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Purpose Gastric cancer has a high mortality rate worldwide. Although treatments, such as molecular-targeted therapy, have been introduced, the resulting long-term survival and prognosis remain unsatisfactory. Downregulation of the target genes using lentivirus-mediated short hairpin RNA (shRNA) can be an effective therapeutic strategy for patients with gastric cancer. Overexpressed vascular endothelial growth factor A (VEGF) in human gastric cancer cells can be an effective novel therapeutic target for human gastric cancer. Thus, this study aimed to evaluate the therapeutic effects of lentivirus-mediated knockdown of VEGF gene expression in human gastric cancer growth. Materials and methods Specific shRNA sequences targeting VEGF were designed to construct a lentiviral expression vector. After human gastric carcinoma cells (cell line NCI-N87) were infected with the lentiviral vector, the therapeutic effects of the lentivirus-mediated shRNA targeting VEGF were analyzed both in vitro and in vivo. Results Stable suppression of VEGF gene expression in NCI-N87 cells using shRNA (ShVEGF) showed significant inhibition of cell proliferation, clonogenicity, and cell motility. ShVEGF also showed increased G0/G1 cell cycle arrest and apoptosis. In addition, in vivo results from nude mice xenografted ShVEGF showed significant inhibition of tumor growth. Assessing the therapeutic effects of intratumoral injection of lentivirus-targeting VEGF (Virus_VEGF) revealed that it significantly inhibited tumor growth compared to that in the Virus_Scramble or saline injection control groups. Conclusion The constructed ShVEGF showed significant inhibition of NCI-N87 gastric cancer cell growth both in vitro and in vivo. These experimental results suggest a novel therapeutic strategy for patients with gastric cancer using lentivirus-mediated shRNA targeting VEGF.

Exposure to ionizing radiation leads to severe damages in radiosensitive organs and induces acute radiation syndrome, including effects on the hematopoietic system and gastrointestinal system. In this study, the radioprotective ability of KMRC011, a novel toll-like receptor 5 (TLR5) agonist, was investigated in C57BL6/N mice exposed to lethal total-body gamma-irradiation. In a 30-day survival study, KMRC011-treated mice had a significantly improved survival rate compared with control after 11 Gy total-body irradiation (TBI), and it was found that the radioprotective activity of KMRC011 depended on its dosage and repeated treatment. In a 5-day short-term study, we demonstrated that KMRC011 treatment stimulated cell proliferation and had an anti-apoptotic effect. Furthermore, KMRC011 increased the expressions of genes related to DNA repair, such as Rad21, Gadd45b, Sod2 and Irg1, in the small intestine of lethally irradiated mice. Interestingly, downregulation of NF-κB p65 in the mouse intestine by KMRC011 treatment was observed. This data indicated that KMRC011 exerted a radioprotective activity partially by regulating NF-κB signaling. Finally, peak expression levels of G-CSF, IL-6, IFN-γ, TNF-α and IP-10 induced by KMRC011 treatment were different depending on the route of administration and type of cytokine. These cytokines could be used as candidate biomarkers for the evaluation of KMRC011 clinical efficacy. Our data indicated that KMRC011 has radioprotective activity in lethally irradiated mice and may be developed as a therapeutic agent for radioprotection.

Robusta beans cultivated with Monascus ruber (RMR) were successively fermented with Leuconostoc mesenteroides (LM) and the antiobesity effects were examined. To produce an obese mouse model to investigate the hypolipidemic effects, ICR mice were fed the same high-fat diet for 6 weeks. Treatment groups were given 10 or 20% RMR-LM. Body weight changes in the 20% RMR-LM group were lower compared with those in the control group. Visceral adipose tissue weight and adipose size were significantly lower in the 20% RMR-LM group compared with those in the control group. Significant improvement in glucose tolerance was observed in the 10 and 20% RMR-LM groups compared with the control group. The 20% RMR-LM group exhibited a significant reduction in serum glucose concentration. Hepatic mRNA levels of sterol regulatory element-binding protein 1, fas cell surface death receptor, and peroxisome proliferator-activated receptor γ, which are associated with lipid, and fatty acid metabolism, in the 20% RMR-LM group were significantly lower compared with those in the control group. The results of the present study demonstrated that 20% RMR-LM may be used to prevent obesity, and ameliorate diabetes and lipid metabolism imbalances.

