Three-dimensional solidification modeling of various materials using the lattice Boltzmann method with an explicit enthalpy equation.

Based on the mesoscopic scale, the lattice Boltzmann method (LBM) with an enthalpy-based model represented in the form of distribution functions is widely used in the liquid-solid phase transition process of energy storage materials due to its direct and relatively accurate characterization of the presence of latent heat of solidification. However, since the enthalpy distribution function itself contains the physical properties of the material, these properties are transferred along with the enthalpy distribution function during the streaming process. This leads to deviations between the enthalpy-based model when simulating the phase transition process of different materials mixed and the actual process. To address this issue, in this paper, we construct an enthalpy-based model for different types of materials. For multiple materials, various forms of enthalpy distribution functions are employed. This method still uses the form of enthalpy distribution functions for collisions and streaming processes among the same type of substance, while for heat transfer between different materials, it avoids the direct transfer of enthalpy distribution functions and instead applies a source term to the enthalpy distribution functions, characterizing the heat transfer between different materials through the energy change before and after mixing based on the temperature. To verify the accuracy of the method proposed in this paper, a detailed solidification model for two different materials is constructed using the example of water droplets solidifying in air, and the results are compared with experimental outcomes. The results of the simulation show that the model constructed in this paper is largely in line with the actual process.

Hepatic artery restriction operation combined with ALPPS (HARO-ALPPS), a novel ALPPS procedure for the treatment of hepatocellular carcinoma with severe fibrosis: retrospective clinical cohort study.

BACKGROUND: Associating liver partition with portal vein ligation for staged liver resection (ALPPS) has been used in the treatment of patients with advanced or massive liver cancer without sufficient future liver remnant, but concerns remain regarding tumor outcomes and surgical safety. This study aims to evaluate the efficacy and safety of a new procedure, hepatic artery restriction operation combined with ALPPS (HARO-ALPPS), in the treatment of hepatocellular carcinoma (HCC) patients especially with severe fibrosis. METHODS: This retrospective study analyzed 8 patients who underwent HARO-ALPPS for HCC and compared their outcomes with 64 patients who underwent conventional ALPPS. The primary outcomes assessed were liver regeneration ability (measured by relative and absolute kinetic growth rates), postoperative complications, and mortality. The secondary outcomes included overall survival and disease-free survival. RESULTS: HARO-ALPPS significantly restricted the blood supply of the hepatic artery. One week after surgery, the blood flow of the right hepatic artery dropped to 62.1%. At the same time, HARO-ALPPS shows superior liver regeneration ability, which is particularly prominent in the background of liver fibrosis. No serious complications occurred after HARO-ALPPS. The overall survival rate of HARO-ALPPS was 75%, which was higher than that of ALPPS (64%, P =0.816). CONCLUSION: Compared to conventional ALPPS, HARO-ALPPS exhibits a better liver regeneration ability, and favorable long-term outcomes. Further prospective studies are needed to validate these findings and evaluate the long-term oncologic outcomes of this novel procedure.

Construction of a 3-mRNA hypoxia prognostic model to evaluate immune microenvironment in hepatocellular carcinoma.

BACKGROUND: Hypoxia is a key factor in the development of hepatocellular carcinoma (HCC), which is the most common primary liver cancer with poor prognosis. The current study aimed to identify the potential prognostic biomarkers of the hypoxia-associated gene signature in patients with HCC, and to further explore the relationship between hypoxia and immune infiltration. METHODS: After the determination of differentially expressed genes (DEGs) using the HCC transcriptome data of The Cancer Genome Atlas database and hypoxia-related gene set, the prognosis-associated genes were identified using univariate Cox regression analysis. Then, the hypoxia prognosis model was established via multivariate Cox regression analysis, with functional annotation conducted using Gene Set Enrichment Analysis. CIBERSORT was utilized to analyze the degree of tumor immune invasion, and an International Cancer Genome Consortium cohort to verify the reliability of the prognosis model. Expression levels of hypoxia-associated genes were detected by real-time quantitative polymerase chain reaction in HCC samples. RESULTS: 3 genes (ENO1, SAP30, and STC2) constructed the hypoxia prognosis model. The patients were subdivided into 2 groups based on median risk score, with a high hypoxic score indicating poor prognosis of HCC. The hypoxia signature could be employed as an independent prognostic factor in HCC. In addition, the proportion of macrophages was higher in the high-risk group. CONCLUSION: The hypoxia-associated signature could be a potential prognostic marker of HCC and provides a different perspective for immunotherapy of HCC.

Case Report: Combining liver partition and portal vein ligation after thrombectomy for tumor isolation (CLAPT) to treat advanced hepatocellular carcinoma with portal vein tumor thrombosis.

