333 research outputs found
African Land Ecology: Opportunities and Constraints for Agricultural Development
Current agriculture in Sub-Sahara Africa is undeveloped and the Green Revolution has left the continent largely untouched. Poor performance is often related to a number of socio-economic factors. In this paper we argue that there are also some specifities of natural resources, namely local homogeneity and spatial diversity of the pre-dominant Basement Complex soils, that imply that simple fertilizer strategies may not produce the yield increases obtained elsewhere. Keywords: Sub-Sahara Africa, Agro-Ecology, Land use, Land resources, Basement Complex, Green Revolution, Micronutrients, Fertilizer Policy
Climate change and global agricultural potential. A case study of nigeria
This study presents a spatially specific assessment of the potential impacts of the greenhouse effect on crop production potentials and land productivity in Nigeria. To this effect a large number of scenarios were used consisting of results from experiments with General Circulation
Models (GCM’s) as well as sensitivity scenarios in which single variables were changed. Each scenario is characterised by level of increase of atmospheric CO2, change of stomatal resistance and climate change in terms of temperatures, rainfall and radiation. The effects of such changes have been assessed within the framework of the agro-ecological zones methodology, that was adapted and expanded for the purpose of the present study. Climate changes are applied to observed baseline conditions for the period 1960-1990 and simulated climate is used in combination with soil and landform conditions, plant physiological adaptations to elevated CO2 and a number of sustainability criteria (e.g. fallow period requirements) to calculate crop production potentials and land productivity. Scenario outputs are compared with current conditions to assess potential impacts and sensitivity of agricultural production to global change phenomena.
A large number of maps and tables summarise the potential impacts on crop production potentials and land productivity. The low predictive value of GCM’s and large differences between GCM’s only allow to draw conclusions of policy relevance taking into account a cautionary bandwidth of possible events. The Nigerian middle belt will hardly be affected because changes are likely to be limited and farmers may adapt by choosing other crop varieties.
The north of the country is very sensitive to changes of climate and the prevailing crops show little response to elevated CO2 levels. GCM’s are consistent in indicating climatic changes that lower land suitability for perennial crops in the south. The south-west, with a bimodal rainfall tendency, is particularly sensitive to climate change. Here small changes in scenario may cause either one long growing period or two short ones. However, lower productivity due to climate change, if any, is likely to be more than compensated by the effects of enhanced CO2 levels.
Prevalent crops in the south have a C3 photosynthesis pathway, that is responsive to enhanced
CO2 levels, which is likely to result in increased of productivity of annual crops such as yams and cassava. Global change may thus exacerbate the current disparities of crop production potentials between the north and the south of the country
Building a super-resolution fluorescence cryomicroscope
Correlated super-resolution fluorescence microscopy and cryo-electron microscopy enables imaging with both high labeling specificity and high resolution. Naturally, combining two sophisticated imaging techniques within one workflow also introduces new requirements on hardware, such as the need for a super-resolution fluorescence capable microscope that can be used to image cryogenic samples. In this chapter, we describe the design and use of the “cryoscope”; a microscope designed for single-molecule localization microscopy (SMLM) of cryoEM samples that fits right into established cryoEM workflows. We demonstrate the results that can be achieved with our microscope by imaging fluorescently labeled vimentin, an intermediate filament, within U2OS cells grown on EM grids, and we provide detailed 3d models that encompass the entire design of the microscope
Ethnic differences in total and HDL cholesterol among Turkish, Moroccan and Dutch ethnic groups living in Amsterdam, the Netherlands
Ethnic differences in total and HDL cholesterol among Turkish, Moroccan and Dutch ethnic groups living in Amsterdam, the Netherlands
Ethnic differences in diabetes, cardiovascular risk factors and health care: the Amsterdam Health Survey of 2004
