A positive feedback loop between HER2 and ADAM12 in human head and neck cancer cells increases migration and invasion.

Increased activation of epidermal growth factor receptor (EGFR) family members such as HER2/Erbb2 can result in more aggressive disease, resistance to chemotherapy and reduced survival of head and neck squamous cell carcinoma (HNSCC) patients. In order to identify mechanisms through which these receptor tyrosine kinases accelerate tumor progression, the regulation of metalloprotease expression by EGFR family members was investigated in 11 squamous cell carcinoma (SCC) cell lines. HER2 expression was significantly correlated with ADAM12 (A Disintegrin And Metalloprotease 12) expression in these cell lines and was co-expressed in human head and neck cancers. Inhibition of HER2 or EGFR decreased ADAM12 transcripts whereas HER2 transfection upregulated ADAM12 expression. To understand the molecular mechanisms underlying HER2 regulation of ADAM12, we investigated the signaling pathways directing ADAM12 production in SCC cells. Inhibition of phosphatidyl inositol-3-kinase or mammalian target of rapamycin decreased ADAM12 transcripts in HER2-expressing SCC cells, whereas transfection with AKT increased ADAM12 mRNA. Experiments utilizing ADAM12 transfection or siRNA targeting of ADAM12 revealed that the protease increased both the migration and invasiveness of oral SCC cells. Surprisingly, ADAM12 also increased HER2 message, protein levels and activity through an Ets1-dependent mechanism. Collectively, these results reveal a novel positive activation loop between ADAM12 and HER2 that may contribute to HNSCC progression.

Fuzzy methods in tremor assessment, prediction, and rehabilitation.

Tremor is a disabling condition for a large segment of population, mainly elderly. To the present date, there are no adequate tools to diagnose and help rehabilitation of subjects with tremor, but recently there is a tremendous surge of interest in the research in the field. We report on the use of fuzzy methods in applications for rehabilitation, namely in tremor diagnosing and control. We synthesize our results regarding the characterization of the tremor by means of nonlinear dynamics techniques and fuzzy logic, and the prediction of tremor movements in view of rehabilitation purposes. Based on linear and nonlinear analysis of tremor, and using fuzzy aggregation, the fusing of tremor parameters in global functional disabling factors is proposed. Nonlinear dynamic parameters, namely correlation dimension and Lyapunov exponent is used in order to improve the assessment of tremor. The benefits of the fuzzy fused tremor parameters rely on more complete and accurate assessment of the functional impairment and on improved feedback for rehabilitation, based on the fused parameters of the tremor. Further steps in rehabilitation may require external muscular control. In turn, the control of tremor by electrical stimulation requires movement prediction. Several neural and neuro-fuzzy predictors are compared and a neuro-fuzzy predictor is presented, allowing us five-step ahead prediction, with an RMS error of the order of 10%. The benefits of the neuro-fuzzy predictor are good prediction capability, versatility, and apparently a high robustness to individual variations of the tremor. The reported research, which extended over several years and included development of sensors, equipment, and software, has been aimed to development of products. The results may also open new ways in tremor rehabilitation.

Report of research activities in fuzzy AI and medicine at USF CSE.

Several projects involving the use of fuzzy and neuro-fuzzy methods in medical applications, developed by members of the Department of Computer Science and Engineering, University of South Florida, Tampa, Florida, are briefly reviewed. The successful applications are emphasized.

Knowledge discovery in time series databases.

Adding the dimension of time to databases produces time series databases (TSDB) and introduces new aspects and difficulties to data mining and knowledge discovery. In this correspondence, we introduce a general methodology for knowledge discovery in TSDB. The process of knowledge discovery in TSDR includes cleaning and filtering of time series data, identifying the most important predicting attributes, and extracting a set of association rules that can be used to predict the time series behavior in the future. Our method is based on signal processing techniques and the information-theoretic fuzzy approach to knowledge discovery. The computational theory of perception (CTP) is used to reduce the set of extracted rules by fuzzification and aggregation. We demonstrate our approach on two types of time series: stock-market data and weather data.

