3D Knee Joint Modeling from MRI Images

Introduction: Osteoarthritis is one of the major diseases that cause disability. Previous research studies implicate that the onset of osteoarthritis is associated with the changes in biomechanics of articular cartilages in the knee joint. In recent years, computer models have been extensively used to study the biomechanics of the cartilaginous tissues. One of the first steps of such studies is to construct anatomically accurate models of the tissues using available software packages. The objective of this study was to compare the capabilities of two software packages, Rhinoceros 3D and Mimics. Method: MRI data was collected from two volunteer subjects (one female age: 28 and one male age: 27). The subjects had no records of previous knee injuries or surgeries. In Rhinoceros 3D, the original MRI data was first imported to Sante DICOM Viewer and then exported as JPEG format. The exported images then were imported by Rhinoceros 3D for segmentation. Mimics software has a built-in tool to read MRI data directly. A tool called 3D LiveWire was used for segmenting. Finally, 3D surface models were obtained using segments. Results: Both Rhinoceros and Mimics have successfully obtained a model for femur. However, Rhinoceros has problems constructing other cartilaginous surfaces. Using Mimics, all other tissues of the knee joint were successfully constructed. A completed joint model included the following parts: Femur, Tibia, Fibula Femoral, Tibial and Fibular Cartilages Menisci Collateral and Cruciate Ligaments Patella and Patellar CartilageDiscussion: Rhinoceros 3D had problems constructing cartilages with complicated surfaces, but its open- programming feature allows it to integrate customized tools and scripts to help construct surfaces. Nevertheless, Mimics has many tools for segmentation and 3D model calculating. It also includes options to modify and optimize the models. In summary, the models from Mimics are qualified for future Finite Element studies

Predicting Transportation Modes of GPS Trajectories using Feature Engineering and Noise Removal

Understanding transportation mode from GPS (Global Positioning System) traces is an essential topic in the data mobility domain. In this paper, a framework is proposed to predict transportation modes. This framework follows a sequence of five steps: (i) data preparation, where GPS points are grouped in trajectory samples; (ii) point features generation; (iii) trajectory features extraction; (iv) noise removal; (v) normalization. We show that the extraction of the new point features: bearing rate, the rate of rate of change of the bearing rate and the global and local trajectory features, like medians and percentiles enables many classifiers to achieve high accuracy (96.5%) and f1 (96.3%) scores. We also show that the noise removal task affects the performance of all the models tested. Finally, the empirical tests where we compare this work against state-of-art transportation mode prediction strategies show that our framework is competitive and outperforms most of them.Comment: 6 page

PArallel, Robust, Interface Simulator (PARIS)

Paris (PArallel, Robust, Interface Simulator) is a finite volume code for simulations of immiscible multifluid or multiphase flows. It is based on the "one-fluid" formulation of the Navier-Stokes equations where different fluids are treated as one material with variable properties, and surface tension is added as a singular interface force. The fluid equations are solved on a regular structured staggered grid using an explicit projection method with a first-order or second-order time integration scheme. The interface separating the different fluids is tracked by a Front-Tracking (FT) method, where the interface is represented by connected marker points, or by a Volume-of-Fluid (VOF) method, where the marker function is advected directly on the fixed grid. Paris is written in Fortran95/2002 and parallelized using MPI and domain decomposition. It is based on several earlier FT or VOF codes such as Ftc3D, Surfer or Gerris. These codes and similar ones, as well as Paris, have been used to simulate a wide range of multifluid and multiphase flows

Case Report The Case for Improved Interprofessional Care: Fatal Analgesic Overdose Secondary to Acute Dental Pain during Pregnancy

Prenatal oral health extends beyond the oral cavity, impacting the general well-being of the pregnant patient and her fetus. This case report follows a 19-year-old pregnant female presenting with acute liver failure secondary to acetaminophen overdose for management of dental pain following extensive dental procedures. Through the course of her illness, the patient suffered adverse outcomes including fetal demise, acute kidney injury, spontaneous bacterial peritonitis, and septic shock before eventual death from multiple organ failure. In managing the pregnant patient, healthcare providers, including physicians and dentists, must recognize and optimize the interconnected relationships shared by the health disciplines. An interdisciplinary approach of collaborative and coordinated care, the timing, sequence, and treatment for the pregnant patient can be improved and thereby maximize overall quality of health. Continued efforts toward integrating oral health into general healthcare education through interprofessional education and practice are necessary to enhance the quality of care that will benefit all patients