The prevalence of diabetes in inhabitants of Amsterdam (18 years and older) is 4%. The prevalence of diabetes is three times higher among Turkish people and four times higher among Moroccans in comparison to Dutch people. Turkish diabetes patients have a higher mean body mass index compared to Dutch diabetes patients, but Turkish and Moroccan diabetes patients are admitted to hospital less often than Dutch diabetes patients. It is important for policy makers to know the differences in disease prevalence and health care use between ethnic groups, considering the expected rise in the proportion of immigrants. These results formed contributions to this report that was brought out by the National Institute for Public Health and the Environment and in cooperation with the Amsterdam Health Monitor of the Amsterdam Health Service. Forty-three percent of the 4042 invited Amsterdam inhabitants participated in the study in 2004. Ethnic differences in health and health care use were analyzed for the age group of 18-70 years, standardized for age and gender. Turkish and Moroccan people without diabetes differed from Dutch people without diabetes on many counts. For example, Turkish and Moroccan people were more often overweight and had higher mean blood glucose levels. They visited their general practitioners more often and experienced their own health as being moderate or poor on a more frequent basis. Turkish people without diabetes experienced more serious cardiac problems than Dutch people. The prevalence of cardiovascular risk factors in diabetes patients was high among all ethnic groups. In general, cardiovascular risk factors were more frequent in Turkish diabetes patients, and to a lesser extent in Moroccan diabetes patients, compared to Dutch diabetes patients. Treatment of cardiovascular risk factors in diabetes patients is important for the prevention of or delay in cardiovascular complications.De prevalentie van diabetes bij inwoners van Amsterdam (18 jaar en ouder) wordt geschat op vier procent. Turken en Marokkanen hebben respectievelijk driemaal en viermaal vaker diabetes vergeleken met Nederlanders. Turkse diabeten zijn gemiddeld zwaarder dan Nederlandse diabeten. Turkse en Marokkaanse diabeten worden echter minder vaak opgenomen in een ziekenhuis dan Nederlandse diabeten. Een beschrijving van etniciteitverschillen in het voorkomen van ziekten en zorggebruik is van belang voor het beleid omdat immigranten een steeds groter deel van de bevolking zullen gaan uitmaken. De Amsterdamse Gezondheidsmonitor 2004 is uitgevoerd door de GGD Amsterdam in samenwerking met het RIVM. Drieenveertig procent van 4042 uitgenodigde Amsterdammers (18 jaar en ouder) heeft aan het onderzoek meegedaan. Etnische verschillen in gezondheid en zorg werden geanalyseerd voor de leeftijd 18-70 jaar, gestandaardiseerd naar leeftijd en geslacht. Turken en Marokkanen zonder diabetes verschilden op bijna alle uitkomsten van Nederlanders zonder diabetes. Turken en Marokkanen waren bijvoorbeeld gemiddeld zwaarder dan Nederlanders en zij hadden hogere gemiddelde bloedglucosewaarden. Zij gingen vaker naar de huisarts en waren minder tevreden over de eigen gezondheid. Acht procent van de Turken zonder diabetes heeft ooit een ernstige hartaandoening gehad, dit is bijna viermaal zo vaak als bij Nederlanders zonder diabetes. Risicofactoren voor hart- en vaatziekten kwamen veel voor bij diabeten uit alle etnische groepen. Turkse diabeten, en in mindere mate Marokkaanse diabeten, hadden over het algemeen een ongunstiger risicoprofiel dan Nederlandse diabeten. Behandeling van het risicoprofiel van diabetespatienten is belangrijk om het optreden van complicaties te voorkomen of uit te stellen
The healthy beverage index is not associated with insulin resistance, prediabetes and type 2 diabetes risk in the Rotterdam Study
Purpose:Whether beverage quality affects changes in glycaemic traits and type 2 diabetes (T2D) risk is unknown. We examined associations of a previously developed Healthy Beverage Index (HBI) with insulin resistance, and risk of prediabetes and T2D. Methods: We included 6769 participants (59% female, 62.0 ± 7.8 years) from the Rotterdam Study cohort free of diabetes at baseline. Diet was assessed using food-frequency questionnaires at baseline. The HBI included 10 components (energy from beverages, meeting fluid requirements, water, coffee and tea, low-fat milk, diet drinks, juices, alcohol, full-fat milk, and sugar-sweetened beverages), with a total score ranging from 0 to 100. A higher score represents a healthier beverage pattern. Data on study