Individual Discrimination Research Articles

The intra- and inter-observer reliability of a novel protocol for two-point discrimination in individuals with chronic low back pain

The intra- and inter-observer reliability of a novel protocol for two-point discrimination in individuals with chronic low back pain

Vision-based discrimination of tuna individuals in grow-out cages through a fish bending model

This paper proposes a robust deformable adaptive 2D model, based on computer vision methods, that automatically fits the body (ventral silhouette) of Bluefin tuna while swimming. Our model (without human intervention) adjusts to fish shape and size, obtaining fish orientation, bending to fit their flexion motion and has proved robust enough to overcome possible segmentation inaccuracies. Once the model has been successfully fitted to the fish it can ensure that the detected object is a tuna and not parts of fish or other objects. Automatic requirements of the fishing industry like biometric measurement, specimen counting or catch biomass estimation could then be addressed using a stereoscopic system and meaningful information extracted from our model. We also introduce a fitting procedure based on a fitting parameter – Fitting Error Index (FEI) – which permits us to know the quality of the results. In the experiments our model has achieved very high success rates (up to 90%) discriminating individuals in highly complex images acquired for us in real conditions in the Mediterranean Sea. Conclusions and future improvements to the proposed model are also discussed.

Predicting early psychiatric readmission with natural language processing of narrative discharge summaries.

The ability to predict psychiatric readmission would facilitate the development of interventions to reduce this risk, a major driver of psychiatric health-care costs. The symptoms or characteristics of illness course necessary to develop reliable predictors are not available in coded billing data, but may be present in narrative electronic health record (EHR) discharge summaries. We identified a cohort of individuals admitted to a psychiatric inpatient unit between 1994 and 2012 with a principal diagnosis of major depressive disorder, and extracted inpatient psychiatric discharge narrative notes. Using these data, we trained a 75-topic Latent Dirichlet Allocation (LDA) model, a form of natural language processing, which identifies groups of words associated with topics discussed in a document collection. The cohort was randomly split to derive a training (70%) and testing (30%) data set, and we trained separate support vector machine models for baseline clinical features alone, baseline features plus common individual words and the above plus topics identified from the 75-topic LDA model. Of 4687 patients with inpatient discharge summaries, 470 were readmitted within 30 days. The 75-topic LDA model included topics linked to psychiatric symptoms (suicide, severe depression, anxiety, trauma, eating/weight and panic) and major depressive disorder comorbidities (infection, postpartum, brain tumor, diarrhea and pulmonary disease). By including LDA topics, prediction of readmission, as measured by area under receiver-operating characteristic curves in the testing data set, was improved from baseline (area under the curve 0.618) to baseline+1000 words (0.682) to baseline+75 topics (0.784). Inclusion of topics derived from narrative notes allows more accurate discrimination of individuals at high risk for psychiatric readmission in this cohort. Topic modeling and related approaches offer the potential to improve prediction using EHRs, if generalizability can be established in other clinical cohorts.

Role of vocal tract characteristics in individual discrimination by Japanese macaques (Macaca fuscata).

The Japanese macaque (Macaca fuscata) exhibits a species-specific communication sound called the “coo call” to locate group members and maintain within-group contact. Monkeys have been demonstrated to be capable of discriminating between individuals based only on their voices, but there is still debate regarding how the fundamental frequencies (F0) and filter properties of the vocal tract characteristics (VTC) contribute to individual discrimination in nonhuman primates. This study was performed to investigate the acoustic keys used by Japanese macaques in individual discrimination. Two animals were trained with standard Go/NoGo operant conditioning to distinguish the coo calls of two unfamiliar monkeys. The subjects were required to continue depressing a lever until the stimulus changed from one monkey to the other. The test stimuli were synthesized by combining the F0s and VTC from each individual. Both subjects released the lever when the VTC changed, whereas they did not when the F0 changed. The reaction times to the test stimuli were not significantly different from that to the training stimuli that shared the same VTC. Our data suggest that vocal tract characteristics are important for the identification of individuals by Japanese macaques.

