Exercise and manual physiotherapy arthritis research trial (EMPART): a multicentre randomised controlled trial

BACKGROUND: Osteoarthritis (OA) of the hip is a major cause of functional disability and reduced quality of life. Management options aim to reduce pain and improve or maintain physical functioning. Current evidence indicates that therapeutic exercise has a beneficial but short-term effect on pain and disability, with poor long-term benefit. The optimal content, duration and type of exercise are yet to be ascertained. There has been little scientific investigation into the effectiveness of manual therapy in hip OA. Only one randomized controlled trial (RCT) found greater improvements in patient-perceived improvement and physical function with manual therapy, compared to exercise therapy. METHODS AND DESIGN: An assessor-blind multicentre RCT will be undertaken to compare the effect of a combination of manual therapy and exercise therapy, exercise therapy only, and a waiting-list control on physical function in hip OA. One hundred and fifty people with a diagnosis of hip OA will be recruited and randomly allocated to one of 3 groups: exercise therapy, exercise therapy with manual therapy and a waiting-list control. Subjects in the intervention groups will attend physiotherapy for 6-8 sessions over 8 weeks. Those in the control group will remain on the waiting list until after this time and will then be re-randomised to one of the two intervention groups. Outcome measures will include physical function (WOMAC), pain severity (numerical rating scale), patient perceived change (7-point Likert scale), quality of life (SF-36), mood (hospital anxiety and depression scale), patient satisfaction, physical activity (IPAQ) and physical measures of range of motion, 50-foot walk and repeated sit-to stand tests. DISCUSSION: This RCT will compare the effectiveness of the addition of manual therapy to exercise therapy to exercise therapy only and a waiting-list control in hip OA. A high quality methodology will be used in keeping with CONSORT guidelines. The results will contribute to the evidence base regarding the clinical efficacy for physiotherapy interventions in hip OA

An 18S rRNA Workflow for Characterizing Protists in Sewage, with a Focus on Zoonotic Trichomonads

Microbial eukaryotes (protists) are important components of terrestrial and aquatic environments, as well as animal and human microbiomes. Their relationships with metazoa range from mutualistic to parasitic and zoonotic (i.e., transmissible between humans and animals). Despite their ecological importance, our knowledge of protists in urban environments lags behind that of bacteria, largely due to a lack of experimentally validated high-throughput protocols that produce accurate estimates of protist diversity while minimizing non-protist DNA representation. We optimized protocols for detecting zoonotic protists in raw sewage samples, with a focus on trichomonad taxa. First, we investigated the utility of two commonly used variable regions of the 18S rRNA marker gene, V4 and V9, by amplifying and Sanger sequencing 23 different eukaryotic species, including 16 protist species such as Cryptosporidium parvum, Giardia intestinalis, Toxoplasma gondii, and species of trichomonad. Next, we optimized wet-lab methods for sample processing and Illumina sequencing of both regions from raw sewage collected from a private apartment building in New York City. Our results show that both regions are effective at identifying several zoonotic protists that may be present in sewage. A combination of small extractions (1 mL volumes) performed on the same day as sample collection, and the incorporation of a vertebrate blocking primer, is ideal to detect protist taxa of interest and combat the effects of metazoan DNA. We expect that the robust, standardized methods presented in our workflow will be applicable to investigations of protists in other environmental samples, and will help facilitate large-scale investigations of protistan diversity

A framework for identifying and characterizing protists in sewage, with a focus on zoonotic trichomonads

<div>This fileset contains QIIME mapping files and outputs used to carry out the analysis in the manuscript entitled <b>"An 18S rRNA workflow for characterizing protists in sewage, with a focus on zoonotic trichomonads" </b>(Maritz, <i>et. al</i>, 2017, https://doi.org/10.1007/s00248-017-0996-9 )</div><div><br></div>Raw sewage samples from a private apartment building in New York City were subjected to environmental marker gene sequencing for the 18S rRNA gene (targeting eukaryotes)

Data from: Temporal transcriptional logic of dynamic regulatory networks underlying nitrogen signaling and use in plants

This study exploits time, the relatively unexplored fourth dimension of gene regulatory networks (GRNs), to learn the temporal transcriptional logic underlying dynamic nitrogen (N) signaling in plants. Our “just-in-time” analysis of time-series transcriptome data uncovered a temporal cascade of cis elements underlying dynamic N signaling. To infer transcription factor (TF)-target edges in a GRN, we applied a time-based machine learning method to 2,174 dynamic N-responsive genes. We experimentally determined a network precision cutoff, using TF-regulated genome-wide targets of three TF hubs (CRF4, SNZ, and CDF1), used to “prune” the network to 155 TFs and 608 targets. This network precision was reconfirmed using genome-wide TF-target regulation data for four additional TFs (TGA1, HHO5/6, and PHL1) not used in network pruning. These higher-confidence edges in the GRN were further filtered by independent TF-target binding data, used to calculate a TF “N-specificity” index. This refined GRN identifies the temporal relationship of known/validated regulators of N signaling (NLP7/8, TGA1/4, NAC4, HRS1, and LBD37/38/39) and 146 additional regulators. Six TFs—CRF4, SNZ, CDF1, HHO5/6, and PHL1—validated herein regulate a significant number of genes in the dynamic N response, targeting 54% of N-uptake/assimilation pathway genes. Phenotypically, inducible overexpression of CRF4 in planta regulates genes resulting in altered biomass, root development, and 15NO3− uptake, specifically under low-N conditions. This dynamic N-signaling GRN now provides the temporal “transcriptional logic” for 155 candidate TFs to improve nitrogen use efficiency with potential agricultural applications. Broadly, these time-based approaches can uncover the temporal transcriptional logic for any biological response system in biology, agriculture, or medicine. External links: 1. DFG: http://cs.nyu.edu/~mirowski/pub/GRN_Krouk_Mirowski_GenomeBiology.zip, 2. GEO dataset: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE9750

Shoot_NxTime_genePlots

Gene expression plots for all N-responsive genes in shoots

Root_NxTime_genePlots

Gene expression plots of all N-responsive genes in Root

Plotting DEgenes

R script to create gene expression plots from the normalized counts

ShootRawCounts

Raw counts of total RNA-Seq reads aligned to each gene model in the Arabidopsis thaliana genome (TAIR10 version). These counts are from the RNA-Seq libraries constructed from shoot samples

RootRawCounts

Raw counts of total RNA-Seq reads aligned to each gene model in the Arabidopsis thaliana genome (TAIR10 version). These counts are from the RNA-Seq libraries constructed from root samples

Plot Data

Data files needed to generate the gene expression plots