Sexual dimorphism of the twelfth thoracic vertebra for sex determination in the Central Thai population.

Analyzing skeletal remains is crucial for identifying individuals, and forensic anthropologists use this analysis to determine biological characteristics, particularly sex, aiding criminal investigations. Among thoracic vertebrae, the twelfth thoracic vertebra (T12) is highly sexually dimorphic in various populations. This study aims to establish a discriminant function equation (DFE) for sex determination based on T12 in the Central Thai population. A total of 15 parameters of T12 were examined in 69 bone samples (43 males and 26 females). Among the 15 parameters, 14 were significantly different between males and females. The discriminant function equation (DFE) was generated as DFE = -19.578 + 0.376(i) BDsm + 0.254(l) PW + 0.081TDm, with a cutoff value of -0.296 for males and females, showing 92.8 % accuracy. The evaluation of the DFE using 10 blind samples showed 90 % accuracy. These findings may offer an additional method for sex determination through T12, complementing the examination of other skeletal elements.

Morphological variation in Schizothorax oconnori, Schizothorax waltoni (Teleostei: Cyprinidae: Schizothoracinae), and their natural hybrids from the middle Yarlung Zangbo River, Tibet.

The morphological variation in Schizothorax oconnori, Schizothorax waltoni, and their natural hybrids was examined using conventional and image-based analysis approaches. In total, 38 specimens of S. oconnori, 35 of S. waltoni, and 37 natural hybrids were collected from the Shigatse to the Lhasa section of the Yarlung Zangbo River during June and July 2021. A total of 21 morphometric, 4 meristic, and 27 truss variables were employed for the classification of S. oconnori, S. waltoni, and natural hybrids. Principal component analysis (PCA) and factor analysis (FA), as well as discriminant function analysis (DFA) and cluster analysis (CA), were conducted to identify differences based on traditional and truss measurements. Four principal components explained 75.92% of the variation among the morphometric characters, while five principal components accounted for 79.69% of the variation among the truss distances. FA results showed that factor 1 was associated with head shape, and factor 2 was associated with fins based on morphometric characters. Among the truss characters, factor 1 was related to head shape, and factor 2 was related to chest shape. In DFA, morphometric measurements achieved higher accuracy (100%) compared to truss distances (94.55%). The head morphology of hybrids exhibited intermediate traits between S. oconnori and S. waltoni. Both morphometry-based and truss-based clustering indicated that the morphology of natural hybrids leaned toward S. oconnori. In conclusion, the combination of morphometric and truss analysis is beneficial for classifying S. oconnori, S. waltoni, and their natural hybrids. The presence of natural hybrids could be considered an evolutionary response to the differentiation of nutritional and spatial niches in the middle Yarlung Zangbo River.

Selection of mungbean (Vigna radiata L.) mutants with respect to seasonal variation of summer and spring using discriminant function analysis.

The current study was carried out at Nuclear Institute of Agriculture, Tandojam to assess ten mungbean mutants together with one check cultivar in two separate cropping seasons. The findings revealed that all mutants, with the exception of the branches per plant, had significantly different examined traits. By characterizing ten variables, including plant height (cm), number of branches/plant, number of seeds per pod, grain yield per plot (g/plot), grain weight per plant, pod length (cm), pods per plant, days to flowering, above ground biological weight per plot (g/plot) and days to maturity, the results could considerably differentiate between low and high producing mutants. Discriminant analysis was used to choose high-yielding genotypes. The discriminant score demonstrated a significant canonical correlation of 0.994** and could account for 98.8 % of differences in mungbean production. According to the results of discriminant function analysis, the most significant features are pod length, days to flowering, plant height and above ground biological weight. The highest discriminant scores were displayed by the genotypes AEM66, AEM27, AEM25 and AEM14, identified as high yielding mutants. The low yielding mungbean mutants, designated Viz, AEM20, AEM30, AEM35, AEM-96, AEM29, AEM40 and AEM32 are those that exhibit the lowest values of the discriminant score. Mungbean cultivation is more successful in the summer than it is in the spring.

Evaluation of morphological traits using multivariate techniques in Kotdhar goat native to Shivalik hill region of Himachal Pradesh.

