Unobtrusive inference of affective states in virtual rehabilitation from upper limb motions: a feasibility study

Virtual rehabilitation environments may afford greater patient personalization if they could harness the patient's affective state. Four states: anxiety, pain, engagement and tiredness (either physical or psychological), were hypothesized to be inferable from observable metrics of hand location and gripping strength -relevant for rehabilitation-. Contributions are; (a) multiresolution classifier built from Semi-Naïve Bayesian classifiers, and (b) establishing predictive relations for the considered states from the motor proxies capitalizing on the proposed classifier with recognition levels sufficient for exploitation. 3D hand locations and gripping strength streams were recorded from 5 post-stroke patients whilst undergoing motor rehabilitation therapy administered through virtual rehabilitation along 10 sessions over 4 weeks. Features from the streams characterized the motor dynamics, while spontaneous manifestations of the states were labelled from concomitant videos by experts for supervised classification. The new classifier was compared against baseline support vector machine (SVM) and random forest (RF) with all three exhibiting comparable performances. Inference of the aforementioned states departing from chosen motor surrogates appears feasible, expediting increased personalization of virtual motor neurorehabilitation therapies

Additional chromosome abnormalities in patients with acute promyelocytic leukemia treated with all-trans retinoic acid and chemotherapy

Background Acute promyelocytic leukemia is a subtype of acute myeloid leukemia characterized by the t(15;17). The incidence and prognostic significance of additional chromosomal abnormalities in acute promyelocytic leukemia is still a controversial matter. Design and Methods Based on cytogenetic data available for 495 patients with acute promyelocytic leukemia enrolled in two consecutive PETHEMA trials (LPA96 and LPA99), we analyzed the incidence, characteristics, and outcome of patients with acute promyelocytic leukemia with and without additional chromosomal abnormalities who had been treated with all-trans retinoic acid plus anthracycline monochemotherapy for induction and consolidation. Results Additional chromosomal abnormalities were observed in 140 patients (28%). Trisomy 8 was the most frequent abnormality (36%), followed by abn(7q) (5%). Patients with additional chromosomal abnormalities more frequently had coagulopathy (P=0.03), lower platelet counts (P=0.02), and higher relapse-risk scores (P=0.02) than their counterparts without additional abnormalities. No significant association with FLT3/ITD or other clinicopathological characteristics was demonstrated. Patients with and without additional chromosomal abnormalities had similar complete remission rates (90% and 91%, respectively). Univariate analysis showed that additional chromosomal abnormalities were associated with a lower relapse-free survival in the LPA99 trial (P=0.04), but not in the LPA96 trial. However, neither additional chromosomal abnormalities overall nor any specific abnormality was identified as an independent risk factor for relapse in multivariate analysis. Conclusions The lack of independent prognostic value of additional chromosomal abnormalities in acute promyelocytic leukemia does not support the use of alternative therapeutic strategies when such abnormalities are found

Whole-genome sequencing to understand the genetic architecture of common gene expression and biomarker phenotypes.

Initial results from sequencing studies suggest that there are relatively few low-frequency (<5%) variants associated with large effects on common phenotypes. We performed low-pass whole-genome sequencing in 680 individuals from the InCHIANTI study to test two primary hypotheses: (i) that sequencing would detect single low-frequency-large effect variants that explained similar amounts of phenotypic variance as single common variants, and (ii) that some common variant associations could be explained by low-frequency variants. We tested two sets of disease-related common phenotypes for which we had statistical power to detect large numbers of common variant-common phenotype associations-11 132 cis-gene expression traits in 450 individuals and 93 circulating biomarkers in all 680 individuals. From a total of 11 657 229 high-quality variants of which 6 129 221 and 5 528 008 were common and low frequency (<5%), respectively, low frequency-large effect associations comprised 7% of detectable cis-gene expression traits [89 of 1314 cis-eQTLs at P < 1 × 10(-06) (false discovery rate ∼5%)] and one of eight biomarker associations at P < 8 × 10(-10). Very few (30 of 1232; 2%) common variant associations were fully explained by low-frequency variants. Our data show that whole-genome sequencing can identify low-frequency variants undetected by genotyping based approaches when sample sizes are sufficiently large to detect substantial numbers of common variant associations, and that common variant associations are rarely explained by single low-frequency variants of large effect

