“
“The number, diversity and complexity of synthetic chemicals produced

and released to the environment are overwhelming. As a consequence, we are rarely exposed to only one single contaminant, but typically to mixtures of numerous man-made-chemicals with varying constituents in varying concentrations and concentration ratios (Faust et al., 2003). However, in contrast to this exposure scenario, the present toxicological approach devotes 95% of its resources to the study of single chemicals (Groten, 2000) and provides threshold doses or concentrations of regulatory concern (such as acceptable daily intakes or predicted no effect concentrations) for individual chemicals, implying that exposures below these levels are to be considered safe. In addition, with a few exceptions, chemical risk Ipilimumab mouse assessment considers the effects of single GSK2118436 substances in isolation, an approach that is only justified if the exposure to mixtures does not bear the risk of an increased toxicity. In fact, the behavior of chemicals in a mixture may not correspond to the one predicted from data obtained with the pure compounds (Altenburger et al., 2004). From the practical point of view, though, the

direct testing of all the potential combinations of contaminants is unfeasible, and thus we are confronted with the task of deriving valid predictions of multiple mixture toxicity from toxicity data on individual compounds (Faust et al., 2003). In a recent review on the state of the art on mixture toxicity (Kortenkamp et al., 2009) it was concluded that there is a deficit on mixtures studies in the area, amongst others, of neurotoxicity and that it is difficult to assess, based on experimentally published data, the type of combination effect. Furthermore, at present toxicity testing for hazard identification relies mostly on the use of animal models. This approach is costly and time-consuming, and is not practical for hazard identification of Cell Penetrating Peptide the thousands of chemicals such as under the REACH directive or in the

high production volume program. Thus, even in the context of mixture toxicity, alternative approaches that have higher throughput capability and are predictive of in vivo effects are needed ( Coecke et al., 2007 and Lilienblum et al., 2008). From a toxicological point of view, in a mixture, chemicals may basically behave in two ways: they can have a joint action or they can interact (Plackett and Hewlett, 1952). In the first case they may act through concentration addition (CA) and independent action (IA) mechanisms also referred to as Loewe additivity and Bliss independence. CA is thought to be valid for mixtures where the components have similar sites and modes of action, while IA is currently held appropriate for mixtures where the components have different sites and dissimilar modes of action ( Greco et al., 1995 and McCarty and Borgert, 2006).

Thus, non-synchronized neuronal activity within the first 80 ms

may also induce competition among local neuronal networks, which culminates in synchronization of inhibitory networks specific for the target. Amplitude of P1–N1 difference or alpha amplitude may be an indicator of the magnitude of synchronization. Increase in alpha activity either increase signal to noise ratio and allows processing of relevant information (contralateral hemisphere) or suppression of irrelevant information (ipsilateral hemisphere) ( Klimesch et al., 2007 and Klimesch, 2012). At the single cell level, estradiol increases, but progesterone decreases neuronal excitability (Majewska et al., 1986, Wong and Moss, 1992, Spencer et al., 2008 and Finocchi and Ferrari, 2011). MG-132 cell line As progesterone and its metabolites affects inhibitory, GABAergic synapses, fluctuations of endogenous progesterone during menstrual

cycle might affect synchronization of inhibitory networks. In the present study, we find that women with fast RTs show higher progesterone level compared to women with slow RTs. Further, progesterone correlates positively with alpha P1–N1 amplitude difference. Thus, assuming that alpha oscillations are inhibitory at the physiological level, an increase in progesterone may enhance inhibition via fine tuning rhythmic synchronization of neural networks leading to improvements in cognitive processing. Critically, the inhibition selleckchem model of alpha oscillations predicts that an increase in functional inhibition causes an increase in alpha amplitude. An increase in alpha amplitude, specifically in P1–N1 difference, may increase signal to noise ratio as well as tonic inhibition of networks processing irrelevant information (Klimesch et al., 2007). Both mechanisms improve cognitive processing. We summarize our results in a progesterone-dependent

alpha-inhibition model. This model combines the “inhibition model” (Klimesch, 2011) with the physiological consequences of progesterone on neuronal excitability these as well as on alpha oscillations. The progesterone-dependent alpha-inhibition model predicts in our cued spatial attention paradigm that an increase in progesterone is associated with (1) tonic mutual inhibition of ipsilateral cerebral hemispheres illustrated by a larger alpha P1–N1 amplitude difference in the ipsilateral hemisphere and (2) increase in signal to noise ratio in the contralateral hemisphere via enhancing GABAergic synaptic transmission visualized by larger alpha P1–N1 amplitude difference in women high in performance compared to women low in performance. Cerebral hemispheres are mutual inhibitory (Innocenti, 2009 and Bocci et al., 2014). Accordingly, in top down controlled attention tasks, neural equivalent of expectancy of a target may include a cue-induced increase in excitability in the contralateral, but an increase in inhibition in ipsilateral hemisphere.

