Macrophage Immunomodulation Through New Polymers that Recapitulate Functional Effects of Itaconate as a Power House of Innate Immunity

Itaconate (ITA) is an emerging powerhouse of innate immunity with therapeutic potential that is limited in its ability to be administered in a soluble form. A library of polyester materials that incorporate ITA into polymer backbones resulting in materials with inherent immunoregulatory behavior is developed. Harnessing hydrolytic degradation release from polyester backbones, ITA polymers result in the mechanism specific immunoregulatory properties on macrophage polarization in vitro. In a functional assay, the polymer-released ITA inhibits bacterial growth on acetate. Translation to an in vivo model of biomaterial associated inflammation, intraperitoneal injection of ITA polymers demonstrate a rapid resolution of inflammation in comparison to a control polymer silicone, demonstrating the value of sustained biomimetic presentation of ITA.     

Ethnocultural factors and substance abuse: Toward culturally sensitive treatment models.

Discusses the role of ethnocultural factors in understanding and treating substance abuse disorders. Research and theory suggest that acculturation experiences, sources of stress, coping mechanisms, social support variations, and beliefs about substance use are key factors associated with differential patterns of substance abuse among some ethnic groups, particularly African Americans, Hispanics, and Native Americans. In recent years, models of substance abuse intervention specifically targeting these ethnic groups have been developed. The author examines the movement toward culturally sensitive psychosocial treatment models. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Recognizing malicious software behaviors with tree automata inference

We explore how formal methods and tools of the verification trade could be used for malware detection and analysis. In particular, we propose a new approach to learning and generalizing from observed malware behaviors based on tree automata inference. Our approach infers k-testable tree automata from system call dataflow dependency graphs. We show how inferred automata can be used for malware recognition and classification.     

The Applicability of Cognitive Mediational and Moderational Models to Explain Children's Depression Inventory Factor Scores in Urban Youth.

This investigation examined whether cognition serves as a direct factor, mediates, or moderates the relationship between stressful life events and Children's Depression Inventory (CDI; Kovacs, 1992) factor scores in urban, ethnic minority youth. Ninety-eight middle school students completed measures of stressful life events, cognition (cognitive triad and locus of control), and depressive symptoms. Results provided support for both mediating and moderating models of depression. Specifically, the cognitive triad mediated the relationship between stressful life events and depressive symptom categories of negative mood, ineffectiveness, and anhedonia, while it interacted with stressful life events to predict negative self-esteem. In addition, locus of control was found to interact with stressful life events to predict anhedonia. Finally, the diathesis-stress model was not supported when predicting the CDI Interpersonal Problems factor score, which taps externalizing behaviors. Implications for school psychology research and practice include the importance of including measures of stressful life events and cognitive styles in assessment of children's social-emotional functioning. In addition, results highlight the need to target children's perceptions for intervention since they appear to play a significant role in psychological reactions to stressors. (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

Evaluation of a statewide foodborne illness complaint surveillance system in Minnesota, 2000 through 2006

Foodborne outbreaks are detected by recognition of similar illnesses among persons with a common exposure or by identification of case clusters through pathogen-specific surveillance. PulseNet USA has created a national framework for pathogen-specific surveillance, but no comparable effort has been made to improve surveillance of consumer complaints of suspected foodborne illness. The purpose of this study was to characterize the complaint surveillance system in Minnesota and to evaluate its use for detecting outbreaks. Minnesota Department of Health foodborne illness surveillance data from 2000 through 2006 were analyzed for this study. During this period, consumer complaint surveillance led to detection of 79% of confirmed foodborne outbreaks. Most norovirus infection outbreaks were detected through complaints. Complaint surveillance also directly led or contributed to detection of 25% of salmonellosis outbreaks. Eighty-one percent of complainants did not seek medical attention. The number of ill persons in a complainant's party was significantly associated with a complaint ultimately resulting in identification of a foodborne outbreak. Outbreak confirmation was related to a complainant's ability to identify a common exposure and was likely related to the process by which the Minnesota Department of Health chooses complaints to investigate. A significant difference (P < 0.001) was found in incubation periods between complaints that were outbreak associated (median, 27 h) and those that were not outbreak associated (median, 6 h). Complaint systems can be used to detect outbreaks caused by a variety of pathogens. Case detection for foodborne disease surveillance in Minnesota happens through a multitude of mechanisms. The ability to integrate these mechanisms and carry out rapid investigations leads to improved outbreak detection.     

The renaissance of yeasts as microbial factories in the modern age of biomanufacturing

Yeasts are essential for many processes, including the production of some of our most beloved foods and beverages. Less is known to the public about the far-reaching impacts of yeasts on other products such as biofuels, pharmaceuticals, and industrial products. By leveraging and combining newly discovered yeast genetic diversity with now affordable and efficient genetic engineering and synthetic biology tools, academic and industrial yeast labs have designed yeast cell factories for a wide range of novel applications such as the production of medicines, components of human breast milk, heme for meat substitutes, bioplastics, and other biomaterials. This review covers the newest technologies developed for yeast research including synthetic biology and their use in the engineering of yeast cell factories for emerging applications.     

Using conscious reflection,group processes,and AI to facilitate development of expertise

Three experiments investigated procedures derived from research on knowledge acquisition, group processes, and artificial intelligence for facilitating the development of expertise. In each experimental session, subjects learned to control a simulated sugar production factory. Then they formulated written policies for controlling sugar production either alone as individuals or in small groups. An adaptive AI system provided feedback on policy quality. The research also investigated the use of forced reflective practice in which learners attempted to predict what their policy would do while performing the task. The AI system provided feedback about what their policy would have done in each situation and the outcome based on their policy's response or their suggested alternative response. Results indicated that group interaction and feedback from the AI system improved policy quality. However, only when all three procedures were employed, group interaction, AI feedback, and forced reflective practice, was the development of individual expertise on the task enhanced.     

Air-dictated bottom spray process: impact of fluid dynamics on granule growth and morphology

Background: Growing interest in the use of the less-explored bottom spray technique for fluidized bed granulation provided impetus for this study. Aim: The impact of fluid dynamics (air accelerator insert diameter; partition gap) and wetting (binder spray rate) on granule properties were investigated. Method: In this 3³ full factorial study, the results were fitted to a quadratic model using response surface methodology. The air velocity at the spray granulation zone for the investigated conditions was measured using a pitot tube. Results: Air accelerator insert diameter correlated to measured air velocity at the spray granulation zone and was found to not only dictate growth but also influence granule morphology. The partition gap was found to play important roles in regulating particle movement into the spray granulation zone and optimizing process yields, whereas binder spray rate significantly affected granule morphology but not granule size. Conclusions: Unlike conventional fluidized bed granulation, ease of modulation of fluid dynamics and insensitivity of the bottom spray process to wetting allow flexible control of granule size, shape, and flow. Its good drying ability also indicated potential use in granulating moisture-sensitive materials.