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Item leakage has been a serious issue in continuous, computer-based testing, especially computerized adaptive testing (CAT), as compromised items jeopardize the fairness and validity of the test. Strategies to detect and address the problem of compromised items have been proposed and investigated, but many solutions are computationally intensive and thus difficult to apply in real-time monitoring. Recently, researchers have proposed several sequential methods aimed at fast detection of compromised items, but applications of these methods have not considered various scenarios of item leakage. In this paper, we introduce a model with a leakage parameter to better characterize the item leaking process and develop a more generalized detection method on its basis. The new model achieves a high level of detection accuracy while maintaining the type-I error at the nominal level, for both fast and slow leakage scenarios. The proposed model also estimates the time point at which an item becomes compromised, thus providing additional useful information for testing practitioners.

As algorithmic decision making is increasingly deployed in every walk of life, many researchers have raised concerns about fairness-related bias from such algorithms. But there is little research on harnessing psychometric methods to uncover potential discriminatory bias inside decision-making algorithms. The main goal of this article is to propose a new framework for algorithmic fairness based on "differential item functioning" (DIF), which has been commonly used to measure item fairness in psychometrics. Our fairness notion, which we call "differential algorithmic functioning" (DAF), is defined based on three pieces of information: a decision variable, a "fair" variable, and a protected variable such as race or gender. Under the DAF framework, an algorithm can exhibit uniform DAF, nonuniform DAF, or neither (i.e., non-DAF). For detecting DAF, we provide modifications of well-established DIF methods: Mantel-Haenszel test, logistic regression, and residual-based DIF. We demonstrate our framework through a real dataset concerning decision-making algorithms for grade retention in K-12 education in the United States.

Computerized adaptive testing (CAT) has gained deserved popularity in the administration of educational and professional assessments, but continues to face test security challenges. To ensure sustained quality assurance and testing integrity, it is imperative to establish and maintain multiple stable item pools that are consistent in terms of psychometric characteristics and content specifications. This study introduces the Honeycomb Pool Assembly (HPA) framework, an innovative solution for the construction of multiple parallel item pools for CAT that maximizes item utilization in the item bank. The HPA framework comprises two stages--cell assembly and pool assembly--and uses a mixed integer programming modeling approach. An empirical study demonstrated HPA's effectiveness in creating a large number of parallel pools using a real-world high-stakes CAT assessment item bank. The HPA framework offers several advantages, including (a) simultaneous creation of multiple parallel pools, (b) simplification of item pool maintenance, and (c) flexibility in establishing statistical and operational constraints. Moreover, it can help testing organizations efficiently manage and monitor the health of their item banks. Thus, the HPA framework is expected to be a valuable tool for testing professionals and organizations to address test security challenges and maintain the integrity of high-stakes CAT assessments.

Differential item functioning (DIF) of test items should be evaluated using practical methods that can produce accurate and useful results. Among a plethora of DIF detection techniques, we introduce the new "Residual DIF" (RDIF) framework, which stands out for its accessibility without sacrificing efficacy. This framework consists of three item response theory (IRT) residual statistics: RDIF[subscript R], RDIF[subscript S], and RDIF[subscript RS]. We conducted a simulation study with a 40-item test to assess the performance of RDIF in comparison with the Mantel-Haenszel, logistic regression, and IRT-based likelihood ratio test methods. Even when analyzing small sample sizes, the results revealed RDIF[subscript RS] to be the most robust DIF detection statistic with strict control of Type I error across all simulated conditions when paired with the purification procedure. Also, RDIF[subscript R] and RDIF[subscript S] proved to be powerful indicators of uniform and nonuniform DIF, respectively. Therefore, RDIF[subscript RS] should serve as the primary flagging criterion, whereas RDIF[subscript R] and RDIF[subscript S] best serve as indicators of DIF type. An empirical DIF study also showed that the RDIF framework could perform satisfactorily with real data from a large-scale assessment. Overall, the RDIF framework demonstrated its potential as a new standard for IRT-based DIF detection methodology.

