a b s t r a c t a r t i c l e i n f oNanoparticulate drug delivery systems offer great promise in addressing challenges of drug toxicity, poor bioavailability and non-specificity for a number of drugs. Much progress has been reported for nano drug delivery systems for intravenous administration, however very little is known about the effects of orally administered nanoparticles. Furthermore, the development of nanoparticulate systems necessitates a thorough understanding of the biological response post exposure. This study aimed to elucidate the in vivo uptake of chitosan and polyethylene glycol (PEG) coated Poly, DL, lactic-co-glycolic Acid (PLGA) nanoparticles and the immunological response within 24 h of oral and peritoneal administration. These PLGA nanoparticles were administered orally and peritoneally to female Balb/C mice, they were taken up by macrophages of the peritoneum. When these particles were fluorescently labelled, intracellular localisation was observed. The expression of pro-inflammatory cytokines IL-2, IL-6, IL-12p70 and TNF-α in plasma and peritoneal lavage was found to remain at low concentration in PLGA nanoparticles treated mice as well as ZnO nanoparticles during the 24 hour period. However, these were significantly increased in lipopolysaccharide (LPS) treated mice. Of these pro-inflammatory cytokines, IL-6 and IL-12p70 were produced at the highest concentration in the positive control group. The anti-inflammatory cytokines IL-10 and chemokines INF-γ, IL-4, IL-5 remained at normal levels in PLGA treated mice. IL-10 and INF-γ were significantly increased in LPS treated mice. MCP-1 was found to be significantly produced in all groups in the first hours, except the saline treated mice. These results provide the first report to detail the induction of cytokine production by PLGA nanoparticles engineered for oral applications.

Ticks secrete bioactive components during feeding that assist them in gaining a blood meal. Compounds secreted are stored in granules until a stimulus induces secretion during feeding. Biogenesis of tick secretory granules has not been investigated before. An adequate understanding of granule biogenesis could advance our understanding of tick salivary gland biology and could aid in the rational design of tick control methods. Putative tick salivary gland proteins 1-4 (TSGP1-4) involved in granule biogenesis were identified in this study based on their abundance in salivary gland extracts and granule preparations and their ability to aggregate under conditions of slight acidity and high calcium concentration. TSGP2 and TSGP3 have been identified as previously described toxic and nontoxic homologues, respectively, while toxicity was also associated with TSGP4.

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Antimicrobial peptides such as ubiquicidin (UBI) are believed to differentiate between mammalian and bacterial or fungal cells. 99m Tc-UBI29-41 was previously tested for detecting infection in humans using SPECT. For the present study, the UBI fragment UBI29-41 (TGRAKRRMQYNRR) was conjugated to 1,4,7-triazacyclononane-triacetic acid (NOTA), radiolabeled with 68 Ga, and investigated in a rabbit infection model. Methods: 68 Ga was obtained from a 1.85-GBq 68 Ge/ 68 Ga generator. New Zealand White rabbits were anesthetized with ketamine/medetomidine before tracer administration and placed in a clinical PET/CT scanner. 68 Ga-1,4,7-triazacyclononane-1,4,7-triacetic-acid-ubiquicidin29-41 ( 68 Ga-NOTA-UBI29-41) was formulated in saline solution, and 101 6 41 MBq were administered intravenously. The tracer distribution was studied by PET/CT imaging in animals (a) that were healthy, (b) bearing muscular Staphylococcus aureus infections and turpentine oilinduced muscular inflammations, and (c) bearing ovalbumin-induced lung inflammations. Static PET/CT imaging was performed at different time intervals up to 120 min after injection. For calculation of target-to-nontarget ratios, standardized uptake values were normalized against healthy thigh muscle, representing nontargeted tissue. Results: PET/CT images of healthy animals showed predominant distribution in the kidneys, liver, and bladder; heart and spleen showed moderate, declining uptake, only. The biologic half-life in blood was 29 min. Urinary accumulation of 68 Ga-NOTA-UBI29-41 peaked at 3.8 6 0.91 percentage injected dose per gram (%ID) at 120 min, and 88 6 5.2 %ID was recovered in total urine. 68 Ga-NOTA-UBI29-41 imaging in (b) selectively visualized the muscular infection site and was differentiated from sterile inflammatory processes. Standardized uptake value ratios for muscles (infected/ inflamed) were 2.9 6 0.93, 2.9 6 0.50, 3.5 6 0.86, and 3.8 6 0.90 at 5, 30, 60, and 90 min after injection, respectively. Rabbit lungs with asthma showed insignificant uptake. Conclusion: 68 Ga-NOTA-UBI29-41 was strongly localized in bacteria-infected areas and minimally detected in a sterile inflammation area in rabbit muscles. The findings propose this compound to be an excellent first-line PET/CT tracer to allow the distinguishing of infection from inflammation.

Forensic analysis requires a keen detective mind, but the human mind has neither the abihty nor the time to process the millions of bytes on a typical computer hard disk. Digital forensic investigators need powerful tools that can automate many of the analysis tasks that are currently being performed manually. This paper argues that forensic analysis can greatly benefit from research in knowledge discovery and data mining, which has developed powerful automated techniques for analyzing massive quantities of data to discern novel, potentially useful patterns. We use the term "evidence mining" to refer to the apphcation of these techniques in the analysis phase of digital forensic investigations. This paper presents a novel approach involving the specialization of CRISP-DM, a cross-industry standard process for data mining, to CRISP-EM, an evidence mining methodology designed specifically for digital forensics. In addition to supporting forensic analysis, the CRISP-EM methodology off'ers a structured approach for defining the research gaps in evidence mining.