Prediction of respiratory complications by quantifying lung contusion volume using chest computed tomography in patients with chest trauma.

Pulmonary contusion is an important risk factor for respiratory complications in trauma patients. Hence, we aimed to determine the relationship between the ratio of pulmonary contusion volume to the total lung volume and patient outcomes and the predictability of respiratory complications. We retrospectively included 73 patients with a pulmonary contusion on chest computed tomography (CT) from 800 patients with chest trauma admitted to our facility between January 2019 and January 2020. Chest injury severity was expressed as the ratio of pulmonary contusion volume to total lung volume by quantifying pulmonary contusion volume on chest CT. The cut-off value was 80%. Among the 73 patients with pulmonary contusion (77% males, mean age: 45.3 years), 28 patients had pneumonia, and five had acute respiratory distress syndrome. The number of patients in the severe risk group with > 20% of pulmonary contusion volume was 38, among whom 23 had pneumonia. For predicting pneumonia, the area under the receiver operating characteristic curves for the ratio of pulmonary contusion volume was 0.85 (95% confidence interval 0.76-0.95, p = 0.008); the optimal threshold was 70.4%. Quantifying pulmonary contusion volume using initial CT enables identifying patients with chest trauma at high risk of delayed respiratory complications.

A User-Friendly, Web-Based Integrative Tool (ESurv) for Survival Analysis: Development and Validation Study.

BACKGROUND: Prognostic genes or gene signatures have been widely used to predict patient survival and aid in making decisions pertaining to therapeutic actions. Although some web-based survival analysis tools have been developed, they have several limitations. OBJECTIVE: Taking these limitations into account, we developed ESurv (Easy, Effective, and Excellent Survival analysis tool), a web-based tool that can perform advanced survival analyses using user-derived data or data from The Cancer Genome Atlas (TCGA). Users can conduct univariate analyses and grouped variable selections using multiomics data from TCGA. METHODS: We used R to code survival analyses based on multiomics data from TCGA. To perform these analyses, we excluded patients and genes that had insufficient information. Clinical variables were classified as 0 and 1 when there were two categories (for example, chemotherapy: no or yes), and dummy variables were used where features had 3 or more outcomes (for example, with respect to laterality: right, left, or bilateral). RESULTS: Through univariate analyses, ESurv can identify the prognostic significance for single genes using the survival curve (median or optimal cutoff), area under the curve (AUC) with C statistics, and receiver operating characteristics (ROC). Users can obtain prognostic variable signatures based on multiomics data from clinical variables or grouped variable selections (lasso, elastic net regularization, and network-regularized high-dimensional Cox-regression) and select the same outputs as above. In addition, users can create custom gene signatures for specific cancers using various genes of interest. One of the most important functions of ESurv is that users can perform all survival analyses using their own data. CONCLUSIONS: Using advanced statistical techniques suitable for high-dimensional data, including genetic data, and integrated survival analysis, ESurv overcomes the limitations of previous web-based tools and will help biomedical researchers easily perform complex survival analyses.

Numerical investigation of the sternoclavicular joint modeling technique for improving the surgical treatment of pectus excavatum.

It is now common to perform the Nuss procedure as a surgical treatment for pectus excavatum. As several types of detailed surgical methods exist as part of the Nuss procedure, studies are currently being conducted to verify their relative superiority via computerized biomechanical methods. However, no studies have considered the influence of sternoclavicular joints on the simulations of the Nuss procedure. Accordingly, this study aims to demonstrate the influence of these joints by comparing the clinical data with the finite element analysis data. Scenarios were set by classifying the movement of the joints based on the constraints of translation and rotation in the coordinate plane. The analyses were performed by applying the set scenarios to the constructed finite element model of a chest wall. The sternal displacement, Haller index, and equivalent stress were obtained from the analysis, and the data were compared with the data of the postoperative patient. When the translation of the anterior direction on the chest wall was constrained, the result obtained thereof was found to be similar to those obtained in the actual surgery. It is suggested that more accurate results can be obtained if the influence of the sternoclavicular joints is considered.