, 2010). On the 40–160-h time scale the correlation Target Selective Inhibitor Library solubility dmso relationship is cleaner for the model than observations, as model SST generally has less variability than observations ( Figs. 1b and 2). To examine the statistics

of that relationship, the lagged correlation is calculated for the filtered time series of both model and observations. Each value of the lagged correlation series is a calculation of correlation with the time series of SST and τ offset from one another by a different lead/lag time. We consider only the correlations in which the τ time series leads SST, because the ocean model is forced by a prescribed atmosphere that has no response to the ocean, rendering lag time meaningless. For comparison between model and observations, we select the largest magnitude correlation for any lead time less than 48 h. The lead time itself is examined separately. The KPP turbulent mixing scheme is implemented in a version of the Massachusetts Institute of Technology general circulation model (MITgcm) (Adcroft, 1995, Marshall et al., 1997a and Marshall et al., 1997b), in hydrostatic configuration

with a 1/3° resolution C-grid on a domain encompassing the Tropical Pacific, from 26°S to 30°N and 104°W to 290°W (Table 1). The model is run for approximately four years, from Nov 1st, 2003 to October 13th, 2007 with a 15-min timestep. The model configuration is based on Hoteit et al., 2008 and Hoteit et al., 2010. Initial and lateral boundary conditions for the ocean temperature, salinity, and velocity come from the OCean Comprehensible Atlas (OCCA) (Forget, 2010). Surface forcing buy AZD4547 for temperature, specific humidity, shortwave and longwave radiation, wind (unless otherwise noted), and precipitation are interpolated to the model grid size and time step from the NCEP/NCAR 1.8°, six-hourly Reanalysis (Kalnay et al., 1996) and prescribed at the ocean surface. The MITgcm calculates

heat fluxes between the ocean and atmosphere. The default experiment (Exp. 0 [Table 2]) uses the NCEP/NCAR forcing and default KPP parameter values. An ensemble of 42 additional experiments is conducted (Table 2). In the first three experiments the KPP parameters are held at their default values while wind forcing is replaced with alternatives: ECMWF (Gibson et al., 1997), NOAA/CIRES Twentieth selleckchem Century reanalysis (Compo et al., 2011), and NASA Cross-Calibrated Multi-Platform Ocean Surface Wind Velocity (Atlas et al., 1996) (Exp. 1–3 [Table 2]). In the next 19 experiments, KPP parameters are perturbed to artificially large and small values (Exp. 4–22 [Table 2]). An additional 20 experiments are conducted using wind forcing that is blended from the NCEP/NCAR, ECMWF, and NASA products (Exp. 23–42 [Table 2]). The blending is done using a mixture model to weight the contribution from each of the three wind products, resulting in a Dirichlet distribution of weighting with the highest probability being an equal weight for each product.

Para rentabilizar os recursos humanos e técnicos, é necessário um enfoque especial na preparação dos doentes para os exames3. A preparação inclui aspectos como o controlo de patologias associadas, a eventual suspensão ou o ajuste de medicação e, no caso da colonoscopia, a limpeza intestinal. A limpeza intestinal para uma colonoscopia é essencial para o sucesso da mesma. Um cólon limpo permite a realização de um exame completo com maior facilidade, rapidez e segurança e a visualização e eventual tratamento de lesões, mesmo de pequenas dimensões. Uma PLX3397 order colonoscopia

num doente com má preparação pode tornar o exame mais demorado e com maior risco de complicações, além de atrasar um diagnóstico e impedir uma terapêutica atempados e leva, muitas vezes, a uma remarcação. Rex e col calcularam que esta remarcação aumenta o custo em 12-22%4. Apesar destes factos serem bem conhecidos, há, em muitos estudos, consistentemente, uma percentagem de doentes mal preparados5, que ronda, em média, os 25%. A Sociedade Francesa de Endoscopia Digestiva calcula que cerca de 20.000 colonoscopias realizadas anualmente em França são devidas a remarcações por má preparação6.

