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Background: Matrix metalloproteinase (MMP)-12 is highly expressed in abdominal aortic aneurysms and its elastolytic function has been implicated in the pathogenesis. This concept is challenged, however, by conflicting data. Here, we sought to revisit the role of MMP-12 in abdominal aortic aneurysm. Methods: Apoe -/- and Mmp12 -/- / Apoe -/- mice were infused with Ang II (angiotensin). Expression of neutrophil extracellular traps (NETs) markers and complement component 3 (C3) levels were evaluated by immunostaining in aortas of surviving animals. Plasma complement components were analyzed by immunoassay. The effects of a complement inhibitor, IgG-FH 1-5 (factor H-immunoglobulin G), and macrophage-specific MMP-12 deficiency on adverse aortic remodeling and death from rupture in Ang II–infused mice were determined. Results: Unexpectedly, death from aortic rupture was significantly higher in Mmp12 -/- / Apoe -/- mice. This associated with more neutrophils, citrullinated histone H3 and neutrophil elastase, markers of NETs, and C3 levels in Mmp12 -/- aortas. These findings were recapitulated in additional models of abdominal aortic aneurysm. MMP-12 deficiency also led to more pronounced elastic laminae degradation and reduced collagen integrity. Higher plasma C5a in Mmp12 -/- mice pointed to complement overactivation. Treatment with IgG-FH 1-5 decreased aortic wall NETosis and reduced adverse aortic remodeling and death from rupture in Ang II–infused Mmp12 -/- mice. Finally, macrophage-specific MMP-12 deficiency recapitulated the effects of global MMP-12 deficiency on complement deposition and NETosis, as well as adverse aortic remodeling and death from rupture in Ang II–infused mice. Conclusions: An MMP-12 deficiency/complement activation/NETosis pathway compromises aortic integrity, which predisposes to adverse vascular remodeling and abdominal aortic aneurysm rupture. Considering these new findings, the role of macrophage MMP-12 in vascular homeostasis demands re-evaluation of MMP-12 function in diverse settings.

A recommender system (RS) refers to an agent that recommends items that are suitable for users, and it is implemented through collaborative filtering (CF). CF has a limitation in improving the accuracy of recommendations based on matrix factorization (MF). Therefore, a new method is required for analyzing preference patterns, which could not be derived by existing studies. This study aimed at solving the existing problems through bias analysis. By analyzing users’ and items’ biases of user preferences, the bias-based predictor (BBP) was developed and shown to outperform memory-based CF. In this paper, in order to enhance BBP, multiple bias analysis (MBA) was proposed to efficiently reflect the decision-making in real world. The experimental results using movie data revealed that MBA enhanced BBP accuracy, and that the hybrid models outperformed MF and SVD++. Based on this result, MBA is expected to improve performance when used as a system in related studies and provide useful knowledge in any areas that need features that can represent users.

In this paper we address the constrained longest common subsequence problem. Given two sequences $X$, $Y$ and a constrained sequence $P$, a sequence $Z$ is a constrained longest common subsequence for $X$ and $Y$ with respect to $P$ if $Z$ is the longest subsequence of $X$ and $Y$ such that $P$ is a subsequence of $Z$. Recently, Tsai \cite{Tsai} proposed an $O(n^2 \cdot m^2 \cdot r)$ time algorithm to solve this problem using dynamic programming technique, where $n$, $m$ and $r$ are the lengths of $X$, $Y$ and $P$, respectively. In this paper, we present a simple algorithm to solve the constrained longest common subsequence problem in $O(n \cdot m \cdot r)$ time and show that the constrained longest common subsequence problem is equivalent to a special case of the constrained multiple sequence alignment problem which can also be solved., Comment: https://doi.org/10.1016/j.ipl.2004.02.008

Recanalization of a completely occluded vertebral artery, which involves ruptured vertebral dissecting aneurysm, to a normal configuration is rare. Here we report the case of a recanalized vertebral artery dissecting aneurysm in a 51-year-old woman that was treated using endovascular trapping and the right vertebral artery was completely occluded. Six months after the procedure, transfemoral cerebral artery angiography showed a normal configuration of the antegrade recanalized vertebral artery. We also suggest three possible mechanisms for the phenomenon of antegrade recanalization, of which we consider the water-hammer effect mechanism to be the most probable. Endovascular trapping, regardless of the presence of a true or false lumen, is capable of providing promising results and good prognosis through antegrade revascularization or complete occlusion. Keywords: Recanalization, Vertebral artery dissecting aneurysm, Endovascular trapping, Aneurysmal Subarachnoid Hemorrhage