outcomes were available from 1993 to 2015. Multivariable linear mixed models and Cox proportional-hazards regression models were used to examine associations of the HBI (per 10 points increment) with two measurements of HOMA-IR (a proxy for insulin resistance), and risk of prediabetes and T2D. Results: During follow-up, we documented 1139 prediabetes and 784 T2D cases. Mean ± SD of the HBI was 66.8 ± 14.4. Higher HBI score was not associated with HOMA-IR (β: 0.003; 95% CI − 0.007, 0.014), or with risk of prediabetes (HR: 1.01; 95% CI 0.97, 1.06), or T2D (HR: 1.01; 95% CI 0.96, 1.07). Conclusion: Our findings suggest no major role for overall beverage intake quality assessed with the HBI in insulin resistance, prediabetes and T2D incidence. The HBI may not be an adequate tool to assess beverage intake quality in our population.</p
Shallow rainwater lenses in deltaic areas with saline seepage
In deltaic areas with saline seepage, freshwater availability is often limited to shallow rainwater lenses lying on top of saline groundwater. Here we describe the characteristics and spatial variability of such lenses in areas with saline seepage and the mechanisms that control their occurrence and size. Our findings are based on different types of field measurements and detailed numerical groundwater models applied in the south-western delta of the Netherlands. By combining the applied techniques we could extrapolate measurements at point scale (groundwater sampling, temperature and electrical soil conductivity (TEC)-probe measurements, electrical cone penetration tests (ECPT)) to field scale (continuous vertical electrical soundings (CVES), electromagnetic survey with EM31), and even to regional scale using helicopter-borne electromagnetic measurements (HEM). The measurements show a gradual mixing zone between infiltrating fresh rainwater and upward flowing saline groundwater. The mixing zone is best characterized by the depth of the centre of the mixing zone <i>D</i><sub>mix</sub>, where the salinity is half that of seepage water, and the bottom of the mixing zone <i>B</i><sub>mix</sub>, with a salinity equal to that of the seepage water (Cl-conc. 10 to 16 g l<sup>−1</sup>). <i>D</i><sub>mix</sub> is found at very shallow depth in the confining top layer, on average at 1.7 m below ground level (b.g.l.), while <i>B</i><sub>mix</sub> lies about 2.5 m b.g.l. The model results show that the constantly alternating upward and downward flow at low velocities in the confining layer is the main mechanism of mixing between rainwater and saline seepage and determines the position and extent of the mixing zone (<i>D</i><sub>mix</sub> and <i>B</i><sub>mix</sub>). Recharge, seepage flux, and drainage depth are the controlling factors
The association between dietary and skin advanced glycation end products: the Rotterdam Study
BackgroundAdvanced glycation end products (AGEs) accumulate in tissues with age and in conditions such as diabetes mellitus and chronic kidney disease (CKD), and they may be involved in age-related diseases. Skin AGEs measured as skin autofluorescence (SAF) are a noninvasive reflection of long-term AGE accumulation in tissues. Whether AGEs present in the diet (dAGEs) contribute to tissue AGEs is unclear.ObjectivesOur aim was to investigate the association between dietary and skin AGEs in the Rotterdam Study, a population-based cohort of mainly European ancestry.MethodsIn 2515 participants, intake of 3 dAGEs [carboxymethyl-lysine (CML), N-(5-hydro-5-methyl-4-imidazolon-2-yl)-ornithine (MGH1), and carboxyethyl-lysine (CEL)] was estimated using FFQs and the content of AGEs measured in commonly consumed foods. SAF was measured 5 y (median value) later using an AGE Reader. The association of dAGEs with SAF was analyzed in linear regression models and stratified for diabetes and chronic kidney disease (CKD, defined as estimated glomerular filtration rate ≤60 mL/min) status.ResultsMean ± SD intake was 3.40 ±0.89 mg/d for CML, 28.98 ±7.87 mg/d for MGH1, and 3.11 ±0.89 mg/d for CEL. None of them was associated with SAF in the total study population. However, in stratified analyses, CML was positively associated with SAF after excluding both individuals with diabetes and individuals with CKD: 1 SD higher daily CML intake was associated with a 0.03 (95% CI: 0.009, 0.05) arbitrary units higher SAF. MGH1 and CEL intake were not significantly associated with SAF. Nevertheless, the associations were stronger when the time difference between dAGEs and SAF measurements was shorter.ConclusionsHigher dietary CML intake was associated with higher SAF only among participants with neither diabetes nor CKD, which may be explained by high AGE formation in diabetes and decreased excretion in CKD or by dietary modifications in these disease groups. The dAGE–SAF associations were also modified by the time difference between measurements. Our results suggest that dAGEs can influence tissue AGE accumulation and possibly thereby age-related diseases. This trial was registered at the Netherlands National Trial Register as NTR6831 (http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=6831) and at the WHO International Clinical Trials Registry Platform as NTR6831 (http://www.who.int/ictrp/network/primary/en/).<br/
