Amplifications of EVX2 and HOXD9-HOXD13 on 2q31 in mature cystic teratomas of the ovary identified by array comparative genomic hybridization may explain teratoma characteristics in chondrogenesis and osteogenesis.

BACKGROUND: Teratomas are a common type of germ cell tumor. However, only a few reports on their genomic constitution have been published. The study of teratomas may provide a better understanding of their stepwise differentiation processes and molecular bases, which could prove useful for the development of tissue-engineering technologies. METHODS: In the present study, we analyzed the copy number aberrations of nine ovarian mature cystic teratomas using array comparative genomic hybridization in an attempt to reveal their genomic aberrations. RESULTS: The many chromosomal aberrations observed on array comparative genomic hybridization analysis reveal the complex genetics of this tumor. Amplifications and deletions of large DNA fragments were observed in some samples, while amplifications of EVX2 and HOXD9-HOXD13 on 2q31.1, NDUFV1 on 11q13.2, and RPL10, SNORA70, DNASE1L1, TAZ, ATP6AP1, and GDI1 on Xq28 were found in all nine mature cystic teratomas. CONCLUSIONS: Our results indicated that amplifications of these genes may play an important etiological role in teratoma formation. Moreover, amplifications of EVX2 and HOXD9-HOXD13 on 2q31.1, found on array comparative genomic hybridization, may help to explain the characteristics of teratomas in chondrogenesis and osteogenesis.

An Iterative Scale Purification Procedure on lz for the Detection of Aberrant Responses.

Many person-fit statistics have been proposed to detect aberrant response behaviors (e.g., cheating, guessing). Among them, lz is one of the most widely used indices. The computation of lz assumes the item and person parameters are known. In reality, they often have to be estimated from data. The better the estimation, the better lz will perform. When aberrant behaviors occur, the person and item parameter estimations are inaccurate, which in turn degrade the performance of lz. In this study, an iterative procedure was developed to attain more accurate person parameter estimates for improved performance of lz. A series of simulations were conducted to evaluate the iterative procedure under two conditions of item parameters, known and unknown, and three aberrant response styles of difficulty-sharing cheating, random-sharing cheating, and random guessing. The results demonstrated the superiority of the iterative procedure over the non-iterative one in maintaining control of Type-I error rates and improving the power of detecting aberrant responses. The proposed procedure was applied to a high-stake intelligence test.

Assessing ChatGPT's capacity for clinical decision support in pediatrics: A comparative study with pediatricians using KIDMAP of Rasch analysis.

BACKGROUND: The application of large language models in clinical decision support (CDS) is an area that warrants further investigation. ChatGPT, a prominent large language models developed by OpenAI, has shown promising performance across various domains. However, there is limited research evaluating its use specifically in pediatric clinical decision-making. This study aimed to assess ChatGPT's potential as a CDS tool in pediatrics by evCDSaluating its performance on 8 common clinical symptom prompts. Study objectives were to answer the 2 research questions: the ChatGPT's overall grade in a range from A (high) to E (low) compared to a normal sample and the difference in assessment of ChatGPT between 2 pediatricians. METHODS: We compared ChatGPT's responses to 8 items related to clinical symptoms commonly encountered by pediatricians. Two pediatricians independently assessed the answers provided by ChatGPT in an open-ended format. The scoring system ranged from 0 to 100, which was then transformed into 5 ordinal categories. We simulated 300 virtual students with a normal distribution to provide scores on items based on Rasch rating scale model and their difficulties in a range between -2 to 2.5 logits. Two visual presentations (Wright map and KIDMAP) were generated to answer the 2 research questions outlined in the objectives of the study. RESULTS: The 2 pediatricians' assessments indicated that ChatGPT's overall performance corresponded to a grade of C in a range from A to E, with average scores of -0.89 logits and 0.90 logits (=log odds), respectively. The assessments revealed a significant difference in performance between the 2 pediatricians (P < .05), with scores of -0.89 (SE = 0.37) and 0.90 (SE = 0.41) in log odds units (logits in Rasch analysis). CONCLUSION: This study demonstrates the feasibility of utilizing ChatGPT as a CDS tool for patients presenting with common pediatric symptoms. The findings suggest that ChatGPT has the potential to enhance clinical workflow and aid in responsible clinical decision-making. Further exploration and refinement of ChatGPT's capabilities in pediatric care can potentially contribute to improved healthcare outcomes and patient management.

