Relationships among nitrogen and total phosphorus,algal biomass and zooplankton density in the central Amazonia lakes

The relationship among concentrations of total nitrogen (TN), total phosphorus (TP), algal biomass (Chl) and the density and size of individuals of the zooplankton community were studied for the dry season (November 1999–January 2000) at 20 lakes of the Central Amazonia. The study was conducted along a productivity gradient to identify the existence of resource or predator-dependent patterns on the primary producers of the trophic web. A strong positive relationship was observed between the log Chl and TN (r ² = 0.88, P = 0.000) and to log Chl and log TP (r ² = 0.85, P = 0.000) in a simple linear regression. However, when both variables were running together in a multiple regression, TN alone explained every variation of algal biomass (r ² = 0.89, P _TN = 0.022, P _TP = 0.233). The total density of the zooplankton showed a positive correlation with log Chl (r ² = 0.53, P = 0.000) and the large zooplankton (>0.5 mm) was found to be a more positive function of the phytoplankton (r ² = 0.65) than the density of the small ones (<0.5 mm, r ² = 0.44). Results show that complex food web interactions could be responsible for patterns in tropical systems. We contend that Chl variation in tropical lake systems is controlled by TN and TP, but the predictor power of the TN increase the fit of the model in analysis and can be use alone to access the variability in algae biomass to Amazonian tropical lakes. We also agree that the density of large zooplankton individuals is regulated by the biomass of primary producers. Hence we concluded that the resource-dependent hypothesis is supported in these systems. Handling editor: J. Padisak     

Visceral Adipose Tissue and Markers of the Insulin Resistance Syndrome in Obese Black and White Teenagers

Objective: To determine the relationships between visceral and general adiposity, cardiovascular fitness, and markers of the insulin resistance syndrome in obese black and white teenagers. Research Methods and Procedures: Cross‐sectional survey of 81 obese 13‐ to 16‐year‐old youths. Visceral adipose tissue was measured with magnetic resonance imaging, and percentage body fat was measured with dual‐energy X‐ray absorptiometry. Cardiovascular fitness was assessed with a submaximal treadmill test. Fasting blood samples were analyzed for lipids/lipoproteins and insulin. Resting blood pressure was obtained using an automated cuff. Results: Visceral adipose tissue was significantly correlated with unfavorable levels of: triacylglycerol (r = 0.27, p < 0.05), total cholesterol (r = 0.27, p < 0.05), high‐density lipoprotein cholesterol (r = ?0.26, p < 0.05), the ratio of total cholesterol/high‐density lipoprotein cholesterol (r = 0.42, p < 0.01), low‐density lipoprotein cholesterol (r = 0.27, p < 0.05), apolipoprotein B (r = 0.38, p < 0.01), and systolic blood pressure (r = 0.30, p < 0.01). Multiple regression analyses revealed that visceral adipose tissue was more powerful than percentage body fat for explaining variance in lipoproteins (e.g., for the ratio of total cholesterol/high‐density lipoprotein cholesterol, r² = 0.13, p < 0.01, and for systolic blood pressure, r² = 0.07, p < 0.05). Ethnicity was the most powerful of the demographic predictors for blood lipids (r² = 0.15 for triacylglycerol with lower levels in blacks; r² = 0.10 for high‐density lipoprotein cholesterol with higher levels in blacks; r² = 0.06 for the ratio of total cholesterol/high‐density lipoprotein cholesterol with lower levels in blacks). Cardiovascular fitness was not retained as a significant predictor of markers of the insulin resistance syndrome. Discussion: Some of the deleterious relationships between visceral adiposity and markers for the insulin resistance syndrome seen in adults were already present in these obese young people.     

