Multivariate measurement error models based on scale mixtures of the skew-normal distribution

Scale mixtures of the skew-normal (SMSN) distribution is a class of asymmetric thick-tailed distributions that includes the skew-normal (SN) distribution as a special case. The main advantage of these classes of distributions is that they are easy to simulate and have a nice hierarchical representation facilitating easy implementation of the expectation-maximization algorithm for the maximum-likelihood estimation. In this paper, we assume an SMSN distribution for the unobserved value of the covariates and a symmetric scale mixtures of the normal distribution for the error term of the model. This provides a robust alternative to parameter estimation in multivariate measurement error models. Specific distributions examined include univariate and multivariate versions of the SN, skew-t, skew-slash and skew-contaminated normal distributions. The results and methods are applied to a real data set.

Measurement error models with a general class of error distribution

In general, the normal distribution is assumed for the surrogate of the true covariates in the classical error model. This paper considers a class of distributions, which includes the normal one, for the variables subject to error. An estimation approach yielding consistent estimators is developed and simulation studies reported.

Influence Diagnostics for a Skew Extension of the Grubbs Measurement Error Model

Influence diagnostics methods are extended in this article to the Grubbs model when the unknown quantity x (latent variable) follows a skew-normal distribution. Diagnostic measures are derived from the case-deletion approach and the local influence approach under several perturbation schemes. The observed information matrix to the postulated model and Delta matrices to the corresponding perturbed models are derived. Results obtained for one real data set are reported, illustrating the usefulness of the proposed methodology.

A robust Bayesian approach to null intercept measurement error model with application to dental data

Measurement error models often arise in epidemiological and clinical research. Usually, in this set up it is assumed that the latent variable has a normal distribution. However, the normality assumption may not be always correct. Skew-normal/independent distribution is a class of asymmetric thick-tailed distributions which includes the Skew-normal distribution as a special case. In this paper, we explore the use of skew-normal/independent distribution as a robust alternative to null intercept measurement error model under a Bayesian paradigm. We assume that the random errors and the unobserved value of the covariate (latent variable) follows jointly a skew-normal/independent distribution, providing an appealing robust alternative to the routine use of symmetric normal distribution in this type of model. Specific distributions examined include univariate and multivariate versions of the skew-normal distribution, the skew-t distributions, the skew-slash distributions and the skew contaminated normal distributions. The methods developed is illustrated using a real data set from a dental clinical trial. (C) 2008 Elsevier B.V. All rights reserved.

Identification of protein-coding and intronic noncoding RNAs down-regulated in clear cell renal carcinoma

The clear cell subtype of renal cell carcinoma (RCC) is the most lethal and prevalent cancer of the urinary system. To investigate the molecular changes associated with malignant transformation in clear cell RCC, the gene expression profiles of matched samples of tumor and adjacent non-neoplastic tissue were obtained from six patients. A custom-built cDNA microarray platform was used, comprising 2292 probes that map to exons of genes and 822 probes for noncoding RNAs mapping to intronic regions. Intronic transcription was detected in all normal and neoplastic renal tissues. A subset of 55 transcripts was significantly down-regulated in clear cell RCC relative to the matched nontumor tissue as determined by a combination of two statistical tests and leave-one-out patient cross-validation. Among the down-regulated transcripts, 49 mapped to untranslated or coding exons and 6 were intronic relative to known exons of protein-coding genes. Lower levels of expression of SIN3B, TRIP3, SYNJ2BP and NDE1 (P<0.02), and of intronic transcripts derived from SND1 and ACTN4 loci (P<0.05), were confirmed in clear cell RCC by Real-time RT-PCR. A subset of 25 transcripts was deregulated in additional six nonclear cell RCC samples, pointing to common transcriptional alterations in RCC irrespective of the histological subtype or differentiation state of the tumor. Our results indicate a novel set of tumor suppressor gene candidates, including noncoding intronic RNAs, which may play a significant role in malignant transformations of normal renal cells. (C) 2008 Wiley-Liss, Inc.

RNA Isolation method for polysaccharide rich algae: agar producing Gracilaria tenuistipitata (Rhodophyta)

RNA isolation is essential to study gene expression at the molecular level. However, RNA isolation is difficult in organisms (plants and algae) that contain large amounts of polysaccharides, which co-precipitate with RNA. Currently, there is no commercial kit available, specifically for the isolation of high-quality RNA from these organisms. Furthermore, because of the large amounts of polysaccharides, the common protocols for RNA isolation usually result in poor yields when applied to algae. Here we describe a simple method for RNA isolation from the marine red macroalga Gracilaria tenuistipitata var. liui Zhang et Xia (Rhodophyta), which can be applied to other plants and algae.

