Dynamic compact thermal models with multiple power sources: application to an ultrathin chip stacking technology

Whereas numerical modeling using finite-element methods (FEM) can provide transient temperature distribution in the component with enough accuracy, it is of the most importance the development of compact dynamic thermal models that can be used for electrothermal simulation. While in most cases single power sources are considered, here we focus on the simultaneous presence of multiple sources. The thermal model will be in the form of a thermal impedance matrix containing the thermal impedance transfer functions between two arbitrary ports. Eachindividual transfer function element ( ) is obtained from the analysis of the thermal temperature transient at node ¿ ¿ after a power step at node ¿ .¿ Different options for multiexponential transient analysis are detailed and compared. Among the options explored, small thermal models can be obtained by constrained nonlinear least squares (NLSQ) methods if the order is selected properly using validation signals. The methods are applied to the extraction of dynamic compact thermal models for a new ultrathin chip stack technology (UTCS).

SBML qualitative models: a model representation format and infrastructure to foster interactions between qualitative modelling formalisms and tools.

BACKGROUND: Qualitative frameworks, especially those based on the logical discrete formalism, are increasingly used to model regulatory and signalling networks. A major advantage of these frameworks is that they do not require precise quantitative data, and that they are well-suited for studies of large networks. While numerous groups have developed specific computational tools that provide original methods to analyse qualitative models, a standard format to exchange qualitative models has been missing. RESULTS: We present the Systems Biology Markup Language (SBML) Qualitative Models Package ("qual"), an extension of the SBML Level 3 standard designed for computer representation of qualitative models of biological networks. We demonstrate the interoperability of models via SBML qual through the analysis of a specific signalling network by three independent software tools. Furthermore, the collective effort to define the SBML qual format paved the way for the development of LogicalModel, an open-source model library, which will facilitate the adoption of the format as well as the collaborative development of algorithms to analyse qualitative models. CONCLUSIONS: SBML qual allows the exchange of qualitative models among a number of complementary software tools. SBML qual has the potential to promote collaborative work on the development of novel computational approaches, as well as on the specification and the analysis of comprehensive qualitative models of regulatory and signalling networks.

Pattern recognition ecological niche models fit to presence-only and presence-absence data

1. Identifying the boundary of a species' niche from observational and environmental data is a common problem in ecology and conservation biology and a variety of techniques have been developed or applied to model niches and predict distributions. Here, we examine the performance of some pattern-recognition methods as ecological niche models (ENMs). Particularly, one-class pattern recognition is a flexible and seldom used methodology for modelling ecological niches and distributions from presence-only data. The development of one-class methods that perform comparably to two-class methods (for presence/absence data) would remove modelling decisions about sampling pseudo-absences or background data points when absence points are unavailable. 2. We studied nine methods for one-class classification and seven methods for two-class classification (five common to both), all primarily used in pattern recognition and therefore not common in species distribution and ecological niche modelling, across a set of 106 mountain plant species for which presence-absence data was available. We assessed accuracy using standard metrics and compared trade-offs in omission and commission errors between classification groups as well as effects of prevalence and spatial autocorrelation on accuracy. 3. One-class models fit to presence-only data were comparable to two-class models fit to presence-absence data when performance was evaluated with a measure weighting omission and commission errors equally. One-class models were superior for reducing omission errors (i.e. yielding higher sensitivity), and two-classes models were superior for reducing commission errors (i.e. yielding higher specificity). For these methods, spatial autocorrelation was only influential when prevalence was low. 4. These results differ from previous efforts to evaluate alternative modelling approaches to build ENM and are particularly noteworthy because data are from exhaustively sampled populations minimizing false absence records. Accurate, transferable models of species' ecological niches and distributions are needed to advance ecological research and are crucial for effective environmental planning and conservation; the pattern-recognition approaches studied here show good potential for future modelling studies. This study also provides an introduction to promising methods for ecological modelling inherited from the pattern-recognition discipline.

Development of an Fn14 agonistic antibody as an anti-tumor agent.

