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B: The host species affects the microbial community in the goat rumen. Lett Appl Microbiol 2008,46(1):132–135.PubMed 13. Lozupone C, Knight R: UniFrac: a new phylogenetic method for comparing microbial communities. Appl Environ Microbiol 2005,71(12):8228–8235.PubMedCrossRef 14. Cho SJ, Cho KM, Shin EC, Lim WJ, Hong SY, Choi BR, Kang JM, Lee SM, Kim YH, Kim H, et al.: 16S rDNA analysis of bacterial diversity in three fractions of cow rumen. J Microbiol Biotechnol 2006,16(1):92–101. 15. Yang SL, Ma SC, Chen J, Mao HM, He YD, Xi DM, Yang LY, He TB, Deng WD: Bacterial diversity in the rumen of Gayals ( Bos frontalis ), Swamp buffaloes ( Bubalus bubalis ) and Holstein cow as revealed by cloned

16S rRNA gene sequences. Mol Biol Rep 2010,37(4):2063–2073.PubMedCrossRef 16. Cunha IS, Barreto CC, Costa OYA, Bomfim selleckchem MA, Castro AP, Kruger RH, Quirino BF: Bacteria and archaea community structure in the rumen microbiome of goats ( Capra hircus ) from the semiarid region of Brazil. Anaerobe 2011,17(3):118–124.PubMedCrossRef 17. Li MJ, Zhou M, LEE011 supplier Adamowicz E, Basarab JA, Guan LL: Characterization of bovine ruminal epithelial bacterial communities using 16S rRNA sequencing, PCR-DGGE, and qRT-PCR analysis. Vet Microbiol 2012,155(1):72–80.PubMedCrossRef 18. Pope PB, Mackenzie AK, Gregor I, Smith W, Sundset MA, McHardy AC, Morrison M, Eijsink VG: Metagenomics of the Svalbard reindeer rumen microbiome

reveals abundance of polysaccharide utilization loci. PLoS One 2012,7(6):e38571.PubMedCrossRef 19. Kim M, Morrison M, Yu Z: Status of the phylogenetic diversity census of ruminal microbiomes. FEMS Microbiol Ecol 2011,76(1):49–63.PubMedCrossRef 20. Bae HD, McAllister TA, Yanke J, Cheng KJ, Muir AD: Effects of condensed tannins on endoglucanase activity and filter paper digestion by Fibrobacter succinogenes S85. Appl Environ Microbiol 1993,59(7):2132–2138.PubMed 21. McSweeney Ergoloid CS, Palmer B, McNeill DM, Krause DO: Microbial interactions with tannins: nutritional consequences for ruminants. Anim Feed Sci Technol 2001,91(1–2):83–93.CrossRef 22. Jones GA, McAllister TA, Muir AD, Cheng KJ: Effects of sainfoin ( Onobrychis viciifolia Scop.) condensed tannins on growth and proteolysis by four strains of ruminal bacteria. Appl Environ Microbiol 1994,60(4):1374–1378.PubMed 23. Min BR, Attwood GT, McNabb WC, Molan AL, Barry TN: The effect of condensed tannins from Lotus corniculatus on the proteolytic activities and growth of rumen bacteria. Anim Feed Sci Technol 2005,121(1–2):45–58.CrossRef 24. Koike S, Yoshitani S, Kobayashi Y, Tanaka K: Phylogenetic analysis of fiber-associated rumen bacterial community and PCR detection of uncultured bacteria. FEMS Microbiol Lett 2003,229(1):23–30.PubMedCrossRef 25.

The FRET-based assay was performed in a final volume of 100 μl buffer F containing 10 μM SrtBΔN26 and 20 μM fluorogenic peptide in clear-bottomed, black polystyrene 384-well plates (Nunc). Plates were incubated for 48 hours at 37°C, during which fluorescence (excitation = 340 nm, emission = 490 nm) was measured

