An ultra-deep multi-band VLA survey of the faint radio sky (COSMOS-XS): New constraints on the cosmic star formation history

We make use of ultra-deep 3 GHz Karl G. Jansky Very Large Array observations of the COSMOS field from the multi-band COSMOS-XS survey to infer radio luminosity functions (LFs) of star-forming galaxies (SFGs). Using $\sim$1300 SFGs with redshifts out to $z\sim4.6$, and fixing the faint and bright end shape of the radio LF to the local values, we find a strong redshift trend that can be fitted by pure luminosity evolution with the luminosity parameter given by $\alpha_L \propto (3.40 \pm 0.11) - (0.48 \pm 0.06)z$. We then combine the ultra-deep COSMOS-XS data-set with the shallower VLA-COSMOS $\mathrm{3\,GHz}$ large project data-set over the wider COSMOS field in order to fit for joint density+luminosity evolution, finding evidence for significant density evolution. By comparing the radio LFs to the observed far-infrared (FIR) and ultraviolet (UV) LFs, we find evidence of a significant underestimation of the UV LF by $21.6\%\, \pm \, 14.3 \, \%$ at high redshift ($3.3\,<\,z\,<\,4.6$, integrated down to $0.03\,L^{\star}_{z=3}$). We derive the cosmic star formation rate density (SFRD) by integrating the fitted radio LFs and find that the SFRD rises up to $z\,\sim\,1.8$ and then declines more rapidly than previous radio-based estimates. A direct comparison between the radio SFRD and a recent UV-based SFRD, where we integrate both LFs down to a consistent limit ($0.038\,L^{\star}_{z=3}$), reveals that the discrepancy between the radio and UV LFs translates to a significant ($\sim$1 dex) discrepancy in the derived SFRD at $z>3$, even assuming the latest dust corrections and without accounting for optically dark sources.Comment: Submitted to ApJ; 27 pages, 13 figures, 4 table

Erratum: “Milky Way red dwarfs in the Borg survey; galactic scale-height and the distribution of dwarfs stars in WFC3 imaging .

In the catalog of M-dwarfs presented in Holwerda et al. (2014, H14 hereafter), there is an issue with the conversion from celestial coordinates to Galactic ones, done with PYEPHEM a wrapper around a trusted and vetted library ephermis. Here we present the corrected coordinates (using ASTROPY) and distances based on AB magnitudes. We have amended the tables and figures accordingly. The relation between vertical scale-height (z0) and M- dwarf subtype found in H14 is no longer present. We find a scale-height of 600 pc for all types, in part due to the presence of a second Galactic structural component

