scholarly journals Linking structural and compositional changes in archaeological human bone collagen: an FTIR-ATR approach

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Antonio Martínez Cortizas ◽  
Olalla López-Costas
Keyword(s):  
Bronze Age ◽  
Quality Indicators ◽  
Principal Components ◽  
Structural Equation ◽  
Structural Equation Models ◽  
Cost Effective ◽  
Bone Collagen ◽  
Spectroscopic Techniques ◽  
C And N ◽  
Atr Spectroscopy

Abstract Collagen is the main structural and most abundant protein in the human body, and it is routinely extracted and analysed in scientific archaeology. Its degree of preservation is, therefore, crucial and several approaches are used to determine it. Spectroscopic techniques provide a cost-effective, non-destructive method to investigate the molecular structure, especially when combined with multivariate statistics (chemometric approach). In this study, we used FTIR-ATR spectroscopy to characterise collagen extracted from skeletons recovered from necropoleis in NW Spain spanning from the Bronze Age to eighteenth century AD. Principal components analysis was performed on a selection of bands and structural equation models (SEM) were developed to relate the collagen quality indicators to collagen structural change. Four principal components represented: (i) Cp1, transformations of the backbone protein with a residual increase in proteoglycans; (ii) Cp2, protein transformations not accompanied by changes in proteoglycans abundance; (iii) Cp3, variations in aliphatic side chains and (iv) Cp4, absorption of the OH of carbohydrates and amide. Highly explanatory SEM models were obtained for the traditional collagen quality indicators (collagen yield, C, N, C:N), but no relationship was found between quality and δ13C and δ15N ratios. The observed decrease in C and N content and increase in C:N ratios is controlled by the degradation of protein backbone components and the relative preservation of carbon-rich compounds, proteoglycans and, to a lesser extent, aliphatic moieties. Our results suggest that FTIR-ATR is an ideal technique for collagen characterization/pre-screening for palaeodiet, mobility and radiocarbon research.

scholarly journals Isotopes, Plants, and Reservoir Effects: Case Study from the Caspian Steppe Bronze Age

Radiocarbon ◽  
2012 ◽  
Vol 54 (3-4) ◽  
pp. 749-760 ◽  
Author(s):  
N Shishlina ◽  
E Zazovskaya ◽  
J van der Plicht ◽  
V Sevastyanov
Keyword(s):  
Bronze Age ◽  
Alternative Explanation ◽  
Bone Collagen ◽  
Human Diet ◽  
Human Bones ◽  
Animal Bone ◽  
Different Types ◽  
C And N ◽  
East And West

Bronze Age human and animal bone collagen from several steppe Bronze Age cultures (i.e. Early Catacomb, East and West Manych Catacomb, and Lola cultures) shows large variations in δ13C and δ15N values. In general, we observed that the older the sample, the lower the δ13C and δ15N values. We hypothesize that more positive values of δ13C and δ15N are caused by change in diet and a more arid climate. For ancient sheep during drier periods of the Early Catacomb, East and West Manych Catacomb, and Lola cultures, we observed 2 groups with different C and N isotopic compositions, reflecting consumption of different types of fodder. During periods of aridization, C4 and C3 plants with high δ15N values appeared in the vegetation, also influencing bone collagen values. Human bones show reservoir effects, caused by aquatic diet components. These effects can be quantified by paired dating of human bone and associated terrestrial samples. Reservoir corrections have revised chronologies for the region. Some paired dates do not reveal reservoir effects. This can be explained in 2 alternative ways. One is that the human diet did not include aquatic components; rather, the diet was based on C3 vegetation with high δ15N values (13–15‰), and flesh/milk of domesticated animals. An alternative explanation is that humans consumed food from freshwater resources without reservoir effects.

Measuring the Big Five in Self-Report and Other Ratings

2000 ◽  
Vol 16 (1) ◽  
pp. 31-43 ◽  
Author(s):  
Claudio Barbaranelli ◽  
Gian Vittorio Caprara
Keyword(s):  
Big Five ◽  
Structural Equation ◽  
Structural Equation Models ◽  
Error Variance ◽  
The Self ◽  
Self Report ◽  
Sources Of Information ◽  
Third Person ◽  
Fit Indexes ◽  
Response Modes

Summary: The aim of the study is to assess the construct validity of two different measures of the Big Five, matching two “response modes” (phrase-questionnaire and list of adjectives) and two sources of information or raters (self-report and other ratings). Two-hundred subjects, equally divided in males and females, were administered the self-report versions of the Big Five Questionnaire (BFQ) and the Big Five Observer (BFO), a list of bipolar pairs of adjectives ( Caprara, Barbaranelli, & Borgogni, 1993 , 1994 ). Every subject was rated by six acquaintances, then aggregated by means of the same instruments used for the self-report, but worded in a third-person format. The multitrait-multimethod matrix derived from these measures was then analyzed via Structural Equation Models according to the criteria proposed by Widaman (1985) , Marsh (1989) , and Bagozzi (1994) . In particular, four different models were compared. While the global fit indexes of the models were only moderate, convergent and discriminant validities were clearly supported, and method and error variance were moderate or low.