TWEAK, a TNF family ligand with pleiotropic cellular functions, was originally described as capable of inducing tumor cell death in vitro. TWEAK functions by binding its receptor, Fn14, which is up-regulated on many human solid tumors. Herein, we show that intratumoral administration of TWEAK, delivered either by an adenoviral vector or in an immunoglobulin Fc-fusion form, results in significant inhibition of tumor growth in a breast xenograft model. To exploit the TWEAK-Fn14 pathway as a therapeutic target in oncology, we developed an anti-Fn14 agonistic antibody, BIIB036. Studies described herein show that BIIB036 binds specifically to Fn14 but not other members of the TNF receptor family, induces Fn14 signaling, and promotes tumor cell apoptosis in vitro. In vivo, BIIB036 effectively inhibits growth of tumors in multiple xenograft models, including colon (WiDr), breast (MDA-MB-231), and gastric (NCI-N87) tumors, regardless of tumor cell growth inhibition response observed to BIIB036 in vitro. The anti-tumor activity in these cell lines is not TNF-dependent. Increasing the antigen-binding valency of BIB036 significantly enhances its anti-tumor effect, suggesting the contribution of higher order cross-linking of the Fn14 receptor. Full Fc effector function is required for maximal activity of BIIB036 in vivo, likely due to the cross-linking effect and/or ADCC mediated tumor killing activity. Taken together, the anti-tumor properties of BIIB036 validate Fn14 as a promising target in oncology and demonstrate its potential therapeutic utility in multiple solid tumor indications.

Ruling out coronary artery disease in primary care: development and validation of a simple prediction rule.

BACKGROUND: Chest pain can be caused by various conditions, with life-threatening cardiac disease being of greatest concern. Prediction scores to rule out coronary artery disease have been developed for use in emergency settings. We developed and validated a simple prediction rule for use in primary care. METHODS: We conducted a cross-sectional diagnostic study in 74 primary care practices in Germany. Primary care physicians recruited all consecutive patients who presented with chest pain (n = 1249) and recorded symptoms and findings for each patient (derivation cohort). An independent expert panel reviewed follow-up data obtained at six weeks and six months on symptoms, investigations, hospital admissions and medications to determine the presence or absence of coronary artery disease. Adjusted odds ratios of relevant variables were used to develop a prediction rule. We calculated measures of diagnostic accuracy for different cut-off values for the prediction scores using data derived from another prospective primary care study (validation cohort). RESULTS: The prediction rule contained five determinants (age/sex, known vascular disease, patient assumes pain is of cardiac origin, pain is worse during exercise, and pain is not reproducible by palpation), with the score ranging from 0 to 5 points. The area under the curve (receiver operating characteristic curve) was 0.87 (95% confidence interval [CI] 0.83-0.91) for the derivation cohort and 0.90 (95% CI 0.87-0.93) for the validation cohort. The best overall discrimination was with a cut-off value of 3 (positive result 3-5 points; negative result <or= 2 points), which had a sensitivity of 87.1% (95% CI 79.9%-94.2%) and a specificity of 80.8% (77.6%-83.9%). INTERPRETATION: The prediction rule for coronary artery disease in primary care proved to be robust in the validation cohort. It can help to rule out coronary artery disease in patients presenting with chest pain in primary care.