Individually distinctive vocalization in Common Cuckoos (Cuculus canorus)

Distinctive individual vocalizations are advantageous in several social contexts. Both genetic and environmental effects are responsible for this phenomenon resulting in different frequencies and time domains of sounds in birds. This individuality can be utilized in breeding bird censuses and abundance estimates. In this study we explored the individuality of the advertisement calls of male Common Cuckoos (Cuculus canorus) with the aims of describing the ways in which individuals differ from each other acoustically, and characterizing the practical requirements for using statistical learning methods for individual recognition. We collected calls from a Hungarian Cuckoo population and conducted discriminant function analysis on acoustic parameters to distinguish individuals. We show that individuals differ in both the frequency and time of their calls, most importantly in maximum frequency of the first syllable. Our discrimination of the calls of 26 male individuals was almost 100 % accurate, and even when the number of samples was reduced to five calls per individual, and the number of acoustic parameters was decreased to five variables, accuracy still exceeded 90 %. Our acoustic individual discrimination technique is applicable to a wide range of ecological and behavioural studies because it is easy to perform and can be readily automated.

UnMarginalizing Workers: How Big Data Drives Lower Wages and How Reframing Labor Law Can Restore Information Equality in the Workplace

While there has been a flurry of new scholarship on how employer use of data analysis may lead to subtle but potentially devastating individual discrimination in employment systems, there has been far less attention to the ways the deployment of big data may be driving down wages for most workers, including those who manage to be hired. This article details the ways big data can and in many cases is actively being deployed to lower wages through hiring practices, in the ways raises are now being offered, and in the ways workplaces are organized (and disorganized) to lower employee bargaining power — and how new interpretations of labor law are beginning to and can in the future reshape the workplace to address these economic harms.Data analysis is increasingly helping to lower wages in companies beginning in the hiring process where pre-hire personality testing helps employers screen out employees who will agitate for higher wages and organize or support unionization drives in their companies. For employees who are hired, companies have massively expanded data-driven workplace surveillance that allows employers to assess which employees are most likely to leave and thereby limit pay increases largely to them, lowering wages over time for workers either less able to find new employment because of their age or less inclined in general to risk doing so. Data analysis and so-called “algorithmic management” has also allowed the centralized monitoring of far flung workers organized nominally in subcontractors or as individual contractors, while traditional firms such as in retail implement data-driven scheduling that resembles the “on-demand” employment of independent contractors. All of this shifts risk and “downtime” costs to employees and lowers their take-home pay, even as the fragmenting of the workplace makes it harder for workers to collectively organize for higher wages. The article addresses how we should rethink and interpret existing labor law in each of these aspects of the employment process. The NLRB can reasonably construe many pre-hire employment tests as violating federal labor law’s prohibition of screening out union sympathizers, much as the EEOC has found many personality tests violate the Americans with Disabilities Act by allowing indirect identification of people with mental illness. Similarly, since big data analysis can reveal pro-union sympathies of current employees, under existing prohibitions of “polling” employees for their views, a reasonable extension of the law would be to prohibit sharing any personal data collected by management that might reveal protected conduct or union sympathies with line managers or outside management consultants involved in advising in labor campaigns. The Board can also level the informational playing field by making both hiring algorithms and those determining pay increases more available during collective bargaining. The Board is already moving to expand its “joint employer” doctrine to allow workers to challenge the fragmented workplace increasingly driven by algorithmic management and a clear recognition that algorithms establish exactly the control of nominally independent contractors or subcontractor’s workers that entitle them to collective bargaining rights with a central employer, strengthening worker bargaining power.Such a “collective action” approach to the problem is far more likely to succeed than other proposals focused on strengthening individual worker privacy or anti-discrimination rights in the workplace in regards to data-driven decision-making. As scholars have noted, disadvantaged groups under the civil rights laws may have sharply different preferences in wage versus benefit packages, so a process that increases informational resources for all workers and allows them to negotiate together for the mix of wages, benefits, work conditions and other “public goods” in the workplace, including privacy protections, will better reflect the overall interests of employees than in either a classic economic model based on a marginal worker’s “exit” or a “rights consciousness” litigation approach to rein in individual employment harms. In making this overall argument, the article partially addresses the debate on why wages have stagnated and even fallen below productivity gains over the last four decades as the deployment of data technology has played a significant and growing role in helping employers extract a disproportionate share of employee productivity gains to the benefit of management and shareholders.

