Microscopic Stress Sensitivity Analysis with In Situ SEM Study and Digital Core Deformation Simulation

Rock stress sensitivity is typically investigated macroscopically. In contrast, a new method combining in situ Scanning Electronic Microscope (SEM) study and digital core deformation simulation is developed in this paper, providing an effective way to investigate the relationship between microstructural deformation and decreasing permeability. The simulation method might replace in situ SEM study under certain scenarios. First, the in situ SEM study was implemented, and the microstructure deformations of rock samples during uniaxial loading were observed and recorded. The SEM images at different stress states were analyzed by digital image correlation (DIC) technique to investigate the principles of these deformations. A deformation simulation method was correspondingly proposed. The simulation effectiveness was demonstrated by comparing the simulation and the in situ SEM study results. To validate the simulation method for the three-dimensional (3D) digital core, porosity-permeability integrated measurements under triaxial stresses were conducted to obtain macroscale data under different stress states for a tight sandstone sample. A 3D digital core was reconstructed by micro-CT imaging with the same rock sample. Under the constraints of the measured porosity changes, the 3D digital core deformation was simulated. A series of simulated cores at different stress states were used for pore network model extraction, and the corresponding permeability was calculated. A comparison of the permeability changes of the simulation and porosity-permeability integrated measurements indicated consistently that the simulation method can characterize the 3D digital core stress sensitivity. In addition, the in situ SEM study results revealed that the throats deformed more severely than the pores by generating the pore and throat diameter frequency distributions at different stress states. Therefore, we concluded that throat deformation is more critical than pore deformation for permeability reduction

Establishment of a risk model by integrating hypoxia genes in predicting prognosis of esophageal squamous cell carcinoma

Abstract Background Esophageal squamous cell carcinoma (ESCC) has a dismal prognosis, and hypoxia plays a key role in metastasis and proliferation of ESCC. Thus, we aimed to develop a hypoxia‐based gene signature to assist in the treatment decisions and prognosis. Methods We performed consensus clustering analysis on samples from GSE53625 dataset from the Gene Expression Omnibus (GEO) database and used weighted gene co‐expression network analysis to filter out candidate modules, which were then intersected with differentially expressed genes from clustered subgroups to obtain hypoxia‐related genes (HRGs). After that, the aforementioned genes were used to construct risk score models and validated in The Cancer Genome Atlas (TCGA) database and Cox regression analysis were used to construct a nomogram. Immunohistochemical was used to detect protein expression levels of relevant genes. Moreover, the relationship between risk scores and tumor microenvironment was explored. Results A hypoxia risk model containing six genes (PNPLA1, CARD18, IL‐18, SLC37A2, ADAMTS18, and FAM83C) was constructed by screening key HRGs. Poorer prognosis in the high‐risk group than in the low‐risk group. And Cox regression analysis showed that risk score was an independent prognostic factor. The nomogram based on risk scores could well predict 1‐, 3‐, and 5‐year survival. P53, Wnt, and hypoxia signaling pathways may be some regulatory mechanisms of hypoxia associated with the tumor microenvironment. In addition, we confirmed the high expression of BGN and low expression of IL‐18 in ESCC tissues. Conclusions Our study determined the prognostic value of a 6‐hypoxia gene signature and a prognostic model, providing potential prognostic predictors and therapeutic targets for ESCC

Development and validation of web-based dynamic nomograms predictive of disease-free and overall survival in patients who underwent pneumonectomy for primary lung cancer

Background The tumour-node-metastasis (TNM) staging system is insufficient to precisely distinguish the long-term survival of patients who underwent pneumonectomy for primary lung cancer. Therefore, this study sought to identify determinants of disease-free (DFS) and overall survival (OS) for incorporation into web-based dynamic nomograms. Methods The clinicopathological variables, surgical methods and follow-up information of 1,261 consecutive patients who underwent pneumonectomy for primary lung cancer between January 2008 and December 2018 at Sun Yat-sen University Cancer Center were collected. Nomograms for predicting DFS and OS were built based on the significantly independent predictors identified in the training cohort (n = 1,009) and then were tested on the validation cohort (n = 252). The concordance index (C-index) and time-independent area under the receiver-operator characteristic curve (AUC) assessed the nomogram’s discrimination accuracy. Decision curve analysis (DCA) was applied to evaluate the clinical utility. Results During a median follow-up time of 40.5 months, disease recurrence and death were observed in 446 (35.4%) and 665 (52.7%) patients in the whole cohort, respectively. In the training cohort, a higher C-reactive protein to albumin ratio, intrapericardial pulmonary artery ligation, lymph node metastasis, and adjuvant therapy were significantly correlated with a higher risk for disease recurrence; similarly, the independent predictors for worse OS were intrapericardial pulmonary artery and vein ligation, higher T stage, lymph node metastasis, and no adjuvant therapy. In the validation cohort, the integrated DFS and OS nomograms showed well-fitted calibration curves and yielded good discrimination powers with C-index of 0.667 (95% confidence intervals CIs [0.610–0.724]) and 0.697 (95% CIs [0.649–0.745]), respectively. Moreover, the AUCs for 1-year, 3-year, and 5-year DFS were 0.655, 0.726, and 0.735, respectively, and those for 3-year, 5-year, and 10-year OS were 0.741, 0.765, and 0.709, respectively. DCA demonstrated that our nomograms could bring more net benefit than the TNM staging system. Conclusions Although pneumonectomy for primary lung cancer has brought encouraging long-term outcomes, the constructed prediction models could assist in precisely identifying patients at high risk and developing personalized treatment strategies to further improve survival

On two-phase flow solvers in irregular domains with contact line

We present numerical methods that enable the direct numerical simulation of two-phase flows in irregular domains. A method is presented to account for surface tension effects in a mesh cell containing a triple line between the liquid, gas and solid phases. Our numerical method is based on the level-set method to capture the liquid–gas interface and on the single-phase Navier–Stokes solver in irregular domain proposed in [35]to impose the solid boundary in an Eulerian framework. We also present a strategy for the implicit treatment of the viscous term and how to impose both a Neumann boundary condition and a jump condition when solving for the pressure field. Special care is given on how to take into account the contact angle, the no-slip boundary condition for the velocity field and the volume forces. Finally, we present numerical results in two and three spatial dimensions evaluating our simulations with several benchmarks