Abstract

The earliest Native Americans have often been portrayed as either megafaunal specialists or generalist foragers, but this debate cannot be resolved by studying the faunal record alone. Stable isotope analysis directly reveals the foods consumed by individuals. We present multi-tissue isotope analyses of two Ancient Beringian infants from the Upward Sun River site (USR), Alaska (~11,500 years ago). Models of fetal bone turnover combined with seasonally-sensitive taxa show that the carbon and nitrogen isotope composition of USR infant bone collagen reflects maternal diets over the summer. Using comparative faunal isotope data, we demonstrate that although terrestrial sources dominated maternal diets, salmon was also important, supported by carbon isotope analysis of essential amino acids and bone bioapatite. Tooth enamel samples indicate increased salmon use between spring and summer. Our results do not support either strictly megafaunal specialists or generalized foragers but indicate that Ancient Beringian diets were complex and seasonally structured.

Identifying the subsistence strategies of the earliest inhabitants of the Americas remains a contentious problem; these populations have been portrayed as megafaunal specialists or as broad-spectrum foragers (1, 2). Addressing this issue is a key in understanding the initial colonization, routes of dispersal, and settlement of the continent. Analyses of archaeological faunal assemblages are essential for elucidating diet breadth but cannot fully resolve it since the compositions of these assemblages may be biased by factors related to preservation, animal processing, and recovery (3). In contrast, stable isotope analysis of human remains provides a powerful tool for directly quantifying ancient diets and revealing the food sources actually consumed by individuals (4). The remains of two infants from the Upward Sun River (USR) site (Fig. 1), the earliest human remains in eastern Beringia, offer a rare opportunity to investigate the diet of ancient Native Americans using stable isotope analysis.

Two female infants were recovered in a single burial dating to ~11,500 calibrated years before present (cal yr. BP) at the USR site in interior Alaska (5). The older individual (Xachiteeaanenh Teede Gaay or USR1) was a newborn infant (~3 to 4 weeks), and the younger individual (Yekaanenh Teede Gaay or USR2) was a late-term prenate (5). Genomic analyses indicate that the two infants are the first known members of one of the two basal branches of Native Americans, termed Ancient Beringians (6). These infants belong to different maternal lineages (C1b and B2 haplogroups, respectively) (7) and provide two independent windows into the paleodiets of the mothers and, more broadly, of Ancient Beringians at the Pleistocene-Holocene transition. USR and the infants are assigned to the Denali Complex, a widespread cultural group present in eastern Beringia from 12,500 to 6000 cal yr. BP (5).

Here, we present multitissue stable isotope analyses of the USR infants to model the diets of their mothers based on a suite of comparative archaeological faunal data from the region, including large terrestrial herbivores (bison and wapiti), small game (hare, ground squirrel, and grouse/ptarmigan), salmon, and freshwater whitefish (tables S1 to S4 and fig. S1). Terminal Pleistocene human remains from North America are extremely rare, and to date, no isotope-based dietary analyses using regional archaeofaunal specimens have been conducted for this time period.

To gain a holistic understanding of the diet, we analyzed multiple tissues, as they reflect different dietary components: (i) carbon and nitrogen stable isotope values (13C and 15N values, respectively) of bulk bone collagen, (ii) 13C values of bone collagen single essential amino acids (EAAs) (compound specific isotope analysis), (iii) 13C values of bone bioapatite, and (iv) 13C values of tooth enamel. Dietary protein sources are reflected in (i) and (ii), and whole diet carbon sources (carbohydrates, lipids, and proteins) are reflected in (iii) and (iv) (4, 8, 9). Because USR2 died before birth, and USR1 likely died shortly after birth, the isotopic composition of their tissues will reflect maternal diets during pregnancy while the tissues were forming (10, 11), although we consider the possible effects of gestation and/or breastfeeding on isotope values.

Season of death for both infants is estimated as early August based on multiple proxies, including seasonally sensitive plant and animal taxa (berries, immature and mature ground squirrel, and salmon) (table S5). To determine the dietary window represented by the bone tissues of USR1 and USR2, we developed models of fetal bone collagen and mineral turnover rates.

Our models of fetal bone tissue turnover indicate rapid turnover rates for bone collagen and mineral during gestation (table S6 and fig. S2). For example, for an infant at age 40 gestational weeks, around 17% of existing bone collagen was formed in the previous week (Fig. 2). Applying the turnover models to the USR infants shows that the majority (~70%) of bone collagen was synthesized in the last 5 to 8 weeks of the infants lives (table S7). On the basis of the estimated time of death, the infants bone tissues would largely reflect maternal diets over the summer.

For a prenate at age 33 gestational weeks (GW), 64% of existing collagen was formed in the previous 4 weeks (30th to 33rd week), while for a newborn (40 GW), 55% of bone collagen was formed in the previous 4 weeks. For a neonate at 3 postnatal weeks (PW), 26% of bone collagen was formed in the previous 4 weeks, and 68% was formed in the previous 8 weeks. Estimates are based on a new model of fetal bone collagen turnover (tables S6 and S7); postnatal estimates are based on a previously published model (15).

We assume that bone collagen formed in utero reflects mothers diet since the fetus derives its nutrition from the maternal bloodstream via the placenta. However, we recognize that the question of whether mother and fetal bone collagen isotope values are identical is unresolved (12). We addressed this uncertainty by incorporating variance parameters for trophic discrimination factors (TDFs; the change in isotope values between food sources and consumer tissues) into our mixing models, as well as by examining the sensitivity of our mixing models to varied TDFs.

We analyzed the bulk bone collagen isotope data of the humans and ancient regional fauna both graphically (13) and using a Bayesian multisource mixing model (MixSIAR) (14) to estimate dietary protein sources for the mothers of USR1 and USR2 (Figs. 3 and 4 and tables S8 and S9). The USR infants have identical bone collagen 13C values (18.4), but USR1 has a slightly higher 15N value (9.1) compared to USR2 (8.7) (table S2), possibly reflecting the onset of nursing, which leads to 15N enrichment in tissues (11). Using the 15N value for USR2 as a prenursing baseline, we estimate that the slight bone collagen 15N enrichment of 0.4 would be achieved between 3 to 4 weeks of nursing, assuming normal bone growth and remodeling for USR1 and a maximum 15N enrichment of 3.0 through breastfeeding (11, 15).

Small game is an average of hare, ground squirrel, and grouse/ptarmigan. (A) Raw bone collagen 13C and 15N values. Salmon (P/H) includes specimens dating to the terminal Pleistocene/early Holocene; Salmon (LH) includes specimens dating to the Late Holocene. (B) Isospace plot showing mean faunal 13C and 15N values corrected for TDFs is as follows: 13CTDF-corrected = 13Ccollagen + 1.1 (0.2) and 15NTDF-corrected = 15Ncollagen + 3.8 (1.1) (66). Source error bars show 1 SD [combined source and TDF SD calculated following (71)]. Salmon includes P/H and LH specimens.

Estimated contributions (%) of food sources to maternal diets were determined using a five-source (bison, wapiti, small game, salmon, and whitefish), two-biotracer (13Ccollagen and 15Ncollagen) mixing model in MixSIAR. Terrestrial is an a posteriori aggregation of bison, wapiti, and small game. (A) Box plots showing median (center line), 50% credible interval (CI) (box edges), and 95% CI (error bars) for estimated contributions. (B) Posterior distributions (colored) superimposed on prior distributions (gray) of source contributions for USR1 (darker color) and USR2 (lighter color). Prior is the uninformative Dirichlet (equal weights for all five original sources).

Biplots of infant and faunal 15N and 13C values (Fig. 3, A and B) show that the infant isotope values fall within the dietary mixing space bounded by the faunal isotope values (after correcting for TDFs), demonstrating that their isotopic compositions can be explained by a mixture of the selected food sources in maternal diets (13). The infant isotope values are located close to those of the TDF-corrected terrestrial fauna (bison, wapiti, and small game), indicating that one or more of these resources contributed substantially to maternal diets. However, the infant 13C values are higher than those of the terrestrial sources (and the whitefish), indicating that a 13C-enriched source, salmon, must have contributed to the diets of both mothers. Furthermore, a plot that includes rarer secondary fauna shows that no other source exhibits the combination of 13C and 15N enrichment necessary to explain the infant isotopic signatures in the absence of salmon (fig. S3).

Bayesian mixing model results for both USR1 and USR2 indicate that although their mothers derived most of their dietary protein from terrestrial resources, salmon also contributed a substantial proportion, with negligible contributions from freshwater fish (Fig. 4A and table S9). Mean dietary contribution estimates for USR1 are 62 8% terrestrial (an a posteriori aggregation of bison, wapiti, and small game), 32 6% salmon, and 6 5% freshwater whitefish. Results are very similar for USR2, with mean estimates of 65 8% terrestrial, 30 7% salmon, and 5 4% freshwater whitefish. Bayesian 95% credible intervals (CIs) for each of the three sources indicate that there are no credible solutions composed of solely terrestrial sources (table S9). All solutions within the 95% CI also contain at least 16% salmon, although there are solutions in this interval that include no whitefish. Mixing model performance indicators are strong when considering the three major resource categories (terrestrial, salmon, and whitefish), with relatively constrained proportional contribution estimates and narrow, unimodal posterior distributions that diverge from the prior distributions, indicating that diet contribution estimates are robust and informed by the isotope data (Fig. 4, A and B) (14, 16). However, mixing model output cannot clearly resolve the relative importance of the discrete terrestrial resources, as there is a high degree of uncertainty for contribution estimates for bison, wapiti, and small game (table S9 and fig. S4).

Given the uncertainty in the estimate of the nitrogen stable isotope TDF (15N), we examined the sensitivity of mixing model contribution estimates to different magnitudes of 15N. We varied 15N in increments of 1 around our main model choice of 15N = 3.8, spanning 2.8 to 5.8. We found that the mean contribution estimates for terrestrial, salmon, and whitefish sources are fairly robust to changes in 15N (table S10). For example, for each 1 increase in 15N, the estimated mean salmon contribution decreases by only about five percentage points.

