Abstract: Novel tools and techniques are provided for implementing intelligent alert automation (“IAA”). In various embodiments, IAA receives alert/event feeds from several different alerting and ticketing systems via input Redis queues, and uses a triage system to determine whether to process the alert/event or disregard it. If so, IAA may create a flow instance, assign a unique instance ID, and place the flow instance in one of a plurality of jobs queues based on alert/event type and/or or source. An abattoir system retrieves a flow instance from one of the jobs queues (in order of the queue's priority), and processes the next node or step in the flow instance. The flow instance is placed back into the jobs queue for subsequent processing by the same or different abattoir system until no additional nodes or steps remain in the flow, at which point the flow instance is considered complete.

Abstract: Novel tools and techniques are provided for implementing dashboard for alert storage and history (“DASH”). In various embodiments, DASH provides for consolidated tracking and monitoring of two or more of current (or active) alerts, cleared alerts, and/or transactional information for alerts that are stored within corresponding alert live database that mirrors current alert instance data in a real-time fault management system, alert history database that contains a snapshot of an alert history of each alert or corresponding network device, and/or alert log database that contains a full transaction record of every copy of an alert either over a first duration or having a total data size within a first total data size. DASH also cleans received alert data and/or enriches the alert data, and provides a user interface (“UI”) that enables a user to view, absorb, filter, manage, and/or organize alert data to facilitate addressing of alerts in the network(s).

Abstract: Disclosed are compositions, assays, methods, diagnostic methods, kits and diagnostic kits for the specific and differential detection of Mycobacterium avium subsp. paratuberculosis from samples including veterinary samples, clinical samples, food samples, forensic sample, an environmental sample (e.g., soil, dirt, garbage, sewage, air, or water), including food processing and manufacturing surfaces, or a biological sample.

Abstract: Disclosed are compositions, assays, methods, diagnostic methods, kits and diagnostic kits for the specific and differential detection of Mycobacterium avium subsp. paratuberculosis from samples including veterinary samples, clinical samples, food samples, forensic sample, an environmental sample (e.g., soil, dirt, garbage, sewage, air, or water), including food processing and manufacturing surfaces, or a biological sample.

Abstract: Disclosed are compositions, assays, methods, diagnostic methods, kits and diagnostic kits for the specific and differential detection of Mycobacterium avium subsp. paratuberculosis from samples including veterinary samples, clinical samples, food samples, forensic sample, an environmental sample (e.g., soil, dirt, garbage, sewage, air, or water), including food processing and manufacturing surfaces, or a biological sample.

Abstract: Disclosed are compositions, assays, methods, diagnostic methods, kits and diagnostic kits for the specific and differential detection of Mycobacterium avium subsp. paratuberculosis from samples including veterinary samples, clinical samples, food samples, forensic sample, an environmental sample (e.g., soil, dirt, garbage, sewage, air, or water), including food processing and manufacturing surfaces, or a biological sample.

Abstract: Disclosed are compositions, assays, methods, diagnostic methods, kits and diagnostic kits for the specific and differential detection of Mycobacterium avium subsp. paratuberculosis from samples including veterinary samples, clinical samples, food samples, forensic sample, an environmental sample (e.g., soil, dirt, garbage, sewage, air, or water), including food processing and manufacturing surfaces, or a biological sample.

Abstract: Disclosed are compositions, assays, methods, diagnostic methods, kits and diagnostic kits for the specific and differential detection of Mycobacterium avium subsp. paratuberculosis from samples including veterinary samples, clinical samples, food samples, forensic sample, an environmental sample (e.g., soil, dirt, garbage, sewage, air, or water), including food processing and manufacturing surfaces, or a biological sample.

Abstract: Disclosed are compositions, assays, methods, diagnostic methods, kits and diagnostic kits for the specific and differential detection of a non-Mycobacterium avium subsp. paratuberculosis (non-MAP) organism, wherein a non-MAP organism is a Mycobacterium avium complex (MAC) organism that does not belong to the Mycobacterium avium subsp. paratuberculosis (MAP) organism, from samples including veterinary samples, clinical samples, food samples, forensic sample, an environmental sample (e.g., soil, dirt, garbage, sewage, air, or water), including food processing and manufacturing surfaces, or a biological sample. Exemplary non-MAP organisms including M. avium subsp. avium (MAA), M. avium subsp. hominissuis (MAH), and M. avium subsp. silvaticum (MAS) can be detected by the present compositions, kits and methods.

Abstract: Disclosed are compositions, assays, methods, diagnostic methods, kits and diagnostic kits for the specific and differential detection of Mycobacterium avium subsp. paratuberculosis from samples including veterinary samples, clinical samples, food samples, forensic sample, an environmental sample (e.g., soil, dirt, garbage, sewage, air, or water), including food processing and manufacturing surfaces, or a biological sample.

Abstract: Disclosed are compositions, assays, methods, diagnostic methods, kits and diagnostic kits for the specific and differential detection of a non-Mycobacterium avium subsp. paratuberculosis (non-MAP) organism, wherein a non-MAP organism is a Mycobacterium avium complex (MAC) organism that does not belong to the Mycobacterium avium subsp. paratuberculosis (MAP) organism, from samples including veterinary samples, clinical samples, food samples, forensic sample, an environmental sample (e.g., soil, dirt, garbage, sewage, air, or water), including food processing and manufacturing surfaces, or a biological sample. Exemplary non-MAP organisms including M. avium subsp. avium (MAA), M. avium subsp. hominissuis (MAH), and M. avium subsp. silvaticum (MAS) can be detected by the present compositions, kits and methods.

Abstract: Disclosed are compositions, assays, methods, diagnostic methods, kits and diagnostic kits for the specific and differential detection of Mycobacterium avium subsp. paratuberculosis from samples including veterinary samples, clinical samples, food samples, forensic sample, an environmental sample (e.g., soil, dirt, garbage, sewage, air, or water), including food processing and manufacturing surfaces, or a biological sample.

Abstract: Disclosed are genomic sequences for nine strains of Cronobacter spp. (C. sakazakii—696, 701, 680; C. malonaticus—507, 681; C. turicensis—564; C. muytjensii—530; C. dublinensis—582; C. genomosp1—581) and compositions, methods, and kits for detecting, identifying and distinguishing Cronobacter spp. strains from each other and from non-Cronobacter spp. strains. Some embodiments describe isolated nucleic acid compositions unique to certain Cronobacter strains as well as compositions that are specific to all Cronobacter spp. Primer and probe compositions and methods of use of primers and probes are also provided. Kits for identification of Cronobacter spp. are also described. Some embodiments relate to computer software methods for setting a control based threshold for analysis of PCR data.