Phenobarbital in Nuclear Receptor Activation: An Update.

Phenobarbital (PB) is a commonly prescribed anti-epileptic drug that can also benefit newborns from hyperbilirubinemia. Being the first drug demonstrating hepatic induction of cytochrome P450 (CYP), PB has since been broadly used as a model compound to study xenobiotic-induced drug metabolism and clearance. Mechanistically, PB-mediated CYP induction is linked to a number of nuclear receptors, such as the constitutive androstane receptor (CAR), pregnane X receptor (PXR), and estrogen receptor α, with CAR being the predominant regulator. Unlike prototypical agonistic ligands, PB-mediated activation of CAR does not involve direct binding with the receptor. Instead, dephosphorylation of threonine 38 in the DNA-binding domain of CAR was delineated as a key signaling event underlying PB-mediated indirect activation of CAR. Further studies revealed that such phosphorylation sites appear to be highly conserved among most human nuclear receptors. Interestingly, while PB is a pan-CAR activator in both animals and humans, PB activates human but not mouse PXR. The species-specific role of PB in gene regulation is a key determinant of its implication in xenobiotic metabolism, drug-drug interactions, energy homeostasis, and cell proliferation. In this review, we summarize the recent progress in our understanding of PB-provoked transactivation of nuclear receptors with a focus on CAR and PXR. SIGNIFICANCE STATEMENT: Extensive studies using PB as a research tool have significantly advanced our understanding of the molecular basis underlying nuclear receptor-mediated drug metabolism, drug-drug interactions, energy homeostasis, and cell proliferation. In particular, CAR has been established as a cell signaling-regulated nuclear receptor in addition to ligand-dependent functionality. This mini-review highlights the mechanisms by which PB transactivates CAR and PXR.

Quantitative Chemical Imaging of Bone Tissue for Intraoperative and Diagnostic Applications.

Bone is difficult to image using traditional histopathological methods, leading to challenges in intraoperative pathological evaluation that is critical in guiding surgical treatment, particularly in orthopedic oncology. In this study, we demonstrate that a multimodal quantitative imaging approach that combines stimulated Raman scattering (SRS) microscopy, two-photon fluorescence (TPF) microscopy, and second-harmonic generation (SHG) microscopy can provide useful diagnostic information regarding intact bone tissue fragments from surgical excision or biopsy specimens. We imaged bone samples from 17 patient cases and performed quantitative chemical and morphological analyses of both mineral and organic components of bone. Our main findings show that carbonate content combined with morphometric analysis of bone organic matrix can separate several major classes of bone cancer-associated diagnostic categories with an average accuracy of 92%. This proof-of-principle study demonstrates that quantitative multimodal imaging and machine learning-based analysis of bony tissue can provide crucial diagnostic information for guiding clinical decisions in orthopedic oncology. Moreover, the general methodology of morphological and chemical imaging combined with machine learning can be readily extended to other tissue types for tissue diagnosis in intraoperative and other clinical settings.

Drug Dissolution in Oral Drug Absorption: Workshop Report.

The in-person workshop "Drug Dissolution in Oral Drug Absorption" was held on May 23-24, 2023, in Baltimore, MD, USA. The workshop was organized into lectures and breakout sessions. Three common topics that were re-visited by various lecturers were amorphous solid dispersions (ASDs), dissolution/permeation interplay, and in vitro methods to predict in vivo biopharmaceutics performance and risk. Topics that repeatedly surfaced across breakout sessions were the following: (1) meaning and assessment of "dissolved drug," particularly of poorly water soluble drug in colloidal environments (e.g., fed conditions, ASDs); (2) potential limitations of a test that employs sink conditions for a poorly water soluble drug; (3) non-compendial methods (e.g., two-stage or multi-stage method, dissolution/permeation methods); (4) non-compendial conditions (e.g., apex vessels, non-sink conditions); and (5) potential benefit of having both a quality control method for batch release and a biopredictive/biorelevant method for biowaiver or bridging scenarios. An identified obstacle to non-compendial methods is the uncertainty of global regulatory acceptance of such methods.

Quantitative Imaging of Intracellular Density with Ratiometric Stimulated Raman Scattering Microscopy.

Cell size and density are tightly controlled in mammalian cells. They impact a wide range of physiological functions, including osmoregulation, tissue homeostasis, and growth regulation. Compared to size, density variation for a given cell type is typically much smaller, implying that cell-type-specific density plays an important role in cell function. However, little is known about how cell density affects cell function or how it is regulated. Current tools for intracellular cell density measurements are limited to either suspended cells or cells grown on 2D substrates, neither of which recapitulate the physiology of single cells in intact tissue. While optical measurements have the potential to noninvasively measure cell density in situ, light scattering in multicellular systems prevents direct quantification. Here, we introduce an intracellular density imaging technique based on ratiometric stimulated Raman scattering microscopy (rSRS). It uses intrinsic vibrational information from intracellular macromolecules to quantify dry mass density. Moreover, water is used as an internal standard to correct for aberration and light scattering effects. We demonstrate real-time measurement of intracellular density and show that density is tightly regulated across different cell types and can be used to differentiate cell types as well as cell states. We further demonstrate dynamic imaging of density change in response to osmotic challenge as well as intracellular density imaging of a 3D tumor spheroid. Our technique has the potential for imaging intracellular density in intact tissue and understanding density regulation and its role in tissue homeostasis.

In vivo simultaneous nonlinear absorption Raman and fluorescence (SNARF) imaging of mouse brain cortical structures.