DUSP5 and PHLDA1 mutations in mature cystic teratomas of the ovary identified on whole-exome sequencing may explain teratoma characteristics.

BACKGROUND: Mature cystic teratomas of the ovary are the most common type of germ cell tumor, comprising 33% of ovarian tumors. Studying these tumors may result in a better understanding of their stepwise developmental processes and molecular bases and provide useful information for the development of tissue-engineering technologies. METHODS: In the present study, 9 mature cystic teratomas of the ovary were analyzed by whole-exome sequencing and the results were compared with the Catalogue of Somatic Mutations in Cancer and dbSNP databases. RESULTS: Mutations were validated in 15 genes with alterations in all 9 (100%) samples and changes in protein coding. The top 10 mutated genes were FLG, MUC17, MUC5B, RP1L1, NBPF1, GOLGA6L2, SLC29A3, SGK223, PTGFRN, and FAM186A. Moreover, 7 variants in exons with changes in protein coding are likely of importance in the development of mature cystic teratomas of the ovary, namely PTGFRN, DUSP5, MPP2, PHLDA1, PRR21, GOLGA6L2, and KRTAP4-2. CONCLUSIONS: These genetic alterations may play an important etiological role in teratoma formation. Moreover, novel mutations in DUSP5 and PHLDA1 genes found on whole-exome sequencing may help to explain the characteristics of teratomas.

Corrigendum: Methylation Statuses of H19DMR and KvDMR at WT2 in Wilms Tumors in Taiwan.

[This corrects the article DOI: 10.1007/s12253-020-00802-6.].

Computerized Adaptive Testing for Ipsative Tests with Multidimensional Pairwise-Comparison Items: Algorithm Development and Applications.

A computerized adaptive testing (CAT) solution for tests with multidimensional pairwise-comparison (MPC) items, aiming to measure career interest, value, and personality, is rare. This paper proposes new item selection and exposure control methods for CAT with dichotomous and polytomous MPC items and present simulation study results. The results show that the procedures are effective in selecting items and controlling within-person statement exposure with no loss of efficiency. Implications are discussed in two applications of the proposed CAT procedures: a work attitude test with dichotomous MPC items and a career interest assessment with polytomous MPC items.

Reducing the Misclassification Costs of Cognitive Diagnosis Computerized Adaptive Testing: Item Selection With Minimum Expected Risk.

Cognitive diagnosis computerized adaptive testing (CD-CAT) aims to identify each examinee's strengths and weaknesses on latent attributes for appropriate classification into an attribute profile. As the cost of a CD-CAT misclassification differs across user needs (e.g., remedial program vs. scholarship eligibilities), item selection can incorporate such costs to improve measurement efficiency. This study proposes such a method, minimum expected risk (MER), based on Bayesian decision theory. According to simulations, using MER to identify examinees with no mastery (MER-U0) or full mastery (MER-U1) showed greater classification accuracy and efficiency than other methods for these attribute profiles, especially for shorter tests or low quality item banks. For other attribute profiles, regardless of item quality or termination criterion, MER methods, modified posterior-weighted Kullback-Leibler information (MPWKL), posterior-weighted CDM discrimination index (PWCDI), and Shannon entropy (SHE) performed similarly and outperformed posterior-weighted attribute-level CDM discrimination index (PWACDI) in classification accuracy and test efficiency, especially on short tests. MER with a zero-one loss function, MER-U0, MER-U1, and PWACDI utilized item banks more effectively than the other methods. Overall, these results show the feasibility of using MER in CD-CAT to increase the accuracy for specific attribute profiles to address different user needs.

Correlations between histological characterizations and methylation statuses of tumour suppressor genes in Wilms' tumours.