We measured the stable carbon isotope composition of several bone collagen EAAs (table S11). Because EAAs cannot be synthesized by animals, their carbon is routed from dietary protein with minimal modification and reflects the stable carbon isotopic composition of primary production sources at the base of the food web (17). In addition, individual amino acid 13C values can be normalized to control for baseline variation in isotope values, allowing comparisons of diets among human groups from different regions or time periods (18). Here, we use two normalized EAA dietary markers, 13CVal-Phe and 13CLys-Phe, calculated from published data, to discriminate between aquatic and terrestrial consumers (Fig. 5 and table S12) [modified from (18, 19)]. There is clear separation among consumers, with higher values of 13CVal-Phe and 13CLys-Phe for marine and freshwater consumers compared to terrestrial consumers, with no overlap in values. These differences parallel those found in algae and plants, which are major primary producers at the base of aquatic and terrestrial food webs, respectively. The USR infant values fall between those of the terrestrial and marine consumers, as expected if maternal diets were based on a combination of terrestrial mammals and salmon.

Comparative values were calculated from published data (table S12) (1719, 7274). 13CVal-Phe = 13Cvaline 13Cphenylalanine and 13CLys-Phe = 13Clysine 13Cphenylalanine. Values are also shown for primary producers. PP, primary producer; FWPC, freshwater protein consumer; MPC, marine protein consumer; TPC, terrestrial protein consumer.

We also measured the stable carbon isotope composition of USR1 bone bioapatite, which is 15.5. Bioapatite sample quality was evaluated using Fourier transform infrared spectroscopy (20, 21), and sample quality indictors including carbonate-to-phosphate ratio (0.28) and infrared splitting factor (2.6) are within the parameters of well-preserved archaeological samples (21). We used 13Cbioapatite and 13Ccollagen values in tandem to provide additional insights into maternal diet. Experimental evidence from animals fed controlled diets shows that 13Ccollagen and 13Cbioapatite distributions form two distinct regression lines depending on whether protein is derived from (i) C3 terrestrial sources or from (ii) marine or C4 terrestrial sources (22). Because C4 plants are extremely rare in the subarctic (23), we consider the second regression line as reflecting a marine diet. USR1 falls between the two protein lines but nearer to the C3 terrestrial protein line (fig. S5), in strong agreement with mixing model results based on bone collagen 13C and 15N values.

The spacing between 13Cbioapatite and 13Ccollagen values (13Cbioapatite-collagen) for USR1 is 2.9, which indicates that the 13C value of the whole diet is lower than that of dietary protein (9). For diets based on terrestrial animals, 13Cbioapatite-collagen is predicted to narrow as the 13C-depleted lipid fraction of the diet increases, with a predicted spacing of around 3 when lipid comprises 50% of macronutrients (24). Overall, the USR spacing suggests a high animal lipid content, which is consistent with diet inferences based on our other proxies, and further suggests substantial consumption of large mammals, which have a much higher percentage of whole body fat than small mammals (25).

Tooth enamel forms incrementally and is not remodeled, so isotopic analysis of serial samples from this tissue can detect changes in diet over the course of tooth formation (26). For USR1, we sampled enamel from the upper second deciduous incisor (di2), which begins forming around the 17th gestational week (27). Serial samples of enamel from di2 produced 13C values of 14.2 for the incisal section (formed earlier, ~February/March to May) and 13.4 from the cervical section (formed later, ~May to August). The increase in USR1 enamel 13C values over time of nearly 1 suggests the incorporation of 13C-enriched salmon in maternal diet during later development, consistent with the timing of modern salmon runs in the Tanana basin (28).

Zooarchaeological analyses of contemporaneous sites in the Tanana basin (29, 30) and USR-specific hearth sediment isotopic analyses (31) provide independent proxies for Ancient Beringian paleodiets. Very large mammals (primarily bison and wapiti) are found at all Denali Complex sites with fauna (n = 16; 100% ubiquity), while small mammals (e.g., ground squirrel and hare), birds (terrestrial and waterfowl), and fish are found at fewer sites (29, 44, and 25% ubiquity, respectively) (tables S13 and S14) (29, 30). Among ungulates, bison (56% occurrence) and wapiti (31%) are most common, followed by caribou and sheep (19%) and moose (6%). Some short-term Denali hunting camps, such as Gerstle River (32), are dominated by bison and wapiti and a narrow range of weapon technology, while Denali residential base camps, such as USR and Broken Mammoth, have a much wider range of faunal taxa (table S14) (5, 33).

Paleoindian use of salmon has only recently been confirmed in a Denali site, at USR component 3 (34). We report here the identification of chum salmon (Oncorhynchus keta) remains from a second site (XBD-318) in the Tanana basin. The salmon specimen was recovered from an archaeological component buried in loess (35) and directly dated to 12,680 to 12,770 cal yr. BP (UGAMS-26403; 10,830 40 BP). The specimen has been confirmed as an anadromous chum salmon through DNA and isotopic analyses (tables S1 to S4).

There is also strong agreement between our estimated terrestrial and salmon contributions to diet based on bone collagen 13C and 15N values and those based on carbon stable isotope analyses of fatty acids in sediments from multiple hearths at USR component 3 (table S15 and fig. S6) (31). Collectively, the regional zooarchaeological record and hearth chemical profiling from the burial component support terrestrial subsistence dominated by bison and wapiti, with some use of salmon, freshwater resources, and small game.

These stable isotope-based paleodiet models provide unique windows into the diets of two Ancient Beringian women over a single spring and summer period 11,500 years ago, providing a link between the broad-scale subsistence patterns observed in the archaeological record over millennia and the short-term foraging decisions made by individuals. Our results indicate that over a summer season, the mothers of USR1 and USR2 obtained a majority of dietary protein from terrestrial food resources but salmon also contributed substantially, while freshwater fish were of minor importance. Salmon were probably only available in the last 4 to 6 weeks of the infants lives, corresponding to the time period during which the bulk of bone collagen was forming, and the tooth enamel data from USR1 indicate that there was increased consumption of a 13C-enriched source, likely salmon, between the spring and summer seasons.

Current models for terminal Pleistocene subsistence and mobility in eastern Beringia indicate that the availability of terrestrial resources, and particularly the availability of megafauna, was the principal conditioning factor for making economic and land use decisions (30). Our paleodiet models do not indicate either strictly megafaunal specialists or generalized broad-spectrum foragers. Collectively, these diet models combined with archaeological data from Denali Complex large mammal hunting stations (32) and residential base camps such as USR (5) provide a more holistic perspective on Ancient Beringian diets. We have shown that several independent proxies of diet, including isotopic analyses of multiple human tissues and hearth sediment fatty acids (31), along with regional zooarchaeological evidence (30), support the conclusion that Ancient Beringian diets were complex and seasonally structured. While the diet models produced here support the primacy of terrestrial resources to Ancient Beringian diets, the isotopic evidence for substantial inputs from salmon suggests that this resource too was important in shaping mobility and settlement systems.

Salmon were historically a critical resource for Athabascan populations in interior Alaska (36), and they continue to be important today. An extensive diet survey of modern indigenous Alaskan populations (37) found that Athabascan groups in the Tanana region derive 24% of their dietary protein from salmon, a figure very similar to our estimate for the salmon contribution to Ancient Beringians living in the area 11,500 years ago.

All human and faunal bone samples analyzed in this study are presented and described in table S1. All specimens came from existing collections permanently curated at the University of Alaska Museum of the North or under active investigation at research laboratories.

USR infants. Excavation and analyses of the USR infant remains were conducted under a Memorandum of Agreement (MOA) signed by the State of Alaska (the land owner), the National Science Foundation (the lead federal agency), the Healy Lake Tribal Council (the federally recognized tribal authority), and the Tanana Chiefs Conference (the regional nonprofit tribal consortium). An amendment to the MOA was signed by all parties to allow for destructive analysis of skeletal remains for the purposes of diet reconstruction through stable isotope analyses and assessment of genetic relationships through DNA analyses. We are grateful for the support and cooperation of all parties.

Osteological and genetic studies of the USR infants have been published previously (57). Mitochondrial DNA sequences show that the infants belong to two separate mitochondrial lineages (B2 and C1b) and, thus, are not maternally related (7). Whole-genome sequence data indicate that relatedness between the USR infants is within the range of half siblings or first cousins, and they confirm that the two infants are female (6).

Osteometric estimates of age at death are around birth to 6 weeks for USR1 and around 33 weeks in utero for USR2 (5). The age estimate based on tooth development is slightly higher for USR1 (~12 postnatal weeks). The discrepancy between the osteometric and dental ages may have resulted from differences between Ancient Beringians and the modern European-derived individuals used to the develop the age schedules, or bone growth could have lagged behind chronological age for USR1, although no skeletal anomalies or pathologies are apparent (5). The uncertainty ranges surrounding the point age estimates are larger for the dental methods (~4 to 13 weeks) than for the osteometric methods (~2 weeks) (5, 38). Given that the one-sigma uncertainty ranges for the two methods overlap at around age 3 to 4 weeks, we suggest that this is a reasonable estimate of the age at death for USR1.

Single middle ribs from USR1 and USR2 were selected for bone collagen extraction. The rib from USR1 produced sufficient material to also allow bioapatite extraction. In addition, enamel from a single tooth (deciduous right maxillary lateral incisor) from USR1 was serially sampled for 13C analysis. Serial enamel sampling was attempted for USR2, but the samples were too small for analysis.

Faunal remains. We selected faunal taxa based on their presence in the USR component 3 faunal assemblage (directly associated with the infants) and/or their ubiquity in regional terminal Pleistocene/early Holocene faunal assemblages. Faunal remains directly associated with the USR infants are generally too burned to be good candidates for collagen extraction and stable isotope analysis. Therefore, we selected faunal remains from other archaeological sites in the Tanana basin of central Alaska to encompass the suite of potential faunal resources used by USR inhabitants and to capture food source isotopic variation (table S1). We used molecular methods (including DNA and/or protein fingerprinting) to confirm or refine the taxonomic identifications of all salmon and nearly all ungulates (tables S1, S3, and S4 and data file S1). To control for interlaboratory and interstudy variation in measurements of 13Ccollagen and 15Ncollagen (39), all faunal specimens were analyzed specifically for this study using the same collagen extraction method and, except for a single specimen, using the same stable isotope laboratory (table S2).

