The frequency of the other haplotypes (Hap_6, Hap_7, Hap_10, and Hap_11) was moderate, between 5.4% and 8.7% (Table 5). The frequencies of GhExp2 haplotypes differed markedly across species ( Table 6). Haplotype diversity ranged from 0.667 in G. arboreum (7 accessions) selleck chemical to 0.767 in G. hirsutum (74 accessions). The difference was particularly evident for the haplotypes (Hap_1, Hap_2, and Hap_3) present only in G. arboreum. The most frequently identified haplotypes were confined to G. hirsutum. Six haplotypes were present in < 10% of accessions sampled, six were unique to one species, and six

were exclusive to accessions from single species, indicating that every allele was unique to one species. Thus, interspecific crossing would create novel alleles. G. hirsutum accessions were largely separated into six haplotypes. In comparison with G. arboreum and G. barbadense, more haplotypes and higher diversity were observed in G. hirsutum ( Table 5). The prerequisite for all subsequent analyses in this study was the characterization of population structure using

the software package Structure 2.3.1 [26]. Based on 132 unlinked SSR markers, providing even coverage of the cotton genome, we ran Structure for K (number of GDC-0199 cell line fixed subpopulations or clusters) ranging from 2 to 10. The model with K = 7 clusters showed higher log likelihood (ln Pr(X|K) = − 9805.2) than for other integer values of K, and the likelihoods for K = 8 and 9 decreased markedly, compared with that for K = 7. Because the likelihood peaked at K = 7 in the range of two to ten subpopulations, the most likely number of putative ancestral populations (K) was identified as seven. RVX-208 The number of these 92 cotton accessions assigned to each of the seven inferred clusters ranged from 2 to 39. Kullback–Leibler distances of pairwise subpopulations were significant (P < 0.001) and ranged from 0.1251 to 1.4933 (average 0.6856), suggesting a genuine difference among these clusters and supporting the existence of genetic structure ( Fig. 5, Table 7). The G. arboreum

accessions (except for CRZM) and G. barbadense accessions (except for Giza 80) lines were very distinct from all other lines from G. hirsutum because of the genetic isolation that occurred during their development, and were accordingly (6 G. arboreum and 10 G. barbadense accessions) assigned to A (Arboreum) and B (Barbadense) groups, respectively. Giza80 (introduced from Egypt) and CRZM (with fiber length approximating that of tetraploid cotton) were assigned to a seventh M (Mixed) group. Four clusters from G. hirsutum are referred to hereafter as H1 (8 accessions), H2 (19 accessions), H3 (39 accessions) and H4 (8 accessions) subpopulations. These results are consistent with their genomic origins and evolutionary histories.

This work was supported by the Nucleus of Support to Research and Teaching (NAPED), Faculty of Medicine of Jundiaí, and Research Foundation of the State of São Paulo (FAPESP) (grant number: 2008/55521-7). We thank Mrs. Kerstin Markendorf and Mrs. Nea Torres for English revision of the manuscript. Funding: Governmental grant – The State of São Paulo Research Foundation (FAPESP). Competing interests: None

declared. Ethical approval: This study was approved by the Brazilian College of Animal Experimentation (COBEA) and the Institutional Ethics Committee (10/56788). “
“Saliva has an important role in the protection of the oral tissues and the gastroenteric epithelium, and its absence or alteration can cause many significant problems.1 and 2 Amongst its functions, it facilitates the formation of the bolus, swallowing, phonation and the retention 17-AAG of complete dentures; it

also prevents the damage of soft and hard tissues in the oral cavity by mechanical, chemical or biological noxious stimuli.3 Cisplatin in vivo Saliva contains a variety of electrolytes, peptides, glycoprotein, enzymes, immunoglobulin A,4 growing factors, amines5 and leucocytes,2 and amongst its properties, the buffering effect prevents the demineralisation of the teeth.6 Xerostomia means the subjective sensation of dry mouth; it can be evaluated by individual questionnaires, salivary tests and sialometry, which can confirm the presence of lower salivary flow or altered composition, associated or not with the complaint.7 and 8 It can be caused by systemic diseases (e.g., Sjögren syndrome, diabetes and hypothyroidism),9, 10, 11 and 12 emotional stress, abuse of drugs, human immunodeficiency virus (HIV) infection,13 radiation of the head and neck14 or chronic

