Gamma Family Research Articles

Gamma distribution and extensions by using pathway idea

Extended forms of gamma and inverse Gaussian densities are considered. Pathway model of Mathai (Linear Algebra Appl 396:317–328, 2005) is utilized for the extension. The Laplace transform of this extended function is evaluated, thereby the moment generating functions in this general class can be obtained. Some Bayesian results are derived for the extended gamma family of densities. Distributions of products and ratios of the extended variables and computable series representations are discussed.

Is the Selected Population the Best?—Location and Scale Parameter Cases

We observe X 1,…,X k , where X i has density f(x,θ i ) possessing monotone likelihood ratio. The best population corresponds to the largest θ i . We select the population corresponding to the largest X i . The goal is to attach the best possible p-value to the inference: the selected population has the uniquely largest θ i . Gutmann and Maymin (1987) considered the location parameter case and derived the supremum of the error probability by conditioning on S, the index of the largest X i . Using this conditioning approach, Kannan and Panchapakesan (2009) considered the problem for the gamma family. We consider here a unified approach to both the location and scale parameter cases, and obtain the supremum of the error probability without using conditioning.

Cytokines as Adjuvants for Vaccine and Cellular Therapies for Cancer

PROBLEM STATEMENT: The development of a potent vaccine that can help treat tumors resistant to conventional cytotoxic therapies remains elusive. While part of the problem may be that trials have focused on patients with bulky residual disease, the desire to maximize responses to the vaccine remains. APPROACH: The gamma(c) family of cytokines offer a unique opportunity to support the expansion and effector potential of vaccine-responding T-cells, as well as stimulate other effectors, such as natural killer (NK) cells, to become activated. RESULTS: Combining vaccines with cytokines seems logical but can bring unwanted toxicity, as has been observed with interleukin (IL)-2. In addition, the nonspecific activation or expansion of unwanted cell subsets, such as regulatory T-cells, can contribute to global immunosuppression and limit vaccine responses. The development of IL-7 and IL-21 for the clinic offers the promise of enhancing anti-tumor responses but with far less systemic toxicity and no expansion of regulatory T cells. Preclinical studies demonstrate that IL-15 could also improve T-cell, and especially NK-cell, responses as well. CONCLUSIONS/RECOMMENDATIONS: Future work should expand the use of vaccines with IL-7, IL-21 and hopefully IL-15 in high-risk patients, and consider treatment while in a state of minimal residual disease to maximize benefit. Identifying tumors that can signal through gamma(c) cytokines will also be essential so that induction of relapse will be avoided.

Structural and Biophysical Studies of the Human IL-7/IL-7Rα Complex

IL-7 and IL-7Ralpha bind the gamma(c) receptor, forming a complex crucial to several signaling cascades leading to the development and homeostasis of T and B cells. We report that the IL-7Ralpha ectodomain uses glycosylation to modulate its binding constants to IL-7, unlike the other receptors in the gamma(c) family. IL-7 binds glycosylated IL-7Ralpha 300-fold more tightly than unglycosylated IL-7Ralpha, and the enhanced affinity is attributed primarily to an accelerated on rate. Structural comparison of IL-7 in complex to both forms of IL-7Ralpha reveals that glycosylation does not participate directly in the binding interface. The SCID mutations of IL-7Ralpha locate outside the binding interface with IL-7, suggesting that the expressed mutations cause protein folding defects in IL-7Ralpha. The IL-7/IL-7Ralpha structures provide a window into the molecular recognition events of the IL-7 signaling cascade and provide sites to target for designing new therapeutics to treat IL-7-related diseases.

Conditionally Gaussian Hypermodels for Cerebral Source Localization

Bayesian modeling and analysis of the magnetoencephalography and electroencephalography modalities provide a flexible framework for introducing prior information complementary to the measured data. This prior information is often qualitative in nature, making the translation of the available information into a computational model a challenging task. We propose a generalized gamma family of hyperpriors which allows the impressed currents to be focal and we advocate a fast and efficient iterative algorithm, the iterative alternating sequential algorithm for computing maximum a posteriori (MAP) estimates. Furthermore, we show that for particular choices of the scalar parameters specifying the hyperprior, the algorithm effectively approximates popular regularization strategies such as the minimum current estimate and the minimum support estimate. The connection between priorconditioning and adaptive regularization methods is also pointed out. The posterior densities are explored by means of a Markov chain Monte Carlo strategy suitable for this family of hypermodels. The computed experiments suggest that the known preference of regularization methods for superficial sources over deep sources is a property of the MAP estimators only, and that estimation of the posterior mean in the hierarchical model is better adapted for localizing deep sources.

