The comparatively high food level is maintained during CHIR-99021 in vivo the summer. When the temperature reaches its maximum, the food concentration assumes a value of about 150 mgC m−3 by the end

of August (see Figure 6a). The annual cycle of the generation time as a result of the above-mentioned parameters is shown in Figure 6b. The simulated mean total development time of T. longicornis during the seasons in the southern Baltic Sea is in the 120–48 day range during the spring bloom, i.e. at 4–10°C with an excess of food, ca 40 days in summer and from 140 to 250 days in winter conditions. The influence of temperature and food availability on the duration of developmental stages in T. longicornis is much the same as in the case of Acartia spp. from the southern Baltic Sea ( Dzierzbicka-Głowacka et al. 2009a), except during the spring bloom, when the simulated generation time of T. longicornis is shorter than TD of Acartia spp., ca 12 days on average. The best conditions for the development of T. longicornis are in the spring/summer and summer/autumn,

but for Acartia spp. definitely in the summer. The www.selleckchem.com/products/sotrastaurin-aeb071.html calculations also suggest that three complete generations of T. longicornis from the Gdańsk Deep can develop during a single year in the upper layer. Simulated generation times are affected mostly by temperature and to a lesser degree by food availability. But in the spring bloom time, the effect of food concentration on the first generation is more evident. The complete mean development time

of T. longicornis in the southern Baltic Sea at temperatures below 10°C is longer, and in the 7–12°C temperature range is unchanged, but at higher temperatures it is shorter than the value found by Fransz et al. (1989) for three generations. The respective differences in TD between these results are ca 5 days, 0.5 day and 10 days. They are probably caused by the food concentration, which depends on the composition used in the numerical calculations. T. longicornis is a eurythermic copepod species that Non-specific serine/threonine protein kinase has a wide geographic range – from temperate to arctic waters. In the North Sea and adjacent waters, i.e. the Baltic Sea and the English Channel, the copepod T. longicornis is one of the more abundant zooplankton species. Knowledge of their life parameters (e.g. development time, growth rate and egg production) provides fundamental information on energy and matter transformation in pelagic food webs. These organisms play a dominant role in marine food webs and biogeochemical cycles of organic matter. The model parameters obtained here from a synthesis of corrected laboratory culture data and simulations can be used to investigate the effects of climate change on the life cycle development of T. longicornis and factors that have consequences for its role in the food web dynamics.

A total of 78 lymph nodes were observed by plain EUS and CH-EUS. The size (short and long axes), shape (round or oval), and edge characteristics (sharp or fuzzy) of each lymph node were assessed by plain EUS. After changing to CH-EUS, the vascularity of the lymph node was observed. The lymph nodes were categorized into 2 vascular enhancement

patterns on CH-EUS: heterogeneous and homogeneous enhancement. How the benign and malignant lesions differed in terms of features on plain EUS and vascular enhancement patterns on CH-EUS was examined. The utility of plain EUS and CH-EUS in differentiating find more malignant from benign lesions was also evaluated. The final diagnoses were made by histological and/or cytological analyses of the samples obtained by EUS-FNA. Of the 20 malignant lymph nodes, 19 (95%) exhibited heterogeneous enhancement. Of the 58 benign lymph nodes, 56 (97%) exhibited homogeneous enhancement. Malignant and benign lymph nodes differed significantly in vascular enhancement patterns (P<0.001). The sensitivity, specificity, and accuracy with which CH-EUS differentiated malignant from benign lesions were 95%, 97%, and 97%, respectively. By receiver operating

characteristics (ROC) analysis, short axes >11mm and long axes >19mm provided the best sensitivity and specificity for predictive malignancy. The sensitivity, specificity, and accuracy with which short axes over 11mm predicted click here most malignancy were 80%, 79%, and 79%, respectively. Those values of long axes over 19mm were 65%, 62%, and 63%, respectively. Those values of round shape were 60%, 74%, and 71%, respectively. Those values of sharp edge were 90%, 28%, and 44%, respectively. The diagnostic accuracy of vascular assessment by CH-EUS was significantly higher than any other parameters of plain EUS. CH-EUS depicts the microvasculature of intra-abdominal lymphadenopathy very clearly and plays an important role in characterization of such lesions. It may be useful for determining the target lymph node of EUS-FNA. “
“Intra-arterial

