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14
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53
Citations
Education
September 2016 - June 2018
August 2014 - May 2015
August 2014 - May 2015
Publications
Publications (14)
Histological staining of tissue biopsies, especially hematoxylin and eosin (H&E) staining, serves as the benchmark for disease diagnosis and comprehensive clinical assessment of tissue. However, the process is laborious and time-consuming, often limiting its usage in crucial applications such as surgical margin assessment. To address these challeng...
Histological staining of tissue biopsies, especially hematoxylin and eosin (H&E) staining, serves as the benchmark for disease diagnosis and comprehensive clinical assessment of tissue. However, the process is laborious and time-consuming, often limiting its usage in crucial applications such as surgical margin assessment. To address these challeng...
We present MindEye, a novel fMRI-to-image approach to retrieve and reconstruct viewed images from brain activity. Our model comprises two parallel submodules that are specialized for retrieval (using contrastive learning) and reconstruction (using a diffusion prior). MindEye can map fMRI brain activity to any high dimensional multimodal latent spac...
Multimodal models trained on large natural image-text pair datasets have exhibited astounding abilities in generating high-quality images. Medical imaging data is fundamentally different to natural images, and the language used to succinctly capture relevant details in medical data uses a different, narrow but semantically rich, domain-specific voc...
Background:
Fluorescence imitating brightfield imaging (FIBI) is a novel alternative microscopy method that can image freshly excised, non-sectioned tissue. We examine its potential utility in dermatopathology by examining readily available specimens embedded in paraffin blocks.
Methods:
Nine skin samples embedded in paraffin blocks were superfi...
Pathology is finally profiting from the recent development of promising novel imaging techniques, as well as exploration of computational methods for extracting increased information from existing slides and conventional microscopy. This chapter focuses largely on the latter, looking at application of artificial intelligence (AI) methods for denois...
We describe 3-dimensional histology of fresh or fixed unimbedded tissue using a vibrating microtome with MUSE (microscopy with UV surface excitation) to acquire block-face images that can be reconstructed into 3-dimensional data sets.
MUSE is a novel slide-free imaging technique for histological examination of tissues that can serve as an alternative to traditional histology. In order to bridge the gap between MUSE and traditional histology, we aim to convert MUSE images to resemble authentic hematoxylin-and eosin-stained (H&E) images. We evaluated four models: a non-machine-lea...
MUSE is a novel slide-free imaging technique for histological examination of tissues that can serve as an alternative to traditional histology. In order to bridge the gap between MUSE and traditional histology, we aim to convert MUSE images to resemble authentic hematoxylin- and eosin-stained (H&E) images. We evaluated four models: a non-machine-le...
Advances in materials engineering have allowed for the development of sophisticated and controlled drug delivery through vesicles. Smart vesicles, capable of sensing single stimulus or multiple stimuli, can be engineered to process specific environmental signals to produce a tailored response. Exhibiting multifunctionality and theranostic abilities...
Questions
Questions (3)
I am interested in studying the dynamics of a lipid vesicle. Surface Evolver seems to be a great program and quite extensible. However, as I understand it, the program only minimizes the total energy of the surface, and cannot be used to study the evolution (ironically) of the surface over time.
Are there any available programs, packages, or even libraries for programming languages, with similar capabilities as Surface Evolver to model the surface dynamics of systems with various topologies, and types of energies?
How can I calculate hepatic clearance for liposomes given only physicochemical properties (like pKa, Log D, size, etc.) and some pharmacokinetic properties/ADME properties. I don't have any microsome or hepatocyte data at all.
I am trying to estimate the tissue-plasma partition coefficient for liposomes but I do not have any in vitro data. I only have physicochemical data like Log D, pKa, etc. But I don't have any properties like fraction unbound to plasma.
I have been looking into predictive models for the tissue-plasma partition coefficients (Poulin and Theil 2002) and they usually use fraction unbound to plasma. Now, I am currently assuming that the liposomes, given that they are pretty big, distribute mainly into the extracellular space (I am not sure if this is a fair assumption). The equation for non-adipose tissue is:
Pt:p=(Veist/Veisp)×(fup/fut)
Please read the publication for more information. Finally, it comes down to only needing the fup (fraction unbound to plasma). This value I am estimating to be about 0.2 or 0.3 since lipopihlic and acidic compounds have much greater protein binding (Ghafourian and Amin 2013).
Is there a better and more accurate way of estimating the partition coefficients given only physicochemical data of the drug? Also, how can I add some size dependence to my calculation of the partition coefficient? After all, the size of the liposome will greatly affect the tissue-plasma distribution in the organs.