In operational testing, item response theory (IRT) models for dichotomous responses are popular for measuring a single latent construct [theta], such as cognitive ability in a content domain. Estimates of [theta], also called IRT scores or [theta hat], can be computed using estimators based on the likelihood function, such as maximum likelihood (ML), weighted likelihood (WL), maximum a posteriori (MAP), and expected a posteriori (EAP). Although the parameter space of [theta] is theoretically unrestricted, the range of finite [theta hat] is constrained by the estimator and test form properties, which is important to consider but often overlooked when developing a score scale for reporting purposes. Irrespective of the estimator or test forms at hand, a common practice is to fix arbitrary points symmetric about zero (e.g., -4 and 4) as anchors for deriving a score transformation, possibly resulting in unintended gaps or truncations at the extremes. Therefore, a systematic framework is proposed for using IRT scores to construct a robust score scale with informed boundaries that are logical and consistent across test forms.

In item response theory test scaling/equating with the three-parameter model, the scaling coefficients A and B have no impact on the c-parameter estimates of the test items since the cparameter estimates are not adjusted in the scaling/equating procedure. The main research question in this study concerned how serious the consequences would be if c-parameter estimates are not adjusted in the test equating procedure when item-parameter drift (IPD) is present. This drift is commonly observed in equating studies and hence, has been the source of considerable research. The results from a series of Monte-Carlo simulation studies conducted under 32 different combinations of conditions showed that some calibration strategies in the study, where the cparameters were adjusted to be identical across two test forms, resulted in more robust equating performance in the presence of IPD. This paper discusses the practical effectiveness and the theoretical importance of appropriately adjusting c-parameter estimates in equating.

The full-information maximum likelihood (FIML) method makes it possible to estimate and analyze structural equation models (SEM) even when data are partially missing, enabling incomplete data to contribute to model estimation. The cornerstone of FIML is the missing-at-random (MAR) assumption. In (unidimensional) computerized adaptive testing (CAT), unselected items (i.e., responses that are not observed) remain at random even though selected items (i.e., responses that are observed) have been associated with a test taker's latent trait that is being measured. In multidimensional adaptive testing (MAT), however, the missingness in the response data partially depends on the unobserved data because items are selected based on various types of information including the covariance among latent traits. This eventually may lead to violations of MAR. This study aimed to evaluate the potential impact such a violation of MAR in MAT could have on FIML estimation performance. The results showed an increase in estimation errors in item parameter estimation when the MAT response data were used, and differences in the level of the impact depending on how items loaded on multiple latent traits.

The "D"-scoring method for scoring and equating tests with binary items proposed by Dimitrov offers some of the advantages of item response theory, such as item-level difficulty information and score computation that reflects the item difficulties, while retaining the merits of classical test theory such as the simplicity of number correct score computation and relaxed requirements for model sample sizes. Because of its unique combination of those merits, the "D"-scoring method has seen quick adoption in the educational and psychological measurement field. Because item-level difficulty information is available with the "D"-scoring method and item difficulties are reflected in test scores, it conceptually makes sense to use the "D"-scoring method with adaptive test designs such as multistage testing (MST). In this study, we developed and compared several versions of the MST mechanism using the "D"-scoring approach and also proposed and implemented a new framework for conducting MST simulation under the "D"-scoring method. Our findings suggest that the score recovery performance under MST with "D"-scoring was promising, as it retained score comparability across different MST paths. We found that MST using the "D"-scoring method can achieve improvements in measurement precision and efficiency over linear-based tests that use "D"-scoring method.

