Biological pathways are known as collections of knowledge of certain biological processes. Although knowledge about a pathway is quite significant to further analysis, it covers only tiny portion of genes that exists. In this paper, we suggest a model to extend each individual pathway using a microarray expression data based on the known knowledge about the pathway. We take the Rosetta compendium dataset to extend pathways of Saccharomyces cerevisiae obtained from KEGG (Kyoto Encyclopedia of genes and genomes) database. Before applying our model, we verify the underlying assumption that microarray data reflect the interactive knowledge from pathway, and we evaluate our scoring system by introducing performance function. In the last step, we validate proposed candidates with the help of another type of biological information. We introduced a pathway extending model using its intrinsic structure and microarray expression data. The model provides the suitable candidate genes for each single biological pathway to extend it.
Biological Processes ; Gene Expression ; Saccharomyces cerevisiae

For over a thousand years, various substances have been applied to the skin to treat pain. Some of these substances have active ingredients that we still use today. However, some have been discontinued due to their harmful effect, while others have been long forgotten. Recent concerns regarding the cardiovascular and renal risk from nonsteroidal anti-inflammatory drugs, and issues with opioids, have resulted in increasing demand and attention to non-systemic topical alternatives. There is increasing evidence of the efficacy and safety of topical agents in pain control. Topical analgesics are great alternatives for pain management and are an essential part of multimodal analgesia. This review aims to describe essential aspects of topical drugs that physicians should consider in their practice as part of multimodal analgesia. This review describes the mechanism of popular topical analgesics and also introduces the most recently released and experimental topical medications.

Background: Transfusion appropriateness is extremely important due to the growing concerns about the decrease in the supply of blood products and the increase in demand. Considerable time and effort are required to effectively collect and analyze large volumes of data. Therefore, we aimed to develop a transfusion appropriateness management program using the Tableau visual analytics platform, which allows intuitive visualization through various visualization options and interactive features and can quickly process large volumes of data. Methods: Using the transfusion prescription history and blood management and distribution history, we created a data mart comprising patient information, hospitalization history, inpatient/outpatient prescriptions, test results, records, and surgical information. Based on this we developed visualization analysis content for monitoring transfusion appropriateness.We automated the periodic aggregation of the data mart into an analysis database and connected it to Tableau. Results: We developed Transfusion Appropriateness Management (TAM), a program for managing transfusion appropriateness linked to Tableau, after analyzing transfusion-related data and metadata extracted from the Daejeon Eulji Medical Center's order communication system/electronic medical record (OCS/EMR) system. Detailed filters were applied to allow users to intuitively view the desired data according to their criteria. Data were visualized in various forms, such as bar graphs, heat maps, and box plots based on filtering criteria. Conclusion The development of the Transfusion Appropriateness Management program at the Daejeon Eulji Medical Center is expected to effectively reduce inappropriate transfusions in clinical settings and enhance patient safety within the hospital by swiftly and conveniently visualizing vast amounts of data.

Background: Transfusion appropriateness is extremely important due to the growing concerns about the decrease in the supply of blood products and the increase in demand. Considerable time and effort are required to effectively collect and analyze large volumes of data. Therefore, we aimed to develop a transfusion appropriateness management program using the Tableau visual analytics platform, which allows intuitive visualization through various visualization options and interactive features and can quickly process large volumes of data. Methods: Using the transfusion prescription history and blood management and distribution history, we created a data mart comprising patient information, hospitalization history, inpatient/outpatient prescriptions, test results, records, and surgical information. Based on this we developed visualization analysis content for monitoring transfusion appropriateness.We automated the periodic aggregation of the data mart into an analysis database and connected it to Tableau. Results: We developed Transfusion Appropriateness Management (TAM), a program for managing transfusion appropriateness linked to Tableau, after analyzing transfusion-related data and metadata extracted from the Daejeon Eulji Medical Center's order communication system/electronic medical record (OCS/EMR) system. Detailed filters were applied to allow users to intuitively view the desired data according to their criteria. Data were visualized in various forms, such as bar graphs, heat maps, and box plots based on filtering criteria. Conclusion The development of the Transfusion Appropriateness Management program at the Daejeon Eulji Medical Center is expected to effectively reduce inappropriate transfusions in clinical settings and enhance patient safety within the hospital by swiftly and conveniently visualizing vast amounts of data.

