Elusive mustelids-18 months in the search of near-threatened stoat (Mustela erminea) and weasel (M. nivalis) reveals low captures

Stoat (Mustela erminea) and weasel (M. nivalis) are hard to monitor as they are elusive of nature and leave few identifying marks in their surroundings. Stoat and weasel are both fully protected in Denmark and are thought to be widely distributed throughout the country. Despite this stoat and weasel were listed on the Danish Red List as Near Threatened in 2019, as their densities and population trends are unknown. Using a modified novel camera trapping device, the Double-Mostela, a wooden box comprising a tracking tunnel and two camera traps, we attempted to obtain density estimates based on identification of individual stoats and weasels. We deployed camera traps both inside Double-Mostela traps and externally in three different study areas in northern Zealand, Denmark, and tested commercial, American scent-based lures to attract stoat and weasel. We obtained very low seasonal trapping rates of weasel in two study areas, but in one study area, we obtained a seasonal trapping rate of stoat larger compared to another study using the Mostela. In one study area, both species were absent. We observed no effect of scent-based lures in attracting small mustelids compared to non-bait traps. Potential reasons behind low capture rates of weasel and stoat are suboptimal habitat placement and timing of deployment of the Double-Mostelas, land-use changes over the last 200 years, predation from larger predators, as well as unintended secondary poisoning with rodenticides. Due to the scarcity of weasel and stoat captures, we were unable to make density estimates based on identification of individuals; however, we identified potential features that could be used for identification and density estimates with more captures.

Individual genotypes from environmental DNA: Fingerprinting snow tracks of three large carnivore species

Continued advancements in environmental DNA (eDNA) research have made it possible to access intraspecific variation from eDNA samples, opening new opportunities to expand non-invasive genetic studies of wildlife populations. However, the use of eDNA samples for individual genotyping, as typically performed in non-invasive genetics, still remains elusive. We present successful individual genotyping of eDNA obtained from snow tracks of three large carnivores: brown bear (Ursus arctos), European lynx (Lynx lynx) and wolf (Canis lupus). DNA was extracted using a protocol for isolating water eDNA and genotyped using amplicon sequencing of short tandem repeats (STR), and for brown bear a sex marker, on a high-throughput sequencing platform. Individual genotypes were obtained for all species, but genotyping performance differed among samples and species. The proportion of samples genotyped to individuals was higher for brown bear (5/7) and wolf (7/10) than for lynx (4/9), and locus genotyping success was greater for brown bear (0.88). The sex marker was typed in six out of seven brown bear samples. Results for three species show that reliable individual genotyping, including sex identification, is now possible from eDNA in snow tracks, underlining its vast potential to complement the non-invasive genetic methods used for wildlife. To fully leverage the application of snow track eDNA, improved understanding of the ideal species- and site-specific sampling conditions, as well as laboratory methods promoting genotyping success, is needed. This will also inform efforts to retrieve and type nuclear DNA from other eDNA samples, thereby advancing eDNA-based individual and population-level studies.

Systematical explorations of forensic feature and population genetic diversity of the Chinese Mongolian group from northwest China via a self-constructed Multi-InDel panel

This study aimed to investigate the genetic polymorphisms and population characteristics of Chinese Mongolian group from northwest China (NCM) through a self-developed panel including 43 autosomal insertion/deletion (A-InDel) polymorphism genetic markers. Herein, 288 unrelated healthy individuals from the NCM group were employed to obtain the genetic data of 43 A-InDels through multiplex PCR amplification and InDel genotyping using capillary electrophoresis platform. In addition, multiplex population genetic analyses were performed between the NCM group and 27 reference populations. There were no deviations at 43 loci from Hardy-Weinberg equilibrium in the NCM group. The observed heterozygosity (Ho) values ranged from 0.312 8 to 0.559 2, and the combined power of discrimination (CPD) and cumulative probability of exclusion (CPE) values in the NCM group were 0.999 999 999 999 999 998 77 and 0.999 814, respectively. The forensic parameter values indicated that this panel was polymorphic and informative in the NCM group and could be used as an effective tool for forensic personal identification. Furthermore, the results of pairwise genetic distances, principal component analysis, multidimensional scaling analysis, phylogenetic tree construction, and admixture analysis among the NCM group and 27 reference populations revealed that there were closer genetic relationships between the NCM group and East Asian populations, especially Chinese Hui group (CHH) from the northwest China, which is consistent with the geographical location. These present findings contributed to the ongoing genetic explorations and insights into the genetic architecture of the NCM group.

Establishment and Application of a 42-plex Microhaplotype Assay in Forensic Genetics

OBJECTIVES

To establish and forensically verify a 42 microhaplotypes (mircohaps, MHs) multiplex assay system based on next-generation sequencing (NGS), and to explore the application value of this system in the practice of forensic genetics.

METHODS

A total of 42 highly polymorphic MHs were selected from previous studies, and sequenced by the MiSeq FGxTM platform to verify the repeata-bility, sensitivity, specificity, stability, and mixture analysis ability of the detection system. Through population genetic investigation of 102 unrelated Chinese Han individuals in Liyang City, Jiangsu Province, China, the application value of this system in forensic genetics was evaluated.

RESULTS

The sequencing repeatability of the 42-plex MHs assay was 100% and the sensitivity was as low as 0.062 5 ng. The system had the ability to withstand the interference of indigo (≤2 500 ng/μL), humic acid (≤9 ng/μL), hemoglobin(≤20 μmol), and urea (≤200 ng/μL) and to detect mixtures of 2 people (1∶19), 3 people (1∶1∶9) and 4 people (1∶1∶1∶9). Based on 102 individual data, the combined power of discrimination and the combined power of exclusion were 1-3.45×10-30 and 1-3.77×10-11, respectively, and the average effect value of alleles was 2.899.

CONCLUSIONS

The 42-plex MHs assay was successfully established in this study and this system has high repeatability and sensitivity, good anti-jamming ability and mixture analysis ability. The 42 MHs are highly polymorphism and have good application value in individual identification and paternity testing.

The Latest Research Progress on Cell-Free DNA and Prospects of Its Forensic Application

In recent years, with the continuous progress of DNA extraction and detection technology, cell-free DNA(cfDNA)has been widely used in the life science field, and its potential application value in forensic identification is becoming more and more obvious. This paper reviews the concept, formation mechanism, and classification of cfDNA, etc., and describes the latest research progress of cfDNA in personal identification of crime scene touch DNA samples and non-invasive prenatal paternity testing (NIPPT). Meanwhile, this paper summarizes the potential application of cfDNA in injury inference, and discusses the advantages and disadvantages of common cfDNA analysis methods and techniques, and its application prospects, to provide a new idea for the wide application of cfDNA in the field of forensic science.

Research Progress on Biological Evidence Identification in Fire Scenes

Biological evidence is relatively common evidence in criminal cases, and it has strong probative power because it carries DNA information for individual identification. At the scene of fire-related cases, the complex thermal environment, the escape of trapped people, the firefighting and rescue operations, and the deliberate destruction of criminal suspects will all affect the biological evidence in the fire scene. Scholars at home and abroad have explored and studied the effectiveness of biological evidence identification in fire scenes, and found that the blood stains, semen stains, bones, etc. are the main biological evidence which can be easily recovered with DNA in fire scenes. In order to analyze the research status and development trend of biological evidence in fire scenes, this paper systematically sorts out the relevant research, mainly including the soot removal technology, appearance method of typical biological evidence, and possibility of identifying other biological evidence. This paper also prospects the next step of research direction, in order to provide reference for the identification of biological evidence and improve the value of biological evidence in fire scenes.