Yield and species density of grasslands during restoration management

Abstract. The relation between the dry matter production and species density of 27 grasslands with different fertilization histories in the Netherlands was studied. The range in species density was 12–28 species on 150 m², the average annual dry matter production in 1983–1985 varied between 3.3 and 12.8 ton /ha. The results show an optimum curve and confirm the hump-backed model proposed by other researchers for a great variety of vegetation types. It is concluded that a high species density can be expected when the annual dry matter production above a stubble height of 5 cm, is between 4 and 6 ton/ha (ca. 4.6 - 6.0 ton seasonal maximum standing biomass). Species density can be expected to decrease when the dry matter production exceeds values of 6 - 7 ton ha^-1yr^-1 (ca. 6.0 - 6.7 ton seasonal maximum standing biomass). The implications of this relation for grassland restoration, aimed at an increase in species density, are discussed. The results agree with other grassland data based on the seasonal maximum standing biomass. The difference between annual production estimated by harvesting the biomass after mowing at 5 cm above the soil surface (mostly in two cuts), and the maximum seasonal standing biomass must be taken into account. It is proposed to compare data on the basis of the estimation that 62 ± 5% of the annual yield is harvested at the first cut, and that there is a linear relation between the total standing biomass, y (g/m²), and the biomass harvested above a stubble height of 5 cm, x (g/m²) that could be described by the regression line y = 1.10 x + 189.6 (r = 0.89, p < 0.01, n = 34).     

Relative competitive performance of 63 species of terrestrial herbaceous plants

Abstract. There is growing evidence that plant and animal species are arranged in hierarchies of relative competitive performance. More work is needed to determine which plant traits best predict relative competitive performance. We therefore measured relative competitive performance of 63 terrestrial herbaceous plant species using Trichostema brachiatum as a reference species (that is, phytometer or target species). The neighbour species came from a wide array of terrestrial vegetation types (e.g. rock barrens, alvars, old fields), and represented a wide array of growth forms (e.g. small rosette species such as Saxifraga virginiensis and large clonal graminoids such as Agropyron repens). The experiment was repeated with two pot sizes: large (control) and small (stress treatment). Relative competitive performance in large pots (controls) was highly correlated with that in small pots (stress treatment) (r= 0.90, p < 0.001). The hierarchy of relative competitive performance in the large pots was also highly correlated with the hierarchy in the small (stressed) pots (r_s= 0.91, p < 0.001). Principal components analysis and multiple linear regression showed that plant size (measured by total biomass, above‐ground biomass, below‐ground biomass, canopy area, height and leaf area index) and leaf shape (measured as length to width ratio, length, width) were the two characteristics that best predicted relative competitive performance (large pots, r²= 0.55; small pots, r²= 0.48).     

Modeling of polygalacturonase enzyme activity and biomass production by <Emphasis Type="Italic">Aspergillus sojae</Emphasis> ATCC 20235

Aspergillus sojae, which is used in the making of koji, a characteristic Japanese food, is a potential candidate for the production of polygalacturonase (PG) enzyme, which of a major industrial significance. In this study, fermentation data of an A. sojae system were modeled by multiple linear regression (MLR) and artificial neural network (ANN) approaches to estimate PG activity and biomass. Nutrient concentrations, agitation speed, inoculum ratio and final pH of the fermentation medium were used as the inputs of the system. In addition to nutrient conditions, the final pH of the fermentation medium was also shown to be an effective parameter in the estimation of biomass concentration. The ANN parameters, such as number of hidden neurons, epochs and learning rate, were determined using a statistical approach. In the determination of network architecture, a cross-validation technique was used to test the ANN models. Goodness-of-fit of the regression and ANN models was measured by the R ² of cross-validated data and squared error of prediction. The PG activity and biomass were modeled with a 5-2-1 and 5-9-1 network topology, respectively. The models predicted enzyme activity with an R ² of 0.84 and biomass with an R ² value of 0.83, whereas the regression models predicted enzyme activity with an R ² of 0.84 and biomass with an R ² of 0.69.     

Leptin Responses to Weight Loss in Postmenopausal Women: Relationship to Sex‐Hormone Binding Globulin and Visceral Obesity