Isolation of Brazilian marine fungi capable of growing on DDD pesticide

The fungi Aspergillus sydowii Ce15, Aspergillus sydowii Ce19, Aspergillus sydowii Gc12, Bionectria sp. Ce5, Penicillium miczynskii Gc5, Penicillium raistrickii Ce16 and Trichoderma sp. Gc1, isolated from marine sponges Geodia corticostylifera and Chelonaplysylla erecta, were evaluated for their ability to grow in the presence of DDD pesticide. Increasing concentrations of DDD pesticide, i.e., 5.0 mg (1.56 x 10(-12) mmol), 10.0 mg (3.12 x 10(-2) mmol) and 15.0 mg (4.68 x 10(-2) mmol) in solid and liquid culture media were tested. The fungi Trichoderma sp. Gc1 and Penicillium miczynskii Gc5 were able to grow in the presence of up to 15.0 mg of DDD, suggesting their potential for biodegradation. A 100% degradation of DDD was attained in liquid culture medium when Trichoderma sp. Gc1 was previously cultivated for 5 days and supplemented with 5.0 mg of DDD in the presence of hydrogen peroxide. However, the quantitative analysis showed that DDD was accumulated on mycelium and biodegradation level reached a maximum value of 58% after 14 days.

Immobilized analogues of sunflower trypsin inhibitor-1 constitute a versatile group of affinity sorbents for selective isolation of serine proteases

Sunflower trypsin inhibitor-1 (SFI-1), a natural 14-residue cyclic peptide, and some of its synthetic acyclic variants are potent protease inhibitors displaying peculiar inhibitory profiles. Here we describe the synthesis and use of affinity sorbents prepared by coupling SFTI-1 analogues to agarose resin. Chymotrypsinand trypsin-like proteases could then be selectively isolated from pancreatin; similarly, other proteases were obtained from distinct biological sources. The binding capacity of [Lys5]-SFTI-1-agarose for trypsin was estimated at over 10 mg/mL of packed gel. SFTI-1-based resins could find application either to improve the performance of current purification protocols or as novel protease-discovery tools in different areas of biological investigation. (C) 2009 Elsevier B.V. All rights reserved.

The Isolation and Characterization of Multiply Antibiotic Resistant Strains of Fish Pathogenic Flavobacterium Species

Since the development of the first antibiotics in the 1940’s, there has been widespread overuse in both clinical and agricultural applications. Antibiotic resistance has become a significant problem as a result of subsequent dissemination of antibiotics into the environment, and multiply-resistant strains of bacteria are now a major pathogenic threat. In this study eight separate strains of Flavobacterium responsible for recent disease outbreaks in fish hatcheries throughout Maine were collected and analyzed. All eight strains were found to be resistant to high levels of a number of different antibiotics, including those used for aquaculture as well as human chemotherapeutic applications. Flavobacterium isolates were also shown phenotypically to transfer antibiotic resistance determinants using a conjugation mating system in which Flavobacterium was the donor and Escherichia coli DH5- alpha was the recipient. This experiment suggests that it may be possible for Flavobacterium strains to transfer their multiple antibiotic resistance determinants to human pathogenic bacterial strains. Importantly, none of the hatcheries from which the Flavobacterium isolates were obtained had ever used antibiotics to treat their fish stock. It is possible that there is another selective agent responsible for the development of antibiotic resistance in the absence of antibiotic pressure. Mercury is one possible candidate, as all of the strains tested were resistant to mercuric chloride and it is known that genes encoding antibiotic resistance can be carried on the same mobile genetic elements that encode for mercury resistance. Preliminary data also suggest that the majority of the Flavobacterium isolates contain genes for mercuric ion reduction, which would confirm the mercury resistance genotype.

Study of Proteinuria: Isolation of Proteins from the Nephrotic Syndrome

One of the most puzzling phenomena of abnormal renal physiology is the occurrence of the nephrotic syndrome. The syndrome has been defined by a collection of clinical and pathological symptoms, but there is no correlation between the clinical and pathological symptoms nor is the etiology of the syndrome known. Proteinuria is probably the most distinguishing feature in the nephrotic syndrome, and there are two possible explanations for its occurrence: (1) the excessive amounts of protein found in nephrotic urine could be due to an increased basement membrane permeability in the glomerulus of the kidney or (2) dysproteinemia. An attempt has been made to evaluate the theory of dysproteinemia in connection with the syndrome. The albumin fractions of nephrotic urine have been studied for their amino acid composition by separating them from the urine by paper electrophoresis, hydrolyzing them, and identifying the amino acids present by two-dimensional chromatography. There seem to be no variations in the qualitative makeup of nephrotic albumin from that of normal albumin, but the literature shows that there are some slight variations in the quantitative amino acid composition of nephrotic albumin compared with normal albumin. More extensive and highly developed experimentation along the lines of protein structure and composition must be done before it can conclusively be stated that dysproteinemia is of importance in the nephrotic syndrome.