Constraining the low-energy pion electromagnetic form factor with space-like and phase of time-like data

The Taylor coefficients c and d of the EM form factor of the pion are constrained using analyticity, knowledge of the phase of the form factor in the time-like region, 4m(pi)(2) <= t <= t(in) and its value at one space-like point, using as input the (g - 2) of the muon. This is achieved using the technique of Lagrange multipliers, which gives a transparent expression for the corresponding bounds. We present a detailed study of the sensitivity of the bounds to the choice of time-like phase and errors present in the space-like data, taken from recent experiments. We find that our results constrain c stringently. We compare our results with those in the literature and find agreement with the chiral perturbation-theory results for c. We obtain d similar to O(10) GeV-6 when c is set to the chiral perturbation-theory values.

Strategic Analysis: A key factor in developing horticultural supply chains in transitional Asian economies

Globalisation is set to have a major impact on world horticultural production and distribution of fruit and vegetables throughout the world. In contrast to developing countries such as China, production and consumption of fresh fruit and vegetables in most developed countries is relatively static. For developed countries, we are starting to see consolidation in the number of farms producing fruit and vegetables with falling or static prices and real farm incomes. Global supply chains are now dominated by a few large multi-national retailers supplied by preferred trans-national distribution companies. The major competitive advantages that are emerging are consistency of supply of high quality product over an extended season and the control of genetic resources and their marketing. To capture these new competitive advantages, new strategic analyses and planning processes must be implemented. In the past, strategic analyses and planning has been undertaken on an ad hoc basis without accurate global intelligence. In the future, working ‘on the supply chain’ will become equally, if not more important, than working ‘in the supply chain’. A revised approach to strategic planning, which encompasses and adjusts for the changes caused by globalisation, is urgently needed. A new 6-step strategic analyses process is described.

Complement factor C4 and immunoglobulins in recurrent or chronic mucosal infections

The study assessed whether plasma concentrations of complement factors C3, C4, or immunoglobulins, serum classical pathway hemolytyic activity, or polymorphisms in the class I and II HLA genes, isotypes and gene numbers of C4, or allotypes of IgG1 and IgG3 heavy chain genes were associated with severe frequently recurring or chronic mucosal infections. According to strict clinical criteria, 188 consecutive voluntary patients without a known immunodeficiency and 198 control subjects were recruited. Frequencies of low levels in IgG1, IgG2, IgG3 and IgG4 were for the first time tested from adult general population and patients with acute rhinosinusitis. Frequently recurring intraoral herpes simplex type 1 infections, a rare form of the disease, was associated with homozygosity in HLA -A*, -B*, -C*, and -DR* genes. Frequently recurrent genital HSV-2 infections were associated with low levels of IgG1 and IgG3, present in 54% of the recruited patients. This association was partly allotype-dependent. The G3mg,G1ma/ax haplotype, together with low IgG3, was more common in patients than in control subjects who lacked antibodies against herpes simplex viruses. This is the first found immunogenetic deficiency in otherwise healthy adults that predisposes to highly frequent mucosal herpes recurrences. According to previous studies, HSV effectively evades the allotype G1ma/ax of IgG1, whereas G3mg is associated with low IgG3. Certain HLA genes were more common in patients than in control subjects. Having more than one C4A or C4B gene was associated with neuralgias caused by the virus. Low levels of IgA, IgG1, IgG2, IgG3, and IgG4 were common in the general adult population, but even more frequent in patients with chronic sinusitis. Only low IgG1 was more common chronic than in acute rhinosinusitis. Clinically, nasal polyposis and bronchial asthma were associated with complicated disease forms. The best differentiating immunologic parameters were C4A deficiency and the combination of low plasma IgG4 together with low IgG1 or IgG2, performing almost equally. The lack of C4A, IgA, and IgG4, all known to possess anti-inflammatory activity, together with a concurrently impaired immunity caused by low subclass levels, may predispose to chronic disease forms. In severe chronic adult periodontitis, any C4A or C4B deficiency combined was associated with the disease. The new quantitative analysis of C4 genes and the conventional C4 allotyping method complemented each other. Lowered levels of plasma C3 or C4 or both, and serum CH50 were found in herpes and periodontitis patients. In rhinosinusitis, there was a linear trend with the highest levels found in the order: acute > chronic rhinosinusitis > general population > blood donors with no self-reported history of rhinosinusitis. Complement is involved in the defense against the tested mucosal infections. Seemingly immunocompetent patients with chronic or recurrent mucosal infections frequently have subtle weaknesses in different arms of immunity. Their susceptibility to chronic disease forms may be caused by these. Host s subtly impaired immunity often coincides with effective immune evasion from the same arms of immunity by the disease-causing pathogens. The interpretation of low subclass levels, if no additional predisposing immunologic factors are tested, is difficult and of limited value in early diagnosis and treatment.

