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Purpose: To understand the unique context forming organizational learning, the current study aims to investigate the antecedents of training and development (TD) practices as an indicator of effective organizational learning from the Vietnam hospitality sector, which has not been studied rigorously. Design/methodology/approach: This study adopts a mixed method of quantitative and qualitative data analysis, including a path analysis partial least squares structural equation modeling (PLS-SEM) based on a sample size of 354 responses and a semi-structured interview of 32 participants to test various paths predicting training effectiveness while exploring contextual differences in the Vietnam hospitality sector. Findings: The results show that among the variables investigated, extrinsic motivation, team support and job quality were found to be significant to TD, while intrinsic motivation was found to have no significant predictive power. To explore the reasons behind these findings, the interviews indicate that the motivations of employees in the hospitality sector, most of whom are young and have a limited length of service, are highly rooted in the organization's cultural context. Originality/value: This study contributes to understanding the complex context of organizational learning through an investigation of an emerging economy from Southeast Asia by adding new insights into the training and motivational theories. It has practical implications for practitioners in the hospitality sector to develop more effective learning organizations during the uncertain period of this unprecedented pandemic.

X-linked juvenile retinoschisis (XLRS) is a hereditary retinal degeneration affecting young males caused by mutations in the retinoschisin (RS1) gene. We generated human induced pluripotent stem cells (hiPSCs) from XLRS patients and established three-dimensional retinal organoids (ROs) for disease investigation. This disease model recapitulates the characteristics of XLRS, exhibiting defects in RS1 protein production and photoreceptor cell development. XLRS ROs also revealed dysregulation of Na/K-ATPase due to RS1 deficiency and increased ERK signaling pathway activity. Transcriptomic analyses of XLRS ROs showed decreased expression of retinal cells, particularly photoreceptor cells. Furthermore, relevant recovery of the XLRS phenotype was observed when co-cultured with control ROs derived from healthy subject during the early stages of differentiation. In conclusion, our in vitro XLRS RO model presents a valuable tool for elucidating the pathophysiological mechanisms underlying XLRS, offering insights into disease progression. Additionally, this model serves as a robust platform for the development and optimization of targeted therapeutic strategies, potentially improving treatment outcomes for patients with XLRS. [ABSTRACT FROM AUTHOR]

Human retinal organoids (ROs) have emerged as valuable tools for studying retinal development, modeling human retinal diseases, and screening drugs. However, their application is limited primarily due to time-intensive generation, high costs, and low reproducibility. Quality assessment of RO differentiation is crucial for their application in research. However, traditional methods such as morphological evaluation and immunohistochemical analysis have limitations due to their lack of precision and invasiveness, respectively. This study aims to identify non-invasive biomarkers for RO differentiation quality using exosomal microRNAs (miRNAs), which are known to reflect cell-specific functions and development in the retina. We differentiated ROs from human induced pluripotent stem cells (hiPSCs) and classified them into 'superior' and 'inferior' groups based on morphological and immunohistochemical criteria. Exosomes from the conditioned media were isolated and analyzed for miRNA content. Our findings revealed distinct miRNA profiles between superior and inferior ROs, with superior ROs exhibiting higher miRNA diversity and specifically up- or down-regulated miRNAs. Gene ontology and pathway enrichment analyses indicated that the target genes of these miRNAs are involved in neuron proliferation and differentiation. The study suggests the potential of exosomal hsa-miR-654-3p and hsa-miR-451a as non-invasive biomarkers for real-time monitoring of RO quality, facilitating the development of standardized, efficient, and cost-effective culture methods. [ABSTRACT FROM AUTHOR]

