While the number of active sites of PdAu SAA is lower than that of Pt(111), the aforementioned desirable properties could bring the overall catalytic performance thereof close to that of Pt/C, indicating that the PdAu SAA could be a viable material for electrocatalytic ORR in PEM fuel‐cells.Single‐atom alloys (SAAs) consisting of isolated transition‐metal atoms doped in the surface of coinage metal hosts exhibit unique catalytic properties, harnessing the high activity of the dopant metals with the selectivity of the coinage metal hosts. Here we use density functional theory (DFT) to study SAAs comprised of Ni, Pd, Pt, Co and Rh doped into Ag and Au hosts, as candidate electrocatalysts for the oxygen reduction reaction (ORR) in proton‐exchange membrane (PEM) fuel‐cells. Our calculations reveal that the PdAu SAA exhibits a slightly lower theoretical overpotential, enhanced selectivity for 4‐e − oxygen reduction reaction, and CO‐poisoning tolerance compared to Pt(111).Single‐atom alloys (SAAs) comprise an exciting class of ultra‐dilute alloys, whereby the minority metal is atomically dispersed and exhibits unique catalytic properties. For electrocatalytic applications, the PdAu SAA is shown to exhibit a slightly lower theoretical overpotential, enhanced selectivity for 4‐e This reduction facilitates the generation of an electric potential which is most commonly used to produce mechanical work for transportation vehicles, or as a portable and stationary emergency backup power. Despite significant effort being expended in the search for novel ORR catalysts, currently the most effective materials for catalysing the ORR are pure Pt and alloys thereof.. Moreover, since CO adsorption is exergonic, the transition state can be taken as the gas‐phase species with “one less” translational degree of freedom (this missing degree of freedom corresponds to the reaction coordinate: the distance from the surface). Thus, equation (16) for CO desorption becomeswhereQ2Dtrn,rot,vibCOgcontains 2 translational, 2 rotational and 1 vibrational contributions and QvibCO*contains only vibrational contributions. For the vibrational components of these partition functions we use the vibrational frequency data from Ref. [18], under the harmonic approximation.CO, host Ag and Au atoms remain unoccupied by CO and dopant atoms are isolated from one another. However, for simulations on Pt(111), we account for first nearest‐neighbour CO−CO lateral interactions and use the DFT setup in Ref. [18] to ensure consistency.where https://dx.doi.org/10.17172/NOMAD/2021.01.02‐1, dataset ID: 6vYHLnjkQwKJgh7BCVq4Jg. The data includes the structures of the pristine slabs and the adsorbed configurations of O2, OOH, OH and O for CoAg, CoAu, NiAg, NiAu, PdAg, PdAu, PtAg, PtAu, RhAg, RhAu, as well as O2 dissociation transition states for PdAg, PdAu and PtAg. Also included are the calculations of the supplementary material for the aforementioned pristine slabs and adsorbed configurations with the PBE−D3 functional.The DFT data that support the findings of this study are openly available in NoMaD at 2*, OOH*, O* and OH*, comparing and contrasting their adsorption free energies at U=0 V (ΔGads0). We go on to evaluate the thermodynamic limiting potential on each material and compare the selectivity between two e-and four e-reduction. We then discuss the dissociation of O2* on each surface without preconceptions about the most probable pathway for ORR in each case. Finally, using DFT data from our previous studies,In this section, we present the findings of our DFT study on the ORR behaviour of SAAs. We begin by providing details on the most favourable adsorption geometries of key ORR intermediates Oe-and four e-(both associative and dissociative) pathways is the non‐electrochemical adsorption of molecular O2. O2* adsorbs weakly to Au(111) and much more strongly to Ag(111), binding in an η2 top‐bridge‐top configuration in both cases. From DFT, we calculate ΔGads0(O2*) to be 4.58 eV and 5.21 eV on Ag and Au, respectively (note that the Gibbs free energy of the left‐hand side of equation 6 is 4.92 eV at U=0 V). Thus, O2* binding is endergonic on Au and is largely responsible for its poor ORR performance. Doping Ag and Au hosts with single atoms of Ni, Pd, Pt, Co and Rh enhances the O2* binding strength in all cases with ΔGads0(O2*) ranging from 3.10 eV to 4.78 eV  of 4.40 eV and 3.83 eV, respectively. On SAAs, the binding strength is enhanced by the dopant atom with ΔGads0(OOH*) ranging from 3.26 eV to 4.03 eV  of 1.82 eV and 2.35 eV, respectively, as well as OH* in bridge sites with ΔGads0(OH*) of 0.74 eV and 1.33 eV, respectively. On SAAs the binding strengths of both species are enhanced due to doping, compared to the pure host materials, with ΔGads0(O*) ranging from 0.16 eV to 2.11 eV and ΔGads0(OH*) ranging from −0.18 eV to 1.16 eV  and ΔGads0(OH*), as well as a good correlation between ΔGads0(O2*) and ΔGads0(OH*)  and ΔGads0(OH*) is notably weaker (R2=0.57). Most materials studied for ORR behaviour follow “standard” scaling relations with well‐correlated ΔGads0for these species.ΔGads0(OH*) and ΔGads0(O*) whereas for ΔGads0(OH*) vs. ΔGads0(OOH*) the correlation is poor.Interestingly when we consider trends in the values of ) Figure . HoweverWe have shown in the past that SAAs may not always follow the traditional linear scaling relations of other metals and their alloys; instead, they are observed to either exhibit distinct linear trends of their own or deviating entirely from linearity.e-and four e-reduction pathways (i. e. H2O2 vs. H2O production), as well as to identify the most promising materials that exhibit the lowest theoretical overpotential. ηis the maximum additional potential above the ORR equilibrium (1.23 eV) for which every proton‐electron pair reduction step is thermodynamically downhill. When the latter condition is satisfied, the proton transfer barriers are expected to be low and consistent. Thus, the activity of ORR catalysts is often qualitatively predicted based on thermodynamic η, with lower values of ηcorresponding to greater predicted activity.We have analysed the thermodynamics of the ORR pathways on each SAA to compare the selectivity between the two ηranging from 0.46 eV to 1.41 eV (Table η(PtAu) <η(PdAu) <η(PdAg) <η(RhAu) <η(NiAu) ≈η(PtAg) <η(RhAg) <η(NiAg) <η(CoAu) <η(CoAg), with the top six (i. e. those with the lower η) being shown in Figure η(NiAu) and η(PtAg) are 0.672 eV and 0.669 eV, respectively, up to 3 decimals). Interestingly, there is a general trend where SAAs with a Au host matrix outperform their Ag counterparts. This trend is consistent with Ag‐based SAAs binding ORR intermediates more strongly than their Au counterparts, which results in greater free energy differences along the reaction coordinate. The greater binding strength of Ag‐based SAAs is attributed to sharper dopant d‐band peaks in the PDOS that are closer to the Fermi level compared to their Au‐based counterparts, as this facilitates more effective hybridisation and filling of surface‐adsorbate bands.Our results indicate that SAAs exhibit values of eV Table , where ηηvalues of 0.46 eV and 0.47 eV. Contextualising these values of η, Pt(111) (the DFT model surface for the Pt/C electrode) has a value of 0.48 eV.