chemotherapy is an effective modality to treat unresectable hepatic metastasis from colorectal primaries if systemic chemotherapy has failed. To evaluate efficacy and safety of a new technique, EUS-guided fine-needle intra-arterial injection of chemotherapy. Between 2007 and 2012, a total of 25 patients with colorectal cancer and liver metastasis were randomized to receive intra-arterial chemotherapy with EUS-FNI (12[48%]) and conventional technique (13 [52%]). Exclusion criteria: Lesions up to 5cm of length, maximum 3 metastasis and localized in segments I, VI, VII and VIII. Chemotherapy regimen and dose were similar in both groups and consisted of 5-Fluoracil or 5-Fluorodeoxymidina. EUS-FNI was performed through the stomach or duodenum using a 22-G needle and searching the intra-hepatic artery by using color and power doppler.

During almost 20 years of IO PAS measurements PLX3397 with the towed profiling system, two CTD probes were used: Idronaut 316 and Seabird 49. The accuracies of the former were C = 0.003 mS cm−1, T = 0.003° C, P = 0.05% of the full scale range, those of the latter were C = 0.0003 mS cm−1, T = 0.002°C, P = 0.1% of the full scale range. The temperature and conductivity sensors of each CTD system were calibrated annualy (post-cruise) by the manufacturers. The profiling system consisted of a CTD probe suspended

in a steel frame towed on a cable behind the vessel. The suspension system ensured the horizontal position of the probe during profiling, the steel frame protected it from mechanical damage, while a metal

chain fixed below the frame reduced the risk of contact with the sea bed. To obtain a profile, the CTD system was lowered or raised between the surface and bottom by releasing or hauling in the towing cable. At a Ku-0059436 concentration constant ship speed of ca 4 knots, a spatial resolution of ca 200–500 m was obtained for a basin with a typical depth of 60–120 m. With the CTD probe operating at a frequency of 10 Hz, the vertical resolution of the towed measurements was ca 3 cm (30 measurements per metre). Along the main axis of the section (Figure 2), three separate regions were reselected with depths exceeding 70 m: the Bornholm Deep, the Słupsk Furrow and the Gdańsk Deep. Temperature and salinity data from 30 982 vertical profiles were collected during the 53 cruises. For a better presentation of the results, the data were vertically averaged into 10 m vertical layers. To study the seasonal variability of temperature and salinity, Fourier analysis was applied to time series of the averaged data (Emery & Thomson 2001). The first three Fourier components were used to represent the

annual cycle. To create de-seasoned data, the Fourier fit was subtracted from the temperature time series. The temperature variability, over time ZD1839 scales different from the seasonal one, was analysed using de-seasoned temperature data (Figure 3). Temperature trends were calculated using de-seasoned time series for layers characterized by a strong seasonal temperature cycle due to atmosphere-ocean interactions. For deeper layers linear regression was employed on the original temperature time series (Emery & Thomson 2001). Fourier analysis was preferred over a number of other available tools, as it faithfully reflects the changes in temperature (Figure 3) while maintaining a high coefficient of determination (> 0.9). In addition, this method faithfully reflects the temperature changes during the sesonal cycle. For the purposes of this analysis, the water column was divided into 3 layers: surface, transition (thermocline, halocline) and bottom. The surface layer, exposed to atmospheric factors, exhibited the greatest variability in temperature (Figure 4).