Vibrio parahaemolyticus is a major gastroenteritis-causing pathogen in Korea. Recent studies have reported that heavy metal and antimicrobial resistance in bacteria are related. In this study, we investigated heavy metal and antimicrobial resistance in wild strains of V. parahaemolyticus. First, we isolated and characterized 38 V. parahaemolyticus strains (toxR-positive) from shellfish collected from the West Sea of Korea between May and November 2018. Antibiotic and heavy metal resistance in the 38 strains were tested by disk diffusion assay and broth dilution assay, respectively. Then, we selected seven strains that showed resistance to cobalt (Co2+) and copper (Cu2+), to examine the relationship between heavy metal resistance and antimicrobial resistance. After heavy metal (Co2+ and Cu2+) pretreatment, the seven strains exhibited increased resistance to kanamycin, streptomycin, tetracycline, and gentamycin. Likewise, antimicrobial pretreatment resulted in increased heavy metal tolerance.

Robusta beans cultivated with Monascus ruber (RMR) were successively fermented with Leuconostoc mesenteroides (LM) and the antiobesity effects were examined. To produce an obese mouse model to investigate the hypolipidemic effects, ICR mice were fed the same high-fat diet for 6 weeks. Treatment groups were given 10 or 20% RMR-LM. Body weight changes in the 20% RMR-LM group were lower compared with those in the control group. Visceral adipose tissue weight and adipose size were significantly lower in the 20% RMR-LM group compared with those in the control group. Significant improvement in glucose tolerance was observed in the 10 and 20% RMR-LM groups compared with the control group. The 20% RMR-LM group exhibited a significant reduction in serum glucose concentration. Hepatic mRNA levels of sterol regulatory element-binding protein 1, fas cell surface death receptor, and peroxisome proliferator-activated receptor γ, which are associated with lipid, and fatty acid metabolism, in the 20% RMR-LM group were significantly lower compared with those in the control group. The results of the present study demonstrated that 20% RMR-LM may be used to prevent obesity, and ameliorate diabetes and lipid metabolism imbalances.

In pattern classification, feature selection is an important factor in the performance of classifiers. In particular, when classifying a large number of features or variables, the accuracy and computational time of the classifier can be improved by using the relevant feature subset to remove the irrelevant, redundant, or noisy data. The proposed method consists of two parts: a wrapper part with an improved genetic algorithm(GA) using a new reproduction method and a filter part using mutual information. We also considered feature selection methods based on mutual information(MI) to improve computational complexity. Experimental results show that this method can achieve better performance in pattern recognition problems than other conventional solutions.

The main objective of this study was to investigate whether Lactobacillus rhamnosus GG (LGG) ameliorated the effects of Citrobactor rodentium infection in Toll-like receptor 2 (TLR2) knockout (KO) and TLR4 KO mice, as well as in wild-type C57BL/6 (B6) mice. TLR2 KO, TLR4 KO, and B6 mice were divided into three groups per each strain. Each group had an uninfected control group (n = 5), C. rodentium-infected group (n = 8), and LGG-pretreated C. rodentium-infected group (n = 8). The survival rate of B6 mice infected with C. rodentium was higher when pretreated with LGG. Pretreatment with LGG ameliorated C. rodentium-induced mucosal hyperplasia in B6 and TLR4 KO mice. However, in C-rodentium-infected TLR2 KO mice, mucosal hyperplasia persisted, regardless of pretreatment with LGG. In addition, LGG-pretreated B6 and TLR4 KO mice showed a decrease in spleen weight and downregulation of tumor necrosis factor alpha, interferon gamma, and monocyte chemotactic protein 1 mRNA expression compared with the non-pretreated group. In contrast, such changes were not observed in TLR2 KO mice, regardless of pretreatment with LGG. From the above results, we conclude that pretreatment with LGG ameliorates C. rodentium-induced colitis in B6 and TLR4 KO mice, but not in TLR2 KO mice. Therefore, LGG protects mice from C. rodentium-induced colitis in a TLR2-dependent manner.

