Brown–Séquard Syndrome after Thoracic Endovascular Aortic Repair for a Stanford Type B Aortic Dissection

Adine J. Klijn,Jennie Heida,Desiree H.C. Burger,Jan M.M. Heyligers,Sjaak Pouwels 대한혈관외과학회 2022 Vascular Specialist International Vol.38 No.2

We present a case of Brown–Séquard syndrome (BSS) after thoracic endovascular aortic repair (TEVAR) to treat Stanford type B aortic dissection. A 49-year-old male presented to the emergency department with acute tearing pain between the scapulae, connected to respiratory movements. Computed tomography showed Stanford type B aortic dissection from the left subclavian artery to the level of the 11th thoracic vertebra. Conservative treatment was initiated with intravenous antihypertensives. However, due to persistent pain and an increase in the aortic diameter with an intramural hematoma, TEVAR was performed. The patient developed symptoms suspicious of spinal cord ischemia postoperatively. A lesion limited to the left-sided spinal cord was observed on magnetic resonance imaging at the level of the 4th to 5th thoracic vertebra. BSS after TEVAR is a rare phenomenon with a fairly good prognosis, depending on the initial injury severity.

Strength and failure analysis of inverse Z joints bonded with Vinylester Atlac 580and Flexo Tix adhesives

Hamit Adin,Aydın Turgut 대한기계학회 2012 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.26 No.11

In this study, the tensile strength and failure loads of the inverse Z joints were analyzed both experimentally and numerically by using two adhesives with different properties under a tensile load. Vinylester Atlac 580 and Flexo Tix were used as adhesives and the joints were prepared with two different composite materials. Initially, the mechanical properties of the adhesives were specified using bulk specimens. Then, the stress analyses were performed using three-dimensional finite element method (3-D FEM) via Ansys (V.10.0.1). The experimental results were compared with the numerical results and they were found quite reasonable. According to the test results, it can be seen that when the adherend thickness is increased, the stress increases as well. The most appropriate value of the adherend thickness is identified as t = 5 mm. Furthermore, it was observed that the lowest failure load was obtained at t = 3 mm the thickness for each specimen.

Performance of growing lambs supplemented with ground licuri (Syagrus coronata)

Daza Adin,Souza Jocely G.,Monnerat Joao Paulo I. S.,Ribeiro Claudio V. D. M. 아세아·태평양축산학회 2021 Animal Bioscience Vol.34 No.6

Objective: The aim of this study was to determine the effect of dietary ground licuri on lamb performance. Methods: Forty male lambs were used in a completely randomized design to test the effects of 0, 5, 10, and 15 g/kg of ground licuri added to diets. The trial lasted for 75 days. Intake, digestibility, physically effective neutral detergent fiber, and chewing activity were estimated. Blood samples were taken on day 45 to determine the concentrations of glucose, urea, nonesterified fatty acids, and triglycerides. Average daily gain (ADG) were determined on the last day of the experimental trial. Results: Licuri inclusion markedly increased dietary neutral detergent fiber and ether extract (EE) content, but it decreased dry matter (DM) intake. However, the intake and digestibility of EE linearly increased. The ADG decreased linearly (p<0.05) with licuri inclusion. Licuri had no effect (p>0.05) on the concentrations of blood metabolites; however, blood urea increased (p<0.05), while serum glucose decreased (p<0.05). Conclusion: The physically effective fiber of ground licuri is similar to Tyfton hay and licuri inclusion decreases lamb performance due to a decreased in DM intake. Objective: The aim of this study was to determine the effect of dietary ground licuri on lamb performance.Methods: Forty male lambs were used in a completely randomized design to test the effects of 0, 5, 10, and 15 g/kg of ground licuri added to diets. The trial lasted for 75 days. Intake, digestibility, physically effective neutral detergent fiber, and chewing activity were estimated. Blood samples were taken on day 45 to determine the concentrations of glucose, urea, nonesterified fatty acids, and triglycerides. Average daily gain (ADG) were determined on the last day of the experimental trial.Results: Licuri inclusion markedly increased dietary neutral detergent fiber and ether extract (EE) content, but it decreased dry matter (DM) intake. However, the intake and digestibility of EE linearly increased. The ADG decreased linearly (p<0.05) with licuri inclusion. Licuri had no effect (p>0.05) on the concentrations of blood metabolites; however, blood urea increased (p<0.05), while serum glucose decreased (p<0.05).Conclusion: The physically effective fiber of ground licuri is similar to Tyfton hay and licuri inclusion decreases lamb performance due to a decreased in DM intake.

