Reconstruction of burn scar of the upper extremities with artificial skin

The management of upper-extremity burn contractures is a major challenge for plastic surgeons. After approval by the Food and Drug Administration, artificial skin (Integra) has been available in Taiwan since 1997. From January of 1997 to July of 1999, the authors applied artificial skin to 13 severely burned patients for the reconstruction of their upper extremities, resulting in an increased range of motion in the upper-extremity joints and improved skin quality. An additional benefit was the rapid reepithelialization of the donor sites. There were no complications of infection throughout the therapeutic course, and the overall results were satisfactory. During the 2-year study, scar condition was monitored between 8 and 24 months, and a good appearance and pliable skin were obtained according to the Vancouver Scar Scale. According to this evaluation of Oriental skin turgor, normal pigmentation was restored about 6 months after the resurfacing procedure. For patients with severe burns in whom there is insufficient available skin for a full-thickness skin graft or another appropriate flap for scar revision, Integra is an alternative. The two major concerns in dealing with artificial skin are (1) a 10- to 14-day waiting period for maturation of the neo-dermis, necessitating a two-stage operation, and (2) prevention of infection with antibiotics and meticulous wound care.     

Uniform GFP-expression in transgenic medaka (Oryzias latipes) at the F0 generation

A green fluorescent protein (GFP) cDNA flanked by inverted terminal repeats (ITR) of adeno-associated virus was constructed. The construct sharply improved the efficiency and specificity of the transient expression of genes driven by two general promoters (cytomegalovirus and medaka -actin) and one muscle-specific promoter (zebrafish -actin) in transgenic medaka. In addition, treatment with ITR sequence-containing constructs resulted in a dramatic increase in the number of embryos showing uniform GFP-expression at F0. Of the GFP-positive embryos, 34.6% (81/234), 10% (10/60), and 18% (38/212) showed homogenous GFP-expression for the derivative constructs of the cytomegalovirus, -actin, and -actin promoters, respectively. As a result of uniform GFP-expression, green fluorescence in founders was (a) extended for an entire lifetime without degradation, and (b) transmitted as a genetic trait to F1 and F2 progeny of some transgenic lines via Mendelian inheritance. A Southern blot analysis revealed a random integration of the transgene into the genome of founders and progeny in both head-to-tail and tail-to-tail concatemerization patterns. Interestingly, some transgenic medaka with uniform and strong fluorescence could be visually noticeable to the unaided eye.     

Efficient combination of multiple word models for improved sequence comparison

MOTIVATION: Studies of efficient and sensitive sequence comparison methods are driven by a need to find homologous regions of weak similarity between large genomes. RESULTS: We describe an improved method for finding similar regions between two sets of DNA sequences. The new method generalizes existing methods by locating word matches between sequences under two or more word models and extending word matches into high-scoring segment pairs (HSPs). The method is implemented as a computer program named DDS2. Experimental results show that DDS2 can find more HSPs by using several word models than by using one word model. AVAILABILITY: The DDS2 program is freely available for academic use in binary code form at http://bioinformatics.iastate.edu/aat/align/align.html and in source code form from the corresponding author.     

Predicting subcellular localization of proteins in a hybridization space

MOTIVATION: The localization of a protein in a cell is closely correlated with its biological function. With the number of sequences entering into databanks rapidly increasing, the importance of developing a powerful high-throughput tool to determine protein subcellular location has become self-evident. In view of this, the Nearest Neighbour Algorithm was developed for predicting the protein subcellular location using the strategy of hybridizing the information derived from the recent development in gene ontology with that from the functional domain composition as well as the pseudo amino acid composition. RESULTS: As a showcase, the same plant and non-plant protein datasets as investigated by the previous investigators were used for demonstration. The overall success rate of the jackknife test for the plant protein dataset was 86%, and that for the non-plant protein dataset 91.2%. These are the highest success rates achieved so far for the two datasets by following a rigorous cross-validation test procedure, suggesting that such a hybrid approach (particularly by incorporating the knowledge of gene ontology) may become a very useful high-throughput tool in the area of bioinformatics, proteomics, as well as molecular cell biology. AVAILABILITY: The software would be made available on sending a request to the authors.     

Bio-support vector machines for computational proteomics

MOTIVATION: One of the most important issues in computational proteomics is to produce a prediction model for the classification or annotation of biological function of novel protein sequences. In order to improve the prediction accuracy, much attention has been paid to the improvement of the performance of the algorithms used, few is for solving the fundamental issue, namely, amino acid encoding as most existing pattern recognition algorithms are unable to recognize amino acids in protein sequences. Importantly, the most commonly used amino acid encoding method has the flaw that leads to large computational cost and recognition bias. RESULTS: By replacing kernel functions of support vector machines (SVMs) with amino acid similarity measurement matrices, we have modified SVMs, a new type of pattern recognition algorithm for analysing protein sequences, particularly for proteolytic cleavage site prediction. We refer to the modified SVMs as bio-support vector machine. When applied to the prediction of HIV protease cleavage sites, the new method has shown a remarkable advantage in reducing the model complexity and enhancing the model robustness.     