Who shall I say is calling? Validation of a caller recognition procedure in Bornean flanged male orangutan (Pongo pygmaeus wurmbii) long calls

Acoustic individual discrimination has been demonstrated for a wide range of animal taxa. However, there has been far less scientific effort to demonstrate the effectiveness of automatic individual identification, which could greatly facilitate research, especially when data are collected via an acoustic localization system (ALS). In this study, we examine the accuracy of acoustic caller recognition in long calls (LCs) emitted by Bornean male orangutans (Pongo pygmaeus wurmbii) derived from two data-sets: the first consists of high-quality recordings taken during individual focal follows (N = 224 LCs by 14 males) and the second consists of LC recordings with variable microphone-caller distances stemming from ALS (N = 123 LCs by 10 males). The LC is a long-distance vocalization. We therefore expect that even the low-quality test-set should yield caller recognition results significantly better than by chance. Automatic individual identification was accomplished using software originally developed for human speaker recognition (i.e. the MSR identity toolbox). We obtained a 93.3% correct identification rate with high-quality recordings, and 72.23% with recordings stemming from the ALS with variable microphone-caller distances (20–420 m). These results show that automatic individual identification is possible even though the accuracy declines compared with the results of high-quality recordings due to severe signal degradations (e.g. sound attenuation, environmental noise contamination, and echo interference) with increasing distance. We therefore suggest that acoustic individual identification with speaker recognition software can be a valuable tool to apply to data obtained through an ALS, thereby facilitating field research on vocal communication.

Grey matter volume patterns in thalamic nuclei are associated with familial risk for schizophrenia

Previous evidence suggests reduced thalamic grey matter volume (GMV) in patients with schizophrenia (SCZ). However, it is not considered an intermediate phenotype for schizophrenia, possibly because previous studies did not assess the contribution of individual thalamic nuclei and employed univariate statistics. Here, we hypothesized that multivariate statistics would reveal an association of GMV in different thalamic nuclei with familial risk for schizophrenia. We also hypothesized that accounting for the heterogeneity of thalamic GMV in healthy controls would improve the detection of subjects at familial risk for the disorder.We acquired MRI scans for 96 clinically stable SCZ, 55 non-affected siblings of patients with schizophrenia (SIB), and 249 HC. The thalamus was parceled into seven regions of interest (ROIs). After a canonical univariate analysis, we used GMV estimates of thalamic ROIs, together with total thalamic GMV and premorbid intelligence, as features in Random Forests to classify HC, SIB, and SCZ. Then, we computed a Misclassification Index for each individual and tested the improvement in SIB detection after excluding a subsample of HC misclassified as patients.Random Forests discriminated SCZ from HC (accuracy=81%) and SIB from HC (accuracy=75%). Left anteromedial thalamic volumes were significantly associated with both multivariate classifications (p<0.05). Excluding HC misclassified as SCZ improved greatly HC vs. SIB classification (Cohen's d=1.39). These findings suggest that multivariate statistics identify a familial background associated with thalamic GMV reduction in SCZ. They also suggest the relevance of inter-individual variability of GMV patterns for the discrimination of individuals at familial risk for the disorder.

Toward the integration of Omics data in epidemiological studies: still a "long and winding road".

Primary and secondary prevention can highly benefit a personalized medicine approach through the accurate discrimination of individuals at high risk of developing a specific disease from those at moderate and low risk. To this end precise risk prediction models need to be built. This endeavor requires a precise characterization of the individual exposome, genome, and phenome. Massive molecular omics data representing the different layers of the biological processes of the host and the nonhost will enable to build more accurate risk prediction models. Epidemiologists aim to integrate omics data along with important information coming from other sources (questionnaires, candidate markers) that has been proved to be relevant in the discrimination risk assessment of complex diseases. However, the integrative models in large-scale epidemiologic research are still in their infancy and they face numerous challenges, some of them at the analytical stage. So far, there are a small number of studies that have integrated more than two omics data sets, and the inclusion of non-omics data in the same models is still missing in most of studies. In this contribution, we aim at approaching the omics and non-omics data integration from the epidemiology scope by considering the "massive" inclusion of variables in the risk assessment and predictive models. We also provide already available examples of integrative contributions in the field, propose analytical strategies that allow considering both omics and non-omics data in the models, and finally review the challenges imbedding this type of research.

Introducing a Recovery Education Centre for Adults Experiencing Mental Health Challenges and Housing Instability in a Large Urban Setting

The Supporting Transitions and Recovery (STAR) Learning Centre is a Recovery Education Centre designed to support housing tenure and community integration among people experiencing mental health challenges and housing instability in a large urban setting. Grounded in principles of emancipatory adult education, and user involvement in program design and delivery, the Recovery Education Centre supports student empowerment, and strengthens key domains of individual vulnerability to homelessness. The Centre can complement traditional mental health services and foster service provider reflexivity, confronting individual and institutional discrimination towards this population.