Background: Primary liver cancer is the third leading cause of cancer-related deaths worldwide in 2020, and hepatocellular carcinoma (HCC) is the major pathological type. Patients with HCC complicated with portal vein tumor thrombosis (PVTT) have a poor prognosis, and controversies regarding treatment options exist among international scholars. Patients with VP4 or Cheng's type III classification are generally considered ineligible for surgical treatment. Methods: We retrospectively analyzed three cases of HCC with PVTT who underwent a novel modified surgical procedure. The procedure included portal vein thrombectomy and portal vein ligation with liver parenchymal separation for the resection of the tumor thrombus involving the main portal vein trunk and for the isolation of the giant tumor. The three cases were then treated with targeted drugs postoperatively. Results: One case developed acute renal failure in the perioperative period, and the renal function gradually recovered after the treatment. The two remaining cases recovered uneventfully postoperatively. The prognosis of the three patients was encouraging. Only one patient died of lung metastasis after 13 months, and the remaining patients were still alive after 41 and 21 months, respectively. Conclusions: We provide a new possible surgical option for patients with advanced HCC with PVTT. The surgical procedure was inspired by associating liver partition with portal vein ligation for staged hepatectomy and portal vein thrombectomy. The survival time was significantly prolonged after the patients underwent thrombectomy, tumor isolation, and postoperative nonsurgical treatment. Hence, the combination of liver partition and portal vein ligation after thrombectomy for tumor isolation has the potential for the treatment of advanced HCC with PVTT.

First Robotic Hepatectomy With Middle Hepatic Vein Reconstruction Using ePTFE Graft for Hepatic Adenoma: A Case Report.

Surgical resection remains the best choice for the treatment of liver tumors. Hepatectomy combined with artificial vascular reconstruction has been proven as an alternative to treating tumors involving the main hepatic veins. As the cutting-edge surgical technique, robotic liver surgery is a novel procedure expanding the field of minimally invasive approaches, especially in complex reconstruction. This study reports, for the first time, on a robotic hepatectomy with middle hepatic vein (MHV) reconstruction using an expanded polytetrafluoroethylene (ePTFE) graft for a patient with hepatic adenoma. The tumor, which was located in segment 8, was adjacent to the MHV. Robot-assisted resection of segment 4 and partial segment 8, and MHV reconstruction using a ePTFE graft were performed. During the post-operative examination and follow-up, the blood flow of the ePTFE graft was patent, and liver function recovered well. Thus, robotic hepatectomy with MHV reconstruction is a safe, minimally invasive, and precise surgery that may provide a novel approach for patients with liver tumors that are invading or adjacent to the main hepatic veins.

Bioinformatics Analysis for Constructing a Six-Immune-Related Long Noncoding RNA Signature as a Prognostic Model of Hepatocellular Carcinoma.

The present study was aimed at identifying the potential prognostic biomarkers of the immune-related long noncoding RNA (IRL) signature for patients with hepatocellular carcinoma (HCC). RNA-sequencing data and clinical information about HCC were obtained from The Cancer Genome Atlas. The IRLs were determined with regard to the coexpression of immune-related genes and differentially expressed lncRNAs. The survival IRLs were obtained using the univariate Cox analysis. Subsequently, the prognosis model was constructed via the multivariate Cox analysis. Subsequently, functional annotation was conducted using Gene Set Enrichment Analysis (GSEA) and principal component analysis (PCA). In total, 341 IRLs were identified, and 6 IRLs were found to have a highly significant association with the prognosis of patients with HCC. The immune prognosis model was constructed with these 6 IRLs (AC099850.4, negative regulator of antiviral response, AL031985.3, PRRT3-antisense RNA1, AL365203.2, and long intergenic nonprotein coding RNA 1224) using the multivariate Cox regression analysis. In addition, immune-related prognosis signatures were confirmed as an independent prognostic factor. The association between prognostic signatures and immune infiltration indicated that the 6 lncRNAs could reflect the immune status of the tumor. Collectively, the present study demonstrates that six-lncRNA signatures may be potential biomarkers to predict the prognosis of patients with HCC.

Bioinformatics analysis and experimental verification of five metabolism-related lncRNAs as prognostic models for hepatocellular carcinoma.