use of several medications.15 and 16 The reduction of the salivary flow causes many consequences that affect oral and the general health. The most common complaints are discomfort and burning sensation,17 caused by the Fludarabine chemical structure dryness of the oral mucosa and the difficulty of feeding.18 There are also taste loss, bad breath19 and difficulties in swallowing, talking20 and using prostheses.21Opportunist oral infections, such as candidiasis, or dental problems (caries and periodontitis) may occur.22 Orofacial pain occurs at least once in a lifetime for 70% of the people.23 Amongst the causes, dental pain and temporomandibular disorders (TMDs) are the most frequent.24 and 25 Dental pain is often inflammatory and causes intense central sensitisation.26 TMD includes articular and muscular diseases involving the masticatory system.24Neuropathic pain syndromes are also common in the face, and they may be associated with TMD or odontalgia.

One may assume that the Talazoparib mouse vertical clines separating the water masses and nutrient pools make a major contribution as sources of ‘foreign’ water upwelled to the surface layer. Nevertheless, the exact contribution of the different layers in the water column to the transport of nutrients is hard to detect from direct measurements, but this is possible from model- based estimates. In topographically asymmetrical regions, like the Gulf of Finland, one may assume a different contribution at different shores under upwelling-favourable wind conditions with the same magnitude. The objective of this paper was to study and estimate the nutrient transport from different depths to the surface

layer during coastal upwelling events along opposite coasts of an elongated basin such as the Gulf of Finland. For this purpose we used a series of numerical experiments in which the initial tracer (simulating short-term nutrient behaviour) source is put at different depths for each experiment. The results of the experiments are summarized as time and depth maps of cumulative nutrient mass transported to the upper layer from a layer of unit

thickness at a certain depth in the Gulf of Finland. We applied the Princeton Ocean Model (POM), which is a primitive equation, find more σ-coordinate, free surface, hydrostatic model with a 2.5 moment turbulence closure sub-model embedded ( Mellor & Yamada 1982, Blumberg & Mellor 1983, 1987). The model domain included the whole Baltic Sea closed at the Danish Straits. The digital topography of the sea bottom was taken from Seifert et al. (2001). We used a horizontal resolution of 0.5 nautical miles within the Gulf of Finland and 2 nautical miles in the rest of the Baltic Sea ( Figure 1); in the vertical direction we used 41 equally spaced σ-layers, which in the Gulf gave the lowest vertical resolution of Δz = 3 m at a Alanine-glyoxylate transaminase point of depth 120 m. A model resolution of 0.5 nautical miles allows good resolution of mesoscale phenomena,

including upwelling filaments/squirts ( Zhurbas et al. 2008) controlled by the internal baroclinic Rossby radius, which in the Gulf of Finland varies within 2–5 km ( Alenius et al. 2003). We chose the simulation period from 20 to 29 July 1999, which represents an intensive upwelling event along the northern coast and is well covered by high-resolution observations including CTD, biological and chemical measurements along with the SST from satellite imagery (Vahtera et al. 2005). Atmospheric forcing (wind stress and heat flux components) for the simulation period was calculated from a meteorological data set of the Swedish Meteorological and Hydrological Institute (SMHI). The 10 m wind components were calculated from the SMHI geostrophic wind vectors by turning the latter 15° counterclockwise and multiplying by a factor of 0.6. The components and other meteorological parameters obtained were afterwards interpolated in space from the 1° resolution to our 2 and 0.5 nautical mile model grid.

The replication levels Sotrastaurin were selected following a review of historical data, indicating the scope to increase resolving power. Different outlier, transformation and linearity methods were evaluated using recent PM data, as follows. Dixon’s test (Böhrer, 2008) and boxplot quartiles (Tukey, 1977) were used to identify potential outliers. The assumed distributions for the Ames test, MLA and IVMNT were Poisson (Roller and Aufderheide, 2008), log-normal

