Imaging Ca²⁺ dynamics in living systems holds great
potential to advance neuroscience and cellular biology. G-GECO1.1
is an intensiometric fluorescent protein Ca²⁺-biosensor with a Thr-Tyr-Gly chromophore. The protonated chromophore emits green
upon photoexcitation via excited-state proton transfer (ESPT). Upon
Ca²⁺ binding, a significant population of the chromophores becomes
deprotonated. It...
Fluorescent proteins (FPs) have played a pivotal role in bioimaging and advancing biomedicine. The versatile fluorescence from engineered, genetically encodable FP variants greatly enhances cellular imaging capabilities, which are dictated by excited state structural dynamics of the embedded chromophore inside the protein pocket. Visualization of the molecular choreography of the...
Fluorescent proteins (FPs) are luminescent biomolecules that emit characteristic hues upon irradiation. A group of calmodulin (CaM)-green FP (GFP) chimeras have been previously engineered to enable the optical detection of calcium ions (Ca²⁺). We investigate one of these genetically encoded Ca²⁺ biosensors for optical imaging (GECOs), GEM-GECO1, which fluoresces green...
Biosensors have become an indispensable tool set in life sciences. Among them, fluorescent protein-based biosensors have great biocompatibility and tunable emission properties but their development is largely on trial and error. To facilitate a rational design, we implement tunable femtosecond stimulated Raman spectroscopy, aided by transient absorption and quantum calculations,...
In this dissertation, excited state proton transfer (ESPT) and its inhibition in solution and protein environments are revealed using both femtosecond transient absorption (fs-TA) spectroscopy and femtosecond stimulated Raman spectroscopy (FSRS). Using a tunable Raman pump to enhance transient vibrational features of the photoacidic chromophore HPTS in methanol and methanol...
Labeling videos is costly, time-consuming and tedious. These costs can escalate in applications such as medical diagnosis or autonomous driving where we need domain expertise for annotation. Few-shot action recognition aims to solve this problem by annotation-efficient learning mechanisms.
This thesis presents MetaUVFS as the first Unsupervised Meta-learning algorithm for...
Deep learning is becoming the latest trend in sensitive applications, such as healthcare, criminal justice, and finance. As these new applications emerge, adversaries are circumventing them.
Further, there have been concerns about the possibility of bias and discrimination in predictive applications.
In order to address these issues, we propose an...
Femtosecond stimulated Raman spectroscopy (FSRS) is a powerful ultrafast technique which can track photoinduced excited state structural events on femtosecond (fs) to picosecond (ps) timescales. In addition to high temporal and spectral resolutions, FSRS provides a broad spectral window from ca. 100—2000 cm-1 for detection, enabling the direct mapping of...
Manufacturing technology has continuously evolved and advanced over the past century; this has led to an increase in the production of consumer and industrial goods driven by simultaneous growth in population and wealth. Despite the resulting economic and labor growth, environmental impacts of manufacturing have increased dramatically due to the...
Multi-robot teams offer promising solutions for many long term deployments in remote and dangerous domains, such as extraterrestrial or underseas exploration. However, long term deployments present many problems preventing robot teams from operating effectively. Learning over long time scales is makes it difficult to assign credit to robots' actions, as...