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Minas Gerais is the fourth largest Brazilian state, and has an estimate of 354 native fish species. However, these fish species may be threatened, as this state has the highest rank of fish introductions reported for Brazil and South America. As one from the total of 85 non-native species detected, Lepomis gibbosus was introduced in the 60s to serve both as foragefish and to improve sport fishing. In this study, we evaluated the establishment of L. gibbosus in a shallow lake in the city ofOuro Preto, Doce River basin, state of Minas Gerais, Southeastern Brazil. We collected fish with fishing rods every two months from March 2002-February 2003. Fragments of gonads from a total of 226 females and 226 males were obtained and processed following standard histological techniques; then 5-7 microm thickness sections were taken and stained in hematoxylin-eosin. Besides, for each specimen, the biometric measurements included the standard length (SL) and body weight (BW); and the sex ratio was obtained. The reproductive cycle stages were confirmed by the distribution of oocytes and spermatogenic cells. The type of spawning was determined by the frequency distribution of the reproductive cycle stages and ovarian histology. Based on the microscopic characteristics of the gonads, the following stages of the reproductive cycle were determined: one=Rest, two=Mature, three=Spawned for females or Spent for males; males and females in reproduction were found throughout the study period. Post-spawned ovaries containing oocytes in stages one (initial perinucleolar), two (advanced perinucleolar), three (pre-vitellogenic), four (vitellogenic) and post-ovulatory follicles indicated fractionated-type spawning in this species. The smallest breeding male and female measured were 4.6 and 4.9cm standard length, respectively, suggesting stunting. The sex ratio did not vary between males and females along the year and bimonthly, being 1:1. Moreover, L. gibbosus appears to be at stage three of biological invasion: establishment through reproduction. We suggest to deliver information about "non-native species" through lectures in schools, colleges/universities, NGOs, government and environmental agencies in the cities and villages, in order to try to prevent environmental degradation by the introduction of non-native fish such as L. gibbosus in the region. We also recommend high fines for red-handed, and the import ban of non-native fish species to the region.

The importance of the promoter sequences in the function regulation of several important mycobacterial pathogens creates the necessity to design simple and fast theoretical models that can predict them. This work proposes two DNA promoter QSAR models based on pseudo-folding lattice network (LN) and star-graphs (SG) topological indices. In addition, a comparative study with the previous RNA electrostatic parameters of thermodynamically-driven secondary structure folding representations has been carried out. The best model of this work was obtained with only two LN stochastic electrostatic potentials and it is characterized by accuracy, selectivity and specificity of 90.87%, 82.96% and 92.95%, respectively. In addition, we pointed out the SG result dependence on the DNA sequence codification and we proposed a QSAR model based on codons and only three SG spectral moments.

The development of the complex network graphs permits us to describe any real system such as social, neural, computer or genetic networks by transforming real properties in topological indices (TIs). This work uses Randic's star networks in order to convert the protein primary structure data in specific topological indices that are used to construct a natural/random protein classification model. The set of natural proteins contains 1046 protein chains selected from the pre-compiled CulledPDB list from PISCES Dunbrack's Web Lab. This set is characterized by a protein homology of 20%, a structure resolution of 1.6A and R-factor lower than 25%. The set of random amino acid chains contains 1046 sequences which were generated by Python script according to the same type of residues and average chain length found in the natural set. A new Sequence to Star Networks (S2SNet) wxPython GUI application (with a Graphviz graphics back-end) was designed by our group in order to transform any character sequence in the following star network topological indices: Shannon entropy of Markov matrices, trace of connectivity matrices, Harary number, Wiener index, Gutman index, Schultz index, Moreau-Broto indices, Balaban distance connectivity index, Kier-Hall connectivity indices and Randic connectivity index. The model was constructed with the General Discriminant Analysis methods from STATISTICA package and gave training/predicting set accuracies of 90.77% for the forward stepwise model type. In conclusion, this study extends for the first time the classical TIs to protein star network TIs by proposing a model that can predict if a protein/fragment of protein is natural or random using only the amino acid sequence data. This classification can be used in the studies of the protein functions by changing some fragments with random amino acid sequences or to detect the fake amino acid sequences or the errors in proteins. These results promote the use of the S2SNet application not only for protein structure analysis but also for mass spectroscopy, clinical proteomics and imaging, or DNA/RNA structure analysis.