Identifying component modules

A computer-based system for modelling component dependencies and identifying component modules is presented. A variation of the Dependency Structure Matrix (DSM) representation was used to model component dependencies. The system utilises a two-stage approach towards facilitating the identification of a hierarchical modular structure. The first stage calculates a value for a clustering criterion that may be used to group component dependencies together. A Genetic Algorithm is described to optimise the order of the components within the DSM with the focus of minimising the value of the clustering criterion to identify the most significant component groupings (modules) within the product structure. The second stage utilises a 'Module Strength Indicator' (MSI) function to determine a value representative of the degree of modularity of the component groupings. The application of this function to the DSM produces a 'Module Structure Matrix' (MSM) depicting the relative modularity of available component groupings within it. The approach enabled the identification of hierarchical modularity in the product structure without the requirement for any additional domain specific knowledge within the system. The system supports design by providing mechanisms to explicitly represent and utilise component and dependency knowledge to facilitate the nontrivial task of determining near-optimal component modules and representing product modularity

A novel multi-network approach reveals tissue-specific cellular modulators of fibrosis in systemic sclerosis

BACKGROUND: Systemic sclerosis (SSc) is a multi-organ autoimmune disease characterized by skin fibrosis. Internal organ involvement is heterogeneous. It is unknown whether disease mechanisms are common across all involved affected tissues or if each manifestation has a distinct underlying pathology. METHODS: We used consensus clustering to compare gene expression profiles of biopsies from four SSc-affected tissues (skin, lung, esophagus, and peripheral blood) from patients with SSc, and the related conditions pulmonary fibrosis (PF) and pulmonary arterial hypertension, and derived a consensus disease-associate signature across all tissues. We used this signature to query tissue-specific functional genomic networks. We performed novel network analyses to contrast the skin and lung microenvironments and to assess the functional role of the inflammatory and fibrotic genes in each organ. Lastly, we tested the expression of macrophage activation state-associated gene sets for enrichment in skin and lung using a Wilcoxon rank sum test. RESULTS: We identified a common pathogenic gene expression signature-an immune-fibrotic axis-indicative of pro-fibrotic macrophages (MØs) in multiple tissues (skin, lung, esophagus, and peripheral blood mononuclear cells) affected by SSc. While the co-expression of these genes is common to all tissues, the functional consequences of this upregulation differ by organ. We used this disease-associated signature to query tissue-specific functional genomic networks to identify common and tissue-specific pathologies of SSc and related conditions. In contrast to skin, in the lung-specific functional network we identify a distinct lung-resident MØ signature associated with lipid stimulation and alternative activation. In keeping with our network results, we find distinct MØ alternative activation transcriptional programs in SSc-associated PF lung and in the skin of patients with an "inflammatory" SSc gene expression signature. CONCLUSIONS: Our results suggest that the innate immune system is central to SSc disease processes but that subtle distinctions exist between tissues. Our approach provides a framework for examining molecular signatures of disease in fibrosis and autoimmune diseases and for leveraging publicly available data to understand common and tissue-specific disease processes in complex human diseases

Wide-Scale Analysis of Human Functional Transcription Factor Binding Reveals a Strong Bias towards the Transcription Start Site

We introduce a novel method to screen the promoters of a set of genes with shared biological function, against a precompiled library of motifs, and find those motifs which are statistically over-represented in the gene set. The gene sets were obtained from the functional Gene Ontology (GO) classification; for each set and motif we optimized the sequence similarity score threshold, independently for every location window (measured with respect to the TSS), taking into account the location dependent nucleotide heterogeneity along the promoters of the target genes. We performed a high throughput analysis, searching the promoters (from 200bp downstream to 1000bp upstream the TSS), of more than 8000 human and 23,000 mouse genes, for 134 functional Gene Ontology classes and for 412 known DNA motifs. When combined with binding site and location conservation between human and mouse, the method identifies with high probability functional binding sites that regulate groups of biologically related genes. We found many location-sensitive functional binding events and showed that they clustered close to the TSS. Our method and findings were put to several experimental tests. By allowing a "flexible" threshold and combining our functional class and location specific search method with conservation between human and mouse, we are able to identify reliably functional TF binding sites. This is an essential step towards constructing regulatory networks and elucidating the design principles that govern transcriptional regulation of expression. The promoter region proximal to the TSS appears to be of central importance for regulation of transcription in human and mouse, just as it is in bacteria and yeast.Comment: 31 pages, including Supplementary Information and figure