(Murphy et al., 1988) and binomial (Hayashi et al., 1994), respectively. A generalised linear model was used, to accommodate response variables that have other than a normal distribution. This required logarithmic transformations for the Ames test and MLA, and a probit

transformation for the IVMNT (Armitage and Berry, 1987a). Two ways to identify the linear part of the dose response (Bernstein et al., 1982) were evaluated. The first was to use a linear regression model and partition the residual error into pure error and lack-of-fit (Draper and Smith, 1998). The linear portion of the response was identified by systematically excluding doses from the model until the lack-of-fit test was non-significant. The second method fitted a generalised linear model with linear and quadratic terms for dose (Roller and Aufderheide, 2008). If the quadratic term was significant (p < 0.01), the same model was fitted again with the highest dose excluded, continuing until the quadratic term was not significant or less than three doses remained. Dose responses Talazoparib manufacturer were compared and significance tested using analysis of covariance (ANCOVA) for slopes and pooled data, and t-tests for individual concentrations ( Werley et al., 2008). Following ANCOVA (Pocock et al., 2002) or t-tests, resolving power was calculated using standard formulae ( Armitage and Berry, 1987b). Dixon’s test occasionally identified

single values as potential outliers, when the other replicate values were close together. The quartiles method required more than 6 replicates per dose. Furthermore, removing potential outliers did not improve the resolving power of the Methocarbamol assays, except for TA1537 data in the Ames test. With sufficient replication (>6 replicates per dose), the quartiles method was used to improve the resolving power of TA1537 data, by identifying potential outliers for removal, before further statistical analysis. Outlier analysis was not applied in the other assays. Examination of the residuals confirmed that the number of revertants in an Ames test were Poisson distributed (Roller and Aufderheide, 2008), the proportion of micronucleated binucleate cells (MnBn) in the IVMNT were binomially distributed and mutation frequency (MF) in the MLA was normally distributed on the log scale, consistent with the assumed distributions of these transformation methods.

Transducer holders or probe fixation devices for conventional TCD Apoptosis inhibitor monitoring have been introduced into clinical settings. Previously, for the examination of neonates, a hood-like probe fixation device via the transfontanellar window has been investigated [14]. Trials in adult patients have focused not only on the middle cerebral artery (MCA) via the TWs [7] and [15], but also in the vertebrobasilar arteries via the FW for high intensity transient signals (HITS)

monitoring [16]. More recently, a commercially available head-frame (Marc 600, Spencer Technologies) for monitoring via the TWs has been used for detection of recanalization in the MCA during tissue plasminogen activator studies [6]. Furthermore, a long-term ambulatory TCD monitoring AZD1208 mouse device placed on a spectacle frame has been introduced for HITS detection in the MCAs via the TWs [9]. A modified head-frame combining two Spencer Technologies’ head-frames for both the TWs and FW has been tried for vasoreactivity tests [8]. Our TCDS transducer fixation device, the Sonopod, is able to monitor not only

via the TWs, but also via the FW (Fig. 2). A further important advantage is long-duration stable TCDS monitoring that implies accurate quantitative measurements in the major cerebral arteries and brain tissue. Proposed criteria for probe-holding systems include ease of application, stability during patient movement, low-cost, compatibility with multiple probes, comfort and durability [7]. The durability of a prototype of this transducer, the Sonopod, has been proven, with no problems in our four-year experience. However, it is still so heavy that long-time TW monitoring

in the sitting position will probably result in discomfort caused by fatigue of the neck muscles. This problem will be improved in changing materials from heavy stainless steel to light weight aluminum, titanium, or similar. L-gulonolactone oxidase For FW monitoring, the Sonopod is unable to be applied in a supine position, therefore patients should be instructed to lie down semi-laterally. It is necessary to tighten four screws during setup of the Sonopod and this may prove a slight time-consuming drawback while searching for appropriate location of vessels or anatomical places. In our experience however, we were usually ready for monitoring in around 5–10 min. Improvements of the Sonopod have been planned for the SONOS 5500 S3 transducer (Philips), compatibility with multiple probes and costs of marketing the products should be confirmed in the near future. Since the clinical introduction of transcranial ultrasound perfusion imaging of brain tissue, depth dependant ultrasound attenuation has been the most challenging problem for qualitative and quantitative evaluation [17] and [18]. In our study, significant depth dependant PI attenuation on the TICs was observed in both image types, particularly in the contralateral hemisphere.