Research progress on the application of 16S rRNA gene sequencing and machine learning in forensic microbiome individual identification

Forensic microbiome research is a field with a wide range of applications and a number of protocols have been developed for its use in this area of research. As individuals host radically different microbiota, the human microbiome is expected to become a new biomarker for forensic identification. To achieve an effective use of this procedure an understanding of factors which can alter the human microbiome and determinations of stable and changing elements will be critical in selecting appropriate targets for investigation. The 16S rRNA gene, which is notable for its conservation and specificity, represents a potentially ideal marker for forensic microbiome identification. Gene sequencing involving 16S rRNA is currently the method of choice for use in investigating microbiomes. While the sequencing involved with microbiome determinations can generate large multi-dimensional datasets that can be difficult to analyze and interpret, machine learning methods can be useful in surmounting this analytical challenge. In this review, we describe the research methods and related sequencing technologies currently available for application of 16S rRNA gene sequencing and machine learning in the field of forensic identification. In addition, we assess the potential value of 16S rRNA and machine learning in forensic microbiome science.

Genetic polymorphism analysis and forensic application evaluation of 57 insertion/deletion polymorphisms from Yi ethnic group in Yunnan

BACKGROUND

As a new kind of diallelic genetic marker, insertion/deletion (InDel) polymorphisms have recently been used in forensic science. However, there are relatively few studies on the forensic evaluation of InDel genetic polymorphisms from different populations.

AIM

The aim of the present work is to assess the genetic polymorphism and forensic applicability of 57 InDels from the Yi ethnic group and explore the genetic background of this group.

SUBJECTS AND METHODS

A total sample of 122 unrelated individuals of Yi group from the Yunnan province were genotyped by the AGCU indel 60 Kit. Multiplex population genetic analyses on the same 57 InDels were carried out among the Yunnan Yi group and 29 reference populations.

RESULTS

The average allele frequency of these loci in the Yi ethnic group was 0.485. Heterozygosity, polymorphism information content, and the power of discrimination were 0.477, 0.362, and 0.612, respectively. The combined power of discrimination and the combined power of exclusion reached to 0.99999999999999999669 and 0.999962965, respectively. The results showed that 57 InDels polymorphisms have high genetic polymorphisms in the Yi ethnic group.

CONCLUSIONS

The 57 InDels could be used for forensic individual identification, paternity testing, and intercontinental population discrimination, with the potential for use in biogeographic ancestry inference.

Forensic Validation and Application Evaluation of IDentifier DNA Typing Kit (Yan-Huang34)

OBJECTIVES

To investigate the technical performance of IDentifier DNA typing kit (YanHuang34) and evaluate its forensic application value.

METHODS

Following the Criterion of Forensic Science Human Fluorescence STR Multiplex Amplification Reagent (GB/T 37226-2018), IDentifier DNA typing kit (YanHuang34) was verified in 11 aspects of species specificity, veracity, sensibility, adaptability, inhibitor tolerance, consistency, balance, reaction condition verification, mixed samples, stability and inter batch consistency. The system efficiency of IDentifier DNA typing kit (YanHuang34) was compared with the PowerPlex® Fusion 6C System, VersaPlex® 27PY System and VeriFilerTM Plus PCR Amplification Kit. The IDentifier DNA typing kit (YanHuang34) was used to detect the swabs of biological samples in daily cases and the STR performances were observed.

RESULTS

IDentifier DNA typing kit (YanHuang34) had good species specificity, veracity, adaptability, inhibitor tolerance and balance. The sensibility was up to 0.062 5 ng. It was able to detect different types of samples, degraded samples and inhibitor mixed samples. Complete DNA typing could be obtained for samples with the mixture ratio less than 4∶1. The system efficiency of IDentifier DNA typing kit (YanHuang34) was very high, with TDP up to 1-1.08×10-37, CPEtrio and CPEduo up to 1-5.47×10-14 and 1-6.43×10-9, respectively. For the touched biological samples in actual cases, the effective detection rate was 21.05%. The system efficiency of kinship, single parent and full sibling identifications was effectively improved.

CONCLUSIONS

The IDentifier DNA typing kit (YanHuang34) is adaptive to the GB/T 37226-2018 requirements. It can be used for individual identification and paternity identification, and is suitable for application in the field of forensic science.

Developmental validation of a novel multiple genotyping assay with 24 Canine STR loci

Canine individual identification and parentage testing are essential in various fields, including forensics and breeding programs. This study aimed to develop and validate the Canine 25 A kit, a multiplex polymerase chain reaction (PCR) system designed to address these critical requirements. This novel system enables the simultaneous amplification of 24 canine autosomal short tandem repeat (STR) loci and one sex-determining marker. Validation of the Canine 25 A kit was conducted following the Scientific Working Group on DNA Analysis Methods (SWGDAM) guidelines, demonstrating significant sensitivity, high inhibitor tolerance, canine specificity within a mixture, species specificity, and precision in genotype determination. The Canine 25 A kit was crucial in resolving several forensic cases, such as casework samples from a dog attack incident and parentage determination. Its effectiveness in genotyping these samples highlights its significance in forensic applications. Population genetic parameter analysis revealed a high discriminatory power, as indicated by the calculated combined discrimination power (CDP) values for each breed exceeding 0.999 999 999 999, while the combined power of exclusion (CPE) surpassed 0.9999. Overall, the Canine 25 A kit offers a precise and dependable tool for canine individual identification and parentage determination.

Process of Forensic Medicine in DNA Identification of Aged Human Remains

Skeleton and teeth are important biological samples. Due to their special structure and strong ability to resist degradation, they are ideal biological materials to retain DNA under natural condition. In many cases, such as historical figure identification, aged skeleton and teeth are usually the only biological samples. However, their DNA is in a state of trace, damage and degradation to different degrees, which requires special experimental treatment to achieve identification. This paper reviews the sample selection, DNA extraction, DNA enrichment and analysis approaches based on relevant research reports in recent years, aiming to promote the further development and improvement of the aged skeleton and teeth identification system.

A Selection of 14 Tetrameric Microsatellite Markers for Genetic Investigations in Fallow Deer (Dama dama)

The fallow deer (Dama dama) represents significant game management value globally, and human activities are significantly impacting the species. Besides the positive effects, these activities can threaten its existence, health, and value. The aim of the authors was to develop a tetranucleotide microsatellite panel that could be clearly interpreted and used for genetic testing of fallow deer. Such a panel did not exist until now and could be particularly useful in the field of conservation genetics and forensics. A total of 99 tetrameric microsatellites, originally designed for related deer species, were tested on 20 fallow deer individuals from five Hungarian sampling areas. Original and newly designed primers were used to amplify the microsatellite regions using previously published or optimized PCR protocols. The lengths and sequences of specific amplicons were detected using capillary electrophoresis, and the rate of polymorphism was determined. Altogether, 80 markers provided PCR products of adequate quality and quantity. Among them, 15 markers proved to be polymorphic (2-5 alleles/locus), and 14 tetrameric markers were selected for further analysis. Statistical calculations showed that the selected polymorphic microsatellites can potentially enable key individualization in many areas of wildlife and population genetics, thus protecting the species.

Study on the Influence of PCA Pre-Treatment on Pig Face Identification with Random Forest

To explore the application of a traditional machine learning model in the intelligent management of pigs, in this paper, the influence of PCA pre-treatment on pig face identification with RF is studied. By this testing method, the parameters of two testing schemes, one adopting RF alone and the other adopting RF + PCA, were determined to be 65 and 70, respectively. With individual identification tests carried out on 10 pigs, accuracy, recall, and f1-score were increased by 2.66, 2.76, and 2.81 percentage points, respectively. Except for the slight increase in training time, the test time was reduced to 75% of the old scheme, and the efficiency of the optimized scheme was greatly improved. It indicates that PCA pre-treatment positively improved the efficiency of individual pig identification with RF. Furthermore, it provides experimental support for the mobile terminals and the embedded application of RF classifiers.