We considered two sets of faunal food sources: (i) primary fauna, which includes only those fauna confirmed in USR component 3 (directly associated with the infants) and/or fauna that are ubiquitous in terminal Pleistocene/early Holocene faunal assemblages in the Tanana basin (bison, wapiti, small game, salmon, and whitefish); and (ii) secondary fauna, which includes taxa that are not confirmed in USR Component 3 but that occasionally occur in the faunal record for this time period (caribou, sheep, and waterfowl) (tables S13 and S14) (5, 30). Additional details on faunal sample composition are found in the Supplementary Materials.

DNA extraction. All prepolymerase chain reaction (PCR) activities were conducted in the ancient DNA facility at the Laboratories of Molecular Anthropology and Microbiome Research at the University of Oklahoma. This facility is a dedicated workspace for processing aged, degraded, and/or low copy number DNA samples. Precautions aimed to minimize and monitor the introduction of contamination are practiced in the laboratory.

Approximately 50 mg or less of bone material was subsampled from each specimen. The subsamples were submerged in 6% (w/v) sodium hypochlorite for 4 min (40). The sodium hypochlorite was poured off, and the samples were quickly submerged in DNA-free water twice.

The bone samples were transferred to 1.5-ml tubes, to which aliquots of 500 l of 0.5 M EDTA were added, and the tubes gently rocked at room temperature for >48 hours. An extraction negative control, to which no bone material was added, accompanied each batch of extractions, typically in a ratio of 1:7 with the samples.

DNA was extracted following the method described by Kemp et al. (41). Ninety microliters of proteinase K (Bio Basic catalog no. 32181) at a concentration of 1 mg/30 l (or >20 U/30 l) was added to each sample, and the tubes were incubated at 64 to 65C for 3 hours. Following proteinase K digestion, the tubes were centrifuged at 15,000 rpm for 1 min to pellet any undigested bone, dirt, and/or sludge. All centrifugation steps in this study were conducted with an Eppendorf centrifuge 5424. The liquid was carefully moved to a new 1.5-ml tube, to which 750 l of 2.5% resin (i.e., 2.5% celite in 6 M guanidine HCl) and 250 l of 6 M guanidine HCl were added. The tubes were vortexed multiple times over approximately a 2-min period.

Promega Wizard minicolumns were attached to 3 ml of Luer-Lok syringe barrels (minus the plunger) and placed on a vacuum manifold. Three milliliters of DNA-free water was first pulled across the columns with the intent to wash away potential contaminating DNA. The DNA/resin mixture was subsequently pulled across the columns. The silica pellet on the minicolumn was then rinsed by pulling 3 ml of 80% isopropanol across the columns.

The minicolumns were then placed in new 1.5-ml tubes and centrifuged at 10,000 rpm for 2 min to remove excess isopropanol. The minicolumns were transferred to new 1.5-ml tubes. Fifty microliters of DNA-free water heated to 64 to 65C was added to the minicolumns and left for 3 min before centrifugation of the tubes for 30 s at 10,000 rpm. This step was repeated, amounting to 100 l of extracted DNA. Ten microliters of the full concentration eluates and extraction negative controls were diluted 1:10 with water and used as described below [under standard PCR, rescue PCR, and PCR buffer enhancer P (PEC-P)].

Inhibition test and repeat silica extraction. The remaining volumes of the full concentration DNA eluates were tested for the presence of PCR inhibitors following the rationale of Kemp et al. (41) using a turkey collective as the ancient DNA positive control (see their figure 1). DNA recovered from seven or more archaeological turkey (Meleagris gallopavo) bones (42) was pooled together to make the turkey collective. The choice to pool these individual extractions was made with the intention to reduce variation between turkey DNA eluates in both endogenous mitochondrial DNA copy number and possible inhibitors coextracted with the turkey DNA. Before they are used in experiments, each turkey collective was demonstrated to PCR amplify consistently (in six or more amplifications), hence serving as a positive control.

Fifteen microliters of PCRs were conducted to amplify a 186base pair portion of turkey displacement loop using the primers T15709F and T15894R described by Kemp et al. (42). The components of these PCRs were as follows: 1 Omni Klentaq Reaction Buffer (including a final concentration of 3.5 mM MgCl2), 0.32 mM deoxynucleotide triphosphates (dNTPs), 0.24 M of each primer, 0.3 U of Omni Klentaq LA polymerase, and 1.5 l of turkey collective DNA. These reactions were spiked with 1.5 l of potentially inhibited, full concentration DNA eluates recovered from the samples under investigation here. The extraction negative controls were also tested for inhibitors in this manner. These PCRs were run in parallel with reactions that contained only turkey collective DNA (i.e., were not spiked). These reactions served as positive controls and allowed us to preclude PCR failure from contributing to our results. PCR negatives also accompanied each round of amplification, allowing us to monitor for possible contamination. Additional positive controls of modern turkey DNA were added in the post-PCR laboratory only before initiating amplification, serving as another check for possible PCR failure. Following denaturing at 94C for 3 min, 60 cycles of PCR was conducted at 94C for 15 s, 60C for 15 s, and 68C (note that this is the optimal extension temperature for Omni Klentaq LA polymerase) for 15 s. Last, a 3-min extension period at 68C was conducted before bringing the reactions to 10C.

If the turkey collective failed to amplify when spiked with any given ancient DNA eluate, then we considered the eluate to be inhibited. In the case that spiking the ancient DNA permitted amplification of the turkey collective DNA, we consider that DNA eluate to be inhibitor free.

Full concentration eluates deemed to be inhibited using the test outlined above were subjected to repeat silica extraction (41). To the remaining volume of the eluate, 750 l of 2.5% resin and 250 l of 6 M guanidine HCl were added. The samples were vortexed numerous times over a 2-min period. The extraction then followed procedures described above under DNA extraction, except that the volume used to elute the DNA from column matched the volume being repeat silica extracted. For example, if the starting volume was 87 l, then 43.5 l of DNA-free water heated to 65C was added to the minicolumns and left for 3 min before centrifugation. This step was repeated twice for a total volume of 87 l.

These repeat silica eluates were tested again for inhibition, as described above. Those still deemed to be inhibited were once again repeat silica extracted and tested again for inhibition. This was carried out until all full concentration eluates were deemed to be uninhibited.

Standard PCR, rescue PCR, and PEC-P. All of the full concentration, uninhibited eluates and the original 1:10 dilutions of the full concentration eluates were subject to three forms of PCR. First, standard PCRs contained 1 Omni Klentaq Reaction Buffer, 0.32 mM dNTPs, 0.24 M of each primer, 0.3 U of Omni Klentaq LA polymerase, and 1.5 l of template DNA. Second, rescue PCR at a 25% increase was carried out, as described by Johnson and Kemp (43). Rescue PCRs contained 1.25 Omni Klentaq Reaction Buffer (including a final concentration of 4.375 mM MgCl2), 0.4 mM dNTPs, 0.3 M of each primer, 0.375 U of Omni Klentaq LA polymerase, and 1.5 l of template DNA. Last, we used PEC-P. The composition of this enhancer cocktail is proprietary, and no safety data sheet is made available at the DNA Polymerase Technology website (www.klentaq.com/). However, Palmer et al. (44) used PEC-P to increase their success in species identification of archaeological remains of smelt and other small fishes. These PCR reactions contained 1 Omni Klentaq Reaction Buffer (including a final concentration of 3.5 mM MgCl2), 0.32 mM dNTPs, 0.24 M of each primer, 0.3 U of Omni Klentaq LA polymerase, 20% (v/v) PEC-P, and 1.5 l of template DNA. All three forms of PCR were conducted as follows: (i) 94C for 3 min; (ii) 60 cycles of PCR at 94C for 15 s, the annealing temperature for 15 s (table S3), and 68C for 15 s; and (iii) a 3-min extension period at 68C before bringing the reactions to 10C.

Primers. Primers are listed in table S3. For salmonid species identification, we used previously described primers by Jordan et al. (45). Note that Jordan et al. (45) originally described their reverse primer in the wrong orientation. The corrected primers are OST12S-forward (5-GCTTAAAACCCAAAGGACTTG-3) and OST12S-reverse (5-CTACACCTCGACCTGACGTT-3). Other primers were designed in this study to differentiate moose (Alces alces), bison (Bison priscus), elk (Cervus canadensis), Dall sheep (Ovis dalli), and caribou (Rangifer tarandus).

Sequencing results. Sequencing results are shown in table S4, and species identification is noted in table S1. Samples 16.179, 16.180, 16.181, 16.182, 16.184, and 17.276 were identified as bison (B. priscus) with repeatable results. DNA from sample 16.185, identified as bison based on morphology and as Bison/Bos based on ZooMS results, failed to amplify despite repeated attempts.

Sample 17.284 was identified as a caribou (R. tarandus) from the amplicon produced with primers Art3F/Art3R. Despite repeated PCRs, this observation was not repeatable. However, note that this sample was believed to be a caribou based on morphology.

Samples 15.301, 16.109, and 17.106 were identified as chum salmon (O. keta), as described by Jordan et al. (45), exhibiting the following mutations relative to the rainbow trout (Oncorhynchus mykiss), reference sequence (DQ288271.1): 660T and 713T. Samples 17.109, 17.110, and 17.112 were also identified as chum salmon with an additional derived mutation of a thymine (T) deletion at nucleotide position 668. Replication was possible for these six salmonid specimens. A single amplicon from sample 17.111 revealed this specimen to be a chum salmon with a T deletion at nucleotide position 668. Sequences from two additional amplicons from this sample showed additional but different mutations, likely attributable to postmortem damage.