Cancer stem cells (CSCs), defined by CD133 expression, harbor heterogeneous subpopulations of cells, including endothelial progenitor cells (EPCs). This study aimed to investigate whether a subpopulation of CSCs could affect the radiographic characteristics of glioblastoma. Tissue samples from 10 patients newly diagnosed with glioblastoma were selected according to the radiographic characteristics of their tumors. The patients were divided into two groups based on preoperative magnetic resonance imaging demonstrating contrast enhancement, necrosis and infiltrative patterns: the enhancement/necrosis group (E/N, n=5) and the non-enhancement/infiltration group (NE/I, n=5). Flow cytometry was used to assess the CSCs while immunohistochemistry was used to study microvessel density and the proliferation index. The EPC (CD34+/CD133+) fraction in CSCs (CD133+) was larger in the NE/I group. However, there was little difference in the angiogenic activity assessed using microvessel density between the two groups. The proliferation index (assessed using the antibody Ki-67) was higher in the E/N group and was negatively correlated with the EPC fraction. The non-EPC (CD34-/CD133+) fraction is a major factor responsible for radiographic characteristics of contrast enhancement, thus establishing an association between a subpopulation fraction of CSCs and radiographic characteristics in glioblastoma. Therefore, the simple non-invasive assessment of studying contrast enhancement lesions in glioblastomas may be used to estimate CSC subpopulations.

Background Coil protrusion occasionally occurs during embolization and can lead to thromboembolic complications. We aimed to evaluate the efficacy of rescue stenting procedures with a low-profile stent system (LVIS Jr.) for treating ruptured intracranial aneurysms during complicated coil embolization. Methods We performed a retrospective review to identify patients who had subarachnoid hemorrhage and were treated with LVIS Jr. stent rescue therapy. We enrolled 15 patients with intracranial aneurysms and evaluated the technical success and immediate postprocedural clinical and angiographic outcomes. Results All 15 patients underwent successful rescue-stent treatment, and no thrombotic or hemorrhagic complications occurred. Immediate postprocedural angiography revealed complete aneurysm occlusion in 40% (6/15) of the patients, whereas 60% (9) of the patients had a residual neck. Among the 12 patients who underwent follow-up angiography, 10 (83.3%) patients had complete aneurysm occlusion, 1 (8.3%) had a residual neck, and 1 (8.3%) showed an increase in the filling status of the aneurysm. There were no thrombotic complications during the follow-up period. Conclusions Our findings indicate that LVIS Jr. stent rescue therapy is clinically useful for handling coil protrusion during the embolization of ruptured intracranial aneurysms.

A recommender system predicts the future preference of a set of items for a user by computing the similarity between users or items, and recommends the top items based on the prediction. Collaborative filtering, the most popular approach to build recommender systems, has been successfully employed in many commercial and non-commercial applications but has reached the limit of performance growth. A novel way to predict user preferences is needed to overcome this problem. Bias-based predictor (BBP) is a prediction model for recommender systems that assumes that bias and preference are highly correlated. In predictive models, bias generally means the intercept where our line intercepts the y-axis, offsetting all predictions we make. Users’ preference ratings are likely to be influenced by biases in many different aspects. This implies that bias can play more significant roles in preference prediction, rather than simply intercepting the y-axis. This paper proposes a prediction model for recommender systems that takes into account bias in multiple aspects. The proposed model called multi-label bias-based predictor (MLBBP) extends the conventional BBP to allow for a more in-depth analysis of bias. Through experiments with movie data, it was demonstrated that MLBBP performs better than BBP. The trained MLBPP model produces numerical data that can explain why a specific item is recommended to a user.

Traumatic basal ganglia hemorrhage (TBGH) is a rare presentation of head injuries. Bilateral lesions are extremely rare. The pathophysiologic mechanism of bilateral TBGH seems to be the same as diffuse axonal injury. However, limited information about childhood bilateral TBGH is available in the literature. We report the case of a child with bilateral TBGH treated with stereotactic aspiration of hemorrhage and periodic urokinase irrigation.

