Electrospun fibrous tissue engineering scaffolds: topographic cues and their influence on cell behavior

Theme of Conference: Research and Regulatory in Biomedical Engineering - Session B: Best Young Engineer's Paper Competitionpublished_or_final_versionThe International Conference and Pre-conference Workshop of Biomedical Engineering (BME2010), Hong Kong, China, 2-5 November 2010. In Proceedings of BME2010, 2010, p. B-

Electrospinning, characterization and in vitro biological evaluation of nanocomposite fibers containing carbonated hydroxyapatite nanoparticles

Poly(hydroxybutyrate-co-hydroxyvalerate) (PHBV) fibers containing carbonated hydroxyapatite (CHA) nanoparticles with different CHA amounts (5, 10 and 15 wt%) were electrospun with the aid of ultrasonic power for dispersing the nanoparticles. Scanning electron microscopy and energy-dispersive x-ray spectroscopy results showed that the distribution of CHA within the CHA/PHBV nanocomposite fibers was homogeneous when the CHA content was 10 wt%. Slight particle agglomeration occurred when the CHA content was 15 wt%. The diameters of the electrospun CHA/PHBV nanocomposite fibers and PHBV polymer fibers were around 3 μm. Fourier transform infrared spectroscopic analysis further confirmed the presence of CHA in CHA/PHBV nanocomposite fibers. Both PHBV and CHA/PHBV fibrous membranes exhibited similar tensile properties. Compared with PHBV solvent-cast film, the PHBV fibrous membrane was hydrophobic but the incorporation of CHA nanoparticles dramatically enhanced its wettability. In vitro studies revealed that both types of electrospun fibrous membranes (PHBV and CHA/PHBV) supported the proliferation of human osteoblastic cells (SaOS-2). The alkaline phosphatase activity of SaOS-2 cells seeded on the CHA/PHBV fibrous membranes was higher than that of the cells seeded on the PHBV fibrous membranes after 14 days of cell culture. The electrospun CHA/PHBV nanocomposite fibrous membranes show promises for bone tissue engineering applications. © 2010 IOP Publishing Ltd.postprin

Probabilistic segmentation of volume data for visualization using SOM-PNN classifier

We present a new probabilistic classifier, called SOM-PNN classifier, for volume data classification and visualization. The new classifier produces probabilistic classification with Bayesian confidence measure which is highly desirable in volume rendering. Based on the SOM map trained with a large training data set, our SOM-PNN classifier performs the probabilistic classification using the PNN algorithm. This combined use of SOM and PNN overcomes the shortcomings of the parametric methods, the nonparametric methods, and the SOM method. The proposed SOM-PNN classifier has been used to segment the CT sloth data and the 20 human MRI brain volumes resulting in much more informative 3D rendering with more details and less artifacts than other methods. Numerical comparisons demonstrate that the SOM-PNN classifier is a fast, accurate and probabilistic classifier for volume rendering.published_or_final_versio

BCI-FES training system design and implementation for rehabilitation of stroke patients

Author name used in this publication: Kai-yu TongAuthor name used in this publication: Suk-tak ChanRefereed conference paper2007-2008 > Academic research: refereed > Refereed conference paperVersion of RecordPublishe

Cerebral plasticity after subcortical stroke as revealed by cortico-muscular coherence

Author name used in this publication: Kai-Yu TongAuthor name used in this publication: Suk-Tak Chan2008-2009 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Anode modification of polyfluorene-based polymer light-emitting devices

A glycerol-modified poly(3,4-ethylene dioxythiophene) (PEDOT): poly(styrene sulfonate) (PSS) layer was used as an anode buffer layer in polymer light-emitting devices using poly(9,9-dioctylfluorene) (F8) as the emitter. Devices with a configuration of indium tin oxide/PEDOT:PSS (with or without glycerol)/F8/CsF/Al were fabricated. It was found that the glycerol-modified device showed a much larger current density than the unmodified device. At an operating voltage of 6 V, the glycerol-modified device showed a luminance of 1300Cd/m 2 and a current efficiency of 1.7 Cd/A compared to the corresponding values of 500Cd/m 2 and 1.3 Cd/A in the unmodified device. Analysis by ultraviolet spectroscopy suggests that the two devices have the same energy level structure and the performance improvement should not be due to change in the PEDOT/polymer interface. It was further found that incorporating a suitable amount of glycerol into the PEDOT:PSS layer can increase its conductivity by six times. This leads to a better balance in the hole and electron currents and thus improved device efficiency. © 2002 American Institute of Physics.published_or_final_versio

