Bone-afide Stress: Methodological Assessment of Cortisol and Osteocalcin Extraction from Archaeological Human Remains

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Kaufman, Amy B. Scott This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9281736/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Objectives This study presents a novel method for extracting cortisol from human archaeological cortical bone and evaluates its usefulness as a stress indicator by comparing it with established hair-cortisol extraction methods. We preliminarily investigate osteocalcin’s potential as a less destructive, more accessible biomarker for physiological stress assessment. Methods This study analyzed ten individuals from the 18th-century Fortress of Louisbourg. Fourier-transform infrared spectroscopy (FTIR) was employed to assess the effects of diagenesis. Cortisol was measured from hair and cortical bone samples, and osteocalcin was quantified from the bone samples using an enzyme-linked immunosorbent assay (ELISA). Results Cortisol was extracted and quantified from 19 hair and 10 bone samples. Bone cortisol significantly correlated with hair cortisol (ρ: 0.68; P: 0.029), whereas osteocalcin showed a significant inverse correlation with hair cortisol (ρ: -0.77; P: 0.009) and a similar, non-significant trend with bone cortisol (ρ: -0.59; P: 0.074). Diagenetic alteration significantly affected bone cortisol (ρ: -0.70; P: 0.007), with increased degradation linked to higher extracted cortisol. Normalizing bone cortisol by the carbonate-phosphate ratio strengthened correlations with osteocalcin (ρ: -0.65; P: 0.043). Discussion These findings help establish a reproducible protocol for extracting and properly normalizing cortisol for inter-individual comparisons in archaeological human bone, enabling cortisol-based research in regions where hair rarely preserves. The correlation between hair and bone cortisol confirms bone as a viable source of cortisol for the study of physiological stress archaeologically. The inverse relationship between osteocalcin and cortisol suggests osteocalcin's potential as a stress biomarker and merits further research. Physiological stress cortisol osteocalcin skeletal biochemistry stress markers diagenesis Figures Figure 1 Figure 2 Figure 3 Figure 4 1. OBJECTIVES AND BACKGROUND This research takes a biomolecular approach to physiological stress and the skeletal response through method testing and a comparative analysis of targeted biomolecules. Specifically, the objectives of this research were to 1) assess the ability to extract cortisol from archaeological human bone using ELISA-based methods by adapting non-human mammal methods, 2) evaluate any correlations between cortisol concentrations extracted from the hair and bone from the same individuals to lend confidence to the extraction method, and 3) preliminarily conduct investigations of the statistical relationship between cortisol and osteocalcin to determine whether the latter, more readily available bone protein, warrants further investigation as a cortisol-adjacent biomarker of physiological stress. 1.1 The Acute Stress Response Stress is a physiological response nearly universal across all vertebrates, highlighting its necessity for long-term survival. Stress encompasses a variety of biological changes, referred to as the acute stress response (ASR), and is activated by threats to homeostasis (Antoun et al. 2017; Trumbull 2020 ). Primarily, the ASR provides the body with sufficient biochemical fuel in the form of sugar to enhance key biological functions essential for survival (i.e., respiration, heart rate) while suppressing secondary processes (i.e., digestion, insulin production) (Bloomfield et al. 2019 ; Grover 2002 ). Cortisol, a glucocorticoid, is the primary chemical messenger in the ASR. As a cholesterol-based hormone, it can be quantified in several tissues, including blood, saliva, urine, hair, and tooth dentin (El-Farhan et al. 2017; Quade et al. 2021 ). While cortisol has yet to be extracted from human bone tissue, it has been extracted and quantified from the cortical bone of other mammals (e.g., walruses) (Charapata et al. 2018 ). Given the biological similarities among mammals, it is expected that the methods used to successfully extract cortisol from non-human mammal bone would also yield positive results when applied to human cortical bone (Fokidis et al. 2023 ). While cortisol is central to the ASR's function, other hormones also play vital roles. For example, osteocalcin, a key metabolic hormone, exists in active (decarboxylated) and inactive (carboxylated) forms, which are regulated by the body’s insulin demand (Berger et al. 2019 ) (see Fig. 1 ). 1.2 Stress in Bioarchaeology The exploration of physiological stress and its impact on the lived experience has been at the forefront of bioarchaeological research for decades (Buikstra et al. 2022 ; Edinborough and Rando 2020 ). Historically, bioarchaeological research has relied almost exclusively on the presence of macroscopic skeletal lesions as evidence of ASR activation (Edinborough and Rando 2020 ; Goodman et al. 1984 ; Scott et al. 2016 ). However, challenges exist related to interobserver error (Biehler-Gomez et al. 2023 ), non-specific aetiologies (Reitsema and McIlvaine 2014 ), and perhaps most significantly, the time depth between ASR activation and when skeletal change occurs (Agarwal 2016 ). For these macroscopic lesions to form, a cascade of biochemical changes occurs, affecting the developmental timing and severity of these lesions (Mays 2018 ). As a result, it can take weeks or months of biochemical fluctuations within the body before macroscopic changes can be observed (Brickley 2018 ; Schats 2021 ). Conversely, biomarkers, such as cortisol, can offer significant insight into the earliest stages of the stress response. Furthermore, the objective quantification of cortisol diminishes inter-observer error, and its abundant preservation in archaeological hair samples makes the continued integration of cortisol-based research significant in studies of stress (East 2021 ; Tisdale et al. 2019 ; Webb et al. 2010 ). However, one of the biggest challenges is that hair preservation is highly environment-dependent, leading most studies to be conducted in arid regions, specifically the Middle East and South America (López-Barrales et al. 2015 ; Tisdale et al. 2019 ; Webb et al. 2015a). In response to the environmental constraints around hair preservation, recent research has focused on extracting cortisol from hard tissues (i.e., human tooth dentin and walrus cortical bone) that are more often preserved across a variety of environmental contexts (Charapata et al. 2018 , 2021 ; Quade et al. 2021 , 2023 ). The work by Charapata and colleagues ( 2021 ) specifically focused on the extraction and quantification of steroid hormones from the cortical bone of modern and archaeological walruses using liquid-column-tandem-mass-spectroscopy (LC-MS/MS), resulting in the successful quantification of cortisol, progesterone, estradiol, and testosterone in both modern and archaeological samples, positing that these concentrations represented a 10–20-year reservoir of captured hormones. Alternatively, using an ELISA-based method, Quade and colleagues ( 2023 , 2021 ) successfully quantified cortisol in dentin from both permanent and deciduous teeth in archaeological samples. While the preliminary results are promising, both of these methods require larger samples (by the gram) than hair extraction, posing concerns related to destructive sampling techniques and limited sample sizes (Charapata et al. 2018 ; Charrié-Duhaut et al. 2021 ; DeWitte 2015 ; Meyer et al. 2014 ; Quade et al. 2021 ). Additionally, while the relative biological similarities between mammal species might suggest that this method, proven successful in walruses, is also applicable to human samples; however, this has yet to be confirmed. Further, it is necessary to determine whether cortisol originating in cortical bone can be quantified using the more accessible ELISA-based method described by Quade and colleagues ( 2023 , 2021 ). While cortisol is a primary stress biomarker, osteocalcin has also gained interest for its link to bone turnover and skeletal metabolism (Berger and Karsenty 2022 ; Scott et al. 2016 ). Previous studies have been able to tentatively associate declining concentrations of bone osteocalcin with pathological lesions, certain demographic factors, and societal upheavals (Hughes and Scott 2023 ; Rich et al. 2022 ; Scott et al. 2016 , 2020 ) and have also established extraction protocols that minimize skeletal destruction (see Scott et al., 2016 , 2020 ). As an abundant non-collagenous protein that can be easily extracted from the skeleton, osteocalcin has the potential to serve as a proxy for cortisol in the study of biochemical stress, making this line of inquiry possibly more accessible and less destructive. 2. METHODS AND MATERIALS 2.1 The Fortress of Louisbourg For this study, samples were collected from the Fortress of Louisbourg skeletal collection, specifically the Rochefort Point Cemetery site. Located in Cape Breton, Nova Scotia, Canada, the Rochefort Point Cemetery was established in 1738, serving the French inhabitants of the site until 1745, after which the occupying New Englanders used the cemetery until 1749, when the French returned. The French used the cemetery for an additional 10 years until the second period of English occupation, which ultimately led to the site’s destruction and abandonment in the early 1760s (Johnston 1984 ; Moore 1974 ). A rescue excavation of the Rochefort Point Cemetery began in 2017 due to ongoing coastal erosion. Permission to excavate and analyze these remains has been granted by Parks Canada, the Roman Catholic Diocese of Antigonish, the Anglican Diocese of Nova Scotia and Prince Edward Island, and in consultation with the Nova Scotia Mi’kmaq Chiefs. All individuals are being temporarily housed at Trent University under the stewardship of Dr. Amy Scott and will be reburied. 2.1.1 Sampling Criteria For this study, only individuals with preserved hair and bone were sampled. This narrow criterion was essential to allow for the comparison of cortisol concentrations across tissue types and to compare osteocalcin concentrations with both hair and bone cortisol values. Due to varying states of skeletal preservation, only adolescent and adult individuals could be sampled. The assessment of age and sex was completed using standard skeletal morphological features (Christensen et al. 2024). For the cortisol and osteocalcin skeletal samples, cortical bone tissue was extracted from the ectocranial surface of the posterior parietal bone, as this element was consistently present and sufficiently preserved across all individuals. While current research shows no significant difference in osteocalcin concentrations across different skeletal elements (see Hughes & Scott, 2023 ; Scott et al., 2016 ), given the novelty of bone cortisol extraction, it was determined that the best practice was to establish sample consistency. 2.2 Sampling and Pre-Treatment 2.2.1 Hair Using tweezers, hairs from each individual were collected with centimetre-long segments sectioned using a scalpel when possible (see B. Schaefer, 2017 ; Webb et al., 2010 ). The directionality of these hair samples was determined by observing the imbricate scale pattern of the hair shaft under a compound microscope (Harland and Plowman 2018 ), as no roots were present. Therefore, the chronology of each hair segment (i.e., most recent to least recent) could be confidently assessed, but it was not possible to determine how close to the time of death these segments represented without a root present. For each segment of analysis, 10 mg of hair was transferred to 2 ml tubes, cleaned with 500 µL of isopropyl alcohol, and finely minced using sterilized dissection scissors. 2.2.2 Bone Using a Dremel rotary tool (model 300) with a rounded carbide burr, the outer cortical surface of the ectocranial posterior-lateral portion of the parietal was removed to expose approximately 3 cm 2 of inner cortical bone free from soil or debris. The carbide burr was then sanitized in an ethanol flame before and after each sample collection. Approximately 260 mg of bone powder was collected from each individual (10 mg for osteocalcin and 250 mg for cortisol analysis) and transferred to an Eppendorf Lo-Bind 2 ml tube (Charapata et al. 2018 ; Hughes 2020 ; Hughes and Scott 2023 ; Scott et al. 2020 ). 