Using intravascular ultrasound image-based fluid-structure interaction models and machine learning methods to predict human coronary plaque vulnerability change

Plaque vulnerability prediction is of great importance in cardiovascular research. In vivo follow-up intravascular ultrasound (IVUS) coronary plaque data were acquired from nine patients to construct fluid-structure interaction models to obtain plaque biomechanical conditions. Morphological plaque vulnerability index (MPVI) was defined to measure plaque vulnerability. The generalized linear mixed regression model (GLMM), support vector machine (SVM) and random forest (RF) were introduced to predict MPVI change (ΔMPVI = MPVI_follow-up‒MPVI_baseline) using ten risk factors at baseline. The combination of mean wall thickness, lumen area, plaque area, critical plaque wall stress, and MPVI was the best predictor using RF with the highest prediction accuracy 91.47%, compared to 90.78% from SVM, and 85.56% from GLMM. Machine learning method (RF) improved the prediction accuracy by 5.91% over that from GLMM. MPVI was the best single risk factor using both GLMM (82.09%) and RF (78.53%) while plaque area was the best using SVM (81.29%).

Multi-Band Surgery for Repaired Tetralogy of Fallot Patients With Reduced Right Ventricle Ejection Fraction: A Pilot Study

Introduction

Right ventricle (RV) failure is one of the most common symptoms among patients with repaired tetralogy of Fallot (TOF). The current surgery treatment approach including pulmonary valve replacement (PVR) showed mixed post-surgery outcomes. A novel PVR surgical strategy using active contracting bands is proposed to improve the post-PVR outcome. In lieu of testing the risky surgical procedures on real patients, computational simulations (virtual surgery) using biomechanical ventricle models based on patient-specific cardiac magnetic resonance (CMR) data were performed to test the feasibility of the PVR procedures with active contracting bands. Different band combination and insertion options were tested to identify optimal surgery designs.

Method

Cardiac magnetic resonance data were obtained from one TOF patient (male, age 23) whose informed consent was obtained. A total of 21 finite element models were constructed and solved following our established procedures to investigate the outcomes of the band insertion surgery. The non-linear anisotropic Mooney–Rivlin model was used as the material model. Five different band insertion plans were simulated (three single band models with different band locations, one model with two bands, and one model with three bands). Three band contraction ratios (10, 15, and 20%) and passive bands (0% contraction ratio) were tested. RV ejection fraction was used as the measure for cardiac function.

Results

The RV ejection fraction from the three-band model with 20% contraction increased to 41.58% from the baseline of 37.38%, a 4.20% absolute improvement. The RV ejection fractions from the other four band models with 20% contraction rate were 39.70, 39.45, and 40.70% (two-band) and 39.17%, respectively. The mean RV stress and strain values from all of the 21 models showed only modest differences (5–11%).

Conclusion

This pilot study demonstrated that the three-band model with 20% band contraction ratio led to 4.20% absolute improvement in the RV ejection fraction, which is considered as clinically significant. The passive elastic bands led to the reduction of the RV ejection fractions. The modeling results and surgical strategy need to be further developed and validated by a multi-patient study and animal experiments before clinical trial could become possible. Tissue regeneration techniques are needed to produce materials for the contracting bands.

Reconstruction and analysis of the aberrant lncRNA-miRNA-mRNA network in systemic lupus erythematosus

OBJECTIVE

A new perspective of determining the pathophysiology of systemic lupus erythematosus (SLE) development is required. The current study explores the aberrant expression of long non-coding RNAs (lncRNA), microRNA (miRNA) and mRNA. The study further constructs and analyses the lncRNA-miRNA-mRNA network to elucidate their gene regulation roles in SLE.

METHOD

We extracted mRNA, lncRNA and miRNA from the whole venous blood of 20 SLE patients and 20 normal control (NC) healthy individuals. A lncRNA-mRNA-miRNA network in SLE was constructed using a bioinformatics approach. Subsequently, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses were performed using the Cytoscape plug-in BinGo, the DAVID database and Cytoscape software to explore the function of mRNAs in this network.