At low pulsing frequency, there are few such frequencies. At high pulsing frequency, there are many more such slowly relaxing terms present. It is these slowly relaxing terms that give rise to the characteristic increase in signal observed in a CPMG experiment. Palbociclib research buy An expression for the effective transverse relaxation rate of the ground state ensemble is sought: equation(1) R2,eff=-1TrellnIG(Trel)IG(0)where Trel   is the total time of the concatenated CPMG elements and IG   specifies the signal intensity from the observed ground state at the specified times. In order to calculate the relevant signal intensities a

kinetic model for the exchange process and types of magnetisation present need to be specified. The simplest and most widely encountered kinetic scheme is the two-site case for in-phase magnetisation. Here, a ground state and an excited state undergo the conformational rearrangement G⇄kEGkGEE. In this scheme, the exchange rate kEX   = kEG   + kGE   and the fractional populations of the excited (PE  ) and ground (PG  ) states are given by kGE  /kEX   and kEG  /kEX   respectively. The CPMG experiment consists of a number of free precession elements interspersed with 180° pulses. To evaluate MDV3100 purchase their combined effect, how magnetisation evolves in the absence of pulses needs first

to be calculated. This is accomplished most conveniently using the shift basis (I  + = Ix   + iIy   and I  −   = Ix   − iIy  ) using a modified Bloch–McConnell equation [33]: equation(2) ddtIG+IE+=R+IG+IE+where E   and G   denote the magnetisation on the excited and ground states, respectively. The evolution matrix is: equation(3) R+=-kGE-R2GkEGkGE-kEG-R2E-iΔωR  2G   and R  2E   specify the intrinsic C-X-C chemokine receptor type 7 (CXCR-7) relaxation of the ground and excited states respectively, and Δω   is the chemical shift difference between the ground and excited states in rad s−1. The solution for Eq. (2) is: equation(4) I(t)=eR+tI(0)=OI(0)I(t)=eR+tI(0)=OI(0)where I  (0) are I  (t  ) specify the magnetisation on the ground and excited states at time zero and t   respectively. Initially the system

is in equilibrium, and so I(0)†=(PG,PE)I(0)†=(PG,PE) where †† indicates a transpose. The derivation of I(t) first requires the well known matrix O (Eq. (17)) that determines how magnetisation evolves during free precession [2]. In the shift basis, the effect of a 180° on-resonance ideal pulse switches magnetisation on I+ terms to I−, leading magnetisation to evolve according to the complex conjugate of R+ (Eq. (3)), (R+)*. Following a 180° pulse therefore, magnetisation will evolve according to the matrix O*. By applying Eq. (4) iteratively, taking the complex conjugate where appropriate, an expression that represents the entire CPMG experiment can be built. This, when used with Eq. (1) enables us to derive an expression for R2,eff. The matrix M that represents the CPMG experiment will enable us to evaluate I(t) = MI(0).

, 2011). Thus, it is not surprising that a monotonic dose response was not found, particularly for endpoints related to the development of the embryos. Carls et al. (1999) stated, but did not demonstrate, that all measured aqueous PAH were freely dissolved and none were associated with oil droplets, which leads to the assumption that all the individual PAH in exposure water were bioconcentrated independent

of each other and other chemicals in the effluent. However, the analytical methods used by Carls et al. (1999) and in related studies, did not distinguish between freely dissolved and particulate oil (see Page et al., 2012). These assumptions are critical to the selection of TPAH as a dose metric and render the findings questionable because the effluents from the different oil-on-gravel loadings this website contained different initial concentrations and compositions of the measured selleck products alkanes and PAH that changed during both of the 16-day experiments. The presence of low solubility alkanes and high molecular weight alkyl PAH in the effluents from the oiled gravel column studies