É importante saber que factores levam a uma má preparação. selleckchem A preparação do cólon pode ser feita com vários produtos, cuja descrição não está no âmbito deste editorial. No entanto, é de salientar que não há preparações perfeitas. Uma preparação ideal, além de barata, seria fácil e agradável de usar, não teria riscos para o doente e conseguiria uma limpeza intestinal excelente. Não existindo tal preparação, há que utilizar

correctamente as que existem no mercado e procurar minimizar factores controláveis, já que algumas causas de má preparação, como a idade avançada, doente internado, a inactividade, comorbilidades como a ZD1839 supplier diabetes e a toma de antidepressivos5, não são modificáveis. O estudo publicado por Rita Carvalho e col neste número do GE-Jornal Português de Gastrenterologia7 incide precisamente num aspecto da preparação do cólon para colonoscopia que pode ser melhorado com uma intervenção relativamente simples e barata. Os autores procuraram avaliar o impacto que o ensino personalizado do doente pode ter na qualidade da preparação intestinal e, nesse sentido, estudaram dois grupos de doentes, um grupo “controlo” com 67 doentes e um grupo “intervenção” com 58 doentes. Os doentes foram randomizados com recurso a tabela de randomização, sendo que todos receberam informação dada pelo gastrenterologista assistente sobre o exame, juntamente com um folheto informativo, uma explicação verbal sobre a solução de limpeza intestinal.

The vector pET 101-D-TOPO containing Jaburetox-2Ec coding buy CHIR-99021 sequence was used as template in a polymerase chain reaction. In order to obtain a recombinant peptide containing the His-tag and lacking the V5 antigen, a set of primers were designed, the cDNA was amplified by PCR, cloned into pET 23-a vector and expressed in BL21-CodonPlus (DE3)-RIL

(Stratagene). This new peptide was called Jaburetox. The forward primer sequence was Jaburetox 5′ CCAACATATGGGTCCAGTTAA TGAAGCCAAT 3′ (the underline shows the NdeI site) and the reverse primer sequence was Jaburetox 5′ CCCCCTCGAGTATAACTTTTCCACCTCCAAAAACA 3′ (the underline shows the XhoI site). The PCR reaction was carried out in the following conditions: denaturation at 95 °C for 3 min, annealing at 55 °C for 30 s and elongation at 72 °C for 2 min. A total of 35 cycles were used and the final product was then digested with NdeI (Fermentas, Eugene, OR, USA) and XhoI (Fermentas, Eugene, OR, USA), dephosphorylated with thermosensitive alkaline phosphatase (Promega, Madison, WI, USA). The plasmid pET 23a::Jaburetox was sequenced using a ABI PRISM 3100 automated sequencer (Applied Biosystems, Foster PCI-32765 city, CA). For isolation and purification

of Jaburetox, 200 mL of Luria broth medium containing 100 μg/mL ampicillin and 40 μg/mL chloramphenicol were inoculated with 2 mL of the overnight culture. The cells were grown 2 h at 37 °C under shaking (OD600 = 0.7) and then 0.5 mM isopropyl β-d-1-thiogalactopyranoside (IPTG) was added.

After 3 h, the cells were harvested by centrifugation and suspended in 10 mL of lysis buffer (50 mM tris buffer, pH 7.5, G protein-coupled receptor kinase 500 mM NaCl, 5 mM imidazole), sonicated, centrifuged (14,000 × g, 30 min) and 10 μL of supernatant or 5 μL of the pellet sample were analyzed by SDS-PAGE. The supernatant was loaded onto a 2 mL Ni affinity column (Ni-NTA, QIAGEN, Hilden, Germany), which was previously equilibrated with the equilibration buffer (50 mM Tris buffer, pH 7.5, 500 mM NaCl, 5 mM imidazole). After 30 min, the column was washed with 20 mL of the same buffer, containing 50 mM imidazole. The recombinant peptide was eluted with the equilibration buffer containing 200 mM imidazole and quantified by the Bradford method [9]. The samples were dialyzed against the 50 mM phosphate buffer, pH 7.5, 1 mM EDTA, 5 mM β-mercaptoethanol. A molecular mass of 10,128.2 Da (ExPASY ProtParam tool) was considered for Jaburetox. The yeasts Candida parapsilosis (CE002), Candida tropicalis (CE017), Candida albicans (CE022), Kluyveromyces marxiannus (CE025), Pichia membranifaciens (CE015), and Saccharomyces cerevisiae (1038) and filamentous fungi Colletotrichum lindemuthianum, Colletotrichum musae, Colletotrichum gloeoporioides, Fusarium laterithium, Fusarium solani, Fusarium oxysporum, Phomopsis sp., Mucor sp., Trichoderma viridae, Pythium oligandrum, Lasiodiplodia theomobrae, Cercospora chevalier and Rhizoctonia solani were kindly provided by Dr.