Collective Efficacy and Organizational Commitment in an Italian City Hall

2009 ◽  
Vol 14 (4) ◽  
pp. 363-371 ◽  
Author(s):  
Laura Borgogni ◽  
Silvia Dello Russo ◽  
Laura Petitta ◽  
Gary P. Latham
Keyword(s):  
Organizational Commitment ◽  
Collective Efficacy ◽  
Structural Equation ◽  
Structural Equation Models ◽  
Practical Significance ◽  
City Hall ◽  
Italian City ◽  
Public Sector Managers ◽  
The Individual ◽  
Level Group

Employees (N = 170) of a City Hall in Italy were administered a questionnaire measuring collective efficacy (CE), perceptions of context (PoC), and organizational commitment (OC). Two facets of collective efficacy were identified, namely group and organizational. Structural equation models revealed that perceptions of top management display a stronger relationship with organizational collective efficacy, whereas employees’ perceptions of their colleagues and their direct superior are related to collective efficacy at the group level. Group collective efficacy had a stronger relationship with affective organizational commitment than did organizational collective efficacy. The theoretical significance of this study is in showing that CE is two-dimensional rather than unidimensional. The practical significance of this finding is that the PoC model provides a framework that public sector managers can use to increase the efficacy of the organization as a whole as well as the individual groups that compose it.

A Cautionary Note on Incremental Fit Indices Reported by LISREL

Methodology ◽  
2005 ◽  
Vol 1 (2) ◽  
pp. 81-85 ◽  
Author(s):  
Stefan C. Schmukle ◽  
Jochen Hardt
Keyword(s):  
Factor Analysis ◽  
Maximum Likelihood ◽  
Structural Equation ◽  
Structural Equation Models ◽  
Null Model ◽  
Likelihood Estimation ◽  
Parameter Estimates ◽  
Fit Indices ◽  
Cautionary Note ◽  
Confirmatory Factor

Abstract. Incremental fit indices (IFIs) are regularly used when assessing the fit of structural equation models. IFIs are based on the comparison of the fit of a target model with that of a null model. For maximum-likelihood estimation, IFIs are usually computed by using the χ2 statistics of the maximum-likelihood fitting function (ML-χ2). However, LISREL recently changed the computation of IFIs. Since version 8.52, IFIs reported by LISREL are based on the χ2 statistics of the reweighted least squares fitting function (RLS-χ2). Although both functions lead to the same maximum-likelihood parameter estimates, the two χ2 statistics reach different values. Because these differences are especially large for null models, IFIs are affected in particular. Consequently, RLS-χ2 based IFIs in combination with conventional cut-off values explored for ML-χ2 based IFIs may lead to a wrong acceptance of models. We demonstrate this point by a confirmatory factor analysis in a sample of 2449 subjects.

Forced Zero Cross-Loading Misspecifications in Measurement Component of Structural Equation Models

Methodology ◽  
2014 ◽  
Vol 10 (4) ◽  
pp. 138-152 ◽  
Author(s):  
Hsien-Yuan Hsu ◽  
Susan Troncoso Skidmore ◽  
Yan Li ◽  
Bruce Thompson
Keyword(s):  
Structural Equation ◽  
Structural Model ◽  
Structural Equation Models ◽  
Equation Model ◽  
Model Fit ◽  
Model Specification ◽  
Simulation Design ◽  
Measurement Models ◽  
Fit Statistics ◽  
Path Coefficients

The purpose of the present paper was to evaluate the effect of constraining near-zero parameter cross-loadings to zero in the measurement component of a structural equation model. A Monte Carlo 3 × 5 × 2 simulation design was conducted (i.e., sample sizes of 200, 600, and 1,000; parameter cross-loadings of 0.07, 0.10, 0.13, 0.16, and 0.19 misspecified to be zero; and parameter path coefficients in the structural model of either 0.50 or 0.70). Results indicated that factor pattern coefficients and factor covariances were overestimated in measurement models when near-zero parameter cross-loadings constrained to zero were higher than 0.13 in the population. Moreover, the path coefficients between factors were misestimated when the near-zero parameter cross-loadings constrained to zero were noteworthy. Our results add to the literature detailing the importance of testing individual model specification decisions, and not simply evaluating omnibus model fit statistics.

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