Nerve excitability studies characterize Kv1.1 fast potassium channel dysfunction in patients with episodic ataxia type 1

Episodic ataxia type 1 is a neuronal channelopathy caused by mutations in the KCNA1 gene encoding the fast K(+) channel subunit K(v)1.1. Episodic ataxia type 1 presents with brief episodes of cerebellar dysfunction and persistent neuromyotonia and is associated with an increased incidence of epilepsy. In myelinated peripheral nerve, K(v)1.1 is highly expressed in the juxtaparanodal axon, where potassium channels limit the depolarizing afterpotential and the effects of depolarizing currents. Axonal excitability studies were performed on patients with genetically confirmed episodic ataxia type 1 to characterize the effects of K(v)1.1 dysfunction on motor axons in vivo. The median nerve was stimulated at the wrist and compound muscle action potentials were recorded from abductor pollicis brevis. Threshold tracking techniques were used to record strength-duration time constant, threshold electrotonus, current/threshold relationship and the recovery cycle. Recordings from 20 patients from eight kindreds with different KCNA1 point mutations were compared with those from 30 normal controls. All 20 patients had a history of episodic ataxia and 19 had neuromyotonia. All patients had similar, distinctive abnormalities: superexcitability was on average 100% higher in the patients than in controls (P < 0.00001) and, in threshold electrotonus, the increase in excitability due to a depolarizing current (20% of threshold) was 31% higher (P < 0.00001). Using these two parameters, the patients with episodic ataxia type 1 and controls could be clearly separated into two non-overlapping groups. Differences between the different KCNA1 mutations were not statistically significant. Studies of nerve excitability can identify K(v)1.1 dysfunction in patients with episodic ataxia type 1. The simple 15 min test may be useful in diagnosis, since it can differentiate patients with episodic ataxia type 1 from normal controls with high sensitivity and specificity.

Identification of markers to characterize and sort human articular chondrocytes with enhanced in vitro chondrogenic capacity

OBJECTIVE: To identify markers associated with the chondrogenic capacity of expanded human articular chondrocytes and to use these markers for sorting of more highly chondrogenic subpopulations. METHODS: The chondrogenic capacity of chondrocyte populations derived from different donors (n = 21) or different clonal strains from the same cartilage biopsy specimen (n = 21) was defined based on the glycosaminoglycan (GAG) content of tissues generated using a pellet culture model. Selected cell populations were analyzed by microarray and flow cytometry. In some experiments, cells were sorted using antibodies against molecules found to be associated with differential chondrogenic capacity and again assessed in pellet cultures. RESULTS: Significance Analysis of Microarrays indicated that chondrocytes with low chondrogenic capacity expressed higher levels of insulin-like growth factor 1 and of catabolic genes (e.g., matrix metalloproteinase 2, aggrecanase 2), while chondrocytes with high chondrogenic capacity expressed higher levels of genes involved in cell-cell or cell-matrix interactions (e.g., CD49c, CD49f). Flow cytometry analysis showed that CD44, CD151, and CD49c were expressed at significantly higher levels in chondrocytes with higher chondrogenic capacity. Flow cytometry analysis of clonal chondrocyte strains indicated that CD44 and CD151 could also identify more chondrogenic clones. Chondrocytes sorted for brighter CD49c or CD44 signal expression produced tissues with higher levels of GAG per DNA (up to 1.4-fold) and type II collagen messenger RNA (up to 3.4-fold) than did unsorted cells. CONCLUSION: We identified markers that allow characterization of the capacity of monolayer-expanded chondrocytes to form in vitro cartilaginous tissue and enable enrichment for subpopulations with higher chondrogenic capacity. These markers might be used as a means to predict and possibly improve the outcome of cell-based cartilage repair techniques.

