Nanofabrication of High-Resolution Periodic Structures with a Gap Size Below 100 nm by Two-Photon Polymerization

In this paper, approaches for the realization of high-resolution periodic structures with gap sizes at sub-100 nm scale by two-photon polymerization (2PP) are presented. The impact of laser intensity on the feature sizes and surface quality is investigated. The influence of different photosensitive materials on the structure formation is compared. Based on the elliptical geometry character of the voxel, the authors present an idea to realize high-resolution structures with feature sizes less than 100 nm by controlling the laser focus position with respect to the glass substrate. This investigation covers structures fabricated respectively in the plane along and perpendicular to the major axis of voxel. The authors also provide a useful approach to manage the fabrication of proposed periodic structure with a periodic distance of 200 nm and a gap size of 65 nm

Automatic segmentation and functional assessment of the left ventricle using u-net fully convolutional network

© 2019 IEEE. A new method for the automatic segmentation and quantitative assessment of the left ventricle (LV) is proposed in this paper. The method is composed of two steps. First, a fully convolutional U-net is used for the segmentation of the epi- A nd endo-cardial boundaries of the LV from cine MR images. This step incorporates a novel loss function that accounts for the class imbalance problem caused by the binary cross entropy (BCE) loss function. Our novel loss function maximizes the segmentation accuracy and penalizes the effect of the class-imbalance caused by BCE. In the second step, the ventricular volume curves are constructed from which LV function parameter is estimated (i.e., ejection fraction). Our method demonstrated a statistical significance in the segmentation of the epi- A nd endo-cardial boundaries (Dice score of 0.94 and 0.96, respectively) compared with the BCE loss (Dice score of 0.89 and 0.86, respectively). Furthermore, a high positive correlation of 0.97 between the estimated ejection fraction and the gold standard was obtained

A Novel Deep Learning Approach for Left Ventricle Automatic Segmentation in Cardiac Cine MR

© 2019 IEEE. Cardiac magnetic resonance imaging provides a way for heart\u27s functional analysis. Through segmentation of the left ventricle from cardiac cine images, physiological parameters can be obtained. However, manual segmentation of the left ventricle requires significant time and effort. Therefore, automated segmentation of the left ventricle is the desired and practical alternative. This paper introduces a novel framework for the automated segmentation of the epi- and endo-cardial walls of the left ventricle, directly from the cardiac images using a fully convolutional neural network similar to the U-net. There is an acute class imbalance in cardiac images because left ventricle tissues comprise a very small proportion of the images. This imbalance negatively affects the learning process of the network by making it biased toward the majority class. To overcome the class imbalance problem, we propose a novel loss function into our framework, instead of the traditional binary cross entropy loss that causes learning bias in the model. Our new loss maximizes the overall accuracy while penalizing the learning bias caused by binary cross entropy. Our method obtained promising segmentation accuracies for the epi- and endo-cardial walls (Dice 0.94 and 0.96, respectively) compared with the traditional loss (Dice 0.89 and 0.87, respectively

A deep learning-based approach for automatic segmentation and quantification of the left ventricle from cardiac cine MR images

© 2020 Elsevier Ltd Cardiac MRI has been widely used for noninvasive assessment of cardiac anatomy and function as well as heart diagnosis. The estimation of physiological heart parameters for heart diagnosis essentially require accurate segmentation of the Left ventricle (LV) from cardiac MRI. Therefore, we propose a novel deep learning approach for the automated segmentation and quantification of the LV from cardiac cine MR images. We aim to achieve lower errors for the estimated heart parameters compared to the previous studies by proposing a novel deep learning segmentation method. Our framework starts by an accurate localization of the LV blood pool center-point using a fully convolutional neural network (FCN) architecture called FCN1. Then, a region of interest (ROI) that contains the LV is extracted from all heart sections. The extracted ROIs are used for the segmentation of LV cavity and myocardium via a novel FCN architecture called FCN2. The FCN2 network has several bottleneck layers and uses less memory footprint than conventional architectures such as U-net. Furthermore, a new loss function called radial loss that minimizes the distance between the predicted and true contours of the LV is introduced into our model. Following myocardial segmentation, functional and mass parameters of the LV are estimated. Automated Cardiac Diagnosis Challenge (ACDC-2017) dataset was used to validate our framework, which gave better segmentation, accurate estimation of cardiac parameters, and produced less error compared to other methods applied on the same dataset. Furthermore, we showed that our segmentation approach generalizes well across different datasets by testing its performance on a locally acquired dataset. To sum up, we propose a deep learning approach that can be translated into a clinical tool for heart diagnosis

