Showing papers by "Tongji University published in 2005"

Electrospinning of gelatin fibers and gelatin/PCL composite fibrous scaffolds.

Abstract: In this article, ultrafine gelatin (Gt) fibers were successfully produced with the use of the electrical spinning or electrospinning technique. A fluorinated alcohol of 2,2,2-trifluoroethanol (TFE) was used as the dissolving solvent. The morphology of the electrospun gelatin fibers was found to be dependent on the alteration of gelatin concentration ranging from 2.5% w/v to 12.5% w/v at 2.5% increment intervals. Based on the electrospun gelatin fibers obtained, 10% w/v gelatin/TFE solution was selected and mixed with 10% w/v poly(epsilon-caprolactone) (PCL) in TFE at a ratio of 50:50 and co-electrospun to produce gelatin/PCL composite membranes. Contact-angle measurement and tensile tests indicated that the gelatin/PCL complex fibrous membrane exhibited improved mechanical properties as well as more favorable wettability than that obtained from either gelatin or PCL alone. The gelatin/PCL fibrous membranes were further investigated as a promising scaffold for bone-marrow stromal cell (BMSC) culture. Scanning electron microscopy (SEM) and laser confocal microscopy observations showed that the cells could not only favorably attach and grow well on the surface of these scaffolds, but were also able to migrate inside the scaffold up to 114 microm within 1 week of culture. These results suggest the potential of using composite gelatin/PCL fibrous scaffolds for engineering three-dimensional tissues.

Recent development of polymer nanofibers for biomedical and biotechnological applications.

Abstract: Research in polymer nanofibers has undergone significant progress in the last one decade. One of the main driving forces for this progress is the increasing use of these polymer nanofibers for biomedical and biotechnological applications. This article presents a review on the latest research advancement made in the use of polymer nanofibers for applications such as tissue engineering, controlled drug release, wound dressings, medical implants, nanocomposites for dental restoration, molecular separation, biosensors, and preservation of bioactive agents.

Characterization and source apportionment of atmospheric organic and elemental carbon during fall and winter of 2003 in Xi'an, China

Abstract: . Continuous measurements of atmospheric organic and elemental carbon (OC and EC) were taken during the high-pollution fall and winter seasons at Xi'an, Shaanxi Province, China from September 2003 through February 2004. Battery-powered mini-volume samplers collected PM2.5 samples daily and PM10 samples every third day. Samples were also obtained from the plumes of residential coal combustion, motor-vehicle exhaust, and biomass burning sources. These samples were analyzed for OC/EC by thermal/optical reflectance (TOR) following the Interagency Monitoring of Protected Visual Environments (IMPROVE) protocol. OC and EC levels at Xi'an are higher than most urban cities in Asia. Average PM2.5 OC concentrations in fall and winter were 34.1±18.0 μg m−3 and 61.9±;33.2 μg m−3, respectively; while EC concentrations were 11.3±6.9 μg m−3 and 12.3±5.3 μg m−3, respectively. Most of the OC and EC were in the PM2.5 fraction. OC was strongly correlated (R>0.95) with EC in the autumn and moderately correlated (R=0.81) with EC during winter. Carbonaceous aerosol (OC×1.6+EC) accounted for 48.8%±10.1% of the PM2.5 mass during fall and 45.9±7.5% during winter. The average OC/EC ratio was 3.3 in fall and 5.1 in winter, with individual OC/EC ratios nearly always exceeding 2.0. The higher wintertime OC/EC corresponded to increased residential coal combustion for heating. Total carbon (TC) was associated with source contributions using absolute principal component analysis (APCA) with eight thermally-derived carbon fractions. During fall, 73% of TC was attributed to gasoline engine exhaust, 23% to diesel exhaust, and 4% to biomass burning. During winter, 44% of TC was attributed to gasoline engine exhaust, 44% to coal burning, 9% to biomass burning, and 3% to diesel engine exhaust.

