Cloning and restriction fragment length polymorphism analysis of a cDNA for swine PIT-1, a gene controlling growth hormone expression*

A partial swine cDNA which encodes the functional domain of PIT-1 was isolated by the polymerse chain reaction (PCR). The swine PIT-1 cDNA clone is 95% identical at the protein level to the rat Pit-1 gene. Thus, Pit-l's known function in control of rat growth hormone and prolactin expression is likely to be conserved in swine. This swine cDNA clone was used to investigate genetic variability at PIT-1 in several American and Chinese breeds. Polymorphic BamIII fragments were found in pure-bred Meishan animals (n= 13), but only monomorphic fragments in five American breeds (n= 36).     

Focus: A Multifaceted Battle Against Cancer: Extracting Knowledge from Chemical Imaging Data Using Computational Algorithms for Digital Cancer Diagnosis

Fourier transform infrared (FTIR) spectroscopic imaging is an emerging microscopy modality for clinical histopathologic diagnoses as well as for biomedical research. Spectral data recorded in this modality are indicative of the underlying, spatially resolved biochemical composition but need computerized algorithms to digitally recognize and transform this information to a diagnostic tool to identify cancer or other physiologic conditions. Statistical pattern recognition forms the backbone of these recognition protocols and can be used for highly accurate results. Aided by biochemical correlations with normal and diseased states and the power of modern computer-aided pattern recognition, this approach is capable of combating many standing questions of traditional histology-based diagnosis models. For example, a simple diagnostic test can be developed to determine cell types in tissue. As a more advanced application, IR spectral data can be integrated with patient information to predict risk of cancer, providing a potential road to precision medicine and personalized care in cancer treatment. The IR imaging approach can be implemented to complement conventional diagnoses, as the samples remain unperturbed and are not destroyed. Despite high potential and utility of this approach, clinical implementation has not yet been achieved due to practical hurdles like speed of data acquisition and lack of optimized computational procedures for extracting clinically actionable information rapidly. The latter problem has been addressed by developing highly efficient ways to process IR imaging data but remains one that has considerable scope for progress. Here, we summarize the major issues and provide practical considerations in implementing a modified Bayesian classification protocol for digital molecular pathology. We hope to familiarize readers with analysis methods in IR imaging data and enable researchers to develop methods that can lead to the use of this promising technique for digital diagnosis of cancer.     

Detection of cyanobacterial sxt genes and paralytic shellfish toxins in freshwater lakes and brackish waters on Åland Islands,Finland

Harmful cyanobacteria are a globally growing concern. They produce a large variety of toxic compounds, including saxitoxin and its many structural variants, a group of potent neurotoxins collectively called paralytic shellfish toxins or PST. Nucleic acid based detection methods, such as qPCR, have been proposed as potential screening and monitoring tools for toxic cyanobacteria, but it is not clear how well the presence and quantity of saxitoxin biosynthesis (sxt) genes can be used to predict the production of PST in the environment. In this study, the prevalence of three sxt genes and their co-occurrence with paralytic shellfish toxins in the environment was investigated. The sxtA, sxtG and sxtB genes were present on average in 31% of the samples collected from lakes and brackish coastal waters on Åland Islands, Finland, during the three-year monitoring period. PST detection frequency varied from 13% to 59% from year to year, and concentrations were generally low. On average higher sxtB copy numbers were associated with PST detection, and although a positive correlation between gene copy numbers and toxin concentrations was observed (Spearman rank correlation, ρ = 0.53, P = 0.012), sxt gene presence or quantity didn’t reliably predict PST production. Sequencing of sxtA fragments and identification of main cyanobacteria indicated that the likely candidate responsible for PST production in the samples belonged to the genus Anabaena.     

Conventional and Molecular Identification of Bacteria with Magnesite Enrichment Potential from Local Quarries in Erzurum

In this study, the bacteria having ore enrichment potential were isolated from three different magnesite quarries located in Erzurum-Askale borderlines. The obtained isolates were identified and characterized according to the conventional (morphological, physiological and biochemical tests) and molecular techniques (fatty acid methyl ester profiles (FAME), BOX PCR and 16S rDNA). According to sequence analysis, they were determined as Exiguobacterium aurantiacum (4), Exiguobacterium sibiricum (2), Bacillus sp. (2), Staphylococcus epidermidis (2), Staphylococcus haemolyticus (1), Shewanella baltica (1) and Klebsiella oxytoca (1), respectively.     