TGF-β and WNT signaling pathways in cardiac fibrosis: non-coding RNAs come into focus

Cardiac fibrosis describes the inappropriate proliferation of cardiac fibroblasts (CFs), leading to accumulation of extracellular matrix (ECM) proteins in the cardiac muscle, which is found in many pathophysiological heart conditions. A range of molecular components and cellular pathways, have been implicated in its pathogenesis. In this review, we focus on the TGF-β and WNT signaling pathways, and their mutual interaction, which have emerged as important factors involved in cardiac pathophysiology. The molecular and cellular processes involved in the initiation and progression of cardiac fibrosis are summarized. We focus on TGF-β and WNT signaling in cardiac fibrosis, ECM production, and myofibroblast transformation. Non-coding RNAs (ncRNAs) are one of the main players in the regulation of multiple pathways and cellular processes. MicroRNAs, long non-coding RNAs, and circular long non-coding RNAs can all interact with the TGF-β/WNT signaling axis to affect cardiac fibrosis. A better understanding of these processes may lead to new approaches for diagnosis and treatment of many cardiac conditions. Video Abstract

Frequency and fate of microRNA editing in human brain

Primary transcripts of certain microRNA (miRNA) genes (pri-miRNAs) are subject to RNA editing that converts adenosine to inosine (A→I RNA editing). However, the frequency of the pri-miRNA editing and the fate of edited pri-miRNAs remain largely to be determined. Examination of already known pri-miRNA editing sites indicated that adenosine residues of the UAG triplet sequence might be edited more frequently. In the present study, therefore, we conducted a large-scale survey of human pri-miRNAs containing the UAG triplet sequence. By direct sequencing of RT–PCR products corresponding to pri-miRNAs, we examined 209 pri-miRNAs and identified 43 UAG and also 43 non-UAG editing sites in 47 pri-miRNAs, which were highly edited in human brain. In vitro miRNA processing assay using recombinant Drosha-DGCR8 and Dicer-TRBP (the human immuno deficiency virus transactivating response RNA-binding protein) complexes revealed that a majority of pri-miRNA editing is likely to interfere with the miRNA processing steps. In addition, four new edited miRNAs with altered seed sequences were identified by targeted cloning and sequencing of the miRNAs that would be processed from edited pri-miRNAs. Our studies predict that ∼16% of human pri-miRNAs are subject to A→I editing and, thus, miRNA editing could have a large impact on the miRNA-mediated gene silencing

Management system for optimizing public transport networks: GPS record

As cities continue to grow in size and population, the design of public transport networks becomes complicated, given the wide diversity in the origins and destinations of users [1], as well as the saturation of vehicle infrastructure in large cities despite their attempts to adapt it according to population distribution. This indicates that, in order to reduce users’ travel time, it is necessary to implement alternative road solutions to the use of cars, increasing investment in public transportation [2, 3] by conducting a comprehensive analysis of the state of transportation. This situation has made appear the solutions and development oriented to transportation based on Internet of Things (IoT) which allows, in a first stage, monitoring of public transport systems, in order to optimize the deployment of transport units and thus reduce the time of transfer of users through the cities [4]. These solution proposals are focused on information collected from user resources (data collected through smart phones) to create a common database [5]. The present study proposes the development of an intelligent monitoring and management system for public transportation networks using a hybrid communication architecture based on wireless node networks using IPv6 and cellular networks (LTE, LTE-M)

Mast cells and eosinophils in invasive breast carcinoma

<p>Abstract</p> <p>Background</p> <p>Inflammatory cells in the tumour stroma has gained increasing interest recently. Thus, we aimed to study the frequency and prognostic impact of stromal mast cells and tumour infiltrating eosinophils in invasive breast carcinomas.</p> <p>Methods</p> <p>Tissue microarrays containing 234 cases of invasive breast cancer were prepared and analysed for the presence of stromal mast cells and eosinophils. Tumour infiltrating eosinophils were counted on hematoxylin-eosin slides. Immunostaining for tryptase was done and the total number of mast cells were counted and correlated to the proliferation marker Ki 67, positivity for estrogen and progesterone receptors, clinical parameters and clinical outcome.</p> <p>Results</p> <p>Stromal mast cells were found to correlate to low grade tumours and estrogen receptor positivity. There was a total lack of eosinophils in breast cancer tumours.</p> <p>Conclusion</p> <p>A high number of mast cells in the tumours correlated to low-grade tumours and estrogen receptor positivity. Eosinophils are not tumour infiltrating in breast cancers.</p