Sample-specific Method Research Articles

Sample specific sex estimation method using parameters around dominant nutrient foramina in unknown femur bones collection of contemporary Egyptians

AbstractBecause there is no widely accepted sexing method of fragmented femoral diaphyses, we argue that the diaphyseal diameters and circumference around nutrient foramina (NF) have comparable sex discrimination capacity to their mid‐shaft counterparts. Construction of reliable reference sample (n = 61, 29 males and 32 females) using the undocumented Alexandria University Osteological Collection was contingent upon consistent sex estimation of the epiphyses using population and sample specific methods. Statistically significant size differences were found between the males and females diaphyseal measurements around NF. Low intraobserver measurements error and high sexual dimorphism indices were observed in the new measurements at NF level. The logistic regression analysis revealed that combinations of anteroposterior diameter and circumference at both levels were the optimal models for sex classification. Testing in the holdout sample showed complete agreement in the results between both models. The best model at the level of NF achieved consistent total sex allocation of 81.1% with high probability >0.80 of correct estimates in approximately 60% of the reference sample. A great applicability pertinent to sex estimation of a tubular fragment of femur bearing a single NF using the diaphyseal measurements around it because the maximal length is not required to determine the location of the mid‐shaft measurements.

SWATH Mass Spectrometry Applied to Cerebrospinal Fluid Differential Proteomics: Establishment of a Sample-Specific Method.

Mass spectrometry (MS) has become the gold standard method for proteomicsby allowingthe simultaneous identification and/or quantification of thousands of proteins of a given sample. Over time, mass spectrometry has evolved into newer quantitative approaches with increased sensitivity and accuracy, such as thesequential windows acquisition of all theoretical fragment-ion spectra (SWATH)-MS approach. Moreover, in the past few years, some improvements were made in the SWATH-acquisition algorithm, allowing the design of sample-customized acquisition methods by adjusting the Q1 windows' width in order to reduce it in the most populated m/z regions. This customization results in an increase in the specificity and a reduction in the interferences, ultimately leading to an improvement in the amount of quantitative data extracted to eventually increase the proteome coverage. These improvements are especially relevant for clinical neuroproteomics, which is mainly based on the analysis of circulatory biofluids, in particular the cerebrospinal fluid (CSF) due to its close connection with the brain.In the present chapter, a detailed description of the methodologies necessary to perform a whole-proteome relative quantification of CSF samples by SWATH-MS is presented, starting with the isolation of the protein fraction, its preparation for MS analysis, with all the necessary information for the design of a SWATH-MS method specific for each sample batch, and finally providing different methodologies for the analysis of the quantitative data obtained.

Visual aesthetic understanding: Sample-specific aesthetic classification and deep activation map visualization

Currently image aesthetic estimation using deep learning has achieved great success compared with the traditional methods by hand-crafted features. Similar to recognition problem, aesthetic estimation categorizes images into visually appealing or not. Nevertheless, it is desirable to understand why certain images are visually more appealing, in specific, which part of the image is contributing to the aesthetic preference. In fact, most traditional approaches adopting hand-crafted feature are, to some extent, able to understand part of image’s aesthetic and content information while few studies have been conducted in the context of deep learning. Moreover, we discover that aesthetic rating is ambiguous so that many examples are uncertain in aesthetic level. This has caused a highly imbalanced distribution of aesthetic ratings. To tackle all these issues, we propose an end-to-end convolutional neural network (CNN) model which simultaneously implements aesthetic classification and understanding. To overcome the imbalanced aesthetic ratings, a sample-specific classification method that re-weights samples’ importance is proposed. We find that dropping out ambiguous image, as common adopted by recent deep learning models, is a special case of the sample-specific method, and also figure out that as the weights of the non-ambiguous images increase, the performance is positively affected. In order to understand what is learned in the deep model, global average pooling (GAP) following the last feature map is employed to generate aesthetic activation map (AesAM) and attribute activation map (AttAM). AesAM and AttAM respectively represent the likelihood of aesthetic level for spatial location, and the likelihood of different attribute information. In particular, AesAM mainly accounts for what is learned in deep model. Experiments are carried out on public aesthetic datasets and state-of-the-art performance is achieved. Thanks to the introduction of AttAM, the aesthetic preference is explainable by visualization. Finally, a simple application on image cropping based on the AesAM is presented. The code and trained model will be publicly available on https://github.com/galoiszhang/AWCU.

