Remission of severe restless legs syndrome and periodic limb movements in sleep after bilateral excision of multiple foot neuromas: a case report

<p>Abstract</p> <p>Introduction</p> <p>Restless legs syndrome is a sensorimotor neurological disorder characterized by an urge to move the legs in response to uncomfortable leg sensations. While asleep, 70 to 90 percent of patients with restless legs syndrome have periodic limb movements in sleep. Frequent periodic limb movements in sleep and related brain arousals as documented by polysomnography are associated with poorer quality of sleep and daytime fatigue. Restless legs syndrome in middle age is sometimes associated with neuropathic foot dysesthesias. The causes of restless legs syndrome and periodic limb movements in sleep are unknown, but the sensorimotor symptoms are hypothesized to originate in the central nervous system. We have previously determined that bilateral forefoot digital nerve impingement masses (neuromas) may be a cause of both neuropathic foot dysesthesias and the leg restlessness of restless legs syndrome. To the best of our knowledge, this case is the first report of bilateral foot neuromas as a cause of periodic limb movements in sleep.</p> <p>Case presentation</p> <p>A 42-year-old Caucasian woman with severe restless legs syndrome and periodic limb movements in sleep and bilateral neuropathic foot dysesthesias was diagnosed as having neuromas in the second, third, and fourth metatarsal head interspaces of both feet. The third interspace neuromas represented regrowth (or 'stump') neuromas that had developed since bilateral third interspace neuroma excision five years earlier. Because intensive conservative treatments including repeated neuroma injections and various restless legs syndrome medications had failed, radical surgery was recommended. All six neuromas were excised. Leg restlessness, foot dysesthesias and subjective sleep quality improved immediately. Assessment after 18 days showed an 84 to 100 percent reduction of visual analog scale scores for specific dysesthesias and marked reductions of pre-operative scores of the Pittsburgh sleep quality index, fatigue severity scale, and the international restless legs syndrome rating scale (36 to 4). Polysomnography six weeks post-operatively showed improved sleep efficiency, a marked increase in rapid eye movement sleep, and marked reductions in hourly rates of both periodic limb movements in sleep with arousal (135.3 to 3.3) and spontaneous arousals (17.3 to 0).</p> <p>Conclusion</p> <p>The immediate and near complete remission of symptoms, the histopathology of the excised tissues, and the marked improvement in polysomnographic parameters documented six weeks after surgery together indicate that this patient's severe restless legs syndrome and periodic limb movements in sleep was of peripheral nerve (foot neuroma) origin. Further study of foot neuromas as a source of periodic limb movements in sleep and as a cause of sleep dysfunction in patients with or without concomitant restless legs syndrome, is warranted.</p

MACSIMS : multiple alignment of complete sequences information management system

BACKGROUND: In the post-genomic era, systems-level studies are being performed that seek to explain complex biological systems by integrating diverse resources from fields such as genomics, proteomics or transcriptomics. New information management systems are now needed for the collection, validation and analysis of the vast amount of heterogeneous data available. Multiple alignments of complete sequences provide an ideal environment for the integration of this information in the context of the protein family. RESULTS: MACSIMS is a multiple alignment-based information management program that combines the advantages of both knowledge-based and ab initio sequence analysis methods. Structural and functional information is retrieved automatically from the public databases. In the multiple alignment, homologous regions are identified and the retrieved data is evaluated and propagated from known to unknown sequences with these reliable regions. In a large-scale evaluation, the specificity of the propagated sequence features is estimated to be >99%, i.e. very few false positive predictions are made. MACSIMS is then used to characterise mutations in a test set of 100 proteins that are known to be involved in human genetic diseases. The number of sequence features associated with these proteins was increased by 60%, compared to the features available in the public databases. An XML format output file allows automatic parsing of the MACSIM results, while a graphical display using the JalView program allows manual analysis. CONCLUSION: MACSIMS is a new information management system that incorporates detailed analyses of protein families at the structural, functional and evolutionary levels. MACSIMS thus provides a unique environment that facilitates knowledge extraction and the presentation of the most pertinent information to the biologist. A web server and the source code are available at

Activation of Type 1 Cannabinoid Receptor (CB1R) promotes neurogenesis in murine subventricular zone cell cultures