First-Line afatinib versus chemotherapy in patients with non–small cell lung cancer and common epidermal growth factor receptor gene mutations and brain metastases

Introduction Metastatic spread to the brain is common in patients with non–small cell lung cancer (NSCLC), but these patients are generally excluded from prospective clinical trials. The studies, phase III study of afatinib or cisplatin plus pemetrexed in patients with metastatic lung adenocarcinoma with EGFR mutations (LUX-Lung 3) and a randomized, open-label, phase III study of BIBW 2992 versus chemotherapy as first-line treatment for patients with stage IIIB or IV adenocarcinoma of the lung harbouring an EGFR activating mutation (LUX-Lung 6) investigated first-line afatinib versus platinum-based chemotherapy in epidermal growth factor receptor gene (EGFR) mutation-positive patients with NSCLC and included patients with brain metastases; prespecified subgroup analyses are assessed in this article. Methods For both LUX-Lung 3 and LUX-Lung 6, prespecified subgroup analyses of progression-free survival (PFS), overall survival, and objective response rate were undertaken in patients with asymptomatic brain metastases at baseline (n = 35 and n = 46, respectively). Post hoc analyses of clinical outcomes was undertaken in the combined data set (n = 81). Results In both studies, there was a trend toward improved PFS with afatinib versus chemotherapy in patients with brain metastases (LUX-Lung 3: 11.1 versus 5.4 months, hazard ratio [HR] = 0.54, p = 0.1378; LUX-Lung 6: 8.2 versus 4.7 months, HR = 0.47, p = 0.1060). The magnitude of PFS improvement with afatinib was similar to that observed in patients without brain metastases. In combined analysis, PFS was significantly improved with afatinib versus with chemotherapy in patients with brain metastases (8.2 versus 5.4 months; HR, 0.50; p = 0.0297). Afatinib significantly improved the objective response rate versus chemotherapy in patients with brain metastases. Safety findings were consistent with previous reports. Conclusions These findings lend support to the clinical activity of afatinib in EGFR mutation–positive patients with NSCLC and asymptomatic brain metastases.

Characterization of the human SLC22A18 gene promoter and its regulation by the transcription factor Sp1

SLC22A18, a poly-specific organic cation transporter, is paternally imprinted in humans and mice. It shows loss-of-heterozygosity in childhood and adult tumors, and gain-of-imprinting in hepatocarcinomas and breast cancers. Despite the importance of this gene, its transcriptional regulation has not been studied, and the promoter has not yet been characterized. We therefore set out to identify the potential cis-regulatory elements including the promoter of this gene. The luciferase reporter assay in human cells indicated that a region from -120 by to +78 by is required for the core promoter activity. No consensus TATA or CHAT boxes were found in this region, but two Sp1 binding sites were conserved in human, chimpanzee, mouse and rat. Mutational analysis of the two Sp1 sites suggested their requirement for the promoter activity. Chromatin-immunoprecipitation showed binding of Sp1 to the promoter region in vivo. Overexpression of Sp1 in Drosophila Sp1-null SL2 cells suggested that Sp1 is the transactivator of the promoter. The human core promoter was functional in mouse 3T3 and monkey COS7 cells. We found a CpG island which spanned the core promoter and exon 1. COBRA technique did not reveal promoter methylation in 10 normal oral tissues, 14 oral tumors, and two human cell lines HuH7 and A549. This study provides the first insight into the mechanism that controls expression of this imprinted tumor suppressor gene. A COBRA-based assay has been developed to look for promoter methylation in different cancers. The present data will help to understand the regulation of this gene and its role in tumorigenesis. (C) 2008 Elsevier B.V. All rights reserved.