Chemotherapeutic agents with discreet antitumor efficacy in metastatic melanoma include DNA alkylating agents (dacarbazine, temozolomide, nitrosoureas), platinum analogs and microtubular toxins. These agents have been used alone or in combination (Bhatia et al., 2009). An understanding of the mechanisms responsible for melanoma’s oncogenesis is critical for developing successful therapies. The deregulation of apoptosis signaling contributes to tumor-cell check details transformation. According Russo et al. (2009), melanoma’s resistance to apoptosis and chemotherapy can be explained as a consequence of the deregulation of the intrinsic (mitochondrial-dependent) apoptotic pathway. It has been shown that melanoma cells have low

levels of spontaneous apoptosis in vivo, compared with other tumor cell types and are relatively resistant to drug-induced apoptosis in vitro ( Gray-Schopfer et al., 2007). Overexpression of the antiapoptotic protein Bcl-2 has been found in melanoma and melanocytes, and this alteration was demonstrated to be involved in melanoma’s progression and chemoresistance ( Ji et al., 2010). Therefore, as changes in apoptotic pathways or in their

regulatory mechanisms are key events in human malignancies, these pathways are interesting targets for therapeutic intervention. Pharmacological studies with compounds extracted from medicinal plants, particularly flavonoids, Bortezomib concentration and synthetic derivatives of natural compounds have generated increased Acesulfame Potassium interest from the scientific community in recent years (Arts et al., 1999 and Mamede et al., 2005). Several studies demonstrated the therapeutic importance of these molecules, such as their antioxidant effect, which protects the body from

various diseases, including cancer (de Gaulejac et al., 1999). The biological properties of gallic acid, which bears a tri-hydroxylated phenolic structure and is an intermediate of secondary plant metabolism, and its analogs have been widely investigated. Gallic acid and some esters of gallate, such as octyl and lauryl gallates, are widely used as scavengers of reactive oxygen species (ROS) (Li et al., 2005). However, these compounds have been demonstrated to have various cytotoxic and antiproliferative effects on tissues and cells (Jagan et al., 2008). The antioxidant effect of the gallate esters is closely related to their hydrogen donor activity (Serrano et al., 1998), while the cytotoxic effects of gallate compounds are assumed to be due to the pro-oxidant action, not to their antioxidant capacity (Sierra-Campos et al., 2009); their antiproliferative effect is thought to be a consequence of an inhibitory activity on protein tyrosine kinases (Serrano et al., 1998). Several studies have reported the anticarcinogenic effects of gallic acid and some of its derivatives in studies using animal models or human cell lines (Calcabrini et al., 2006, Chen et al., 2009, Galati and O’Brien, 2004, Giftson et al.

S1). As anticipated co-exposure to 1 μM TCC and varying concentrations of DHT amplified the luciferase reporter activity by ∼40% ( Fig. 2A). Meanwhile the corresponding EC50 values remained unchanged at 8.0 × 10−11 M and 8.2 × 10−11 M for control and TCC treated cells, respectively. Nevertheless, the suggested stimulation of the AR is in line with earlier studies, which confirms the functionality of the reporter construct ( Christen et al., 2010). The next aim was to validate the AR-antagonistic function of TCC on a transcriptional level. This was

done by RT-PCR, targeting several transcripts known to be regulated by the AR (i.e. SARG, NDRG1 and SORD) ( Doane et al., 2006). Prior to RNA-extraction the cells Selleck Ivacaftor were treated for 24 h with 1 or 10 nM DHT ± 1 μM TCC, respectively. Exposure to DHT led to an increased expression of all three transcripts. Yet, in the presence of TCC only SORD selleck kinase inhibitor showed a slight but statistically significant decrease in gene expression (p = 0.02) ( Fig. 2D). It was thus not possible to confirm the initially observed androgenic effect of TCC on the level of the AR regulon. An unspecific off-target effect of TCC on luciferase should, however, be apparent independent of the receptor investigated. Hence an estrogenic luciferase reporter was used to investigate the effects of TCC in presence of estrogen

