Exploring future agricultural development and biodiversity in Uganda, Rwanda and Burundi: a spatially explicit scenario-based assessment

Competition for land is increasing as a consequence of the growing demands for food and other commodities and the need to conserve biodiversity and ecosystem services. Land conversion and the intensification of current agricultural systems continues to lead to a loss of biodiversity and trade-offs among ecosystem functions. Decision-makers need to understand these trade-offs in order to better balance different demands on land and resources. There is an urgent need for spatially explicit information and analyses on the effects of different trajectories of human-induced landscape change in biodiversity and ecosystem services. We assess the potential implications of a set of plausible socio-economic and climate scenarios for agricultural production and demand and model-associated land use and land cover changes between 2005 and 2050 to assess potential impacts on biodiversity in Uganda, Rwanda and Burundi. We show that different future socio-economic scenarios are consistent in their projections of areas of high agricultural development leading to similar spatial patterns of habitat and biodiversity loss. Yet, we also show that without protected areas, biodiversity losses are higher and that expanding protected areas to include other important biodiversity areas can help reduce biodiversity losses in all three countries. These results highlight the need for effective protection and the potential benefits of expanding the protected area network while meeting agricultural production needs

Exploring future agricultural development and biodiversity in Uganda, Rwanda and Burundi: a spatially explicit scenario-based assessment

Competition for land is increasing as a consequence of the growing demands for food and other commodities and the need to conserve biodiversity and ecosystem services. Land conversion and the intensification of current agricultural systems continues to lead to a loss of biodiversity and trade-offs among ecosystem functions. Decision-makers need to understand these trade-offs in order to better balance different demands on land and resources. There is an urgent need for spatially explicit information and analyses on the effects of different trajectories of human-induced landscape change in biodiversity and ecosystem services. We assess the potential implications of a set of plausible socio-economic and climate scenarios for agricultural production and demand and model-associated land use and land cover changes between 2005 and 2050 to assess potential impacts on biodiversity in Uganda, Rwanda and Burundi. We show that different future socio-economic scenarios are consistent in their projections of areas of high agricultural development leading to similar spatial patterns of habitat and biodiversity loss. Yet, we also show that without protected areas, biodiversity losses are higher and that expanding protected areas to include other important biodiversity areas can help reduce biodiversity losses in all three countries. These results highlight the need for effective protection and the potential benefits of expanding the protected area network while meeting agricultural production needs

Multi-factor, multi-state, multi-model scenarios: Exploring food and climate futures for Southeast Asia

Decision-makers aiming to improve food security, livelihoods and resilience are faced with an uncertain future. To develop robust policies they need tools to explore the potential effects of uncertain climatic, socioeconomic, and environmental changes. Methods have been developed to use scenarios to present alternative futures to inform policy. Nevertheless, many of these can limit the possibility space with which decision-makers engage. This paper will present a participatory scenario process that maintains a large possibility space through the use of multiple factors and factor-states and a multi-model ensemble to create and quantify four regional scenarios for Southeast Asia. To do this we will explain 1) the process of multi-factor, multi-state building was done in a stakeholder workshop in Vietnam, 2) the scenario quantification and model results from GLOBIOM and IMPACT, two economic models, and 3) how the scenarios have already been applied to diverse policy processes in Cambodia, Laos, and Vietnam

Patient’s characteristics and outcomes in necrotising soft-tissue infections: results from a Scandinavian, multicentre, prospective cohort study

Purpose: Necrotising soft-tissue infections (NSTI) are characterised by necrosis, fast progression, and high rates of morbidity and mortality, but our knowledge is primarily derived from small prospective studies and retrospective studies. Methods: We performed an international, multicentre, prospective cohort study of adults with NSTI describing patient’s characteristics and associations between baseline variables and microbiological findings, amputation, and 90-day mortality. Results: We included 409 patients with NSTI; 402 were admitted to the ICU. Cardiovascular disease [169 patients (41%)] and diabetes [98 (24%)] were the most common comorbidities; 122 patients (30%) had no comorbidity. Before surgery, bruising of the skin [210 patients (51%)] and pain requiring opioids [172 (42%)] were common. The sites most commonly affected were the abdomen/ano-genital area [140 patients (34%)] and lower extremities [126 (31%)]. Monomicrobial infection was seen in 179 patients (44%). NSTI of the upper or lower extremities was associated with monomicrobial group A streptococcus (GAS) infection, and NSTI located to the abdomen/ano-genital area was associated with polymicrobial infection. Septic shock [202 patients (50%)] and acute kidney injury [82 (20%)] were common. Amputation occurred in 22% of patients with NSTI of an extremity and was associated with higher lactate level. All-cause 90-day mortality was 18% (95% CI 14–22); age and higher lactate levels were associated with increased mortality and GAS aetiology with decreased mortality. Conclusions: Patients with NSTI were heterogeneous regarding co-morbidities, initial symptoms, infectious localisation, and microbiological findings. Higher age and lactate levels were associated with increased mortality, and GAS infection with decreased mortality

