International Research Ethics Education

This paper assesses the state of research ethics in low- and middle-income countries and the achievements of the Fogarty International Center's bioethics training program since 2000. The vision of FIC for the next decade of research ethics education is encapsulated in four proposed goals: (1) Ensure sufficient expertise in ethics review by having someone with long-term training on every high-workload REC; (2) Develop LMIC capacity to conduct original research on critical ethical issues by supporting doctoral and postdoctoral training and career paths for research ethicists; (3) Make research training and review at LMIC institutions sustainable by identifying additional funding mechanisms and models; (4) Make institutional research systems more ethical and efficient through context-specific training integrated into all levels of scientific training

Ensembles of Deep Neural Networks for Action Recognition in Still Images

Despite the fact that notable improvements have been made recently in the field of feature extraction and classification, human action recognition is still challenging, especially in images, in which, unlike videos, there is no motion. Thus, the methods proposed for recognizing human actions in videos cannot be applied to still images. A big challenge in action recognition in still images is the lack of large enough datasets, which is problematic for training deep Convolutional Neural Networks (CNNs) due to the overfitting issue. In this paper, by taking advantage of pre-trained CNNs, we employ the transfer learning technique to tackle the lack of massive labeled action recognition datasets. Furthermore, since the last layer of the CNN has class-specific information, we apply an attention mechanism on the output feature maps of the CNN to extract more discriminative and powerful features for classification of human actions. Moreover, we use eight different pre-trained CNNs in our framework and investigate their performance on Stanford 40 dataset. Finally, we propose using the Ensemble Learning technique to enhance the overall accuracy of action classification by combining the predictions of multiple models. The best setting of our method is able to achieve 93.17$\%$ accuracy on the Stanford 40 dataset.Comment: 5 pages, 2 figures, 3 tables, Accepted by ICCKE 201

Correlates of Immunity to Filovirus Infection

Filoviruses can cause severe, often fatal hemorrhagic fever in humans. Recent advances in vaccine and therapeutic drug development have provided encouraging data concerning treatment of these infections. However, relatively little is known about immune responses in fatal versus non-fatal filovirus infection. This review summarizes the published literature on correlates of immunity to filovirus infection, and highlights deficiencies in our knowledge on this topic. It is likely that there are several types of successful immune responses, depending on the type of filovirus, and the presence and timing of vaccination or drug treatment

Mechanical Properties of Silicon Nanowires with Native Oxide Surface State

Silicon nanowires have attracted considerable interest due to their wide-ranging applications in nanoelectromechanical systems and nanoelectronics. Molecular dynamics simulations are powerful tools for studying the mechanical properties of nanowires. However, these simulations encounter challenges in interpreting the mechanical behavior and brittle to ductile transition of silicon nanowires, primarily due to surface effects such as the assumption of an unreconstructed surface state. This study specifically focuses on the tensile deformation of silicon nanowires with a native oxide layer, considering critical parameters such as cross-sectional shape, length-to-critical dimension ratio, temperature, the presence of nano-voids, and strain rate. By incorporating the native oxide layer, the article aims to provide a more realistic representation of the mechanical behavior for different critical dimensions and crystallographic orientations of silicon nanowires. The findings contribute to the advancement of knowledge regarding size-dependent elastic properties and strength of silicon nanowires.Comment: 11 pages, 10 figure

Korona Günlerinde Antroposen Söylemi

Işık Üniversitesi öğretim görevlileri tarafından Covid-19 Pandemisi'nin ele alındığı yazı dizisi serisinin "Korona Günlerinde Antroposen Söylemi" konu başlıklı yayınıdır.İnsan Çağı anlamında gelen Antroposen (Anthropocene) kavramı ilk olarak 2000 yılında, Nobel Kimya Ödüllü Paul J. Crutzen ve biyolog Eugene F. Stoermer tarafından, insanlığın doğadan farklılaşmakla yetinmeyip gezegenin tamamı üzerinde değiştirme ve dönüştürme kudretine sahip olması anlamında kullanılmıştır. Son dönemlerde sıklıkla kullanılan kavram insan ve doğa arasındaki eşitsiz ilişkiye vurgu yaparken insanın doğa üzerindeki tahakkümünün eninde sonunda insan yaşamını da tehlikeye atacağını, dolayısıyla tüketim ilişkileri değil ama tüketim şekillerinin sorgulanmasını önerir. Çözümün ise ancak bütün insanlığa sorumluluklar yüklenerek ve bu sorumlulukların yerine getirilmesi ile mümkün olacağı savunulur

