Spine-shaped gold protrusions improve the adherence and electrical coupling of neurons with the surface of micro-electronic devices

Interfacing neurons with micro- and nano-electronic devices has been a subject of intense study over the last decade. One of the major problems in assembling efficient neuro-electronic hybrid systems is the weak electrical coupling between the components. This is mainly attributed to the fundamental property of living cells to form and maintain an extracellular cleft between the plasma membrane and any substrate to which they adhere. This cleft shunts the current generated by propagating action potentials and thus reduces the signal-to-noise ratio. Reducing the cleft thickness, and thereby increasing the seal resistance formed between the neurons and the sensing surface, is thus a challenge and could improve the electrical coupling coefficient. Using electron microscopic analysis and field potential recordings, we examined here the use of gold micro-structures that mimic dendritic spines in their shape and dimensions to improve the adhesion and electrical coupling between neurons and micro-electronic devices. We found that neurons cultured on a gold-spine matrix, functionalized by a cysteine-terminated peptide with a number of RGD repeats, readily engulf the spines, forming tight apposition. The recorded field potentials of cultured Aplysia neurons are significantly larger using gold-spine electrodes in comparison with flat electrodes.     

The need and ability to achieve cognitive structuring: Individual differences that moderate the effect of stress on information processing.

The authors examined the hypothesis that the interaction between the need for cognitive structure (NCS) and the ability to achieve cognitive structure (AACS) moderates the effect of stress on information processing. NCS is the preference for using cognitive structuring, as opposed to piecemeal processes, as a means to achieve certainty. AACS is the extent to which individuals are able to apply information processes that are consistent with their levels of NCS. The hypothesis was validated in 4 studies, which showed that stress increased high-AACS participants' use of cognitive structuring if they had high NCS and reduced it if they had low NCS. An opposite effect was found for low-AACS participants. The implications of these results for the understanding of the mechanisms responsible for the effect of stress on information processing are discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Relation between Pro-inflammatory Cytokines and Acetylcholine Levels in Relapsing-Remitting Multiple Sclerosis Patients

Multiple sclerosis (MS) is a chronic inflammatory, demyelinating and neurodegenerative disorder. Since acetylcholine (ACh) is known to participate in the inflammatory response, we investigated the possible relationship between pro-inflammatory cytokines and acetylcholine levels in relapsing-remitting multiple sclerosis (RR-MS) patients. Levels of ACh and pro-inflammatory cytokines IL1-β and IL-17 were measured both in cerebrospinal fluid (CSF) and sera of 22 RR-MS patients in the relapsing phase and in 17 control subjects affected by other non-neurological diseases (OND). We observed higher levels of pro-inflammatory cytokines such as IL-1β and IL-17 in both CSF and serum of RR-MS patients compared to control subjects. Moreover, ACh levels were lower in CSF and serum of RR-MS patients compared to levels of control subjects. Although the relationship between high inflammatory cytokine levels and low ACh levels need to be further investigated in the future, our data suggest that IL-1β, and cytokines induced by it, such as IL-17 and ACh, may be involved in the pathogenesis of MS.     

Consuming cassava as a staple food places children 2-5 years old at risk for inadequate protein intake,an observational study in Kenya and Nigeria

Background  

Inadequate protein intake is known to be deleterious in animals. Using WHO consensus documents for human nutrient requirements, the protein:energy ratio (P:E) of an adequate diet is > 5%. Cassava has a very low protein content. This study tested the hypothesis that Nigerian and Kenyan children consuming cassava as their staple food are at greater risk for inadequate dietary protein intake than those children who consume less cassava.     

(<Emphasis Type="Italic">α</Emphasis>, <Emphasis Type="Italic">k</Emphasis>)-anonymous data publishing

Privacy preservation is an important issue in the release of data for mining purposes. The k-anonymity model has been introduced for protecting individual identification. Recent studies show that a more sophisticated model is necessary to protect the association of individuals to sensitive information. In this paper, we propose an (α, k)-anonymity model to protect both identifications and relationships to sensitive information in data. We discuss the properties of (α, k)-anonymity model. We prove that the optimal (α, k)-anonymity problem is NP-hard. We first present an optimal global-recoding method for the (α, k)-anonymity problem. Next we propose two scalable local-recoding algorithms which are both more scalable and result in less data distortion. The effectiveness and efficiency are shown by experiments. We also describe how the model can be extended to more general cases.     

