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Submillimetre galaxies reside in dark matter haloes with masses greater than 3 × 10(11) solar masses.

Nature

Amblard A, Cooray A, Serra P, Altieri B, Arumugam V, Aussel H, Blain A, Bock J, Boselli A, Buat V, Castro-Rodríguez N, Cava A, Chanial P, Chapin E, Clements DL, Conley A, Conversi L, Dowell CD, Dwek E, Eales S, Elbaz D, Farrah D, Franceschini A, Gear W, Glenn J, Griffin M, Halpern M, Hatziminaoglou E, Ibar E, Isaak K, Ivison RJ, Khostovan AA, Lagache G, Levenson L, Lu N, Madden S, Maffei B, Mainetti G, Marchetti L, Marsden G, Mitchell-Wynne K, Nguyen HT, O'Halloran B, Oliver SJ, Omont A, Page MJ, Panuzzo P, Papageorgiou A, Pearson CP, Pérez-Fournon I, Pohlen M, Rangwala N, Roseboom IG, Rowan-Robinson M, Portal MS, Schulz B, Scott D, Seymour N, Shupe DL, Smith AJ, Stevens JA, Symeonidis M, Trichas M, Tugwell K, Vaccari M, Valiante E, Valtchanov I, Vieira JD, Vigroux L, Wang L, Ward R, Wright G, Xu CK, Zemcov M.
PMID: 21326201
Nature. 2011 Feb 24;470(7335):510-2. doi: 10.1038/nature09771. Epub 2011 Feb 16.

The extragalactic background light at far-infrared wavelengths comes from optically faint, dusty, star-forming galaxies in the Universe with star formation rates of a few hundred solar masses per year. These faint, submillimetre galaxies are challenging to study individually because...

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Amblard A, Cooray A, Serra P, et al. Submillimetre galaxies reside in dark matter haloes with masses greater than 3 × 10(11) solar masses. Nature. 2011;470(7335):510-2doi: 10.1038/nature09771.
Amblard, A., Cooray, A., Serra, P., Altieri, B., Arumugam, V., Aussel, H., Blain, A., Bock, J., Boselli, A., Buat, V., Castro-Rodríguez, N., Cava, A., Chanial, P., Chapin, E., Clements, D. L., Conley, A., Conversi, L., Dowell, C. D., Dwek, E., Eales, S., Elbaz, D., Farrah, D., Franceschini, A., Gear, W., Glenn, J., Griffin, M., Halpern, M., Hatziminaoglou, E., Ibar, E., Isaak, K., Ivison, R. J., Khostovan, A. A., Lagache, G., Levenson, L., Lu, N., Madden, S., Maffei, B., Mainetti, G., Marchetti, L., Marsden, G., Mitchell-Wynne, K., Nguyen, H. T., O'Halloran, B., Oliver, S. J., Omont, A., Page, M. J., Panuzzo, P., Papageorgiou, A., Pearson, C. P., Pérez-Fournon, I., Pohlen, M., Rangwala, N., Roseboom, I. G., Rowan-Robinson, M., Portal, M. S., Schulz, B., Scott, D., Seymour, N., Shupe, D. L., Smith, A. J., Stevens, J. A., Symeonidis, M., Trichas, M., Tugwell, K., Vaccari, M., Valiante, E., Valtchanov, I., Vieira, J. D., Vigroux, L., Wang, L., Ward, R., Wright, G., Xu, C. K., & Zemcov, M. (2011). Submillimetre galaxies reside in dark matter haloes with masses greater than 3 × 10(11) solar masses. Nature, 470(7335), 510-2. https://doi.org/10.1038/nature09771
Amblard, Alexandre, et al. "Submillimetre galaxies reside in dark matter haloes with masses greater than 3 × 10(11) solar masses." Nature vol. 470,7335 (2011): 510-2. doi: https://doi.org/10.1038/nature09771
Amblard A, Cooray A, Serra P, Altieri B, Arumugam V, Aussel H, Blain A, Bock J, Boselli A, Buat V, Castro-Rodríguez N, Cava A, Chanial P, Chapin E, Clements DL, Conley A, Conversi L, Dowell CD, Dwek E, Eales S, Elbaz D, Farrah D, Franceschini A, Gear W, Glenn J, Griffin M, Halpern M, Hatziminaoglou E, Ibar E, Isaak K, Ivison RJ, Khostovan AA, Lagache G, Levenson L, Lu N, Madden S, Maffei B, Mainetti G, Marchetti L, Marsden G, Mitchell-Wynne K, Nguyen HT, O'Halloran B, Oliver SJ, Omont A, Page MJ, Panuzzo P, Papageorgiou A, Pearson CP, Pérez-Fournon I, Pohlen M, Rangwala N, Roseboom IG, Rowan-Robinson M, Portal MS, Schulz B, Scott D, Seymour N, Shupe DL, Smith AJ, Stevens JA, Symeonidis M, Trichas M, Tugwell K, Vaccari M, Valiante E, Valtchanov I, Vieira JD, Vigroux L, Wang L, Ward R, Wright G, Xu CK, Zemcov M. Submillimetre galaxies reside in dark matter haloes with masses greater than 3 × 10(11) solar masses. Nature. 2011 Feb 24;470(7335):510-2. doi: 10.1038/nature09771. Epub 2011 Feb 16. PMID: 21326201.
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Dataset exploited for the development and validation of automated cyanobacteria quantification algorithm, ACQUA.