On fuzzy correlations.

A general framework for dealing with numerical measurements in an approximate, uncertain, or fuzzy environment is presented. A fuzzy measurement is defined. It possesses several unique properties, which arise from its physical nature and distinguish it from concepts such as the fuzzy number. These properties, which include the fuzzy correlation term and the fuzzy Equality relation, follow directly from physical considerations. The introduction of the fuzzy correlation term provides a mathematical tool for representing any correlation relations, which may exist between different fuzzy measurements. The main function of the fuzzy correlation term is to eliminate, or filter out, measurement values that are unlikely, given other fuzzy measurements. Thus, using the fuzzy correlation term, the range of possible measurement values is limited by physical realities. The information represented by the fuzzy correlation term is shown to be of great value in providing a wider picture of reality than it is possible to obtain by simply considering individual fuzzy measurements. Arithmetic operations on fuzzy measurements and functions of fuzzy measurements are also discussed, leading to the derivation of the fuzzy Riemann integral and its applications.

Granular neural networks for numerical-linguistic data fusion and knowledge discovery.

In this paper, we present a neural-networks-based knowledge discovery and data mining (KDDM) methodology based on granular computing, neural computing, fuzzy computing, linguistic computing, and pattern recognition. The major issues include 1) how to make neural networks process both numerical and linguistic data in a data base, 2) how to convert fuzzy linguistic data into related numerical features, 3) how to use neural networks to do numerical-linguistic data fusion, 4) how to use neural networks to discover granular knowledge from numerical-linguistic data bases, and 5) how to use discovered granular knowledge to predict missing data. In order to answer the above concerns, a granular neural network (GNN) is designed to deal with numerical-linguistic data fusion and granular knowledge discovery in numerical-linguistic databases. From a data granulation point of view, the GNN can process granular data in a database. From a data fusion point of view, the GNN makes decisions based on different kinds of granular data. From a KDDM point of view, the GNN is able to learn internal granular relations between numerical-linguistic inputs and outputs, and predict new relations in a database. The GNN is also capable of greatly compressing low-level granular data to high-level granular knowledge with some compression error and a data compression rate. To do KDDM in huge data bases, parallel GNN and distributed GNN will be investigated in the future.

Normal forms of fuzzy middle and fuzzy contradictions.

The expressions of "excluded middle" and "crisp contradiction" are reexamined starting with their original linguistic expressions which are first restated in propositional and then predicate forms. It is shown that, in order to generalize the truth tables and hence the normal forms, the membership assignments in predicate expressions must be separated from their truth qualification. In two-valued logic, there is no need to separate them from each other due to reductionist Aristotalean dichotomy. Whereas, in infinite (fuzzy) valued set and logic, the separation of membership assignments from their truth qualification forms the bases of a new reconstruction of the truth tables. The results obtained from these extended truth tables are reducible to their Boolean equivalents under the axioms of Boolean theory. Whereas, in fuzzy set and logic theory, we obtain a richer and more complex interpretations of the "fuzzy middle" and "fuzzy contradiction."

Comments on "Constraints on belief functions imposed by fuzzy random variables": some technical remarks on Romer/Kandel.

First, we would like to thank V. Kratschmer for his validation of our results in the paper regarding the belief measure by using a topological approach. Though assertions (1) and (3) are presented in a weakened fashion, our results still remain valid, as he claims. It is true that assertion (2) has been proved by us only for Borel sets B, which have at most countable components. We were not able to prove the same result for Borel sets with uncountable components (such as the irrational numbers, for example) using our line of reasoning. We therefore applaud the proof presented by V. Kratschmer for the more general Borel sets using an interesting use of some topological properties induced by the Hansdorff metric defined on the space of closed intervals of the real numbers. This certainly makes our original approach to fuzzy data analysis combining fuzzy sets theory and Dempster-Shafer even more useful.

Somadendritic backpropagation of action potentials in cortical pyramidal cells of the awake rat.