Characterization of the human SLC22A18 gene promoter and its regulation by the transcription factor Sp1

SLC22A18, a poly-specific organic cation transporter, is paternally imprinted in humans and mice. It shows loss-of-heterozygosity in childhood and adult tumors, and gain-of-imprinting in hepatocarcinomas and breast cancers. Despite the importance of this gene, its transcriptional regulation has not been studied, and the promoter has not yet been characterized. We therefore set out to identify the potential cis-regulatory elements including the promoter of this gene. The luciferase reporter assay in human cells indicated that a region from -120 by to +78 by is required for the core promoter activity. No consensus TATA or CHAT boxes were found in this region, but two Sp1 binding sites were conserved in human, chimpanzee, mouse and rat. Mutational analysis of the two Sp1 sites suggested their requirement for the promoter activity. Chromatin-immunoprecipitation showed binding of Sp1 to the promoter region in vivo. Overexpression of Sp1 in Drosophila Sp1-null SL2 cells suggested that Sp1 is the transactivator of the promoter. The human core promoter was functional in mouse 3T3 and monkey COS7 cells. We found a CpG island which spanned the core promoter and exon 1. COBRA technique did not reveal promoter methylation in 10 normal oral tissues, 14 oral tumors, and two human cell lines HuH7 and A549. This study provides the first insight into the mechanism that controls expression of this imprinted tumor suppressor gene. A COBRA-based assay has been developed to look for promoter methylation in different cancers. The present data will help to understand the regulation of this gene and its role in tumorigenesis. (C) 2008 Elsevier B.V. All rights reserved.

Dynamic Factor Models and Forecasting Finnish Macroeconomic Variables

In recent years, thanks to developments in information technology, large-dimensional datasets have been increasingly available. Researchers now have access to thousands of economic series and the information contained in them can be used to create accurate forecasts and to test economic theories. To exploit this large amount of information, researchers and policymakers need an appropriate econometric model.Usual time series models, vector autoregression for example, cannot incorporate more than a few variables. There are two ways to solve this problem: use variable selection procedures or gather the information contained in the series to create an index model. This thesis focuses on one of the most widespread index model, the dynamic factor model (the theory behind this model, based on previous literature, is the core of the first part of this study), and its use in forecasting Finnish macroeconomic indicators (which is the focus of the second part of the thesis). In particular, I forecast economic activity indicators (e.g. GDP) and price indicators (e.g. consumer price index), from 3 large Finnish datasets. The first dataset contains a large series of aggregated data obtained from the Statistics Finland database. The second dataset is composed by economic indicators from Bank of Finland. The last dataset is formed by disaggregated data from Statistic Finland, which I call micro dataset. The forecasts are computed following a two steps procedure: in the first step I estimate a set of common factors from the original dataset. The second step consists in formulating forecasting equations including the factors extracted previously. The predictions are evaluated using relative mean squared forecast error, where the benchmark model is a univariate autoregressive model. The results are dataset-dependent. The forecasts based on factor models are very accurate for the first dataset (the Statistics Finland one), while they are considerably worse for the Bank of Finland dataset. The forecasts derived from the micro dataset are still good, but less accurate than the ones obtained in the first case. This work leads to multiple research developments. The results here obtained can be replicated for longer datasets. The non-aggregated data can be represented in an even more disaggregated form (firm level). Finally, the use of the micro data, one of the major contributions of this thesis, can be useful in the imputation of missing values and the creation of flash estimates of macroeconomic indicator (nowcasting).