RESULT

A total of 855 mRNA, 7311 lncRNA and 134 miRNA with differentially expressed profiles were identified. Meanwhile, we established a competing endogenous RNA (ceRNA) subnetwork composed of 52 differentially expressed lncRNAs (DElncRNAs), seven differentially expressed miRNAs and 10 differentially expressed mRNAs. We extracted the subnetwork from the ceRNA network and found that three novel miRNAs were key: hsa-miR-145, hsa-miR-17 and hsa-miR-143. We also deduced that the DElncRNAs MIAT and NEAT1 might play crucial roles in the pathogenesis of SLE. The results were verified by bioinformatics analysis.

CONCLUSION

Our results provide a novel perspective for studying lncRNA-related and miRNA-related ceRNA networks in SLE.

Combining IVUS and Optical Coherence Tomography for More Accurate Coronary Cap Thickness Quantification and Stress/Strain Calculations: A Patient-Specific Three-Dimensional Fluid-Structure Interaction Modeling Approach

Accurate cap thickness and stress/strain quantifications are of fundamental importance for vulnerable plaque research. Virtual histology intravascular ultrasound (VH-IVUS) sets cap thickness to zero when cap is under resolution limit and IVUS does not see it. An innovative modeling approach combining IVUS and optical coherence tomography (OCT) is introduced for cap thickness quantification and more accurate cap stress/strain calculations. In vivo IVUS and OCT coronary plaque data were acquired with informed consent obtained. IVUS and OCT images were merged to form the IVUS + OCT data set, with biplane angiography providing three-dimensional (3D) vessel curvature. For components where VH-IVUS set zero cap thickness (i.e., no cap), a cap was added with minimum cap thickness set as 50 and 180 μm to generate IVUS50 and IVUS180 data sets for model construction, respectively. 3D fluid-structure interaction (FSI) models based on IVUS + OCT, IVUS50, and IVUS180 data sets were constructed to investigate cap thickness impact on stress/strain calculations. Compared to IVUS + OCT, IVUS50 underestimated mean cap thickness (27 slices) by 34.5%, overestimated mean cap stress by 45.8%, (96.4 versus 66.1 kPa). IVUS50 maximum cap stress was 59.2% higher than that from IVUS + OCT model (564.2 versus 354.5 kPa). Differences between IVUS and IVUS + OCT models for cap strain and flow shear stress (FSS) were modest (cap strain <12%; FSS <6%). IVUS + OCT data and models could provide more accurate cap thickness and stress/strain calculations which will serve as basis for further plaque investigations.

miR-142-3p Inhibits the Metastasis of Hepatocellular Carcinoma Cells by Regulating HMGB1 Gene Expression

BACKGROUND

Non-coding small RNAs are involved in organism development, and their aberrant regulation induces various diseases, including hepatocellular carcinoma (HCC), but their exact mechanisms have not been determined.

OBJECTIVE

The aim was to investigate the role of miR-142-3p on HMGB1 expression in hepatocellular carcinoma.

METHODS

Expression levels of miR-142-3p in HCC tissues and cultured cells were measured by RT-PCR. The invasion and metastasis abilities of HepG2 cells according to Transwell migration and invasion assays, and protein expression was measured by western blotting.

RESULTS

The present study reported that miR-142-3p promotes the invasion and migration of HCC cells. miR-142-3p levels are lower in HCC tissues than in adjacent non-cancerous tissues, suggesting a tumor suppressor role for miR-142-3p. Highmobility group box protein 1 (HMGB1) is an oncogene that promotes the metastasis of HCC. miR-142-3p or HMGB1 knockdown alone inhibits the invasion and migration of HCC cells, and HMGB1 overexpression impedes the effect of miR-142-3p. Further studies showed that HMGB1 is a direct target gene of miR-142-3p in HCC. miR-142-3p represses HMGB1 gene transcription by directly binding to the 3' untranslated region (UTR) of HMGB1, thereby inhibiting cancer cell invasion and migration.