Data in brief

Gandola E, Antonioli M, Traficante A, Franceschini S, Scardi M, Congestri R.
PMID: 27500194
Data Brief. 2016 Jun 29;8:817-23. doi: 10.1016/j.dib.2016.06.042. eCollection 2016 Sep.

The estimation and quantification of potentially toxic cyanobacteria in lakes and reservoirs are often used as a proxy of risk for water intended for human consumption and recreational activities. Here, we present data sets collected from three volcanic Italian...

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Gandola E, Antonioli M, Traficante A, et al. Dataset exploited for the development and validation of automated cyanobacteria quantification algorithm, ACQUA. Data Brief. 2016;8:817-23doi: 10.1016/j.dib.2016.06.042.
Gandola, E., Antonioli, M., Traficante, A., Franceschini, S., Scardi, M., & Congestri, R. (2016). Dataset exploited for the development and validation of automated cyanobacteria quantification algorithm, ACQUA. Data in brief, 8817-23. https://doi.org/10.1016/j.dib.2016.06.042
Gandola, Emanuele, et al. "Dataset exploited for the development and validation of automated cyanobacteria quantification algorithm, ACQUA." Data in brief vol. 8 (2016): 817-23. doi: https://doi.org/10.1016/j.dib.2016.06.042
Gandola E, Antonioli M, Traficante A, Franceschini S, Scardi M, Congestri R. Dataset exploited for the development and validation of automated cyanobacteria quantification algorithm, ACQUA. Data Brief. 2016 Jun 29;8:817-23. doi: 10.1016/j.dib.2016.06.042. eCollection 2016 Sep. PMID: 27500194; PMCID: PMC4957007.
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Myositis autoantibodies and clinical phenotypes.

Auto- immunity highlights

Ghirardello A, Borella E, Beggio M, Franceschini F, Fredi M, Doria A.
PMID: 26000158
Auto Immun Highlights. 2014 Aug 23;5(3):69-75. doi: 10.1007/s13317-014-0060-4. eCollection 2014 Dec.

Autoantibodies are powerful diagnostic tools in idiopathic inflammatory myopathies, especially for confirming the diagnosis and contributing to the definition of disease subsets. They are present in over 80 % of patients with immuno-mediated myositis and directed towards ubiquitously expressed...

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Ghirardello A, Borella E, Beggio M, et al. Myositis autoantibodies and clinical phenotypes. Auto Immun Highlights. 2014;5(3):69-75doi: 10.1007/s13317-014-0060-4.
Ghirardello, A., Borella, E., Beggio, M., Franceschini, F., Fredi, M., & Doria, A. (2014). Myositis autoantibodies and clinical phenotypes. Auto- immunity highlights, 5(3), 69-75. https://doi.org/10.1007/s13317-014-0060-4
Ghirardello, Anna, et al. "Myositis autoantibodies and clinical phenotypes." Auto- immunity highlights vol. 5,3 (2014): 69-75. doi: https://doi.org/10.1007/s13317-014-0060-4
Ghirardello A, Borella E, Beggio M, Franceschini F, Fredi M, Doria A. Myositis autoantibodies and clinical phenotypes. Auto Immun Highlights. 2014 Aug 23;5(3):69-75. doi: 10.1007/s13317-014-0060-4. eCollection 2014 Dec. PMID: 26000158; PMCID: PMC4386580.
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Tendon transfer for irreparable rotator cuff tears: indications and surgical rationale.

Muscles, ligaments and tendons journal

Merolla G, Chillemi C, Franceschini V, Cerciello S, Ippolito G, Paladini P, Porcellini G.
PMID: 25767779
Muscles Ligaments Tendons J. 2015 Feb 05;4(4):425-32. eCollection 2014.

BACKGROUND: treatment of symptomatic irreparable rotator cuff tears is extremely challenging because, at present, there are no ideal solutions to this problem. Many patients respond favorably to nonsurgical treatment. However, when conservative measures fail to improve the patient's pain...

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Merolla G, Chillemi C, Franceschini V, et al. Tendon transfer for irreparable rotator cuff tears: indications and surgical rationale. Muscles Ligaments Tendons J. 2015;4(4):425-32
Merolla, G., Chillemi, C., Franceschini, V., Cerciello, S., Ippolito, G., Paladini, P., & Porcellini, G. (2014). Tendon transfer for irreparable rotator cuff tears: indications and surgical rationale. Muscles, ligaments and tendons journal, 4(4), 425-32.
Merolla, Giovanni, et al. "Tendon transfer for irreparable rotator cuff tears: indications and surgical rationale." Muscles, ligaments and tendons journal vol. 4,4 (2014): 425-32.
Merolla G, Chillemi C, Franceschini V, Cerciello S, Ippolito G, Paladini P, Porcellini G. Tendon transfer for irreparable rotator cuff tears: indications and surgical rationale. Muscles Ligaments Tendons J. 2015 Feb 05;4(4):425-32. eCollection 2014. PMID: 25767779; PMCID: PMC4327351.
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Biosimilar Oncology Drugs in Europe: Regulatory and Pharmacovigilance Considerations.