(EVOSTC, 2009, Brannon et al., 2012 and Page et al., 2012; Supplementary data) is indicative of the presence of a non-dissolved or micro droplet oil phase in the column effluents that probably contained all or most of the higher molecular weight PAH (Faksness et al., 2004 and Redman et al., 2012). Therefore, the uptake and toxicity of PAH in the Carls et al. (1999) study likely cannot be attributed solely to a freely dissolved fraction of the oil PAH, and the likely presence of oil droplets represents an additional confounding factor that would affect the accumulated dose and that was not reported or discussed as part of the toxicology evaluation. Thus, total aqueous PAH, as measured, represented both freely dissolved and unknown amounts of PAH associated with oil droplets. TPAH concentrations in exposure water declined rapidly and PAH composition changed continuously over the course of the 16-day exposures in all doses of LWO and MWO (Carls et al., 1997, Carls et al., 1999 and EVOSTC, 2009; Supplementary data). The rapid decline of TPAH concentration in the LWO and MWO effluents during the 16-day

exposures (Fig. 1) was largely the result of losses C-X-C chemokine receptor type 7 (CXCR-7) of lower molecular weight PAH, particularly naphthalene and alkyl-naphthalenes (Table 1). The relative concentrations of different individual PAH and PAH congener groups, as a percentage of TPAH concentration (%TPAH), changed in all effluent doses during the 16-day exposures, with percent alkyl-naphthalenes declining and percent alkyl-phenanthrenes, alkyl-dibenzothiophenes, and alkyl-chrysenes increasing in the low, mid, and high doses during the first 4 days of exposure (Table 1) and during the remainder of the two 16-day experiments. Thus, PAH exposure concentration declined and relative compositions were different for each dose during the course of the LWO and MWO experiments (EVOSTC, 2009).

Axitinib acting as a receptor tyrosine kinase inhibitor could interfere with TGFβR and other growth factor receptors signaling involved in fibrogenesis to inhibit the cascade of selleck screening library events leading to fibroblast activation and fibrosis that is triggered by radiation [48]. Alternatively, axitinib may act like sunitinib and inhibit myeloid derived suppressor cells which could be involved

in the inflammatory response caused by radiation [49]. Further studies are warranted to investigate these mechanisms. Overall, our data demonstrate that axitinib is a potent and safe drug to use in conjunction with radiotherapy for lung cancer that could also act as a radioprotector for lung tissue by reducing pneumonitis and fibrosis. This study was supported click here by Pfizer grant IIR # WS832344. We thank Mohit Agarwal for excellent technical assistance. “
“Ovarian cancer is characterized by a multisequential process, which involves multiple gains in cell functions, conferring to the transformed cells the capacity for

increased proliferation and metastasis. These changes are partially mediated by alterations in genetic and protein expression levels, thus allowing for increased cell division, tissue invasion, and cell adhesion as well as colonization in new microenvironments [1]. Among the newest recognized molecular actors involved, the proprotein convertases (PCs) are important in cancer progression through their processing and activation of cancer-associated proteins [2]. Although numerous cancer-associated proteins are likely involved, proprotein processing can still be considered as a limiting step that cancer cells require to gain

their full self-sustaining capabilities [2]. PCs are a family of serine proteases responsible for protein processing within Meloxicam the secretory pathway. Nine family members have been identified in mammalian cells, including furin, PACE4, PC1/3, PC2, PC4, PC5/6, PC7, PCSK9, and substilisin-kexin isoenzyme 1 (SKI-1) [3]. Only the first seven PCs cleave their substrates in the C terminus at the R-X-X-R consensus motif. Among these PCs, furin is ubiquitous, whereas PC1/3 and PC2 are categorized as endocrine specific. Despite the well-accepted identity of PC substrates, which are largely known from their consensus cleavage site in their primary sequences, the cleavage specificity among the enzyme family is still fragmentary and remains difficult to establish because the PC catalytic domain is highly conserved [4]. The role of PCs has been described in breast cancer [5], head and neck cancer [6], and recently prostate cancer [7]. Various PC substrates have recognized roles in cell growth, tumor angiogenesis, invasion, and metastasis, including secreted growth factors, matrix metalloproteinases, and adhesion molecules [8].

