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Biomedical subjects

W L Tung

Publications and source records attributed to W L Tung.

11 recordsLinked to original sources
PubMed2006

Effect of bilateral reaching on affected arm motor control in stroke--with and without loading on unaffected arm.

PURPOSE: To investigate the effect of bilateral reaching, with/without inertial loading on the unaffected arm, on hemiparetic arm motor control in stroke. METHODS: Twenty unilateral stroke patients were recruited. A three-dimensional optical motion capture system was used to measure the movement trajectory of the hemiparetic arm while performing three tasks: affected limb reaching forward; two-limb reaching forward; and two-limb reaching forward with inertia loading of 25% upper limb weight on the unaffected limb, respectively. Kinematical parameters were utilized to quantify the reaching performance of the affected arm. RESULTS: No matter whether loading was applied on the unaffected arm or not, the bilateral reaching task did not significantly facilitate smoother and faster movement. Furthermore, during bilateral reaching task with/without loading on the unaffected arm, stroke patients showed slower movement, lower maximal movement velocity, feedback control dominant and discontinuous movements in the affected arm than the same task with unilateral reaching. Subjects showed the greatest active upper extremity range of motion in proximal joints during the bilateral reaching task without unaffected arm loading. The amount of trunk movement also increased during bilateral reaching either with or without loading on the unaffected arm. Patients with moderate upper extremity motor impairment performed more discontinuous movements and less active elbow range of motion during bilateral reaching tasks; however, those with mild upper extremity motor impairment performed smoother movements and demonstrated greater active elbow range of motion during bilateral reaching tasks. CONCLUSIONS: Bilateral reaching tasks with/without loading on the unaffected arm could be considered as adding challenges during motor control training. Training with bilateral arm movements may be considered as a treatment strategy, and can be incorporated in stroke rehabilitation to facilitate greater arm active movement and improve motor control performance in the affected arm.

Adult↗
PubMed2006

FCMAC-Yager: a novel Yager-inference-scheme-based fuzzy CMAC.

The cerebellum is a brain region important for a number of motor and cognitive functions. It is able to generate error correction signals to drive learning and for the acquisition of memory skills. The cerebellar model articulation controller (CMAC) is a neural network inspired by the neurophysiologic theory of the cerebellum and is recognized for its localized generalization and rapid algorithmic computation capabilities. The main deficiencies in the basic CMAC structure are: (1) it is difficult to interpret the internal operations of the CMAC network and (2) the resolution (quantization) problem arising from the partitioning of the input training space. These limitations lead to the synthesis of a fuzzy quantization technique and the mapping of a fuzzy inference scheme onto the CMAC structure. The discrete incremental clustering (DIC) technique is employed to alleviate the quantization problem in the CMAC structure, resulting in the fuzzy CMAC (FCMAC) network. The Yager inference scheme (Yager), which possesses firm fuzzy logic foundation and maps closely to the logical implication operations in the classical (binary) logic framework, is subsequently mapped onto the FCMAC structure. This results in a novel fuzzy neural architecture known as thefuzzy cerebellar model articulation controller-Yager (FCMAC-Yager) system. The proposed FCMAC-Yager network exhibits learning and memory capabilities of the cerebellum through the CMAC structure while emulating the human way of reasoning through the Yager. The new FCMAC-Yager network employs a two-phase training algorithm consisting of structural learning based on the DIC technique and parameter learning using hebbian learning (associative long-term potentiation). The proposed FCMAC-Yager architecture is evaluated using an extensive suite of real-life applications such as highway traffic-trend modeling and prediction and performing as an early warning system for bank failure classification and medical diagnosis of breast cancer. The experimental results are encouraging.

Algorithms↗
PubMed2005

GenSo-FDSS: a neural-fuzzy decision support system for pediatric ALL cancer subtype identification using gene expression data.

OBJECTIVE: Acute lymphoblastic leukemia (ALL) is the most common malignancy of childhood, representing nearly one third of all pediatric cancers. Currently, the treatment of pediatric ALL is centered on tailoring the intensity of the therapy applied to a patient's risk of relapse, which is linked to the type of leukemia the patient has. Hence, accurate and correct diagnosis of the various leukemia subtypes becomes an important first step in the treatment process. Recently, gene expression profiling using DNA microarrays has been shown to be a viable and accurate diagnostic tool to identify the known prognostically important ALL subtypes. Thus, there is currently a huge interest in developing autonomous classification systems for cancer diagnosis using gene expression data. This is to achieve an unbiased analysis of the data and also partly to handle the large amount of genetic information extracted from the DNA microarrays. METHODOLOGY: Generally, existing medical decision support systems (DSS) for cancer classification and diagnosis are based on traditional statistical methods such as Bayesian decision theory and machine learning models such as neural networks (NN) and support vector machine (SVM). Though high accuracies have been reported for these systems, they fall short on certain critical areas. These included (a) being able to present the extracted knowledge and explain the computed solutions to the users; (b) having a logical deduction process that is similar and intuitive to the human reasoning process; and (c) flexible enough to incorporate new knowledge without running the risk of eroding old but valid information. On the other hand, a neural fuzzy system, which is synthesized to emulate the human ability to learn and reason in the presence of imprecise and incomplete information, has the ability to overcome the above-mentioned shortcomings. However, existing neural fuzzy systems have their own limitations when used in the design and implementation of DSS. Hence, this paper proposed the use of a novel neural fuzzy system: the generic self-organising fuzzy neural network (GenSoFNN) with truth-value restriction (TVR) fuzzy inference, as a fuzzy DSS (denoted as GenSo-FDSS) for the classification of ALL subtypes using gene expression data. RESULTS AND CONCLUSION: The performance of the GenSo-FDSS system is encouraging when benchmarked against those of NN, SVM and the K-nearest neighbor (K-NN) classifier. On average, a classification rate of above 90% has been achieved using the GenSo-FDSS system.

