Identification of schizophrenia by applying interpretable radiomics modeling with structural magnetic resonance imaging of the cerebellum.

AIMS: The cerebellum is involved in higher-order mental processing as well as sensorimotor functions. Although structural abnormalities in the cerebellum have been demonstrated in schizophrenia, neuroimaging techniques are not yet applicable to identify them given the lack of biomarkers. We aimed to develop a robust diagnostic model for schizophrenia using radiomic features from T1-weighted magnetic resonance imaging (T1-MRI) of the cerebellum. METHODS: A total of 336 participants (174 schizophrenia; 162 healthy controls [HCs]) were allocated to training (122 schizophrenia; 115 HCs) and test (52 schizophrenia; 47 HCs) cohorts. We obtained 2568 radiomic features from T1-MRI of the cerebellar subregions. After feature selection, a light gradient boosting machine classifier was trained. The discrimination and calibration of the model were evaluated. SHapley Additive exPlanations (SHAP) was applied to determine model interpretability. RESULTS: We identified 17 radiomic features to differentiate participants with schizophrenia from HCs. In the test cohort, the radiomics model had an area under the curve, accuracy, sensitivity, and specificity of 0.89 (95% confidence interval: 0.82-0.95), 78.8%, 88.5%, and 75.4%, respectively. The model explanation by SHAP suggested that the second-order size zone non-uniformity feature from the right lobule IX and first-order energy feature from the right lobules V and VI were highly associated with the risk of schizophrenia. CONCLUSION: The radiomics model focused on the cerebellum demonstrates robustness in diagnosing schizophrenia. Our results suggest that microcircuit disruption in the posterior cerebellum is a disease-defining feature of schizophrenia, and radiomics modeling has potential for supporting biomarker-based decision-making in clinical practice.

Dynamic contrast-enhanced MRI radiomics model predicts epidermal growth factor receptor amplification in glioblastoma, IDH-wildtype.

PURPOSE: To develop and validate a dynamic contrast-enhanced (DCE) MRI-based radiomics model to predict epidermal growth factor receptor (EGFR) amplification in patients with glioblastoma, isocitrate dehydrogenase (IDH) wildtype. METHODS: Patients with pathologically confirmed glioblastoma, IDH wildtype, from January 2015 to December 2020, with an EGFR amplification status, were included. Patients who did not undergo DCE or conventional brain MRI were excluded. Patients were categorized into training and test sets by a ratio of 7:3. DCE MRI data were used to generate volume transfer constant (Ktrans) and extracellular volume fraction (Ve) maps. Ktrans, Ve, and conventional MRI were then used to extract the radiomics features, from which the prediction models for EGFR amplification status were developed and validated. RESULTS: A total of 190 patients (mean age, 59.9; male, 55.3%), divided into training (n = 133) and test (n = 57) sets, were enrolled. In the test set, the radiomics model using the Ktrans map exhibited the highest area under the receiver operating characteristic curve (AUROC), 0.80 (95% confidence interval [CI], 0.65-0.95). The AUROC for the Ve map-based and conventional MRI-based models were 0.74 (95% CI, 0.58-0.90) and 0.76 (95% CI, 0.61-0.91). CONCLUSION: The DCE MRI-based radiomics model that predicts EGFR amplification in glioblastoma, IDH wildtype, was developed and validated. The MRI-based radiomics model using the Ktrans map has higher AUROC than conventional MRI.

Blockchain-Based Data Access Control and Key Agreement System in IoT Environment.

