Suchergebnisse

Customs Service is a financial authority responsible for controlling the flow of importation and exportation goods in each country and for collecting the relevant taxes. Customs officers are considered as 'high-demand' and 'high-responsibility' governmental officials, which constitute members of multidisciplinary teams at the local, as well as international level and collaborate with different authorities, including medical officers. Despite limited data in the medical literature, customs officers are considered as a 'high-risk' occupational group for infections and environmental health risk. During the severe acute respiratory syndrome (SARS) and influenza A/H1N1 pandemic outbreaks in 2003 and 2009, respectively, customs officers had a fundamental front-line input in the establishment of the recommended at that time border measures. In Belgium in 1994, a psittacosis outbreak occurred in customs officers following their exposure to illegally imported parakeets. During the recent increased immigration proceedings, customs officers have been involved in detaining unauthorized populations for various infectious diseases, such as tuberculosis, varicella and measles. Occupational risk for customs officers also includes noise-induced hearing loss, exposure to diesel engine emission and stored tobacco and occupational stress due to their increased time-schedule and decision-making duties. In this review, we discuss customs officers' occupational risk towards environmental and infectious factors, including viral infections, tuberculosis and psittacosis.

Genome assemblers are computational tools for de novo genome assembly, based on a plenitude of primary sequencing data. The quality of genome assemblies is estimated by their contiguity and the occurrences of misassemblies (duplications, deletions, translocations or inversions). The rapid development of sequencing technologies has enabled the rise of novel de novo genome assembly strategies. The ultimate goal of such strategies is to utilise the features of each sequencing platform in order to address the existing weaknesses of each sequencing type and compose a complete and correct genome map. In the present study, the hybrid strategy, which is based on Illumina short paired-end reads and Nanopore long reads, was benchmarked using MaSuRCA and Wengan assemblers. Moreover, the long-read assembly strategy, which is based on Nanopore reads, was benchmarked using Canu or PacBio HiFi reads were benchmarked using Hifiasm and HiCanu. The assemblies were performed on a computational cluster with limited computational resources. Their outputs were evaluated in terms of accuracy and computational performance. PacBio HiFi assembly strategy outperforms the other ones, while Hi-C scaffolding, which is based on chromatin 3D structure, is required in order to increase continuity, accuracy and completeness when large and complex genomes, such as the human one, are assembled. The use of Hi-C data is also necessary while using the hybrid assembly strategy. The results revealed that HiFi sequencing enabled the rise of novel algorithms which require less genome coverage than that of the other strategies making the assembly a less computationally demanding task. Taken together, these developments may lead to the democratisation of genome assembly projects which are now approachable by smaller labs with limited technical and financial resources.

The 'George N. Papanicolaou Medal' is a brass medal commissioned by the Academy of Athens on the occasion of the 100th anniversary of the birth of Dr George N. Papanicolaou in 1983. It was created by Professor Theodoros Papagiannis, Professor Emeritus of Sculpture at the Athens School of Fine Arts in Athens, Greece; the medal presents Dr George N. Papanicolaou with his microscope. According to Professor Papagiannis, the medal was requested by Professor Nikolaos Louros, Emeritus Professor of Obstetrics and Gynecology at the University of Athens School of Medicine and it was created according to the ancient Greek style. The medal was given to all honored participants of the special ceremony organized by the Academy of Athens in May 13th, 1983, in the context of the 100 years from the birth of Dr George N. Papanicolaou. The ceremony was performed at the Central Hall of the Academy of Athens in Athens under the auspices of the President of the Hellenic Democracy Constantinos Caramanlis. A copy of this medal is being exhibited at the 'Museum of Contemporary Sculpture Theodoros Papagiannis' in Elliniko at the Municipality of Katsanochoria close to Ioannina (Greece), as well as at the newly founded Institute of Paediatric Virology based on the island of Euboea, birth place of Dr George N. Papanicolaou.

The coronavirus disease-2019 (COVID-19) pandemic, caused by the new coronavirus SARS-CoV-2, has spread around the globe with unprecedented consequences for the health of millions of people. While the pandemic is still in progress, with new incidents being reported every day, the resilience of the global society is constantly being challenged. Under these circumstances, the future seems uncertain. SARS-CoV-2 coronavirus has spread panic among civilians and insecurity at all socio-political and economic levels, dramatically disrupting everyday life, global economy, international travel and trade. The disease has also been linked to the onset of depression in many individuals due to the extreme restriction measures that have been taken for the prevention of the rapid spreading of COVID-19. First, the socio-economic, political and psychological implications of the COVID-19 pandemic were explored. Substantial evidence is provided for the consequences of the pandemic on all aspects of everyday life, while at the same time we unravel the role and the pursuits of national regimes during this unforeseen situation. The second goal of this review is related to the scientific aspect of the pandemic. Hence, we explain why SARS-CoV-2 is not a so-called 'invisible enemy', and also attempt to give insight regarding the origin of the virus, in an effort to reject the conspiracy theories that have arisen during the pandemic. Finally, rational strategies were investigated for successful vaccine development. We are optimistic that this review will complement the knowledge of specialized scientists and inform non-specialized readers on basic scientific questions, and also on the social and economic implications of the COVID-19 pandemic.

Potentially suspicious breast neoplasms could be masked by high tissue density, thus increasing the probability of a false-negative diagnosis. Furthermore, differentiating breast tissue type enables patient pre-screening stratification and risk assessment. In this study, we propose and evaluate advanced machine learning methodologies aiming at an objective and reliable method for breast density scoring from routine mammographic images. The proposed image analysis pipeline incorporates texture [Gabor filters and local binary pattern (LBP)] and gradient-based features [histogram of oriented gradients (HOG) as well as speeded-up robust features (SURF)]. Additionally, transfer learning approaches with ImageNet trained weights were also used for comparison, as well as a convolutional neural network (CNN). The proposed CNN model was fully trained on two open mammography datasets and was found to be the optimal performing methodology (AUC up to 87.3%). Thus, the findings of this study indicate that automated density scoring in mammograms can aid clinical diagnosis by introducing artificial intelligence-powered decision-support systems and contribute to the 'democratization' of healthcare by overcoming limitations, such as the geographic location of patients or the lack of expert radiologists.