Wilms' tumour is a solid tumour that frequently occurs in children. Genetic changes in WT1 and epigenetic aberrations that affect imprinted control region 1 in WT2 loci are implicated in its aetiology. Moreover, tumour suppressor genes are frequently silenced by methylation in this tumour. In the present study, we analysed the methylation statuses of promoter regions of 24 tumour suppressor genes using a methylation-specific multiplex ligation-dependent probe amplification (MS-MLPA)-based approach in 6 Wilms' tumours. Methylation of RASSF1 was specific to all 6 Wilms' tumours and was not observed in normal tissues. Moreover, methylated HIC1 was identified in stromal-type Wilms' tumours and methylated BRCA1 was identified in epithelial-type Wilms' tumours. Unmethylated CASP8, RARB, MLH1_167, APC and CDKN2A were found only in blastemal predominant-type Wilms' tumour. Our results indicated that methylation of RASSF1 may be a vital event in the tumorigenesis of Wilms' tumour, which informs its clinical and therapeutic management. In addition, mixed-type Wilms' tumours may be classified according to epithelial, stromal and blastemal components via MS-MLPA-based approach.

A new item response theory model for rater centrality using a hierarchical rater model approach.

Rater centrality, in which raters overuse middle scores for rating, is a common rater error which can affect test scores and subsequent decisions. Past studies on rater errors have focused on rater severity and inconsistency, neglecting rater centrality. This study proposes a new model within the hierarchical rater model framework to explicitly specify and directly estimate rater centrality in addition to rater severity and inconsistency. Simulations were conducted using the freeware JAGS to evaluate the parameter recovery of the new model and the consequences of ignoring rater centrality. The results revealed that the model had good parameter recovery with small bias, low root mean square errors, and high test score reliability, especially when a fully crossed linking design was used. Ignoring centrality yielded poor item difficulty estimates, person ability estimates, rater errors estimates, and underestimated reliability. We also showcase how the new model can be used, using an empirical example involving English essays in the Advanced Placement exam.

A Lognormal Ipsative Model for Multidimensional Compositional Items.

Compositional items - a form of forced-choice items - require respondents to allocate a fixed total number of points to a set of statements. To describe the responses to these items, the Thurstonian item response theory (IRT) model was developed. Despite its prominence, the model requires that items composed of parts of statements result in a factor loading matrix with full rank. Without this requirement, the model cannot be identified, and the latent trait estimates would be seriously biased. Besides, the estimation of the Thurstonian IRT model often results in convergence problems. To address these issues, this study developed a new version of the Thurstonian IRT model for analyzing compositional items - the lognormal ipsative model (LIM) - that would be sufficient for tests using items with all statements positively phrased and with equal factor loadings. We developed an online value test following Schwartz's values theory using compositional items and collected response data from a sample size of N = 512 participants with ages from 13 to 51 years. The results showed that our LIM had an acceptable fit to the data, and that the reliabilities exceeded 0.85. A simulation study resulted in good parameter recovery, high convergence rate, and the sufficient precision of estimation in the various conditions of covariance matrices between traits, test lengths and sample sizes. Overall, our results indicate that the proposed model can overcome the problems of the Thurstonian IRT model when all statements are positively phrased and factor loadings are similar.

Genetic Analysis Reveals the Important Role of the APC Gene in Clear Cell Renal Cell Carcinoma.

BACKGROUND/AIM: Renal cell carcinoma (RCC) is the most common type of kidney cancer in adults. The aim of this study was to elucidate the molecular pathogenesis of sporadic RCC in Taiwan. MATERIALS AND METHODS: Fifteen patients with RCC were screened for mutations in the von Hippel-Lindau (VHL) gene by PCR and Sanger sequencing. The methylation status of promoters of 24 tumor suppressor genes by methylation sensitive multiplex ligation-dependent probe amplification analysis was also determined. RESULTS: Inactivation of the VHL gene was observed in 5 cases: three missense somatic mutations, one promoter methylation, and one small deletion. In RCCs, methylation was most frequently observed in APC (100%), CDKN2B (92.9%), CASP8, MLH1_167, and KLLN (85.7.4%), but not in FHIT, MLH1_463, DAPK1, or HIC1 (0%). CONCLUSION: In addition to VHL inactivation, promoter methylation of APC may be a universal pathognomonic event in the tumorigenesis of RCC and a candidate diagnostic and therapeutic biomarker.

Variable Speed Across Dimensions of Ability in the Joint Model for Responses and Response Times.