Periostin-like-factor and Periostin in an animal model of work-related musculoskeletal disorder

Work-related musculoskeletal disorders (WMSDs), also known as overuse injuries, account for a substantial proportion of work injuries and workers' compensation claims in the United States. However, the pathophysiological mechanisms underlying WMSDs are not well understood, especially the early events in their development. In this study we used an animal model of upper extremity WMSD, in which rats perform a voluntary repetitive reaching and pulling task for a food reward. This innovative model provides us an opportunity to investigate the role of molecules which may be used either as markers of early diagnosis of these disorders, and/or could be targeted for therapeutic purposes in the future. Periostin-like-factor (PLF), and Periostin were examined in this study. Both belong to a family of vitamin K-dependent gamma carboxylated proteins characterized by the presence of conserved Fasciclin domains and not detected in adult tissues except under conditions of chronic overload, injury, stress or pathology. The spatial and temporal pattern of PLF and Periostin localization was examined by immunohistochemistry and western blot analysis in the radius and ulna of animals performing a high repetition, high force task for up to 12 weeks and in controls. We found that PLF was present primarily in the cellular periosteum, articular cartilage, osteoblasts, osteocytes and osteoclasts at weeks 3 and 6 in all distal bone sites examined. This increase coincided with a transient increase in serum osteocalcin in week 6, indicative of adaptive bone formation at this time point. PLF immunoexpression decreased in the distal periosteum and metaphysis by week 12, coincided temporally with an increase in serum Trap5b, thinning of the growth plate and reduced cortical thickness. In contrast to PLF, once Periostin was induced by task performance, it continued to be present at a uniformly high level between 3 and 12 weeks in the trabeculae, fibrous and cellular periosteum, osteoblasts and osteocytes. In general, the data suggest that PLF is located in tissues during the early adaptive stage of remodeling but not during the pathological phase and therefore might be a marker of early adaptive remodeling.

Azimuthal correlations and alignment of particles in gamma families

Azimuthal angular correlations and the alignment of photons are studied in gamma families recorded by the Pamir Collaboration in a carbon x-ray emulsion chamber. The present interpretation of these experimental data is based on a model of semihard parton scattering in nucleon-nucleus collisions and on arguments favoring the production of exotic beam strings and heavy leading resonances undergoing quasicoplanar decays.

A Novel Mechanism by Which Thiazolidinediones Facilitate the Proteasomal Degradation of Cyclin D1 in Cancer Cells

This study identifies a novel mechanism by which thiazolidinediones mediate cyclin D1 repression in prostate cancer cells. Based on the finding that the thiazolidinedione family of peroxisome proliferator-activated receptor gamma (PPARgamma) agonists mediated PPARgamma-independent cyclin D1 degradation, we developed a novel PPARgamma-inactive troglitazone derivative, STG28, with high potency in cyclin D1 ablation. STG28-mediated cyclin D1 degradation was preceded by Thr-286 phosphorylation and nuclear export, which however, were independent of glycogen synthase kinase 3beta. Mutational analysis further confirmed the pivotal role of Thr-286 phosphorylation in STG28-induced nuclear export and proteolysis. Of several kinases examined, inhibition of IkappaB kinase alpha blocked STG28-mediated cytoplasmic sequestration and degradation of cyclin D1. Pulldown of ectopically expressed Cul1, the scaffold protein of the Skp-Cullin-F-box E3 ligase, in STG28-treated cells revealed an increased association of cyclin D1 with beta-TrCP, whereas no specific binding was noted with other F-box proteins examined, including Skp2, Fbw7, Fbx4, and Fbxw8. This finding represents the first evidence that cyclin D1 is targeted by beta-TrCP. Moreover, beta-TrCP expression was up-regulated in response to STG28, and ectopic expression and small interfering RNA-mediated knock-down of beta-TrCP enhanced and protected against STG28-facilitated cyclin D1 degradation, respectively. Because cyclin D1 lacks the DSG destruction motif, mutational and modeling analyses indicate that cyclin D1 was targeted by beta-TrCP through an unconventional recognition site, (279)EEVDLACpT(286), reminiscent to that of Wee1. Moreover, we obtained evidence that this beta-TrCP-dependent degradation takes part in controlling cyclin D1 turnover when cancer cells undergo glucose starvation, which endows physiological relevance to this novel mechanism.

