The method used for

The method used for Venetoclax cell line hydroperoxide determination was adapted from that of Gay and Gebicki (2002a), with some modifications. The drying (concentration) step for non-polar phase was omitted, as there was no need for it. Also, perchloric acid was replaced with H2SO4, due to safety requirements in the laboratory. The assay was adapted to use a 2 ml Eppendorf tube due to the efficiency and convenience during the assay. Effendorf tubes were stable without chemical

reactions and did not affect the optical readings in this assay (Ewald, 2010). The assay was designed to make it possible to calculate the total amount of peroxides in meat, as opposed to only the peroxides extracted in one specific solvent (Miyazawa et al., 1988 and Schmedes and Hølmer, 1989). Thus, polar peroxides and protein-bound peroxides were included. The assay used in this study relates to the approach described by Volden et al. (2011), where the protein is left as an interphase between extracting

solvents. Peroxides can be formed on several amino acid side chains but also on the protein backbone following exposure to reactive oxygen species. Detection of peroxides in a pure protein model system, using the FOX method, has been demonstrated (Gay & Gebicki, 2002a). These authors reported the presence of 0.44 mmol of peroxides/kg of ovalbumin when Rose Bengal was used to generate reactive oxygen species. They also reported that the amount of peroxides/kg of protein depended on the type of protein. There is, to our knowledge, www.selleckchem.com/products/pexidartinib-plx3397.html Progesterone no comparison between the method used by Morgan, Li, Jang, el Sayed, and Chan (1989) and ours regarding the amount of peroxides to be formed on proteins, but the amount of protein-bound

peroxides measured here is in a range comparable to their values. With regard to lipid peroxides, our values were on the high side if compared to the values normally given as 20–40 meqv peroxide/kg of oil (we only had, on average, about 1.5% w/w fat in the samples). But the determination of hydroperoxide is challenging because different types of hydroperoxide can be produced during the oxidation procedure (Bou et al., 2008). Many methods have been carried out to investigate lipid hydroperoxide in biological materials and foods (Dobarganes and Velasco, 2002, Gray and Monahan, 1992 and Moore and Roberts, 1998) but the analysis is sensitive to different laboratory details (Bou et al., 2008). Thus our higher non-polar peroxide values could relate to the choice of analytical method. It has been claimed that the more traditional peroxide measurement loses peroxides during the assay (Meisner & Gebicki, 2009). This may explain why our values are relatively high. Regarding polar peroxides, it makes sense that these are the lowest, since the dry matter content of the water–methanol phase will be low. The polar phase contains degradation products from lipids (Volden et al.

For initial characterisation of the assay systems (DGGR and olive

For initial characterisation of the assay systems (DGGR and olive oil) three replicates were used. The analysis between the level of inhibition by alginates from two seaweed sources was tested with a one way ANOVA with Tukey post test. All subsequent measurements used six replicates. The number of replicates is shown in each figure legend. Using DGGR as a substrate, the activity of lipase could be measured by the increase in absorbance

(Panteghini et al., 2001). As expected, there was a marked change in the absorbance over time for the negative control (lipase Y-27632 order plus substrate) illustrating the maximum rate of reaction (Fig. 1), whereas, for the inhibition control (Orlistat (0.025 mg/ml)) there was minimal change in absorbance over time. Fig. 1 also shows that alginate could inhibit the activity of lipase. To compare the inhibition of a range of alginates, the absorbance at 12 min reaction time was chosen. This time point was used because the reaction was still close to the linear phase. Fig. 2A shows that there was a significant difference in the level of inhibition depending

INCB024360 on the seaweed source of the alginate. The alginates extracted from Laminaria hyperborea seaweed inhibited pancreatic lipase to a significantly higher degree (two way ANOVA, p = 0.0015) than the alginates extracted from Lessonia nigrescens. A dose dependent inhibition was seen for both sets of seaweed alginates. Fig. 2B shows that