Integration of decision support systems to improve decision support performance

Decision support system (DSS) is a well-established research and development area. Traditional isolated, stand-alone DSS has been recently facing new challenges. In order to improve the performance of DSS to meet the challenges, research has been actively carried out to develop integrated decision support systems (IDSS). This paper reviews the current research efforts with regard to the development of IDSS. The focus of the paper is on the integration aspect for IDSS through multiple perspectives, and the technologies that support this integration. More than 100 papers and software systems are discussed. Current research efforts and the development status of IDSS are explained, compared and classified. In addition, future trends and challenges in integration are outlined. The paper concludes that by addressing integration, better support will be provided to decision makers, with the expectation of both better decisions and improved decision making processes

Behavior and Impact of Zirconium in the Soil–Plant System: Plant Uptake and Phytotoxicity

Because of the large number of sites they pollute, toxic metals that contaminate terrestrial ecosystems are increasingly of environmental and sanitary concern (Uzu et al. 2010, 2011; Shahid et al. 2011a, b, 2012a). Among such metals is zirconium (Zr), which has the atomic number 40 and is a transition metal that resembles titanium in physical and chemical properties (Zaccone et al. 2008). Zr is widely used in many chemical industry processes and in nuclear reactors (Sandoval et al. 2011; Kamal et al. 2011), owing to its useful properties like hardness, corrosion-resistance and permeable to neutrons (Mushtaq 2012). Hence, the recent increased use of Zr by industry, and the occurrence of the Chernobyl and Fukashima catastrophe have enhanced environmental levels in soil and waters (Yirchenko and Agapkina 1993; Mosulishvili et al. 1994 ; Kruglov et al. 1996)

"I know that you know that I know": neural substrates associated with social cognition deficits in DM1 patients

Myotonic dystrophy type-1 (DM1) is a genetic multi-systemic disorder involving several organs including the brain. Despite the heterogeneity of this condition, some patients with non-congenital DM1 can present with minimal cognitive impairment on formal testing but with severe difficulties in daily-living activities including social interactions. One explanation for this paradoxical mismatch can be found in patients' dysfunctional social cognition, which can be assessed in the framework of the Theory of Mind (ToM). We hypothesize here that specific disease driven abnormalities in DM1 brains may result in ToM impairments. We recruited 20 DM1 patients who underwent the "Reading the Mind in the Eyes" and the ToM-story tests. These patients, together with 18 healthy controls, also underwent resting-state functional MRI. A composite Theory of Mind score was computed for all recruited patients and correlated with their brain functional connectivity. This analysis provided the patients' "Theory of Mind-network", which was compared, for its topological properties, with that of healthy controls. We found that DM1 patients showed deficits in both tests assessing ToM. These deficits were associated with specific patterns of abnormal connectivity between the left inferior temporal and fronto-cerebellar nodes in DM1 brains. The results confirm the previous suggestions of ToM dysfunctions in patients with DM1 and support the hypothesis that difficulties in social interactions and personal relationships are a direct consequence of brain abnormalities, and not a reaction symptom. This is relevant not only for a better pathophysiological comprehension of DM1, but also for non-pharmacological interventions to improve clinical aspects and impact on patients' success in life

An embryonic stem cell–like gene expression signature in poorly differentiated aggressive human tumors

Cancer cells possess traits reminiscent of those ascribed to normal stem cells. It is unclear, however, whether these phenotypic similarities reflect the activity of common molecular pathways. Here, we analyze the enrichment patterns of gene sets associated with embryonic stem (ES) cell identity in the expression profiles of various human tumor types. We find that histologically poorly differentiated tumors show preferential overexpression of genes normally enriched in ES cells, combined with preferential repression of Polycomb-regulated genes. Moreover, activation targets of Nanog, Oct4, Sox2 and c-Myc are more frequently overexpressed in poorly differentiated tumors than in well-differentiated tumors. In breast cancers, this ES-like signature is associated with high-grade estrogen receptor (ER)-negative tumors, often of the basal-like subtype, and with poor clinical outcome. The ES signature is also present in poorly differentiated glioblastomas and bladder carcinomas. We identify a subset of ES cell-associated transcription regulators that are highly expressed in poorly differentiated tumors. Our results reveal a previously unknown link between genes associated with ES cell identity and the histopathological traits of tumors and support the possibility that these genes contribute to stem cell–like phenotypes shown by many tumors

Extensive and coordinated transcription of noncoding RNAs within cell-cycle promoters