2.3 Extraction and Quantification 2.3.1 Osteocalcin Osteocalcin samples were collected, demineralized, filtered, and quantified following the procedure outlined by Hughes and Scott ( 2023 ). This involved adding 10% by weight of ethylenediaminetetraacetic acid (EDTA) to each bone sample for 24 hours of demineralization at 5°C, followed by centrifugation at 14,000g for 10 minutes to separate the liquid substrate. To lower the concentration of EDTA from 342.2mM to below the 6.1mM threshold needed for quantification, samples were filtered down to 50 µl in an Amicon Ultra-0.5 filter and subsequently diluted by three cycles of dilution and 14,000g centrifugation to reduce concentrations of the EDTA 1,000-fold with buffer exchange using 1X PBS. Finally, samples were eluted from 50 µl to 200 µl. All samples were quantified at a 1:30 dilution using a commercially available osteocalcin ELISA kit (ALPCO Diagnostics 43-OSNHU-E01) according to the manufacturer’s protocols. All samples were run in duplicate. The ELISA’s ODs were read and converted to ng/ml with a Fisher Scientific Multiskan FC Microplate Reader Version 1.01.16 at 450nm and a 4-parameter logarithmic curve. The total protein content per sample was quantified using a commercially available bicinchoninic acid (BCA) assay (Thermo Scientific Pierce BCA Protein Assay) to normalize osteocalcin concentrations. Following the manufacturer’s protocols, protein concentrations in a 1:2 dilution were quantified on a Fisher Scientific Multiskan FC Microplate Reader Version 1.01.16 at 562 nm and translated to concentrations with a 4-parameter logarithmic curve. The final conversion of concentrations of osteocalcin from the original ELISA (ng/ml) output to the standard osteocalcin reporting language (nanogram of osteocalcin per microgram of total protein content [ng/µg]) was calculated with Eq. 1. $$\:A\times\:\frac{B}{C}\times\:\frac{D}{E}=F$$ Equation 1: The mathematical conversion of samples initially reported osteocalcin concentrations in ng/ml to ng/µg. A, the original ELISA output (ng/ml), is multiplied by B, the ELISA dilution factor (30X), divided by C, the filtration ratio (0.5). This product is subsequently multiplied by the elution volume (ml) (D) divided by the original BCA protein assay output (µg/ml) (E) to result in F, the final osteocalcin concentration in the units ng/µg (Hughes 2020 ). 2.3.2 Cortisol Methanol solvent was added to each hair and bone tube, approximately 1 ml and 1.46 ml, respectively, to match the amounts of methanol used in previous successful methods (see Webb et al., 2010 ; Charapata et al., 2018 ). All samples were placed on a test-tube shaker at 250 revolutions per minute (rpm) for 18 hours at ambient temperature. Samples were then spun down, and the supernatants were transferred to new tubes, which were then dried in a vacuum centrifuge. Each sample was reconstituted in 250 µL of pH 7.6 PBS. Recent research has identified a link between long-term storage and the decrease of cortisol levels found in modern hair samples (see Huthsteiner et al., 2025). Suggesting this decline was no longer statistically significant after six months of storage as cortisol concentrations stabilize in hair samples. Considering the samples in this study have been exposed to burial conditions for over two centuries, the effects of laboratory storage were likely minimal in comparison. Additionally, the continued success of comparable archaeological hair studies (see Webb et al., 2010 ; López-Barrales et al., 2015 ; Tisdale et al., 2019 ) further supports that cortisol can remain sufficiently preserved and stable for comparative analyses. Both hair and bone samples were quantified using the same commercially available enzyme-linked immunosorbent assay (ELISA, ALPCO Diagnostics 11-CORHU-E01-SLV), following the manufacturer's protocol. All samples were run in duplicate. The ODs per read were translated to ng/ml in the same manner as osteocalcin. Cortisol concentrations were converted from ng/ml (the original ELISA output) to the standard reporting language of previous hair cortisol studies (ng of cortisol per gram of substrate [ng/g]) using Eq. 2. $$\:\frac{A}{B}\times\:\frac{C}{D}\times\:E\times\:\text{1,000}=F$$ Equation 2: The mathematical conversion of samples initially reported cortisol concentrations in ng/ml to ng/g. A, the original ELISA output (ng/ml), is divided by B, the weight (mg) of the substrate used for the extraction. This result is then multiplied by C, the volume of methanol (ml) used for cortisol extraction. The product is divided by D, the volume of methanol (ml) transferred for drying. Finally, the result is multiplied by E, the volume of PBS solution used for reconstituting the cortisol extract, and then multiplied by 1,000 to obtain F, the final value expressed in picogram-per-milligram—mathematically equivalent to nanogram-per-gram (Meyer et al. 2014 ). 2.4 Diagenesis Given the novelty of hormone extraction from mineralized tissues, the relationship between these extracted hormones and diagenesis remains understudied; however, it was evaluated in this study. Fourier-transform infrared spectroscopy (FTIR) was used to quantify the degree of diagenesis in each sample. Using approximately 1-2mg of powdered bone, IR spectra were collected with a Bruker Alpha II FTIR spectrometer with an attenuated-total reflectance (ATR) accessory. All IR spectra were composited from twenty-four absorbance scans collected for each sample between 400-4,000 cm − 1 with a resolution of 8 cm − 1 and automatically baseline-corrected for absorbance peak heights in Opus FTIR software. The carbonate-phosphate ratio (C/P), infrared splitting factor (IRSF), and amide I-phosphate ratio (AmI/P) were calculated using wavenumber ranges and absolute absorbance peaks as recommended by Smith et al. ( 2023 ). 3. RESULTS For this study, 10 individuals were assessed. All individuals whose age could be estimated were over 14.5 years. Sex could be determined for only four individuals, all male. All 10 individuals had hair and sufficient preservation of the ectocranial parietal bone (see Table 1 ). Table 1 Skeletal sample information, hair and bone cortisol and osteocalcin concentrations, and the FTIR-based measurements of diagenetic alteration (IRSF, C/P, AmI/P) for the Rochefort Point Cemetery Burial # Est.Age (years) Sex Hair Skeletal element Hair Cortisol (ng/g) Avg.Hair Cortisol (ng/g) Bone Cortisol (ng/g) Osteocalcin (ng/µg) IRSF C/P AmI/P Segment 1 Segment 2 Segment 3 3/2017 30–35 M ✓ Parietal 15.785 6.651 N/A 11.22 ± 6.5 3.926 6.796 3.268 0.306 0.220 12/2017 24+ M ✓ Parietal 5.101 N/A N/A 5.10 3.339 7.606 3.452 0.241 0.223 15/2017 U U ✓ Parietal 15.438 12.019 7.372 11.61 ± 4.1 5.632 4.206 3.206 0.292 0.259 88/2019 25–29 M ✓ Parietal 11.218 N/A N/A 11.218 4.422 7.335 3.255 0.287 0.246 120/2021 15.5+ U ✓ Parietal 29.567 31.864 8.200 23.21 ± 13.1 8.175 2.361 3.908 0.161 0.124 136/2022 18+ M ✓ Parietal 16.453 17.254 N/A 16.85 ± 0.6 7.286 6.619 3.785 0.132 0.078 154/2022 16.5+ U ✓ Parietal 18.296 N/A N/A 18.30 8.093 6.961 3.677 0.155 0.124 172/2023 14.5+ U ✓ Parietal 9.936 20.833 N/A 15.38 ± 7.7 11.011 5.778 3.276 0.227 0.255 194/2023 15.5+ U ✓ Parietal 18.697 12.126 20.326 17.05 ± 4.34 9.438 3.849 3.703 0.152 0.126 211/2023 15.5+ U ✓ Parietal 18.376 N/A N/A 18.38 6.207 3.610 3.715 0.164 0.154 U - undetermined 3.2 Coefficient of Variance To assess intra-observer error, since assays were conducted in duplicate for each sample, the coefficient of variance (CV) was calculated — the standard method for measuring error in assay analyses (Reed et al. 2002 ). Mean %CV per assay is shown in Table 2 , with intra-assay reproducibility falling well within accepted limits of below 10% (Klymus et al. 2020 ; Reed et al. 2002 ). Table 2 Description of per-assay-per-tissue mean coefficient of variance Assay Tissue %CV Cortisol Hair 14.02 † Cortisol Bone 6.18 † Osteocalcin Bone 3.88 BCA Bone 4.32 † While cortisol extracted from hair shows an elevated CV, all cortisol extractions (hair and bone) were collected in a single assay; the overall CV was 9.53% 3.3 Osteocalcin All ten parietal bone samples produced quantifiable osteocalcin concentrations (see Table 1 ). Concentration values ranged between 2.361 and 7.606 nanograms of osteocalcin per microgram of total bone protein (ng/µg). The average osteocalcin concentration across these 10 individuals fell slightly to the left of the center at 5.370 ± 1.82 ng/µg with a median concentration value of 5.778 ng/µg (see Table 1 ). 3.4 Cortisol and Its Relationship to Osteocalcin Cortisol was successfully extracted and quantified from 19 hair samples (4 individuals with 1 segment, 3 individuals with 2 segments, and 3 individuals with 3 segments) (see Table 1 ). Cortisol concentrations ranged between 5.101 and 31.864 nanograms of cortisol per gram of hair (ng/g), with an average value of 15.55 ± 7.17 ng/g and a median value of 15.785 ng/g. All 10 bone samples showed quantifiable cortisol levels, representing the first successful extraction from human cortical bone. These bone cortisol concentrations ranged from 3.339 ng/g to 11.011 ng/g, with an average value of 6.75 ± 2.49 ng/g and a median value of 6.747 ng/g (see Table 1 ). The comparison of cortisol in hair and bone samples showed a significant positive relationship (ρ = 0.68; P = 0.029). Comparing bone cortisol to osteocalcin indicated a nonsignificant indirect relationship (ρ = -0.59; P = 0.074). The osteocalcin and hair cortisol comparison showed a significant inverse trend (ρ = -0.77; P = 0.009) (see Fig. 2 ). 3.5 Diagenesis To evaluate the severity of diagenetic alteration, the upper and lower limits for IRSF and C/P proposed by France and colleagues ( 2020 ) and the threshold for AmI/P from Hollund et al., (2012) were used. No individual fell outside of the range of well-preserved archaeological remains (see Table 1 and Fig. 3 ). When bone-derived cortisol was compared to our collected metrics of diagenesis, there was a statistically significant indirect correlation between bone-derived cortisol concentrations and worsening preservation [IRSF (ρ = 0.72; P = 0.019); C/P (ρ = -0.79; P = 0.007)]. This contrasted with comparisons between the same metrics and osteocalcin, which, while not statistically significant [IRSF (ρ = -0.56; P = 0.09); C/P (ρ = 0.44; P = 0.206)], showed positive correlations between increased osteocalcin concentrations and better skeletal preservation (see Fig. 3 ). 4. DISCUSSION 4.1 Osteocalcin The initial observation of the extracted osteocalcin concentrations showed noticeably lower levels compared to other studies from other geographic/temporal sites (Scott et al. 2016 , 2020 ) and, while not statistically significant (Z:1.11; P: 0.27), lower than previous osteocalcin samplings at the Fortress of Louisbourg site (Hughes and Scott 2023 ) (see Table 3 ). The higher osteocalcin concentrations observed in Scott et al. ( 2020 ) compared to other studies are likely because it is the only one among these four to use LC/MS for quantification, and therefore, it is not an ideal comparison in this regard. Outside of that, the most significant difference is observed between Scott et al. ( 2016 ) and this study, possibly due to differences in cortical thickness at the sampling site. As shown in Table 3 , when cortical thickness decreases osteocalcin decreases accordingly. Table 3 Reference ranges of archaeological osteocalcin concentrations compared to the concentrations from this study, as well as comparisons of median osteocalcin concentrations to sampled element and cortical bone thickness Study Sample Size Reference Range (ng/µg) Sampled Element Average cortical thickness (mm)* Median osteocalcin concentration (ng/µg) Hughes & Scott ( 2023 ) 27 1.80-19.13 Femur 5.7 6.81 Scott et al., ( 2020 ) 46 26.0-310.0 Femur 5.7 –– Scott et al., ( 2016 ) 20 3.28–60.64 Femur 5.7 11.1 Scott et al., ( 2016 ) 20 2.91–53.34 Clavicle 3.2 8.2 This study 10 2.36–7.61 Parietal 1.26 5.8 *(Hollensteiner et al. 2018 ; Kakutani et al. 2023 ; Peebles et al. 2022 ) While visibly apparent, this comparison was also statistically significant when evaluated using a Kruskal-Wallis test (H: 6.29; P: 0.043) with Dunn’s post hoc test between each skeletalt element [Femur to Clavicle (Z: 0.064; P:0.61); Clavicle to Parietal (Z: 1.95; P: 0.153); Femur to Parietal (Z: 2.48; P: 0.04)]. This is not surprising as thicker cortical bone, representing a longer time depth, would have more opportunity to store osteocalcin, compared to thinner cortical bone, which represents a shorter time depth, and would have less time to accumulate these biomolecules before sampling. As discussed by Scott et al. ( 2016 ), the future of osteocalcin cortical bone sampling will be impacted by how the sampling site can be better sectioned to represent succinct periods of time and possible stress events, rather than arbitrary sectioning, which may lead to an averaging effect of osteocalcin concentrations across various periods of time when the cortical bone was forming. 