Modified Bianchi pyloromyotomy versus laparoscopic pyloromyotomy for patients with infantile hypertrophic pyloric stenosis: Intraoperative considerations and parents’ satisfaction

Introduction Infantile hypertrophic pyloric stenosis is a common cause of persistent nonbilious vomiting during infancy. Ramstedt pyloromyotomy through right upper quadrant transverse incision is the conventional treatment. The laparoscopic and Tan-Bianchi approaches were introduced to improve the cosmesis and decrease postoperative morbidity. In this study, we compared between laparoscopic and modified Bianchi approaches regarding intraoperative technical considerations and postoperative outcomes.Patients and methods The study included 40 patients with infantile hypertrophic pyloric stenosis. Overall, 20 patients underwent laparoscopic pyloromyotomy (LP) and the other 20 patients underwent modified Bianchi pyloromyotomy (MBP). Patients’ characteristics, including age, sex, gestational age, and associated  comorbidities, were documented. Intraoperative details and complications and postoperative outcomes were recorded.Results The operative time and intraoperative complications including mucosal perforation and bleeding did not significantly differ between both the groups. From the laparoscopic group, one (5%) case was complicated by mucosal perforation and converted to open and another case (5%) developed hypercapnia. There was no statistically significant difference between the two groups regarding time till full feed (P=0.648) and postoperative hospital stay (P=0.082). In addition, there was no statistically significant difference between the two groups regarding postoperative complications, with one (5%) case from the laparoscopic group underwent incomplete myotomy and required redo-operation and another case (5%) developed wound infection. MBP had a significantly more parent satisfaction regarding cosmesis than LP (P=0.016).Conclusion MBP is comparable to LP regarding intraoperative complications and postoperative outcomes; however, the modified Bianchi approach offered more parent satisfaction than laparoscopic approach.  Keywords: laparoscopic, modified Bianchi, pyloric stenosis, pyloromyotom

In Vitro Development of Human iPSC-Derived Functional Neuronal Networks on Laser-Fabricated 3D Scaffolds

Neural progenitor cells generated from human induced pluripotent stem cells (hiPSCs) are the forefront of ″brain-on-chip″ investigations. Viable and functional hiPSC-derived neuronal networks are shaping powerful in vitro models for evaluating the normal and abnormal formation of cortical circuits, understanding the underlying disease mechanisms, and investigating the response to drugs. They therefore represent a desirable instrument for both the scientific community and the pharmacological industry. However, culture conditions required for the full functional maturation of individual neurons and networks are still unidentified. It has been recognized that three-dimensional (3D) culture conditions can better emulate in vivo neuronal tissue development compared to 2D cultures and thus provide a more desirable in vitro approach. In this paper, we present the design and implementation of a 3D scaffold platform that supports and promotes intricate neuronal network development. 3D scaffolds were produced through direct laser writing by two-photon polymerization (2PP), a high-resolution 3D laser microstructuring technology, using the biocompatible and nondegradable photoreactive resin Dental LT Clear (DClear). Neurons developed and interconnected on a 3D environment shaped by vertically stacked scaffold layers. The developed networks could support different cell types. Starting at the day 50 of 3D culture, neuronal progenitor cells could develop into cortical projection neurons (CNPs) of all six layers, different types of inhibitory neurons, and glia. Additionally and in contrast to 2D conditions, 3D scaffolds supported the long-term culturing of neuronal networks over the course of 120 days. Network health and functionality were probed through calcium imaging, which revealed a strong spontaneous neuronal activity that combined individual and collective events. Taken together, our results highlight advanced microstructured 3D scaffolds as a reliable platform for the 3D in vitro modeling of neuronal functions.publishedVersio

Heart slice culture system reliably demonstrates clinical drug-related cardiotoxicity.

The limited availability of human heart tissue and its complex cell composition are major limiting factors for the reliable testing of drug efficacy and toxicity. Recently, we developed functional human and pig heart slice biomimetic culture systems that preserve the viability and functionality of 300 μm heart slices for up to 6 days. Here, we tested the reliability of this culture system for testing the cardiotoxicity of anti-cancer drugs. We tested three anti-cancer drugs (doxorubicin, trastuzumab, and sunitinib) with known different mechanisms of cardiotoxicity at three concentrations and assessed the effect of these drugs on heart slice viability, structure, function and gene expression. Slices incubated with any of these drugs for 48 h showed diminished in viability as well as loss of cardiomyocyte structure and function. Mechanistically, RNA sequencing of doxorubicin-treated tissues demonstrated a significant downregulation of cardiac genes and upregulation of oxidative stress responses. Trastuzumab treatment downregulated cardiac muscle contraction-related genes consistent with its clinically known effect on cardiomyocytes. Interestingly, sunitinib treatment resulted in significant downregulation of angiogenesis-related genes, in line with its mechanism of action. Similar to hiPS-derived-cardiomyocytes, heart slices recapitulated the expected toxicity of doxorubicin and trastuzumab, however, slices were superior in detecting sunitinib cardiotoxicity and mechanism in the clinically relevant concentration range of 0.1-1 μM. These results indicate that heart slice culture models have the potential to become a reliable platform for testing and elucidating mechanisms of drug cardiotoxicity

