Risk Factors for Failure of Initial Intravenous Immunoglobulin Treatment in Kawasaki Disease

The aims of this study were to determine the occurrence and variables associated with the initial intravenous immunoglobulin (IVIG) treatment failure in Kawasaki disease (KD) and to categorize differences in clinical characteristics between responders and nonresponders to initial IVIG treatment. Patients were classified into two groups. Group A included 33 patients who received a single dose of IVIG treatment and responded. Group B included 18 patients who received more than two doses of IVIG due to failure of the initial treatment. The mean duration of fever after initial treatment in group B was significantly longer than it was in group A. In group B, we found that higher bilirubin, aspartate aminotransferase (AST), polymorphonuclear cells (PMN) (%), and lower platelet values at baseline were independent predictors of persistent or recurrent fever in patients with KD. Coronary artery abnormalities were found in 8 patients (44.4%) in group B and in two patients (6.1%) in group A. We found that abnormal liver function tests and a lower platelet count at baseline were possible predictors of nonresponders to IVIG in patients with KD. There is a need for a prospective study focused on baseline hepatobiliary parameters

RainSD: Rain Style Diversification Module for Image Synthesis Enhancement using Feature-Level Style Distribution

Autonomous driving technology nowadays targets to level 4 or beyond, but the researchers are faced with some limitations for developing reliable driving algorithms in diverse challenges. To promote the autonomous vehicles to spread widely, it is important to address safety issues on this technology. Among various safety concerns, the sensor blockage problem by severe weather conditions can be one of the most frequent threats for multi-task learning based perception algorithms during autonomous driving. To handle this problem, the importance of the generation of proper datasets is becoming more significant. In this paper, a synthetic road dataset with sensor blockage generated from real road dataset BDD100K is suggested in the format of BDD100K annotation. Rain streaks for each frame were made by an experimentally established equation and translated utilizing the image-to-image translation network based on style transfer. Using this dataset, the degradation of the diverse multi-task networks for autonomous driving, such as lane detection, driving area segmentation, and traffic object detection, has been thoroughly evaluated and analyzed. The tendency of the performance degradation of deep neural network-based perception systems for autonomous vehicle has been analyzed in depth. Finally, we discuss the limitation and the future directions of the deep neural network-based perception algorithms and autonomous driving dataset generation based on image-to-image translation.Comment: Under Revie

Site-Specific Bioconjugation of an Organometallic Electron Mediator to an Enzyme with Retained Photocatalytic Cofactor Regenerating Capacity and Enzymatic Activity

Photosynthesis consists of a series of reactions catalyzed by redox enzymes to synthesize carbohydrates using solar energy. In order to take the advantage of solar energy, many researchers have investigated artificial photosynthesis systems mimicking the natural photosynthetic enzymatic redox reactions. These redox reactions usually require cofactors, which due to their high cost become a key issue when constructing an artificial photosynthesis system. Combining a photosensitizer and an Rh-based electron mediator (RhM) has been shown to photocatalytically regenerate cofactors. However, maintaining the high concentration of cofactors available for efficient enzymatic reactions requires a high concentration of the expensive RhM; making this process cost prohibitive. We hypothesized that conjugation of an electron mediator to a redox enzyme will reduce the amount of electron mediators necessary for efficient enzymatic reactions. This is due to photocatalytically regenerated NAD(P)H being readily available to a redox enzyme, when the local NAD(P)H concentration near the enzyme becomes higher. However, conventional random conjugation of RhM to a redox enzyme will likely lead to a substantial loss of cofactor regenerating capacity and enzymatic activity. In order to avoid this issue, we investigated whether bioconjugation of RhM to a permissive site of a redox enzyme retains cofactor regenerating capacity and enzymatic activity. As a model system, a RhM was conjugated to a redox enzyme, formate dehydrogenase obtained from Thiobacillus sp. KNK65MA (TsFDH). A RhM-containing azide group was site-specifically conjugated to p-azidophenylalanine introduced to a permissive site of TsFDH via a bioorthogonal strain-promoted azide-alkyne cycloaddition and an appropriate linker. The TsFDH-RhM conjugate exhibited retained cofactor regenerating capacity and enzymatic activityope

Subdermal Flexible Solar Cell Arrays for Powering Medical Electronic Implants

A subdermally implantable flexible photovoltatic (IPV) device is proposed for supplying sustainable electric power to in vivo medical implants. Electric properties of the implanted IPV device are characterized in live animal models. Feasibility of this strategy is demonstrated by operating a flexible pacemaker with the subdermal IPV device which generates DC electric power of ≈647 μW under the skin

