Fine grained process modelling: An experiment at British Airways

We report on the experimental application of process technology at British Airways (BA). We used SLANG to model BA's C++ class library management process, and we constructed an experimental process centred software engineering environment (PSEE) based on SPADE. BA required processes to be automated at a finer degree of granularity than tool invocation. We have demonstrated that SLANG and SPADE offer the basic mechanisms for modelling these fine grained processes. We have also shown that it is feasible to generate tools for dedicated processes and integrate them with a SLANG model so as to facilitate fine grained process automation. However, our experience highlighted some open problems. For instance, SLANG process models are tuned to efficient enactment, thus containing very detailed process fragments. These are not the most appropriate representation for humans trying to understand the process model. A more comprehensible notation is needed for design and documentation purposes. Although the airline did not deploy the PSEE in its production environment, the experiment proved beneficial for BA. The modelling uncovered serious flaws in the existing process, and the BA engineers improved their knowledge of process technology

Application of an artificial neural network (ANN) for the identification of grapevine genotypes

Neural networks were employed to distinguish between 15 accessions of "coloured" (fruit gives intense red colour to the wine) grapevines found in some viticultural zones of Tuscany. Our results enabled us to distinguish, with considerable certainty, between 9 accessions and to denote three pairs of synonyms. The use of neural networks opens interesting prospects for ampelography; its advantages over traditional ampelographic methods are demonstrated

Relationship between bone cross-sectional area and indices of peripheral artery disease

Most studies on the relationship between bone mineral density and atherosclerosis have used dual-energy X-ray absorptiometry, but this method is relatively insensitive to bone geometry. The aim of this study was to investigate the relationship between bone area and indices of carotid and peripheral atherosclerosis. We studied 841 persons aged 65 years or older (women = 444, mean age 73.8 years; men = 397, mean age = 75.3 years) enrolled in the InCHIANTI study and free from active malignancies, chronic use of bisphosphonates or steroids, and estrogen replacement therapy. The tibial cortical and total cross-sectional area (CSA) were measured by peripheral quantitative computed tomography and their ratio was calculated (cortical/total cross-sectional area ratio, cCSA/tCSA); carotid plaques were screened by echography, and peripheral artery disease (PAD) was defined as an ankle/brachial index <0.9 or presence of intermittent claudication. No association between cCSA/tCSA and atherosclerosis was observed in men. In women, lower cCSA/tCSA was associated with both carotid plaques [odds ratio (OR) for lowest vs. best quartile = 2.09, 95 % confidence interval (CI) 1.2-3.68] and PAD (OR = 3.43, 95 % CI 1.58-8.12). After correction for potential confounders (age since menopause, body mass index, Parathyroid hormone, vitamin D, leptin, DHEA-S, testosterone, physical activity, chronic obstructive pulmonary disease, and reduced renal function), the association was not confirmed. According to partial logistic regression, the carotid plaque-cCSA/tCSA association, but not the PAD-cCSA/tCSA association, was mostly dependent on years since menopause. In women the association between osteoporosis and carotid plaques likely reflects hormonal deprivation, whereas that between osteoporosis and PAD seems multifactorial in origin. © 2013 Springer Science+Business Media New York

The transcript expression levels of HNRNPM, HNRNPA0 and AKAP17A splicing factors may be predictively associated with ageing phenotypes in human peripheral blood

Dysregulation of splicing factor expression is emerging as a driver of human ageing; levels of transcripts encoding splicing regulators have previously been implicated in ageing and cellular senescence both in vitro and in vivo. We measured the expression levels of an a priori panel of 20 age- or senescence-associated splicing factors by qRT-PCR in peripheral blood samples from the InCHIANTI Study of Aging, and assessed longitudinal relationships with human ageing phenotypes (cognitive decline and physical ability) using multivariate linear regression. AKAP17A, HNRNPA0 and HNRNPM transcript levels were all predictively associated with severe decline in MMSE score (p = 0.007, 0.001 and 0.008 respectively). Further analyses also found expression of these genes was associated with a performance decline in two other cognitive measures; the Trail Making Test and the Purdue Pegboard Test. AKAP17A was nominally associated with a decline in mean hand-grip strength (p = 0.023), and further analyses found nominal associations with two other physical ability measures; the Epidemiologic Studies of the Elderly-Short Physical Performance Battery and calculated speed (m/s) during a timed 400 m fast walking test. These data add weight to the hypothesis that splicing dyregulation may contribute to the development of some ageing phenotypes in the human population.This article is freely available via Open Access. Click on the Publisher URL to access it via the publisher's site.This work was funded by the Velux Stiftung Foundation (Grant Number 822) and supported in part by the Intramural Research Program of the NIH, National institute on Aging.published version, accepted version (12 month embargo

Association between the multidimensional prognostic index and mortality during 15 Years of Follow-up in the InCHIANTI Study