An intelligent system for estimating frog community calling activity and species richness

Over the past decade, dramatic declines in frog populations have been noticed worldwide. To examine this decline, monitoring frogs is becoming increasingly important. Compared to traditional field survey methods, recent advances in acoustic sensor technology have greatly extended spatial and temporal scales for monitoring animal populations. In this paper, we examine the problem of monitoring frog populations by analysing acoustic sensor data, where the population is reflected by community calling activity and species richness. Specifically, a novel acoustic event detection (AED) algorithm is first proposed to filter out those recordings without frog calls. Then, multi-label learning is used to classify each individual recording with six acoustic features: linear predictive coding coefficients, Mel-frequency cepstral coefficients, linear-frequency cepstral coefficients, acoustic complexity index, acoustic diversity index, and acoustic evenness index. Next, frog community calling activity and species richness are estimated by accumulating the results of AED and multi-label learning, respectively. Finally, ordinary least squares regression (OLS) is conducted to reveal the relationship between frog populations (frog calling activity and species richness) and weather variables (maximum temperature and rainfall). Experimental results demonstrate that our proposed intelligent system can significantly facilitate the effort to estimate frog community calling activity and species richness with comparable accuracies. The statistical results of OLS indicate that rainfall pattern has a lagged impact on frog community calling activity (significant in the first day after rainy day) and species richness (significant in the fourth day after rainy day). Temperature is shown to affect species richness but is less likely to change calling activity.     

Denaturing gradient gel electrophoresis detection of polymorphism in a PCR fragment of sheep epidermal growth factor gene

The ovine map is not yet well-developed, which represents a problem when looking for markers of a region of interest in sheep. A means of circumventing this is to use comparative mapping. In this study primers were determined using consensus sequences for the epidermal growth factor gene of humans, rats and mice, and an ovine epidermal growth factor gene fragment was amplified by polymerase chain reaction (PCR). A new set of specific ovine primers was chosen to study the polymorphism of this DNA fragment by denaturing gradient gel electrophoresis. Eighty-four individuals belonging to seven sheep breeds were studied with this technique and four alleles were detected. The heterozygosity rate was 0.57. Family analysis showed mendelian inheritance of the alleles. Usually, genetic analysis of type-I loci used in the comparative mapping is based on the detection of restriction fragment length polymorphisms in sheep DNA using cDNA probes from other species. Our work shows that another method, based on PCR and denaturing gradient gel electrophoresis techniques, can be efficiently used.     

Molecular fingerprinting of peppermint (Mentha piperita) and some Mentha hybrids by sequencing and RFLP analysis of the 5S rRNA Non-Transcribed Spacer (NTS) region

Hybridization of species belonging to the genus Mentha is quite common. However, the indicators of hybridity are many and make Mentha hybrids' identification difficult. By using the same molecular strategy that allowed us to unequivocally identify some Mentha species, we amplified the Not-Transcribed-Spacer (NTS) of the 5S-rRNA gene to characterize the industrial crop peppermint, M. × piperita and some important Mentha interspecific hybrids: M. × dalmatica, M. × dumetorum, M. × rotundifolia, M. × maximilianea, M. × smithiana, M. × verticillata, M. × villosa. DNA amplification, sequence and cluster analysis revealed differences in the 5S-rRNA NTS region of Mentha hybrids. Peppermint and all other hybrids were unequivocally discriminated by RFLP analysis by using TaqI restriction enzyme, while a further discrimination between M. × dumetorum and M. × verticillata was obtained by XhoI restriction enzyme. Essential oil composition showed clustering patterns similar to DNA fingerprint, with a clear discrimination between plants producing menthofuran (e.g. M. aquatica and its related hybrids, including peppermint) and those containing piperitenone oxide (M. longifolia and its related hybrids).