Considering the genotypic and biological diversity of T. cruzi strains ( Zingales et al., 2012), we wondered whether the depressive

profile induced by infection with the type I Colombian strain could also be elicited by the distinct type II Y strain. To investigate this question, C3H/He mice were infected with 500-bt of the Y strain and followed daily for parasitemia and mortality. Parasitemia was detected as early as 4 dpi, peaked at 7–8 dpi and was controlled subsequently. No circulating parasite was detected at or after 18 dpi, which CP-868596 solubility dmso marked the resolution of acute infection and the onset of chronic infection ( Fig. 4A). All the infected animals survived (data not shown). Next, we investigated whether the mice appeared to be depressed with the TST. A significant increase in immobility was detected at 7 dpi (p < 0.05; at the peak of parasitemia) and reached a maximum at 14 dpi (p < 0.001). At 28 and 35 dpi, the immobility of infected mice was similar (p > 0.05) to that of sex- and age-matched NI controls ( Fig. 4B). Importantly, the duration of immobility time did not correlate with CNS parasitism: at 7 dpi in the Y strain, when behavioral alterations were first detected, no parasites

were found by IHS in brain sections. A few parasites were detected in the CNS tissue at 14 dpi. CNS parasitism peaked at 28 dpi and declined at 35 dpi ( Fig. 4C and D). CNS parasitism was found mainly in the cerebellum (data not shown) and hippocampus ( Fig. 4D) at 35 dpi when depressive-like SSR128129E behavior was not detected in the Y-strain-infected C3H/He mice ( Fig. 4B). Thus, there was no association between CNS parasitism and depressive-like selleck inhibitor behavior. Furthermore, the type I Colombian T. cruzi strain, but not the type II Y strain, induced chronic depressive-like

behavior in mice. Depressive-like behavior was detected in the Colombian-infected C3H/He mice at 30 dpi and persisted until 90 dpi (Fig. 3A and B). Although a consistent, slight increase in immobility time was detected at 14 dpi, the onset of depressive-like behavior in the Colombian-infected C3H/He mice occurred at 21 dpi, when a significant increase in immobility was detected, and persisted during the chronic phase (Fig. 5A; p < 0.05; H (5) = 29.46). Given the participation of tryptophan-degrading enzymes such as IDO in depression ( Dantzer et al., 2008), we investigated the status of IDO mRNA in the CNS of T. cruzi-infected mice. Compared with NI controls, an increase in IDO mRNA expression was observed in the CNS of T. cruzi-infected mice during the acute (30 dpi) and chronic (90 dpi) phases of infection ( Fig. 5B). To further investigate depressive-like behavior during T. cruzi infection, Colombian-infected C3H/He and C57BL/6 mice were subjected to treatment with the selective serotonin reuptake inhibitor (SSRI) antidepressant fluoxetine (FX) from 14 to 34 dpi and analyzed at 35 dpi ( Fig. 5C). As expected ( D’Souza et al., 2004), FX-treated mice presented body weight loss (p < 0.001; H (3) = 19.

(52): equation(54) R2∞=R2G+PEΔR21+ΔR2/kEXWhich is identical to the relaxation rate expected for the R1ρ experiment in the strong DNA Damage inhibitor field limit (Ref. [44], ω1 ≫ δG, δE, kEX, ΔR2, Eqs. (5), (6), (7) and (8)). Thus the fast pulsing limit of the CPMG experiment, and the strong field limit of the R1ρ experiment

