Dynamic contrast-enhanced magnetic resonance imaging for monitoring neovascularization during bone regeneration—a randomized in vivo study in rabbits

Clinical Oral Investigations - Micro-computed tomography (μ-CT) and histology, the current gold standard methods for assessing the formation of new bone and blood vessels, are invasive and/or...     

Microsatellite loci-based distribution of Trypanosoma cruzi genotypes from Chilean chronic Chagas disease patients and Triatoma infestans is concordant with a specific host-parasite association hypothesis

The objective of this study was to investigate if there is specific host-parasite association in Chilean populations of Trypanosoma cruzi. For this purpose, two groups of parasites were analyzed, one from chronic chagasic patients, and the other from Triatoma infestans triatomines in three regions of the country. The first group consisted of four types of samples: parasites from peripheral blood of non-cardiopathic T. cruzi infected patients (NB); parasites from their corresponding xenodiagnosis (NX); parasites from peripheral blood of T. cruzi infected cardiopathic patients (CB) and parasites from their xenodiagnostics (CX). The T. infestans sample in turn was from three regions: III, V and M (Metropolitan). The genetic differentiation by the Fisher exact method, the lineage distribution of the samples, the molecular phylogeny and the frequency of multiclonality were analysed. The results show that not only are the groups of T. cruzi clones from Chagas disease patients and vectors genetically differentiated, but also all the sub-groups (NB, NX, CB and CX) from the III, V and M regions. The analysis of lineage distribution was concordant with the above results, because significant differences among the percentages of TcI, TcIII and hybrids (TcV or TcVI) were observed. The phylogenetic reconstruction with these Chilean T. cruzi samples was coherent with the above results because the four chagasic samples clustered together in a node with high bootstrap support, whereas the three triatomine samples (III, V and M) were located apart from that node. The topology of the tree including published T. cruzi clones and isolates was concordant with the known topology, which confirmed that the results presented here are correct and are not biased by experimental error. Taken together the results presented here are concordant with a specific host-parasite association between some Chilean T. cruzi populations.     

Increased nuclear ?-catenin expression in oral potentially malignant lesions: A marker of epithelial dysplasia

Background

Deregulation of ?-catenin is associated with malignant transformation; however, its relationship with potentially malignant and malignant oral processes is not fully understood. The aim of this study was to determine and compare the nuclear ?-catenin expression in oral dysplasia and oral squamous cell carcinoma (OSCC).

Material and Methods

Cross sectional study. Immunodetection of ?-catenin was performed on 72 samples, with the following distribution: 21 mild dysplasia, 12 moderate dysplasia, severe dysplasia 3, 36 OSCC including 19 well differentiated, 15 moderately differentiated and 2 poorly differentiated. Through microscopic observation the number of positive cells per 1000 epithelial cells was counted. For the statistical analysis, the Kruskal Wallis test was used.

Results

Nuclear expression of ?-catenin was observed in all samples with severe and moderate dysplasia, with a median of 267.5, in comparison to mild dysplasia whose median was 103.75. Only 10 samples (27.7%) with OSCC showed nuclear expression, with statistically significant differences between groups (p < 0.05).

Conclusions

Our results are consistent with most of the reports which show increased presence of ?-catenin in severe and moderate dysplasia compared to mild dysplasia; however the expression of nuclear ?-catenin decreased after starting the invasive neoplastic process. This suggests a role for this protein in the progression of dysplasia and early malignant transformation to OSCC. Immunodetection of ?-catenin could be a possible immune marker in the detection of oral dysplasia. Key words:Oral squamous cell carcinoma (OSCC), ?-catenin, oral dysplasia.     

TLR2 engagement on CD4+ T cells enhances effector functions and protective responses to Mycobacterium tuberculosis

We have previously demonstrated that mycobacterial lipoproteins engage TLR2 on human CD4⁺ T cells and upregulate TCR‐triggered IFN‐γ secretion and cell proliferation in vitro. Here we examined the role of CD4⁺ T‐cell‐expressed TLR2 in Mycobacterium tuberculosis (MTB) Ag‐specific T‐cell priming and in protection against MTB infection in vivo. Like their human counterparts, mouse CD4⁺ T cells express TLR2 and respond to TLR2 costimulation in vitro. This Th1‐like response was observed in the context of both polyclonal and Ag‐specific TCR stimulation. To evaluate the role of T‐cell TLR2 in priming of CD4⁺ T cells in vivo, naive MTB Ag85B‐specific TCR transgenic CD4⁺ T cells (P25 TCR‐Tg) were adoptively transferred into Tlr2^?/? recipient C57BL/6 mice that were then immunized with Ag85B and with or without TLR2 ligand Pam₃Cys‐SKKKK. TLR2 engagement during priming resulted in increased numbers of IFN‐γ‐secreting P25 TCR‐Tg T cells 1 week after immunization. P25 TCR‐Tg T cells stimulated in vitro via TCR and TLR2 conferred more protection than T cells stimulated via TCR alone when adoptively transferred before MTB infection. Our findings indicate that TLR2 engagement on CD4⁺ T cells increases MTB Ag‐specific responses and may contribute to protection against MTB infection.     