Recently, with the increasing application of the Internet of Things (IoT), various IoT environments such as smart factories, smart homes, and smart grids are being generated. In the IoT environment, a lot of data are generated in real time, and the generated IoT data can be used as source data for various services such as artificial intelligence, remote medical care, and finance, and can also be used for purposes such as electricity bill generation. Therefore, data access control is required to grant access rights to various data users in the IoT environment who need such IoT data. In addition, IoT data contain sensitive information such as personal information, so privacy protection is also essential. Ciphertext-policy attribute-based encryption (CP-ABE) technology has been utilized to address these requirements. Furthermore, system structures applying blockchains with CP-ABE are being studied to prevent bottlenecks and single failures of cloud servers, as well as to support data auditing. However, these systems do not stipulate authentication and key agreement to ensure the security of the data transmission process and data outsourcing. Accordingly, we propose a data access control and key agreement scheme using CP-ABE to ensure data security in a blockchain-based system. In addition, we propose a system that can provide data nonrepudiation, data accountability, and data verification functions by utilizing blockchains. Both formal and informal security verifications are performed to demonstrate the security of the proposed system. We also compare the security, functional aspects, and computational and communication costs of previous systems. Furthermore, we perform cryptographic calculations to analyze the system in practical terms. As a result, our proposed protocol is safer against attacks such as guessing attacks and tracing attacks than other protocols, and can provide mutual authentication and key agreement functions. In addition, the proposed protocol is more efficient than other protocols, so it can be applied to practical IoT environments.

iAKA-CIoT: An Improved Authentication and Key Agreement Scheme for Cloud Enabled Internet of Things Using Physical Unclonable Function.

The Internet of Things (IoT) with cloud services are important functionalities in the latest IoT systems for providing various convenient services. These cloud-enabled IoT environments collect, analyze, and monitor surrounding data, resulting in the most effective handling of large amounts of heterogeneous data. In these environments, secure authentication with a key agreement mechanism is essential to ensure user and data privacy when transmitting data between the cloud server and IoT nodes. In this study, we prove that the previous scheme contains various security threats, and hence cannot guarantee essential security requirements. To overcome these security threats, we propose an improved authentication and key agreement scheme for cloud-enabled IoT using PUF. Furthermore, we evaluate its security by performing informal, formal (mathematical), and simulation analyses using the AVISPA tool and ROR model. The performance and security properties of our scheme are subsequently compared with those of other related schemes. The comparison confirms that our scheme is suitable for a practical cloud-enabled IoT environment because it provides a superior security level and is more efficient than contemporary schemes.

Laser asymmetric ablation method to improve corneal shape.

This study aims to assess whether central-symmetric corneal thickness reduces off-centered corneal shift caused by intraocular pressure (IOP). In this retrospective study, 122 healthy eyes of 62 presbyopic patients, mostly myopic, were divided into two groups. Two distinct asymmetric corneal ablations were applied in peripheral presbyopia correction to produce central-symmetric corneal thickness, which reduces the off-centered corneal shift by utilizing intraocular pressure. The first method used a 90° angled combination in group 1 and the second method used a 45° angled combination in group 2. Target refraction was spherical equivalent of - 1D. Self-developed image processing algorithm analyzed the change in thickness and the posterior cone, and obtained two factors: central symmetry (f) and visual axis deviation (d), from each eye's pre and postoperative maps of Orbscan II. UDVA and UNVA were also analyzed. In both groups, mean SE was about - 1D and there was no significant difference in UDVA. UNVA was better in group 2 than group 1. Only in group 2, corneal thickness and posterior cone became central-symmetric and the posterior corneal apex point relocated towards the visual axis. The p values were 0.03, 0.04, and 0.03, respectively. This is the first study to control corneal shape by utilizing the interaction between intraocular pressure and corneal thickness. Only group 2 was applied with asymmetric corneal ablation created by the 45° angled combination of semi-cylindrical ablation patterns, and intraocular pressure contributed significantly to reduce the off-centered corneal shift and reshaped the posterior corneal cone to the center.

A Secure Lightweight Three-Factor Authentication Scheme for IoT in Cloud Computing Environment.