Oncology and therapy

Francescon S, Fornasier G, Baldo P.
PMID: 28261647
Oncol Ther. 2016;4(2):173-182. doi: 10.1007/s40487-016-0028-9. Epub 2016 Aug 11.

The introduction in clinical practice of pharmaceutical products known as biosimilars, as part of a more complex series of progress in the field of biological drugs, represents an excellent therapeutic resource. A biosimilar drug is a biological/biotechnological drug that...

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Francescon S, Fornasier G, Baldo P. Biosimilar Oncology Drugs in Europe: Regulatory and Pharmacovigilance Considerations. Oncol Ther. 2016;4(2):173-182doi: 10.1007/s40487-016-0028-9.
Francescon, S., Fornasier, G., & Baldo, P. (2016). Biosimilar Oncology Drugs in Europe: Regulatory and Pharmacovigilance Considerations. Oncology and therapy, 4(2), 173-182. https://doi.org/10.1007/s40487-016-0028-9
Francescon, Sara, et al. "Biosimilar Oncology Drugs in Europe: Regulatory and Pharmacovigilance Considerations." Oncology and therapy vol. 4,2 (2016): 173-182. doi: https://doi.org/10.1007/s40487-016-0028-9
Francescon S, Fornasier G, Baldo P. Biosimilar Oncology Drugs in Europe: Regulatory and Pharmacovigilance Considerations. Oncol Ther. 2016;4(2):173-182. doi: 10.1007/s40487-016-0028-9. Epub 2016 Aug 11. PMID: 28261647; PMCID: PMC5315076.
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Joint analysis of BICEP2/keck array and Planck Data.

Physical review letters

Ade PA, Aghanim N, Ahmed Z, Aikin RW, Alexander KD, Arnaud M, Aumont J, Baccigalupi C, Banday AJ, Barkats D, Barreiro RB, Bartlett JG, Bartolo N, Battaner E, Benabed K, Benoît A, Benoit-Lévy A, Benton SJ, Bernard JP, Bersanelli M, Bielewicz P, Bischoff CA, Bock JJ, Bonaldi A, Bonavera L, Bond JR, Borrill J, Bouchet FR, Boulanger F, Brevik JA, Bucher M, Buder I, Bullock E, Burigana C, Butler RC, Buza V, Calabrese E, Cardoso JF, Catalano A, Challinor A, Chary RR, Chiang HC, Christensen PR, Colombo LP, Combet C, Connors J, Couchot F, Coulais A, Crill BP, Curto A, Cuttaia F, Danese L, Davies RD, Davis RJ, de Bernardis P, de Rosa A, de Zotti G, Delabrouille J, Delouis JM, Désert FX, Dickinson C, Diego JM, Dole H, Donzelli S, Doré O, Douspis M, Dowell CD, Duband L, Ducout A, Dunkley J, Dupac X, Dvorkin C, Efstathiou G, Elsner F, Enßlin TA, Eriksen HK, Falgarone E, Filippini JP, Finelli F, Fliescher S, Forni O, Frailis M, Fraisse AA, Franceschi E, Frejsel A, Galeotta S, Galli S, Ganga K, Ghosh T, Giard M, Gjerløw E, Golwala SR, González-Nuevo J, Górski KM, Gratton S, Gregorio A, Gruppuso A, Gudmundsson JE, Halpern M, Hansen FK, Hanson D, Harrison DL, Hasselfield M, Helou G, Henrot-Versillé S, Herranz D, Hildebrandt SR, Hilton GC, Hivon E, Hobson M, Holmes WA, Hovest W, Hristov VV, Huffenberger KM, Hui H, Hurier G, Irwin KD, Jaffe AH, Jaffe TR, Jewell J, Jones WC, Juvela M, Karakci A, Karkare KS, Kaufman JP, Keating BG, Kefeli S, Keihänen E, Kernasovskiy SA, Keskitalo R, Kisner TS, Kneissl R, Knoche J, Knox L, Kovac JM, Krachmalnicoff N, Kunz M, Kuo CL, Kurki-Suonio H, Lagache G, Lähteenmäki A, Lamarre JM, Lasenby A, Lattanzi M, Lawrence CR, Leitch EM, Leonardi R, Levrier F, Lewis A, Liguori M, Lilje PB, Linden-Vørnle M, López-Caniego M, Lubin PM, Lueker M, Macías-Pérez JF, Maffei B, Maino D, Mandolesi N, Mangilli A, Maris M, Martin PG, Martínez-González E, Masi S, Mason P, Matarrese S, Megerian KG, Meinhold PR, Melchiorri A, Mendes L, Mennella A, Migliaccio M, Mitra S, Miville-Deschênes MA, Moneti A, Montier L, Morgante G, Mortlock D, Moss A, Munshi D, Murphy JA, Naselsky P, Nati F, Natoli P, Netterfield CB, Nguyen HT, Nørgaard-Nielsen HU, Noviello F, Novikov D, Novikov I, O'Brient R, Ogburn RW, Orlando A, Pagano L, Pajot F, Paladini R, Paoletti D, Partridge B, Pasian F, Patanchon G, Pearson TJ, Perdereau O, Perotto L, Pettorino V, Piacentini F, Piat M, Pietrobon D, Plaszczynski S, Pointecouteau E, Polenta G, Ponthieu N, Pratt GW, Prunet S, Pryke C, Puget JL, Rachen JP, Reach WT, Rebolo R, Reinecke M, Remazeilles M, Renault C, Renzi A, Richter S, Ristorcelli I, Rocha G, Rossetti M, Roudier G, Rowan-Robinson M, Rubiño-Martín JA, Rusholme B, Sandri M, Santos D, Savelainen M, Savini G, Schwarz R, Scott D, Seiffert MD, Sheehy CD, Spencer LD, Staniszewski ZK, Stolyarov V, Sudiwala R, Sunyaev R, Sutton D, Suur-Uski AS, Sygnet JF, Tauber JA, Teply GP, Terenzi L, Thompson KL, Toffolatti L, Tolan JE, Tomasi M, Tristram M, Tucci M, Turner AD, Valenziano L, Valiviita J, Van Tent B, Vibert L, Vielva P, Vieregg AG, Villa F, Wade LA, Wandelt BD, Watson R, Weber AC, Wehus IK, White M, White SD, Willmert J, Wong CL, Yoon KW, Yvon D, Zacchei A, Zonca A.
PMID: 25815919
Phys Rev Lett. 2015 Mar 13;114(10):101301. doi: 10.1103/PhysRevLett.114.101301. Epub 2015 Mar 09.