CONCLUSION

This study, for the first time, reports that miR-142-3p is a novel tumor suppressor that inhibits the invasion and migration of HCC cells by directly regulating gene transcription of HMGB1. Thus, miR-142-3p may be a potential diagnostic and therapeutic biomarker for HCC patients.

Normal fertility with deletion of sY84 and sY86 in AZFa region

BACKGROUND

Entire deletion of the azoospermia factor a (AZFa) region commonly results in non-obstructive-azoospermia (NOA). Although sY84 and sY86 are recommended as the first choice of sequence-tagged sites (STSs) primers in AZFa region, and their deletions suggest a very high probability of complete deletion of AZFa, extension analysis is now compulsory to identify the deletion pattern.

OBJECTIVES

We aim to verify that extension analysis is relevant in assessing the deletion pattern of AZF by reporting a family in which two normal fertile men were confirmed to have a deletion of sY84 and sY86.

MATERIALS AND METHODS

According to the EAA/EMQN recommendation, AZF evaluation was detected by multiplex polymerase chain reaction (PCR) with six STSs, and extension analysis was performed to identify the deletion pattern due to the deletions of sY84 and sY86. And the further exploration was conducted to map the breakpoints of deleted DNA fragment.

RESULTS

Deletion of sY84 and sY86 was found in the case with coinstantaneous normal semen analysis. An identically partial deletion pattern of AZFa region with the absence of an hg38Y fragment (12470437~12690385, 219949 bp in total) was found in both the case and his father, which includes three pseudogenes and one non-coding-RNA gene.

DISCUSSION AND CONCLUSION

The extension analysis has permitted the diagnosis of a partial AZFa deletion and confirmed the importance of the extension analysis in order to provide a more accurate prediction for the testis phenotype.

Identification of key pathways and genes changes in pancreatic cancer cells (BXPC-3) after cross-talk with primary pancreatic stellate cells using bioinformatics analysis

Pancreatic ductal adenocarcinoma (PDAC) is one of the most malignant tumors with poor prognosis, and the interaction between activated pancreatic stellate cells (PSCs) and PDAC cells plays an important role in the development of PDAC. The aim of this study was to identify gene changes in BXPC-3 after cross-talk with PSCs and reveal their potential mechanisms. The gene expression profiling analysis of BXPC-3 was completed after co-culture with primary PSCs for 48 h. The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analyses were performed, and the differentially expressed genes (DEGs) were identified by Agilent GeneSpring GX software. In total, 3657 DEGs were identified in BXPC-3, including 1881 up-regulated genes and 1776 downregulated genes. GO analysis results showed that upregulated DEGs were significantly enriched in biological processes (BP), including peptide metabolic process, response to stress and electron transport chain; the downregulated DEGs were significantly enriched in biological processes, including signaling, multicellular organism development and anatomical structure development. KEGG pathway analysis revealed that 19 pathways were upregulated and 32 pathways were downregulated, and that upregulated DEGs were enriched in protein export and glutathione metabolism, while the downregulated DEGs were enriched in axon guidance and focal adhesion. The top 10 upregulated genes and the top 10 downregulated genes were identified. By constructing PPI network, we selected out 10 key genes (TP53, SRC, IL6, JUN, ISG15, CAD, STAT1, OAS3, OAS1, VIM) and significant pathways. The associated survival analysis was performed and the SRC, IL-6, ISG15, STAT1, OAS3, OAS1 and VIM were proved to be related to worse overall survival time of PDAC patients. In conclusion, the present study indicated that the identified DEGs promote our understanding of the molecular mechanisms underlying the interaction between pancreatic cancer cells and PSCs and might be used as molecular targets in the future to study the role of tumor microenvironment in the progression of PDAC.