Cooperative Regulation of NOTCH1 Protein-Phosphatidylinositol 3-Kinase (PI3K) Signaling by NOD1, NOD2, and TLR2 Receptors Renders Enhanced Refractoriness to Transforming Growth Factor-beta (TGF-beta)- or Cytotoxic T-lymphocyte Antigen 4 (CTLA-4)-mediated Impairment of Human Dendritic Cell Maturation

Dendritic cells (DCs) as sentinels of the immune system are important for eliciting both primary and secondary immune responses to a plethora of microbial pathogens. Cooperative stimulation of a complex set of pattern-recognition receptors, including TLR2 and nucleotide-binding oligomerization domain (NOD)-like receptors on DCs, acts as a rate-limiting factor in determining the initiation and mounting of the robust immune response. It underscores the need for ``decoding'' these multiple receptor interactions. In this study, we demonstrate that TLR2 and NOD receptors cooperatively regulate functional maturation of human DCs. Intriguingly, synergistic stimulation of TLR2 and NOD receptors renders enhanced refractoriness to TGF-beta- or CTLA-4-mediated impairment of human DC maturation. Signaling perturbation data suggest that NOTCH1-PI3K signaling dynamics assume critical importance in TLR2- and NOD receptor-mediated surmounting of CTLA-4- and TGF-beta -suppressed maturation of human DCs. Interestingly, the NOTCH1-PI3K signaling axis holds the capacity to regulate DC functions by virtue of PKC delta-MAPK-dependent activation of NF-kappa B. This study provides mechanistic and functional insights into TLR2-and NOD receptor-mediated regulation of DC functions and unravels NOTCH1-PI3K as a signaling cohort for TLR2 and NOD receptors. These findings serve in building a conceptual foundation for the design of improved strategies for adjuvants and immunotherapies against infectious diseases.

A constant factor approximation algorithm for boxicity of circular arc graphs

Boxicity of a graph G(V, E) is the minimum integer k such that G can be represented as the intersection graph of k-dimensional axis parallel boxes in Rk. Equivalently, it is the minimum number of interval graphs on the vertex set V such that the intersection of their edge sets is E. It is known that boxicity cannot be approximated even for graph classes like bipartite, co-bipartite and split graphs below O(n0.5-ε)-factor, for any ε > 0 in polynomial time unless NP = ZPP. Till date, there is no well known graph class of unbounded boxicity for which even an nε-factor approximation algorithm for computing boxicity is known, for any ε < 1. In this paper, we study the boxicity problem on Circular Arc graphs - intersection graphs of arcs of a circle. We give a (2+ 1/k)-factor polynomial time approximation algorithm for computing the boxicity of any circular arc graph along with a corresponding box representation, where k ≥ 1 is its boxicity. For Normal Circular Arc(NCA) graphs, with an NCA model given, this can be improved to an additive 2-factor approximation algorithm. The time complexity of the algorithms to approximately compute the boxicity is O(mn+n2) in both these cases and in O(mn+kn2) which is at most O(n3) time we also get their corresponding box representations, where n is the number of vertices of the graph and m is its number of edges. The additive 2-factor algorithm directly works for any Proper Circular Arc graph, since computing an NCA model for it can be done in polynomial time.

A Hybrid Parallel Algorithm for Computing and Tracking Level Set Topology

The contour tree is a topological abstraction of a scalar field that captures evolution in level set connectivity. It is an effective representation for visual exploration and analysis of scientific data. We describe a work-efficient, output sensitive, and scalable parallel algorithm for computing the contour tree of a scalar field defined on a domain that is represented using either an unstructured mesh or a structured grid. A hybrid implementation of the algorithm using the GPU and multi-core CPU can compute the contour tree of an input containing 16 million vertices in less than ten seconds with a speedup factor of upto 13. Experiments based on an implementation in a multi-core CPU environment show near-linear speedup for large data sets.

