Additional file 2: Table S2. of Discovery and profiling of small RNAs responsive to stress conditions in the plant pathogen Pectobacterium atrosepticum

Predicted transcription start sites of RNA-seq detected sRNAs (XLSX 9114 kb

Additional file 9: Table S9. of Discovery and profiling of small RNAs responsive to stress conditions in the plant pathogen Pectobacterium atrosepticum

List of primers used for RT-qPCR validation of RNA-seq expression data (DOCX 12 kb

Additional file 1: Table S1. of Discovery and profiling of small RNAs responsive to stress conditions in the plant pathogen Pectobacterium atrosepticum

Complete list of RNA-seq detected sRNAs (XLSX 19 kb

Additional file 7: Table S7. of Discovery and profiling of small RNAs responsive to stress conditions in the plant pathogen Pectobacterium atrosepticum

Differentially expressed sRNA under nutrient-rich and starvation conditions (XLSX 19 kb

Additional file 4: Table S4. of Discovery and profiling of small RNAs responsive to stress conditions in the plant pathogen Pectobacterium atrosepticum

Combined list of predicted sRNA using SIPHT and RITs from WebGester DB. S3A: Matches of in silico predictions with SIPHT (forward strand) S3B: Matches of in silico predictions with SIPHT (complementary strand) (XLSX 15 kb

Mary Strobel Price, collaborative piano

Jake HeggieFernando ObradorsWilliam BolcomFritz Kreisler & Eddie Sout

Additional file 3: Table S3. of Discovery and profiling of small RNAs responsive to stress conditions in the plant pathogen Pectobacterium atrosepticum

List of in silico predicted sRNAs using RITs from WebGester DB. S2A: Forward strand predictions. S2B: Complementary strand predictions (XLSX 30 kb

Additional file 5: Table S5. of Discovery and profiling of small RNAs responsive to stress conditions in the plant pathogen Pectobacterium atrosepticum

Conservation analysis in Soft Rot Enterobacteriaceae (XLSX 16 kb

Predicting the environmental suitability for onchocerciasis in Africa as an aid to elimination planning

Recent evidence suggests that, in some foci, elimination of onchocerciasis from Africa may be feasible with mass drug administration (MDA) of ivermectin. To achieve continental elimination of transmission, mapping surveys will need to be conducted across all implementation units (IUs) for which endemicity status is currently unknown. Using boosted regression tree models with optimised hyperparameter selection, we estimated environmental suitability for onchocerciasis at the 5 × 5-km resolution across Africa. In order to classify IUs that include locations that are environmentally suitable, we used receiver operating characteristic (ROC) analysis to identify an optimal threshold for suitability concordant with locations where onchocerciasis has been previously detected. This threshold value was then used to classify IUs (more suitable or less suitable) based on the location within the IU with the largest mean prediction. Mean estimates of environmental suitability suggest large areas across West and Central Africa, as well as focal areas of East Africa, are suitable for onchocerciasis transmission, consistent with the presence of current control and elimination of transmission efforts. The ROC analysis identified a mean environmental suitability index of 0.71 as a threshold to classify based on the location with the largest mean prediction within the IU. Of the IUs considered for mapping surveys, 50.2% exceed this threshold for suitability in at least one 5×5-km location. The formidable scale of data collection required to map onchocerciasis endemicity across the African continent presents an opportunity to use spatial data to identify areas likely to be suitable for onchocerciasis transmission. National onchocerciasis elimination programmes may wish to consider prioritising these IUs for mapping surveys as human resources, laboratory capacity, and programmatic schedules may constrain survey implementation, and possibly delaying MDA initiation in areas that would ultimately qualify

Additional file 1 of Mapping age- and sex-specific HIV prevalence in adults in sub-Saharan Africa, 2000–2018

Additional file 1: Supplemental information.1. Compliance with the Guidlines for Accurate and Transparent Health Estimates Reporting (GATHER). 2. HIV data sources and data processing. 3. Covariate and auxiliary data. 4. Statistical model. 5. References