Ventricle stress/strain comparisons between Tetralogy of Fallot patients and healthy using models with different zero-load diastole and systole morphologies

Patient-specific in vivo ventricle mechanical wall stress and strain conditions are important for cardiovascular investigations and should be calculated from correct zero-load ventricle morphologies. Cardiac magnetic resonance (CMR) data were obtained from 6 healthy volunteers and 12 Tetralogy of Fallot (TOF) patients with consent obtained. 3D patient-specific CMR-based ventricle models with different zero-load diastole and systole geometries due to myocardium contraction and relaxation were constructed to qualify right ventricle (RV) diastole and systole stress and strain values at begin-filling, end-filling, begin-ejection, and end-ejection, respectively. Our new models (called 2G models) can provide end-diastole and end-systole stress/strain values which models with one zero-load geometries (called 1G models) could not provide. 2G mean end-ejection stress value from the 18 participants was 321.4% higher than that from 1G models (p = 0.0002). 2G mean strain values was 230% higher than that of 1G models (p = 0.0002). TOF group (TG) end-ejection mean stress value was 105.4% higher than that of healthy group (HG) (17.54±7.42kPa vs. 8.54±0.92kPa, p = 0.0245). Worse outcome group (WG, n = 6) post pulmonary valve replacement (PVR) begin-ejection mean stress was 57.4% higher than that of better outcome group (BG, 86.94±26.29 vs. 52.93±22.86 kPa; p = 0.041). Among 7 selected parameters, End-filling stress was the best predictor to differentiate BG patients from WG patients with prediction accuracy = 0.8208 and area under receiver operating characteristic curve (AUC) value at 0.8135 (EE stress). Large scale studies are needed to further validate our findings.

Combining morphological and biomechanical factors for optimal carotid plaque progression prediction: An MRI-based follow-up study using 3D thin-layer models

Plaque progression prediction is of fundamental significance to cardiovascular research and disease diagnosis, prevention, and treatment. Magnetic resonance image (MRI) data of carotid atherosclerotic plaques were acquired from 20 patients with consent obtained. 3D thin-layer models were constructed to calculate plaque stress and strain. Data for ten morphological and biomechanical risk factors were extracted for analysis. Wall thickness increase (WTI), plaque burden increase (PBI) and plaque area increase (PAI) were chosen as three measures for plaque progression. Generalized linear mixed models (GLMM) with 5-fold cross-validation strategy were used to calculate prediction accuracy and identify optimal predictor. The optimal predictor for PBI was the combination of lumen area (LA), plaque area (PA), lipid percent (LP), wall thickness (WT), maximum plaque wall stress (MPWS) and maximum plaque wall strain (MPWSn) with prediction accuracy = 1.4146 (area under the receiver operating characteristic curve (AUC) value is 0.7158), while PA, plaque burden (PB), WT, LP, minimum cap thickness, MPWS and MPWSn was the best for WTI (accuracy = 1.3140, AUC = 0.6552), and a combination of PA, PB, WT, MPWS, MPWSn and average plaque wall strain (APWSn) was the best for PAI with prediction accuracy = 1.3025 (AUC = 0.6657). The combinational predictors improved prediction accuracy by 9.95%, 4.01% and 1.96% over the best single predictors for PAI, PBI and WTI (AUC values improved by 9.78%, 9.45%, and 2.14%), respectively. This suggests that combining both morphological and biomechanical risk factors could lead to better patient screening strategies.

Epidermal autophagy and beclin 1 regulator 1 and loricrin: a paradigm shift in the prognostication and stratification of the American Joint Committee on Cancer stage I melanomas

BACKGROUND

The updated American Joint Committee on Cancer (AJCC) staging criteria for melanoma remain unable to identify high-risk stage I tumour subsets.

OBJECTIVES

To determine the utility of epidermal autophagy and beclin 1 regulator 1 (AMBRA1)/loricrin (AMLo) expression as a prognostic biomarker for AJCC stage I cutaneous melanoma.

METHODS

Peritumoral AMBRA1 expression was evaluated in a retrospective discovery cohort of 76 AJCC stage I melanomas. AMLo expression was correlated with clinical outcomes up to 12 years in two independent powered, retrospective validation and qualification cohorts comprising 379 AJCC stage I melanomas.