The role of microRNAs in the development of type 2 diabets

Pancreatic ß cells are highly specialized endocrine cells located within the islets of Langerhans in the pancreas. Their main role is to produce and secrete insulin, the hormone essential for the regulation of glucose homeostasis and body's metabolism. Diabetes mellitus develops when the amount of insulin released by ß cells is not sufficient to cover the metabolic demand. In type 1 diabetes (5-10% of diagnoses) insulin deficiency is caused by the autoimmune destruction of pancreatic ß cells. Type 2 diabetes (90% of diagnoses) results from a genetic predisposition and from the presence of adverse environmental conditions. The combination of these factors reduces insulin sensitivity of peripheral target tissues, causes impairment in ß-cell function and can lead to partial loss of ß cells. The development of novel therapeutic strategies for the treatment of diabetes necessitates the comprehension of the cellular processes involved in dysfunction and loss of ß cells. My thesis was focused on the involvement in the physiopathological processes leading to the development of diabetes of a class of small regulatory RNA molecules, called microRNAs (miRNAs) that post- transcriptionally regulate gene expression. Global miRNA profiling in pancreatic islets of two animal models of diabetes, the db/db mice and mice that were fed a high fat diet (HFD), characterized by obesity and insulin resistance, led us to identify two groups of miRNAs displaying expression changes under pre-diabetic and diabetic conditions. Among the miRNAs already upregulated in pre-diabetic db/db mice and HFD mice, miR- 132 was found to have beneficial effects on pancreatic ß cell function and survival. Indeed, mimicking the upregulation of miR-132 in primary pancreatic islet cells and ß-cell lines improved glucose- induced insulin secretion and favored survival of the cells upon exposure to pro-apoptotic stimuli such as palmitate and cytokines. MiR-132 was found to exert its action by enhancing the expression of MafA, a transcription factor essential for ß-cell function, survival and identity. On the other hand, up-regulation of miR-199a-5p and miR-199a-3p was detectable only in the islets of diabetic db/db mice and resulted in impaired insulin secretion and sensitization of the cells to apoptosis. MiR-199a- 5p was found to decrease insulin secretion by inducing the expression of granuphilin, a potent inhibitor of ß cell exocytosis. In contrast, miR-199a-3p was demonstrated to directly target and reduce the expression of two key ß-cell genes, mTOR and cMET, resulting in impaired ß-cell adaptation to metabolic demands and loss by apoptosis. Our findings suggest that miRNAs are important players in the onset of type 2 diabetes. MiRNA expression is adjusted in pancreatic ß cells exposed to a diabetogenic environment. These changes initially concern miRNAs responsible for adaptive processes aimed at compensating the onset of insulin resistance, but later such changes can be overlapped by modifications in the level of several additional miRNAs that favor ß-cell failure and the onset of type 2 diabetes.

On the problematic of reserving and stochastic loss models

Abstract Traditionally, the common reserving methods used by the non-life actuaries are based on the assumption that future claims are going to behave in the same way as they did in the past. There are two main sources of variability in the processus of development of the claims: the variability of the speed with which the claims are settled and the variability between the severity of the claims from different accident years. High changes in these processes will generate distortions in the estimation of the claims reserves. The main objective of this thesis is to provide an indicator which firstly identifies and quantifies these two influences and secondly to determine which model is adequate for a specific situation. Two stochastic models were analysed and the predictive distributions of the future claims were obtained. The main advantage of the stochastic models is that they provide measures of variability of the reserves estimates. The first model (PDM) combines one conjugate family Dirichlet - Multinomial with the Poisson distribution. The second model (NBDM) improves the first one by combining two conjugate families Poisson -Gamma (for distribution of the ultimate amounts) and Dirichlet Multinomial (for distribution of the incremental claims payments). It was found that the second model allows to find the speed variability in the reporting process and development of the claims severity as function of two above mentioned distributions' parameters. These are the shape parameter of the Gamma distribution and the Dirichlet parameter. Depending on the relation between them we can decide on the adequacy of the claims reserve estimation method. The parameters have been estimated by the Methods of Moments and Maximum Likelihood. The results were tested using chosen simulation data and then using real data originating from the three lines of business: Property/Casualty, General Liability, and Accident Insurance. These data include different developments and specificities. The outcome of the thesis shows that when the Dirichlet parameter is greater than the shape parameter of the Gamma, resulting in a model with positive correlation between the past and future claims payments, suggests the Chain-Ladder method as appropriate for the claims reserve estimation. In terms of claims reserves, if the cumulated payments are high the positive correlation will imply high expectations for the future payments resulting in high claims reserves estimates. The negative correlation appears when the Dirichlet parameter is lower than the shape parameter of the Gamma, meaning low expected future payments for the same high observed cumulated payments. This corresponds to the situation when claims are reported rapidly and fewer claims remain expected subsequently. The extreme case appears in the situation when all claims are reported at the same time leading to expectations for the future payments of zero or equal to the aggregated amount of the ultimate paid claims. For this latter case, the Chain-Ladder is not recommended.

Official Positions for FRAX® clinical regarding smoking from Joint Official Positions Development Conference of the International Society for Clinical Densitometry and International Osteoporosis Foundation on FRAX®.