The objective of this study was to analyze the diverse morphological attributes of Kotdhar goat native to Shivalik hill region of Himachal Pradesh. A total number of 180 goats, comprising 150 females and 30 males aged between 1 and 3 years, were randomly selected to estimate15 distinct morphological traits and ten body indices. Mean values of 17.66 cm, 11.68 cm, 8.73 cm, 71.94 cm, 69.83 cm, 74.48 cm, 38.10 cm, 73.38 cm, 20.55 cm, 16.48 cm, 14.89 cm, 13.57 cm, 19.20 cm, 7.71 cm and 26.12 kg were estimated for head length, head width, face length, body length, wither height, heart girth, chest depth, rump height, rump length, rump width, haunch width, bicoastal width, shoulder width, cannon bone and body weight respectively. In addition, morphological indices viz. body index, length index, body ratio, thoracic development, pelvic index, longitudinal pelvic index, transverse pelvic index, proportionality index, dactyl thorax index and relative depth of thorax were estimated from morphological traits. Results of morphological indices indicated that Kotdhar goat are medium bodied, longilinear, tall animals and well-suited for meat production. Phenotypic correlation among most of traits was positive and significant. Among all correlations, correlation between head length and head width was found lowest (- 0.270), while the correlation between heart girth and chest depth was observed highest (0.861). Canonical discriminant function analysis showed that there was no considerable level of intermixing for morphological traits in Kotdhar goat. Employing principal component analysis with varimax rotation, three principal components were observed, accounting for 68.47% of the total variation. First principal component (PC1) encapsulated the highest proportion of variance (44.39), revealing the high loadings on head length (0.777), body length (0.747), wither height (0.782), heart girth (0.785), chest depth (0.706), rump height (0.762), haunch width (0.734) and bicoastal width (0.793). Hence, it is possible to utilize these eight variables out of the 15 morphological traits for the characterization of the Kotdhar goat.

Estimation of sex using dimensions around the metatarsal diaphyseal nutrient foramen: Application of discriminant function analysis and logistic regression models.

Sex estimation equations are population-specific, and a wider use of multiple bones to generate equations will increase the accuracy of sex estimation in forensic settings. The metatarsal bones have been used previously, however the dimensions around the diaphyseal nutrient foramen have not been utilised in sex estimation. The current study aimed to determine the utility of the dimensions around the nutrient foramen of metatarsal bones in estimating sex in the South Africans of European descent (SAED). Five measurements around the nutrient foramen were taken from a total of 876 metatarsal bones (first to fifth) from 186 individual skeletons (99 males, 87 females) obtained from the Raymond A. Dart Modern Skeletal Collection. Measurements subjected to direct and stepwise discriminant function (DFA) and logistic regression (LRA) analyses included total length, distance from proximal end to nutrient foramen, circumference, and mediolateral and dorsoplantar diameters at the level of the nutrient foramen. The original classification accuracies for multivariable functions of the stepwise and direct DFA ranged from 83.1-88.3% to 85.5-88.3%, respectively. The original classification accuracies for multivariable functions of the stepwise and direct LRA ranged from 83.3%-88.7% to 86.2%-88.3%, respectively. The cross-validation classifications showed a drop of 0-2.4% for DFA and 0.2-1.1% for LRA. The width measurements were better predictors of sex than length. The dimensions around the metatarsal bone nutrient foramen exhibit sexual dimorphism in the SAED. The generated DFA and LRA functions produced high average classification accuracies which are useful in sex estimation during forensic human identification.

Sex estimation from the hyoid bone measurements in an adult Eastern Turkish population using 3D CT images, discriminant function analysis, support vector machines, and artificial neural networks☆.

The hyoid bone is one of the bones in the human body that shows sexual dimorphism. The anthropological and anthropometric characteristics that determine sexual dimorphism are influenced by demographic differences. The aim of this study was to investigate the rate of sexual dimorphism of the hyoid bone in the adult Eastern Turkish population from the examination of the 3D computed tomography images of 240 patients, using discriminant function analysis (DFA), support vector machines (SVM), and artificial neural networks (ANN). These evaluations were based on eight hyoid measurements that have been frequently used in previous CT studies. The results showed that all eight measurements were higher in males than in females (p = 0.000). It was determined that sex could be estimated accurately at up to 93.3 % using DFA, 93.8 % using SVM and 95.4 % using ANN. The maximum accuracy rate achieved to 94.2 % in males using SVM, and 95.8 % in females using ANN. These high rates of sexual dimorphism found using DFA, SVM, and ANN in this study indicate that characteristics of the hyoid bone can be utilized to determine sex in the Eastern Turkish population.

