Sungjoon Park

Processing of partial video data for detection of wipes

With the currently existing shot change detection algorithms, abrupt changes are detected fairly well. It is thus more challenging to detect gradual changes, including fades, dissolves, and wipes, as these are often missed or falsely detected. In this paper, we focus on the detection of wipes. The proposed algorithm begins by processing the visual rhythm, a portion of the DC image sequence. It is a single image, a sub-sampled version of a full video, in which the sampling is performed in a predetermined and systematic fashion. The visual rhythm contains distinctive patterns or visual features for many different types of video effects. The different video effects manifest themselves differently on the visual rhythm. In particular, wipes appear as curves, which run from the top to the bottom of the visual rhythm. Thus, using the visual rhythm, it becomes possible to automatically detect wipes, simply by determining various lines and curves on the visual rhythm.

Preoperative and Postoperative Comparisons of Navigation and Radiologic Limb Alignment Measurements After High Tibial Osteotomy

PURPOSEnTo determine whether navigation-assisted intraoperative lower limb alignment in open wedge high tibial osteotomy (HTO) correlates with preoperative and postoperative radiographic alignment.nnnMETHODSnThis prospective study involved 35 patients (39 knees) who underwent navigation HTO for primary medial osteoarthritis. The mechanical axis (MA) and weight-bearing line (WBL) ratio were calculated from preoperative radiographs, intraoperative navigation, and postoperative (6 months) radiographs. Reliability between navigation and radiographic alignment was analyzed by use of intraclass correlation coefficients (ICCs) with thresholds as follows: good, greater than 0.75; fair, 0.4 to 0.75; and poor, less than 0.4. The surgical target for the MA was a final valgus overcorrection of 2° to 8°, and the WBL ratio target was between 50% and 70%. Outliers for differences between intraoperative navigation and postoperative radiographic results were defined as greater than ±3° for the MA and greater than ±10% for the WBL ratio.nnnRESULTSnThe MA target was achieved in 33 of 39 knees (84.6%), and the WBL ratio target was achieved in 30 of 39 knees (74.4%). ICCs for navigational reliability were good for preoperative MA and WBL ratio and fair for postoperative MA and WBL ratio. The ICCs for the MA were better than those for the WBL ratio for both preoperative and postoperative measurements. The differences between the number of outliers between the navigation and radiographic MA and WBL were greater postoperatively than preoperatively. In addition, the postoperative differences in the extent of the outliers between navigation and radiographic measurements were greater for WBL ratios than the MA (P = .023).nnnCONCLUSIONSnThis study found that use of a navigation system achieved the target value for MA lower limb correction in over 80% of open wedge HTO cases, using radiographic data as the gold standard for alignment. Because the navigational measurements of lower limbs during open wedge HTO did not correlate with postoperative radiographic alignment, corrections should not be based solely on navigational results. In assessing the reliability of navigational open wedge HTO for correction of lower limb alignment, the MA is a better radiologic parameter than the WBL ratio.nnnLEVEL OF EVIDENCEnLevel IV, therapeutic case series.

Control of adsorption and alignment of V2O5 nanowires via chemically functionalized patterns

We developed a method to precisely control the locations and orientations of deposited divanadium pentoxide (V2O5) nanowires on SiO2 surfaces using chemically functionalized patterns. The nanowires were deposited onto the substrates either from solution or via the edge transfer mechanism of micro-contact printing. In both cases, negatively charged V2O5 nanowires showed a strong adsorption selectivity onto 3-aminopropyltriethoxysilane (APS) self-assembled monolayers (SAMs) with positively charged functional groups, whereas the SAMs with non-polar and neutral terminal groups of octadecyltrichlorosilane (OTS) worked as perfect passivation layers. In particular, directional alignment of nanowires inside the chemically patterned area, depending upon the shapes of the patterns, was observed. The wires were aligned along the long axis of the pattern when the width of the APS pattern was as small as 1xa0µm. This strategy allows us to control the adsorption and alignment of V2O5 nanowires on the substrates, which could be used for various nano-device applications such as interconnection of electronic circuits.