The endocannabinoid system has been implicated in the modulation of adult neurogenesis. Here, we describe the effect of type 1 cannabinoid receptor (CB1R) activation on self-renewal, proliferation and neuronal differentiation in mouse neonatal subventricular zone (SVZ) stem/progenitor cell cultures. Expression of CB1R was detected in SVZ-derived immature cells (Nestin-positive), neurons and astrocytes. Stimulation of the CB1R by (R)-(+)-Methanandamide (R-m-AEA) increased self-renewal of SVZ cells, as assessed by counting the number of secondary neurospheres and the number of Sox2+/+ cell pairs, an effect blocked by Notch pathway inhibition. Moreover, R-m-AEA treatment for 48 h, increased proliferation as assessed by BrdU incorporation assay, an effect mediated by activation of MAPK-ERK and AKT pathways. Surprisingly, stimulation of CB1R by R-m-AEA also promoted neuronal differentiation (without affecting glial differentiation), at 7 days, as shown by counting the number of NeuN-positive neurons in the cultures. Moreover, by monitoring intracellular calcium concentrations ([Ca2+](i)) in single cells following KCl and histamine stimuli, a method that allows the functional evaluation of neuronal differentiation, we observed an increase in neuronal-like cells. This proneurogenic effect was blocked when SVZ cells were co-incubated with R-m-AEA and the CB1R antagonist AM 251, for 7 days, thus indicating that this effect involves CB1R activation. In accordance with an effect on neuronal differentiation and maturation, R-m-AEA also increased neurite growth, as evaluated by quantifying and measuring the number of MAP2-positive processes. Taken together, these results demonstrate that CB1R activation induces proliferation, self-renewal and neuronal differentiation from mouse neonatal SVZ cell cultures.Fundacao para a Ciencia e a Tecnologia - Portugal [POCTI/SAU-NEU/68465/2006, PTDC/SAU-NEU/104415/2008, PTDC/SAU-NEU/101783/2008, POCTI/SAU-NEU/110838/2009]; Fundacao Calouste Gulbenkian [96542]; Fundacao para a Ciencia e Tecnologiainfo:eu-repo/semantics/publishedVersio

Daily Rhythms of Plasma Melatonin, but Not Plasma Leptin or Leptin mRNA, Vary between Lean, Obese and Type 2 Diabetic Men

Melatonin and leptin exhibit daily rhythms that may contribute towards changes in metabolic physiology. It remains unclear, however, whether this rhythmicity is altered in obesity or type 2 diabetes (T2DM). We tested the hypothesis that 24-hour profiles of melatonin, leptin and leptin mRNA are altered by metabolic status in laboratory conditions. Men between 45–65 years old were recruited into lean, obese-non-diabetic or obese-T2DM groups. Volunteers followed strict sleep-wake and dietary regimes for 1 week before the laboratory study. They were then maintained in controlled light-dark conditions, semi-recumbent posture and fed hourly iso-energetic drinks during wake periods. Hourly blood samples were collected for hormone analysis. Subcutaneous adipose biopsies were collected 6-hourly for gene expression analysis. Although there was no effect of subject group on the timing of dim light melatonin onset (DLMO), nocturnal plasma melatonin concentration was significantly higher in obese-non-diabetic subjects compared to weight-matched T2DM subjects (p<0.01) and lean controls (p<0.05). Two T2DM subjects failed to produce any detectable melatonin, although did exhibit plasma cortisol rhythms comparable to others in the group. Consistent with the literature, there was a significant (p<0.001) effect of subject group on absolute plasma leptin concentration and, when expressed relative to an individual’s 24-hour mean, plasma leptin showed significant (p<0.001) diurnal variation. However, there was no difference in amplitude or timing of leptin rhythms between experimental groups. There was also no significant effect of time on leptin mRNA expression. Despite an overall effect (p<0.05) of experimental group, post-hoc analysis revealed no significant pair-wise effects of group on leptin mRNA expression. Altered plasma melatonin rhythms in weight-matched T2DM and non-diabetic individuals supports a possible role of melatonin in T2DM aetiology. However, neither obesity nor T2DM changed 24-hour rhythms of plasma leptin relative to cycle mean, or expression of subcutaneous adipose leptin gene expression, compared with lean subjects

FastBLAST: Homology Relationships for Millions of Proteins

BackgroundAll-versus-all BLAST, which searches for homologous pairs of sequences in a database of proteins, is used to identify potential orthologs, to find new protein families, and to provide rapid access to these homology relationships. As DNA sequencing accelerates and data sets grow, all-versus-all BLAST has become computationally demanding.Methodology/principal findingsWe present FastBLAST, a heuristic replacement for all-versus-all BLAST that relies on alignments of proteins to known families, obtained from tools such as PSI-BLAST and HMMer. FastBLAST avoids most of the work of all-versus-all BLAST by taking advantage of these alignments and by clustering similar sequences. FastBLAST runs in two stages: the first stage identifies additional families and aligns them, and the second stage quickly identifies the homologs of a query sequence, based on the alignments of the families, before generating pairwise alignments. On 6.53 million proteins from the non-redundant Genbank database ("NR"), FastBLAST identifies new families 25 times faster than all-versus-all BLAST. Once the first stage is completed, FastBLAST identifies homologs for the average query in less than 5 seconds (8.6 times faster than BLAST) and gives nearly identical results. For hits above 70 bits, FastBLAST identifies 98% of the top 3,250 hits per query.Conclusions/significanceFastBLAST enables research groups that do not have supercomputers to analyze large protein sequence data sets. FastBLAST is open source software and is available at http://microbesonline.org/fastblast

