diagnostic values of APOL1 and weak APOL6 were validated in Oncomine database (AUC > 0.700, 0.694); prognostic values of APOL3 and APOL6 were validated in HCCDB database (all P < 0.05). Differentially expressed APOL1 and APOL6 might be diagnostic biomarkers; APOL3 and APOL6 might be prognostic biomarkers of RFS and OS for HCC via chemokine signaling pathways.

Clinical implications of RAB13 expression in pan-cancer based on multi-databases integrative analysis.

Worldwide, cancer is a huge burden, and each year sees an increase in its incidence. RAB (Ras-related in brain) 13 is crucial for a number of tumor types. But more research on RAB13's tumor-related mechanism is still required. This study's goal was to investigate RAB13's function in human pan-cancer, and we have also preliminarily explored the relevant mechanisms. To investigate the differential expression, survival prognosis, immunological checkpoints, and pathological stage of RAB13 in human pan-cancer, respectively, databases of TIMER2.0, GEPIA 2, and UALCAN were employed. CBioPortal database was used to analyze the mutation level, meanwhile, PPI network was constructed based on STRING website. The putative functions of RAB13 in immunological infiltration were investigated using single sample gene set enrichment analysis (ssGSEA). The mechanism of RAB13 in hepatocellular cancer was also briefly investigated by us using gene set enrichment analysis (GSEA). RAB13 was differentially expressed in a number of different cancers, including liver hepatocellular carcinoma (LIHC), stomach adenocarcinoma (STAD), etc. Additionally, RAB13 overexpression in LGG and LIHC is associated with a worse prognosis, including overall survival (OS) and disease-free survival (DFS). Then, we observed that early in BLCA, BRAC, CHOL, ESCA, HNSC, KICH, KIRC, LIHC, LUAD, LUSC, and STAD, the level of RAB13 expression was raised. Next, we found that "amplification" was the most common mutation in RAB13. The expression of SLC39A1, JTB, SSR2, SNAPIN, and RHOC was strongly positively linked with RAB13, according to a correlation study. RAB13 favorably regulated B cell, CD8 + T cell, CD4 + T cell, macrophage, neutrophil, and dendritic cell in LIHC, according to immune infiltration analysis. Immune checkpoint study revealed a positive correlation between RAB13 expression and PD1, PDL1, and CTLA4 in LIHC. According to GSEA, RAB13 is involved in a number of processes in LIHC, including MTORC1 signaling, MYC targets v1, G2M checkpoint, MITOTIC spindle, DNA repair, P53 pathway, glycolysis, PI3K-AKT-MTOR signaling, etc. RAB13 is a possible therapeutic target in LIHC and can be used as a prognostic marker.

Hexavalent chromium disrupts the skin barrier by targeting ROS-mediated mitochondrial pathway apoptosis in keratinocytes.

Hexavalent chromium (Cr(VI)), a toxic heavy metal, is ubiquitous in daily life. Exposure to this toxic substance in occupational settings can cause dermatitis and cancer. As the body's largest organ, the skin plays a crucial role in protecting the organism against external aggressions. While previous studies have focused on the effects of Cr(VI) on skin inflammation, this study investigates the potential toxicity of Cr(VI) from the skin barrier and integrity perspective. The in vivo results of this study showed that mice exposed to Cr(VI) experienced skin deterioration and hemorrhaging, as well as a reduction in the thickness of the collagen fiber layer. TUNEL and Occludin staining results revealed that Cr(VI)'s toxicity primarily targeted keratinocytes. Experiments in vitro demonstrated that Cr(VI) treatment decreased the activity of HaCaT cells, altered cell morphology, and increased LDH secretion. Further research revealed that Cr(VI) could modify membrane permeability, impair membrane integrity, and reduce the protein expression of ZO-1 and Occludin. In addition, it was discovered that Cr(VI) promoted cell apoptosis and inhibited AKT activation. However, the addition of a caspase inhibitor and an AKT activator prevented Cr(VI)-induced injury to the cell membrane barrier, indicating that apoptosis plays a crucial role in this process. The addition of three apoptotic pathway inhibitors, confirmed that Cr(VI) damaged the cell barrier through ROS-mediated mitochondrial pathway apoptosis. Moreover, the use of a ROS inhibitor significantly reduced Cr(VI)-induced apoptosis and cell barrier injury. In conclusion, this study provides an experimental foundation for the treatment of skin injury caused by Cr(VI).