A Novel Approach for Data Encryption Depending on User Location

The wide spread of WLAN and the popularity of mobile devices increases the frequency of data transmission between information system and mobile user. However, most of the data encryption technology is location-independent. An encrypted data can be decrypted anywhere. The encryption technology cannot restrict the location of data decryption. In order to meet the demand of data transmission in the future, a location-dependent approach, called location-dependent data encryption algorithm (LDEA), is proposed in this paper. A target latitude/longitude coordinate is determined firstly. The coordinate is incorporated with a random key for data encryption. The receiver can only decrypt the ciphertext when the coordinate acquired from GPS receiver match with the target coordinate. However, current GPS receiver is inaccuracy and inconsistent. The location of a mobile user is difficult to exactly match with the target coordinate. A toleration distance (TD) is also designed in LDEA to increase its practicality. The security analysis shows that the probability to break LDEA is almost impossible since the length of the random key is adjustable. A prototype is also implemented for experimental study. The results show that the ciphertext can only be decrypted under the restriction of TD. It illustrates that LDEA is effective and practical for data transmission to mobile users

High-throughput Automated Muropeptide Analysis (HAMA) Reveals Peptidoglycan Composition of Gut Microbial Cell Walls

Peptidoglycan (PGN), a net-like polymer constituted by muropeptides, provides protection for microorganisms and has been a major target for antibiotics for decades. Researchers have explored host-microbiome interactions through PGN recognition systems and discovered key muropeptides modulating host responses. However, most common characterization techniques for muropeptides are labor-intensive and require manual analysis of mass spectra due to the complex cross-linked PGN structures. Each species has unique moiety modifications and inter-/intra-bridges, which further complicates the structural analysis of PGN. Here, we developed a high-throughput automated muropeptide analysis (HAMA) platform leveraging tandem mass spectrometry and in silico muropeptide MS/MS fragmentation matching to comprehensively identify muropeptide structures, quantify their abundance, and infer PGN cross-linking types. We demonstrated the effectiveness of HAMA platform using well-characterized PGNs from E. coli and S. aureus and further applied it to common gut bacteria including Bifidobacterium, Bacteroides, Lactobacillus, Enterococcus, and Akkermansia muciiniphila. Specifically, we found that the stiffness and strength of the cell envelopes may correspond to the lengths and compositions of interpeptide bridges within Bifidobacterium species. In summary, the HAMA framework exhibits an automated, intuitive, and accurate analysis of PGN compositions, which may serve as a potential tool to investigate the post-synthetic modifications of saccharides, the variation in interpeptide bridges, and the types of cross-linking within bacterial PGNs.</p

Incorporating Evolutionary Information and Functional Domains for Identifying RNA Splicing Factors in Humans

Regulation of pre-mRNA splicing is achieved through the interaction of RNA sequence elements and a variety of RNA-splicing related proteins (splicing factors). The splicing machinery in humans is not yet fully elucidated, partly because splicing factors in humans have not been exhaustively identified. Furthermore, experimental methods for splicing factor identification are time-consuming and lab-intensive. Although many computational methods have been proposed for the identification of RNA-binding proteins, there exists no development that focuses on the identification of RNA-splicing related proteins so far. Therefore, we are motivated to design a method that focuses on the identification of human splicing factors using experimentally verified splicing factors. The investigation of amino acid composition reveals that there are remarkable differences between splicing factors and non-splicing proteins. A support vector machine (SVM) is utilized to construct a predictive model, and the five-fold cross-validation evaluation indicates that the SVM model trained with amino acid composition could provide a promising accuracy (80.22%). Another basic feature, amino acid dipeptide composition, is also examined to yield a similar predictive performance to amino acid composition. In addition, this work presents that the incorporation of evolutionary information and domain information could improve the predictive performance. The constructed models have been demonstrated to effectively classify (73.65% accuracy) an independent data set of human splicing factors. The result of independent testing indicates that in silico identification could be a feasible means of conducting preliminary analyses of splicing factors and significantly reducing the number of potential targets that require further in vivo or in vitro confirmation