Using Lower Limb Wearable Sensors to Identify Gait Modalities: A Machine-Learning-Based Approach.

Real-world gait analysis can aid in clinical assessments and influence related interventions, free from the restrictions of a laboratory setting. Using individual accelerometers, we aimed to use a simple machine learning method to quantify the performance of the discrimination between three self-selected cyclical locomotion types using accelerometers placed at frequently referenced attachment locations. Thirty-five participants walked along a 10 m walkway at three different speeds. Triaxial accelerometers were attached to the sacrum, thighs and shanks. Slabs of magnitude, three-second-long accelerometer data were transformed into two-dimensional Fourier spectra. Principal component analysis was undertaken for data reduction and feature selection, followed by discriminant function analysis for classification. Accuracy was quantified by calculating scalar accounting for the distances between the three centroids and the scatter of each category's cloud. The algorithm could successfully discriminate between gait modalities with 91% accuracy at the sacrum, 90% at the shanks and 87% at the thighs. Modalities were discriminated with high accuracy in all three sensor locations, where the most accurate location was the sacrum. Future research will focus on optimising the data processing of information from sensor locations that are advantageous for practical reasons, e.g., shank for prosthetic and orthotic devices.

Assessment of sex and sexual dimorphism in children from Tamilnadu, India through odontometrics in primary dentition - a cross sectional study with discriminant function analysis.

One of the crucial steps in the process of identification of human remains is sex determination of an unknown individual. Sex can be determined using the human skeleton, especially by examining the pelvis and skull. Odontometric analysis and assessment of sexual dimorphism of the human dentition has been less investigated, especially in primary dentition. Hence, this research was designed to verify the presence of sexual dimorphism through odontometric approach in paediatric population of Tamil Nadu, India. The present study was performed on 229 females and 244 males between 3 and 6 years of age. Linear measurements such as maximum mesio distal width, maximum bucco lingual width and clinical crown length were measured in all the primary teeth. Statistical analysis was performed using the Statistical Package for Social Science version 20.0 software (SPSS Inc., Chicago, IL, USA). Mann-Whitney-U test was used to check the statistical significance of the differences observed between males and females. Six equations were derived by discriminant function analysis for practical use. Sexual dimorphism existed in odontometric parameters of primary dentition. The maximum sexual dimorphism was observed in maximum bucco lingual width of 51 and maximum bucco lingual width of 75. The equations derived using discriminant function analysis yielded a jackknife accuracy ranging between 87.5% and 99.8%. These equations may be used to assess the sex from the children of Tamil Nadu, India.

Can Shoulder Impairments Be Classified From 3-Dimensional Kinematics Using Inertial Sensors?

Inertial sensors may help clinicians to assess patients' movement and potentially support clinical decision making. Our aim was to determine whether shoulder range of motion during movement tasks measured using inertial sensors is capable of accurately discriminating between patients with different shoulder problems. Inertial sensors were used to measure 3-dimensional shoulder motion during 6 tasks of 37 patients on the waiting list for shoulder surgery. Discriminant function analysis was used to identify whether the range of motion of different tasks could classify patients with different shoulder problems. The discriminant function analysis could correctly classify 91.9% of patients into one of the 3 diagnostic groups based. The tasks that associated a patient with a particular diagnostic group were the following: subacromial decompression: abduction, rotator cuff repair of tears ≤5 cm: flexion and rotator cuff repair of tears >5 cm: combing hair, abduction, and horizontal abduction-adduction. The discriminant function analysis showed that range of motion measured by inertial sensors can correctly classify patients and could be used as a screening tool to support surgery planning.

Sex estimation of Malaysian sub-adults using craniometrics: A computed tomography study.