The asymmetric meiosis in pentaploid dogroses (Rosa sect. Caninae) is associated with a skewed distribution of rRNA gene families in the gametes

In pentaploid dogroses, Rosa section Caninae (2n=5x=35), the pollen transmits one basic genome (x=7) derived from the seven segregating bivalents, whereas the egg transmits four basic genomes (4x=28) one set derived from the segregation of seven bivalents and three sets of univalent-forming chromosomes. Chromosomes from all five genomes carry 18-5.8-26S nuclear ribosomal DNA (rDNA) sites. This mode of sexual reproduction, known as permanent odd polyploidy, can potentially lead to the independent evolution of rDNA on bivalent- and univalent-forming chromosomes. To test this hypothesis, we analyzed rRNA gene families in pollen and somatic leaf tissue of R. canina, R. rubiginosa and R. dumalis. Six major rRNA gene families (alpha, beta, beta' gamma, delta and epsilon) were identified based on several highly polymorphic sites in the internal transcribed spacers (ITSs). At least two of the major rRNA gene families were found in each species indicating that rDNAs have not been homogenized across subgenomes. A comparison of ITS1 sequences from leaf and pollen showed differences: the shared beta rRNA gene family was more abundant among pollen clones compared to leaf clones and must constitute a major part of the rDNA loci on bivalent-forming chromosomes. The gamma and delta families were underrepresented in pollen genomes and are probably located predominantly (or solely) on the univalents. The results support the hypothesis that pentaploid dogroses inherited a bivalent-forming genome from a common proto-canina ancestor, a likely donor of the beta rDNA family. Allopolyploidy with distantly related species is likely to have driven evolution of Rosa section Caninae.

Maximum likelihood estimation in processes of Ornstein-Uhlenbeck type

In this article we propose a maximum likelihood methodology to estimate the parameters of a one-dimensional stationary process of Ornstein-Uhlenbeck type that is constructed via a self-decomposable distribution D. Our approach is based on the inversion of the characteristic function and the use of the classical or fractional discrete fast Fourier transform. The results are illustrated throughout an extensive simulation study. This includes the cases where D belongs to the gamma, tempered stable and normal inverse Gaussian family of distributions.

Le Cycle de Renart: From the Enfances to the Jugement in a Cyclical Roman de Renart Manuscript

This article is a reading of a Roman de Renart manuscript from the often neglected gamma family, which subsumes the narrative to a broadly biographical (or cyclical) framework. The manuscript studied here therefore opens with an Enfances text, which lays the ground for seeing the fox as a radically evil creation, and his crimes as inevitable repetitions of his evil propensities. Whereas the alpha and beta families open with the famous trial (Le Jugement de Renart), the gamma family locates it later, after a series of misdeeds by the fox, meaning that this episode now serves less as an attempt to punish Renart for a single sexual crime than to mark the impossibility of holding him to justice for anything he has done. Using an approach to repetition deriving from Lacanian theory, the author argues that the Jugement, itself now a rerun of a previous trial, represents the community's failure to confront the Renardian trauma that haunts it, and, by extension, its inability to function effectively. Thwarting the ideological closure of justice allows Renart to become an emblem of the fiction itself.

The Anatomy of the Knee and Gamma-Families

It is shown that the fine stucture of the cosmic ray energy spectrum in the knee region, if explained by the Single Source Model (SSM), can, in principle, be clearly revealed and magnified in the size spectrum of extensive air showers (EAS) associated with gamma families. Existing experimental data on EAS at mountain level give support to this hypothesis.

On generalized distributions and pathways

The pathway model of Mathai (2005) mainly deals with the rectangular matrix-variate case. In this paper the scalar version is shown to be associated with a large number of probability models used in physics. Different families of densities are listed here, which are all connected through the pathway parameter 'alpha', generating a distributional pathway. The idea is to switch from one functional form to another through this parameter and it is shown that basically one can proceed from the generalized type-1 beta family to generalized type-2 beta family to generalized gamma family when the real variable is positive and a wider set of families when the variable can take negative values also. For simplicity, only the real scalar case is discussed here but corresponding families are available when the variable is in the complex domain. A large number of densities used in physics are shown to be special cases of or associated with the pathway model. It is also shown that the pathway model is available by maximizing a generalized measure of entropy, leading to an entropic pathway. Particular cases of the pathway model are shown to cover Tsallis statistics (Tsallis, 1988) and the superstatistics introduced by Beck and Cohen (2003).

An application of mixture distributions in modelization of length of hospital stay

Length of hospital stay (LOS) is an important indicator of the hospital activity and management of health care. The skewness exhibited by this variable poses problems in statistical modeling. The aim of this work is to model the variable LOS within diagnosis-related groups (DRG) through finite mixtures of distributions. A mixture of the union of Gamma, Weibull and Lognormal families is used in the model, instead of a mixture of a unique distribution family. Some theoretical questions regarding the model, such as the identifiability and study of asymptotic properties of ML estimators, are analyzed. The EM algorithm is proposed for performing these estimators. Finally, this new proposed model is illustrated by using data from different DRGs.