η, the activity of the Pt/C electrode for ORR will likely be much greater than the best performing SAAs. We also performed these calculations with a D3 dispersion correction (PBE−D3) and found that the O2* binding strength is increased. This leads to small changes in η, however the overall trends across the SAAs remain consistent (see supporting information). However, there may still be advantages of using SAAs over traditional Pt electrodes, such as high selectivity and tolerance to poisoning, which we discuss in subsequent sections.The best performing SAAs are PtAu and PdAu with e-pathways is that the O−O bond in O2* is cleaved in the latter, bypassing the formation of the OOH* intermediate and the mitigating the risk of forming H2O2 as a product. Instead, two O* adatoms are formed, and each is reduced twice to yield H2O via OH*. Of the 10 SAAs studied here, O2* reduction to OOH* is the thermodynamically limiting step for five materials . Thus, these five SAAs may stand to benefit thermodynamically from the O2 scission step, since this will bypass OOH* formation and subsequent protonation. Studying the potential‐dependent reaction free energies for each of the five SAAs  for which ΔGrxn5=0.95 eV and 0.76 eV, respectively. On the other hand, the subsequent limiting step for PdAu is reaction 4 , for PdAg reaction 5 (ΔGrxn5=0.51 eV), and for PtAg reaction 4 (ΔGrxn4=0.51 eV). The pertinent ΔGrxnvalues are sufficiently low that they suggest fast kinetics. We therefore compute the O2* dissociation barrier for these materials to determine which pathway will be most feasible under ambient conditions.The key difference between the associative and dissociative four 2* dissociation transition states yield activation barriers of 0.71 eV for PdAg, 0.86 eV for PdAu and 0.77 eV for PtAg. Of these three SAAs, no material exhibits an O2* dissociation barrier that is lower than ηsuggesting that they will not facilitate ORR via the dissociative mechanism and bypass OOH* formation. Though the barriers for PdAg and PtAg are greater than the ηthat is dictated by the O2* reduction step, they are similar. Given the reduction of O2* to OOH* is unlikely to be a barrierless process, if we considered a small, approximate activation energy (i. e. 0 to 0.1 eV) then the kinetics of O2* dissociation and reduction would appear to be comparable. Thus, we predict that the kinetics of the associative and dissociative four e-pathways on PdAg and PtAg will be competitive, close to the equilibrium potential. At the equilibrium potential, the activation barrier for O2* dissociation on PdAu is 0.39 eV greater than ΔGrxn2for the rate limiting OOH* formation step and we suppose this to be sufficiently high for O2* reduction and the associative pathway to be dominant. Indeed for more negative potentials , the activation barrier will become increasingly greater than the thermodynamic limiting step and therefore the associative pathway will be more dominant.Our calculations of the O−reduction relative to hydrogen peroxide via the two e-pathway. ORR to water through the four e-pathway is more efficient, as the two e-pathway involves incomplete oxygen reduction that results in low energy conversion efficiency, as well as the formation of unwanted intermediate and radical species. On Pt, site blocking by H* adatoms combined with comparable free energies around the operating potential of OOH* reduction to H2O2 and OH* reduction to H2O mean that the two e-pathway is prevalent. Thus, we assess the thermodynamic selectivity of the four versus the two e-pathways on SAAs.A common issue with Pt‐based ORR catalysts is selectivity towards water via four eUT) determined in the previous section to determine the free energy landscape for each SAA operating at their most efficient potential . At UT, by definition all steps in the four e-pathway are thermodynamically downhill. We assess the selectivity by comparing the difference in free energy of reaction at UTfor the OOH* reduction step to H2O2 (ΔGrxnH2O2UT) and for the thermodynamically limiting step along the four e-pathway after the formation of OOH*  such that:We use the values of the thermodynamically limiting potential , as well as strong selectivity for four In our previous work, we simulated the temperature programmed desorption kinetics of CO from SAAs/PGMs and benchmarked the results against experiments.kTSTat 298.15 K for use in our KMC model here. Using KMC, we determine θCOacross a range of pCOand plot the resulting isotherms for Pt(111) and PdAu(111) in Figure θCOfor PdAu(111) is normalised with respect to the number of Pd active sites). Analysing the isotherms, we observe that Pt(111) begins to poison at pCOof 10−19 atm and is saturated by 100 atm. The Pt(111) isotherm also shows the formation of two CO adlayer phases, in excellent agreement with experiment.θCOon Pt(111) from experiment is obtained at approximately 6×10−10 atm and agrees very well with our simulated pCOof 10−10 atm.pCOof 10−9 atm leading to full saturation at 10−4 atm. Notably PdAu(111) SAA does not have ordered phases of CO on the surface due to the dispersion of the Pd dopant atoms negating any potential adlayer interaction effects.In order to illustrate the extent of CO poisoning resistance on SAAs compared to Pt(111), we use the CO adsorption energies on Pt(111), PtAu(111) and PdAu(111) from Ref. [18] and compute pCOthat corresponds to the onset of CO poisoning between Pt(111) and PdAu(111) SAA. Moreover, at the half‐maximum θCOpoint on Pt(111), PdAu(111) SAA remains pristine, indicating a significant increase in the CO tolerance of the latter over the former. Thus, Pt(111) active sites are much more likely to undergo poisoning than Pd sites in PdAu, which ultimately could result in comparable availability of active sites for both and therefore similar activities of these materials despite a 20–100 fold dopant atom dilution in the SAA.Comparing the isotherms, there is approximately 10 orders of magnitude difference in 2*, OOH*, O* and OH* on each SAA, demonstrating that isolated atoms of Ni, Pd, Pt, Co and Rh within the surface matrix of Au(111) and Ag(111) significantly increase the reactivity of their host metal. In general, we found that ORR intermediates bind most strongly to Co SAAs, closely followed by Ni and Rh, with Pd and Pt binding the weakest. Additionally, we determined that Ag based SAAs are more reactive towards ORR intermediates than their Au counterparts. Using the CHE model, we evaluated the potential dependence of ORR thermodynamics on SAAs in order to elucidate the selectivity of four e-over two e-reduction, as well as to yield ηas an activity metric. Our results indicate that SAAs, especially those with the lowest overpotentials, have significant thermodynamic bias for water formation via four e-reduction over hydrogen peroxide formation via two e-reduction, indicating they will be highly selective. Evaluation of η, the maximum potential difference from equilibrium at which all steps are thermodynamically downhill and a strong metric for ORR activity, predicts that the best performing SAAs are PtAu and PdAu with overpotentials that are slightly lower than model Pt(111). In view of these calculations the SAAs just noted will be as active as Pt(111) on an individual platinum group metal basis, though one may argue that the low density of these atoms in a SAA  will hamper the observed (apparent) activity. However, we demonstrate that a significant advantage of the PdAu SAA is its resistance to CO poisoning. Crucially, KMC simulations reveal that PdAu is tolerant to CO poisoning for partial pressures that are 10 orders of magnitude greater than for pure Pt, suggesting that during operation, the availability of active sites on each surface will be similar. Therefore, the predicted activity and selectivity of SAAs, along with the high tolerance to CO poisoning, constitute an exciting combination of desirable properties, which makes SAAs attractive for electrocatalytic ORR compared to the traditional Pt/C catalysts. Our theoretical investigations are thus expected to stimulate further research and pave the way towards the experimental synthesis and testing of these promising materials.In this contribution we have systematically studied the behaviour of 10 SAAs towards ORR intermediates. We have elucidated the most favourable adsorption configurations of OComparison of the potential Gibbs free energy diagrams obtained with PBE versus PBE−D3 for the four e‐ ORR on SAAs of Co, Ni, Pd, Pt and Rh doped into Ag and Au hosts.https://dx.doi.org/10.17172/NOMAD/2021.01.02‐1The DFT data of this paper can be accessed via: The authors declare no conflict of interest.As a service to our authors and readers, this journal provides supporting information supplied by the authors. Such materials are peer reviewed and may be re‐organized for online delivery, but are not copy‐edited or typeset. Technical support issues arising from supporting information (other than missing files) should be addressed to the authors.SupplementaryClick here for additional data file.