Label-free multiphoton microscopy is a powerful platform for biomedical imaging. Recent advancements have demonstrated the capabilities of transient absorption microscopy (TAM) for label-free quantification of hemoglobin and stimulated Raman scattering (SRS) microscopy for pathological assessment of label-free virtual histochemical staining. We propose the combination of TAM and SRS with two-photon excited fluorescence (TPEF) to characterize, quantify, and compare hemodynamics, vessel structure, cell density, and cell identity in vivo between age groups. In this study, we construct a simultaneous nonlinear absorption, Raman, and fluorescence (SNARF) microscope with the highest reported in vivo imaging depth for SRS and TAM at 250-280 µm to enable these multimodal measurements. Using machine learning, we predict capillary-lining cell identities with 90% accuracy based on nuclear morphology and capillary relationship. The microscope and methodology outlined herein provides an exciting route to study several research topics, including neurovascular coupling, blood-brain barrier, and neurodegenerative diseases.

A Versatile Deep Learning Architecture for Classification and Label-Free Prediction of Hyperspectral Images.

Hyperspectral imaging is a technique that provides rich chemical or compositional information not regularly available to traditional imaging modalities such as intensity imaging or color imaging based on the reflection, transmission, or emission of light. Analysis of hyperspectral imaging often relies on machine learning methods to extract information. Here, we present a new flexible architecture, the U-within-U-Net, that can perform classification, segmentation, and prediction of orthogonal imaging modalities on a variety of hyperspectral imaging techniques. Specifically, we demonstrate feature segmentation and classification on the Indian Pines hyperspectral dataset and simultaneous location prediction of multiple drugs in mass spectrometry imaging of rat liver tissue. We further demonstrate label-free fluorescence image prediction from hyperspectral stimulated Raman scattering microscopy images. The applicability of the U-within-U-Net architecture on diverse datasets with widely varying input and output dimensions and data sources suggest that it has great potential in advancing the use of hyperspectral imaging across many different application areas ranging from remote sensing, to medical imaging, to microscopy.

Phenobarbital Induces SLC13A5 Expression through Activation of PXR but Not CAR in Human Primary Hepatocytes.

Phenobarbital (PB), a widely used antiepileptic drug, is known to upregulate the expression of numerous drug-metabolizing enzymes and transporters in the liver primarily via activation of the constitutive androstane receptor (CAR, NR1I3). The solute carrier family 13 member 5 (SLC13A5), a sodium-coupled citrate transporter, plays an important role in intracellular citrate homeostasis that is associated with a number of metabolic syndromes and neurological disorders. Here, we show that PB markedly elevates the expression of SLC13A5 through a pregnane X receptor (PXR)-dependent but CAR-independent signaling pathway. In human primary hepatocytes, the mRNA and protein expression of SLC13A5 was robustly induced by PB treatment, while genetic knockdown or pharmacological inhibition of PXR significantly attenuated this induction. Utilizing genetically modified HepaRG cells, we found that PB induces SLC13A5 expression in both wild type and CAR-knockout HepaRG cells, whereas such induction was fully abolished in the PXR-knockout HepaRG cells. Mechanistically, we identified and functionally characterized three enhancer modules located upstream from the transcription start site or introns of the SLC13A5 gene that are associated with the regulation of PXR-mediated SLC13A5 induction. Moreover, metformin, a deactivator of PXR, dramatically suppressed PB-mediated induction of hepatic SLC13A5 as well as its activation of the SLC13A5 luciferase reporter activity via PXR. Collectively, these data reveal PB as a potent inducer of SLC13A5 through the activation of PXR but not CAR in human primary hepatocytes.

Quantitative chemical imaging of breast calcifications in association with neoplastic processes.

Calcifications play an essential role in early breast cancer detection and diagnosis. However, information regarding the chemical composition of calcifications identified on mammography and histology is limited. Detailed spectroscopy reveals an association between the chemical composition of calcifications and breast cancer, warranting the development of novel analytical tools to better define calcification types. Previous investigations average calcification composition across broad tissue sections with no spatially resolved information or provide qualitative visualization, which prevents a robust linking of specific spatially resolved changes in calcification chemistry with the pathologic process. Method: To visualize breast calcification chemical composition at high spatial resolution, we apply hyperspectral stimulated Raman scattering (SRS) microscopy to study breast calcifications associated with a spectrum of breast changes ranging from benign to neoplastic processes, including atypical ductal hyperplasia, ductal carcinoma in situ, and invasive ductal carcinoma. The carbonate content of individual breast calcifications is quantified using a simple ratiometric analysis. Results: Our findings reveal that intra-sample calcification carbonate content is closely associated with local pathological processes. Single calcification analysis supports previous studies demonstrating decreasing average carbonate level with increasing malignant potential. Sensitivity and specificity reach >85% when carbonate content level is used as the single differentiator in separating benign from neoplastic processes. However, the average carbonate content is limiting when trying to separate specific diagnostic categories, such as fibroadenoma and invasive ductal carcinoma. Second harmonic generation (SHG) data can provide critical information to bridge this gap. Conclusion: SRS, combined with SHG, can be a valuable tool in better understanding calcifications in carcinogenesis, diagnosis, and possible prognosis. This study not only reveals previously unknown large variations of breast microcalcifications in association with local malignancy but also corroborates the clinical value of linking microcalcification chemistry to breast malignancy. More importantly, it represents an important step in the development of a label-free imaging strategy for breast cancer diagnosis with tremendous potential to address major challenges in diagnostic discordance in pathology.