Development of a Core Outcome Set and Minimum Reporting Set for intervention studies in growth restriction in the NEwbOrN (COSNEON): study protocol for a Delphi study.

BACKGROUND: Growth restriction in the newborn (GRN) can predispose to severe complications including hypoglycemia, sepsis, and necrotizing enterocolitis. Different interventions and treatments, such as feeding strategies, for GRN have specific benefits and risks. Comparing results from studies investigating intervention studies in GRN is challenging due to the use of different baseline and study characteristics and differences in reported study outcomes. In order to be able to compare study results and to allow pooling of data, uniform reporting of study characteristics (minimum reporting set [MRS]) and outcomes (core outcome set [COS]) are needed. We aim to develop both an MRS and a COS for interventional and treatment studies in GRN. METHODS/DESIGN: The MRS and COS will be developed according to Delphi methodology. First, a scoping literature search will be performed to identify study characteristics and outcomes in research focused on interventions/treatments in the GRN. An international group of stakeholders, including experts (clinicians working with GRN, and researchers who focus on GRN) and lay experts ([future] parents of babies with GRN), will be questioned to rate the importance of the study characteristics and outcomes in three rounds. After three rounds there will be two consensus meetings: a face-to-face meeting and an electronic meeting. During the consensus meetings multiple representatives of stakeholder groups will reach agreement upon which study characteristics and outcomes will be included into the COS and MRS. The second electronic consensus meeting will be used to test if an electronic meeting is as effective as a face-to-face meeting. DISCUSSION: In our opinion a COS alone is not sufficient to compare and aggregate trial data. Hence, to ensure optimum comparison we also will develop an MRS. Interventions in GRN infants are often complicated by coexisting preterm birth. A COS already has been developed for preterm birth. The majority of GRN infants are born at term, however, and we therefore chose to develop a separate COS for interventions in GRN, which can be combined (with expected overlap) in intervention studies enrolling preterm GRN babies. TRIAL REGISTRATION: Not applicable. This study is registered in the Core Outcome Measures for Effectiveness ( COMET ) database. Registered on 30 June 2017

Mycobacterium tuberculosis Responds to Chloride and pH as Synergistic Cues to the Immune Status of its Host Cell

PubMed ID: 23592993This 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

Machine learning algorithms for systematic review: reducing workload in a preclinical review of animal studies and reducing human screening error

BACKGROUND: Here, we outline a method of applying existing machine learning (ML) approaches to aid citation screening in an on-going broad and shallow systematic review of preclinical animal studies. The aim is to achieve a high-performing algorithm comparable to human screening that can reduce human resources required for carrying out this step of a systematic review. METHODS: We applied ML approaches to a broad systematic review of animal models of depression at the citation screening stage. We tested two independently developed ML approaches which used different classification models and feature sets. We recorded the performance of the ML approaches on an unseen validation set of papers using sensitivity, specificity and accuracy. We aimed to achieve 95% sensitivity and to maximise specificity. The classification model providing the most accurate predictions was applied to the remaining unseen records in the dataset and will be used in the next stage of the preclinical biomedical sciences systematic review. We used a cross-validation technique to assign ML inclusion likelihood scores to the human screened records, to identify potential errors made during the human screening process (error analysis). RESULTS: ML approaches reached 98.7% sensitivity based on learning from a training set of 5749 records, with an inclusion prevalence of 13.2%. The highest level of specificity reached was 86%. Performance was assessed on an independent validation dataset. Human errors in the training and validation sets were successfully identified using the assigned inclusion likelihood from the ML model to highlight discrepancies. Training the ML algorithm on the corrected dataset improved the specificity of the algorithm without compromising sensitivity. Error analysis correction leads to a 3% improvement in sensitivity and specificity, which increases precision and accuracy of the ML algorithm. CONCLUSIONS: This work has confirmed the performance and application of ML algorithms for screening in systematic reviews of preclinical animal studies. It has highlighted the novel use of ML algorithms to identify human error. This needs to be confirmed in other reviews with different inclusion prevalence levels, but represents a promising approach to integrating human decisions and automation in systematic review methodology

A Single Nucleotide Change Affects Fur-Dependent Regulation of sodB in H. pylori

Helicobacter pylori is a significant human pathogen that has adapted to survive the many stresses found within the gastric environment. Superoxide Dismutase (SodB) is an important factor that helps H. pylori combat oxidative stress. sodB was previously shown to be repressed by the Ferric Uptake Regulator (Fur) in the absence of iron (apo-Fur regulation) [1]. Herein, we show that apo regulation is not fully conserved among all strains of H. pylori. apo-Fur dependent changes in sodB expression are not observed under iron deplete conditions in H. pylori strains G27, HPAG1, or J99. However, Fur regulation of pfr and amiE occurs as expected. Comparative analysis of the Fur coding sequence between G27 and 26695 revealed a single amino acid difference, which was not responsible for the altered sodB regulation. Comparison of the sodB promoters from G27 and 26695 also revealed a single nucleotide difference within the predicted Fur binding site. Alteration of this nucleotide in G27 to that of 26695 restored apo-Fur dependent sodB regulation, indicating that a single base difference is at least partially responsible for the difference in sodB regulation observed among these H. pylori strains. Fur binding studies revealed that alteration of this single nucleotide in G27 increased the affinity of Fur for the sodB promoter. Additionally, the single base change in G27 enabled the sodB promoter to bind to apo-Fur with affinities similar to the 26695 sodB promoter. Taken together these data indicate that this nucleotide residue is important for direct apo-Fur binding to the sodB promoter

Значение мотивации персонала на предприятии

Основная цель – систематизировать сведения о мотивации персонала и его значении на предприятии