Because of this, we also undertook analyses where models were compared at relevant clinical intervention threshold ( Fig. 1). Kanis et al. [23] also criticized comparison of “home NVP-LDE225 manufacturer grown” models with the FRAX® tool using the population

from which the “home grown” model was derived. This is a relevant concern as the best model to fit a dataset will invariably be a model developed from that particular dataset even if the diagnostic performance may not at all translate to other populations. In our study, we compared the performance of FRAX® and other models to that of age alone. This is a simple epidemiological tabulation of fracture incidence as a function of age and does not constitute a bespoke model to fit the data. Furthermore, OST, ORAI, OSIRIS and SCORE are already well validated simpler tools derived from other cohorts [15], [18], [19] and [20]. Another limitation accurately identified by Kanis et al. [23] is the comparison between predicted and observed outcomes. Since we do not have 10 years of follow-up we look at the observed fractures and compared

it with the FRAX® probability of being in risk of fracture. Moreover, we took time-to-event into account by estimating the Harrell’s C which did not influence the results. Same results were seen in the GLOW study [36]; these results also showed that AUC values and Harrell’s C values were similar for major osteoporotic fractures. Finally, FRAX® adjusts for risk of death while the other tools do not. Our findings, Rucaparib research buy however, were robust to competing-risks regression with both incident fractures and death as failure as alternative to Kaplan–Meier analysis. In the analyses with each tool dividing participants into those with high versus low risk of fracture we chose to use the cut-off suggested by the developers from validation studies of tools in Caucasian populations. Different cut-offs have been also recommended even among Caucasian populations from studies validating the tools but there was no clear agreement regarding cut-off values for the different tools [41], [42], Sirolimus in vitro [43] and [44]. One study by Rud et al.

[41] investigated the performance of SCORE, OST and ORAI in a Danish population. The sensitivity of SCORE, OST and ORAI was 69%, 90% and 50%, respectively, when applied as described by the developers. The authors also tried different cut-offs with higher sensitivities, but since the study only included peri- and early postmenopausal women (mean age 50.5 years) and there are no other studies on Danish women confirming the suggested cut-off from Rud et al. [41] we found it most reasonable to use the cut-offs from the developer of the tools in this study. The aim of the different tools, i.e. FRAX® with OST, ORAI, OSIRIS or SCORE, differs. FRAX® predicts the probability of fractures while ORAI, OSIRIS, OST and SCORE are designed to predict low BMD.

(3)). Vd for [3H]colchicine was corrected for non-specific binding by subtracting the Vd for [14C]sucrose, as non-permeant extracellular marker. equation(3) Vd(μl)=dpmincells/[dpminaliquotofuptakemedium/volumeofaliquot(μl)] All dpm values were corrected for background dpm. Vd was then normalised for the cell protein concentration (mg) to give units of μl/mg protein. BYL719 purchase P.1 PBECs or RBE4 cells were grown in 96-well plates at 1.0×104 cells/200 μl growth medium per well. Cells were washed three times with PBS, and cell membranes disrupted by freezing at −80 °C for 20 min. Alkaline phosphatase (ALP)

assay was performed using Sigma Fast p-nitrophenyl phosphate tablets. Two hundred microlitres of pNPP was added to each well and incubated in the dark for 60 min at room temperature. Absorbance at 405 nm was read in a Labsystems Multiskan Ascent plate reader and protein concentration determined using the BCA protein assay kit. ALP activity levels are reported as absorbance per milligram protein.

Two vials each of PBECs from two different batches (batch 1 and 2) of PBEC were used to obtain primary and P.1 PBECs. RNA was extracted from three primary and P.1 cultures from each vial (24 samples) using the EZ1 RNA cell mini E7080 price kit. Twelve microlitres of RNA (∼300–450 ng) from each sample was reverse transcribed using the QuantiTect reverse transcription kit to generate cDNA. RNA and cDNA were analysed (260/280 ratio: RNA∼2.0; cDNA∼1.8) and quantified using the NanoDrop® ND-1000 spectrophotometer (NanoDrop Technologies, USA). Primers and TaqMan® probes for porcine glyceraldehyde-3-phosphate DOCK10 dehydrogenase (GAPDH, reference gene), occludin, claudin-5 and BCRP were designed using Primer Express® software from Applied Biosystems. The total gene specificity of the nucleotide sequences chosen for the primers and probes was confirmed using nucleotide-nucleotide BLAST searches (GenBank database sequences) (National Center for Biotechnology Information 2006). The nucleotide sequences

of the oligonucleotide hybridisation primers and probes for TaqMan analysis are shown in Table 3. TaqMan real-time polymerase chain reaction (PCR) assays were performed using the AB 7900HT Real-Time PCR System with a 384-well configuration. The TaqMan probes used in this study were dual-labelled with a 5′ end 6-FAM (a high-energy ‘Reporter’ dye) and a 3′ end TAMRA (a low-energy ‘Quencher’ dye). The optimum primer and probe concentrations were determined by running replicate standard samples at different primer and probe concentrations. The PCR reaction mixture contained 2 μl of cDNA sample (10 ng) and 2×TaqMan Universal PCR Master Mix with 900 nM primers and 250 nM TaqMan probe in a total volume of 20 μl.