for Laminaria hyperborea alginate the percentage of lipase inhibition increased with increasing concentration. For LFR5/60, there was a 75% relative increase in inhibition when the alginate concentration was increased fourfold from 0.21 mg/ml to 0.86 mg/ml, and a 56% increase from 0.86 mg/ml to 3.43 mg/ml. Similarly, the increases for alginates SF120 and SF/LF were 90% and 122%, respectively when the alginate concentration was increased from 0.21 to 0.86 mg/ml, and again 64% and 47%, respectively increased to 3.43 mg/ml. The alginate SF200 level of inhibition increased 44% and 46% when the alginate concentration increased from 0.21 to 0.86 and then 3.43 mg/ml. Pyruvate dehydrogenase As seen in Fig. 2, not all alginates inhibited lipase to the same extent, even those from the same genus of seaweed. To understand why the levels differed, the compositional characteristics of the various alginates were correlated with the level of lipase inhibition (Table 2). Statistical significant positive correlations were found between levels of inhibition and increasing guluronate content (F(G)), the fraction of guluronate dimers (F(GG)), the fraction of guluronate trimers (F(GGG)) and the number of guluronate blocks greater than one in the alginate polymer (N(G > 1)). Surprisingly, the reciprocal correlations with mannuronate levels were not always significant. Only F(M) and F(MG) were statistically significant negative correlations.

Nowadays it is known that excesses of either n-6 or n-3 PUFAs sho

Nowadays it is known that excesses of either n-6 or n-3 PUFAs show immunosuppressive effects, and that maintenance of the immune response can be verified by administering LEs with n-6/n-3 FA ratios between 2:1 and 4:1 (Fan et al.,

2003 and Palombo et al., 1999). Soybean oil-based LEs show an n-6/n-3 FA ratio of about 7:1 (Horie, Torrinhas, Nardi, Cilengitide in vivo Waitzberg, & Falcão, 2007). SLs show metabolic advantages not provided by physical mixtures of different types of oil. They contain medium- and long-chain FAs on the same glycerol backbone, in contrast with the currently available ELs, which are a physical mixture of separate medium- and long-chain TAGs. One potential advantage of SLs is that they offer a broad choice of FAs in the composition of the TAGs. For example, soybean oil can be used to provide n-6 essential FAs, and FAs from fish oil can display anti-inflammatory effects and contribute to the structure of the central nervous system via their n-3 PUFAs. Due to its high concentration of eicosapentaenoic acid (EPA, C20:5, n-3) and docosahexaenoic acid (DHA, C22:6, n-3), fish oil has been shown to have anti-inflammatory potential by interfering with the arachidonic acid pathway and producing the anti-inflammatory eicosanoids prostaglandin E3, leukotriene B5 and thromboxane A3 (Dudrick, Wilmore, Vars, & Rhoads, 1969). PUFAs from the n-3 family also

play a primary role in brain and retina development and DHA has a special role in visual and cerebral function selleck chemical in premature children, probably extending throughout their entire childhood (Innis, 2000), being incorporated mafosfamide into the central nervous system during development of the infant brain (Hartvigsen, Mu, & Hoy, 2003). Many studies have investigated the lipase-catalysed interesterification for the production of n-3 PUFA-enriched fats (Fajardo et al., 2003 and Osório et al., 2001) and a number of procedures patented (Macrae and How, 1983, Matsuo et al., 1979 and Nakamura et al., 1987). Most

of these were kinetic studies on model reactions for acidolysis on a laboratory scale in the presence of organic solvents (Ghazali et al., 1995, Senanayake et al., 2002a, Soumanou et al., 1997 and Senanayake and Shahidi, 2002b). However, in these systems the recovery of the modified TAGs posed a separation problem. The aim of the present study was to model the production of SLs with n-6/n-3 ratios adequate for parenteral nutrition via response surface methodology (RSM), using lipase-catalysed acidolysis in solvent-free media. The process consists of a set of mathematical and statistical methods developed for modelling phenomena and finding combinations of a number of experimental factor variables that will lead to optimum responses. With RSM, several variables are tested simultaneously with a minimum number of trials, according to special experimental designs based on factorial designs (Box et al.