Objective: Leptin concentrations increase with obesity and tend to decrease with weight loss. However, there is large variation in the response of serum leptin levels to decreases in body weight. This study examines which endocrine and body composition factors are related to changes in leptin concentrations following weight loss in obese, postmenopausal women. Research Methods and Procedures: Body composition (DXA), visceral obesity (computed tomography), leptin, cortisol, insulin, and sex hormone‐binding globulin (SHBG) concentrations were measured in 54 obese (body mass index [BMI] = 32.0 ± 4.5 kg/m²; mean ± SD), women (60 ± 6 years) before and after a 6‐month hypocaloric diet (250 to 350 kcal/day deficit). Results: Body weight decreased by 5.8 ± 3.4 kg (7.1%) and leptin levels decreased by 6.6 ± 11.9 ng/mL (14.5%) after the 6‐month treatment. Insulin levels decreased 10% (p < 0.05), but mean SHBG and cortisol levels did not change significantly. Relative changes in leptin with weight loss correlated positively with relative changes in body weight (r = 0.50, p < 0.0001), fat mass (r = 0.38, p < 0.01), subcutaneous fat area (r = 0.52, p < 0.0001), and with baseline values of SHBG (r = 0.38, p < 0.01) and baseline intra‐abdominal fat area (r = ?0.27, p < 0.06). Stepwise multiple regression analysis showed that baseline SHBG levels (r² = 0.24, p < 0.01), relative changes in body weight (cumulative r² = 0.40, p < 0.05), and baseline intra‐abdominal fat area (cumulative r² = 0.48, p < 0.05) were the only independent predictors of the relative change in leptin, accounting for 48% of the variance. Discussion: These results suggest that obese, postmenopausal women with a lower initial SHBG and more visceral obesity have a greater decrease in leptin with weight loss, independent of the amount of weight lost.     

An empirical model for sediment resuspension in shallow lakes

Suspended solids concentrations were measured at routine 2–3 week intervals and on additional windy days for at least one year in each of seven shallow (mean depth < 2 m) south Island, New Zealand lakes. Surface wave characteristics were estimated from water depths and local meteorological data using a shallow-water wave forecasting model for fetch-limited waves. Bottom shear stresses were computed from surface wave characteristics for the sampling stations and for a hypothetical lake-average station. The calculated shear stresses were, on average, much better predictors of suspended solids concentrations than alternative models using two different functions of wind speed, wave height²/depth or wavelength/depth. A combination of the sample station and lake average shear stresses provided slightly better predictions than the sample station values alone, suggesting that currents also contribute significantly to the concentration at a given point. Regressions of suspended solids on the combined functions had r ² values ranging from 0.74–0.73 in the seven lakes. The slopes of these regressions were negatively related to the settling velocity of the lowest quartile of the sediment, and to macrophyte biomass, in multiple regression (r ² = 0.94, p < 0.01).     

The use of Artemia biomass sampling to predict cyst yields in culture ponds

The possibility of using biomass volume (= mean biomass present in the pond.week ^–1) to predict the total amount of harvestable cysts (= kg wet weight collected. week ^–1) produced in a culture pond by an Artemia franciscana population using a mixed model regression was evaluated for two different sampling methods; horizontal transects and vertical point samples. For transects, the following equation was found: `log (0.01 + cyst yields) = –2.05 + 0.025<sup>*</sup>(biomass volume)' with F <sub>(1, 4.87)</sub> = 8.83 and p = 0.032. For the point samples, the regression was also significant with F <sub>(1, 55.2)</sub> = 13.62 and p = 0.0005 for following equation: `log (0.01 + cyst yield) = –3.613 + 0.021^*(biomass volume). As pond effect and interaction terms did not significantly explain a significant portion of the variance for either of the sampling methods (Transects: pond: F _{(3, 14.3)} = 2.48; p = 0.103; pond^*biomass volume: F _{(3, 3.61)} = 4.63; p = 0.0976; Point samples: pond: F _{(3, 44.5)} = 0.00; p = 0.999; pond^*biomass volume: F _{(3, 44.2)} = 0.11; p = 0.954 ), the variable pond (repeated measurement factor) was not included in the final calculations for the regression equations. Although a combination of factors influences the equation, the high significance levels of the regression indicate biomass volume can be safely used to predict production trends. The low investment requirements of this method make it especially attractive for on farm use, where correctly determining the point of cyst decline will help farmers to allocate resources where needed.     