Anticancer Gene Transfer for Cancer Gene Therapy

Gene therapy vectors are among the treatments currently used to treat malignant tumors. Gene therapy vectors use a specific therapeutic transgene that causes death in cancer cells. In early attempts at gene therapy, therapeutic transgenes were driven by non-specific vectors which induced toxicity to normal cells in addition to the cancer cells. Recently, novel cancer specific viral vectors have been developed that target cancer cells leaving normal cells unharmed. Here we review such cancer specific gene therapy systems currently used in the treatment of cancer and discuss the major challenges and future directions in this field

A UMLS-based spell checker for natural language processing in vaccine safety

BACKGROUND: The Institute of Medicine has identified patient safety as a key goal for health care in the United States. Detecting vaccine adverse events is an important public health activity that contributes to patient safety. Reports about adverse events following immunization (AEFI) from surveillance systems contain free-text components that can be analyzed using natural language processing. To extract Unified Medical Language System (UMLS) concepts from free text and classify AEFI reports based on concepts they contain, we first needed to clean the text by expanding abbreviations and shortcuts and correcting spelling errors. Our objective in this paper was to create a UMLS-based spelling error correction tool as a first step in the natural language processing (NLP) pipeline for AEFI reports. METHODS: We developed spell checking algorithms using open source tools. We used de-identified AEFI surveillance reports to create free-text data sets for analysis. After expansion of abbreviated clinical terms and shortcuts, we performed spelling correction in four steps: (1) error detection, (2) word list generation, (3) word list disambiguation and (4) error correction. We then measured the performance of the resulting spell checker by comparing it to manual correction. RESULTS: We used 12,056 words to train the spell checker and tested its performance on 8,131 words. During testing, sensitivity, specificity, and positive predictive value (PPV) for the spell checker were 74% (95% CI: 74–75), 100% (95% CI: 100–100), and 47% (95% CI: 46%–48%), respectively. CONCLUSION: We created a prototype spell checker that can be used to process AEFI reports. We used the UMLS Specialist Lexicon as the primary source of dictionary terms and the WordNet lexicon as a secondary source. We used the UMLS as a domain-specific source of dictionary terms to compare potentially misspelled words in the corpus. The prototype sensitivity was comparable to currently available tools, but the specificity was much superior. The slow processing speed may be improved by trimming it down to the most useful component algorithms. Other investigators may find the methods we developed useful for cleaning text using lexicons specific to their area of interest

Isolates of Liao Ning Virus from Wild-Caught Mosquitoes in the Xinjiang Province of China in 2005

Liao ning virus (LNV) is related to Banna virus, a known human-pathogen present in south-east Asia. Both viruses belong to the genus Seadornavirus, family Reoviridae. LNV causes lethal haemorrhage in experimentally infected mice. Twenty seven isolates of LNV were made from mosquitoes collected in different locations within the Xinjiang province of north-western China during 2005. These mosquitoes were caught in the accommodation of human patients with febrile manifestations, or in animal barns where sheep represent the main livestock species. The regions where LNV was isolated are affected by seasonal encephalitis, but are free of Japanese encephalitis (JE). Genome segment 10 (Seg-10) (encoding cell-attachment and serotype-determining protein VP10) and Seg-12 (encoding non-structural protein VP12) were sequenced for multiple LNV isolates. Phylogenetic analyses showed a less homogenous Seg-10 gene pool, as compared to segment 12. However, all of these isolates appear to belong to LNV type-1. These data suggest a relatively recent introduction of LNV into Xinjiang province, with substitution rates for LNV Seg-10 and Seg-12, respectively, of 2.29×10−4 and 1.57×10−4 substitutions/nt/year. These substitution rates are similar to those estimated for other dsRNA viruses. Our data indicate that the history of LNV is characterized by a lack of demographic fluctuations. However, a decline in the LNV population in the late 1980s - early 1990s, was indicated by data for both Seg-10 and Seg-12. Data also suggest a beginning of an expansion in the late 1990s as inferred from Seg-12 skyline plot