2–2 8) pg/ml higher plasma EEQs, but this was difficult to attrib

2–2.8) pg/ml higher plasma EEQs, but this was difficult to attribute to a specific type of drug. For BMI, weight loss, use of personal care products, and living within a city centre, no clear associations with plasma EEQs and AEQs were found. Table 3 presents the effect estimates for occupational exposures. Reporting of any occupational exposure seemed to be associated with an increase in plasma EEQs of 1.2 (95%CI − 0.1–2.4) pg/ml. Exposure to pesticides appeared to be associated with an increase in plasma EEQ of 1.5 (95%CI − 0.2–3.2) pg/ml. For the associations between

the recent use of disinfectants and plasma EEQs and AEQs, more convincing effect estimates were calculated: beta 2.1 (95%CI 0.2–3.9) pg/ml and beta www.selleckchem.com/products/fg-4592.html 1.6 (95%CI 0.3–3.5) × 10− 1 ng/ml, respectively. Disinfectants mostly involved cleaning buy Selumetinib hands or equipment with alcohol, which was reported by men with very diverse job titles. Occupational exposure to organic solvents, including industrial cleaning agents, paint, ink, adhesives and thinners, seemed to be linked with a slightly increased plasma EEQ: beta 1.3 (95%CI − 0.3–3.0) pg/ml,

whereas no elevated of reduced EEQs or AEQs were noted in 31 men with exposures to these products from leisure time activities (e.g. home improvements or hobbies). Men who reported exposure to welding or soldering fumes seemed to have somewhat higher plasma AEQs: beta 1.4 (95%CI − 0.2–2.9) × 10− 1 ng/ml. Working with copper or lead or exposure to fumes from plastics could not be associated with EEQs or AEQs in plasma. An approximately 30% higher plasma EEQ was found in six men with indoor exposure to vehicle exhaust fumes for at least 5 h/week: beta 2.9 (95%CI 0.6–5.2) pg/ml. Effect estimates of dietary intake variables are presented in Table 4. Plasma EEQs and AEQs could not be associated with the triclocarban current intake frequency of any food item. The DR CALUX® measurements, however, revealed that men with TEQs over 60 pg/g lipids, which represent moderate to high internal levels

of total dioxins, had approximately 20% higher plasma AEQs compared to men with TEQs below 50 pg/g lipids (Table 5). In this observational study, we explored the effects of exposure to a variety of sources of potential endocrine disruptors on total estrogenic and androgenic plasma activities measured by CALUX® bioassays. To our knowledge, this is the first study in which the CALUX® technology was used to assess hormone activities in total plasma, in contrast to previous reports in which measurements were performed on plasma extracts of specific lipophilic pollutants. The total estrogenic and androgenic activities in plasma would reflect receptor activation by any prevalent xenobiotics, as well as by endogenous hormones (Fig. 1), also detecting certain ‘indirect’ effects of xenobiotics, such as interference with the bioavailability of endogenous hormones or competitive receptor binding.

5–15 2 m); a dbh of 15 cm (mean of 15 trees, range8–23 cm) and a

5–15.2 m); a dbh of 15 cm (mean of 15 trees, range8–23 cm) and a stem density of ca 3600 ha−1. The surface vegetation within the forest was dominated by needle-litter and a dense cover of mosses with Hylocomium splendens (Hedw.) Schimp. and Pleurozium schreberi (Willd. ex Brid.) Mitt. dominant and Hypnum cupressiforme Hedw., Dicranum scoparium Hedw., Plagiothecium undulatum (Hedw.) Schimp. and Polytrichum spp. frequent. Diplophyllum albicans (L.) Dumort. was observed on peat banks. The soil over the majority of the site was shallow peat (20–50 cm) above a stony/gravelly granite bed. The ground within the forest had been ploughed before planting with furrows cut

through to the underlying mineral material. Trees were planted on mounded peat which was coarsely mixed in places with mineralsubsoil and this website stones brought to the surface by ploughing. Weather data for the year of the wildfire were obtained, courtesy of the Met Office, for the Aviemore weather station, located approximately 9 km to the NW of the fire ground. Data were used to examine patterns in rainfall, temperature and humidity in the lead-up to the wildfire and to calculate fuel moisture codes

and fire danger indices (Table 1) from the FWI system. selleck inhibitor The FWI system underlies the UK Met Office Fire Severity Index which is currently implemented in Wales and England to forecast “exceptional” fire weather conditions (Kitchen et al., 2006). The codes and indices were calculated using temperature, Metformin manufacturer humidity and wind speed measured at 12:00 local time and with total daily rainfall. We used the “fume” package (Santander Meteorology Group, 2012) in R (R Development Core Team, 2012) to calculate FWI system codes and indices. The DMC and DC have long lag times (12 and 52 days respectively) so we calculated

