Experimental muscle hyperalgesia modulates sensorimotor cortical excitability, which is partially altered by unaccustomed exercise

Impaired corticomotor function is reported in patients with lateral epicondylalgia, but the causal link to pain or musculotendinous overloading is unclear. In this study, sensorimotor cortical changes were investigated using a model of persistent pain combined with an overloading condition. In 24 healthy subjects, the effect of nerve growth factor (NGF)-induced pain, combined with delayed-onset muscle soreness (DOMS), was examined on pain perception, pressure pain sensitivity, maximal force, and sensorimotor cortical excitability. Two groups (NGF alone and NGF + DOMS) received injections of NGF into the extensor carpi radialis brevis (ECRB) muscle at day 0, day 2, and day 4. At day 4, the NGF + DOMS group undertook wrist eccentric exercise to induce DOMS in the ECRB muscle. Muscle soreness scores, pressure pain thresholds over the ECRB muscle, maximal grip force, transcranial magnetic stimulation mapping of the cortical ECRB muscle representation, and somatosensory-evoked potentials from radial nerve stimulation were recorded at day 0, day 4, and day 6. Compared with day 0, day 4 showed in both groups: (1) increased muscle soreness (P < 0.01); (2) reduced pressure pain thresholds (P < 0.01); (3) increased motor map volume (P < 0.01); and (4) decreased frontal N30 somatosensory-evoked potential. At day 6, compared with day 4, only the DOMS + NGF group showed: (1) increased muscle soreness score (P < 0.01); (2) decreased grip force (P < 0.01); and (3) decreased motor map volume (P < 0.05). The NGF group did not show any difference on the remaining outcomes from day 4 to day 6. These data suggest that sustained muscle pain modulates sensorimotor cortical excitability and that exercise-induced DOMS alters pain-related corticomotor adaptation

Erratum to: pegylated liposomal doxorubicin in combination with dexamethasone and bortezomib (VMD) or lenalidomide (RMD) in multiple myeloma pretreated patients

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Bortezomib with Thalidomide plus Dexamethasone Compared with Thalidomide plus Doxorubicin and Dexamethasone as Induction Therapy in Previously Untreated Multiple Myeloma Patients

We conducted a retrospective study to compare thalidomide, bortezomib and dexamethasone (VTD) with thalidomide plus doxorubicin and dexamethasone (TAD). Until now, first-line treatment with these combinations has not been reported in any comparative study. The principal objective of this study was to determine whether VTD would improve the complete response (CR) and CR plus very good partial response rates compared with TAD. Second, using additional methods, such as flow cytometric assays and polymerase chain reaction technology, we evaluated the molecular residual disease in the subgroup of patients that obtained CR. Our study shows that VTD is a superior induction regimen compared with TAD, with a higher response rate after induction, translating into greater CR plus very good partial response

parSMURF, a high-performance computing tool for the genome-wide detection of pathogenic variants.

BACKGROUND: Several prediction problems in computational biology and genomic medicine are characterized by both big data as well as a high imbalance between examples to be learned, whereby positive examples can represent a tiny minority with respect to negative examples. For instance, deleterious or pathogenic variants are overwhelmed by the sea of neutral variants in the non-coding regions of the genome: thus, the prediction of deleterious variants is a challenging, highly imbalanced classification problem, and classical prediction tools fail to detect the rare pathogenic examples among the huge amount of neutral variants or undergo severe restrictions in managing big genomic data. RESULTS: To overcome these limitations we propose parSMURF, a method that adopts a hyper-ensemble approach and oversampling and undersampling techniques to deal with imbalanced data, and parallel computational techniques to both manage big genomic data and substantially speed up the computation. The synergy between Bayesian optimization techniques and the parallel nature of parSMURF enables efficient and user-friendly automatic tuning of the hyper-parameters of the algorithm, and allows specific learning problems in genomic medicine to be easily fit. Moreover, by using MPI parallel and machine learning ensemble techniques, parSMURF can manage big data by partitioning them across the nodes of a high-performance computing cluster. Results with synthetic data and with single-nucleotide variants associated with Mendelian diseases and with genome-wide association study hits in the non-coding regions of the human genome, involhing millions of examples, show that parSMURF achieves state-of-the-art results and an 80-fold speed-up with respect to the sequential version. CONCLUSIONS: parSMURF is a parallel machine learning tool that can be trained to learn different genomic problems, and its multiple levels of parallelization and high scalability allow us to efficiently fit problems characterized by big and imbalanced genomic data. The C++ OpenMP multi-core version tailored to a single workstation and the C++ MPI/OpenMP hybrid multi-core and multi-node parSMURF version tailored to a High Performance Computing cluster are both available at https://github.com/AnacletoLAB/parSMURF