(E2). The corresponding results were then compared with those of a commonly used proliferation assay, namely the E-screen. The effect of TCC on an estrogenic luciferase reporter was studied using HeLa9903 cells, a cell line previously suggested for the detection Epothilone B (EPO906, Patupilone) of xenoestrogens by the OECD and EPA (OECD, 2009). These cells are stably transfected with human ERα and an ERE-driven luciferase reporter gene. The molecular phenotype was verified by quantitative RT-PCR, detecting transcripts of ESR1, GPR30 and AHR but not AR or ESR2 ( Fig. S1). As described previously ( Ahn et al., 2008) cellular co-exposure

to E2 and 1 μM TCC resulted in a 50% increase of luciferase signal intensity ( Fig. 3). Although signal amplification was consistent for all E2-concentrations tested (10−11 to 10−8 M), the maximal effect was seen at 1 nM E2 and 1 μM TCC ( Fig. 3). Higher concentrations of TCC quickly became cytotoxic ( Fig. S2). The suggested xenoestrogenic potential of TCC was further examined using the E-screen (Fig. 4). This assay uses the estrogen dependent proliferation of human mammary carcinoma MCF-7 cells as readout. Cellular exposure to E2 triggered a dose dependent increase of MCF-7 cell numbers. Addition of 1 μM TCC, however, failed to have any further proliferative effect. The E2 concentrations producing 50% of the maximal effect (EC50) were comparable between the two assays, ranging from 2.9 × 10−11 M for the luciferase assay to 3.0 × 10−11 M for the E-screen.

for providing samples of rubber. “
“The above mentioned paper did not include any acknowledgment to co-author Lucy Waskell’s funding source agency. Sotrastaurin solubility dmso The funding source which was inadvertently omitted is as follows: Veterans Administration Merit Review Grant. “
“The above mentioned paper did not include any acknowledgment to co-author Lucy Waskell’s funding source agency. The funding source which was inadvertently omitted is as follows: Veterans Administration Merit Review Grant. “
“Diffusion-weighted

imaging (DWI) and diffusion-tensor imaging (DTI) are non-invasive MRI techniques with broad clinical applications. While many clinical applications of diffusion imaging are in the brain, there is an increasing number of DWI and DTI studies in other organs [1], including the spinal cord [2], breast [3], prostate [4], liver [5], kidney [6], pancreas [7] and in the heart [8] and [9]. Bulk physiological motion has initially been a barrier to performing diffusion imaging in organs affected by motion. In cardiac selleck diffusion, this has been alleviated by technical advances including the use of cardiac/respiratory navigator techniques, single-shot echo planar imaging (EPI) readouts, and sequence modifications that reduce the effects of any motion that occurs

during the diffusion gradients. Such techniques have improved the robustness and reproducibility of diffusion-imaging applications in moving organs such as cardiac DTI [8] and [9]. Unfortunately, diffusion imaging suffers from substantial artifacts such as those caused by eddy currents, which are induced in conducting structures of the magnet bore by gradient switching. Diffusion Rolziracetam imaging is particularly prone to eddy-current artifacts due to relatively long EPI readouts combined with strong

diffusion-sensitizing gradients. Unlike static field inhomogeneities, eddy currents do not remain constant over diffusion-encoding directions. Rather, they vary depending upon the magnitude and direction of the applied diffusion gradients. This leads to spatial misregistration and inconsistency between uncorrected images obtained with different diffusion-encoding directions or b-values. Ignoring eddy currents in the image reconstruction results in ghosting, bulk object shifts and deformations, as well as signal dropouts [10]. In DTI, this also leads to inaccuracies in estimates of the fractional anisotropy (FA). In this study, we investigate the effects of eddy currents in sequences that are suitable for performing cardiac DTI where there is substantial motion. Two sequences previously used for cardiac diffusion are compared: (i) the Stejskal-Tanner or “unipolar” spin-echo diffusion sequence [11] and (ii) a “bipolar” spin-echo sequence [12], [13] and [14]. The unipolar sequence has a shorter echo time (TE) while the bipolar sequence offers insensitivity to first-order bulk motion through its velocity-compensated nature [12], [13] and [14]. The twice-refocused sequence, described in Reese et al.