1 M sodium phosphate pH 8 under gentle mixing. Poly-prep columns (Bio-Rad) were packed with the mixture and washed extensively with PBS pH 7.4. Elution buffer was 0.1 M Sodium Citrate pH 2.5 and neutralization buffer was 1 M Tris–HCl pH 9. Electrophoresis was performed on 4–15% SDS-PAGE and Coomassie brilliant blue was learn more used for staining. MW standards were HyperPage Prestained Protein Marker (#BIO-33066, Bioline). Multiple immunizations were carried out with 100–125 μg β-galactosidase (β-gal) or human progranulin (hPG) or ovalbumin (OVA) or hen egg lysozyme (HEL) as described (Osborn et al., 2013). For flow cytometry cell suspensions were washed and adjusted

to 5 × 105 cells/100 μl in PBS with 1% BSA and 0.1% Azide. Identification of B-cell subsets was with anti-rat IgM FITC-labeled mAb (MARM 4, Jackson Immunoresearch Laboratories) in combination with anti-B cell CD45R (B220)-PE-conjugated mAb (His 24, BD biosciences). FACS CantoII flow cytometer and FlowJo software (Becton Dickinson, Pont de Claix, France) were used

for the analysis (Menoret et al., 2010). To provide an extensive human VH repertoire, 2 BACs with 22 VH genes were chosen and modified to facilitate homologous integration (Hu BAC6-3 and Hu BAC3, Fig. 1 top) (Osborn et al., 2013). The assembly of a BAC construct accommodating human VH6-1, all D and JH segments linked to part of the rat C region, termed HC14 Hu-Rat Annabel, has been described see more recently (Osborn et al., 2013). Various difficulties were encountered in the assembly of the rat C-region; first, cloning into PIK-5 a BAC restricted the region selected to below 250 kb, second, to allow class-switch recombination several highly repetitive and unstable switch sequences had to be retained, and finally, it was unclear how much of the 3′RR was needed for appropriate expression. In Fig. 1 the assembled BACs are illustrated with VH-region BACs at the top, followed by C-region BACs with overlapping region in the middle part, and the rat CH region in natural configuration shown

at the bottom. For the construction of HC10 Hu-Rat Emma, a region immediately 3′ of rat JH4, including rat Eμ, Sμ, Cμ, Cδ and all sequences up to Sγ2c was added to the human VH6-1, D and JH sequence. A further addition of rat Sγ2b, Cγ2b, Cε, Cα and the 3′RR in natural configuration was made (Bruggemann et al., 1986). In this 202 kb construct Cγ2b is in the position where normally Cγ2c is located. In HC13 Hu-Rat Belinda, the authentic region from rat Eμ to Cγ2c was added, which is followed by Sγ2b, Cγ2b and the 3′RR hs1,2 (Pettersson et al., 1990) on a 160 kb fragment. For HC17 Hu-Rat Frieda, the Hu-Rat Belinda BAC was modified by adding Cα with ~ 30 kb 3′ region after Cγ2b, which generated a 202 kb BAC. In HC10, HC13 and HC17 the rat Cγ2b CH1 exon was exchanged for human γ1 CH1. Purified BAC clones with the same human VH region but different rat C-regions were microinjected into fertilized oocytes.

A total of 12 replicates were performed for each treatment. The results

were expressed as mean and standard error (SEM). Data were checked for normality by the Shapiro–Wilk test, and for homoscedasticity by Levene’s test using the Statview 5.0 (SAS Institute Inc. Cary, NY, United States). The values expressed in percentages were Arcsine transformed. The effect of each step of the procedure (fresh, dilution, glycerol addition at 5 °C or post-thawing) on subjective sperm motility was evaluated by variance analysis—ANOVA—for repeated measures. Comparisons among different treatments (freezing curves, straw sizes, and thawing rates) on the semen parameters were made Nintedanib datasheet by ANOVA, followed by the selleck chemicals Student Newman Keul’s t test. The same effects on sperm kinetic rating were evaluated by the nonparametric Mann–Whitney test. Differences were considered significant when P < 0.05. A total of 15 attempts for semen collection were conducted in 8 animals. From those ejaculates, only 12 samples were used in the experiment due to adequate sperm motility, concentration and volume. Regarding ejaculates used, two were collected from each of four males, and the other four males ejaculated only once. The 12 ejaculates used were white and watery, with an average volume of 6.8 ± 1.3 mL. The other semen characteristics are expressed in Table 1. The evaluation