lead to identical relaxation rates, as would be expected. Eq. (54) is similar, but not identical to similarly reported results [2] and [6]. Going further, when kEX ≫ ΔR2 > 0, both the CPMG and R1ρ (in the strong field limit) experiments converge on the intuitive population averaged relaxation rate [42]: equation(55) limPE→0kex>ΔR2R2∞=PGR2G+PER2E Finally, in the limit ΔR2 = 0, the CPMG propagator (Eq. (46)) in the limit of fast pulsing (Eq. (80) using the results in Supplementary Section 1) becomes: equation(56) MΔR2=0∞=e-TrelR2GPGPGPEPEWhich is identical to the evolution matrix for free precession in the limit of fast exchange (Eq. (17) and using the results in Supplementary Section 1). High pulse frequency CPMG experiments only act to make the system appear to be formally in fast exchange limit when ΔR2 = 0. Physical insight into the CPMG experiment is obtained by considering the overall propagator for the CPMG experiment (Eq. (42)), raised to the power Ncyc. equation(57) M=e-2τcpNcyc(2R2G+f00R+f11R)(F0eτcpE0-F2eτcpE2)B00N+(F0e-τcpE0-F2e-τcpE2)B11N+(e-τcpE1-eτcpE1)B01NNcyc

selleckchem The CPMG experiment can be considered in terms of a series expansion. The propagator initially contains six unequally weighted evolution frequencies, ±E0, Avelestat (AZD9668) ±E1 and ±E2, where the cofactors are the product of an Fx (x = 0, 2) constant, (Eq. (36)), and a Bxx (xx = 00, 11, 01) matrix (Eqs. (18) and (40)). Raising these terms to the power Ncyc will result in new terms that can be represented in terms of sums and differences of the six frequencies, and weighting coefficients. Temporarily ignoring the coefficients, the frequencies that can be involved in the expansion can be revealed using Eq. (41), noting that ε0

is real and ε1 is imaginary: equation(58) (etcp2∊0+etcp2∊1+e-tcp2∊0+e-tcp2∊1+e-tcp(∊0+∊1)+etcp(∊0+∊1))Ncyc=(etcp(∊0+∊1)+e-tcp(∊0+∊1))Ncyc(etcp(∊0-∊1)+1+e-tcp(∊0-∊1))Ncyc(etcp2∊0+etcp2∊1+e-tcp2∊0+e-tcp2∊1+e-tcp(∊0+∊1)+etcp(∊0+∊1))Ncyc=(etcp(∊0+∊1)+e-tcp(∊0+∊1))Ncyc(etcp(∊0-∊1)+1+e-tcp(∊0-∊1))Ncyc The expansion results therefore in the product of a binomial expansion over τcp(ε0 + ε1), and a trinomial expansion over τcp(ε0 − ε1). The expansion in Eq. (57) will therefore result in 3Ncyc2Ncyc individual terms, arranged over (1 + Ncyc)(1 + 2Ncyc) possible frequencies ( Fig. 4A). Including the average relaxation rate factor at the front of Eq. (57), 2τcpNcyc(f00R + f11R), the real part of the frequencies will fall between 4Ncycτcpf00R and 4Ncycτcpf11R, or Trelf00R to Trelf11R.

The click here classic presentation of type 1 AIP is obstructive jaundice and/or a pancreatic mass, but patients seldom present with chronic

abdominal pain.14 Similarly, most reported cases of pediatric AIP focus on patients presenting with obstructive jaundice; in our patients, however, the most common presentation was acute or recurrent episodes of pancreatitis, which may reflect a different phenotype of AIP type 2 in the pediatric population as compared with adults with similar histology.13, 15 and 16 The potential for AIP should be considered among pediatric patients presenting with pancreatitis or chronic abdominal pain of unclear etiology, and EUS TCB may be considered in the diagnostic workup of these patients. Although more data are needed, our findings support the diagnostic utility and safety of pancreatic EUS TCB in a pediatric population. In children with a clinical presentation suspicious for pancreatic pathology, particularly AIP, EUS