With the development of cloud computing and communication technology, users can access the internet of things (IoT) services provided in various environments, including smart home, smart factory, and smart healthcare. However, a user is insecure various types of attacks, because sensitive information is often transmitted via an open channel. Therefore, secure authentication schemes are essential to provide IoT services for legal users. In 2019, Pelaez et al. presented a lightweight IoT-based authentication scheme in cloud computing environment. However, we prove that Pelaez et al.'s scheme cannot prevent various types of attacks such as impersonation, session key disclosure, and replay attacks and cannot provide mutual authentication and anonymity. In this paper, we present a secure and lightweight three-factor authentication scheme for IoT in cloud computing environment to resolve these security problems. The proposed scheme can withstand various attacks and provide secure mutual authentication and anonymity by utilizing secret parameters and biometric. We also show that our scheme achieves secure mutual authentication using Burrows-Abadi-Needham logic analysis. Furthermore, we demonstrate that our scheme resists replay and man-in-the-middle attacks usingthe automated validation of internet security protocols and applications (AVISPA) simulation tool. Finally, we compare the performance and the security features of the proposed scheme with some existing schemes. Consequently, we provide better safety and efficiency than related schemes and the proposed scheme is suitable for practical IoT-based cloud computing environment.

Secure Three-Factor Authentication Protocol for Multi-Gateway IoT Environments.

Internet of Things (IoT) environments such as smart homes, smart factories, and smart buildings have become a part of our lives. The services of IoT environments are provided through wireless networks to legal users. However, the wireless network is an open channel, which is insecure to attacks from adversaries such as replay attacks, impersonation attacks, and invasions of privacy. To provide secure IoT services to users, mutual authentication protocols have attracted much attention as consequential security issues, and numerous protocols have been studied. In 2017, Bae et al. presented a smartcard-based two-factor authentication protocol for multi-gateway IoT environments. However, we point out that Bae et al.'s protocol is vulnerable to user impersonation attacks, gateway spoofing attacks, and session key disclosure, and cannot provide a mutual authentication. In addition, we propose a three-factor mutual authentication protocol for multi-gateway IoT environments to resolve these security weaknesses. Then, we use Burrows-Abadi-Needham (BAN) logic to prove that the proposed protocol achieves secure mutual authentication, and we use the Automated Validation of Internet Security Protocols and Applications (AVISPA) tool to analyze a formal security verification. In conclusion, our proposed protocol is secure and applicable in multi-gateway IoT environments.

A Secure Charging System for Electric Vehicles Based on Blockchain.

Smart grids incorporating internet-of-things are emerging solutions to provide a reliable, sustainable and efficient electricity supply, and electric vehicle drivers can access efficient charging services in the smart grid. However, traditional electric vehicle charging systems are vulnerable to distributed denial of service and privileged insider attacks when the central charging server is attacked. The blockchain-based charging systems have been proposed to resolve these problems. In 2018, Huang et al. proposed the electric vehicle charging system using lightning network and smart contract. However, their system has an inefficient charging mechanism and does not guarantee security of key. We propose a secure charging system for electric vehicles based on blockchain to resolve these security flaws. Our charging system ensures the security of key, secure mutual authentication, anonymity, and perfect forward secrecy, and also provides efficient charging. We demonstrate that our proposed system provides secure mutual authentication using Burrows-Abadi-Needham logic and prevents replay and man-in-the-middle attacks using automated validation of internet security protocols and applications simulation tool. Furthermore, we compare computation and communication costs with previous schemes. Therefore, the proposed charging system efficiently applies to practical charging systems for electric vehicles.

Secure Authentication Protocol for Wireless Sensor Networks in Vehicular Communications.

With wireless sensor networks (WSNs), a driver can access various useful information for convenient driving, such as traffic congestion, emergence, vehicle accidents, and speed. However, a driver and traffic manager can be vulnerable to various attacks because such information is transmitted through a public channel. Therefore, secure mutual authentication has become an important security issue, and many authentication schemes have been proposed. In 2017, Mohit et al. proposed an authentication protocol for WSNs in vehicular communications to ensure secure mutual authentication. However, their scheme cannot resist various attacks such as impersonation and trace attacks, and their scheme cannot provide secure mutual authentication, session key security, and anonymity. In this paper, we propose a secure authentication protocol for WSNs in vehicular communications to resolve the security weaknesses of Mohit et al.'s scheme. Our authentication protocol prevents various attacks and achieves secure mutual authentication and anonymity by using dynamic parameters that are changed every session. We prove that our protocol provides secure mutual authentication by using the Burrows⁻Abadi⁻Needham logic, which is a widely accepted formal security analysis. We perform a formal security verification by using the well-known Automated Validation of Internet Security Protocols and Applications tool, which shows that the proposed protocol is safe against replay and man-in-the-middle attacks. We compare the performance and security properties of our protocol with other related schemes. Overall, the proposed protocol provides better security features and a comparable computation cost. Therefore, the proposed protocol can be applied to practical WSNs-based vehicular communications.