4.2 Cortisol Cortisol extraction methods for hair have been well-established in archaeological studies for nearly two decades; therefore, the successful extraction of cortisol in this study was not unexpected. However, the low cortisol levels compared to similar studies (see Table 4 ) were surprising. Given Louisbourg’s historical context, there is no reason to believe that the stress experienced at this site was systematically less than that experienced by other populations. Therefore, methodological factors are likely responsible for the lower cortisol concentrations observed. Heat is often, but not universally, applied in the methanol aliquoting stage of cortisol extraction (Meyer et al. 2014 ). Applying heat increases the solubility of a solute (i.e., cortisol) in a solvent (i.e., methanol), meaning there would likely be an increased extraction efficiency of cortisol when subjected to heat (Meyer et al. 2014 ; Schmid and Voigt 1954 ). Comparing this study’s hair cortisol concentrations to those who similarly did not employ heat in their extraction (see Table 3 ), the values more closely align with one another. In a round-robin study by Russell et al. ( 2015 ) focused on quantification methods, labs also differed in heat use in cortisol extractions, and despite a strong correlation, the lab that did not use heat had lower values. This highlights the importance of considering procedural steps in cross-study comparisons to ensure concentration values reflect genuine physiological stress, not extraction efficiency. Table 4 Clinical and archaeological reference ranges of hair cortisol concentrations compared to the concentrations from this study, studies without heated extraction bolded Study Archaeological or Clinical Sample Size Age Range (years) Reference range (ng/g) Cieszynski, Jendrzejewski, Wisniewski, Owczarzak, & Sworczak, 2018 Clinical 44 53–73 2.0-51.63 Chan, Sauvé, Tokmakejian, Koren, & Van Uum, 2014 Clinical 39 20–76 27–200 Dettenborn, Tietze, Kirschbaum, & Stalder, 2012 Clinical 360 1–91 7.2–31.2 Föcker et al., 2016 Clinical 20 15–18 2.86–22.24 Henley et al., 2014 Clinical 15 < 20–60+ 189–400 Henley et al., 2013 Clinical 32 NA 26–204 Gonzalez et al., 2019 Clinical 232 30–60 40–128 Pereg et al., 2011 Clinical 56 50–72 76.58–949.9 Sauvé, Koren, Walsh, Tokmakejian, & Van Uum, 2007 Clinical 46 20–76 17.7-153.2 Smeeth et al., 2023 Clinical 923 6–19 31.6-181.2 Stalder et al., 2012 Clinical 155 20–30 7.1–28.3 Thomson et al., 2010 Clinical 32 20–51 26–204 East, 2021 ; Kellis 2 Cemetery - Egypt Archaeological 119 > 18–69 1.16-255.11 East, 2021 ;Terry Collection - United States Archaeological † 38 18–91 34.66-1190.49 Kellner, Kerchusky, Dillon, Buck, & Ramos, 2022; Zorropata -Peru Archaeological 2 20–35 3.9–10.3 López-Barrales et al., 2015 ; San Pedro de Atacama - Chile Archaeological 19 19–38 33.7–152 B. Schaefer, 2017 ; Huaca De Los Sacrificios – Peru Archaeological 10 NA 18.02-247.95 Tisdale et al., 2019 ; Kellis 2 cemetery - Egypt Archaeological 10 19–60 272.5–467 Webb et al., 2015a; Cahuachi - Peru Archaeological 5 > 3–12 757–2507 Webb et al., 2015b; Cahuachi and Huaca del Loro - Peru Archaeological 14 NA 125–2392 Webb et al., 2010 ; Cajamarquilla, Leymebamba, Puruchuco, Tucume, and Nasca - Peru Archaeological 10 Adult ‡ 91–707 This study Archaeological 10 < 14.5–35 5.10-31.86 † Historical (early-to-mid twentieth century) ‡ Description of age lacked specificity This study is the first to extract and quantify cortisol from human cortical bone successfully. While this is a significant outcome, it is not surprising, given the previous successes in other non-human mammals and the chemical similarities of cortisol across mammal species (Charapata et al. 2018 ; Fokidis et al. 2023 ; Sperou et al. 2023 ). The correlation between hair and bone cortisol values, while limited in power due to the small sample size, is a significant step toward validating this novel method for extracting cortisol from human cortical bone. Since cortisol was extracted from hair and bone in parallel, any methodological effects on concentrations (e.g., heat versus no-heat extraction) would affect samples equally and thus would not be a major factor in the observed correlation between cortisol concentrations across tissues. 4.3 Osteocalcin and Cortisol The correlation between hair-derived cortisol and osteocalcin is a highly significant yet unsurprising result of this study, given the biological relationship between these two hormones (Berger and Karsenty 2022 ). Although limited in statistical power, this correlation offers initial support for further research into osteocalcin’s potential as a proxy for cortisol levels in studies of physiological stress, where lower osteocalcin levels suggest increased physiological stress throughout life. While bone-derived cortisol showed a similarly inverse relationship, it did not reach statistical significance, likely due to limited statistical power. From a methodological standpoint, the directional alignment between the two sources of cortisol and osteocalcin provides some additional validation of the extraction of cortisol from human cortical bone and of ELISA-based quantification, as both show the theoretically expected inverse directionality with osteocalcin concentrations. 4.4 Diagenesis Given the novelty of extracting cortisol from archaeological bone, the significant correlation between bone cortisol levels and two of three diagenesis metrics (see Fig. 3 ) is a key finding. While notable, this result is unsurprising given the impact of diagenetic alteration and the chemistry of methanol-based hormone extraction. As bone undergoes diagenetic alteration, the tissue becomes more permeable and thus more susceptible to leaching (Bosio et al. 2021 ; Martin 2021 ). Since methanol-based hormone extraction depends on solubility and permeation into a substrate, we are likely observing increased extraction efficiency as methanol penetrates more compromised bone tissue (Fernández Ajó et al. 2022 ). This observed impact of diagenesis on cortisol extraction from bone is a crucial consideration, as it can lead to comparisons of physiological stress between individuals in which differences may stem from extraction efficiency rather than genuine biological phenomena. Given the ongoing need for a reporting language that normalizes cortisol concentrations extracted from mineralized tissues, we propose normalizing bone-derived cortisol using a preservation metric. Given that C/P showed the strongest correlation with our bone-derived cortisol concentrations (see Fig. 3 ), we adopt a new reporting language: nanograms of cortisol per gram of bone per C/P value (ng/g/CP). Using this new scale, it is possible to maintain a statistically significant relationship between cortisol derived from hair and bone, while also garnering a statistically significant relationship between osteocalcin and bone-derived cortisol (see Fig. 4 ). We likely observe the opposite phenomenon in osteocalcin concentrations, with levels decreasing as diagenesis worsens (see Fig. 3 ) due to contrasting impacts of diagenesis on these chemical extraction processes. Osteocalcin extraction using EDTA works by cleaving the protein from the calcium ion in the bone’s bioapatite molecule (Kanje et al. 2020 ). As the bioapatite structure continues to be compromised by diagenesis, there will understandably be lower quantifiable levels of osteocalcin (Keenan 2016 ; Scott et al. 2020 ). While this correlation was not statistically significant, in part due to sample size, it may also be influenced by the fact that no sample fell outside the established range of well-preserved archaeological remains (France et al. 2020 ; Hollund et al. 2013 ). Presumably, if there were a mix of samples above and below these thresholds, we would likely see a stronger statistical connection. 4.5 Limitations This study is constrained by its small sample size, limiting the strength of its statistical conclusions. Focused on confirming human cortical bone as a source for cortisol extraction and investigating the relationship between osteocalcin and the ASR, the research design prioritized individuals with both hair and usable cortical tissue present, thereby restricting the number of individuals who could be sampled. For both cortisol and osteocalcin analyses, only one type of cortical bone was examined due to sample preservation limitations, limiting the ability to directly assess the effects of cortical thickness and vascularity on hormone concentrations. The difference between heated and non-heated extraction resulted in lower cortisol concentrations in this study. While this does not directly affect the ability to compare cortisol concentrations relative to other samples extracted and quantified in parallel, it does restrict cross-study comparisons of cortisol. Since hair samples from this study did not have intact roots, we could not confirm that each individual's hair segments represented the same period of life, even though we could confirm the chronology per person. We also could not confirm the timeline of the collected osteocalcin concentrations based on the depth of cortical bone removed for demineralization and extraction. 5. CONCLUSIONS 5.2 Future Works This study has demonstrated that extraction methods can significantly influence hair cortisol concentrations, making cross-study comparisons challenging. Clarifying the reporting language and the normalization of bone cortisol is essential, given its novelty. Charapata et al. ( 2018 , 2021 ), for instance, normalize cortisol concentrations to total lipid content obtained through Soxhlet extraction. We propose normalizing based on the degree of diagenetic alteration, as measured by FTIR, but further research would be needed to determine what is most informative. Further sampling from different skeletal elements and cortical bone layers will enhance our understanding of temporal hormone assessments. Larger-sample studies are also needed to establish robust reference ranges for osteocalcin and bone cortisol comparisons across studies. The relationship between osteocalcin concentrations in hard and soft tissues has not yet been examined, but is needed to more conclusively understand the correlation between the two and to better understand how osteocalcin present in bone relates to systemic levels circulating within the body. 5.3 Research Impact This study confirms that cortisol can be extracted from human cortical bone using adapted animal procedures, expanding the geographic potential for bioarchaeological cortisol-based stress studies beyond regions where hair typically preserves well. The correlation between hair and bone cortisol provides initial validation of this extraction method, suggesting bone as a viable alternative tissue when hair is unavailable. Importantly, normalizing bone cortisol concentrations using C/P ratios appears to account for diagenetic effects, enabling more confident, authentic comparisons between individuals. The observed inverse correlation between osteocalcin and cortisol, while preliminary, suggests osteocalcin warrants further investigation as a potential stress-related biomarker. If substantiated, the lower sampling requirements for osteocalcin could enable research on physiological stress that is less destructive to human remains. Studies such as this one, which help to establish extraction protocols, appropriate normalizations, and cautiously evaluate the relationships between biomarkers, represent crucial foundations for advancing stress research in bioarchaeology. Declarations FUNDING DECLARATION This work was supported by a SSHRC Partnership Development Grant (Scott 890-2017-0049). HUMAN ETHICS AND CONSENT TO PARTICIPATE Permission to excavate and analyze these remains has been granted by Parks Canada, the Roman Catholic Diocese of Antigonish, the Anglican Diocese of Nova Scotia and Prince Edward Island, and in consultation with the Nova Scotia Mi’kmaq Chiefs. All individuals are being temporarily housed at Trent University under the stewardship of Dr. Amy Scott and will be reburied. CRediT AUTHORSHIP CONTRIBUTION STATEMENT Author Contribution Benjamin Kaufman: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Visualization, Writing – original draft. Amy Scott: Funding acquisition, Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Visualization, Supervision, Project administration, Resources, Validation, Writing – review & editing. Acknowledgement The authors of this publication acknowledge that the Fortress of Louisbourg Historic Site lies on the unsurrendered and unceded territory of the Mi’kmaq nation. The authors would like to thank Parks Canada, the Roman Catholic Diocese of Antigonish, the Anglican Diocese of Nova Scotia and Prince Edward Island, the Mi’kmaq Chiefs of Cape Breton, and to staff, students, and volunteers at the Bioarchaeology Field School held at the Fortress of Louisbourg, as well as Arra Oman. Thank you to Dr. Anna Ignaszak for access to the J. Richard Armstrong Chemistry Laboratory, and the FTIR-ATR instrument. Thank you to Dr. Dion Dunford for the UNB Department of Biology’s vacufuge. Data Availability The authors of paper do not have the authorization to make data collected in this study open to the public based on agreements with Parks Canada, the Roman Catholic Diocese of Antigonish, the Anglican Diocese of Nova Scotia and Prince Edward Island, and the Mi’kmaq Chiefs of Cape Breton. References AGARWAL SC (2016) BONE MORPHOLOGIES AND HISTORIES: LIFE COURSE APPROACHES IN BIOARCHAEOLOGY. Am J Phys Anthropol 159(S61):130–149. 