A constant factor approximation algorithm for boxicity of circular arc graphs

The boxicity (resp. cubicity) of a graph G(V, E) is the minimum integer k such that G can be represented as the intersection graph of axis parallel boxes (resp. cubes) in R-k. Equivalently, it is the minimum number of interval graphs (resp. unit interval graphs) on the vertex set V, such that the intersection of their edge sets is E. The problem of computing boxicity (resp. cubicity) is known to be inapproximable, even for restricted graph classes like bipartite, co-bipartite and split graphs, within an O(n(1-epsilon))-factor for any epsilon > 0 in polynomial time, unless NP = ZPP. For any well known graph class of unbounded boxicity, there is no known approximation algorithm that gives n(1-epsilon)-factor approximation algorithm for computing boxicity in polynomial time, for any epsilon > 0. In this paper, we consider the problem of approximating the boxicity (cubicity) of circular arc graphs intersection graphs of arcs of a circle. Circular arc graphs are known to have unbounded boxicity, which could be as large as Omega(n). We give a (2 + 1/k) -factor (resp. (2 + log n]/k)-factor) polynomial time approximation algorithm for computing the boxicity (resp. cubicity) of any circular arc graph, where k >= 1 is the value of the optimum solution. For normal circular arc (NCA) graphs, with an NCA model given, this can be improved to an additive two approximation algorithm. The time complexity of the algorithms to approximately compute the boxicity (resp. cubicity) is O(mn + n(2)) in both these cases, and in O(mn + kn(2)) = O(n(3)) time we also get their corresponding box (resp. cube) representations, where n is the number of vertices of the graph and m is its number of edges. Our additive two approximation algorithm directly works for any proper circular arc graph, since their NCA models can be computed in polynomial time. (C) 2014 Elsevier B.V. All rights reserved.

Context dependent non canonical WNT signaling mediates activation of fibroblasts by transforming growth factor-beta

Actions of transforming growth factor-beta are largely context dependent. For instance, TGF-beta is growth inhibitory to epithelial cells and many tumor cell-lines while it stimulates the growth of mesenchymal cells. TGF-beta also activates fibroblast cells to a myofibroblastic phenotype. In order to understand how the responsiveness of fibroblasts to TGF-beta would change in the context of transformation, we have compared the differential gene regulation by TGF-beta in immortal fibroblasts (hFhTERT), transformed fibroblasts (hFhTERT-LTgRAS) and a human fibrosarcoma cell-line (HT1080). The analysis revealed regulation of 6735, 4163, and 3478 probe-sets by TGF-beta in hFhTERT, hFhTERT-LTgRAS and HT1080 cells respectively. Intriguingly, 5291 probe-sets were found to be either regulated in hFhTERT or hFhTERT-LTgRAS cells while 2274 probe-sets were regulated either in hFhTERT or HT1080 cells suggesting that the response of immortal hFhTERT cells to TGF-beta is vastly different compared to the response of both the transformed cells hFhTERT-LTgRAS and HT1080 to TGF-beta. Strikingly, WNT pathway showed enrichment in the hFhTERT cells in Gene Set Enrichment Analysis. Functional studies showed induction of WNT4 by TGF-beta in hFhTERT cells and TGF-beta conferred action of these cells was mediated by WNT4. While TGF-beta activated both canonical and non-canonical WNT pathways in hFhTERT cells, Erk1/2 and p38 Mitogen Activated Protein Kinase pathways were activated in hFhTERT-LTgRAS and HT1080 cells. This suggests that transformation of immortal hFhTERT cells by SV40 large T antigen and activated RAS caused a switch in their response to TGF-beta which matched with the response of HT1080 cells to TGF-beta. These data suggest context dependent activation of non-canonical signaling by TGF-beta. (C) 2015 Published by Elsevier Inc.