We report the results of a joint analysis of data from BICEP2/Keck Array and Planck. BICEP2 and Keck Array have observed the same approximately 400  deg^{2} patch of sky centered on RA 0 h, Dec. -57.5°. The combined maps...

Cite
Ade PA, Aghanim N, Ahmed Z, et al. Joint analysis of BICEP2/keck array and Planck Data. Phys Rev Lett. 2015;114(10):101301doi: 10.1103/PhysRevLett.114.101301.
Ade, P. A., Aghanim, N., Ahmed, Z., Aikin, R. W., Alexander, K. D., Arnaud, M., Aumont, J., Baccigalupi, C., Banday, A. J., Barkats, D., Barreiro, R. B., Bartlett, J. G., Bartolo, N., Battaner, E., Benabed, K., Benoît, A., Benoit-Lévy, A., Benton, S. J., Bernard, J. P., Bersanelli, M., Bielewicz, P., Bischoff, C. A., Bock, J. J., Bonaldi, A., Bonavera, L., Bond, J. R., Borrill, J., Bouchet, F. R., Boulanger, F., Brevik, J. A., Bucher, M., Buder, I., Bullock, E., Burigana, C., Butler, R. C., Buza, V., Calabrese, E., Cardoso, J. F., Catalano, A., Challinor, A., Chary, R. R., Chiang, H. C., Christensen, P. R., Colombo, L. P., Combet, C., Connors, J., Couchot, F., Coulais, A., Crill, B. P., Curto, A., Cuttaia, F., Danese, L., Davies, R. D., Davis, R. J., de Bernardis, P., de Rosa, A., de Zotti, G., Delabrouille, J., Delouis, J. M., Désert, F. X., Dickinson, C., Diego, J. M., Dole, H., Donzelli, S., Doré, O., Douspis, M., Dowell, C. D., Duband, L., Ducout, A., Dunkley, J., Dupac, X., Dvorkin, C., Efstathiou, G., Elsner, F., Enßlin, T. A., Eriksen, H. K., Falgarone, E., Filippini, J. P., Finelli, F., Fliescher, S., Forni, O., Frailis, M., Fraisse, A. A., Franceschi, E., Frejsel, A., Galeotta, S., Galli, S., Ganga, K., Ghosh, T., Giard, M., Gjerløw, E., Golwala, S. R., González-Nuevo, J., Górski, K. M., Gratton, S., Gregorio, A., Gruppuso, A., Gudmundsson, J. E., Halpern, M., Hansen, F. K., Hanson, D., Harrison, D. L., Hasselfield, M., Helou, G., Henrot-Versillé, S., Herranz, D., Hildebrandt, S. R., Hilton, G. C., Hivon, E., Hobson, M., Holmes, W. A., Hovest, W., Hristov, V. V., Huffenberger, K. M., Hui, H., Hurier, G., Irwin, K. D., Jaffe, A. H., Jaffe, T. R., Jewell, J., Jones, W. C., Juvela, M., Karakci, A., Karkare, K. S., Kaufman, J. P., Keating, B. G., Kefeli, S., Keihänen, E., Kernasovskiy, S. A., Keskitalo, R., Kisner, T. S., Kneissl, R., Knoche, J., Knox, L., Kovac, J. M., Krachmalnicoff, N., Kunz, M., Kuo, C. L., Kurki-Suonio, H., Lagache, G., Lähteenmäki, A., Lamarre, J. M., Lasenby, A., Lattanzi, M., Lawrence, C. R., Leitch, E. M., Leonardi, R., Levrier, F., Lewis, A., Liguori, M., Lilje, P. B., Linden-Vørnle, M., López-Caniego, M., Lubin, P. M., Lueker, M., Macías-Pérez, J. F., Maffei, B., Maino, D., Mandolesi, N., Mangilli, A., Maris, M., Martin, P. G., Martínez-González, E., Masi, S., Mason, P., Matarrese, S., Megerian, K. G., Meinhold, P. R., Melchiorri, A., Mendes, L., Mennella, A., Migliaccio, M., Mitra, S., Miville-Deschênes, M. A., Moneti, A., Montier, L., Morgante, G., Mortlock, D., Moss, A., Munshi, D., Murphy, J. A., Naselsky, P., Nati, F., Natoli, P., Netterfield, C. B., Nguyen, H. T., Nørgaard-Nielsen, H. U., Noviello, F., Novikov, D., Novikov, I., O'Brient, R., Ogburn, R. W., Orlando, A., Pagano, L., Pajot, F., Paladini, R., Paoletti, D., Partridge, B., Pasian, F., Patanchon, G., Pearson, T. J., Perdereau, O., Perotto, L., Pettorino, V., Piacentini, F., Piat, M., Pietrobon, D., Plaszczynski, S., Pointecouteau, E., Polenta, G., Ponthieu, N., Pratt, G. W., Prunet, S., Pryke, C., Puget, J. L., Rachen, J. P., Reach, W. T., Rebolo, R., Reinecke, M., Remazeilles, M., Renault, C., Renzi, A., Richter, S., Ristorcelli, I., Rocha, G., Rossetti, M., Roudier, G., Rowan-Robinson, M., Rubiño-Martín, J. A., Rusholme, B., Sandri, M., Santos, D., Savelainen, M., Savini, G., Schwarz, R., Scott, D., Seiffert, M. D., Sheehy, C. D., Spencer, L. D., Staniszewski, Z. K., Stolyarov, V., Sudiwala, R., Sunyaev, R., Sutton, D., Suur-Uski, A. S., Sygnet, J. F., Tauber, J. A., Teply, G. P., Terenzi, L., Thompson, K. L., Toffolatti, L., Tolan, J. E., Tomasi, M., Tristram, M., Tucci, M., Turner, A. D., Valenziano, L., Valiviita, J., Van Tent, B., Vibert, L., Vielva, P., Vieregg, A. G., Villa, F., Wade, L. A., Wandelt, B. D., Watson, R., Weber, A. C., Wehus, I. K., White, M., White, S. D., Willmert, J., Wong, C. L., Yoon, K. W., Yvon, D., Zacchei, A., Zonca, A. (2015). Joint analysis of BICEP2/keck array and Planck Data. Physical review letters, 114(10), 101301. https://doi.org/10.1103/PhysRevLett.114.101301