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C., VAN UUM SHM, PROVIDES A HISTORICAL RECORD OF CORTISOL LEVELS IN CUSHING’S SYNDROME (2010) Exp Clin Endocrinol Diabetes 118(02):133–138. HTTPS://DOI.ORG/10.1055/S-0029-1220771 . HAIR ANALYSIS TISDALE E, WILLIAMS L, SCHULTZ, J. J., WHEELER SM, TESTOSTERONE IN ARCHAEOLOGICAL HUMAN HAIR FROM THE DAKHLEH OASIS, EGYPT (2019) DETECTION OF CORTISOL, ESTRADIOL, AND. J Archaeol SCIENCE: Rep 27:101968. HTTPS://DOI.ORG/10.1016/J.JASREP.2019.101968 TRUMBULL D (2020) SHAME: AN ACUTE STRESS RESPONSE TO INTERPERSONAL TRAUMATIZATION. PSYCHIATRY (NEW YORK) 83(1). HTTPS://DOI.ORG/10.1080/00332747.2020.1717308 WEBB EC, THOMSON S, NELSON A, WHITE C, KOREN G, RIEDER, M., VAN UUM S (2010) ASSESSING INDIVIDUAL SYSTEMIC STRESS THROUGH CORTISOL ANALYSIS OF ARCHAEOLOGICAL HAIR. J Archaeol Sci 37(4):807–812. HTTPS://DOI.ORG/10.1016/J.JAS.2009.11.010 WEBB EC, WHITE CD, VAN UUM S, LONGSTAFFE FJ, INTEGRATING CORTISOL AND ISOTOPIC ANALYSES OF ARCHEOLOGICAL HAIR: RECONSTRUCTING INDIVIDUAL EXPERIENCES OF HEALTH AND STRESS (2015A). AMERICAN JOURNAL OF PHYSICAL ANTHROPOLOGY , 156 (4), 577–594. HTTPS://DOI.ORG/10.1002/AJPA.22673 WEBB EC, WHITE CD, VAN UUM S, LONGSTAFFE FJ, INTEGRATING CORTISOL AND ISOTOPIC ANALYSES OF ARCHAEOLOGICAL HAIR: ELUCIDATING JUVENILE ANTE-MORTEM STRESS AND BEHAVIOUR (2015B) Int J Paleopathol 9:28–37. HTTPS://DOI.ORG/10.1016/J.IJPP.2014.12.001 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 15 May, 2026 Reviewers invited by journal 14 May, 2026 Editor assigned by journal 02 Apr, 2026 Submission checks completed at journal 01 Apr, 2026 First submitted to journal 31 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9281736","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":616424982,"identity":"7e86d9f4-60d5-451a-933d-b22c210e2c23","order_by":0,"name":"Benjamin L. Kaufman","email":"data:image/png;base64,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","orcid":"","institution":"McGill University","correspondingAuthor":true,"prefix":"","firstName":"Benjamin","middleName":"L.","lastName":"Kaufman","suffix":""},{"id":616424983,"identity":"3ee0b6ee-4910-4e6c-977b-3265e1012ac3","order_by":1,"name":"Amy B. Scott","email":"","orcid":"","institution":"Trent University","correspondingAuthor":false,"prefix":"","firstName":"Amy","middleName":"B.","lastName":"Scott","suffix":""}],"badges":[],"createdAt":"2026-03-31 15:09:27","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9281736/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9281736/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108675649,"identity":"48cfe95a-4b28-494e-a579-80b31147a4e6","added_by":"auto","created_at":"2026-05-07 08:29:43","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":591944,"visible":true,"origin":"","legend":"\u003cp\u003eDepiction of osteocalcin regulation under normal conditions (left) and during elevated stress (right). Normally, when insulin is low and glucose demand is high, osteoclasts release osteocalcin into the blood, where it binds to the pancreas and performs other functions. When insulin is sufficient, it binds to osteoblasts, encouraging them to carboxylate osteocalcin and store it in new bone. Excess cortisol, released during the activation of the ASR, inhibits this process by blocking insulin production, preventing osteocalcin storage, and keeping it in its active form. As such, when cortisol is elevated through ASR activation, osteocalcin levels in bone are reduced.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-9281736/v1/0fa15ffba61629243d755186.png"},{"id":108806013,"identity":"c9f6373a-33ca-4bb6-90bf-2d9c19eb2312","added_by":"auto","created_at":"2026-05-08 15:27:27","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":576989,"visible":true,"origin":"","legend":"\u003cp\u003eScatter plots displaying the Spearman's rank correlation between (A) cortisol extracted from hair against cortisol extracted from bone, (B) osteocalcin against bone-derived cortisol, and (C) osteocalcin against hair-derived cortisol and fitted regression line (dotted) with confidence interval, * Significant at a 95% confidence interval\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-9281736/v1/b4c07c6b3f09de8053701d15.png"},{"id":108675650,"identity":"97fcabc3-bcf7-4476-8a66-67eebf5f66d2","added_by":"auto","created_at":"2026-05-07 08:29:43","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":852003,"visible":true,"origin":"","legend":"\u003cp\u003eA graph of collected IRSF (A), C/P (B), and AmI/P (B) values of samples compared to their respective limits outlined by France et al. (2020), and Hollund et al. (2012). Scatter plots displaying the Spearman's rank correlation between bone-derived cortisol and osteocalcin against (C) IRSF, (D) CP, and (E) AmIP and fitted regression line (dotted) with confidence interval, * Significant at a 95% confidence interval\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-9281736/v1/dca5bde55191b4764d8ca284.png"},{"id":108806034,"identity":"8dc6f8ed-6bec-4ae7-9446-72e28929ec3e","added_by":"auto","created_at":"2026-05-08 15:27:32","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":803628,"visible":true,"origin":"","legend":"\u003cp\u003eScatter plots showing previously described Spearman's rank correlations (A and C) between bone-derived cortisol and hair-derived cortisol or osteocalcin, respectively and the same comparisons (B and D) with bone-derived cortisol normalized by C/P, with fitted regression line (dotted), * Significant at a 95% confidence interval\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-9281736/v1/d663ca185c3fe378c91c9beb.png"},{"id":108809909,"identity":"dc8c3ae7-2d5f-42b9-b8ff-39d695f6d031","added_by":"auto","created_at":"2026-05-08 15:56:13","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3329407,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9281736/v1/685a7bcd-3be5-4256-9f9c-597d73652766.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Bone-afide Stress: Methodological Assessment of Cortisol and Osteocalcin Extraction from Archaeological Human Remains","fulltext":[{"header":"1. OBJECTIVES AND BACKGROUND","content":"\u003cp\u003eThis research takes a biomolecular approach to physiological stress and the skeletal response through method testing and a comparative analysis of targeted biomolecules. Specifically, the objectives of this research were to 1) assess the ability to extract cortisol from archaeological human bone using ELISA-based methods by adapting non-human mammal methods, 2) evaluate any correlations between cortisol concentrations extracted from the hair and bone from the same individuals to lend confidence to the extraction method, and 3) preliminarily conduct investigations of the statistical relationship between cortisol and osteocalcin to determine whether the latter, more readily available bone protein, warrants further investigation as a cortisol-adjacent biomarker of physiological stress.\u003c/p\u003e \u003cdiv id=\"Sec2\" class=\"Section2\"\u003e \u003ch2\u003e1.1 The Acute Stress Response\u003c/h2\u003e \u003cp\u003eStress is a physiological response nearly universal across all vertebrates, highlighting its necessity for long-term survival. Stress encompasses a variety of biological changes, referred to as the acute stress response (ASR), and is activated by threats to homeostasis (Antoun et al. 2017; Trumbull \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Primarily, the ASR provides the body with sufficient biochemical fuel in the form of sugar to enhance key biological functions essential for survival (i.e., respiration, heart rate) while suppressing secondary processes (i.e., digestion, insulin production) (Bloomfield et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Grover \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2002\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eCortisol, a glucocorticoid, is the primary chemical messenger in the ASR. As a cholesterol-based hormone, it can be quantified in several tissues, including blood, saliva, urine, hair, and tooth dentin (El-Farhan et al. 2017; Quade et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). While cortisol has yet to be extracted from human bone tissue, it has been extracted and quantified from the cortical bone of other mammals (e.g., walruses) (Charapata et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Given the biological similarities among mammals, it is expected that the methods used to successfully extract cortisol from non-human mammal bone would also yield positive results when applied to human cortical bone (Fokidis et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWhile cortisol is central to the ASR's function, other hormones also play vital roles. For example, osteocalcin, a key metabolic hormone, exists in active (decarboxylated) and inactive (carboxylated) forms, which are regulated by the body\u0026rsquo;s insulin demand (Berger et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) (see Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e1.2 Stress in Bioarchaeology\u003c/h2\u003e \u003cp\u003eThe exploration of physiological stress and its impact on the lived experience has been at the forefront of bioarchaeological research for decades (Buikstra et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Edinborough and Rando \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Historically, bioarchaeological research has relied almost exclusively on the presence of macroscopic skeletal lesions as evidence of ASR activation (Edinborough and Rando \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Goodman et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e1984\u003c/span\u003e; Scott et al. \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). However, challenges exist related to interobserver error (Biehler-Gomez et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), non-specific aetiologies (Reitsema and McIlvaine \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), and perhaps most significantly, the time depth between ASR activation and when skeletal change occurs (Agarwal \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFor these macroscopic lesions to form, a cascade of biochemical changes occurs, affecting the developmental timing and severity of these lesions (Mays \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). As a result, it can take weeks or months of biochemical fluctuations within the body before macroscopic changes can be observed (Brickley \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Schats \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Conversely, biomarkers, such as cortisol, can offer significant insight into the earliest stages of the stress response. Furthermore, the objective quantification of cortisol diminishes inter-observer error, and its abundant preservation in archaeological hair samples makes the continued integration of cortisol-based research significant in studies of stress (East \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Tisdale et al. \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Webb et al. \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). However, one of the biggest challenges is that hair preservation is highly environment-dependent, leading most studies to be conducted in arid regions, specifically the Middle East and South America (L\u0026oacute;pez-Barrales et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Tisdale et al. \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Webb et al. 2015a).\u003c/p\u003e \u003cp\u003eIn response to the environmental constraints around hair preservation, recent research has focused on extracting cortisol from hard tissues (i.e., human tooth dentin and walrus cortical bone) that are more often preserved across a variety of environmental contexts (Charapata et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2018\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Quade et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2021\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The work by Charapata and colleagues (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) specifically focused on the extraction and quantification of steroid hormones from the cortical bone of modern and archaeological walruses using liquid-column-tandem-mass-spectroscopy (LC-MS/MS), resulting in the successful quantification of cortisol, progesterone, estradiol, and testosterone in both modern and archaeological samples, positing that these concentrations represented a 10\u0026ndash;20-year reservoir of captured hormones. Alternatively, using an ELISA-based method, Quade and colleagues (\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2023\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) successfully quantified cortisol in dentin from both permanent and deciduous teeth in archaeological samples. While the preliminary results are promising, both of these methods require larger samples (by the gram) than hair extraction, posing concerns related to destructive sampling techniques and limited sample sizes (Charapata et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Charri\u0026eacute;-Duhaut et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; DeWitte \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Meyer et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Quade et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Additionally, while the relative biological similarities between mammal species might suggest that this method, proven successful in walruses, is also applicable to human samples; however, this has yet to be confirmed. Further, it is necessary to determine whether cortisol originating in cortical bone can be quantified using the more accessible ELISA-based method described by Quade and colleagues (\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2023\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWhile cortisol is a primary stress biomarker, osteocalcin has also gained interest for its link to bone turnover and skeletal metabolism (Berger and Karsenty \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Scott et al. \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Previous studies have been able to tentatively associate declining concentrations of bone osteocalcin with pathological lesions, certain demographic factors, and societal upheavals (Hughes and Scott \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Rich et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Scott et al. \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2016\u003c/span\u003e, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) and have also established extraction protocols that minimize skeletal destruction (see Scott et al., \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2016\u003c/span\u003e, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). As an abundant non-collagenous protein that can be easily extracted from the skeleton, osteocalcin has the potential to serve as a proxy for cortisol in the study of biochemical stress, making this line of inquiry possibly more accessible and less destructive.