The role of parallel computing in bioinformatics

The need to intelligibly capture, manage and analyse the ever-increasing amount of publicly available genomic data is one of the challenges facing bioinformaticians today. Such analyses are in fact impractical using uniprocessor machines, which has led to an increasing reliance on clusters of commodity-priced computers. An existing network of cheap, commodity PCs was utilised as a single computational resource for parallel computing. The performance of the cluster was investigated using a whole genome-scanning program written in the Java programming language. The TSpaces framework, based on the Linda parallel programming model, was used to parallelise the application. Maximum speedup was achieved at between 30 and 50 processors, depending on the size of the genome being scanned. Together with this, the associated significant reductions in wall-clock time suggest that both parallel computing and Java have a significant role to play in the field of bioinformatics

Molecular imaging phenotyping for selecting and monitoring radioligand therapy of neuroendocrine neoplasms

Neuroendocrine neoplasia (NEN) is an umbrella term that includes a widely heterogeneous disease group including well-differentiated neuroendocrine tumours (NETs), and aggressive neuroendocrine carcinomas (NECs). The site of origin of the NENs is linked to the intrinsic tumour biology and is predictive of the disease course. It is understood that NENs demonstrate significant biologic heterogeneity which ultimately translates to widely varying clinical presentations, disease course and prognosis. Thus, significant emphasis is laid on the pre-therapy evaluation of markers that can help predict tumour behavior and dynamically monitors the response during and after treatment. Most well-differentiated NENs express somatostatin receptors (SSTRs) which make them appropriate for peptide receptor radionuclide therapy (PRRT). However, the treatment outcomes of PRRT depend heavily on the adequacy of patient selection by molecular imaging phenotyping not only utilizing pre-treatment SSTR PET bu

Predictive Value of Initial PET-SUVmax in Patients with Locally Advanced Esophageal and Gastroesophageal Junction Adenocarcinoma

Introduction:We have previously shown that in early clinical stage esophageal adenocarcinoma, a positron emission tomography standardized uptake values (PET SUVmax) of <4.5 is associated with earlier pathologic stage and predicts better survival. In this study, we analyze the impact of the pretreatment PET SUVmax in patients with locally advanced esophageal adenocarcinoma who undergo preoperative chemoradiotherapy.Methods:We performed a retrospective analysis, selecting patients with adenocarcinoma of the esophagus who had a pretreatment PET scan and who received chemoradiotherapy before esophagectomy. Data recorded included demographics, PET SUVmax, treatment details, pathologic details, and survival data. Comparison of categorical variables was done by χ2 analysis, continuous variables by t test, survival analysis by the Kaplan-Meier method, and comparisons of survival using the log-rank test.Results:Between January 1996 and September 2007, 189 patients were appropriate for this analysis. The initial PET SUVmax was <4.5 in 28 patients and ≥4.5 in 161 patients. The two groups were similar with regards to demographics and treatment details. Patients in the low SUV group were less likely to show evidence of treatment response after chemoradiotherapy, including a higher likelihood of residual nodal disease and a lower likelihood of a pathologic complete response and estimated treatment response. However, both groups had similar survival.Conclusions:Although the initial PET SUVmax does not predict survival in patients with locally advanced esophageal adenocarcinoma who receive preoperative chemoradiotherapy, patients with a high initial SUVmax respond better to preoperative therapy. These results can be used to better select esophageal cancer patients for combined modality treatment

Detection and impacts of leakage from sub-seafloor deep geological carbon dioxide storage

Fossil fuel power generation and other industrial emissions of carbon dioxide are a threat to global climate1, yet many economies will remain reliant on these technologies for several decades2. Carbon dioxide capture and storage (CCS) in deep geological formations provides an effective option to remove these emissions from the climate system3. In many regions storage reservoirs are located offshore4, 5, over a kilometre or more below societally important shelf seas6. Therefore, concerns about the possibility of leakage7, 8 and potential environmental impacts, along with economics, have contributed to delaying development of operational CCS. Here we investigate the detectability and environmental impact of leakage from a controlled sub-seabed release of CO2. We show that the biological impact and footprint of this small leak analogue (&lt;1 tonne CO2 d?1) is confined to a few tens of metres. Migration of CO2 through the shallow seabed is influenced by near-surface sediment structure, and by dissolution and re-precipitation of calcium carbonate naturally present in sediments. Results reported here advance the understanding of environmental sensitivity to leakage and identify appropriate monitoring strategies for full-scale carbon storage operations