using a SpectraMax M3 plate reader (Molecular Devices). Five mM 2-(trimethylamonium)ethylmethanethiosulfonate (MTSET, Affymetrix) was added to the reaction as indicated. Each experiment was performed in triplicate with a minimum BMS-777607 datasheet of three biological replicates, and the results are presented as the means and the standard error of the data obtained. The two-tailed Student’s T-test was used to analyze the data. MALDI analysis of FRET reaction samples was performed by the Protein and Nucleic Acid Chemistry Facility (University of Cambridge) to determine exact cleavage site within each peptide. Kinetic measurements Kinetic data for SrtBΔN26 were obtained by incubating varying concentrations of peptide (8, Paclitaxel 10, 20, 40, 80, 160, 200 and 240 μM) with 10 μM SrtBΔN26. All reactions were performed as described above, with fluorescence monitored every ten minutes over a 13 hour period. To correlate fluorescence signal,

expressed as arbitrary relative fluorescence units (RFU), with the concentration of product formed, standard curves of the fluorophore Edans were collected. The linear segment of the fluorophore standard curve generated a conversion ratio of 703.9 RFU/ μM Edans. Initial velocities (V) were determined from the progress curves and plotted against substrate concentration [S]. The data were fitted to a modified version of the Michaelis-Menten equation incorporating substrate inhibition using SciPy 0.11.0 in Python these 2.7.3, where V max is the maximal enzymatic velocity, K m is the Michaelis constant,

and K i is the inhibitor dissociation constant for unproductive substrate binding. All data points were collected in triplicate, and the overall assay was run in duplicate. Identification of SrtB inhibitors The proprietary LeadBuilder virtual screening method (Domainex, Ltd) was used to interrogate a database (PROTOCATS) of 80,000 potential compounds which had been pre-selected as protease inhibitors. The virtual screening protocol used pharmacophoric and docking filters derived from analysis of the BaSrtB crystal structure (with which the C. difficile SrtB shows 70% identity and 90% similarity at the active site). Sixty-two compounds identified in this screen as potential SrtB inhibitors were obtained from Enamine, ChemBridge, and Key Organics, and solubilized in DMSO. Selected compounds and MTSET were incubated with 10 μM SrtBΔN26 at a range of concentrations in the FRET-based assay conditions described above, so that final DMSO concentrations were ≤ 3.75%, a concentration shown to have no significant effect on control fluorescence (data not shown).

09 mM CaCl2, 0.081 mM MgSO4∙7H2O, 3 μM H3BO3, 2.1 μM MnCl2∙4H2O, 1 μM Na2EDTA∙2H2O, 0.6 μM FeCl3∙6H2O, 0.03 μM

NaMoO4∙2H2O , 0.025 μM ZnCl2, , 0.01 Cell Cycle inhibitor μM CoCl2∙6H2O, 0.07 nM CuCl2∙2H2O in double deionized water. Cyanidioschyzon merolae 10D was acquired from the Microbial Culture Collection of the National Institute for Environmental Studies (Tsukuba, Japan). Cyanidioschyzon was propagated using a Cyanidium medium [37] composed of 9.85 mM (NH4)2SO4, 2.06 mM K2HPO4, 1.01 mM MgSO4∙7H2O, 0.67 mM CaCl2, 13 μM Na2EDTA, 3.0 μM H3BO3, 2.2 μM FeCl3 .6H2O, 1.2 μM MnCl2∙4H2O, 0.32 μM CuSO4∙5H2O, 0.22 μM ZnSO4∙7H2O, 0.12 μM Na2MoO4 and 0.05 μM CoCl2 .6H2O in double deionized water. The medium was adjusted to pH 3.5 with HCl. Synechococcus leopoliensis (UTEX 2434), a cyanobacteria species, was obtained from the Culture Collection of Algae, University of Texas at Austin. Cells were grown in medium using 50X Cyanobacteria BG-11 Freshwater Solution (Sigma Aldrich, catalogue # C3061) [68] that was diluted to 1X in double deionized water to final concentrations of: 17.65 mM NaNO3, 0.3 mM MgSO4∙7H2O, 0.24 mM CaCl2∙2H2O, 0.18 mM K2HPO4, 46.0 μM H3BO3, 31 μM citric acid, 21 μM ferric ammonium citrate, 9.1 μM MnCl2∙4H2O, 2.8 μM MnNa2EDTA, 1.7 μM NaMoO4∙2H2O, 0.77 μM ZnSO4∙7H2O, 0.32 μM CuSO4∙5H2O, 0.17 μM Co(NO3)2∙6H2O.