Background: Transfusion appropriateness is extremely important due to the growing concerns about the decrease in the supply of blood products and the increase in demand. Considerable time and effort are required to effectively collect and analyze large volumes of data. Therefore, we aimed to develop a transfusion appropriateness management program using the Tableau visual analytics platform, which allows intuitive visualization through various visualization options and interactive features and can quickly process large volumes of data. Methods: Using the transfusion prescription history and blood management and distribution history, we created a data mart comprising patient information, hospitalization history, inpatient/outpatient prescriptions, test results, records, and surgical information. Based on this we developed visualization analysis content for monitoring transfusion appropriateness.We automated the periodic aggregation of the data mart into an analysis database and connected it to Tableau. Results: We developed Transfusion Appropriateness Management (TAM), a program for managing transfusion appropriateness linked to Tableau, after analyzing transfusion-related data and metadata extracted from the Daejeon Eulji Medical Center's order communication system/electronic medical record (OCS/EMR) system. Detailed filters were applied to allow users to intuitively view the desired data according to their criteria. Data were visualized in various forms, such as bar graphs, heat maps, and box plots based on filtering criteria. Conclusion The development of the Transfusion Appropriateness Management program at the Daejeon Eulji Medical Center is expected to effectively reduce inappropriate transfusions in clinical settings and enhance patient safety within the hospital by swiftly and conveniently visualizing vast amounts of data.

Background: Transfusion appropriateness is extremely important due to the growing concerns about the decrease in the supply of blood products and the increase in demand. Considerable time and effort are required to effectively collect and analyze large volumes of data. Therefore, we aimed to develop a transfusion appropriateness management program using the Tableau visual analytics platform, which allows intuitive visualization through various visualization options and interactive features and can quickly process large volumes of data. Methods: Using the transfusion prescription history and blood management and distribution history, we created a data mart comprising patient information, hospitalization history, inpatient/outpatient prescriptions, test results, records, and surgical information. Based on this we developed visualization analysis content for monitoring transfusion appropriateness.We automated the periodic aggregation of the data mart into an analysis database and connected it to Tableau. Results: We developed Transfusion Appropriateness Management (TAM), a program for managing transfusion appropriateness linked to Tableau, after analyzing transfusion-related data and metadata extracted from the Daejeon Eulji Medical Center's order communication system/electronic medical record (OCS/EMR) system. Detailed filters were applied to allow users to intuitively view the desired data according to their criteria. Data were visualized in various forms, such as bar graphs, heat maps, and box plots based on filtering criteria. Conclusion The development of the Transfusion Appropriateness Management program at the Daejeon Eulji Medical Center is expected to effectively reduce inappropriate transfusions in clinical settings and enhance patient safety within the hospital by swiftly and conveniently visualizing vast amounts of data.

Gene Expression Omnibus (GEO) has kept the largest amount of gene-expression microarray data that have grown exponentially. Microarray data in GEO have been generated in many different formats and often lack standardized annotation and documentation. It is hard to know if preprocessing has been applied to a dataset or not and in what way. Standard-based integration of heterogeneous data formats and metadata is necessary for comprehensive data query, analysis and mining. We attempted to integrate the heterogeneous microarray data in GEO based on Minimum Information About a Microarray Experiment (MIAME) standard. We unified the data fields of GEO Data table and mapped the attributes of GEO metadata into MIAME elements. We also discriminated non-preprocessed raw datasets from others and processed ones by using a two-step classification method. Most of the procedures were developed as semi-automated algorithms with some degree of text mining techniques. We localized 2,967 Platforms, 4,867 Series and 103,590 Samples with covering 279 organisms, integrated them into a standard-based relational schema and developed a comprehensive query interface to extract. Our tool, GEOQuest is available at http://www.snubi.org/software/GEOQuest/
Data Mining ; DNA ; Gene Expression ; Mining ; Oligonucleotide Array Sequence Analysis

