RefSeq Functional Elements as experimentally assayed nongenic reference standards and functional interactions in human and mouse

Eukaryotic genomes contain many nongenic elements that function in gene regulation, chromosome organization, recombination, repair or replication, and mutation of those elements can affect genome function and cause disease. While numerous epigenomic studies provide high coverage of gene regulatory regions, those data are not usually exposed in traditional genome annotation, and can be difficult to access and interpret without field-specific expertise. The National Center for Biotechnology Information (NCBI) therefore provides RefSeq Functional Elements (RefSeqFEs), which represent experimentally validated human and mouse nongenic elements derived from the literature. The curated dataset is comprised of richly annotated sequence records, descriptive records in the NCBI Gene database, reference genome feature annotation, and activity-based interactions between nongenic regions, target genes and each other. The dataset provides succinct functional details and transparent experimental evidence, leverages data from multiple experimental sources, is readily accessible and adaptable, and utilizes a flexible data model. The data have multiple uses for basic functional discovery, bioinformatics studies, genetic variant interpretation, as known positive controls for epigenomic data evaluation, and as reference standards for functional interactions. Comparisons to other gene regulatory datasets show that the RefSeqFE dataset includes a wider range of feature types representing more areas of biology, but it is comparatively smaller and subject to data selection biases. RefSeqFEs thus provide an alternative and complementary resource for experimentally assayed functional elements, with future dataset growth expected.

The Selective Effects of Environmental Change on the Functional Diversity of Soil Decomposers

Whether decomposition can be affected by the biodiversity of soil organisms is an important question. Biodiversity is commonly expressed through indices that are based on species richness and abundances. Soil processes tend to saturate at low levels of species richness. A component of biodiversity is functional diversity, and we have shown that the absence of the influence of species richness on decomposition switched into a positive relationship between fauna diversity and decomposition when we expressed biodiversity in terms of interspecific functional dissimilarity. Communities with functionally dissimilar species are characterized by complementary resource use and facilitative interactions among species. It is suggested that the effects of environmental changes on ecosystem functions such as decomposition can be better understood if we have more knowledge about the selective effect of these changes on specific facets of soil biodiversity, such as functional diversity.

Complementary resource preferences spontaneously emerge in diauxic microbial communities

Many microbes grow diauxically, utilizing the available resources one at a time rather than simultaneously. The properties of communities of microbes growing diauxically remain poorly understood, largely due to a lack of theory and models of such communities. Here, we develop and study a minimal model of diauxic microbial communities assembling in a serially diluted culture. We find that unlike co-utilizing communities, diauxic community assembly repeatably and spontaneously leads to communities with complementary resource preferences, namely communities where species prefer different resources as their top choice. Simulations and theory explain that the emergence of complementarity is driven by the disproportionate contribution of the top choice resource to the growth of a diauxic species. Additionally, we develop a geometric approach for analyzing serially diluted communities, with or without diauxie, which intuitively explains several additional emergent community properties, such as the apparent lack of species which grow fastest on a resource other than their most preferred resource. Overall, our work provides testable predictions for the assembly of natural as well as synthetic communities of diauxically shifting microbes.

Toward Using Twitter Data to Monitor COVID-19 Vaccine Safety in Pregnancy: Proof-of-Concept Study of Cohort Identification (Preprint)

BACKGROUND COVID-19 during pregnancy is associated with an increased risk of maternal death, intensive care unit admission, and preterm birth; however, many people who are pregnant refuse to receive COVID-19 vaccination because of a lack of safety data. OBJECTIVE The objective of this preliminary study was to assess whether Twitter data could be used to identify a cohort for epidemiologic studies of COVID-19 vaccination in pregnancy. Specifically, we examined whether it is possible to identify users who have reported (1) that they received COVID-19 vaccination during pregnancy or the periconception period, and (2) their pregnancy outcomes. METHODS We developed regular expressions to search for reports of COVID-19 vaccination in a large collection of tweets posted through the beginning of July 2021 by users who have announced their pregnancy on Twitter. To help determine if users were vaccinated during pregnancy, we drew upon a natural language processing (NLP) tool that estimates the timeframe of the prenatal period. For users who posted tweets with a timestamp indicating they were vaccinated during pregnancy, we drew upon additional NLP tools to help identify tweets that reported their pregnancy outcomes. RESULTS We manually verified the content of tweets detected automatically, identifying 150 users who reported on Twitter that they received at least one dose of COVID-19 vaccination during pregnancy or the periconception period. We manually verified at least one reported outcome for 45 of the 60 (75%) completed pregnancies. CONCLUSIONS Given the limited availability of data on COVID-19 vaccine safety in pregnancy, Twitter can be a complementary resource for potentially increasing the acceptance of COVID-19 vaccination in pregnant populations. The results of this preliminary study justify the development of scalable methods to identify a larger cohort for epidemiologic studies.