The invasion of fast (Na+) spikes from the soma into dendrites was studied in single pyramidal cells of the sensorimotor cortex by simultaneous extracellular recordings of the somatic and dendritic action potentials in freely behaving rats. Field potentials and unit activity were monitored with multiple-site silicon probes along trajectories perpendicular to the cortical layers at spatial intervals of 100 micron. Dendritic action potentials of individual layer V pyramidal neurons could be recorded up to 400 micron from the cell body. Action potentials were initiated at the somatic recording site and traveled back to the apical dendrite at a velocity of 0.67 m/s. Current source density analysis of the action potential revealed time shifted dipoles, supporting the view of active spike propagation in dendrites. The presented method is suitable for exploring the conditions affecting the somadendritic propagation action of potentials in the behaving animal.

Compensatory neurofuzzy systems with fast learning algorithms.

In this paper, a new adaptive fuzzy reasoning method using compensatory fuzzy operators is proposed to make a fuzzy logic system more adaptive and more effective. Such a compensatory fuzzy logic system is proved to be a universal approximator. The compensatory neural fuzzy networks built by both control-oriented fuzzy neurons and decision-oriented fuzzy neurons cannot only adaptively adjust fuzzy membership functions but also dynamically optimize the adaptive fuzzy reasoning by using a compensatory learning algorithm. The simulation results of a cart-pole balancing system and nonlinear system modeling have shown that: 1) the compensatory neurofuzzy system can effectively learn commonly used fuzzy IF-THEN rules from either well-defined initial data or ill-defined data; 2) the convergence speed of the compensatory learning algorithm is faster than that of the conventional backpropagation algorithm; and 3) the efficiency of the compensatory learning algorithm can be improved by choosing an appropriate compensatory degree.

Defuzzification using most typical values.

A new approach for the defuzzification process, based on the Most Typical Value (MTV) concept, is being introduced and investigated. It assumes that the single decision, based on the output fuzzy subset, should represent a typical value of this set, rather than a numerical "central tendency" of its elements. The MTV defuzzification method is compared with previous defuzzification procedures and its applicability is illustrated.

Cellular-synaptic generation of sleep spindles, spike-and-wave discharges, and evoked thalamocortical responses in the neocortex of the rat.

Thalamocortical neuronal oscillations underlie various field potentials that are expressed in the neocortex, including sleep spindles and high voltage spike-and-wave patterns (HVSs). The mechanism of extracellular current generation in the neocortex was studied in the anesthetized and awake rat. Field potentials and unit activity were recorded simultaneously along trajectories perpendicular to the cortical layers at spatial intervals of 100 microm by multiple-site recording silicon probes. Current source density (CSD) analysis revealed that the spatial positions of sinks in layers IV, V-VI, and II-III and of the accompanying sources were similar during sleep spindles, HVSs, and thalamic-evoked responses, although their relative strengths and timings differed. The magnitude and relative timing of the multiple pairs of sinks and sources determined the amplitude variability of HVSs and sleep spindles. The presence of temporally shifted dipoles was also supported by the time distribution of unit discharges in different layers. Putative interneurons discharged with repetitive bursts of 300-500 Hz. The spike component of HVSs was associated with fast field oscillations (400-600 Hz "ripples"). Discharges of pyramidal cells were phase-locked to the ripples. These findings indicate that the major extracellular currents underlying sleep spindles, HVSs, and evoked responses result from activation of intracortical circuitries. We hypothesize that the fast field ripples reflect summed IPSPs in pyramidal cells resulting from the high frequency barrage of interneurons.

On typical values and fuzzy integrals.

A new approach for obtaining a typical value of a fuzzy set as a fuzzy integral is developed by replacing the classic Lebesgue measure with the "typicality" measure. A new method for representing and calculating the one-dimensional fuzzy integral with respect to arbitrary measure derived by monotonic increasing function is proposed and its applicability is illustrated with examples.

Lack of hippocampal involvement in a rat model of petit mal epilepsy.