This paper presents a variable step size incrementalconductance direct Maximum Power Point Tracking (MPPT) method using fuzzy membership for a standalone photovoltaic (PV) system under rapidly changing irradiation. MPPT techniques have been widely applied in PV systems to make a PV array generate maximum power, which depends on solar irradiation. In most applications of MPPT technologies, MPPT algorithm design methods are performed and tested under slowly changing atmospheric conditions such as irradiation and temperature. The short-term effect under rapidly changing irradiation should be considered, however, to improve the dynamic performance of PV system. Our proposed MPPT method is based on an incremental conductance algorithm with a direct control scheme that can directly adjust the duty cycle for the PI controller. A fuzzy membership function is adopted to determine the variable step size according to rapidly changing irradiation. The proposed methods thus has not only faster dynamic performance but also high tracking accuracy. In order to show the effect of the proposed method, the simulation model and proposed MPPT is designed with MATLAB/Simpower and simulated with MATLAB/Stateflow.

The nutrient composition, including the proximate composition and the mineral, vitamin, amino acid, and free-amino-acid levels, of baechu kimchi (Chinese cabbage kimchi) to which 14 kinds of seafood (flatfish, yellow corvina, sea beam, pollack gizzard shad, ray, gray mullet, skate, hairtail, anchovy, sea squit, pen shell, scallop, small octopus)were added was analyzed. The seafoods were added to salted cabbage at concentration of 10% (w/w) and the prepared seafood baechu Kimchi (BK) was stored at for seven days. The levels of moisture (82.09-88.56%), crude lipid (0.31-0.64%), and crude ash (2.70-3.50%) did not differ much among the samples, but the level of crude protein of the BK-with-seafood samples (2.42-5.15%) was greater than that of the control BK (2%), without seafood. The Fe and Ca contents of BK with flatfish showed the highest values (4.1 and 74 mg/100 g, respectively). The vitamin A contents of BK samples with 14 different kinds of seafood were higher than that of the control BK. Moreover, the BK with sea squit had higher vitamin (0.90 mg/100 g) and vitamin C (8.48 mg/100 g) contents among all the BK-with-different-kinds-of-seafood samples. Total amino acids were detected in all BK-with-seafood samples, most of which had high levels of glutamic acid, aspartic acid, proline and alanine. Glutamic acid was the most abundant of all the amino acids. The major free amino acids were hydroxyproline, glutamic acid, alanine, proline, leucine, and valine, of which hydroxyproline was the most abundant. In conclusion, BK with seafood is thought to be a very good source of protein, which is very important from dietary life of humans.

It is difficult to predict water quality in a reservoir because of the complex physical, chemical, and biological processes involved. In contrast to the well-known numeric models and artificial neural network models, Linguistic Models (LM) with context-based fuzzy clustering can offer reliable predictions of water quality. The main characteristics of LM are that it is user-centric and that it inherently dwells upon collections of highly interpretable and user-oriented entities, such as information granules. In this paper, we propose a model for evaluating water quality and then evaluate the effectiveness of the proposed method by performing comparisons on water quality data sets from a reservoir. Finally, we found that the proposed method not only has the better prediction performance than other models, but also can offer reliable intervals for uncertainty evaluation about the water quality.

Since the fuzzy time series forecasting methods provide a powerful framework to cope with vague or ambiguous problems, they have been widely used in real applications. The forecasting accuracy of these methods usually, however, depend on their universe of discourse and the length of intervals. So, we present a new forecasting method using two-factors high-order fuzzy time series and particle swarm optimization (PSO) for increasing the forecasting accuracy. To show the effectiveness of the proposed method, we applied our method for the Taiwan futures exchange (TAIFEX) forecasting and the Korea composite price index (KOSPI) 200 forecasting. The results show better forecasting accuracy than previous methods.

