Bacillus subtilis HmoB is a heme oxygenase with a novel structure

Iron availability is limited in the environment and mostbacteria have developed a system to acquire iron from hosthemoproteins. Heme oxygenase plays an important role bydegrading heme group and releasing the essential nutrientiron. The structure of Bacillus subtilis HmoB was determinedto 2.0 Å resolution. B. subtilis HmoB contains a typicalantibiotic biosynthesis monooxygenase (ABM) domain thatspans from 71 to 146 residues and belongs to the IsdG familyheme oxygenases. Comparison of HmoB and IsdG familyproteins showed that the C-terminal region of HmoB hassimilar sequence and structure to IsdG family proteins andcontains conserved critical residues for heme degradation.However, HmoB is distinct from other IsdG family proteins inthat HmoB is about 60 amino acids longer in the N-terminusand does not form a dimer whereas previously studied IsdGfamily heme oxygenases form functional homodimers.Interestingly, the structure of monomeric HmoB resembles thedimeric structure of IsdG family proteins. Hence, B. subtilisHmoB is a heme oxygenase with a novel structural feature.[BMB reports 2012; 45(4): 239-241

ECG-QA: A Comprehensive Question Answering Dataset Combined With Electrocardiogram

Question answering (QA) in the field of healthcare has received much attention due to significant advancements in natural language processing. However, existing healthcare QA datasets primarily focus on medical images, clinical notes, or structured electronic health record tables. This leaves the vast potential of combining electrocardiogram (ECG) data with these systems largely untapped. To address this gap, we present ECG-QA, the first QA dataset specifically designed for ECG analysis. The dataset comprises a total of 70 question templates that cover a wide range of clinically relevant ECG topics, each validated by an ECG expert to ensure their clinical utility. As a result, our dataset includes diverse ECG interpretation questions, including those that require a comparative analysis of two different ECGs. In addition, we have conducted numerous experiments to provide valuable insights for future research directions. We believe that ECG-QA will serve as a valuable resource for the development of intelligent QA systems capable of assisting clinicians in ECG interpretations.Comment: 39 pages (9 pages for main text, 2 pages for references, 28 pages for supplementary materials

In situ electrochemical surface modification for high-voltage LiCoO2 in lithium ion batteries

High-voltage LiCoO2 has been revisited to improve the energy density of lithium ion batteries. LiCoO2 can deliver the reversible capacity of about 200 mA h g(-1) when the upper cut-off voltage increases to 4.55 V (vs. Li/Li+). However, the high upper cut-off voltage causes the severe failures of LiCoO2 such as structural degradation, electrolyte decomposition, and Co dissolution. Various surface-modified LiCoO2 materials have been introduced to suppress electrolyte decomposition and Co dissolution, thereby leading to the improved electrochemical performance. Most of the coated LiCoO2 materials are obtained through a conventional coating process such as sol-gel synthesis, which is complex and high-cost. In this paper, the in situ electrochemical coating method is introduced as a simple and low-cost coating process, where the electrolyte additive of Mg salts is electrochemically decomposed to form a MgF2-based coating layer on the LiCoO2 surface. LiCoO2 electrochemically coated with MgF2 suppresses Co dissolution in electrolytes, resulting in excellent electrochemical performance such as high reversible capacity of 198 mA h g(-1) and stable cycle performance over 100 cycles in the voltage range between 3 and 4.55 V (vs. Li/Li+) at 45 degrees C. The formation mechanism of MgF2 is also demonstrated through ex situ XPS and XANES analyses.

Short-term Effect of Ambient Air Pollution on Emergency Department Visits for Diabetic Coma in Seoul, Korea

Objectives A positive association between air pollution and both the incidence and prevalence of diabetes mellitus (DM) has been reported in some epidemiologic and animal studies, but little research has evaluated the relationship between air pollution and diabetic coma. Diabetic coma is an acute complication of DM caused by diabetic ketoacidosis or hyperosmolar hyperglycemic state, which is characterized by extreme hyperglycemia accompanied by coma. We conducted a time-series study with a generalized additive model using a distributed-lag non-linear model to assess the association between ambient air pollution (particulate matter less than 10 μm in aerodynamic diameter, nitrogen dioxide [NO2], sulfur dioxide, carbon monoxide, and ozone) and emergency department (ED) visits for DM with coma in Seoul, Korea from 2005 to 2009. Methods The ED data and medical records from the 3 years previous to each diabetic coma event were obtained from the Health Insurance Review and Assessment Service to examine the relationship with air pollutants. Results Overall, the adjusted relative risks (RRs) for an interquartile range (IQR) increment of NO2 was statistically significant at lag 1 (RR, 1.125; 95% confidence interval [CI], 1.039 to 1.219) in a single-lag model and both lag 0-1 (RR, 1.120; 95% CI, 1.028 to 1.219) and lag 0-3 (RR, 1.092; 95% CI, 1.005 to 1.186) in a cumulative-lag model. In a subgroup analysis, significant positive RRs were found for females for per-IQR increments of NO2 at cumulative lag 0-3 (RR, 1.149; 95% CI, 1.022 to 1.291). Conclusions The results of our study suggest that ambient air pollution, specifically NO2, is associated with ED visits for diabetic coma

GenHPF: General Healthcare Predictive Framework with Multi-task Multi-source Learning

