Terminated LDPC Convolutional Codes with Thresholds Close to Capacity

An ensemble of LDPC convolutional codes with parity-check matrices composed of permutation matrices is considered. The convergence of the iterative belief propagation based decoder for terminated convolutional codes in the ensemble is analyzed for binary-input output-symmetric memoryless channels using density evolution techniques. We observe that the structured irregularity in the Tanner graph of the codes leads to significantly better thresholds when compared to corresponding LDPC block codes.Comment: To appear in the proceedings of the 2005 IEEE International Symposium on Information Theory, Adelaide, Australia, September 4-9, 200

Recombinant gamma interferon induces hypertriglyceridemia and inhibits post-heparin lipase activity in cancer patients.

Animals suffering from malignancy or chronic infection develop characteristic metabolic abnormalities, including a well-defined hypertriglyceridemic state. These abnormalities have been attributed to release of one or more mediators from activated macrophages. We report that cancer patients receiving RIFN-gamma, a potent macrophage activator, at doses of greater than or equal to 0.25 mg/m2/d i.m. show marked increases in triglyceride but not in cholesterol levels (pretreatment triglyceride level of 180 +/- 190 mg/dl [mean +/- SD] vs. a day-14 level of 370 +/- 242 mg/dl, n = 23, p less than 0.001 by the paired t test). This hypertriglyceridemia was characterized by an increase in very low-density lipoproteins and a decrease in plasma post-heparin lipase activity, consistent with defective triglyceride clearance (mean pretreatment lipase level of 2.1 mumol/ml/h vs. a day-14 level of 1.2 mumol/ml/h, n = 6, p = 0.02 by the paired t test). rIFN-gamma did not directly inhibit lipoprotein lipase enzymatic activity in vitro. Other possible mechanisms of action, such as suppression of lipase by an rIFN-gamma-induced mediator released from activated macrophages, or a direct effect of interferon on lipase biosynthesis, require further investigation. Our observations provide evidence that factors produced by the immune system can regulate lipid metabolism in man

Learning a Static Analyzer from Data

To be practically useful, modern static analyzers must precisely model the effect of both, statements in the programming language as well as frameworks used by the program under analysis. While important, manually addressing these challenges is difficult for at least two reasons: (i) the effects on the overall analysis can be non-trivial, and (ii) as the size and complexity of modern libraries increase, so is the number of cases the analysis must handle. In this paper we present a new, automated approach for creating static analyzers: instead of manually providing the various inference rules of the analyzer, the key idea is to learn these rules from a dataset of programs. Our method consists of two ingredients: (i) a synthesis algorithm capable of learning a candidate analyzer from a given dataset, and (ii) a counter-example guided learning procedure which generates new programs beyond those in the initial dataset, critical for discovering corner cases and ensuring the learned analysis generalizes to unseen programs. We implemented and instantiated our approach to the task of learning JavaScript static analysis rules for a subset of points-to analysis and for allocation sites analysis. These are challenging yet important problems that have received significant research attention. We show that our approach is effective: our system automatically discovered practical and useful inference rules for many cases that are tricky to manually identify and are missed by state-of-the-art, manually tuned analyzers

Distribution of Capillary Transit Times in Isolated Lungs of Oxygen-Tolerant Rats

Rats pre-exposed to 85% O2 for 5–7 days tolerate the otherwise lethal effects of 100% O2. The objective was to evaluate the effect of rat exposure to 85% O2 for 7 days on lung capillary mean transit time (t¯c) and distribution of capillary transit times (h c(t)). This information is important for subsequent evaluation of the effect of this hyperoxia model on the redox metabolic functions of the pulmonary capillary endothelium. The venous concentration vs. time outflow curves of fluorescein isothiocyanate labeled dextran (FITC-dex), an intravascular indicator, and coenzyme Q1 hydroquinone (CoQ1H2), a compound which rapidly equilibrates between blood and tissue on passage through the pulmonary circulation, were measured following their bolus injection into the pulmonary artery of isolated perfused lungs from rats exposed to room air (normoxic) or 85% O2 for 7 days (hyperoxic). The moments (mean transit time and variance) of the measured FITC-dex and CoQ1H2 outflow curves were determined for each lung, and were then used in a mathematical model [Audi et al. J. Appl. Physiol. 77: 332–351, 1994] to estimate t¯c and the relative dispersion (RDc) of h c(t). Data analysis reveals that exposure to hyperoxia decreases lung t¯c by 42% and increases RDc, a measure h c(t) heterogeneity, by 40%

How does predicate invention affect human comprehensibility?