Detecting Early Warning Signal of Influenza A Disease Using Sample-Specific Dynamical Network Biomarkers.

Aims/Introduction. Evidences have shown that the deteriorated procession of disease is not a smooth change with time and conditions, in which a critical transition point denoted as predisease state drives the state from normal to disease. Considering individual differences, this paper provides a sample-specific method that constructs an index with individual-specific dynamical network biomarkers (DNB) which are defined as early warning index (EWI) for detecting predisease state of individual sample. Based on microarray data of influenza A disease, 144 genes are selected as DNB and the 7th time period is defined as predisease state. In addition, according to functional analysis of the discovered DNB, it is relevant with experience data, which can illustrate the effectiveness of our sample-specific method.

Sample-specific sex estimation in archaeological contexts with commingled human remains: a case study from the Middle Neolithic cave of Bom Santo in Portugal

Estimating sex on large assemblages of commingled skeletal human remains is challenging because it prevents the systemic observation of the skeleton and thus reduces the reliability of sex-ratio estimation. In order to tackle this problem, the applicability of sample-specific odontometric methods was assessed on the human skeletal remains from the Middle Neolithic cave necropolis of Bom Santo in Portugal. We present an approach that confirms some of the assumptions – the normal distribution of the data and the 1:1.5 sex ratio – indicated by Albanese et al. (2005) for the application of sample-specific methods. These assumptions are often difficult to assess in archaeological samples and thus prevent the use of sample-specific methods.The mean bucco-lingual diameter of 51 lower right canine teeth was used as a cut-off point to discriminate between sexes within a sample from Bom Santo. Before that, Shapiro–Wilk statistics was used to confirm that the distribution of the data in a sample of 51 lower canine teeth was normal. In addition, the range and central tendency of the data were compared to other samples for which the sex of the individuals was known in order to confirm that those parameters were consistent with those of a sample presenting a balanced sex ratio. The canine sex estimations were then compared with the sex estimation obtained from mandibles where canine teeth were still in situ (n = 8). No clear disagreement between the two methods was found thus demonstrating good potential of this method for sex estimation and for the sex ratio estimation in commingled human skeletal remains. Results indicated that sex ratios in Room A and Room B at Bom Santo were quite different. This indicates that the two locations may have been used in a different way according to sex.

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Sample-specific (universal) metric approaches for determining the sex of immature human skeletal remains using permanent tooth dimensions

In this paper, three approaches for developing sample-specific sex determination methods of immature skeletal remains based on permanent tooth dimensions are proposed and tested using a sample of identified skeletons. The sample comprises adult and subadult individuals selected from the Lisbon documented skeletal collection, housed at the National Museum of Natural History in Lisbon, Portugal. Faciolingual and mesiodistal diameters were the tooth dimensions utilized. In the first approach, sex-specific logistic regression formulae based on adult tooth dimensions are developed and then used to determine the sex of the subadult sample. The second and third approaches are based on the sectioning point procedure, which uses the overall mean of a measurement (tooth diameter) collected from the sample as the discriminant criteria for determining the sex of the individuals in that sample. While in the second approach the adult overall mean of each dimension is used as the discriminant criteria for determining the sex of the subadults, in the third approach it is the subadult overall mean of each dimension that comprises the discriminant criteria that is applied back to the subadults for determining sex. Results show that the canines are the teeth with the highest sexual dimorphism and methods of sex determination based on canine dimensions provide correct allocation accuracies between 58.8% and 100% depending on the diameter and the approach that is being used. Canine faciolingual dimensions provide the best overall results. Combinations of measurements from the same and different teeth do not increase significantly the accuracy of the methods and approaches. Some of the problems of subadult sex determination methods based on adult tooth dimensions result from differing levels of sexual dimorphism between the adult and subadult segment of the sample. Mortality or cultural bias may increase or decrease the sexual dimorphism of the subadults compared to the adults. Small subadult samples utilized in this study may also raise questions regarding the accuracy of the three different sample-specific approaches. However, high consistency of results using the canine and different approaches, suggests that adult and subadult canine dimensions can be reliable sex discriminators of immature skeletal remains in archaeological samples. The major advantage of the approaches presented here is that they can be used to derive sample-specific methods and, therefore, eliminate the problem of applying morphological or metric methods to individuals originating from a population that differs from the one that contributed to the development of the method.