Samples 16.171, 16.175, and 16.176 were identified as elk (C. canadensis) with primers ElkCOIF/ElkCOIR, matching the reference sequence (JF443209.1). Only a single amplicon was produced for sample 16.171, despite repeated attempts at amplification. Three additional amplicons produced from sample 16.175 differed from the reference sequence by different mutations, likely as a product of postmortem damage. A second amplicon sequenced from sample 16.176 also showed signs of damage with mutations at nucleotide positions 230T and 234T. Samples 16.171, 16.175, and 16.176 were identified as elk by morphological assessment and as Cervidae by ZooMS analysis. DNA from samples 16.168, 16.169, 16.170, 16.172, 16.173, 16.174, and 16.177 failed to amplify.

A subsample of approximately 1 to 2 mg of bone collagen (below) was resuspended with 50 mM ammonium bicarbonate and digested with 0.4 g of sequencing grade trypsin (Promega, UK) overnight at 37C. Digests were then acidified to 0.1% trifluoroacetic acid (TFA) and fractionated into 10 and 50% acetonitrile (in 0.1% TFA) before being dried down to completion by centrifugal evaporation and resuspension in 10 l of 0.1% TFA. One microliter of resuspended peptide mixture was then spotted onto a stainless steel matrix-assisted laser desorption/ionizationtime-of-flight (MALDI-TOF) plate along with an equal volume of -cyano hydroxycinnamic acid matrix (10 mg/ml) in 50% ACN (acetonitrile)/0.1% TFA and allowed to air dry. MALDI-TOF mass spectrometry was carried out using a Bruker Ultraflex II with 2000 laser acquisitions over the range mass/charge ratio of 700 to 3700, and the resultant spectra were compared with reference spectra published previously (46). Results are shown in table S1, fig. S1, and data file S1.

All carbon and nitrogen stable isotope measurements are expressed in delta notation (as 13C and 15N, respectively) relative to internationally accepted standards as follows: = (Rsample Rstandard)/Rstandard, where R is the ratio of the heavy to light isotope (e.g., 13C/12C) (47); by convention, this quantity is multiplied by 1000 to report the result in parts per thousand (). The international standard for carbon is Vienna Pee Dee belemnite (VPDB) and that for nitrogen is atmospheric N2 (AIR). The standard reference materials used to calibrate raw isotopic measurements to the internationally accepted scales are described for each laboratory below.

Bone collagen (13C and 15N values). All human and faunal bone collagen extractions were conducted in the same laboratory (Laboratory of Environmental Archaeology, University of Alaska Fairbanks) using the modified Longin (48) protocol described previously (34). Briefly, powdered bone was demineralized in HCl (0.5 M), followed by treatment in NaOH (0.1 M), and gelatinization at 70C in dilute HCl (0.001 M, pH 3). Bone collagen samples were submitted to the Washington State University Stable Isotope Core Laboratory for carbon and nitrogen stable isotope measurement on a Thermo Finnigan Delta Plus XP continuous flow isotope ratio mass spectrometer, coupled to a Costech elemental analyzer (ECS 4010). The carbon and nitrogen stable isotope compositions were calibrated relative to VPDB and AIR, respectively, using at least two internal standards, which had been previously calibrated against internationally certified standards (table S16). In addition, all sample sequences included the same quality control check standard, casein (B2155 Elemental Microanalysis), as a check of the normalization. Precision was calculated as the pooled SD of all repeated measures of calibration and check standards over the relevant analytical runs following Szpak et al. (49) and was 0.14 for both 13C and 15N. One extracted bone collagen sample (#17.260) was analyzed by the Center for Applied Isotope Studies at the University of Georgia. This laboratory calibrated relative to VPDB and AIR using two in-house standards, spinach (13C = 27.22 and 15N = 0.19) and bovine (13C = 17.53 and 15N = 8.14), which had been previously calibrated to National Institute of Standards and Technology standards.

All bone collagen samples used in this study met well-accepted quality standards: %N > 5%, %C > 13%, an atomic C/N ratio of 2.9 to 3.6, and an collagen yield of >1% (table S2) (5053). Further, our 13C and 15N values for ungulates are generally comparable to those previously reported for archaeological specimens in the region and elsewhere in Alaska, although there is variation among studies (5457). We further note that the stable carbon isotope composition of our salmon specimens, as in other archaeological and modern Pacific salmon samples, is relatively depleted in 13C compared to many marine fishes, likely due to the offshore feeding location of many salmon species (5862).

Bone collagen EAAs (13C values). We measured amino acid 13C values using gas chromatographycombustionstable isotope ratio mass spectrometry (GC-C-IRMS) in the Alaska Stable Isotope Facility (ASIF) at the niversity of Alaska Fairbanks. To prepare samples for analysis, we hydrolyzed dried collagen (~1 mg) using 1 ml of HCl (6 M) at 110C for 20 hours and dried them under N2. We derivatized the amino acids to N-acetyl methyl esters (NACMEs) for analysis by GC-C-IRMS (63). First, we methylated the amino acids with acidified methanol, prepared by the addition of acetyl chloride to methanol (1:6, v/v) in an ice bath. The methylation was completed during 75C incubation for 1 hour. Samples were then dried down under N2 and acetylated with the addition of acetic anhydride, triethylamine, and acetone (1:2:5, v/v/v) and an incubation at 60C for 10 min. The NACMEs (i.e., the derivatized amino acids) were dried down and purified with a phosphate buffer wash [1 M potassium phosphate and 1 M sodium phosphate (pH 7)], extracted with chloroform, and, again, dried down under N2. Last, the NACMEs were dissolved in ethyl acetate. A mix of amino acid standards with known 13C values was prepared alongside samples, and an internal standard (norleucine) was added to standards and samples. Amino acid NACMEs were injected onto a VF-35ms column (Agilent) in a TRACE 1310 GC interfaced with an Isolink II (Thermo Scientific), combusted into CO2 gas, and the carbon isotope ratios of individual NACME peaks were measured on a Delta V Plus IRMS (Thermo Scientific). The 13C calculation was based on NACME peak integration, which was performed by the program Isodat (version 3.0, Thermo Scientific). Peak integration was visually assessed for correct identification, width and background assignment, and adequate baseline separation between peaks. We measured the 13C in six EAAs: isoleucine (Ile), leucine (Leu), lysine (Lys), phenylalanine (Phe), threonine (Thr), and valine (Val). The 13C values of individual amino acids are measured relative to the 13C values of standard amino acids; these are internal (in-house ASIF) standards, and their 13C, before derivatization, are given in table S17. Internal (rather than international) individual amino acids are used to account for the potential influence of slightly different fractionations that can occur between batches of sample derivatizations and to allow for the correction of carbon added during the derivatization process (17, 63). Analytical precision was <0.3 for each of the amino acids in both the standards (<0.2) and samples (with the exception of phenylalanine that was <0.8 in samples and <0.2 in standards).

Bone bioapatite (13C values). The USR1 bone sample yielded sufficient bulk bone powder to allow both collagen and bioapatite extraction, but the USR2 bone sample was exhausted after collagen extraction. Bone bioapatite for USR1 was extracted following Garvie-Lok et al. (20) with minor modifications. Briefly, organics were removed from cleaned, powdered bone by soaking in 2% NaOCl for 48 hours (with a refresh at 24 hours), followed by rinsing and removal of contaminating carbonate by treatment in 0.1 M acetic acid (unbuffered) for 24 hours, and followed by a final rinsing and freeze drying for 48 hours. Bioapatite samples were submitted to the University of California Santa Cruz Stable Isotope Laboratory for carbon stable isotope measurement by acid digestion using a Thermo Scientific Kiel IV carbonate device interfaced to a Thermo Scientific MAT 253 isotope ratio mass spectrometer. Carbon stable isotope composition was calibrated relative to VPDB using NBS-18 and the internal standard CM12 (Carrara Marble; 13C = 2.05). The internal standard was previously calibrated against NBS-19 and NBS-18. Precision for 13C over the analytical run was calculated as defined above and was 0.11.

Tooth enamel bioapatite (13C values). Enamel from a single tooth (deciduous right maxillary lateral incisor) from USR1 was serially sampled for 13C analysis. Serial enamel sampling was attempted for USR2, but yields were too low for analysis. Because enamel forms incrementally and is not remodeled once formed, serial samples can be used to detect changes in diet over the course of tooth formation. Tooth enamel formation for the maxillary di2 begins at approximately 163 days before birth (~17 gestational weeks) (27). Assuming a time of death in early August, if USR1 died at birth (40 gestational weeks), then her di2 tooth enamel likely began forming in early March, whereas if USR1 lived for several weeks after birth, then the start of enamel formation would be pushed back accordingly (e.g., ~mid-February if USR1 lived for 3 weeks, ~mid-January if USR lived for 6 weeks, etc.). Enamel formation begins at the cusp of the developing tooth and proceeds toward the tooth cervix. The tooth was serially sampled in two locations, one (cuspal) reflecting earlier development (i.e., ~spring) and one (cervical) reflecting later development (i.e., ~summer).

To prepare enamel bioapatite, the tooth was mechanically cleaned to remove surface contaminants and then ultrasonically cleaned in deionized double-distilled water (DDH2O) for 30 min. Approximately 2.0 mg of cleaned enamel powder was drilled from the tooth. The samples were first treated in microcentrifuge tubes with 3% H2O2 for 15 min and then were rinsed three times with DDH2O water before being treated with 0.1 M CH3COOH for 15 min. Samples were rinsed three times with DDH2O water and then dried overnight in an oven at 60C. 13C values were measured by continuous-flow IRMS at IsoForensics in Salt Lake City, Utah using a GasBench (Thermo Scientific) interfaced to an isotope ratio mass spectrometer (Thermo Finnigan MAT 253). The carbon stable isotope composition was calibrated relative to VPDB using NBS-19 and LSVEC. Precision for 13C over the analytical run was calculated as described above and was 0.10.

To estimate proportional contributions of food sources to the diets of the USR infants mothers, we used MixSIAR (14), a Bayesian stable isotope mixing model framework available as an open-source package in R (64).