Working speed as a latent variable reflects a respondent's efficiency to apply a specific skill, or a piece of knowledge to solve a problem. In this study, the common assumption of many response time models is relaxed in which respondents work with a constant speed across all test items. It is more likely that respondents work with different speed levels across items, in specific when these items measure different dimensions of ability in a multidimensional test. Multiple speed factors are used to model the speed process by allowing speed to vary across different domains of ability. A joint model for multidimensional abilities and multifactor speed is proposed. Real response time data are analyzed with an exploratory factor analysis as an example to uncover the complex structure of working speed. The feasibility of the proposed model is examined using simulation data. An empirical example with responses and response times is presented to illustrate the proposed model's applicability and rationality.

The Q-Matrix Anchored Mixture Rasch Model.

Mixture item response theory (IRT) models include a mixture of latent subpopulations such that there are qualitative differences between subgroups but within each subpopulation the measure model based on a continuous latent variable holds. Under this modeling framework, students can be characterized by both their location on a continuous latent variable and by their latent class membership according to Students' responses. It is important to identify anchor items for constructing a common scale between latent classes beforehand under the mixture IRT framework. Then, all model parameters across latent classes can be estimated on the common scale. In the study, we proposed Q-matrix anchored mixture Rasch model (QAMRM), including a Q-matrix and the traditional mixture Rasch model. The Q-matrix in QAMRM can use class invariant items to place all model parameter estimates from different latent classes on a common scale regardless of the ability distribution. A simulation study was conducted, and it was found that the estimated parameters of the QAMRM recovered fairly well. A real dataset from the Certificate of Proficiency in English was analyzed with the QAMRM, LCDM. It was found the QAMRM outperformed the LCDM in terms of model fit indices.

Assessment of Differential Statement Functioning in Ipsative Tests With Multidimensional Forced-Choice Items.

Ipsative tests with multidimensional forced-choice (MFC) items have been widely used to assess career interest, values, and personality to prevent response biases. Recently, there has been a surge of interest in developing item response theory models for MFC items. In reality, a statement in an MFC item may have different utilities for different groups, which is referred to as differential statement functioning (DSF). However, few studies have been investigated methods for detecting DSF owing to the challenges related to the features of ipsative tests. In this study, three methods were adapted for DSF assessment in MFC items: equal-mean-utility (EMU), all-other-statement (AOS), and constant-statement (CS). Simulation studies were conducted to evaluate the recovery of parameters and the performance of the proposed methods. Results showed that statement parameters and DSF parameters were well recovered for all the three methods when the test did not contain any DSF statement. When the test contained one or more DSF statements, only the CS method yielded accurate estimates. With respect to DSF assessment, both the EMU method using the bootstrap standard error and the AOS method performed appropriately so long as the test did not contain any DSF statement. The CS method performed well in cases where one or more DSF-free statements were chosen as an anchor. The longer the anchor statements, the higher the power of DSF detection.

Generation of paternal haploids in wheat by genome editing of the centromeric histone CENH3.

New breeding technologies accelerate germplasm improvement and reduce the cost of goods in seed production1-3. Many such technologies could use in vivo paternal haploid induction (HI), which occurs when double fertilization precedes maternal (egg cell) genome loss. Engineering of the essential CENTROMERIC HISTONE (CENH3) gene induces paternal HI in Arabidopsis4-6. Despite conservation of CENH3 function across crops, CENH3-based HI has not been successful outside of the Arabidopsis model system7. Here we report a commercially operable paternal HI line in wheat with a ~7% HI rate, identified by screening genome-edited TaCENH3α-heteroallelic combinations. Unlike in Arabidopsis, edited alleles exhibited reduced transmission in female gametophytes, and heterozygous genotypes triggered higher HI rates than homozygous combinations. These developments might pave the way for the deployment of CENH3 HI technology in diverse crops.

Hints from a Female Patient with Breast Cancer Who Later Presented with Cowden Syndrome.

A 51-year-old woman presented with metachronous tumor development in bilateral breasts, thyroid, and endometrium. Additional signs and symptoms fulfilled the National Comprehensive Cancer Network criteria for Cowden syndrome. Immunohistochemistry showed loss of PTEN expression in all tumors. Single nucleotide variants, 647 germline variants (including one each in PTEN and MSH3), and 21 somatic mutations within exons were detected in all tumors after whole-exome sequencing. There were 0, 11, and 46 specific somatic mutations in bilateral breasts, thyroid, and endometrial cancers, respectively. Although PTEN mutation is key to the development of Cowden syndrome, DNA repair dysfunction might be the initial driver of mutations. Fewer mutations were required to induce initial bilateral breast carcinomas, with subsequent thyroid and endometrial carcinomas requiring more mutations for induction. When genetic screening is unavailable, breast cancer patients with clinical manifestations of Cowden syndrome must be carefully assessed for secondary malignancies, such as thyroid and endometrial carcinomas.

