Miniaturized Multi Sensor Implant for Monitoring of Hemodynamic Parameters.

t a novel miniaturized multi sensor implant for monitoring hemodynamic parameters in cardiovascular regions. Pressure measurements are performed with a highly accurate capacitive pressure sensor. An additional acceleration and temperature sensor allows compensating the impact of patient's inclination and temperature variations on the pressure measurement, respectively. A multi-functional transponder application-specific integrated circuit (ASIC) manages sensor signal processing, storage of ID, sensor calibration data, telemetric energy, and data transmission with an extracorporeal reading unit. Each component of the implant is assembled on a low temperature co-fired ceramics (LTCC) circuit board with an integrated antenna coil enabling an inductive near-field coupling at a frequency of 13.56 MHz. For a streamlined shape and reduction of thrombogenicity, the implant is encapsulated by biocompatible polymers.

Disease-relevant signalling-pathways in head and neck cancer: Taspase1's proteolytic activity fine-tunes TFIIA function.

Head and neck cancer (HNC) is the seventh most common malignancy in the world and its prevailing form, the head and neck squamous cell carcinoma (HNSCC), is characterized as aggressive and invasive cancer type. The transcription factor II A (TFIIA), initially described as general regulator of RNA polymerase II-dependent transcription, is part of complex transcriptional networks also controlling mammalian head morphogenesis. Posttranslational cleavage of the TFIIA precursor by the oncologically relevant protease Taspase1 is crucial in this process. In contrast, the relevance of Taspase1-mediated TFIIA cleavage during oncogenesis of HNSCC is not characterized yet. Here, we performed genome-wide expression profiling of HNSCC which revealed significant downregulation of the TFIIA downstream target CDKN2A. To identify potential regulatory mechanisms of TFIIA on cellular level, we characterized nuclear-cytoplasmic transport and Taspase1-mediated cleavage of TFIIA variants. Unexpectedly, we identified an evolutionary conserved nuclear export signal (NES) counteracting nuclear localization and thus, transcriptional activity of TFIIA. Notably, proteolytic processing of TFIIA by Taspase1 was found to mask the NES, thereby promoting nuclear localization and transcriptional activation of TFIIA target genes, such as CDKN2A. Collectively, we here describe a hitherto unknown mechanism how cellular localization and Taspase1 cleavage fine-tunes transcriptional activity of TFIIA in HNSCC.

Taspase1: a 'misunderstood' protease with translational cancer relevance.

Proteolysis is not only a critical requirement for life, but the executing enzymes also play important roles in numerous pathological conditions, including cancer. Therefore, targeting proteases is clearly relevant for improving cancer patient care. However, to effectively control proteases, a profound knowledge of their mechanistic function as well as their regulation and downstream signalling in health and disease is required. The highly conserved protease Threonine Aspartase1 (Taspase1) is overexpressed in numerous liquid and solid malignancies and was characterized as a 'non-oncogene addiction' protease. Although Taspase1 was shown to cleave various regulatory proteins in humans as well as leukaemia provoking mixed lineage leukaemia fusions, our knowledge on its detailed functions and the underlying mechanisms contributing to cancer is still incomplete. Despite superficial similarity to type 2 asparaginases as well as Ntn proteases, such as the proteasome, Taspase1-related research so far gives us the picture of a unique protease exhibiting special features. Moreover, neither effective genetic nor chemical inhibitors for this enzyme are available so far, thus hampering not only to further dissect Taspase1's pathobiological functions but also precluding the assessment of its clinical impact. Based on recent insights, we here critically review the current knowledge of Taspase1's structure-function relationship and its mechanistic relevance for tumorigenesis obtained from in vitro and in vivo cancer models. We provide a comprehensive overview of tumour entities for which Taspase1 might be of predictive and therapeutic value, and present the respective experimental evidence. To stimulate progress in the field, a comprehensive overview of Taspase1 targeting approaches is presented, including coverage of Taspase1-related patents. We conclude by discussing future inhibition strategies and relevant challenges, which need to be resolved by the field.