Developmental validation of the Yfiler® Plus PCR Amplification Kit: An enhanced Y-STR multiplex for casework and database applications

Y-chromosomal loci have proven useful in solving investigations where low levels of male DNA are present in a high female DNA background. An intrinsic limitation of Y-STRs compared with autosomal STRs is a reduced power of discrimination due to a lack of recombination throughout most of the Y-chromosome. Thus, in an effort to increase the power of discrimination we have developed a new 6-dye, 27-plex Y-STR system that includes the 17 loci from the Yfiler® and Yfiler® Direct kits (DYS19, DYS385a/b, DYS389I/II, DYS390, DYS391, DYS392, DYS393, DYS437, DYS438, DYS439, DYS448, DYS456, DYS458, DYS635 (Y GATA C4), and Y GATA H4) plus three highly polymorphic Y-STR loci (DYS460, DYS481, and DYS533), and seven rapidly mutating Y-STR loci (DYF387S1a/b, DYS449, DYS518, DYS570, DYS576, DYS627) which allow for improved discrimination of related individuals. The Yfiler® Plus PCR Amplification Kit is a dual application assay designed to amplify DNA from extracted casework and database samples from storage cards and swab lysates via direct amplification. Compared to the Yfiler PCR Amplification Kit, the new multiplex shows increased discrimination of male lineages and also improved performance in inhibited samples, improved balance in male DNA samples mixed with female DNA at ratios >1:1000, and faster time to results. The Yfiler Plus Kit shows very high concordance to the Yfiler Kit but discordance with the PowerPlex® Y23 Kit at the DYS481 locus was observed in 2 out of 30 samples tested. This developmental validation work follows the SWGDAM guidelines and demonstrates that the assay is robust and suitable for use on forensic casework and database samples.

COMBINATION OF VERBAL DELAYED RECALL, STROOP COLOR-WORD, AND MRI CAN BE UTILIZED FOR THE DISCRIMINATION OF AMYLOID DEPOSITION STATUS IN MCI INDIVIDUALS

COMBINATION OF VERBAL DELAYED RECALL, STROOP COLOR-WORD, AND MRI CAN BE UTILIZED FOR THE DISCRIMINATION OF AMYLOID DEPOSITION STATUS IN MCI INDIVIDUALS

COMBINATION OF VERBAL DELAYED RECALL, STROOP COLOR-WORD, AND MRI CAN BE UTILIZED FOR THE DISCRIMINATION OF AMYLOID DEPOSITION STATUS IN MCI INDIVIDUALS

COMBINATION OF VERBAL DELAYED RECALL, STROOP COLOR-WORD, AND MRI CAN BE UTILIZED FOR THE DISCRIMINATION OF AMYLOID DEPOSITION STATUS IN MCI INDIVIDUALS

The bark, the howl and the bark-howl: Identity cues in dingoes’ multicomponent calls

Dingoes (genus Canis) produce a stereotyped bark-howl vocalisation, which is a unimodal complex signal formed by the concatenation of two call types (a bark and a howl). Bark-howls may function as alarm signals, although there has been no empirical investigation of this vocalisation’s structure or function. We quantified the content and efficacy of the bark and howl segments separately and when combined, using 140 calls from 10 individuals. We found that both segments are individually distinctive, although howl segments are more accurately classified, suggesting a higher level of individuality. Furthermore, howls convey signature characteristics that are conserved across different contexts of production, and thus may act as ‘identity signals’. The individual distinctiveness of full bark-howls increases above that of isolated segments, which may be a result of selection on improved signal discriminability. Propagation tests revealed that bark-howls are best described as medium-range signals, with both segments potentially allowing for individual discrimination up to 200m regardless of environmental conditions. We discuss our findings regarding the fitness benefits of encoding identity cues in a potential alarm call and propose additional hypotheses for the function(s) of bark and howl segments.

Maize proteomic responses to separate or overlapping soil drought and two-spotted spider mite stresses.