The worldwide prevalence of smoking has been estimated at about 50% in men, and 10% in women, with larger variations among different populations studied. Smoking has been shown to affect many organ systems resulting in severe morbidity and increased mortality. In addition, smoking has been identified as a predictor of ten-year fracture risk in men and women, largely independent of an individual's bone mineral density. This finding has eventually lead to incorporation of this risk factor into FRAX®, an algorithm that has been developed to calculate an individual's ten-year fracture risk. However, only little, or conflicting data is available on a possible association between smoking dose, duration, length of time after cessation, type of tobacco and fracture risk, limiting this risk factor's applicability in the context of FRAX®.

The hourglass and the early conservation models--co-existing patterns of developmental constraints in vertebrates.

Developmental constraints have been postulated to limit the space of feasible phenotypes and thus shape animal evolution. These constraints have been suggested to be the strongest during either early or mid-embryogenesis, which corresponds to the early conservation model or the hourglass model, respectively. Conflicting results have been reported, but in recent studies of animal transcriptomes the hourglass model has been favored. Studies usually report descriptive statistics calculated for all genes over all developmental time points. This introduces dependencies between the sets of compared genes and may lead to biased results. Here we overcome this problem using an alternative modular analysis. We used the Iterative Signature Algorithm to identify distinct modules of genes co-expressed specifically in consecutive stages of zebrafish development. We then performed a detailed comparison of several gene properties between modules, allowing for a less biased and more powerful analysis. Notably, our analysis corroborated the hourglass pattern at the regulatory level, with sequences of regulatory regions being most conserved for genes expressed in mid-development but not at the level of gene sequence, age, or expression, in contrast to some previous studies. The early conservation model was supported with gene duplication and birth that were the most rare for genes expressed in early development. Finally, for all gene properties, we observed the least conservation for genes expressed in late development or adult, consistent with both models. Overall, with the modular approach, we showed that different levels of molecular evolution follow different patterns of developmental constraints. Thus both models are valid, but with respect to different genomic features.

Cilengitide: an RGD pentapeptide ανβ3 and ανβ5 integrin inhibitor in development for glioblastoma and other malignancies.

Cilengitide, a cyclicized arginine-glycine-aspartic acid-containing pentapeptide, potently blocks ανβ3 and ανβ5 integrin activation. Integrins are upregulated in many malignancies and mediate a wide variety of tumor-stroma interactions. Cilengitide and other integrin-targeting therapeutics have preclinical activity against many cancer subtypes including glioblastoma (GBM), the most common and deadliest CNS tumor. Cilengitide is active against orthotopic GBM xenografts and can augment radiotherapy and chemotherapy in these models. In Phase I and II GBM trials, cilengitide and the combination of cilengitide with standard temozolomide and radiation demonstrate consistent antitumor activity and a favorable safety profile. Cilengitide is currently under evaluation in a pivotal, randomized Phase III study (Cilengitide in Combination With Temozolomide and Radiotherapy in Newly Diagnosed Glioblastoma Phase III Randomized Clinical Trial [CENTRIC]) for newly diagnosed GBM. In addition, randomized controlled Phase II studies with cilengitide are ongoing for non-small-cell lung cancer and squamous cell carcinoma of the head and neck. Cilengitide is the first integrin inhibitor in clinical Phase III development for oncology.

Joint Official Positions of the International Society for Clinical Densitometry and International Osteoporosis Foundation on FRAX(®). Executive Summary of the 2010 Position Development Conference on Interpretation and use of FRAX® in clinical practice.

The International Society for Clinical Densitometry (ISCD) and the International Osteoporosis Foundation (IOF) convened the FRAX(®) Position Development Conference (PDC) in Bucharest, Romania, on November 14, 2010, following a two-day joint meeting of the ISCD and IOF on the "Interpretation and Use of FRAX(®) in Clinical Practice." These three days of critical discussion and debate, led by a panel of international experts from the ISCD, IOF and dedicated task forces, have clarified a number of important issues pertaining to the interpretation and implementation of FRAX(®) in clinical practice. The Official Positions resulting from the PDC are intended to enhance the quality and clinical utility of fracture risk assessment worldwide. Since the field of skeletal assessment is still evolving rapidly, some clinically important issues addressed at the PDCs are not associated with robust medical evidence. Accordingly, some Official Positions are based largely on expert opinion. Despite limitations inherent in such a process, the ISCD and IOF believe it is important to provide clinicians and technologists with the best distillation of current knowledge in the discipline of bone densitometry and provide an important focus for the scientific community to consider. This report describes the methodology and results of the ISCD-IOF PDC dedicated to FRAX(®).