Convolutional Neural Network for Individual Identification Using Phase Space Reconstruction of Electrocardiogram

Electrocardiogram (ECG) biometric provides an authentication to identify an individual on the basis of specific cardiac potential measured from a living body. Convolutional neural networks (CNN) outperform traditional ECG biometrics because convolutions can produce discernible features from ECG through machine learning. Phase space reconstruction (PSR), using a time delay technique, is one of the transformations from ECG to a feature map, without the need of exact R-peak alignment. However, the effects of time delay and grid partition on identification performance have not been investigated. In this study, we developed a PSR-based CNN for ECG biometric authentication and examined the aforementioned effects. Based on a population of 115 subjects selected from the PTB Diagnostic ECG Database, a higher identification accuracy was achieved when the time delay was set from 20 to 28 ms, since it produced a well phase-space expansion of P, QRS, and T waves. A higher accuracy was also achieved when a high-density grid partition was used, since it produced a fine-detail phase-space trajectory. The use of a scaled-down network for PSR over a low-density grid with 32 × 32 partitions achieved a comparable accuracy with using a large-scale network for PSR over 256 × 256 partitions, but it had the benefit of reductions in network size and training time by 10 and 5 folds, respectively.

Development of Genetic Markers for Sex and Individual Identification of the Japanese Giant Flying Squirrel (Petaurista leucogenys) by an Efficient Method Using High-Throughput DNA Sequencing

DNA markers that detect differences in the number of microsatellite repeats can be highly effective for genotyping individuals that lack differences in external morphology. However, isolation of sequences with different microsatellite repeat numbers between individuals has been a time-consuming process in the development of DNA markers. Individual identification of Japanese giant flying squirrels (Petaurista leucogenys) has been challenging because this species is arboreal and nocturnal and exhibits little to no morphological variation between individuals. In this study, we developed DNA markers for sex and individual identification of this species by an efficient method using high-throughput DNA sequence data. Paired-end 5 Gb (2 × 250 bp) and 15 Gb (2 × 150 bp) genome sequences were determined from a female and a male Japanese giant flying squirrel, respectively. We searched SRY and XIST genes located on Y and X chromosomes, respectively, from high-throughput sequence data and designed primers to amplify these genes. Using these primer sets, we succeeded to identify the sex of individuals. In addition, we selected 12 loci containing microsatellites with different numbers of repeats between two individuals from the same data set, and designed primers to amplify these sequences. Twenty individuals from nine different locations were discriminated using these primer sets. Furthermore, both sex and microsatellite markers were amplified from DNA extracted non-invasively from single fecal pellet samples. Based on our results for flying squirrels, we expect our efficient method for developing non-invasive high-resolution individual- and sex-specific genotyping to be applicable to a diversity of mammalian species.

Forensic efficiencies of individual identification, kinship testing and ancestral inference in three Yunnan groups based on a self-developed multiple DIP panel

Deletion/insertion polymorphism (DIP), as a short insertion/deletion sequence polymorphic genetic marker, has attracted the attention of forensic genetic scientist due to its lack of stutter, short amplicon and abundant ancestral information. In this study, based on a self-developed 43 autosomal deletion/insertion polymorphism (A-DIP) loci panel which could meet the forensic application purposes of individual identification, kinship testing and ancestral inference to some extent, we evaluated the forensic efficiencies of the above three forensic objectives in Chinese Yi, Hani and Miao groups of Yunnan province. The cumulative match probability (CPM) and combined probability of exclusion (CPE) of these three groups were 1.11433E-18, 8.24299E-19, 4.21721E-18; 0.999610217, 0.999629285 and 0.999582084, respectively. Average 96.65% full sibling pairs could be identified from unrelated individual pairs (as likelihood ratios > 1) using this DIP panel, whereas the average false positive rate was 3.69% in three target Yunnan groups. With the biogeographical ancestor prediction models constructed by extreme gradient boosting (XGBoost) and support vector machine (SVM) algorithms, 0.8239 (95% CI 0.7984, 0.8474) of the unrelated individuals could be correctly divided according to the continental origins based on the 43 A-DIPs which were large frequency distribution differentiations among different continental populations. The present results of principal component analysis (PCA), multidimensional scaling (MDS), neighbor joining (NJ) and maximum likelihood (ML) phylogenetic trees and STRUCTURE analyses indicated that these three Yunnan groups had relatively close genetic distances with East Asian populations.

Research Progress of Exosomes and Their Forensic Significance

Exosomes are membranous tiny vesicles secreted by cells, which are widely found in the extracellular matrix and various body fluids and carry a variety of biologically functional molecules such as proteins, lipids, messenger RNA (mRNA) and microRNA (miRNA). Exosomes not only play important biological roles in the field of immunology and oncology, but also have potential application value in the field of forensic medicine. This article reviews the discovery, production and degeneration mechanism, biological functions, isolation and identification methods of exosomes, summarizes the research on exosomes and their significance in the field of forensic science, and discusses their applications in body fluid identification, individual identification, postmortem interval estimation to provide ideas for the application of exosomes in forensic work.

The value of individual identification in studies of free-living hyenas and aardwolves

From population estimates to social evolution, much of our understanding of the family Hyaenidae is drawn from studies of known individuals. The extant species in this family (spotted hyenas, Crocuta crocuta, brown hyenas, Parahyaena brunnea, striped hyenas, Hyaena hyaena, and aardwolves, Proteles cristata) are behaviorally diverse, presenting an equally diverse set of logistical constraints on capturing and marking individuals. All these species are individually identifiable by their coat patterns, providing a useful alternative to man-made markings. Many studies have demonstrated the utility of this method in answering a wide range of research questions across all four species, with some employing a creative fusion of techniques. Despite its pervasiveness in basic research on hyenas and aardwolves, individual identification has rarely been applied to the conservation and management of these species. We argue that individual identification using naturally occurring markings in applied research could prove immensely helpful, as this could further improve accuracy of density estimates, reveal characteristics of suitable habitat, identify threats to population persistence, and help to identify individual problem animals.

Microsatellite Characterization and Panel Selection for Brown Bear (Ursus arctos) Population Assessment

An assessment of the genetic diversity and structure of a population is essential for designing recovery plans for threatened species. Italy hosts two brown bear populations, Ursus arctos marsicanus (Uam), endemic to the Apennines of central Italy, and Ursus arctos arctos (Uaa), in the Italian Alps. Both populations are endangered and occasionally involved in human-wildlife conflict; thus, detailed management plans have been in place for several decades, including genetic monitoring. Here, we propose a simple cost-effective microsatellite-based protocol for the management of populations with low genetic variation. We sampled 22 Uam and 22 Uaa individuals and analyzed a total of 32 microsatellite loci in order to evaluate their applicability in individual identification. Based on genetic variability estimates, we compared data from four different STR marker sets, to evaluate the optimal settings in long-term monitoring projects. Allelic richness and gene diversity were the highest for the Uaa population, whereas depleted genetic variability was noted for the Uam population, which should be regarded as a conservation priority. Our results identified the most effective STR sets for the estimation of genetic diversity and individual discrimination in Uam (9 loci, PIC 0.45; PID 2.0 × 10-5), and Uaa (12 loci, PIC 0.64; PID 6.9 × 10-11) populations, which can easily be utilized by smaller laboratories to support local governments in regular population monitoring. The method we proposed to select the most variable markers could be adopted for the genetic characterization of other small and isolated populations.