Food source selection and aggregation. For diet estimation using stable isotope mixing models, the number of diet sources should be kept as low as possible without excluding important sources (14, 16, 65). Bayesian mixing models assume that all sources included in the model contributed to diet, so it is important to include only sources that were actually consumed (65). For the MixSIAR analyses, we used the five sources (bison, salmon, small game, wapiti, and whitefish) described above as primary fauna.

Trophic discrimination factors. We used the following collagensource-to-collagenconsumer TDFs (with associated SDs) following Bocherens et al. (66): 13Cconsumer collagensource collagen = 1.1 0.2 and 15Nconsumer collagensource collagen = 3.8 1.1. We further assumed that fetal and neonate bone collagen isotope values reflect those of the mothers diet (after adjusting for the standard TDFs) but with caveats. The assumption is supported by limited isotopic analyses of accessible proteinaceous hard tissues (fingernails) in living mother/infant pairs, which show that newborn and mother fingernail 15N and 13C values are similar (11, 67). A study of hair from newborn-mother pairs likewise found a negligible difference (+0.4) for 13C values but a +0.9 enrichment for 15N (68). Studies comparing archaeological adult and infant bone collagen isotope values are mixed for 15N values, with a meta-analysis by Reynard and Tuross (12) showing neonate bone collagen 15N values both above and below the adult female mean.

Addressing uncertainty in the 15N TDF (15N). To address uncertainty in 15N between consumer and source collagen, as well as between mothers diet and fetal/neonate bone collagen, (i) we include a variance parameter in our 15N our isotope mixing models, and (ii) we explore the sensitivity of model mean proportional contribution estimates to various magnitudes of 15N. We set 15N variance at 1.2, the squared SD of 1.1 found by Bocherens et al. (66) in their meta-analysis of prey-to-predator, collagen-to-collagen offsets in 15N values. We varied 15N in increments of 1 around our main model choice of 3.8, from 2.8 to 5.8, to approximate the range of reported nitrogen isotope TDFs for humans and other mammals (69, 70).

We used the Bayesian multisource mixing model MixSIAR (14) to estimate dietary protein sources for the mothers of USR1 and USR2. MixSIAR models were run separately for USR1 and USR2. Table S8 provides the consumer and food source isotope values, TDFs, and associated uncertainties included in the models. Markov chain Monte Carlo parameters were as follows: (i) normal run: chain length = 100,000, burn-in = 50,000, thinning = 50, and chains = 3; (ii) alpha.prior: Dirichlet prior (default, 1; uninformative); and (iii) error structure: residual error: FALSE (not included) and process error: TRUE (included) (note that this is the only error structure appropriate for fitting a single consumer) (14).

T. A. Surovell, N. M. Waguespack, Human prey choice in the late Pleistocene and its relation to megafaunal extinctions, in American Megafaunal Extinctions at the End of the Pleistocene, G. Haynes, Ed. (Springer, 2009), pp. 77105.

E. J. Reitz, E. S. Wing, Zooarchaeology (Cambridge Univ. Press, 1999).

M. P. Richards, Isotope analysis for diet studies, in Archaeological Science: An Introduction, M. P. Richards, K. Britton, Eds. (Cambridge Univ. Press, 2020), pp. 125143.

S. H. Ambrose, L. Norr, Experimental evidence for the relationship of the carbon isotope ratios of whole diet and dietary protein to those of bone collagen and carbonate, in Prehistoric Human Bone: Archaeology at the Molecular Level, J. B. Lambert, G. Grupe, Eds. (Springer-Verlag, 1993), pp. 137.

B. A. Potter, C. E. Holmes, D. R. Yesner, Technology and economy among the earliest prehistoric foragers in interior eastern Beringia, in Paleoamerican Odyssey, K. E. Graf, C. V. Ketron, M. R. Waters, Eds. (Center for the Study of the First Americans, Texas A&M University, 2013), pp. 81103.

B. A. Potter, E. P. Gaines, P. M. Bowers, M. Proue, Results of the 2006 cultural resource survey of proposed Alaska Railroad northern rail extension routes and ancillary facilities, Alaska (NLUR technical report #278b-c, Northern Land Use Research Inc., 2007).

H. T. Allen, Report of an Expedition to the Copper, Tanan, and Kyukuk Rivers, in the Territory of Alaska, in the Year 1885 (Government Printing Office, 1887).

C. Ballew, A. Ross, R. S. Wells, V. Hiratsuka, Final Report on the Alaska Traditional Diet Survey (Alaska Native Health Board, 2004).

M. L. Fogel, N. Tuross, D. W. Owsley, Nitrogen isotope tracers of human lactation in modern and archaeological populations, in Annual report of the Director of the Geophysical Laboratory, 19881989 (Carnegie Institution, 1989), pp. 111117.

D. R. Yesner, Faunal extinction, hunter-gatherer foraging strategies, and subsistence diversity among eastern Beringian Paleoindians, in Foragers of the Terminal Pleistocene in North America, R. B. Walker, B. N. Driskell, Eds. (University of Nebraska Press, 2007), pp. 1531.

R. A. McKennan, The Upper Tanana Indians. Yale University Publications in Anthropology, No. 55 (Yale University, 1959).

C. R. Holloway, Paleoethnobotany in interior Alaska, thesis, University of Alaska Fairbanks (2016).

L. Halpin, Living Off the Land: Contemporary Subsistence in Tetlin, Alaska (Alaska Department of Fish and Game, 1987).

J. W. Wood, Dynamics of Human Reproduction: Biology, Biometry, Demography (Aldine De Gruyter, 1994).

B. A. Potter, J. D. Reuther, Site chronology, in Archaeological Investigations at Delta River Overlook, B. A. Potter, Ed. (Archaeology GIS Laboratory, University of Alaska Fairbanks, 2018), pp. 5870.

B. A. Potter, Site structure and organization in Central Alaska: Archaeological investigations at Gerstle River, thesis, University of Alaska Fairbanks (2005).

C. R. Harington, Ed., Annotated Bibliography of Quaternary Vertebrates of Northern North America (University of Toronto Press, 2003).

E. J. Bartelink, Resource intensification in pre-contact central California: A bioarchaeological perspective on diet and health patterns among hunter-gatherers from the lower Sacramento Valley and San Francisco Bay, thesis, Texas A&M University (2006).

J. Tackney, J. Coltrain, J. Raff, D. ORourke, Ancient DNA and stable isotopes: Windows on Arctic prehistory, in The Oxford Handbook of the Prehistoric Arctic, T. M. Friesen, O. K. Mason, Eds. (Oxford Univ. Press, 2016), pp. 5179.

The rest is here:
Ancient Beringian paleodiets revealed through multiproxy stable isotope analyses - Science Advances

Maintaining a healthy lifestyle, including a well-rounded diet is crucial to prolonging your lifespan.

You could also boost your lifespan by doing regular exercise. Its the miracle cure weve all been waiting for, according to the NHS.

Making some small diet or lifestyle changes could help to increase your life expectancy and avoid an early death.

One of the easiest ways to make sure that you live longer is to use olive oil, it's been revealed.

READ MORE: How to live longer - the spice that may reduce heart and cancer risk

"The science is clear - eating the right foods can lead to a longer, healthier life," it said.

"A basic heart-healthy diet can help you control your weight.

"Thats important because more than a third of people 65 and older are obese. That can lead to diabetes, some cancers, and heart disease.

"A heart-healthy diet is one that includes fruits and vegetables, whole grains, low-fat dairy products, skinless poultry, lots of fish, nuts and beans, and non-tropical vegetable oils."

Read the rest here:
How to live longer - the best cooking oil to prevent an early death and heart disease - Express

Holly Willoughby's huge smile and contagious energy is always just what we need at 10am when she takes her spot on the This Morning sofa.

She's been our TV screens alongside Phillip Schofield for 11 years this week, and her time on the show has seen her try out a number of weird and wonderful activities.

But one thing she always seems to enjoy is having a go in the studio's kitchen with a top chef - which is hardly surprising as she loves cooking.

She's spoken about her passion for food a number of times, especially when it comes to keeping her children Harry, Belle and Chester.

In an interview with Asda Living magazine, she explained: "I want to fill them with goodness and make sure they dont snack between meals. I like them to try new things, like crab and cockles.

"But I love a processed cheese slice myself, so I cant be that militant about nutrition."

Presenting This Morning means Holly has a very, very early alarm clock, but she makes sure she tucks into breakfast.

She's said to like yogurt, granola and berries. Delicious!

Holly is said to stick to a low-carb diet when she can including a lot of fish with lots of veg. However she also eats chicken occasionally.

However, Holly still tucks into the things she loves and often shares snaps on Instagram of her delicious looking plates.

These include pizza, fondue, cakes and mince pie - good on her.

But there is one thing she hates - tinned tuna.

Holly's also loves sushi, especially yellowtail sashimi with jalapeno.

While her celebrity status means she gets to go to lots of fancy restaurants - when shes cooking for the family her go-to treats are said to be mac 'n cheese or a spaghetti bolognese.

Even though she tries to stick to the main meals, just like everyone else, she can't always resist a snack.

A source told the Mirror: "Holly is determined to keep her new-look body so she eats chicken, carrots and hummus.

"Youll never see her without a pack of mango either, to satisfy her sweet tooth."

Just like the rest of us, Holly enjoys a well-deserved few drinks after a hard day at work, and loves fizz and cocktails.

And we've famously seen a few of her hangovers live on TV - including the morning she presented the show after a full night of partying at the NTAs, without even having had time to change out of her dress.

On her Instagram page she regularly shares snaps of her enjoying a glass of wine or a cocktail with her girlfriends.

Holly also admitted having the "worst hangover of 2020" during lockdown.

During an interview with her pal Keith Lemon, she said: "I haven't stopped, I literally clock watch like - is it time for an Aperol Spritz yet?

"The trouble is you've got your own bottle of wine and you're sitting there doing this [mimes pouring wine].

