The role of extracellular matrix metalloproteinase inducer protein in prostate cancer progression

Extracellular matrix metalloproteinase inducer (EMMPRIN/CD147) is a multifunctional membrane glycoprotein overexpressed in many solid tumors, and involved in tumor invasion and angiogenesis. We investigated EMMPRIN expression in human prostate cancer (CaP) tissues and cells, and evaluated whether EMMPRIN expression is related to tumor progression and matrix metalloproteinase (MMPs) expression in human CaP. An immunohistochemical study using tissue microarrays of 120 primary CaPs of different grades and 20 matched lymph node metastases from untreated patients was performed. The association of EMMPRIN expression with clinicopathological parameters was evaluated. Co-immunolocalization for EMMPRIN and MMP-1, MMP-2 or MMP-9 in primary tumors was examined using confocal microscopy. Flow cytometry and immunoblotting were used to examine EMMPRIN expression in 11 metastatic CaP cell lines. Heterogeneous expression of EMMPRIN was found in 78/120 (65%) CaPs, correlated significantly with progression parameters including pre-treatment PSA level (P < 0.05) and increased with progression of CaP (Gleason score, P < 0.05; pathological stage, P < 0.01; nodal involvement, P < 0.05 and surgical margin, P < 0.05). Heterogeneous cytoplasmic MMP-1, MMP-2 and MMP-9 associated with EMMPRIN immunolabeling was observed, particularly in tumors with Gleason scores >3 + 4. Metastatic CaP cell lines, except DuCaP, expressed abundant EMMPRIN protein, indicating highly ( approximately 45 to approximately 65 kDa) and less ( approximately 30 kDa) glycosylated forms, although with no relationship to cells being either androgen responsive or nonresponsive. Our results suggest that EMMPRIN may regulate MMPs and be involved in CaP progression, and as such, could provide a target for treating metastatic CaP disease.     

Bone modeling response to voluntary exercise in the hindlimb of mice

The functional adaptation of juvenile mammalian limb bone to mechanical loading is necessary to maintain bone strength. Diaphyseal size and shape are modified during growth through the process of bone modeling. Although bone modeling is a well-documented response to increased mechanical stress on growing diaphyseal bone, the effect of proximodistal location on bone modeling remains unclear. Distal limb elements in cursorial mammals are longer and thinner, most likely to conserve energy during locomotion because they require less energy to move. Therefore, distal elements are hypothesized to experience greater mechanical loading during locomotion and may be expected to exhibit a greater modeling response to exercise. In this study, histomorphometric comparisons are made between femora and tibiae of mice treated with voluntary exercise and a control group (N = 20). We find that femora of exercised mice exhibit both greater bone growth rates and growth areas than do controls (P < 0.05). The femora of exercised mice also have significantly greater cortical area, bending rigidity, and torsional rigidity (P < 0.05), although bending and torsional rigidity are comparable when standardized by bone length. Histomorphometric and cross-section geometric properties of the tibial midshaft of exercised and control mice did not differ significantly, although tibial length was significantly greater in exercised mice (P < 0.05). Femora of exercised mice were able to adapt to increased mechanical loading through increases in compressive, bending, and torsional rigidity. No such adaptations were found in the tibia. It is unclear if this is a biomechanical adaptation to greater stress in proximal elements or if distal elements are ontogenetically constrained in a tradeoff of bone strength of distal elements for bioenergetic efficiency during locomotion.     

Partitioning direct and indirect human-induced effects on carbon sequestration of managed coniferous forests using model simulations and forest inventories

Temperate forest ecosystems have recently been identified as an important net sink in the global carbon budget. The factors responsible for the strength of the sinks and their permanence, however, are less evident. In this paper, we quantify the present carbon sequestration in Thuringian managed coniferous forests. We quantify the effects of indirect human‐induced environmental changes (increasing temperature, increasing atmospheric CO₂ concentration and nitrogen fertilization), during the last century using BIOME‐BGC, as well as the legacy effect of the current age‐class distribution (forest inventories and BIOME‐BGC). We focused on coniferous forests because these forests represent a large area of central European forests and detailed forest inventories were available. The model indicates that environmental changes induced an increase in biomass C accumulation for all age classes during the last 20 years (1982–2001). Young and old stands had the highest changes in the biomass C accumulation during this period. During the last century mature stands (older than 80 years) turned from being almost carbon neutral to carbon sinks. In high elevations nitrogen deposition explained most of the increase of net ecosystem production (NEP) of forests. CO₂ fertilization was the main factor increasing NEP of forests in the middle and low elevations. According to the model, at present, total biomass C accumulation in coniferous forests of Thuringia was estimated at 1.51 t C ha^?1 yr^?1 with an averaged annual NEP of 1.42 t C ha^?1 yr^?1 and total net biome production of 1.03 t C ha^?1 yr^?1 (accounting for harvest). The annual averaged biomass carbon balance (BCB: biomass accumulation rate‐harvest) was 1.12 t C ha^?1 yr^?1 (not including soil respiration), and was close to BCB from forest inventories (1.15 t C ha^?1 yr^?1). Indirect human impact resulted in 33% increase in modeled biomass carbon accumulation in coniferous forests in Thuringia during the last century. From the forest inventory data we estimated the legacy effect of the age‐class distribution to account for 17% of the inventory‐based sink. Isolating the environmental change effects showed that these effects can be large in a long‐term, managed conifer forest.     

