The descriptive epidemiology of congenital and acquired cryptorchidism in a UK infant cohort.

INTRODUCTION: Recent studies in other European countries suggest that the prevalence of congenital cryptorchidism continues to increase. This study aimed to explore the prevalence and natural history of congenital cryptorchidism in a UK centre. METHODS: Between October 2001 and July 2008, 784 male infants were born in the prospective Cambridge Baby Growth Study. 742 infants were examined by trained research nurses at birth; testicular position was assessed using standard techniques. Follow-up assessments were completed at ages 3, 12, 18 and 24 months in 615, 462, 393 and 326 infants, respectively. RESULTS: The prevalence of cryptorchidism at birth was 5.9% (95% CI 4.4% to 7.9%). Congenital cryptorchidism was associated with earlier gestational age (p<0.001), lower birth weight (p<0.001), birth length (p<0.001) and shorter penile length at birth (p<0.0001) compared with other infants, but normal size after age 3 months. The prevalence of cryptorchidism declined to 2.4% at 3 months, but unexpectedly rose again to 6.7% at 12 months as a result of new cases. The cumulative incidence of "acquired cryptorchidism" by age 24 months was 7.0% and these cases had shorter penile length during infancy than other infants (p = 0.003). CONCLUSIONS: The prevalence of congenital cryptorchidism was higher than earlier estimates in UK populations. Furthermore, this study for the first time describes acquired cryptorchidism or "ascending testis" as a common entity in male infants, which is possibly associated with reduced early postnatal androgen activity.

Inference approach to grammar construction

A system of computer assisted grammar construction (CAGC) is presented in this paper. The CAGC system is designed to generate broad-coverage grammars for large natural language corpora by utilizing both an extended inside-outside algorithm and an automatic phrase bracketing (AUTO) system which is designed to provide the extended algorithm with constituent information during learning. This paper demonstrates the capability of the CAGC system to deal with realistic natural language problems and the usefulness of the AUTO system for constraining the inside-outside based grammar re-estimation. Performance results, including coverage, recall and precision, are presented for a grammar constructed for the Wall Street Journal (WSJ) corpus using the Penn Treebank.