\u003c/p\u003e \u003c/div\u003e"},{"header":"2. METHODS AND MATERIALS","content":"\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.1 The Fortress of Louisbourg\u003c/h2\u003e \u003cp\u003eFor this study, samples were collected from the Fortress of Louisbourg skeletal collection, specifically the Rochefort Point Cemetery site. Located in Cape Breton, Nova Scotia, Canada, the Rochefort Point Cemetery was established in 1738, serving the French inhabitants of the site until 1745, after which the occupying New Englanders used the cemetery until 1749, when the French returned. The French used the cemetery for an additional 10 years until the second period of English occupation, which ultimately led to the site\u0026rsquo;s destruction and abandonment in the early 1760s (Johnston \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e1984\u003c/span\u003e; Moore \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e1974\u003c/span\u003e). A rescue excavation of the Rochefort Point Cemetery began in 2017 due to ongoing coastal erosion. Permission to excavate and analyze these remains has been granted by Parks Canada, the Roman Catholic Diocese of Antigonish, the Anglican Diocese of Nova Scotia and Prince Edward Island, and in consultation with the Nova Scotia Mi\u0026rsquo;kmaq Chiefs. All individuals are being temporarily housed at Trent University under the stewardship of Dr. Amy Scott and will be reburied.\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e2.1.1 Sampling Criteria\u003c/h2\u003e \u003cp\u003eFor this study, only individuals with preserved hair and bone were sampled. This narrow criterion was essential to allow for the comparison of cortisol concentrations across tissue types and to compare osteocalcin concentrations with both hair and bone cortisol values. Due to varying states of skeletal preservation, only adolescent and adult individuals could be sampled. The assessment of age and sex was completed using standard skeletal morphological features (Christensen et al. 2024). For the cortisol and osteocalcin skeletal samples, cortical bone tissue was extracted from the ectocranial surface of the posterior parietal bone, as this element was consistently present and sufficiently preserved across all individuals. While current research shows no significant difference in osteocalcin concentrations across different skeletal elements (see Hughes \u0026amp; Scott, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Scott et al., \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), given the novelty of bone cortisol extraction, it was determined that the best practice was to establish sample consistency.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Sampling and Pre-Treatment\u003c/h2\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e2.2.1 Hair\u003c/h2\u003e \u003cp\u003eUsing tweezers, hairs from each individual were collected with centimetre-long segments sectioned using a scalpel when possible (see B. Schaefer, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Webb et al., \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). The directionality of these hair samples was determined by observing the imbricate scale pattern of the hair shaft under a compound microscope (Harland and Plowman \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), as no roots were present. Therefore, the chronology of each hair segment (i.e., most recent to least recent) could be confidently assessed, but it was not possible to determine how close to the time of death these segments represented without a root present. For each segment of analysis, 10 mg of hair was transferred to 2 ml tubes, cleaned with 500 \u0026micro;L of isopropyl alcohol, and finely minced using sterilized dissection scissors.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003e2.2.2 Bone\u003c/h2\u003e \u003cp\u003eUsing a Dremel rotary tool (model 300) with a rounded carbide burr, the outer cortical surface of the ectocranial posterior-lateral portion of the parietal was removed to expose approximately 3 cm\u003csup\u003e2\u003c/sup\u003e of inner cortical bone free from soil or debris. The carbide burr was then sanitized in an ethanol flame before and after each sample collection. Approximately 260 mg of bone powder was collected from each individual (10 mg for osteocalcin and 250 mg for cortisol analysis) and transferred to an Eppendorf Lo-Bind 2 ml tube (Charapata et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Hughes \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Hughes and Scott \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Scott et al. \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Extraction and Quantification\u003c/h2\u003e \u003cdiv id=\"Sec11\" class=\"Section3\"\u003e \u003ch2\u003e2.3.1 Osteocalcin\u003c/h2\u003e \u003cp\u003eOsteocalcin samples were collected, demineralized, filtered, and quantified following the procedure outlined by Hughes and Scott (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). This involved adding 10% by weight of ethylenediaminetetraacetic acid (EDTA) to each bone sample for 24 hours of demineralization at 5\u0026deg;C, followed by centrifugation at 14,000g for 10 minutes to separate the liquid substrate. To lower the concentration of EDTA from 342.2mM to below the 6.1mM threshold needed for quantification, samples were filtered down to 50 \u0026micro;l in an Amicon Ultra-0.5 filter and subsequently diluted by three cycles of dilution and 14,000g centrifugation to reduce concentrations of the EDTA 1,000-fold with buffer exchange using 1X PBS. Finally, samples were eluted from 50 \u0026micro;l to 200 \u0026micro;l. All samples were quantified at a 1:30 dilution using a commercially available osteocalcin ELISA kit (ALPCO Diagnostics 43-OSNHU-E01) according to the manufacturer\u0026rsquo;s protocols. All samples were run in duplicate. The ELISA\u0026rsquo;s ODs were read and converted to ng/ml with a Fisher Scientific Multiskan FC Microplate Reader Version 1.01.16 at 450nm and a 4-parameter logarithmic curve.\u003c/p\u003e \u003cp\u003eThe total protein content per sample was quantified using a commercially available bicinchoninic acid (BCA) assay (Thermo Scientific Pierce BCA Protein Assay) to normalize osteocalcin concentrations. Following the manufacturer\u0026rsquo;s protocols, protein concentrations in a 1:2 dilution were quantified on a Fisher Scientific Multiskan FC Microplate Reader Version 1.01.16 at 562 nm and translated to concentrations with a 4-parameter logarithmic curve. The final conversion of concentrations of osteocalcin from the original ELISA (ng/ml) output to the standard osteocalcin reporting language (nanogram of osteocalcin per microgram of total protein content [ng/\u0026micro;g]) was calculated with Eq.\u0026nbsp;1.\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:A\\times\\:\\frac{B}{C}\\times\\:\\frac{D}{E}=F$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eEquation 1: The mathematical conversion of samples initially reported osteocalcin concentrations in ng/ml to ng/\u0026micro;g. A, the original ELISA output (ng/ml), is multiplied by B, the ELISA dilution factor (30X), divided by C, the filtration ratio (0.5). This product is subsequently multiplied by the elution volume (ml) (D) divided by the original BCA protein assay output (\u0026micro;g/ml) (E) to result in F, the final osteocalcin concentration in the units ng/\u0026micro;g (Hughes \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e \u003ch2\u003e2.3.2 Cortisol\u003c/h2\u003e \u003cp\u003eMethanol solvent was added to each hair and bone tube, approximately 1 ml and 1.46 ml, respectively, to match the amounts of methanol used in previous successful methods (see Webb et al., \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Charapata et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). All samples were placed on a test-tube shaker at 250 revolutions per minute (rpm) for 18 hours at ambient temperature. Samples were then spun down, and the supernatants were transferred to new tubes, which were then dried in a vacuum centrifuge. Each sample was reconstituted in 250 \u0026micro;L of pH 7.6 PBS. Recent research has identified a link between long-term storage and the decrease of cortisol levels found in modern hair samples (see Huthsteiner et al., 2025). Suggesting this decline was no longer statistically significant after six months of storage as cortisol concentrations stabilize in hair samples. Considering the samples in this study have been exposed to burial conditions for over two centuries, the effects of laboratory storage were likely minimal in comparison. Additionally, the continued success of comparable archaeological hair studies (see Webb et al., \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; L\u0026oacute;pez-Barrales et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Tisdale et al., \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) further supports that cortisol can remain sufficiently preserved and stable for comparative analyses.\u003c/p\u003e \u003cp\u003eBoth hair and bone samples were quantified using the same commercially available enzyme-linked immunosorbent assay (ELISA, ALPCO Diagnostics 11-CORHU-E01-SLV), following the manufacturer's protocol. All samples were run in duplicate. The ODs per read were translated to ng/ml in the same manner as osteocalcin. Cortisol concentrations were converted from ng/ml (the original ELISA output) to the standard reporting language of previous hair cortisol studies (ng of cortisol per gram of substrate [ng/g]) using Eq.\u0026nbsp;2.\u003cdiv id=\"Equb\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equb\" name=\"EquationSource\"\u003e\n$$\\:\\frac{A}{B}\\times\\:\\frac{C}{D}\\times\\:E\\times\\:\\text{1,000}=F$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eEquation 2: The mathematical conversion of samples initially reported cortisol concentrations in ng/ml to ng/g. A, the original ELISA output (ng/ml), is divided by B, the weight (mg) of the substrate used for the extraction. This result is then multiplied by C, the volume of methanol (ml) used for cortisol extraction. The product is divided by D, the volume of methanol (ml) transferred for drying. Finally, the result is multiplied by E, the volume of PBS solution used for reconstituting the cortisol extract, and then multiplied by 1,000 to obtain F, the final value expressed in picogram-per-milligram\u0026mdash;mathematically equivalent to nanogram-per-gram (Meyer et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Diagenesis\u003c/h2\u003e \u003cp\u003eGiven the novelty of hormone extraction from mineralized tissues, the relationship between these extracted hormones and diagenesis remains understudied; however, it was evaluated in this study. Fourier-transform infrared spectroscopy (FTIR) was used to quantify the degree of diagenesis in each sample. Using approximately 1-2mg of powdered bone, IR spectra were collected with a Bruker Alpha II FTIR spectrometer with an attenuated-total reflectance (ATR) accessory. All IR spectra were composited from twenty-four absorbance scans collected for each sample between 400-4,000 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e with a resolution of 8 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and automatically baseline-corrected for absorbance peak heights in Opus FTIR software. The carbonate-phosphate ratio (C/P), infrared splitting factor (IRSF), and amide I-phosphate ratio (AmI/P) were calculated using wavenumber ranges and absolute absorbance peaks as recommended by Smith et al. (\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"3. RESULTS","content":"\u003cp\u003eFor this study, 10 individuals were assessed. All individuals whose age could be estimated were over 14.5 years. Sex could be determined for only four individuals, all male. All 10 individuals had hair and sufficient preservation of the ectocranial parietal bone (see Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSkeletal sample information, hair and bone cortisol and osteocalcin concentrations, and the FTIR-based measurements of diagenetic alteration (IRSF, C/P, AmI/P) for the Rochefort Point Cemetery\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"14\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eBurial #\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eEst.Age (years)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eHair\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSkeletal element\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003eHair Cortisol (ng/g)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAvg.Hair Cortisol (ng/g)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eBone Cortisol (ng/g)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eOsteocalcin (ng/\u0026micro;g)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eIRSF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eC/P\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c14\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAmI/P\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSegment 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSegment 2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eSegment 3\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3/2017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30\u0026ndash;35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e✓\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eParietal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e15.785\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6.651\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e11.22\u0026thinsp;\u0026plusmn;\u0026thinsp;6.