Early prediction of iron deficiency in females in child bearing age in central Saudi Arabia

No Abstrac

Incidence and predictive biomarkers of Clostridioides difficile infection in hospitalized patients receiving broad-spectrum antibiotics

Trial enrichment using gut microbiota derived biomarkers by high-risk individuals can improve the feasibility of randomized controlled trials for prevention of Clostridioides difficile infection (CDI). Here, we report in a prospective observational cohort study the incidence of CDI and assess potential clinical characteristics and biomarkers to predict CDI in 1,007 patients ≥ 50 years receiving newly initiated antibiotic treatment with penicillins plus a beta lactamase inhibitor, 3rd/4th generation cephalosporins, carbapenems, fluoroquinolones or clindamycin from 34 European hospitals. The estimated 90-day cumulative incidences of a first CDI episode is 1.9% (95% CI 1.1-3.0). Carbapenem treatment (Hazard Ratio (95% CI): 5.3 (1.7-16.6)), toxigenic C. difficile rectal carriage (10.3 (3.2-33.1)), high intestinal abundance of Enterococcus spp. relative to Ruminococcus spp. (5.4 (2.1-18.7)), and low Shannon alpha diversity index as determined by 16 S rRNA gene profiling (9.7 (3.2-29.7)), but not nor malized urinary 3-indoxyl sulfate levels, predicts an increased CDI risk

Microbial Monitoring in the EDEN ISS Greenhouse, a Mobile Test Facility in Antarctica

The EDEN ISS greenhouse, integrated in two joined containers, is a confined mobile test facility in Antarctica for the development and optimization of new plant cultivation techniques for future space programs. The EDEN ISS greenhouse was used successfully from February to November 2018 for fresh food production for the overwintering crew at the Antarctic Neumayer III station. During the 9 months of operation, samples from the different plants, from the nutrition solution of the aeroponic planting system, and from diverse surfaces within the three different compartments of the container were taken [future exploration greenhouse (FEG), service section (SS), and cold porch (CP)]. Quantity as well as diversity of microorganisms was examined by cultivation. In case of the plant samples, microbial quantities were in a range from 102 to 104 colony forming units (CFU) per gram plant material. Compared to plants purchased from a German grocery, the produce hosted orders of magnitude more microorganisms than the EDEN ISS plants. The EDEN ISS plant samples contained mainly fungi and a few bacteria. No classical food associated pathogenic microorganism, like Escherichia and Salmonella, could be found. Probably due to the used cultivation approach, Archaea were not found in the samples. The bioburden in the nutrition solutions increased constantly over time but never reached critical values like 10² –10³ CFU per 100 mL in irrigation water as it is stated, e.g., for commercial European plant productions. The surface samples revealed high differences in the microbial burden between the greenhouse part of the container and the SS and CP part. However, the numbers of organisms (bacteria and fungi) found in the planted greenhouse were still not critical. The microbial loaded surfaces showed strong temporal as well as spatial fluctuations. In samples of the nutrition solution and the surface, the number of bacteria exceeded the amount of fungi by many times. For identification, 16S rRNA gene sequencing was performed for the isolated prokaryotic organisms. Phylogenetic analyses revealed that the most abundant bacterial phyla were Firmicutes and Actinobacteria. These phyla include plant- and human-associated bacterial species. In general, it could be shown that it is possible to produce edible fresh food in a remote environment and this food is safe for consumption from a microbiological point of view