values starting from the 1st January 2006 (199 days prior to the fire). Long-term weather data were obtained from the National Climate Information Centre (Met Office n.d.). Peat fuel consumption was estimated using a four-stage processes: 1. Cores were extracted from ground fuels in burnt and unburnt areas in order to determine pre-fire fuel structure. Eight peat cores were taken with a 5 cm × 5 cm box corer during the first site visit. Four cores were taken from lightly burnt areas (i.e. with litter or duff layer still intact) within the fire area and four from outside the burn perimeter but within ca. 10 m of the edge of the fire. Cores from burnt areas had been subject to flaming fire spreading through the litter layer but did not show signs of peat or duff consumption. A major issue in post-fire fuel reconstruction is that unburnt fuels may differ substantially from those in areas that burnt – such differences determining the position of the fire perimeter. Taking cores in fuels remaining within the burnt area allowed us to compare their structure to those that were not subject to any fire.

, 2008) In addition, since geographically-proximate timber trees

, 2008). In addition, since geographically-proximate timber trees are (typically) more similar than those farther apart, even trees not individually fingerprinted before harvesting can be tracked based on reference samples, allowing discrimination between legal concessions and illegal harvest zones (see, e.g., GTTN, 2014). To respond to climate change, Alfaro et al. (2014) indicate the importance of new breeding approaches (e.g., El-Kassaby et al., 2012). This is because current methods are often too slow to respond adequately

due to long generation times in breeding cycles (Yanchuk and Allard, 2009). Such approaches are facilitated by advances in genomics, but the importance of participatory domestication, working with local communities, also has much selleck compound to offer (Dawson et al., 2014 and Leakey et al., 2012). Another important issue to address is the role of epigenetic buffering in climate change responses (Aitken et al., 2008). The most well known example of epigenetic effects in trees is variation in the phenology of bud set in Norway spruce (Picea abies; Johnsen et al., 2009), but similar effects have been observed in other species (e.g., Greenwood and Hutchison, 1996 and Webber et al., 2005). There is, however, a general

lack of information on epigenetic selleck effects in angiosperm trees ( Rohde and Junttila, 2008). Finally, further studies on geographic patterns of molecular genetic variation in trees in combination with more advanced ensemble methods of past-, present- and predicted future-climate ecological niche modelling are required to understand learn more climate impacts on species and forests,

and prioritise geographic regions for conservation (Cavers and Dick, 2013, Lefèvre et al., 2013 and Thomas et al., 2012). Because data on tree species distributions are often deficient, the utility of vegetation maps as proxies for distributions is also an important area of research (VECEA, 2014). Bioversity International and ICRAF are part of the CGIAR Consortium Research Programme on Forests, Trees and Agroforestry (www.foreststreesagroforestry.org/). We thank colleagues within the Forest Genetic Resources Programme (Bioversity International), Science Domain 3: Tree Diversity, Domestication and Delivery (ICRAF) and Forestry Department (FAO) for their advice in writing this editorial. “
“The elemental role played by trees in the lives of rural people in the tropics appears obvious through the many uses made of tree products, in construction, fencing, furniture, foods, medicines, fibres, fuels and in livestock feed, and in their cultural value. Indeed, in a World Bank report published a few years ago, forests and trees-outside-forests were reported to contribute to the livelihoods of more than 1.6 billion people worldwide (World Bank, 2008).

As expected, the ltLR for both phase 1 and phase 2 enhancement ex

As expected, the ltLR for both phase 1 and phase 2 enhancement exceeds that for standard 28 PCR cycles at all numbers of replicates, and phase 2 enhancement ltLR typically gives a small improvement over phase 1 enhancement. For

30 PCR cycles, the ltLR exceeds the mixLR for a single replicate but dips slightly below it at six replicates. For the other conditions, the mixLR is always exceeded from four replicates. All three curves in Fig. 3 (middle) show an increasing trend with number of replicates, with the median ltLR being in the expected order throughout (decreasing ltLR with increasing dropout for Q). The median ltLR exceeds the mixLR after one replicate (low dropout), after two replicates (medium dropout) and after four replicates (high dropout). The range is often wide, reflecting a strong dependence of the ltLR on the details of the simulation (in particular the number check details of alleles shared across contributors). The ltLR returned when only standard or only sensitive replicates are used shows a similar trend, but nearly five bans lower for the standard replicates

