28 research outputs found

    The Differential Choice Of Chaebol In Earnings Management

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    This study examines the methods of the differential choice of Korean “chaebol” in earnings management. Consistent with our prediction, we find a negative association between chaebols’ ownership and accrual-based earnings management, whereas there is no clear difference between chaebols’ ownership and real-based earnings management. Furthermore, we find evidence that chaebols exhibit a strongly positive relationship with overproduction-based real activities manipulation, indicating that chaebols prefer overproduction as a method of real earnings management. From additional analyses, we also find that abnormal cash flow from operations is negatively associated with suspect chaebol firm-years that just met zero

    Recognition of Transmembrane Protein 39A as a Tumor-Specific Marker in Brain Tumor

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    Transmembrane protein 39A (TMEM39A) belongs to the TMEM39 family. TMEM39A gene is a susceptibility locus for multiple sclerosis. In addition, TMEM39A seems to be implicated in systemic lupus erythematosus. However, any possible involvement of TMEM39A in cancer remains largely unknown. In the present report, we provide evidence that TMEM39A may play a role in brain tumors. Western blotting using an anti-TMEM39A antibody indicated that TMEM39A was overexpressed in glioblastoma cell lines, including U87-MG and U251-MG. Deep-sequencing transcriptomic profiling of U87-MG and U251-MG cells revealed that TMEM39A transcripts were upregulated in such cells compared with those of the cerebral cortex. Confocal microscopic analysis of U251-MG cells stained with anti-TMEM39A antibody showed that TMEM39A was located in dot-like structures lying close to the nucleus. TMEM39A probably located to mitochondria or to endosomes. Immunohistochemical analysis of glioma tissue specimens indicated that TMEM39A was markedly upregulated in such samples. Bioinformatic analysis of the Rembrandt knowledge base also supported upregulation of TMEM39A mRNA levels in glioma patients. Together, the results afford strong evidence that TMEM39A is upregulated in glioma cell lines and glioma tissue specimens. Therefore, TMEM39A may serve as a novel diagnostic marker of, and a therapeutic target for, gliomas and other cancers

    S6 kinase 1 plays a key role in mitochondrial morphology and cellular energy flow

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    Mitochondrial morphology, which is associated with changes in metabolism, cell cycle, cell development and cell death, is tightly regulated by the balance between fusion and fission. In this study, we found that S6 kinase 1 (S6K1) contributes to mitochondrial dynamics, homeostasis and function. Mouse embryo fibroblasts lacking S6K1 (S6K1 KO MEFs) exhibited more fragmented mitochondria and a higher level of Dynamin related protein 1 (Drp1) and active Drp1 (pS616) in both whole cell extracts and mitochondria' fraction. In addition, there was no evidence for autophagy and mitophagy induction in S6K1 depleted cells. Glycolysis and mitochondrial respiratory activity was higher in S6K1-KO MEFs, whereas OxPhos ATP production was not altered. However, inhibition of Drp1 by Mdivi1 (Drp1 inhibitor) resulted in higher OxPhos ATP production and lower mitochondrial membrane potential. Taken together the depletion of S6K1 increased Drpl-mediated fission, leading to the enhancement of glycolysis. The fission form of mitochondria resulted in lower yield for OxPhos ATP production as well as in higher mitochondrial membrane potential. Thus, these results have suggested a potential role of S6K1 in energy metabolism by modulating mitochondrial respiratory capacity and mitochondrial morphology.

    Robust estimation of bacterial cell count from optical density

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    Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

    Energy values and protein digestibility of soybean milk by-product in pigs based on in vitro assays

