Prognostic significance and gene expression profiles of p53 mutations in microsatellite-stable stage III colorectal adenocarcinomas

Although the prognostic value of p53 abnormalities in Stage III microsatellite stable (MSS) colorectal cancers (CRCs) is known, the gene expression profiles specific to the p53 status in the MSS background are not known. Therefore, the current investigation has focused on identification and validation of the gene expression profiles associated with p53 mutant phenotypes in MSS Stage III CRCs. Genomic DNA extracted from 135 formalin-fixed paraffin-embedded tissues, was analyzed for microsatellite instability (MSI) and p53 mutations. Further, mRNA samples extracted from five p53-mutant and five p53-wild-type MSS-CRC snap-frozen tissues were profiled for differential gene expression by Affymetrix Human Genome U133 Plus 2.0 arrays. Differentially expressed genes were further validated by the high-throughput quantitative nuclease protection assay (qNPA), and confirmed by quantitative real-time polymerase chain reaction (qRT-PCR) and by immunohistochemistry (IHC). Survival rates were estimated by Kaplan-Meier and Cox regression analyses. A higher incidence of p53 mutations was found in MSS (58%) than in MSI (30%) phenotypes. Both univariate (log-rank, P = 0.025) and multivariate (hazard ratio, 2.52; 95% confidence interval, 1.25–5.08) analyses have demonstrated that patients with MSS-p53 mutant phenotypes had poor CRC-specific survival when compared to MSS-p53 wild-type phenotypes. Gene expression analyses identified 84 differentially expressed genes. Of 49 down-regulated genes, LPAR6, PDLIM3, and PLAT, and, of 35 up-regulated genes, TRIM29, FUT3, IQGAP3, and SLC6A8 were confirmed by qNPA, qRT-PCR, and IHC platforms. p53 mutations are associated with poor survival of patients with Stage III MSS CRCs and p53-mutant and wild-type phenotypes have distinct gene expression profiles that might be helpful in identifying aggressive subsets.     

Hyperuricemia and metabolic syndrome in type 2 diabetes mellitus patients at Hawassa university comprehensive specialized hospital,South West Ethiopia

Background

Metabolic syndrome is a cluster of the most dangerous heart attack risk factors such as diabetes and prediabetes, abdominal obesity, high cholesterol and high blood pressure. Hyperuricemia is a condition in which the serum uric acid concentration is greater than 5.5 mg per deciliter for child and greater than 7.2 and 6.0 mg per deciliters for male and female adults respectively.

Methods

A cross-sectional study was conducted to determine the magnitude of hyperuricemia and associated factors among type 2 diabetes mellitus patients at Hawassa Comprehensive Specialized Hospital (HCSH) from February 28 to May 30 /2017. A random sampling technique was used to include 319 study subjects and a signed consent had been provided by each study subject before running any data collection. An interviewer administered structured questionnaire was used to collect socio-demographic and some clinically useful data. In addition to this, we reviewed the records of the study subjects to obtain other useful clinical data. Five milliliter blood specimen was collected from each study subjects after overnight fasting. A25TM Bio-System Random Access chemistry analyzer was used for blood sample analysis. All data were checked visually, coded and entered into epi-data version 3.4 and statistical analysis was performed using SPSS version 20.0 software. Bi-variate and multivariate logistic regressions were used to determine the association between explanatory and the outcome variables.

Results

The prevalence of hyperuricemia and metabolic syndrome among type 2 diabetic patients in the study area were 33.8%(n?=?106) and 70.1% (n?=?220) respectively. Having age greater or equal to 45 years (AOR: 1.9, CI: 1.-3.2, P value =0.015) and having metabolic syndrome (AOR: 2.6, CI: 1.5–4.7, P value?=?0.001) were the determinant variables for hyperuricemia among type 2 diabetic patients.

Conclusion

There was high prevalence of hyperuricemia among type 2 diabetic patients with high prevalence of metabolic syndrome. Therefore, regular health information about life style modification, early diagnosis and treatment for hyperuricemia and metabolic syndrome are essential to reduce hyperuricemia and metabolic syndrome in type 2 diabetic patients.

     

Linking DNA damage to cell cycle checkpoints

Cell cycle checkpoints constitute a network of signal transduction mechanisms to monitor DNA damage and replication and thereby regulate progression through the cell cycle. A series of events is triggered in cells upon DNA damage. Here we describe a framework for the understanding of the functions of the core components involved in the cell cycle response to DNA damage and the relevance to the origin of cancer.     

