Background and objective: The percentage of fat (%BF), essential data in the health or nutrition field, can be estimated by different methods. This work compares the %BF values obtained by anthropometry, Near Infrared Interactance (NIR), and Bioimpedance Analysis (BIA), in childhood and adolescence. Material and Methods: The sample consisted of 1015 schoolchildren aged 9 to 16 years. Height, weight, and four adipose folds were measured: tricipital, bicipital, subscapular, and suprailiac. The %BF by anthropometry was calculated using a specific formula based on body density (BD). A tetrapolar analyzer was used for the BIA calculation. The optical density in the biceps was measured for the one observed by NIR. Results: The high correlation and determination coefficients show that the relationship between %BF by anthropometry, BIA, or NIR is very strong, mainly between the first two. The intraclass correlation coefficient (ICC) results between Anthropometry and BIA show an almost perfect agreement. Its graphical contrast attests that the correlation is higher in the male sex. In general, the agreement between Anthropometry and BIA is higher than between Anthropometry and NIR. Conclusions: The three techniques used to measure %BF show high concordance. All ICC values between pairs of methods are above 0.90. The comparison of %BF by anthropometry with BIA or NIR shows that the affinity is higher in intermediate adiposity percentages than in extreme ones. This trend occurs in both sexes and age groups.

The Megalitho da Capella (Figueira da Foz, Coimbra, Portugal) is one of at least 21 dolmens in a megalithic complex explored by António dos Santos Rocha between 1880 and 1909. Among the human remains from Megalitho da Capella is an incomplete and fragmented cranium. Santos Rocha interpreted a groove on the parietal bone as an incision of traumatic origin with signs of remodeling that was suggestive of prolonged survival after an intentional intervention. This study provides a new examination of the groove using microcomputed tomographic (microCT) imaging, microscopy, and macroscopic observations of the groove in addition to the direct dating the skeletal remains. Results indicate that the human remains are dated to the Late Neolithic and that the "incision" is a normal anatomical variant corresponding to impressions from vascular tissue and temporal projections of the squamosal. We conclude that studies of bone surface modifications should consider normal anatomical variants (e.g., sulci, grooves, and furrows) when reporting results. Paleoimaging, microscopy, and comparative observations can assist in the identification bone modifications versus anatomical variants.

The pubic symphyseal surface is one of the reliable parameters used to estimate age, as it consistently shows degenerative observational variations throughout the lifespan, particularly from the 3rd decade onwards. These changes have been extensively studied to generate population-specific models for forensic age estimation. In the past, there have been many studies used to estimate age at death from the pubis symphysis using skeletal remains. However, due to dearth of contemporary skeletal repositories, and the resource intensive maceration process required for obtaining examination quality bones, studies on cadaver are difficult to conduct. Moreover, due to recent advancements in the science of medical imaging, newer radiological modalities like computed tomography (CT) can be used to visualize previously inaccessible areas such as the pubic symphysis in cadavers and the living alike, and subsequent age estimation is feasible. Recently, Chen et al. (2008, 2011) conducted a study on the cadaveric Chinese Han population in both males and females separately by using nine morphological changes and scoring them according to the changes that occurred. The present study aimed to estimate an individual's age using CT images of the pubic symphysis, by applying the scoring method for its morphological changes given by Chen et al. The present study was conducted on 263 randomly selected participants (Males = 154, Females = 109), who came for diagnostic purposes to the hospital. The CT images of these individuals were collected after obtaining ethical approval and proper consent from the study participants. Each of the morphological indicators was assessed, and appropriate scores were given according to criteria given by Chen et al. In the present study, both linear and multiple regression models to estimate age using the pubic symphyseal morphological changes were developed. From the results of the present study, it was concluded that the Chen et al. scoring method can be used to accurately estimate age from 3DCT images of the living, and the models derived in the present study could be applicable to individuals from the Indian subcontinent.

Within the pelvis the iliac crest and ischial tuberosity display delayed ossification and fusion, thus, presenting as reliable maturity indicators. Amongst the different iliac crest and ischial tuberosity age estimation methods, the modified Kreitner-Kellinghaus stages constitute one of the more promising methods. The present study was directed towards establishing the applicability of the modified Kreitner-Kellinghaus method using five supervised machine learning approaches. Clinical CT scans of consenting individuals were collected and scored using the modified Kreitner-Kellinghaus method for the iliac crest and ischial tuberosity, independently. Age was subsequently estimated using different machine learning models. Cumulative scores computed from both markers were additionally employed for age estimation using machine learning. For iliac crest age estimation, Random Forest and Gradient Boosting Regression furnished lowest mean absolute error (2.42 years) and root mean square error (3.06 years). For ischial tuberosity age estimation, Gradient Boosting Regression garnered the lowest computations of mean absolute error (2.60 years) and root mean square error (3.09 years). For cumulative score based age estimation, Support Vector Regression and Gradient Boosting Regression yielded lowest mean absolute error (2.48 years) and root mean square error (3.07 years). Obtained error computations indicate that the iliac crest is a more accurate age marker in comparison to the ischial tuberosity. Additionally, cumulative score-based approaches garnered similar/ marginally more precise results in comparison to the iliac crest with all five models. This marginal improvement is not sufficient to justify employing the relatively more complicated cumulative score-based approach for age estimation. Hence, whenever available, the iliac crest should be preferred over the ischial tuberosity/ cumulative score-based approaches for age estimation.

