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  1. Abstract

    Purpose: Paracrine activation of pro-fibrotic hedgehog (HH) signaling in pancreatic ductal adenocarcinoma (PDAC) results in stromal amplification that compromises tumor drug delivery, efficacy, and patient survival. Interdiction of HH-mediated tumor-stroma crosstalk with smoothened (SMO) inhibitors (SHHi) ‘primes’ PDAC patient-derived xenograft (PDX) tumors for increased drug delivery by transiently increasing vascular patency/permeability, and thereby macromolecule delivery. However, patient tumor isolates vary in their responsiveness, and responders show co-induction of epithelial-mesenchymal transition (EMT). We aimed to identify the signal derangements responsible for EMT induction and reverse them, and devise approaches to stratify SHHi-responsive tumors non-invasively based on clinically-quantifiable parameters. Experimental design: Animals underwent diffusion-weighted magnetic resonance (DW-MR) imaging for measurement of intra-tumor diffusivity. In parallel, tissue-level deposition of nanoparticle probes was quantified as a marker of vascular permeability/perfusion. Transcriptomic and bioinformatic analysis was employed to investigate SHHi-induced gene reprogramming and identify key ‘nodes’ responsible for EMT induction. Results: multiple patient tumor isolates responded to short-term SHH inhibitor exposure with increased vascular patency and permeability, with proportionate increases in tumor diffusivity. Non-responding PDXs did not. SHHi-treated tumors showed elevated FGF drive and distinctly higher nuclear localization of fibroblast growth factor receptor (FGFR1) in EMT-polarized tumor cells. Pan-FGFR inhibitor NVP-BGJ398 (Infigratinib) reversed the SHHi-induced EMT marker expression and nuclear FGFR1 accumulation without compromising the enhanced permeability effect. Conclusion: This dual-hit strategy of SMO and FGFR inhibition provides a clinically-translatable approach to compromise the profound impermeability of PDAC tumors. Furthermore, clinical deployment of DW-MR imaging could fulfill the essential clinical-translational requirement for patient stratification.

     
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    Free, publicly-accessible full text available January 25, 2025
  2. Abstract

    The field of wireless communication has witnessed tremendous advancements in the past few decades, leading to more pervasive and ubiquitous networks. Human bodies are continually exposed to electromagnetic radiation, but typically this does not impact the body as the radiation is non-ionizing and the waves carry low power. However, with progress in the sixth generation (6G) of wireless networks and the adoption of the spectrum above 100 GHz in the next few years, higher power radiation is needed to cover larger areas, exposing humans to stronger and more prolonged radiation. Also, water has a high absorption coefficient at these frequencies and could lead to thermal effects on the skin. Hence, there is a need to study the radiation effects on human tissues, specifically the photothermal effects. In this paper, we present a custom-built, multi-physics model to investigate electromagnetic wave propagation in human tissue and study its subsequent photothermal effects. The proposed finite-element model consists of two segments—the first one estimates the intensity distribution along the beam path, while the second calculates the increase in temperature due to the wave distribution inside the tissue. We determine the intensity variation in the tissue using the radiative transfer equation and compare the results with Monte Carlo analysis and existing analytical models. The intensity information is then utilized to predict the rise in temperature with a bio-heat transfer module, powered by Pennes’ bioheat equation. The model is parametric, and we perform a systematic photothermal analysis to recognize the crucial variables responsible for the temperature growth inside the tissue, particularly for terahertz and near-infrared optical frequencies. Our numerical model can serve as a benchmark for studying the high-frequency radiation effects on complex heterogeneous media such as human tissue.

     
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  3. Free, publicly-accessible full text available September 20, 2024