Association of Insulin Resistance and Type 2 Diabetes With Gut Microbial Diversity A Microbiome-Wide Analysis From Population Studies
IMPORTANCE Previous studies have indicated that gut microbiome may be associated with development of type 2 diabetes. However, these studies are limited by small sample size and insufficient for confounding. Furthermore, which specific taxa play a role in the development of type 2 diabetes remains unclear.OBJECTIVE To examine associations of gut microbiome composition with insulin resistance and type 2 diabetes in a large population-based setting controlling for various sociodemographic and lifestyle factors.DESIGN, SETTING, AND PARTICIPANTS This cross-sectional analysis included 2166 participants from 2 Dutch population-based prospective cohorts: the Rotterdam Study and the LifeLines-DEEP study.EXPOSURES The 16S ribosomal RNA method was used to measure microbiome composition in stool samples collected between January 1, 2012, and December 31, 2013. The alpha diversity (Shannon, richness, and Inverse Simpson indexes), beta diversity (Bray-Curtis dissimilarity matrix), and taxa (from domain to genus level) were identified to reflect gut microbiome composition.MAIN OUTCOMES AND MEASURES Associations among alpha diversity, beta diversity, and taxa with the Homeostatic Model Assessment of Insulin Resistance (HOMA-IR) and with type 2 diabetes were examined. Glucose and insulin were measured to calculate the HOMA-IR. Type 2 diabetes cases were identified based on glucose levels and medical records from January 2012 to December 2013. Analyses were adjusted for technical covariates, lifestyle, sociodemographic, and medical factors. Data analysis was performed from January 1, 2018, to December 31, 2020.RESULTS There were 2166 participants in this study: 1418 from the Rotterdam Study (mean [SD] age, 62.4 [5.9] years; 815 [57.5%] male) and 748 from the LifeLines-DEEP study (mean [SD] age, 44.7 [13.4] years; 431 [57.6%] male); from this total, 193 type 2 diabetes cases were identified. Lower microbiome Shannon index and richness were associated with higher HOMA-IR (eg, Shannon index, -0.06; 95% CI, -0.10 to -0.02), and patients with type 2 diabetes had a lower richness than participants without diabetes (odds ratio [OR], 0.93; 95% CI, 0.88-0.99). The beta diversity (Bray-Curtis dissimilarity matrix) was associated with insulin resistance (R-2 = 0.004, P = .001 in the Rotterdam Study and R-2 = 0.005, P = .002 in the LifeLines-DEEP study). A total of 12 groups of bacteria were associated with HOMA-IR or type 2 diabetes. Specifically, a higher abundance of Christensenellaceae (beta = -0.08; 95% CI, -0.12 to -0.03: P < .001), Christensenellaceae R7 group (beta = -0.07; 95% CI, -0.12 to -0.03; P < .001), Marvinbryantia (beta = -0.07; 95% CI, -0.11 to -0.03; P < .001), Ruminococcaceae UCG005 (beta = -0.09; 95% CI, -0.13 to -0.05; P < .001), Ruminococcaceae UCG008 (beta = -0.07; 95% CI, -0.11 to -0.03; P < .001), Ruminococcaceae UCG010 (beta = -0.08; 95% CI, -0.12 to -0.04; P < .001), or Ruminococcaceae NK4A214 group (beta = -0.09; 95% CI, -0.13 to -0.05; P < .001) was associated with lower HOMA-IR. A higher abundance of Clostridiaceae 1 (OR, 0.51; 95% CI, 0.41-0.65; P < .001), Peptostreptococcaceae (OR, 0.56; 95% CI, 0.45-0.70; P < .001), C sensu stricto 1 (OR, 0.51; 95% CI, 0.40-0.65; P < .001), Intestinibacter (OR, 0.60; 95% CI, 0.48-0.76; P < .001), or Romboutsia (OR, 0.55; 95% CI, 0.44-0.70; P < .001) was associated with less type 2 diabetes. These bacteria are all known to produce butyrate.CONCLUSIONS AND RELEVANCE In this cross-sectional study, higher microbiome alpha diversity, along with more butyrate-producing gut bacteria, was associated with less type 2 diabetes and with lower insulin resistance among individuals without diabetes. These findings could help provide insight into the etiology, pathogenesis, and treatment of type 2 diabetes.</p
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