Background: The use of glucagon‐like‐peptide 1 receptor agonists (GLP1‐RA) has dramatically increased over the past 5 years for diabetes mellitus type 2 (T2DM) and obesity. These comorbidities are prevalent in adult heart transplant (HT) recipients. However, there are limited data evaluating the efficacy of this drug class in this population. The aim of the current study was to describe cardiometabolic changes in HT recipients prescribed GLP1‐RA at a large‐volume transplant center. Methods: We retrospectively reviewed all adult HT recipients who received GLP1‐RA after HT for a minimum of 1‐month. Cardiometabolic parameters including body mass index (BMI), lipid panel, hemoglobin A1C, estimated glomerular filtration rate (eGFR), and NT‐proBNP were compared prior to initiation of the drug and at most recent follow‐up. We also evaluated for significant dose adjustments to immunosuppression after drug initiation and adverse effects leading to drug discontinuation. Results: Seventy‐four patients were included (28% female, 53% White, 20% Hispanic) and followed for a median of 383 days [IQR 209, 613] on a GLP1‐RA. The majority of patients (n = 56, 76%) were prescribed semaglutide. The most common indication for prescription was T2DM alone (n = 33, 45%), followed by combined T2DM and obesity (n = 26, 35%). At most recent follow‐up, mean BMI decreased from 33.3 to 31.5 kg/m2 (p < 0.0001), HbA1C from 7.3% to 6.7% (p = 0.005), LDL from 78.6 to 70.3 mg/dL (p = 0.018) and basal insulin daily dose from 32.6 to 24.8 units (p = 0.0002). Conclusion: HT recipients prescribed GLP1‐RA therapy showed improved glycemic control, weight loss, and cholesterol levels during the study follow‐up period. GLP1‐RA were well tolerated and were rarely associated with changes in immunosuppression dosing. [ABSTRACT FROM AUTHOR]

For several decades, the "three-parameter logistic model" (3PLM) has been the dominant choice for practitioners in the field of educational measurement for modeling examinees' response data from multiple-choice (MC) items. Past studies, however, have pointed out that the c-parameter of 3PLM should not be interpreted as a guessing parameter. This study found logical, empirical evidence showing that neither the "a-", "b-", or "c-" parameters of 3PLM can accurately reflect the discrimination, difficulty, and guessing properties of an item, respectively. This study reconceptualized the problem-solving and guessing processes with a modification of the 3PLM that eliminates ambiguity in modeling the guessing process. A series of studies using various real and simulated data demonstrated that the suggested model, in which the c-parameters were fixed at a computed probability for successful random guessing (i.e., c = 1 / k with k being the number of options), could provide a more feasible, stable, and accurate item estimation solution without sacrificing the model fit compared with a typical 3PLM. (Contains 15 figures, 4 tables and 1 footnote.)

As algorithmic decision making is increasingly deployed in every walk of life, many researchers have raised concerns about fairness-related bias from such algorithms. But there is little research on harnessing psychometric methods to uncover potential discriminatory bias inside decision-making algorithms. The main goal of this article is to propose a new framework for algorithmic fairness based on differential item functioning (DIF), which has been commonly used to measure item fairness in psychometrics. Our fairness notion, which we call differential algorithmic functioning (DAF), is defined based on three pieces of information: a decision variable, a "fair" variable, and a protected variable such as race or gender. Under the DAF framework, an algorithm can exhibit uniform DAF, nonuniform DAF, or neither (i.e., non-DAF). For detecting DAF, we provide modifications of well-established DIF methods: Mantel–Haenszel test, logistic regression, and residual-based DIF. We demonstrate our framework through a real dataset concerning decision-making algorithms for grade retention in K–12 education in the United States. [ABSTRACT FROM AUTHOR]