Response of Escherichia coli growth rate to osmotic shock

It has long been proposed that turgor pressure plays an essential role during bacterial growth by driving mechanical expansion of the cell wall. This hypothesis is based on analogy to plant cells, for which this mechanism has been established, and on experiments in which the growth rate of bacterial cultures was observed to decrease as the osmolarity of the growth medium was increased. To distinguish the effect of turgor pressure from pressure-independent effects that osmolarity might have on cell growth, we monitored the elongation of single Escherichia coli cells while rapidly changing the osmolarity of their media. By plasmolyzing cells, we found that cell-wall elastic strain did not scale with growth rate, suggesting that pressure does not drive cell-wall expansion. Furthermore, in response to hyper- and hypoosmotic shock, E. coli cells resumed their preshock growth rate and relaxed to their steady-state rate after several minutes, demonstrating that osmolarity modulates growth rate slowly, independently of pressure. Oscillatory hyperosmotic shock revealed that although plasmolysis slowed cell elongation, the cells nevertheless “stored” growth such that once turgor was reestablished the cells elongated to the length that they would have attained had they never been plasmolyzed. Finally, MreB dynamics were unaffected by osmotic shock. These results reveal the simple nature of E. coli cell-wall expansion: that the rate of expansion is determined by the rate of peptidoglycan insertion and insertion is not directly dependent on turgor pressure, but that pressure does play a basic role whereby it enables full extension of recently inserted peptidoglycan.Cell growth is the result of a complex system of biochemical processes and mechanical forces. For bacterial, plant, and fungal cells, growth requires both the synthesis of cytoplasmic components and the expansion of the cell wall, a stiff polymeric network that encloses these cells. It is well established that plant cells use turgor pressure, the outward normal force exerted by the cytoplasm on the cell wall, to drive mechanical expansion of the cell wall during growth (1, 2). In contrast, our understanding of the physical mechanisms of cell-wall expansion in bacteria is limited. Furthermore, the bacterial cell wall is distinct from its eukaryotic counterparts in both ultrastructure and chemical composition. In particular, the peptidoglycan cell wall of Gram-negative bacteria is extremely thin, comprising perhaps a molecular monolayer (3). This raises the question of whether these organisms require turgor pressure for cell-wall expansion, or whether they use a different strategy than organisms with thicker walls.Turgor pressure is established within cells according to the Morse equation, P = RT(C_in ? C_out), where C_in is the osmolarity of the cytoplasm, C_out is the osmolarity of the extracellular medium, R is the gas constant, and T is the temperature. In the Gram-negative bacterium Escherichia coli, P has been estimated to be 1–3 atm (4, 5). A primary role of the cell wall is to bear this load by balancing it with mechanical stress, thereby preventing cell lysis. In 1924, Walter proposed a theory of bacterial growth based on the premise that mechanical stress, in turn, is responsible for stretching the cell wall during growth (6). In support of this theory, he and others showed that the growth rate of a number of bacterial species, including E. coli, decreases as the osmolarity of their growth medium is increased (6–9) (Fig. 1A). This result would be predicted by the Morse equation if growth rate, e˙, scaled with pressure: e˙∼P∼−Cout. The decrease in growth rate did not depend on the chemical used to modulate the osmolarity, which demonstrated that this effect was not due to specific, toxic reactions. More recently, several theoretical studies have offered plausible molecular mechanisms by which turgor pressure could drive cell-wall expansion. These theories range from ones in which the cell wall is irreversibly stretched by turgor pressure when peptidoglycan cross-links are hydrolyzed (10, 11) to ones in which the rate of peptidoglycan biosynthesis is directly dependent on turgor pressure (12, 13). Two of these theories explicitly predict the scaling between cellular growth rate and pressure (12, 13), providing possible explanations of the classic experiments (6–9).Open in a separate windowFig. 1.E. coli cells maintain their elongation rate after hyperosmotic shock. (A) The population-averaged steady-state elongation rate as a function of the concentration of sorbitol in the growth medium, C_out (red circles). Also shown are the population-averaged elongation rates during phase III of recovery from a 400 mM hyperosmotic shock (blue triangles) and immediately after a 400 mM hypoosmotic shock (green squares). Each data point is averaged over 20–100 cells. Error bars indicate ±1 SE. (Inset) Definition of elongation rate. (B) E. coli stained with fluorescent WGA, imaged with phase and epifluorescence microscopy. (Lower) Schematic defining the length and width of a rod-shaped cell. (C) Longitudinal strain, ε_l, and radial strain, ε_w, as a function of medium osmolarity. Error bars indicate ±1 SE. (Inset) Tracked outlines of the wall of four cells before (red) and after (blue) plasmolysis. (D) (Left) Initial images of a single cell: phase, epifluorescence, and overlay. In the overlay, the epifluorescence kymograph is false-colored green and the inverse of the phase kymograph is false-colored red. (Right) Kymographs of this cell elongating and dividing during a 400 mM hyperosmotic shock. The kymographs consist of a montage of a one-pixel-wide region around the long axis of the cell, indicated by the dashed line. The white arrow indicates the time of the shock. The red arrow indicates the period of plasmolysis during which the cytoplasm is shorter than the cell wall. The black arrow indicates the formation of a septum during cell division. (E) The concentration of sorbitol in the growth medium versus time during a hyperosmotic shock. (F) The length of the cell walls of representative cells during the same shock. The background colors indicate the four phases of response. (G) The population-averaged elongation rate of both the cytoplasm and the cell wall during the same shock (n = 42 cells). The data were smoothed with a moving-average filter with a 2-min window for illustrative purposes. The blue dotted lines indicate the steady-state elongation rates in LB (upper line) and LB+400 mM sorbitol (lower line). The confidence intervals indicate ±1 SE. The cell wall could not be tracked indefinitely owing to dilution of the cell-wall stain. (Lower) Key describing the four phases of response to hyperosmotic shock.However, bacterial cells possess several mechanisms for regulating their cytoplasmic osmolarity in response to changes in their external osmotic environment (14). Specifically, E. coli imports and synthesizes compatible solutes, and imports ions, in response to high external osmolarities (15). For example, the concentration of potassium ions in the cytoplasm scales as the external osmolality (16). Therefore, it is unclear whether raising medium osmolarity actually causes a decrease in turgor pressure over long time scales. The inverse correlation between growth rate and medium osmolarity could result from another osmotic effect such as altered water potential within the cell, which could affect, for example, protein folding (17) or signaling (18). We sought to distinguish between these possibilities by measuring the elastic strain within the cell wall as a function of medium osmolarity and by determining the time scale over which osmotic shock (acute changes in medium osmolarity) modulates growth rate and cell-wall synthesis. If growth rate scales with turgor pressure, then (i) growth rate should also scale with cell-wall elastic strain, and therefore elastic strain should decrease with increasing medium osmolarity, and (ii) growth rate, and perhaps the rate of cell-wall synthesis, should rapidly change upon osmotic shock. However, if medium osmolarity modulates growth rate independently of pressure, these processes may adapt more slowly to changes in osmolarity.We found that elastic strain decreases only moderately with increasing medium osmolarity. By measuring the growth-rate response of E. coli across time scales that spanned four orders of magnitude we concluded that osmotic shock had little effect on growth rate, except in the case of plasmolysis (when P ≤ 0, causing the cytoplasm to separate from the cell wall). The growth rate of E. coli adapted slowly to changes in medium osmolarity, over the course of tens of minutes. Furthermore, when turgor pressure was restored after slight plasmolysis, E. coli cells quickly elongated to the length that they would have attained had they never been plasmolyzed. From this result, we inferred that peptidoglycan synthesis is insensitive to changes in turgor pressure. In support of this hypothesis, we found that the speed of MreB, a protein whose motion is dependent on peptidoglycan synthesis (19–21), is largely unaffected by osmotic shock. Therefore, our results demonstrate that cell-wall biosynthesis is the rate-limiting factor in cell-wall expansion and that turgor pressure is not required for cell-wall biosynthesis, but that pressure does play a simple role whereby it stretches recently assembled, unextended peptidoglycan.     