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    Background: Soybean milk by-product (SMBP) is a potential alternative feed ingredient in swine diets due to its high protein content. However, information on energy and nutritional values of SMBP used as swine feed ingredient is limited. Objective: To estimate energy values and protein digestibility of SMBP in pigs based on in vitro assays. Methods: Four SMBP samples were obtained from 3 soybean milk-producing facilities. In vitro total tract disappearance (IVTTD) and in vitro ileal disappearance (IVID) of dry matter (DM) in the SMBP samples were determined. In vitro ileal disappearance of crude protein was determined by analyzing crude protein content in undigested residues after determining IVID of DM. Digestible and metabolizable energy of SMBP were estimated using gross energy, IVTTD of DM, and prediction equations. Results: Sample 4 had greater IVTTD of DM than that of sample 3 (97.7 vs. 94.4%, p<0.05), whereas IVID of DM in sample 4 was lower compared with sample 1 (53.5 vs. 65.0%, p<0.05). In vitro ileal disappearance of crude protein in sample 2 was greater than that in sample 1 and 3 (92.6 vs. 90.6 and 90.1%; p<0.05). The estimated metabolizable energy of SMBP ranged from 4,311 to 4,619 kcal/kg as-is basis and the value of sample 3 was the least (p<0.05) among SMBP samples. Conclusion: Energy values and protein digestibility should be determined before using SMBP in swine diets.Antecedentes: O subproduto do leite de soja (SMBP) é um potencial ingrediente alternativo na dieta de suínos, considerando seu alto teor de proteínas. No entanto, as informações sobre os valores energéticos e nutricionais do SMBP usado como ingrediente alimentar para suínos são limitadas. Objetivo: Estimar valores energéticos e digestibilidade protéica do SMBP em suínos com base em ensaios in vitro. Métodos: Foram obtidas quatro amostras de SMBP de três instalações produtores de leite de soja. Foram determinados o desaparecimento total do trato in vitro (IVTTD) e o desaparecimento ileal in vitro (IVID) da matéria seca (DM) nas amostras de SMBP. O desaparecimento ileal in vitro da proteína bruta foi determinado pela análise do conteúdo de proteína bruta em resíduos não digeridos após a determinação da IVID do DM. A energia digerível e metabolizável do SMBP foi estimada usando energia bruta, IVTTD do DM e equações de predição. Resultados: a amostra 4 apresentou maior IVTTD de DM do que a amostra 3 (97,7 vs. 94,4%, p<0,05) enquanto a IVID do DM na amostra 4 foi menor em comparação com a amostra 1 (53,5 vs. 65,0%, p<0,05). O desaparecimento ileal in vitro da proteína bruta na amostra 2 foi superior ao da amostra 1 e 3 (92,6 vs. 90,6 e 90,1%; p<0,05). A energia metabolizável estimada do SMBP variou de 4.311 a 4.619 kcal/kg no estado em que se encontra e o valor da amostra 3 foi o menor (p<0,05) entre as amostras do SMBP. Conclusão: os valores energéticos e a digestibilidade das proteínas devem ser determinados antes do uso do SMBP nas dietas suínas.Antecedentes: El subproducto de la leche de soja (SMBP) es un ingrediente alimenticio alternativo con uso potencial en dietas porcinas dado su alto contenido de proteína. Sin embargo, la información sobre sus valores energéticos y nutricionales para alimentación de cerdos es muy limitada. Objetivo: Estimar los valores de energía y la digestibilidad de la proteína del SMBP en cerdos con base en ensayos in vitro. Métodos: Se obtuvieron cuatro muestras de SMBP de tres empresas productoras de leche de soja. Se determinaron la desaparición de tracto total in vitro (IVTTD) y la desaparición ileal in vitro (IVID) de la materia seca (DM) en las muestras de SMBP. La desaparición ileal in vitro de proteína cruda se determinó analizando el contenido de proteína cruda en residuos no digeridos después de determinar la IVID de la DM. La energía digestible y metabolizable de SMBP se estimó utilizando la energía bruta, IVTTD de la DM y ecuaciones de predicción. Resultados: La muestra 4 tuvo una mayor IVTTD de la DM que la muestra 3 (97,7 vs. 94,4%, p<0,05), mientras que la IVID de la DM en la muestra 4 fue menor en comparación con la muestra 1 (53,5 vs. 65,0%, p<0,05). La desaparición ileal in vitro de la proteína cruda en la muestra 2 fue mayor que la de las muestras 1 y 3 (92,6 vs. 90,6 y 90,1%; p<0,05). La energía metabolizable estimada de SMBP varió de 4.311 a 4.619 kcal/kg (en base húmeda) y el valor de la muestra 3 fue el menor (p<0.05) entre las muestras de SMBP. Conclusión: Los valores de energía y la digestibilidad de la proteína deben determinarse antes de usar el SMBP en dietas porcinas

    Correlation Analysis of Noise, Vibration, and Harshness in a Vehicle Using Driving Data Based on Big Data Analysis Technique

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    A new development process for the noise, vibration, and harshness (NVH) of a vehicle is presented using data analysis and machine learning with long-term NVH driving data. The process includes exploratory data analysis (EDA), variable importance analysis, correlation analysis, sensitivity analysis, and development target selection. In this paper, to dramatically reduce the development period and cost related to vehicle NVH, we propose a technique that can accurately identify the precise connectivity and relationship between vehicle systems and NVH factors. This new technique uses whole big data and reflects the nonlinearity of dynamic characteristics, which was not considered in existing methods, and no data are discarded. Through the proposed method, it is possible to quickly find areas that need improvement through correlation analysis and variable importance analysis, understand how much room noise increases when the NVH level of the system changes through sensitivity analysis, and reduce vehicle development time by improving efficiency. The method could be used in the development process and the validation of other deep learning and machine learning models. It could be an essential step in applying artificial intelligence, big data, and data analysis in the vehicle and mobility industry as a future vehicle development process

    GeniAuti: Toward Data-Driven Interventions to Challenging Behaviors of Autistic Children through Caregivers&apos; Tracking

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    © 2022 Owner/Author.Challenging behaviors significantly impact learning and socialization of autistic children and can stress and burden their caregivers. Documentation of challenging behaviors is fundamental for identifying what environmental factors influence them, such as how others respond to a child&apos;s such behaviors. Caregiver-tracked data on their child&apos;s challenging behaviors can help clinical experts make informed recommendations about how to manage such behaviors. To support caregivers in recording their children&apos;s challenging behaviors, we developed GeniAuti, a mobile-based data-collection tool built upon a clinical data collection form to document challenging behaviors and other clinically relevant contextual information such as place, duration, intensity, and what triggers such behaviors. Through an open-ended deployment with 19 parent-child pairs and three expert collaborators, caregivers found GeniAuti valuable for (1) becoming more attentive and reflective to behavioral contexts, including their own response strategies, (2) discovering positive aspects of their children&apos;s behaviors, and (3) promoting collaboration with clinical experts around the caregiver-tracked data to develop tailored intervention strategies for their children. However, participant experiences surface challenges of logging behaviors in social circumstances, conflicting views between caregivers and clinical experts around the structured recording process, and emotional struggles resulting from recording and reflecting on intensely negative experiences. Considering the complex nature of caregiver-based health tracking and caregiver - clinician collaboration, we suggest design opportunities for facilitating negotiations between caregivers and clinicians and accounting for caregivers&apos; emotional needs.N
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