Reactive oxygen species in endothelial signaling in COVID-19: Protective role of the novel peptide PIP-2.

INTRODUCTION: Recent research suggests that endothelial activation plays a role in coronavirus disease 2019 (COVID-19) pathogenesis by promoting a pro-inflammatory state. However, the mechanism by which the endothelium is activated in COVID-19 remains unclear. OBJECTIVE: To investigate the mechanism by which COVID-19 activates the pulmonary endothelium and drives pro-inflammatory phenotypes. HYPOTHESIS: The "inflammatory load or burden" (cytokine storm) of the systemic circulation activates endothelial NADPH oxidase 2 (NOX2) which leads to the production of reactive oxygen species (ROS) by the pulmonary endothelium. Endothelial ROS subsequently activates pro-inflammatory pathways. METHODS: The inflammatory burden of COVID-19 on the endothelial network, was recreated in vitro, by exposing human pulmonary microvascular endothelial cells (HPMVEC) to media supplemented with serum from COVID-19 affected individuals (sera were acquired from patients with COVID-19 infection that eventually died. Sera was isolated from blood collected at admission to the Intensive Care Unit of the Hospital of the University of Pennsylvania). Endothelial activation, inflammation and cell death were assessed in HPMVEC treated with serum either from patients with COVID-19 or from healthy individuals. Activation was monitored by measuring NOX2 activation (Rac1 translocation) and ROS production; inflammation (or appearance of a pro-inflammatory phenotype) was monitored by measuring the induction of moieties such as intercellular adhesion molecule (ICAM-1), P-selectin and the NLRP3 inflammasome; cell death was measured via SYTOX™ Green assays. RESULTS: Endothelial activation (i.e., NOX2 activation and subsequent ROS production) and cell death were significantly higher in the COVID-19 model than in healthy samples. When HPMVEC were pre-treated with the novel peptide PIP-2, which blocks NOX2 activation (via inhibition of Ca2+-independent phospholipase A2, aiPLA2), significant abrogation of ROS was observed. Endothelial inflammation and cell death were also significantly blunted. CONCLUSIONS: The endothelium is activated during COVID-19 via cytokine storm-driven NOX2-ROS activation, which causes a pro-inflammatory phenotype. The concept of endothelial NOX2-ROS production as a unifying pathophysiological axis in COVID-19 raises the possibility of using PIP-2 to maintain vascular health.

Deep learning segmentation of mandible with lower dentition from cone beam CT.

OBJECTIVES: This study aimed to train a 3D U-Net convolutional neural network (CNN) for mandible and lower dentition segmentation from cone-beam computed tomography (CBCT) scans. METHODS: In an ambispective cross-sectional design, CBCT scans from two hospitals (2009-2019 and 2021-2022) constituted an internal dataset and external validation set, respectively. Manual segmentation informed CNN training, and evaluations employed Dice similarity coefficient (DSC) for volumetric accuracy. A blinded oral maxillofacial surgeon performed qualitative grading of CBCT scans and object meshes. Statistical analyses included independent t-tests and ANOVA tests to compare DSC across patient subgroups of gender, race, body mass index (BMI), test dataset used, age, and degree of metal artifact. Tests were powered for a minimum detectable difference in DSC of 0.025, with alpha of 0.05 and power level of 0.8. RESULTS: 648 CBCT scans from 490 patients were included in the study. The CNN achieved high accuracy (average DSC: 0.945 internal, 0.940 external). No DSC differences were observed between test set used, gender, BMI, and race. Significant differences in DSC were identified based on age group and the degree of metal artifact. The majority (80%) of object meshes produced by both manual and automatic segmentation were rated as acceptable or higher quality. CONCLUSION: We developed a model for automatic mandible and lower dentition segmentation from CBCT scans in a demographically diverse cohort including a high degree of metal artifacts. The model demonstrated good accuracy on internal and external test sets, with majority acceptable quality from a clinical grader.

Virtual Growing Child (VGC): A general normative comparative system via quantitative dynamic MRI for quantifying pediatric regional respiratory anomalies with application in thoracic insufficiency syndrome (TIS).