Cyclooxygenase‐2 in epilepsy

Epilepsy is one of the more prevalent neurologic disorders in the world, affecting approximately 50 million people of different ages and backgrounds. Epileptic seizures propagating through both lobes of the forebrain can have permanent debilitating effects on a patient's cognitive and somatosensory brain functions. Epilepsy, defined by the sporadic occurrence of spontaneous recurrent seizures (SRS), is often accompanied by inflammation of the brain. Pronounced increases in the expression of key inflammatory mediators (e.g., interleukin ‐1β [IL‐1β], tumor necrosis factor alpha [TNFα], cyclooxygenase‐2 [COX‐2], and C‐X‐C motif chemokine 10 [CXCL10]) after seizures may cause secondary damage in the brain and increase the likelihood of repetitive seizures. The COX‐2 enzyme is induced rapidly during seizures. The increased level of COX‐2 in specific areas of the epileptic brain can help to identify regions of seizure‐induced brain inflammation. A good deal of effort has been expended to determine whether COX‐2 inhibition might be neuroprotective and represent an adjunct therapeutic strategy along with antiepileptic drugs used to treat epilepsy. However, the effectiveness of COX‐2 inhibitors on epilepsy animal models appears to depend on the timing of administration. With all of the effort placed on making use of COX‐2 inhibitors as therapeutic agents for the treatment of epilepsy, inflammation, and neurodegenerative diseases there has yet to be a selective and potent COX‐2 inhibitor that has shown a clear therapeutic outcome with acceptable side effects.