Collaborative filtering (CF), a technique used by recommendation systems, predicts and recommends items (information, products or services) that the user might like. Amazon.com's recommender system is one of the most famous examples of CF. Recommendation systems are popular in both commercial and research sectors, and they are applied in a variety of applications such as movies, music, books, social connections and venues. In particular, movie recommendation systems produce personal recommendations for movies. Existing CF algorithms employed in movie recommendation systems predict the unknown rating of a given user for a movie using only the ratings (i.e., preferences) of other like-minded users who have seen the movie. In such approaches, there exist certain limits in improving the accuracy of recommendation systems. This paper proposes an algorithm for movie recommendation that exploits the genre of the movie to enhance the accuracy of rating predictions. The proposed algorithm 1) numerically measures the correlation between movie genres using movie rating information; 2) classifies movies using the genre correlations and generates a list of recommended movies for the target user with the classified movies; and finally 3) predicts the ratings of the movies in the list using traditional CF algorithms. The experimental results show that the proposed algorithm yields higher accuracy in movie rating predictions than existing movie recommendation algorithms.

Background The Guideline Working Group of the Korean Society for Neuro-Oncology (KSNO) conducted a nationwide questionnaire survey for diverse queries faced in the treatment of brain tumors. As part I of the survey, the aim of this study is to evaluate national patterns of clinical practice about antiepileptic drug (AED) and steroid usage for management of brain tumors. Methods A web-based survey was sent to all members of the KSNO by email. The survey included 9 questions of AED usage and 5 questions of steroid usage for brain tumor patients. All questions were developed by consensus of the Guideline Working Group. Results The overall response rate was 12.8% (54/423). Regarding AED usage, the majority of respondents (95.2%) routinely prescribed prophylactic AEDs for patients with seizure at the peri/postoperative period. However, as many as 72.8% of respondents prescribed AED routinely for seizure-naïve patients, and others prescribed AED as the case may be. The duration of AED prophylaxis showed wide variance according to the epilepsy status and the location of tumor. Levetiracetam (82.9%) was the most preferred AED for epilepsy prophylaxis. Regarding steroid usage, 90.5% of respondents use steroids in perioperative period, including 34.2% of them as a routine manner. Presence of peritumoral edema (90.9%) was considered as the most important factor determining steroid usage followed by degree of clinical symptoms (60.6%). More than half of respondents (51.2%) replied to discontinue the steroids within a week after surgery if there are no specific medical conditions, while 7.3% preferred slow tapering up to a month after surgery. Conclusion The survey demonstrated the prevailing practice patterns on AED and steroid usage in neuro-oncologic field among members of the KSNO. This information provides a point of reference for establishing a practical guideline in the management of brain tumor patients.

// Ja Eun Kim 1,* , Hye Rim Cho 2,* , Wen Jun Xu 3,* , Ji Young Kim 1 , Sung Kwon Kim 4 , Seung-Ki Kim 1,5 , Sung-Hye Park 6 , Hyeonjin Kim 2 , Se-Hoon Lee 7 , Seung Hong Choi 2 , Sunghyouk Park 3 and Chul-Kee Park 1 1 Department of Neurosurgery, Seoul National University College of Medicine, Seoul National University Hospital, Jongno-gu, Seoul, Korea 2 Department of Radiology, Seoul National University College of Medicine, Seoul National University Hospital, Jongno-gu, Seoul, Korea 3 College of Pharmacy, Natural Product Research Institute, Seoul National University, Sillim-dong, Gwanak-gu, Seoul, Korea 4 Department of Neurosurgery, Gyeongsang National University School of Medicine, Gyeongsang National University Hospital, Jinju, Korea 5 Division of Pediatric Neurosurgery, Seoul National University Children’s Hospital, Jongno-gu, Seoul, Korea 6 Department of Pathology, Seoul National University College of Medicine, Seoul National University Hospital, Jongno-gu, Seoul, Korea 7 Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea * These authors have contributed equally to this work Correspondence to: Chul-Kee Park, email: // Sunghyouk Park, email: // Seung Hong Choi, email: // Keywords : brain tumors, oncology, 5-ALA, fluorescence, IDH1, glioma, NADPH Received : March 01, 2015 Accepted : April 22, 2015 Published : May 10, 2015 Abstract Fluorescence-guided surgery using 5-aminolevulinic acid (5-ALA) has become the main treatment modality in malignant gliomas. However unlike glioblastomas, there are inconsistent result about fluorescence status in WHO grade III gliomas. Here, we show that mutational status of IDH1 is linked to 5-ALA fluorescence. Using genetically engineered malignant glioma cells harboring wild type (U87MG-IDH1 WT ) or mutant (U87MG-IDH1 R132H ) IDH1 , we demonstrated a lag in 5-ALA metabolism and accumulation of protoporphyrin IX (PpIX) in U87MG-IDH1 R132H cells. Next, we used liquid chromatography–mass spectrometry (LC-MS) to screen for tricarboxylic acid (TCA) cycle-related metabolite changes caused by 5-ALA exposure. We observed low baseline levels of NADPH, an essential cofactor for the rate-limiting step of heme degradation, in U87MG-IDH1 R132H cells. High levels of NADPH are required to metabolize excessive 5-ALA, giving a plausible reason for the temporarily enhanced 5-ALA fluorescence in mutant IDH1 cells. This hypothesis was supported by the results of metabolic screening in human malignant glioma samples. In conclusion, we have discovered a relationship between enhanced 5-ALA fluorescence and IDH1 mutations in WHO grade III gliomas. Low levels of NADPH in tumors with mutated IDH1 is responsible for the enhanced fluorescence.