To identify the food characteristics of seven melania snail species in Korea, the detailed proximate, fatty/amino acid, mineral composition and chlorophyll contents were investigated. The content ranges of moisture, crude protein, crude lipid and ash were 70.1-81.0%, 11.6-16.9%, 0.4-1.6% and 1.9-3.4%, respectively. K. nadifila showed the significant mineral contents Fe, P, Ca than other species. Total Chlorophyll level was highest in K. globus ovalis (1.2±0.2 mg/g). The major fatty acids were 16:0, 22:1, 20:1, 18:1, 20:5 and 22:6 were identified as small amounts (1.0-3.3%) of total fatty acids. Citrulline was shown to be the major free amino acids (20.4-53.1%).

This study was conducted to compare the biological activities of 7 melania snails from the family Pleuroceridae (Semisulcospira coreana, Koreanomelania nodifila, Semisulcospira forticosta, Koreoleptoxis globus ovalis, Semisulcospira libertina, Semisulcospira tegulata and Semisulcospira gottschei) in Korea. Among the 7 species, S. coreana, Korean. nodifila, S. forticosta and S. gottschei showed over 80% cytotoxicities on three cancer cell lines (SNU-1, A549 and Hep 3B) compared to the non-treatment, whereas S. libertina and S. tegulata showed almost no growth inhibition activities on the same cancer cell lines. In relation to ACE inhibition activity, only S. coreana, Korean. nodifila, and S. forticosta showed over 60% ACE inhibition activities, whereas other melania snails exhibited inhibition activities of lower than 25%. DPPH radical scavenging activities were also determined, and used to categories melania snails into three groups based on Duncan`s multiple range test at P produced by in vitro mouse peritoneal macrophage was determined according to bioactivity on L-929 cells. Three melania snails, S. coreana, Korean. nodifila and S. gottschei, exhibited 95.2%, 89.7% and 93.7% cell death(%) on L-929 cells, respectively. Glucose-6-phosphate dehydrogenase inhibitory activity was also obtained in the extract of S. coreana (31.9%) and Korean. nodifila (28.1%), showing that these extracts can be used as supplemental dietary health foods. In conclusion, we believe that the extracts of melania snails should be given due consideration in functional health food development.

There have been much difficulties to construct an optimized neural network in complex nonlinear regression problems such as selecting the networks structure and avoiding overtraining problem generated by noise. In this paper, we propose a stepwise constructive method for neural networks using a flexible incremental algorithm. When the hidden nodes are added, the flexible incremental algorithm adaptively controls the number of hidden nodes by a validation dataset for minimizing the prediction residual error. Here, the ELM (Extreme Learning Machine) was used for fast training. The proposed neural network can be an universal approximator without user intervene in the training process, but also it has faster training and smaller number of hidden nodes. From the experimental results with various benchmark datasets, the proposed method shows better performance for real-world regression problems than previous methods.

In this paper, we propose the biomedical spectral pattern classification techniques by the fusion scheme based on the SpPCA and MLP in extended feature space. A conventional PCA technique for the dimension reduction has the problem that it can`t find an optimal transformation matrix if the property of input data is nonlinear. To overcome this drawback, we extract features by the SpPCA technique in extended space which use the local patterns rather than whole patterns. In the classification step, individual classifier based on MLP calculates the similarity of each class for local features. Finally, biomedical spectral patterns is classified by the fusion scheme to effectively combine the individual information. As the simulation results to verify the effectiveness, the proposed method showed more improved classification results than conventional methods.

