Results 61 to 70 of about 1,936,786 (367)

Aggressive prostate cancer is associated with pericyte dysfunction

Molecular Oncology, EarlyView.
Tumor‐produced TGF‐β drives pericyte dysfunction in prostate cancer. This dysfunction is characterized by downregulation of some canonical pericyte markers (i.e., DES, CSPG4, and ACTA2) while maintaining the expression of others (i.e., PDGFRB, NOTCH3, and RGS5).
Anabel Martinez‐Romero, Ane Martinez‐Larrinaga, Joaquim Grego‐Bessa, Saioa Garcia‐Longarte, Hielke van Splunder, Ianire Astobiza, Amaia Ercilla, Laura Bozal‐Basterra, Isabel Mendizabal, Pilar Villacampa, Arkaitz Carracedo, Mariona Graupera   +11 more
wiley   +1 more source

Tumor and germline testing with next generation sequencing in epithelial ovarian cancer: a prospective paired comparison using an 18‐gene panel

Molecular Oncology, EarlyView.
Genetic testing in epithelial ovarian cancer includes both germline and tumor‐testing. This approach often duplicates resources. The current prospective study assessed the feasibility of tumor‐first multigene testing by comparing tumor tissue with germline testing of peripheral blood using an 18‐gene NGS panel in 106 patients.
Elisabeth Spenard, Cristina Mitric, Melanie Care, Tracy L. Stockley, Raymond H. Kim, Jeanna McCuaig, Blaise Clarke, Laura Ranich, Clare Sheen, Sarah E. Ferguson, Liat Hogen, Taymaa May, Marcus Q. Bernardini   +12 more
wiley   +1 more source

Preparation and characterization of renal cell peptides from fetal rats for their antitumor activity

FEBS Open Bio, EarlyView.
This study aimed to prepare renal cells (RCs) from fetal rats which were digested by enzymes. Candidate peptides RCPs were characterized by capillary HPLC and MS and their bioactivity was predicted using peptideranker. The predicted top 10 bioactive peptides were synthesized.
Zhe Zhang, Yuan Cao, Jing Du, Ying Zhang, Junxia Wang, Ying Yuan, Lianqing Sun   +6 more
wiley   +1 more source

Acknowledgement to Reviewers of Robotics in 2016

Robotics, 2017
The editors of Robotics would like to express their sincere gratitude to the following reviewers for assessing manuscripts in 2016.[...]
Robotics Editorial Office
doaj   +1 more source

Robotics and Neuroscience [PDF]

Current Biology, 2014
In the attempt to build adaptive and intelligent machines, roboticists have looked at neuroscience for more than half a century as a source of inspiration for perception and control. More recently, neuroscientists have resorted to robots for testing hypotheses and validating models of biological nervous systems. Here, we give an overview of the work at
Stefan Schaal, Auke Jan Ijspeert, Dario Floreano   +2 more
openaire   +4 more sources

State Estimation for Robotics

, 2017
A key aspect of robotics today is estimating the state (e.g., position and orientation) of a robot, based on noisy sensor data. This book targets students and practitioners of robotics by presenting classical state estimation methods (e.g., the Kalman ...
T. Barfoot
semanticscholar   +1 more source

Teaching Python with team‐based learning: using cloud‐based notebooks for interactive coding education

FEBS Open Bio, EarlyView.
This study presents a novel approach to teaching Python and bioinformatics using team‐based learning and cloud‐hosted notebooks. By integrating interactive coding into biomedical education, the method improves accessibility, student engagement, and confidence—especially for those without a computing background.
Nuno S. Osório, Leonardo D. Garma
wiley   +1 more source

Walking Humanoids for Robotics Research [PDF]

, 2002
We present three humanoid robots aimed as platforms for research in robotics, and cognitive development in robotics systems. The 'priscilla' robot is a 180cm full scale humanoid, and the mid-size prototype is called 'elvis' and is about 70cm tall.
Nordin, Peter, Wolff, Krister
core   +2 more sources

Robotic Wireless Sensor Networks

, 2018
In this chapter, we present a literature survey of an emerging, cutting-edge, and multi-disciplinary field of research at the intersection of Robotics and Wireless Sensor Networks (WSN) which we refer to as Robotic Wireless Sensor Networks (RWSN).
A Balasubramanian, A Chattopadhyay, A Fida, A Gasparri, A Gasparri, A Ghaffarkhah, A Gonzalez-Ruiz, A Gonzalez-Ruiz, A Sanfeliu, A Tiderko, AM Hsieh, AM Ladd, B Mohar, C Dixon, C Lochert, CE Perkins, CR Lin, D Calkins, D Son, D Tardioli, DV Dimarogonas, DV Dimarogonas, E Aahin, E Prassler, EA Thompson, EW Dijkstra, F Knorn, FT Dagefu, G Holland, G Sun, G Tuna, H Choset, HG Nguyen, Hui Liu, I Guvenc, J Baber, J Cortes, J Fink, J Ny Le, J Penders, J Zhou, JB Petelin, JC Curlander, JG Dai, JK Erickson, JR Pinta De La, K Fall, K Kamei, K Konolige, K Savla, KA Qaraqe, L Oliveira, L Sabattini, L Tassiulas, LE Parker, M Fiedler, M Franceschelli, M Guo, M Malmirchegini, M Mauve, M Mauve, M Michael, M Michael, M Michael, M Michael, M Naghshvar, M Saumitra, M Schuresko, MA Batalin, MA Hsieh, MD Weiss, N Bezzo, N Boillot, N Hazon, N Xiong, NP Papanikolopoulos, O Tekdas, P Brass, P Wilke, P Yang, P Yang, P. Ibach, Pradipta Ghosh, Pradipta Ghosh, PX Liu, Q Dong, R Olfati-Saber, RC Arkin, RR Murphy, RR Murphy, S Depatla, S Gil, S Manfredi, S Thrun, S Wang, SJ Lee, SR Theodore, T Gustavi, V Milanés, Y Mostofi, Y Mostofi, Y Mostofi, Y Mostofi, Y Uchimura, Y Yan, Y Yan, Z Lin   +106 more
core   +1 more source

Acknowledgement to Reviewers of Robotics in 2018

Robotics, 2019
Rigorous peer-review is the corner-stone of high-quality academic publishing [...]
Robotics Editorial Office
doaj   +1 more source