Computerized adaptive testing (CAT) has gained deserved popularity in the administration of educational and professional assessments, but continues to face test security challenges. To ensure sustained quality assurance and testing integrity, it is imperative to establish and maintain multiple stable item pools that are consistent in terms of psychometric characteristics and content specifications. This study introduces the Honeycomb Pool Assembly (HPA) framework, an innovative solution for the construction of multiple parallel item pools for CAT that maximizes item utilization in the item bank. The HPA framework comprises two stages—cell assembly and pool assembly—and uses a mixed integer programming modeling approach. An empirical study demonstrated HPA's effectiveness in creating a large number of parallel pools using a real‐world high‐stakes CAT assessment item bank. The HPA framework offers several advantages, including (a) simultaneous creation of multiple parallel pools, (b) simplification of item pool maintenance, and (c) flexibility in establishing statistical and operational constraints. Moreover, it can help testing organizations efficiently manage and monitor the health of their item banks. Thus, the HPA framework is expected to be a valuable tool for testing professionals and organizations to address test security challenges and maintain the integrity of high‐stakes CAT assessments. [ABSTRACT FROM AUTHOR]

Abstract This study investigates the impact of environmental factors on the quality changes of mackerel (Scomber japonicus), a globally significant fish species valued for its high nutritional content, especially its unsaturated fatty acids and proteins. In South Korea, marine products like mackerel undergo auction, sorting, packaging, and transportation. Assessing the fish freshness and quality during these processes, before it reaches consumers, is crucial. This research aimed to track the changes in mackerel quality indicators after the auction and correlate them with the environmental factors affecting transportation. Using a transportation model established for both summer and winter, mackerel samples were categorized by their weight (200 and 300 g). Results show poorer quality indicators in summer compared to winter, particularly in the 200 g group. Microbiological indicators such as the total viable count (0.923) and total coliforms (0.958) were most strongly correlated with the season, whereas the lipid oxidation indicators acid value (0.627) and peroxide value (0.536) were moderately correlated with the season. Interestingly, the wider standard deviation distribution observed in summer suggests that individual mackerel characteristics may influence the degree of quality changes. These findings offer insights into mackerel quality fluctuations during auction and transportation, aiding in future efforts to maintain seafood quality amidst climate change.

Abstract We demonstrated an inline synthesizer for generating ultrashort pulses in the ultraviolet (UV) range. The inline UV pulse synthesizer comprised three nonlinear crystals located in the propagation path of the fundamental driving laser pulse. Second-harmonic signals with central wavelengths of 420, 375, and 345 nm were generated in turn in the three BBO crystals, resulting in a synthesized UV pulse subsequent to the final nonlinear crystal. Its temporal amplitude and phase could be manipulated easily by changing the relative positions of the crystals, allowing for flexibility of the waveform. The minimum pulse duration of the synthesized UV pulse was 4.7 fs, which was close to the Fourier-transform-limited pulse duration. This ultrashort UV pulse with 19 $$\upmu$$ μ J energy can be utilized in various applications such as high harmonic generation and frustrated tunneling ionization.

Most computerized adaptive testing (CAT) programs do not allow test takers to review and change their responses because it could seriously deteriorate the efficiency of measurement and make tests vulnerable to manipulative test-taking strategies. Several modified testing methods have been developed that provide restricted review options while limiting the trade-off in CAT efficiency. The extent to which these methods provided test takers with options to review test items, however, still was quite limited. This study proposes the item pocket (IP) method, a new testing approach that allows test takers greater flexibility in changing their responses by eliminating restrictions that prevent them from moving across test sections to review their answers. A series of simulations were conducted to evaluate the robustness of the IP method against various manipulative test-taking strategies. Findings and implications of the study suggest that the IP method may be an effective solution for many CAT programs when the IP size and test time limit are properly set. (Contains 1 table, 4 figures and 1 note.)

This article reviews a new item response theory (IRT) model estimation program, IRTPRO 2.1, for Windows that is capable of unidimensional and multidimensional IRT model estimation for existing and user-specified constrained IRT models for dichotomously and polytomously scored item response data. (Contains 1 figure and 2 notes.)