Reliable and accurate diagnostics from highly multiplexed sequencing assays

Scalable, inexpensive, and secure testing for SARS-CoV-2 infection is crucial for control of the novel coronavirus pandemic. Recently developed highly multiplexed sequencing assays (HMSAs) that rely on high-throughput sequencing can, in principle, meet these demands, and present promising alternatives to currently used RT-qPCR-based tests. However, reliable analysis, interpretation, and clinical use of HMSAs requires overcoming several computational, statistical and engineering challenges. Using recently acquired experimental data, we present and validate a computational workflow based on kallisto and bustools, that utilizes robust statistical methods and fast, memory efficient algorithms, to quickly, accurately and reliably process high-throughput sequencing data. We show that our workflow is effective at processing data from all recently proposed SARS-CoV-2 sequencing based diagnostic tests, and is generally applicable to any diagnostic HMSA

Resonantly enhanced second-harmonic generation using III-V semiconductor all-dielectric metasurfaces

Nonlinear optical phenomena in nanostructured materials have been challenging our perceptions of nonlinear optical processes that have been explored since the invention of lasers. For example, the ability to control optical field confinement, enhancement, and scattering almost independently, allows nonlinear frequency conversion efficiencies to be enhanced by many orders of magnitude compared to bulk materials. Also, the subwavelength length scale renders phase matching issues irrelevant. Compared with plasmonic nanostructures, dielectric resonator metamaterials show great promise for enhanced nonlinear optical processes due to their larger mode volumes. Here, we present, for the first time, resonantly enhanced second-harmonic generation (SHG) using Gallium Arsenide (GaAs) based dielectric metasurfaces. Using arrays of cylindrical resonators we observe SHG enhancement factors as large as 104 relative to unpatterned GaAs. At the magnetic dipole resonance we measure an absolute nonlinear conversion efficiency of ~2X10^(-5) with ~3.4 GW/cm2 pump intensity. The polarization properties of the SHG reveal that both bulk and surface nonlinearities play important roles in the observed nonlinear process

A STAT-1 knockout mouse model for Machupo virus pathogenesis

<p>Abstract</p> <p>Background</p> <p>Machupo virus (MACV), a member of the <it>Arenaviridae</it>, causes Bolivian hemorrhagic fever, with ~20% lethality in humans. The pathogenesis of MACV infection is poorly understood, and there are no clinically proven treatments for disease. This is due, in part, to a paucity of small animal models for MACV infection in which to discover and explore candidate therapeutics.</p> <p>Methods</p> <p>Mice lacking signal transducer and activator of transcription 1 (STAT-1) were infected with MACV. Lethality, viral replication, metabolic changes, hematology, histopathology, and systemic cytokine expression were analyzed throughout the course of infection.</p> <p>Results</p> <p>We report here that STAT-1 knockout mice succumbed to MACV infection within 7-8 days, and presented some relevant clinical and histopathological manifestations of disease. Furthermore, the model was used to validate the efficacy of ribavirin in protection against infection.</p> <p>Conclusions</p> <p>The STAT-1 knockout mouse model can be a useful small animal model for drug testing and preliminary immunological analysis of lethal MACV infection.</p

Primary human organoids models: Current progress and key milestones

During the past 10 years the world has experienced enormous progress in the organoids field. Human organoids have shown huge potential to study organ development, homeostasis and to model diseases in vitro. The organoid technology has been widely and increasingly applied to generate patient-specific in vitro 3D cultures, starting from both primary and reprogrammed stem/progenitor cells. This has consequently fostered the development of innovative disease models and new regenerative therapies. Human primary, or adult stem/progenitor cell-derived, organoids can be derived from both healthy and pathological primary tissue samples spanning from fetal to adult age. The resulting 3D culture can be maintained for several months and even years, while retaining and resembling its original tissue’s properties. As the potential of this technology expands, new approaches are emerging to further improve organoid applications in biology and medicine. This review discusses the main organs and tissues which, as of today, have been modelled in vitro using primary organoid culture systems. Moreover, we also discuss the advantages, limitations, and future perspectives of primary human organoids in the fields of developmental biology, disease modelling, drug testing and regenerative medicine