of semen at each step of the freezing–thawing procedure is reported in Table 2. The addition of the extenders induced no decline (P > 0.05) in sperm motility or kinetic rating in any group. However, the addition of glycerol at 5 °C

and also the freezing–thawing process significantly (P < 0.05) reduced the values for sperm motility and kinetic rating for all samples, but no difference was evidenced among treatments (P > 0.05). After thawing, no differences (P > 0.05) for sperm characteristics were verified between freezing curves when similar variables (straw size and thawing rate) were considered ( Table 2 and Table 3). In general, values for sperm characteristics found after thawing at 37 °C were better preserved than at 70 °C (P < 0.05), Unoprostone both in the use of 0.25 mL or 0.50 mL straws ( Table 2 and Table 3). The evaluation of the kinematic parameters of sperm motility generated by CASA (Table 4) confirmed that no differences were verified either between the different freezing curves (P > 0.05) or between the straw sizes (P > 0.05). Similarly, sperm quality was better preserved in the use of thawing at 37 °C (P < 0.05). Semen cryopreservation is an instrument indispensable to the establishment of animal sperm banks [23]. Using the current methods for freezing boar semen, a substantial sperm number—usually more than 50%—do not survive the freezing–thawing procedure [13].

The increased side scatter of this

“swollen” cell population indicates that they are also in the apoptotic state. The pro-apoptotic effect of long-term exposure (19 h in the medium used for cell growth) to 0.1-10 μM curcumin in the main population of cells (depicted in red in Fig. 6a) was further investigated by flow cytometry (Fig. 7). Quadrant regions (Fig. 7a) were set to segregate cells into four different populations: 7-AAD negative/Annexin-V negative cells were considered as non-apoptotic, non-necrotic (viable), 7-AAD negative/Annexin-V positive cells as early apoptotic, 7-AAD positive/Annexin-V positive cells as late apoptotic, and 7-AAD positive/Annexin-V negative cells as post-late apoptotic/necrotic. As expected, 4 hours incubation with 20 μM staurosporine led to a significant increase of the percentage www.selleckchem.com/products/BKM-120.html of cells in the early and late apoptosis, paralleled by a respective significant decrease of the percentage of viable (non apoptotic, non-necrotic) cells (data not shown). Exposure to 10 μM curcumin significantly increased the percentage of cells in the early apoptosis state (Fig. ABT-737 mouse 7e). The percentage of late apoptotic cells was significantly increased

after treatment with both 5.0 and 10 μM curcumin (Fig. 7c). Accordingly, after incubation with 5.0 and 10 μM curcumin, the number of viable (non-apoptotic, non-necrotic) cells was significantly decreased (Fig. 7d), whereas the percentage of necrotic cells was not significantly affected (Fig. 7b). To verify if the effects induced by long-term exposure to curcumin in HEK293 Phoenix cells are restricted to this particular cell line, flow cytometry was used to investigate the possible pro-apoptotic Immune system effect of long-term exposure (22 h in the medium used for cell growth) on human colorectal adenocarcinoma HT-29 cells

to 5.0–50 μM curcumin. Exposure to 50 μM curcumin significantly increased the percentage of 7-AAD positive/Annexin-V positive cells (Fig. 8b), clearly indicating a pro-apoptotic effect. Accordingly, a significant increase in the side scatter signal was observed (Fig. 9a). Surprisingly, curcumin-induced cell death in these cells was paralleled by a significant increase in the volume of necrotic (Fig. 9b) and late apoptotic (Fig. 9c) cells. To gain further insights about the mechanisms of the curcumin-induced cell volume increase, the cell cycle distribution of HT-29 cells after exposure to curcumin was assessed. Isolated nuclei were stained with DAPI and analyzed by flow cytometry. Long-term exposure (22 h in the medium used for cell growth) to 0.5–20 μM curcumin significantly increased the percentage of cells in G1-phase and decreased the percentage of cells in S-phase (Fig. 10a and b), thereby suggesting a cell cycle arrest in G1-phase. Curcumin is an active compound of turmeric for which anticancer, antioxidative and antiinflammatory properties have been described.