Racial Differences in Metabolic Predictors of Obesity among Postmenopausal Women

NICKLAS, BARBARA S., DORA M. BERMAN, DAWN C. DAVIS, C. LYNNE DOBROVOLNY, AND KAREN E. DENNIS. Racial differences in metabolic predictors of obesity among postmenopausal women. Ober Res. Objective: This study determined whether there are racial differences in resting metabolic rate (RMR), fat oxidation, and maximal oxygen consumption (VO,max) in obese [body mass index (BMI = 34±2 kg/m²)], postmenopausal (58±2 years) women. Research Methods and Procedures: Twenty black and 20 white women were matched for fat mass and lean mass (LM), as determined by dual energy X-ray absorptiometry. RMR and fat oxidation were measured by indirect calorimetry in the early morning after a 12-hour fast using the ventilated hood technique. VO₂max was measured on a treadmill during a progressive exercise test to voluntary exhaustion. Results: RMR, adjusted for differences in LM, was 5% higher in white than black women (1566±27 and 1490±26 kcal/day, respectively; p<0. 05); and fat oxidation rate was 17% higher in white than black women (87±4 and 72±3 g/day, respectively; p<0. 01). VO₂max (L/minute) was 150 mL per minute (8%) higher (p<0. 05) in white than black women. VO₂max correlated with LM in black (r = 0. 44, p = 0. 05) and white (r=0. 53, p<0. 05) women, but the intercept of the regression line was higher in white than black women (p<0. 05), with no significant difference in slopes. In a multiple regression model including race, body weight, LM, and age, LM was the only independent predictor of RMR (r² = 0. 46, p<0. 0001), whereas race was the only independent predictor of fat oxidation (r² = 0. 18,p<0. 05). The best predictors of VO,max were LM (r² = 0. 22, p<0. 05) and race (cumulative r² = 0. 30, p<0. 05). Discussion: These results show there are racial differences in metabolic predictors of obesity. Determination of whether these ethnic differences lead to, or are an effect of, obesity status or other lifestyle factors requires further study.     

Epicardial Fat from Echocardiography: A New Method for Visceral Adipose Tissue Prediction

Objective: To validate transthoracic echocardiography as an easy and reliable imaging method for visceral adipose tissue (VAT) prediction. VAT is recognized as an important indicator of high cardiovascular and metabolic risk. Several methods are applied to estimate VAT, with different results. Research Methods and Procedures: We selected 60 healthy subjects (29 women, 31 men, 49.5 ± 16.2 years) with a wide range of body mass indexes. Each subject underwent transthoracic echocardiogram and magnetic resonance imaging (MRI) to measure epicardial fat thickness on the right ventricle. Measurements of epicardial adipose tissue thickness were obtained from the same echocardiographic and MRI views and points. MRI was also used to measure VAT cross‐sectional areas at the level of L4 to L5. Anthropometric indexes were also measured. Results: Subjects with predominant visceral fat accumulation showed higher epicardial adipose tissue thickness than subjects with predominant peripheral fat distribution: 9.97 ± 2.88 vs. 4.34 ± 1.98 (p = 0.005) and 7.19 ± 2.74 vs. 3.43 ± 1.64 (p = 0.004) in men and women, respectively. Simple linear regression analysis showed an excellent correlation between epicardial adipose tissue and waist circumference (r = 0.895, p = 0.01) and MRI abdominal VAT (r = 0.864, p = 0.01). Multiple regression analysis showed that epicardial adipose tissue thickness (r² = 0.442, p = 0.02) was the strongest independent variable correlated to MRI VAT. Bland test confirmed the good agreement between the two methods. Discussion: Epicardial adipose tissue showed a strong correlation with anthropometric and imaging measurements of VAT. Hence, transthoracic echocardiography could be an easy and reliable imaging method for VAT prediction.     

Elevated serum monocyte chemoattractant protein-4 and chronic inflammation in overweight subjects