"It's not like you've got to go to the bar. I woke up on Sunday morning, it was like my worst hangover of 2020."

She's also been the face of Diet Coke, so we're sure she's had a fair few bottles of the pop drink.

See the article here:
Holly Willoughby's daily diet - healthy dinners, snack she's 'never without' and cocktails - Mirror Online

Sep 3rd 2020

THE STUDY of working life tends to be dominated by economists, management consultants and business-school professors. So it is nice to get a new perspective. James Suzman, an anthropologist, provides that fresh appraisal in an ambitious new book called Work: A History of How We Spend Our Time.

Mr Suzmans interpretation has a quasi-Biblical feel in which hunter-gatherers, like the Ju/hoansi tribesmen of southern Africa whom he has studied, lived in the garden of Eden. They worked only 15 hours a week and shared their provisions equally. Then came the fall and the arrival of agriculture, which brought with it hierarchical societies, inequality, harder work and poorer diets. Farmings only, but crucial, advantage was that the pastoralists were able to outbreed the hunter-gatherers and eventually displace them from the land.

Farming also brought a change of mentality. Hunter-gatherers may occasionally go short of food but they are rarely short of time. Agriculture is more driven by the calendar: a time to plant and a time to harvest. It also requires regular maintenance: weeding of plants, milking of cows and mending of fences. Human life became more regimented.

The seasonal nature of agriculture also had implications. Grain needed to be stored and those who controlled the stores became the elite. This led to the development of writing, as the surplus was traded and rations allocated. As well as grain silos, some agricultural societies built monumental edifices like the pyramids. That, too, required new professions like stonemasons and carpenters. In time, humans gathered in towns and cities, which also created specialist occupations like shopkeepers.

Perhaps the development of sophisticated societies was inevitable. As Mr Suzman notes, humans complex brains expend a lot of energy processing information. When you are awake you constantly seek out stimulation and engagement, and when you are deprived of information you suffer from boredom.

This analysis helps explain modern habits. The efficiency of agriculture and the exploitation of energy sources such as coal and oil has allowed people in the developed world to meet their basic needs of food and warmth. But human brains need to be kept active. People created tasks for themselves. First there was the Industrial Revolution, which sent workers into factories. Automation subsequently made manufacturing more efficient, at the cost of many jobs.

The rise of the service sector, Mr Suzman suggests, is a way for people to keep themselves busy, even though many individuals are dissatisfied with work they feel is meaningless. Another sign of the human need for activity is that people now undertake what was once considered work (fishing, gardening, baking) as hobbies.

The result of this process, he argues, is an unsatisfactory relationship between humans and their jobs. The work we do also defines who we are; determines our future prospects, dictates where and with whom we spend most of our time; mediates our sense of self-worth; moulds many of our values and orients our political loyalties, he writes.

Humans have come to view idleness as a sin and industriousness as a virtue, and teach children that hard work will pay off. In todays developed economies, though, there is little correspondence between time worked and monetary reward. Indeed, Mr Suzman questions why we are content to let our markets reward those in often pointless or parasitic roles so much more than those we recognise as essential.

This familiar criticism may strike a chord with many readers. However, Mr Suzmans view of modern society gives little credit to economic growth. Thanks to prosperity, fewer mothers die in childbirth or infants in their early years. People in general are taller and live longer; they have a higher level of education and more choices than before.

Economic growth also brings innovation. Bartlebys mother was particularly grateful for the invention of the washing machine, which saved her a day a week of scrubbing and wringing wet clothes through the mangle.

If humankind had stuck to hunting and gathering, there would be a lot fewer humans. Even if Mr Suzman had been alive in such a world, he would have been unable to study anthropology or write books. Modern work can indeed be boringand so, as the pandemic has shown, can sitting at home. Not many people would want to live their lives back in the year 1020, or even 102000 BC.

This article appeared in the Business section of the print edition under the headline "After the fall"

Read the original post:
How has humans relationship with work changed over millennia? - The Economist

Do you have any pre-bedtime routines to make sure you get a good night's sleep?

I meditate before I go to bed, a quick 5-minute wind-down, going over my day, what I'm thankful for, what's coming. It's kind of affirmation-esque. Building myself up in a humble, compassionate, open-hearted way and telling myself to let go of stress helps me fall asleep really quickly.

They all work off each otherit's like a circle. When you're eating right and you're exercising, you will sleep better. Taking the walks and meditating calms your stress, then you're able to sleep better. It's that holistic approach.

You only missed two games throughout your entire career. Do you attribute that to being vigilant about habits like sleep and nutrition that help keep your muscles in good shape and prevent injury?

Luck and genetics, I ain't gonna lie. There are so many really good athletes out there that just have the injury bug. I tried to make sure that I would stretch, get good sleep, and nutrition.

As far as athleticism, basketball helped me tremendously in football. You need to spread yourself around and train those different muscles to avoid injuries. The greatest athletes of all time, like Bo Jackson, Deion Sanders, LeBron James, Tiger Woods, they played a bunch of different sports growing up. These guys are considered the greatest athletes of all time because they hardly ever get hurt. And the reason you don't get hurt is because they've always been cross-training all their muscles, so everything is strong. I also did volleyball, surfing, skateboarding, growing up, and it made me a better athlete. So when I finally did choose football, I had that advantage over most people that just play one sport.

Did you play basketball consistently throughout your NFL career?

Basketball was my off-season workout program every year. I never touched a football during the offseason. Id play in the summer pro leagues against guys like Antoine Walker, Paul Pierce, all the NBA pros that would come back to LA to train during the off season. I played for the Miami Heat summer league team for Pat Riley and Stan Van Gundy.

You had a tough first few years in the NFL, leading the league in dropped passes and almost quitting football. How did turning that around help you handle stress and hardship beyond your football career?

Adjusting to the physicality of football wasnt a problem for me. I didn't have the confidence. I didn't believe in myself. Genetically, I was better than everybody else, but I just did what was required of me and got by on talent. I had to learn the hard way that that's not how it goes. You have doubt, but you go right through that. You have fear, you go through those fears.

Part of my morning meditation is getting joy and fulfillment and being where you're supposed to be in life, from a spiritual and emotional perspective, and owning that. My tricks now are to find joy in doing what I'm doing. Slowly but surely, I'm getting better and better and better at...getting better.

Going into this season, were seeing a lot of athletes take a firmer stand than ever against racism and pressuring their leagues to work towards real change. Does that give you hope as a Latino player who joined the NFL before activism was really a prominent part of sports?

It gives me tremendous hope. I always felt like sports has set the tone for what America should be. Sports is a good teacher on how to keep evolving. In football, for instance, with the concussions. What did the NFL do? They changed the rules. Some people didn't like the new rules. And we moved past that. We did what's better for the player, and the product is just as good. There's going to be people that say athletes shouldn't have an opinion, just shut up and play sports. That's ridiculous. What do you think, just because we play sports that we don't have opinions on things? We have an influence and we have a right to speak. So I love seeing what's going on.

Have you given any thought to how things might play out if there is an NFL strike?

I'll deal with that if it happens. One of the biggest things that stood out to me in The Last Dance was that Michael Jordan has an unbelievable ability to be present. That's what makes him so great. People would ask him about the pressure that he feels in the games to make the last shot. He said, "Why would I worry about a shot that I haven't taken yet?"

The pop star has always been a fitness devotee, but his newest challenge is staying in shape while he's stuck at homeand rapidly becoming one of the biggest stars on TikTok.

Continue reading here:
Tony Gonzalez Thinks Sleep Is the Fountain of Youth - GQ

Oatmeal is a classic breakfast. And if youve gotten the impression that its a plain and boring meal that is only carbs, think again. Make it right, and you can have a well-balanced bowl of oats that contains the right amount of carbohydrates, protein, and fat, which will keep you full and satisfied throughout your morning. Oh, and, youll want to make it delicious, too. By acknowledging these common missteps and following registered dietitians' tips, you can prioritize health and taste. Heres what you need to know.

One cup of cooked oatmeal is a healthy serving size, says Jessica CrandallSnyder, RDN, CDCES, and CEO ofVital RDin Centennial, Colorado. That amount will contain 154 calories, 27 grams (g) of carbs, and 4 g of fiber, according to the U.S. Department of Agriculture.

That doesnt have to be the only part of your breakfast either. Go ahead and have eggs on the side or throw berries on top, she says, which will add more filling nutrients (protein, fiber) and volume. If one cup looks disappointingly puny in your bowl, it might be helpful to downgrade to a smaller vessel, like an appetizer bowl, she says.

RELATED: 8 Ways to Sneak More Fiber Into Your Diet

If you love the way oatmeal tastes when its made with water and oats, continue to make it as you wish. But dont be afraid to experiment with dairy and nondairy milk, says Seattle-based registered dietitian nutritionist Ginger Hultin, spokesperson for the Academy of Nutrition and Dietetics and owner ofChampagne Nutrition.

These liquids do add calories: 37 per cup for unsweetened almond milk, according to the USDA, and around 100 for soy or low-fat (1%) cows milk. Your choice depends on your goal. If youre aiming to make your bowl creamier for fewer calories, opt for almond milk. If youre looking to add in protein, try soy (6 g per cup) or low-fat cows (8 g per cup). Along with that, any dairy or fortified nondairy milk will add in extra minerals, so youll get a boost of nutrients, too, says Hultin.

When putting together meals, Snyder makes sure she has a source of healthy complex carbs, protein, and produce. The same goes for oatmeal, but it may be even more important because its easy to think of your bowl as a complete meal. The oats supply healthy complex carbs and topping it with fruit will get you the produce (and more carbs), but youll want to incorporate protein to round things out. (One cup of cooked oatmeal made with water has 5 g of protein, per the USDA.) I recommend 15 to 20 grams of protein at breakfast. Getting to this number creates more satiety, supports muscle mass and metabolism, and helps balance out your blood sugar, she says.

Some ideas: Make your oats with soy, cows, or protein-fortified plant milks. Add in a scoop of protein powder. Stir in PB2, a personal favorite of Snyders; the powdered peanut butter nicely dissolves when stirred in and 2 tablespoons adds 6 g of protein. Nuts, nut butters, and seeds will also bump up protein. For instance, one ounce of almonds has 6 g of protein, according to the USDA.