Controlled direct patterning of V2O5 nanowires onto SiO2 substrates by a microcontact printing technique

Vanadium pentoxide (V2O5) nanowires were directly transferred to desired patterns on SiO2 substrates using the microcontact printing (MCP) technique. The hydrophilicity of the poly(dimethylsiloxane) (PDMS) stamp exerted a strong influence on the mechanism of transfer of polar V2O5 nanowires onto the substrate. The V2O5 nanowires were transferred from the relief side of the hydrophilic stamp, whereas they were transferred from the recess edges of the hydrophobic one forming agglomerated nanowire patterns on the substrate. When the hydrophobic stamp was used, the width of the agglomerated nanowire patterns could be controlled by the concentration of the nanowire solution as well as by the width of the recess area of the PDMS stamp. This method allows us to generate nanowire patterns with a submicrometre line width, which is much smaller than a the few-micrometre sizes of PDMS stamp patterns. When the hydrophilic stamp with a small-sized (≤ the average length of V2O5 nanowires) pattern was used, alignment of individual nanowires in the direction of the boundary of the line pattern was obtained. These results suggest that the transfer mechanism in the MCP process strongly depends on the wetting interaction between the stamp and the nanowire ink.

Spontaneous Late Dissociation of the Tibial Insert After High-Flex Posterior-Stabilized Genesis II Total Knee Arthroplasty

We report a rare complication of spontaneous late dissociation of the tibial insert 2 years after total knee arthroplasty using a high-flex posterior-stabilized Genesis II prosthesis (Smith & Nephew, Memphis, Tenn). It appears that 2 factors may have contributed to dissociation, namely, incomplete seating of the insert and the design of the prosthesis, which involves a shallow anterior tab snap-fit locking mechanism and thin dovetail lips.

BRONCO: Biomedical entity Relation ONcology COrpus for extracting gene-variant-disease-drug relations

Comprehensive knowledge of genomic variants in a biological context is key for precision medicine. As next-generation sequencing technologies improve, the amount of literature containing genomic variant data, such as new functions or related phenotypes, rapidly increases. Because numerous articles are published every day, it is almost impossible to manually curate all the variant information from the literature. Many researchers focus on creating an improved automated biomedical natural language processing (BioNLP) method that extracts useful variants and their functional information from the literature. However, there is no gold-standard data set that contains texts annotated with variants and their related functions. To overcome these limitations, we introduce a Biomedical entity Relation ONcology COrpus (BRONCO) that contains more than 400 variants and their relations with genes, diseases, drugs and cell lines in the context of cancer and anti-tumor drug screening research. The variants and their relations were manually extracted from 108 full-text articles. BRONCO can be utilized to evaluate and train new methods used for extracting biomedical entity relations from full-text publications, and thus be a valuable resource to the biomedical text mining research community. Using BRONCO, we quantitatively and qualitatively evaluated the performance of three state-of-the-art BioNLP methods. We also identified their shortcomings, and suggested remedies for each method. We implemented post-processing modules for the three BioNLP methods, which improved their performance. Database URL: http://infos.korea.ac.kr/bronco

Percolation network of growing V2O5 nanowires

Percolation network of the growing V2O5 nanowires was demonstrated by devising a simple but practical method to investigate the percolation phenomena. As the reaction proceeded in the ammonium(meta)vanadate solution at room temperature, the lengths of V2O5 nanowires increased at a speed of 0.13μm∕day at an early stage of the growth and 0.03μm∕day on the average up to 3 months. Percolation network was made by abruptly freezing the homogeneously dispersed aqueous solutions of V2O5 nanowires in liquid nitrogen. After 7h of aging time, an abrupt increase of the conductance was observed, revealing the satisfaction of the percolation threshold (pc∼0.17) at the average wire length of 40nm.

