Isoform-specific O-glycosylation by murine UDP-GalNAc:polypeptide N- acetylgalactosaminyltransferase-T3, in vivo

Multiple isoforms of UDP-GalNAc:polypeptide N-acetylgalactosaminyl- transferase (ppGaNTase) have been cloned and expressed from a variety of organisms. In general, these isoforms display different patterns of tissue-specific expression, but exhibit overlapping substrate specificities, in vitro . A peptide substrate, derived from the sequence of the V3 loop of the HIV gp120 protein (HIV peptide), has previously been shown to be glycosylated in vitro exclusively by the ppGaNTase-T3 (Bennett et al. , 1996). To determine if this isoform- specificity is maintained in vivo , we have examined the glycosylation of this substrate when it is expressed as a reporter peptide (rHIV) in a cell background (COS7 cells) which lacks detectable levels of the ppGaNTase-T3. Glycosylation of rHIV was greatly increased by coexpression of a recombinant ppGaNTase-T3. Overexpression of ppGaNTase- T1 yielded only partial glycosylation of the reporter. We have also determined that the introduction of a proline residue at the +3 position flanking the potential glycosylation site eliminated ppGaNTase- T3 selectivity toward rHIV observed both in vivo and in vitro .      

Ten-year changes in central obesity and BMI in rural and urban Cameroon

Objective: To compare the 10‐year changes in the distribution of adiposity in rural and urban Cameroonian populations. Methods and Procedures: Two cross‐sectional surveys of populations in the same rural and urban areas of Cameroon, aged ≥24 years, were carried out in 1994 (1,762 subjects) and 2003 (1,398 subjects) using similar methodology. All eligible subjects answered a structured questionnaire on their educational level, alcohol consumption, and tobacco smoking and weight, height, and waist circumference (WC) were measured. Results: Between 1994 and 2003, the age‐standardized prevalence of BMI ≥25 kg/m² increased significantly only in the rural area (+54% for women and +82% for men), while the age‐standardized prevalence of central obesity (WC ≥80 cm (women), ≥94 cm (men)) increased significantly only in the urban population (+32% for women and +190% for men). These differences persisted after adjustments for age group, alcohol consumption, tobacco smoking, and level of education, and within almost all the strata of the studied risk factors. Discussion: Changes in adiposity over time in Cameroon were characterized by an increase of BMI in the rural area and of WC in the urban area.     

Predicting Physical Activity Energy Expenditure Using Accelerometry in Adults From Sub‐Sahara Africa

Lack of physical activity may be an important etiological factor in the current epidemiological transition characterized by increasing prevalence of obesity and chronic diseases in sub‐Sahara Africa. However, there is a dearth of data on objectively measured physical activity energy expenditure (PAEE) in this region. We sought to develop regression equations using body composition and accelerometer counts to predict PAEE. We conducted a cross‐sectional study of 33 adult volunteers from an urban (n = 16) and a rural (n = 17) residential site in Cameroon. Energy expenditure was measured by doubly labeled water (DLW) over a period of seven consecutive days. Simultaneously, a hip‐mounted Actigraph accelerometer recorded body movement. PAEE prediction equations were derived using accelerometer counts, age, sex, and body composition variables, and cross‐validated by the jack‐knife method. The Bland and Altman limits of agreement (LOAs) approach was used to assess agreement. Our results show that PAEE (kJ/kg/day) was significantly and positively correlated with activity counts from the accelerometer (r = 0.37, P = 0.03). The derived equations explained 14–40% of the variance in PAEE. Age, sex, and accelerometer counts together explained 34% of the variance in PAEE, with accelerometer counts alone explaining 14%. The LOAs between DLW and the derived equations were wide, with predicted PAEE being up to 60 kJ/kg/day below or above the measured value. In summary, the derived equations performed better than existing published equations in predicting PAEE from accelerometer counts in this population. Accelerometry could be used to predict PAEE in this population and, therefore, has important applications for monitoring population levels of total physical activity patterns.