We conducted bulk stable-isotope analysis and lipid residue analysis on the charred food macro-remains, carbonized thin layer organic patina residues and absorbed lipids over the course of the experiment. Our results indicate that: (1) the composition of charred macro-remains represent the final foodstuffs cooked within vessels, (2) thin-layer patina residues represent a mixture of previous cooking events with bias towards the final product(s) cooked in the pot, and (3) absorbed lipid residues are developed over a number of cooking events and are replaced slowly over time, with little evidence of the final recipe ingredients.Chemical analyses of carbonized and absorbed organic residues from archaeological ceramic cooking vessels can provide a unique window into the culinary cultures of ancient people, resource use, and environmental effects by identifying ingredients used in ancient meals. However, it remains uncertain whether recovered organic residues represent only the final foodstuffs prepared or are the accumulation of various cooking events within the same vessel. To assess this, we cooked seven mixtures of C Meals are representations of the environment, revealing the resources that are harvested from local areas or shedding light on exchange networks4. The foods consumed can also represent the values of the people who eat them7, being often a smaller selection of what their environment has to offer, and reflecting specific culturally-based choices about what constitutes any item as “food”8. Analysis of the residues from cooking pots and other materials  can bring us one step closer to reconstructing the environmental and social circumstances of our ancestors1.The study of ancient cooking pots resonates with a fundamental aspect of what it means to be human—the transformation of raw ingredients into a meal is a shared human experience throughout history14. Chemical analyses of lipids absorbed into the fabric of unglazed pottery vessels (the primary residue form studied in archaeology), in conjunction with carbonized surface residues, including charred food macro-remains and deposited thin-layer patina residues, are lines of evidence towards understanding ancient culinary practices by potentially providing a direct reflection of the original contents of the ceramic vessels21. Carbonized food residues derived from the burning of food during cooking have been hypothesised to represent a snapshot of the foodstuffs cooked within the vessel. However, it is not certain whether these organic residues reflect only the most recent ingredients prepared in the vessel or if they are the accumulation of cooking events across the vessel’s use life. It is important to understand the relationship between the use of the vessel over its lifespan, and the residues ultimately extracted and analyzed.Culturally-driven food preferences and practices are often difficult to discern from archaeological datasets: while fragments of past cooking activities and meals may be recovered through archaeobotanical and zooarchaeological evidence, rarely are these lines of evidence sufficient to capture the entire range of plant and animal species that were prepared for consumption, or their relative importance  within a particular society and ecosystem context. Cooking practices can incorporate a diverse array of materials organic materials, hot stones, lithic tools, and more) and preparation techniques . Pioneering studies beginning in the 1970s demonstrated that organic residues recovered from archaeological materials retained aspects of their chemical composition24. This method allows broad assignment of the contributions of C3 and C4 plants, terrestrial, and aquatic foodstuffs to be assessed in these carbonized remains. Similarly, lipid residue analysis can be performed on both carbonized and absorbed residues25, which provides biomarker evidence for the natural products processed by people in the past26. The range of food-related commodities detectable in pottery vessels continues to increase, and currently includes: terrestrial animal products28, leafy vegetables29, specific plant oils31, beeswax32, cereals33 and aquatic commodities34.Such residues have been investigated using bulk carbon and nitrogen stable isotope approaches, with ingredient compositions determined using the principles applied in food web studiesδ13C values of carbonized residues and absorbed lipids, where the combination of analyses have provided complementary data to support conclusions regarding vessel use40. For example, both bulk δ13C values and individual fatty acid δ13C values can discriminate between habitats, such as terrestrial versus aquatic species , since marine species are 13C enriched41.Several studies have shown a correspondence between the bulk 43. Cooking methods and residue formation processes will also differentially impact the degree to which analyzed carbon and nitrogen reflect contributions from carbohydrates, lipids, and proteins. Equally, isotopic differences will exist between superficial residues composed of carbonized products (created by Maillard reactions and therefore predominantly carbohydrate and protein based) and absorbed residues (predominantly lipid based) due to the differences in composition of these residue types28. Differences in the inferred compositions of carbonized and absorbed lipid residues have also been hypothesised to represent different periods of vessel use 42. As noted in Roffet-Salque et al.4 “…the majority of analyses now target absorbed organic residues in unglazed ceramic vessels, which generally originate from the original contents that were either stored or processed in the vessels, representing either a single use or an accumulation of cooking events over a vessel’s lifetime” . However, there is currently limited data on lipid turnover as it has been assumed that lipids are absorbed over the lifetime of the pot, and little is known about turnover speed and timing in the ceramic matrix once lipids have been incorporated44. Our study aims to address how a pot’s cooking life history shapes its residues and the resulting chemical fidelity of the residues in comparison to the original ingredients47.Comparisons of lipid and bulk residue compositions can vary due to differential preservation of lipids and other food constituents in different sample types(i)Do surface residues (food crust macro-remains and thin-layer organic patina deposits) reflect a single cooking event, specifically the final use, or are surface residues a mixture of previous cooking events in that vessel?(ii)Do the stable isotopic values of macroscopic carbonized residues relate to the biogenic isotopic values of the original (first) ingredients cooked in the pot or the final ingredients prepared in the pot?(iii)Are absorbed lipid residues accumulated over the use lifetime of the vessel?(iv)Do absorbed lipid residues represent the early cooking history, becoming saturated after multiple cooking events, or indicate the final cooking event(s)?Here we report the results of a year-long cooking experiment (minimum of 52 cooking episodes per pot) designed to test the following research questions:The overall cooking experiment was performed over the course of one year, and comprised seven cooking experiments, with periodic charring episodes to mimic the conditions under which some archaeological food residues are recovered  and wheat . To explore the impacts of more complex recipes on carbonized and absorbed residue chemical and isotopic composition, ingredients were prepared in several combinations 2, also known as lime) are essentially the same, indicating the lime treatment of maize does not significantly alter the δ13C value (maize/hominy δ13C = – 11‰). Lovis et al.49 found that hominy prepared by combining maize with hardwood ash  could potentially alter δ13C values of resulting residues if the hardwood ash was not completely removed from the mixture . Previous studies have not explicitly attended to nitrogen isotope effects but our results show maize and hominy have slightly different δ15N values , suggesting that the process of creating hominy may have altered the nitrogen isotope ratio of the original maize and caused slight 15N enrichment in the hominy product. Similarly, Warinner52 reports no difference in δ13C values between raw and nixtamalized maize but found similar changes to δ15N values: raw dried maize average δ15N value =  + 3.6‰ ± 0.8‰, while the nixtamal maize average δ15N value =  + 4.2‰ ± 0.4‰, showing the same ~ 0.6‰ offset between untreated and lime-treated maize as our