All chemicals were obtained from Sigma-Aldrich (Oakville, Canada) or Fisher Scientific (Ottawa, Canada). CB-839 price Synechococcus and Chlamydomonas were grown in 1.0 L of their respective media in 1.5 L Pyrex oxyclozanide glass cylindrical bioreactors under fluorescent lighting of 150 μE /m2/s at 28°C. Cells were kept suspended by aerating at a 1 L per min flow rate. Cyanidioschyzon was grown similarly except that the temperature was maintained at 45°C [53]. Cell treatments The effect of sulfur nutrition on heavy metal resistance and biotransformation was investigated by exposing each species to supplemental sulfur treatments. Supplemental sulfur was provided in the form of sulfate, sulfite or cysteine. Sulfate and sulfite were added as K2SO4 and K2SO3,

respectively, at ten-fold the amount of sulfur equivalents in the original media and the L-cysteine treatments were supplemented to twice the original amount of sulfur equivalents in the media. Experimental treatments included 1) no additional sulfur containing compounds, 2) additional sulfur containing compound, and 3) additional sulfur containing compound both before (pre-fed) and during the treatment period (plus). All treatments were performed in 100 mL of medium in 150 mL glass plant tissue culture vessels with translucent magenta B-caps obtained from Sigma-Aldrich (Oakville, Canada). Continuous fluorescent illumination was at 150 μE / m2/ s with 120 rpm rotary shaking. Culturing temperatures were 27°C for Synechococcus and Chlamydomonas, and 45°C for Cyanidioschyzon. The initial cell density for all cultures was O.D.665 = 0.1. These were grown to an O.D.665 = 1.

The all too slow evolution of eukaryotes to encode a new recognition became no match for the evolutionary potential of the prokaryotes to rapidly encode escape from that recognition. The only solution was to somatically generate a random recognitive repertoire that divided the antigenic universe into combinatorials of determinants referred selleck chemicals llc to as epitopes. This somatically generated repertoire characterizes what is referred to as the adaptive immune system. While this made it very difficult for an infectious agent to escape recognition, a random somatically generated repertoire posed two new problems that demanded

concurrent solutions. First, the repertoire had to be sorted into those specificities which if expressed would debilitate the host [i.e. anti-self (S)] and those specificities which if not expressed would result in the debilitation of the host by infection [i.e. anti-nonself (NS)]. The anti-S had to be purged leaving as a residue the anti-NS to protect the host. This process is metaphorically referred to as ‘the S-NS discrimination’. Second, the sorted anti-NS repertoire had to be selectively coupled to largely

the same panoply of effector functions that were used by the recognitive repertoire GDC-0973 clinical trial of the innate system. These two problems need comment. It is the fact that the output is just as biodestructive Phospholipase D1 and ridding for the host as it is for the pathogen that mandates a mechanism to sort the repertoire. The innate repertoire is sorted by germline selection over evolutionary time with the result

that it distinguishes the self-of-the-species from the pathogenic universe. On the one hand, any mutation in the innate repertoire that resulted in recognition of a self-component of the species would be lethal in the offspring of a mating between that mutant and an individual expressing that self-component. On the other hand, any mutation that resulted in the recognition of an antigenic determinant common to many pathogens would be distinctly advantageous. As a consequence, the innate repertoire is blind to the self-of-the-species and recognizes a limited number of epitopes shared by many pathogens. This can be easily seen as hosts without adaptive immune systems permit grafting without rejection between individuals of a species and in many cases between species. In the presence of the adaptive system, grafts between individuals of a randomly mating species are rejected. The adaptive system is individual-specific; the innate system is species-specific. Specificity of the epitope-recognitive receptors (paratopes) is evolutionarily driven by the necessity to make a S-NS discrimination. For the innate system, its specificity must be sufficient to distinguish the pathogen from the self-of-the-species.

“
“CD4+ T cell anergy reflects the inability of CD4+ T cells to respond functionally to antigenic stimulation through proliferation or IL-2 secretion. Histone deacetylase (HDAC) inhibitors have been shown to induce anergy in antigen-activated CD4+ T cells. However, questions remain if HDAC inhibitors mediate anergy through direct action upon activated CD4+ T cells or through this website the generation and/or enhancement of regulatory T (Treg) cells. To assess if HDAC inhibitor n-butyrate induces anergy independent of the generation or expansion of FoxP3+ Treg cells in vitro, we examine n-butyrate-treated murine CD4+ T cells for anergy induction and FoxP3+ Treg activity. Whereas n-butyrate