DIMPACK Version 1.0 for assessing test dimensionality based on a nonparametric conditional covariance approach is reviewed. This software was originally distributed by Assessment Systems Corporation and now can be freely accessed online. The software consists of Windows-based interfaces of three components: DIMTEST, DETECT, and CCPROX/HAC, which conduct hypothesis test for unidimensionality, cluster items, and perform hierarchical cluster analysis, respectively. Two simulation studies were conducted to evaluate the software in confirming test unidimensionality (a Type I error study) and detecting multidimensionality (a statistical power study). The results suggested that different data always be used in selecting assessment subtest items independent of calculating the DIMTEST statistic. The Type I error rate was excessively inflated otherwise. The statistical power was found low when sample size was small or the dimensions were highly correlated. It is suggested that some major changes be made to the software before it can be successfully useful among practitioners. (Contains 3 figures.)

When power tests include a time limit, it is important to assess the possibility of speededness for examinees. Past research on differential speededness has examined gender and ethnic subgroups in the United States on paper and pencil tests. When considering the needs of a global audience, research regarding different native language speakers is warranted. Data from a computerized adaptive test administered globally in English were used to compare different measures of time pressure and speed for 15 language groups compared to native-speaking English examinees. Results indicated that examinees whose native language was Korean had issues with speededness when many of the metrics were considered, but when test score was controlled, there were no relevant differences for any of the languages compared to English. (Contains 2 tables and 6 figures.)

This paper explores the implementation of machine learning-based algorithms for TL dose assessment. It focuses on the radiation field classification, performance quotient evaluation, and shallow and deep dose equivalent assessment of ANN and LGBM, in comparison to the traditional method of DT. We evaluate these algorithms based on the element response data measured by TLD. A data set was built for training, and the base element responses of test categories were amplified, and normalized to 1 mSv Cs-137 within the range of ±3 %. Both algorithms consist of five subset models for classifying radiation fields and identifying ratios of mixed fields. The LGBM showed the best accuracy in classifying considered radiation fields and the lowest performance quotients. By comparing the tolerance levels of deep dose and shallow dose equivalents among the three algorithms, the LGBM yields the smallest difference between the predicted and true dose equivalents. This smaller difference implies the LGBM offers the least bias and standard deviation in the expected value, giving higher accuracy and precision in dose assessment over the traditional DT method. The findings from this study further contribute to the adoption of ML-based algorithms for TL dose assessment, underscoring its importance in the field.

Recently, nanovaccine-based immunotherapy has been robustly investigated due to its potential in governing the immune response and generating long-term protective immunity. However, the presentation of a tumor peptide-major histocompatibility complex to T lymphocytes is still a challenge that needs to be addressed for eliciting potent antitumor immunity. Type 1 conventional dendritic cell (cDC1) subset is of particular interest due to its pivotal contribution in the cross-presentation of exogenous antigens to CD8+ T cells. Here, the DC-derived nanovaccine (denoted as Si9GM) selectively targets cDC1s with marginal loss of premature antigen release for effective stimulator of interferon genes (STING)-mediated antigen cross-presentation. Bone marrow dendritic cell (BMDC)-derived membranes, conjugated to cDC1-specific antibody (αCLEC9A) and binding to tumor peptide (OVA257-264), are coated onto dendrimer-like polyethylenimine (PEI)-grafted silica nanoparticles. Distinct molecular weight-cargos (αCLEC9A-OVA257-264 conjugates and 2′3′-cGAMP STING agonists) are loaded in hierarchical center-radial pores that enables lysosome escape for potent antigen-cross presentation and activates interferon type I, respectively. Impressively, Si9GM vaccination leads to the upregulation of cytotoxic T cells, a reduction in tumor regulatory T cells (Tregs), M1/M2 macrophage polarization, and immune response that synergizes with αPD-1 immune checkpoint blockade. This nanovaccine fulfills a dual role for both direct T cell activation as an artificial antigen-presenting cell and DC subset maturation, indicating its utility in clinical therapy and precision medicine.