Query rewritings using views for XPath queries,framework, and methodologies

Query rewriting using views is a technique that allows a query to be answered efficiently by using pre-computed materialized views. It has many applications, such as data caching, query optimization, schema integration, etc. This issue has been studied extensively for relational databases and, as a result, the technology is maturing. For XML data, however, the work is inadequate. Recently, several frameworks have been proposed for query rewriting using views for XPath queries, with the requirement that a rewriting must be complete. In this paper, we study the problem of query rewriting using views for XPath queries without requiring that the rewriting be complete. This will increase its applicability since in many cases, complete rewritings using views do not exist. We give formal definitions for various concepts to formulate the problem, and then propose solutions. Our solutions are built under the framework for query containment. We look into the problem from both theoretic perspectives, and algorithmic approaches. Two methods to generate rewritings using views are proposed, with different characteristics in terms of generalities and efficiencies. The maximality properties of the rewritings generated by these methods are discussed.     

Factors contributing to officers' fatigue in high-speed maritime craft operations

The purpose of this study was to investigate the difference in the level of fatigue induced by high-speed maritime craft operation between the day- and night-shift officers. The demographic and work-related factors that contribute to fatigue were also explored. A total of 93 high-speed maritime craft officers participated in the survey, of whom 35 worked a day shift (Mean age=48.3 years) and 58 worked a night shift (Mean age=45.8 years). Fatigue experience was measured with the Chinese version of the Swedish Occupational Fatigue Inventory (SOFI-C) at the beginning, in the middle and at the end of the work shift. Information on age, work experience, perceived voyage difficulty and duty schedule was obtained. The study found that the night-shift officers seemed to manifest an overall higher level of perceived fatigue than the day-shift officers, while the day-shift officers demonstrated a fatigue carry-over effect across the two workdays. Besides the shift pattern, age, experience in operating high-speed maritime craft and perceived voyage difficulty were the significant factors contributing to the officers' fatigue experience. The finding that the fatigue experience associated with high-speed maritime craft operation has a rapid and accumulative nature suggests that different occupational safety and health guidelines should be devised for these two groups of officers.     

Top-k typicality queries and efficient query answering methods on large databases

Finding typical instances is an effective approach to understand and analyze large data sets. In this paper, we apply the idea of typicality analysis from psychology and cognitive science to database query answering, and study the novel problem of answering top-k typicality queries. We model typicality in large data sets systematically. Three types of top-k typicality queries are formulated. To answer questions like “Who are the top-k most typical NBA players?”, the measure of simple typicality is developed. To answer questions like “Who are the top-k most typical guards distinguishing guards from other players?”, the notion of discriminative typicality is proposed. Moreover, to answer questions like “Who are the best k typical guards in whole representing different types of guards?”, the notion of representative typicality is used. Computing the exact answer to a top-k typicality query requires quadratic time which is often too costly for online query answering on large databases. We develop a series of approximation methods for various situations: (1) the randomized tournament algorithm has linear complexity though it does not provide a theoretical guarantee on the quality of the answers; (2) the direct local typicality approximation using VP-trees provides an approximation quality guarantee; (3) a local typicality tree data structure can be exploited to index a large set of objects. Then, typicality queries can be answered efficiently with quality guarantees by a tournament method based on a Local Typicality Tree. An extensive performance study using two real data sets and a series of synthetic data sets clearly shows that top-k typicality queries are meaningful and our methods are practical.     

Efficient Rule-Based Attribute-Oriented Induction for Data Mining

Data mining has become an important technique which has tremendous potential in many commercial and industrial applications. Attribute-oriented induction is a powerful mining technique and has been successfully implemented in the data mining system DBMiner (Han et al. Proc. 1996 Int'l Conf. on Data Mining and Knowledge Discovery (KDD'96), Portland, Oregon, 1996). However, its induction capability is limited by the unconditional concept generalization. In this paper, we extend the concept generalization to rule-based concept hierarchy, which enhances greatly its induction power. When previously proposed induction algorithm is applied to the more general rule-based case, a problem of induction anomaly occurs which impacts its efficiency. We have developed an efficient algorithm to facilitate induction on the rule-based case which can avoid the anomaly. Performance studies have shown that the algorithm is superior than a previously proposed algorithm based on backtracking.