MysiRNA-designer: a workflow for efficient siRNA design

The design of small interfering RNA (siRNA) is a multi factorial problem that has gained the attention of many researchers in the area of therapeutic and functional genomics. MysiRNA score was previously introduced that improves the correlation of siRNA activity prediction considering state of the art algorithms. In this paper, a new program, MysiRNA-Designer, is described which integrates several factors in an automated work-flow considering mRNA transcripts variations, siRNA and mRNA target accessibility, and both near-perfect and partial off-target matches. It also features the MysiRNA score, a highly ranked correlated siRNA efficacy prediction score for ranking the designed siRNAs, in addition to top scoring models Biopredsi, DISR, Thermocomposition21 and i-Score, and integrates them in a unique siRNA score-filtration technique. This multi-score filtration layer filters siRNA that passes the 90% thresholds calculated from experimental dataset features. MysiRNA-Designer takes an accession, finds conserved regions among its transcript space, finds accessible regions within the mRNA, designs all possible siRNAs for these regions, filters them based on multi-scores thresholds, and then performs SNP and off-target filtration. These strict selection criteria were tested against human genes in which at least one active siRNA was designed from 95.7% of total genes. In addition, when tested against an experimental dataset, MysiRNA-Designer was found capable of rejecting 98% of the false positive siRNAs, showing superiority over three state of the art siRNA design programs. MysiRNA is a freely accessible (Microsoft Windows based) desktop application that can be used to design siRNA with a high accuracy and specificity. We believe that MysiRNA-Designer has the potential to play an important role in this area

Microbiota-based markers predictive of development of Clostridioides difficile infection

Antibiotic-induced modulation of the intestinal microbiota can lead to Clostridioides difficile infection (CDI), which is associated with considerable morbidity, mortality, and healthcare-costs globally. Therefore, identification of markers predictive of CDI could substantially contribute to guiding therapy and decreasing the infection burden. Here, we analyze the intestinal microbiota of hospitalized patients at increased CDI risk in a prospective, 90-day cohort-study before and after antibiotic treatment and at diarrhea onset. We show that patients developing CDI already exhibit significantly lower diversity before antibiotic treatment and a distinct microbiota enriched in Enterococcus and depleted of Ruminococcus, Blautia, Prevotella and Bifidobacterium compared to non-CDI patients. We find that antibiotic treatment-induced dysbiosis is class-specific with beta-lactams further increasing enterococcal abundance. Our findings, validated in an independent prospective patient cohort developing CDI, can be exploited to enrich for high-risk patients in prospective clinical trials, and to develop predictive microbiota-based diagnostics for management of patients at risk for CDI

Incidence and predictive biomarkers of Clostridioides difficile infection in hospitalized patients receiving broad-spectrum antibiotics

Trial enrichment using gut microbiota derived biomarkers by high-risk individuals can improve the feasibility of randomized controlled trials for prevention of Clostridioides difficile infection (CDI). Here, we report in a prospective observational cohort study the incidence of CDI and assess potential clinical characteristics and biomarkers to predict CDI in 1,007 patients ≥ 50 years receiving newly initiated antibiotic treatment with penicillins plus a beta- lactamase inhibitor, 3rd/4th generation cephalosporins, carbapenems, fluoroquinolones or clindamycin from 34 European hospitals. The estimated 90-day cumulative incidences of a first CDI episode is 1.9% (95% CI 1.1-3.0). Carbapenem treatment (Hazard Ratio (95% CI): 5.3 (1.7-16.6)), toxigenic C. difficile rectal carriage (10.3 (3.2-33.1)), high intestinal abundance of Enterococcus spp. relative to Ruminococcus spp. (5.4 (2.1-18.7)), and low Shannon alpha diversity index as determined by 16 S rRNA gene profiling (9.7 (3.2-29.7)), but not nor- malized urinary 3-indoxyl sulfate levels, predicts an increased CDI risk

Computational Design of Artificial RNA Molecules For Gene Regulation

This volume provides an overview of RNA bioinformatics methodologies, including basic strategies to predict secondary and tertiary structures, and novel algorithms based on massive RNA sequencing. Interest in RNA bioinformatics has rapidly increased thanks to the recent high-throughput sequencing technologies allowing scientists to investigate complete transcriptomes at single nucleotide resolution. Adopting advanced computational technics, scientists are now able to conduct more in-depth studies and present them to you in this book. Written in the highly successful Methods of Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and equipment, step-by-step, readily reproducible bioinformatics protocols, and key tips to avoid known pitfalls.Authoritative and practical, RNA Bioinformatics seeks to aid scientists in the further study of bioinformatics and computational biology of RNA