Item parameter drift (IPD) occurs when item parameter values change from their original value over time. IPD may pose a serious threat to the fairness and validity of test score interpretations, especially when the goal of the assessment is to measure growth or improvement. In this study, we examined the effect of multidirectional IPD (i.e., some items become harder while other items become easier) on the linking procedure and rescaled proficiency estimates. The impact of different combinations of linking items with various multidirectional IPD on the test equating procedure was investigated for three scaling methods (mean-mean, mean-sigma, and TCC method) via a series of simulation studies. It was observed that multidirectional IPD had a substantive effect on examinees' scores and achievement level classifications under some of the studied conditions. Choice of linking method had a direct effect on the results, as did the pattern of IPD. (Contains 3 tables, 4 figures, and 1 footnote.)

Successful administration of computerized adaptive testing (CAT) programs in educational settings requires that test security and item exposure control issues be taken seriously. Developing an item selection algorithm that strikes the right balance between test precision and level of item pool utilization is the key to successful implementation and long-term quality control of CAT. This study proposed a new item selection method using the "efficiency balanced information" criterion to address issues with the maximum Fisher information method and stratification methods. According to the simulation results, the new efficiency balanced information method had desirable advantages over the other studied item selection methods in terms of improving the optimality of CAT assembly and utilizing items with low a-values while eliminating the need for item pool stratification. (Contains 1 note, 5 tables and 8 figures.)

Background Poorly differentiated thyroid carcinoma (PDTC) accounts for a small portion of thyroid carcinomas but contributes to a significant proportion of thyroid carcinoma-associated deaths. The clinicopathological prognostic factors and clinical outcomes of PDTC remain unclear. We aimed to evaluate the clinical outcomes of patients with PDTC after curative treatment. Methods A comprehensive search was performed up to September 2023. We included studies investigating treatment outcomes in patients with PDTC who underwent initial surgery. The 5-year disease-free survival (DFS) and overall survival (OS) were extracted. In this meta-analysis, the enrolled PDTC histological criteria included 3rd, 4th, and 5th World Health Organization (WHO) and Memorial Sloan Kettering Cancer Center (MSKCC) classification. A random-effects model was used for the pooled proportion analysis. Meta-regression analysis was conducted to evaluate the prognostic factors. Results Twenty retrospective studies published between 2007 and 2023, including 1,294 patients, met all inclusion criteria. Studies that diagnosed PDTC based on various histological criteria including 3rd WHO (n=5), 4th WHO (n=12), 5th WHO (n=2), and MSKCC (n=1) were included. Overall, 5-year DFS and 5-year OS were 49.4% (95% confidence interval [CI], 42.3 to 56.4) and 73.8% (95% CI, 66.5 to 79.9), with moderate heterogeneity of 58% and 55%, respectively. In meta-regression analysis, extrathyroidal extension (ETE) was a prognostic factor for OS. Conclusion The meta-analysis of DFS and OS in patients with PDTC show the moderate heterogeneity with a variety of histological criteria. ETE appears to have a significant impact on OS, regardless of histological criteria.

Crack-free Al–Zn–Mg–Cu alloy, processed by laser powder bed fusion, displays a characteristic microstructure comprising fine equiaxed grains (EGs) and coarse columnar grains (CGs). Notably, the CGs show a high hardness compared to EGs due to the high density of in-situ precipitates. Analysis of mechanical properties takes into account the precipitates in the grain and hierarchical differences in grain morphologies near the melt pool boundary. Strengthening mechanisms are elucidated through synergistic hetero-deformation-induced strengthening, where multi-modal-sized EGs induce significant strain gradients within EG regions. Our findings demonstrate the potential to enhance strength of Al–Zn–Mg–Cu-based alloy in as-built state through architecting microstructures.