Despite the remarkable progress in the development of predictive models for healthcare, applying these algorithms on a large scale has been challenging. Algorithms trained on a particular task, based on specific data formats available in a set of medical records, tend to not generalize well to other tasks or databases in which the data fields may differ. To address this challenge, we propose General Healthcare Predictive Framework (GenHPF), which is applicable to any EHR with minimal preprocessing for multiple prediction tasks. GenHPF resolves heterogeneity in medical codes and schemas by converting EHRs into a hierarchical textual representation while incorporating as many features as possible. To evaluate the efficacy of GenHPF, we conduct multi-task learning experiments with single-source and multi-source settings, on three publicly available EHR datasets with different schemas for 12 clinically meaningful prediction tasks. Our framework significantly outperforms baseline models that utilize domain knowledge in multi-source learning, improving average AUROC by 1.2%P in pooled learning and 2.6%P in transfer learning while also showing comparable results when trained on a single EHR dataset. Furthermore, we demonstrate that self-supervised pretraining using multi-source datasets is effective when combined with GenHPF, resulting in a 0.6%P AUROC improvement compared to models without pretraining. By eliminating the need for preprocessing and feature engineering, we believe that this work offers a solid framework for multi-task and multi-source learning that can be leveraged to speed up the scaling and usage of predictive algorithms in healthcare.Comment: Accepted by IEEE Journal of Biomedical and Health Informatic

Cooperative evolution of polar distortion and nonpolar rotation of oxygen octahedra in oxide heterostructures

Polarity discontinuity across LaAlO3/SrTiO3 (LAO/STO) heterostructures induces electronic reconstruction involving the formation of two-dimensional electron gas (2DEG) and structural distortions characterized by antiferrodistortive (AFD) rotation and ferroelectric (FE) distortion. We show that AFD and FE modes are cooperatively coupled in LAO/STO (111) heterostructures; they coexist below the critical thickness (t(c)) and disappear simultaneously above tc with the formation of 2DEG. Electron energy-loss spectroscopy and density functional theory (DFT) calculations provide direct evidence of oxygen vacancy (VO) formation at the LAO (111) surface, which acts as the source of 2DEG. Tracing the AFD rotation and FE distortion of LAO reveals that their evolution is strongly correlated with VO distribution. The present study demonstrates that AFD and FE modes in oxide heterostructures emerge as a consequence of interplay between misfit strain and polar field, and further that their combination can be tuned to competitive or cooperative coupling by changing the interface orientation

Genome-wide analysis of DNA methylation patterns in horse

Background: DNA methylation is an epigenetic regulatory mechanism that plays an essential role in mediating biological processes and determining phenotypic plasticity in organisms. Although the horse reference genome and whole transcriptome data are publically available the global DNA methylation data are yet to be known. Results: We report the first genome-wide DNA methylation characteristics data from skeletal muscle, heart, lung, and cerebrum tissues of thoroughbred (TH) and Jeju (JH) horses, an indigenous Korea breed, respectively by methyl-DNA immunoprecipitation sequencing. The analysis of the DNA methylation patterns indicated that the average methylation density was the lowest in the promoter region, while the density in the coding DNA sequence region was the highest. Among repeat elements, a relatively high density of methylation was observed in long interspersed nuclear elements compared to short interspersed nuclear elements or long terminal repeat elements. We also successfully identified differential methylated regions through a comparative analysis of corresponding tissues from TH and JH, indicating that the gene body regions showed a high methylation density. Conclusions: We provide report the first DNA methylation landscape and differentially methylated genomic regions (DMRs) of thoroughbred and Jeju horses, providing comprehensive DMRs maps of the DNA methylome. These data are invaluable resource to better understanding of epigenetics in the horse providing information for the further biological function analyses.open1

Construção de um protótipo de Data Warehouse como suporte ao sistema de informação numa instituição de ensino superior

Uma das dificuldades que se verifica na extracção de informação numa organização é a falta de integração dos dados existentes dispersos em diversos formatos: ficheiros de processadores de texto, folhas de cálculo, bases de dados, entre outras fontes. A partir deste problema, este trabalho propõe a estruturação de um modelo de Data Warehouse com o objectivo de organizar, armazenar e integrar as informações provenientes de outros formatos e sistemas, numa única base de dados para uma futura utilização no suporte à tomada de decisão. Existem, neste momento, na comunidade de Data Warehousing duas principais abordagens, uma preconizada por William H. Inmon, mais centrada nos dados, e outra por Ralph Kimball, mais centrada no projecto. Assim, com a metodologia proposta foi desenvolvido um caso de estudo com a finalidade de verificar e avaliar a aplicabilidade da metodologia no Instituto Politécnico de Tomar; ABSTRACT: One difficulty that exists in the extraction of information in organizations is the lack of integration of existing data scattered in various formats: word processing files, spreadsheets, databases, among other sources. From this problem, this paper proposes to structure a model of Data Warehouse in order to organize, store and integrate information from other systems and formats in a single database for future use in supporting decision making. There are at present in the community of Data Warehousing two main approaches, one advocated by William H. Inmon, more data-centric, and one by Ralph Kimball, more focused on the project. So with the proposed methodology was developed a case study in order to verify and evaluate the applicability of the methodology at the Polytechnic Institute of Tomar