Estimating fishing and natural mortality rates, and catchability coefficient, from a series of observations on mean length and fishing effort

Gedamke and Hoenig (2006) (Transactions of the American Fisheries Society, 135: 476-487) developed a non-equilibrium version of the Beverton and Holt estimator of total mortality rate, Z, based on mean length and thereby increased the usefulness of length-based methods. In this study, we extend their model by replacing period-specific Z parameters with the year-specific parameterization Z(y) = qf(y) + M where q is the catchability coefficient, f(y) is the fishing effort in year y, F (= qf) is the fishing mortality rate, and M is the natural mortality rate. Thus, the problem reduces to estimating just three parameters: q, M and residual variance. We used Monte Carlo simulation to study the model behaviour. Estimates of q and M are highly negatively correlated and may or may not be reliable; however, the estimates of corresponding Z\u27s are more precise than estimates of F and are generally reliable, even when uncertainty about the mean lengths is high. This length-based method appears to work best for stocks with rapid growth rate. Contrast in effort data may not be necessary for reliable estimates of Z\u27s. This approach forms a bridge between data-limited models and more complex models. We apply the method to the Norway lobster Nephrops norvegicus stock in Portugal as an example

Complete genome characterization of two wild-type measles viruses from Vietnamese infants during the 2014 outbreak

A large measles virus outbreak occurred across Vietnam in 2014. We identified and obtained complete measles virus genomes in stool samples collected from two diarrheal pediatric patients in Dong Thap Province. These are the first complete genome sequences of circulating measles viruses in Vietnam during the 2014 measles outbreak

Genome sequences of a novel Vietnamese bat bunyavirus

To document the viral zoonotic risks in Vietnam, fecal samples were systematically collected from a number of mammals in southern Vietnam and subjected to agnostic deep sequencing. We describe here novel Vietnamese bunyavirus sequences detected in bat feces. The complete L and S segments from 14 viruses were determined

Identification and characterization of Coronaviridae genomes from Vietnamese bats and rats based on conserved protein domains

The Coronaviridae family of viruses encompasses a group of pathogens with a zoonotic potential as observed from previous outbreaks of the severe acute respiratory syndrome coronavirus and Middle East respiratory syndrome coronavirus. Accordingly, it seems important to identify and document the coronaviruses in animal reservoirs, many of which are uncharacterized and potentially missed by more standard diagnostic assays. A combination of sensitive deep sequencing technology and computational algorithms is essential for virus surveillance, especially for characterizing novel- or distantly related virus strains. Here, we explore the use of profile Hidden Markov Model-defined Pfam protein domains (Pfam domains) encoded by new sequences as a Coronaviridae sequence classification tool. The encoded domains are used first in a triage to identify potential Coronaviridae sequences and then processed using a Random Forest method to classify the sequences to the Coronaviridae genus level. The application of this algorithm on Coronaviridae genomes assembled from agnostic deep sequencing data from surveillance of bats and rats in Dong Thap province (Vietnam) identified thirty-four Alphacoronavirus and eleven Betacoronavirus genomes. This collection of bat and rat coronaviruses genomes provided essential information on the local diversity of coronaviruses and substantially expanded the number of coronavirus full genomes available from bat and rats and may facilitate further molecular studies on this group of viruses

Epigenomics of breast cancer

Breast cancer is the second most common malignant cancer and accounts for 1.38 million of the total new cancer cases and 458,400 of the total cancer deaths reported in 2008. Breast cancer with several subtypes is an extremely heterogeneous disease caused by interaction of both genetic and environmental risk factors. In order to understand the etiology of this heterogeneity, new perspectives like epigenetics are needed. The term epigenetics was coined by Conrad Hal Waddington in the early 1940s. It refers to the study of gene function and regulation alterations without changes in the DNA sequence of the genome. The main epigenetic modifications are DNA methylation, histone modifications, and small noncoding RNAs (miRNAs). DNA methylation is the first to be associated with cancer and the most widely studied among epigenetic modifications. It regulates the gene expression by modifying the accessibility of DNA to the transcriptional machinery. The importance of histone modification has been realized during the last 10 years, after identification of the coexistence of histone modifications. From the dynamically changing pattern of histone modification has emerged a new concept termed histone cross talk. The epigenetic modifications are faster and reversible than mutation and easily affected by aging, environmental stimuli, and food in heritable manner. These characteristics provide a vital position in the etiology of diseases. After several investigations, it is well understood that the epigenetic modifications are involved in not only many biological processes such as X-chromosome inactivation, genomic imprinting, RNA interference, and programming of the genome but also several disease like breast cancer. Today we realize that the accumulation of epigenetic modifications occurs in the development of breast cancer. In addition, the epigenetic modifications improve our knowledge about the biology and heterogeneity of breast cancer by large-scale methods. Therefore, the researchers focused on epigenetic alterations-based breast cancer therapy, and it is speculated that epigenetic modifications may be markers for breast cancer. It is likely that epigenetics-based therapy will become a reality in the near future. © 2014 Springer India. All rights reserved