The tyrosinase inhibition effects of 23 marine-derived seaweeds harvested in Korea were screened to determine their potential as skin-whitening agents. Of the 23 species initially screened, the total phenolic (TP) content of brown, green, and red seaweeds were 7.62–280.11, 5.24–62.37, and 0.63–28.76 phloroglucinol equivalents (PGE) mg/g, respectively. Brown seaweed extracts exhibited much stronger inhibitory activities than green and red seaweed extracts. Among the brown seaweeds, Ecklonia cava had the highest TP content (280.11 PGE mg/g) and the strongest tyrosinase inhibitory effect with a half maximal inhibitory concentration (IC50) value of 4.38 μg/mL. The kinetics of tyrosinase inhibition, analyzed by Lineweaver–Burk plots, found E. cava extract to be a non-competitive inhibitor. This study’s results indicated that E. cava’s inhibition of tyrosinase may have potential applications in the cosmetic industry.

Abstract To investigate alteration of outer nuclear layer (ONL) and choroidal vascularity index (CVI) in different status of central serous chorioretinopathy (CSC). A retrospective review of 65 CSC eyes with subretinal fluid (manifest CSC) and 40 control eyes was conducted in a single tertiary university hospital. Differences in best-corrected visual acuity (BCVA), ONL, and CVI were compared. CVI was assessed both in the entire choroid (CVI-EC) and around the 1500 μm leakage area (CVI-1500). Measurements were repeated after the subretinal fluid resorption (quiescent CSC), and compared. CSC eyes showed worse BCVA, thinner ONL and greater CVI than controls. Quiescent CSC showed a recovery of ONL compared to the manifest CSC, along with the BCVA improvement. The resolution of the CSC revealed a decrease across all three choroidal areas (total, stromal and luminal), with a more pronounced reduction in the stromal than in the luminal choroidal area, leading to an increase in the CVI. This phenomenon was shown in both CVI-EC and CVI-1500. Conclusively, ONL thickness can be used as a quantitative biomarker for photoreceptor function in CSC. Increased CVI may reflect a disease activity. The stromal choroidal area is particularly sensitive in illustrating leakage from the choroidal vasculature.

Purpose In Korea, the field of transitional urology (TU) is in its nascent stages, with its introduction only beginning. This study aims to evaluate the existing state of TU prior to implementing a transition protocol, and to identify key areas of focus for the development of an effective transition protocol. Methods From June 1, 2021 to May 31, 2023, clinical data were retrospectively collected for patients who visited the adult urology or pediatric urology outpatient departments of this hospital and were aged 10 or older, with medical conditions falling under the category of TU. We analyzed the patient distribution across different disease groups. The transitional stages were categorized from T1, indicating initial care by pediatric urologists, to T4, denoting complete transition to adult care. ‘T4x’ was used for patients with unknown medical histories, and ‘T4only’ for those who had never been under pediatric urology care. Results During a 2-year period, a total of 1,484 patients received outpatient care for diseases in TU field. The most prevalent diseases were hypospadias (40.4%), spinal bifida (37.3%), and congenital ureteral anomalies (17.7%), with other conditions accounting for 4.6%. Among 553 spinal bifida patients, only 5.3% completed transitional care (T4), while 80.1% were in the initial phase (T1). For patients introduced to adult urology (T2–T4), 37.7% reached T4, highlighting a marked increase in transition completion within this subset (P

In the United States, when English language learners (ELLs) are tested, they are usually tested in English and their limited English proficiency is a potential cause of construct-irrelevant variance. When such irrelevancies affect test scores, inaccurate interpretations of ELLs' knowledge, skills, and abilities may occur. In this article, we review validity issues relevant to the educational assessment of ELLs and discuss methods that can be used to evaluate the degree to which interpretations of their test scores are valid. Our discussion is organized using the five sources of validity evidence promulgated by the "Standards for Educational and Psychological Testing". Technical details for some validation methods are provided. When evaluating the validity of a test for ELLs, the evaluation methods should be selected so that the evidence gathered specifically addresses appropriate test use. Such evaluations should be comprehensive and based on multiple sources of validity evidence. (Contains 1 table, 2 figures and 2 footnotes.)

