Victim identification from the September 11, 2001 attack on the World Trade Center: Past trends and future projections.

Victim identification following mass fatality events is critically important. Extensive traumatic injuries and body fragmentation add complexity to this process. World Trade Center (WTC) identification efforts have been ongoing for over 20 years and this study tracks identification trends from the 2753 known WTC victims and the 21,905 recovered remains. For identified victims, data include the number of remains identified, date(s) of the identification(s), and identification modalities. Results show a heavy reliance on DNA due to body fragmentation. Other modalities played an important role initially, but DNA eventually became the singular identification modality. For large-scale disasters involving significant body fragmentation, aggressive DNA testing strategies are critical for victim identification. Over time, the number of linked remains (portions of previously identified individuals) will greatly outnumber the new identifications (first-time identifications). A novel approach using statistical modeling from ecology studies was applied to estimate future WTC identification rates using Identification Accumulation Curve extrapolation with the Good-Toulmin estimator. Projections indicate there will be 76 first-time identifications (95% CI: 49-117) through the successful DNA testing of 3404 unidentified, fragmentary remains. The remainder of the identifications would be additional portions of previously identified victims. These results may be instructional for management of other large-scale, protracted victim identification efforts.

A Pilot Study of Microbial Succession in Human Rib Skeletal Remains during Terrestrial Decomposition.

The bones of decomposing vertebrates are colonized by a succession of diverse microbial communities. If this succession is similar across individuals, microbes may provide clues about the postmortem interval (PMI) during forensic investigations in which human skeletal remains are discovered. Here, we characterize the human bone microbial decomposer community to determine whether microbial succession is a marker for PMI. Six human donor subjects were placed outdoors to decompose on the soil surface at the Southeast Texas Applied Forensic Science facility. To also assess the effect of seasons, three decedents were placed each in the spring and summer. Once ribs were exposed through natural decomposition, a rib was collected from each body for eight time points at 3 weeks apart. We discovered a core bone decomposer microbiome dominated by taxa in the phylum Proteobacteria and evidence that these bone-invading microbes are likely sourced from the surrounding decomposition environment, including skin of the cadaver and soils. Additionally, we found significant overall differences in bone microbial community composition between seasons. Finally, we used the microbial community data to develop random forest models that predict PMI with an accuracy of approximately ±34 days over a 1- to 9-month time frame of decomposition. Typically, anthropologists provide PMI estimates based on qualitative information, giving PMI errors ranging from several months to years. Previous work has focused on only the characterization of the bone microbiome decomposer community, and this is the first known data-driven, quantitative PMI estimate of terrestrially decomposed human skeletal remains using microbial abundance information. IMPORTANCE Microbes are known to facilitate vertebrate decomposition, and they can do so in a repeatable, predictable manner. The succession of microbes in the skin and associated soil can be used to predict time since death during the first few weeks of decomposition. However, when remains are discovered after months or years, often the only evidence are skeletal remains. To determine if microbial succession in bone would be useful for estimating time since death after several months, human subjects were placed to decompose in the spring and summer seasons. Ribs were collected after 1 to 9 months of decomposition, and the bone microbial communities were characterized. Analysis revealed a core bone decomposer microbial community with some differences in microbial assembly occurring between seasons. These data provided time since death estimates of approximately ±34 days over 9 months. This may provide forensic investigators with a tool for estimating time since death of skeletal remains, for which there are few current methods.

DNA Testing Reveals the Putative Identity of JB55, a 19th Century Vampire Buried in Griswold, Connecticut.

In 1990 in Griswold, Connecticut, archaeologists excavated a burial found in a "skull and crossbones" orientation. The lid of the 19th century coffin had brass tacks that spelled "JB55", the initials of the person lying there and age at death. JB55 had evidence of chronic pulmonary infection, perhaps tuberculosis. It is possible that JB55 was deemed a vampire due to his disease, and therefore had to be "killed" by mutilating his corpse. In an attempt to reveal the identity of JB55, DNA testing was performed. Ancestry informative single nucleotide polymorphism (SNP) analysis using the Precision ID Ancestry Panel indicated European ancestry. A full Y-chromosomal short tandem repeat (Y-STR) profile was obtained, belonging to haplogroup R1b. When the Y-STR profile was searched in the publicly accessible FamilyTreeDNA R1b Project website, the two closest matches had the surname "Barber". A search of historical records led to a death notice mentioning John Barber, whose son Nathan Barber was buried in Griswold in 1826. The description of Nathan Barber closely fits the burial of "NB13," found near JB55. By applying modern forensic DNA tools to a historical mystery, the identity of JB55 as John Barber, the 19th century Connecticut vampire, has been revealed.