Structural Studies of V2O5 Nanowires by Ultrahigh Vacuum-Scanning Tunneling Microscope and Atomic Force Microscope

We have investigated the structures and electronic properties of vanadium pentoxide (V2O5) nanowires synthesized by a sol–gel process. The time-dependent evolution of the V2O5 nanowires at different temperatures was systematically studied by atomic force microscopy. The structural dimension and the current–voltage (I–V) characteristics were measured by scanning tunneling microscopy/spectroscopy. V2O5 nanowires with a cross section of 10×1.5 nm2, whose length varied with the duration time in sol, were synthesized. The V2O5 nanowires adsorbed on a self-assembled monolayer of aminothiophenol (ATP) on a Au(111)/mica substrate showed semiconducting I–V characteristics. The height of the V2O5 nanowires decreased from 1.5 to 0.8 nm with prolonged annealing at temperatures above 100 °C, implying the existence of a water interlayer in the V2O5 double-layer structure.

Deep learning of mutation-gene-drug relations from the literature

BackgroundMolecular biomarkers that can predict drug efficacy in cancer patients are crucial components for the advancement of precision medicine. However, identifying these molecular biomarkers remains a laborious and challenging task. Next-generation sequencing of patients and preclinical models have increasingly led to the identification of novel gene-mutation-drug relations, and these results have been reported and published in the scientific literature.ResultsHere, we present two new computational methods that utilize all the PubMed articles as domain specific background knowledge to assist in the extraction and curation of gene-mutation-drug relations from the literature. The first method uses the Biomedical Entity Search Tool (BEST) scoring results as some of the features to train the machine learning classifiers. The second method uses not only the BEST scoring results, but also word vectors in a deep convolutional neural network model that are constructed from and trained on numerous documents such as PubMed abstracts and Google News articles. Using the features obtained from both the BEST search engine scores and word vectors, we extract mutation-gene and mutation-drug relations from the literature using machine learning classifiers such as random forest and deep convolutional neural networks.Our methods achieved better results compared with the state-of-the-art methods. We used our proposed features in a simple machine learning model, and obtained F1-scores of 0.96 and 0.82 for mutation-gene and mutation-drug relation classification, respectively. We also developed a deep learning classification model using convolutional neural networks, BEST scores, and the word embeddings that are pre-trained on PubMed or Google News data. Using deep learning, the classification accuracy improved, and F1-scores of 0.96 and 0.86 were obtained for the mutation-gene and mutation-drug relations, respectively.ConclusionWe believe that our computational methods described in this research could be used as an important tool in identifying molecular biomarkers that predict drug responses in cancer patients. We also built a database of these mutation-gene-drug relations that were extracted from all the PubMed abstracts. We believe that our database can prove to be a valuable resource for precision medicine researchers.

BTNET : boosted tree based gene regulatory network inference algorithm using time-course measurement data

BackgroundIdentifying gene regulatory networks is an important task for understanding biological systems. Time-course measurement data became a valuable resource for inferring gene regulatory networks. Various methods have been presented for reconstructing the networks from time-course measurement data. However, existing methods have been validated on only a limited number of benchmark datasets, and rarely verified on real biological systems.ResultsWe first integrated benchmark time-course gene expression datasets from previous studies and reassessed the baseline methods. We observed that GENIE3-time, a tree-based ensemble method, achieved the best performance among the baselines. In this study, we introduce BTNET, a boosted tree based gene regulatory network inference algorithm which improves the state-of-the-art. We quantitatively validated BTNET on the integrated benchmark dataset. The AUROC and AUPR scores of BTNET were higher than those of the baselines. We also qualitatively validated the results of BTNET through an experiment on neuroblastoma cells treated with an antidepressant. The inferred regulatory network from BTNET showed that brachyury, a transcription factor, was regulated by fluoxetine, an antidepressant, which was verified by the expression of its downstream genes.ConclusionsWe present BTENT that infers a GRN from time-course measurement data using boosting algorithms. Our model achieved the highest AUROC and AUPR scores on the integrated benchmark dataset. We further validated BTNET qualitatively through a wet-lab experiment and showed that BTNET can produce biologically meaningful results.