Transcription of long noncoding RNAs (lncRNAs) within gene regulatory elements can modulate gene activity in response to external stimuli, but the scope and functions of such activity are not known. Here we use an ultrahigh-density array that tiles the promoters of 56 cell-cycle genes to interrogate 108 samples representing diverse perturbations. We identify 216 transcribed regions that encode putative lncRNAs, many with RT-PCR–validated periodic expression during the cell cycle, show altered expression in human cancers and are regulated in expression by specific oncogenic stimuli, stem cell differentiation or DNA damage. DNA damage induces five lncRNAs from the CDKN1A promoter, and one such lncRNA, named PANDA, is induced in a p53-dependent manner. PANDA interacts with the transcription factor NF-YA to limit expression of pro-apoptotic genes; PANDA depletion markedly sensitized human fibroblasts to apoptosis by doxorubicin. These findings suggest potentially widespread roles for promoter lncRNAs in cell-growth control.National Institutes of Health (U.S.)National Institute of Arthritis and Musculoskeletal and Skin Diseases (U.S.) (NIAMS) (K08-AR054615))National Cancer Institute (U.S.) (NIH/(NCI) (R01-CA118750))National Cancer Institute (U.S.) (NIH/(NCI) R01-CA130795))Juvenile Diabetes Research Foundation InternationalAmerican Cancer SocietyHoward Hughes Medical Institute (Early career scientist)Stanford University (Graduate Fellowship)National Science Foundation (U.S.) (Graduate Research Fellowship)United States. Dept. of Defense (National Defense Science and Engineering Graduate Fellowship

Effects of early feeding on growth velocity and overweight/obesity in a cohort of HIV unexposed South African infants and children

BACKGROUND: South Africa has the highest prevalence of overweight/obesity in Sub-Saharan Africa. Assessing the effect of modifiable factors such as early infant feeding on growth velocity and overweight/obesity is therefore important. This paper aimed to assess the effect of infant feeding in the transitional period (12 weeks) on 12–24 week growth velocity amongst HIV unexposed children using WHO growth velocity standards and on the age and sex adjusted body mass index (BMI) Z-score distribution at 2 years. METHODS: Data were from 3 sites in South Africa participating in the PROMISE-EBF trial. We calculated growth velocity Z-scores using the WHO growth standards and assessed feeding practices using 24-hour and 7-day recall data. We used quantile regression to study the associations between 12 week infant feeding and 12–24 week weight velocity (WVZ) with BMI-for-age Z-score at 2 years. We included the internal sample quantiles (70th and 90th centiles) that approximated the reference cut-offs of +2 (corresponding to overweight) and +3 (corresponding to obesity) of the 2 year BMI-for-age Z-scores. RESULTS: At the 2-year visit, 641 children were analysed (median age 22 months, IQR: 17–26 months). Thirty percent were overweight while 8.7% were obese. Children not breastfed at 12 weeks had higher 12–24 week mean WVZ and were more overweight and obese at 2 years. In the quantile regression, children not breastfed at 12 weeks had a 0.37 (95% CI 0.07, 0.66) increment in BMI-for-age Z-score at the 50th sample quantile compared to breast-fed children. This difference in BMI-for-age Z-score increased to 0.46 (95% CI 0.18, 0.74) at the 70th quantile and 0.68 (95% CI 0.41, 0.94) at the 90th quantile . The 12–24 week WVZ had a uniform independent effect across the same quantiles. CONCLUSIONS: This study demonstrates that the first 6 months of life is a critical period in the development of childhood overweight and obesity. Interventions targeted at modifiable factors such as early infant feeding practices may reduce the risks of rapid weight gain and subsequent childhood overweight/obesity.Scopu

Queen mandibular pheromone: questions that remain to be resolved

The discovery of ‘queen substance’, and the subsequent identification and synthesis of keycomponents of queen mandibular pheromone, has been of significant importance to beekeepers and to thebeekeeping industry. Fifty years on, there is greater appreciation of the importance and complexity of queenpheromones, but many mysteries remain about the mechanisms through which pheromones operate. Thediscovery of sex pheromone communication in moths occurred within the same time period, but in this case,intense pressure to find better means of pest management resulted in a remarkable focusing of research activityon understanding pheromone detection mechanisms and the central processing of pheromone signals in themoth. We can benefit from this work and here, studies on moths are used to highlight some of the gaps in ourknowledge of pheromone communication in bees. A better understanding of pheromone communication inhoney bees promises improved strategies for the successful management of these extraordinary animals