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Background Forensic anthropological examinations help in identification of unidentified human remains. This study aims to establish population-specific standards for age estimation from the sternal ends of left fourth ribs in the Nepalese population. A quantitative, observational study was conducted on 387 Nepalese deceased (106 females, 281 males) between November 2021 and March 2023. Left fourth ribs were collected, macerated and examined for the study. The variables examined included pit depth, pit shape, rim and wall configurations and rib phase. Results Pit depth significantly predicted age, β = 0.642, t(385) = 16.42, p < 0.001. Pit depth also explained a significant proportion of variance in age, R2 = 0.41, F(1, 385) = 269.54, p < 0.001. The age estimates from pit depth stage were 7–36 (stage 0), 7–49 (stage 1), 16–51 (stage 2), 10–58 (stage 3), 22–70 (stage 4) and 32–81 (stage 5). Age estimates for pit shape were 17–20 (stage 0), 13–48 (stage 2), 15–55 (stage 3), 24–68 (stage 4) and 39–82 (stage 5). Age estimates for rim and wall configurations were 17–20 (stage 0), 13–47 (stage 2), 17–53 (stage 3), 24–68 (stage 4) and 40–82 (stage 5). Similarly, age estimates for rib phase were 17–20 (phase 0), 18–20 (phase 1), 13–46 (phase 2), 18–50 (phase 3), 23–60 (phase 4), 32–71 (phase 5), 50–76 (phase 6), 44–81 (phase 7) and 62–85 (phase 8). The study also examined the use of transitional analysis to develop posterior probability distributions for estimation of age using rib phases. Conclusion This study found significant differences in the age estimates from previous studies and shows the importance of developing population-specific models for use in forensic anthropology.
Background Forensic anthropological examinations help in identification of unidentified human remains. This study aims to establish population-specific standards for age estimation from the sternal ends of left fourth ribs in the Nepalese population. A quantitative, observational study was conducted on 387 Nepalese deceased (106 females, 281 males) between November 2021 and March 2023. Left fourth ribs were collected, macerated and examined for the study. The variables examined included pit depth, pit shape, rim and wall configurations and rib phase. Results Pit depth significantly predicted age, β = 0.642, t(385) = 16.42, p < 0.001. Pit depth also explained a significant proportion of variance in age, R2 = 0.41, F(1, 385) = 269.54, p < 0.001. The age estimates from pit depth stage were 7–36 (stage 0), 7–49 (stage 1), 16–51 (stage 2), 10–58 (stage 3), 22–70 (stage 4) and 32–81 (stage 5). Age estimates for pit shape were 17–20 (stage 0), 13–48 (stage 2), 15–55 (stage 3), 24–68 (stage 4) and 39–82 (stage 5). Age estimates for rim and wall configurations were 17–20 (stage 0), 13–47 (stage 2), 17–53 (stage 3), 24–68 (stage 4) and 40–82 (stage 5). Similarly, age estimates for rib phase were 17–20 (phase 0), 18–20 (phase 1), 13–46 (phase 2), 18–50 (phase 3), 23–60 (phase 4), 32–71 (phase 5), 50–76 (phase 6), 44–81 (phase 7) and 62–85 (phase 8). The study also examined the use of transitional analysis to develop posterior probability distributions for estimation of age using rib phases. Conclusion This study found significant differences in the age estimates from previous studies and shows the importance of developing population-specific models for use in forensic anthropology.
Background Noninvasive ultrasound (US) has been used therapeutically for decades, with applications in tissue ablation, lithotripsy, and physical therapy. There is increasing evidence that low intensity US stimulation of organs can alter physiological and clinical outcomes for treatment of health disorders including rheumatoid arthritis and diabetes. One major translational challenge is designing portable and reliable US devices that can be used by patients in their homes, with automated features to detect rib location and aid in efficient transmission of energy to organs of interest. This feasibility study aimed to assess efficacy in rib bone detection without conventional imaging, using a single channel US pitch-catch technique integrated into an US therapy device to detect pulsed US reflections from ribs. Methods In 20 healthy volunteers, the location of the ribs and spleen were identified using a diagnostic US imaging system. Reflected ultrasound signals were recorded at five positions over the spleen and adjacent ribs using the therapy device. Signals were classified as between ribs (intercostal), partially over a rib, or fully over a rib using four models: threshold-based time domain classification, threshold-based frequency domain classification, logistic regression, and support vector machine (SVM). Results SVM performed best overall on the All Participants cohort with accuracy up to 96.25%. All models’ accuracies were improved by separating participants into two cohorts based on Body Mass Index (BMI) and re-fitting each model. After separation into Low BMI and High BMI cohorts, a simple time-thresholding approach achieved accuracies up to 100% and 93.75%, respectively. Conclusion These results demonstrate that US reflection signal classification can accurately provide low complexity, real-time automated onboard rib detection and user feedback to advance at-home therapeutic US delivery.
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