A mutation analysis of the phenylalanine hydroxylase (PAH) gene in the Israeli population.

Hyperphenylalaninemia (HPA) is a group of diseases characterized by a persistent elevation of phenylalanine levels in tissues and biological fluids. The most frequent form is phenylalanine hydroxylase deficiency, causing phenylketonuria (PKU). Among 159 Israeli patients (Jews, Muslim and Christian Arabs and Druze) with HPA, in whom at least one of the mutations was characterized, a total of 43 different mutations were detected, including seven novel ones. PKU was very rare among Ashkenazi Jews and relatively frequent among Jews from Yemen, the Caucasian Mountains, Bukhara and Tunisia. The mutations responsible for the high frequency were: exon3del (Yemenite Jews), L48S (Tunisian Jews) and E178G, P281L and L48S (Jews from the Caucasian Mountains and Bukhara). Among the non-Jewish Israeli citizens, the disease was relatively frequent in the Negev and in the Nazareth vicinity, and in many localities a unique mutation was detected, often in a single family. While marked genetic heterogeneity was observed in the Arab and Jewish populations, only one mutation A300S, was frequent in all of the communities. Several of the other frequent mutations were shared by the non-Ashkenazi Jews and Arabs; none were mutual to Ashkenazi Jews and Arabs.

Peak bone mass in patients with phenylketonuria.

OBJECTIVE: Several studies have suggested a compromised bone mass in phenylketonuria patients but most reported on heterogeneous or small patient groups. Our aim was to evaluate peak bone mass in adult PKU patients and to relate BMD to nutritional parameters. PATIENTS AND METHODS: BMD was measured by dual-energy x-ray absorptiometry in 31 adult PKU patients (18 female), mean age 25 +/- 5.3 years. Nutritional intake was calculated based on food diaries. Diet adherence was determined based on patients' report. RESULTS: Mean blood phenylalanine (Phe) concentration was 968 +/- 526 micromol/L (16 +/- 8.7 mg/dl). Eight patients (32.2%) met the recommended blood Phe concentration of <726 micromol/L (<12 mg/dl), and there was no significant difference in Phe concentrations between diet-adherent and non-adherent patients. Osteopenia was detected in 11 patients (38.7%), while osteoporosis was detected in 2 patients (6.5%). No correlation was found between BMD and age, blood minerals, Phe, vitamin D and alkaline phosphatase levels, calcium and protein intake, body mass index, and body fat percentage. CONCLUSIONS: Peak bone mass is decreased in PKU patients. Possible explanations include long-standing dietary deficiency in protein, calcium, vitamin D or trace elements, or a primary defect in bone turnover inherent to the disease itself. Our data do not favour any of these hypotheses. Further studies are needed to elucidate the cause of low bone density in PKU patients.

Observations and modeling of synchronized bursting in two-dimensional neural networks.

We present long-term (approximately hours) measurements of the spontaneous activity of two-dimensional cortical cell neural networks placed on multielectrode arrays. We compare histograms of single neuron interspike intervals and the network intersynchronized bursting events intervals. In addition, the effect of Ca concentration on the network activity is being studied. At 1 mM Ca concentration, the network exhibits periodic synchronized bursting that fades away after about 20 min. We present a feedback-regulated integrate and fire model to account for the observations. In the model we include two additional features: dynamical threshold and synapse fatigue.

Detection and sorting of neural spikes using wavelet packets.

We propose a novel method for the detection and sorting of recorded neural spikes using wavelet packets. We employ the best basis via the Shannon's information cost function and local discriminant basis using mutual information. We demonstrate the efficiency of the method on data recorded in vitro from 2D neural networks. We show that our method is superior both in separation from noise and in identifying superimposed spikes.

Generic modeling of chemotactic based self-wiring of neural networks.

The proper functioning of the nervous system depends critically on the intricate network of synaptic connections that are generated during the system development. During the network formation, the growth cones migrate through the embryonic environment to their targets using chemical communication. A major obstacle in the elucidation of fundamental principles underlying this self-wiring is the complexity of the system being analyzed. Hence much effort is devoted to in vitro experiments of simpler (two-dimensional) 2D model systems. In these experiments neurons are placed on Poly-L-Lysine (PLL) surfaces, so it is easier to monitor their self-wiring. We developed a model to reproduce the salient features of the 2D systems, inspired by the study of the growth of bacterial colonies and the aggregation of amoebae. We represent the neurons (each composed of cell's soma, neurites and growth cones) by active elements that capture the generic features of the real neurons. The model also incorporates stationary units representing the cells' soma and communicating walkers representing the growth cones. The stationary units send neurites one at a time, and respond to chemical signaling. The walkers migrate in response to chemotaxis substances emitted by the soma and communicate with each other and with the soma by means of chemotactic "feedback". The interplay between the chemo-repulsive and chemo-attractive responses is determined by the dynamics of the walker's internal energy which is controlled by the soma. These features enable the neurons to perform the complex task of self-wiring. We present numerical experiments of the model to demonstrate its ability to form fine structures in simple networks of few neurons. Our results raise two fundamental issues: (1) one needs to develop characterization methods (beyond number of connections per neuron) to distinguish the various possible networks; (2) what are the relations between the network organization and its computational properties and efficiency?