Distance-Constraint k-Nearest Neighbor Searching in Mobile Sensor Networks.

The κ-Nearest Neighbors ( κNN) query is an important spatial query in mobile sensor networks. In this work we extend κNN to include a distance constraint, calling it a l-distant κ-nearest-neighbors (l-κNN) query, which finds the κ sensor nodes nearest to a query point that are also at or greater distance from each other. The query results indicate the objects nearest to the area of interest that are scattered from each other by at least distance l. The l-κNN query can be used in most κNN applications for the case of well distributed query results. To process an l-κNN query, we must discover all sets of κNN sensor nodes and then find all pairs of sensor nodes in each set that are separated by at least a distance l. Given the limited battery and computing power of sensor nodes, this l-κNN query processing is problematically expensive in terms of energy consumption. In this paper, we propose a greedy approach for l-κNN query processing in mobile sensor networks. The key idea of the proposed approach is to divide the search space into subspaces whose all sides are l. By selecting κ sensor nodes from the other subspaces near the query point, we guarantee accurate query results for l-κNN. In our experiments, we show that the proposed method exhibits superior performance compared with a post-processing based method using the κNN query in terms of energy efficiency, query latency, and accuracy.

Chylothorax associated with primary membranous nephropathy: a case report.

BACKGROUND: Chylothorax is a state in which pleurisy is induced by chylomicron leakage due to lymphatic injury. Membranous nephropathy (MN) is one of the relatively common glomerular diseases that cause nephrotic syndrome in adults. Chylothorax at the onset of nephrotic syndrome is very rare in adult patients. CASE DESCRIPTION: We report a case of chylothorax associated with primary MN. A 64-year-old man visited the hospital complaining of lower extremity edema and dyspnea for 4 weeks. Laboratory findings showed no azotemia but hypercholesterolemia, hypoalbuminemia, nephrotic-range proteinuria, and microscopic hematuria. Chest and abdominal computed tomography (CT) revealed no ascites, venous thrombosis, or malignancy with the presence of right-side pleurisy. Biochemical analysis of the pleural fluid was consistent with chylothorax. The patient was confirmed to have MN by percutaneous kidney biopsy. An angiotensin receptor blocker, diuretics, and a hypolipidemic agent were prescribed; non-per os, total parenteral nutrition (TPN), and subcutaneous injection of octreotide were added for management of chylothorax. As serum anti-phospholipase receptor 2 antibody (Ab) concentration increased again, immunosuppressive therapy (IST) consisting of alternating monthly cycles of glucocorticoids and oral cyclophosphamide was instituted. With no improvement in chylothorax and deteriorating nutritional status despite 3 weeks of medical therapy, lymphangiography was performed, followed by thoracic duct embolization (TDE). The patient was discharged from the hospital on day 53 with clinical improvement. At 9 months after discharge, clinical remission of primary MN was achieved without recurrence of chylothorax. CONCLUSIONS: Patients with nephrotic syndrome may rarely exhibit refractory chylothorax without chylous ascites, increasing the risk of serious metabolic complications such as severe malnutrition. Therefore, upon confirming chylothorax associated with primary nephrotic syndrome, prompt radiologic intervention for lymphatic leakage must be considered in addition to specific IST.

Development and Testing of a Machine Learning Model Using 18F-Fluorodeoxyglucose PET/CT-Derived Metabolic Parameters to Classify Human Papillomavirus Status in Oropharyngeal Squamous Carcinoma.