Molecular phylogeny and species delimitation in the section Longibrachiatum of Trichoderma

The phylogenetically most derived group of the genus Trichoderma - section Longibrachiatum, includes some of the most intensively studied species, such as the industrial cellulase producer T. reesei (teleomorph Hypocrea jecorina), or the facultative opportunistic human pathogens T. longibrachiatum and H. orientalis. At the same time, the phylogeny of this clade is only poorly understood. Here we used a collection of 112 strains representing all currently recognized species and isolates that were tentatively identified as members of the group, to analyze species diversity and molecular evolution. Bayesian phylogenetic analyses based on several unlinked loci in individual and concatenated datasets confirmed 13 previously described species and 3 previously recognized phylogenetic species all of which were not yet described formally. When the genealogical concordance criterion, the K/θ method and comparison of frequencies of pairwise nucleotide differences were applied to the data sample, 10 additional new phylogenetic species were recognized, seven of which consisted only of a single lineage. Our analysis thus identifies 26 putative species in section Longibrachiatum, what doubles the currently estimated taxonomic diversity of the group, and illustrates the power of combining genealogical concordance and population genetic analysis for dissecting species in a recently diverged group of fungal species.     

Codominant PCR-based markers for Pinus taeda developed from mapped cDNA clones

 We report a strategy for developing codominant PCR-based genetic markers by using sequenced cDNA clones from loblolly pine (Pinus taeda L.). These clones were previously used as probes for detecting restriction fragment length polymorphisms (RFLPs) to generate linkage maps. After assessing the complexity of banding patterns from Southern blots, we selected clones representing relatively simple gene families, and then determined nucleotide sequences for about 200 bp at each end of the cDNA inserts. Specific PCR primers were designed to amplify samples of genomic DNA derived from two loblolly pine mapping populations. Polymorphisms were detected after digesting the amplified DNA fragments with a battery of restriction endonucleases, and most polymorphisms were inherited in a Mendelian fashion. These newly identified genetic markers are codominant and relatively simple to use. By assaying DNA from individuals used to construct RFLP maps, we show that most of these markers map to the same position as the RFLP loci detected using their corresponding cDNAs as probes, implying that these markers have been converted from RFLP to PCR-based methods. These PCR-based markers will be useful for genome mapping and population genetics. Received: 10 February 1998 / Accepted: 25 February 1998     

High risk of early sub-therapeutic penicillin concentrations after intramuscular benzathine penicillin G injections in Ethiopian children and adults with rheumatic heart disease

IntroductionIntramuscular benzathine penicillin G (BPG) injections are a cornerstone of secondary prophylaxis to prevent acute rheumatic fever (ARF) and rheumatic heart disease (RHD). Uncertainties regarding inter-ethnic and preparation variability, and target exposure profiles of BPG injection are key knowledge gaps for RHD control.MethodsTo evaluate BPG pharmacokinetics (PK) in patients receiving 4-weekly doses in Ethiopia, we conducted a prospective cohort study of ARF/RHD patients attending cardiology outpatient clinics. Serum samples were collected weekly for one month after injection and assayed with a liquid chromatography-mass spectroscopy assay. Concentration-time datasets for BPG were analyzed by nonlinear mixed effects modelling using NONMEM.ResultsA total of 190 penicillin concentration samples from 74 patients were included in the final PK model. The median age, weight, BMI was 21 years, 47 kg and 18 kg/m², respectively. When compared with estimates derived from Indigenous Australian patients, the estimate for median (95% confidence interval) volume of distribution (V/F) was lower (54.8 [43.9–66.3] l.70kg^-1) whilst the absorption half-life (t_1/2-abs2) was longer (12.0 [8.75–17.7] days). The median (IQR) percentage of time where the concentrations remained above 20 ng/mL and 10 ng/mL within the 28-day treatment cycle was 42.5% (27.5–60) and 73% (58.5–99), respectively.ConclusionsThe majority of Ethiopian patients receiving BPG as secondary prophylaxis to prevent RHD do not attain target concentrations for more than two weeks during each 4-weekly injection cycle, highlighting the limitations of current BPG strategies. Between-population variation, together with PK differences between different preparations may be important considerations for ARF/RHD control programs.     

A Comparison of the Spatial Linear Model to Nearest Neighbor (k-NN) Methods for Forestry Applications

Forest surveys provide critical information for many diverse interests. Data are often collected from samples, and from these samples, maps of resources and estimates of aerial totals or averages are required. In this paper, two approaches for mapping and estimating totals; the spatial linear model (SLM) and k-NN (k-Nearest Neighbor) are compared, theoretically, through simulations, and as applied to real forestry data. While both methods have desirable properties, a review shows that the SLM has prediction optimality properties, and can be quite robust. Simulations of artificial populations and resamplings of real forestry data show that the SLM has smaller empirical root-mean-squared prediction errors (RMSPE) for a wide variety of data types, with generally less bias and better interval coverage than k-NN. These patterns held for both point predictions and for population totals or averages, with the SLM reducing RMSPE from 9% to 67% over some popular k-NN methods, with SLM also more robust to spatially imbalanced sampling. Estimating prediction standard errors remains a problem for k-NN predictors, despite recent attempts using model-based methods. Our conclusions are that the SLM should generally be used rather than k-NN if the goal is accurate mapping or estimation of population totals or averages.