The clinical features of the piriformis syndrome: a systematic review

Piriformis syndrome, sciatica caused by compression of the sciatic nerve by the piriformis muscle, has been described for over 70 years; yet, it remains controversial. The literature consists mainly of case series and narrative reviews. The objectives of the study were: first, to make the best use of existing evidence to estimate the frequencies of clinical features in patients reported to have PS; second, to identify future research questions. A systematic review was conducted of any study type that reported extractable data relevant to diagnosis. The search included all studies up to 1 March 2008 in four databases: AMED, CINAHL, Embase and Medline. Screening, data extraction and analysis were all performed independently by two reviewers. A total of 55 studies were included: 51 individual and 3 aggregated data studies, and 1 combined study. The most common features found were: buttock pain, external tenderness over the greater sciatic notch, aggravation of the pain through sitting and augmentation of the pain with manoeuvres that increase piriformis muscle tension. Future research could start with comparing the frequencies of these features in sciatica patients with and without disc herniation or spinal stenosis

Chronic non-specific low back pain - sub-groups or a single mechanism?

Copyright 2008 Wand and O'Connell; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Background: Low back pain is a substantial health problem and has subsequently attracted a considerable amount of research. Clinical trials evaluating the efficacy of a variety of interventions for chronic non-specific low back pain indicate limited effectiveness for most commonly applied interventions and approaches. Discussion: Many clinicians challenge the results of clinical trials as they feel that this lack of effectiveness is at odds with their clinical experience of managing patients with back pain. A common explanation for this discrepancy is the perceived heterogeneity of patients with chronic non-specific low back pain. It is felt that the effects of treatment may be diluted by the application of a single intervention to a complex, heterogeneous group with diverse treatment needs. This argument presupposes that current treatment is effective when applied to the correct patient. An alternative perspective is that the clinical trials are correct and current treatments have limited efficacy. Preoccupation with sub-grouping may stifle engagement with this view and it is important that the sub-grouping paradigm is closely examined. This paper argues that there are numerous problems with the sub-grouping approach and that it may not be an important reason for the disappointing results of clinical trials. We propose instead that current treatment may be ineffective because it has been misdirected. Recent evidence that demonstrates changes within the brain in chronic low back pain sufferers raises the possibility that persistent back pain may be a problem of cortical reorganisation and degeneration. This perspective offers interesting insights into the chronic low back pain experience and suggests alternative models of intervention. Summary: The disappointing results of clinical research are commonly explained by the failure of researchers to adequately attend to sub-grouping of the chronic non-specific low back pain population. Alternatively, current approaches may be ineffective and clinicians and researchers may need to radically rethink the nature of the problem and how it should best be managed

Features of mammalian microRNA promoters emerge from polymerase II chromatin immunoprecipitation data

Background: MicroRNAs (miRNAs) are short, non-coding RNA regulators of protein coding genes. miRNAs play a very important role in diverse biological processes and various diseases. Many algorithms are able to predict miRNA genes and their targets, but their transcription regulation is still under investigation. It is generally believed that intragenic miRNAs (located in introns or exons of protein coding genes) are co-transcribed with their host genes and most intergenic miRNAs transcribed from their own RNA polymerase II (Pol II) promoter. However, the length of the primary transcripts and promoter organization is currently unknown. Methodology: We performed Pol II chromatin immunoprecipitation (ChIP)-chip using a custom array surrounding regions of known miRNA genes. To identify the true core transcription start sites of the miRNA genes we developed a new tool (CPPP). We showed that miRNA genes can be transcribed from promoters located several kilobases away and that their promoters share the same general features as those of protein coding genes. Finally, we found evidence that as many as 26% of the intragenic miRNAs may be transcribed from their own unique promoters. Conclusion: miRNA promoters have similar features to those of protein coding genes, but miRNA transcript organization is more complex. © 2009 Corcoran et al

Distinct Mechanisms for Induction and Tolerance Regulate the Immediate Early Genes Encoding Interleukin 1β and Tumor Necrosis Factor α