Host range and symptomatology of Pepino mosaic virus strains occurring in Europe

Pepino mosaic virus (PepMV) has caused great concern in the greenhouse tomato industry after it was found causing a new disease in tomato in 1999. The objective of this paper is to investigate alternative hosts and compare important biological characteristics of the three PepMV strains occurring in Europe when tested under different environmental conditions. To this end we compared the infectivity and symptom development of three, well characterized isolates belonging to three different PepMV strains, EU-tom, Ch2 and US1, by inoculating them on tomato, possible alternative host plants in the family Solanaceae and selected test plants. The inoculation experiments were done in 10 countries from south to north in Europe. The importance of alternative hosts among the solanaceous crops and the usefulness of test plants in the biological characterization of PepMV isolates are discussed. Our data for the three strains tested at 10 different European locations with both international and local cultivars showed that eggplant is an alternative host of PepMV. Sweet pepper is not an important host of PepMV, but potato can be infected when the right isolate is matched with a specific cultivar. Nicotiana occidentalis 37B is a useful indicator plant for PepMV studies, since it reacts with a different symptomatology to each one of the PepMV strains.Ravnikar, M.; Blystad, D.; Van Der Vlugt, R.; Alfaro Fernández, AO.; Del Carmen Cordoba, M.; Bese, G.; Hristova, D.... (2015). Host range and symptomatology of Pepino mosaic virus strains occurring in Europe. European Journal of Plant Pathology. 143(1):43-56. doi:10.1007/s10658-015-0664-1S43561431Alfaro-Fernández, A., Córdoba-Sellés, M. C., Herrera-Vásquez, J. A., Cebrián, M. C., & Jordá, C. (2009). Transmission of Pepino mosaic virus by the fungal vector Olpidium virulentus. Journal of Phytopathology, 158, 217–226.Charmichael, D. J., Rey, M. E. C., Naidoo, S., Cook, G., & van Heerden, S. W. (2011). First report of Pepino mosaic virus infecting tomato in South Africa. Plant Disease, 95(6), 767.2.Córdoba, M. C., Martínez-Priego, L., & Jordá, C. (2004). New natural hosts of Pepino mosaic virus in Spain. Plant Disease, 88, 906.Córdoba-Sellés, M. C., García-Rández, A., Alfaro-Fernández, A., & Jordá-Gutiérrez, C. (2007). Seed transmission of pepino mosaic virus and efficacy of tomato seed disinfection treatments. Plant Disease, 91, 1250–1254.Efthimiou, K. E., Gatsios, A. P., Aretakis, K. C., Papayannis, L. C., & Katis, N. I. (2011). First report of Pepino mosaic virus infecting greenhouse cherry tomato in Greece. Plant Disease, 95(1), 78.2.Fakhro, A., von Bargen, S., Bandte, M., Büttner, C., Franken, P., & Schwarz, D. (2011). Susceptibility of different plant species and tomato cultivars to two isolates of Pepino mosaic virus. European Journal of Plant Pathology, 129, 579–590.Gómez, P., Sempere, R. N., Elena, S. F., & Aranda, M. A. (2009). Mixed infections of Pepino mosaic virus strains modulate the evolutionary dynamics of this emergent virus. Journal of Virology, 83, 12378–12387.Hanssen, I. M., Paeleman, A., Wittemans, L., Goen, K., Lievens, B., Bragard, C., Vanachter, A. C. R. C., & Thomma, B. P. H. J. (2008). Genetic characterization of Pepino mosaic virus isolates from Belgian greenhouse tomatoes reveals genetic recombination. European Journal of Plant Pathology, 121, 131–146.Hanssen, I. M., Paeleman, A., Vandewoestijne, E., Van Bergen, L., Bragard, C., Lievens, B., Vanachter, A. C. R. C., & Thomma, B. P. H. J. (2009). Pepino mosaic virus isolates and differential symptomatology in tomato. Plant Pathology, 58, 450–460.Hanssen, I. M., Mumford, R., Blystad, D.-G., Cortez, I., Hasiów-Jaroszewska, B., Hristova, D., Pagán, I., Pereira, A.-M., Peters, J., Pospieszny, H., Ravnikar, M., Stijger, I., Tomassoli, L., Varveri, C., van der Vlugt, R., & Nielsen, S. L. (2010). Seed transmission of Pepino mosaic virus in tomato. European Journal of Plant Pathology, 126, 145–152.Hasiów-Jaroszewska, B., Borodynko, N., Jackowiak, P., Figlerowicz, M., & Pospieszny, H. (2010a). Pepino mosaic virus – a pathogen of tomato crops in Poland: biology, evolution and diagnostics. Journal of Plant Protection Research, 50, 470–476.Hasiów-Jaroszewska, B., Jackowiak, P., Borodynko, N., Figlerowicz, M., & Pospieszny, H. (2010b). Quasispecies nature of Pepino mosaic virus and its evolutionary dynamics. Virus Genes, 41, 260–267.Jeffries, C. J. (1998). FAO/IPGRI technical guidelines for the safe movement of germplasm no. 19. Potato. Food and agriculture organization of the United Nations, Rome/International Plant Genetic Resources Institute, Rome pp 177Jones, R. A. C., Koenig, R., & Lesemann, D. E. (1980). Pepino mosaic virus, a new potexvirus from pepino (Solanum muricatum). Annals of Applied Biology, 94, 61–68.Jordá, C., Lázaro Pérez, A., & Martínez Culebras, P. (2001). First report of Pepino mosaic virus on natural hosts. Plant Disease, 85, 1292.King, A. M. Q., Adams, M. J., Carstens, E. B., Lefkowitz, E. J., (eds). (2012). potexvirus, pp 912–915, in virus taxonomy, classification and nomenclature of viruses; ninth report of the international committee on taxonomy of viruses (p 1327) London, UK: Elsevier Academic PressLing, K.-S., & Zhang, W. (2011). First report of Pepino mosaic virus infecting tomato in Mexico. Plant Disease, 95(8), 1035.Martin, J., & Mousserion, C. (2002). Potato varieties which are sensitive to the tomato strains of Pepino mosaic virus (PepMV). Phytoma Défence Végétaux, 552, 26–28.Mehle, N., Gutierrez-Aguirre, I., Prezelj, N., Delić, D., Vidic, U., & Ravnikar, M. (2014). Survival and transmission of potato virus Y, pepino mosaic virus, and potato spindle tuber viroid in water. Applied and Environmental Microbiology, 80(4), 1455–1462.Moreno-Pérez, M. G., Pagán, I., Aragón-Caballero, L., Cáceres, F., Aurora Fraile, A., & García-Arenal, F. (2014). Ecological and genetic determinants of Pepino mosaic virus emergence. Journal of Virology, 88(6), 3359–3368.Noël, P., Hance, T., & Bragard, C. (2014). Transmission of the pepino mosaic virus by whitefly. European Journal of Plant Pathology, 138, 23–27.Pagan, I., Cordoba-Selles, M. D., Martinez-Priego, L., Fraile, A., Malpica, J. M., Jorda, C., & Garcia-Arenal, F. (2006). Genetic structure of the population of pepino mosaic virus infecting tomato crops in Spain. Phytopathology, 96, 274–279.Papayiannis, L. C., Kokkinos, C. D., & Alfaro-Fernández, A. (2012). Detection, characterization and host range studies of Pepino mosaic virus in Cyprus. European Journal of Plant Pathology, 132, 1–7.Pospieszny, H., Haslow, B., & Borodynko, N. (2008). Characterization of two Polish isolates of Pepino mosaic virus. European Journal of Plant Pathology, 122, 443–445.Salomone, A., & Roggero, P. (2002). Host range, seed transmission and detection by ELISA and lateral flow of an Italian isolate of Pepino mosaic virus. Journal of Plant Pathology, 84, 65–68.Samson, R. G., Allen, T. C., & Whitworth, J. L. (1993). Evaluation of direct tissue blotting to detect potato viruses. American Potato Journal, 70, 257–265.Schwarz, D., Beuch, U., Bandte, M., Fakhro, A., Büttner, C., & Obermeier, C. (2010). Spread and interaction of pepino mosaic virus (PepMV) and pythium aphanidermatum in a closed nutrient solution recirculation system: effects on tomato growth and yield. Plant Pathology, 59(3), 443–452.Shipp, J. L., Buitenhuis, R., Stobbs, L., Wang, K., Kim, W. S., & Ferguson, G. (2008). Vectoring of pepino mosaic virus by bumble-bees in tomato greenhouses. Annals of Applied Biology, 153, 149–155.Van der Vlugt, R. A. A. (2009). Pepino mosaic virus (review). Hellenic Plant Protection Journal, 2, 47–56.Van der Vlugt, R. A. A., & Stijger, C. C. M. M. (2008). Pepino mosaic virus. In B. W. J. Mahy & M. H. V. Van Regenmortel (Eds.), Encyclopedia of virology (5th ed., pp. 103–108). Wageningen: Oxford Elsevier.Van der Vlugt, R. A. A., Stijger, C. C. M. M., Verhoeven, J. T. J., & Lesemann, D.-E. (2000). First report of Pepino mosaic virus on tomato. Plant Disease, 84, 103.Van der Vlugt, R. A. A., Cuperus, C., Vink, J., Stijger, I. C. M. M., Lesemann, D.-E., Verhoeven, J. T. J., & Roenhorst, J. W. (2002). Identification and characterization of Pepino mosaic potexvirus in tomato. Bulletin EPPO/EPPO Bulletin, 32, 503–508.Verchot-Lubicz, J., Chang-Ming, Y., & Bamunusinghe, D. (2007). Molecular biology of potexviruses: recent advances. Journal of General Virology, 88(6), 1643–1655.Verhoeven, J. T. H. J., van der Vlugt, R., & Roenhorst, J. W. (2003). High similarity between tomato isolates of pepino mosaic virus suggests a common origin. European Journal of Plant Pathology, 109, 419–425.Werkman, A.W., & Sansford, C.E. (2010). Pest risk analysis for pepino mosaic virus for the EU. Deliverable Report 4.3. EU Sixth Framework project PEPEIRA. http:// www.pepeira.com .Wright, D., & Mumford, R. (1999). Pepino mosaic potexvirus (PepMV): first records in tomato in the United Kingdom. Plant disease notice (89th ed.). York, UK: Central Science Laboratory