Ipsilateral Malignant Axillary Lymphadenopathy and Contralateral Reactive Lymph Nodes in a COVID-19 Vaccine Recipient With Breast Cancer

Mehmet Emin Adin,Jennifer Wu,Edvin Isuf,Edison Tsui,Darko Pucar 한국유방암학회 2022 Journal of breast cancer Vol.25 No.2

Vaccine-related axillary nodal enlargement is a common benign condition that many mRNA vaccine receivers experience. However, a false attribution of axillary swelling to vaccination may result in delay in cancer care and potential disease progression, particularly in breast cancer patients presenting with ipsilateral axillary lymphadenopathy. We report the case of a 41-year-old pre-menopausal female who presented with suspicious axillary nodal enlargement and a right breast lump (triple-negative invasive ductal carcinoma) after recent administration of the second dose of Moderna mRNA coronavirus disease 2019 (COVID-19) vaccine. On imaging, bilateral axillary lymph nodes were detected. The ipsilateral rightsided node was proven to be metastatic, whereas contralateral nodes were related to a recent mRNA COVID-19 vaccination. Right-sided lymph node had intense uptake (maximum standardized uptake value [SUVmax] = 5), while the contralateral reactive nodes were mildly avid (SUVmax = 2.6). On magnetic resonance imaging, the right-sided node revealed asymmetric cortical thickening and marked cortical enhancement as opposed to normalappearing left-sided nodes.

Spatiotemporal Directional Number Transitional Graph for Dynamic Texture Recognition

Ramirez Rivera, Adin,Chae, Oksam IEEE 2015 IEEE transactions on pattern analysis and machine Vol.37 No.10

<P>Spatiotemporal image descriptors are gaining attention in the image research community for better representation of dynamic textures. In this paper, we introduce a dynamic-micro-texture descriptor, i.e., spatiotemporal directional number transitional graph (DNG), which describes both the spatial structure and motion of each local neighborhood by capturing the direction of natural flow in the temporal domain. We use the structure of the local neighborhood, given by its principal directions, and compute the transition of such directions between frames. Moreover, we present the statistics of the direction transitions in a transitional graph, which acts as a signature for a given spatiotemporal region in the dynamic texture. Furthermore, we create a sequence descriptor by dividing the spatiotemporal volume into several regions, computing a transitional graph for each of them, and represent the sequence as a set of graphs. Our results validate the robustness of the proposed descriptor in different scenarios for expression recognition and dynamic texture analysis.</P>

Background Modeling Through Statistical Edge-Segment Distributions

Ramirez Rivera, Adin,Murshed, Mahbub,Jaemyun Kim,Oksam Chae IEEE 2013 IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDE Vol.23 No.8

<P>Background modeling is challenging due to background dynamism. Most background modeling methods fail in the presence of intensity changes, because the model cannot handle sudden changes. A solution to this problem is to use intensity-robust features. Despite the changes of an edge's shape and position among frames, edges are less sensitive than a pixel's intensity to illumination changes. Furthermore, background models in the presence of moving objects produce ghosts in the detected output, because high quality models require ideal backgrounds. In this paper, we propose a robust statistical edge-segment-based method for background modeling of non-ideal sequences. The proposed method learns the structure of the scene using the edges' behaviors through the use of kernel-density distributions. Moreover, it uses segment features to overcome the shape and position variations of the edges. Hence, the use of segments gives us local information of the scene, and that helps us to predict the objects and background precisely. Furthermore, we accumulate segments to build edge distributions, which allow us to perform unconstrained training and to overcome the ghost effect. In addition, the proposed method uses adaptive thresholding (in the segments) to detect the moving objects. Therefore, this approach increases the accuracy over previous methods, which use fixed thresholds.</P>