OBJECTIVE: To develop and test a machine learning model for classifying human papillomavirus (HPV) status of patients with oropharyngeal squamous cell carcinoma (OPSCC) using 18F-fluorodeoxyglucose (18F-FDG) PET-derived parameters in derived parameters and an appropriate combination of machine learning methods in patients with OPSCC. MATERIALS AND METHODS: This retrospective study enrolled 126 patients (118 male; mean age, 60 years) with newly diagnosed, pathologically confirmed OPSCC, that underwent 18F-FDG PET-computed tomography (CT) between January 2012 and February 2020. Patients were randomly assigned to training and internal validation sets in a 7:3 ratio. An external test set of 19 patients (16 male; mean age, 65.3 years) was recruited sequentially from two other tertiary hospitals. Model 1 used only PET parameters, Model 2 used only clinical features, and Model 3 used both PET and clinical parameters. Multiple feature transforms, feature selection, oversampling, and training models are all investigated. The external test set was used to test the three models that performed best in the internal validation set. The values for area under the receiver operating characteristic curve (AUC) were compared between models. RESULTS: In the external test set, ExtraTrees-based Model 3, which uses two PET-derived parameters and three clinical features, with a combination of MinMaxScaler, mutual information selection, and adaptive synthetic sampling approach, showed the best performance (AUC = 0.78; 95% confidence interval, 0.46-1). Model 3 outperformed Model 1 using PET parameters alone (AUC = 0.48, p = 0.047) and Model 2 using clinical parameters alone (AUC = 0.52, p = 0.142) in predicting HPV status. CONCLUSION: Using oversampling and mutual information selection, an ExtraTree-based HPV status classifier was developed by combining metabolic parameters derived from 18F-FDG PET/CT and clinical parameters in OPSCC, which exhibited higher performance than the models using either PET or clinical parameters alone.

Development and Validation of MRI-Based Radiomics Models for Diagnosing Juvenile Myoclonic Epilepsy.

OBJECTIVE: Radiomic modeling using multiple regions of interest in MRI of the brain to diagnose juvenile myoclonic epilepsy (JME) has not yet been investigated. This study aimed to develop and validate radiomics prediction models to distinguish patients with JME from healthy controls (HCs), and to evaluate the feasibility of a radiomics approach using MRI for diagnosing JME. MATERIALS AND METHODS: A total of 97 JME patients (25.6 ± 8.5 years; female, 45.5%) and 32 HCs (28.9 ± 11.4 years; female, 50.0%) were randomly split (7:3 ratio) into a training (n = 90) and a test set (n = 39) group. Radiomic features were extracted from 22 regions of interest in the brain using the T1-weighted MRI based on clinical evidence. Predictive models were trained using seven modeling methods, including a light gradient boosting machine, support vector classifier, random forest, logistic regression, extreme gradient boosting, gradient boosting machine, and decision tree, with radiomics features in the training set. The performance of the models was validated and compared to the test set. The model with the highest area under the receiver operating curve (AUROC) was chosen, and important features in the model were identified. RESULTS: The seven tested radiomics models, including light gradient boosting machine, support vector classifier, random forest, logistic regression, extreme gradient boosting, gradient boosting machine, and decision tree, showed AUROC values of 0.817, 0.807, 0.783, 0.779, 0.767, 0.762, and 0.672, respectively. The light gradient boosting machine with the highest AUROC, albeit without statistically significant differences from the other models in pairwise comparisons, had accuracy, precision, recall, and F1 scores of 0.795, 0.818, 0.931, and 0.871, respectively. Radiomic features, including the putamen and ventral diencephalon, were ranked as the most important for suggesting JME. CONCLUSION: Radiomic models using MRI were able to differentiate JME from HCs.

A sphingosine 1-phosphate 1 receptor agonist modulates brain death-induced neurogenic pulmonary injury.