(Fig. 3, right). For three or more replicates, using mixed types of replicates is superior this website even to only using sensitive replicates, coming to within two bans of the IMP. This partly reflects the limited pool of replicates used in the actual crime case, but suggests that using different sensitivities in the profiling replicates may convey an advantage due to different contributors being better distinguished. We have shown that ltLR computed by likeLTD is bounded above by the IMP in every condition considered, as predicted by theory (Eq. (3)). That the bound is often tight when

Q is the major contributor (Fig. 1 and Fig. 2 (top)) supports the validity of the underlying mathematical model, and its correct implementation in the likeLTD software. Our results should help counter any misconception that FAD combining multiple noisy profiling replicates only compounds the noise: in fact, multiple noisy replicates can fully recover the genotype of a contributor [14]. A novel feature of likeLTD, is that it can accommodate uncertain allele designations, which diminishes the problem of an all-or-nothing allele call, therefore mitigating the problem highlighted by [15] of choosing a detection threshold. We have shown (Fig. 1 (right)) that introducing many uncertain allele calls leads to ltLRs that satisfy the bound, which is reasonably tight with as few as three replicates even when 80% of true alleles are designated as uncertain and there are also multiple uncertain non-alleles. We have further shown that mixLR, the LR computed from knowing every allele that is represented in the profile of at least one contributor to the CSP, is often surpassed after only a handful of replicates.

Fig 2 summarizes the results from the three different methods us

Fig. 2 summarizes the results from the three different methods used in our study by DENV serotype. None of our patients were infected with DENV-4. PRNT and most other neutralization assays have used epithelial cells, such as Vero or BHK-21 as host cells for DENV infection. These cells neither express FcγR nor are they the primary targets of DENV in vivo. Monocytes, on the other hand, play a central role in dengue virus replication ( Durbin et al., 2008 and Halstead, 1988) as well as the clearance of immune complexes. Using THP-1, which was derived from a patient with acute monocytic leukemia, we had observed that convalescent serum could only neutralize the homologous serotypes in the presence of FcγR-mediated phagocytosis

( Chan et al., 2011). Our present finding supports this hypothesis and demonstrates that such an approach find more could be used to determine the serotype of the infection. This approach CP-673451 mouse could be useful in assessing the efficacy of vaccination to each of the four DENV serotypes. As the tetravalent formulation of candidate dengue vaccines would elicit pan-dengue antibodies, clarifying whether these antibodies are able to neutralize each of the four DENV serotypes in the presence of FcγR phagocytosis,

similar to antibodies generated following an acute infection, could inform on whether vaccination is likely to result in long-term serotype-specific immunity. Our current findings also raise important questions. It is not evident why neutralization of heterologous serotypes could not occur in the presence of FcγR-mediated phagocytosis. It is possible that cross-reactive antibodies need higher of amounts of antibodies to fulfill the stoichiometric requirement for DENV neutralization compared to serotype-specific antibodies (Pierson et al., 2007) and these antibody concentrations coincide with that which aggregates DENV for FcγRIIB co-ligation (Chan et al., 2011). It is also possible that the cross-reactive antibodies to DENV antigens have lower binding

affinities that are compromised in the low pH environment within phagosomes. Indeed, serotype-specific antibodies appear to be more potent in DENV neutralization although cross-reactive antibodies were more abundant in convalescent sera (de Alwis et al., 2012). Hence, we suggest that in addition to blocking specific ligand-receptor interactions for viral entry, antibodies must prevent viral uncoating during FcγR-mediated phagocytosis for complete humoral protection. Clarifying this could be important for identifying suitable antibodies for therapeutic development (de Alwis et al., 2011, de Alwis et al., 2012 and Teoh et al., 2012). In conclusion, determining if virus neutralization occurs in the presence of FcγR-mediated phagocytosis can clarify the serotype of the DENV infection serologically. We thank our collaborators in the EDEN study for their assistance in patient enrolment and clinical specimen collections.