Abstract BackgroundCataract is a leading cause of vision impairment. Obesity-related risk factors, including insulin resistance, increase the risk of cataract. The fatty liver index (FLI) is a biomarker for noninvasive fat layer prediction of nonalcoholic fatty liver disease. The FLI has been used to evaluate the metabolic contribution in other organs besides the eye. However, no study exists on the FLI and eye disease. ObjectiveThis retrospective cohort study for the association between the FLI and incidence of cataract surgery in individuals older than 50 years was designed to show that a higher FLI is associated with an increased incidence of cataract surgery in individuals aged 50 years and older. MethodsThis study was retrospectively designed based on the Korean National Health Insurance Service-Health Screening Cohort (NHIS-HEALS) cohort (median follow-up of 9.8 years). Participants were assigned to 1 of 3 groups based on the FLI: low (FLI

BackgroundMethotrexate (MTX) is the primary drug used in the treatment of pediatric acute lymphoblastic leukemia (ALL). However, some patients exhibit delayed clearance of high-dose (HD) MTX, which induces severe nephrotoxicity, mucositis, hepatotoxicity, and neurotoxicity. We sought to identify relevant variants associated with delayed clearance of HD-MTX in pediatric patients with ALL.MethodsWhole-exome sequencing of germline DNA was performed in 51 Korean pediatric patients with ALL. A total of 341 HD-MTX infusion data points from 51 patients were analyzed. MTX levels and laboratory measurements reflecting toxicity outcomes were obtained. Correlations between peak serum MTX levels at 24 h and toxicity outcomes were assessed. Analyses were performed to identify variants affecting delayed MTX clearance.ResultsThe 24 h MTX level strongly correlated with the subsequent creatinine (Cr) level. Moreover, rs2229866 in contactin 2 (CNTN2), rs200687372 in myotubularin Related Protein 9 (MTMR9), rs777260512 in polymerase iota (POLI), rs16954698 in polycystic kidney disease 1-like 2 (PKD1L2), rs117765468 in NSE1 Homolog, SMC5-SMC6 Complex Component (NSMCE1), and rs1800956 in endoglin (ENG) were identified as candidate variants associated with delayed MTX clearance. In particular, ENG rs1800956 was significantly associated with delayed MTX clearance in all analyses and PKD1L2 rs16954698 was replicated in an external dataset (phs000637.v1.p1) from the Database of Genotypes and Phenotypes (dbGaP).ConclusionThis is the first whole-exome sequencing-based analysis of delayed MTX clearance in pediatric patients with ALL. ENG rs1800956 and PKD1L2 rs16954698 were found to be potentially influential variants associated with delayed MTX clearance. These findings provide insights into HD-MTX-induced nephrotoxicity and may contribute to reducing adverse reactions through treatment modification.

While spray-drying has been widely utilized to improve the bioavailability of poorly water-soluble drugs, the outcomes often exhibit suboptimal particle size distribution and large particle sizes, limiting their effectiveness. In this study, we introduce electrostatic spraying as an advanced technology tailored for poorly water-soluble drugs, enabling the fabrication of nanoparticles with fine and uniform particle size distribution. Regorafenib (1 g), as a model drug, copovidone (5 g), and sodium dodecyl sulfate (0.1 g) were dissolved in 200 ml ethanol and subjected to conventional-spray-dryer and electrostatic spray dryer. The electrostatic spray-dried nanoparticles (ESDN) showed smaller particle sizes with better uniformity compared to conventional spray-dried nanoparticles (CSDN). ESDN demonstrated significantly enhanced solubility and rapid release in water. In vitro studies revealed that ESDN induced apoptosis in HCT-116 cells to a greater extent, exhibiting superior cytotoxicity compared to CSDN. Furthermore, ESDN substantially improved oral bioavailability and antitumor efficacy compared to CSDN. These findings suggest that ESD shows potential in developing enhanced drug delivery systems for poorly water-soluble drugs, effectively addressing the limitations associated with CSD methods.