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Progression on therapy in non-small cell lung carcinoma (NSCLC) is often evaluated radiographically, however, image-based evaluation of said therapies may not distinguish disease progression due to intrinsic tumor drug resistance or inefficient tumor penetration of the drugs. Here we report that the inhibition of mutated EGFR promotes the secretion of a potent vasoconstrictor, endothelin-1 (EDN1), which continues to increase as the cells become resistant with a mesenchymal phenotype. As EDN1 and its receptor (EDNR) is linked to cancer progression, EDNR-antagonists have been evaluated in several clinical trials with disappointing results. These trials were based on a hypothesis that the EDN1-EDNR axis activates the MAPK-ERK signaling pathway that is vital to the cancer cell survival; the trials were not designed to evaluate the impact of tumor-derived EDN1 in modifying tumor microenvironment or contributing to drug resistance. Ectopic overexpression of EDN1 in cells with mutated EGFR resulted in poor drug delivery and retarded growth in vivo but not in vitro. Intratumoral injection of recombinant EDN significantly reduced blood flow and subsequent gefitinib accumulation in xenografted EGFR-mutant tumors. Furthermore, depletion of EDN1 or the use of endothelin receptor inhibitors bosentan and ambrisentan improved drug penetration into tumors and restored blood flow in tumor-associated vasculature. Correlatively, these results describe a simplistic endogenous yet previously unrealized resistance mechanism inherent to a subset of EGFR-mutant NSCLC to attenuate tyrosine kinase inhibitor delivery to the tumors by limiting drug-carrying blood flow and the drug concentration in tumors. SIGNIFICANCE: EDNR antagonists can be repurposed to improve drug delivery in VEGFA-secreting tumors, which normally respond to TKI treatment by secreting EDN1, promoting vasoconstriction, and limiting blood and drug delivery.

Background: Etiological classification of ischemic stroke is fundamental for secondary prevention, but frequently results in undetermined cause. We aimed to develop a Deep Learning (DL)-based model for automatic etiological classification of ischemic stroke using digital images of thrombi retrieved by mechanical thrombectomy. Methods: Patients with large vessel occlusion stroke subjected to mechanical thrombectomy between April 2016 and January 2023 at La Fe University and Polytechnic Hospital in Valencia were included. Thrombus digital images were obtained and clinical characteristics, including TOAST etiological classification as reference standard, were retrieved. Statistical analysis was performed to compare clinical characteristics between atherothrombotic and cardioembolic strokes. A DL method was designed based on two deep neural networks for: (1) image segmentation and (2) image classification including clinical characteristics. The metrics used were DICE coefficient for the segmentation network, and accuracy, precision, sensitivity, specificity and area under the curve (AUC) for the predictions of the classification network. Results: A total of 166 patients (mean age 69 [SD, 13], 67 female) were included. TOAST classification was: 31 atherothrombotic, 87 cardioembolic, and 48 cryptogenic. The segmentation network achieved an average DICE coefficient of 0.96 [SD, 0.13]. The optimal fused imaging and clinical classification network had a 0.968 accuracy [95% CI, 0.935–0.994], and AUC of 0.947 [95% CI, 0.870–1]. Cryptogenic thrombi were classified as cardioembolic (96%) or atherothrombotic (4%). Conclusion: Two convolutional neural networks perform the automatic segmentation of thrombus images and, combined with selected clinical characteristics, their accurate and precise classification into atherothrombotic or cardioembolic etiology in patients with acute ischemic stroke. [ABSTRACT FROM AUTHOR]

The momentum of the Fourth Industrial Revolution is driving increased demand for certain specific metals. These include copper, silver, gold, and platinum group metals (PGMs), which have important applications in renewable energies, green hydrogen, and electronic products. However, the continuous extraction of these metals is leading to a rapid decline in their ore grades and, consequently, increasing the environmental impact of extraction. Hence, obtaining metals from secondary sources, such as waste electrical and electronic equipment (WEEE), has become imperative for both environmental sustainability and ensuring their availability. To evaluate the sustainability of the process, this paper proposes using an exergy approach, which enables appropriate allocation among co-products, as well as the assessment of exergy losses and the use of non-renewable resources. As a case study, this paper analyzes the recycling process of waste printed circuit boards (PCBs) by disaggregating the exergy cost into renewable and non-renewable sources, employing different exergy-based cost allocation methods for the mentioned metals. It further considers the complete life cycle of metals using the Circular Thermoeconomics methodology. The results show that, when considering the entire life cycle, between 47% and 53% of the non-renewable exergy is destroyed during recycling. Therefore, delaying recycling as much as possible would be the most desirable option for minimizing the use of non-renewable resources. [ABSTRACT FROM AUTHOR]

ApTOLL, a TLR4 modulator aptamer, has demonstrated cerebroprotective effects in a permanent ischemic stroke mouse model, as well as safety and efficacy in early phase clinical trials. We carried out reverse translation research according to STAIR recommendations to further characterize the effects and mechanisms of ApTOLL after transient ischemic stroke in rats and to better inform the design of pivotal clinical trials. Adult male rats subjected to transient middle cerebral artery occlusion were treated either with ApTOLL or the vehicle intravenously at different doses and time-points. ApTOLL was compared with TAK-242 (a TLR4 inhibitor). Female rats were also studied. After neurofunctional evaluation, brains were removed for infarct/edema volume, hemorrhagic transformation, and histologic determinations. Peripheral leukocyte populations were assessed via flow cytometry. ApTOLL showed U-shaped dose-dependent cerebroprotective effects. The maximum effective dose (0.45 mg/kg) was cerebroprotective when given both before reperfusion and up to 12 h after reperfusion and reduced the hemorrhagic risk. Similar effects occurred in female rats. Both research and clinical ApTOLL batches induced slightly superior cerebroprotection when compared with TAK-242. Finally, ApTOLL modulated circulating leukocyte levels, reached the brain ischemic tissue to bind resident and infiltrated cell types, and reduced the neutrophil density. These results show the cerebroprotective effects of ApTOLL in ischemic stroke by reducing the infarct/edema volume, neurofunctional impairment, and hemorrhagic risk, as well as the peripheral and local immune response. They provide information about ApTOLL dose effects and its therapeutic time window and target population, as well as its mode of action, which should be considered in the design of pivotal clinical trials. [ABSTRACT FROM AUTHOR]