RESULTS

Decreased AMBRA1 expression in the epidermis overlying primary melanomas in a discovery cohort of 76 AJCC stage I tumours was associated with a 7-year disease-free survival (DFS) rate of 81·5% vs. 100% survival with maintained AMBRA1 (P < 0·081). Following an immunohistochemistry protocol for semi-quantitative analysis of AMLo, analysis was undertaken in validation (n = 218) and qualification cohorts (n = 161) of AJCC stage I melanomas. Combined cohort analysis revealed a DFS rate of 98·3% in the AMLo low-risk group (n = 239) vs. 85·4% in the AMLo high-risk cohort (n = 140; P < 0·001). Subcohort multivariate analysis revealed that an AMLo hazard ratio (HR) of 4·04 [95% confidence interval (CI) 1·69-9·66; P = 0·002] is a stronger predictor of DFS than Breslow depth (HR 2·97, 95% CI 0·93-9·56; P = 0·068) in stage IB patients.

CONCLUSIONS

Loss of AMLo expression in the epidermis overlying primary AJCC stage I melanomas identifies high-risk tumour subsets independently of Breslow depth. What's already known about this topic? There is an unmet clinical need for biomarkers of early-stage melanoma. Autophagy and beclin 1 regulator 1 (AMBRA1) is a proautophagy regulatory protein with known roles in cell proliferation and differentiation, and is a known tumour suppressor. Loricrin is a marker of epidermal terminal differentiation. What does this study add? AMBRA1 has a functional role in keratinocyte/epidermal proliferation and differentiation. The combined decrease/loss of peritumoral AMBRA1 and loricrin is associated with a significantly increased risk of metastatic spread in American Joint Committee on Cancer (AJCC) stage I tumours vs. melanomas, in which peritumoral AMBRA1 and loricrin are maintained, independently of Breslow depth. What is the translational message? The integration of peritumoral epidermal AMBRA1/loricrin biomarker expression into melanoma care guidelines will facilitate more accurate, personalized risk stratification for patients with AJCC stage I melanomas, thereby facilitating stratification for appropriate follow-up and informing postdiagnostic investigations, including sentinel lymph node biopsy, ultimately resulting in improved disease outcomes and rationalization of healthcare costs.

Identification of key pathways and genes changes in pancreatic cancer cells (BXPC-3) after cross-talked with primary pancreatic stellate cells using bioinformatics analysis

Pancreatic ductal adenocarcinoma (PDAC) is one of the most malignant tumors with poor prognosis, and the interaction between activated pancreatic stellate cells (PSCs) and PDAC cells plays an important role in the development of PDAC. The aim of this study was to identify gene changes in BXPC-3 after cross-talked with PSCs and reveal their potential mechanisms. The gene expression profiling analysis of BXPC-3 was completed after co-cultured with primary PSCs for 48 h. The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analyses were performed, and the differentially expressed genes (DEGs) were identified by Agilent GeneSpring GX software. In total, 3657 DEGs were identified in BXPC-3, including 1881 up-regulated genes and 1776 downregulated genes. GO analysis results showed that up-regulated DEGs were significantly enriched in biological processes (BP), including peptide metabolic process, response to stress, and electron transport chain; the down-regulated DEGs were significantly enriched in biological processes, including signaling, multicellular organismal development, and anatomical structure development. KEGG pathway analysis revealed that 19 pathways were upregulated and 32 pathways were downregulated, and that up-regulated DEGs were enriched in protein export and glutathione metabolism, while the down-regulated DEGs were enriched in axon guidance and focal adhesion. The top 10 up-regulated genes, and the top 10 down-regulated genes were identified. By constructing PPI network, we selected out 10 key genes (TP53, SRC, IL6, JUN, ISG15, CAD, STAT1, OAS3, OAS1, VIM) and significant pathways. The associated survival analysis was performed and the SRC, IL-6, ISG15, STAT1, OAS3, OAS1 and VIM were proved to be related to worse overall survival time of PDAC patients. In conclusion, the present study indicated that the identified DEGs promote our understanding of the molecular mechanisms underlying the interaction between pancreatic cancer cells and PSCs and might be used as molecular targets in the future to study the role of tumor microenvironment in the progression of PDAC.