Although petit mal epilepsy is believed to arise from the thalamocortical system, it has been suggested recently that high-voltage spike-and-wave activity (HVS) in mutant mice can cause structural reorganization in the hippocampus, similar to that seen in temporal lobe epilepsy. We tested this assumption in rat strains with low and high incidence of HVS. No relationship was found between mossy fiber sprouting and HVS incidence. Hippocampal neurons were not driven by HVS. These findings suggest that petit mal seizures do not invade the hippocampus and are not causally related to sprouting of the mossy fibers.

Genetic threshold hypothesis of neocortical spike-and-wave discharges in the rat: an animal model of petit mal epilepsy.

Neocortical high-voltage spike-and-wave discharges (HVS) in the rat are an animal model of petit mal epilepsy. Genetic analysis of total duration of HVS (s/12 hr) in reciprocal F1 and F2 hybrids of F344 and BN rats indicated that the phenotypic variability of HVS cannot be explained by a simple, monogenic Mendelian model. Biometrical analysis suggested the presence of additive, dominance, and sex-linked-epistatic effects, buffering maternal influence, and heterosis. High correlation was observed between average duration (s/episode) and frequency of occurrence of spike-and-wave episodes (n/12 hr) in parental and segregating generations, indicating that common genes affect both duration and frequency of the spike-and-wave pattern. We propose that both genetic and developmental-environmental factors control an underlying quantitative variable, which, above a certain threshold level, precipitates HVS discharges. These findings, together with the recent availability of rat DNA markers for total genome mapping, pave the way to the identification of genes that control the susceptibility of the brain to spike-and-wave discharges.

Spike-and-wave epilepsy in rats: sex differences and inheritance of physiological traits.

Spontaneously occurring spike-and-wave patterns were examined in seven to eight-month-old rats of the inbred Fischer 344 and Brown Norway strains and their F1 and F2 hybrids. Neocortical activity and movement were monitored for 12 night h. Spike-and-wave episodes were identified by a three-layer back-propagation neural network. The incidence, average duration and total duration of spike-and-wave episodes were significantly higher in F1 males and F2 hybrids than in the parental strains. Male rats of the Brown Norway strain had significantly more and longer episodes than females, whereas no sex differences were present in Fischer rats. The average intraepisodic frequency of spike-and-wave patterns was significantly lower in Fischer rats than in the other groups and significantly higher in males than females. Tremor (myoclonic movements) associated with spike-and-wave episodes was absent or of very small amplitude in Fischer rats but frequent and of large amplitude in Brown Norway rats and their F1 and F2 descendants. Most of the interstrain differences were limited to male rats. Spike-and-wave episodes recurred at predictable short-term (10-30 s) and long-term (15-30 min) periods. The long-term oscillation corresponded to a similar fluctuation of motor activity. The maximum probability of spike-and-wave patterns occurred at a relatively narrow range of delta power (0-3.1 Hz) of the background EEG activity. Systemic administration of the adrenergic alpha-2 agonist, clonidine, increased the incidence of spike-and-wave episodes several-fold. The total duration of spike-and-wave episodes in the clonidine sessions (15 min) and night sessions (12 h test) correlated significantly. We suggest that several genes interact with maturational, environmental and endocrine factors, resulting in sex differences, and produce the variety of EEG and behavioral findings encountered. In addition, we submit that the clonidine test may be useful in genetic investigations of human absence epilepsies. The findings of this work demonstrate that genetic manipulation of rodents is a promising method for producing analogous models for the various forms of human absence epilepsies.

Cerebellar neuronal activity correlates with spike and wave EEG patterns in the rat.