New Advances, Challenges and Opportunities in Forensic Applications of Microbiomics

The succession of microbiota is closely associated with several essential factors, including race, sex, health condition, lifestyle, postmortem interval, etc., and it has great potential application value in forensic medicine. This paper summarizes recent studies on the forensic applications of the microbiome, including individual identification, geographical feature identification, origin identification of the tissue or body fluid, and postmortem interval estimation, and introduces the current machine learning algorithms for microbiology research based on next-generation sequencing data. In addition, the current problems facing forensic microbiomics such as the extraction and preservation of samples, construction of standardization and database, ethical review and practical applicability are discussed. Future multi-omics studies are expected to explore micro ecosystems from a comprehensive and dynamic perspective, to promote the development of forensic microbiomics application.

Individual Identification by Late Information Fusion of EmgCNN and EmgLSTM from Electromyogram Signals

This paper is concerned with individual identification by late fusion of two-stream deep networks from Electromyogram (EMG) signals. EMG signal has more advantages on security compared to other biosignals exposed visually, such as the face, iris, and fingerprints, when used for biometrics, at least in the aspect of visual exposure, because it is measured through contact without any visual exposure. Thus, we propose an ensemble deep learning model by late information fusion of convolutional neural networks (CNN) and long short-term memory (LSTM) from EMG signals for robust and discriminative biometrics. For this purpose, in the ensemble model's first stream, one-dimensional EMG signals were converted into time-frequency representation to train a two-dimensional convolutional neural network (EmgCNN). In the second stream, statistical features were extracted from one-dimensional EMG signals to train a long short-term memory (EmgLSTM) that uses sequence input. Here, the EMG signals were divided into fixed lengths, and feature values were calculated for each interval. A late information fusion is performed by the output scores of two deep learning models to obtain a final classification result. To confirm the superiority of the proposed method, we use an EMG database constructed at Chosun University and a public EMG database. The experimental results revealed that the proposed method showed performance improvement by 10.76% on average compared to a single stream and the previous methods.

Real-Time Prediction of Growth Characteristics for Individual Fruits Using Deep Learning

Understanding the growth status of fruits can enable precise growth management and improve the product quality. Previous studies have rarely used deep learning to observe changes over time, and manual annotation is required to detect hidden regions of fruit. Thus, additional research is required for automatic annotation and tracking fruit changes over time. We propose a system to record the growth characteristics of individual apples in real time using Mask R-CNN. To accurately detect fruit regions hidden behind leaves and other fruits, we developed a region detection model by automatically generating 3000 composite orchard images using cropped images of leaves and fruits. The effectiveness of the proposed method was verified on a total of 1417 orchard images obtained from the monitoring system, tracking the size of fruits in the images. The mean absolute percentage error between the true value manually annotated from the images and detection value provided by the proposed method was less than 0.079, suggesting that the proposed method could extract fruit sizes in real time with high accuracy. Moreover, each prediction could capture a relative growth curve that closely matched the actual curve after approximately 150 elapsed days, even if a target fruit was partially hidden.

Research Progress on the Application of Human Oral Microbiome in Forensic Individual Identification

The oral cavity is the second largest microbial bank in humans after the intestinal canal, colonizing a large number of microorganisms including viruses, bacteria, archaea, fungi and protozoa. The great number of microbial cells, good DNA stability, and individual has a unique microbial community, these characteristics make the human microbiome expected to become a new biomarker for forensic individual identification. This article describes the characteristics of human oral microorganisms and microbial molecular markers in detail, analyzes the potential application value of microorganisms in forensic individual identification, and reviews the research progress of human oral microorganisms in forensic individual identification.

Individual Identification in Facial Appearance Biometrics Based on Macroscopical Comparison

Individual identification is one of the research hotspots in the practice of forensic science, and the judgment is usually built on the comparison of the unique biological characteristics of the individual, such as fingerprints, iris and DNA. With the dramatic increase in the number of cases related to video image investigations, there is an increasing need for the technology to identify individuals based on the macroscopic comparison of facial appearance biometrics. At present, with the introduction of computer three-dimensional (3D) modeling and 3D superimposition comparison technology, considerable progress has been made in individual identification methods based on macroscopic comparison of facial appearance biometrics. This paper reviews individual facial appearance biometric methods based on macroscopical comparison, comprehensively analyzes the advantages and limitations of different methods, and puts forward recommendations and prospects for subsequent research.

Establishment of Multiplex Amplification System of STR Loci in Felis Catus and Its Forensic Application

OBJECTIVES

To construct a Felis catus STR loci multiplex amplification system and to evaluate its application value by testing the technical performance.

METHODS

The published Felis catus STR loci data were reviewed and analyzed to select the STR loci and sex identification loci that could be used for Felis catus individual identification and genetic identification. The fluorescent labeling primers were designed to construct the multiplex amplification system. The system was validated for sensitivity, accuracy, balance, stability, species specificity, tissue identity and mixture analysis, and investigated the genetic polymorphisms in 145 unrelated Felis catus samples.

RESULTS

Sixteen Felis catus autosomal STR loci and one sex determining region of Y (SRY) were successfully selected, and constructed a multiplex amplification system containing the above loci. The complete profile of all alleles could still be obtained when the amount of DNA template was as low as 0.25 ng. There was no specific amplification peak in other common animal samples. Population genetic surveys showed that total discrimination power (TDP) of the 16 STR loci was 1-3.57×10^-20, the cumulative probability of exclusion (CPE) was 1-6.35×10^-5 and the cumulative probability of matching was 3.61×10^-20.

CONCLUSIONS

The Felis catus STR multiplex amplification system constructed in this study is highly sensitive, species-specific, and accurate in typing results, which can provide an effective solution for Felis catus species identification, individual identification and kinship identification in the field of forensic science.

Evaluation of the stability of the palatal rugae using the three-dimensional superimposition technique following orthodontic treatment

OBJECTIVES

To determine the uniqueness and stability of the palatal rugae after orthodontic treatment.

METHODS

Cast models of untreated subjects (n=50) were obtained twice at intervals of 8-30 months. Cast models of patients who received non-extraction (n=50) and extraction (n=50) orthodontic treatment were obtained before and after treatment at intervals of 11-41 months and 14-49 months, respectively. All 300 cast models were scanned digitally. The palatal rugae were manually extracted and transformed into 3D point clouds using reverse engineering software. An iterative closest point (ICP) registration algorithm based on correntropy was applied, and the minimum point-to-point root mean square (RMS) distances were calculated to analyze the deviation of palatal rugae for scans of the same subject (intrasubject deviation [ISD]) and between different subjects (between-subject deviation [BSD]). Differences in ISD between each group and the deviation between ISD and BSD of all 150 subjects were evaluated.

RESULTS

Significant differences were found in the 150 ISD and 1225 BSD in each group, as well as the 150 ISD and 11175 BSD across all groups. The mean values of ISD in untreated, non-extraction and extraction group were 0.178, 0.229 and 0.333 mm, respectively. When the first ruga was excluded in the extraction group, the mean ISD decreased to 0.241 mm, which was not significantly different from that in the non-extraction group (p=0.314).

CONCLUSIONS

Orthodontic treatment can influence the palatal rugae, especially in cases of extraction. Furthermore, variation mainly existed in the first ruga in cases of extraction. However, palatal rugae are still unique and may be used as a supplementary tool for individual identification.

