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Thermophilic composting is a promising soil and waste management approach involving diverse micro and macro-organisms, including eukaryotes. Due to sub-optimal amounts of nutrients in manure, supplemental feedstock materials such as Lantana camara, and Tithonia diversifolia twigs are used in composting. These materials have, however, been reported to have antimicrobial activity in in-vitro experiments. Furthermore, the phytochemical analysis has shown differences in their complexities, thus possibly requiring various periods to break down. Therefore, it is necessary to understand these materials' influence on the biological and physical-chemical stability of compost. Most compost microbiome studies have been bacterial-centric, leaving out eukaryotes despite their critical role in the environment. Here, the influence of different green feedstock on the fungal and non-fungal eukaryotic community structure in a thermophilic compost environment was examined. Total community fungal and non-fungal eukaryotic DNA was recovered from triplicate compost samples of four experimental regimes. Sequencing for fungal ITS and non-fungal eukaryotes; 18S rDNA was done under the Illumina Miseq platform, and bioinformatics analysis was done using Divisive Amplicon Denoising Algorithm version 2 workflow in R version 4.1. Samples of mixed compost and composting day 84 recorded significantly (P<0.05) higher overall fungal populations, while Lantana-based compost and composting day 84 revealed the highest fungal community diversity. Non-fungal eukaryotic richness was significantly (P< 0.05) more abundant in Tithonia-based compost and composting day 21. The most diverse non-fungal eukaryotic biome was in the Tithonia-based compost and composting day 84. Sordariomycetes and Holozoa were the most contributors to the fungal and non-fungal community interactions in the compost environment, respectively. The findings of this study unravel the inherent influence of diverse composting materials and days on the eukaryotic community structure and compost's biological and chemical stability., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Matheri et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Importance: Mortality prediction among critically ill patients in resource limited settings is difficult. Identifying the best mortality prediction tool is important for counseling patients and families, benchmarking quality improvement efforts, and defining severity of illness for clinical research studies., Objective: Compare predictive capacity of the Modified Early Warning Score (MEWS), Universal Vital Assessment (UVA), Tropical Intensive Care Score (TropICS), Rwanda Mortality Probability Model (R-MPM), and quick Sequential Organ Failure Assessment (qSOFA) for hospital mortality among adults admitted to a medical-surgical intensive care unit (ICU) in rural Kenya. We performed a pre-planned subgroup analysis among ICU patients with suspected infection., Design Setting and Participants: Prospective single-center cohort study at a tertiary care, academic hospital in Kenya. All adults 18 years and older admitted to the ICU January 2018-June 2019 were included., Main Outcomes and Measures: The primary outcome was association of clinical prediction tool score with hospital mortality, as defined by area under the receiver operating characteristic curve (AUROC). Demographic, physiologic, laboratory, therapeutic, and mortality data were collected. 338 patients were included, none were excluded. Median age was 42 years (IQR 33-62) and 61% ( n = 207) were male. Fifty-nine percent ( n = 199) required mechanical ventilation and 35% ( n = 118) received vasopressors upon ICU admission. Overall hospital mortality was 31% ( n = 104). 323 patients had all component variables recorded for R-MPM, 261 for MEWS, and 253 for UVA. The AUROC was highest for MEWS (0.76), followed by R-MPM (0.75), qSOFA (0.70), and UVA (0.69) ( p < 0.001). Predictive capacity was similar among patients with suspected infection., Conclusion and Relevance: All tools had acceptable predictive capacity for hospital mortality, with variable observed availability of the component data. R-MPM and MEWS had high rates of variable availability as well as good AUROC, suggesting these tools may prove useful in low resource ICUs., Competing Interests: KR reports consulting fees from Janssen Pharmaceuticals. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Brotherton, Joshi, Otieno, Wandia, Gitura, Mueller, Nguyen, Letchford, Riviello, Karanja and Rudd.)