An C

An PCI 32765 increase in islands and lateral sand bars in the reach is also shown in Fig. 5C. Analysis indicates that the reach gained 23,600 m2 of island area in 40 km of reach (the length of the reach is limited by the extent of the aerial photos). The areal extent of island area in 1999 was 150% greater

in 1950. Additionally, the island morphology has shifted from in-channel islands (indicative of the pre-dam river) to large islands attached to the outside of meander bends with distinctive distributary channels running through them. These are essentially former islands that have become attached to the banks as a result of excess sediment cutting off side channels. The Reservoir-Dominated selleck screening library Interaction reach is located 140–190 km downstream from the Garrison Dam. Reservoir effects vary both annually and seasonally due

to changing reservoir levels creating a recognizable deltaic morphology. The Reservoir-Dominated Interaction reach is characterized by aggrading islands, sand bars, and the flooded meander bends (former meanders that have been flooded by the reservoir). 9 of 11 sites indicate deposition greater than the natural variability (269 m2). Fig. 4A is typical of cross sections in this area and shows al decrease in cross-sectional area of 411 m2. No suitable historic aerial imagery was available for this section of the river but current conditions indicate higher levels of low elevation sand bars than other sections of the river. The active extent of this reach can migrate drastically

from year to year depending on the reservoir level (as much as 160 km longitudinally, Fig. 6). Although the 50 km reach encompasses most of the delta in a typical discharge year, changes in releases from either dam can substantially change the active extent of the reach. Consequently, the depositional morphology and ultimately the Reservoir-Dominated Interaction reach can have a broader spatial distribution (Fig. 6A and B) than can be accounted for by a single year (insets A1 and A2, B1 and Cyclooxygenase (COX) B2). Although the lake level and backwater effects are highly spatially and temporally variable, the most recent set of aerial photos indicate the area of maximum deposition encompasses only this 50 km section of river. The morphology of this reach changes with varying lake levels. Islands, flooded meander scrolls, and deltaic splays are alternatively exposed and flooded. A large numbers of dead trees from flooding and those washed downstream litter the landscape and are present in channel. The Reservoir reach (Lake Oahe) is remarkably stable. This reach extends from approximately 190 km to just upstream of the Oahe Dam; 512 km downstream from Garrison Dam. Cross-sections in this section extend into the first 100 km into this reach. All 12 cross sections in the Oahe reach shows deposition greater than natural variability from 1963 to 1989 (269 m2).

Two proposed natural causes for an observed increase in CO2 aroun

Two proposed natural causes for an observed increase in CO2 around 8000 years ago (natural loss of terrestrial biomass and changes in ocean carbonate chemistry) are considered and rejected. Instead, the rise in CO2

is attributed to the widespread initial pre-industrial forest clearance in Eurasia associated with the expansion of agricultural landscapes (Ruddiman, 2003). This increase in CO2 is characterized as being “imperceptibly gradual, and partially masked by a larger cooling trend” (2003, p. 285). The supporting evidence offered for deforestation associated with agriculture being the cause of the observed CO2 rise at ca. 8000 B.P. is also admittedly limited: “these estimates of land clearance and carbon emissions are obviously just rough first approximations” (2003, p. 277), consisting of general observations regarding the BIBW2992 in vivo initial expansion of agricultural societies out of the Near East into Europe and their subsequent intensification,

as well as similar but less well documented trends in China and India. Like Certini and Scalenghe, ecologists Christopher Doughty, Adam Wolf, and Christopher B. Field (2010) use a pedospheric Selleckchem Alpelisib indicator to mark the beginning of the Anthropocene, but focus on a much smaller, regional scale of proposed human impact. Their proposed marker for the onset of the Anthropocene is a large increase in Birch (Betula) pollen from Alaska and the Yukon during a narrow 1000 year period at ∼13,800 B.P. They suggest that this increase in Betula modified the land surface

albedo (i.e. reduced reflectivity), resulting in a projected regional warming of up to 1 °C. Given the general temporal correlation between this documented increase in Betula and the extinction of mammoths, they hypothesize that reduced herbivory associated with the disappearance of megafauna played a causal role in the expansion of birch forests and the resultant rise in regional temperature levels. The extinction of mammoths is then linked to human predation, and they propose that humans contributed to global warming: We hypothesize that the extinction of mammoths increased Carnitine palmitoyltransferase II Betula cover, which would have warmed Siberia and Beringia by on average 0.2 degrees C, but regionally by up to 1 degree C. If humans were partially responsible for the extinction of mammoths, then human influences on global climate predate the origin of agriculture. ( Doughty et al., 2010) They go on to conclude that this anthropogenic regional warming trend represents the onset of the Anthropocene: “Together, these results suggest that the human influence on climate began even earlier than previously believed (Ruddiman, 2003), and that the onset of the Anthropocene should be extended back many thousand years.” (Doughty et al., 2010).