CLINICAL SIGNIFICANCE

This study indicates that palatal rugae might be applied in the evaluation of orthodontic tooth movement and forensic individual identification. The registration algorithm based on correntropy provides a credible, precise, and convenient method for palatal rugae superimposition.

Individual Discriminative Ability of Resting Functional Brain Connectivity is Susceptible to the Time Span of MRI Scans

Recent studies have suggested that resting-state brain functional connectivity (RSFC) has the potential to discriminate among individuals in a population. These studies mostly utilized a pattern of RSFC obtained from one scan to identify a given individual from the set of patterns obtained from the second scan. However, it remains unclear whether the discriminative ability would change with the extension of the time span between the two brain scans. This study explores the variations in the discriminative ability of RSFC on eight time spans, including 6 hours, 12 hours, 1 day, 1 month, 3-6 months, 7-12 months, 1-2 years and 2-3 years. We first searched for a set of the most discriminative RSFCs using the data of 200 healthy adult subjects from the Human Connectome Project dataset, and we then utilized this set of RSFCs to identify individuals from a population. The variations in the discriminative accuracies over different time spans were evaluated on datasets from a total of 682 unseen adult subjects acquired from four different sites. We found that although the accuracies were detectable at above-chance levels, the discriminative accuracies showed a significant decrease (F = 17.87, p < 0.01) along with the extension of brain imaging time span, from over 90% within one month to 66% at 2-3 years. Furthermore, the decreasing trend was robust and not dependent on the training set or analysis method. Therefore, we suggest that the discriminative ability of RSFC in identifying individuals should be susceptible to the length of time between brain scans.

Forensic examination and application of areca nuts as material evidence

In this study, we aimed to explore the possibility of DNA analysis of areca nut as material evidence and the value of short tandem repeat (STR) typing of areca nut as material evidence under the condition of simulating external environment. In this study, water soaking, soil burial, sun exposure, and wet environment were used to treat areca nut residues. Chelex 100 was used to extract DNA, the PowerPlex21 kit to amplify, and the ABI PRISM^® 310 Genetic Analyzer to analyze the DNA of areca nut residues. DNA and STR typing were performed to analyze the residue after chewing. The results showed that the number of residual sites decreased with time under the conditions of water soaking, soil burial, sun exposure, and wet environment. Thus, areca nut can be used as forensic material evidence for DNA analysis and individual identification.

An inter-laboratory study of DNA-based identity, parentage and species testing in animal forensic genetics

The probative value of animal forensic genetic evidence relies on laboratory accuracy and reliability. Inter-laboratory comparisons allow laboratories to evaluate their performance on specific tests and analyses and to continue to monitor their output. The International Society for Animal Genetics (ISAG) administered animal forensic comparison tests (AFCTs) in 2016 and 2018 to assess the limitations and capabilities of laboratories offering forensic identification, parentage and species determination services. The AFCTs revealed that analyses of low DNA template concentrations (≤300 pg/µL) constitute a significant challenge that has prevented many laboratories from reporting correct identification and parentage results. Moreover, a lack of familiarity with species testing protocols, interpretation guidelines and representative databases prevented over a quarter of the participating laboratories from submitting correct species determination results. Several laboratories showed improvement in their genotyping accuracy over time. However, the use of forensically validated standards, such as a standard forensic short tandem repeat (STR) kit, preferably with an allelic ladder, and stricter guidelines for STR typing, may have prevented some common issues from occurring, such as genotyping inaccuracies, missing data, elevated stutter products and loading errors. The AFCTs underscore the importance of conducting routine forensic comparison tests to allow laboratories to compare results from each other. Laboratories should keep improving their scientific and technical capabilities and continuously evaluate their personnel's proficiency in critical techniques such as low copy number (LCN) analysis and species testing. Although this is the first time that the ISAG has conducted comparison tests for forensic testing, findings from these AFCTs may serve as the foundation for continuous improvements of the overall quality of animal forensic genetic testing.

No effect of passive integrated transponder tagging method on survival or body condition in a northern population of Black-capped Chickadees (Poecile atricapillus)

Passive integrated transponder (PIT) tags allow a range of individual-level data to be collected passively and have become a commonly used technology in many avian studies. Although the potential adverse effects of PIT tags have been evaluated in several species, explicit investigations of their impacts on small (<12 g) birds are limited. This is important, because it is reasonable to expect that smaller birds could be impacted more strongly by application of PIT tags. In this study, we individually marked Black-capped Chickadees (Poecile atricapillus), a small (circa 10 g) passerine, at the University of Alberta Botanic Garden to evaluate potential lethal and sublethal effects of two PIT tagging methods: attachment to leg bands or subcutaneous implantation. We used a Cox proportional hazards model to compare the apparent survival of chickadees with leg band (N = 79) and implanted PIT tags (N = 77) compared with control birds that received no PIT tags (N = 76) over the subsequent 2 years based on mist net recaptures. We used radio-frequency identification (RFID) redetections of leg band PIT tags to evaluate sex-specific survival and increase the accuracy of our survival estimates. We also used a generalized linear regression model to compare the body condition of birds recaptured after overwintering with leg band PIT tags, implanted PIT tags, or neither. Our analysis found no evidence for adverse effects of either PIT tagging method on survival or body condition. While we recommend carefully monitoring study animals and evaluating the efficacy of different PIT tagging methods, we have shown that both leg band and subcutaneously implanted PIT tags ethical means of obtaining individualized information in a small passerine.

Key Intrinsic Connectivity Networks for Individual Identification With Siamese Long Short-Term Memory

In functional magnetic resonance imaging (fMRI) analysis, many studies have been conducted on inter-subject variability as well as intra-subject reproducibility. These studies indicate that fMRI could have unique characteristics for individuals. In this study, we hypothesized that the dynamic information during 1 min of fMRI was unique and repetitive enough for each subject, so we applied long short-term memory (LSTM) using initial time points of dynamic resting-state fMRI for individual identification. Siamese network is used to obtain robust individual identification performance without additional learning on a new dataset. In particular, by adding a new structure called region of interest–wise average pooling (RAP), individual identification performance could be improved, and key intrinsic connectivity networks (ICNs) for individual identification were also identified. The average performance of individual identification was 97.88% using the test dataset in eightfold cross-validation analysis. Through the visualization of features learned by Siamese LSTM with RAP, ICNs spanning the parietal region were observed as the key ICNs in identifying individuals. These results suggest the key ICNs in fMRI could represent individual uniqueness.

Microsatellite DNA Analysis for Diversity Study, Individual Identification and Parentage Control in Pig Breeds in Poland

Swine DNA profiling is of high importance for animal identification and parentage verification. The aim of this study was to test a set of 14 microsatellite (STR) markers recommended by ISAG for parentage verification in Polish Landrace (PL, n = 900), Polish Large White (PLW, n = 482), Pulawska (PUL, n = 127), and Duroc pigs (DU n = 108). The studied breeds showed a medium level of genetic differentiation. The average value of heterozygosity and degree of polymorphism (PIC) were above 0.5 for the studied breeds, except for the DU breed (PIC = 0.477). The population inbreeding coefficient indicates an absence of inbreeding in the studied breeds (an average value of F_IS = 0.007). The cumulative power of discrimination for all breeds reached high values close to 1.0, while the probability of identity (P_ID) was low, with P_ID values ranging between 10⁻⁹ (for DU) and 10⁻¹² (for PLW). The cumulative exclusion probability for PE₁ and PE₂ showed that the parentage can be confirmed with a probability of from 92.75% to 99.01% and from 99.49% to 99.97%, respectively.