Insights from modeling the tertiary structure of human BACE2

BACE1, or beta-secretase, is a putative prime therapeutic target for the treatment of Alzheimer's disease. Mapping to the Down syndrome critical region (chromosome 21) and identified as a homologue of BACE1, BACE2 also cleaves amyloid precursor protein at the beta-site. Thus, BACE2, named also as Asp1 or Memapsin1, represents a second beta-secretase candidate. In this paper, the tertiary structure of the protease domain of BACE2 was developed. Although the overall structural topology between BACE1 and BACE2 protease domains is quite similar, the former contains 3 disulfide bonds but the latter only two. Particularly, a subtle structural difference around the DTG/DSG active site between the two structures has been observed that is useful for the in-depth selectivity study of BACE1 and BACE2 inhibitors, stimulating new therapeutic strategies for the treatment of Alzheimer's disease and Down syndrome as well.     

'Signature sets', minimal fragment sets for identifying protein disulfide structures with cyanylation-based mass mapping methodology

Our cyanylation (CN)-based methodology for determining disulfide structure of cystinyl proteins overcomes the limitations of conventional proteolytic methods. However, the CN-based method has the potential drawback that occasionally some CN-induced cleavage fragments may not be detected. We show that CN-based methods can overcome the failure to detect fragments by demonstrating the existence of small 'signature sets' of fragments. The link between signature sets and the robustness of CN-based methodology is validated by two case studies.     

Gas chromatography-isotope dilution mass spectrometry preceded by liquid-liquid extraction and chemical derivatization for the determination of ketamine and norketamine in urine

An analytical scheme using gas chromatography (GC)-isotope dilution mass spectrometry (MS) assisted by precedent liquid-liquid extraction (LLE) and chemical derivatization (ChD) is described for the simultaneous determination of ketamine (KT) and its major metabolite, norketamine (NK), in urine. The simultaneous ChD of the two analytes, one primary amine and one secondary amine, with pentafluorobenzoyl chloride (PFBC) has not only enhanced their instrumental responses and mass-spectrum uniqueness but also afforded more proper yet easier selection of qualifier and quantifier ions and hence achieved more evidential identification and quantitation. Thus, the regression calibration curves for KT and NK in urine are linear within 100-5000 ng/ml, with correlation coefficients typically exceeding 0.99 and NK curves exclusively showing larger slopes than KT curves. The method limits of detection (LODs) determined by two definitions for KT and NK range from 3 to 75 ng/ml, and limits of quantitation (LOQs) from 9 to 100 ng/ml. The mean recoveries (N = 3) calculated for the LLE/ChD of KT and NK from 50 and 100 microl, respectively, of a 100 microg/ml urinary spike vary from 71.0 to 97.8%, with NK consistently giving better recoveries than KT. The precisions (N = 3) calculated for the total analyses of four real-case samples are typically below 12.3%. GC-MS operated in the positive ion chemical ionization (PCI) mode can offer both qualitative and quantitative information complementary to those given by the EI mode. The proposed scheme is simple, effective, reliable, and robust. It may serve as a confirmatory protocol for forensic urine drug testing.     

Adaptive combinatorial design to explore large experimental spaces: approach and validation

Systems biology requires mathematical tools not only to analyse large genomic datasets, but also to explore large experimental spaces in a systematic yet economical way. We demonstrate that two-factor combinatorial design (CD), shown to be useful in software testing, can be used to design a small set of experiments that would allow biologists to explore larger experimental spaces. Further, the results of an initial set of experiments can be used to seed further 'Adaptive' CD experimental designs. As a proof of principle, we demonstrate the usefulness of this Adaptive CD approach by analysing data from the effects of six binary inputs on the regulation of genes in the N-assimilation pathway of Arabidopsis. This CD approach identified the more important regulatory signals previously discovered by traditional experiments using far fewer experiments, and also identified examples of input interactions previously unknown. Tests using simulated data show that Adaptive CD suffers from fewer false positives than traditional experimental designs in determining decisive inputs, and succeeds far more often than traditional or random experimental designs in determining when genes are regulated by input interactions. We conclude that Adaptive CD offers an economical framework for discovering dominant inputs and interactions that affect different aspects of genomic outputs and organismal responses.     

LUCY2: an interactive DNA sequence quality trimming and vector removal tool

Lucy2 is a raw DNA sequence trimming and visualization tool based on the popular command-line Lucy1. Users can change parameters, trim multiple sequences and visualize the results within an integrated, easy-to-use graphical user interface. Lucy2 is designed specifically for non-programmers to use, and is currently available on Windows, Linux and MacOS X. Source code is also available for porting to the other platforms. AVAILABILITY: Lucy2 is distributed under the GNU General Public License and can be downloaded from www.complex.iastate.edu