Discriminatory plasma biomarkers predict specific clinical phenotypes of necrotizing soft-tissue infections

BACKGROUND: Necrotizing soft-tissue infections (NSTIs) are rapidly progressing infections frequently complicated by septic shock and associated with high mortality. Early diagnosis is critical for patient outcome, but challenging due to vague initial symptoms. Here, we identified predictive biomarkers for NSTI clinical phenotypes and outcomes using a prospective multicenter NSTI patient cohort. METHODS: Luminex multiplex assays were used to assess 36 soluble factors in plasma from NSTI patients with positive microbiological cultures (n = 251 and n = 60 in the discovery and validation cohorts, respectively). Control groups for comparative analyses included surgical controls (n = 20), non-NSTI controls (i.e., suspected NSTI with no necrosis detected upon exploratory surgery, n = 20), and sepsis patients (n = 24). RESULTS: Thrombomodulin was identified as a unique biomarker for detection of NSTI (AUC, 0.95). A distinct profile discriminating mono- (type II) versus polymicrobial (type I) NSTI types was identified based on differential expression of IL-2, IL-10, IL-22, CXCL10, Fas-ligand, and MMP9 (AUC >0.7). While each NSTI type displayed a distinct array of biomarkers predicting septic shock, granulocyte CSF (G-CSF), S100A8, and IL-6 were shared by both types (AUC >0.78). Finally, differential connectivity analysis revealed distinctive networks associated with specific clinical phenotypes. CONCLUSIONS: This study identifies predictive biomarkers for NSTI clinical phenotypes of potential value for diagnostic, prognostic, and therapeutic approaches in NSTIs. TRIAL REGISTRATION: ClinicalTrials.gov NCT01790698. FUNDING: Center for Innovative Medicine (CIMED); Region Stockholm; Swedish Research Council; European Union; Vinnova; Innovation Fund Denmark; Research Council of Norway; Netherlands Organisation for Health Research and Development; DLR Federal Ministry of Education and Research; and Swedish Children’s Cancer Foundation

Necrotizing Soft Tissue Infection Staphylococcus aureus but not S. pyogenes Isolates Display High Rates of Internalization and Cytotoxicity Toward Human Myoblasts

Necrotizing soft tissue infections (NSTIs) caused by group A Streptococcus (GAS) and occasionally by Staphylococcus aureus (SA) frequently involve the deep fascia and often lead to muscle necrosis. Methods: To assess the pathogenicity of GAS and S. aureus for muscles in comparison to keratinocytes, adhesion and invasion of NSTI-GAS and NSTI-SA isolates were assessed in these cells. Bloodstream infections (BSI-SA) and noninvasive coagulase-negative staphylococci (CNS) isolates were used as controls. Results: NSTI-SA and BSI-SA exhibited stronger internalization into human keratinocytes and myoblasts than NSTI-GAS or CNS. S. aureus internalization reached over 30% in human myoblasts due to a higher percentage of infected myoblasts (>11%) as compared to keratinocytes (<3%). Higher cytotoxicity for myoblasts of NSTI-SA as compared to BSI-SA was attributed to higher levels of psmα and RNAIII transcripts in NSTI-SA. However, the 2 groups were not discriminated at the genomic level. The cellular basis of high internalization rate in myoblasts was attributed to higher expression of α5β1 integrin in myoblasts. Major contribution of FnbpAB-integrin α5β1 pathway to internalization was confirmed by isogenic mutants. Conclusions: Our findings suggest a factor in NSTI-SA severity is the strong invasiveness of S. aureus in muscle cells, a property not shared by NSTI-GAS isolates