In silico analysis of lactic acid secretion metabolism through the top-down approach: Effect of grouping in enzyme kinetics

A top-down approach is known to be a useful and effective technique for the design and analysis of metabolic systems. In this study, we have constructed a grouped metabolic network forLactococcus lactis under aerobic conditions using grouped enzyme kinetics. To test the usefulness of grouping work, a non-grouped system and grouped systems were compared quantitatively with each other. Here, grouped systems were designed as two groups according to the extent of grouping. The overall simulated flux values in grouped and non-grouped models had pretty similar distribution trends, but the details on flux ratio at the pyruvate branch point showed a little difference. This result indicates that our grouping technique can be used as a good model for complicated metabolic networks, however, for detailed analysis of metabolic network, a more robust mechanism should be considered. In addition to the data for the pyruvate branch point analysis, some major flux control coefficients were obtained in this research.     

Modeling changes in soil organic matter in Amazon forest to pasture conversion with the Century model

Land use and land cover changes in the Brazilian Amazon region have major implications for regional and even global carbon cycling. We analyzed the effects of the predominant land use change, conversion of tropical forest to pasture, on total soil C and N, using the Century ecosystem model and data collected from the Nova Vida ranch, Western Brazilian Amazon. We estimated equilibrium organic matter levels, plant productivity and residue carbon inputs under native forest conditions, then simulated deforestation following the slash and burn procedure. Soil organic matter dynamics were simulated for pastures established in 1989, 1987, 1983, 1979, 1972, 1951, and 1911. Using input data from the Nova Vida ranch, the Century model predicted that forest clearance and conversion to pasture would cause an initial decline in soil C and N stocks, followed by a slow rise to levels exceeding those under native forest. Simulated soil total C and N levels (2500 g C m^?2 and 245 g N m^?2 in the 0–20 cm layer) prior to conversion to pasture were close to those measured in the native forest. Simulated above‐ and below‐ground biomass for the forest and pasture were comparable with literature values from this region. The model predicted the long‐term changes in soil C and N under pasture inferred from the pasture chronosequence, but there was considerable variation in soil C stocks for pastures <20 years in age. Differences in soil texture between pastures were relatively small and could not account for much of the variability between different pastures of similar ages, in either the measured or simulated data. It is likely that much of the variability in C stocks between pastures of similar ages is related to initial C stocks immediately following deforestation and that this was the largest source of variability in the chronosequence. Internal C cycling processes in Century were evaluated using measurements of microbial biomass and soil δ¹³C. The relative magnitude and long‐term trend in microbial biomass simulated by the model were consistent with measurements. The close fit of simulated to measured values of δ¹³C over time suggests that the relative loss of forest‐derived C and its replacement by pasture‐derived C was accurately predicted by the model. After 80 years, almost 90% of the organic matter in the top 20 cm was pasture derived. While our analysis represents a single ‘case study’ of pasture conversion, our results suggest that modeling studies in these pasture systems can help to evaluate the magnitude of impacts on C and N cycling, and determine the effect of management strategies on pasture sustainability.     

The net carbon flux due to deforestation and forest re-growth in the Brazilian Amazon: analysis using a process-based model

We developed a process‐based model of forest growth, carbon cycling and land‐cover dynamics named CARLUC (for CARbon and Land‐Use Change) to estimate the size of terrestrial carbon pools in terra firme (nonflooded) forests across the Brazilian Legal Amazon and the net flux of carbon resulting from forest disturbance and forest recovery from disturbance. Our goal in building the model was to construct a relatively simple ecosystem model that would respond to soil and climatic heterogeneity that allows us to study the impact of Amazonian deforestation, selective logging and accidental fire on the global carbon cycle. This paper focuses on the net flux caused by deforestation and forest re‐growth over the period from 1970 to 1998. We calculate that the net flux to the atmosphere during this period reached a maximum of ～0.35 PgC yr^?1 (1 PgC= 1 × 10¹⁵ gC) in 1990, with a cumulative release of ～7 PgC from 1970 to 1998. The net flux is higher than predicted by an earlier study ( Houghton et al., 2000 ) by a total of 1 PgC over the period 1989–1998 mainly because CARLUC predicts relatively high mature forest carbon storage compared with the datasets used in the earlier study. Incorporating the dynamics of litter and soil carbon pools into the model increases the cumulative net flux by～1 PgC from 1970 to 1998, while different assumptions about land‐cover dynamics only caused small changes. The uncertainty of the net flux, calculated with a Monte‐Carlo approach, is roughly 35% of the mean value (1 SD).     