Ade, P A R, et al. "Joint analysis of BICEP2/keck array and Planck Data." Physical review letters vol. 114,10 (2015): 101301. doi: https://doi.org/10.1103/PhysRevLett.114.101301
Ade PA, Aghanim N, Ahmed Z, Aikin RW, Alexander KD, Arnaud M, Aumont J, Baccigalupi C, Banday AJ, Barkats D, Barreiro RB, Bartlett JG, Bartolo N, Battaner E, Benabed K, Benoît A, Benoit-Lévy A, Benton SJ, Bernard JP, Bersanelli M, Bielewicz P, Bischoff CA, Bock JJ, Bonaldi A, Bonavera L, Bond JR, Borrill J, Bouchet FR, Boulanger F, Brevik JA, Bucher M, Buder I, Bullock E, Burigana C, Butler RC, Buza V, Calabrese E, Cardoso JF, Catalano A, Challinor A, Chary RR, Chiang HC, Christensen PR, Colombo LP, Combet C, Connors J, Couchot F, Coulais A, Crill BP, Curto A, Cuttaia F, Danese L, Davies RD, Davis RJ, de Bernardis P, de Rosa A, de Zotti G, Delabrouille J, Delouis JM, Désert FX, Dickinson C, Diego JM, Dole H, Donzelli S, Doré O, Douspis M, Dowell CD, Duband L, Ducout A, Dunkley J, Dupac X, Dvorkin C, Efstathiou G, Elsner F, Enßlin TA, Eriksen HK, Falgarone E, Filippini JP, Finelli F, Fliescher S, Forni O, Frailis M, Fraisse AA, Franceschi E, Frejsel A, Galeotta S, Galli S, Ganga K, Ghosh T, Giard M, Gjerløw E, Golwala SR, González-Nuevo J, Górski KM, Gratton S, Gregorio A, Gruppuso A, Gudmundsson JE, Halpern M, Hansen FK, Hanson D, Harrison DL, Hasselfield M, Helou G, Henrot-Versillé S, Herranz D, Hildebrandt SR, Hilton GC, Hivon E, Hobson M, Holmes WA, Hovest W, Hristov VV, Huffenberger KM, Hui H, Hurier G, Irwin KD, Jaffe AH, Jaffe TR, Jewell J, Jones WC, Juvela M, Karakci A, Karkare KS, Kaufman JP, Keating BG, Kefeli S, Keihänen E, Kernasovskiy SA, Keskitalo R, Kisner TS, Kneissl R, Knoche J, Knox L, Kovac JM, Krachmalnicoff N, Kunz M, Kuo CL, Kurki-Suonio H, Lagache G, Lähteenmäki A, Lamarre JM, Lasenby A, Lattanzi M, Lawrence CR, Leitch EM, Leonardi R, Levrier F, Lewis A, Liguori M, Lilje PB, Linden-Vørnle M, López-Caniego M, Lubin PM, Lueker M, Macías-Pérez JF, Maffei B, Maino D, Mandolesi N, Mangilli A, Maris M, Martin PG, Martínez-González E, Masi S, Mason P, Matarrese S, Megerian KG, Meinhold PR, Melchiorri A, Mendes L, Mennella A, Migliaccio M, Mitra S, Miville-Deschênes MA, Moneti A, Montier L, Morgante G, Mortlock D, Moss A, Munshi D, Murphy JA, Naselsky P, Nati F, Natoli P, Netterfield CB, Nguyen HT, Nørgaard-Nielsen HU, Noviello F, Novikov D, Novikov I, O'Brient R, Ogburn RW, Orlando A, Pagano L, Pajot F, Paladini R, Paoletti D, Partridge B, Pasian F, Patanchon G, Pearson TJ, Perdereau O, Perotto L, Pettorino V, Piacentini F, Piat M, Pietrobon D, Plaszczynski S, Pointecouteau E, Polenta G, Ponthieu N, Pratt GW, Prunet S, Pryke C, Puget JL, Rachen JP, Reach WT, Rebolo R, Reinecke M, Remazeilles M, Renault C, Renzi A, Richter S, Ristorcelli I, Rocha G, Rossetti M, Roudier G, Rowan-Robinson M, Rubiño-Martín JA, Rusholme B, Sandri M, Santos D, Savelainen M, Savini G, Schwarz R, Scott D, Seiffert MD, Sheehy CD, Spencer LD, Staniszewski ZK, Stolyarov V, Sudiwala R, Sunyaev R, Sutton D, Suur-Uski AS, Sygnet JF, Tauber JA, Teply GP, Terenzi L, Thompson KL, Toffolatti L, Tolan JE, Tomasi M, Tristram M, Tucci M, Turner AD, Valenziano L, Valiviita J, Van Tent B, Vibert L, Vielva P, Vieregg AG, Villa F, Wade LA, Wandelt BD, Watson R, Weber AC, Wehus IK, White M, White SD, Willmert J, Wong CL, Yoon KW, Yvon D, Zacchei A, Zonca A. Joint analysis of BICEP2/keck array and Planck Data. Phys Rev Lett. 2015 Mar 13;114(10):101301. doi: 10.1103/PhysRevLett.114.101301. Epub 2015 Mar 09. PMID: 25815919.
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Seroprevalence of antibodies against Kaposi's sarcoma-associated herpesvirus among HIV-negative people in China.