Background: A normative database of regional respiratory structure and function in healthy children does not exist. Methods: VGC provides a database with four categories of regional respiratory measurement parameters including morphological, architectural, dynamic, and developmental. The database has 3,820 3D segmentations (around 100,000 2D slices with segmentations). Age and gender group analysis and comparisons for healthy children were performed using those parameters via two-sided t-testing to compare mean measurements, for left and right sides at end-inspiration (EI) and end-expiration (EE), for different age and gender specific groups. We also apply VGC measurements for comparison with TIS patients via an extrapolation approach to estimate the association between measurement and age via a linear model and to predict measurements for TIS patients. Furthermore, we check the Mahalanobis distance between TIS patients and healthy children of corresponding age. Findings: The difference between male and female groups (10-12 years) behave differently from that in other age groups which is consistent with physiology/natural growth behavior related to adolescence with higher right lung and right diaphragm tidal volumes for females(p<0.05). The comparison of TIS patients before and after surgery show that the right and left components are not symmetrical, and the left side diaphragm height and tidal volume has been significantly improved after surgery (p <0.05). The left lung volume at EE, and left diaphragm height at EI of TIS patients after surgery are closer to the normal children with a significant smaller Mahalanobis distance (MD) after surgery (p<0.05). Interpretation: The VGC system can serve as a reference standard to quantify regional respiratory abnormalities on dMRI in young patients with various respiratory conditions and facilitate treatment planning and response assessment. Funding: The grant R01HL150147 from the National Institutes of Health (PI Udupa).

Characterizing Lung Parenchymal Aeration via Standardized Signal Intensity from Free-breathing 4D Dynamic MRI in Phantoms, Healthy Children, and Pediatric Patients with Thoracic Insufficiency Syndrome.

Purpose To investigate free-breathing thoracic bright-blood four-dimensional (4D) dynamic MRI (dMRI) to characterize aeration of parenchymal lung tissue in healthy children and patients with thoracic insufficiency syndrome (TIS). Materials and Methods All dMR images in patients with TIS were collected from July 2009 to June 2017. Standardized signal intensity (sSI) was investigated, first using a lung aeration phantom to establish feasibility and sensitivity and then in a retrospective research study of 40 healthy children (16 male, 24 female; mean age, 9.6 years ± 2.1 [SD]), 20 patients with TIS before and after surgery (11 male, nine female; mean age, 6.2 years ± 4.2), and another 10 healthy children who underwent repeated dMRI examinations (seven male, three female; mean age, 9 years ± 3.6). Individual lungs in 4D dMR images were segmented, and sSI was assessed for each lung at end expiration (EE), at end inspiration (EI), preoperatively, postoperatively, in comparison to normal lungs, and in repeated scans. Results Air content changes of approximately 6% were detectable in phantoms via sSI. sSI within phantoms significantly correlated with air occupation (Pearson correlation coefficient = -0.96 [P < .001]). For healthy children, right lung sSI was significantly lower than that of left lung sSI (at EE: 41 ± 6 vs 47 ± 6 and at EI: 39 ± 6 vs 43 ± 7, respectively; P < .001), lung sSI at EI was significantly lower than that at EE (P < .001), and left lung sSI at EE linearly decreased with age (r = -0.82). Lung sSI at EE and EI decreased after surgery for patients (although not statistically significantly, with P values of sSI before surgery vs sSI after surgery, left and right lung separately, in the range of 0.13-0.51). sSI varied within 1.6%-4.7% between repeated scans. Conclusion This study demonstrates the feasibility of detecting change in sSI in phantoms via bright-blood dMRI when air occupancy changes. The observed reduction in average lung sSI after surgery in pediatric patients with TIS may indicate postoperative improvement in parenchymal aeration. Keywords: MR Imaging, Thorax, Lung, Pediatrics, Thoracic Surgery, Lung Parenchymal Aeration, Free-breathing Dynamic MRI, MRI Intensity Standardization, Thoracic Insufficiency Syndrome Supplemental material is available for this article. © RSNA, 2024.