experiment. Alkaline processing of maize is known to alter the protein structure of the resulting hominy (amongst other changes), perhaps shifting the isotopic composition, which in turn may have downstream effects on organic residues and consumer isotopic values; these aspects of nixtamalization should be considered and studied further53.Our ingredient reference materials exhibited re Table . Few stuδ13C value typical for a C3-plant (– 26.4‰) and has the lowest δ15N value at + 1.4‰. The difference in δ15N values between maize and wheat largely relates to the different environments where these crops were grown 56. The deer meat δ13C value is consistent with a wild deer diet of C3 plants (δ13C = – 26.9‰). The deer meat displayed the highest δ15N value (δ15N =  + 4.9‰) which reflects the isotopic average of the C3 plants the deer consumed during life plus a trophic enrichment factor of ~  + 3–5‰58.The wheat flour has a δ13C and δ15N values of the charred macro-remains from the burned foods cooked over the experimental timeframe are reported in Table δ13C values of their respective recipe ingredients60. Charred macro-remain δ13C values also remain consistent with ingredient δ13C values after the recipe was changed  to maize (C4) or vice versa . For example, δ13C values of carbonized macro-remains for experiment GT shifted from – 11 to – 26‰, concurrent with the shift from a 100% hominy to a 100% wheat-based recipe.The ged Fig. . This is3 and C4 foodstuffs (e.g. CH1) display an isotopic signature (ca. – 18‰) consistent with a 50:50 mixture of the C3 (– 26‰) and C4 plants (– 11‰). Similarly, experiment JS1 comprised a recipe of 25% maize and 75% wheat, and the resulting carbonized macro-remains exhibited a δ13C value around –23‰, which is roughly equivalent to a 25% shift in δ13C value towards C4 plant values. This is also observed in the 75% maize, 25% deer meat mixture (AM1) where the carbonized residues exhibit δ13C values ranging from – 16 to – 11‰ (average δ13C = – 14‰) consistent with a 25% shift in δ13C values towards those displayed by C3 plants and wild deer. We observed no difference in the δ13C values of residues produced by processing maize in different forms, i.e. ground, whole and hominy.Charred macro-remains of recipes involving mixtures of Cδ15N values of the charred macro-remains generally display similar δ15N values to their respective recipe ingredients but show a slight positive offset, implying fractionation caused by heating, wherein the charred product becomes enriched in the heavier 15N isotope60. For example, experiments MM1 and KV1 used 100% maize flour, and their carbonized residues displayed average δ15N values =  + 4.3‰, which is + 0.5‰ higher than the raw maize flour value. In almost all experimental conditions we see significant changes in the charred macro-remain δ15N values after the recipe changed (sample collections 9 and 10), which are consistent with δ15N values of newly introduced ingredient(s). No change in δ15N values are observed in experiments KV2 and MM2 due to the similarity of deer and maize ingredient δ15N values (+ 4 to + 5‰). As observed for the δ13C values (above), the most pronounced changes in δ15N values occur in experiments with 100% recipe swaps  to δ15N =  + 2‰ . Also consistent with trends in δ13C values are δ15N values of charred macro-remains from recipes with mixtures of C3 and C4 foods , which reflect a mixing of the recipe ingredients. For example, the mean δ15N value of CH1 is + 2.9‰, consistent with a 50:50 mixture of maize (δ15N =  + 3.8‰) and wheat (δ15N = 1.4‰) plus a slight increase in 15N likely due to heating effects. After the recipe swap, the δ15N values of charred macro-remains from CH2 became more elevated (δ15N =  + 4‰), which is consistent with the recipe switch to 100% maize. For experiment AM, we only observed a slight change in δ15N values when deer (AM1) was replaced with wheat (AM2), despite their difference in δ15N values; there was only a slight depletion from + 4.9 to + 3.8‰ after the change from 75% hominy/25% deer to 75% hominy/25% wheat flour. This is likely because hominy has a high δ15N value similar to the deer, and in AM2 hominy is still the dominant ingredient and therefore skews the δ15N value of the charred macro-remains sample towards that ingredient.The δ13C and δ15N values predominantly reflect the final recipe but chemically hints of the previous recipe remain. Our initial hypothesis was that patina residue 1 (corresponding to charred macro-remain sample collection 8) would accurately reflect the original recipe ingredients and that subsequent sampling of this patina residue layer after the recipe change (sample collections 9 and 10) would display a complete chemical shift (“over-write”) to the isotopic values of the new ingredients. Instead, we see more variability in this carbonized patina residue, with values reflecting both the final ingredients and previous ingredients prepared in the pot  closely reflects the primary recipe isotopic values, patina residue 2 (sample collection 9) has intermediate isotope values but is generally closer to the final recipe, and patina residue 3 (sample collection 10) is closer still to the final recipe ingredients. For example, experiment GT1 began with 100% hominy, and patina residue 1 (sample collection 8r) displays δ13C and δ15N values that are very close to those of the charred macro-remains . Between collection 8 and 9, experiment GT2 switches recipes to 100% wheat flour (an ingredient shift from C4 to C3) and patina residue 2  displays significantly lower δ13C and δ15N values, though not as low as the charred macro-remains  displays further reduction in δ13C and δ15N values, this time with the effect more significant in δ13C value  contact with the pot’s inner surface, often observable on archaeological pottery) show a more complex picture of cooking events and the relationship between original recipe ingredients Fig. ; Table 3pot Fig. . Therefo61) to see how the bulk isotopic values would be interpreted given the known ingredients (sources) and known quantities in the recipes (see Supplementary Methods and Supplementary Table 2 and FB2 experiments (recipes comprised 100% wheat after months of cooking 100% hominy/maize), we see that those residues were estimated to be 95–100% wheat and only 0–5% hominy/maize . The IsoSource mixing models also generally returned good estimations for recipes with C3/C4 mixtures . For example, the JS1 recipe comprised 3:1 wheat to maize, and the mixing model generally estimated 75–80% wheat and 20–25% maize for those corresponding macro-remains. The JS2 recipe then switched to 100% maize, and the resulting mixing model estimates for those macro-remain samples were 95–100% maize and 0–5% wheat.We ran the isotopic results from the charred macro-remains and the organic patina residues through a basic mixing model  was estimated by IsoSource at 95–100% maize and 0–5% wheat, . The recipe then changed for FB2 to 100% wheat, and the following patina residue (FB_9r) was estimated to have 65–75% maize and 25–35% wheat, followed by further cooking of the FB2 recipe and another organic patina sample (FB_10r), which was estimated to have 30–45% maize and 55–70% wheat. We see the declining influence of the previous ingredient (maize from FB1) in the organic patina residue over time. Therefore, the mixing model results also support the interpretation that patinas reflect multiple cooking events and do not reflect the very final ingredients prepared in the pot. We did find that deer meat was over-estimated by the mixing model when it was a source along with wheat . Heavy burnishing on the interior surface of the vessel may also have intensified this by interfering with the absorption of lipids into the pottery fabric, further experimental work should examine different pottery treatments to better characterize these relationships62. The TLEs from wheat-based experiments were dominated by C16:0, C18:1 and C18:2 fatty acids  of carbon chain length C14 to C30 were detected in the majority of the TLEs. Due to low concentrations of C16:0 and C18:0 fatty acids it was not possible to determine stable carbon isotope values for all lipid components. Therefore, C16:0 fatty acid was chosen to determine the isotopic composition of the absorbed residues as it is common to all food ingredients and would enable the contributions of C3 and C4 plant lipids to the TLEs to be clearly distinguished.Acid-extracted lipids from the pottery fabric were analysed by gas chromatography (GC) and GC-mass spectrometry (GC–MS) to enable