The industrial use of bovine and porcine collagen has been expanded to include foods, cosmetics, and biomaterials. However, due to outbreaks of bovine spongiform encephalopathy and foot and mouth disease, new, alternative, safe sources of collagen are being sought. In this study, pepsinsolubilized collagen (PSC) was isolated from the tissue of a starfish (Asterias amurensis) and shown to consist of (α1)2α2 heterotrimer, which is similar to calf skin type I collagen. However, the PSC was denaturated at 24.7oC, which is about 12oC lower than mammalian collagen. Immunoblotting assay using polyclonal anti-type I collagen antibody revealed that the starfish collagen contained similar affinity motifs. In XTT assay, PSC suspension had cell growth activity and no showed no cytotoxicity.

The surveillance robot has been an important component in the field of service robot industry. In the surveillance robot technology, one of the most important technology is to identify a person. In this paper, we propose a gait recognition method based on contourlet and fuzzy LDA (Linear Discriminant Analysis) for surveillance robots. After decomposing a gait image into directional subband images by contourlet, features are obtained in each subband by the fuzzy LDA. The final gait recognition is performed by a fusion technique that effectively combines similarities calculated respectively in each local subband. To show the effectiveness of the proposed algorithm, various experiments are performed for CBNU and NLPR DB datasets. From these, we obtained better classification rates in comparison with the result produced by previous methods.

In this paper, we propose a fault diagnosis algorithm for BLDC motors by principle component analysis (PCA) and implement a real-time fault diagnosis system for BLDC motors. To verify the proposed diagnosis algorithm, various faulty data are acquired by Lab VIEW program from experimental system. We extract a fault feature using principle component analysis after preprocessing and then finally the fault diagnosis is performed by Euclidean similarity. Also, we embed the PCA algorithm and k-NN classification algorithm into a digital signal processor. From various experiments, we found that the proposed algorithm can be used as a powerful technique to classify the several fault signals acquired from BLDC motors.

This paper describes how to protect the personal information of a biometric reference provider wherein biometric reference and personally identifiable information are bounded in a biometric system. To overcome the shortcomings of the simple personal authentication method using a password, such as identify theft, a biometric system that utilizes physical and behavioral characteristics of each person is usually adopted. In the biometric system, the biometric information itself is personal information, and it can be used as an unique identifier that can identify a particular individual when combining with the other information. As a result, secure protection methods are required for generating, storing, and transmitting biometric information. Considering these issues, this paper proposes a method for ensuring confidentiality and integrity in storing and transferring personally identifiable information that is used in conjunction with biometric information, by extending the related X9.84 standard. This paper also outlines the usefulness of the proposition by defining a standard format represented by ASN.1, and implementing it.

Crude saponin, extracted from the starfish Asterias amurensis, was assessed for its capacity as a biological pesticide. As part of this analysis, its insecticidal and repellent activities, in addition to its acute and chronic toxicities were tested. In comparison with the control group, insecticidal activity of saponin against tobacco cutworm, Spodoptera litura, in kale, Brassica loeracea was low at 36.4%. Repellent activities of the extracted saponin against green peach aphid, Myzus persicae, and S. litura, on soybean leaf, Glycine max and kale were 65.6% and 35.0% at day, and 54.5% and 30.0% at day, respectively. Acute and chronic toxicity analysis was carried out using acute immobilizatioin test and reproduction impairment test, respectively. The saponin had 48 h- of . Twenty-one day accumulative reproduction after treatment was lower in Daphnia magna at $7{\mu}g/mL$ saponin (78 youngs), compared with the control group (129 youngs). These results indicate that the extracted saponin exhibited some toxicity and has potential as a repellent against insects.