Molecular and cytological features of the mouse B-cell lymphoma line iMyc(Eμ)-1

BACKGROUND: Myc-induced lymphoblastic B-cell lymphoma (LBL) in iMyc(Eμ )mice may provide a model system for the study of the mechanism by which human MYC facilitates the initiation and progression of B cell and plasma cell neoplasms in human beings. We have recently shown that gene-targeted iMyc(Eμ )mice that carry a His(6)-tagged mouse Myc cDNA, Myc(His), just 5' of the immunoglobulin heavy-chain enhancer, Eμ, are prone to B cell and plasma cell tumors. The predominant tumor (~50%) that arose in the iMyc(Eμ )mice on the mixed genetic background of segregating C57BL/6 and 129/SvJ alleles was LBL. The purpose of this study was to establish and characterize a cell line, designated iMyc(Eμ)-1, for the in-depth evaluation of LBL in vitro. METHODS: The morphological features and the surface marker expression profile of the iMyc(Eμ)-1 cells were evaluated using cytological methods and FACS, respectively. The cytogenetic make-up of the iMyc(Eμ)-1 cells was assessed by spectral karyotyping (SKY). The expression of the inserted Myc(His )gene was determined using RT-PCR and qPCR. Clonotypic immunoglobulin gene arrangements were detected by Southern blotting. The global gene expression program of the iMyc(Eμ)-1 cells and the expression of 768 "pathway" genes were determined with the help of the Mouse Lymphochip(© )and Superarray(© )cDNA micro- and macroarrays, respectively. Array results were verified, in part, by RT-PCR and qPCR. RESULTS: Consistent with their derivation from LBL, the iMyc(Eμ)-1 cells were found to be neoplastic IgM(high)IgD(low )lymphoblasts that expressed typical B-cell surface markers including CD40, CD54 (ICAM-1), CD80 (B7-1) and CD86 (B7-2). The iMyc(Eμ)-1 cells harbored a reciprocal T(9;11) and three non-reciprocal chromosomal translocations, over-expressed Myc(His )at the expense of normal Myc, and exhibited gene expression changes on Mouse Lymphochip(© )microarrays that were consistent with Myc(His)-driven B-cell neoplasia. Upon comparison to normal B cells using eight different Superarray(© )cDNA macroarrays, the iMyc(Eμ)-1 cells showed the highest number of changes on the NFκB array. CONCLUSION: The iMyc(Eμ)-1 cells may provide a uniquely useful model system to study the growth and survival requirements of Myc-driven mouse LBL in vitro

Hydrogen-Tolerant La0.6Ca0.4Co0.2Fe0.8O3–d Oxygen Transport Membranes from Ultrasonic Spray Synthesis for Plasma-Assisted CO2 Conversion

La0.6Ca0.4Co1–xFexO3–d in its various compositions has proven to be an excellent CO2-resistant oxygen transport membrane that can be used in plasma-assisted CO2 conversion. With the goal of incorporating green hydrogen into the CO2 conversion process, this work takes a step further by investigating the compatibility of La0.6Ca0.4Co1–xFexO3–d membranes with hydrogen fed into the plasma. This will enable plasma-assisted conversion of the carbon monoxide produced in the CO2 reduction process into green fuels, like methanol. This requires the La0.6Ca0.4Co1–xFexO3–d membranes to be tolerant towards reducing conditions of hydrogen. The hydrogen tolerance of La0.6Ca0.4Co1–xFexO3–d (x = 0.8) was studied in detail. A faster and resource-efficient route based on ultrasonic spray synthesis was developed to synthesise the La0.6Ca0.4Co0.2Fe0.8O3–d membranes. The La0.6Ca0.4Co0.2Fe0.8O3–d membrane developed using ultrasonic spray synthesis showed similar performance in terms of its oxygen permeation when compared with the ones synthesised with conventional techniques, such as co-precipitation, sol–gel, etc., despite using 30% less cobalt

Development and Validation of an Arterial Pressure-Based Cardiac Output Algorithm Using a Convolutional Neural Network: Retrospective Study Based on Prospective Registry Data