Interleukin-1β and Tumor Necrosis Factor α play related, but distinct, roles in immunity and disease. Our study revealed major mechanistic distinctions in the Toll-like receptor (TLR) signaling-dependent induction for the rapidly expressed genes (IL1B and TNF) coding for these two cytokines. Prior to induction, TNF exhibited pre-bound TATA Binding Protein (TBP) and paused RNA Polymerase II (Pol II), hallmarks of poised immediate-early (IE) genes. In contrast, unstimulated IL1B displayed very low levels of both TBP and paused Pol II, requiring the lineage-specific Spi-1/PU.1 (Spi1) transcription factor as an anchor for induction-dependent interaction with two TLR-activated transcription factors, C/EBPβ and NF-κB. Activation and DNA binding of these two pre-expressed factors resulted in de novo recruitment of TBP and Pol II to IL1B in concert with a permissive state for elongation mediated by the recruitment of elongation factor P-TEFb. This Spi1-dependent mechanism for IL1B transcription, which is unique for a rapidly-induced/poised IE gene, was more dependent upon P-TEFb than was the case for the TNF gene. Furthermore, the dependence on phosphoinositide 3-kinase for P-TEFb recruitment to IL1B paralleled a greater sensitivity to the metabolic state of the cell and a lower sensitivity to the phenomenon of endotoxin tolerance than was evident for TNF. Such differences in induction mechanisms argue against the prevailing paradigm that all IE genes possess paused Pol II and may further delineate the specific roles played by each of these rapidly expressed immune modulators. © 2013 Adamik et al

Atmospheric Evolution

Earth's atmosphere has evolved as volatile species cycle between the atmosphere, ocean, biomass and the solid Earth. The geochemical, biological and astrophysical processes that control atmospheric evolution are reviewed from an "Earth Systems" perspective, with a view not only to understanding the history of Earth, but also to generalizing to other solar system planets and exoplanets.Comment: 34 pages, 3 figures, 2 tables. Accepted as a chapter in "Encyclopaedia of Geochemistry", Editor Bill White, Springer-Nature, 201

Seasonal and Spatial Variation in the Location and Reactivity of a Nitrate‐Contaminated Groundwater Discharge Zone in a Lakebed

Groundwater discharge delivering anthropogenic N from surrounding watersheds can impact lake nutrient budgets. However, upgradient groundwater processes and changing dynamics in N biogeochemistry at the groundwater‐lake interface are complex. In this study, seasonal water‐level variations in a groundwater flow‐through lake altered discharge patterns of a wastewater‐derived groundwater contaminant plume, thereby affecting biogeochemical processes controlling N transport. Pore water collected 15 cm under the lakebed along transects perpendicular to shore varied from oxic to anoxic with increasing nitrate concentrations (10–75 μM) and corresponding gradients in nitrite and nitrous oxide. Pore water depth profiles of nitrate concentrations and stable isotopic compositions largely reflected upgradient groundwater N sources and N cycle processes, with minor additional nitrate reduction in the near‐surface lakebed sediments. Potential denitrification rates determined in laboratory microcosms were 10–100 times higher in near‐surface sediments (0–5 cm) than in deeper sediments (5–30 cm) and were correlated with sediment carbon content and abundance of denitrification genes (nirS, nosZI, and nosZII). Potential anammox‐driven N2 production was detectable in deeper anoxic sediments. Injection of bromide and nitrite in the lake sediments showed that the highest net nitrite consumption rates were within the top 10 cm. However, short transit times owing to rapid upward pore water velocities (4–5 cm hr−1) limited removal of the contaminant nitrate transiting through the sediments. Results demonstrate that local hydrologic and biogeochemical processes at the point of discharge affect the distribution and discharge rate of N through lakebed sediments, but processes in the upgradient groundwater can be more important for affecting N speciation and concentration

Active learning and optimal climate policy

This paper develops a climate-economy model with uncertainty, irreversibility, and active learning. Whereas previous papers assume learning from one observation per period, or experiment with control variables to gain additional information, this paper considers active learning from investment in monitoring, specifically in improved observations of the global mean temperature. We find that the decision maker invests a significant amount of money in climate research, far more than the current level, in order to increase the rate of learning about climate change. This helps the decision maker make improved decisions. The level of uncertainty decreases more rapidly in the active learning model than in the passive learning model with only temperature observations. As the uncertainty about climate change is smaller, active learning reduces the optimal carbon tax. The greater the risk, the larger is the effect of learning. The method proposed here is applicable to any dynamic control problem where the quality of monitoring is a choice variable, for instance, the precision at which we observe GDP, unemployment, or the quality of education