During the 1980s Michie defined Machine Learning in terms of two orthogonal axes of performance: predictive accuracy and comprehensibility of generated hypotheses. Since predictive accuracy was readily measurable and comprehensibility not so, later definitions in the 1990s, such as that of Mitchell, tended to use a one-dimensional approach to Machine Learning based solely on predictive accuracy, ultimately favouring statistical over symbolic Machine Learning approaches. In this paper we provide a definition of comprehensibility of hypotheses which can be estimated using human participant trials. We present the results of experiments testing human comprehensibility of logic programs learned with and without predicate invention. Results indicate that comprehensibility is affected not only by the complexity of the presented program but also by the existence of anonymous predicate symbols

Signal peptide peptidases and gamma-secretase: Cousins of the same protease family?

Signal peptide peptidase (SPIP) is an unusual aspartyl protease, which mediates clearance of signal peptides by proteolysis within the endoplasmic reticulum (ER). Like presenilins, which provide the proteolytically active subunit of the,gamma-secretase complex, SPP contains a conserved GxGD motif in its C-terminal domain which is critical for its activity. While SPIP is known to be an aspartyl protease of the GxGD type, several presenilin homologues/SPP-like proteins (PSHs/ SPPL) of unknown function have been identified by database searches. In contrast to SPP and SPPL3, which are both restricted to the endoplasmic reticulum, SPPL2b is targeted through the secretory pathway to endosomes/lysosomes. As suggested by the differential subcellular localization of SPPL2b and SPPL3 distinct phenotypes were found upon antisense gripNA-mediated knockdown in zebrafish. spp and sppl3 knockdowns in zebrafish result in cell death within the central nervous system, whereas reduction of sppl2b expression causes erythrocyte accumulation in an enlarged caudal vein. Moreover, expression of D/A mutants of the putative C-terminal active sites of spp, sppl2, and spp13 produced phenocopies of the respective knockdown phenotypes. These data suggest that all investigated PSHs/SPPLs are members of the novel family of GxGD aspartyl proteases. More recently, it was shown that SPPL2b utilizes multiple intramembrane cleavages to liberate the TNF(x intracellular domain into the cytosol and to release the C-terminal counterpart into the lumen. These findings suggest common principles of intramembrane proteolysis by GxGD type aspartyl proteases. In this article,we will review the similarities of SPPs and gamma-secretase based on recent findings by us and others

Asymptotically Good LDPC Convolutional Codes Based on Protographs

LDPC convolutional codes have been shown to be capable of achieving the same capacity-approaching performance as LDPC block codes with iterative message-passing decoding. In this paper, asymptotic methods are used to calculate a lower bound on the free distance for several ensembles of asymptotically good protograph-based LDPC convolutional codes. Further, we show that the free distance to constraint length ratio of the LDPC convolutional codes exceeds the minimum distance to block length ratio of corresponding LDPC block codes.Comment: Proceedings of the 2008 IEEE International Symposium on Information Theory, Toronto, ON, Canada, July 6 - 11, 200

Non-invasive testing for liver pathology in alpha-1 antitrypsin deficiency

BACKGROUND: Many patients with alpha-1 antitrypsin deficiency (A1ATD) receive care in respiratory clinics without access to specialist hepatology expertise. Liver disease can develop asymptomatically, and non-invasive markers of fibrosis may help identify patients who require definitive assessment with liver biopsy. We evaluated the utility of non-invasive markers of liver fibrosis in A1ATD to guide testing in settings without ready access to hepatology expertise. METHODS: Patients attending the London A1ATD service undergo assessment using blood tests to calculate the 'APRI' and 'FIB-4' score, liver ultrasound and Fibroscan. Liver biopsy is offered to patients who have abnormal liver function tests with abnormal liver ultrasound and/or liver stiffness >6 kPa on Fibroscan. Liver biopsies were assessed for the presence of A1AT, steatosis, fibrosis and inflammation. RESULTS: 75 patients with A1ATD had results for analysis, 56% were female, age 16-82 years. 75% of patients had Fibroscan 8 kPa. There was a significant correlation between FIB-4 and Fibroscan (r=0.244, p=0.035). Fibroscan >6 kPa corresponded to a FIB-4 score of >1.26. However, FIB-4 >1.26 had poor sensitivity (47%), specificity (32%) and positive-predictive value (PPV; 36%) to identify Fibroscan >6 kPa. The negative-predictive value (NPV) was stronger at 81%. APRI data were similar. Twelve patients underwent liver biopsy, with 11 reports available for analysis. Six had FIB-4 scores<1.26 and five had Fibroscan of <6 kPa. A1AT was present in 64% of biopsies, steatosis in 82%, mild fibrosis in 36%, moderate fibrosis in 9% and severe fibrosis in 9%. CONCLUSION: A combination of liver ultrasound and non-invasive fibrosis tests can help identify patients with A1ATD liver injury. However, APRI and FIB-4 scores alone had poor sensitivity and specificity to justify use as an independent tool for liver pathology in A1ATD