The demographic costs of nectar production in the desert perennial Prosopis glandulosa (Mimosoideae): a modular approach

Nectar production in angiosperms is considered to represent a reproductive cost, and has been associated with a decrease in fruit set or an overall decrease in the energetic budget of the plant. Populations of Prosopis glandulosa var. torreyana (honey mesquite) are a suitable system to evaluate the demographic costs of nectar production, as populations are composed of a 1:1 proportion of nectarful to nectarless individuals. The study was carried out in a population of 404 individuals of Prosopis g1andulosa var. torreyana found in an area with differing water availability in the Southern Chihuahuan Desert. The possible costs of nectar production were assessed on 1212 shoots of the honey mesquite that were tagged in 1994 and followed until 1998. We used two methods of analysis to describe the effect of nectar production on modular population dynamics: matrix analysis and log-xlinear models. Water availability and the varying environmental conditions affected plant growth, but nectar production did not have an effect on the demographic parameters we measured. The values of λ did not differ between nectar morphs and the only important effects we detected were the year to year variation in precipitation and microclimate differences at each site. Furthermore, the elasticity of each demographic process (growth, fecundity, retrogression and stasis) between nectar morphs did not differ. The log-linear models suggested a similar pattern but could discriminate the importance of each factor (nectar morph, year and site) on module fate. We were not able to detect a demographic cost of nectar production in the honey mesquite. The absence of a demographic response could be due to the negligible cost of producing nectar for this species or that the resources allocated for growth are different from those allocated for reproduction. Our results suggest that the modular fates of mesquites are mainly determined by environmental factors. This revised version was published online in August 2006 with corrections to the Cover Date.     

Effects of forest fragmentation on small mammals in an Atlantic Forest landscape

Recent studies on the effects of tropical forest fragmentation indicate that fragmented landscapes are complex and heterogeneous systems influenced by factors other than the size or degree of isolation of forest remnants: of particular importance are the quality of the matrix and the edge-induced habitat changes. In order to investigate the influence of these factors, small mammals were surveyed in 36 sites in the landscape of Una, a region that encompasses some of the last and largest Atlantic Forest remnants in northeastern Brazil. Six sites were distributed on each of six landscape components – the interiors and edges of small remnants, the interiors and edges of large remnants, and the most common forested habitats found in the matrix. The survey comprised 46,656 trap-nights and yielded 1725 individuals of 20 species of rodents and marsupials. Results revealed: an increase in beta-diversity caused by fragmentation; the contrasting effects of the altered forested habitats of the matrix, which harbor both forest and disturbance-adapted species; a greater importance of edge effect than of patch size to the observed changes in small mammal community in remnants; an association among terrestrial forest species and among arboreal forest species in terms of the distribution and abundance in the Una mosaic; and a distinctive vulnerability of these two groups of species to fragmentation. Results emphasize the biological importance and conservation value of both fragmented landscapes and small remnants in the Atlantic Forest, as well as the importance of management techniques to control and attenuate edge effects.     

具有吸收状态的昆虫种群矩阵模型的研究

在Vandermeer的昆虫矩阵模型的基础上,提出了具有吸收状态的昆虫种群矩阵模型。并且导出了k步吸收状态与转移状态的矩阵表达式,将有助于昆虫种群动态的研究．     

Charting epilepsy by searching for intelligence in network space with the help of evolving autonomous agents

The problem of demarcating neural network space is formidable. A simple fully connected recurrent network of five units (binary activations, synaptic weight resolution of 10) has 3.2 *10(26) possible initial states. The problem increases drastically with scaling. Here we consider three complementary approaches to help direct the exploration to distinguish epileptic from healthy networks. [1] First, we perform a gross mapping of the space of five-unit continuous recurrent networks using randomized weights and initial activations. The majority of weight patterns (>70%) were found to result in neural assemblies exhibiting periodic limit-cycle oscillatory behavior. [2] Next we examine the activation space of non-periodic networks demonstrating that the emergence of paroxysmal activity does not require changes in connectivity. [3] The next challenge is to focus the search of network space to identify networks with more complex dynamics. Here we rely on a major available indicator critical to clinical assessment but largely ignored by epilepsy modelers, namely: behavioral states. To this end, we connected the above network layout to an external robot in which interactive states were evolved. The first random generation showed a distribution in line with approach [1]. That is, the predominate phenotypes were fixed-point or oscillatory with seizure-like motor output. As evolution progressed the profile changed markedly. Within 20 generations the entire population was able to navigate a simple environment with all individuals exhibiting multiply-stable behaviors with no cases of default locked limit-cycle oscillatory motor behavior. The resultant population may thus afford us a view of the architectural principles demarcating healthy biological networks from the pathological. The approach has an advantage over other epilepsy modeling techniques in providing a way to clarify whether observed dynamics or suggested therapies are pointing to computational viability or dead space.