een dogs and other animals. These infections might be an under-recognized threat to public health and animal welfare. Further research on the identification of the serovars of Leptospira and biotypes of Brucella circulating in dogs is encouraged. Finally, knowledge of the comprehensive epidemiology of these diseases is an invaluable input for veterinarians, healthcare professionals, and policy-makers to avoid or manage canine leptospirosis and brucellosis.To enhance the process of bacterial remediation of weathered hydrocarbons, the area of Dukhan, Qatar, was considered as a model for weathering processes. Self-purification by indigenous hydrocarbon-degrading bacteria showed low performance. Biostimulation/seeding using one or another of the indigenous bacteria improved the performance. Symbiosis between three strains dominating the soil; Bacillus sorensis D11, Bacillus cereus D12, and Pseudomonas stutzeri D13, was highly performant for removal of total petroleum hydrocarbons in the weathered soil. D11, the most sensitive, showed the highest performance when mixed with D12 or D13. D12, less performant than D11, was more active on diesel range organics (DRO C10-C28), similar to D11. D13 showed a metabolic behavior close to commensal and co-metabolic ones. It was more active on hydrocarbons above C29. Combination of the three strains conducted to the removal of at least 80% of C10-C35 organics in the extract at concentrations of 31.1 mg/g TPH-DRO.A universal method for rapid identifying super-enhancers which are large domains of multiple closely-spaced enhancers is proposed. The method applies configurable cloud virtual machines (cVMs) and the rank-ordering of super-enhancers (ROSE) algorithm. To identify super-enhancers a сVM-based analysis of the ChIP-seq binding patterns of the active enhancer-associated mark is employed. https://www.selleckchem.com/products/jnj-77242113-icotrokinra.html The use of the proposed method is described step-by-step configuration of cVM; ChIP-seq data alignment; peak calling; ROSE algorithm; interpretation of the results on a client machine. The method was validated for the search of super-enhancers using the H3K27ac mark in the sample datasets of a cell line (human MCF-7), mouse tissue (heart), and human tissue (adrenal gland). The total analysis cycle time of raw ChIP-seq data ranges from 15 to 48 min, depending on the number of initial short reads. Depending on the data processing step and availability of multi-threading, a cVM can be scaled up to a multi-CPU configuration with large amount of RAM. An important feature of the method is that it can run on a client machine that has low-performance with virtually any OS. The proposed method allows for simultaneous and independent processing of different sample datasets on multiple clones of a single cVM.•Cloud VMs were used for rapid processing of ChIP-seq data to identify super-enhancers.•The method can use a low-performance computer with virtually any OS on it.•It can be scaled up for parallel processing of individual sample datasets on their own VMs for rapid high-throughput processing.The methods summarized in this video tutorial series are based on the open source Digital Methods Initiative - Twitter Capture and Analysis Toolkit (DMI-TCAT) that allows media researchers to collect tweets off the STREAM API (application programming interface) on an ongoing basis. With DMI - TCAT and the open source data visualization software Gephi, social data in the millions of units is quickly and easily sorted by algorithms to find users or items of importance on Twitter, such as in the Fig. 1 below. While these figures and the data gathered though the DMI-TCAT do not provide full firehose access to all historical tweets, they do provide a generally representative sample of tweets that is relatively proportional to the total volume of tweets being posted at any given time (Gerlitz & Rieder, 2013; Groshek & Tandoc, 2016). For more details on the DMI-TCAT and its operation, we encourage readers to visit its github page (https//github.com/digitalmethodsinitiative/dmi-tcat) and note that this cloud-based analytics program is free and customizable. The specific techniques covered in the methodology reported here in text and expanded upon in the video tutorial series include how to • Model influence users by sizing nodes with the betweenness centrality algorithm; • Identify community groups by adding color using the modularity algorithm; • Spatialize networks through applying the openord algorithm; • Make social network graphs dynamic and interactive online.Extraction of high-quality RNA from pancreatic tumors for sequencing purposes is technically challenging, as the pancreas is an organ rich in ribonucleases. The majority of the established RNA isolation protocols for use with primary pancreatic tissue involve perfusion of RNA stabilizing reagent into the pancreatic tissue to protect RNA integrity before extraction. However, the additional time needed for this procedure can actually lead to further RNA degradation. We optimized a protocol suitable for high quality RNA isolation from mouse pancreatic tumors that is a simple, fast, and inexpensive modification of existing methods, combining the use of liquid nitrogen and guanidinium thiocyanate-chloroform extraction. Through this procedure, the mean RNA Integrity Number value obtained for RNA isolated from pancreatic tumors was 9.0, and was reproducibly suitable for RNAseq and qPCR.•a protocol suitable for high quality RNA isolation from mouse pancreatic tumors as well as normal pancreas•combining the use of liquid nitrogen and guanidinium thiocyanate-chloroform extraction.Echocardiographic imaging has been acquired in historical longitudinal cohorts of cardiovascular disease. Many cohorts were established prior to digital recording of echocardiography, and thus have preserved their archival imaging on Video Home System (VHS) tapes. These tapes require large physical storage space, are affected by physical degradation, and cannot be analyzed using modern digital techniques. We have designed and implemented a standardized methodology for digitizing analog data in historical longitudinal cohorts. The methodology creates a pipeline through critical steps of initial review, digitization, anonymization, quality control, and storage. The methodology has been implemented in the Framingham Offspring Study, a community-based epidemiological cohort study with echocardiography performed during serial examinations between 1987 and 1998. We present this method as an accessible pipeline for preserving and repurposing historical imaging data acquired from large cohort studies. The described technique•Outlines a generalizable pipeline for digitization of analog recordings of echocardiography stored on VHS tapes•Addresses research concerns including quality control, anonymization, and storage•Expresses the authors' individual experience regarding observed image quality, training needs, and potential limitations to help readers understand the costs and benefits of this method.