Gene length corrected trimmed mean of M-values (GeTMM) processing of RNA-seq data performs similarly in intersample analyses while improving intrasample comparisons

Background: Current normalization methods for RNA-sequencing data allow either for intersample comparison to identify differentially expressed (DE) genes or for intrasample comparison for the discovery and validation of gene signatures. Most studies on optimization of normalization methods typically use simulated data to validate methodologies. We describe a new method, GeTMM, which allows for both inter- and intrasample analyses with the same normalized data set. We used actual (i.e. not simulated) RNA-seq data from 263 colon cancers (no biological replicates) and used the same read count data to compare GeTMM with the most commonly used normalization methods (i.e. TMM (used by edgeR), RLE (used by DESeq2) and TPM) with respect to distributions, effect of RNA quality, subtype-classification, recurrence score, recall of DE genes and correlation to RT-qPCR data. Results: We observed a clear benefit for GeTMM and TPM with regard to intrasample comparison while GeTMM performed similar to TMM and RLE normalized data in intersample comparisons. Regarding DE genes, recall was found comparable among the normalization methods, while GeTMM showed the lowest number of false-positive DE genes. Remarkably, we observed limited detrimental effects in samples with low RNA quality. Conclusions: We show that GeTMM outperforms established methods with regard to intrasample comparison while performing equivalent with regard to intersample normalization using the same normalized data. These combined properties enhance the general usefulness of RNA-seq but also the comparability to the many array-based gene expression data in the public domain