Infectious agents and cancer

Zhang T, Liu Z, Wang J, Minhas V, Wood C, Clifford GM, He N, Franceschi S.
PMID: 28572838
Infect Agent Cancer. 2017 May 30;12:32. doi: 10.1186/s13027-017-0142-9. eCollection 2017.

BACKGROUND: Little information on the prevalence of Kaposi's sarcoma associated herpesvirus (KSHV) among HIV-negative individuals is available from Asia.METHODS: In the present study, we report findings from a new survey of KSHV in 983 HIV-negative male migrants from Shanghai...

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Zhang T, Liu Z, Wang J, et al. Seroprevalence of antibodies against Kaposi's sarcoma-associated herpesvirus among HIV-negative people in China. Infect Agent Cancer. 2017;12:32doi: 10.1186/s13027-017-0142-9.
Zhang, T., Liu, Z., Wang, J., Minhas, V., Wood, C., Clifford, G. M., He, N., & Franceschi, S. (2017). Seroprevalence of antibodies against Kaposi's sarcoma-associated herpesvirus among HIV-negative people in China. Infectious agents and cancer, 1232. https://doi.org/10.1186/s13027-017-0142-9
Zhang, Tiejun, et al. "Seroprevalence of antibodies against Kaposi's sarcoma-associated herpesvirus among HIV-negative people in China." Infectious agents and cancer vol. 12 (2017): 32. doi: https://doi.org/10.1186/s13027-017-0142-9
Zhang T, Liu Z, Wang J, Minhas V, Wood C, Clifford GM, He N, Franceschi S. Seroprevalence of antibodies against Kaposi's sarcoma-associated herpesvirus among HIV-negative people in China. Infect Agent Cancer. 2017 May 30;12:32. doi: 10.1186/s13027-017-0142-9. eCollection 2017. PMID: 28572838; PMCID: PMC5450136.
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Induction of Antihuman C-C Chemokine Receptor Type 5 Antibodies by a Bovine Herpesvirus Type-4 Based Vector.