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e3.926\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e6.796\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e3.268\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.306\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e0.220\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12/2017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e✓\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eParietal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5.101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e3.339\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e7.606\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e3.452\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.241\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e0.223\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15/2017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e✓\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eParietal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e15.438\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e12.019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7.372\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e11.61\u0026thinsp;\u0026plusmn;\u0026thinsp;4.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e5.632\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e4.206\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e3.206\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.292\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e0.259\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e88/2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25\u0026ndash;29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e✓\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eParietal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e11.218\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e11.218\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e4.422\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e7.335\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e3.255\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.287\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e0.246\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e120/2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15.5+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e✓\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eParietal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e29.567\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e31.864\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8.200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e23.21\u0026thinsp;\u0026plusmn;\u0026thinsp;13.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e8.175\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e2.361\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e3.908\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.161\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e0.124\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e136/2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e✓\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eParietal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e16.453\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e17.254\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e16.85\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e7.286\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e6.619\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e3.785\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.132\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e0.078\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e154/2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16.5+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e✓\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eParietal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e18.296\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e18.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e8.093\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e6.961\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e3.677\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.155\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e0.124\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e172/2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14.5+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e✓\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eParietal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e9.936\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e20.833\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e15.38\u0026thinsp;\u0026plusmn;\u0026thinsp;7.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e11.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e5.778\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e3.276\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.227\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e0.255\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e194/2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15.5+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e✓\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eParietal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e18.697\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e12.126\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e20.326\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e17.05\u0026thinsp;\u0026plusmn;\u0026thinsp;4.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e9.438\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e3.849\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e3.703\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.152\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e0.126\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e211/2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15.5+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e✓\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eParietal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e18.376\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e18.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e6.207\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e3.610\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e3.715\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.164\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e0.154\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"14\"\u003eU - undetermined\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Coefficient of Variance\u003c/h2\u003e \u003cp\u003eTo assess intra-observer error, since assays were conducted in duplicate for each sample, the coefficient of variance (CV) was calculated \u0026mdash; the standard method for measuring error in assay analyses (Reed et al. \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). Mean %CV per assay is shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, with intra-assay reproducibility falling well within accepted limits of below 10% (Klymus et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Reed et al. \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2002\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescription of per-assay-per-tissue mean coefficient of variance\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAssay\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTissue\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e%CV\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCortisol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHair\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14.02\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCortisol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.18\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOsteocalcin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.88\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBCA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003e\u003csup\u003e\u0026dagger;\u003c/sup\u003eWhile cortisol extracted from hair shows an elevated CV, all cortisol extractions (hair and bone) were collected in a single assay; the overall CV was 9.53%\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Osteocalcin\u003c/h2\u003e \u003cp\u003eAll ten parietal bone samples produced quantifiable osteocalcin concentrations (see Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Concentration values ranged between 2.361 and 7.606 nanograms of osteocalcin per microgram of total bone protein (ng/\u0026micro;g). The average osteocalcin concentration across these 10 individuals fell slightly to the left of the center at 5.370\u0026thinsp;\u0026plusmn;\u0026thinsp;1.82 ng/\u0026micro;g with a median concentration value of 5.778 ng/\u0026micro;g (see Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Cortisol and Its Relationship to Osteocalcin\u003c/h2\u003e \u003cp\u003eCortisol was successfully extracted and quantified from 19 hair samples (4 individuals with 1 segment, 3 individuals with 2 segments, and 3 individuals with 3 segments) (see Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Cortisol concentrations ranged between 5.101 and 31.864 nanograms of cortisol per gram of hair (ng/g), with an average value of 15.55\u0026thinsp;\u0026plusmn;\u0026thinsp;7.17 ng/g and a median value of 15.785 ng/g. All 10 bone samples showed quantifiable cortisol levels, representing the first successful extraction from human cortical bone. These bone cortisol concentrations ranged from 3.339 ng/g to 11.011 ng/g, with an average value of 6.75\u0026thinsp;\u0026plusmn;\u0026thinsp;2.49 ng/g and a median value of 6.747 ng/g (see Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe comparison of cortisol in hair and bone samples showed a significant positive relationship (ρ\u0026thinsp;=\u0026thinsp;0.68; P\u0026thinsp;=\u0026thinsp;0.029). Comparing bone cortisol to osteocalcin indicated a nonsignificant indirect relationship (ρ = -0.59; P\u0026thinsp;=\u0026thinsp;0.074). The osteocalcin and hair cortisol comparison showed a significant inverse trend (ρ = -0.77; P\u0026thinsp;=\u0026thinsp;0.009) (see Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e3.5 Diagenesis\u003c/h2\u003e \u003cp\u003eTo evaluate the severity of diagenetic alteration, the upper and lower limits for IRSF and C/P proposed by France and colleagues (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) and the threshold for AmI/P from Hollund et al., (2012) were used. No individual fell outside of the range of well-preserved archaeological remains (see Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWhen bone-derived cortisol was compared to our collected metrics of diagenesis, there was a statistically significant indirect correlation between bone-derived cortisol concentrations and worsening preservation [IRSF (ρ\u0026thinsp;=\u0026thinsp;0.72; P\u0026thinsp;=\u0026thinsp;0.019); C/P (ρ = -0.79; P\u0026thinsp;=\u0026thinsp;0.007)]. This contrasted with comparisons between the same metrics and osteocalcin, which, while not statistically significant [IRSF (ρ = -0.56; P\u0026thinsp;=\u0026thinsp;0.09); C/P (ρ\u0026thinsp;=\u0026thinsp;0.44; P\u0026thinsp;=\u0026thinsp;0.206)], showed positive correlations between increased osteocalcin concentrations and better skeletal preservation (see Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. DISCUSSION","content":"\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Osteocalcin\u003c/h2\u003e \u003cp\u003eThe initial observation of the extracted osteocalcin concentrations showed noticeably lower levels compared to other studies from other geographic/temporal sites (Scott et al. \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2016\u003c/span\u003e, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) and, while not statistically significant (Z:1.11; P: 0.27), lower than previous osteocalcin samplings at the Fortress of Louisbourg site (Hughes and Scott \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) (see Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe higher osteocalcin concentrations observed in Scott et al. (\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) compared to other studies are likely because it is the only one among these four to use LC/MS for quantification, and therefore, it is not an ideal comparison in this regard. Outside of that, the most significant difference is observed between Scott et al. (\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) and this study, possibly due to differences in cortical thickness at the sampling site. As shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, when cortical thickness decreases osteocalcin decreases accordingly.