Toward Using Twitter Data to Monitor Covid-19 Vaccine Safety in Pregnancy

Background: Coronavirus Disease 2019 (Covid-19) during pregnancy is associated with an increased risk of maternal death, intensive care unit (ICU) admission, and preterm birth; however, many people who are pregnant refuse to receive Covid-19 vaccination because of a lack of safety data. Objective: The objective of this preliminary study was to assess whether we could identify (1) users who have reported on Twitter that they received Covid-19 vaccination during pregnancy or the periconception period, and (2) reports of their pregnancy outcomes. Methods: We searched for reports of Covid-19 vaccination in a large collection of tweets posted by users who have announced their pregnancy on Twitter. To help determine if users were vaccinated during pregnancy, we drew upon a natural language processing (NLP) tool that estimates the timeframe of the prenatal period. For users who posted tweets with a timestamp indicating they were vaccinated during pregnancy, we drew upon additional NLP tools to help identify tweets that report their pregnancy outcomes. Results: Upon manually verifying the content of tweets detected automatically, we identified 150 users who reported on Twitter that they received at least one dose of Covid-19 vaccination during pregnancy or the periconception period. Among the 60 completed pregnancies, we manually verified at least one reported outcome for 45 (75%) of them. Conclusions: Given the limited availability of data on Covid-19 vaccine safety in pregnancy, Twitter can be a complementary resource for potentially increasing the acceptance of Covid-19 vaccination in pregnant populations. Directions for future work include developing machine learning algorithms to detect a larger number of users for observational studies.

APPLYING NANOPARTICLES FOR TREATING GIARDIA INFECTION: A SYSTEMATIC REVIEW

At present, chemotherapy with some drugs such as nitroimidazoes derivatives is the preferred treatment for giardiasis. However, these agents are associated with adverse side effects ranging from nausea to possible genotoxicity. The present investigation was designed to systematically review the in vitro, in vivo, and clinical studies about the efficacy of nanoparticles against giardiasis. The study was carried out based on the 06-PRISMA guideline and registered in the CAMARADES-NC3Rs Preclinical Systematic Review and Meta-analysis Facility (SyRF) database. The search was performed in five English databases, including Scopus, PubMed, Web of Science, EMBASE, and Google Scholar, without time limitation for publications around the world about anti-Giardia effects of all organic and inorganic nanoparticles without date limitation in order to identify all the published articles. The searched words and terms were “Giardiasis”, “Giardia lamblia”, “Giardia intestinalis”, “Giardia duodenalis”, “nanoparticles”, “nanomedicine”, “in vitro”, in vivo”, and “clinical trial”. Out of 312 papers, 10 papers, including 4 in vitro (40.0%), 5 in vivo (50.0%), and 1 in vitro/in vivo (10.0%) up to 2021 met the inclusion criteria for discussion in this systematic review. The most common type of nanoparticles was metal nanoparticles (5 studies, 50.0%) such as silver, gold, etc., followed by organic nanoparticles such as chitosan nanoparticles (4 studies, 40.0%). The results of this review study showed the high efficacy of a wide range of organic and non-organic NPs against giardiasis, indicating that nanoparticles could be considered as an alternative and complementary resource for treating giardiasis, since they have no significant toxicity. However, more studies are required to elucidate this conclusion, especially in clinical systems.

Chiropractic students’ experiences on the use of virtual radiography simulation: a pilot observational study

Background Virtual radiography provides students with an opportunity to practise their clinical skills in patient positioning and evaluating radiographic images. The purpose of this pilot study was to introduce Projection VR™, a software radiography simulation program, into a student chiropractic program and evaluate its potential application as a teaching and learning tool. Methods Undergraduate chiropractic students, enrolled in a radiographic course (unit within the chiropractic program), were invited to attend a scheduled laboratory where they were introduced to, and undertook purposefully designed activities using the radiography simulation. At the end of this activity, students were asked to complete an online survey (see Virtual Radiography Survey) to describe their experiences of the educational value of the software program. Descriptive statistics were used to evaluate outcomes. Content analysis was performed for free-text comments provided by respondents with key themes provided by the predetermined quantitative categories of the questionnaire. Results Responses were received from 44 out of the 47 students who attended the scheduled laboratory (response rate 92%). Overall students were positive about this simulation identifying that it was easy to use (95%) and that they could control the equipment as needed (95%). The main reported benefits included students being enabled to repeat tasks until they were satisfied with the results (98%) and being able to quickly assess images and determine if changes needed to be made (98%). Participants reported improvement in their understanding of the effect of exposure factors on patient radiation dose (93%) as well as their technical image evaluation (84%) and problem-solving skills (80%). Conclusions The results of this study suggest that virtual radiography is a valuable complementary resource in providing chiropractic students with radiographic knowledge and skills.

MtExpress, a Comprehensive and Curated RNAseq-based Gene Expression Atlas for the Model Legume Medicago truncatula

Although RNA sequencing has been becoming the main transcriptomic approach in the model legume Medicago truncatula, there is currently no genome-wide gene expression atlas covering the whole set of RNAseq data published for this species. Nowadays, such tool is highly valuable to provide a global view of gene expression in a wide range of conditions and tissues/organs. Here, we present MtExpress, a gene expression atlas that compiles an exhaustive set of published M. truncatula RNAseq data (https://medicago.toulouse.inrae.fr/MtExpress). MtExpress makes use of recent releases of M. truncatula genome sequence and annotation, as well as up-to-date tools to perform mapping, quality control, statistical analysis and normalization of RNAseq data. MtExpress combines semi-automated pipelines with manual re-labelling and organization of samples, to produce an attractive and user-friendly interface, fully integrated with other available Medicago genomic resources. Importantly, MtExpress is highly flexible, in terms of both queries, e.g. allowing searches with gene names and orthologous gene IDs from Arabidopsis and other legume species, and outputs, to customize visualization and redirect gene study to relevant Medicago webservers. Thanks to its semi-automated pipeline, MtExpress will be frequently updated to follow the rapid pace of M. truncatula RNAseq data publications, as well as the constant improvement of genome annotation. MtExpress also hosts legacy GeneChip expression data originally stored in the Medicago Gene Expression Atlas (MtGEA), as a very valuable and complementary resource.