A case of amoebic liver abscess and emphysematous gallbladder in a 65-year-old male with situs inversus totalis.

INTRODUCTION AND IMPORTANCE: Situs inversus totalis, a rare congenital condition, is characterized by the mirror-image reversal of the abdominal and thoracic organs. Amoebic liver abscess and emphysematous gallbladder are severe gastrointestinal infections. The coexistence of these three conditions is extremely rare. CASE PRESENTATION: We present the case of a 65-year-old male who presented with abdominal pain, fever, and jaundice. Investigations revealed situs inversus totalis, amoebic liver abscess, and emphysematous gallbladder. The patient underwent successful treatment with antibiotics and open surgery drainage of the liver abscess, and subtotal cholecystectomy. CLINICAL DISCUSSION: The co-occurrence of situs inversus totalis, amoebic liver abscess, and emphysematous gallbladder poses a diagnostic challenge and requires thorough evaluation and appropriate management. CONCLUSION: Situs inversus totalis may coincide with other conditions like amebic abscess and emphysematous gallbladder, complicating diagnosis and treatment. Early diagnosis and prompt intervention are crucial to improve outcomes.

Streaming support for data intensive cloud-based sequence analysis.

Cloud computing provides a promising solution to the genomics data deluge problem resulting from the advent of next-generation sequencing (NGS) technology. Based on the concepts of "resources-on-demand" and "pay-as-you-go", scientists with no or limited infrastructure can have access to scalable and cost-effective computational resources. However, the large size of NGS data causes a significant data transfer latency from the client's site to the cloud, which presents a bottleneck for using cloud computing services. In this paper, we provide a streaming-based scheme to overcome this problem, where the NGS data is processed while being transferred to the cloud. Our scheme targets the wide class of NGS data analysis tasks, where the NGS sequences can be processed independently from one another. We also provide the elastream package that supports the use of this scheme with individual analysis programs or with workflow systems. Experiments presented in this paper show that our solution mitigates the effect of data transfer latency and saves both time and cost of computation.

Tavaxy: integrating Taverna and Galaxy workflows with cloud computing support.

BACKGROUND: Over the past decade the workflow system paradigm has evolved as an efficient and user-friendly approach for developing complex bioinformatics applications. Two popular workflow systems that have gained acceptance by the bioinformatics community are Taverna and Galaxy. Each system has a large user-base and supports an ever-growing repository of application workflows. However, workflows developed for one system cannot be imported and executed easily on the other. The lack of interoperability is due to differences in the models of computation, workflow languages, and architectures of both systems. This lack of interoperability limits sharing of workflows between the user communities and leads to duplication of development efforts. RESULTS: In this paper, we present Tavaxy, a stand-alone system for creating and executing workflows based on using an extensible set of re-usable workflow patterns. Tavaxy offers a set of new features that simplify and enhance the development of sequence analysis applications: It allows the integration of existing Taverna and Galaxy workflows in a single environment, and supports the use of cloud computing capabilities. The integration of existing Taverna and Galaxy workflows is supported seamlessly at both run-time and design-time levels, based on the concepts of hierarchical workflows and workflow patterns. The use of cloud computing in Tavaxy is flexible, where the users can either instantiate the whole system on the cloud, or delegate the execution of certain sub-workflows to the cloud infrastructure. CONCLUSIONS: Tavaxy reduces the workflow development cycle by introducing the use of workflow patterns to simplify workflow creation. It enables the re-use and integration of existing (sub-) workflows from Taverna and Galaxy, and allows the creation of hybrid workflows. Its additional features exploit recent advances in high performance cloud computing to cope with the increasing data size and complexity of analysis.The system can be accessed either through a cloud-enabled web-interface or downloaded and installed to run within the user's local environment. All resources related to Tavaxy are available at http://www.tavaxy.org.