PARP1-targeted fluorescence molecular endoscopy as novel tool for early detection of esophageal dysplasia and adenocarcinoma.

BACKGROUND: Esophageal cancer is one of the 10 most common cancers worldwide and its incidence is dramatically increasing. Despite some improvements, the current surveillance protocol with white light endoscopy and random untargeted biopsies collection (Seattle protocol) fails to diagnose dysplastic and cancerous lesions in up to 50% of patients. Therefore, new endoscopic imaging technologies in combination with tumor-specific molecular probes are needed to improve early detection. Herein, we investigated the use of the fluorescent Poly (ADP-ribose) Polymerase 1 (PARP1)-inhibitor PARPi-FL for early detection of dysplastic lesions in patient-derived organoids and transgenic mouse models, which closely mimic the transformation from non-malignant Barrett's Esophagus (BE) to invasive esophageal adenocarcinoma (EAC). METHODS: We determined PARP1 expression via immunohistochemistry (IHC) in human biospecimens and mouse tissues. We also assessed PARPi-FL uptake in patient- and mouse-derived organoids. Following intravenous injection of 75 nmol PARPi-FL/mouse in L2-IL1B (n = 4) and L2-IL1B/IL8Tg mice (n = 12), we conducted fluorescence molecular endoscopy (FME) and/or imaged whole excised stomachs to assess PARPi-FL accumulation in dysplastic lesions. L2-IL1B/IL8Tg mice (n = 3) and wild-type (WT) mice (n = 2) without PARPi-FL injection served as controls. The imaging results were validated by confocal microscopy and IHC of excised tissues. RESULTS: IHC on patient and murine tissue revealed similar patterns of increasing PARP1 expression in presence of dysplasia and cancer. In human and murine organoids, PARPi-FL localized to PARP1-expressing epithelial cell nuclei after 10 min of incubation. Injection of PARPi-FL in transgenic mouse models of BE resulted in the successful detection of lesions via FME, with a mean target-to-background ratio > 2 independently from the disease stage. The localization of PARPi-FL in the lesions was confirmed by imaging of the excised stomachs and confocal microscopy. Without PARPi-FL injection, identification of lesions via FME in transgenic mice was not possible. CONCLUSION: PARPi-FL imaging is a promising approach for clinically needed improved detection of dysplastic and malignant EAC lesions in patients with BE. Since PARPi-FL is currently evaluated in a phase 2 clinical trial for oral cancer detection after topical application, clinical translation for early detection of dysplasia and EAC in BE patients via FME screening appears feasible.

Framework for Armature-Based 3D Shape Reconstruction of Sensorized Soft Robots in eXtended Reality.

Soft robots are typically intended to operate in highly unpredictable and unstructured environments. Although their soft bodies help them to passively conform to their environment, the execution of specific tasks within such environments often requires the help of an operator that supervises the interaction between the robot and its environment and adjusts the actuation inputs in order to successfully execute the task. However, direct observation of the soft robot is often impeded by the environment in which it operates. Therefore, the operator has to depend on a real-time simulation of the soft robot based on the signals from proprioceptive sensors. However, the complicated three-dimensional (3D) configurations of the soft robot can be difficult to interpret using traditional visualization techniques. In this work, we present an open-source framework for real-time 3D reconstruction of soft robots in eXtended Reality (Augmented and Virtual Reality), based on signals from their proprioceptive sensors. This framework has a Robot Operating System (ROS) backbone, allowing for easy integration with existing soft robot control algorithms for intuitive and real-time teleoperation. This approach is demonstrated in Augmented Reality using a Microsoft Hololens device and runs at up to 60 FPS. We explore the influence that system parameters such as mesh density and armature complexity have on the reconstruction's key performance metrics (i.e., speed, scalability). The open-source framework is expected to function as a platform for future research and developments on real-time remote control of soft robots operating in environments that impede direct observation of the robot.