Maternal diabetes affects cell proliferation in developing rat placenta

Placentation starts with the formation of a spheroidal trophoblastic shell surrounding the embryo, thus facilitating both implantation into the uterine stroma and contact with maternal blood. Although it is known that diabetes increases the placental size and weight, the mechanisms responsible for this alteration are still poorly understood. In mammals, cellular proliferation occurs in parallel to placental development and it is possible that diabetes induces abnormal uncontrolled cell proliferation in the placenta similar to that seen in other organs (e.g. retina). To test this hypothesis, the objective of this work was to determine cell proliferation in different regions of the placenta during its development in a diabetic rat model. Accordingly, diabetes was induced on day 2 of pregnancy in Wistar rats by a single injection of alloxan (40 mg/kg i.v.). Placentas were collected on days 14, 17, and 20 postcoitum. Immunoperoxidase was used to identify Ki67 nuclear antigen in placental sections. The number of proliferating cells was determined in the total placental area as well as in the labyrinth, spongiotrophoblast and giant trophoblast cell regions. During the course of pregnancy, the number of Ki67 positive cells decreased in both control and diabetic rat placentas. However, starting from day 17 of pregnancy, the number of Ki67 positive cells in the labyrinth and spongiotrophoblast regions was higher in diabetic rat placentas as compared to control. The present results demonstrate that placentas from the diabetic rat model have a significantly higher number of proliferating cells in specific regions of the placenta and at defined developmental stages. It is possible that this increased cell proliferation promotes thickness of the placental barrier consequently affecting the normal maternal-fetal exchanges.

Activation of endogenous p53 by combined p19Arf gene transfer and nutlin-3 drug treatment modalities in the murine cell lines B16 and C6

Background: Reactivation of p53 by either gene transfer or pharmacologic approaches may compensate for loss of p19Arf or excess mdm2 expression, common events in melanoma and glioma. In our previous work, we constructed the pCLPG retroviral vector where transgene expression is controlled by p53 through a p53-responsive promoter. The use of this vector to introduce p19Arf into tumor cells that harbor p53wt should yield viral expression of p19Arf which, in turn, would activate the endogenous p53 and result in enhanced vector expression and tumor suppression. Since nutlin-3 can activate p53 by blocking its interaction with mdm2, we explored the possibility that the combination of p19Arf gene transfer and nutlin-3 drug treatment may provide an additive benefit in stimulating p53 function. Methods: B16 (mouse melanoma) and C6 (rat glioma) cell lines, which harbor p53wt, were transduced with pCLPGp19 and these were additionally treated with nutlin-3 or the DNA damaging agent, doxorubicin. Viral expression was confirmed by Western, Northern and immunofluorescence assays. p53 function was assessed by reporter gene activity provided by a p53-responsive construct. Alterations in proliferation and viability were measured by colony formation, growth curve, cell cycle and MTT assays. In an animal model, B16 cells were treated with the pCLPGp19 virus and/or drugs before subcutaneous injection in C57BL/6 mice, observation of tumor progression and histopathologic analyses. Results: Here we show that the functional activation of endogenous p53wt in B16 was particularly challenging, but accomplished when combined gene transfer and drug treatments were applied, resulting in increased transactivation by p53, marked cell cycle alteration and reduced viability in culture. In an animal model, B16 cells treated with both p19Arf and nutlin-3 yielded increased necrosis and decreased BrdU marking. In comparison, C6 cells were quite susceptible to either treatment, yet p53 was further activated by the combination of p19Arf and nutlin-3. Conclusions: To the best of our knowledge, this is the first study to apply both p19Arf and nutlin-3 for the stimulation of p53 activity. These results support the notion that a p53 responsive vector may prove to be an interesting gene transfer tool, especially when combined with p53- activating agents, for the treatment of tumors that retain wild-type p53.