RELATED:15 Top Food Sources of Lean Protein

Its easy to go overboard on sugar, as a result of including sneaky and obvious sources in your bowl. For instance, flavored, sweetened nondairy milk, some nut butters, and sweetened dried fruit contain added sugar, as the USDA notes. Then, theres the addition of brown sugar, maple syrup, or honey, all of which are sugar. Adding a lot of sugar to an already carbohydrate-rich breakfast can cause it to become imbalanced, as its high in carbs but low in fat and protein, says Hultin. Make sure youre using unsweetened nondairy milks and unsweetened nut butters to restrain added sugar. She also likes to mash in half of a banana for high-fiber, natural sweetness. (A half of a medium banana has 1.5 g of fiber, per the USDA. Thats about 5 percent of your daily value.) You could also sprinkle your oats with cinnamon and nutmeg during or after cooking to impart a natural sweetness, says Snyder. Topping with fresh fruit, such as berries, is another way to sweeten your bowl!

Stirring oats on the stovetop may be the most traditional way to make oatmeal, but it takes time and requires attention, lest they scald. (Yuck.) Steel-cut oats take 20 to 30 minutes to make, says Hultin, while rolled oats can be made in five minutes. But if thats unappealing, you can make oatmeal in ways that work better with your lifestyle. You can actually microwave either type of oat for a more hands-off approach so you can multitask, she says. Stovetop or microwave will not change the nutritional properties of oatmeal. Another option: If you have a slow cooker or an Instant Pot, make a larger batch, portion it out for the week, and reheat, says Hultin. Just stir in a splash of liquid to get it creamy again and grab a spoon.

RELATED: 8 Ways to Take Your Oatmeal to the Next Level

Steel-cut, old-fashioned oats, and rolled oats: Its shocking, but theyre all essentially the same, says Snyder. The manufacturing and processing [to get the different shapes of oats] differs, but the nutritional values are the same, she says. Each type of oatmeal offers unique textures, and some youll find more enjoyable than others. Go for the type you like the most, because eating healthy should make you happy. The one exception is the prepackaged packets of instant oats. Many of these are flavored and contain added sugar. If opting for instant, choose the plain variety and gussy it up yourself.

Oatmeal is known as a hot cereal, but a wonderful thing happens when you combine dry oats, yogurt or milk, fruit, and (maybe) chia seeds in a container in the fridge, says Snyder. After several hours (or, ahem, overnight), the oats absorb the liquid, plump up and soften into a familiar texture, and become overnight oats. These are eaten cold. The benefit is that theres little prep, you dont have to cook a thing, it switches up the style of oats to add variety, and theyre perfect as a snack. I like to make overnight oats in to-go coffee cups, which I could just grab and head out the door, Snyder says.

RELATED: The Best Oatmeal for People With Type 2 Diabetes

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7 Oatmeal Mistakes to Avoid - Everyday Health

What is an Athletics Communications Director to do when there are no athletics to communicate about? Brent Harris H03 is just as busy as he always is this time of yearif not more sowith his transition from sports statistics to COVID-19 statistics.

Every day, students, faculty, and staff enter their daily temperature symptom information into a COVID Pass app to receive either a green pass (Youre able to be attend class or work.) or a red alert (You may not attend class or work and should speak with a doctor.)

Harris is one of the people who collects, monitors, and analyzes this data. If a student receives a positive COVID-19 test result, he works with state and local health departments and uploads the information to the state database. Harris is also a certified contact tracer after completing a training through Johns Hopkins University. On top of all of that, he is also managing the hotel rooms in Trippet Hall, where students are quarantining if they cant go home.

This semester proves there is much more to Harris than sportsfor example, he was a theater major in college. We wanted to know what else we could find out, so we asked him to take a break from statistics and finish the following sentences:

Go here to read the rest:
Behind the Mask: Brent Harris H'03 - Wabash College

The food you eat can impact not only your body but our brain, specifically your sharpness, mood, and cognitive process, studies show. The growing field of nutritional psychiatry is exploring the association between what we eat, how we feel, and how we behave. (Feed any three-year-old sugar and wait ten minutes; they didn't need a study to tell us food impacts our mood, behavior, and cognitive ability to focus.)

Perhaps the most exciting part of the science points to the fact that antioxidants, those compounds found in plant foods that help fight oxidative stressand reduce the risk of chronic diseases,are nowalso linkedto boosting your brain's function, your mood, and yourcognitive health.

A 2019 report published in thejournalAntioxidantsexamined the linkbetween dietary antioxidants and mental health. Studies show that those adults with depression have "defective antioxidant defenses" meaning they're low in antioxidants. Moreover, your dailyintake of antioxidants such as isoflavonoids and polyphenols (from plants) has beenlinked toimproving move and brain function. Essentiallythe more antioxidants you eat, the less likely you are to be depressed and the more likely to focus and function highly. While the link between antioxidants and mental disorders isn't fully understood, eating a diet rich in antioxidants may ease symptoms of mental disorders, and boost your brain's ability to run well.

If you want to boost your mental stateeitheryour mood and your sharpnesstry these healthy antioxidant-rich snacks with brain-boosting properties that will not only help you feel more relaxed but also improve your ability to concentrate, focus and think quickly, according toDr. Uma Naidoo, M.D., a Harvard-trained Nutritional Psychiatrist and the author of the best-selling book This Is Your Brain On Food.One fast fact: salami can lead to depression, wheras healthy foods can power your brain to overcome ADHD, trauma, and mood disorders. Here are five healthy plant-based or vegan snacks that can optimize your brain'sfull potential and powermorepositive thinking right when you need it: today.

Studies have shown that magnesium canhelp lower stress hormones inpatients with major depression. But magnesium gets removed from processed foods, so the key is to eat legumes high in magnesium but stay away from processed foods.Dry roasted beans, like garbanzo beans and soybeans, can be baked and eaten like peanuts.One of my favorite recipes entails cooking chickpeas witha tiny bit of avocado oil and brain-boosting spices like cayenne pepper, turmeric, black pepper, and garlic," says Dr. Naidoo. "You can substitute cannellini or black beans for this recipe.

Blueberries, strawberries, cranberries, and goji berrieshave some ofthe greatest amounts of antioxidants around. Berries alsocontainflavonoids, which have been shown to have mood-boosting properties, according to a study published in Nutrients. In this experiment, children and young adults were asked to drink a flavonoid-rich blueberry juice, and their moods were assessed before and then two hours after the drink was consumed. This blueberry intervention increased positive effect but had no negative effect, meaning no one got crabbier. (Doctors want to further test how flavonoids impact mood positively--until then we'll justtrust our mood-altering benefits of red wine).

Berries are my personal favorite fruit, says Dr. Naidoo. "They're lower on the glycemic index and a great option when adding fruit to your daily meal plan. The bright colors of berries represent the polyphenols, which provide that antioxidant boost. Cheers.

As surprising as it may seem,dark chocolate with high cocoa content is one of the most nutritious and antioxidant-rich snacks and great for your brain. A study published in Frontiers in Nutrition found a link between flavonoids in cocoa and improvements in general cognition, attention, processing speed, and working memory. (Study break chocolate is real!) Other earlier studies with smaller sample sizes have found similar results with dark chocolate, however there may be other factors at work (such as sugar or fuel). While more research is needed indeveloping acause and effect, dark chocolateis high iini flavonoids that are known to be beneficial for brain health.

Dr. Naidoo recommends pairing up a bar of raw dark chocolate with citrus, like an orange, to add Vitamin C, since this can enhance the bodys absorption of the iron in the dark chocolate. Try to have extra dark chocolate with at least 70% cocoa with low fat and sugar which allows for the benefit of the flavonoid boost, adds Dr. Naidoo.

Superfoods such as kale, spinach, and arugula can do wonders for your brain, as they are dense in crucial nutrients such as lutein, vitamin K, nitrate, folate, alpha-tocopherol, beta-carotene, and kaempferol that have impressive health benefits. A cup of leafy green vegetables a day can prevent the decline of brain function, according to a 2018 study published in Neurology. Researchers suggest adding half a cup of cooked greens or one cup of raw greens toyour daily diet for optimal brain health and to prevent or delay dementia.

One of the best ways to get your greens is to have them as a midday snack, Dr. Naidoo suggests. For raw greens, dress them up with a vegan vinaigrette made with healthy fats such as extra virgin olive oil or avocado. For cooked greens, Dr. Naidoo recommends tossing them with spices. I love a quick broccolini stir fry tossed with less than a tablespoon of avocado oil, crushed red pepper flakes, fresh minced garlic, and a sprinkle of salt and pepper. This is super quick and easy, plus you get all of the nutrients like brain-boosting folate, capsaicin and so much more. I also switch out taco shells for romaine lettuce cups to add back more greens on Taco Tuesday Dr. Naidoo says.

One ounce of walnuts contains 2.5 grams of ALA, the Omega-3 fatty acid that is known to build cell membranes in the body and the brain. Nuts are brain food:Astudy of5,000 older adults published in The Journal of Nutrition, Health & Aging, found that consuming10 grams of nuts or more a day is linked to better cognitive functioning, as participants experienced improved thinking, reasoning, and memory. Findings show that eating nuts daily could reduce the risk of cognitive decline and contribute to mental sharpness, especially among adults ages 55+.

My favorite nuts are Brazilian nuts for the selenium-rich brain-boosting benefit and macadamia nuts, as they are low in omega-6 and high in omega-7,"Dr. Naidoo says. "Walnuts are great too, but they are high in omega-6, so eating them in moderation as part of a healthy meal plan is the way to go. Have a variety of nuts and eat up to cup a day so that the calories dont add up! says Dr. Naidoo.

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The 5 Best Plant Foods to Eat for Brain Health and Your Mood - The Beet

METAIRIE, La. -- A month into training camp, the New Orleans Saints are seeing the full spectrum of what Jameis Winston brings to the field.

