Matrix Metalloproteinases 2 and 9 Polymorphism in Patients With Myeloproliferative Diseases: A STROBE-Compliant Observational Study

Chronic myeloproliferative disorders such as polycythemia vera (PV), essential thrombocytosis (ET), and idiopathic myelofibrosis arise from clonal proliferation of neoplastic stem cells in the bone marrow. Matrix metalloproteinases (MMPs) are a family of zinc-dependent endopeptidases that have potential to degrade all types of extracellular matrix (ECM) and also play a role in remodeling of the ECM. It is known that MMPs play a role in bone marrow remodeling.The primary goal of our study is to explore the relationship between chronic myeloproliferative diseases and some of MMP gene polymorphisms. The demonstration of a relationship will help to understand whether these polymorphisms may be a potential early diagnosis marker of the diseases.Patients were selected from outpatient clinics of Turgut Ozal University Hospital, Ankara, Turkey, between December 2010 and May 2011. Twenty-eight patients that previously diagnosed and followed-up with PV, 17 with secondary polycythemia (SP), and 12 with ET were enrolled in the study, along with a control group of 22 healthy people.DNA was isolated from peripheral blood. Using polymerase chain reaction–restriction fragment length polymorphism method, MMP2 and MMP9 gene polymorphisms were analyzed with agarose gel electrophoresis. There was a statistically significant difference between the study groups and the control group in terms of Gln279Arg polymorphisms rates of MMP9. The highest MMP9 Gln279Arg polymorphism rate was observed in the ET group. But nobody from the control group had polymorphic MMP9. There was no statistically significant difference between the groups in terms of MMP2-735 C > T polymorphism rates.In conclusion, MMP9 gene Gln279Arg polymorphism was associated with ET, SP, and PV diseases. Hence, we believe that these gene polymorphisms may play a role in the mechanism of bone marrow fibrosis and may be a factor that increases the risk of thrombosis. Illumination of the molecular basis of the relationship between MMP-thrombosis and MMP-fibrosis provides a better understanding of the pathophysiology of PV and ET diseases and will allow new approaches to diagnosis and treatment.     

Imaging in secondary tumors of the ovary

Abdominal Radiology - Metastatic involvement of the ovaries is not rare. The most common tumor types metastasizing to the ovaries, from non-gynecological organs, are breast, colorectal, gastric,...     

A Stacked Generalization of 3D Orthogonal Deep Learning Convolutional Neural Networks for Improved Detection of White Matter Hyperintensities in 3D FLAIR Images

BACKGROUND AND PURPOSE:Accurate and reliable detection of white matter hyperintensities and their volume quantification can provide valuable clinical information to assess neurologic disease progression. In this work, a stacked generalization ensemble of orthogonal 3D convolutional neural networks, StackGen-Net, is explored for improving automated detection of white matter hyperintensities in 3D T2-FLAIR images.MATERIALS AND METHODS:Individual convolutional neural networks in StackGen-Net were trained on 2.5D patches from orthogonal reformatting of 3D-FLAIR (n = 21) to yield white matter hyperintensity posteriors. A meta convolutional neural network was trained to learn the functional mapping from orthogonal white matter hyperintensity posteriors to the final white matter hyperintensity prediction. The impact of training data and architecture choices on white matter hyperintensity segmentation performance was systematically evaluated on a test cohort (n = 9). The segmentation performance of StackGen-Net was compared with state-of-the-art convolutional neural network techniques on an independent test cohort from the Alzheimer’s Disease Neuroimaging Initiative-3 (n = 20).RESULTS:StackGen-Net outperformed individual convolutional neural networks in the ensemble and their combination using averaging or majority voting. In a comparison with state-of-the-art white matter hyperintensity segmentation techniques, StackGen-Net achieved a significantly higher Dice score (0.76 [SD, 0.08], F1-lesion (0.74 [SD, 0.13]), and area under precision-recall curve (0.84 [SD, 0.09]), and the lowest absolute volume difference (13.3% [SD, 9.1%]). StackGen-Net performance in Dice scores (median = 0.74) did not significantly differ (P = .22) from interobserver (median = 0.73) variability between 2 experienced neuroradiologists. We found no significant difference (P = .15) in white matter hyperintensity lesion volumes from StackGen-Net predictions and ground truth annotations.CONCLUSIONS:A stacked generalization of convolutional neural networks, utilizing multiplanar lesion information using 2.5D spatial context, greatly improved the segmentation performance of StackGen-Net compared with traditional ensemble techniques and some state-of-the-art deep learning models for 3D-FLAIR.

