Soil-induced impacts on forest structure drive coarse woody debris stocks across central Amazonia

PublishedJournal Article© 2014, © 2014 Botanical Society of Scotland and Taylor & Francis. Background: Coarse woody debris (CWD) is an essential component in tropical forest ecosystems and its quantity varies widely with forest types. Aims: Relationships among CWD, soil, forest structure and other environmental factors were analysed to understand the drivers of variation in CWD in forests on different soil types across central Amazonia. Methods: To estimate CWD stocks and density of dead wood debris, 75 permanent forest plots of 0.5 ha in size were assessed along a transect that spanned ca. 700 km in undisturbed forests from north of the Rio Negro to south of the Rio Amazonas. Soil physical properties were evaluated by digging 2-m-deep pits and by taking auger samples. Results: Soil physical properties were the best predictors of CWD stocks; 37% of its variation was explained by effective soil depth. CWD stocks had a two-fold variation across a gradient of physical soil constraints (i.e. effective soil depth, anoxia and soil structure). Average biomass per tree was related to physical soil constraints, which, in turn, had a strong relationship with local CWD stocks. Conclusions: Soil physical properties appear to control average biomass per tree (and through this affect forest structure and dynamics), which, in turn, is correlated with CWD production and stocks

Bridging Time Scales in Cellular Decision Making with a Stochastic Bistable Switch

Cellular transformations which involve a significant phenotypical change of the cell's state use bistable biochemical switches as underlying decision systems. In this work, we aim at linking cellular decisions taking place on a time scale of years to decades with the biochemical dynamics in signal transduction and gene regulation, occuring on a time scale of minutes to hours. We show that a stochastic bistable switch forms a viable biochemical mechanism to implement decision processes on long time scales. As a case study, the mechanism is applied to model the initiation of follicle growth in mammalian ovaries, where the physiological time scale of follicle pool depletion is on the order of the organism's lifespan. We construct a simple mathematical model for this process based on experimental evidence for the involved genetic mechanisms. Despite the underlying stochasticity, the proposed mechanism turns out to yield reliable behavior in large populations of cells subject to the considered decision process. Our model explains how the physiological time constant may emerge from the intrinsic stochasticity of the underlying gene regulatory network. Apart from ovarian follicles, the proposed mechanism may also be of relevance for other physiological systems where cells take binary decisions over a long time scale.Comment: 14 pages, 4 figure

Gene expression profiling in genetic animal models of provide elements to unveil the molecular mechanisms underlying epileptogenesis in rodents

OBJECTIVE: The objective of this study was to characterize and compare the genetic profile of two rodent models of epilepsy (Wistar Audiogenic Rat - WAR and rats with generalized epilepsy with absence seizures-GEAS) using gene expression analysis METHODS: We used microarray technology for gene expression analysis. RESULTS: The analysis of gene expression profiles in WAR showed among genes up-regulated Neurod1, involved in the development of the cochlear duct. In addition, we found significant differences in gene expression of Apbb1, Foxg1 and Scn1A. GEAS rats had differentially expressed genes related to the development of central nervous system, as well as genes involved in the MAPK pathway, transcription factors, neuronal migration and apoptosis. CONCLUSION: This study may help to clarify the underlying molecular mechanism that leads to the predisposition to seizures in these animals. Our results indicate the activation of distinct molecular pathways in both models.OBJETIVO: O objetivo desse trabalho foi caracterizar e comparar o perfil genético de dois modelos de epilepsia em roedores (Wistar Audiogenic Rat - WAR e generalized epilepsy with absence seizures - GEAS) através da análise da expressão gênica em larga escala. MÉTODOS: Para a análise do perfil de expressão gênica foi utilizada a técnica de microarranjos de DNA (microarray). RESULTADOS: Na linhagem WAR a análise do perfil de expressão mostrou que dentro os genes mais hiperexpressos está o Neurod1, envolvido com o desenvolvimento do ducto coclear. Além desse encontramos também diferenças significativas na expressão dos genes Apbb1, Foxg1 e Scn1A. Já nos animais GEAS os genes com maior expressão diferencial foram àqueles relacionados com o desenvolvimento do sistema nervoso central, além de genes envolvidos com a via da MAPK, fatores de transcrição, migração neuronal e apoptose. CONCLUSÃO: Esta análise pode ajudar a esclarecer o mecanismo molecular subjacente que leva a predisposição a crises nesses animais. Até o momento, nossos resultados apontam para a ativação de vias moleculares distintas em ambos os modelos.505

Chemical resistance of the gram-negative bacteria to different sanitizers in a water purification system

BACKGROUND: Purified water for pharmaceutical purposes must be free of microbial contamination and pyrogens. Even with the additional sanitary and disinfecting treatments applied to the system (sequential operational stages), Pseudomonas aeruginosa, Pseudomonas fluorescens, Pseudomonas alcaligenes, Pseudomonas picketti, Flavobacterium aureum, Acinetobacter lowffi and Pseudomonas diminuta were isolated and identified from a thirteen-stage purification system. To evaluate the efficacy of the chemical agents used in the disinfecting process along with those used to adjust chemical characteristics of the system, over the identified bacteria, the kinetic parameter of killing time (D-value) necessary to inactivate 90% of the initial bioburden (decimal reduction time) was experimentally determined. METHODS: Pseudomonas aeruginosa, Pseudomonas fluorescens, Pseudomonas alcaligenes, Pseudomonas picketti, Flavobacterium aureum, Acinetobacter lowffi and Pseudomonas diminuta were called in house (wild) bacteria. Pseudomonas diminuta ATCC 11568, Pseudomonas alcaligenes INCQS , Pseudomonas aeruginosa ATCC 15442, Pseudomonas fluorescens ATCC 3178, Pseudomonas picketti ATCC 5031, Bacillus subtilis ATCC 937 and Escherichia coli ATCC 25922 were used as 'standard' bacteria to evaluate resistance at 25°C against either 0.5% citric acid, 0.5% hydrochloric acid, 70% ethanol, 0.5% sodium bisulfite, 0.4% sodium hydroxide, 0.5% sodium hypochlorite, or a mixture of 2.2% hydrogen peroxide (H(2)O(2)) and 0.45% peracetic acid. RESULTS: The efficacy of the sanitizers varied with concentration and contact time to reduce decimal logarithmic (log(10)) population (n cycles). To kill 90% of the initial population (or one log(10 )cycle), the necessary time (D-value) was for P. aeruginosa into: (i) 0.5% citric acid, D = 3.8 min; (ii) 0.5% hydrochloric acid, D = 6.9 min; (iii) 70% ethanol, D = 9.7 min; (iv) 0.5% sodium bisulfite, D = 5.3 min; (v) 0.4% sodium hydroxide, D = 14.2 min; (vi) 0.5% sodium hypochlorite, D = 7.9 min; (vii) mixture of hydrogen peroxide (2.2%) plus peracetic acid (0.45%), D = 5.5 min. CONCLUSION: The contact time of 180 min of the system with the mixture of H(2)O(2)+ peracetic acid, a total theoretical reduction of 6 log(10 )cycles was attained in the water purified storage tank and distribution loop. The contact time between the water purification system (WPS) and the sanitary agents should be reviewed to reach sufficient bioburden reduction (over 6 log(10))