Objective: Chronic inflammation observed in obesity has been reported to be implicated in the development of atherosclerosis. We screened candidate chemokines that link chronic inflammation and obesity. Research Methods and Procedures: Japanese overweight (n = 39, BMI 28.7 ± 0.65 kg/m²) and normal‐weight (n = 24, BMI 22.3 ± 0.45 kg/m²) subjects were enrolled. Using antibody‐based protein microarray, spot intensities of monocyte chemoattractant protein (MCP)‐4, eotaxin, and eotaxin‐2 correlated with anthropometric parameters. We further measured serum concentration of these chemokines and mRNA levels in adipose tissues obtained from volunteers. Results: Serum MCP‐4 levels showed positive correlation with BMI (r = 0.318, p = 0.014), waist (r = 0.316, p = 0.018), and waist‐to‐hip ratio (WHR) (r = 0.264, p = 0.049). Furthermore, MCP‐4 correlated with homeostasis model assessment of insulin resistance (r = 0.392, p = 0.002), high‐sensitivity C‐reactive protein (hsCRP) (r = 0.350, p = 0.006). In step‐wise multiple regression analyses, hsCRP independently correlated with MCP‐4 levels. The expression of MCP‐4 mRNA in visceral adipose tissue positively correlates with BMI. Serum eotaxin levels correlate with BMI (r = 0.262, p = 0.045) and WHR (r = 0.383, p = 0.003). Serum eotaxin‐2 levels correlated with BMI (r = 0.464, p < 0.001), waist (r = 0.333, p = 0.017), and WHR (r = 0.278, p = 0.048). However, eotaxin and eotaxin‐2 levels did not show significant correlation with hsCRP. Discussion: Serum levels of MCP‐4, eotaxin, and eotaxin‐2, which belong to CC chemokine family and share CC chemokine receptor 3, correlated with BMI. These chemokines, especially MCP‐4, may be critical molecules that link obesity and chronic inflammation.     

Methods of Estimation of Visceral Fat: Advantages of Ultrasonography

Objective: To compare methods for the assessment of visceral fat with computed tomography (CT) and establish cutoffs to define visceral obesity based on such alternative methods. Research Methods and Procedures: One hundred women (50.4 ± 7.7 years; BMI 39.2 ± 5.4 kg/m²) underwent anthropometric evaluation, bioelectrical impedance, DXA, abdominal ultrasonography (US), and CT scan. Results: Waist circumference, waist‐to‐hip ratio (WHR), and US‐determined visceral fat values showed the best correlation coefficients with visceral fat determined by CT (r = 0.55, 0.54, and 0.71, respectively; p < 0.01). Fat mass determined by DXA was inversely correlated with visceral‐to‐subcutaneous‐fat ratio (r = ?0.47, p < 0.01). Bioimpedance‐determined fat mass and skinfolds were correlated with only subcutaneous abdominal fat quantified by CT. Linear regression indicated US visceral‐fat distance and WHR as the main predictors of CT‐determined visceral fat (adjusted r² = 0.51, p < 0.01). A waist measurement of 107 cm (82.7% specificity, 60.6% sensitivity) and WHR of 0.97 (78.8% specificity, 63.8% sensitivity) were chosen as discriminator values corresponding with visceral obesity diagnosed by CT. A value of 6.90 cm for visceral fat US‐determined diagnosed visceral obesity with a specificity of 82.8%, a sensitivity of 69.2%, and a diagnostic concordance of 74% with CT. Discussion: US seemed to be the best alternative method for the assessment of intra‐abdominal fat in obese women. Its diagnostic value could be optimized by an anthropometric measurement. Prospective studies are needed to establish CT and US cutoffs for defining visceral‐fat levels related to elevated cardiovascular risk.     

Computational neural network analysis of the affinity of N-n-alkylnicotinium salts for the α4β2* nicotinic acetylcholine receptor

Based on an 85 molecule database, linear regression with different size datasets and an artificial neural network approach have been used to build mathematical relationships to fit experimentally obtained affinity values (K_i) of a series of mono- and bis-quaternary ammonium salts from [³H]nicotine binding assays using rat striatal membrane preparations. The fitted results were then used to analyze the pattern among the experimental K_i values of a set of N-n-alkylnicotinium analogs with increasing n-alkyl chain length from 1 to 20 carbons. The affinity of these N-n-alkylnicotinium compounds was shown to parabolically vary with increasing numbers of carbon atoms in the n-alkyl chain, with a local minimum for the C₄ (n-butyl) analogue. A decrease in K_i value between C₁₂ and C₁₃ was also observed. The statistical results for the best neural network fit of the 85 experimental K_i values are r² = 0.84, rmsd = 0.39; r_cv² = 0.68, and loormsd = 0.56. The generated neural network model with the 85 molecule training set may also be of value for future predictions of K_i values for new virtual compounds, which can then be identified, subsequently synthesized, and tested experimentally.     