quantification and identification. Lipids were recovered from 24 of the 32 cooking experiment total lipid extracts (TLEs) analysed (75%). Low lipid recovery was likely a result of two factors; the lipid content of plant-based food generally is at least tenfold lower than that of meat, and plant lipids are poorly mobilised resulting in limited transfer to the pot matrix . This was likely due to changes taking place during the nixtamalization process but it is unclear how this has occurred49.The TLEs were subsequently analysed using GC-combustion isotope ratio-MS (GC-C-IRMS) in order to determine the isotopic composition of the absorbed lipids Table . In ordeδ13C16:0 values of –34.2 ‰ and –33.4 ‰, respectively. The deer meat δ13C16:0 value was –33.5 ‰ which is consistent with the animal having lived in a C3 environment. The δ13C values of the C16:0 fatty acids from cooking experiments with an 100% C4 to C3 recipe swap (FB and GT) exhibit a shift in δ13C values towards the values of the wheat cooked after the recipe swap .This isotopic difference is also observed in experiments with mixtures of foods of differing isotope values (e.g. CH) where the 50% wheat, 50% maize mixture does not have a consistent isotopic value across time Table . This isδ13C16:0 values across the first three fabric samples in experiments  indicates that the lipids are incorporated into the vessel wall over time as the δ13C values do not immediately reflect their reference materials (ingredients) after the initial cook, but instead shift towards the δ13C16:0 of the ingredients from fabric sample 2 onwards. After the recipe swap the δ13C16:0 values show a small but gradual shift towards the isotopic value of the “new” foodstuffs. The more extreme shift in δ13C16:0 value observed in experiments containing deer meat is likely due to the higher lipid content of meat relative to plants, making this overprinting more pronounced63.The results from the compound-specific analyses of the absorbed lipid residues demonstrate that lipids retained within the ceramic fabric reflect the lipid composition of commodities cooked within the vessel. A shift in the isotopic composition of 33. The characteristic cereal lipids were identified in reference wheat  and 396.3756 (trimethylsilylated sitosterol and sitosterol fatty acid esters). Maize did not contain any alkylresorcinols, yet, contained plant sterols identical to those detected in the reference wheat, making analytical discrimination challenging. However, it was found that both the ratio of free to esterified sitosterol and the ratio of C16 to C18 fatty acid esters was distinctly different in wheat and maize . Both the presence (or absence) of alkylresorcinols and the pattern of free and esterified sitosterol were used to identify absorbed lipids deriving from wheat or maize in ceramics from cooking experiments.Total lipid extracts of maize and wheat were analysed by GC and GC/Quadrupole-Time of Flight MS (GC/Q-ToF MS) in order to identify characteristic lipids that could be used for their identification in the absorbed residues from the cooking experiments Table . Recentl16 to C18 esters of ca. 100:15 was comparable to the ratio observed in the wheat reference. In the TLE JS #8  the ratio of free to esterified sitosterol was about 2:1, which clearly represented a mixture of the ratios found in the pure wheat and maize references  after the recipe change. Finally, the biomarker pattern observed in the TLE from the cooking experiment using 100% hominy  corresponded with the pattern observed in the maize reference runs  no alkylresorcinols and only free sitosterol were detected, which reflected the absence of alkylresorcinols and low proportions of esterified sitosterol in the reference maize Table  online. 47.Comparing the respective changes in isotopic composition of the charred macro-remains, carbonized thin-layer patina residues, absorbed lipid residues, and the presence/absence of characteristic plant lipids across the year-long cooking experiment has enabled a better understanding of absorbed and surface residues during the use-life of ceramic cooking vesselsδ13C and δ15N values of charred macro-remains generally reflect the ingredients of the final foodstuffs that were cooked in the vessel. After changing recipes, δ13C values of these burned food crusts accurately reflect the ingredients of the new recipe. The δ15N values also shift towards but do not entirely reach the values of the new recipe. Bulk analyses of charred macro-remains therefore closely represent the last foods that were cooked within the vessel rather than an accumulation of the foodstuffs cooked over the lifetime, or recent life, of the pot. These findings are in accordance with other studies of bulk δ13C and δ15N values from charred plants64. Early work by DeNiro and Hastorf59 indicated that charred ancient plant remains retained their isotopic values , and further studies by Fraser et al.60 and Styring et al.65 and others, found no significant systematic changes to δ13C values in charred cereals and pulses, and small (< 1‰) changes to δ15N values. Recently, Szpak and Chiou66 found that under particularly favourable taphonomic conditions, some desiccated but uncharred ancient plants may also retain their biogenic bulk isotopic values. Further studies of organic residues recovered from environments such as those of the north coast of Peru may indicate that those conditions are favourable for the survival not only of bulk isotopic values but of many resource biomarkers despite hundreds to thousands of years of time elapsing66.The δ13C and δ15N values of carbonized adhering organic patina residues are far less likely to represent only the final ingredients cooked in the pot. We believe this would be particularly true in culinary contexts where individual vessels have multiple purposes, or where a wide range of ingredients  are utilized in a variety of combinations over the use-life of the vessel. While the patina residues are influenced by the final foods cooked, these patina residues may also retain chemical signatures of ingredients from previous cooking/charring events. It is therefore critical for archaeologists to carefully consider the use life of a ceramic vessel and its surrounding ecological context: not all superficial carbonized residue layers—and indeed likely very few—reflect a single depositional charring event (i.e. the last supper).Unlike the charred macro-remains, the Lipid biomarker analysis demonstrates that the lipids absorbed into the vessel wall correspond to a gradual overprinting of the lipids from previous cooking events. Notably, although the ratios of different lipid components clearly shifted after a recipe change, they did not fully reach the typical values of the pure newly added foodstuff, even after several additional cooking events. This demonstrates that a slow replacement of lipids took place over sequential cooking events, but the absorbed lipids still represented a mixture of the commodities cooked over the history of vessel’s use and were not only indicative of the most recently processed foodstuffs. Further experiments are required to determine whether lipids are replaced entirely with subsequent cooking events.In summary: (1) bulk stable isotope analysis of carbonized food macro-remains represent the last foods cooked within the vessel; (2) bulk stable isotope analysis of the carbonized adhering organic patina residues represent a palimpsest of previously cooked ingredients but are strongly skewed towards the final recipe. The stable isotope values of these organic patina residues were slower to change over time than the more substantial carbonized macro-remains; (3) the absorbed lipids within the ceramic matrix are not immediately replaced by the new recipes. Instead, lipids are replaced slowly, over time, and represent a mixture of the ingredients cooked during the vessel’s use-life. These three different residue types reveal cooking events across different time scales: the lipids absorbed into the pottery walls reveal the pot’s use history, the carbonized surface thin-layer patina shows a mixture of the most recent few cooking events, and the most superficial samples, the charred macro-remains, show the final snapshot of the ingredients last cooked (burned) in that vessel.44. However, experiments such as this one contribute to our ability to quantitatively understand residues better: known ingredients prepared in specific proportions help us understand the resulting residue data. This knowledge can then be applied in archaeological settings . Our