Lung transplantation remains the only viable therapy for patients with end-stage lung disease. However, the full utilization of this strategy is severely compromised by a lack of donor lung availability. The vast majority of donor lungs available for transplantation are from individuals after brain death (BD). Unfortunately, the early autonomic storm that accompanies BD often results in neurogenic pulmonary edema (NPE), producing varying degrees of lung injury or leading to primary graft dysfunction after transplantation. We demonstrated that sphingosine 1-phosphate (S1P)/analogues, which are major barrier-enhancing agents, reduce vascular permeability via the S1P1 receptor, S1PR1. Because primary lung graft dysfunction is induced by lung vascular endothelial cell barrier dysfunction, we hypothesized that the S1PR1 agonist, SEW-2871, may attenuate NPE when administered to the donor shortly after BD. Significant lung injury was observed after BD, with increases of approximately 60% in bronchoalveolar lavage (BAL) total protein, cell counts, and lung tissue wet/dry (W/D) weight ratios. In contrast, rats receiving SEW-2871 (0.1 mg/kg) 15 minutes after BD and assessed after 4 hours exhibited significant lung protection (∼ 50% reduction, P = 0.01), as reflected by reduced BAL protein/albumin, cytokines, cellularity, and lung tissue wet/dry weight ratio. Microarray analysis at 4 hours revealed a global impact of both BD and SEW on lung gene expression, with a differential gene expression of enriched immune-response/inflammation pathways across all groups. Overall, SEW served to attenuate the BD-mediated up-regulation of gene expression. Two potential biomarkers, TNF and chemokine CC motif receptor-like 2, exhibited gene array dysregulation. We conclude that SEW-2871 significantly attenuates BD-induced lung injury, and may serve as a potential candidate to improve human donor availability.

Preoperative Risk Factors for Pathologic N2 Metastasis in Positron Emission Tomography-Computed Tomography-Diagnosed N0-1 Non-Small Cell Lung Cancer.

BACKGROUND: Accurate mediastinal lymph node staging is vital for the optimal therapy and prognostication of patients with lung cancer. This study aimed to determine the preoperative risk factors for pN2 disease, as well as its incidence and long-term outcomes, in patients with clinical N0-1 non-small cell lung cancer. METHODS: We retrospectively analyzed patients who were treated surgically for primary non-small cell lung cancer from November 2005 to December 2014. Patients staged as clinical N0-1 via chest computed tomography (CT) and positron emission tomography (PET)-CT were divided into two groups (pN0-1 and pN2) and compared. RESULTS: In a univariate analysis, the significant preoperative risk factors for pN2 included a large tumor size (p=0.083), high maximum standard uptake value on PET (p<0.001), and central location of the tumor (p<0.001). In a multivariate analysis, central location of the tumor (p<0.001) remained a significant preoperative risk factor for pN2 status. The 5-year overall survival rates were 75% and 22.9% in the pN0-1 and pN2 groups, respectively, and 50% and 78.2% in the patients with centrally located and peripherally located tumors, respectively. In a Cox proportional hazard model, central location of the tumor increased the risk of death by 3.4-fold (p<0.001). CONCLUSION: More invasive procedures should be considered when pre-operative risk factors are identified in order to improve the efficacy of diagnostic and therapeutic plans and, consequently, the patient's prognosis.

The treatment of post-traumatic facial skin defect with artificial dermis.

BACKGROUND: When a skin defect occurs, clinicians must work to restore the original skin quality as soon as possible. Accordingly, an artificial dermis can be used to supplement the wound and prevent severe scar contracture formation. The Terudermis is an artificial dermis that is simple and easy to use. We investigated the effectiveness of the Terudermis in the treatment of facial skin defects by analyzing previous relevant cases treated in our institution. METHODS: We retrospectively examined 143 patients who were treated with the Terudermis graft in facial skin defect at Dong Kang General Hospital in 2015 and 2016. The patients' age, sex and location, wound size, complications were analyzed. In addition, the patients were asked to complete a self-satisfaction questionnaire after 18 months from the completion of treatment. The results were compared with that of autologous full-thickness skin graft (FTSG) and split-thickness skin graft (STSG) patients in same period. RESULTS: The mean self-satisfaction scores evaluated by patients were 4.1±1.0, 4.0±1.3 and 3.5±1.8 for the Terudermis graft, FTSG and STSG patients, respectively. With respect to complications, there were fewer incidences of hematoma, partial skin loss and complete skin loss in the Terudermis graft patients. CONCLUSION: In the present study, the Terudermis, when used to treat post-traumatic facial skin defects, is a good alternative option to obtain satisfactory aesthetic outcomes. Also, the Terudermis grafting is a simple and easy treatment method to perform.