Spanish guidelines for the use of targeted deep sequencing in myelodysplastic syndromes and chronic myelomonocytic leukaemia

The landscape of medical sequencing has rapidly changed with the evolution of next generation sequencing (NGS). These technologies have contributed to the molecular characterization of the myelodysplastic syndromes (MDS) and chronic myelomonocytic leukaemia (CMML), through the identification of recurrent gene mutations, which are present in >80% of patients. These mutations contribute to a better classification and risk stratification of the patients. Currently, clinical laboratories include NGS genomic analyses in their routine clinical practice, in an effort to personalize the diagnosis, prognosis and treatment of MDS and CMML. NGS technologies have reduced the cost of large-scale sequencing, but there are additional challenges involving the clinical validation of these technologies, as continuous advances are constantly being made. In this context, it is of major importance to standardize the generation, analysis, clinical interpretation and reporting of NGS data. To that end, the Spanish MDS Group (GESMD) has expanded the present set of guidelines, aiming to establish common quality standards for the adequate implementation of NGS and clinical interpretation of the results, hoping that this effort will ultimately contribute to the benefit of patients with myeloid malignancies

Second Revision of the International Staging System (R2-ISS) for Overall Survival in Multiple Myeloma: A European Myeloma Network (EMN) Report Within the HARMONY Project

PURPOSEPatients with newly diagnosed multiple myeloma (NDMM) show heterogeneous outcomes, and approximately 60% of them are at intermediate-risk according to the Revised International Staging system (R-ISS), the standard-of-care risk stratification model. Moreover, chromosome 1q gain/amplification (1q+) recently proved to be a poor prognostic factor. In this study, we revised the R-ISS by analyzing the additive value of each single risk feature, including 1q+.PATIENTS AND METHODSThe European Myeloma Network, within the HARMONY project, collected individual data from 10,843 patients with NDMM enrolled in 16 clinical trials. An additive scoring system on the basis of top features predicting progression-free survival (PFS) and overall survival (OS) was developed and validated.RESULTSIn the training set (N = 7,072), at a median follow-up of 75 months, ISS, del(17p), lactate dehydrogenase, t(4;14), and 1q+ had the highest impact on PFS and OS. These variables were all simultaneously present in 2,226 patients. A value was assigned to each risk feature according to their OS impact (ISS-III 1.5, ISS-II 1, del(17p) 1, high lactate dehydrogenase 1, and 1q+ 0.5 points). Patients were stratified into four risk groups according to the total additive score: low (Second Revision of the International Staging System [R2-ISS]-I, 19.2%, 0 points), low-intermediate (II, 30.8%, 0.5-1 points), intermediate-high (III, 41.2%, 1.5-2.5 points), high (IV, 8.8%, 3-5 points). Median OS was not reached versus 109.2 versus 68.5 versus 37.9 months, and median PFS was 68 versus 45.5 versus 30.2 versus 19.9 months, respectively. The score was validated in an independent validation set (N = 3,771, of whom 1,214 were with complete data to calculate R2-ISS) maintaining its prognostic value.CONCLUSIONThe R2-ISS is a simple prognostic staging system allowing a better stratification of patients with intermediate-risk NDMM. The additive nature of this score fosters its future implementation with new prognostic variables