A computer-aided diagnostic system to characterize CT focal liver lesions: design and optimization of a neural network classifier

In this paper, a computer-aided diagnostic (CAD) system for the classification of hepatic lesions from computed tomography (CT) images is presented. Regions of interest (ROIs) taken from nonenhanced CT images of normal liver, hepatic cysts, hemangiomas, and hepatocellular carcinomas have been used as input to the system. The proposed system consists of two modules: the feature extraction and the classification modules. The feature extraction module calculates the average gray level and 48 texture characteristics, which are derived from the spatial gray-level co-occurrence matrices, obtained from the ROIs. The classifier module consists of three sequentially placed feed-forward neural networks (NNs). The first NN classifies into normal or pathological liver regions. The pathological liver regions are characterized by the second NN as cyst or "other disease." The third NN classifies "other disease" into hemangioma or hepatocellular carcinoma. Three feature selection techniques have been applied to each individual NN: the sequential forward selection, the sequential floating forward selection, and a genetic algorithm for feature selection. The comparative study of the above dimensionality reduction methods shows that genetic algorithms result in lower dimension feature vectors and improved classification performance.

Non-phenotypic tests to detect and characterize antibiotic resistance mechanisms in Enterobacteriaceae

In the past 2 decades, we have observed a rapid increase of infections due to multidrug-resistant Enterobacteriaceae. Regrettably, these isolates possess genes encoding for extended-spectrum β-lactamases (e.g., blaCTX-M, blaTEM, blaSHV) or plasmid-mediated AmpCs (e.g., blaCMY) that confer resistance to last-generation cephalosporins. Furthermore, other resistance traits against quinolones (e.g., mutations in gyrA and parC, qnr elements) and aminoglycosides (e.g., aminoglycosides modifying enzymes and 16S rRNA methylases) are also frequently co-associated. Even more concerning is the rapid increase of Enterobacteriaceae carrying genes conferring resistance to carbapenems (e.g., blaKPC, blaNDM). Therefore, the spread of these pathogens puts in peril our antibiotic options. Unfortunately, standard microbiological procedures require several days to isolate the responsible pathogen and to provide correct antimicrobial susceptibility test results. This delay impacts the rapid implementation of adequate antimicrobial treatment and infection control countermeasures. Thus, there is emerging interest in the early and more sensitive detection of resistance mechanisms. Modern non-phenotypic tests are promising in this respect, and hence, can influence both clinical outcome and healthcare costs. In this review, we present a summary of the most advanced methods (e.g., next-generation DNA sequencing, multiplex PCRs, real-time PCRs, microarrays, MALDI-TOF MS, and PCR/ESI MS) presently available for the rapid detection of antibiotic resistance genes in Enterobacteriaceae. Taking into account speed, manageability, accuracy, versatility, and costs, the possible settings of application (research, clinic, and epidemiology) of these methods and their superiority against standard phenotypic methods are discussed.

Evaluating gillnetting protocols to characterize lacustrine fish communities

Ecological research and monitoring of lacustrine ecosystems often requires a whole-lake assessment of fish communities. Gillnet sampling offers an efficient means of estimating abundance, biomass and fish community composition. However the choice of gillnet sampling protocol may influence lake characterization via physical properties of the nets and allocation of sampling effort between littoral, benthic and pelagic habitats. This paper compares two commonly used, whole-lake sampling protocols applied across 17 prealpine, subalpine and alpine European lakes ranging widely in size, depth and altitude to determine their relative strength for research and management applications. Effort-corrected estimates of abundance, biomass and species richness were correlated between the protocols and both distinguished the trout-dominated alpine communities from subalpine and prealpine lakes dominated by whitefish and perch. A considerable amount of variance remained unexplained between the two protocols however, which seemed to correspond with differences in the proportion of effort among benthic and pelagic habitats. We suggest that both the European standard (CEN) and vertical (VERT) netting protocols are suitable for assessing ecological status and monitoring changes in lake fish communities through time. However the details of each protocol should be kept in mind when comparing fish communities between lakes. Mesh sizes used in CEN nets produce a more even size frequency distribution, suggesting that this protocol is most appropriate for assessing size structure of fish assemblages. The high proportion of netting effort in benthic habitats shallower than 70 m depth under the CEN protocol means that, particularly in larger lakes, outcomes will be disproportionately influenced by the ecological condition of this habitat. The VERT protocol presumably provides a more accurate estimate of whole-lake CPUE and community composition because effort, in terms of net area, is more evenly distributed across the entire volume of the lake. This is particularly important in large and deep lakes where pelagic habitats occupy a high proportion of the lake volume.