Functional connectome fingerprinting: Identifying individuals and predicting cognitive functions via autoencoder

Functional network connectivity has been widely acknowledged to characterize brain functions, which can be regarded as “brain fingerprinting” to identify an individual from a pool of subjects. Both common and unique information has been shown to exist in the connectomes across individuals. However, very little is known about whether and how this information can be used to predict the individual variability of the brain. In this paper, we propose to enhance the uniqueness of individual connectome based on an autoencoder network. Specifically, we hypothesize that the common neural activities shared across individuals may reduce the individual identification. By removing contributions from shared activities, inter‐subject variability can be enhanced. Our experimental results on HCP data show that the refined connectomes obtained by utilizing autoencoder with sparse dictionary learning can distinguish an individual from the remaining participants with high accuracy (up to 99.5% for the rest–rest pair). Furthermore, high‐level cognitive behaviors (e.g., fluid intelligence, executive function, and language comprehension) can also be better predicted with the obtained refined connectomes. We also find that high‐order association cortices contribute more to both individual discrimination and behavior prediction. In summary, our proposed framework provides a promising way to leverage functional connectivity networks for cognition and behavior study, in addition to a better understanding of brain functions.

Microsatellite DNA Analysis of Genetic Diversity and Parentage Testing in the Popular Dog Breeds in Poland

There is growing concern that extreme breed standardization contributes to a reduction of the effective population size and high levels of inbreeding, resulting in the loss of genetic diversity in many breeds. This study examined genetic diversity among eight popular dog breeds in Poland and evaluated the effectiveness of a 21-microsatellite (STR) panel recommended by the International Society for Animal Genetics (ISAG) for parent verification. The following breeds were characterized: German Shepherd, Maltese, Irish Wolfhound, Yorkshire Terrier, Biewer Yorkshire Terrier, Golden Retriever, Labrador Retriever, and French Bulldog. STRUCTURE analysis showed breed distinctiveness among all the dog breeds under study. Reynold’s distance ranged between θ_w = 0.634 and θ_w = 0.260. The studied breeds showed a medium level of genetic differentiation; the mean number of alleles per locus ranged from 3.4 to 6.6, and the effective number of alleles from 2.1 to 3.5. The mean degree of heterozygosity varied from 49% to 69% and from 47% to 68% for H_O and H_E, respectively. The population inbreeding coefficient (FIS) indicated an absence of inbreeding in the studied breeds. The average polymorphism information content (PIC) values for most of the breeds were higher than 0.5. The cumulative power of discrimination (PD) for all the markers in all breeds reached high values (close to 1.0), while the probability of identity (P_ID) was low, ranging between 10⁻¹¹ and 10⁻¹⁹. The cumulative exclusion probability when the genotypes of one (PE₁) and both parents (PE₂) are known and showed that the parentage can be confirmed with a probability of 94.92% to 99.95% and 99.78% to 99.9999%, respectively.

How I See Me-A Meta-Analysis Investigating the Association Between Identities and Pro-environmental Behaviour

Prolific research suggests identity associates with pro-environmental behaviours (PEBs) that are individual and/or group focused. Individual PEB is personally driven, self-reliant, and are conducted on one's own (e.g., home recycling). Group focused PEB is other people-reliant and completed as part of a group (e.g., attending meetings of an environmental organisation). A wide range of identities have been related to PEBs. For example, a recent systematic qualitative review revealed 99 different types of identities studied in a PEB context. Most studies were correlational, few had an experimental design. However, the relationships between all these identities and PEBs have so far not been tested quantitatively with meta-analytical techniques. As such, a clear overview of this field is currently lacking. Due to the diverse nature of the field, a priori hypotheses were not possible and relatively broad definitions of identity had to be used to encompass all types of identities and the diverse meanings of identity that have been included in PEB research. What prior theory did allow for was to assess the distinction between two main types of identity, namely how people label, describe, and recognise oneself individually (individual identity), or as part of a group (group identity). Our overall goal was thus to assess the current state of knowledge on identities and PEBs. In 104 studies using a meta-regression following the preferred reporting items for systematic reviews and meta-analyses guidelines, our random-effects meta-analysis showed that the overall concept of identity associated with PEB with a medium Pearson's r (Aim 1). Furthermore, we found that individual identities associated more strongly with PEBs than group identities (Aim 2). The associations between individual and group identities were stronger when the identity and PEB were from the same category (e.g., when both were group-focused; Aim 3). Methodologically, the findings revealed that group identities and group PEBs were most strongly associated for self-reported rather than observed PEBs (Aim 4). Overall identity associated most strongly with group PEBs in the field rather than in the lab (Aim 5) and in student- rather than non-student samples (Aim 6). We discuss the theoretical and practical implications.

A Novel Panel of 43 Insertion/Deletion Loci for Human Identifications of Forensic Degraded DNA Samples: Development and Validation

Insertion/deletion polymorphism is a promising genetic marker in the forensic genetic fields, especially in the forensic application of degraded sample at crime scene. In this research, a novel five-dye multiplex amplification panel containing 43 highly polymorphic Insertion/deletion (InDel) loci and one Amelogenin gene locus is designed and constructed in-house for the individual identification in East Asian populations. The amplicon sizes of 43 InDel loci are less than 200 bp, which help to ensure that full allele profiles can be obtained from degraded DNA sample. A series of optimizations and developmental validations including optimization of PCR conditions, detection efficiency of the degraded and casework samples, sensitivity, reproducibility, precision, tolerance for inhibitors, species specificity and DNA mixtures are performed according to the Scientific Working Group on DNA Analysis Methods (SWGDAM) guideline. The results of the internal validation demonstrated that this novel InDel panel was a reliable, sensitive and accurate system with good tolerances to different inhibitors, and performed the considerable detection efficiency for the degraded or mixed samples, which could be used in the forensic applications.

Surface-enhanced Raman Scattering and X-ray Fluorescence Analyses of a Single Hair Colored with a Hair Dye Product

This paper describes a method for obtaining information that can contribute to individual identification from a single hair colored with a hair dye product using a combination of surface-enhanced Raman scattering (SERS) and X-ray fluorescence (XRF) analyses. SERS and XRF spectra of single hog hairs colored with several commercially available hair dye products were measured. SERS spectral patterns tended to be different depending on the hair dye products used for hair coloring. However, SERS spectral patterns of single hog hairs colored with different hair dye products that would produce similar types of dyes were similar. By performing XRF analysis, characteristic metallic elements originating from some hair dye products were detected. Therefore, XRF can contribute to identifying the difference among colored hairs that cannot be identified only by SERS. SERS and XRF analyses of a single shed hair can contribute to individual identification used in forensic science.

Development of microsatellite markers for a soricid water shrew, Chimarrogale platycephalus, and their successful use for individual identification

The soricid water shrew Chimarrogale platycephalus is a mammalian species endemic to the Japanese Islands. The animals inhabit the islands of Honshu and Kyushu, and are considered to be extinct in Shikoku. Information on this water shrew from Honshu and Kyushu is scarce, and C. platycephalus is registered on many local governments' red lists as an endangered species. There are very few studies on their ethology, ecology or phylogenetics, due to difficulties related to the shrews being both nocturnal and aquatic: to study C. platycephalus, field research must be conducted in mountain streams at night. To overcome these challenges, we previously established a genetic analysis method using the feces of C. platycephalus, as a result of which the amount of phylogenetic and phylogeographic data has increased and our understanding of the species has improved. In this study, microsatellite markers were developed, and analyses using markers for 21 loci were performed. Moreover, to confirm the ability of these 21 microsatellite markers to differentiate individuals, all markers were tested using fecal and tissue specimens from 12 individuals reared separately in an aquarium. Using as few as 12 of these loci, individual differentiation with 100% accuracy should be achievable. The development of microsatellite markers in this study and the establishment of individual identification methods should greatly contribute to future ecological, ethological, population genetics and biogeographical research on C. platycephalus.

