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1. Binge Drinking Decreases Corticotropin‐Releasing Factor‐Binding Protein Expression in the Medial Prefrontal Cortex of Mice

   https://doi.org/10.1111/acer.13119  

   Ketchesin, Kyle D. ; Stinnett, Gwen S. ; Seasholtz, Audrey F. ( July 2016 , Alcoholism: Clinical and Experimental Research)

   Dysregulation of the corticotropin‐releasing factor (CRF) system has been observed in rodent models of binge drinking, with a large focus onCRFreceptor 1 (CRF‐R1). The role ofCRF‐binding protein (CRF‐BP), a key regulator ofCRFactivity, in binge drinking is less well understood. In humans, single‐nucleotide polymorphisms inCRHBPare associated with alcohol use disorder and stress‐induced alcohol craving, suggesting a role forCRF‐BPin vulnerability to alcohol addiction.

   The role and regulation ofCRF‐BPin binge drinking were examined in mice exposed to the drinking in the dark (DID) paradigm. Using in situ hybridization, the regulation ofCRF‐BP,CRF‐R1, andCRFmRNAexpression was determined in the stress and reward systems of C57BL/6J mice after repeated cycles ofDID. To determine the functional role ofCRF‐BPin binge drinking,CRF‐BPknockout (CRF‐BP KO) mice were exposed to 6 cycles ofDID, during which alcohol consumption was measured and compared to wild‐type mice.

   CRF‐BPmRNAexpression was significantly decreased in the prelimbic (PL) and infralimbic medial prefrontal cortex (mPFC) of C57BL/6J mice after 3 cycles and in thePLmPFCafter 6 cycles ofDID. No significant changes inCRForCRF‐R1 mRNAlevels were observed in mPFC, ventral tegmental area, bed nucleus of the stria terminalis, or amygdala after 3 cycles ofDID.CRF‐BP KOmice do not show significant alterations in drinking compared to wild‐type mice across 6 cycles of DID.

   These results reveal that repeated cycles of binge drinking alterCRF‐BPmRNAexpression in the mPFC, a region responsible for executive function and regulation of emotion and behavior, including responses to stress. We observed a persistent decrease inCRF‐BPmRNAexpression in the mPFCafter 3 and 6DIDcycles, which may allow for increasedCRFsignaling atCRF‐R1 and contribute to excessive binge‐like ethanol consumption.

    

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2. Acoustic metamaterials-driven transdermal drug delivery for rapid and on-demand management of acute disease

   https://doi.org/10.1038/s41467-023-36581-2  

   Xu, Junhua ; Cai, Hongwei ; Wu, Zhuhao ; Li, Xiang ; Tian, Chunhui ; Ao, Zheng ; Niu, Vivian C. ; Xiao, Xiao ; Jiang, Lei ; Khodoun, Marat ; et al ( February 2023 , Nature Communications)

   Transdermal drug delivery provides convenient and pain-free self-administration for personalized therapy. However, challenges remain in treating acute diseases mainly due to their inability to timely administrate therapeutics and precisely regulate pharmacokinetics within a short time window. Here we report the development of active acoustic metamaterials-driven transdermal drug delivery for rapid and on-demand acute disease management. Through the integration of active acoustic metamaterials, a compact therapeutic patch is integrated for penetration of skin stratum corneum and active percutaneous transport of therapeutics with precise control of dose and rate over time. Moreover, the patch device quantitatively regulates the dosage and release kinetics of therapeutics and achieves better delivery performance in vivo than through subcutaneous injection. As a proof-of-concept application, we show our method can reverse life-threatening acute allergic reactions in a female mouse model of anaphylaxis via a multi-burst delivery of epinephrine, showing better efficacy than a fixed dosage injection of epinephrine, which is the current gold standard ‘self-injectable epinephrine’ strategy. This innovative method may provide a promising means to manage acute disease for personalized medicine.