Sex estimation is crucial in biological profiling of skeletal human remains. Methods used for sex estimation in adults are less effective for sub-adults due to varied cranium patterns during the growth period. Hence, this study aimed to develop a sex estimation model for Malaysian sub-adults using craniometric measurements obtained through multi-slice computed tomography (MSCT). A total of 521 cranial MSCT dataset of sub-adult Malaysians (279 males, 242 females; 0-20 years old) were collected. Mimics software version 21.0 (Materialise, Leuven, Belgium) was used to construct three-dimensional (3D) models. A plane-to-plane (PTP) protocol was utilised to measure 14 selected craniometric parameters. Discriminant function analysis (DFA) and binary logistic regression (BLR) were used to statistically analyze the data. In this study, low level of sexual dimorphism was observed in cranium below 6 years old. The level was then increased with age. For sample validation data, the accuracy of DFA and BLR in estimating sex improved with age from 61.6% to 90.3%. All age groups except 0-2 and 3-6 showed high accuracy percentage (≥75%) when tested using DFA and BLR. DFA and BLR can be utilised to estimate sex for Malaysian sub-adult using MSCT craniometric measurements. However, BLR showed higher accuracy than DFA in sex estimation of sub-adults.

A methodological comparison of discriminant function analysis and binary logistic regression for estimating sex in forensic research and case-work.

The purpose of this study is to assess the accuracy of two multivariate statistical approaches for estimating sex from human external ear anthropometry, namely, discriminant function analysis (DFA) and binary logistic regression (BLR). A cross-sectional sample of 497 participants (233 males and 264 females) aged 18-35 years (24.42 ± 5.17) was obtained from Himachal Pradesh state of North India. Both the ears of the participants (994) were examined for anthropometric measurements. A total of 12 anthropometric measurements were taken independently on the left and right ear of each individual with the help of a pair of sliding calipers using a standard method. The sex of the population groups was discriminated against using binary logistic regression and discriminant function analysis. The predictive percentage of sex estimation computed from both the models were substantially the same, that is, 76.3% from DFA and 76.2% from BLR, with nearly comparable (∼0.02) sensitivity, specificity, positive predictive value, and negative predictive values, whereas the values of correct predicted percentage were 0.1% higher in DFA than BLR. Moreover, the other comparison metrics, such as classification error, B-index, and Matthews correlation coefficient indicated that both models performed equally well. The study highlighted that if the assumptions of the statistical methods are met, both methods are equally capable of discriminating the population depending on sex. The study recommends that the discriminant function analysis and binary logistic regression may be used synonymously in forensic research and case-work pertaining to the estimation of sex and various other forensic situations.

Sex estimation using foramen magnum measurements, discriminant analyses and artificial neural networks on an eastern Turkish population sample.

BACKGROUND: Although many studies have been conducted using the foramen magnum for sex estimation, recent findings have indicated that the discriminant and regression models obtained from the foramen magnum may not be reliable. Artificial Neural Networks, was used as a classification technique in sex estimation studies on some other bones, did not used in sex estimation studies on the foramen magnum until now. The aim of this study was sex estimation on an Eastern Turkish population sample using foramen magnum measurements, discriminant analyses and Artificial Neural Networks. METHODOLOGY: The study was performed on the CT images of a total of 720 cases, comprising 360 males and 360 females. For sex estimation, discriminant analysis and Artificial Neural Networks were used. RESULTS: The accuracy rate was 86.7% with discriminant analysis and when sex estimation accuracy was determined according to cases with posterior probabilities above 95%, the accuracy ranged from 0% to 33.3%. With the use of the discriminant formulas of 2 other studies, obtained from different Turkish samples, sex could be determined at a rate of 84.6%. Some formulas were found to be unsuccessful in sex estimation. Sex estimation accuracy of 88.2% was achieved with Artificial Neural Networks. CONCLUSION: In this study, it was found that sex could be determined to some extent with discriminant formulas from other samples from the same population, although some formulas were unsuccessful. With the use of image processing techniques and machine learning algorithms, better results can be obtained in sex estimation.

Quick classification of strong-aroma types of base Baijiu using potentiometric and voltammetric electronic tongue combined with chemometric techniques.