Evaluation of the prognostic significances of γ-secretase genes in pancreatic cancer.

With the growing requirement for novel prognostic biomarkers for pancreatic cancer, many studies have focused on clinical and/or genomic variables. Although many studies have been performed, carbohydrate antigen 19-9 is the only biomarker in clinical use. Therefore, the present study examined whether γ-secretase genes, including presenilin (PSEN), nicastrin (NCSTN), presenilin enhancer protein 2 (PSENEN), and anterior pharynx-defective 1 (APH1-), could serve as prognostic factors for pancreatic cancer. The cohorts selected included >100 pancreatic cancer patients. Patient data were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GSE21501). The prognostic roles of the γ-secretase genes were analyzed by several survival analysis methods. Among the γ-secretase genes, the prognosis tended to be worse in the 2 cohorts with increasing expression of PSEN1, APH1A, and PSENEN, while the remaining genes were the opposite in the 2 cohorts. Notably, although the patient characteristics were quite different, APH1A was statistically significantly associated with prognosis in the 2 cohorts. The hazard ratio of APH1A for overall survival was 1.598 (TCGA) and 2.724 (GSE21501). These results contribute to the study of γ-secretase in pancreatic cancer. We believe that γ-secretase, particularly APH1A, will be a new prognostic biomarker for pancreatic cancer.

mRNA Expression of SLC5A5 and SLC2A Family Genes in Papillary Thyroid Cancer: An Analysis of The Cancer Genome Atlas.

PURPOSE: The present study investigated the dynamics and prognostic role of messenger RNA (mRNA) expression responsible for ¹8F-fluorodeoxyglucose (FDG) uptake in FDG positron emission tomography (PET) and radioactive iodine (¹³¹I) uptake in whole-body radioactive iodine scans (WBS) in papillary thyroid cancer (PTC) patients. MATERIALS AND METHODS: The primary and processed data were downloaded from the Genomic Data Commons Data Portal. Expression data for sodium/iodide symporter (solute carrier family 5 member 5, SLC5A5), hexokinase (HK1-3), glucose-6-phosphate dehydrogenase (G6PD), and glucose transporter (solute carrier family 2, SLC2A1-4) mRNA were collected. RESULTS: Expression of SLC5A5 mRNA were negatively correlated with SLC2A1 mRNA and positively correlated with SLC2A4 mRNA. In PTC with BRAF mutations, expressions of SLC2A1, SLC2A3, HK2, and HK3 mRNA were higher than those in PTC without BRAF mutations. Expression of SLC5A5, SLC2A4, HK1, and G6PD mRNA was lower in PTC without BRAF mutation. PTCs with higher expression of SLC5A5 mRNA had more favorable disease-free survival, but no association with overall survival. CONCLUSION: Expression of SLC5A5 mRNA was negatively correlated with SLC2A1 mRNA. This finding provides a molecular basis for the management of PTC with negative WBS using ¹8F-FDG PET scans. In addition, higher expression of SLC5A5 mRNA was associated with less PTC recurrence, but not with deaths.

Gene network inherent in genomic big data improves the accuracy of prognostic prediction for cancer patients.