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eReference ranges of archaeological osteocalcin concentrations compared to the concentrations from this study, as well as comparisons of median osteocalcin concentrations to sampled element and cortical bone thickness\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStudy\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSample Size\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReference Range (ng/\u0026micro;g)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSampled Element\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAverage cortical thickness (mm)*\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMedian osteocalcin concentration (ng/\u0026micro;g)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHughes \u0026amp; Scott (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2023\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.80-19.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFemur\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.81\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScott et al., (\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2020\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26.0-310.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFemur\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026ndash;\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScott et al., (\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2016\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.28\u0026ndash;60.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFemur\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScott et al., (\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2016\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.91\u0026ndash;53.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eClavicle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThis study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.36\u0026ndash;7.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eParietal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e*(Hollensteiner et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Kakutani et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Peebles et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eWhile visibly apparent, this comparison was also statistically significant when evaluated using a Kruskal-Wallis test (H: 6.29; P: 0.043) with Dunn\u0026rsquo;s post hoc test between each skeletalt element [Femur to Clavicle (Z: 0.064; P:0.61); Clavicle to Parietal (Z: 1.95; P: 0.153); Femur to Parietal (Z: 2.48; P: 0.04)]. This is not surprising as thicker cortical bone, representing a longer time depth, would have more opportunity to store osteocalcin, compared to thinner cortical bone, which represents a shorter time depth, and would have less time to accumulate these biomolecules before sampling. As discussed by Scott et al. (\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), the future of osteocalcin cortical bone sampling will be impacted by how the sampling site can be better sectioned to represent succinct periods of time and possible stress events, rather than arbitrary sectioning, which may lead to an averaging effect of osteocalcin concentrations across various periods of time when the cortical bone was forming.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Cortisol\u003c/h2\u003e \u003cp\u003eCortisol extraction methods for hair have been well-established in archaeological studies for nearly two decades; therefore, the successful extraction of cortisol in this study was not unexpected. However, the low cortisol levels compared to similar studies (see Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e) were surprising. Given Louisbourg\u0026rsquo;s historical context, there is no reason to believe that the stress experienced at this site was systematically less than that experienced by other populations. Therefore, methodological factors are likely responsible for the lower cortisol concentrations observed. Heat is often, but not universally, applied in the methanol aliquoting stage of cortisol extraction (Meyer et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Applying heat increases the solubility of a solute (i.e., cortisol) in a solvent (i.e., methanol), meaning there would likely be an increased extraction efficiency of cortisol when subjected to heat (Meyer et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Schmid and Voigt \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e1954\u003c/span\u003e). Comparing this study\u0026rsquo;s hair cortisol concentrations to those who similarly did not employ heat in their extraction (see Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), the values more closely align with one another. In a round-robin study by Russell et al. (\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) focused on quantification methods, labs also differed in heat use in cortisol extractions, and despite a strong correlation, the lab that did not use heat had lower values. This highlights the importance of considering procedural steps in cross-study comparisons to ensure concentration values reflect genuine physiological stress, not extraction efficiency.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eClinical and archaeological reference ranges of hair cortisol concentrations compared to the concentrations from this study, studies without heated extraction bolded\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStudy\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eArchaeological or Clinical\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSample Size\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAge Range (years)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eReference range (ng/g)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCieszynski, Jendrzejewski, Wisniewski, Owczarzak, \u0026amp; Sworczak, 2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eClinical\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e53\u0026ndash;73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.0-51.63\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChan, Sauv\u0026eacute;, Tokmakejian, Koren, \u0026amp; Van Uum, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2014\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eClinical\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20\u0026ndash;76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e27\u0026ndash;200\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDettenborn, Tietze, Kirschbaum, \u0026amp; Stalder, 2012\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eClinical\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e360\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1\u0026ndash;91\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e7.2\u0026ndash;31.2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eF\u0026ouml;cker et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2016\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eClinical\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e20\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e15\u0026ndash;18\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e2.86\u0026ndash;22.24\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHenley et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2014\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eClinical\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;20\u0026ndash;60+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e189\u0026ndash;400\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHenley et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2013\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eClinical\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e26\u0026ndash;204\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGonzalez et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2019\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eClinical\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e232\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30\u0026ndash;60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e40\u0026ndash;128\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePereg et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2011\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eClinical\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50\u0026ndash;72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e76.58\u0026ndash;949.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSauv\u0026eacute;, Koren, Walsh, Tokmakejian, \u0026amp; 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Ramos, 2022; Zorropata -Peru\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eArchaeological\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e20\u0026ndash;35\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e3.9\u0026ndash;10.3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eL\u0026oacute;pez-Barrales et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; San Pedro de Atacama - Chile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eArchaeological\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19\u0026ndash;38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e33.7\u0026ndash;152\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eB. Schaefer, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Huaca De Los Sacrificios \u0026ndash; Peru\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eArchaeological\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18.02-247.95\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTisdale et al., \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Kellis 2 cemetery - Egypt\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eArchaeological\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19\u0026ndash;60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e272.5\u0026ndash;467\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWebb et al., 2015a; Cahuachi - Peru\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eArchaeological\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;3\u0026ndash;12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e757\u0026ndash;2507\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWebb et al., 2015b; Cahuachi and Huaca del Loro - Peru\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eArchaeological\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e125\u0026ndash;2392\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWebb et al., \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Cajamarquilla, Leymebamba, Puruchuco, Tucume, and Nasca - Peru\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eArchaeological\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAdult \u003csup\u003e\u0026Dagger;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e91\u0026ndash;707\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eThis study\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eArchaeological\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e10\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;14.5\u0026ndash;35\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e5.10-31.86\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003e\u0026dagger;\u003c/sup\u003eHistorical (early-to-mid twentieth century) \u003csup\u003e\u0026Dagger;\u003c/sup\u003eDescription of age lacked specificity\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThis study is the first to extract and quantify cortisol from human cortical bone successfully. While this is a significant outcome, it is not surprising, given the previous successes in other non-human mammals and the chemical similarities of cortisol across mammal species (Charapata et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Fokidis et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Sperou et al. \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The correlation between hair and bone cortisol values, while limited in power due to the small sample size, is a significant step toward validating this novel method for extracting cortisol from human cortical bone. Since cortisol was extracted from hair and bone in parallel, any methodological effects on concentrations (e.g., heat versus no-heat extraction) would affect samples equally and thus would not be a major factor in the observed correlation between cortisol concentrations across tissues.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Osteocalcin and Cortisol\u003c/h2\u003e \u003cp\u003eThe correlation between hair-derived cortisol and osteocalcin is a highly significant yet unsurprising result of this study, given the biological relationship between these two hormones (Berger and Karsenty \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Although limited in statistical power, this correlation offers initial support for further research into osteocalcin\u0026rsquo;s potential as a proxy for cortisol levels in studies of physiological stress, where lower osteocalcin levels suggest increased physiological stress throughout life. While bone-derived cortisol showed a similarly inverse relationship, it did not reach statistical significance, likely due to limited statistical power. From a methodological standpoint, the directional alignment between the two sources of cortisol and osteocalcin provides some additional validation of the extraction of cortisol from human cortical bone and of ELISA-based quantification, as both show the theoretically expected inverse directionality with osteocalcin concentrations.