A Comparison Study of Validity Indices on Swarm-Intelligence-Based Clustering.

Swarm intelligence has emerged as a worthwhile class of clustering methods due to its convenient implementation, parallel capability, ability to avoid local minima, and other advantages. In such applications, clustering validity indices usually operate as fitness functions to evaluate the qualities of the obtained clusters. However, as the validity indices are usually data dependent and are designed to address certain types of data, the selection of different indices as the fitness functions may critically affect cluster quality. Here, we compare the performances of eight well-known and widely used clustering validity indices, namely, the Calinski-Harabasz index, the CS index, the Davies-Bouldin index, the Dunn index with two of its generalized versions, the I index, and the silhouette statistic index, on both synthetic and real data sets in the framework of differential-evolution-particle-swarm-optimization (DEPSO)-based clustering. DEPSO is a hybrid evolutionary algorithm of the stochastic optimization approach (differential evolution) and the swarm intelligence method (particle swarm optimization) that further increases the search capability and achieves higher flexibility in exploring the problem space. According to the experimental results, we find that the silhouette statistic index stands out in most of the data sets that we examined. Meanwhile, we suggest that users reach their conclusions not just based on only one index, but after considering the results of several indices to achieve reliable clustering structures.

Coordinated machine learning and decision support for situation awareness.

Domains such as force protection require an effective decision maker to maintain a high level of situation awareness. A system that combines humans with neural networks is a desirable approach. Furthermore, it is advantageous for the calculation engine to operate in three learning modes: supervised for initial training and known updating, reinforcement for online operational improvement, and unsupervised in the absence of all external signaling. An Adaptive Resonance Theory based architecture capable of seamlessly switching among the three types of learning is discussed that can be used to help optimize the decision making of a human operator in such a scenario. This is followed by a situation assessment module.

Early post-transplant urinary IP-10 expression after kidney transplantation is predictive of short- and long-term graft function.

The early identification of renal transplant recipients at enhanced risk of developing acute and subclinical rejection would allow individualized adjustment of immunosuppression before functional graft injury occurs and would exclude these patients from drug-weaning studies. Protein and reverse transcriptase-polymerase chain reaction-based analyses of candidate markers in urine open the opportunity to closely monitor kidney-transplanted patients non-invasively. The chemokine interferon-inducible protein 10 (IP-10; CXCL10) might be an interesting candidate to uncover ongoing immune processes within the graft. Urine samples from kidney-transplanted recipients were retrospectively analyzed for IP-10 mRNA and protein expression. IP-10 levels were correlated with the incidence of acute rejection episodes proven by histology and long-term graft function assessed by the glomerular filtration rate 6 months post transplantation. IP-10 expression in urine identified patients with ongoing acute rejection episodes several days before a biopsy was indicated by rising serum creatinine levels. Most importantly, elevated levels of urinary IP-10 protein within the first four postoperative weeks were predictive of graft function at 6 months even in the absence of acute rejection. These data reveal a correlation between elevated IP-10 expression in urine at early time points post-transplantation and intragraft immune activation that leads to acute rejection and compromised long-term graft function.

Implementation of adaptive critic-based neurocontrollers for turbogenerators in a multimachine power system.

This paper presents the design and practical hardware implementation of optimal neurocontrollers that replace the conventional automatic voltage regulator (AVR) and the turbine governor of turbogenerators on multimachine power systems. The neurocontroller design uses a powerful technique of the adaptive critic design (ACD) family called dual heuristic programming (DHP). The DHP neurocontrollers' training and testing are implemented on the Innovative Integration M67 card consisting of the TMS320C6701 processor. The measured results show that the DHP neurocontrollers are robust and their performance does not degrade unlike the conventional controllers even when a power system stabilizer (PSS) is included, for changes in system operating conditions and configurations. This paper also shows that it is possible to design and implement optimal neurocontrollers for multiple turbogenerators in real time, without having to do continually online training of the neural networks, thus avoiding risks of instability.

Query-based learning for aerospace applications.