Differential regulation and properties of MAPKs

Mitogen-activated protein kinases (MAPKs) regulate diverse cellular programs including embryogenesis, proliferation, differentiation and apoptosis based on cues derived from the cell surface and the metabolic state and environment of the cell. In mammals, there are more than a dozen MAPK genes. The best known are the extracellular signal-regulated kinases 1 and 2 (ERK1/2), c-Jun N-terminal kinase (JNK(1-3)) and p38(alpha, beta, gamma and delta) families. ERK3, ERK5 and ERK7 are other MAPKs that have distinct regulation and functions. MAPK cascades consist of a core of three protein kinases. Despite the apparently simple architecture of this pathway, these enzymes are capable of responding to a bewildering number of stimuli to produce exquisitely specific cellular outcomes. These responses depend on the kinetics of their activation and inactivation, the subcellular localization of the kinases, the complexes in which they act, and the availability of substrates. Fine-tuning of cascade activity can occur through modulatory inputs to cascade component from the primary kinases to the scaffolding accessory proteins. Here, we describe some of the properties of the three major MAPK pathways and discuss how these properties govern pathway regulation and activity.

Mixtures in nonstable Lévy processes

We analyse the Lévy processes produced by means of two interconnected classes of nonstable, infinitely divisible distribution: the variance gamma and the Student laws. While the variance gamma family is closed under convolution, the Student one is not: this makes its time evolution more complicated. We prove that—at least for one particular type of Student processes suggested by recent empirical results, and for integral times—the distribution of the process is a mixture of other types of Student distributions, randomized by means of a new probability distribution. The mixture is such that along the time the asymptotic behaviour of the probability density functions always coincide with that of the generating Student law. We put forward the conjecture that this can be a general feature of the Student processes. We finally analyse the Ornstein-Uhlenbeck process driven by our Lévy noises and show a few simulations of it.

The centaurin gamma-1 GTPase-like domain functions as an NTPase.

Centaurins are a family of proteins that contain GTPase-activating protein domains, with the gamma family members containing in addition a GTPase-like domain. Centaurins reside mainly in the nucleus and are known to activate phosphoinositide 3-kinase, a key regulator of cell proliferation, motility and vesicular trafficking. In the present study, using X-ray structural analysis, enzymatic assays and nucleotide-binding studies, we show that, for CENTG1 (centaurin gamma-1) the GTPase-like domain has broader trinucleotide specificity. Alterations within the G4 motif of CENTG1 from the highly conserved NKXD found in typical GTPases to TQDR result in the loss of specificity, a lower affinity for the nucleotides and higher turnover rates. These results indicate that the centaurins could be more accurately classified as NTPases and point to alternative mechanisms of cell signalling control.

A conservative parametric approach to motif significance analysis.

We suggest a novel, parametric, approach to estimating the significance of the output of motif finders. Specifically, we rely on the good fit we observe between the 3-parameters Gamma family and the null distribution of motif scores. This fit was observed across multiple motif finders, background models and scoring functions. Under this parametric assumption we compute and show the utility of a conservative confidence interval for the p-value of the observed score. Since our method relies on the 3-parameters Gamma fit it should be applicable to a variety of finders.

Gamma Protocadherin Expression in the Embryonic Chick Nervous System

Protocadherin gamma (pcdh-gamma) family expression was examined in the embryonic chick central nervous system by in situ hybridization. Transcripts were visualized in discrete regions of fore-, mid-, and hindbrain at stages 23 and 25 and in spinal cord and optic lobe at stages 27 and 43, respectively. Results suggest that pcdh-gamma may function cooperatively with other cell adhesion molecules in neuronal differentiation and establishment of neural networks in several areas of the developing brain, particularly regions involved in visual processing.

Information measures for generalized gamma family

The objective of this paper is to integrate the generalized gamma (GG) distribution into the information theoretic literature. We study information properties of the GG distribution and provide an assortment of information measures for the GG family, which includes the exponential, gamma, Weibull, and generalized normal distributions as its subfamilies. The measures include entropy representations of the log-likelihood ratio, AIC, and BIC, discriminating information between GG and its subfamilies, a minimum discriminating information function, power transformation information, and a maximum entropy index of fit to histogram. We provide the full parametric Bayesian inference for the discrimination information measures. We also provide Bayesian inference for the fit of GG model to histogram, using a semi-parametric Bayesian procedure, referred to as the maximum entropy Dirichlet (MED). The GG information measures are computed for duration of unemployment and duration of CEO tenure.