RÉSUMÉ
OBJECTIVE: To report on a Chinese family from Wenzhou with genetically confirmed Kennedy disease and describe its clinical and genetic features. METHODS: The clinical phenotype and the level of relevant biochemical markers were assessed. To determine the number of CAG repeats in the exon 1 of androgen receptor (AR) gene, genomic DNA was extracted from peripheral blood samples of the family members, amplified by PCR and identified by DNA sequencing. RESULTS: The proband showed predominantly proximal limb weakness, fasciculation, muscle atrophy, gynecomastia, sexual dysfunction and increased serum creatine kinase. Myopathy and neuropathy were identified by electromyography. Two other affected males and 2 affected female carriers were identified to carry an expanded CAG repeat in the AR gene. The numbers of CAG repeats were found to be 43 in the proband, 43 and 42 in the other two affected males, one of which had similar clinical symptoms to the proband. CONCLUSION: The family was diagnosed with Kennedy disease by analysis of the AR gene.
Sujet(s)
Amyotrophie bulbospinale liée à l'X/génétique , Récepteurs aux androgènes/génétique , Adolescent , Adulte , Séquence nucléotidique , Amyotrophie bulbospinale liée à l'X/sang , Amyotrophie bulbospinale liée à l'X/diagnostic , Creatine kinase/sang , Femelle , Humains , Mâle , Adulte d'âge moyen , Données de séquences moléculaires , Pedigree , Expansion de trinucléotide répété , Jeune adulteRÉSUMÉ
Decision-making, as a way to discover the preference of ranking, has been used in various fields. However, owing to the uncertainty in group decision-making, how to rank alternatives by incomplete pairwise comparisons has become an open issue. In this paper, an improved method is proposed for ranking of alternatives by incomplete pairwise comparisons using Dempster-Shafer evidence theory and information entropy. Firstly, taking the probability assignment of the chosen preference into consideration, the comparison of alternatives to each group is addressed. Experiments verified that the information entropy of the data itself can determine the different weight of each group's choices objectively. Numerical examples in group decision-making environments are used to test the effectiveness of the proposed method. Moreover, the divergence of ranking mechanism is analyzed briefly in conclusion section.