Models of real-world applications often include a large number of parameters with a wide dynamic range, which contributes to the difficulties of neural network training. Creating the training data set for such applications becomes costly, if not impossible. In order to overcome the challenge, one can employ an active learning technique known as query-based learning (QBL) to add performance-critical data to the training set during the learning phase, thereby efficiently improving the overall learning/generalization. The performance-critical data can be obtained using an inverse mapping called network inversion (discrete network inversion and continuous network inversion) followed by oracle query. This paper investigates the use of both inversion techniques for QBL learning, and introduces an original heuristic to select the inversion target values for continuous network inversion method. Efficiency and generalization was further enhanced by employing node decoupled extended Kalman filter (NDEKF) training and a causality index (CI) as a means to reduce the input search dimensionality. The benefits of the overall QBL approach are experimentally demonstrated in two aerospace applications: a classification problem with large input space and a control distribution problem.

Comparison of heuristic dynamic programming and dual heuristic programming adaptive critics for neurocontrol of a turbogenerator.

This paper presents the design of an optimal neurocontroller that replaces the conventional automatic voltage regulator (AVR) and the turbine governor for a turbogenerator connected to the power grid. The neurocontroller design uses a novel technique based on the adaptive critic designs (ACDs), specifically on heuristic dynamic programming (HDP) and dual heuristic programming (DHP). Results show that both neurocontrollers are robust, but that DHP outperforms HDP or conventional controllers, especially when the system conditions and configuration change. This paper also shows how to design optimal neurocontrollers for nonlinear systems, such as turbogenerators, without having to do continually online training of the neural networks, thus avoiding risks of instability.

Dynamic re-optimization of a fed-batch fermentor using adaptive critic designs.

Traditionally, fed-batch biochemical process optimization and control uses complicated off-line optimizers, with no online model adaptation or re-optimization. This study demonstrates the applicability of a class of adaptive critic designs for online re-optimization and control of an aerobic fed-batch fermentor. Specifically, the performance of an entire class of adaptive critic designs, viz., heuristic dynamic programming, dual heuristic programming and generalized dual heuristic programming, was demonstrated to be superior to that of a heuristic random optimizer, on optimization of a fed-batch fermentor operation producing monoclonal antibodies.

Neurocontroller alternatives for "fuzzy" ball-and-beam systems with nonuniform nonlinear friction.

The ball-and-beam problem is a benchmark for testing control algorithms. In the World Congress on Neural Networks, 1994, Prof. L. Zadeh proposed a twist to the problem, which, he suggested, would require a fuzzy logic controller. This experiment uses a beam, partially covered with a sticky substance, increasing the difficulty of predicting the ball's motion. We complicated this problem even more by not using any information concerning the ball's velocity. Although it is common to use the first differences of the ball's consecutive positions as a measure of velocity and explicit input to the controller, we preferred to exploit recurrent neural networks, inputting only consecutive positions instead. We have used truncated backpropagation through time with the node-decoupled extended Kalman filter (NDEKF) algorithm to update the weights in the networks. Our best neurocontroller uses a form of approximate dynamic programming called an adaptive critic design. A hierarchy of such designs exists. Our system uses dual heuristic programming (DHP), an upper-level design. To our best knowledge, our results are the first use of DHP to control a physical system. It is also the first system we know of to respond to Zadeh's challenge. We do not claim this neural network control algorithm is the best approach to this problem, nor do we claim it is better than a fuzzy controller. It is instead a contribution to the scientific dialogue about the boundary between the two overlapping disciplines.

[Activity of the climbing fiber innervating various Purkinje cells]. / Aktivnost' vetvei liannogo volokna, innerviruiushchikh raznye kletki Purkin'e.

Low-amplitude potentials (10-130 microV) related to the action of a distant branch of the climbing fiber, which elicits complex spikes of the reference Purkinje cell were revealed by means of potential averaging synchronously with complex spikes of Purkinje cells in 10 out of 255 paired records of cerebellar Purkinje cells activity and extracellular field potentials at interelectrode distances of 200-1500 microns. These potential waves had a stable form in independent sets of data. In 3 out of 10 cases, the low-amplitude potentials included a slow (about 100 ms in duration) component. In one case, both test and reference electrodes recorded both simple and complex spikes of different Purkinje cells so that complex spikes of both cells were practically synchronous (conditional probability of complex spikes p = 0.97, onset time difference 0.54 ms). Thus for the first time in cerebellar physiology both simple and complex spikes activity of two Purkinje cells controlled by the same climbing fiber was recorded.