Low-Level Laser Irradiation (InGaAlP-660 nm) Increases Fibroblast Cell Proliferation and Reduces Cell Death in a Dose-Dependent Manner

Background and Objective: Impaired cell metabolism and increased cell death in fibroblast cells are physiological features of chronic tendinopathy. Although several studies have shown that low-level laser therapy (LLLT) at certain parameters has a biostimulatory effect on fibroblast cells, it remains uncertain if LLLT effects depend on the physiological state. Study Design/Material and Methods: High-metabolic immortal cell culture and primary human keloid fibroblast cell culture were used in this study. Trypan blue exclusion and the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) test were used to determine cell viability and proliferation. Propidium iodide stain was used for cell-cycle analysis by flow cytometry. Laser irradiation was performed daily on three consecutive days with a GaAlAs 660-nm laser (mean output: 50 mW, spot size 2 mm(2), power density = 2.5 W/cm(2)) and a typical LLLT dose and a high LLLT dose (irradiation times: 60 or 420 s; fluences: 150 or 1050 J/cm(2); energy delivered: 3 or 21 J). Results: Primary fibroblast cell culture from human keloids irradiated with 3 J showed significant proliferation by the trypan blue exclusion test (p < 0.05), whereas the 3T3 cell culture showed no difference using this method. Propidium iodide staining flow cytometry data showed a significant decrease in the percentage of cells being in proliferative phases of the cell cycle (S/g(2)/M) when irradiated with 21 J in both cell types (hypodiploid cells increased). Conclusions: Our data support the hypothesis that the physiological state of the cells affects the LLLT results, and that high-metabolic rate and short-cell-cycle 3T3 cells are not responsive to LLLT. In conclusion, LLLT with a dose of 3 J reduced cell death significantly, but did not stimulate cell cycle. A LLLT dose of 21 J had negative effects on the cells, as it increased cell death and inhibited cell proliferation.

Comparison Between Single-Diode Low-Level Laser Therapy (LLLT) and LED Multi-Diode (Cluster) Therapy (LEDT) Applications Before High-Intensity Exercise

Background Data and Objective: There is anecdotal evidence that low-level laser therapy (LLLT) may affect the development of muscular fatigue, minor muscle damage, and recovery after heavy exercises. Although manufacturers claim that cluster probes (LEDT) maybe more effective than single-diode lasers in clinical settings, there is a lack of head-to-head comparisons in controlled trials. This study was designed to compare the effect of single-diode LLLT and cluster LEDT before heavy exercise. Materials and Methods: This was a randomized, placebo-controlled, double-blind cross-over study. Young male volleyball players (n = 8) were enrolled and asked to perform three Wingate cycle tests after 4 x 30 sec LLLT or LEDT pretreatment of the rectus femoris muscle with either (1) an active LEDT cluster-probe (660/850 nm, 10/30mW), (2) a placebo cluster-probe with no output, and (3) a single-diode 810-nm 200-mW laser. Results: The active LEDT group had significantly decreased post-exercise creatine kinase (CK) levels (-18.88 +/- 41.48U/L), compared to the placebo cluster group (26.88 +/- 15.18U/L) (p < 0.05) and the active single-diode laser group (43.38 +/- 32.90U/L) (p<0.01). None of the pre-exercise LLLT or LEDT protocols enhanced performance on the Wingate tests or reduced post-exercise blood lactate levels. However, a non-significant tendency toward lower post-exercise blood lactate levels in the treated groups should be explored further. Conclusion: In this experimental set-up, only the active LEDT probe decreased post-exercise CK levels after the Wingate cycle test. Neither performance nor blood lactate levels were significantly affected by this protocol of pre-exercise LEDT or LLLT.