BACKGROUND: The number of patients with hepatocellular carcinoma (HCC) is showing a growing trend all over the world. The metabolic microenvironment has been shown to play a key role in the pathogenesis of HCC in recent studies. The expression of metabolites and metabolic processes in tumor cells can be regulated by gene regulation mediated by long non-coding RNAs (lncRNAs), the abnormal expression of which is closely related to tumor occurrence and metastasis. However, the fundamental mechanism of applying metabolism-related lncRNAs to predicting HCC is still unclear. METHODS: With the complete RNA sequence data and clinical data obtained from The Cancer Genome Atlas database and metabolism-related genes downloaded from the Kyoto Encyclopedia of Genes and Genomes database, with false discovery rate < 0.001, log fold change > 1.5 selected as the screening criteria for lncRNA, the relationship between the expression level of metabolism-related LncRNAs (MRLs) and the overall survival rate was determined by the Univariate Cox regression analyses with the establishment of the metabolic prognosis model by the application of Multivariate Cox regression analyses, revealing the different biological processes and signaling pathways in both high-risk groups and low-risk groups by Gene Ontology, Kyoto Encyclopedia of Genes and Genomes enrichment analysis, and gene set enrichment analysis, leading the expression of lncRNA to be assessed by the reverse transcription-polymerase chain reaction results. RESULTS: The overall survival rate of HCC patients is significantly correlated with signature of 5-MRLs. The prognosis characteristics of lncRNA reveal the relatively high death rate of patients in the high-risk groups, with the predicted signals by functional and pathway enrichment analysis related to biosynthesis, metabolic process, and metabolic pathway, with the prognostic characteristics of 5-MRLs by the combined analysis showing that it is an independent factor of HCC superior to the traditional clinical indicators in predicting the prognosis. A trend of high-expression was shown in MRLs in tumors by reverse transcription-polymerase chain reaction. CONCLUSION: The new 5-MRLs as potential biomarkers provide more powerful prognostic information for HCC patients. In the future clinical treatment of HCC, it will provide doctors with more methods.

Identification of prognostic metabolic genes in adrenocortical carcinoma and establishment of a prognostic nomogram: A bioinformatic study.

ABSTRACT: Adrenocortical carcinoma is an invasive malignancy with poor prognosis, high recurrence rate and limited therapeutic options. Therefore, it is necessary to establish an effective method to diagnose and evaluate the prognosis of patients, so as to realize individualized treatment and improve their survival rate.This study investigated metabolic genes that may be potential therapeutic targets for Adrenocortical carcinoma (ACC). Level 3 gene expression data from the ACC cohort and the relevant clinical information were obtained from The Cancer Genome Atlas (TCGA) database. To verify, other ACC datasets (GSE76021, GSE19750) were downloaded from the Gene Expression Omnibus (GEO) database. The ACC datasets from TCGA and GEO were used to screen metabolic genes through the Molecular Signatures Database using gene set enrichment analysis. Then, the overlapping metabolic genes of the 2 datasets were identified.A signature of five metabolic genes (CYP11B1, GSTM2, IRF9, RPL31, and UBE2C) was identified in patients with ACC. The signature could be used to divide the patients with ACC into high- and low-risk groups based on their median risk score. Multivariate Cox regression analysis was performed to determine the independent prognostic factors of ACC. Time-dependent receiver operating characteristic (ROC) curve analysis was conducted to assess the prediction accuracy of the prognostic signature. Last, a nomogram was established to assess the individualized prognosis prediction model.The results indicated that the signature of 5 metabolic genes had excellent predictive value for ACC. These findings might help improve personalized treatment and medical decisions.

Efficacy of the association liver partition and portal vein ligation for staged hepatectomy for the treatment of solitary huge hepatocellular carcinoma: a retrospective single-center study.

BACKGROUND: The feasibility of association liver partition and portal vein ligation for staged hepatectomy (ALPPS) for solitary huge hepatocellular carcinoma (HCC, maximal diameter ≥ 10 cm) remains uncertain. This study aims to evaluate the safety and the efficacy of ALPPS for patients with solitary huge HCC. METHODS: Twenty patients with solitary huge HCC who received ALPPS during January 2017 and December 2019 were retrospectively analyzed. The oncological characteristics of contemporaneous patients who underwent one-stage resection and transcatheter arterial chemoembolization (TACE) were compared using propensity score matching (PSM). RESULTS: All patients underwent complete two-staged ALPPS. The median future liver remnant from the ALPPS-I stage to the ALPPS-II stage increased by 64.5% (range = 22.3-221.9%) with a median interval of 18 days (range = 10-54 days). The 90-day mortality rate after the ALPPS-II stage was 5%. The 1- and 3-year overall survival (OS) rates were 70.0% and 57.4%, respectively, whereas the 1- and 3-year progression-free survival (PFS) rates were 60.0% and 43.0%, respectively. In the one-to-one PSM analysis, the long-term survival of patients who received ALPPS was significantly better than those who received TACE (OS, P = 0.007; PFS, P = 0.011) but comparable with those who underwent one-stage resection (OS, P = 0.463; PFS, P = 0.786). CONCLUSION: The surgical outcomes of ALPPS were superior to those of TACE and similar to those of one-stage resection. ALPPS is a safe and effective treatment strategy for patients with unresectable solitary huge HCC.