Background: Arterial pressure-based cardiac output (APCO) is a less invasive method for estimating cardiac output without concerns about complications from the pulmonary artery catheter (PAC). However, inaccuracies of currently available APCO devices have been reported. Improvements to the algorithm by researchers are impossible, as only a subset of the algorithm has been released. Objective: In this study, an open-source algorithm was developed and validated using a convolutional neural network and a transfer learning technique. Methods: A retrospective study was performed using data from a prospective cohort registry of intraoperative bio-signal data from a university hospital. The convolutional neural network model was trained using the arterial pressure waveform as input and the stroke volume (SV) value as the output. The model parameters were pretrained using the SV values from a commercial APCO device (Vigileo or EV1000 with the FloTrac algorithm) and adjusted with a transfer learning technique using SV values from the PAC. The performance of the model was evaluated using absolute error for the PAC on the testing dataset from separate periods. Finally, we compared the performance of the deep learning model and the FloTrac with the SV values from the PAC. Results: A total of 2057 surgical cases (1958 training and 99 testing cases) were used in the registry. In the deep learning model, the absolute errors of SV were 14.5 (SD 13.4) mL (10.2 [SD 8.4] mL in cardiac surgery and 17.4 [SD 15.3] mL in liver transplantation). Compared with FloTrac, the absolute errors of the deep learning model were significantly smaller (16.5 [SD 15.4] and 18.3 [SD 15.1], P<.001). Conclusions: The deep learning-based APCO algorithm showed better performance than the commercial APCO device. Further improvement of the algorithm developed in this study may be helpful for estimating cardiac output accurately in clinical practice and optimizing high-risk patient care. © Hyun-Lim Yang, Chul-Woo Jung, Seong Mi Yang, Min-Soo Kim, Sungho Shim, Kook Hyun Lee, Hyung-Chul Lee. Originally published in JMIR Medical Informatics (https://medinform.jmir.org), 16.08.2021. This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Medical Informatics, is properly cited. The complete bibliographic information, a link to the original publication on https://medinform.jmir.org/, as well as this copyright and license information must be included.1

Subdermal Flexible Solar Cell Arrays for Powering Medical Electronic Implants

with aims of overcoming limitation

Molecular surveillance reveals the presence of pfhrp2 and pfhrp3 gene deletions in Plasmodium falciparum parasite populations in Uganda, 2017–2019

Abstract Background Histidine-rich protein-2 (HRP2)-based rapid diagnostic tests (RDTs) are the only RDTs recommended for malaria diagnosis in Uganda. However, the emergence of Plasmodium falciparum histidine rich protein 2 and 3 (pfhrp2 and pfhrp3) gene deletions threatens their usefulness as malaria diagnostic and surveillance tools. The pfhrp2 and pfhrp3 gene deletions surveillance was conducted in P. falciparum parasite populations in Uganda. Methods Three-hundred (n = 300) P. falciparum isolates collected from cross-sectional malaria surveys in symptomatic individuals in 48 districts of eastern and western Uganda were analysed for the presence of pfhrp2 and pfhrp3 genes. Presence of parasite DNA was confirmed by PCR amplification of the 18s rRNA gene, msp1 and msp2 single copy genes. Presence or absence of deletions was confirmed by amplification of exon1 and exon2 of pfhrp2 and pfhrp3 using gene specific PCR. Results Overall, pfhrp2 and pfhrp3 gene deletions were detected in 29/300 (9.7%, 95% CI 6.6–13.6%) parasite isolates. The pfhrp2 gene was deleted in 10/300 (3.3%, 95% CI 1.6–6.0%) isolates, pfhrp3 in 9/300 (3.0%, 95% CI 1.4–5.6%) while both pfhrp2 and pfhrp3 were deleted in 10/300 (3.3%, 95% CI 1.6–6.0%) parasite isolates. Proportion of pfhrp2/3 deletions was higher in the eastern 14.7% (95% CI 9.7–20.0%) compared to the western region 3.1% (95% CI 0.8–7.7%), p = 0.001. Geographical location was associated with gene deletions aOR 6.25 (2.02–23.55), p = 0.003. Conclusions This is the first large-scale survey reporting the presence of pfhrp2/3 gene deletions in P. falciparum isolates in Uganda. Roll out of RDTs for malaria diagnosis should take into consideration the existence of pfhrp2/3 gene deletions particularly in areas where they were detected. Periodic pfhrp2/3 surveys are recommended to inform future decisions for deployment of alternative RDTs

APOE Promoter Polymorphism-219T/G is an Effect Modifier of the Influence of APOE ε4 on Alzheimer's Disease Risk in a Multiracial Sample

Variants in the APOE gene region may explain ethnic differences in the association of Alzheimer's disease (AD) with ε4. Ethnic differences in allele frequencies for three APOE region SNPs (single nucleotide polymorphisms) were identified and tested for association in 19,398 East Asians (EastA), including Koreans and Japanese, 15,836 European ancestry (EuroA) individuals, and 4985 African Americans, and with brain imaging measures of cortical atrophy in sub-samples of Koreans and EuroAs. Among ε4/ε4 individuals, AD risk increased substantially in a dose-dependent manner with the number of APOE promoter SNP rs405509 T alleles in EastAs (TT: OR (odds ratio) = 27.02, p = 8.80 × 10-94; GT: OR = 15.87, p = 2.62 × 10-9) and EuroAs (TT: OR = 18.13, p = 2.69 × 10-108; GT: OR = 12.63, p = 3.44 × 10-64), and rs405509-T homozygotes had a younger onset and more severe cortical atrophy than those with G-allele. Functional experiments using APOE promoter fragments demonstrated that TT lowered APOE expression in human brain and serum. The modifying effect of rs405509 genotype explained much of the ethnic variability in the AD/ε4 association, and increasing APOE expression might lower AD risk among ε4 homozygotes