Seeing revolution non-linearly: www.filmingrevolution.org

Filming Revolution, launched in 2015, is an online interactive data base documentary tracing the strands and strains of independent (mostly) documentary filmmaking in Egypt since the revolution. Consisting of edited interviews with 30 filmmakers, archivists, activists, and artists based in Egypt, the website is organised by the themes that emerged from the material, allowing the viewer to engage in an unlimited set of “curated dialogues” about issues related to filmmaking in Egypt since 2011. With its constellatory interactive design, Filming Revolution creates as much as documents a community of makers, as it attempts to grapple with approaches to filmmaking in the wake of such momentous historical events. The non-hierarchical polysemous structure of the project is meant to echo the rhizomatic, open-ended aspect of the revolution and its aftermath, in yet another affirmation and instantiation of contemporary civil revolution as a non-linear, ever-unfolding, on-going, event

HER2/neu expression status of post BCG recurrent non-muscle-invasive bladder urothelial carcinomas in relation to their primary ones

Background: Transurethral resection (TUR) followed by adjuvant therapy is still the treatment of choice of Non-Muscle-Invasive Bladder Urothelial Carcinoma (NMIBUC). However, recurrence is one of the most troublesome features of these lesions. Early second resection and adjuvant BCG therapy has been shown to improve the outcome. Objective: To evaluate the prognostic value of C-erbB-2 (HER2/neu) expression status in Non-Muscle-Invasive Bladder Urothelial Carcinoma cases, before and after intravesical Bacillus Calmette Guerin (BCG immunotherapy). Materials and methods: HER2/neu expression was studied in 120 (Ta-T1) Non-Muscle-Invasive Urothelial Carcinoma cases. The expression was evaluated and compared to the expression after Bacillus Calmette Guerin (BCG) immunotherapy. Results: HER2/neu expression in low and high grade of the Non- Muscle-Invasive Urothelial Carcinoma was (38%) and (83%) respectively. The difference of the expression rates by tumor grade was statistically significant. In recurring lesions post BCG therapy, C-erbB-2 expression was markedly decreased (31.6%) when compared to its expression before therapy (65%). Conclusions: The HER2/neu expression increased as the tumor grade rose. The reduction in expression following BCG treatment in Non-Invasive transitional cell carcinoma cases could reflect a reduction of the potential malignancy of the tumor

Burnout among surgeons before and during the SARS-CoV-2 pandemic: an international survey

Background: SARS-CoV-2 pandemic has had many significant impacts within the surgical realm, and surgeons have been obligated to reconsider almost every aspect of daily clinical practice. Methods: This is a cross-sectional study reported in compliance with the CHERRIES guidelines and conducted through an online platform from June 14th to July 15th, 2020. The primary outcome was the burden of burnout during the pandemic indicated by the validated Shirom-Melamed Burnout Measure. Results: Nine hundred fifty-four surgeons completed the survey. The median length of practice was 10 years; 78.2% included were male with a median age of 37 years old, 39.5% were consultants, 68.9% were general surgeons, and 55.7% were affiliated with an academic institution. Overall, there was a significant increase in the mean burnout score during the pandemic; longer years of practice and older age were significantly associated with less burnout. There were significant reductions in the median number of outpatient visits, operated cases, on-call hours, emergency visits, and research work, so, 48.2% of respondents felt that the training resources were insufficient. The majority (81.3%) of respondents reported that their hospitals were included in the management of COVID-19, 66.5% felt their roles had been minimized; 41% were asked to assist in non-surgical medical practices, and 37.6% of respondents were included in COVID-19 management. Conclusions: There was a significant burnout among trainees. Almost all aspects of clinical and research activities were affected with a significant reduction in the volume of research, outpatient clinic visits, surgical procedures, on-call hours, and emergency cases hindering the training. Trial registration: The study was registered on clicaltrials.gov "NCT04433286" on 16/06/2020