Nowadays, the classification of strong-aroma types of base Baijiu (base SAB) is mainly achieved by human sensory evaluation. However, prolonged tasting brings difficulties for sommeliers in guaranteeing the consistency of results, and may even cause health problems. Herein, an electronic tongue (E-Tongue) combined with a gas chromatography-mass spectrometry (GC-MS) method was successfully developed to grade high-alcoholic base SAB. The E-tongue was capable of identifying base SAB samples into four grades by a discriminant function analysis (DFA) model based on human sensory evaluation results. More importantly, it could effectively and rapidly predict the quality grade of unknown base SAB with an average accuracy up to 95%. The differences of chemical components between base SAB samples were studied by the GC-MS analysis and 52 aroma compounds were identified. The qualitative and quantitative results showed that with the increase of base SAB grade, the varieties and contents of aroma compounds increased. Overall, the comprehensive analysis of E-tongue data and GC-MS results could be in good agreement with human sensory evaluation results, which also proved that the newly developed method has a potential to be a useful alternative to the overall quality grading of base Baijiu.

Morphometric Analysis of Mandibular Ramus for Sex Determination on Orthopantomogram.

BACKGROUND: Mandible is the strongest and most dimorphic bone of skull which resists postmortem changes and plays an important role in sex determination. Skeletal characteristic differ in different population therefore need of population specific studies. The aim of present study was to determine sex by morphometric analysis of mandibular ramus. METHODS: A cross sectionalstudy was performed in orthopantomogram of patients collected from Dental Department of Patan Hospital, Lalitpur, Nepal. One hundred and fifty digital orthopantomogram of patient fulfilling inclusion criteria were included in the study. Five different mandibular parameters (maximum ramus breadth, minimum ramus breadth, condylar height/maximum ramus height, projective height of ramus, and coronoid height) were measured bilaterally resulting in total 300 rami being assessed. Orthopantomogram were made with Planmeca ProMax classic 2D machine and all the measurements on digital radiograph were performed with Planmeca Romexis viewer software version 5.1.0.R. Discriminant function analysis was performed to find the most significant predictors for determining sex. RESULTS: All the measured mandibular parameters were statistically significantly higher in male than females (P<0.001). Condylar height was the most significant predictors for determining sex. The discriminate function equation was derived to determine sex with an overall accuracy of 84.0%. CONCLUSIONS: Morphometric analysis of mandibular ramus using digital orthopantomogram showed a high sexual dimorphism.

Detection and Classification of Bacterial Cells After Centrifugation and Filtration of Liquid Specimens Using Laser-Induced Breakdown Spectroscopy.

Five species of bacteria including Escherichia coli, Mycobacterium smegmatis, Pseudomonas aeruginosa, Staphylococcus epidermidis, and Enterobacter cloacae were deposited from suspensions of various titers onto disposable nitrocellulose filter media for analysis by laser-induced breakdown spectroscopy (LIBS). Bacteria were concentrated and isolated in the center of the filter media during centrifugation using a simple and convenient sample preparation step. Summing all the single-shot LIBS spectra acquired from a given bacterial deposition provided perfectly sensitive and specific discrimination from sterile water control specimens in a partial least squares discriminant analysis (PLS-DA). Use of the single-shot spectra provided only a 0.87 and 0.72 sensitivity and specificity, respectively. To increase the statistical validity of chemometric analyses, a library of pseudodata was created by adding Gaussian noise to the measured intensity of every emission line in an averaged spectrum of each bacterium. The normally distributed pseudodata, consisting of 4995 spectra, were used to compare the performance of the PLS-DA with a discriminant function analysis (DFA) and an artificial neural network (ANN). For the highly similar bacterial data, no algorithm showed significantly superior performance, although the PLS-DA performed least accurately with a classification error of 0.21 compared to 0.16 and 0.17 for ANN and DFA, respectively. Single-shot LIBS spectra from all of the bacterial species were classified in a DFA model tested with a tenfold cross-validation. Classification errors ranging from 20% to 31% were measured due to repeatability limitations in the single-shot data.

Dokha brand differentiation by elemental analysis measured by inductively coupled plasma-mass spectrometry.

