A comprehensive regression tree to estimate body weight from the skeleton

The purpose of this research is to estimate actual body weight (in particular obesity) from the human skeleton. Known individuals (total n=187) were studied from the Bass Collection from the University of Tennessee, Knoxville. This research combines bone density, cross-sectional geometry of the femur and skeletal pathologies. Bone mineral density was calculated for the proximal femur. Three-dimensional bone surface models were created from computed tomographic scans. Cross-sectional geometry of the femur was calculated at five locations along the diaphysis. The pathologies analyzed were heel spurs, diffuse idiopathic skeletal hyperostosis (DISH), and tibial osteoarthritis. The best regression tree model included only four variables. The first split to estimate body weight was the minimum moment of inertia (I(y) ) at the distal femur, the second was midshaft width, then anteroposterior thickness at the proximal slice and the final split was the degree of DISH (SD 17.1-31.0 kg). The ability to estimate body weight from the skeleton is one more useful tool for the osteologist.     

Radiographic comparison of a fractured clavicle exhibiting a pseudo-arthrosis

Bone remodeling is a natural process that is potentially problematic for radiographic comparisons because it can occur after antemortem (AM) imaging, thus interfering with the comparability of AM and postmortem (PM) radiographs from the same individual. While the effects of age-related remodeling have been studied, limited attention has been given to trauma-related remodeling with respect to radiographic comparisons. This report adds to the latter topic by presenting a case of AM clavicle fracture that developed into a pseudo-arthrosis over a 12-month period prior to the individual's death. Even though remodeling was discernable along the fracture margins, adjacent skeletal features on the PM radiograph remained unaltered and constituted compelling evidence for the identification. This case illustrates the potential of using both normal and pathological anatomy concurrently to maximize the surety of findings from radiographic comparisons.     

Differentiating fragmented human and nonhuman long bone using osteon circularity

Distinguishing between human and nonhuman bone is important in forensic anthropology and archeology when remains are fragmentary and DNA cannot be obtained. Histological examination of bone is affordable and practical in such situations. This study suggests using osteon circularity to distinguish human bone fragments and hypothesizes that osteons will more closely resemble a perfect circle in nonhumans than in humans. Standard histological methods were used, and circularity was determined using an image analysis program, where circularity was controlled for by Haversian canal measurements. Homogeneity was first tested for multiple variables within human and nonhuman samples. No significant differences were found between human sexes (p = 0.657) or among nonhuman species (p = 0.553). Significant differences were found among intraskeletal elements of both humans (p = 0.016) and nonhumans (p = 0.013) and between pooled samples of humans and nonhumans (p < 0.001). Results of this study indicate that osteon circularity can be used to distinguish between fragmented human and nonhuman long bone.     

Identification from Chest X‐Rays: Reliability of Bone Density Patterns of the Humerus*

Abstract: A critical review of Kahana and Hiss’ study on identification from bone trabecular pattern and a test of their method conducted on the humerus are presented. Bone trabecular pattern was studied through the generation of a numerical file representing the gray scale. Using the correlation coefficient, several pairwise comparisons between numerical files were performed. The test gave nearly 30% of incorrect exclusions (the method did not recognize couples of radiographs belonging to the same subject) and 50% of misidentifications (the method recognized couples of radiographs belonging to different subjects, as belonging to the same subject); therefore, this research shows that at the present time, it is not possible to safely quantify identification through bone density patterns, of the proximal humerus taken from thoracic X‐rays. Thus, an “easy”—but dangerous—use of trabecular density patterns on this specific type of radiogram as an identification method should be currently avoided.     

应用Miseq FGx平台检测降解骨骼样本效果初探

目的评估Miseq FGx平台检测降解骨骼样本效果。方法对10例基于PCR-CE方法 STR分型结果不理想的降解骨骼样本用Miseq FGx平台检测,比较两个平台STR位点的检出结果和检出率。结果 10例降解骨骼样本在Mi Seq FGx平台上的STR位点检出率均高于PCR-CE方法,一些用PCR-CE方法没有检出的STR位点,很有可能在Miseq FGx平台中检出。同时,Miseq FGx平台测序还获得了X-STR、Y-STR、SNP等遗传标记的大量信息。结论 Mi Seq FGx平台检测降解骨骼样本有较好的应用价值。     

利用AutoMate Express~(TM)系统提取陈旧性骨骼DNA

目的建立利用AutoMate Express~(TM)系统提取陈旧性骨骼DNA的方法。方法将骨骼用冷冻研磨机研磨成骨粉,经AutoMate Express~(TM)系统提取后,用Identifiler~Plus、MiniFiler~(TM)试剂盒扩增分型。结果10例保存在不同环境中、死亡时间在10~20年的骨骼样本利用AutoMate Express~(TM)系统3 h内完成DNA提取,有8例获得完整STR分型。结论 AutoMate Express~(TM)系统能快速、高效地提取陈旧性骨骼DNA,可应用于法医实际案件检验。     

An Examination of the Transition of Fracture Characteristics in Long Bones from Fresh to Dry in Central Florida: Evaluating the Timing of Injury

It is important to conduct timing of injury research analyzing fracture characteristics at known postmortem intervals (PMI) because bone can retain fresh characteristics throughout the PMI. Defleshed pig (Sus scrofa) long bones were fractured weekly in two environments (full sun and shade) over 14 weeks in Central Florida and fracture characteristics were categorized (N = 136) for analysis. Results of analysis of variance (ANOVA) using time in weeks (PMI) as a dependent variable indicate significant relationships between PMI and Fracture Angle (p < 0.001), Fracture Surface (p < 0.001), and Fracture Outline (p < 0.001). Fracture characteristics associated with perimortem trauma (smooth Fracture Surfaces and curved or V‐shaped Fracture Outlines) were commonly observed. Analysis of fracture characteristics for each environment demonstrated similar patterns. Overall, the loss of only fresh fracture characteristics for each bone was noted earlier in the PMI for the Central Florida region than previously reported.     

Estimating the Temperature of Heat‐exposed Bone via Machine Learning Analysis of SCI Color Values: A Pilot Study

Determining maximum heating temperatures of burnt bones is a long‐standing problem in forensic science and archaeology. In this pilot study, controlled experiments were used to heat 14 fleshed and defleshed pig vertebrae (wet bones) and archaeological human vertebrae (dry bones) to temperatures of 400, 600, 800, and 1000°C. Specular component included (SCI) color values were recorded from the bone surfaces with a Konica‐Minolta cm‐2600d spectrophotometer. These color values were regressed onto heating temperature, using both a traditional linear model and the k‐nearest neighbor (k‐NN) machine‐learning algorithm. Mean absolute errors (MAE) were computed for 1000 rounds of temperature prediction. With the k‐NN approach, the median MAE prediction errors were 41.6°C for the entire sample, and 20.9°C for the subsample of wet bones. These results indicate that spectrophotometric color measurements combined with machine learning methods can be a viable tool for estimating bone heating temperature.