This paper propose a method to hide not only biometric features in the biometric image such as face and fingerprint for protecting them from unauthorized entity but also information of responsible person expressed as binary image which can be used to identify the responsibility of divulgence. For this, we investigate the recognition rates and bit error rates of extracted responsible person information watermark for the cases of using face and fingerprint images as cover images for fingerprint and face recognition which are the most popular biometric techniques. From these experiments, we confirm that the proposed method can be used for various application requiring to protect personal biometric information

Cluster based fuzzy model tree has certain drawbacks to decrease performance of testinB data when over-fitting of training data exists. To reduce the sensitivity of performance due to over-fitting problem, we proposed a modified cluster based fuzzy model tree with node information. To construct model tree, cluster centers are calculated by fuzzy clustering method using all input and output attributes in advance. And then, linear models are constructed at internal nodes with fuzzy membership values between centers and input attributes. In the prediction step, membership values are calculated by using fuzzy distance between input attributes and all centers that passing the nodes from root to leaf nodes. Finally, data prediction is performed by the weighted average method with the linear models and fuzzy membership values. To show the effectiveness of the proposed method, we have applied our method to various dataset. Under various experiments, our proposed method shows better performance than conventional cluster based fuzzy model tree.

An acidic ent-cyclic peroxide was isolated from a sponge, Plakotis sp., and showed activity against leishmaniasis and pathogenic fungi. To improve the activity of this compound, we coupled the acidic ent-cyclic at the C1 position of ircinol A. Compound 3 exhibited significant activity against Leishmania mexican a and fungi with values of 0.7 and , respectively. The yield of compound 3 was 98%.

This paper proposes a c-fuzzy model tree using partial least square method to predict the Chlorophyll-a concentration in each zone. First, cluster centers are calculated by fuzzy clustering method using all input and output attributes. And then, each internal node is produced according to fuzzy membership values between centers and input attributes. Linear models are constructed by partial least square method considering input-output pairs remained in each internal node. The expansion of internal node is determined by comparing errors calculated in parent node with ones in child node, respectively. On the other hands, prediction is performed with a linear model haying the highest fuzzy membership value between input attributes and cluster centers in leaf nodes. To show the effectiveness of the proposed method, we have applied our method to water quality data set measured at several stations. Under various experiments, our proposed method shows better performance than conventional least square based model tree method.

This paper proposes a fuzzy model tree consisting of local linear models using fuzzy cluster for data modeling. First, cluster centers are calculated by fuzzy clustering method using all input and output attributes. And then, linear models are constructed at internal nodes with fuzzy membership values between centers and input attributes. The expansion of internal node is determined by comparing errors calculated in parent node with ones in child node, respectively. As a final step, data prediction is performed with a linear model having the highest fuzzy membership value between input attributes and cluster centers in leaf nodes. To show the effectiveness of the proposed method, we have applied our method to various dataset. Under various experiments, our proposed method shows better performance than conventional model tree and artificial neural networks.

Klebsiella pneumoniae is an opportunistic and clinically significant emerging pathogen. We investigated the relative roles of Toll-like receptor (TLR) 2 and TLR4 in initiating host defenses against K. pneumoniae. TLR2 knockout (KO), TLR4 KO, TLR2/4 double KO (DKO), and wild-type (WT) mice were inoculated with K. pneumoniae. Mice in each group were sacrificed after either 12 or 24h, and the lungs, liver, and blood were harvested to enumerate bacterial colony-forming units (CFU). Cytokine and chemokine levels were analyzed using enzyme-linked immunosorbent assay and real-time PCR, and pneumonia severity was determined by histopathological analysis. Survival was significantly shortened in TLR4 KO and TLR2/4 DKO mice compared with that of WT mice after infection with 5 × 103 CFU. TLR2 KO mice were more susceptible to infection than WT mice after exposure to a higher infectious dose. Bacterial burdens in the lungs and liver were significantly higher in TLR2/4 DKO mice than in WT mice. Serum TNF-α, MCP-1, MIP-2, and nitric oxide levels were significantly decreased in TLR2/4 DKO mice relative to those in WT mice, and TLR2/4 DKO mice showed significantly decreased levels of TNF-α, IL-6, MCP-1, and inducible nitric oxide synthase mRNA in the lung compared with those in WT mice. Collectively, these data indicate that TLR2/4 DKO mice were more susceptible to K. pneumoniae infection than single TLR2 KO and TLR4 KO mice. These results suggest that TLR2 and TLR4 play cooperative roles in lung innate immune responses and bacterial dissemination, resulting in systemic inflammation during K. pneumoniae infection.

