Asynchronous video messaging promotes family involvement and mitigates separation in neonatal care

From BMJ via Jisc Publications RouterVoR closed-deposited 2020-09-16; AM deposited OA 2020-12-01.Objective: To evaluate the parent and staff experience of a secure video messaging service as a component of neonatal care. Design: Multicentre evaluation incorporating quantitative and qualitative items. Setting: Level II and level III UK neonatal units. Population: Families of neonatal inpatients and neonatal staff. Intervention: Use of a secure, cloud-based asynchronous video messaging service to send short messages from neonatal staff to families. Evaluation undertaken July–November 2019. Main outcome measures: Parental experience, including anxiety, involvement in care, relationships between parents and staff, and breastmilk expression. Results: In pre-implementation surveys (n=41), families reported high levels of stress and anxiety and were receptive to use of the service. In post-implementation surveys (n=42), 88% perceived a benefit of the service on their neonatal experience. Families rated a positive impact of the service on anxiety, sleep, family involvement and relationships with staff. Qualitative responses indicated enhanced emotional closeness, increased involvement in care and a positive effect on breastmilk expression. Seventy-seven post-implementation staff surveys were also collected. Staff rated the service as easy to use, with minimal impact on workload. Seventy-one percent (n=55) felt the service had a positive impact on relationships with families. Staff identified the need to manage parental expectations in relation to the number of videos that could be sent. Conclusions: Asynchronous video messaging improves parental experience, emotional closeness to their baby and builds supportive relationships between families and staff. Asynchronous video supports models of family integrated care and can mitigate family separation, which could be particularly relevant during the COVID-19 pandemic.https://doi.org/10.1136/archdischild-2020-319353106pubpub

Whole blood gene expression profiling of neonates with confirmed bacterial sepsis

peer-reviewedNeonatal infection remains a primary cause of infant morbidity and mortality worldwide and yet our understanding of how human neonates respond to infection remains incomplete. Changes in host gene expression in response to infection may occur in any part of the body, with the continuous interaction between blood and tissues allowing blood cells to act as biosensors for the changes. In this study we have used whole blood transcriptome profiling to systematically identify signatures and the pathway biology underlying the pathogenesis of neonatal infection. Blood samples were collected from neonates at the first clinical signs of suspected sepsis alongside age matched healthy control subjects. Here we report a detailed description of the study design, including clinical data collected, experimental methods used and data analysis workflows and which correspond with data in Gene Expression Omnibus (GEO) data sets (GSE25504). Our data set has allowed identification of a patient invariant 52-gene classifier that predicts bacterial infection with high accuracy and lays the foundation for advancing diagnostic, prognostic and therapeutic strategies for neonatal sepsis

Identification of Novel Mt-Guab2 Inhibitor Series Active against M. tuberculosis

Tuberculosis (TB) remains a leading cause of mortality worldwide. With the emergence of multidrug resistant TB, extensively drug resistant TB and HIV-associated TB it is imperative that new drug targets be identified. The potential of Mycobacterium tuberculosis inosine monophosphate dehydrogenase (IMPDH) as a novel drug target was explored in the present study. IMPDH exclusively catalyzes the conversion of inosine monophosphate (IMP) to xanthosine monophosphate (XMP) in the presence of the cofactor nicotinamide adenine dinucleotide (NAD+). Although the enzyme is a dehydrogenase, the enzyme does not catalyze the reverse reaction i.e. the conversion of XMP to IMP. Unlike other bacteria, M. tuberculosis harbors three IMPDH-like genes, designated as Mt-guaB1, Mt-guaB2 and Mt-guaB3 respectively. Of the three putative IMPDH's, we previously confirmed that Mt-GuaB2 was the only functional ortholog by characterizing the enzyme kinetically. Using an in silico approach based on designed scaffolds, a series of novel classes of inhibitors was identified. The inhibitors possess good activity against M. tuberculosis with MIC values in the range of 0.4 to 11.4 µg mL−1. Among the identified ligands, two inhibitors have nanomolar Kis against the Mt-GuaB2 enzyme

nSeP: immune and metabolic biomarkers for early detection of neonatal sepsis-protocol for a prospective multicohort study

Introduction Diagnosing neonatal sepsis is heavily dependent on clinical phenotyping as culture-positive body fluid has poor sensitivity, and existing blood biomarkers have poor specificity. A combination of machine learning, statistical and deep pathway biology analyses led to the identification of a tripartite panel of biologically connected immune and metabolic markers that showed greater than 99% accuracy for detecting bacterial infection with 100% sensitivity. The cohort study described here is designed as a large-scale clinical validation of this previous work. Methods and analysis This multicentre observational study will prospectively recruit a total of 1445 newborn infants (all gestations)—1084 with suspected early—or late-onset sepsis, and 361 controls—over 4 years. A small volume of whole blood will be collected from infants with suspected sepsis at the time of presentation. This sample will be used for integrated transcriptomic, lipidomic and targeted proteomics profiling. In addition, a subset of samples will be subjected to cellular phenotype and proteomic analyses. A second sample from the same patient will be collected at 24 hours, with an opportunistic sampling for stool culture. For control infants, only one set of blood and stool sample will be collected to coincide with clinical blood sampling. Along with detailed clinical information, blood and stool samples will be analysed and the information will be used to identify and validate the efficacy of immune-metabolic networks in the diagnosis of bacterial neonatal sepsis and to identify new host biomarkers for viral sepsis

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Increased Incidence of Pseudotumor Cerebri Syndrome Among Users of Tetracycline Antibiotics

Background: To determine whether the use of a tetracycline-class antibiotic is associated with an increased risk of developing pseudotumor cerebri syndrome (PTCS). Methods: We identified patients in the University of Utah Health system who were prescribed a tetracycline-class antibiotic and determined what percentage of those individuals were subsequently diagnosed with PTCS secondary to tetracycline use. We compared this calculation to the number of patients with PTCS unrelated to tetracycline use. Results: Between 2007 and 2014, a total of 960 patients in the University system between the ages of 12 and 50 were prescribed a tetracycline antibiotic. Among those, 45 were diagnosed with tetracycline-induced PTCS. We estimate the incidence of tetracycline-induced PTCS to be 63.9 per 100,000 person-years. By comparison, the incidence of idiopathic intracranial hypertension (IIH) is estimated to be less than one per 100,000 person-years (Calculated Risk Ratio = 178). Conclusions: Although a causative link between tetracycline use and pseudotumor cerebri has yet to be firmly established, our study suggests that the incidence of pseudotumor cerebri among tetracycline users is significantly higher than the incidence of IIH in the general population

Whole blood gene expression profiling of neonates with confirmed bacterial sepsis

Neonatal infection remains a primary cause of infant morbidity and mortality worldwide and yet our understanding of how human neonates respond to infection remains incomplete. Changes in host gene expression in response to infection may occur in any part of the body, with the continuous interaction between blood and tissues allowing blood cells to act as biosensors for the changes. In this study we have used whole blood transcriptome profiling to systematically identify signatures and the pathway biology underlying the pathogenesis of neonatal infection. Blood samples were collected from neonates at the first clinical signs of suspected sepsis alongside age matched healthy control subjects. Here we report a detailed description of the study design, including clinical data collected, experimental methods used and data analysis workflows and which correspond with data in Gene Expression Omnibus (GEO) data sets (GSE25504). Our data set has allowed identification of a patient invariant 52-gene classifier that predicts bacterial infection with high accuracy and lays the foundation for advancing diagnostic, prognostic and therapeutic strategies for neonatal sepsis