In this study we investigated the involvement of the cerebellum in high voltage spike-and-wave spindles, a rodent model of petit mal epilepsy. High voltage spindles, recorded epidurally from the sensorimotor neocortex, were correlated with single or multiple unit activity in the cerebellar cortex and deep cerebellar nuclei. The majority of neurons or neuronal groups in the cerebellum (77.9%) fired rhythmically and phase-locked with the high voltage spindles, either during the spike (43.2%; n = 41) or during the wave (34.7%; n = 33) component of the high voltage spindle. Tremor of the head and neck musculature, recorded with an accelero-meter, occurred during the high voltage spindle in approximately half of the rats. When present, rhythmic movement occurred predominantly during the wave phase of the high voltage spindle. The remaining half of the rats did not show tremor during high voltage spindles but, nevertheless, had cerebellar units that burst during the spike or wave phase of the high voltage spindle. These latter results demonstrate that phase-locked bursting of cerebellar units during high voltage spindle is independent of rhythmic movement. The findings suggest that rhythmic output from the cerebellum may contribute to the maintenance of generalized petit mal seizures.

Survival of 2,4-dichlorophenoxyacetic acid degrading Alcaligenes eutrophus AE0106(pR0101) in lake water microcosms.

Survival of the 2,4-dichlorophenoxyacetic acid (2,4-D) degrading Alcaligenes eutrophus strain AEO 106 harboring the catabolic plasmid pRO101 was studied in lake water from the eutrophic lake Frederiksborg Slotssø. Survival experiments were performed for periods of 7 days in laboratory microcosms containing filtered (0.2-µm pore size) or natural lake water amended with increasing concentrations of 2,4-D. A. eutrophus AE0106 was detected by combining the fluorescent antibody method with selective and nonselective plating followed by colony blotting and colony hybridization. Comparison of colony blotting and colony hybridization demonstrated that the A. eutrophus AE0106 host organism and the catabolic plasmid pRO101 had similar fates in the model system employed. In all experiments culturable counts of A. eutrophus AE0106 were lower than fluorescent antibody counts and frequently a decline in culturable counts occurred at times when the fluorescent antibody method showed an increasing population size. Amendment with 2,4-D increased survival of A. eutrophus AE0106 both in filtered and in natural lake water. Survival was always poorer in model systems with natural water than in 0.2 µm-filtered water.

Leukocyte migration inhibitory factor (LIF) to sperm from autoimmune men in infertile couples.

Leukocyte migration inhibitory factor (LIF) is produced by lymphocytes with receptors specific to sensitizing antigens. This principle was used to detect possible antigenic differences between sperm of autoimmune and nonautoimmune men. Sixteen fertile and 91 infertile couples were screened for cytotoxic and hemagglutinating antibodies to sperm from their husbands and controls. Their lymphocytes were tested for the production of LIF to sperm extracts and seminal plasma from the husbands and controls by a direct leukocyte migration inhibition assay. Twenty-nine of 35 men producing LIF to sperm and/or seminal plasma were positive for sperm antibodies (p = 0.0004, vs sperm antibody-negative controls). Twenty-three of 29 wives with LIF production had sperm-autoimmune husbands (p = 0.04). Leukocyte migration was significantly inhibited in sperm-autoimmune men by autologous sperm extracts and seminal plasma in contrast to control sperm extracts and seminal plasma (p = 0.0006 and 0.001, respectively). The wives of autoimmune men had significantly higher LIF responses to their husbands' sperm extracts than to other antigens (p = 0.02). Men with cytotoxic antibodies in their seminal plasma produced LIF to autologous sperm (p = 0.001). It is suggested that certain sperm and seminal plasma antigens of autoimmune men may lead to specific humoral and cell-mediated immune responses in both partners.

Changes in future time perception of day hospital psychiatric patients in response to small group treatment approaches.

Attempted to assess the effects of small group approaches on future time perception of psychiatric patients in a day hospital. The research employed two patient groups within the day hospital: A control group, (N = 12) which received routine day hospital treatment, and an experimental group, (N = 12) which received, in addition, the small group treatment. Measures of future time perception were administered to both groups before and after a 12-week treatment. Results indicated significant positive changes in response to group treatment on Future Events and the dimension of Importance. However, no positive significant differences were found on Time Extension, Directionality, and Quality of Affect. While it is not within the scope of this research to evaluate whether the secured change can be maintained, it was clear that in immediate posttesting important changes had resulted from the treatment strategy.