Comparative study of stock trend prediction using time delay, recurrent and probabilistic neural networks.

Three networks are compared for low false alarm stock trend predictions. Short-term trends, particularly attractive for neural network analysis, can be used profitably in scenarios such as option trading, but only with significant risk. Therefore, we focus on limiting false alarms, which improves the risk/reward ratio by preventing losses. To predict stock trends, we exploit time delay, recurrent, and probabilistic neural networks (TDNN, RNN, and PNN, respectively), utilizing conjugate gradient and multistream extended Kalman filter training for TDNN and RNN. We also discuss different predictability analysis techniques and perform an analysis of predictability based on a history of daily closing price. Our results indicate that all the networks are feasible, the primary preference being one of convenience.

Glucose phosphate isomerase deficiency: biochemical and molecular genetic studies on the enzyme variants of two patients with severe haemolytic anaemia.

UNLABELLED: Biochemical and molecular genetic studies were performed on the enzyme variants of two patients compound heterozygous for glucose phosphate isomerase (GPI) deficiency, both suffering from severe haemolytic anaemia. The enzymes of case 1 (GPI 'Zwickau') and case 2 (GPI 'Nordhorn' [25]), revealed reduced GPI activity and remarkable thermolability. Glucose-6-phosphate (Gluc-6-P) concentration was elevated 2.3 times in case 1 and 3.8 times in case 2. Sequencing the patients' GPI genes showed four different point mutations, two of them involving highly conserved amino acids. The c1039 C-->T substitution, found in the gene of GPI 'Zwickau', has been described recently [30] and causes an Arg 347-->Cys substitution close to the putative catalytic site. The second mutation in this case is a novel c1538 G-->A substitution causing a Trp-->stop mutation at position 513 apparently resulting in premature RNA degradation thus resulting either in a complete lack of protein or a protein which does not show GPI activity. In the gene of GPI 'Nordhorn' a c1028 A-->G mutation was discovered, also previously described [1, 9] causing a Gln 343-->Trp substitution. The second mutation was a novel splice site mutation at the border of intron 15 to exon 16: IVS15-(-2) A-->C which leads to an aberrant splicing of exon 16, thus resulting either in a truncated and most likely inactive enzyme or in no protein at all. CONCLUSION: Biochemical and molecular genetic studies performed with the enzyme variants GPI 'Zwickau' and GPI 'Nordhorn' showed that in both cases the simultaneous occurrence of a single amino acid substitution affecting the active site, together with a nonsense mutation leading to the loss of major parts of the enzyme probably explains the severe clinical course of the disease.

Adaptive critic designs.

We discuss a variety of adaptive critic designs (ACDs) for neurocontrol. These are suitable for learning in noisy, nonlinear, and nonstationary environments. They have common roots as generalizations of dynamic programming for neural reinforcement learning approaches. Our discussion of these origins leads to an explanation of three design families: heuristic dynamic programming, dual heuristic programming, and globalized dual heuristic programming (GDHP). The main emphasis is on DHP and GDHP as advanced ACDs. We suggest two new modifications of the original GDHP design that are currently the only working implementations of GDHP. They promise to be useful for many engineering applications in the areas of optimization and optimal control. Based on one of these modifications, we present a unified approach to all ACDs. This leads to a generalized training procedure for ACDs.

An optoelectronic implementation of the adaptive resonance neural network.