decreases CD4+ T cell proliferation and IL-2 secretion, n-butyrate did not augment FoxP3 protein production or confer a suppressive phenotype upon CD4+ T cells. Collectively, these data suggest that HDAC inhibitors can facilitate CD4+ T cell functional unresponsiveness directly and independently of Treg cell involvement. Selectively inducing antigen-specific anergy in activated CD4+ T cells through short-term exposure to HDAC inhibitors may have important ramifications for treatment of autoimmune diseases. Traditional long-term immunosuppressive strategies often induce detrimental bystander effects. For example, although glucocorticoid treatments can control autoimmunity, eventual side effects from long-term Selleck BMS 354825 exposure include

immature thymic T cell apoptosis, osteoporosis, cataracts, hypertension and truncal obesity [1]. In contrast, short-term treatments with an HDAC inhibitor could deactivate problematic effector T

cells without introducing issues identified with long-term immunosuppression. Understanding the therapeutic potential of HDAC inhibitors to combat autoimmunity requires a better understanding of the mechanism behind HDAC inhibitor–induced CD4+ T cell anergy. Delineating this mechanism is complicated by the complexity of the response generated by these inhibitors. HDACs are a class of enzymes that remove acetyl groups from lysine residues on histone and non-histone proteins [2]. In the case of histone proteins, HDAC activity promotes a greater attraction between the now positively charged histones and negatively Etofibrate charged chromatin and causes transcriptional regulation through chromatin condensation [3]. HDAC inhibitors bind the catalytic domains of HDACs, thereby blocking their enzymatic activity. Thus, one of the chief effects of HDAC inhibition is genome-wide histone hyperacetylation, granting an ‘open’ chromatin transcriptional profile and increased gene expression. There are six structurally different classes of HDAC inhibitors: hydroxamic acids, cyclic peptides, benzamides, epoxyketones, short-chain fatty acids and assorted hybrid molecules. These different classes of HDAC inhibitors induce functionally similar but non-identical gene expression profiles [4–6].

Moreover, we continue to add to the evidence that modulatory cytokines, such as IL-10, are co-regulated

with macrophage-activating cytokines such as IFN-γ and TNF-α. Further studies are under way to directly measure these T cell subpopulations at the lesion site and in other clinical forms of leishmaniasis. Moreover, the use of this information in attempts to define the antigens responsible for the preferential use of the subpopulations defined here could aid in the selection of immunodominant antigens used by the human immune response against Leishmania. We thank the funding agencies: NIH-TMRC, NIH-R03AI066253-02, FAPEMIG-Infra, CNPq-INCT-DT and CNPq for fellowships. None. “
“Citation Pictilisib concentration Thaxton JE, Sharma S. Interleukin-10: a multi-faceted agent of pregnancy. Am J Reprod Immunol 2010 It is widely accepted that

pregnancy constitutes a unique developmental event. Unprecedented intrauterine actions of angiogenesis, immunity, and neuroendocrine regulation are juxtaposed to mechanisms of senescence that enable fetal growth and protection. The suppressive and regulatory factors that facilitate healthy pregnancy are under investigation. In non-pregnant see more systems of infection and inflammation, the cytokine interleukin-10 (IL-10) has been widely investigated because of its potential as a key immunosuppressant in response to a multitude of inflammatory events. In the context of pregnancy, IL-10 levels increase markedly in women during early pregnancy and remain elevated well into the third trimester immediately prior to onset of labor. The role of second IL-10 during pregnancy as a suppressor of active maternal immunity to allow acceptance of the fetal allograft has been a point of study. Moreover, secretion of IL-10 by a diverse set of maternal and fetal cells has proven to aid in the orchestration of normal processes of pregnancy. Interestingly, some of the more profound findings regarding the actions of IL-10 during pregnancy

have manifested from research that focuses on aberrant pregnancy outcomes as a result of inflammation, hormonal imbalances, or gene–environment interactions. This review focuses on the role of IL-10 as a facilitator of successful pregnancy both as an immune suppressive agent and a mediator of cross talk between the placenta and the decidua. Importantly, we discuss investigations on adverse pregnancy conditions to further elucidate the multifarious role of IL-10 at the maternal–fetal interface. Interleukin-10 was first reported by Mosmann et al. under the name of cytokine synthesis inhibitory factor (CSIF) as a protein with the ability to inhibit the activity of inflammatory T-helper 1 (Th1)-type cells.