results indicate that charred macro-remains have the potential to tell us both qualitative and quantitative recipe ingredient information, while absorbed residues demonstrated more timescale variability and are thus more amenable to qualitative interpretations. This information could be particularly important in estimating the lifespan of a pottery vessel (of which very little is known) especially if used in conjunction with compound-specific radiocarbon dating of both absorbed lipid and carbonized residues67.We propose that these different residue forms present unique opportunities for archaeologists to study the various resources that may have been used across multiple time-scales within a cooking vessel’s use history. The chemical data from these residues highlight different dietary components (emphasizing carbohydrates and proteins in surface residues and lipids in absorbed residues), and therefore using them in conjunction offers a potentially more robust and more complex picture of ancient food practices. Most studies of organic residues have used biomarkers in the qualitative sense (i.e. using presence/absence of specific compounds to indicate the inclusion of particular ingredients in the past) without significant reflection or interrogation of the timescale and events under which those residues were formed, and whether or not they represent the lifetime use of the potThe residues tested here were derived from a subset of potential cooking, processing, and storage practices that people utilize, and this research specifically focused on residues formed within one material type (ceramics) by specific methods, boiling and “accidental” charring, and for a predetermined use life (1 year). Therefore, the results presented here may be specific to residues created in clay pots over a particular duration, and residues extracted from other materials or formed under other preparation methods may or may not follow the same patterns. For example, we still do not know how many cooking events are required to completely change the lipid signature of a pot and thus cannot differentiate between a pot that has been used to process one foodstuff its entire life or if its function was changed and the lipids completely replaced. Further experimental studies are recommended to understand how residues form on other materials and under different conditions  over variable periods of time.3 foods within the same recipe and mixtures of terrestrial and aquatic foods) to provide further qualitative and quantitative information for interpreting organic residues from archaeological specimens. We hope that future studies examining archaeological pottery sherds and other materials will aim to retain these various residue deposits  so as to further unlock these different scalar residue records and potentially provide greater insights into human subsistence practices and resource use in the past.The findings we report here indicate the value of experimental archaeological projects, and additional studies should expand on the range of ingredient combinations  as well as a mixture of previously utilized ingredients . These results in turn can complement other lines of archaeological and paleoenvironmental evidence including faunal, macro-and micro-botanical remains to provide new insight not only into ancient culinary practices, but also how past food procurement and production strategies integrated and adapted to local environments. Past human subsistence strategies have generated lasting, interconnected transformations to global environments72, and archaeological studies of human foodways through residue analyses can make important contributions to understanding resource use in the past. Interpreting archaeological dietary proxies requires careful consideration of material use-life including pre- and post-depositional processes. Controlled “middle-range” studies, particularly long-term experiments designed to mimic the full duration of an object’s use-life, enhance our interpretations of the ‘residues’ of human activities left behind in the archaeological record.Combined isotopic and biomarker analyses on both carbonized and absorbed residues from the same vessel can refine archaeological interpretations regarding vessel use and culinary practices by providing a chemical signature of the ingredients used in the pot’s final meal (Zea mays L.) and USDA Certified Organic whole hard red winter wheat kernels (Triticum aestivum L.). Maize and wheat grains were ground to flour in a  grain mill (NutriMill). Portions of the maize kernels were left whole and others were prepared as hominy. The hominy processing involved soaking whole maize kernels with water and food-grade lime  for 8 h, warming the mixture over low heat for 4 h, rinsing the hominy in water, followed by transferring into plastic bags which were frozen and used over the course of the experiment. Meat from a young deer  was donated by the University of California, Santa Cruz (UCSC) Laboratory of Anthropology, from which 7 cups (1.5 kg) of venison were utilized (taken from different parts of the body of the deer). All dry ingredients were stored under cool and dry conditions, while the venison and hominy were stored in a freezer until required for cooking. Uncooked primary ingredients were reserved for chemical analyses and included ground maize, ground wheat, hominy and deer meat.The grains utilized in this experiment were USDA Certified Organic dried whole maize kernels  had sufficient ingredients to continue with the cooking regimen and in these cases the foodstuffs were cooked twice more without burning  followed by a cooking event in which the foods were charred and a 10th charred food residue was collected. Therefore, 8 charred food macro-remains were collected from the primary recipe and followed by 1 or 2 additional charred food crusts from the final (changed) recipe, depending on ingredient availability.All recipe information is provided in Table During the later stages of the experiment, it was noted that a thin, finely textured carbonized layer (organic patina) visibly adhering to the pot’s interior surface had accumulated across cooking episodes, particularly at the base of the pot  using a Vario Isocube Elemental Analyzer coupled to an IsoPrime 100 isotope ratio mass spectrometer (IRMS). Stable isotope values for the ingredients are reported in Table δ13C = – 25.9‰; δ15N =  + 2.1‰) and additional quality control standards were analyzed including IAEA-CH-6 sucrose (δ13C = – 10.45‰), bovine liver , and spirulina . CSIB reports long-term isotopic precision data to be ± 0.1 ‰ for δ13C values and ± 0.2‰ for δ15N values. A sub-set of samples were analyzed in replicates to assess homogeneity and intra-sample error and are reported as the average values in Table The charred food macro-remains and the adhering thin, organic patina carbonized residues were freeze dried, weighed into tin capsules and their 73. Recovery of cereal lipids followed the procedure outlined in Hammann and Cramp33. Briefly, a known amount of internal standard  was added to approximately 50 mg of the powder, then the lipids were extracted using 5 mL of 4% sulfuric acid/methanol solution  or using CHCl3:CH3OH with sonication for recovery of cereal lipids. Total lipid extracts (TLEs) were trimethylsilylated before gas chromatography (GC) in order to determine the lipid concentrations. The samples with detectable organic components were further analysed using GC-mass spectrometry (GC–MS) and GC-combustion-IRMS (GC-C-IRMS) in order to identify the presence and isotopic composition of lipids (full methods are presented in Supplementary Methods online).Throughout the cooking year, at least four interior pottery fabric samples were taken for absorbed lipid and compound-specific carbon isotope compositions. The ceramic fabric samples were taken at the beginning of the experiment , mid-way through the experiment , at the end of the experiment when the primary recipe was cooked a final time , and after the recipes were changed . Ceramic fabric samples were taken from the body of the pot, from the upper limit of where the ingredients reached when they were being cooked  materials and recipes in order to provide calibration points, for use in assessing the extent of mixing or replacement of lipids within the pottery vessels. Additional compositional analyses were performed using high temperature GC-high resolution MS to provide additional biomarker evidence for the impacts of cooking of different foods on the formation of organic residues.Supplementary Information.


