Practices and ethical concerns regarding preimplantation diagnosis. Who regulates preimplantation genetic diagnosis in Brazil?

Preimplantation genetic diagnosis (PGD) was originally developed to diagnose embryo-related genetic abnormalities for couples who present a high risk of a specific inherited disorder. Because this technology involves embryo selection, the medical, bioethical, and legal implications of the technique have been debated, particularly when it is used to select features that are not related to serious diseases. Although several initiatives have attempted to achieve regulatory harmonization, the diversity of healthcare services available and the presence of cultural differences have hampered attempts to achieve this goal. Thus, in different countries, the provision of PGD and regulatory frameworks reflect the perceptions of scientific groups, legislators, and society regarding this technology. In Brazil, several texts have been analyzed by the National Congress to regulate the use of assisted reproduction technologies. Legislative debates, however, are not conclusive, and limited information has been published on how PGD is specifically regulated. The country requires the development of new regulatory standards to ensure adequate access to this technology and to guarantee its safe practice. This study examined official documents published on PGD regulation in Brazil and demonstrated how little direct oversight of PGD currently exists. It provides relevant information to encourage reflection on a particular regulation model in a Brazilian context, and should serve as part of the basis to enable further reform of the clinical practice of PGD in the country.     

SEROPOSITIVITY FOR ASCARIOSIS AND TOXOCARIOSIS AND CYTOKINE EXPRESSION AMONG THE INDIGENOUS PEOPLE IN THE VENEZUELAN DELTA REGION

The present study aimed at measuring seropositivities for infection by Ascaris suum and Toxocara canis using the excretory/secretory (E/S) antigens from Ascaris suum (AES) and Toxocara canis (TES) within an indigenous population. In addition, quantification of cytokine expressions in peripheral blood cells was determined. A total of 50 Warao indigenous were included; of which 43 were adults and seven children. In adults, 44.1% were seropositive for both parasites; whereas children had only seropositivity to one or the other helminth. For ascariosis, the percentage of AES seropositivity in adults and children was high; 23.3% and 57.1%, respectively. While that for toxocariosis, the percentage of TES seropositivity in adults and children was low; 9.3% and 14.3%, respectively. The percentage of seronegativity was comparable for AES and TES antigens in adults (27.9%) and children (28.6%). When positive sera were analyzed by Western blotting technique using AES antigens; three bands of 97.2, 193.6 and 200.2 kDas were mostly recognized. When the TES antigens were used, nine major bands were mostly identified; 47.4, 52.2, 84.9, 98.2, 119.1, 131.3, 175.6, 184.4 and 193.6 kDas. Stool examinations showed that Blastocystis hominis, Hymenolepis nana and Entamoeba coli were the most commonly observed intestinal parasites. Quantification of cytokines IFN-γ, IL-2, IL-6, TGF-β, TNF-α, IL-10 and IL-4 expressions showed that there was only a significant increased expression of IL-4 in indigenous with TES seropositivity (p < 0.002). Ascaris and Toxocara seropositivity was prevalent among Warao indigenous.     

A new approach to prevent HIV transmission: Project Protect intervention for recently infected individuals

Past research suggests that as many as 50% of onward human immunodeficiency virus (HIV) transmissions occur during acute and recent HIV infection. It is clearly important to develop interventions which focus on this highly infectious stage of HIV infection to prevent further transmission in the risk networks of acutely and recently infected individuals. Project Protect tries to find recently and acutely infected individuals and prevents HIV transmission in their risk networks. Participants are recruited by community health outreach workers at community-based HIV testing sites and drug users' community venues, by coupon referrals and through referrals from AIDS clinics. When a network with acute/recent infection is identified, network members are interviewed about their risky behaviors, network information is collected, and blood is drawn for HIV testing. Participants are also educated and given prevention materials (condoms, syringes, educational materials); HIV-infected participants are referred to AIDS clinics and are assisted with access to care. Community alerts about elevated risk of HIV transmission are distributed within the risk networks of recently infected. Overall, 342 people were recruited to the project and screened for acute/recent HIV infection. Only six index cases of recent infection (2.3% of all people screened) were found through primary screening at voluntary counseling and testing (VCT) sites, but six cases of recent infection were found through contact tracing of these recently infected participants (7% of network members who came to the interview). Combining screening at VCT sites and contact tracing the number of recently infected people we located as compared to VCT screening alone. No adverse events were encountered. These first results provide evidence for the theory behind the intervention, i.e., in the risk networks of recently infected people there are other people with recent HIV infection and they can be successfully located without increasing stigma for project participants.     