Background: Thermophilic composting is a promising method of sanitizing pathogens in manure and a source of agriculturally important thermostable enzymes and microorganisms from organic wastes. Despite the extensive studies on compost prokaryotes, shifts in microbial profiles under the influence of various green materials and composting days are still not well understood, considering the complexity of the green material sources. Here, the effect of regimens of green composting material on the diversity, abundance, and metabolic capacity of prokaryotic communities in a thermophilic compost environment was examined., Methods: Total community 16S rRNA was recovered from triplicate compost samples of Lantana-based, Tithonia-based, Grass-based, and mixed (Lantana + Tithonia + Grass)- based at 21, 42, 63, and 84 days of composting. The 16S rRNA was sequenced using the Illumina Miseq platform. Bioinformatics analysis was done using Divisive Amplicon Denoising Algorithm version 2 (DADA2) R version 4.1 and Phylogenetic Investigation of Communities by Reconstruction of Unobserved States version 2 (PICRUSt2) pipelines for community structure and metabolic profiles, respectively. In DADA2, prokaryotic classification was done using the Refseq-ribosomal database project (RDP) and SILVA version 138 databases., Results: Our results showed apparent differences in prokaryotic community structure for total diversity and abundance within the four compost regimens and composting days. The study showed that the most prevalent phyla during composting included Acidobacteriota, Actinobacteriota, Bacteroidota, Chloroflexi, and Proteobacteria. Additionally, there were differences in the overall diversity of metabolic pathways but no significant differences among the various compost treatments on major metabolic pathways like carbohydrate biosynthesis, carbohydrate degradation, and nitrogen biosynthesis., Conclusion: Various sources of green material affect the succession of compost nutrients and prokaryotic communities. The similarity of amounts of nutrients, such as total Nitrogen, at the end of the composting process, despite differences in feedstock material, indicates a significant influence of composting days on the stability of nutrients during composting., (© 2023. The Author(s).)

Kenya has, in the last decade, made tremendous progress in the fight against malaria. Nevertheless, continued surveillance of the genetic diversity and population structure of Plasmodium falciparum is required to refine malaria control and to adapt and improve elimination strategies. Twelve neutral microsatellite loci were genotyped in 201 P. falciparum isolates obtained from the Kenyan-Ugandan border (Busia) and from two inland malaria-endemic sites situated in western (Nyando) and coastal (Msambweni) Kenya. Analyses were done to assess the genetic diversity (allelic richness and expected heterozygosity, [H e ]), multilocus linkage disequilibrium ( I S A ) and population structure. A similarly high degree of genetic diversity was observed among the three parasite populations surveyed (mean H e  = 0.76; P > 0.05). Except in Msambweni, random association of microsatellite loci was observed, indicating high parasite out-breeding. Low to moderate genetic structure (F ST   = 0.022-0.076; P < 0.0001) was observed with only 5% variance in allele frequencies observed among the populations. This study shows that the genetic diversity of P. falciparum populations at the Kenyan-Ugandan border is comparable to the parasite populations from inland Kenya. In addition, high genetic diversity, panmixia and weak population structure in this study highlight the fitness of Kenyan P. falciparum populations to successfully withstand malaria control interventions., (© 2019 John Wiley & Sons Ltd.)

Plasmodium falciparum histidine-rich proteins 2 (PfHRP2) based RDTs are advocated in falciparum malaria-endemic regions, particularly when quality microscopy is not available. However, diversity and any deletion in the pfhrp2 and pfhrp3 genes can affect the performance of PfHRP2-based RDTs. A total of 400 samples collected from uncomplicated malaria cases from Kenya were investigated for the amino acid repeat profiles in exon 2 of pfhrp2 and pfhrp3 genes. In addition, PfHRP2 levels were measured in 96 individuals with uncomplicated malaria. We observed a unique distribution pattern of amino acid repeats both in the PfHRP2 and PfHRP3. 228 PfHRP2 and 124 PfHRP3 different amino acid sequences were identified. Of this, 214 (94%) PfHRP2 and 81 (65%) PfHRP3 amino acid sequences occurred only once. Thirty-nine new PfHRP2 and 20 new PfHRP3 amino acid repeat types were identified. PfHRP2 levels were not correlated with parasitemia or the number of PfHRP2 repeat types. This study shows the variability of PfHRP2, PfHRP3 and PfHRP2 concentration among uncomplicated malaria cases. These findings will be useful to understand the performance of PfHRP2-based RDTs in Kenya.

Competing Interests: Conflict of Interest Disclosure: Dr. Chinnadurai is a full-time senior staff scientist at Siemens Healthcare, USA. Dr. Lin is a data monitoring committee member of ACI Clinical and speaker for Abiomed.