Patrick Ye

All Publications

• FREQUENCY DEPENDENCE OF ULTRASOUND NEUROSTIMULATION IN THE MOUSE BRAIN ULTRASOUND IN MEDICINE AND BIOLOGY Ye, P. P., Brown, J. R., Pauly, K. B. 2016; 42 (7): 1512-1530

  Abstract

  Ultrasound neuromodulation holds promise as a non-invasive technique for neuromodulation of the central nervous system. However, much remains to be determined about how the technique can be transformed into a useful technology, including the effect of ultrasound frequency. Previous studies have demonstrated neuromodulation in vivo using frequencies <1 MHz, with a trend toward improved efficacy with lower frequency. However, using higher frequencies could offer improved ultrasound spatial resolution. We investigate the ultrasound neuromodulation effects in mice at various frequencies both below and above 1 MHz. We find that frequencies up to 2.9 MHz can still be effective for generating motor responses, but we also confirm that as frequency increases, sonications require significantly more intensity to achieve equivalent efficacy. We argue that our results provide evidence that favors either a particle displacement or a cavitation-based mechanism for the phenomenon of ultrasound neuromodulation.

  View details for DOI 10.1016/j.ultrasmedbio.2016.02.012

  View details for Web of Science ID 000377305500011

  View details for PubMedID 27090861

  View details for PubMedCentralID PMC4899295

• Ultrasound-based neurostimulation in the mouse model. journal of the Acoustical Society of America Butts Pauly, K., King, R., Ye, P., Brown, J. 2013; 134 (5): 4090-?

  Abstract

  Ultrasound-based neurostimulation would be a useful tool prior to MR-guided focused ultrasound treatments in the brain. In this work, we report on our studies on ultrasound-based neurostimulation in the mouse model. We define the success rate as the ratio of the number of positive EMG responses to the number of sonications. A single element ultrasound transducer with a center frequency of 500 kHz was applied to the mouse head via a coupling column and coupling gel on the mouse head. EMG electrodes were placed in the mouse neck and tail muscles to measure contraction of the relevant muscles as the ultrasound transducer is moved across the mouse head. The success rate increases with ultrasound intensity or with ultrasound duration, following a sigmoidal curve. As the ultrasound frequency is increased, the ultrasound intensity must be increased for the same success rate. Movement of the ultrasound transducer across the brain changes the response in the relevant EMG systems such that the neck EMG response is stronger when the transducer is more rostrally placed, while the tail EMG response is stronger when the transducer is more caudally placed. Our findings present evidence for selective targeting in the mouse model of ultrasound-based neurostimulation.

  View details for DOI 10.1121/1.4830937

  View details for PubMedID 24181342

• Data-Driven Prediction of Drug Effects and Interactions SCIENCE TRANSLATIONAL MEDICINE Tatonetti, N. P., Ye, P. P., Daneshjou, R., Altman, R. B. 2012; 4 (125)

  Abstract

  Adverse drug events remain a leading cause of morbidity and mortality around the world. Many adverse events are not detected during clinical trials before a drug receives approval for use in the clinic. Fortunately, as part of postmarketing surveillance, regulatory agencies and other institutions maintain large collections of adverse event reports, and these databases present an opportunity to study drug effects from patient population data. However, confounding factors such as concomitant medications, patient demographics, patient medical histories, and reasons for prescribing a drug often are uncharacterized in spontaneous reporting systems, and these omissions can limit the use of quantitative signal detection methods used in the analysis of such data. Here, we present an adaptive data-driven approach for correcting these factors in cases for which the covariates are unknown or unmeasured and combine this approach with existing methods to improve analyses of drug effects using three test data sets. We also present a comprehensive database of drug effects (Offsides) and a database of drug-drug interaction side effects (Twosides). To demonstrate the biological use of these new resources, we used them to identify drug targets, predict drug indications, and discover drug class interactions. We then corroborated 47 (P < 0.0001) of the drug class interactions using an independent analysis of electronic medical records. Our analysis suggests that combined treatment with selective serotonin reuptake inhibitors and thiazides is associated with significantly increased incidence of prolonged QT intervals. We conclude that confounding effects from covariates in observational clinical data can be controlled in data analyses and thus improve the detection and prediction of adverse drug effects and interactions.