MET inhibition sensitizes rhabdomyosarcoma cells to NOTCH signaling suppression

Rhabdomyosarcoma (RMS) is a pediatric myogenic soft tissue sarcoma. The Fusion-Positive (FP) subtype expresses the chimeric protein PAX3-FOXO1 (P3F) while the Fusion-Negative (FN) is devoid of any gene translocation. FP-RMS and metastatic FN-RMS are often unresponsive to conventional therapy. Therefore, novel therapeutic approaches are needed to halt tumor progression. NOTCH signaling has oncogenic functions in RMS and its pharmacologic inhibition through gamma-secretase inhibitors blocks tumor growth in vitro and in vivo. Here, we show that NOTCH signaling blockade resulted in the up-regulation and phosphorylation of the MET oncogene in both RH30 (FP-RMS) and RD (FN-RMS) cell lines. Pharmacologic inhibition of either NOTCH or MET signaling slowed proliferation and restrained cell survival compared to control cells partly by increasing Annexin V and CASP3/7 activation. Co-treatment with NOTCH and MET inhibitors significantly amplified these effects and enhanced PARP1 cleavage in both cell lines. Moreover, it severely hampered cell migration, colony formation, and anchorage-independent growth compared to single-agent treatments in both cell lines and significantly prevented the growth of FN-RMS cells grown as spheroids. Collectively, our results unveil the overexpression of the MET oncogene by NOTCH signaling targeting in RMS cells and show that MET pathway blockade sensitizes them to NOTCH inhibition

Identification of a deep intronic mutation in the COL6A2 gene by a novel custom oligonucleotide CGH array designed to explore allelic and genetic heterogeneity in collagen VI-related myopathies

BACKGROUND: Molecular characterization of collagen-VI related myopathies currently relies on standard sequencing, which yields a detection rate approximating 75-79% in Ullrich congenital muscular dystrophy (UCMD) and 60-65% in Bethlem myopathy (BM) patients as PCR-based techniques tend to miss gross genomic rearrangements as well as copy number variations (CNVs) in both the coding sequence and intronic regions. METHODS: We have designed a custom oligonucleotide CGH array in order to investigate the presence of CNVs in the coding and non-coding regions of COL6A1, A2, A3, A5 and A6 genes and a group of genes functionally related to collagen VI. A cohort of 12 patients with UCMD/BM negative at sequencing analysis and 2 subjects carrying a single COL6 mutation whose clinical phenotype was not explicable by inheritance were selected and the occurrence of allelic and genetic heterogeneity explored. RESULTS: A deletion within intron 1A of the COL6A2 gene, occurring in compound heterozygosity with a small deletion in exon 28, previously detected by routine sequencing, was identified in a BM patient. RNA studies showed monoallelic transcription of the COL6A2 gene, thus elucidating the functional effect of the intronic deletion. No pathogenic mutations were identified in the remaining analyzed patients, either within COL6A genes, or in genes functionally related to collagen VI. CONCLUSIONS: Our custom CGH array may represent a useful complementary diagnostic tool, especially in recessive forms of the disease, when only one mutant allele is detected by standard sequencing. The intronic deletion we identified represents the first example of a pure intronic mutation in COL6A genes

A polygenic risk score for multiple myeloma risk prediction

This work was partially supported by intramural funds of the University of Pisa, DKFZ, and University Hospital of Southern Jutland, Denmark, and by a grant of the French National Cancer Institute (INCA). The authors wish to thank Dr. Dominic Edelmann (Division of Biostatistics, DKFZ) for helpful advice about data analysis.There is overwhelming epidemiologic evidence that the risk of multiple myeloma (MM) has a solid genetic background. Genome-wide association studies (GWAS) have identified 23 risk loci that contribute to the genetic susceptibility of MM, but have low individual penetrance. Combining the SNPs in a polygenic risk score (PRS) is a possible approach to improve their usefulness. Using 2361 MM cases and 1415 controls from the International Multiple Myeloma rESEarch (IMMEnSE) consortium, we computed a weighted and an unweighted PRS. We observed associations with MM risk with OR = 3.44, 95% CI 2.53-4.69, p = 3.55 x 10(-15) for the highest vs. lowest quintile of the weighted score, and OR = 3.18, 95% CI 2.1 = 34-4.33, p = 1.62 x 10(-13) for the highest vs. lowest quintile of the unweighted score. We found a convincing association of a PRS generated with 23 SNPs and risk of MM. Our work provides additional validation of previously discovered MM risk variants and of their combination into a PRS, which is a first step towards the use of genetics for risk stratification in the general population.University of Pisa, DKFZUniversity Hospital of Southern Jutland, DenmarkInstitut National du Cancer (INCA) Franc

Introducing EDEN ISS - A European project on advancing plant cultivation technologies and operations

Plant cultivation in large-scale closed environments is challenging and several key technologies necessary for space-based plant production are not yet space-qualified or remain in early stages of development. The EDEN ISS project foresees development and demonstration of higher plant cultivation technologies, suitable for future deployment on the International Space Station and from a long-term perspective, within Moon and Mars habitats. The EDEN ISS consortium will design and test essential plant cultivation technologies using an International Standard Payload Rack form factor cultivation system for potential testing on-board the International Space Station. Furthermore, a Future Exploration Greenhouse will be designed with respect to future planetary bio-regenerative life support system deployments. The technologies will be tested in a laboratory environment as well as at the highly-isolated German Antarctic Neumayer Station III. A small and mobile container-sized test facility will be built in order to provide realistic mass flow relationships. In addition to technology development and validation, food safety and plant handling procedures will be developed. This paper describes the goals and objectives of EDEN ISS and the different project phases and milestones. Furthermore, the project consortium will be introduced and the role of each partner within the project is explained