*Remarks: The Thailand peritonitis study group included (by alphabet list) SOHARA EISEI, SUSA KOICHIRO, RAI TATEMITSU, ZENIYA MOKO, MORI YUTARO, SASAKI SEI, Small Molecule Compound Library UCHIDA

SHINICHI Department of Nephrology, Tokyo Medical and Dental University Introduction: Pseudohypoaldosteronism type II (PHAII) is a hereditary disease characterized by salt-sensitive hypertension, hyperkalemia and metabolic acidosis, and genes encoding the WNK1 and WNK4 kinases were known to be responsible. Recently, two genes (KLHL3 and Cullin3) were newly identified as responsible for PHAII. KLHL was identified as substrate adaptors in the Cullin3-based ubiquitin E3 ligase. We have reported that WNK4 is the substrate of KLHL3-Cullin3 E3 ligase-mediated ubiquitination. However, WNK1 and NCC were also reported to be a substrate of KLHL3-Cullin3 E3 ligase by other groups. Therefore, it remains unclear which molecule is true substrate(s) of KLHL3-Cullin3 E3 ligase, in other words, what is the true pathogenesis of PHAII caused Y-27632 price by KLHL3 mutation. Methods: To investigate the pathogenesis of PHAII by KLHL3 mutation, we generated and analyzed KLHL3R528H/+ knock-in mice. Results: Under high-salt diet, the systolic blood pressure oxyclozanide of KLHL3R528H/+ mice was higher

than that of wild-type mice. Metabolic acidosis and hyperkalemia were also observed in KLHL3R528H/+ mice. Moreover, the phosphorylation of OSR1, SPAK and NCC were also increased in KLHL3R528H/+ mice kidney. These data clearly indicated that the KLHL3R528H/+ knock-in mice are ideal mouse model of PHAII. Interestingly, both of WNK1 and WNK4 protein expression was significantly increased in KLHL3R528H/+ mouse kidney, indicating that these

increased WNK kinases caused the activation of WNK-OSR1/SPAK-NCC phosphorylation cascade in KLHL3R528H/+ knock-in mice. To examine whether mutant KLHL3 R528H can interact with WNK kinases, we measured the binding of TAMRA-labeled WNK1 and WNK4 peptide to the whole KLHL3, using fluorescence correlation spectroscopy. The diffusion time of TAMRA-labeled WNK1 and WNK4 peptide was not affected by the addition of mutant KLHL3 R528H protein, indicating that neither WNK1 nor WNK4 bind to mutant KLHL3 R528H. Conclusion: Thus, we found that increased protein expression levels of WNK1 and WNK4 kinases, due to impaired KLHL3-Cullin3 mediated ubiquitination, cause PHAII by KLHL3 R528H mutant. Our findings also implicated that both WNK1 and WNK4 are physiologically regulated by KLHL3-Cullin3 mediated ubiquitination.

For example, a subset of leucocytes found in fat-associated lymphoid clusters of the mesentery regulate B1 lymphocyte renewal in the peritoneal cavity, promote B cell proliferation in Peyer’s patches and IgA and mucus production in the small intestine during N. brasiliensis Selleck CB-839 infections (23). These cells are

dependent on the common cytokine γ chain (γc) and are of lymphoid morphology, but lack typical T, B or NK cell markers (Lin−). These cells are FcεRI−, c-kit+, Sca-1+, Thy1+, IL-7R+, T1/ST2+, IL-2R+, IL-25R+ and in response to IL-33, express large amounts of IL-5 and IL-13 during N. brasiliensis infections. Although from a different lymphoid tissue, this subset appears similar to an IL-25-dependent non-B non-T lymph node cell that facilitates early expulsion of N. brasiliensis from the gut (24). Studies with N. brasiliensis have also contributed to the renewal of interest in basophils as a bridge between innate and adaptive immunity (25,26). Graham Le Gros (Malaghan Institute, Wellington, New Zealand) began working with N. brasiliensis in the USA and Europe more than 30 years ago and has continued to do so on his return to the Antipodes. Le Gros joined a team led by Bill Paul, which used N. brasiliensis to understand how Type 2 cytokine responses are regulated (27) and this has been an ongoing theme of interest.