The Algorithm-Oriented Management of Nasal Bone Fracture according to Stranc's Classification System.

BACKGROUND: Nasal bone fracture is one of the most common facial bone fracture types, and the surgical results exert a strong influence on the facial contour and patient satisfaction. Preventing secondary deformity and restoring the original bone state are the major goals of surgeons managing nasal bone fracture patients. In this study, a treatment algorithm was established by applying the modified open reduction technique and postoperative care for several years. METHODS: This article is a retrospective chart review of 417 patients who had been received surgical treatment from 2014 to 2015. Using prepared questionnaires and visual analogue scale, several components (postoperative nasal contour; degree of pain; minor complications like dry mouth, sleep disturbance, swallowing difficulty, conversation difficulty, and headache; and degree of patient satisfaction) were evaluated. RESULTS: The average scores for the postoperative nasal contour given by three experts, and the degree of patient satisfaction, were within the "satisfied" (4) to "very satisfied" (5) range (4.5, 4.6, 4.5, and 4.2, respectively). The postoperative degree of pain was sufficiently low that the patients needed only the minimum dose of painkiller. The scores for the minor complications (dry mouth, sleep disturbance, swallowing difficulty, conversation difficulty, headache) were relatively low (36.4, 40.8, 65.2, 32.3, and 34 out of the maximum score of 100, respectively). CONCLUSION: Satisfactory results were obtained through the algorithm-oriented management of nasal bone fracture. The degree of postoperative pain and minor complications were considerably low, and the degree of satisfaction with the nasal contour was high.

Epithelial-mesenchymal transition in patients of pulmonary adenocarcinoma: correlation with cancer stem cell markers and prognosis.

Adenocarcinoma is the most common histologic type of non-small cell lung carcinomas. The existence of lung cancer stem cells (CSCs) and epithelial-mesenchymal transition (EMT) in human tissue is controversy. The aim of this study is to investigate the expression and clinical significance of CSCs and EMT markers and evaluate the correlation between the two in lung adenocarcinoma. A total of 97 cases comprise the tissue microarray from surgical resection for primary lung adenocarcinoma. Immunohistochemistry for ALDH1 and CD44 as CSC markers and E-cadherin, vimentin, fibronectin, SMA as EMT markers was performed. High ALDH1A1 expression was statistically associated with female gender (P=0.001), smoker (P=0.012), and high pT stages (P=0.046). High CD44 expression was statistically associated with female gender (P=0.008), non-smoker (P=0.000), and no pleural invasion (P=0.039). High expression of ALDH1 was associated with good overall survival (P=0.021). High expression of CD44 was correlated with both good overall survival (P=0.024) and disease-free survival (P=0.000). Vimentin expression was associated with pT stage (P=0.001) and pleural invasion (P=0.028). E-cadherin, fibronectin and SMA were not associated with clinicopathologic correlation and all EMT markers were not correlated with survival of lung adenocarcinoma. CSC markers expression was not related to EMT. Our results showed that the expression of CSCs was associated with a good prognosis in lung adenocarcinoma. The prognostic significance of EMT markers was skeptical in this study. There is a need for more research about CSC, EMT, and the relation between these two in human lung adenocarcinoma.

Successful management of a recurrent primary malignant fibrous histiocytoma of the lung: report of a case.

We describe herein an extremely rare case of a recurrent primary pulmonary malignant fibrous histiocytoma 3 months after operation that occurred in a 55-year-old man who was treated with chemotherapy and radiotherapy successfully. Until now, 36 months later, the patient has shown no evidence of tumor recurrence. The clinical, radiographic, and pathologic features are reported here together with a brief review of the literature.