TCB should be considered for diagnosis and to allow timely and disease-specific therapy. “
“On the surface, the blinded, randomized study by Bang et al1 of the ProCore EUS needle from Cook Medical versus a standard needle, the Expect EUS needle from Boston Scientific, appears well Ganetespib designed. But on closer reading, it becomes apparent that the study harbors design issues and potential biases that make the results difficult to interpret. It is unclear why the authors chose to compare 2 different needle designs from Carnitine palmitoyltransferase II 2 different manufacturers rather than different designs from the same manufacturer or the same needle

design of different constructions. This suggests that the intention was to compare different companies’ lead products rather than a particular design. In addition, the study has many small areas that invite an unfair comparison, all of which can be rationalized as inherent to the different devices or consistent with the manufacturer’s guidelines at the time that the study was designed. For example, in another article in the same issue of GIE, Varadarajulu and Jhala 2 recommend 5 to 7 needle passes for pancreatic masses and no suction. However, the standard needle technique used 12 to 16 passes, whereas the reverse-bevel needle technique used only 4. Suction was used for the reverse-bevel needle but not for standard needle. High suction increases blood aspiration and makes quick stains harder to interpret. Also, the investigators chose to count a case with a broken stylet as a “failure” rather than excluding it or simply use another needle. There are bigger problems. It appears that diagnostic yields were based on the results of the quick stain, not on the aggregate of the quick stain and the cell block, which is the more common determinant of accuracy, not only in most studies, but in real life. It was not stated whether the 2 false negatives on quick stain by using the reverse-bevel needle also yielded negative cell blocks.

The present work aims to evaluate the genotoxic potential of venoms from B. jararacussu,

Bothrops alternatus (Rhinocerophis alternatus), B. atrox, Bothrops brazili and Bothrops moojeni together with some isolated toxins (BthTX-I, BthTX-II, MjTX-I, BjussuMP-II and BatxLAAO) by micronucleus and comet assays using human lymphocytes. Doxorubicin (DXR, Rubidox®, chemical abstract service register number 25316-40-9) was kindly provided by Laboratório Químico Farmacêutico Bergamo Ltda (São Paulo, Brazil). DXR was diluted with distilled water according to manufacturer recommendations. Cisplatin (PLATINIL®) was kindly provided by Quiral Química do Brasil S.A. RPMI 1640 medium, penicillin/streptomycin, Cobimetinib phytohemagglutinin and fetal bovine serum were purchased from Cultlab. Cytochalasin B and ethidium bromide were purchased from Sigma Aldrich. All other reagents used were

of the highest purity degree. Dried crude Bothrops venoms were obtained from Bioagents Serpentarium, Batatais-SP, Brazil. Toxins MjTX-I, BthTX-I and II were isolated from B. moojeni and B. jararacussu snake Natural Product Library mw venom, respectively, as previously described by Andrião-Escarso et al. (2000); BjussuMP-II was isolated from B. jararacussu snake venom according to Marcussi et al. (2007); BatxLAAO was isolated from B. atrox snake venom as previously described by Alves et al. (2008). Human blood was obtained from 6 healthy volunteers between 18 and 30 years old, women or men, after obtaining their formal consent. Volunteers have not made use of any medication in a minimum period of C59 clinical trial one month before the blood collection. Briefly, venous blood was collected in heparinized tubes and distributed in fractions of 500 μL per flask for cultivation. Peripheral blood mononuclear cells (PBMCs) were cultivated in total blood RPMI 1640 medium (5 mL) supplemented with 10% fetal bovine serum (FBS, Gibco

BRL), 100 U/mL penicillin and streptomycin and 1% phytohemagglutinin (Gibco BRL) in 5% CO2 at 37 °C. Experiments were approved by the Research Ethics Committee of FCFRP-USP (n° 102). In order to determine the concentrations of venoms or toxins which would allow the evaluation of the DNA damage without affecting the cell cycles or inducing cell death, cellular viability tests were performed using a concentration response curve before carrying out the micronucleus and comet tests. The toxicity of samples on human lymphocytes, using ficoll®, was assayed using the Trypan blue exclusion method after incubation of cells with samples of B. jararacussu snake venom or BthTX-I at the concentrations of 5, 15 and 30 μg/mL for 24 h. Viable cells were determined based on the ability of cells to exclude the dye.