When using physiologically relevant concentrations of nine estrogenic/anti-estrogenic compounds, including five SERMs, we observed no significant modulation of PCa cell proliferation. Using RNA-seq and validated antibodies, we demonstrate that these PCa models do not express ERs. In contrast, RNA-seq from PCa samples from patients have detectable expression of ERα. Overall, our study reveals that commonly used PCa models are inappropriate to study ERs and indicate that usage of alternative models is essential to properly assess the roles of the estrogen signaling pathway in PCa.The estrogen signaling pathway has been reported to modulate prostate cancer (PCa) progression through the activity of estrogen receptors α and β (ERα and ERβ). Given that selective estrogen receptor modulators (SERMs) are used to treat breast cancer, ERs have been proposed as attractive therapeutic targets in PCa. However, many inconsistencies regarding the expression of ERs and the efficacy of SERMs for PCa treatment exist, notably due to the use of ERβ antibodies lacking specificity and treatments with high SERM concentrations leading to off-target effects. To end this confusion, our objective was to study the impact of estrogenic and anti-estrogenic ligands in well-studied  Furthermore, it is also now known that AR is an important regulator of metabolic pathways that sustain aberrant proliferation of PCa cells6. Accordingly, current hormonal treatments target this receptor with the objective of inhibiting its functions, with anti-androgens or androgen deprivation therapies7. However, despite a positive response to these treatments initially, progression of the disease to castration-resistant PCa (CRPC) is mostly inevitable7. This highlights the need to find novel approaches for the treatment of PCa.In the context of prostate cancer (PCa), the androgen receptor (AR) has many oncogenic functions such as increasing the proliferation and survival of cancer cells2) are naturally produced from androgens through steroidogenesis and have been linked to PCa evolution, as reviewed recently by Dobbs et al.8. Indeed, it has been demonstrated in murine models and in human patients that increased levels of estrogens were positively correlated with the aggressiveness of PCa15, and that estrogen synthesis increases in cancer cells during disease progression20. This modulation of cancer evolution is thought to be caused by the activity of the estrogen receptors ERα and ERβ, two transcription factors that are both essential for the normal development of the prostate23. The actual model supports that ERα has oncogenic functions, as seen in murine models where its activation leads to an increased proliferation of cancer cells26; on the other hand, ERβ is thought to act as a tumor suppressor since its loss promotes prostate hyperplasia and the development of the disease30. Further supporting this model, ERα expression is reported to be increased and ERβ to be decreased during PCa progression37. These findings suggest that targeting the estrogen signaling pathway could be a viable therapeutic avenue for the management of PCa and CRPC.Estrogens and the most active form estradiol . As their name implies, they have the interesting capacity to be antagonist or agonist of the ERs in a tissue-specific manner; for example, tamoxifen is an antagonist of ERα in the mammary gland and breast cancer cells, but is an agonist in other peripheric tissues, such as the bone, thus limiting adverse side-effects of estrogen blockade throughout the whole body39. Importantly in the breast cancer field, assessing ERα expression levels in patient tumors is always performed prior to the selection of anti-estrogen therapies, as the presence of the receptor is tightly linked to the patient’s response. In the context of PCa, a few clinical studies using these compounds were conducted with limited sample sizes, and both null and positive responses were observed45. However, no initial molecular characterization have been performed in these studies, such as ERα and ERβ expression or activity in prostate tumors, explaining—at least in part—the discrepancies and the heterogeneity in patient responses.Several anti-estrogen therapies are currently in use for the treatment of ERα-positive breast cancer tumorsin vitro PCa models are appropriate to study ER functions, but they have still been inconsistently used in this context. For example, it has been known for decades that LNCaP cells—the most widely used human PCa model—have a mutated AR that can be activated by E2 in addition to androgens47 and have low, if any, expression of both ERs49. Nevertheless, several groups used this model to study E2 impact on PCa cell proliferation and survival52. In addition, the lack of specific ERβ antibody, as clearly described recently54, has also lead to controvorsies in the literature regarding which PCa cell line models express or not ERβ. Finally, specific ligands for both ERs exist, such as PPT for ERα and DPN for ERβ. Yet, precise dosages have to be used to keep this specificity, as higher concentrations will lead to dual activation of ERs or modulation of other pathways. For example, the EC50 of DPN is of 66 nM and 0.85 nM for ERα and ERβ , no expression of ERβ and weak but detectable expression of AR .We also used RNA-seq data from 3 of these cell lines and from patient biopsies to analyze expression of the SR1 Fig. . In compseq Fig. . ESR2 mRin vitro models, it is hard to reconcile with previously published results that showed decreased proliferation and survival of these cell lines following treatments with various SERMs. These studies, as reviewed in the introduction, mostly used high concentrations of SERMs, often 100 to a 1000 times over their selectivity for ERs, suggesting that the observed effects were due to off-target effects. In that context, we wanted to specifically delineate the impact of estrogens and SERMs treatment on PCa cells by using specific ERα and ERβ ligands and SERMs at concentrations specific to ERs to mimize off-target effects.Given the lack of detectable expression of ERα and ERβ in most PCa 48. These cells have been widely used to study the estrogen-dependent growth of breast cancer as well as to test anti-estrogen treatments. To validate that the different ERα ligand concentrations were biologically relevant, we used this model to optimize our proliferation assays using estradiol (E2), the ERα-specific ligand PPT, the ERβ-specific ligand DPN, five distinct SERMs that show anti-estrogen activity in breast cancer cells, and fulvestrant, a pure anti-estrogen that show antagonist functions of both receptors in all tissues tested.We first used MCF7 cells as controls to optimize treatments, as they are well-established in the breast cancer field to harbour high expression levels of ERα and no detectable expression of ERβ, and to be highly sensitive to estrogen stimulation2 significantly increased MCF7 cell proliferation  nor the anti-estrogenic compounds had a significant impact of PC3 cell proliferation and survival after 4 days of treatments when compared to vehicles. Our results indicate that even if ERα is expressed at low levels in PC3 cells, it does not contribute to cell proliferation in standard in vitro culture conditions.We then studied two AR-negative PCa cell lines, namely PC3 and DU145 cells. Contrary to MCF7 cells, Ells Fig. , in linells Fig. , we obse65. LNCaP cells have high AR expression and depend on its activity for proliferation, while LAPC4 and 22Rv1 are considered as androgen-sensitive cell lines, i.e. that do not depend on AR for proliferation but that are positively stimulated by androgens.Then, we studied three AR-positive PCa cell lines, namely LNCaP, LAPC4, and 22Rv1 PCa cells. They were all isolated from patients with castration-resistant PCa2 besides androgens47. Thus, as expected, E2 significantly increased LNCaP cell proliferation compared to controls , located at the plasma membrane and not part of the nuclear receptor family like the ERs, was not investigated in this study. Although it can also be activated by E80. A few clinical trials have tested toremifene in that context, which revealed well-kept bone mineralization in patients taking this SERM combined with anti-androgen therapy84. Interestingly, the significant decrease of proliferation induced by this SERM only occurred in 22Rv1 cells, which express high levels of AR-V7. Considering that E2 had no significant effect on proliferation , two AR-negative PCa cell lines (PC3 [RRID: CVCL_0035] and DU145 [RRID: CVCL_0105]) and three AR-positive PCa cell lines . All of them were initially obtained from ATCC, were kept in culture for no more than 3 months after resuscitation and were tested every 4 months for mycoplasma presence. They were grown in phenol red RPMI media supplemented with 10% fetal bovine serum (FBS), penicillin, streptomycin, and sodium pyruvate, and kept in incubators at 37 °C and 5% CO5 before analysis by Western Blots. The primary antibodies used were to detect α-tubulin , AR , ERα  and ERβ . Complete Western Blot figures are shown in Supplemental Fig. To evaluate the protein expression of the receptors, cell lysates of all cell lines were harvested in Buffer K supplemented with protease and phosphatase inhibitors as previously describedERS1 gene in LNCaP and LAPC4 cells85. Briefly, cells were seeded for 48 h in RPMI 1640 media without phenol red and with 5% CSS for steroid deprivation. They were then treated for 24 h with 10 nM R1881 or vehicle (96% EtOH) before being harvested for RNA purification and sequencing. We used the same protocol for 22Rv1 cells and after sequencing they were processed as described previously to obtain transcripts per million (TPM) values. In short, FastQC was used for raw sequencing data quality control86 and Trimmomatic was used to trim adaptor and over-represented sequences87. Pseudoalignement to the transcriptome (hg38) was then performed using Kallisto88 and samples were visualized using the UCSC genome browser. Results were then converted to bedgraphs before being loaded in the UCSC genome browser for visualization.RNA-seq data we previously generated were used to study mRNA expression of ERα, encoded by the 50/IC50 specific to each compound, except for tamoxifen and toremifene  and incubated for 48 h to allow steroid deprivation. Media was then renewed (100 μL per well) and treatment was added. The chosen treatment concentration for estrogenic/anti-estrogenic compounds and SERMs correspond to 5-fold the ECet al.89 was used to stain the cells in order to determine cell number after treatment. Media was firstly removed, then 50 μL of a 0.5% crystal violet solution was added in each well. The plates were left on a rocking bench for 30 mins at room temperature, rinsed thoroughly 4 times with water, and left to dry at least 48 h (protected from light). The stained cells were then lysed by adding 200 μL of SDS 2% in each well, and the plates were left on a rocking bench for 4 h at room temperature. The plates had their optical density (OD) measured at 570 nm using a spectrophotometer. OD values were converted into cell numbers by using standard curves specific to each cell line.The crystal violet assay developed by Feoktistova Given weaker adherence of LAPC4 and LNCaP cells, the CyQUANT Cell Proliferation Assay Kit  was also used to confirm proliferation assays. After treatment, media was removed from wells, then the plates were frozen at −20 °C at least 24 hours before analysis using the manufacturer’s instructions. The plates were then thawed, and a solution of CyQUANT was added in each well containing cells. The plates were incubated in the dark for 5 minutes, and the fluorescence was measured at 480 nm of excitation and 520 nm of emission using a spectrophotometer. Fluorescence values were converted into cell numbers by using standard curves specific for each cell line.post-hoc tests were performed using XL STATS.Proliferation assays were done at least 3 times independently for each cell line, with 4–8 biological samples per group per experiment. To test for statistical significance of estrogenic, anti-estrogenic, and androgenic treatments, one-way ANOVA with Tukey HSD and Dunnett’s Supplementary information.