The establishment of the degree of carotid stenosis by duplex US and angiography (magnetic resonance angiography – MRA, computed tomography angiography – CTA, digital subtraction angiography – DSA) is an important part of the indication of carotid reconstruction surgery in asymptomatic patients. Prophylactic carotid revascularization may be considered in highly selected asymptomatic patients if the degree of stenosis reaches at least 60%

by angiography and 70% by duplex US (Class IIb, Level of Evidence: B) [5] and [6]. Elective coronary artery bypass graft (CABG) surgery makes previous carotid duplex US reasonable in patients with the following conditions: ROCK inhibitor older than 65 years, history of cigarette smoking, PAD, left main coronary stenosis, history of stroke, TIA or carotid bruit (Class IIa, Level of Evidence:

C). Olaparib Among survivors of ischemic stroke or TIA after the immediate management further investigations should be performed to assess the cause and pathophysiology of the event. The possible origin of ischemic stroke includes intra- or extracranial-artery atherosclerotic infarction, cardiac embolism, small-vessel disease, hypercoagulable state, dissection, sickle cell disease or it can be an infarct of undetermined cause. As initial evaluation all patients with the symptoms of TIA or ischemic stroke should have non-invasive brain imaging (Class I, Level of Evidence: C). As a first step duplex US is recommended to detect carotid stenosis for patients with acute, focal neurological symptoms, which reflect the insufficient supply of certain brain territories from the left or 6-phosphogluconolactonase right ICA (Class I, Level of Evidence: C). If duplex US cannot be obtained or does not result in clear and diagnostic results, MRA or CTA is indicated as further imaging tools in the detection of carotid stenosis (Class I, Level

of Evidence: C). Correlation of findings detected by different non-invasive methods is very important in the aspect of quality assurance in every laboratory. When extra- or intracranial vascular alterations are found with such severity which cannot explain the neurological symptoms, further investigation should be performed to reveal the possible cardiac origin by means of echocardiography (Class I, Level of Evidence: C). Echocardiography serves as the gold standard in the examination of these patients. Detection of the source of cardiac embolism is of great importance regarding that this mechanism accounts for 15–30% of ischemic stroke or TIA [7] and [8]. Fig. 2 shows the diagnostic steps recommended in patients with symptoms of ischemic stroke or TIA.

Sediments from TB (1.06 phi ± 0.43) were significantly (F (1, 113) = 69.5; p = 0.0001) larger than those from SHB (2.02 phi ± 0.71), but only in SHB was there a significant difference between pipeline and non-pipeline sites ( Supplementary data Fig. 5). Those of the latter were significantly coarser (1.86 phi ± 0.74) than those of the former (2.44 phi ± 0.35) (F1, 68 = 11.93; p = 0.002). The % N varied from 0.02% to 0.8% in all samples ( Supplementary data Table 2), and samples from site SHD (a pipeline site at SHB) were much generally richer in this regard than the rest. The mean % N in sediment samples from TB (0.1%, ±0.06) was lower than in samples from SHB (0.17% ± 0.2), and in both locations, the % N of sediments

Protein Tyrosine Kinase inhibitor around the pipeline was higher than that from non-pipeline sites. That said, none of these relationships were significant owing to the pooled nature

of the % N data. With the exception of Pb, all measured trace metals occurred at significantly higher concentrations in sediments from SHB than TB ( Supplementary data Figs. 6 and 7 and Table 3). And with the exception of Cr, trace metal concentrations in the sediments were generally significantly higher from pipeline than non-pipeline sites in samples from SHB; no significant differences Ceritinib purchase were found in TB samples. Non-parametric Spearman Rank Order correlations of all environmental variables revealed significant positive relationships between most variables (Supplementary data Table 4a) indicating a common response between them. This pattern was repeated even with the average data Supplementary data Table 4b) data, when a strong correlation between % N and trace metal concentration was observed. Interestingly, there was Niclosamide no correlation between % N and mean grain size (Supplementary data Table 4b). Twenty-eight living morpho-species of Foraminifera were identified from samples collected in SHB and 34 from TB; a total of 38 from the two study areas (Supplementary Table 5). Elphidium articulatum was the most common species

in samples from TB while Ammonia parkinsoniana and the bolivinids were most abundant in SHB ( Supplementary Table 5). Cibicides lobatulus, Quinqueloculina seminulum and Glabratella australensis were present in large numbers in TB. Assemblages of dead Foraminifera showed much the same structure as those of the live assemblages, with the same species being dominant ( Supplementary Table 5). Examination of the nMMDS ordination plots of the living and dead assemblages (stress = 0.17 in both instances), reveals a clear separation of assemblages in the two locations (Fig. 2). And while there appears to be less overlap between assemblages from pipeline and non-pipeline sites in SHB than in TB (Fig. 2), this is less obvious for the dead assemblages. Indeed, there is a greater general similarity in the numerical composition of assemblages of dead, than living, Foraminifera (Supplementary data Fig. 8).