    

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3. Assessing combined effects of varenicline and N ‐acetylcysteine on reducing nicotine seeking in rats

   https://doi.org/10.1111/adb.13151  

   Nall, Rusty W. ; Beloate, Lauren N. ; Meyerink, Michael E. ; Penaloza, Tiffany ; Doolittle, Jade ; Froeliger, Brett ; Kalivas, Peter W. ; Garcia‐Keller, Constanza ( February 2022 , Addiction Biology)

   Nicotine addiction is a chronic relapsing brain disorder, and cigarette smoking is the leading cause of preventable death in the United States. Currently, the most effective pharmacotherapy for smoking cessation is Varenicline (VRN), which reduces both positive and negative reinforcement by nicotine. Clinically, VRN attenuates withdrawal symptoms and promotes abstinence, but >50% of smokers relapse within 3 months following a quit attempt. This may indicate that VRN fails to ameliorate components of nicotine‐induced neuroplasticity that promote relapse vulnerability. Animal models reveal that glutamate dysregulation in the nucleus accumbens is associated with nicotine relapse. N‐acetylcysteine (NAC) normalizes glutamate transmission and prolongs cocaine abstinence. Thus, combining VRN and NAC may promote and maintain, respectively, nicotine abstinence. In rats, we found that VRN effectively reduced nicotine self‐administration and seeking in early abstinence, but not seeking later in abstinence. In contrast, NAC reduced seeking only later in abstinence. Because VRN and NAC are sometimes associated with mild adverse effects, we also evaluated a sequential approach combining subthreshold doses of VRN during self‐administration and early abstinence with subthreshold doses of NAC during late abstinence. As expected, subthreshold VRN did not reduce nicotine intake. However, subthreshold VRN and NAC reduced seeking in late abstinence, suggesting a combined effect. Overall, our results suggest that combining subthreshold VRN and NAC is a viable and drug‐specific approach to promote abstinence and reduce relapse while minimizing adverse effects. Our data also suggest that different components and time points in addiction engage the different neurocircuits targeted by VRN and NAC.

    

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4. Measuring dissolution profiles of single controlled-release drug pellets

   https://doi.org/10.1038/s41598-020-76089-z  

   Bhakta, Heran C. ; Lin, Jessica M. ; Grover, William H. ( November 2020 , Scientific Reports)

   Many solid-dose oral drug products are engineered to release their active ingredients into the body at a certain rate. Techniques for measuring the dissolution or degradation of a drug product in vitro play a crucial role in predicting how a drug product will perform in vivo. However, existing techniques are often labor-intensive, time-consuming, irreproducible, require specialized analytical equipment, and provide only “snapshots” of drug dissolution every few minutes. These limitations make it difficult for pharmaceutical companies to obtain full dissolution profiles for drug products in a variety of different conditions, as recommended by the US Food and Drug Administration. Additionally, for drug dosage forms containing multiple controlled-release pellets, particles, beads, granules, etc. in a single capsule or tablet, measurements of the dissolution of the entire multi-particle capsule or tablet are incapable of detecting pellet-to-pellet variations in controlled release behavior. In this work, we demonstrate a simple and fully-automated technique for obtaining dissolution profiles from single controlled-release pellets. We accomplished this by inverting the drug dissolution problem: instead of measuring the increase in the concentration of drug compounds in the solution during dissolution (as is commonly done), we monitor the decrease in the buoyant mass of the solid controlled-release pellet as it dissolves. We weigh single controlled-release pellets in fluid using a vibrating tube sensor, a piece of glass tubing bent into a tuning-fork shape and filled with any desired fluid. An electronic circuit keeps the glass tube vibrating at its resonance frequency, which is inversely proportional to the mass of the tube and its contents. When a pellet flows through the tube, the resonance frequency briefly changes by an amount that is inversely proportional to the buoyant mass of the pellet. By passing the pellet back-and-forth through the vibrating tube sensor, we can monitor its mass as it degrades or dissolves, with high temporal resolution (measurements every few seconds) and mass resolution (700 nanogram resolution). As a proof-of-concept, we used this technique to measure the single-pellet dissolution profiles of several commercial controlled-release proton pump inhibitors in simulated stomach and intestinal contents, as well as comparing name-brand and generic formulations of the same drug. In each case, vibrating tube sensor data revealed significantly different dissolution profiles for the different drugs, and in some cases our method also revealed differences between different pellets from the same drug product. By measuring any controlled-release pellets, particles, beads, or granules in any physiologically-relevant environment in a fully-automated fashion, this method can augment and potentially replace current dissolution tests and support product development and quality assurance in the pharmaceutical industry.