A Household Perspective for Biodiversity Conservation

Abstract: Many researchers have implicated human population density in species endangerment, but these correlative studies do not demonstrate causality. We propose that hypotheses implicating human population density in wildlife endangerment at global and national scales owe their public and academic currency as thoroughly to inductive reasoning and repetition as to scientific experimentation. It follows that alternative research hypotheses generated from the same facts should provide equally tenable results. Household density provides such an alternative hypothesis and is growing faster than human population density. We used linear multiple regression models to demonstrate that household density provides a viable alternative statistical hypothesis to human population density for explaining species endangerment (household model, r² = 0.85; population model, r² = 0.84). We then suggest adopting a household perspective for biodiversity conservation because 1) social norms and practices render a household approach to conservation more pragmatic than a human population perspective and 2) shifting the focus toward households could facilitate movement from a human-versus-nature ethic to a humans-situated-within-nature ethic (e.g., a land ethic). Wildlife managers and researchers concerned about the negative influence humans have on biodiversity should consider grounding research, theory, and policy decisions in the dynamics of human households as an alternative to human population.     

Quantification of dead ectomycorrhizae from forest soils using computerized image analysis

A first-generation regression model is presented, describing a linear relationship between dead ectomycorrhizal biomass (mg dry weight) and mycorrhizal area in the xy-plane (mm²) (r²=0.996). This model enables reliable estimates of dead ectomycorrhizal biomass in soils through area measurements of mycorrhizae using computerized image analysis.     

Physical Factors Control Phytoplankton Production and Nitrogen Fixation in Eight Texas Reservoirs

We compared regression tree analyses and multiple linear regression models to explore the relative importance of physical factors, land use, and water quality in predicting phytoplankton production and N₂ fixation potentials at 85 locations along riverine to lacustrine gradients within eight southern reservoirs. The regression tree model (r ² = 0.73) revealed that differences in phytoplankton production were primarily a function of water depth. The highest rates of production (mg C m⁻³ h⁻¹) occurred at shallow sites (<0.9 m), where rates were also related to total phosphorus (TP) levels. At deeper sites, production rates were higher at sites with relative drainage area (RDA, ratio of drainage area to water surface area) below 45, potentially due to longer hydraulic residence times. In contrast, multiple linear regression selected TP, RDA, dissolved phosphorus, and percent developed land as significant model variables (r ² = 0.63). The regression tree model (r ² = 0.67) revealed that N₂ fixation potentials (mg N m⁻³ h⁻¹) were substantially higher at sites with relatively smaller drainage areas (RDA < 45). Within this subgroup, fixation rates were additionally related to TP values (threshold = 41 μg l⁻¹). The multiple linear regression model (r ² = 0.67) also selected RDA as the primary predictor of N₂ fixation. Regression tree models suggest that nutrient controls (phosphorus) were subordinate to physical factors such as depth and RDA. We concluded that regression tree analysis was well suited to revealing nonlinear trends in data (for example, depth), but yielded large uncertainty estimates when applied to linear data (for example, phosphorus).     

Ethnic Differences in Visceral Adipose Tissue and Type 2 Diabetes: Filipino,African‐American,and White Women

