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Bonyadi Camacho, Hinman, and Won present at Nov. 1 Graduate Student Seminar

Mariam Bonyadi Camacho, a graduate student researcher in the Cellular and Molecular Foundations of Intelligent Behavior Group; Joshua Hinman, a Ph.D. candidate in the Nanoelectronics and Nanomaterials Group, and Jungeun (Jenny) Won, a graduate research assistant in the Bioimaging Science and Technology Group, will discuss their research at the Graduate Student Seminar held at noon Wed., Nov. 1, in Room 1005 Beckman. Lunch will be provided.

Published on Oct. 20, 2017

Computers and Mood Disorders: A Computational Model of Antidepressant Drug Effects

Mariam Bonyadi Camacho, Ph.D. Candidate, Cellular and Molecular Foundations of Intelligent Behavior

The majority of depressed patients who take an antidepressant chronically do not experience complete depression relief. The reason for this clinically observed heterogeneity in antidepressant response is not fully understood. We previously developed a computational model that represents the interactions between the monoaminergic neurotransmitter-producing brain regions and three non-monoaminergic neurotransmitter systems that are believed to be involved in the antidepressant response. The model represented the latency in antidepressant response by allowing the network to homeostatically adjust to chronic antidepressant administration with sequential receptor strength adjustments. In terms of the percentage of adapted states with therapeutically elevated monoamines, our model findings agreed closely with clinically observed efficacies of twelve antidepressant drugs and combinations. Importantly, the model demonstrated that the brain can reach similar levels of adaptation in many ways, but not all adapted configurations are associated with therapeutic monoamine levels. We have since expanded this model by enlarging both the interactions between model elements and the input-output behavior of the model. The procedure used to optimize model parameters was switched to a more efficient, gradient-based machine-learning paradigm. Some key results using this expanded model with improved optimization capability will be discussed during the seminar.

Anisotropic Silica Coating of Gold Nanorods

Joshua Hinman, Ph.D. Candidate, Nanoelectronics and Nanomaterials

Image by Joshua Hinman

Achieving spatial control over the surface chemistry of colloidal nanoparticles has been a longstanding challenge but could have important implications for synthesizing new nanomaterials and directing the assembly of nanoparticles. Known for their striking colors, the size and shape-dependent optical properties of gold nanorods have inspired research into their use for applications ranging from sensing to biomedical imaging and even photothermal cancer treatment. Their shape has also made gold nanorods a favorite system for studying the effects of morphological anisotropy on the surface chemistry of colloidal nanoparticles. A number of studies have attempted to leverage slight, site-specific differences in the surface chemistry of gold nanorods to anisotropically functionalize their surfaces. It has been suggested that the sides of gold nanorods can be selectively coated with silica if their ends are first functionalized with thiol-terminated polyethylene glycol (PEG-thiol), but it has proven difficult to implement such a protocol reproducibly. Here we demonstrate that the oxidation state of the thiol-terminated polymer is critical for silica coating the sides of gold nanorods, and that only PEG-disulfide, not PEG-thiol, is useful for selectively blocking their ends. Our research sheds light on the role that the ligands play in the anisotropic functionalization of gold nanorods and provides insights that can help inform the choice of ligands used for the site-specific chemical modification of other anisotropic colloidal nanoparticles.

Assessing Middle Ear Dynamics in vivo using Low Coherence Interferometry

Jungeun (Jenny) Won, graduate research assistant, Bioimaging Science and Technology Group

Image by Jenny Won

A middle ear infection is a widespread disease in early childhood, characterized by the accumulation of fluid in a normally air-filled middle ear space. Middle ear fluid may cause eardrum perforation, hearing loss, and delayed learning if fluid remains untreated. Nonetheless, standard diagnostic tools provide subjective and qualitative information about a middle ear space to physicians, especially when determining a presence of middle ear fluid. This work utilizes a light ranging technique, called low coherence interferometry (LCI), to capture the dynamics of an eardrum when a gentle, short pneumatic stimulus is applied to the eardrum. Quantitative metrics are defined to represent a pneumatic mobility of the eardrum and the middle ear pressure. With in vivo measurements from 42 pediatric ears, a presence of a middle ear fluid was indicated with significantly low pneumatic mobility and positive middle ear pressure. The results were also compared with current methodologies, such as otoscopy and tympanometry. This study highlights the potential of our pneumatic LCI system in detecting middle ear fluid and quantifying middle ear characteristics, which may provide new quantitative metrics for diagnosing a middle ear infection.

In this article

  • Jungeun Won
    Jungeun Won's directory photo.

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