Synergistic antibacterial effects of β-lactam antibiotic combined with silver nanoparticles

Abstract: The bactericidal action of silver (0) nanoparticles and amoxicillin on Escherichia coli is studied, respectively Increasing concentration of both amoxicillin (0–0525 mg ml−1) and silver nanoparticles (0–40 µg ml−1) showed a higher antibacterial effect in Luria–Bertani (LB) medium Escherichia coli cells have different bactericidal sensitivity to them When amoxicillin and silver nanoparticles are combined, it results in greater bactericidal efficiency on Escherichia coli cells than when they were applied separately Dynamic tests on bacterial growth indicated that exponential and stationary phases are greatly decreased and delayed in the synergistic effect of amoxicillin and silver nanoparticles In addition, the effect induced by a preincubation with silver nanoparticles is examined The results show that solutions with more silver nanoparticles have better antimicrobial effects One hypothesized mechanism is proposed to explain this phenomenon

Nuclear or cytoplasmic expression of survivin: what is the significance?

Abstract: Growing evidence suggests that survivin expression in cancer cell nuclei may represent an important prognostic marker to predict disease outcome for cancer patients. Current reports in this research area, however, are inconsistent and propose opposing conclusions regarding the significance and prognostic value of survivin nuclear expression. The aim of our study is to review and discuss the data reported in the original publications. We have also provided new experimental data to support our view regarding the possible reasons for the observed inconsistencies in the literature. This would alert researchers to pay attention to potential pitfalls in the determination of nuclear or cytoplasmic expression of survivin for the future.

Shelter location-allocation model for flood evacuation planning

Abstract: The optimal shelter locations for the flood evacuation planning are studied in this paper. We assume that the authority can control the traffic in certain part of the network while the evacuees choose which shelter to go and by which route. The shelter location problem is posed as a Stackelberg game, consisting of the leader (authority) determining the shelter locations to minimize the total evacuation time and the follower (evacuees) choosing the destination (shelter) and route to evacuate. The problem is formulated as a bi-level programming. The upper level problem is a location problem that models the authority's decision. A combined distribution and assignment (CDA) model is proposed to model the evacuees' decision as the lower level problem. In this study, the bi-level programming problem is solved using genetic algorithm. Numerical example with a real world network is given to demonstrate the application of the proposed model.

Structural features and molecular evolution of Bowman-Birk protease inhibitors and their potential application.

Abstract: The Bowman-Birk inhibitors (BBIs) are well-studied serine protease inhibitors that are abundant in dicotyledonous and monocotyledonous plants. BBIs from dicots usually have a molecular weight of 8k and are double-headed with two reactive sites, whereas those from monocots can be divided into two classes, one approximately 8 kDa in size with one reactive site (another reactive site was lost) and the other approximately 16 kDa in size with two reactive sites. The reactive site is located at unique exposed surfaces formed by a disulfide-linked beta-sheet loop that is highly conserved, rigid and mostly composed of nine residues. The structural features and molecular evolution of inhibitors are described, focusing on the conserved disulfide bridges. The sunflower trypsin inhibitor-1 (SFTI-1), with 14 amino acid residues, is a recently discovered bicyclic inhibitor, and is the most small and potent naturally occurring Bowman-Birk inhibitor. Recently, BBIs have become a hot topic because of their potential applications. BBIs are now used for defense against pathogens and insects in transgenic plants, which has advantages over using toxic and polluting insecticides. BBIs could also be applied in the prevention of cancer, Dengue fever, and inflammatory and allergic disorders, because of their inhibitory activity with respect to the serine proteases that play a pivotal role in the development and pathogenesis of these diseases. The canonical nine-residue loop of BBIs/STFI-1 provides an ideal template for drug design of specific inhibitors to target their respective proteases.

One-year record of organic and elemental carbon in fine particles in downtown Beijing and Shanghai

Abstract: . Weekly PM2.5 samples were collected for one year (1999-2000) in Beijing and Shanghai and the carbonaceous species analyzed to investigate and compare their time series patterns and possible sources in the two biggest cities of China. Weekly carbonaceous concentrations varied in wide ranges with 8.6-59µg m-3 for OC and 1.5-25.4µg m-3 for EC in Beijing, and with 5.1-38.4µg m-3 for OC and 2.3-13.0µg m-3 for EC in Shanghai. Similar weekly and seasonal variations of OC and EC concentrations were found in each city though major combustion sources presented source-dependent emission characteristics and seasonal differences in emission amount for carbonaceous species. Both OC and EC maintained much higher concentrations in late fall through winter, probably due to enhanced emissions coupled with unfavorable meteorological conditions. In Beijing, the 14C analysis of limited samples suggested there was a significant contribution (33-48%) of modern carbon to the total fine carbonaceous PM burden with higher fractions in the harvest seasons. The high mass ratios of excessive potassium to EC in both Beijing and Shanghai also indicated that biomass burning had important contribution to fine carbonaceous particles.

