Biomedical subjects

Giuseppe Didonè

Publications and source records attributed to Giuseppe Didonè.

2 recordsLinked to original sources

PubMed2005

Nerve stimulation boosts botulinum toxin action in spasticity.

Spasticity leads to functional and structural changes in nerves and muscles, which alter skeletal muscle function. To evaluate whether short-term electrical nerve stimulation (NS) improves the effect of botulinum toxin in spastic skeletal muscle, we studied changes in the amplitude of the compound muscle action potential (CMAP) recorded from the extensor digitorum brevis (EDB) muscle in response to peroneal nerve stimulation at the ankle after injection of botulinum toxin type A (BTXA) alone or combined with short-term NS. In paraparetic patients, both EDB muscles were injected with BTXA; and NS was applied to one EDB muscle alone. All patients received a 30-minute session of electrical NS once a day for 5 consecutive days after BTXA injection. We used two different stimulation frequencies (low-frequency, 4 Hz; and high-frequency, 25 Hz). EDB-CMAP amplitudes were evaluated before BTXA injection (day 0) and changes in CMAP amplitude, expressed as a percentage (CMAP%), were measured at various time points over a 30-day period after BTXA injection. We compared changes in the CMAP% amplitude on the stimulated and contralateral nonstimulated sides. We also studied the electromyographic activity recorded from EDB muscles over a 30-day period. CMAP% amplitudes measured at all time points after BTXA injections were significantly reduced in both EDB muscles. On days 4, 10, and 15, the CMAP% amplitude reduction was significantly greater for the low-frequency stimulated EDB than for the contralateral nonstimulated EDB. No significant differences in CMAP% were observed for the high-frequency stimulated and nonstimulated EDB. After BTXA injection, spontaneous activity appeared in both EDB muscles; but it appeared earlier and involved larger areas in the stimulated than in the nonstimulated EDB. In conclusion, short-term NS accelerates the effectiveness of intramuscular BTXA injections on the neuromuscular blockade in patients with spastic paraparesis and could induce a rapid and persistent improvement in spasticity. Its action probably arises mainly from low-frequency NS.

Aged↗

PubMed2003

Pattern identification and classification in gene expression data using an autoassociative neural network model.

The application of DNA microarray technology for analysis of gene expression creates enormous opportunities to accelerate the pace in understanding living systems and identification of target genes and pathways for drug development and therapeutic intervention. Parallel monitoring of the expression profiles of thousands of genes seems particularly promising for a deeper understanding of cancer biology and the identification of molecular signatures supporting the histological classification schemes of neoplastic specimens. However, the increasing volume of data generated by microarray experiments poses the challenge of developing equally efficient methods and analysis procedures to extract, interpret, and upgrade the information content of these databases. Herein, a computational procedure for pattern identification, feature extraction, and classification of gene expression data through the analysis of an autoassociative neural network model is described. The identified patterns and features contain critical information about gene-phenotype relationships observed during changes in cell physiology. They represent a rational and dimensionally reduced base for understanding the basic biology of the onset of diseases, defining targets of therapeutic intervention, and developing diagnostic tools for the identification and classification of pathological states. The proposed method has been tested on two different microarray datasets-Golub's analysis of acute human leukemia [Golub et al. (1999) Science 286:531-537], and the human colon adenocarcinoma study presented by Alon et al. [1999; Proc Natl Acad Sci USA 97:10101-10106]. The analysis of the neural network internal structure allows the identification of specific phenotype markers and the extraction of peculiar associations among genes and physiological states. At the same time, the neural network outputs provide assignment to multiple classes, such as different pathological conditions or tissue samples, for previously unseen instances.

Adenocarcinoma↗