    

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5. Investigation of autosegmentation techniques on T2‐weighted MRI for off‐line dose reconstruction in MR‐linac workflow for head and neck cancers

   https://doi.org/10.1002/mp.16582  

   McDonald, Brigid A. ; Cardenas, Carlos E. ; O'Connell, Nicolette ; Ahmed, Sara ; Naser, Mohamed A. ; Wahid, Kareem A. ; Xu, Jiaofeng ; Thill, Dan ; Zuhour, Raed J. ; Mesko, Shane ; et al ( July 2023 , Medical Physics)

   In order to accurately accumulate delivered dose for head and neck cancer patients treated with the Adapt to Position workflow on the 1.5T magnetic resonance imaging (MRI)‐linear accelerator (MR‐linac), the low‐resolution T2‐weighted MRIs used for daily setup must be segmented to enable reconstruction of the delivered dose at each fraction.

   In this pilot study, we evaluate various autosegmentation methods for head and neck organs at risk (OARs) on on‐board setup MRIs from the MR‐linac for off‐line reconstruction of delivered dose.

   Seven OARs (parotid glands, submandibular glands, mandible, spinal cord, and brainstem) were contoured on 43 images by seven observers each. Ground truth contours were generated using a simultaneous truth and performance level estimation (STAPLE) algorithm. Twenty total autosegmentation methods were evaluated in ADMIRE: 1–9) atlas‐based autosegmentation using a population atlas library (PAL) of 5/10/15 patients with STAPLE, patch fusion (PF), random forest (RF) for label fusion; 10–19) autosegmentation using images from a patient's 1–4 prior fractions (individualized patient prior [IPP]) using STAPLE/PF/RF; 20) deep learning (DL) (3D ResUNet trained on 43 ground truth structure sets plus 45 contoured by one observer). Execution time was measured for each method. Autosegmented structures were compared to ground truth structures using the Dice similarity coefficient, mean surface distance (MSD), Hausdorff distance (HD), and Jaccard index (JI). For each metric and OAR, performance was compared to the inter‐observer variability using Dunn's test with control. Methods were compared pairwise using the Steel‐Dwass test for each metric pooled across all OARs. Further dosimetric analysis was performed on three high‐performing autosegmentation methods (DL, IPP with RF and 4 fractions [IPP_RF_4], IPP with 1 fraction [IPP_1]), and one low‐performing (PAL with STAPLE and 5 atlases [PAL_ST_5]). For five patients, delivered doses from clinical plans were recalculated on setup images with ground truth and autosegmented structure sets. Differences in maximum and mean dose to each structure between the ground truth and autosegmented structures were calculated and correlated with geometric metrics.

   DL and IPP methods performed best overall, all significantly outperforming inter‐observer variability and with no significant difference between methods in pairwise comparison. PAL methods performed worst overall; most were not significantly different from the inter‐observer variability or from each other. DL was the fastest method (33 s per case) and PAL methods the slowest (3.7–13.8 min per case). Execution time increased with a number of prior fractions/atlases for IPP and PAL. For DL, IPP_1, and IPP_RF_4, the majority (95%) of dose differences were within ± 250 cGy from ground truth, but outlier differences up to 785 cGy occurred. Dose differences were much higher for PAL_ST_5, with outlier differences up to 1920 cGy. Dose differences showed weak but significant correlations with all geometric metrics (R2 between 0.030 and 0.314).

   The autosegmentation methods offering the best combination of performance and execution time are DL and IPP_1. Dose reconstruction on on‐board T2‐weighted MRIs is feasible with autosegmented structures with minimal dosimetric variation from ground truth, but contours should be visually inspected prior to dose reconstruction in an end‐to‐end dose accumulation workflow.

    

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