  View details for DOI 10.1126/scitranslmed.3003377

  View details for Web of Science ID 000301538300005

  View details for PubMedID 22422992

  View details for PubMedCentralID PMC3382018

• Cutting edge: TLR2 is a functional receptor for acute-phase serum amyloid A JOURNAL OF IMMUNOLOGY Cheng, N., He, R., Tian, J., Ye, P. P., Ye, R. D. 2008; 181 (1): 22-26

  Abstract

  Induced secretion of acute-phase serum amyloid A (SAA) is a host response to danger signals and a clinical indication of inflammation. The biological functions of SAA in inflammation have not been fully defined, although recent reports indicate that SAA induces proinflammatory cytokine expression. We now show that TLR2 is a functional receptor for SAA. HeLa cells expressing TLR2 responded to SAA with potent activation of NF-kappaB, which was enhanced by TLR1 expression and blocked by the Toll/IL-1 receptor/resistance (TIR) deletion mutants of TLR1, TLR2, and TLR6. SAA stimulation led to increased phosphorylation of MAPKs and accelerated IkappaBalpha degradation in TLR2-HeLa cells, and results from a solid-phase binding assay showed SAA interaction with the ectodomain of TLR2. Selective reduction of SAA-induced gene expression was observed in tlr2-/- mouse macrophages compared with wild-type cells. These results suggest a potential role for SAA in inflammatory diseases through activation of TLR2.

  View details for Web of Science ID 000257404900006

  View details for PubMedID 18566366

  View details for PubMedCentralID PMC2464454

• Pharmacological characterization of a novel nonpeptide antagonist for formyl peptide receptor-like 1 MOLECULAR PHARMACOLOGY Zhou, C., Zhang, S., Nanamori, M., Zhang, Y., Liu, Q., Li, N., Sun, M., Tian, J., Ye, P. P., Cheng, N., Ye, R. D., Wang, M. 2007; 72 (4): 976-983

  Abstract

  A series of quinazolinone derivatives were synthesized based on a hit compound identified from a high-throughput screening campaign targeting the human formyl peptide receptor-like 1 (FPRL1). Based on structure-activity relationship analysis, we found that substitution on the para position of the 2-phenyl group of the quinazolinone backbone could alter the pharmacological properties of the compound. The methoxyl substitution produced an agonist 4-butoxy-N-[2-(4-methoxy-phenyl)-4-oxo-1,4-dihydro-2H-quinazolin-3-yl]-benzamide (Quin-C1; C1), whereas a hydroxyl substitution resulted in a pure antagonist, Quin-C7 (C7). Several partial agonists were derived from other substitutions on the para position. C7 partially displaced [(125)I]Trp-Lys-Tyr-Met-Val-d-Met-NH(2) (WKYMVm) binding to FPRL1 but not [(3)H]N-formyl-Met-Leu-Phe to formyl peptide receptor. In functional assays using FPRL1-expressing RBL-2H3 cells, C7 inhibited calcium mobilization and chemotaxis induced by WKYMVm and C1 and degranulation elicited by C1. C7 also suppressed C1-induced extracellular signal-regulated kinase phosphorylation and reduced arachidonic acid-induced ear edema in mice. This study represents the first characterization of a nonpeptidic antagonist for FPRL1 and suggests the prospect of using low molecular weight compounds as modulators of chemoattractant receptors in vitro and in vivo.

  View details for DOI 10.1124/mol.107.037564

  View details for Web of Science ID 000249561500018

  View details for PubMedID 17652444