Cellular Renewal and Improvement of Local Cell Effector Activity in Peritoneal Cavity in Response to Infectious Stimuli

The peritoneal cavity (PerC) is a singular compartment where many cell populations reside and interact. Despite the widely adopted experimental approach of intraperitoneal (i.p.) inoculation, little is known about the behavior of the different cell populations within the PerC. To evaluate the dynamics of peritoneal macrophage (Mempty set) subsets, namely small peritoneal Mempty set (SPM) and large peritoneal Mempty set (LPM), in response to infectious stimuli, C57BL/6 mice were injected i.p. with zymosan or Trypanosoma cruzi. These conditions resulted in the marked modification of the PerC myelo-monocytic compartment characterized by the disappearance of LPM and the accumulation of SPM and monocytes. In parallel, adherent cells isolated from stimulated PerC displayed reduced staining for beta-galactosidase, a biomarker for senescence. Further, the adherent cells showed increased nitric oxide (NO) and higher frequency of IL-12-producing cells in response to subsequent LPS and IFN-gamma stimulation. Among myelo-monocytic cells, SPM rather than LPM or monocytes, appear to be the central effectors of the activated PerC; they display higher phagocytic activity and are the main source of IL-12. Thus, our data provide a first demonstration of the consequences of the dynamics between peritoneal Mempty set subpopulations by showing that substitution of LPM by a robust SPM and monocytes in response to infectious stimuli greatly improves PerC effector activity.

The Spleen CD4(+) T Cell Response to Blood-Stage Plasmodium chabaudi Malaria Develops in Two Phases Characterized by Different Properties

The pivotal role of spleen CD4(+) T cells in the development of both malaria pathogenesis and protective immunity makes necessary a profound comprehension of the mechanisms involved in their activation and regulation during Plasmodium infection. Herein, we examined in detail the behaviour of non-conventional and conventional splenic CD4(+) T cells during P. chabaudi malaria. We took advantage of the fact that a great proportion of CD4(+) T cells generated in CD1d(-/-) mice are I-A(b)-restricted (conventional cells), while their counterparts in I-Ab(-/-) mice are restricted by CD1d and other class IB major histocompatibility complex (MHC) molecules (non-conventional cells). We found that conventional CD4(+) T cells are the main protagonists of the immune response to infection, which develops in two consecutive phases concomitant with acute and chronic parasitaemias. The early phase of the conventional CD4(+) T cell response is intense and short lasting, rapidly providing large amounts of proinflammatory cytokines and helping follicular and marginal zone B cells to secrete polyclonal immunoglobulin. Both TNF-alpha and IFN-gamma production depend mostly on conventional CD4(+) T cells. IFN-gamma is produced simultaneously by non-conventional and conventional CD4(+) T cells. The early phase of the response finishes after a week of infection, with the elimination of a large proportion of CD4(+) T cells, which then gives opportunity to the development of acquired immunity. Unexpectedly, the major contribution of CD1d-restricted CD4(+) T cells occurs at the beginning of the second phase of the response, but not earlier, helping both IFN-gamma and parasite-specific antibody production. We concluded that conventional CD4(+) T cells have a central role from the onset of P. chabaudi malaria, acting in parallel with non-conventional CD4(+) T cells as a link between innate and acquired immunity. This study contributes to the understanding of malaria immunology and opens a perspective for future studies designed to decipher the molecular mechanisms behind immune responses to Plasmodium infection.

Impaired Innate Immunity in Tlr4(-/-) Mice but Preserved CD8(+) T Cell Responses against Trypanosoma cruzi in Tlr4-, Tlr2-, Tlr9- or Myd88-Deficient Mice