Visualising biological data: a semantic approach to tool and database integration

<p>Abstract</p> <p>Motivation</p> <p>In the biological sciences, the need to analyse vast amounts of information has become commonplace. Such large-scale analyses often involve drawing together data from a variety of different databases, held remotely on the internet or locally on in-house servers. Supporting these tasks are <it>ad hoc </it>collections of data-manipulation tools, scripting languages and visualisation software, which are often combined in arcane ways to create cumbersome systems that have been customised for a particular purpose, and are consequently not readily adaptable to other uses. For many day-to-day bioinformatics tasks, the sizes of current databases, and the scale of the analyses necessary, now demand increasing levels of automation; nevertheless, the unique experience and intuition of human researchers is still required to interpret the end results in any meaningful biological way. Putting humans in the loop requires tools to support real-time interaction with these vast and complex data-sets. Numerous tools do exist for this purpose, but many do not have optimal interfaces, most are effectively isolated from other tools and databases owing to incompatible data formats, and many have limited real-time performance when applied to realistically large data-sets: much of the user's cognitive capacity is therefore focused on controlling the software and manipulating esoteric file formats rather than on performing the research.</p> <p>Methods</p> <p>To confront these issues, harnessing expertise in human-computer interaction (HCI), high-performance rendering and distributed systems, and guided by bioinformaticians and end-user biologists, we are building reusable software components that, together, create a toolkit that is both architecturally sound from a computing point of view, and addresses both user and developer requirements. Key to the system's usability is its direct exploitation of semantics, which, crucially, gives individual components knowledge of their own functionality and allows them to interoperate seamlessly, removing many of the existing barriers and bottlenecks from standard bioinformatics tasks.</p> <p>Results</p> <p>The toolkit, named Utopia, is freely available from <url>http://utopia.cs.man.ac.uk/</url>.</p

Considering Usual Medical Care in Clinical Trial Design

Liza Dawson and colleagues discuss the scientific and ethical issues associated with choosing clinical trial designs when there is no consensus on what constitutes usual care

EVEREST: automatic identification and classification of protein domains in all protein sequences

BACKGROUND: Proteins are comprised of one or several building blocks, known as domains. Such domains can be classified into families according to their evolutionary origin. Whereas sequencing technologies have advanced immensely in recent years, there are no matching computational methodologies for large-scale determination of protein domains and their boundaries. We provide and rigorously evaluate a novel set of domain families that is automatically generated from sequence data. Our domain family identification process, called EVEREST (EVolutionary Ensembles of REcurrent SegmenTs), begins by constructing a library of protein segments that emerge in an all vs. all pairwise sequence comparison. It then proceeds to cluster these segments into putative domain families. The selection of the best putative families is done using machine learning techniques. A statistical model is then created for each of the chosen families. This procedure is then iterated: the aforementioned statistical models are used to scan all protein sequences, to recreate a library of segments and to cluster them again. RESULTS: Processing the Swiss-Prot section of the UniProt Knoledgebase, release 7.2, EVEREST defines 20,230 domains, covering 85% of the amino acids of the Swiss-Prot database. EVEREST annotates 11,852 proteins (6% of the database) that are not annotated by Pfam A. In addition, in 43,086 proteins (20% of the database), EVEREST annotates a part of the protein that is not annotated by Pfam A. Performance tests show that EVEREST recovers 56% of Pfam A families and 63% of SCOP families with high accuracy, and suggests previously unknown domain families with at least 51% fidelity. EVEREST domains are often a combination of domains as defined by Pfam or SCOP and are frequently sub-domains of such domains. CONCLUSION: The EVEREST process and its output domain families provide an exhaustive and validated view of the protein domain world that is automatically generated from sequence data. The EVEREST library of domain families, accessible for browsing and download at [1], provides a complementary view to that provided by other existing libraries. Furthermore, since it is automatic, the EVEREST process is scalable and we will run it in the future on larger databases as well. The EVEREST source files are available for download from the EVEREST web site