Introduction to the SAMPLES Approach
Methods for Measuring Greenhouse Gas Balances and Evaluating Mitigation Options in Smallholder Agriculture,
2016
Book Chapter
Climate-induced livelihood transitions in the agricultural systems of Africa are increasingly likely. A recent study by Jones and Thornton (2009) points to the possibility of such climate-induced ...livelihood transitions in the mixed crop-livestock rainfed arid-semiarid systems of Africa. These mixed systems cover over one million square kilometers of farmland in West Africa, Eastern Africa, and Southeastern Africa. Their characteristically scant rainfall usually causes crop failure in one out of every six growing seasons and is thus already marginal for crop production. Under many projected climate futures, these systems will become drier and even more marginal for crop production. This will greatly increase the risk of cropping and among the several possible coping and adaptation mechanisms, (e.g. totally abandoning farming, diversification of income-generating activities such as migration and off-farm employment, etc.) agro-pastoralists may alter the relative emphasis that they currently place on the crop and livestock components of the farming system in favor of livestock. There has been only limited analysis on what such climate induced transitions might look like, but it is clear that the implications could be profound in relation to social, environmental, economic and political effects at local and national levels. This study sought to identify areas in the mixed crop-livestock systems in arid and semi-arid Africa where climate change could compel currently sedentary farmers to abandon cropping and to turn to nomadic pastoralism as a livelihood strategy, using East Africa as a case study. While the current study found no direct evidence for the hypothesized extensification across semiarid areas in East Africa, it is clear that systems are in transition with associated changes not necessarily climate driven but linked to broader socio-economic trends. Not surprisingly, many of the households in the piloted sites face a wide array of problems including poverty, food insecurity and inadequate diets which will be aggravated by the looming risks posed by climate change.
Zanthoxylum rhoifolium Lam. (Rutaceae) has been traditionally used in the treatment of microbial infections and parasitic diseases. In the present study, the antileishmanial effect induced by the ...ethanol extract of stem barks from Z. rhoifolium (ZR-EEtOH) and its n-hexane fraction (ZR-FHEX) on infection and infectivity of murine macrophages by promastigote forms of Leishmania amazonensis were investigated. In different set of experiments, macrophages or promastigotes were pretreated with ZR-EEtOH or ZR-FHEX at non-lethal concentrations for 24 hours, and then macrophages were submitted to infection by promastigotes. Moreover, their effects on activation of macrophages, as well as on the DNA content, size and number of promastigotes by flow cytometry were also evaluated. The infection rate and the number of internalized amastigote forms were markedly decreased after pretreatment of macrophages or promastigotes when compared with non-treated cells. The increase in phagocytic capability and nitrite content was also observed. Furthermore, the decrease of DNA content, size and number of promastigotes was also observed. In conclusion, ZR-EEtOH and ZR-FHEX promoted a markedly significant antileishmanial effect and reduction of infection of macrophages, probably underlying defense mechanisms activation in macrophages. These findings reinforce the potential application of Z. rhoifolium in the treatment of leishmaniasis.
The majority of available scores to assess mortality risk of coronavirus disease 2019 (COVID-19) patients in the emergency department have high risk of bias. Therefore, this cohort aimed to develop ...and validate a score at hospital admission for predicting in-hospital mortality in COVID-19 patients and to compare this score with other existing ones.
Consecutive patients (≥ 18 years) with confirmed COVID-19 admitted to the participating hospitals were included. Logistic regression analysis was performed to develop a prediction model for in-hospital mortality, based on the 3978 patients admitted between March-July, 2020. The model was validated in the 1054 patients admitted during August-September, as well as in an external cohort of 474 Spanish patients.
Median (25-75th percentile) age of the model-derivation cohort was 60 (48-72) years, and in-hospital mortality was 20.3%. The validation cohorts had similar age distribution and in-hospital mortality. Seven significant variables were included in the risk score: age, blood urea nitrogen, number of comorbidities, C-reactive protein, SpO
/FiO
ratio, platelet count, and heart rate. The model had high discriminatory value (AUROC 0.844, 95% CI 0.829-0.859), which was confirmed in the Brazilian (0.859 95% CI 0.833-0.885) and Spanish (0.894 95% CI 0.870-0.919) validation cohorts, and displayed better discrimination ability than other existing scores. It is implemented in a freely available online risk calculator (https://abc2sph.com/).
An easy-to-use rapid scoring system based on characteristics of COVID-19 patients commonly available at hospital presentation was designed and validated for early stratification of in-hospital mortality risk of patients with COVID-19.
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