Accurate prediction of prognosis is critical for therapeutic decisions regarding cancer patients. Many previously developed prognostic scoring systems have limitations in reflecting recent progress in the field of cancer biology such as microarray, next-generation sequencing, and signaling pathways. To develop a new prognostic scoring system for cancer patients, we used mRNA expression and clinical data in various independent breast cancer cohorts (n=1214) from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) and Gene Expression Omnibus (GEO). A new prognostic score that reflects gene network inherent in genomic big data was calculated using Network-Regularized high-dimensional Cox-regression (Net-score). We compared its discriminatory power with those of two previously used statistical methods: stepwise variable selection via univariate Cox regression (Uni-score) and Cox regression via Elastic net (Enet-score). The Net scoring system showed better discriminatory power in prediction of disease-specific survival (DSS) than other statistical methods (p=0 in METABRIC training cohort, p=0.000331, 4.58e-06 in two METABRIC validation cohorts) when accuracy was examined by log-rank test. Notably, comparison of C-index and AUC values in receiver operating characteristic analysis at 5 years showed fewer differences between training and validation cohorts with the Net scoring system than other statistical methods, suggesting minimal overfitting. The Net-based scoring system also successfully predicted prognosis in various independent GEO cohorts with high discriminatory power. In conclusion, the Net-based scoring system showed better discriminative power than previous statistical methods in prognostic prediction for breast cancer patients. This new system will mark a new era in prognosis prediction for cancer patients.

Prognostic value of microRNAs in osteosarcoma: A meta-analysis.

BACKGROUND: Osteosarcoma is the most common primary bone malignancy. We meta-analyzed the prognostic value of altered miRNAs in patients with osteosarcoma. METHODS: Sources from MEDLINE (from inception to August 2016) and EMBASE (from inception to August 2016) were searched. Studies of osteosarcoma with results of miRNA and studies that reported survival data were included and two authors performed the data extraction independently. Any discrepancies were resolved by a consensus. The outcome was overall survival and event-free survival assessed using hazard ratios (HRs). RESULTS: After reviewing the full text of 65 articles, 25 studies including 2,278 patients were eligible in this study. The pooled HR for deaths was 1.40 (95% confidence interval [CI] 1.01-1.94, p=0.04) with random-effects model (χ2=113.08, p<0.00001, I2=79%) for patients of osteosarcoma with lower expression of miRNA. However, the pooled HR for events was not significant (HR 0.97, 0.63-1.48, p=0.87, χ2=72.65, p<0.00001, I2=79%). In pathway analysis of miRNAs, miRNA449a, 199-5p, 542-5p have common target genes. CONCLUSIONS: Expression level of miRNA in patients of osteosarcoma is important as a prognostic factor.

Virtual Preoperative Simulation for Excision of Spinal Tumors: Surgeon Processing of Medical Computer-Assisted Design Software.

As medical computer-aided design (CAD) has improved, virtual 3-dimensional medical images have been gaining more easily without any special practice. These images can be applied to various clinical fields. This article illustrates virtual preoperative simulation for excision of spinal tumors using medical CAD software. The software was used directly by the surgeon. The process of virtual preoperative simulation for spinal tumor surgery was found to be not inordinately complicated. And, virtual simulation was helpful in determining surgical steps as well as understanding the surgical anatomy.

Human adipose tissue-derived mesenchymal stem cells alleviate atopic dermatitis via regulation of B lymphocyte maturation.

Mesenchymal stem cell (MSC) has been applied for the therapy of allergic disorders due to its beneficial immunomodulatory abilities. However, the underlying mechanisms for therapeutic efficacy are reported to be diverse according to the source of cell isolation or the route of administration. We sought to investigate the safety and the efficacy of human adipose tissue-derived MSCs (hAT-MSCs) in mouse atopic dermatitis (AD) model and to determine the distribution of cells after intravenous administration. Murine AD model was established by multiple treatment of Dermatophagoides farinae. AD mice were intravenously infused with hAT-MSCs and monitored for clinical symptoms. The administration of hAT-MSCs reduced the gross and histological signatures of AD, as well as serum IgE level. hAT-MSCs were mostly detected in lung and heart of mice within 3 days after administration and were hardly detectable at 2 weeks. All of mice administered with hAT-MSCs survived until sacrifice and did not demonstrate any adverse events. Co-culture experiments revealed that hAT-MSCs significantly inhibited the proliferation and the maturation of B lymphocytes via cyclooxygenase (COX)-2 signaling. Moreover, mast cell (MC) degranulation was suppressed by hAT-MSC. In conclusion, the intravenous infusion of hAT-MSCs can alleviate AD through the regulation of B cell function.