The murine model of T. cruzi infection has provided compelling evidence that development of host resistance against intracellular protozoans critically depends on the activation of members of the Toll-like receptor (TLR) family via the MyD88 adaptor molecule. However, the possibility that TLR/MyD88 signaling pathways also control the induction of immunoprotective CD8(+) T cell-mediated effector functions has not been investigated to date. We addressed this question by measuring the frequencies of IFN-gamma secreting CD8(+) T cells specific for H-2K(b)-restricted immunodominant peptides as well as the in vivo Ag-specific cytotoxic response in infected animals that are deficient either in TLR2, TLR4, TLR9 or MyD88 signaling pathways. Strikingly, we found that T. cruzi-infected Tlr2(-/-), Tlr4(-/-), Tlr9(-/-) or Myd88(-/-) mice generated both specific cytotoxic responses and IFN-gamma secreting CD8(+) T cells at levels comparable to WT mice, although the frequency of IFN-gamma(+)CD4(+) cells was diminished in infected Myd88(-/-) mice. We also analyzed the efficiency of TLR4-driven immune responses against T. cruzi using TLR4-deficient mice on the C57BL genetic background (B6 and B10). Our studies demonstrated that TLR4 signaling is required for optimal production of IFN-gamma, TNF-alpha and nitric oxide (NO) in the spleen of infected animals and, as a consequence, Tlr4(-/-) mice display higher parasitemia levels. Collectively, our results indicate that TLR4, as well as previously shown for TLR2, TLR9 and MyD88, contributes to the innate immune response and, consequently, resistance in the acute phase of infection, although each of these pathways is not individually essential for the generation of class I-restricted responses against T. cruzi.

The influence of adsorption phenomena on the impedance spectroscopy of an electrolytic cell

In this work we investigate the influence of the adsorption of ions on the impedance spectroscopy of an electrolytic cell. We consider that the positive and negative ions present in a dielectric liquid are adsorbed in the electrode surfaces with different adsorption energies. This difference in adsorption energies causes an additional plateaux in the limit of the low-frequency range of the real part of the impedance Z. In the same frequency range, a second minimum in the imaginary part of Z is predicted. The theory is illustrated with measurements of the impedance of an electrolytic solution in the frequency range from 10(-2) Hz to 1 KHz. A comparison between the present model and others from the literature to describe the experimental results is also made.

Theoretical investigation of atomic and electronic structures of Ga(2)O(3)(ZnO)(6)

Transparent conducting oxides (TCO) are widely used in technological applications ranging from photovoltaics to thin-film transparent field-effect transistors. In this work we report a first-principles investigation, based on density-functional theory, of the atomic and electronic properties of Ga(2)O(3)(ZnO)(6) (GZO(6)), which is a promising candidate to be used as host oxide for wide band gap TCO applications. We identify a low-energy configuration for the coherent distribution of the Ga and Zn atoms in the cation positions within the experimentally reported orthorhombic GZO(6) structure. Four Ga atoms are located in four-fold sites, while the remaining 12 Ga atoms in the unit cell form four shared Ga agglomerates (a motif of four atoms). The Zn atoms are distributed in the remaining cation sites with effective coordination numbers from 3.90 to 4.50. Furthermore, we identify the natural formation of twin-boundaries in GZO(6), which can explain the zigzag modulations observed experimentally by high-resolution transmission electron microscopy in GZO(n) (n=9). Due to the intrinsic twin-boundary formation, polarity inversion in the ZnO tetrahedrons is present which is facilitated by the formation of the Ga agglomerates. Our analysis shows that the formation of fourfold Ga sites and Ga agglomerates are stabilized by the electronic octet rule, while the distribution of Ga atoms and the formation of the twin-boundary help alleviate excess strain. Finally we identify that the electronic properties of GZO(6) are essentially determined by the electronic properties of ZnO, i.e., there are slight changes in the band gap and optical absorption properties.