Multiple imputation for competing risks survival data via pseudo-observations

Han, Seungbong,Andrei, Adin-Cristian,Tsui, Kam-Wah The Korean Statistical Society 2018 Communications for statistical applications and me Vol.25 No.4

Competing risks are commonly encountered in biomedical research. Regression models for competing risks data can be developed based on data routinely collected in hospitals or general practices. However, these data sets usually contain the covariate missing values. To overcome this problem, multiple imputation is often used to fit regression models under a MAR assumption. Here, we introduce a multivariate imputation in a chained equations algorithm to deal with competing risks survival data. Using pseudo-observations, we make use of the available outcome information by accommodating the competing risk structure. Lastly, we illustrate the practical advantages of our approach using simulations and two data examples from a coronary artery disease data and hepatocellular carcinoma data.

Local Directional Ternary Pattern for Facial Expression Recognition

Byungyong Ryu,Ramirez Rivera, Adin,Jaemyun Kim,Oksam Chae IEEE 2017 IEEE TRANSACTIONS ON IMAGE PROCESSING - Vol.26 No.12

<P>This paper presents a new face descriptor, local directional ternary pattern (LDTP), for facial expression recognition. LDTP efficiently encodes information of emotion-related features (i.e., eyes, eyebrows, upper nose, and mouth) by using the directional information and ternary pattern in order to take advantage of the robustness of edge patterns in the edge region while overcoming weaknesses of edge-based methods in smooth regions. Our proposal, unlike existing histogram-based face description methods that divide the face into several regions and sample the codes uniformly, uses a two-level grid to construct the face descriptor while sampling expression-related information at different scales. We use a coarse grid for stable codes (highly related to non-expression), and a finer one for active codes (highly related to expression). This multi-level approach enables us to do a finer grain description of facial motions while still characterizing the coarse features of the expression. Moreover, we learn the active LDTP codes from the emotion-related facial regions. We tested our method by using person-dependent and independent cross-validation schemes to evaluate the performance. We show that our approaches improve the overall accuracy of facial expression recognition on six data sets.</P>

A Flexible Modeling Approach for Current Status Survival Data via Pseudo-Observations

Han, Seungbong,Andrei, Adin-Cristian,Tsui, Kam-Wah The Korean Statistical Society 2012 응용통계연구 Vol.25 No.6

When modeling event times in biomedical studies, the outcome might be incompletely observed. In this paper, we assume that the outcome is recorded as current status failure time data. Despite well-developed literature the routine practical use of many current status data modeling methods remains infrequent due to the lack of specialized statistical software, the difficulty to assess model goodness-of-fit, as well as the possible loss of information caused by covariate grouping or discretization. We propose a model based on pseudo-observations that is convenient to implement and that allows for flexibility in the choice of the outcome. Parameter estimates are obtained based on generalized estimating equations. Examples from studies in bile duct hyperplasia and breast cancer in conjunction with simulated data illustrate the practical advantages of this model.

Acute Pancreatitis and Gastroduodenal Intussusception Induced by an Underlying Gastric Gastrointestinal Stromal Tumor: A Case Report

Mehmet Siddik Yildiz,Mehmet Emin Adin,Ahmet Dogan,Ibrahim Halil Koparan 대한위암학회 2016 Journal of gastric cancer Vol.16 No.1

Gastrointestinal stromal tumors (GISTs) are rare tumors of the gastrointestinal system and comprise only 1% to 3% of all gastrointestinal tract tumors, with the majority of them arising in the stomach. In this report, we present the unique findings of a case of gastroduodenal intussusception caused by an underlying gastric GIST and complicated with severe acute pancreatitis.