Hepatic progenitor cells of biliary origin with liver repopulation capacity

Hepatocytes and cholangiocytes self-renew following liver injury. Following severe injury hepatocytes are increasingly senescent, but whether hepatic progenitor cells (HPCs) then contribute to liver regeneration is unclear. Here, we describe a mouse model where the E3 ubiquitin ligase Mdm2 is inducibly deleted in more than 98% of hepatocytes, causing apoptosis, necrosis and senescence with nearly all hepatocytes expressing p21. This results in florid HPC activation, which is necessary for survival, followed by complete, functional liver reconstitution. HPCs isolated from genetically normal mice, using cell surface markers, were highly expandable and phenotypically stable in vitro. These HPCs were transplanted into adult mouse livers where hepatocyte Mdm2 was repeatedly deleted, creating a non-competitive repopulation assay. Transplanted HPCs contributed significantly to restoration of liver parenchyma, regenerating hepatocytes and biliary epithelia, highlighting their in vivo lineage potency. HPCs are therefore a potential future alternative to hepatocyte or liver transplantation for liver disease

Symbolic control analysis of cellular systems

Thesis (PhD (Biochemistry))--University of Stellenbosch, 2011.ENGLISH ABSTRACT: Metabolic Control Analysis (MCA) provides a powerful quantitative framework for understanding and explaining the control and regulation within a cellular system. MCA allows the global control of a steady-state system to be quantified in terms of control coeficients, which we can express in terms of the local properties referred to as elasticity coeficients. MCA relates elasticities to control coeficients through a matrix inversion, thus allowing scientists to predict and quantify how the kinetics of the individual enzymes affect the systemic behaviour of cellular systems. Traditionally we solved this problem numerically, while we used algebraic and symbolic control analysis techniques less frequently. By using symbolic algebraic computation we present a general implementation of the symbolic matrix inversion of MCA, known as SymCA, which requires only the description of any allosteric modifier interactions and the stoichiometry of a cellular system. The algebraic expressions generated allow an in-depth analysis of the distribution of the control within a system and also of the parameters which exhibit the greatest effect on this control distribution. This also applies when the exact values for the elasticities or control coeficients are unknown. We have demonstrated that by quantifying the control patterns, referred to as `routes of regulation', inherent in all control coeficient expressions, we can gain insight into how perturbations are propagated through a cellular system and which regulatory pathways are favoured under changing conditions.AFRIKAANSE OPSOMMING: Metaboliese Kontrole-Analise (MKA) bied 'n kragtige kwantitatiewe raamwerk om die beheer en regulering binne sellulere sisteme te verstaan en te verduidelik. 'n Sleutelaspek van MKA is dat die globale beheer van 'n sisteem met 'n bestendige toestand gekwantifiseer kan word in terme van kontrole-koefisente en dat hierdie koefisente uitgedruk kan word in terme van die sisteem se lokale eienskappe, genaamd elastisiteitskoefisente. Deur van matriksinversie gebruik te maak kan MKA die verband tussen elastisiteitskoefisente en kontrole-koefisente aflei wat mens in staat stel om te sien hoe die kinetika van die individuele ensiemreaksies die sisteemgedrag op sellulere vlak beinvloed. Die probleem word tradisioneel hoofsaaklik op numeriese wyse bereken terwyl die gebruik van algebraiese en simboliese kontrole-analise minder gereeld gebruik word. In hierdie proefskrif verskaf ons, deur van simboliese algebraiese metodes gebruik te maak, 'n generiese implementasie van die simboliese matriksinversie van MKA, genaamd SymCA, wat slegs 'n beskrywing van 'n sellulere sisteem se allosetriese interaksies en die stoichiometrie benodig. Die algebraiese uitdrukkings sodanig gegenereer stel mens in staat om 'n in-diepte analise te doen om vas te stel waar die beheer binne 'n sisteem le, asook watter parameters die grootste effek op die kontrole-verspreiding het. Dit geld selfs in die geval waar die presiese waardes van die elastisiteitskoefisente of kontrole-koefisente onbekend is. Hierdie proefskrif demonstreer hoe die kwantifisering van kontrole-patrone, ook gesien as 'roetes van regulering', wat inherent is aan kontrole-koefisent vergelykings, mens in staat stel om te sien hoe perturbasies in 'n sellulere sisteem voortplant en watter regulatoriese paaie bevoordeel word onder veranderde kondisies

