A Trinomial Difference Distribution

A trinomial difference distribution is defined and its distributional properties are illustrated. This distribution present the binomial difference distribution as a special case. The moment estimators and maximum likelihood estimators of the trinomial difference distribution are compared via simulation study. Two applications are modeled with the trinomial difference distribution and compared with other possible distributions.Una distribución de diferencia trinomial se define en este artículo así como sus propiedades distribucionales. Esta distribución cuenta con la distribución de diferencia binomial como un caso particular. Los estimadores de momentos y de máxima verosimilitud son comparados vía un estudio de simulación. Dos aplicaciones son modelados con la distribución diferencia trinomial y se comparan con otras distribuciones posibles

A Bivariate Model based on Compound Negative Binomial Distribution

A new bivariate model is introduced by compounding negative binomial and geometric distributions. Distributional properties, including joint, marginal and conditional distributions are discussed. Expressions for the product moments, covariance and correlation coefficient are obtained. Some properties such as ordering, unimodality, monotonicity and self-decomposability are studied. Parameter estimators using the method of moments and maximum likelihood are derived. Applications to traffic accidents data are illustrated.Un nuevo modelo de dos variables se introduce mediante la composición distribuciones binomiales negativos y geométricos. propiedades distributivas, incluyendo distribuciones conjuntas, marginales y condicionales se discuten. se obtienen las expresiones para los momentos de productos, la covarianza y el coeficiente de correlación. Se estudian algunas propiedades tales como pedidos, unimodalidad, monotonía y la auto-decomposability. estimadores de parámetros utilizando el método de los momentos y de máxima verosimilitud se derivan. Aplicaciones a los datos de accidentes de tráfico se ilustra

On bivariate Poisson regression models

In this paper, we consider estimating the parameters of bivariate and zero-inflated bivariate Poisson regression models using the conditional method. This method is compared with the standard method, which uses the joint probability function. Simulations and real applications show that the two methods have almost identical Akaike Information Criteria and parameter estimates, but the conditional method has a much faster execution time than the joint method. We conducted our computations using the R and SAS package. Our results also indicate that the execution time of SAS is faster than that of R

The Fidelity of Rheumatoid Arthritis Multivariate Diagnostic Biomarkers Using Discriminant Analysis and Binary Logistic Regression

Rheumatoid arthritis (RA) is an autoimmune inflammatory disease that causes multi-articular synovitis. The illness is characterized by worsening inflammatory synovitis, which causes joint swelling and pain. Synovitis erodes articular cartilage and marginal bone, resulting in joint deterioration. This bone injury is expected to be permanent. Cytokines play a prominent role in the etiology of RA and could be useful as early diagnostic biomarkers. This research was carried out at Riyadh’s King Khalid University Hospital (KKUH). Patients were enrolled from the Rheumatology unit. Seventy-eight RA patients were recruited (67 (85.9%) females and 11 (14.1%) males). Patients were selected for participation by convenience sampling. Demographic data were collected, and disease activity measurements at 28 joints were recorded using the disease activity score (DAS-28). Age- and sex-matched controls from the general population were included in the study. A panel of 27 cytokines, chemokines, and growth factors was determined in patient and control sera. Binary logistic regression (BLR) and discriminant analysis (DA) were used to analyze the data. We show that multiple cytokine biomarker profiles successfully distinguished RA patients from healthy controls. IL-17, IL-4, and RANTES were among the most predictive variables and were the only biomarkers incorporated into both BLR and DA predictive models for pooled participants (men and women). In the women-only models, the significant cytokines incorporated in the model were IL-4, IL-17, MIP-1b, and RANTES for the BLR model and IL-4, IL-1Ra, GM-CSF, IL-17, and eotaxin for the DA model. The BLR and DA men-only models contained one cytokine each, eotaxin for BLR and platelet-derived growth factor-bb (PDGF-BB) for DA. We show that BLR has a higher fidelity in identifying RA patients than DA. We also found that the use of gender-specific models marginally improves detection fidelity, indicating a possible benefit in clinical diagnosis. More research is needed to determine whether this conclusion will hold true in various and larger patient populations

Safety of prolonged use of metoclopramide and domperidone as treatment for chronic gastrointestinal dysmotility disorders in patients with systemic sclerosis

Background: Metoclopramide and domperidone are prokinetic agents commonly used to treat gastrointestinal dysmotility disorders. This study aimed to evaluate the safety and associated side effects of prolonged-use metoclopramide and domperidone as treatment for chronic gastrointestinal dysmotility disorders in patients with systemic sclerosis (SSc). Methods: A quantitative observational survey was conducted by interview questionnaire in rheumatology outpatients at a tertiary teaching hospital in Riyadh, Saudi Arabia. The study included all patients aged 25–80 years diagnosed with SSc. All patients were on metoclopramide or domperidone for the treatment of chronic gastrointestinal dysmotility symptoms over at least 12 weeks. Results: Eighteen eligible patients were included. Most study participants were diagnosed with SSc complicated by interstitial lung disease (n = 13; 72.2 %). The most frequently reported side effect that occurred while taking prokinetic drugs was shortness of breath (n = 12; 66.7 %). None of the participants reported experiencing depression, galactorrhea, or syncope. CNS side effects were reported in 5.6 %. There were no differences in side effects based on the type and dosage of prokinetic drug used. Conclusions: Use of metoclopramide and domperidone for the treatment of chronic gastrointestinal dysmotility in SSc patients for 12 weeks or longer was not associated with any troublesome side effects. Further studies with more participants are needed to confirm our findings

Expression and new exon mutations of the human Beta defensins and their association on colon cancer development.

The development of cancer involves genetic predisposition and a variety of environmental exposures. Genome-wide linkage analyses provide evidence for the significant linkage of many diseases to susceptibility loci on chromosome 8p23, the location of the human defensin gene cluster. Human β-defensins (hBDs) are important molecules of innate immunity. This study was designed to analyze the expression and genetic variations in hBDs (hBD-1, hBD-2, hBD-3 and hBD-4) and their putative association with colon cancer. hBD gene expression and relative protein expression were evaluated by Real-Time polymerase chain reaction (qPCR) and immunohistochemistry, respectively, from 40 normal patients and 40 age-matched patients with colon cancer in Saudi Arabia. In addition, hBD polymorphisms were genotyped by exon sequencing and by promoter methylation. hBD-1, hBD-2, hBD-3 and hBD-4 basal messenger RNA expression was significantly lower in tumor tissues compared with normal tissues. Several insertion mutations were detected in different exons of the analyzed hBDs. However, no methylation in any hBDs promoters was detected because of the limited number of CpG islands in these regions. We demonstrated for the first time a link between hBD expression and colon cancer. This suggests that there is a significant link between innate immunity deregulation through disruption of cationic peptides (hBDs) and the potential development of colon cancer

Differents structures of hBDs: hBD-1 (panel A), hBD2 (Panel B), and hBD3mutant and wild type (panel C and D).

<p>Differents structures of hBDs: hBD-1 (panel A), hBD2 (Panel B), and hBD3mutant and wild type (panel C and D).</p

Clinical data of patients diagnosed with colon cancer via colonoscopy.

<p>Clinical data of patients diagnosed with colon cancer via colonoscopy.</p