In recent years, research on collaborative filtering-based recommendation systems emphasized the accuracy of rating predictions, and this has led to an increase in computation time. As a result, such systems have divergeded from the original purpose of making quick recommendations. In this paper, we propose a recommendation algorithm that uses a Preference Difference Metric to reduce the computation time and to maintain adequate performance. The system recommends items according to their preference classification.

SUMMARY Given an edge-weighted tree with n vertices and a positive integer L, the length-constrained maximum-density path problem is to find a path of length at least L with maximum density in the tree. The density of a path is the sum of the weights of the edges in the path divided by the number of edges in the path. We present an O(n) time algorithm for the problem. The previously known algorithms run in O(nL )o rO(nlogn) time.

Fluorescence-guided surgery using 5-aminolevulinic acid (5-ALA) is now a widely-used modality for glioblastoma (GBM) treatment. However, intratumoral heterogeneity of fluorescence intensity may reflect different onco-metabolic programs. Here, we investigated the metabolic mechanism underlying the heterogeneity of 5-ALA fluorescence in GBM. Using an in-house developed fluorescence quantification system for tumor tissues, we collected 3 types of GBM tissues on the basis of their fluorescence intensity, which was characterized as strong, weak, and none. Expression profiling by RNA-sequencing revealed 77 genes with a proportional relationship and 509 genes with an inverse relationship between gene expression and fluorescence intensity. Functional analysis and in vitro experiments confirmed glutaminase 2 (GLS2) as a key gene associated with the fluorescence heterogeneity. Subsequent metabolite profiling discovered that insufficient NADPH due to GLS2 underexpression was responsible for the delayed metabolism of 5-ALA and accumulation of protoporphyrin IX (PpIX) in the high fluorescence area. The expression level of GLS2 and related NADPH production capacity is associated with the regional heterogeneity of 5-ALA fluorescence in GBM.

Background To evaluate the clinical impact of fluorescence-guided surgery (FGS) in glioblastoma, we analyzed the clinical data of 80 consecutive patients operated on by a single surgeon with or without 5-aminolevulinic acid (5-ALA). Methods We compared 3-dimensional volumetric extent of resection and clinical outcomes between 40 consecutive patients undergoing resection using a white-light (WL) microscope and 40 subsequent consecutive patients undergoing resection using FGS with 5ALA. Results By introducing FGS, there was a significant difference in the mean volumetric extent of the resection rate of T1-enhancing lesions (84.7% in the white-light group and 97.0% in the 5-ALA group, P = .002). The complete resection rate was improved from 43% to 80%, and the proportion of resections that were Conclusions The present study adds practical evidence of the clinical impact of 5-ALA FGS on glioblastomas from the surgeon's standpoint.

With the advent of the Internet, the types and amount of information one can access have increased dramatically. In today's overwhelming information environment, recommendation systems that quickly analyze large amounts of available information and help users find items of interest are increasingly needed. This paper proposes an improvement of an existing preference prediction algorithm to increase the accuracy of recommendation systems. In a recommendation system, prediction of items preferred by users is based on their ratings. However, individual users with the same degree of satisfaction to an item may give different ratings to the item. We intend to make more precise preference prediction by perceiving differences in users' rating dispositions. The proposed method consists of two processes of perceiving users' rating dispositions with clustering and of performing rating normalization according to such rating dispositions. The experimental results show that our method yields higher performance than ordinary collaborative filtering approach.