Objective: To compare ethnic differences in visceral adipose tissue (VAT), assessed by computed tomography, and type 2 diabetes risk among 55‐ to 80‐year‐old Filipino, African‐American, and white women without known cardiovascular disease. Research Methods and Procedures: Subjects were participants in the Rancho Bernardo Study (n = 196), the Filipino Women's Health Study (n = 181), and the Health Assessment Study of African‐American Women (n = 193). Glucose and anthropometric measurements were assessed between 1995 and 2002. Results: African‐American women had significantly higher age‐adjusted BMI (29.7 kg/m²) and waist girth (88.1 cm) compared with Filipino (BMI, 25.5 kg/m²; waist girth, 81.9 cm) or white (BMI: 26.0 kg/m²; waist girth: 80.7 cm) women. However, VAT was significantly higher among Filipino (69.1 cm³) compared with white (62.3 cm³; p = 0.037) or African‐American (57.5 cm³, p < 0.001) women. VAT correlated better with BMI (r = 0.69) and waist (r = 0.77) in whites, compared with Filipino (r = 0.42; r = 0.59) or African‐American (r = 0.50; r = 0.56) women. Age‐adjusted type 2 diabetes prevalence was significantly higher in Filipinas (32.1%) than in white (5.8%) or African‐American (12.1%) women. Filipinas had higher type 2 diabetes risk compared with African Americans [adjusted odds ratio, 2.30; 95% confidence interval (CI), 1.09 to 4.86] or whites (adjusted odds ratio, 7.51; 95% CI, 2.51 to 22.5) after adjusting for age, VAT, exercise, education, and alcohol intake. Discussion: VAT was highest among Filipinas despite similar BMI and waist circumference as whites. BMI and waist circumference were weaker estimates of VAT in Filipino and African‐American women than in whites. Type 2 diabetes prevalence was highest among Filipino women at every level of VAT, but VAT did not explain their elevated type 2 diabetes risk.     

Lipoprotein Oxidation and Plasma Vitamin E in Nondiabetic Normotensive Obese Patients

Objective: To correlate the susceptibility of low‐(LDL) and very‐low‐density lipoprotein to oxidation in vitro and the concentrations of serum antibodies against malondialdehyde‐modified LDL and plasma vitamin E with the anthropometric and laboratory characteristics of obesity. Research Methods and Procedures: A total of 75 nondiabetic, normotensive obese patients were assigned to one of four groups according to their body mass index (BMI): moderately obese (30 ≤ BMI ≤ 34.9 kg/m², n = 11), severely obese (35 ≤ BMI ≤ 39.9 kg/m², n = 20), morbidly obese (40 ≤ BMI ≤ 50 kg/m², n = 29), and very severely obese (BMI > 50 kg/m², n = 15). Results: The oxidation lag time for LDL from patients with a BMI ≥35 kg/m² was shorter than that for LDL from non‐obese controls (n = 13), whereas very‐low‐density lipoprotein oxidation lag times were not significantly different. The serum antibodies against modified LDL were similar in all groups, whereas the plasma vitamin E concentrations of obese patients were decreased (p ≤ 0.01). There was a negative correlation between LDL oxidation lag time and BMI (r = ?0.35, p = 0.0008), and between plasma vitamin E and BMI (r = ?0.53, p < 0.0001) and waist‐to‐hip ratio (r = ?0.40, p = 0.0003). Discussion: The LDL of nondiabetic, normotensive obese patients is more readily oxidized, and plasma vitamin E concentrations are low. These are both risk factors for coronary heart disease.     

Macroinfaunal biomass and energy flow in a shallow reef flat of the northwestern Philippines

Macrofaunal biomass of the Lucero reef flat in the northwestern Philippines accounted for 9 to 52% of total sediment organic matter, and did not exhibit any significant temporal trend. The polychaetes and crustaceans consistently alternated as biomass dominants; the latter group showed monthly and seasonal variations along with the chaetognaths, molluscs, chordates, and chelicerates, among the major groups (p<0.05). Faunal abundance correlated significantly with biomass. Salinity, mean sediment grain size, sediment heterogeneity, and total organic matter were found to significantly influence faunal biomass.The sandy substrate community was characteristically heterotrophic throughout the monitoring period, i.e., P/R<1. Hourly rates of net primary production (p _n ) did not exhibit any significant diurnal pattern. Monthly comparisons yielded significant differences for estimates of daily gross primary production, P, and respiration, R. Values of P were relatively low, and ranged from 2240 (± 1526 S.D.) to 4890 (± 1377) mg O₂ m^–2 d^–1 while R ranged from 3744 (± 1504) to 6879 (± 903) mg O₂ m^–2 d^–1. R was lower during the dry warm months than the wet months. Multiple regression analyses indicate that primary production was a positive function of light intensity and temperature, and a negative correlate of salinity (adjusted R ² = 0.2444, p< 0.05). Respiration (r) did not appear to relate with any environmental variable, with total macroinfaunal abundance nor with biomass.Results of the study suggest that other heterotrophic components of the sand community were probably responsible for most of the energy consumption, and that these may be dependent on external sources of organic matter.