Evidential relevance in scene to offender transfer cases: development and analysis of a likelihood ratio for offence level propositions

The present paper focuses on the analysis and discussion of a likelihood ratio (LR) development for propositions at a hierarchical level known in the context as 'offence level'. Existing literature on the topic has considered LR developments for so-called offender to scene transfer cases. These settings involve-in their simplest form-a single stain found on a crime scene, but with possible uncertainty about the degree to which that stain is relevant (i.e. that it has been left by the offender). Extensions to multiple stains or multiple offenders have also been reported. The purpose of this paper is to discuss a development of a LR for offence level propositions when case settings involve potential transfer in the opposite direction, i.e. victim/scene to offender transfer. This setting has previously not yet been considered. The rationale behind the proposed LR is illustrated through graphical probability models (i.e. Bayesian networks). The role of various uncertain parameters is investigated through sensitivity analyses as well as simulations.

Development of Performance Properties of Ternary Mixtures and Concrete Pavement Mixture Design and Analysis (MDA): Effect of Paste Quality on Fresh and Hardened Properties of Ternary Mixtures, TPF-5(117), 2012

The purpose of this study was to investigate the effect of cement paste quality on the concrete performance, particularly fresh properties, by changing the water-to-cementitious materials ratio (w/cm), type and dosage of supplementary cementitious materials (SCM), and airvoid system in binary and ternary mixtures. In this experimental program, a total matrix of 54 mixtures with w/cm of 0.40 and 0.45; target air content of 2%, 4%, and 8%; a fixed cementitious content of 600 pounds per cubic yard (pcy), and the incorporation of three types of SCMs at different dosages was prepared. The fine aggregate-to- total aggregate ratio was fixed at 0.42. Workability, rheology, air-void system, setting time, strength, Wenner Probe surface resistivity, and shrinkage were determined. The effects of paste variables on workability are more marked at the higher w/cm. The compressive strength is strongly influenced by the paste quality, dominated by w/cm and air content. Surface resistivity is improved by inclusion of Class F fly ash and slag cement, especially at later ages. Ternary mixtures performed in accordance with their ingredients. The data collected will be used to develop models that will be part of an innovative mix proportioning procedure.

Official Positions for FRAX® clinical regarding rheumatoid arthritis from Joint Official Positions Development Conference of the International Society for Clinical Densitometry and International Osteoporosis Foundation on FRAX®.

Rheumatoid arthritis is the only secondary cause of osteoporosis that is considered independent of bone density in the FRAX(®) algorithm. Although input for rheumatoid arthritis in FRAX(®) is a dichotomous variable, intuitively, one would expect that more severe or active disease would be associated with a greater risk for fracture. We reviewed the literature to determine if specific disease parameters or medication use could be used to better characterize fracture risk in individuals with rheumatoid arthritis. Although many studies document a correlation between various parameters of disease activity or severity and decreased bone density, fewer have associated these variables with fracture risk. We reviewed these studies in detail and concluded that disability measures such as HAQ (Health Assessment Questionnaire) and functional class do correlate with clinical fractures but not morphometric vertebral fractures. One large study found a strong correlation with duration of disease and fracture risk but additional studies are needed to confirm this. There was little evidence to correlate other measures of disease such as DAS (disease activity score), VAS (visual analogue scale), acute phase reactants, use of non-glucocorticoid medications and increased fracture risk. We concluded that FRAX(®) calculations may underestimate fracture probability in patients with impaired functional status from rheumatoid arthritis but that this could not be quantified at this time. At this time, other disease measures cannot be used for fracture prediction. However only a few, mostly small studies addressed other disease parameters and further research is needed. Additional questions for future research are suggested.