OBJECTIVES: We examined the associations of socioeconomic factors, health behaviors, and comorbidities with early-onset lung cancer. METHODS: The study included 6,794,287 individuals aged 20-39 years who participated in a Korean national health check-up program from 2009 to 2012. During the follow-up period, 4,684 participants developed lung cancer. Multivariable Cox regression analysis was used to estimate the independent associations of potential risk factors with incident lung cancer. RESULTS: Older age (multivariable hazard ratio [mHR], 1.13; 95% confidence interval [CI], 1.12 to 1.14) and female sex (mHR, 1.62; 95% CI, 1.49 to 1.75) were associated with increased lung cancer risk. Current smoking was also associated with elevated risk (<10 pack-years: mHR, 1.12; 95% CI, 1.01 to 1.24; ≥10 pack-years: mHR, 1.30; 95% CI, 1.18 to 1.45), but past smoking was not. Although mild alcohol consumption (<10 g/day) was associated with lower lung cancer risk (mHR, 0.92; 95% CI, 0.86 to 0.99), heavier alcohol consumption (≥10 g/day) was not. Higher income (highest vs. lowest quartile: mHR, 0.86; 95% CI, 0.78 to 0.94), physical activity for at least 1,500 metabolic equivalent of task-min/wk (vs. non-exercisers: mHR, 0.83; 95% CI, 0.69 to 0.99) and obesity (vs. normal weight: mHR, 0.89; 95% CI, 0.83 to 0.96) were associated with lower lung cancer risk, whereas metabolic syndrome was associated with increased risk (mHR, 1.13; 95% CI, 1.03 to 1.24). CONCLUSIONS In young adults, age, female sex, smoking, and metabolic syndrome were risk factors for early-onset lung cancer, while high income, physical activity, and obesity displayed protective effects.

Background and Objectives: Stem cell therapy is a promising strategy for treating neurological diseases but its effectiveness is influenced by the route of administration and the characteristics of the stem cells. We determined whether neural induction of mesenchymal stem cells (MSCs) was beneficial when the cells were delivered intra-arterially through the carotid artery. Methods: and Results: MSCs were neurally induced using a retroviral vector expressing the neurogenic transcription factor neurogenin-1 (Ngn1). The LacZ gene encoding bacterial β-galactosidase was used as a control. Ischemic stroke was induced by transluminal occlusion of the middle cerebral artery and 3 days later the MSCs were delivered intra- arterially through the internal carotid artery. Magnetic resonance imaging analysis indicated that compared to MSCs expressing LacZ (MSCs/LacZ), MSCs expressing Ngn1 (MSCs/Ngn1) exhibited increased recruitment to the ischemic region and populated this area for a longer duration. Immunohistochemical analysis indicated that compared to MSCs/LacZ, MSCs/Ngn1 more effectively alleviated neurological dysfunction by blocking secondary damage associated with neuronal cell death and brain inflammation. Microarray and real-time PCR analysis indicated that MSCs/Ngn1 exhibited increased expression of chemotactic cytokine receptors, adherence to endothelial cells, and migration ability. Conclusions Neural induction with Ngn1 increases the homing ability of MSCs, enhancing their engraftment efficiency in the ischemic rat brain. Intra-arterial delivery of neurally induced MSCs/Ngn1 3 days after ischemic injury blocks neuronal cell death and inflammation, and improves functional recovery. Thus, intra-arterial administration of stem cells with neural properties may be a novel therapy for the treatment of ischemic stroke.

Purpose: We evaluated the efficacy and safety of avelumab, an anti-PD-L1 antibody, in patients with metastatic or unresectable colorectal cancer (mCRC) with mismatch repair deficiency (dMMR)/microsatellite instability-high (MSI-H) or POLE mutations. Materials and Methods: In this prospective, open-label, multicenter phase II study, 33 patients with mCRC harboring dMMR/MSI-H or POLE mutations after failure of ≥1st-line chemotherapy received avelumab 10 mg/kg every 2 weeks. dMMR/MSI-H was confirmed with immunohistochemical staining (IHC) by loss of expression of MMR proteins or polymerase chain reaction (PCR) for microsatellite sequences. POLE mutation was confirmed by next-generation sequencing (NGS). The primary endpoint was the objective response rate (ORR) by Response Evaluation Criteria in Solid Tumors ver. 1.1. Results: The median age was 60 years, and 78.8% were male. Thirty patients were dMMR/MSI-H and three had POLE mutations. The ORR was 24.2%, and all of the responders were dMMR/MSI-H. For 21 patients with MSI-H by PCR or NGS, the ORR was 28.6%. At a median follow-up duration of 16.3 months, median progression-free survival and overall survival were 3.9 and 13.2 months in all patients, and 8.1 months and not reached, respectively, in patients with MSI-H by PCR or NGS. Dose interruption and discontinuation due to treatment-related adverse events occurred in 4 and 2 patients, respectively, with no treatment-related deaths. Conclusion Avelumab displayed antitumor activity with manageable toxicity in patients with previously treated mCRC harboring dMMR/MSI-H. Diagnosis of dMMR/MSI-H with PCR or NGS could be complementary to IHC to select patients who would benefit from immunotherapy.