The body mass index (BMI) is used as the most common and simplest measure to predict obesity. The aim of the study was to compare the BMI method and % BF (body fat) determined by bioimpedance analysis for obesity screening and to evaluate the correlation between these methods. 200 women aged 18-25 years were included in the study. BMI ≥ 25/ ≥ 30 kg/m2 was the criterion for assessment of overweight/obesity. Body fat (BF) in % and kg was determined by bioimpedance analysis. For assessment of obesity by % BF, the criterion was ≥ 30% fat. Based on BMI, 4.5% of women were obese, 14.5% were overweight. According to % BF, up to 30% of women were obese. The largest differences between BMI and % BF categorization were found in the underweight and overweight groups. According to the BMI 43% of women in the underweight category and 34.5% in the overweight category had a % BF in the normal range. By correlation analysis, we found a strong positive statistically significant correlation in women between BMI and BF (%) (rs = 0.782, p < 0.01) and also between BMI and BF (kg) (rs = 0.880, p < 0.01). Both of these methods assess body composition in their own specific way, complement each other, and other combining them, we achieve more accurate results for determining the overall health status of an individual.

Early childhood is an important period for the rapid growth of the brain, which is crucial to neural connection and cognitive development. The purpose of this study is to characterize the age changes of endocasts in ancient children in Northwestern China (2600-2100 BP) to enrich our understanding of brain growth. 28 crania of ancient children excavated from the Zaghunluq cemetery were analyzed using endocasts generated from CT images. The endocast features of age-related changes were assessed by comparing the endocranial volume (cranial capacity), the intracranial surface area, and their ratios among different age groups: 2, 3-5, 6-7, 8-10, 12-15, and 17-19 years. The results demonstrated that with the increase of age, the volume and the surface area of children's endocasts seem to increase between age groups. The growth spurt periods of endocranial volume are 3-5 years old and 8-10 years old, and the growth spurt period of endocranial surface area is 3-5 years old, similar to the patterns in modern children. The increase of endocast surface area is smaller than that of volume, resulting in an overall increase in the ratio of endocranial volume to surface area, indicating a trend of gradual globularization of the brain.

Diagnosis of specific infectious diseases in the skeleton is often difficult and relies on expert opinion. Statistics is not often used as a tool to assist in such diagnoses, and therefore this study aimed at employing data mining and machine learning in the form of decision tree analysis to aid in recognizing tuberculosis (TB) in skeletal remains and find patterns of skeletal involvement. The sample included 387 modern South African individuals (n = 207 individuals known to have died of TB and n = 180 as a control group) which were scored for the presence or absence of 21 skeletal lesions documented to be associated with TB. A pruned decision tree classification analysis was done to detect significant patterns and associations between variables which produced a model with a moderate classification rate based on four of the variables. As expected, vertebral changes were selected first, followed by rib, acetabular and lastly cranial changes. As a proof of concept, it was shown that machine learning was able to identify patterns of changes in TB skeletons versus a control group. However, further investigation into the use of machine learning in assessing skeletal changes associated with specific diseases is needed.

Manufacturers aim to design implants fitting for the broadest possible population segment. Due to the scarcity of available morphological data of intact long bones, anatomical collections of historical bone specimens may represent valuable additional sources. Previous work on femoral morphology measurements suggests that historical specimens are widely consistent with data from present-day populations. This study aimed to investigate whether this also applies to the anatomical fitting of a clinically used femoral nail. Nail fit was computer-graphically quantified through virtual implantation into CT-based 3D models of 52 femora, comprising a subset representative of the present-day Caucasian population (n = 31), a subset from a historical medieval European bone collection (n = 20), and additionally, a dataset from a natural ice mummy from the Neolithic period. Nail fit was assessed by nail protrusion (area and distance) to the inner cortex surface and the distal nail tip's position in the medullary canal. Assessed measurements and parameters of the present-day Caucasian subset were mostly consistent with those of the medieval European subset. After adjusting for multiple testing, only the distance from lateral nail entry point to shaft axis remained significantly (p = 0.03) different when comparing our modern and medieval subsets. Subsequent bivariate (Spearman) correlation analyses for both subsets (modern and medieval) combined showed that of the three variables representing basic demographic parameters, individual age, biological sex, and femur length, most statistically significant associations to the examined nail fit measurements were found for age (six measurements at a level of p < 0.05), however, with a relatively weak monotonic correlation (rho values ranging between ±0.31 and ±0.37). The measurements for the Iceman's femur lie within the range of the modern and historical subgroups, but in some cases, differ by more than one standard deviation from the mean. Our results confirm previous findings, suggesting that more recent historical bone specimen collections may indeed be a convenient and easily accessible source of new 3D morphological data and complement existing data to be used for the development of femoral nails.

We discuss the coexistence of a postmortem cut and a pathological alteration, recorded on a skeleton belonging to an adult man that was discovered during the archaeological investigations of the cemetery of the Church of Santa Maria Maggiore in Vercelli (northern Italy, 18th-19th century). The skull presents an oblique cleft, which from the top of the frontal bone bends towards the occipital, and the left styloid process is elongated compared to normal values (48 mm). The elongated styloid process is due to the ossification of the styloid ligament which has several possible causes. To increase the knowledge about this pathological condition in the past, it was necessary to compare all the data present in the literature today and consider the few cases published in the paleopathological field. In this paper, our main goals are: i) to investigate the reasons for which the craniotomy was performed; ii) to examine the possible cause of the ossification of the styloid process, described as Eagle's syndrome; iii) to enrich the archaeological literature of elongated styloid process cases and iv) to investigate the presence of a hypothetical relationship between the autopsy cut and the diagnosed Eagle's syndrome on this skull.