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec23\" class=\"Section2\"\u003e \u003ch2\u003e4.4 Diagenesis\u003c/h2\u003e \u003cp\u003eGiven the novelty of extracting cortisol from archaeological bone, the significant correlation between bone cortisol levels and two of three diagenesis metrics (see Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) is a key finding. While notable, this result is unsurprising given the impact of diagenetic alteration and the chemistry of methanol-based hormone extraction. As bone undergoes diagenetic alteration, the tissue becomes more permeable and thus more susceptible to leaching (Bosio et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Martin \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Since methanol-based hormone extraction depends on solubility and permeation into a substrate, we are likely observing increased extraction efficiency as methanol penetrates more compromised bone tissue (Fern\u0026aacute;ndez Aj\u0026oacute; et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThis observed impact of diagenesis on cortisol extraction from bone is a crucial consideration, as it can lead to comparisons of physiological stress between individuals in which differences may stem from extraction efficiency rather than genuine biological phenomena. Given the ongoing need for a reporting language that normalizes cortisol concentrations extracted from mineralized tissues, we propose normalizing bone-derived cortisol using a preservation metric. Given that C/P showed the strongest correlation with our bone-derived cortisol concentrations (see Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), we adopt a new reporting language: nanograms of cortisol per gram of bone per C/P value (ng/g/CP). Using this new scale, it is possible to maintain a statistically significant relationship between cortisol derived from hair and bone, while also garnering a statistically significant relationship between osteocalcin and bone-derived cortisol (see Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eWe likely observe the opposite phenomenon in osteocalcin concentrations, with levels decreasing as diagenesis worsens (see Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) due to contrasting impacts of diagenesis on these chemical extraction processes. Osteocalcin extraction using EDTA works by cleaving the protein from the calcium ion in the bone\u0026rsquo;s bioapatite molecule (Kanje et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). As the bioapatite structure continues to be compromised by diagenesis, there will understandably be lower quantifiable levels of osteocalcin (Keenan \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Scott et al. \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). While this correlation was not statistically significant, in part due to sample size, it may also be influenced by the fact that no sample fell outside the established range of well-preserved archaeological remains (France et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Hollund et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Presumably, if there were a mix of samples above and below these thresholds, we would likely see a stronger statistical connection.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003e4.5 Limitations\u003c/h2\u003e \u003cp\u003eThis study is constrained by its small sample size, limiting the strength of its statistical conclusions. Focused on confirming human cortical bone as a source for cortisol extraction and investigating the relationship between osteocalcin and the ASR, the research design prioritized individuals with both hair and usable cortical tissue present, thereby restricting the number of individuals who could be sampled. For both cortisol and osteocalcin analyses, only one type of cortical bone was examined due to sample preservation limitations, limiting the ability to directly assess the effects of cortical thickness and vascularity on hormone concentrations. The difference between heated and non-heated extraction resulted in lower cortisol concentrations in this study. While this does not directly affect the ability to compare cortisol concentrations relative to other samples extracted and quantified in parallel, it does restrict cross-study comparisons of cortisol. Since hair samples from this study did not have intact roots, we could not confirm that each individual's hair segments represented the same period of life, even though we could confirm the chronology per person. We also could not confirm the timeline of the collected osteocalcin concentrations based on the depth of cortical bone removed for demineralization and extraction.\u003c/p\u003e \u003c/div\u003e"},{"header":"5. CONCLUSIONS","content":"\u003cdiv id=\"Sec26\" class=\"Section2\"\u003e \u003ch2\u003e5.2 Future Works\u003c/h2\u003e \u003cp\u003eThis study has demonstrated that extraction methods can significantly influence hair cortisol concentrations, making cross-study comparisons challenging. Clarifying the reporting language and the normalization of bone cortisol is essential, given its novelty. Charapata et al. (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2018\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), for instance, normalize cortisol concentrations to total lipid content obtained through Soxhlet extraction. We propose normalizing based on the degree of diagenetic alteration, as measured by FTIR, but further research would be needed to determine what is most informative. Further sampling from different skeletal elements and cortical bone layers will enhance our understanding of temporal hormone assessments. Larger-sample studies are also needed to establish robust reference ranges for osteocalcin and bone cortisol comparisons across studies. The relationship between osteocalcin concentrations in hard and soft tissues has not yet been examined, but is needed to more conclusively understand the correlation between the two and to better understand how osteocalcin present in bone relates to systemic levels circulating within the body.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec27\" class=\"Section2\"\u003e \u003ch2\u003e5.3 Research Impact\u003c/h2\u003e \u003cp\u003eThis study confirms that cortisol can be extracted from human cortical bone using adapted animal procedures, expanding the geographic potential for bioarchaeological cortisol-based stress studies beyond regions where hair typically preserves well. The correlation between hair and bone cortisol provides initial validation of this extraction method, suggesting bone as a viable alternative tissue when hair is unavailable. Importantly, normalizing bone cortisol concentrations using C/P ratios appears to account for diagenetic effects, enabling more confident, authentic comparisons between individuals. The observed inverse correlation between osteocalcin and cortisol, while preliminary, suggests osteocalcin warrants further investigation as a potential stress-related biomarker. If substantiated, the lower sampling requirements for osteocalcin could enable research on physiological stress that is less destructive to human remains. Studies such as this one, which help to establish extraction protocols, appropriate normalizations, and cautiously evaluate the relationships between biomarkers, represent crucial foundations for advancing stress research in bioarchaeology.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003ch2\u003eFUNDING DECLARATION\u003c/h2\u003e\n\u003cp\u003eThis work was supported by a SSHRC Partnership Development Grant (Scott 890-2017-0049).\u003c/p\u003e\n\u003cp\u003eHUMAN ETHICS AND CONSENT TO PARTICIPATE\u003c/p\u003e\n\u003cp\u003ePermission to excavate and analyze these remains has been granted by Parks Canada, the Roman Catholic Diocese of Antigonish, the Anglican Diocese of Nova Scotia and Prince Edward Island, and in consultation with the Nova Scotia Mi\u0026rsquo;kmaq Chiefs. All individuals are being temporarily housed at Trent University under the stewardship of Dr. Amy Scott and will be reburied.\u003c/p\u003e\n\u003cp\u003eCRediT AUTHORSHIP CONTRIBUTION STATEMENT\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eBenjamin Kaufman: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Visualization, Writing \u0026ndash; original draft. Amy Scott: Funding acquisition, Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Visualization, Supervision, Project administration, Resources, Validation, Writing \u0026ndash; review \u0026amp; editing.\u003c/p\u003e\n\u003ch2\u003eAcknowledgement\u003c/h2\u003e\n\u003cp\u003eThe authors of this publication acknowledge that the Fortress of Louisbourg Historic Site lies on the unsurrendered and unceded territory of the Mi\u0026rsquo;kmaq nation. The authors would like to thank Parks Canada, the Roman Catholic Diocese of Antigonish, the Anglican Diocese of Nova Scotia and Prince Edward Island, the Mi\u0026rsquo;kmaq Chiefs of Cape Breton, and to staff, students, and volunteers at the Bioarchaeology Field School held at the Fortress of Louisbourg, as well as Arra Oman. Thank you to Dr. Anna Ignaszak for access to the J. Richard Armstrong Chemistry Laboratory, and the FTIR-ATR instrument. Thank you to Dr. Dion Dunford for the UNB Department of Biology\u0026rsquo;s vacufuge.\u003c/p\u003e\n\u003ch2\u003eData Availability\u003c/h2\u003e\n\u003cp\u003eThe authors of paper do not have the authorization to make data collected in this study open to the public based on agreements with Parks Canada, the Roman Catholic Diocese of Antigonish, the Anglican Diocese of Nova Scotia and Prince Edward Island, and the Mi\u0026rsquo;kmaq Chiefs of Cape Breton.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAGARWAL SC (2016) BONE MORPHOLOGIES AND HISTORIES: LIFE COURSE APPROACHES IN BIOARCHAEOLOGY. 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We preliminarily investigate osteocalcin\u0026rsquo;s potential as a less destructive, more accessible biomarker for physiological stress assessment.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis study analyzed ten individuals from the 18th-century Fortress of Louisbourg. Fourier-transform infrared spectroscopy (FTIR) was employed to assess the effects of diagenesis. Cortisol was measured from hair and cortical bone samples, and osteocalcin was quantified from the bone samples using an enzyme-linked immunosorbent assay (ELISA).\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eCortisol was extracted and quantified from 19 hair and 10 bone samples. Bone cortisol significantly correlated with hair cortisol (ρ: 0.68; P: 0.029), whereas osteocalcin showed a significant inverse correlation with hair cortisol (ρ: -0.77; P: 0.009) and a similar, non-significant trend with bone cortisol (ρ: -0.59; P: 0.074). Diagenetic alteration significantly affected bone cortisol (ρ: -0.70; P: 0.007), with increased degradation linked to higher extracted cortisol. Normalizing bone cortisol by the carbonate-phosphate ratio strengthened correlations with osteocalcin (ρ: -0.65; P: 0.043).\u003c/p\u003e\u003ch2\u003eDiscussion\u003c/h2\u003e \u003cp\u003eThese findings help establish a reproducible protocol for extracting and properly normalizing cortisol for inter-individual comparisons in archaeological human bone, enabling cortisol-based research in regions where hair rarely preserves. The correlation between hair and bone cortisol confirms bone as a viable source of cortisol for the study of physiological stress archaeologically. The inverse relationship between osteocalcin and cortisol suggests osteocalcin's potential as a stress biomarker and merits further research.\u003c/p\u003e","manuscriptTitle":"Bone-afide Stress: Methodological Assessment of Cortisol and Osteocalcin Extraction from Archaeological Human Remains","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-07 08:29:39","doi":"10.21203/rs.3.rs-9281736/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"46780622265425397020425100934718311849","date":"2026-05-15T08:29:29+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-05-14T11:46:06+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-02T08:00:00+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-01T23:49:53+00:00","index":"","fulltext":""},{"type":"submitted","content":"Archaeological and Anthropological Sciences","date":"2026-03-31T15:02:33+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"archaeological-and-anthropological-sciences","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"aasc","sideBox":"Learn more about [Archaeological and Anthropological Sciences](http://link.springer.com/journal/12517)","snPcode":"12520","submissionUrl":"https://submission.nature.com/new-submission/12520/3","title":"Archaeological and Anthropological Sciences","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"4d392058-1a1b-43b1-9d5f-b68029ec8e91","owner":[],"postedDate":"May 7th, 2026","published":true,"recentEditorialEvents":[{"type":"reviewerAgreed","content":"46780622265425397020425100934718311849","date":"2026-05-15T08:29:29+00:00","index":6,"fulltext":""},{"type":"reviewersInvited","content":"2","date":"2026-05-14T11:46:06+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-14T11:54:19+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-07 08:29:39","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9281736","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9281736","identity":"rs-9281736","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}