Six, heretofore undescribed, 5′-Methyl-5′-(5-Substituted uracil-1-ylmethyl)-2′-oxo-3′-methylenetetrahydrofurans (F, Cl, Br, I, CH3, H) (6a-f) were synthesized and evaluated against three cell lines (FM-3A, P-388 and U-937). For the preparation of α-methylene-γ-butyrolactone bearing 5-substituted uracils (6a-f), the efficient Reformatsky type reaction was employed which involves the treatment of ethyl α-(bromomethyl) acrylate and zinc with the respective 5-substituted uracil-1-ylacetones (5a-f). The acetone derivatives (5a-f) were directly obtained by the respective alkylation reaction of 5-substituted uracils with chloroacetone in the presence of K2CO3 (or NaH). These lactone compounds6a-f exhibited moderate to significant activity in all of the three cell lines, and6b, 6c and6e showed significant antitumor activities (inhibitory concentrations (IC50) ranged from 1.3–3.8 μg/ml).

Whereas increasing concerns about radiation exposure to nuclear disasters or side effects of anticancer radiotherapy, relatively little research for radiation damages or remedy has been done. The purpose of this study was to establish level of LD70/30 (a lethal dose for 70% of mice within 30 days) by total-body γ irradiation (TBI) in a mouse model. For this purpose, at first, 8-week-old male ICR and C57BL/6N mice from A and B companies were received high dose (10, 11, 12 Gy) TBI. After irradiation, the body weight and survival rate were monitored for 30 days consecutively. In next experiment, 5-week-old male ICR and C57BL/6N mice from B company were received same dose irradiation. Results showed that survival rate and body weight change rate in inbred C57BL/6N mice were similar between A and B company. In ICR mice, however, survival rate and body weight change rate were completely different among the companies. Significant difference of survival rate both ICR and C57BL6N mice was not observed in between 5-week-old and 8-week-old groups receiving 10 or 12 Gy TBI. Our results indicate that the strain and age of mice, and even purchasing company (especially outbred), should be matched over experimental groups in TBI experiment. Based on our results, 8-week-old male ICR mice from B company subjected to 12 Gy of TBI showed LD70/30 and suitable as a mouse model for further development of new drug using the ideal total-body irradiation model.

We have reviewed 178 intertrochanteric fractures treated by dynamic hip screw (DHS) fixation between March 1995 and December 1999 and followed for a minimum of 1 year. We used Singh's classification of the trabecular bone structure in the proximal femur as a measure of osteoporosis and also classified the fractures according to three different systems (Boyd-Griffin, Evans, AO). The postoperative radiographs were examined for loss of reduction, i.e. varus angulation >100, perforation of the femoral head, more than 20-mm extrusion of a lag screw or metal failure. We found 49 cases which showed radiographic failures. Two were stable fractures and 47 unstable fractures (Evans' classification). Unstable fractures with osteoporosis had a failure rate of more than 50%. In such cases DHS should not be the first choice for treatment.

A series of 4-(2-chloroethyl)nitrosocarbamoyl- and 4-methyl nitrosocarbamoyl analogs of 4-Aza--cholestane (5a and 5b), 4-Aza-5-cholestene (6a and 6b) were synthesized and evaluated for their inhibitory activity against the Sarcoma 180 cell. The steroidal nitrosoureas, 5a, 5b, 6a and 6b displayed modest activity in vitro.

In this paper, we propose a novel tree based modeling method, Generalized Cluster based Fuzzy Model Tree (G-CFMT) which can model piecewise linear or piecewise nonlinear dataset and predict a continuous output value. To construct the G-CFMT, data cluster centers are calculated by fuzzy clustering and Extreme Learning Machine (ELM) are obtained at the tree nodes. Since the fuzzy clustering method can render the granulation of dataset, the complexity of the constructed tree is usually low. Moreover, we show that the ELM based scheme can also produce a linear regression model. In the prediction step, fuzzy membership values are calculated from the distance between input data and all cluster centers, the passing nodes from root to the leaf node. Final data prediction is performed by fusing the intermediate induction results, which renders capability of overcoming over-fitting problem of deteriorating the performance for testing data. To validate the proposed method, we have applied our method to various real world datasets. The experimental results clearly underline better performance over other conventional linear and nonlinear modeling and prediction methods in terms of several performance indices.

