Objective To assess the learnability of two magnetic resonance imaging (MRI) grading systems for lumbar central canal stenosis based on inter-observer agreement and test-retest reliability of doctors with no prior knowledge of the two systems. Materials and methods Two clinical fellows, one novice radiology resident, one neurosurgeon, and one orthopedic surgeon, who were unaware of the two qualitative MRI grading systems prior to this study, acquainted themselves with the teaching files. All five observers independently assessed the LCCS grade of 70 patients using T2-weighted axial magnetic resonance images at the L2-3, L3-4, L3-4, and L5-S1 disc levels. Analysis was performed twice at an interval of two months. Results The inter-observer agreement among all five readers was excellent and test-retest reliability was moderate to excellent for both the Schizas and Lee systems. Positive percentage agreements were found to be over 0.8 in almost all observers with relatively narrow 95% confidence limits. Conclusion Both Schizas and Lee MRI grading systems for LCCS are reliable grading systems, and can be used as a learnable method for both clinicians and radiologists.Marine microbial plankton hold high structural and functional diversity, however, high-resolution data are lacking in a large part of the Global Ocean, such as in subpolar areas of the SW Atlantic. The Burdwood Bank (BB) is a submerged plateau (average depth 100 m) that constitutes the westernmost segment of the North Scotia Ridge (54°-55°S; 56°-62°W). The BB hosts rich benthic biodiversity in low chlorophyll waters of the southern Patagonian Shelf, Argentina, declared Namuncurá Marine Protected Area (NMPA) in 2013. So far, the pelagic microorganisms above the bank have not been described. 5-FU inhibitor During austral summer 2016, we assessed the microbial plankton (0.2-200 μm cell size) biomass and their taxonomical and functional diversity along a longitudinal transect (54.2-55.3°S, 58-68°W) from the Beagle Channel (BC) to the BB, characterized by contrasting hydrography. Results displayed a marked zonation in the composition and structure of the microbial communities. The biomass of phytoplankton >5 μm was 28 times higher in the BC, attributed mainly to large diatom blooms, than in oceanic waters above the BB, where the small coccolithophore Emiliania huxleyi and flagellates 5 μm, emphasizing the importance of small-sized phytoplankton in low chlorophyll waters. The homogeneous water column and high retention above the bank seem to favor the development of abundant picophytoplankton and microzooplankton communities. Overall, our findings unfold the plankton configuration in the Southern Patagonian Shelf, ascribed as a sink for anthropogenic CO2, and highlight the diverse ecological traits that microorganisms develop to adjust their yield to changing conditions.NCT02646943.In order to cope with the problems of high frequency and multiple causes of mountain fires, it is very important to adopt appropriate technologies to monitor and warn mountain fires through a few surface parameters. At the same time, the existing mobile terminal equipment is insufficient in image processing and storage capacity, and the energy consumption is high in the data transmission process, which requires calculation unloading. For this circumstance, first, a hierarchical discriminant analysis algorithm based on image feature extraction is introduced, and the image acquisition software in the mobile edge computing environment in the android system is designed and installed. Based on the remote sensing data, the land surface parameters of mountain fire are obtained, and the application of image recognition optimization algorithm in the mobile edge computing (MEC) environment is realized to solve the problem of transmission delay caused by traditional mobile cloud computing (MCC). Then, according to the f surface parameters of MEC can be used to effectively predict the mountain fire and provide preventive measures in time.Many drugs are promiscuous and bind to multiple targets. On the one hand, these targets may be linked to unwanted side effects, but on the other, they may achieve a combined desired effect (polypharmacology) or represent multiple diseases (drug repositioning). With the growth of 3D structures of drug-target complexes, it is today possible to study drug promiscuity at the structural level and to screen vast amounts of drug-target interactions to predict side effects, polypharmacological potential, and repositioning opportunities. Here, we pursue such an approach to identify drugs inactivating B-cells, whose dysregulation can function as a driver of autoimmune diseases. Screening over 500 kinases, we identified 22 candidate targets, whose knock out impeded the activation of B-cells. Among these 22 is the gene KDR, whose gene product VEGFR2 is a prominent cancer target with anti-VEGFR2 drugs on the market for over a decade. The main result of this paper is that structure-based drug repositioning for the identified kinase targets identified the cancer drug ibrutinib as micromolar VEGFR2 inhibitor with a very high therapeutic index in B-cell inactivation. These findings prove that ibrutinib is not only acting on the Bruton’s tyrosine kinase BTK, against which it was designed. Instead, it may be a polypharmacological drug, which additionally targets angiogenesis via inhibition of VEGFR2. Therefore ibrutinib carries potential to treat other VEGFR2 associated disease. Structure-based drug repositioning explains ibrutinib’s anti VEGFR2 action through the conservation of a specific pattern of interactions of the drug with BTK and VEGFR2. Overall, structure-based drug repositioning was able to predict these findings at a fraction of the time and cost of a conventional screen.Researchers and clinicians face a significant challenge in keeping up-to-date with the rapid rate of new associations between genetic mutations and diseases. To remedy this problem, this research mined the ClinicalTrials.gov corpus to extract relevant biological insights, produce unique reports to summarize findings, and make the meta-data available via APIs. An automated text-analysis pipeline performed the following features parsing the ClinicalTrials.gov files, extracting and analyzing mutations from the corpus, mapping clinical trials to Human Phenotype Ontology (HPO), and finding associations between clinical trials and HPO nodes. Unique reports were created for each mutation (SNPs and protein mutations) mentioned in the corpus, as well as for each clinical trial that references a mutation. These reports, which have been run over multiple time points, along with APIs to access meta-data, are freely available at http//snpminertrials.com. Additionally, HPO was used to normalize disease terms and associate clinical trials with relevant genes.