Dokha is a tobacco product commonly used in Middle Eastern and Northern African regions. It is available in three blends purportedly corresponding to the degree of "buzz" experienced by the user. The "buzz" has been linked in part to nicotine levels, which are higher than those found in cigarettes and is believed to be the reason dokha is abused as a "legal high." There have been reports of seizure activity from dokha users, and elevated concentrations of toxic metals have been measured in dokha tobacco. The purpose of this work was to determine whether we could use dokha's elemental content, measured by inductively coupled plasma-mass spectrometry, to link dokha back to its brand. This could aid investigators in identifying brands and/or distribution routes in the case of adverse effects resulting from dokha use. We measured the concentrations of Mg, K, Mn, Ni, Cu, Rb, Sr, and Ba in Medwakh, Nirvana, Scorpion, Enjoy, Kingdom, and Iconic dokha brands. Analysis of variance revealed statistical differences in concentrations of elements among groups. Discriminant function analysis (using leave-one-out classification) was 58.3% successful at differentiating brands. Enjoy dokha was the most, and Kingdom dokha the least, correctly classified among groups. Attempts to further link dokha blends back to light, medium, and heavy blends were less successful. These results indicate potential for using elemental content to discriminate among dokha brands. Our data may also help to understand the degree of additional processing and/or adulteration of dokha products available to users in the United States.

Distinguishing primate taxa with enamel incremental variables.

Enamel has long been of interest for its functional and phylogenetic significance among fossil hominins and other primates. Previous studies demonstrated that enamel incremental features distinguish among hominin fossil taxa, suggesting utility for highlighting taxonomy. However, not all features appear to be useful in mixed samples of fossils, living humans, and apes. Here we tested enamel incremental data from closely related primate taxa to determine which features, if any, distinguish among them. Enamel incremental variables were measured from the M2 of 40 living primate taxa, and we tested our variables using discriminant function analysis at the taxonomic ranks of parvorder, family, tribe, and genus. We then included enamel incremental data from Australopithecus afarensis, Australopithecus africanus, Paranthropus aethiopicus, Paranthropus boisei, and Paranthropus robustus to determine if these features distinguished fossil taxa from living humans and apes. Our initial results show that enamel incremental variables distinguish among primate taxa, but with low classification rates. Further testing with jackknifing methods shows overlap between groups at all taxonomic ranks, suggesting enamel incremental variables are unreliable for taxonomy. The addition of many common enamel incremental growth variables also resulted in multicollinearity in our multivariate analysis. As the dentition and isolated teeth remain a significant portion of the hominin fossil record, verifying enamel incremental features as a useful taxonomic tool is fundamentally important for hominin paleobiology.

Sex estimation from the clavicle using 3D reconstruction, discriminant analyses, and neural networks in an Eastern Turkish population.

Sex estimation of skeletal remains is an important aspect of forensic anthropology. The clavicle is a bone with relatively high accuracy in sex determination. In this study, 7 clavicular parameters were obtained using the CT images and 3D reconstruction of 360 cases equally distributed as 180 males and 180 females. Sex determination was made using univariate, linear, and stepwise discriminant analyses, and multilayer perceptron neural networks. Maximum sex determination accuracy of 85.3% was achieved with univariate analysis, 89.4% with linear discriminant analysis, 90.0% with stepwise discriminant analysis, and 91.4% with multilayer perceptron neural networks. Significant changes were observed in the MLC, APMD-R and CDC parameters according to age, and these were determined to affect the accuracy of sex determination in different age groups. In forensic anthropological studies, more reliable results can be obtained by considering the confounding factors during sampling. Although high accuracy rates can be achieved with neural networks, the results should be approached with caution.

Morphometric assessment methods for estimation of sexual dimorphism from cranial occipital condyles / Métodos de evaluación morfométrica para la estimación del dimorfismo sexual de los cóndilos occipitales craneales

SUMMARY: Identification of fragmentary human remains is an integral par of medico legal investigations. Occipital region is commonly not affected in traumatic injuries and accidents due to its secluded position which makes it the integral part in determination of sex in the absence of entire skeleton. Occipital condylar region is also the most common area for degenerative and neoplastic diseases. So thorough knowledge of anatomy of occipital condyle is very essential during surgical interventions. 86 skulls were studied from osteological collections of Department of Anatomy, Yenepoya Medical College. Maximum length and breadth of the occipital condyle, anterior intercondylar distance and posterior intercondylar distance was measured with the help of vernier callipers. Descriptive statistics was calculated for the parameters considered. Metric data of right and left sides were compared with student t test and p value was calculated.All data obtained was subjected for discriminant function analysis to derive the statistical model. All the measurements were significantly high in males compared to females. Condylar length and width, anterior and posterior intercondylar distance can be used to derive formula for determination of sex in south Indian population with an accuracy of 66.3 %.

