Chloramphenicol (Cm) and its fluorinated derivative florfenicol (Ff) represent highly potent inhibitors of bacterial protein biosynthesis. As a consequence of the use of Cm in human and veterinary medicine, bacterial pathogens of various species and genera have developed and/or acquired Cm resistance. Ff is solely used in veterinary medicine and has been introduced into clinical use in the mid-1990s. Of the Cm resistance genes known to date, only a small number also mediates resistance to Ff. In this review, we present an overview of the different mechanisms responsible for resistance to Cm and Ff with particular focus on the two different types of chloramphenicol acetyltransferases (CATs), specific exporters and multidrug transporters. Phylogenetic trees of the different CAT proteins and exporter proteins were constructed on the basis of a multisequence alignment. Moreover, information is provided on the mobile genetic elements carrying Cm or Cm/Ff resistance genes to provide a basis for the understanding of the distribution and the spread of Cm resistance--even in the absence of a selective pressure imposed by the use of Cm or Ff. 相似文献
Biomechanics and Modeling in Mechanobiology - One of only a few approved and available anabolic treatments for severe osteoporosis is daily injections of PTH (1-34). This drug has a specific dual... 相似文献
Input–output analysis is one of the central methodological pillars of industrial ecology. However, the literature that discusses different structures of environmental extensions (EEs), that is, the scope of physical flows and their attribution to sectors in the monetary input–output table (MIOT), remains fragmented. This article investigates the conceptual and empirical implications of applying two different but frequently used designs of EEs, using the case of energy accounting, where one represents energy supply while the other energy use in the economy. We derive both extensions from an official energy supply–use dataset and apply them to the same single‐region input–output (SRIO) model of Austria, thereby isolating the effect that stems from the decision for the extension design. We also crosscheck the SRIO results with energy footprints from the global multi‐regional input–output (GMRIO) dataset EXIOBASE. Our results show that the ranking of footprints of final demand categories (e.g., household and export) is sensitive to the extension design and that product‐level results can vary by several orders of magnitude. The GMRIO‐based comparison further reveals that for a few countries the supply‐extension result can be twice the size of the use‐extension footprint (e.g., Australia and Norway). We propose a graph approach to provide a generalized framework to disclosing the design of EEs. We discuss the conceptual differences between the two extension designs by applying analogies to hybrid life‐cycle assessment and conclude that our findings are relevant for monitoring of energy efficiency and emission reduction targets and corporate footprint accounting. 相似文献
A detailed understanding of the mechanisms underlying the capacity of a virus to break the species barrier is crucial for pathogen surveillance and control. New World (NW) mammarenaviruses constitute a diverse group of rodent-borne pathogens that includes several causative agents of severe viral hemorrhagic fever in humans. The ability of the NW mammarenaviral attachment glycoprotein (GP) to utilize human transferrin receptor 1 (hTfR1) as a primary entry receptor plays a key role in dictating zoonotic potential. The recent isolation of Tacaribe and lymphocytic choriominingitis mammarenaviruses from host-seeking ticks provided evidence for the presence of mammarenaviruses in arthropods, which are established vectors for numerous other viral pathogens. Here, using next generation sequencing to search for other mammarenaviruses in ticks, we identified a novel replication-competent strain of the NW mammarenavirus Tamiami (TAMV-FL), which we found capable of utilizing hTfR1 to enter mammalian cells. During isolation through serial passaging in mammalian immunocompetent cells, the quasispecies of TAMV-FL acquired and enriched mutations leading to the amino acid changes N151K and D156N, within GP. Cell entry studies revealed that both substitutions, N151K and D156N, increased dependence of the virus on hTfR1 and binding to heparan sulfate proteoglycans. Moreover, we show that the substituted residues likely map to the sterically constrained trimeric axis of GP, and facilitate viral fusion at a lower pH, resulting in viral egress from later endosomal compartments. In summary, we identify and characterize a naturally occurring TAMV strain (TAMV-FL) within ticks that is able to utilize hTfR1. The TAMV-FL significantly diverged from previous TAMV isolates, demonstrating that TAMV quasispecies exhibit striking genetic plasticity that may facilitate zoonotic spillover and rapid adaptation to new hosts. 相似文献
Genetically modified (GM) pigs hold great promises for pig genetic improvement, human health and life science. When GM pigs are produced, selectable marker genes (SMGs) are usually introduced into their genomes for host cell or animal recognition. However, the SMGs that remain in GM pigs might have multiple side effects. To avoid the possible side effects caused by the SMGs, they should be removed from the genome of GM pigs before their commercialization. The Cre recombinase is commonly used to delete the LoxP sites-flanked SMGs from the genome of GM animals. Although SMG-free GM pigs have been generated by Cre-mediated recombination, more efficient and cost-effective approaches are essential for the commercialization of SMG-free GM pigs. In this article we describe the production of a recombinant Cre protein containing a cell-penetrating and a nuclear localization signal peptide in one construct. This engineered Cre enzyme can efficiently excise the LoxP-flanked SMGs in cultured fibroblasts isolated from a transgenic pig, which then can be used as nuclear donor cells to generate live SMG-free GM pigs harboring a desired transgene by somatic cell nuclear transfer. This study describes an efficient and far-less costly method for production of SMG-free GM pigs.
Ecological camera traps are increasingly used by wildlife biologists to unobtrusively monitor an ecosystems animal population. However, manual inspection of the images produced is expensive, laborious, and time‐consuming. The success of deep learning systems using camera trap images has been previously explored in preliminary stages. These studies, however, are lacking in their practicality. They are primarily focused on extremely large datasets, often millions of images, and there is little to no focus on performance when tasked with species identification in new locations not seen during training. Our goal was to test the capabilities of deep learning systems trained on camera trap images using modestly sized training data, compare performance when considering unseen background locations, and quantify the gradient of lower bound performance to provide a guideline of data requirements in correspondence to performance expectations. We use a dataset provided by Parks Canada containing 47,279 images collected from 36 unique geographic locations across multiple environments. Images represent 55 animal species and human activity with high‐class imbalance. We trained, tested, and compared the capabilities of six deep learning computer vision networks using transfer learning and image augmentation: DenseNet201, Inception‐ResNet‐V3, InceptionV3, NASNetMobile, MobileNetV2, and Xception. We compare overall performance on “trained” locations where DenseNet201 performed best with 95.6% top‐1 accuracy showing promise for deep learning methods for smaller scale research efforts. Using trained locations, classifications with <500 images had low and highly variable recall of 0.750 ± 0.329, while classifications with over 1,000 images had a high and stable recall of 0.971 ± 0.0137. Models tasked with classifying species from untrained locations were less accurate, with DenseNet201 performing best with 68.7% top‐1 accuracy. Finally, we provide an open repository where ecologists can insert their image data to train and test custom species detection models for their desired ecological domain. 相似文献