Removal of phosphate from phosphohistidine in proteins

AbstractKinetic constants of KM = 0.8 μM, 3 μM and 1.6 μM, and kcat = 9 s−1, 7 s−1 or 9 s−1 were determined for histidine dephosphorylation by protein phosphatases 1, 2A and 2C respectively. IC50 values were determined for the inhibition of protein phosphatase 1 by inhibitor 1 (IC50 = 1 nM), inhibitor-2 (IC50 = 3 nM) and okadaic acid (IC50 = 30 nM) and for the inhibition of protein phosphatase 2A by okadaic acid (IC50 = 0.02 nM) and microcystin-LR (IC50 = 1 nM). Inhibitor-1 (Ki = 0.7 nM) and okadaic acid (Ki = 32 nM) are noncompetitive with protein phosphatase 1. some of the IC50 values were low enough to violate the assumptions of the usual inhibition equations and a more general approach to the analysis of the data was used. On the basis of these kinetic parameters and the presence of phosphohistidine, the major cellular protein serine/threonine phosphatases are likely to act as protein histidine phosphatases in the cell

The Measurement of Health Care System Efficiency: Cross-country Comparison by Geographical Region

Performance of health care delivery at the cross-country level has not often been directly evaluated by given inputs and outputs. This study estimates the efficiency of the health care systems of 170 countries by extending recent research using Simar and Wilsons bootstrap data envelopment analysis with a sensitivity test. The 170 countries are divided into four groups to compute efficiency estimators necessary to attaining a homogeneity requirement. The major finding is that most countries were inefficient to maximize the use of their inputs at the given output level. Countries in the high-income group have a relatively high average efficiency, but only 16.7% of the countries performed efficiently in the management of their health care systems. Notably, Asian countries performed more efficiently among other regions in each group. This study suggests that inefficient countries should pay attention to benchmark health care best practices within their regional peer groups.This work was supported by the National Research Foundation of Korea Grant funded by the Korean government (NRF-2012S1A3A2033416)

End-to-End Learnable Multi-Scale Feature Compression for VCM

The proliferation of deep learning-based machine vision applications has given rise to a new type of compression, so called video coding for machine (VCM). VCM differs from traditional video coding in that it is optimized for machine vision performance instead of human visual quality. In the feature compression track of MPEG-VCM, multi-scale features extracted from images are subject to compression. Recent feature compression works have demonstrated that the versatile video coding (VVC) standard-based approach can achieve a BD-rate reduction of up to 96% against MPEG-VCM feature anchor. However, it is still sub-optimal as VVC was not designed for extracted features but for natural images. Moreover, the high encoding complexity of VVC makes it difficult to design a lightweight encoder without sacrificing performance. To address these challenges, we propose a novel multi-scale feature compression method that enables both the end-to-end optimization on the extracted features and the design of lightweight encoders. The proposed model combines a learnable compressor with a multi-scale feature fusion network so that the redundancy in the multi-scale features is effectively removed. Instead of simply cascading the fusion network and the compression network, we integrate the fusion and encoding processes in an interleaved way. Our model first encodes a larger-scale feature to obtain a latent representation and then fuses the latent with a smaller-scale feature. This process is successively performed until the smallest-scale feature is fused and then the encoded latent at the final stage is entropy-coded for transmission. The results show that our model outperforms previous approaches by at least 52% BD-rate reduction and has $\times5$ to $\times27$ times less encoding time for object detection. It is noteworthy that our model can attain near-lossless task performance with only 0.002-0.003% of the uncompressed feature data size.Comment: Under peer review for IEEE TCSV

Routine breast milk monitoring using automated molecular assay system reduced postnatal CMV infection in preterm infants

Human cytomegalovirus (CMV) transmitted through breast milk poses fatal risks to preterm infants. However, current molecular assay systems often do not accommodate breast milk samples. In this study, we evaluated the analytical and clinical performance of the measurement procedure of CMV load in breast milk utilizing the Cobas CMV test on the Cobas 6,800 system. This was enabled by incorporating a simple independent sample preparation procedure before the application of samples on the automated assay system. Clinical data from electronic medical records were retrospectively analyzed. Breast milk samples from mothers of preterm infants born before 33 weeks of gestation were screened for CMV using the automated assay system. CMV positivity rates in breast milk and neonatal samples and the CMV transmission rate were calculated. Furthermore, to validate the analytical accuracy of the overall measurement procedure with newly obtained residual breast milk samples, the linearity of the measurement procedure was assessed, and a simplified sample preparation method was validated against a conventional method. The CMV positivity rates in maternal breast milk and neonatal samples were 57.8 and 5.2%, respectively. The CMV transmission rate through breast milk was 7.7%. No significant differences in gestational age or birth weight were found between the CMV-negative and CMV-positive neonates. The linearity of the procedure was observed within a range of 1.87–4.73 log IU/mL. The simplified sample preparation method had an equivalent or even improved CMV detection sensitivity than the conventional method. Incorporating a simple independent sample preparation procedure effectively resolved any potential issues regarding the application of breast milk on the automated assay system. Our approach contributed to reduced vertical transmission of CMV by providing a convenient and reliable method for the monitoring of breast milk CMV positivity for clinicians

Evaluation of the UniCel™ DxI 800 Immunoassay Analyzer in Measuring Five Tumor Markers

∙ The authors have no financial conflicts of interest. © Copyright: Yonsei University College of Medicine 2012 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial Licens