Cognitive Diagnostic Models for Rater Effects.

In recent decades, cognitive diagnostic models (CDMs) have been intensively researched and applied to various educational and psychological tests. However, because existing CDMs fail to consider rater effects, the application of CDMs to constructed-response (CR) items that involve human raters is seriously limited. Given the popularity of CR items, it is desirable to develop new CDMs that are capable of describing and estimating rater effects on CR items. In this study, we developed such new CDMs within the frameworks of facets models and hierarchical rater models, using the log-linear cognitive diagnosis model as a template. The parameters of the new models were estimated with the Markov chain Monte Carlo methods implemented in the freeware JAGS. Simulations were conducted to evaluate the parameter recovery of the new models. Results showed that the parameters were recovered fairly well and the more data there were, the better the recovery. Implications and applications of the new models were illustrated with an empirical study that adopted a fine-grained checklist to assess English academic essays.

Methylation Statuses of H19DMR and KvDMR at WT2 in Wilms Tumors in Taiwan.

Wilms tumor is the most common pediatric renal malignancy. Several genetic loci have been shown to be associated with its formation. Genetic or epigenetic aberrations at WT1 and WT2 loci have been implicated in the etiology of the majority of sporadic Wilms tumors. In our previous study, most Wilms tumors tested negative for both constitutional mutations and somatic mutations in the WT1 gene. Thus, WT2 may play an important role in these tumors. In the present study, we analyzed the methylation statuses of WT2 at 11p15 using methylation sensitive multiplex ligation-dependent probe amplification in six Wilms tumors. Paternal uniparental disomy at WT2 was observed in two Wilms tumors with epithelial components due to hypermethylation at H19DMR and hypomethylation at KvDMR. Our findings highlight the benefits of testing for 11p15 epigenetic abnormalities to identify Wilms tumors with epithelial components.

Measuring dynamic goals for marriage: Development and validation of the Marital Goal Scale using Rasch modeling.

Both the dynamic goal theory of marital satisfaction and the suffocation model of marriage argue that whether people are satisfied with their marriage largely depends on their marital goals. However, the lack of a validated measure has greatly limited empirical investigations about marital goals. The current study developed the Marital Goal Scale (MGS) using Rasch modeling. We provided evidence for the validity of the scale scores and confirmed its factorial structure using confirmatory factor analysis. The MGS contains 3 subscales assessing personal growth, instrumental, and companionship goals, respectively. The functioning of each subscale with a 4-point rating scale was supported by Rasch modeling in a married sample (from Hong Kong and the United States) and an unmarried sample (from Hong Kong). The discriminant and convergent validity of the subscale scores were supported in both samples. Major assumptions of the dynamic goal theory were also examined and partially supported. The MGS provides a useful tool to support empirical research about marital goals. Future studies are encouraged to utilize this tool to further investigate the important role of marital goals in marital dynamics. (PsycINFO Database Record (c) 2020 APA, all rights reserved).

Item Response Theory Modeling for Examinee-selected Items with Rater Effect.

Some large-scale testing requires examinees to select and answer a fixed number of items from given items (e.g., select one out of the three items). Usually, they are constructed-response items that are marked by human raters. In this examinee-selected item (ESI) design, some examinees may benefit more than others from choosing easier items to answer, and so the missing data induced by the design become missing not at random (MNAR). Although item response theory (IRT) models have recently been developed to account for MNAR data in the ESI design, they do not consider the rater effect; thus, their utility is seriously restricted. In this study, two methods are developed: the first one is a new IRT model to account for both MNAR data and rater severity simultaneously, and the second one adapts conditional maximum likelihood estimation and pairwise estimation methods to the ESI design with the rater effect. A series of simulations was then conducted to compare their performance with those of conventional IRT models that ignored MNAR data or rater severity. The results indicated a good parameter recovery for the new model. The conditional maximum likelihood estimation and pairwise estimation methods were applicable when the Rasch models fit the data, but the conventional IRT models yielded biased parameter estimates. An empirical example was given to illustrate these new initiatives.