Identification of Spindle and Kinetochore-Associated Family Genes as Therapeutic Targets and Prognostic Biomarkers in Pancreas Ductal Adenocarcinoma Microenvironment.

AIM: The role of spindle and kinetochore-associated (SKA) genes in tumorigenesis and cancer progression has been widely studied. However, so far, the oncogenic involvement of SKA family genes in pancreatic cancer and their prognostic potential remain unknown. METHODS: Here, we carried out a meta-analysis of the differential expression of SKA genes in normal and tumor tissue. Univariate and multivariate survival analyses were done to evaluate the correlation between SKA family gene expression and pancreas ductal adenocarcinoma (PDAC) prognosis. Joint-effect and stratified survival analysis as well as nomogram analysis were used to estimate the prognostic value of genes. The underlying regulatory and biological mechanisms were identified by Gene set enrichment analysis. Interaction between SKA prognosis-related genes and immune cell infiltration was assessed using the Tumor Immune Estimation Resource tool. RESULTS: We find that SKA1-3 are highly expressed in PDAC tissues relative to non-cancer tissues. Survival analysis revealed that high expression of SKA1 and SKA3 independently indicate poor prognosis but they are not associated with relapse-free survival. The prognostic value of SKA1 and SKA3 was further confirmed by the nomogram, joint-effect, and stratified survival analysis. Analysis of underlying mechanisms reveals that these genes influence cancer-related signaling pathways, kinases, miRNA, and E2F family genes. Notably, prognosis-related genes are inversely correlated with several immune cells infiltrating levels. CONCLUSION: We find that SKA1 and SKA3 expression correlates with prognosis and immune cell infiltration in PDAC, highlighting their potential as pancreatic cancer prognostic biomarkers.

Identification of Prognostic Immune-Related Genes in Pancreatic Adenocarcinoma and Establishment of a Prognostic Nomogram: A Bioinformatic Study.

BACKGROUND: The prognosis of pancreatic adenocarcinoma (PAAD) is extremely poor and has not been improved. Thus, an effective method to assess the prognosis of patients must be established to improve their survival rate. METHOD: This study investigated immune-related genes that could be used as potential therapeutic targets for PAAD. Level 3 gene expression data from the PAAD cohort and the relevant clinical information were obtained from The Cancer Genome Atlas (TCGA) database. For validation, other PAAD datasets (DSE62452) were downloaded from the Gene Expression Omnibus (GEO) database. The PAAD datasets from TCGA and GEO were used to screen immune-related genes through the Molecular Signatures Database using gene set enrichment analysis. Then, the overlapping immune-related genes of the two datasets were identified. Coexpression networks of the immune-related genes were constructed. RESULTS: A signature of three immune-related genes (CKLF, ERAP2, and EREG) was identified in patients with PAAD. The signature could be used to divide the patients with PAAD into high- and low-risk groups based on their median risk score. Multivariate Cox regression analysis was performed to determine the independent prognostic factors of PAAD. Time-dependent receiver operating characteristic (ROC) curve analysis was conducted to assess the prediction accuracy of the prognostic signature. Last, a nomogram was established to assess the individualized prognosis prediction model based on the clinical characteristics and risk score of the TCGA PAAD dataset. The accuracy of the prognostic signature was further evaluated through functional evaluation and principal component analysis. CONCLUSIONS: The results indicated that the signature of three immune-related genes had excellent predictive value for PAAD. These findings might help improve personalized treatment and medical decisions.

Mining TCGA Database for Tumor Microenvironment-Related Genes of Prognostic Value in Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is one of the most common and lethal malignancies. Recent studies reveal that tumor microenvironment (TME) components significantly affect HCC growth and progression, particularly the infiltrating stromal and immune cells. Thus, mining of TME-related biomarkers is crucial to improve the survival of patients with HCC. Public access of The Cancer Genome Atlas (TCGA) database allows convenient performance of gene expression-based analysis of big data, which contributes to the exploration of potential association between genes and prognosis of a variety of malignancies, including HCC. The "Estimation of STromal and Immune cells in MAlignant Tumors using Expression data" algorithm renders the quantification of the stromal and immune components in TME possible by calculating the stromal and immune scores. Differentially expressed genes (DEGs) were screened by dividing the HCC cohort of TCGA database into high- and low-score groups according to stromal and immune scores. Further analyses of functional enrichment and protein-protein interaction networks show that the DEGs are mainly involved in immune response, cell adhesion, and extracellular matrix. Finally, seven DEGs have significant association with HCC poor outcomes. These genes contain FABP3, GALNT5, GPR84, ITGB6, MYEOV, PLEKHS1, and STRA6 and may be candidate biomarkers for HCC prognosis.