Main conclusionIn maize, leaf proteome responses evoked by soil drought applied separately differ from those evoked by mite feeding or both types of stresses occurring simultaneously.This study focuses on the involvement of proteomic changes in defence responses of a conventional maize cultivar (Bosman) to the two-spotted spider mite infestation, soil drought and both stresses coexisting for 6 days. Under watering cessation or mite feeding applied separately, the protein carbonylation was not directly linked to the antioxidant enzymes’ activities. Protein carbonylation increased at higher and lower SOD, APX, GR, POX, PPO activities following soil drought and mite feeding, respectively. Combination of these stresses resulted in protein carbonylation decrease despite the increased activity of all antioxidant enzymes (except the CAT). However, maize protein network modification remains unknown upon biotic/abiotic stresses overlapping. Here, using multivariate chemometric methods, 94 leaf protein spots (out of 358 considered; 2-DE) were identified (LC–MS/MS) as differentiating the studied treatments. Only 43 of them had individual discrimination power. The soil drought increased abundance of leaf proteins related mainly to photosynthesis, carbohydrate metabolism, defence (molecular chaperons) and protection. On the contrary, mite feeding decreased the abundance of photosynthesis related proteins and enhanced the abundance of proteins protecting the mite-infested leaf against photoinhibition. The drought and mites occurring simultaneously increased abundance of proteins that may improve the efficiency of carbon fixation, as well as carbohydrate and amino acid metabolism. Furthermore, increased abundance of the Rubisco large subunit-binding protein (subunit β), fructose-bisphosphate aldolase and mitochondrial precursor of Mn-SOD and decreased abundance of the glycolysis-related enzymes in the mite-free leaf (in the vicinity of mite-infested leaf) illustrate the involvement of these proteins in systemic maize response to mite feeding.Electronic supplementary materialThe online version of this article (doi:10.1007/s00425-016-2559-6) contains supplementary material, which is available to authorized users.

Thermogravimetric analysis coupled with chemometrics as a powerful predictive tool for ß-thalassemia screening

β-Thalassemia is a hemoglobin genetic disorder characterized by the absence or reduced β-globin chain synthesis, one of the constituents of the adult hemoglobin tetramer. In this study the possibility of using thermogravimetric analysis (TGA) followed by chemometrics as a new approach for β-thalassemia detection is proposed. Blood samples from patients with β-thalassemia were analyzed by the TG7 thermobalance and the resulting curves were compared to those typical of healthy individuals. Principal Component Analysis (PCA) was used to evaluate the correlation between the hematological parameters and the thermogravimetric results. The thermogravimetric profiles of blood samples from β-thalassemia patients were clearly distinct from those of healthy individuals as result of the different quantities of water content and corpuscular fraction. The hematological overview showed significant decreases in the values of red blood cell indices and an increase in red cell distribution width value in thalassemia subjects when compared with those of healthy subjects. The implementation of a predictive model based on Partial Least Square Discriminant Analysis (PLS-DA) for β-thalassemia diagnosis, was performed and validated. This model permitted the discrimination of anemic patients and healthy individuals and was able to detect thalassemia in clinically heterogeneous patients as in the presence of δβ-thalassemia and β-thalassemia combined with Hb Lepore. TGA and Chemometrics are capable of predicting ß-thalassemia syndromes using only a few microliters of blood without any pretreatment and with an hour of analysis time. A fast, rapid and cost-effective diagnostic tool for the β-thalassemia screening is proposed.

The intra- and inter-observer reliability of a novel protocol for two-point discrimination in individuals with chronic low back pain

Two-point discrimination is measured as an indicator of cortical reorganisation in musculoskeletal medicine. Nevertheless, data are lacking for the reliability of this measure in patients with non-specific chronic low back pain (NSCLBP). We aimed to quantify the intra- and inter-observer reliability of a novel protocol for measuring two-point discrimination in these patients. 35 participants (12 males, 23 females, mean age 52, SD 15 years) with NSCLBP were recruited. Three clinicians made 14 consecutive measurements of two-point discrimination with callipers. One of these clinicians repeated the assessment protocol within 7 d. During each measurement, the calliper width was widened in 5 mm increments until participants could consistently identify two points. Intra- and inter-observer agreement was quantified using mean difference, within-subject SD and limits of agreement (LOA). After using the first measurement for familiarisation, the mean of measurements 2–5 within an assessment resulted in the optimum compromise between clinic time constraints and acceptable intra-observer reliability; the within-subjects SD being 7.5 mm (LOA: 20.8 mm). Inter-observer reliability was generally poorer; requiring the mean of measurements 2–9 within an assessment for a similar within-subjects SD of 8.6 mm (LOA: 23.7 mm). It was estimated that these within-subjects SDs were small enough for a clinically-important change to be detected with a feasible sample size in future studies. The intra-observer reliability of our assessment protocol is acceptable for detecting a clinically relevant difference in two-point discrimination for future research purposes. Nevertheless, individual patient measurement variability is relatively high, especially between different clinicians.