Reanalysis of the Trotter Tibia Quandary and its Continued Effect on Stature Estimation of Past-Conflict Service Members.

Forensic casework from past-conflicts relies on the corrected historical Trotter data for stature estimation in Fordisc. For roughly 10 years', stature estimation using this data has produced point estimates for the tibia that are on average 1.25 inches less than the other long bones. This issue was identified after applying the equations derived from Fordisc to the USS Oklahoma commingled assemblage. Reevaluation of Fordisc revealed that a correction factor of 20 mm, instead of 10 mm, was mistakenly applied to the Trotter tibia data. Historical forensic anthropology reports written at the Defense POW/MIA Accounting Agency were utilized to identify that the overcorrection is isolated to Fordisc 3 with an error rate of 5% of known antemortem statures falling outside of the prediction intervals that relied on the tibia. Further evaluation of the Oklahoma sample indicates the 10 mm correction is still producing point estimates less than the other long bones.

Z-Transform Method for Pairwise Osteometric Pair-matching.

A new pairwise osteometric pair-matching approach based on the Z-transform method is presented. In contrast to previous methods that perform a global t-test on the summed skeletal element pair measurement distances, this approach performs t-tests on each individual distance, facilitating the capture of measurement-specific variation. This new approach is compared to published pairwise sorting methods using a standard reference dataset of postcranial remains maintained by the Defense POW/MIA Accounting Agency. Receiver operating characteristic curve analysis indicates significantly improved performance for the clavicle and radius over all previous methods (p < 0.01). The z-transform method weighted by the effect size outperformed the t-test (Byrd and Adams) and the mean t-test (Lynch) for all elements (p < 0.01). The method performed better than the absolute value t-test (Lynch) for five elements (p < 0.01) and performed at least as well for the remainder. To facilitate usability all methods are available at: https://github.com/spawaskar-cora/z-transform-method.

Potential Use of Bacterial Community Succession in Decaying Human Bone for Estimating Postmortem Interval.

Bacteria are taphonomic agents of human decomposition, potentially useful for estimating postmortem interval (PMI) in late-stage decomposition. Bone samples from 12 individuals and three soil samples were analyzed to assess the effects of decomposition and advancing time on bacterial communities. Results indicated that partially skeletonized remains maintained a presence of bacteria associated with the human gut, whereas bacterial composition of dry skeletal remains maintained a community profile similar to soil communities. Variation in the UniFrac distances was significantly greater between groups than within groups (p < 0.001) for the unweighted metric and not the weighted metric. The members of the bacterial communities were more similar within than between decomposition stages. The oligotrophic environment of bone relative to soft tissue and the physical protection of organic substrates may preclude bacterial blooms during the first years of skeletonization. Therefore, community membership (unweighted) may be better for estimating PMI from skeletonized remains than community structure (weighted).

Potential carcass enrichment of the University of Tennessee Anthropology Research Facility: a baseline survey of edaphic features.

The University of Tennessee Anthropology Research Facility (ARF) is known for its unique contribution to forensic science as a site of human decomposition research. Studies conducted at ARF are integral in our understanding of the processes of human decomposition. As such, the authors are interested in the long-term effects of continuous human decomposition on the soil environment. Soil samples collected from within and outside the ARF were evaluated for moisture content, pH, organic content, total carbon and nitrogen content, and biomass by lipid-bound phosphorus, and total extracted DNA. Analyses revealed no significant differences (p<0.05) among the sampled areas within the facility, and yet demonstrated a possible trend toward increased levels of total N, Lipid-P, and water, suggesting an influx of high-quality nutrients into the ARF soil. Furthermore, elevated pH readings, presumably resulting from ammonification of the soil, were observed in areas of high decomposition. The negative control samples proved significantly different from nearly all samples collected within the facility, the exceptions being total carbon content and extractable DNA. These findings indicate that while landscape samples inside may be similar to themselves, they are dissimilar to those taken in a similar temperate forest biome with no recorded history of human decomposition.