Several N(1)-arylalkylpolyamines containing various aromatic ring systems were synthesized as their respective HCl salts. The N(1)-substituents evaluated ranged in size from N(1)-benzyl, N(1)-naphthalen-1-ylmethyl, N(1)-2-(naphthalen-1-yl)ethyl, N(1)-3-(naphthalen-1-yl)propyl, N(1)-anthracen-9-ylmethyl, N(1)-2-(anthracen-9-yl)ethyl, N(1)-3-(anthracen-9-yl)propyl, and pyren-1-ylmethyl. The polyamine architecture was also altered and ranged from diamine to triamine and tetraamine systems. Biological activities in L1210 (murine leukemia), Chinese hamster ovary (CHO), and CHO's polyamine transport-deficient mutant (CHO-MG) cell lines were investigated via IC(50) cytotoxicity determinations. K(i) values for spermidine uptake were also determined in L1210 cells. The size of the N(1)-arylalkyl substituent as well as the polyamine sequence used had direct bearing on the observed cytotoxicity profiles. N(1)-Tethers longer than ethylene showed dramatic loss of selectivity for the polyamine transporter (PAT) as shown in a CHO/CHO-MG cytotoxicity screen. In summary, there are clear limits to the size of N(1)-substituents, which can be accommodated by the polyamine transporter. A direct correlation was observed between polyamine-conjugate uptake and cytotoxicity. In this regard, a cytotoxicity model was proposed, which describes a hydrophobic pocket of set dimensions adjacent to the putative PAT polyamine-binding site.

Content-based image retrieval (CBIR) techniques have currently gained increasing popularity in the medical field because they can use numerous and valuable archived images to support clinical decisions. In this paper, we concentrate on developing a CBIR system for retrieving brain tumors in T1-weighted contrast-enhanced MRI images. Specifically, when the user roughly outlines the tumor region of a query image, brain tumor images in the database of the same pathological type are expected to be returned. We propose a novel feature extraction framework to improve the retrieval performance. The proposed framework consists of three steps. First, we augment the tumor region and use the augmented tumor region as the region of interest to incorporate informative contextual information. Second, the augmented tumor region is split into subregions by an adaptive spatial division method based on intensity orders; within each subregion, we extract raw image patches as local features. Third, we apply the Fisher kernel framework to aggregate the local features of each subregion into a respective single vector representation and concatenate these per-subregion vector representations to obtain an image-level signature. After feature extraction, a closed-form metric learning algorithm is applied to measure the similarity between the query image and database images. Extensive experiments are conducted on a large dataset of 3604 images with three types of brain tumors, namely, meningiomas, gliomas, and pituitary tumors. The mean average precision can reach 94.68%. Experimental results demonstrate the power of the proposed algorithm against some related state-of-the-art methods on the same dataset.

The responses of antioxidative system of rice to chilling were investigated in a tolerant cultivar, Xiangnuo-1, and a susceptible cultivar, IR-50. The electrolyte leakage and malondialdehyde content of Xiangnuo-1 were little affected by chilling treatment but those of IR-50 increased. Activities of suoperoxide dismutase, catalase, ascorbate peroxidase and glutathione reductase, and ascorbic acid content of Xiangnuo-1 were remained high, while those of IR-50 decreased under chilling. The results indicated that higher activities of defense enzymes and higher content of antioxidant under stress were associated with tolerance to chilling.Additional key words: ascorbate peroxidase, ascorbic acid, catalase, glutathione reductase, superoxide dismutase.