Frontiers in immunology

Verna AE, Franceschi V, Tebaldi G, Macchi F, Menozzi V, Pastori C, Lopalco L, Ottonello S, Cavirani S, Donofrio G.
PMID: 29118763
Front Immunol. 2017 Oct 25;8:1402. doi: 10.3389/fimmu.2017.01402. eCollection 2017.

Bovine herpesvirus 4 (BoHV-4) is a promising vector for the delivery and intracellular expression of recombinant antigens and can thus be considered as a new prototype vaccine formulation system. An interesting, and actively pursued, antigen in the context of...

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Verna AE, Franceschi V, Tebaldi G, et al. Induction of Antihuman C-C Chemokine Receptor Type 5 Antibodies by a Bovine Herpesvirus Type-4 Based Vector. Front Immunol. 2017;8:1402doi: 10.3389/fimmu.2017.01402.
Verna, A. E., Franceschi, V., Tebaldi, G., Macchi, F., Menozzi, V., Pastori, C., Lopalco, L., Ottonello, S., Cavirani, S., & Donofrio, G. (2017). Induction of Antihuman C-C Chemokine Receptor Type 5 Antibodies by a Bovine Herpesvirus Type-4 Based Vector. Frontiers in immunology, 81402. https://doi.org/10.3389/fimmu.2017.01402
Verna, Andrea Elizabeth, et al. "Induction of Antihuman C-C Chemokine Receptor Type 5 Antibodies by a Bovine Herpesvirus Type-4 Based Vector." Frontiers in immunology vol. 8 (2017): 1402. doi: https://doi.org/10.3389/fimmu.2017.01402
Verna AE, Franceschi V, Tebaldi G, Macchi F, Menozzi V, Pastori C, Lopalco L, Ottonello S, Cavirani S, Donofrio G. Induction of Antihuman C-C Chemokine Receptor Type 5 Antibodies by a Bovine Herpesvirus Type-4 Based Vector. Front Immunol. 2017 Oct 25;8:1402. doi: 10.3389/fimmu.2017.01402. eCollection 2017. PMID: 29118763; PMCID: PMC5660961.
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Combined multi-distance frequency domain and diffuse correlation spectroscopy system with simultaneous data acquisition and real-time analysis.

Biomedical optics express

Carp SA, Farzam P, Redes N, Hueber DM, Franceschini MA.
PMID: 29026684
Biomed Opt Express. 2017 Aug 07;8(9):3993-4006. doi: 10.1364/BOE.8.003993. eCollection 2017 Sep 01.

Frequency domain near infrared spectroscopy (FD-NIRS) and diffuse correlation spectroscopy (DCS) have emerged as synergistic techniques for the non-invasive assessment of tissue health. Combining FD-NIRS oximetry with DCS measures of blood flow, the tissue oxygen metabolic rate can be...

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Carp SA, Farzam P, Redes N, et al. Combined multi-distance frequency domain and diffuse correlation spectroscopy system with simultaneous data acquisition and real-time analysis. Biomed Opt Express. 2017;8(9):3993-4006doi: 10.1364/BOE.8.003993.
Carp, S. A., Farzam, P., Redes, N., Hueber, D. M., & Franceschini, M. A. (2017). Combined multi-distance frequency domain and diffuse correlation spectroscopy system with simultaneous data acquisition and real-time analysis. Biomedical optics express, 8(9), 3993-4006. https://doi.org/10.1364/BOE.8.003993
Carp, Stefan A, et al. "Combined multi-distance frequency domain and diffuse correlation spectroscopy system with simultaneous data acquisition and real-time analysis." Biomedical optics express vol. 8,9 (2017): 3993-4006. doi: https://doi.org/10.1364/BOE.8.003993
Carp SA, Farzam P, Redes N, Hueber DM, Franceschini MA. Combined multi-distance frequency domain and diffuse correlation spectroscopy system with simultaneous data acquisition and real-time analysis. Biomed Opt Express. 2017 Aug 07;8(9):3993-4006. doi: 10.1364/BOE.8.003993. eCollection 2017 Sep 01. PMID: 29026684; PMCID: PMC5611918.
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MetaDB a Data Processing Workflow in Untargeted MS-Based Metabolomics Experiments.

Frontiers in bioengineering and biotechnology

Franceschi P, Mylonas R, Shahaf N, Scholz M, Arapitsas P, Masuero D, Weingart G, Carlin S, Vrhovsek U, Mattivi F, Wehrens R.
PMID: 25566535
Front Bioeng Biotechnol. 2014 Dec 16;2:72. doi: 10.3389/fbioe.2014.00072. eCollection 2014.

Due to their sensitivity and speed, mass-spectrometry based analytical technologies are widely used to in metabolomics to characterize biological phenomena. To address issues like metadata organization, quality assessment, data processing, data storage, and, finally, submission to public repositories, bioinformatic...