Mass extinctions drove increased global faunal cosmopolitanism on the supercontinent Pangaea

Mass extinctions have profoundly impacted the evolution of life through not only reducing taxonomic diversity but also reshaping ecosystems and biogeographic patterns. In particular, they are considered to have driven increased biogeographic cosmopolitanism, but quantitative tests of this hypothesis are rare and have not explicitly incorporated information on evolutionary relationships. Here we quantify faunal cosmopolitanism using a phylogenetic network approach for 891 terrestrial vertebrate species spanning the late Permian through Early Jurassic. This key interval witnessed the Permian–Triassic and Triassic–Jurassic mass extinctions, the onset of fragmentation of the supercontinent Pangaea, and the origins of dinosaurs and many modern vertebrate groups. Our results recover significant increases in global faunal cosmopolitanism following both mass extinctions, driven mainly by new, widespread taxa, leading to homogenous ‘disaster faunas’. Cosmopolitanism subsequently declines in post-recovery communities. These shared patterns in both biotic crises suggest that mass extinctions have predictable influences on animal distribution and may shed light on biodiversity loss in extant ecosystems

Methods to study splicing from high-throughput RNA Sequencing data

The development of novel high-throughput sequencing (HTS) methods for RNA (RNA-Seq) has provided a very powerful mean to study splicing under multiple conditions at unprecedented depth. However, the complexity of the information to be analyzed has turned this into a challenging task. In the last few years, a plethora of tools have been developed, allowing researchers to process RNA-Seq data to study the expression of isoforms and splicing events, and their relative changes under different conditions. We provide an overview of the methods available to study splicing from short RNA-Seq data. We group the methods according to the different questions they address: 1) Assignment of the sequencing reads to their likely gene of origin. This is addressed by methods that map reads to the genome and/or to the available gene annotations. 2) Recovering the sequence of splicing events and isoforms. This is addressed by transcript reconstruction and de novo assembly methods. 3) Quantification of events and isoforms. Either after reconstructing transcripts or using an annotation, many methods estimate the expression level or the relative usage of isoforms and/or events. 4) Providing an isoform or event view of differential splicing or expression. These include methods that compare relative event/isoform abundance or isoform expression across two or more conditions. 5) Visualizing splicing regulation. Various tools facilitate the visualization of the RNA-Seq data in the context of alternative splicing. In this review, we do not describe the specific mathematical models behind each method. Our aim is rather to provide an overview that could serve as an entry point for users who need to decide on a suitable tool for a specific analysis. We also attempt to propose a classification of the tools according to the operations they do, to facilitate the comparison and choice of methods.Comment: 31 pages, 1 figure, 9 tables. Small corrections adde

Mapping and simulating systematics due to spatially-varying observing conditions in DES Science Verification data

Spatially-varying depth and characteristics of observing conditions, such as seeing, airmass, or sky background, are major sources of systematic uncertainties in modern galaxy survey analyses, in particular in deep multi-epoch surveys. We present a framework to extract and project these sources of systematics onto the sky, and apply it to the Dark Energy Survey (DES) to map the observing conditions of the Science Verification (SV) data. The resulting distributions and maps of sources of systematics are used in several analyses of DES SV to perform detailed null tests with the data, and also to incorporate systematics in survey simulations. We illustrate the complementarity of these two approaches by comparing the SV data with the BCC-UFig, a synthetic sky catalogue generated by forward-modelling of the DES SV images. We analyse the BCC-UFig simulation to construct galaxy samples mimicking those used in SV galaxy clustering studies. We show that the spatially-varying survey depth imprinted in the observed galaxy densities and the redshift distributions of the SV data are successfully reproduced by the simulation and well-captured by the maps of observing conditions. The combined use of the maps, the SV data and the BCC-UFig simulation allows us to quantify the impact of spatial systematics on $N(z)$, the redshift distributions inferred using photometric redshifts. We conclude that spatial systematics in the SV data are mainly due to seeing fluctuations and are under control in current clustering and weak lensing analyses. The framework presented here is relevant to all multi-epoch surveys, and will be essential for exploiting future surveys such as the Large Synoptic Survey Telescope (LSST), which will require detailed null-tests and realistic end-to-end image simulations to correctly interpret the deep, high-cadence observations of the sky