Purpose The Korean Society of Pediatric Neuro-Oncology (KSPNO) conducted treatment strategies for children with medulloblastoma (MB) by using alkylating agents for maintenance chemotherapy or tandem high-dose chemotherapy (HDC) with autologous stem cell rescue (ASCR) according to the risk stratification. The purpose of the study was to assess treatment outcomes and complications based on risk-adapted treatment and HDC. Materials and Methods Fifty-nine patients diagnosed with MB were enrolled in this study. Patients in the standard-risk (SR) group received radiotherapy (RT) after surgery and chemotherapy using the KSPNO M051 regimen. Patients in the high-risk (HR) group received two and four chemotherapy cycles according to the KSPNO S081 protocol before and after reduced RT for age following surgery and two cycles of tandem HDC with ASCR consolidation treatment. Results In the SR group, 24 patients showed 5-year event-free survival (EFS) and overall survival (OS) estimates of 86.7% (95% confidence interval [CI], 73.6 to 100) and 95.8% (95% CI, 88.2 to 100), respectively. In the HR group, more infectious complications and mortality occurred during the second HDC than during the first. In the HR group, the 5-year EFS and OS estimates were 65.5% (95% CI, 51.4 to 83.4) and 72.3% (95% CI, 58.4 to 89.6), respectively. Conclusion High intensity of alkylating agents for SR resulted in similar outcomes but with a high incidence of hematologic toxicity. Tandem HDC with ASCR for HR induced favorable EFS and OS estimates compared to those reported previously. However, infectious complications and treatment-related mortalities suggest that a reduced chemotherapy dose is necessary, especially for the second HDC. [ABSTRACT FROM AUTHOR]

Aims: This study was conducted to develop a population pharmacokinetic (PK) model of methotrexate in Korean patients with haematologic malignancy, identify factors affecting methotrexate PK, and propose an optimal dosage regimen for the Korean population. Methods: Data were retrospectively collected from 188 patients with acute leukaemia or non‐Hodgkin's lymphoma who were admitted to Severance Hospital during the period from November 2005 to January 2016. Using demographic factors and laboratory results as potential covariates for PK parameters, model development was performed using NONMEM and optimal dosing regimens were developed using the final PK model. Results: A two‐compartment model incorporating body weight via allometry best described the data, yielding typical parameter values of 25.09 L for central volume of distribution (V1), 17.65 L for peripheral volume of distribution (V2), 12.89 L/h for clearance (CL) and 0.655 L/h for inter‐compartmental clearance in a 50 kg patient. Covariate analyses showed that, at the weight of 50 kg, CL decreased by 0.11 L/h for each 1‐year increase in age above 14 years old and decreased 0.8‐fold when serum creatinine level doubled, indicating the importance of age‐specific dose individualization in methotrexate treatment. Volume of distribution at steady state derived from PK parameters (= V1 + V2) was 0.85 L/kg, which was similar to those in the Western or Chinese populations. Optimal doses simulated from the final model successfully produced the PK measures close to the target chosen. Conclusions: The population PK model and optimal dosage regimens developed in this study can be used as a basis to achieve precision dosing in Korean patients with haematologic malignancy. [ABSTRACT FROM AUTHOR]

Optical coherence tomography (OCT) is a noninvasive, high-resolution imaging technique widely used in clinical practice to depict the structure of the retina. Over the past few decades, ophthalmologists have used OCT to diagnose, monitor, and treat retinal diseases. However, manual analysis of the complicated retinal layers using two colors, black and white, is time consuming. Although ophthalmologists have more experience, their results may be prone to erroneous diagnoses. Therefore, in this study, we propose an automatic method for diagnosing five retinal diseases based on the use of hybrid and ensemble deep learning (DL) methods. DL extracts a thousand constitutional features from images as features for training classifiers. The machine learning method classifies the extracted features and fuses the outputs of the two classifiers to improve classification performance. The distribution probabilities of two classifiers of the same class are aggregated; then, class prediction is made using the class with the highest probability. The limited dataset is resolved by the fine-tuning of classification knowledge and generating augmented images using transfer learning and data augmentation. Multiple DL models and machine learning classifiers are used to access a suitable model and classifier for the OCT images. The proposed method is trained and evaluated using OCT images collected from a hospital and exhibits a classification accuracy of 97.68% (InceptionResNetV2, ensemble: Extreme gradient boosting (XG-Boost) and k-nearest neighbor (k-NN). The experimental results show that our proposed method can improve the OCT classification performance; moreover, in the case of a limited dataset, the proposed method is critical to develop accurate classifications. [ABSTRACT FROM AUTHOR]