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Franceschi P, Mylonas R, Shahaf N, et al. MetaDB a Data Processing Workflow in Untargeted MS-Based Metabolomics Experiments. Front Bioeng Biotechnol. 2014;2:72doi: 10.3389/fbioe.2014.00072.
Franceschi, P., Mylonas, R., Shahaf, N., Scholz, M., Arapitsas, P., Masuero, D., Weingart, G., Carlin, S., Vrhovsek, U., Mattivi, F., & Wehrens, R. (2014). MetaDB a Data Processing Workflow in Untargeted MS-Based Metabolomics Experiments. Frontiers in bioengineering and biotechnology, 272. https://doi.org/10.3389/fbioe.2014.00072
Franceschi, Pietro, et al. "MetaDB a Data Processing Workflow in Untargeted MS-Based Metabolomics Experiments." Frontiers in bioengineering and biotechnology vol. 2 (2014): 72. doi: https://doi.org/10.3389/fbioe.2014.00072
Franceschi P, Mylonas R, Shahaf N, Scholz M, Arapitsas P, Masuero D, Weingart G, Carlin S, Vrhovsek U, Mattivi F, Wehrens R. MetaDB a Data Processing Workflow in Untargeted MS-Based Metabolomics Experiments. Front Bioeng Biotechnol. 2014 Dec 16;2:72. doi: 10.3389/fbioe.2014.00072. eCollection 2014. PMID: 25566535; PMCID: PMC4267269.
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Pre-Operative, High-IL-6 Blood Level is a Risk Factor of Post-Operative Delirium Onset in Old Patients.

Frontiers in endocrinology

Capri M, Yani SL, Chattat R, Fortuna D, Bucci L, Lanzarini C, Morsiani C, Catena F, Ansaloni L, Adversi M, Melotti MR, Di Nino G, Franceschi C.
PMID: 25368603
Front Endocrinol (Lausanne). 2014 Oct 17;5:173. doi: 10.3389/fendo.2014.00173. eCollection 2014.

BACKGROUND: Post-operative delirium (POD) is a common complication in elderly patients undergoing surgery, but the underpinning causes are not clear. We hypothesized that inflammaging, the subclinical low and chronic grade inflammation characteristic of old people, can contribute to POD...

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Capri M, Yani SL, Chattat R, et al. Pre-Operative, High-IL-6 Blood Level is a Risk Factor of Post-Operative Delirium Onset in Old Patients. Front Endocrinol (Lausanne). 2014;5:173doi: 10.3389/fendo.2014.00173.
Capri, M., Yani, S. L., Chattat, R., Fortuna, D., Bucci, L., Lanzarini, C., Morsiani, C., Catena, F., Ansaloni, L., Adversi, M., Melotti, M. R., Di Nino, G., & Franceschi, C. (2014). Pre-Operative, High-IL-6 Blood Level is a Risk Factor of Post-Operative Delirium Onset in Old Patients. Frontiers in endocrinology, 5173. https://doi.org/10.3389/fendo.2014.00173
Capri, Miriam, et al. "Pre-Operative, High-IL-6 Blood Level is a Risk Factor of Post-Operative Delirium Onset in Old Patients." Frontiers in endocrinology vol. 5 (2014): 173. doi: https://doi.org/10.3389/fendo.2014.00173
Capri M, Yani SL, Chattat R, Fortuna D, Bucci L, Lanzarini C, Morsiani C, Catena F, Ansaloni L, Adversi M, Melotti MR, Di Nino G, Franceschi C. Pre-Operative, High-IL-6 Blood Level is a Risk Factor of Post-Operative Delirium Onset in Old Patients. Front Endocrinol (Lausanne). 2014 Oct 17;5:173. doi: 10.3389/fendo.2014.00173. eCollection 2014. PMID: 25368603; PMCID: PMC4201145.
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Diffuse correlation spectroscopy for measurement of cerebral blood flow: future prospects.

Neurophotonics

Buckley EM, Parthasarathy AB, Grant PE, Yodh AG, Franceschini MA.
PMID: 25593978
Neurophotonics. 2014 Jun 20;1(1). doi: 10.1117/1.NPh.1.1.011009.

Diffuse correlation spectroscopy (DCS) is an emerging optical modality used to measure cortical cerebral blood flow. This outlook presents a brief overview of the technology, summarizing the advantages and limitations of the method, and describing its recent applications to...

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Buckley EM, Parthasarathy AB, Grant PE, et al. Diffuse correlation spectroscopy for measurement of cerebral blood flow: future prospects. Neurophotonics. 2014;1(1)doi: 10.1117/1.NPh.1.1.011009.
Buckley, E. M., Parthasarathy, A. B., Grant, P. E., Yodh, A. G., & Franceschini, M. A. (2014). Diffuse correlation spectroscopy for measurement of cerebral blood flow: future prospects. Neurophotonics, 1(1), . https://doi.org/10.1117/1.NPh.1.1.011009
Buckley, Erin M, et al. "Diffuse correlation spectroscopy for measurement of cerebral blood flow: future prospects." Neurophotonics vol. 1,1 (2014). doi: https://doi.org/10.1117/1.NPh.1.1.011009
Buckley EM, Parthasarathy AB, Grant PE, Yodh AG, Franceschini MA. Diffuse correlation spectroscopy for measurement of cerebral blood flow: future prospects. Neurophotonics. 2014 Jun 20;1(1). doi: 10.1117/1.NPh.1.1.011009. PMID: 25593978; PMCID: PMC4292799.
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