Antidiabetic effect and mode of action of cytopiloyne

Cytopiloyne was identified as a novel polyacetylenic compound. However, its antidiabetic properties are poorly understood. The aim of the present study was to investigate the anti-diabetic effect and mode of action of cytopiloyne on type 2 diabetes (T2D). We first evaluated the therapeutic effect of cytopiloyne on T2D in db/db mice. We found that one dose of cytopiloyne reduced postprandial glucose levels while increasing blood insulin levels. Accordingly, long-term treatment with cytopiloyne reduced postprandial blood glucose levels, increased blood insulin, improved glucose tolerance, suppressed the level of glycosylated hemoglobin A1c (HbA1c), and protected pancreatic islets in db/db mice. Next, we studied the anti-diabetic mechanism of action of cytopiloyne. We showed that cytopiloyne failed to decrease blood glucose in streptozocin- (STZ-)treated mice whose β cells were already destroyed. Additionally, cytopiloyne dose dependently increased insulin secretion and expression in β cells. The increase of insulin secretion/expression of cytopiloyne was regulated by protein kinase C α (PKC α ) and its activators, calcium, and diacylglycerol (DAG). Overall, our data suggest that cytopiloyne treats T2D via regulation of insulin production involving the calcium/DAG/PKC α cascade in β cells. These data thus identify the molecular mechanism of action of cytopiloyne and prove its therapeutic potential in T2D

EFFECT OF SHORT MEDIALSIDE STUDS OM FOOT BIOMECHANICS IN COLLEGIATE SOCCER PLAYERS

The purpose of this study was to examine the effect of modified stud on ankle and foot kinematics, ground reaction force and forefoot force and pressure during sidestep cut (SC) and change direction (CD) movement 6 male collegiate soccer players wore original and medial-side 2mm cut stud shoes and performed SC and CD on the artificial grass. Non-parametric Wilcoxon signed-rank test was used to compare difference between the original and modified studs. The modified stud of non-dominant leg show less inversion than the original stud in SC and CD. The modified stud of non-dominant leg show more force peak form and pressure and that of nondominant legs show more pressure an the original stud during SC and CD. The short medial-side studs with 2mm length can decrease the force inversion of the nondmiiant leg during SC and CD movement and increase the force production of the lower extremities in recreational soccer players

miRTar: an integrated system for identifying miRNA-target interactions in human

<p>Abstract</p> <p>Background</p> <p>MicroRNAs (miRNAs) are small non-coding RNA molecules that are ~22-nt-long sequences capable of suppressing protein synthesis. Previous research has suggested that miRNAs regulate 30% or more of the human protein-coding genes. The aim of this work is to consider various analyzing scenarios in the identification of miRNA-target interactions, as well as to provide an integrated system that will aid in facilitating investigation on the influence of miRNA targets by alternative splicing and the biological function of miRNAs in biological pathways.</p> <p>Results</p> <p>This work presents an integrated system, miRTar, which adopts various analyzing scenarios to identify putative miRNA target sites of the gene transcripts and elucidates the biological functions of miRNAs toward their targets in biological pathways. The system has three major features. First, the prediction system is able to consider various analyzing scenarios (1 miRNA:1 gene, 1:N, N:1, N:M, all miRNAs:N genes, and N miRNAs: genes involved in a pathway) to easily identify the regulatory relationships between interesting miRNAs and their targets, in 3'UTR, 5'UTR and coding regions. Second, miRTar can analyze and highlight a group of miRNA-regulated genes that participate in particular KEGG pathways to elucidate the biological roles of miRNAs in biological pathways. Third, miRTar can provide further information for elucidating the miRNA regulation, i.e., miRNA-target interactions, affected by alternative splicing.</p> <p>Conclusions</p> <p>In this work, we developed an integrated resource, miRTar, to enable biologists to easily identify the biological functions and regulatory relationships between a group of known/putative miRNAs and protein coding genes. miRTar is now available at <url>http://miRTar.mbc.nctu.edu.tw/</url>.</p