RESUMEN: La identificación de restos humanos fragmentarios es una parte integral de las investigaciones médico legales. La región occipital comúnmente no se ve afectada en lesiones traumáticas y accidentes debido a su posición apartada que la convierte en parte integral en la determinación del sexo en ausencia de un esqueleto completo. La región condilar occipital es también el área más común de enfermedades degenerativas y neoplásicas. Por lo tanto, el conocimiento integral de la anatomía del cóndilo occipital es esencial durante las intervenciones quirúrgicas. Se estudiaron 86 cráneos de colecciones osteológicas del Departamento de Anatomía, Facultad de Medicina de Yenepoya. Se midió el largo y ancho máximo del cóndilo occipital, la distancia intercondilar anterior y la distancia intercondilar posterior con la ayuda de un calibrador vernier. Se calculó la estadística descriptiva para los parámetros considerados. Los datos métricos de los lados derecho e izquierdo se compararon con la prueba t de Student y se calculó el valor de p. Todos los datos obtenidos se sometieron a análisis de función discriminante para derivar el modelo estadístico. Todas las medidas fueron significativamente altas en los hombres en comparación con las mujeres. La longitud y el ancho del cóndilo, la distancia intercondilar anterior y posterior se pueden utilizar para derivar la fórmula para determinar el sexo en la población del sur de la India con una precisión del 66,3 %.

Sex estimation using ulna in a Thai population / Estimación del sexo utilizando la ulna en una población tailandesa

SUMMARY: Sex estimation from fragmentary bone remain is still challenge for forensic pathologist. Ulna has been reported useful for sex estimation by metric analysis. This study generated sex estimation function for fragment and complete of ulnar bone in a Thai population. The function was generated from 200 pairs of ulnar bone, and others 20 pair of ulnar bone were used for test the accuracy of the functions. Olecranon width was the best single variable for sex predicting of proximal part of ulna, which right olecranon width could be classified the sex 90.5 %. While distal end width of ulna was the variable for predicting the sex of distal part, which left distal end width could be classified the sex with 83.0 %. Stepwise discriminant function analysis was applied to proximal part. For proximal part of right ulna 4 measurements were selected (inferior-medial trochlear notch length, olecranon width, olecranon-coronoid process length, and maximum proximal ulnar width), while the left side, superior trochlear notch width, olecranon width, and maximum proximal ulnar width were chosen, and their functions could be predicted the sex with 91.0 % and 90.0 %, respectively. Our results indicated the ulnar bone had high ability for estimating the sex in a Thai population.

RESUMEN: La estimación del sexo a partir de restos óseos fragmentarios sigue siendo un desafío para el patólogo forense. Se ha informado de la utilidad de la ulna para la estimación del sexo mediante análisis métrico. En este estudio se analizó la estimación del sexo para un fragmento y de la ulna completa en una población tailandesa. La función se generó a partir de 200 pares de ulnas y se utilizaron otras 20 pares de ulnas estimando la precisión de las funciones. El ancho del olécranon fue la mejor variable individual para predecir el sexo en la parte proximal de la ulna (90, 5 %). Si bien el ancho del extremo distal de la ulna fue la variable para predecir el sexo, el ancho del extremo distal izquierdo podría clasificarse por sexo con un 83,0 % de certeza. Se aplicó un análisis de función discriminante escalonada a la parte proximal. Para la parte proximal de la ulna derecha se seleccionaron 4 medidas (longitud de la incisura troclear inferior-medial, ancho del olécranon, longitud del proceso olecraneano-proceso coronoides y ancho ulnar proximal máximo), mientras que en el lado izquierdo, fue determinado el ancho de la incisura superior troclear, ancho del olécranon y ancho ulnar proximal máximo. Se eligió el ancho, y se pudo predecir el sexo en el 91,0 % y 90,0 % de los casos, respectivamente. Nuestros resultados indicaron que la ulna tenía una alta capacidad para estimar el sexo en una población tailandesa.