Amur tiger stripes: individual identification based on deep convolutional neural network

The automatic individual identification of Amur tigers (Panthera tigris altaica) is important for population monitoring and making effective conservation strategies. Most existing research primarily relies on manual identification, which does not scale well to large datasets. In this paper, the deep convolution neural networks algorithm is constructed to implement the automatic individual identification for large numbers of Amur tiger images. The experimental data were obtained from 40 Amur tigers in Tieling Guaipo Tiger Park, China. The number of images collected from each tiger was approximately 200, and a total of 8277 images were obtained. The experiments were carried out on both the left and right side of body. Our results suggested that the recognition accuracy rate of left and right sides are 90.48% and 93.5%, respectively. The accuracy of our network has achieved the similar level compared to other state of the art networks like LeNet, ResNet34, and ZF_Net. The running time is much shorter than that of other networks. Consequently, this study can provide a new approach on automatic individual identification technology in the case of the Amur tiger.

Construction and forensic application of 20 highly polymorphic microhaplotypes

Microhaplotype markers have become an important research focus in forensic genetics. However, many reported microhaplotype markers have limited polymorphisms. In this study, we developed a set of highly polymorphic microhaplotype markers based on tri-allelic single-nucleotide polymorphisms. Eleven newly discovered microhaplotypes along with nine previously identified in our laboratory were studied. The microhaplotype genotypes of unrelated individuals and familial samples were generated on the MiSeq PE300 platform. These 20 loci have an average greater than 3.5 effective number of alleles. Over the whole set, the cumulative power of discrimination was 1-3.3 × 10^-18, the cumulative power of exclusion was 1-1.928 × 10^-7 and the theoretical probability of detecting a mixture was 1-1.427 × 10^-6. Differentiation comparisons of 26 populations from the 1000 Genomes Project distinguished among East Asian, South Asian, African and European populations. Overall, these markers enrich the current microhaplotype marker databases and can be applied for individual identification, paternity testing and biogeographic ancestry distinction.

A study on giant panda recognition based on images of a large proportion of captive pandas

As a highly endangered species, the giant panda (panda) has attracted significant attention in the past decades. Considerable efforts have been put on panda conservation and reproduction, offering the promising outcome of maintaining the population size of pandas. To evaluate the effectiveness of conservation and management strategies, recognizing individual pandas is critical. However, it remains a challenging task because the existing methods, such as traditional tracking method, discrimination method based on footprint identification, and molecular biology method, are invasive, inaccurate, expensive, or challenging to perform. The advances of imaging technologies have led to the wide applications of digital images and videos in panda conservation and management, which makes it possible for individual panda recognition in a noninvasive manner by using image-based panda face recognition method.In recent years, deep learning has achieved great success in the field of computer vision and pattern recognition. For panda face recognition, a fully automatic deep learning algorithm which consists of a sequence of deep neural networks (DNNs) used for panda face detection, segmentation, alignment, and identity prediction is developed in this study. To develop and evaluate the algorithm, the largest panda image dataset containing 6,441 images from 218 different pandas, which is 39.78% of captive pandas in the world, is established.The algorithm achieved 96.27% accuracy in panda recognition and 100% accuracy in detection.This study shows that panda faces can be used for panda recognition. It enables the use of the cameras installed in their habitat for monitoring their population and behavior. This noninvasive approach is much more cost-effective than the approaches used in the previous panda surveys.

An innovative panel containing a set of insertion/deletion loci for individual identification and its forensic efficiency evaluations in Chinese Hui ethnic minority

BACKGROUND

Individual identification is one of the most important tasks in the field of forensic genetics. Insertion/Deletion (InDel) polymorphism marker has been a promising marker for individual identification. However, a part of InDel loci in commonly used commercial kit show low polymorphisms in Chinese populations.

METHODS

We evaluated a panel of 35 InDel loci constructed previously for individual identifications in Hui group. Subsequently, population data of three Chinese populations from 1,000 Genomes Project database were used to evaluate individual identification performance of these 35 InDels. Forensic parameters, such as heterozygosity, power of exclusion, match probability and power of discrimination, were calculated to evaluate the forensic efficiency of these loci in Hui group. The heatmap of insertion allelic frequencies, Nei's genetic distances, pairwise fixation index values, principal component analyses and admixture analyses were used to analyze the genetic differentiations and structure between Hui group and other populations.

RESULTS

In studied Hui group, besides rs3054057, polymorphism information content values of the remaining loci were greater than 0.3. Values of expected heterozygosity of these loci were close to 0.5. The combined power of discrimination and power of exclusion values were 0.99999999999999659609 and 0.998682, respectively. Analyses of population genetics revealed that Chinese Hui group had closer genetic relationships with East Asian populations than other intercontinental populations.

CONCLUSION

The forensic statistical analyses revealed these loci showed relatively high genetic polymorphisms in Chinese Hui group, and could be served as a useful tool for individual identifications in Hui group. Population genetic evaluations indicated that Chinese Hui group had close genetic relationships with East Asian populations.

Genetic affinity between Ningxia Hui and eastern Asian populations revealed by a set of InDel loci

According to historical records, ethnic Hui in China obtained substantial genetic components from western Eurasian populations during their Islamization. However, some scholars believed that the ancestry of Hui people were native Chinese populations. In this context, the formation of Hui is due to simple cultural diffusion rather than demic diffusion. In this study, we examined the forensic and population genetic application of the 30 InDel loci in Hui population from Ningxia Hui Autonomous Region, Northwest China. Genotype analysis of 129 unrelated individuals revealed that all loci were in the Hardy-Weinberg equilibrium in Ningxia Hui. Forensic indices calculated from genotypes demonstrated that this panel, Qiagen DIPplex® Investigator kit, was powerful enough to be used in individual identification but not in paternity cases. Through population genetic analysis, we found that Ningxia Hui received much more genetic contributions from East Asian populations than those from western Eurasian populations. Finally, we statistically identified the admixture signal of eastern and western Eurasians, although the latter is weak, in Ningxia Hui via the three-population test. All this evidence suggested that the formation of Ningxia Hui was mainly attributed to the cultural transformation of local Chinese residents with minor gene flow from western Eurasian populations.

Automatic monitoring system for individual dairy cows based on a deep learning framework that provides identification via body parts and estimation of body condition score

Body condition score (BCS) is a common tool for indirectly estimating the mobilization of energy reserves in the fat and muscle of cattle that meets the requirements of animal welfare and precision livestock farming for the effective monitoring of individual animals. However, previous studies on automatic BCS systems have used manual scoring for data collection, and traditional image extraction methods have limited model performance accuracy. In addition, the radio frequency identification device system commonly used in ranching has the disadvantages of misreadings and damage to bovine bodies. Therefore, the aim of this research was to develop and validate an automatic system for identifying individuals and assessing BCS using a deep learning framework. This work developed a linear regression model of BCS using ultrasound backfat thickness to determine BCS for training sets and tested a system based on convolutional neural networks with 3 channels, including depth, gray, and phase congruency, to analyze the back images of 686 cows. After we performed an analysis of image model performance, online verification was used to evaluate the accuracy and precision of the system. The results showed that the selected linear regression model had a high coefficient of determination value (0.976), and the correlation coefficient between manual BCS and ultrasonic BCS was 0.94. Although the overall accuracy of the BCS estimations was high (0.45, 0.77, and 0.98 within 0, 0.25, and 0.5 unit, respectively), the validation for actual BCS ranging from 3.25 to 3.5 was weak (the F1 scores were only 0.6 and 0.57, respectively, within the 0.25-unit range). Overall, individual identification and BCS assessment performed well in the online measurement, with accuracies of 0.937 and 0.409, respectively. A system for individual identification and BCS assessment was developed, and a convolutional neural network using depth, gray, and phase congruency channels to interpret image features exhibited advantages for monitoring thin cows.