White matter hyperintensities (WMHs) correspond to pathologic features of axonal degeneration, demyelination, and gliosis observed within cerebral white matter.¹ Clinically, the extent of WMHs in the brain has been associated with cognitive impairment, Alzheimer’s disease and vascular dementia, and increased risk of stroke.^2,3 The detection and quantification of WMH volumes to monitor lesion burden evolution and its correlation with clinical outcomes have been of interest in clinical research.^4,5 Although the extent of WMHs can be visually scored,⁶ the categoric nature of such scoring systems makes quantitative evaluation of disease progression difficult. Manually segmenting WMHs is tedious, prone to inter- and intraobserver variability, and is, in most cases, impractical. Thus, there is an increased interest in developing fast, accurate, and reliable computer-aided automated techniques for WMH segmentation.Convolutional neural network (CNN)-based approaches have been successful in several semantic segmentation tasks in medical imaging.⁷ Recent works have proposed using deep learning–based methods for segmenting WMHs using 2D-FLAIR images.^8-11 More recently, a WMH segmentation challenge¹² was also organized (http://wmh.isi.uu.nl/) to facilitate comparison of automated segmentation of WMHs of presumed vascular origin in 2D multislice T2-FLAIR images. Architectures that used an ensemble of separately trained CNNs showed promising results in this challenge, with 3 of the top 5 winners using ensemble-based techniques.¹²Conventional 2D-FLAIR images are typically acquired with thick slices (3–4 mm) and possible slice gaps. Partial volume effects from a thick slice are likely to affect the detection of smaller lesions, both in-plane and out-of-plane. 3D-FLAIR images, with isotropic resolution, have been shown to achieve higher resolution and contrast-to-noise ratio¹³ and have shown promising results in MS lesion detection using 3D CNNs.¹⁴ Additionally, the isotropic resolution enables viewing and evaluation of the images in multiple planes. This multiplanar reformatting of 3D-FLAIR without the use of interpolating kernels is only possible due to the isotropic nature of the acquisition. Network architectures that use information from the 3 orthogonal views have been explored in recent works for CNN-based segmentation of 3D MR imaging data.¹⁵ The use of data from multiple planes allows more spatial context during training without the computational burden associated with full 3D training.¹⁶ The use of 3 orthogonal views simultaneously mirrors how humans approach this segmentation task.Ensembles of CNNs have been shown to average away the variances in the solution and the choice of model- and configuration-specific behaviors of CNNs.¹⁷ Traditionally, the solutions from these separately trained CNNs are combined by averaging or using a majority consensus. In this work, we propose the use of a stacked generalization framework (StackGen-Net) for combining multiplanar lesion information from 3D CNN ensembles to improve the detection of WMH lesions in 3D-FLAIR. A stacked generalization¹⁸ framework learns to combine solutions from individual CNNs in the ensemble. We systematically evaluated the performance of this framework and compared it with traditional ensemble techniques, such as averaging or majority voting, and state-of-the-art deep learning techniques.     

A comparison of double single suture-button fixation,suture-button fixation,and screw fixation for ankle syndesmosis injury: A retrospective cohort study

Different methods have been used throughout the years for syndesmotic injury but there is no consensus on the ideal treatment. Some methods are expensive and some have more complications. The aim of this study is to compare single suture endobutton with double suture endobutton and screw fixation for syndesmotic injury.Sixty nine patients with syndesmotic injury with fibular fractures whom were treated with a single interosseous suture endobutton system (ZipTight^TM, Zimmer Biomet), a double interosseous suture endobutton system (ZipTight^TM, Zimmer Biomet) and 1 syndesmotic screw (TST, Istanbul, Turkey) were included in this study. Functional and radiological results from patient records between 2015 and 2018 were retrospectively evaluated.Twenty patients were treated with the double interosseous suture endobutton, 23 were treated with the single interosseous suture endobutton, and 26 were treated with traditional AO screw fixation. Three patients from the screw fixation group (11.5%) required revision surgery (P < .05). All the radiologic and clinical outcomes were statistical similar in all 3 groups.Our findings showed that the interosseous suture endobutton system is at least as safe as the screw fixation technique for treatment of syndesmosis joint injuries and can be used as an alternative to the screw method. The interosseous suture endobutton system eliminates the need for a second surgery to remove the hardware, which minimizes the probability of re-diastasis. Since our results showed no statistical difference between single and double interosseous suture endobutton systems, the less costly single endobutton system may be the better alternative.     

Burden of illness among patients with severe aplastic anemia who have had insufficient response to immunosuppressive therapy: a multicenter retrospective chart review study

Annals of Hematology - This study assessed treatment patterns and healthcare resource utilization (HRU) of patients with severe aplastic anemia (SAA) with insufficient response to immunosuppressive...     

Silicone-based simulation models for peripheral nerve microsurgery

Background

There is a need for a peripheral nerve model on which surgeons-in-training can simulate the repair of nerve injuries at their own pace. Although practicing on animal models/cadavers is considered the “gold standard” of microsurgical training, the proposed model aims to provide a platform for improving the technical skills of surgical trainees prior to their practice on cadaver/animal models. In addition, this model has the potential to serve as a standardized test medium for assessing the skill sets of surgeons.

Design and synthesis of novel organometallic complexes using boronated phenylalanine derivatives as potential anticancer agents

Drug design and discovery studies are important because of the prevalence of diseases without available medical cures. New anticancer agents are particularly urgent because of the high mortality rate associated with cancer. A series of mononuclear gold (III) and platinum (II) complexes based on boronated phenylalanine (BPA) were designed and synthesized using 4,4’-dimethyl-2,2’-dipyridyl (L1) or 1,10-phenanthroline-5,6-dion (L2) ligands to obtain promising anticancer drug candidates. Proton nuclear magnetic resonance, infrared, mass spectrometry, and elemental analyses were utilized for chemical characterizations. Cell viability, cancer cell colony formation, endothelial tube formation, and cytoskeleton staining assays were performed using A549 lung adenocarcinoma and human umbilical vein endothelial cells (HUVECs) to investigate preliminary pharmacological activities. L1-based platinum (II) complex (BPA-L1-Pt) was the most promising complex, and has similar activity with the approved chemotherapy drug cis-platinum. Half maximal inhibitory concentration values for BPA-L1-Pt were 9.15 µM on A549s and 16.61 µM on HUVECs; the values for cis-platinum were 5.24 µM on A549s and 23.14 µM on HUVECs. Consequently, further synthesis studies should be performed to boost the cancer cell selectivity feature of BPA by varying metal and ligand types.