A Multi-Modality Image-Based FSI Modeling Approach for Prediction of Coronary Plaque Progression Using IVUS and OCT Data with Follow-Up

Medical image resolution has been a serious limitation in plaque progression research. A modeling approach combining intravascular ultrasound (IVUS) and optical coherence tomography (OCT) was introduced and patient follow-up IVUS and OCT data were acquired to construct 3D coronary models for plaque progression investigations. Baseline and follow-up in vivo IVUS and OCT coronary plaque data were acquired from one patient with 105 matched slices selected for model construction. 3D FSI models based on IVUS and OCT data (denoted as IVUS+OCT model) were constructed to obtain stress/strain and wall shear stress (WSS) for plaque progression prediction. IVUS-based IVUS50 and IVUS200 models were constructed for comparison with cap thickness set as 50 and 200 microns, respectively. Lumen area increase (LAI), plaque area increase (PAI) and plaque burden increase (PBI) were chosen to measure plaque progression. The least squares support vector machine method was employed for plaque progression prediction using 19 risk factors. For IVUS+OCT model with LAI, PAI and PBI, the best single predictor was plaque strain, local plaque stress, and minimal cap thickness, with prediction accuracy as 0.766, 0.838 and 0.890, respectively; The prediction accuracy using best combinations of 19 factors was 0.911, 0.881 and 0.905, respectively. Compared to IVUS+OCT model, IVUS50 and IVUS200 models had errors ranging from 1% to 66.5% in quantifying cap thickness, stress, strain and prediction accuracies. WSS showed relatively lower prediction accuracy compared to other predictors in all 9 prediction studies.

Identification of key pathways and gene changes in primary pancreatic stellate cells after cross-talk with pancreatic cancer cells (BXPC-3) using bioinformatics analysis

It is well known that as the king of cancer, pancreatic ductal adenocarcinoma (PDAC) has relatively malignant biological behavior and poor prognosis. The interaction between pancreatic stellate cells and PDAC cells promotes the development of PDAC. The aim of this study was to describe gene characteristics in pancreatic stellate cell (PSCs) after cross-talked with BXPC-3 and unravel their underlying mechanisms. The expression profiling analysis of genes in PSCs was completed after co-cultured with primary BXPC-3 for 48h. The Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analysis and gene ontology (GO) analysis were performed, and the differentially expressed genes (DEGs) were identified by Agilent GeneSpring GX program. In total, 1804 DEGs were filtered out in PSCs, including 958 up-regulated genes and 846 downregulated genes. GO analysis showed that the up-regulated DEGs were significantly enriched in biological processes (BP) such as defense response, immune system process and immune response; the down-regulated DEGs were significantly enriched in biological regulation and cytoskeleton organization. KEGG pathway analysis showed that 28 pathways were upregulated and 5 were downregulated. By constructing PPI network, we selected out 10 key genes (IL6，IL8, IL1B, BCL2, CCL2, CSF2, KIT, ICAM1, PTPRC and IGF1) and significant enriched pathways. In conclusion, the current study suggests that the filtered DEGs contribute to our understanding of the molecular mechanisms underlying the interaction between PSCs and pancreatic cancer cells, and might be used as molecular targets to further the study the role of tumor microenvironment in the progression of PDAC.

Calibration process for rechargeable cell and battery test systems

Coulombic efficiency is a powerful metric for evaluating the performance of materials in rechargeable cells and batteries. The ideal Coulombic efficiency, the ratio of charge removed to charge inserted, is unity. Some specialized systems can accurately measure cell capacity and Coulombic efficiency within 0.001%, which requires precise control and measurement of current, voltage, time, and temperature. Most battery electrode and electrolyte research is not performed with such precise but complex systems. The purpose of this paper is to demonstrate a simple, robust procedure to measure and possibly improve the accuracy of capacity and Coulombic efficiency measurements on standard systems in their as-used state. This approach is built on a commercially available thin film rechargeable cell for micro or milliampere currents and can be extended to, e.g., 18 650, cells for higher currents. An improved method to display Coulombic efficiency data is also presented. Regular, consistent calibration of testing systems and reporting of system resolution at specified test conditions is encouraged.