A novel 13-plex STR typing system for individual identification and parentage testing of donkeys (Equus asinus)

BACKGROUND

Previous studies investigating donkey parentage and genetic diversity used horse-specific multiplex systems. However, several mis-allele and null-allele issues were found with some of the horse primers when used in donkeys. In 2017, the International Society for Animal Genetics (ISAG) recommended 13 dinucleotide short tandem repeats (STRs) (AHT4, ASB23, HMS2, HMS3, HMS6, HMS7, HMS18, HTG7, HTG10, TKY297, TKY312, TKY337 and TKY343) as a core panel that should be used to identify individuals and to test for parentage in donkeys. To date, no single multiplex STR typing system containing all 13 donkey STRs recommended by the ISAG has been reported.

OBJECTIVES

To establish a novel and donkey-specific multiplex STR typing system containing all 13 recommended STRs.

STUDY DESIGN

Assay development and validation in field population.

METHODS

Primers for seven of the STRs were redesigned and conditions for polymerase chain reaction (PCR) were optimised. We analysed the allele sequences, sensitivity, species-specificity and stutter ratios of this new system.

RESULTS

A 13-plex STR typing system for donkey was established. A full profile could be generated from a single PCR reaction using as little as 5 ng of DNA template with the 13 pairs of primers labelled with fluorescent dyes. An allele ladder, containing 101 alleles from the 13 STRs, was generated. No full genotype profile was generated with these primers if DNA from humans, or 11 other commonly encountered animals, was used. Genotypes could be generated for the horse and horse-donkey hybrids (mule and hinny). Stutter ratios and population genetic parameters were calculated based on samples from 150 donkeys. The combined probabilities of paternity exclusion for this system were 0.988907326 (CPEduo) and 0.999665018 (CPEtrio).

MAIN LIMITATIONS

This system cannot detect sex.

CONCLUSIONS

Our results indicate that our donkey-specific 13-plex STR typing system is sensitive, species-specific and robust for individual identification, paternity testing and population genetic analysis in donkeys, and has potential forensic applications.

Refined measure of functional connectomes for improved identifiability and prediction

Brain functional connectome analysis is commonly based on population-wise inference. However, in this way precious information provided at the individual subject level may be overlooked. Recently, several studies have shown that individual differences contribute strongly to the functional connectivity patterns. In particular, functional connectomes have been proven to offer a fingerprint measure, which can reliably identify a given individual from a pool of participants. In this work, we propose to refine the standard measure of individual functional connectomes using dictionary learning. More specifically, we rely on the assumption that each functional connectivity is dominated by stable group and individual factors. By subtracting population-wise contributions from connectivity patterns facilitated by dictionary representation, intersubject variability should be increased within the group. We validate our approach using several types of analyses. For example, we observe that refined connectivity profiles significantly increase subject-specific identifiability across functional magnetic resonance imaging (fMRI) session combinations. Besides, refined connectomes can also improve the prediction power for cognitive behaviors. In accordance with results from the literature, we find that individual distinctiveness is closely linked with differences in neurocognitive activity within the brain. In summary, our results indicate that individual connectivity analysis benefits from the group-wise inferences and refined connectomes are indeed desirable for brain mapping.

Application of Convolutional Recurrent Neural Network for Individual Recognition Based on Resting State fMRI Data

In most task and resting state fMRI studies, a group consensus is often sought, where individual variability is considered a nuisance. None the less, biological variability is an important factor that cannot be ignored and is gaining more attention in the field. One recent development is the individual identification based on static functional connectome. While the original work was based on the static connectome, subsequent efforts using recurrent neural networks (RNN) demonstrated that the inclusion of temporal features greatly improved identification accuracy. Given that convolutional RNN (ConvRNN) seamlessly integrates spatial and temporal features, the present work applied ConvRNN for individual identification with resting state fMRI data. Our result demonstrates ConvRNN achieving a higher identification accuracy than conventional RNN, likely due to better extraction of local features between neighboring ROIs. Furthermore, given that each convolutional output assembles in-place features, they provide a natural way for us to visualize the informative spatial pattern and temporal information, opening up a promising new avenue for analyzing fMRI data.

CORTICAL FOLDINGPRINTS FOR INFANT IDENTIFICATION

Cortical folding of the adult brain is highly convoluted and encodes inter-subject variable characteristics. Recent studies suggest that it is useful for individual identification in adults. However, little is known about whether the infant cortical folding, which undergoes dynamic postnatal development, can be used for individual identification. To fill this gap, we propose to explore cortical folding patterns for infant subject identification. This study thus aims to address two important questions in neuroscience: 1) whether the infant cortical folding is unique for individual identification; and 2) considering the region-specific inter-subject variability, which cortical regions are more distinct and reliable for infant identification. To this end, we propose a novel discriminative descriptor of regional cortical folding based on multi-scale analysis of curvature maps via spherical wavelets, called FoldingPrint. Experiments are carried out on a large longitudinal dataset with 1,141 MRI scans from 472 infants. Despite the dramatic development in the first two years, successful identification of 1-year-olds and 2-year-olds using their neonatal cortical folding (with accuracy > 98%) indicates the effectiveness of the proposed method. Moreover, we reveal that regions with high identification accuracy and large inter-subject variability mainly distribute in high-order association cortices.

[Application progress of gas chromatography-mass spectrometry in the analysis of human body odor]

Gas chromatography-mass spectrometry (GC-MS) is currently the most technical approach for the analysis of human body odor, which can be used to determine the composition of human body odor and compare the differences between different individual odors. This paper focuses on the application progress of GC-MS in human body odor analysis. First, the extraction and sample pretreatment of human body odor are briefly introduced. The applications of the human body odor analysis by GC-MS in collection and storage, the composition analysis and study of difference, and individual identification and health characterization are summarized. Finally, the application trends of GC-MS in human body odor analysis are discussed.

DNA recovery and analysis from skeletal material in modern forensic contexts

The generation of a DNA profile from skeletal remains is an important part of the identification process in both mass disaster and unidentified person cases. Since bones and teeth are often the only biological materials remaining after exposure to environmental conditions, intense heat, certain traumatic events and in cases where a significant amount of time has passed since the death of the individual, the ability to purify large quantities of informative DNA from these hard tissues would be beneficial. Since sampling the hard tissues for genetic analysis is a destructive process, it is important to understand those environmental and intrinsic factors that contribute to DNA preservation. This will serve as a brief introduction to these topics, since skeletal sampling strategies and molecular taphonomy have been discussed in depth elsewhere. Additionally advances in skeletal DNA extraction and analysis will be discussed. Currently there is great variation in the DNA isolation methods used by laboratories to purify DNA from the hard tissues; however, a standardized set of short tandem repeat (STR) loci is analyzed by many US laboratories to allow for comparisons across samples and jurisdictions. Recent advances have allowed for the generation of DNA profiles from smaller quantities of template DNA and have expanded the number of loci analyzed for greater discriminatory power and predictions regarding the geographic ancestry and phenotype of the individual. Finally, utilizing databases and expanding the number of comparison samples will be discussed in light of their role in the identification process.