Yes, that means some interceptions, some deep overthrows and some off-target days -- along with the beautiful 55-yard strikes that flick easily off his wrist and the funny body throws that have impressed coach Sean Payton when Winston uses his combination of strength and athleticism to stay alive in the pocket and create on the move.

But more than all of that, the former No. 1 overall draft pick brings an energy and enthusiasm to work every day.

Without fail, those traits are the first thing anyone seems to mention when asked about Winston -- from Payton to fellow quarterbacks Drew Brees and Taysom Hill to every other coach and teammate on down.

Jameis, amongst many things, is a bright light in the locker room, Saints receiver Austin Carr said. From Day 1, he was all smiles, he was shaking hands, he was getting to know his teammates. It felt like we had been teammates for years already within the first week.

He brings energy, he brings joy, he brings happiness in a time that is one of the most grueling of our careers -- its training camp. So I think that joy in playing the game, and then getting to know his teammates, is just something that disarms guys and that you don't expect initially.

Tight end Jared Cook and center Erik McCoy both cracked a smile and laughed a little when asked what Winston is like in the huddle.

He comes in there with his eyes really wide, and he's just looking around at everybody with the hugest smile on his face. And it just, it makes everyone in the huddle laugh every time, McCoy said. Man, Jameis is one of the funniest guys in the locker room. He brings great chemistry, great charisma to the locker room. He's just a fun guy to have around.

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Even undrafted rookie cornerback Keith Washington Jr. listed Winston, along with veteran defensive backs Malcolm Jenkins and Janoris Jenkins, when asked if there is anyone in particular he has leaned on during his first camp.

Winston was the same way during his five years with the Tampa Bay Buccaneers, when he also endeared himself to teammates and coaches by showing his dedication and love of the game.

I think the only thing I try to do is to serve. I think thats an important part of leadership, Winston said. I see No. 9 [Brees] doing it each and every day. Just finding a way I can serve each and every one of my teammates, whether its on the offensive side of the ball or the defensive side of the ball.

As long as youre genuine with these guys ... and trying to be the best teammate I can be.

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Of course, leadership and chemistry werent the issues in Tampa Bay, where the Bucs decided to move on to Tom Brady this offseason after Winstons historically turbulent season.

Last year, Winston became just the fifth quarterback in NFL history to throw for more than 5,100 yards in a season (Brees has done it four times). But Winston also became the first player in NFL history with at least 30 TD passes and 30 interceptions in the same season; he finished with 33 TDs and 30 picks.

To Winstons credit, he has acknowledged his need for an overhaul. The 26-year-old began the offseason by having LASIK surgery. He also decided to change his diet and exercise routine and said he now weighs 225 pounds -- the lowest of his pro career.

Most dramatic of all, he decided to accept a one-year deal with the Saints worth just $1.1 million plus incentives so that he could receive "a Harvard education in quarterback school" under Payton, Brees, offensive coordinator Pete Carmichael Jr. and quarterbacks coach Joe Lombardi.

By changing up my diet and going all-out this offseason, you definitely can see the improvements. And the LASIK definitely has helped me out, just seeing a clearer picture. But one of the best things I get, man, its a privilege to be in that quarterback room and see firsthand from one of the best thats ever done it, Winston said. Im blessed and privileged to have that opportunity.

Check out our annual ranking of the top 100 NFL players for the 2020 season. NFL Rank list: The top 100 for 2020 Experts pick snubs, surprises, more McShay: Ranking rookies most likely to make the 2021 list Cimini: How Le'Veon Bell fell from No. 7 to off the list in two short years

Man, these guys are really a family. And Im just happy to be embraced by this family and being allowed to kind of see firsthand how this team has been so successful and how this quarterback has been one of the greatest quarterbacks to play this game.

Winston said it also helps to be around friends and former Florida State teammates P.J. Williams and Mario Edwards Jr.

Yeah, I know I was the enemy the past five years. But, man, these guys have really took me in, and Ive had a chance to gain a lot of great friends, Winston said. This team is amazing.

The results on the field have been mixed so far. But that should be expected, considering NFL teams had no OTAs or minicamps in the summer and Winston has spent most of the past four weeks alternating with Hill on the second- and third-string units.

Winston had a particularly hard time finding a rhythm in full-team drills during the first week of practice. But then he started to hit on a few of those deep passes, while also showing his arm strength on intermediate strikes and his ability to move and throw outside the pocket.

As Payton put it, It doesnt have to be perfect around him.

Wednesdays practice was a good example, when Winston spent some time with the first string while Brees had a scheduled rest day. About three-fourths of the way through the session, most media observers agreed it was one of his most impressive days yet. But then he had a deep ball picked off by Washington and another ball intercepted by defensive end Carl Granderson after it was batted at the line of scrimmage.

Ideally the Saints would like for Winston to prove hes ready to be the No. 2 quarterback on game days so they can continue to use Hill in his versatile role as a QB/RB/TE/WR. But its far too soon to predict whether Hill or Winston can secure a long-term role as Brees successor.

I think he's doing well; I think hes doing real well. I've been pleased, said Payton, who described Winston as having exceptional arm talent.

He's in good shape. I think he's very quickly picked up what we're doing from a system standpoint. And yet there are a number of things that he continues to work on to improve, Payton said. But I think he's made that transition with us pretty quickly. He's a smart player, and weve just got to continue to give him the reps.

Saints pass-catchers are having to make adjustments as well. Cook said Brees passes come out a lot earlier and its a timing thing with him. With Winston, meanwhile, the ball comes out a lot faster and he could put some heat on the ball, man.

So a lot of times, being the receiver, it comes down to focus, Cook said.

As for the risk-reward nature of some of Winstons more aggressive throws, he said that will always be a part of his makeup. But he knows he can improve his decision-making and efficiency.

I think its a happy medium, Winston said. Im never gonna shy away from playing football the way that I know how to play it. But you get to learn from a guy (Brees) who does it so well and you get to talk through situations where he will take a chance and where he will not. And I think thats great to just see him and visualize myself doing the same thing.

Continued here:
How Saints' Jameis Winston is working to revive his career behind Drew Brees - New Orleans Saints Blog- ESPN - ESPN

While many people are looking at ways to lose weight fast, there are also quite few who would want to know how to gain weight and build muscle, mostly men with fast metabolism. Not being able to put on weight can be just as frustrating as trying to lose weight, but following our handy weight gain tips, you can nudge your metabolism in the right direction easily.

The basic concept is fairly straightforward: in order to gain weight, you need to maintain a positive energy balance by supplying your body with more calories than you expend. The actual process can be a bit more difficult than this and involves close monitoring of food intake and tracking workouts too.

Here we'll try to share some tips that might help you get out of the weight gain rut. Some of them will be related to nutrition of course but if you would like to gain weight the right way and also build muscle in the process, you will have to pay close attention on your workout regime too.

IMPORTANT: If you are underweight, have any underlying medical conditions or eating disorders, please consult your doctor first before you apply any changes to your diet. The below tips are more suited for people with fast metabolism who are otherwise healthy and by no means to be taken as medical advice.

The main reason why many people fail to gain weight is the lack of perseverance. Mark Twain once said: "Giving up smoking is the easiest thing in the world. I know because I've done it thousands of times." Most people who struggle with gaining weight have started the process numerous times but never sticked with any diet and/or workout plan for long enough for it to show results.

Another reason might be not knowing just how many calories certain food items contain and not eating enough despite 'eating loads' of food. It is worth tracking your food intake, especially at the beginning, using free apps like MyFitnessPal until you learn roughly how many calories and what macronutrient are in certain food items.

Thirdly, you must keep in mind that a calorie is not always equal to a calorie. One calorie from a broccoli will fuel your body differently than one calorie from fries. Carbohydrates in general take less effort for the body to break down and even the temperature of the food you eat can determine how easily your body can digest it (cold, fibrous food takes more energy to digest).

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Let's say you need 3,000 calories a day to put on weight. Would you rather eat three 1000-calorie meal or five 600-calorie meal a day? The latter sounds a bit more manageable, no? Breaking your food intake down into smaller installments will help you eat more food on the long run.

If you are planning on eating five meals a day, meal prep can also come in handy. Ideally, you want to eat food that you cooked/prepared yourself but we admit that might be a bit too much effort for some. Regardless, you should still plan ahead and at least roughly assemble the food you are planning on eating throughout the day tomorrow.

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Carbohydrates are important for muscle building but the other two macronutrients, namely protein and fat, are equally as important when it comes to gaining weight. Fatty food will make you feel sated for longer and food with higher fat content tend to taste better too.

Fatty foods you should include in your diet are oily fish, such as salmon and mackerel, nuts (e.g. Brazil nuts), avocado, butter, heavy/double cream, dark chocolate, olive oil and eggs. Most of these are also high in protein so by eating them, you will be killing two birds with one stone.

Talking about protein: protein is essential for muscle building and recovery and you will need to eat more than you'd think to aid weight gain. It is advised to have at least 20-30 grams of protein with each meal if the plan is to eat five times a day. Protein should be supplied from a variety of sources including green leafy vegetables, fish, lean meat, eggs etc.

Alternatively, you can also consider supplementing protein and have the best protein powder shakes and the best protein bars / best jerky as snacks throughout the day.

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One of the main reasons why you might not be gaining weight and particularly muscle mass is the lack of resistance training. If you are after muscle growth, you need to stimulate that muscle growth by training the muscles often. How often? Check out our how to build muscle guide to find out more.

The type of resistance training is up to you but don't fall into the trap of only tracking calories. Even the best running watches and best heart rate monitors can't track muscle activation and by tracking workouts with them, you can easily end up focusing only on burning calories.

What you want to do is the complete opposite: maxing out of workouts that increase strength but don't burn calories. Sure, you should still do some cardio: it's great for heart health and to maintain/improve the cardiovascular system, but try limiting the duration of cardio and let the bulk of your workout be anaerobic movements.

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How to gain weight fast: 3 tips to build muscle mass and pack on weight easier - T3