Background: Multidimensional Prognostic Index (MPI) is recognized as a prognostic tool in hospitalized patients, but data on the value of MPI in community-dwelling older persons are limited. Using data from a representative cohort of community-dwelling persons, we tested the hypothesis that MPI explains mortality during 15 years of follow-up. Methods: A standardized comprehensive geriatric assessment was used to calculate the MPI and to categorize participants in low-, moderate-, and high-risk classes. The results were reported as hazard ratios (HRs) and the accuracy was evaluated with the area under the curve (AUC), with 95% confidence intervals (CIs) and the C-index. We also reported the median survival time by standard age groups. Results: All 1453 participants (mean age 68.9 years, women = 55.8%) enrolled in the InCHIANTI study at baseline were included. Compared to low-risk group, participants in moderate (HR = 2.10; 95% CI: 1.73-2.55) and high-risk MPI group (HR = 4.94; 95% CI: 3.91-6.24) had significantly higher mortality risk. The C-index of the model containing age, sex, and MPI was 82.1, indicating a very good accuracy of this model in explaining mortality. Additionally, the time-dependent AUC indicated that the accuracy of the model incorporating MPI to age and sex was excellent (>85.0) during the whole follow-up period. Compared to participants in the low-risk MPI group across different age groups, those in moderate- and high-risk groups survived 2.9-7.0 years less and 4.3-8.9 years less, respectively. Conclusions: In community-dwelling individuals, higher MPI values are associated with higher risk of all-cause mortality with a dose-response effect. © 2020 The Author(s) 2020

FRAT-up, a Web-based fall-risk assessment tool for elderly people living in the community.

Background: About 30% of people over 65 are subject to at least one unintentional fall a year. Fall prevention protocols and interventions can decrease the number of falls. To be effective, a prevention strategy requires a prior step to evaluate the fall risk of the subjects. Despite extensive research, existing assessment tools for fall risk have been insufficient for predicting falls. Objective: The goal of this study is to present a novel web-based fall-risk assessment tool (FRAT-up) and to evaluate its accuracy in predicting falls, within a context of community-dwelling persons aged 65 and up. Methods: FRAT-up is based on the assumption that a subject\u2019s fall risk is given by the contribution of their exposure to each of the known fall-risk factors. Many scientific studies have investigated the relationship between falls and risk factors. The majority of these studies adopted statistical approaches, usually providing quantitative information such as odds ratios. FRAT-up exploits these numerical results to compute how each single factor contributes to the overall fall risk. FRAT-up is based on a formal ontology that enlists a number of known risk factors, together with quantitative findings in terms of odds ratios. From such information, an automatic algorithm generates a rule-based probabilistic logic program, that is, a set of rules for each risk factor. The rule-based program takes the health profile of the subject (in terms of exposure to the risk factors) and computes the fall risk. A Web-based interface allows users to input health profiles and to visualize the risk assessment for the given subject. FRAT-up has been evaluated on the InCHIANTI Study dataset, a representative population-based study of older persons living in the Chianti area (Tuscany, Italy). We compared reported falls with predicted ones and computed performance indicators. Results: The obtained area under curve of the receiver operating characteristic was 0.642 (95% CI 0.614-0.669), while the Brier score was 0.174. The Hosmer-Lemeshow test indicated statistical significance of miscalibration. Conclusions: FRAT-up is a web-based tool for evaluating the fall risk of people aged 65 or up living in the community. Validation results of fall risks computed by FRAT-up show that its performance is comparable to externally validated state-of-the-art tools. A prototype is freely available through a web-based interface. Trial Registration: ClinicalTrials.gov NCT01331512 (The InChianti Follow-Up Study); http://clinicaltrials.gov/show/NCT01331512 (Archived by WebCite at http://www.webcitation.org/6UDrrRuaR)

Astrocyte senescence may drive alterations in GFAPα, CDKN2A p14ARF, and TAU3 transcript expression and contribute to cognitive decline

The accumulation of senescent cells in tissues is causally linked to the development of several age-related diseases; the removal of senescent glial cells in animal models prevents Tau accumulation and cognitive decline. Senescent cells can arise through several distinct mechanisms; one such mechanism is dysregulation of alternative splicing. In this study, we characterised the senescent cell phenotype in primary human astrocytes in terms of SA-β-Gal staining and SASP secretion, and then assessed splicing factor expression and candidate gene splicing patterns. Finally, we assessed associations between expression of dysregulated isoforms and premature cognitive decline in 197 samples from the InCHIANTI study of ageing, where expression was present in both blood and brain. We demonstrate here that senescent astrocytes secrete a modified SASP characterised by increased IL8, MMP3, MMP10, and TIMP2 but decreased IL10 levels. We identified significant changes in splicing factor expression for 10/20 splicing factors tested in senescent astrocytes compared with early passage cells, as well as dysregulation of isoform levels for 8/13 brain or senescence genes tested. Finally, associations were identified between peripheral blood GFAPα, TAU3, and CDKN2A (P14ARF) isoform levels and mild or severe cognitive decline over a 3-7-year period. Our data are suggestive that some of the features of cognitive decline may arise from dysregulated splicing of important genes in senescent brain support cells, and that defects in alternative splicing or splicing regulator expression deserve exploration as points of therapeutic intervention in the future.This article is freely available under Open Access. Click on the Publisher URL to access the full-text