Negative regulators of a growth factor-mediated signaling pathway in the nematode Caenorhabditis elegans

Vulval differentiation in C. elegans is mediated by an Epidermal growth factor (EGF)- EGF receptor (EGFR) signaling pathway. I have cloned unc-101, a negative regulator of vulval differentiation of the nematode C. elegans. unc-101 encodes a homolog of AP47, the medium chain of the trans-Golgi clathrin-associated protein complex. This identity was confirmed by cloning and comparing sequence of a C. elegans homolog of AP50, the medium chain of the plasma membrane clathrin-associated protein complex. I provided the first genetic evidence that the trans-Golgi clathrin-coated vesicles are involved in regulation of an EGF signaling pathway. Most of the unc-101 alleles are deletions or nonsense mutations, suggesting that these alleles severely reduce the unc-101 activity. A hybrid gene that contains parts of unc-101 and mouse AP4 7 rescued at least two phenotypes of unc-101 mutations, the Unc and the suppression of vulvaless phenotype of let-23(sy1) mutation. Therefore, the functions of AP47 are conserved between nematodes and mammals.

unc-101 mutations can cause a greater than wild-type vulval differentiation in combination with certain mutations in sli-1, another negative regulator of the vulval induction pathway. A mutation in a new gene, rok-1, causes no defect by itself, but causes a greater than wild-type vulval differentiation in the presence of a sli-1 mutation. The unc-101; rok-1; sli-1 triple mutants display a greater extent of vulval differentiation than any double mutant combinations of unc-101, rok-1 and sli-1. Therefore, rok-1 locus defines another negative regulator of the vulval induction pathway.

I analyzed a second gene encoding an AP47 homolog in C. elegans. This gene, CEAP47, encodes a protein 72% identical to both unc-101 and mammalian AP47. A hybrid gene containing parts of unc-101 and CEAP47 sequences can rescue phenotypes of unc-101 mutants, indicating that UNC- 101 and CEAP47 proteins can be redundant if expressed in the same set of cells.

Does precision decrease with set size?

The brain encodes visual information with limited precision. Contradictory evidence exists as to whether the precision with which an item is encoded depends on the number of stimuli in a display (set size). Some studies have found evidence that precision decreases with set size, but others have reported constant precision. These groups of studies differed in two ways. The studies that reported a decrease used displays with heterogeneous stimuli and tasks with a short-term memory component, while the ones that reported constancy used homogeneous stimuli and tasks that did not require short-term memory. To disentangle the effects of heterogeneity and short-memory involvement, we conducted two main experiments. In Experiment 1, stimuli were heterogeneous, and we compared a condition in which target identity was revealed before the stimulus display with one in which it was revealed afterward. In Experiment 2, target identity was fixed, and we compared heterogeneous and homogeneous distractor conditions. In both experiments, we compared an optimal-observer model in which precision is constant with set size with one in which it depends on set size. We found that precision decreases with set size when the distractors are heterogeneous, regardless of whether short-term memory is involved, but not when it is homogeneous. This suggests that heterogeneity, not short-term memory, is the critical factor. In addition, we found that precision exhibits variability across items and trials, which may partly be caused by attentional fluctuations.

Independence is elusive: set size effects on encoding precision in visual search.

Looking for a target in a visual scene becomes more difficult as the number of stimuli increases. In a signal detection theory view, this is due to the cumulative effect of noise in the encoding of the distractors, and potentially on top of that, to an increase of the noise (i.e., a decrease of precision) per stimulus with set size, reflecting divided attention. It has long been argued that human visual search behavior can be accounted for by the first factor alone. While such an account seems to be adequate for search tasks in which all distractors have the same, known feature value (i.e., are maximally predictable), we recently found a clear effect of set size on encoding precision when distractors are drawn from a uniform distribution (i.e., when they are maximally unpredictable). Here we interpolate between these two extreme cases to examine which of both conclusions holds more generally as distractor statistics are varied. In one experiment, we vary the level of distractor heterogeneity; in another we dissociate distractor homogeneity from predictability. In all conditions in both experiments, we found a strong decrease of precision with increasing set size, suggesting that precision being independent of set size is the exception rather than the rule.