Towards precise classification of cancers based on robust gene functional expression profiles

Abstract: Development of robust and efficient methods for analyzing and interpreting high dimension gene expression profiles continues to be a focus in computational biology. The accumulated experiment evidence supports the assumption that genes express and perform their functions in modular fashions in cells. Therefore, there is an open space for development of the timely and relevant computational algorithms that use robust functional expression profiles towards precise classification of complex human diseases at the modular level. Inspired by the insight that genes act as a module to carry out a highly integrated cellular function, we thus define a low dimension functional expression profile for data reduction. After annotating each individual gene to functional categories defined in a proper gene function classification system such as Gene Ontology applied in this study, we identify those functional categories enriched with differentially expressed genes. For each functional category or functional module, we compute a summary measure (s) for the raw expression values of the annotated genes to capture the overall activity level of the module. In this way, we can treat the gene expressions within a functional module as an integrative data point to replace the multiple values of individual genes. We compare the classification performance of decision trees based on functional expression profiles with the conventional gene expression profiles using four publicly available datasets, which indicates that precise classification of tumour types and improved interpretation can be achieved with the reduced functional expression profiles. This modular approach is demonstrated to be a powerful alternative approach to analyzing high dimension microarray data and is robust to high measurement noise and intrinsic biological variance inherent in microarray data. Furthermore, efficient integration with current biological knowledge has facilitated the interpretation of the underlying molecular mechanisms for complex human diseases at the modular level.

Steganalysis based on multiple features formed by statistical moments of wavelet characteristic functions

Abstract: In this paper, a steganalysis scheme based on multiple features formed by statistical moments of wavelet characteristic functions is proposed. Our theoretical analysis has pointed out that the defined n-th statistical moment of a wavelet characteristic function is related to the n-th derivative of the corresponding wavelet histogram, and hence is sensitive to data embedding. The selection of the first three moments of the characteristic functions of wavelet subbands of the three-level Haar wavelet decomposition as well as the test image has resulted in total 39 features for steganalysis. The effectiveness of the proposed system has been demonstrated by extensive experimental investigation. The detection rate for Cox et al.'s non-blind spread spectrum (SS) data hiding method, Piva et al.'s blind SS method, Huang and Shi's 8×8 block SS method, a generic LSB method (as embedding capacity being 0.3 bpp), and a generic QIM method (as embedding capacity being 0.1 bpp) are all above 90% over all of the 1096 images in the CorelDraw image database using the Bayes classifier. Furthermore, when these five typical data hiding methods are jointly considered for steganalysis, i.e., when the proposed steganalysis scheme is first trained sequentially for each of these five methods, and is then tested blindly for stego-images generated by all of these methods, the success classification rate is 86%, thus pointing out a new promising approach to general blind steganalysis. The detection results of steganalysis on Jsteg, Outguess and F5 have further demonstrated the effectiveness of the proposed steganalysis scheme.

Mechanical Properties of a Single Electrospun Fiber and its Structures

Abstract: A method to measure the Young's modulus of a single electrospun polyacrylonitrile (PAN) fiber is reported. The Young's modulus can be calculated from the force-displacement curves obtained by the bending of a single fiber attached to an atomic force microscopy (AFM) cantilever. It is suggested that the high modulus of electrospun fibers is caused by the orientation of molecular chains, which is confirmed by wide-angle X-ray diffraction (WAXD) measurements. The communication will provide a basic understanding of the relationship between mechanical properties and structures of electrospun fibers.

Complex primary crystallization kinetics of amorphous Finemet alloy

Abstract: The complex primary crystallization kinetics of the amorphous Finemet soft magnetic alloys has been analyzed by non-isothermal DSC measurements. The local activation energies E c ( α ) were determined by an isoconversional method without assuming the kinetic model function and its average value was about 383 kJ/mol. The nucleation activation energy E n and growth activation energy E g were 425 and 333 kJ/mol, respectively. And the apparent local activation energies E c can be expressed by E n and E g as follows: E c = aE n + bE g . The local Avrami exponents lies between 1 and 2 in a wide range of 0.2 α E c ( α ) and local Avrami exponents n ( α ) are applicable and correct in describing the primary crystallization process of the amorphous Finemet alloy according to the theoretical DSC curve simulation.