Gene Expression Complex Networks: Synthesis, Identification, and Analysis

Thanks to recent advances in molecular biology, allied to an ever increasing amount of experimental data, the functional state of thousands of genes can now be extracted simultaneously by using methods such as cDNA microarrays and RNA-Seq. Particularly important related investigations are the modeling and identification of gene regulatory networks from expression data sets. Such a knowledge is fundamental for many applications, such as disease treatment, therapeutic intervention strategies and drugs design, as well as for planning high-throughput new experiments. Methods have been developed for gene networks modeling and identification from expression profiles. However, an important open problem regards how to validate such approaches and its results. This work presents an objective approach for validation of gene network modeling and identification which comprises the following three main aspects: (1) Artificial Gene Networks (AGNs) model generation through theoretical models of complex networks, which is used to simulate temporal expression data; (2) a computational method for gene network identification from the simulated data, which is founded on a feature selection approach where a target gene is fixed and the expression profile is observed for all other genes in order to identify a relevant subset of predictors; and (3) validation of the identified AGN-based network through comparison with the original network. The proposed framework allows several types of AGNs to be generated and used in order to simulate temporal expression data. The results of the network identification method can then be compared to the original network in order to estimate its properties and accuracy. Some of the most important theoretical models of complex networks have been assessed: the uniformly-random Erdos-Renyi (ER), the small-world Watts-Strogatz (WS), the scale-free Barabasi-Albert (BA), and geographical networks (GG). The experimental results indicate that the inference method was sensitive to average degree k variation, decreasing its network recovery rate with the increase of k. The signal size was important for the inference method to get better accuracy in the network identification rate, presenting very good results with small expression profiles. However, the adopted inference method was not sensible to recognize distinct structures of interaction among genes, presenting a similar behavior when applied to different network topologies. In summary, the proposed framework, though simple, was adequate for the validation of the inferred networks by identifying some properties of the evaluated method, which can be extended to other inference methods.

Feature selection environment for genomic applications

Background: Feature selection is a pattern recognition approach to choose important variables according to some criteria in order to distinguish or explain certain phenomena (i.e., for dimensionality reduction). There are many genomic and proteomic applications that rely on feature selection to answer questions such as selecting signature genes which are informative about some biological state, e. g., normal tissues and several types of cancer; or inferring a prediction network among elements such as genes, proteins and external stimuli. In these applications, a recurrent problem is the lack of samples to perform an adequate estimate of the joint probabilities between element states. A myriad of feature selection algorithms and criterion functions have been proposed, although it is difficult to point the best solution for each application. Results: The intent of this work is to provide an open-source multiplataform graphical environment for bioinformatics problems, which supports many feature selection algorithms, criterion functions and graphic visualization tools such as scatterplots, parallel coordinates and graphs. A feature selection approach for growing genetic networks from seed genes ( targets or predictors) is also implemented in the system. Conclusion: The proposed feature selection environment allows data analysis using several algorithms, criterion functions and graphic visualization tools. Our experiments have shown the software effectiveness in two distinct types of biological problems. Besides, the environment can be used in different pattern recognition applications, although the main concern regards bioinformatics tasks.

An algorithmic Friedman-Pippenger theorem on tree embeddings and applications

An (n, d)-expander is a graph G = (V, E) such that for every X subset of V with vertical bar X vertical bar <= 2n - 2 we have vertical bar Gamma(G)(X) vertical bar >= (d + 1) vertical bar X vertical bar. A tree T is small if it has at most n vertices and has maximum degree at most d. Friedman and Pippenger (1987) proved that any ( n; d)- expander contains every small tree. However, their elegant proof does not seem to yield an efficient algorithm for obtaining the tree. In this paper, we give an alternative result that does admit a polynomial time algorithm for finding the immersion of any small tree in subgraphs G of (N, D, lambda)-graphs Lambda, as long as G contains a positive fraction of the edges of Lambda and lambda/D is small enough. In several applications of the Friedman-Pippenger theorem, including the ones in the original paper of those authors, the (n, d)-expander G is a subgraph of an (N, D, lambda)-graph as above. Therefore, our result suffices to provide efficient algorithms for such previously non-constructive applications. As an example, we discuss a recent result of Alon, Krivelevich, and Sudakov (2007) concerning embedding nearly spanning bounded degree trees, the proof of which makes use of the Friedman-Pippenger theorem. We shall also show a construction inspired on Wigderson-Zuckerman expander graphs for which any sufficiently dense subgraph contains all trees of sizes and maximum degrees achieving essentially optimal parameters. Our algorithmic approach is based on a reduction of the tree embedding problem to a certain on-line matching problem for bipartite graphs, solved by Aggarwal et al. (1996).