Algorithms↗
PubMed2004

GenSo-EWS: a novel neural-fuzzy based early warning system for predicting bank failures.

Bank failure prediction is an important issue for the regulators of the banking industries. The collapse and failure of a bank could trigger an adverse financial repercussion and generate negative impacts such as a massive bail out cost for the failing bank and loss of confidence from the investors and depositors. Very often, bank failures are due to financial distress. Hence, it is desirable to have an early warning system (EWS) that identifies potential bank failure or high-risk banks through the traits of financial distress. Various traditional statistical models have been employed to study bank failures [J Finance 1 (1975) 21; J Banking Finance 1 (1977) 249; J Banking Finance 10 (1986) 511; J Banking Finance 19 (1995) 1073]. However, these models do not have the capability to identify the characteristics of financial distress and thus function as black boxes. This paper proposes the use of a new neural fuzzy system [Foundations of neuro-fuzzy systems, 1997], namely the Generic Self-organising Fuzzy Neural Network (GenSoFNN) [IEEE Trans Neural Networks 13 (2002c) 1075] based on the compositional rule of inference (CRI) [Commun ACM 37 (1975) 77], as an alternative to predict banking failure. The CRI based GenSoFNN neural fuzzy network, henceforth denoted as GenSoFNN-CRI(S), functions as an EWS and is able to identify the inherent traits of financial distress based on financial covariates (features) derived from publicly available financial statements. The interaction between the selected features is captured in the form of highly intuitive IF-THEN fuzzy rules. Such easily comprehensible rules provide insights into the possible characteristics of financial distress and form the knowledge base for a highly desired EWS that aids bank regulation. The performance of the GenSoFNN-CRI(S) network is subsequently benchmarked against that of the Cox's proportional hazards model [J Banking Finance 10 (1986) 511; J Banking Finance 19 (1995) 1073], the multi-layered perceptron (MLP) and the modified cerebellar model articulation controller (MCMAC) [IEEE Trans Syst Man Cybern: Part B 30 (2000) 491] in predicting bank failures based on a population of 3635 US banks observed over a 21 years period. Three sets of experiments are performed-bank failure classification based on the last available financial record and prediction using financial records one and two years prior to the last available financial statements. The performance of the GenSoFNN-CRI(S) network as a bank failure classification and EWS is encouraging.

Accidents↗
PubMed2004

Falcon: neural fuzzy control and decision systems using FKP and PFKP clustering algorithms.

Neural fuzzy networks proposed in the literature can be broadly classified into two groups. The first group is essentially fuzzy systems with self-tuning capabilities and requires an initial rule base to be specified prior to training. The second group of neural fuzzy networks, on the other hand, is able to automatically formulate the fuzzy rules from the numerical training data. Examples are the Falcon-ART, and the POPFNN family of networks. A cluster analysis is first performed on the training data and the fuzzy rules are subsequently derived through the proper connections of these computed clusters. This correspondence proposes two new networks: Falcon-FKP and Falcon-PFKP. They are extensions of the Falcon-ART network, and aimed to overcome the shortcomings faced by the Falcon-ART network itself, i.e., poor classification ability when the classes of input data are very similar to each other, termination of training cycle depends heavily on a preset error parameter, the fuzzy rule base of the Falcon-ART network may not be consistent Nauck, there is no control over the number of fuzzy rules generated, and learning efficiency may deteriorate by using complementarily coded training data. These deficiencies are essentially inherent to the fuzzy ART, clustering technique employed by the Falcon-ART network. Hence, two clustering techniques--Fuzzy Kohonen Partitioning (FKP) and its pseudo variant PFKP, are synthesized with the basic Falcon structure to compute the fuzzy sets and to automatically derive the fuzzy rules from the training data. The resultant neural fuzzy networks are Falcon-FKP and Falcon-PFKP, respectively. These two proposed networks have a lean and efficient training algorithm and consistent fuzzy rule bases. Extensive simulations are conducted using the two networks and their performances are encouraging when benchmarked against other neural and neural fuzzy systems.