Optimization methods have been developed by many researchers. Especially, the methods based on Evolutionary Algorithms (EAs) have received increased attention from diversity fields. Recently, bacterial foraging algorithm mimicked bacterial behavior has been introduced by Passino. However, his work did not implement an important bacterial behavior regulating division so-called ‘quorum-sensing’. The quorum-sensing is a chemical communication including producing, releasing, detecting, and responding to small hormone-like molecules termed autoinducers. This communication allows bacteria to coordinate the behavior of the group. This paper proposes an optimization algorithm based on the bacterial quorum sensing. In order to estimate the performance of the algorithm, we use a multimodal Gaussian having several minima and maxima, and also four benchmark functions. Experimental results show that this proposed method can achieve better performance than conventional bacterial foraging algorithm

Energy saving becomes a significant issue in recent years. There are two conventional methods of using the infrared ray sensor and CCD camera to detect human movement. The method of using the infrared ray sensor, however, frequently causes malfunction problems. On the other hand, the method which uses CCD camera requires accompanying high price equipments. To save electric energy, this paper proposes an algorithm to recognize human presence with USB Web camera. The proposed algorithm detects human movement using the circle detection and morphological methods. Under various experiments, the proposed method shows better performance in terms of the recognition rate and speed.

In the preparation of acyclic thymidine nucleoside analogues, K(2)CO(3) (or NaH) treated thymine in DMSO was alkylated with omega-chloroalkyl nitrite (Cl-(CH(2))(n)-CN; n=1, 2, 3, 4) to provide an isomeric mixture of 1-(omega-cyanoalkyl)thymine (2a-d) and 1,3-bis(omega-cyanoalkyl)thymine in approximately 5ratio1 ratios. Reduction of the cyano function2a-d with NaBH(4)/CoCl(2).6H(2)O gave the corresponding 1-(omega-aminoalkyl)thymine (3a-d). The newly formed primary amino function in3a-d was directly reacted with 2-chloroethylisocyanate to afford the 1-[omega-(N'2-chloroethy-lureido) alkyl]thymine (4a-d) in good yields. Nitrosation of 1-[5-(N'-2-chloroethylureido)pentyl] thymine (4d) with glacial acetic acid and dry NaNO(2) powder in anhydrous CH(2)Cl(2) gave two types of regioisomeric nitrosoureas, 1-[5-(N'-2-chloroethyl-N'-nitrosoureido)pentyl]thymine (5d) and 1-[5-(N'-2-chloroethyl-N-nitrosoureido)pentyl]thymine in approximately 5ratio1 ratios. The in vitro cytotoxicity of the synthesized compounds (2a-d, 3a-d, 4a-d and5a-d) against three cell lines (K-562, P-388 and FM-3A) are measured as IC(50) values. Compounds3d and4c showed moderate activities against all three cell lines, and all other compounds were found to be not active.

A number of 5-substituted pyrimidine acyclic nucleosides were synthesized and tested for in vitro cytotoxicity against four cell lines (J-82 cell, P-388 cell, FM-3A cell and U-938 cell lines). Synthesis of 1-cyanomethyl-5-substituted pyrimidines (1a-e) and 1-(4-cyanobutyl)-5-substituted pyrimidines (2a-e) was accomplished from the series of alkylation reactions of 5-substituted uracils with the corresponding chloroacetonitrile and 5-chlorovaleronitile in DMSO under 50 degrees C temperature. These 5-substituted pyrimidine acylic nucleosides (1a-e and 2a-e) exhibited moderate to significant activity against four cell lines.