TESTING STATISTICAL HYPOTHESIS ON RANDOM TREES AND APPLICATIONS TO THE PROTEIN CLASSIFICATION PROBLEM

Efficient automatic protein classification is of central importance in genomic annotation. As an independent way to check the reliability of the classification, we propose a statistical approach to test if two sets of protein domain sequences coming from two families of the Pfam database are significantly different. We model protein sequences as realizations of Variable Length Markov Chains (VLMC) and we use the context trees as a signature of each protein family. Our approach is based on a Kolmogorov-Smirnov-type goodness-of-fit test proposed by Balding et at. [Limit theorems for sequences of random trees (2008), DOI: 10.1007/s11749-008-0092-z]. The test statistic is a supremum over the space of trees of a function of the two samples; its computation grows, in principle, exponentially fast with the maximal number of nodes of the potential trees. We show how to transform this problem into a max-flow over a related graph which can be solved using a Ford-Fulkerson algorithm in polynomial time on that number. We apply the test to 10 randomly chosen protein domain families from the seed of Pfam-A database (high quality, manually curated families). The test shows that the distributions of context trees coming from different families are significantly different. We emphasize that this is a novel mathematical approach to validate the automatic clustering of sequences in any context. We also study the performance of the test via simulations on Galton-Watson related processes.

Functional microarray analysis suggests repressed cell-cell signaling and cell survival-related modules inhibit progression of head and neck squamous cell carcinoma

Background: Cancer shows a great diversity in its clinical behavior which cannot be easily predicted using the currently available clinical or pathological markers. The identification of pathways associated with lymph node metastasis (N+) and recurrent head and neck squamous cell carcinoma (HNSCC) may increase our understanding of the complex biology of this disease. Methods: Tumor samples were obtained from untreated HNSCC patients undergoing surgery. Patients were classified according to pathologic lymph node status (positive or negative) or tumor recurrence (recurrent or non-recurrent tumor) after treatment (surgery with neck dissection followed by radiotherapy). Using microarray gene expression, we screened tumor samples according to modules comprised by genes in the same pathway or functional category. Results: The most frequent alterations were the repression of modules in negative lymph node (N0) and in non-recurrent tumors rather than induction of modules in N+ or in recurrent tumors. N0 tumors showed repression of modules that contain cell survival genes and in non-recurrent tumors cell-cell signaling and extracellular region modules were repressed. Conclusions: The repression of modules that contain cell survival genes in N0 tumors reinforces the important role that apoptosis plays in the regulation of metastasis. In addition, because tumor samples used here were not microdissected, tumor gene expression data are represented together with the stroma, which may reveal signaling between the microenvironment and tumor cells. For instance, in non-recurrent tumors, extracellular region module was repressed, indicating that the stroma and tumor cells may have fewer interactions, which disable metastasis development. Finally, the genes highlighted in our analysis can be implicated in more than one pathway or characteristic, suggesting that therapeutic approaches to prevent tumor progression should target more than one gene or pathway, specially apoptosis and interactions between tumor cells and the stroma.

Generation and characterization of human insulin-releasing cell lines

Background: The in vitro culture of insulinomas provides an attractive tool to study cell proliferation and insulin synthesis and secretion. However, only a few human beta cell lines have been described, with long-term passage resulting in loss of insulin secretion. Therefore, we set out to establish and characterize human insulin-releasing cell lines. Results: We generated ex-vivo primary cultures from two independent human insulinomas and from a human nesidioblastosis, all of which were cultured up to passage number 20. All cell lines secreted human insulin and C-peptide. These cell lines expressed neuroendocrine and islets markers, confirming the expression profile found in the biopsies. Although all beta cell lineages survived an anchorage independent culture, none of them were able to invade an extracellular matrix substrate. Conclusion: We have established three human insulin-releasing cell lines which maintain antigenic characteristics and insulin secretion profiles of the original tumors. These cell lines represent valuable tools for the study of molecular events underlying beta cell function and dysfunction.