Discordant Electrocardiogram Left Ventricular Wall Thickness and Strain Findings in Influenza Myocarditis

A 42‐year‐old man presented with a viral prodrome and tested positive for influenza A. He rapidly deteriorated developing cardiogenic shock, rhabdomyolysis, and acute kidney injury. Patient improved 1 week later with supportive measures including vasopressors, inotropes, and an intraaortic balloon pump. We report this case as it highlights the discordance between echocardiographic ventricular wall thickening as a result of myocardial edema, and electrocardiographic findings at presentation, with a reversal in findings at time of resolution. Additionally, there was some suggestion of a regional pattern to the reduced longitudinal strain.     

Efficacy,effectiveness and side effects of medications used to prevent fractures

There is an increasing number of effective therapies for fracture prevention in adults at risk of osteoporosis. However, shortcomings in the evidence underpinning our management of osteoporosis still exist. Evidence of antifracture efficacy in the groups of patients who most commonly use calcium and vitamin D supplements is lacking, the safety of calcium supplements is in doubt, and the safety and efficacy of high doses of vitamin D give cause for concern. Alendronate, risedronate, zoledronate and denosumab have been shown to prevent spine, nonspine and hip fractures; in addition, teriparatide and strontium ranelate prevent both spine and nonspine fractures, and raloxifene and ibandronate prevent spine fractures. However, most trials provide little information regarding long‐term efficacy or safety. A particular concern at present is the possibility that oral bisphosphonates might cause atypical femoral fractures. Observational data suggest that the incidence of this type of fracture increases steeply with duration of bisphosphonate use, resulting in concern that the benefit–risk balance may become negative in the long term, particularly in patients in whom the osteoporotic fracture risk is not high. Therefore, reappraisal of ongoing use of bisphosphonates after about 5 years is endorsed by expert consensus, and ‘drug holidays’ should be considered at this time. Further studies are needed to guide clinical practice in this area.     

Simeprevir added to peginterferon and ribavirin lessens time with fatigue,depressive symptoms and functional limitations in patients with chronic hepatitis C compared with peginterferon and ribavirin: results from 1161 patients in the QUEST‐1, QUEST‐2 and PROMISE studies

The value of adding simeprevir (SMV) vs placebo (PBO) to peginterferon and ribavirin (PR) for treatment of chronic hepatitis C virus infection was examined using patient‐reported outcomes (PROs); further, concordance of PROs with virology endpoints and adverse events (AEs) was explored. Patients (n = 768 SMV/PR, n = 393 PBO/PR) rated fatigue (FSS), depressive symptoms (CES‐D) and functional impairment (WPAI: Hepatitis C Productivity, Daily Activity and Absenteeism) at baseline and throughout treatment in three randomised, double‐blind trials comparing the addition of SMV or PBO during initial 12 weeks of PR. PR was administered for 48 weeks (PBO group) and 24/48 weeks (SMV group) using a response‐guided therapy (RGT) approach. Mean PRO scores (except Absenteeism) worsened from baseline to Week 4 to the same extent in both groups but reverted after Week 24 for SMV/PR and only after Week 48 for PBO/PR. Accordingly, there was a significantly lower area under the curve (baseline–Week 60, AUC₆₀) and fewer weeks with clinically important worsening of scores in the SMV/PR group at any time point. Incidences of patients with fatigue and anaemia AEs were similar in both groups, but FSS scores showed that clinically important increases in fatigue lasted a mean of 6.9 weeks longer with PBO/PR (P < 0.001). PRO score subgroup analysis indicated better outcomes for patients who met the criteria for RGT or achieved sustained virological response 12 weeks post‐treatment (SVR12); differences in mean PRO scores associated with fibrosis level were only observed with PBO/PR. Greater efficacy of SMV/PR enabled reduced treatment duration and reduced time with PR‐related AEs without adding to AE severity.     

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.