By

The need to intelligibly capture, manage and analyse the ever-increasing amount of publicly available genomic data is one of the challenges facing bioinformaticians today. Such analyses are in fact impractical using uniprocessor machines, which has led to an increasing reliance on clusters of commodity-priced computers. An existing network of cheap, commodity PCs was utilised as a single computational resource for parallel computing. The performance of the cluster was investigated using a whole genome-scanning program written in the Java programming language. The TSpaces framework, based on the Linda parallel programming model, was used to parallelise the application. Maximum speedup was achieved at between 30 and 50 processors, depending on the size of the genome being scanned. Together with this, the associated significant reductions in wall-clock time suggest that both parallel computing and Java have a significant role to play in the field of bioinformatics. ii Acknowledgement

Advanced imaging including PET/CT for cardiothoracic surgery

Medical imaging has always been essential for the diagnosis and management of many problems encountered in cardiothoracic surgical practice, from the assessment of cardiac function (e.g., by providing the location and extent of an infarct), to defining the extent of a malignancy via noninvasive imaging modalities to guide the choice of more invasive steps (e.g., biopsies or resections). Although most imaging still relies on standard radiological modalities such as computed tomography (CT), positron emission tomography (PET) has become more widely used in the US since its most recent clinical breakthrough. With the increasing availability of combined PET/CT units that deliver both anatomical and metabolic information in a single examination, PET imaging can potentially be used to a greater extent than what has been previously attainable. This review will provide an overview of recent advances in imaging that are likely to influence the direction of cardiothoracic surgery in the near future. © 2004 Elsevier Inc. All rights reserved

Personalised insulin calculator enables safe and effective correction of hyperglycaemia prior to FDG PET/CT

Background: Hyperglycaemia can influence F-fluorodeoxyglucose (FDG) uptake due to competition for glucose transport and phosphorylation by hexokinase. Major international nuclear medicine societies recommend blood glucose level (BGL) 10\ua0mmol/L) prior to FDG PET/CT at the Peter MacCallum Cancer Centre over a 2-year period. Cohort 1 comprised a 12-month period (April 1, 2014–March 31, 2015) using the department’s established empiric-dose insulin protocol, and Cohort 2 the 12\ua0months (April 1, 2015–March 31, 2016) following introduction of a personalised insulin calculator protocol. Variables including body mass index, insulin-dose calculated and/or administered, BGL at baseline and nadir, and time to FDG injection were analysed. There were 115 and 136 patients treated with insulin in Cohorts 1 and 2 respectively, with similar baseline variables including mean BGL (14.5 vs 14.4 mmol/L) and range (10.5–22.7 vs 10.4–24.3 mmol/L). Use of the new personalised insulin calculator resulted in significantly fewer hypoglycaemic events (0.7% vs 5.2%; P < 0.03), shorter median time from insulin to FDG injections (108 min vs 136 min; P < 0.001) and greater individualised range in insulin prescription (3–32 IU vs 4–20 IU). The majority of patients (88.3%) receiving the personalised insulin calculator prescribed dose achieved BGL < 10.0 mmol/L. All scans obtained were of diagnostic quality. Conclusions: The use of our personalised insulin calculator protocol effectively lowered BGL to the target range, resulted in significantly fewer hypoglycaemic events and reduced median time between insulin and FDG injection compared to a pre-existing empiric protocol whilst achieving diagnostic scans