Lake Baikal (Siberia) is the world’s oldest and deepest lake and a UNESCO World Heritage Site. Containing an exceptionally high level of biodiversity and endemism, in addition to a fifth of global freshwater not stored in ice sheets, the lake has been cited by UNESCO as the “most outstanding example of a freshwater ecosystem.” Using geochemical and climate data, we demonstrate that rates of nutrient supply to the lake’s photic zone have risen to unprecedented levels in the last 2,000 y through the 20th and 21st centuries. Linked to increases in wind speed enhancing deep ventilation, we show that these changes are capable of altering lake primary production and community dynamics, including the balance between endemic and cosmopolitan species. Lake Baikal, lying in a rift zone in southeastern Siberia, is the world's oldest, deepest, and most voluminous lake that began to form over 30 million years ago. Cited as the “most outstanding example of a freshwater ecosystem” and designated a World Heritage Site in 1996 due to its high level of endemicity, the lake and its ecosystem have become increasingly threatened by both climate change and anthropogenic disturbance. Here, we present a record of nutrient cycling in the lake, derived from the silicon isotope composition of diatoms, which dominate aquatic primary productivity. Using historical records from the region, we assess the extent to which natural and anthropogenic factors have altered biogeochemical cycling in the lake over the last 2,000 y. We show that rates of nutrient supply from deep waters to the photic zone have dramatically increased since the mid-19th century in response to changing wind dynamics, reduced ice cover, and their associated impact on limnological processes in the lake. With stressors linked to untreated sewage and catchment development also now impacting the near-shore region of Lake Baikal, the resilience of the lake’s highly endemic ecosystem to ongoing and future disturbance is increasingly uncertain. Ancient lakes have long been associated with both high levels of biodiversity and endemicity. However, they are also being threatened by anthropogenic forcings that have led to impacts ranging from the warming of lake waters , hydrolo30Sidiatom), we show that nutrient supply to the surface waters of Lake Baikal has rapidly increased through the 20th and 21st centuries coincident with increased wind-driven Ekman transport and reduced ice cover. These changes in photic zone nutrient availability have the potential to alter resource competition and prey–predator interactions across the lake  are supplied to the photic zone and the rates at which the same nutrients are utilized by diatoms . An increase (decrease) in δ30Sidiatom could therefore be driven by the following: 1) an increase (decrease) in biogenic silicic acid utilization due to the isotope fractionation associated with this process; 2) a decrease (increase) in nutrient supply to the photic zone, which replenishes the pool of nutrients and their isotope composition; or 3) a combination of these two processes, with their relative magnitudes determining the direction of change in δ30Sidiatom . These two parameters can be constrained from δ30Sidiatom using modern Lake Baikal values that account for the δ30Sidiatom fractionation factor   , and bio30Sidiatom follow rates of silicic acid utilization, which predominantly varies from 70 to 90% . Rates in the 20th and 21st centuries  are lower than during the Little Ice Age (LIA) from 1180 to 1840 CE  (P < 0.05) and Dark Ages Cold Period (DACP) from 500 to 750 CE , but similar to the Medieval Climate Anomaly (MCA) from 880 to 1180 CE  (P < 0.001)  B. Eviden = 6.6%) . By cons< 0.001) C and D. < 0.001) C, the ra2⋅m−2⋅y−1; 93 mmol NO3−⋅m−2⋅y−1; 5 mmol P⋅m−2⋅y−1)  and the persistence of a fully oxygenated water column  also supply nutrients to the lake, but due to the long residence time of both waters and nutrients in Lake Baikal these inputs represent only a fraction of all nutrients annually cycled within the lake 2) also se Baikal , it is ue Baikal , 12, thiCrateriportula inconspicua and Cyclotella minuta , with breakpoint analyses and generalized additive models (GAMs) indicating a significant escalation from the 1970s onward  and cosmopolitan Ulnaria acus , trends that are mirrored elsewhere across the lake  and BAIK13-4  were collected from the south basin of Lake Baikal in March 2013 using a UWITEC corer with PVC-liners (Ø 63 mm) that enabled undisturbed recovery of material at the sediment/water interface . Cored t210Pb-derived age models for core BAIK13-1C and BAIK13-4F have previously been published covering the last ∼150 y (14C) dating was completed on two samples at BAIK13-1C and one sample at BAIK13-4F. All 210Pb and calibrated 14C dates were then combined to create a new Bayesian radiocarbon age model for each site using Bacon (SI Appendix).Well-constrained t ∼150 y . To exte2O2, alongside sodium polytungstate heavy liquid separation at specific gravities of ∼2.2 g/mL, used to remove nondiatom contaminants  agreeing well with the published consensus value   of cleaned diatom samples and subsequent cation exchange  followed existing methodologies . Samples.2‰, 2σ) .2CO3) solution, designed to minimize dissolution of aluminosilicates, aliquots were taken after 5 h and analyzed for dissolved silica using colorimetric determination. Replicate analyses of sample material indicated an analytical reproducibility of 0.49%. BSi MARs were then calculated using dry bulk density and sediment accumulation rates for the core.In line with previous work on Lake Baikal, BSi concentrations were measured on samples from BAIK13-1C at 0.2-cm resolution using a single-step wet-alkaline digestion technique. Following digestion of 30 mg of freeze-dried sediment in a weak (1% Na30Sidiatom are a function of the isotope composition of dissolved silicic acid [δ30Si(OH)4] supplied to the photic zone (δ30Silake), the fraction of Si(OH)4 remaining in the water (f), and the enrichment factor between diatoms and silicic acid (ε):Lake Baikal is best characterized by an open system model  in whichf) can be obtained given that δ30Silake and ε have been constrained in Lake Baikal at 1.71‰ and −1.61‰, respectively  and downwelling season (s), the cumulative Ekman transport (SI Appendix):in which nwelling , 29. Usinwelling  .Data normality was checked using a Shapiro–Wilk test with comparisons between datasets then performed using either a Wilcoxon rank sum test or c supply 3 was calSI Appendix). The axis 1 gradient length was 0.652 SD units, so data were reanalysed using principal-components analysis (PCA). Diatom compositional turnover through time was estimated by constraining relative abundance data with sample dates derived from 210Pb radiometric dating. Compositional turnover was calculated using detrended canonical correspondence analysis (DCCA), with a square root transformation of diatom relative abundance taxa (SI Appendix). The degree to which nutrient supply may influence diatom community composition was estimated using redundancy analysis, with time partialled out as a covariable.The magnitude of diatom turnover at site Baik13-7  was estiSI Appendix).GAMs were calculated with restricted maximum-likelihood smoothness selection. To account for temporal autocorrelation, all models included a continuous-time first-order autoregressive [CAR(1)] process. Intervals of significant temporal change in a GAM were detected using the first-order derivative of the fitted trend and a 95% simultaneous confidence interval  (SI AppeSupplementary FileSupplementary FileSupplementary FileSupplementary FileSupplementary File