Riding the Stagecoach to Hell: A Qualitative Analysis of Racial Discrimination in Mortgage Lending.

Recent studies have used statistical methods to show that minorities were more likely than equally qualified whites to receive high cost, high risk loans during the U.S. housing boom, evidence taken to suggest widespread discrimination in the mortgage lending industry. The evidence, however, was indirect, being inferred from racial differentials that persisted after controlling for other factors known to affect the terms of lending. Here we assemble a qualitative database to generate direct evidence of discrimination. Using a sample of 220 statements randomly selected from documents assembled in the course of recent fair lending lawsuits, we code texts for evidence of individual discrimination, structural discrimination, and potential discrimination in mortgage lending practices. We find that 76% of the texts indicated the existence of structural discrimination, with only 11% suggesting individual discrimination alone. We then present a sample of texts that were coded as discriminatory to reveal the way in which racial discrimination was embedded within the social structure of U.S. mortgage lending, and to reveal the specific micro-social mechanisms by which this discrimination was effected.

Mental illness sexual stigma: Implications for health and recovery.

The majority of people in psychiatric care worldwide are sexually active, and studies have revealed sharply elevated rates of HIV infection in that group compared with the general population. Recovery-oriented treatment does not routinely address sexuality. We examined the relationship between gender, severe mental illness diagnosis, and stigma experiences related to sexuality among people in psychiatric outpatient care. Sexually active adults attending 8 public outpatient psychiatric clinics in Rio de Janeiro (N = 641) were interviewed for psychiatric diagnosis and stigma experiences. Stigma mechanisms well-established in the literature but not previously examined in relation to sexuality were measured with the Mental Illness Sex Stigma Questionnaire, a 27-item interview about stigma in sexual situations and activities. Experiences of stigma were reported by a majority of participants for 48% of questionnaire items. Most people reported supportive attitudes toward their sexuality from providers and family members. Those with severe mental illness diagnoses showed greater stigma on individual discrimination and structural stigma mechanisms than did those with nonsevere mental illness diagnoses, whereas there was no difference on the social psychological processes (internalized stigma) mechanism. Regardless of diagnosis or gender, a majority of participants devalued themselves as sexual partners. Adults in psychiatric outpatient care frequently reported stigma experiences related to aspects of their sexual lives. From the perspectives of both HIV prevention and recovery from mental illness, examinations of the consequences of stigma in the sexual lives of people in psychiatric care and improving their measurement would have wide applicability. (PsycINFO Database Record

Evaluation of the genetic parameters and mutation analysis of 22 STR loci in the central Chinese Han population.

At present, the Han nationality is China's main ethnic group and also the most populous nation in the world. This is a great resource to study microsatellite mutations and for the study of ethnogeny. The aim of this study is to investigate the genetic polymorphisms and mutations of 22 autosomal STR loci in 2475 individuals from Henan province, China. DNA is amplified and genotyped using PowerPlex™24 system. The gene frequencies, forensic parameters, and the mutation rate of the 22 STR loci are analyzed. A total of 295 alleles are observed in this Henan Han population, and the allelic frequencies ranged from 0.0003 to 0.5036. In order to investigate the genetic relationships between the Henan Han and the other 14 different populations, our present data were compared with previously published data for the same 15 STR loci. The results indicated that the Henan Han had closer genetic relationships the groups including Minnan Han, Maonan, Yi and Guangdong Han groups while the South morocco population, the Moroccan population, the Malay group, and the Uigur stand away from Henan Han. Except of D2S441, D13S317, PentaE, D2S1338, D5S818, TPOX and D19S433, the mutation events are found in the other 15 STR loci. A total of 40 mutation events are observed in the 15 STR loci. The mutation rates are ranged from 0 to 4.85 × 10-3. In this study, 39 mutations are single-step mutations, and only one at FGA comprised two steps. STR mutation is commonly existed in paternity testing, while there are no STR mutation studies of the 22 STR loci in the Henan Han population. It is of great importance in forensic individual discrimination and paternal testing.