Muscle weakness and lack of reflex gain adaptation predominate during post-stroke posture control of the wrist

Instead of hyper-reflexia as sole paradigm, post-stroke movement disorders are currently considered the result of a complex interplay between neuronal and muscular properties, modified by level of activity. We used a closed loop system identification technique to quantify individual contributors to wrist joint stiffness during an active posture task. Continuous random torque perturbations applied to the wrist joint by a haptic manipulator had to be resisted maximally. Reflex provoking conditions were applied i.e. additional viscous loads and reduced perturbation signal bandwidth. Linear system identification and neuromuscular modeling were used to separate joint stiffness into the intrinsic resistance of the muscles including co-contraction and the reflex mediated contribution. Compared to an age and sex matched control group, patients showed an overall 50% drop in intrinsic elasticity while their reflexive contribution did not respond to provoking conditions. Patients showed an increased mechanical stability compared to control subjects. Post stroke, we found active posture tasking to be dominated by: 1) muscle weakness and 2) lack of reflex adaptation. This adds to existing doubts on reflex blocking therapy as the sole paradigm to improve active task performance and draws attention to muscle strength and power recovery and the role of the inability to modulate reflexes in post stroke movement disorders.Mechanical, Maritime and Materials Engineerin

A rigorous model of reflex function indicates that position and force feedback are flexibly tuned to position and force tasks

This study aims to quantify the separate contributions of muscle force feedback, muscle spindle activity and co-contraction to the performance of voluntary tasks (“reduce the influence of perturbations on maintained force or position”). Most human motion control studies either isolate only one contributor, or assume that relevant reflexive feedback pathways during voluntary disturbance rejection tasks originate mainly from the muscle spindle. Human ankle-control experiments were performed, using three task instructions and three perturbation characteristics to evoke a wide range of responses to force perturbations. During position tasks, subjects (n = 10) resisted the perturbations, becoming more stiff than when being relaxed (i.e., the relax task). During force tasks, subjects were instructed to minimize force changes and actively gave way to imposed forces, thus becoming more compliant than during relax tasks. Subsequently, linear physiological models were fitted to the experimental data. Inhibitory, as well as excitatory force feedback, was needed to account for the full range of measured experimental behaviors. In conclusion, force feedback plays an important role in the studied motion control tasks (excitatory during position tasks and inhibitory during force tasks), implying that spindle-mediated feedback is not the only significant adaptive system that contributes to the maintenance of posture or force

Patient-reported burden of intensified surveillance and surgery in high-risk individuals under pancreatic cancer surveillance

In high-risk individuals participating in a pancreatic cancer surveillance program, worrisome features warrant for intensified surveillance or, occasionally, surgery. Our objectives were to determine the patient-reported burden of intensified surveillance and/or surgery, and to assess post-operative quality of life and opinion of surgery. Participants in our pancreatic cancer surveillance program completed questionnaires including the Cancer Worry Scale (CWS) and the Hospital Anxiety and Depression Scale (HADS). For individuals who underwent intensified surveillance, questionnaires before, during, and ≥ 3 weeks after were analyzed. In addition, subjects who underwent intensified surveillance in the past 3 years or underwent surgery at any time, were invited for an interview, that included the Short-Form 12 (SF-12). A total of 31 high-risk individuals were studied. During the intensified surveillance period, median CWS scores were higher (14, IQR 7), as compared to before (12, IQR 9, P = 0.007) and after (11, IQR 7, P = 0.014), but eventually returned back to baseline (P = 0.823). Median HADS scores were low: 5 (IQR 6) for anxiety and 3 (IQR 5) for depression, and they were unaff

Confirmation of a metastasis-specific microRNA signature in primary colon cancer

The identification of patients with high-risk stage II colon cancer who may benefit from adjuvant therapy may allow the clinical approach to be tailored for these patients based on an understanding of tumour biology. MicroRNAs have been proposed as markers of the prognosis or treatment response in colorectal cancer. Recently, a 2-microRNA signature (l et-7i and miR-10b) was proposed to identify colorectal cancer patients at risk of developing distant metastasis. We assessed the prognostic value of this signature and additional candidate microRNAs in an independent, clinically well-defined, prospectively collected cohort of primary colon cancer patients including stage I-II colon cancer without and stage III colon cancer with adjuvant treatment. The 2-microRNA signature specifically predicted hepatic recurrence in the stage I-II group, but not the overall ability to develop distant metastasis. The addition of miR-30b to the 2-microRNA signature allowed the prediction of both distant metastasis and hepatic recurrence in patients with stage I-II colon cancer who did not receive adjuvant chemotherapy. Available gene expression data allowed us to associate m iR-30b expression with axon guidance and l et-7i expression with cell adhesion, migration, and motility