Latin America: the next region for haematopoietic transplant progress

Haematopoietic cell transplant activity in the 28 countries comprising Latin America is poorly defined. We conducted a voluntary survey of members of the Latin American Bone Marrow Transplantation Group regarding transplant activity 2009–2012. Collated responses were compared with data of transplant rates from the Worldwide Network for Blood and Marrow Transplantation for other geographic regions. Several socio-economic variables were analysed to determine correlations with transplant rates. In total, 94 teams from 12 countries reported 11519 transplants including 7033 autotransplants and 4486 allotransplants. Annual activity increased from 2517 transplants in 2009 to 3263 in 2012, a 30% increase. Median transplants rate (transplant per million inhabitants) in 2012 was 64 (autotransplants, median 40; allotransplants, median 24). This rate is substantially lower than that in North America and European regions (482 and 378) but higher than that in the Eastern Mediterranean and Asia Pacific regions (30 and 45). However, the Latin America transplant rate is 5–8-fold lower than that in America and Europe, suggesting a need to increase transplant availability. Transplant team density in Latin America (teams per million population; 1.8) is 3–4-fold lower than that in North America (6.2) or Europe (7.6). Within Latin America, there is substantial diversity in transplant rates by country partially explained by diverse socio-economic variables including per capita gross national income, health expenditure and physician density. These data should help inform future health-care policy in Latin America

Discovering cis-Regulatory RNAs in Shewanella Genomes by Support Vector Machines

An increasing number of cis-regulatory RNA elements have been found to regulate gene expression post-transcriptionally in various biological processes in bacterial systems. Effective computational tools for large-scale identification of novel regulatory RNAs are strongly desired to facilitate our exploration of gene regulation mechanisms and regulatory networks. We present a new computational program named RSSVM (RNA Sampler+Support Vector Machine), which employs Support Vector Machines (SVMs) for efficient identification of functional RNA motifs from random RNA secondary structures. RSSVM uses a set of distinctive features to represent the common RNA secondary structure and structural alignment predicted by RNA Sampler, a tool for accurate common RNA secondary structure prediction, and is trained with functional RNAs from a variety of bacterial RNA motif/gene families covering a wide range of sequence identities. When tested on a large number of known and random RNA motifs, RSSVM shows a significantly higher sensitivity than other leading RNA identification programs while maintaining the same false positive rate. RSSVM performs particularly well on sets with low sequence identities. The combination of RNA Sampler and RSSVM provides a new, fast, and efficient pipeline for large-scale discovery of regulatory RNA motifs. We applied RSSVM to multiple Shewanella genomes and identified putative regulatory RNA motifs in the 5′ untranslated regions (UTRs) in S. oneidensis, an important bacterial organism with extraordinary respiratory and metal reducing abilities and great potential for bioremediation and alternative energy generation. From 1002 sets of 5′-UTRs of orthologous operons, we identified 166 putative regulatory RNA motifs, including 17 of the 19 known RNA motifs from Rfam, an additional 21 RNA motifs that are supported by literature evidence, 72 RNA motifs overlapping predicted transcription terminators or attenuators, and other candidate regulatory RNA motifs. Our study provides a list of promising novel regulatory RNA motifs potentially involved in post-transcriptional gene regulation. Combined with the previous cis-regulatory DNA motif study in S. oneidensis, this genome-wide discovery of cis-regulatory RNA motifs may offer more comprehensive views of gene regulation at a different level in this organism. The RSSVM software, predictions, and analysis results on Shewanella genomes are available at http://ural.wustl.edu/resources.html#RSSVM

Protein–Protein Interactions Essentials: Key Concepts to Building and Analyzing Interactome Networks

8 páginas, 3 figuras, 1 tabla.-- This is an open-access article distributed under the terms of the Creative Commons Attribution License.This work has been supported by funds provided by the Local Government Junta de Castilla y León (JCyL, ref. project: CSI07A09), by the Spanish Ministry of Science and Innovation (MICINN - ISCiii, ref. projects: PI061153 and PS09/00843) and by the European Commission Research Grant PSIMEx (ref. FP7-HEALTH-2007-223411).Peer Reviewe