In this early study, IL-4 production was sourced to a leucocyte lacking T, B and NK cell markers, which was subsequently learn more shown

to have morphological characteristics of the basophil (28). These leucocytes are FcεRI+, CD49bbright, c-kit−, Gr1− and can be found in the liver, spleen and lungs 9–10 days after infection of mice with N. brasiliensis (29). T cells provide Methane monooxygenase the IL-3 necessary for production of basophils under these conditions (30). Studies with N. brasiliensis helped to demonstrate that in vivo production of the Type 2 cytokines IL-4, IL-5 and IL-9 and also IL-10, is dependent on IL-4 secreted by T lymphocytes (31). N. brasiliensis was also used to determine that in an infectious disease setting, dendritic cells prime for production of IL-4, IL-5 and eosinophilia (32). Basophils responding via IgE and the IgεRI may also provide an IL-4-rich environment for the differentiation of T cells into phenotypes secreting Type 2 cytokines (33). However, the differentiation of IL-4-producing CD4+ T cells can occur normally in the absence of IL-4 and the associated STAT6 signalling pathway in N. brasiliensis infections. This should now direct inquiry in the Nippostrongulus model towards T cell costimulatory molecules such as OX40, ICOS, TIM-1 and Notch Delta/Jagged (34). N. brasiliensis has also been used by the Le Gros group to dissect allergic asthma. N. brasiliensis is a potent inducer of IgE, and the model has been used to explore the role of CD23 (FcεRII), the low affinity receptor for this immunoglobulin isotype (35,36), and to define the development of IgE memory B cells (37).

The E-cadherin surface expression was further reduced after treatment of the siRNA-transfected cells with elastase (Fig. 5F). As described above, elastase had no effect on MiaPaCa-2 nor Su8686 monolayers, compatible with the fact that these cells do not express E-cadherin, or only very little (Table 1). An important question is whether or not neutrophil elastase has an impact on the functional activity of pancreatic cancer cells. To this end, the effect of elastase on the migration of pancreatic cancer cells was tested in a “wound healing” assay. Following treatment with elastase, migration of T3M4 cells was markedly enhanced (on average 22.7%) compared

with that of the untreated cells (Fig. 6A–C). In line with these data, Roxadustat cost silencing of E-cadherin expression also enhanced the migration of the transfected T3M4 cells compared with that of mock-transfected cells (by 29.6% for siRNA1, and 31.7% for siRNA2). To assess the invasive capacity of pancreatic cancer cells, a standardized Matrigel™ invasion assay was used. T3M4 cells were incubated with 1 μg/mL neutrophil

elastase and migration was followed up for 24 h. Compared with untreated cells, about threefold more cells invaded the membrane (elastase-treated cells: 212 ± 70 invading cells/0.3 cm2 versus untreated cells: 70 ± 11 https://www.selleckchem.com/products/CAL-101.html respectively; mean ± SD of n = 4; the mean values differed from each other with p = 0.007, according to t-test) (Fig. 6D). In parallel, nuclear accumulation of β-catenin, a transcription cofactor regulated by E-cadherin activity and associated with for tumor cell migration and invasion, was detected by western blotting (Fig. 6E). Our data so far suggested that neutrophil-derived elastase causes a dyshesion of tumor cells by degrading E-cadherin. To assess a correlation between neutrophils and E-cadherin expression in vivo, biopsies of patients with PDAC (n = 112; Supporting Information Fig. 2) were examined with regard to neutrophil infiltrates and E-cadherin expression. Neutrophils were identified by elastase expression and by staining with naphthol-ASD-chloracetate (NASDCL). Cells were counted within the tumor and in the desmoplastic

Benzatropine tumor stroma as well. Of note, the distribution of the neutrophils was not homogenous throughout the biopsy. There were areas with high density (more than 100 cells per high-power field) and those with none at all (Fig. 7). Therefore, neutrophils in ten high-power fields were counted, according to the mean values, three groups were formed: 0 and 0.5 neutrophils were considered as “negative,” 0.6–10 cells as “intermediate” and more than ten cells as “severe” (Supporting Information Table 2). Staining with NASDCL or immunostaining for elastase gave essentially similar results. The majority of cases presented a PMN infiltrate (n = 108), 51 with severe (on average 60 cells) and in 57 with an intermediate (on average 6.5 cells) infiltration of PMN.