Journal Article↗
PubMed2000

Magnetic field exposure enhances DNA repair through the induction of DnaK/J synthesis.

In contrast to the common impression that exposure to a magnetic field of low frequency causes mutations to organisms, we have demonstrated that a magnetic field can actually enhance the efficiency of DNA repair. Using Escherichia coli strain XL-1 Blue as the host and plasmid pUC8 that had been mutagenized by hydroxylamine as the vector for assessment, we found that bacterial transformants that had been exposed to a magnetic field of 50 Hz gave lower percentages of white colonies as compared to transformants that had not been exposed to the magnetic field. This result was indicative that the efficiency of DNA repair had been improved. The improvement was found to be mediated by the induced overproduction of heat shock proteins DnaK/J (Hsp70/40).

Bacterial Proteins↗
PubMed2000

Magnetic field exposure stimulates transposition through the induction of DnaK/J synthesis.

Like some naturally occurring environmental stress factors such as heat shock and UV irradiation, magnetic field exposure is also stimulatory to transposition activity. This feature could be illustrated by a bacterial conjugation study using an Escherichia coli strain that carries the transposable element Tn5 as the donor. When the donor cultures were exposed to a low-frequency (50 Hz) magnetic field of 1.2 mT, Tn5 located on the bacterial chromosome was stimulated to transpose and settled on the extrachromosomal episome, and eventually transferred to the recipient cell through conjugation. Such transposition activity stimulation was mediated by the induced synthesis and accumulation of the heat shock proteins DnaK/J.

Bacterial Proteins↗
PubMed1998

Overexpression of dnaK/dnaJ and groEL confers freeze tolerance to Escherichia coli.

Heat shock proteins not only can protect host cells against heat stress, they can also enable freeze tolerance as well. With respect to this unexpected feature, we are able to show that, at least in Escherichia coli, the heat shock proteins DnaK/DnaJ and GroEL play a very significant role. We found that the recovery rate of E. coli cultures that had been stored at -80 degreesC in the absence of any cryoprotectant was related to the abundance of these heat shock proteins accumulated before the freeze treatment. Before freezing, the DnaK in the bacterial cells was induced to accumulate to a level comparable to that produced in response to heat shock. After the freezing treatment, the recovery rate of the induced culture was very similar to that of the heat-shocked culture. Over production of GroEL was also protective but less effective. While freezing inevitably leads to protein denaturation, we propose that advance synthesis of DnaK/DnaJ and GroEL can accordingly prevent irreversible denaturation by chaperoning the unfolded polypeptides during freezing.

Adaptation, Physiological↗
PubMed1992

Tachykinin-stimulated inositol phospholipid hydrolysis and taurine release from human astrocytoma cells.

The activation of NK1 receptors on U373 MG human astrocytoma cells by substance P (SP) and related tachykinins was accompanied by an increase in taurine release and an accumulation of inositol phosphates. Both of these effects could be inhibited by spantide, a SP receptor antagonist. The relative potency of tachykinins in stimulating 3H-inositol phosphate accumulation correlated very well with their effects in stimulating the release of [3H]-taurine and inhibition 125I-Bolton-Hunter reagent-conjugated SP binding. The effect on [3H]taurine release was mimicked by a protein kinase C (PKC) activator, phorbol 12-myristate 13-acetate (PMA). The inactive phorbol ester analogue 4-alpha-phorbol 12,13-didecanoate, however, was without effect. Both SP- and PMA-induced releases of [3H]-taurine were markedly inhibited by staurosporine, a potent PKC inhibitor. Pretreatment of U373 MG cells with 10 microM PMA for 19 h to down-regulate PKC activity also markedly inhibited both SP- and PMA-induced releases of [3H]-taurine. Treatment of cells with 100 nM SP induced a time-dependent translocation of PKC from the cytosolic fraction to the membrane fraction. These findings are consistent with the hypothesis that an activation of NK1 receptors on U373 MG cells results in the release of inositol phosphates and activation of PKC, which in turn may regulate the release of taurine.

Alkaloids↗
PubMed1991

Effects of tachykinins on [3H]taurine release from human astrocytoma cells (U-373 MG).

Substance P (SP) stimulated [3H]taurine release from human astrocytoma cells (U-373 MG). This effect was concentration dependent and the EC50 was 0.3 nM. This stimulatory effect of SP can be inhibited by spantide, a SP receptor antagonist. The rank order of potencies of related tachykinins and their analogues in stimulating the release of [3H]taurine was SP much greater than neurokinin A much greater than neurokinin B and [Glp6,L-Pro9]SP (6-11) much greater than [Glp6, D-Pro9]SP (6-11) which conformed to that reported for the tachykinin NK-1 receptor. In addition to SP, isoproterenol, a beta-adrenergic agonist, can also increase the release of [3H]taurine from these cells and the effects of SP and isoproterenol were additive.

Astrocytoma↗