A solution to the problem of implementation of the adaptive resonance theory (ART) of neural networks that uses an optical correlator which allows the large body of correlator research to be leveraged in the implementation of ART is presented. The implementation takes advantage of the fact that one ART-based architecture, known as ART1, can be broken into several parts, some of which are better to implement in parallel. The control structure of ART, often regarded as its most complex part, is actually not very time consuming and can be done in electronics. The bottom-up and top-down gated pathways, however, are very time consuming to simulate and are difficult to implement directly in electronics due to the high number of interconnections. In addition to the design, the authors present experiments with a laboratory prototype to illustrate its feasibility and to discuss implementation details that arise in practice. This device can potentially outperform alternative implementations of ART1 by as much as two to three orders of magnitude in problems requiring especially large input fields.

Regulation of progesterone formation by human placental cells in culture.

In the present study, a culture system of human placental cells was established to examine the role of estrogen and androgen in progesterone (P4) formation. Normal human placentae were obtained at term, and cells were dispersed in Hank's Balanced Salt Solution (5 ml/g tissue) containing 0.1% collagenase, 0.1% hyaluronidase, 0.01% deoxyribonuclease, and 1% fetal bovine serum for 2 h at 37 C. Dispersed placental cells (10(6) cells/ml) were placed in medium 199 with modified Earle's salts (pH 7.4) containing 10% fetal bovine serum, 12.5 mM HEPES buffer, 26 mM NaHCO3, and 40 micrograms/ml Gentamycin-SO4 and incubated for 72 h at 37 C and 5% CO2 in air to allow cell attachment. Medium was then changed (time zero), and P4 formation was studied thereafter. Culture of placental cells for 96 h resulted in linear increases in P4 and estradiol (E2) formation, indicating the maintenance of cell viability and steroidogenic function. Mean +/- SE P4 formation at 48 h was 246 +/- 16 pg/micrograms DNA. To assess the role of estrogen on P4 formation, placental cells were incubated for a period of 48 h with various amounts (10(-7)-10(-4)M) of the antiestrogen ethamoxytriphetol (MER-25), the aromatase inhibitor 4-hydroxyandrostenedione (4-OHA), and/or E2. Both MER-25 and 4-OHA resulted in a dose-dependent decline (P less than 0.01) in P4 formation (greater than 80% decline at 10(-4)M MER-25 or 4-OHA). The marked reduction in P4 formation caused by 4-OHA alone was reversed by concomitant addition of E2; however, E2 alone had no effect. To assess the role of androgens on P4 formation, cells were incubated for 48 h with increasing amounts (10(-7)-10(-4)M) of androstenedione, dehydroepiandrosterone (DHA), or dihydrotestosterone. Although the formation of E2 was enhanced by DHA, formation of P4 was not affected by the aromatizable androgens DHA or androstenedione or the nonaromatizable dihydrotestosterone. The decline in P4 formation by human placental cells in culture elicited by MER-25 or 4-OHA supports the hypothesis of a regulatory role for estrogen in placental P4 formation during human pregnancy. The lack of effect of exogenous estrogen suggests that the action of estrogen on P4 formation may be permissive.

Effects of 13-nle-motilin on the electrical and mechanical activity of the isolated perfused canine stomach and duodenum.

Synthetic 13-norleucine-motilin (13-nle-motilin), structural and biological analogue of the naturally-occurring duodenal polypeptide, motilin, is known to stimulate antral and duodenal motor activity in vitro, but delays gastric emptying in man. In this study the direct actions of the synthetic polypeptide on myoelectrical activity and intraluminal pressure have been studied in the isolated vascular-perfused canine stomach and duodenum. 13-nle-motilin increased intraluminal pressure in the pylorus and duodenum, and dose-response analysis showed the duodenum to be twice as sensitive as the pylorus to the polypeptide. Pressure changes in the antrum were small and not dose-related, but, whereas the basic electrical rhythm in the duodenum was not altered, slow wave frequency, rhythm, and propagation in the antrum were disturbed. Electronic analysis of the duodenal spike increase which accompanied pressure rises demonstrated correlations between increases in spikes, intraluminal pressure, and dose. These results show that the direct effect of the polypeptide on adjacent organs may explain the combination of increased motor activity with delayed gastric emptying as a consequence of disturbance in the co-ordination between antrum, pylorus, and duodenum.