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Malware threat is a major hindrance to efficient information exchange on the Internet of Things (IoT). Modelling malware propagation is one of the most imperative applications aimed at understanding mechanisms for protecting the Internet of Things environment. Internet of Things can be realized using agent-based modelling over complex networks. In this paper, a malware propagation model using agent-based approach and deep-reinforcement learning on scale free network in IoT (SFIoT) is assiduously detailed. The proposed model is named based on transition states as Susceptible-Infected-Immuned-Recovered-Removed (SIIRR) that represents the states of nodes on large-scale complex networks. The reliability of each node is investigated using the Mean Time To Failure (MTTF). The factors considered for MTTF computations are: degree of a node, node mobility rate, node transmission rate and distance between two nodes computed using Euclidean distance. The results illustrate that the model is comparable to previous models on effects of malware propagation in terms of average energy consumption, average infections at time (t), node mobility and propagation speed.

The frequency and richness of the theories developed, tested, and used by researchers in an academic discipline exemplify several pertinent factors, namely, the growth, the maturity, the independence, the legitimacy, and the influence of the discipline. Although organizations have been working on projects for centuries, Project Management (PM) is a considerably new academic discipline with emerging research themes, models, methodologies, frameworks, and paradigms. These PM concepts are anchored on or reinforced by new or existing theories. This exploratory study aims to add to the existing PM body of knowledge by investigating the prevalence of theory use in PM research. A systematic content analysis of 9200 PM research articles published from 2000 to 2019 (20 years) in the leading PM journals identified 248 unique theories. These results reveal that the PM discipline is increasingly embracing the use of theories with game theory, fuzzy theory, agency theory, contingency theory, and stakeholder theory emerging as the most dominant theories in the reviewed research articles. Also, although PM is developing its theories, the results revealed that PM researchers continue to heavily use theories borrowed from other academic disciplines such as psychology, sociology, mathematics, and economics., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

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).)

Answer ALS is a biological and clinical resource of patient-derived, induced pluripotent stem (iPS) cell lines, multi-omic data derived from iPS neurons and longitudinal clinical and smartphone data from over 1,000 patients with ALS. This resource provides population-level biological and clinical data that may be employed to identify clinical-molecular-biochemical subtypes of amyotrophic lateral sclerosis (ALS). A unique smartphone-based system was employed to collect deep clinical data, including fine motor activity, speech, breathing and linguistics/cognition. The iPS spinal neurons were blood derived from each patient and these cells underwent multi-omic analytics including whole-genome sequencing, RNA transcriptomics, ATAC-sequencing and proteomics. The intent of these data is for the generation of integrated clinical and biological signatures using bioinformatics, statistics and computational biology to establish patterns that may lead to a better understanding of the underlying mechanisms of disease, including subgroup identification. A web portal for open-source sharing of all data was developed for widespread community-based data analytics., (© 2022. The Author(s).)

Inclusion body myositis (IBM) is a slowly progressive and heterogeneous disorder that is a challenge for measuring clinical trial efficacy. The current methods of measuring progression of the disease utilizes the Inclusion Body Myositis Functional Rating Scale, grip strength by dynamometer, and finger flexor strength. One of the hallmarks of the disease is selective deep finger flexor weakness. To date, no adequate data has been available to determine how well the Functional Rating Scale relates to this hallmark physical exam deficit. Our study is the first to investigate the degree of correlation between items pertaining to hand function in the Functional Rating Scale with measured grip and finger flexor strength in IBM patients. We have found a lower than expected correlation with finger flexor strength and even lower with grip strength. The current Functional Rating Scale will benefit from optimization to measure clinical progression more accurately., (Copyright © 2019 Elsevier B.V. All rights reserved.)

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.

Rapid diagnostic tests (RDT) are valuable tools that support prudent and timely use of antimalarial drugs, particularly if reliable microscopy is not available. However, the performance and reliability of these tests vary between and within geographical regions. The present study evaluated the performance of routine malaria RDT in Kenyan febrile patients in Busia County, Kenya. A cross sectional study design was employed to recruit febrile patients attending health facilities between August and November 2016. A total of 192 febrile patients who were slide positive and negative were evaluated for their infection status by nested PCR and RDTs (PfHRP2/pLDH). In addition, P. falciparum diversity of the histidine-rich proteins 2 and 3, that influences the RDT test results were determined. All individuals were P. falciparum positive. Among the investigated 192 febrile patients, 76 (40%) were positive by microscopy, 101 (53%) by RDTs and 80 (42%) were PCR positive. The performance of the CareStart™ HRP2/pLDH (pf) RDTs was better than microscopy (Sensitivity 94%; Specificity 75%) and Nucleic acid testing (sensitivity 95%, specificity 77%) with high negative predictive values, indicating the suitability of the RDT in routine practice. Specific pfhrp2/pfhrp3 deletions shown to associate with RDT false negativity was not observed. However, high genetic diversity among pfhrp2 gene was observed. Eleven new PfHRP2 and nine PfHRP3 repeats were observed. False positivity by microscopy and under reporting of infections may thus be a barrier in malaria control and elimination programs. The HRP2/pLDH(Pf) based RDT yet demonstrate to be an effective tool for malaria surveillance program., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Purpose of the Review: The purpose of this review is to illustrate specific challenges and opportunities in the building of an adult congenital heart disease (ACHD) program and to highlight critical components and important allies., Recent Findings: With more than 1.4 million adults with congenital heart disease in the USA alone, access to specialized, compassionate, high-quality comprehensive care requires a shift toward more aggressive expansion of ACHD care, especially in the context of sparse ACHD provider representation in the vast majority of adult medical centers. The effective build of an ACHD program requires measured escalation in management of ACHD complexity matched with cultivation of key resources and clinical services ranging from congenital cardiac surgery and interventional cardiology to acquired heart disease as well as partnerships with non-cardiac specialists. By reframing ACHD care as a shared goal between patients, providers, hospitals, pharmaceutical and device industry, and payers, a potent business model can be built around the developing ACHD program to facilitate acquisition of these key resources.