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Background: In the case of an unresectable malignant hilar biliary obstruction (MHBO), the optimal drainage method has not yet been established. Recently, an 8 mm, fully covered, self-expandable metal stent (FCSEMS) with an ultra-slim introducer has become available. In this article, the results of whole-liver drainage tests using this novel FCSEMS for MHBO are reported. Methods: Unresectable MHBOs up to Bismuth IIIa with strictures limited to the secondary branches were eligible. The proximal end of the stent was placed in such a way as to avoid blocking the side branches, and the distal end was placed above the papilla when possible. Consecutive patients treated between April 2017 and January 2021 were retrospectively analyzed. The technical and functional success rates, rates and causes of recurrent biliary obstruction (RBO), time to RBO (TRBO), revision for RBO, and adverse events (AEs) were evaluated. Results: Eleven patients (Bismuth I/II/IIIa: 1/7/3) were enrolled. Two stents were placed in nine patients and three were placed in two patients. Both the technical and functional success rates were 100%. RBO occurred in four (36%) patients due to sludge formation. Revision was performed for three patients, with the successful removal of all stents. The median TRBO was 187 days, and no late AEs other than the RBO occurred. Regarding the distal position of the stent, the RBO rate was significantly lower (14.3% vs. 75%, p = 0.041) and the cumulative TRBO was significantly longer (median TRBO: not reached vs. 80 days, p = 0.031) in the case of the placement above the papilla than the placement across the papilla. Conclusion: For unresectable MHBOs of Bismuth I, II, and IIIa, whole-liver drainage with a novel 8 mm FCSEMS possessing an ultra-slim introducer was feasible and potentially safe, with favorable stent patency. Placement above the papilla might be preferrable to placement across the papilla.

Background: Endoscopic-ultrasound-guided gastrojejunostomy (EUS-GJ) can be a new alternative for patients with malignant afferent loop syndrome (MALS). However, a fully covered self-expandable metal stent (FCSEMS) has not been well investigated in this setting. Methods: This is a multicenter retrospective cohort study. Consecutive patients that underwent EUS-GJ using a FCSEMS for MALS between April 2017 and November 2022 were enrolled. Primary outcomes were technical and clinical success rates. Secondary outcomes were adverse events, recurrent symptoms, and overall survival. Results: Twelve patients (median age: 67.5 years (interquartile range: 58–74.8); 50% male) were included. The most common primary disease and type of previous surgery were pancreatic cancer (67%) and pancreatoduodenectomy (75%), respectively. Technical success and clinical success were achieved in all patients. Procedure-related adverse events occurred in one patient (8%) with mild peritonitis. During a median follow-up of 96.5 days, one patient (8%) had recurrent symptoms due to the EUS-GJ stent dysfunction; including biliary events unrelated to the EUS-GJ stent, five patients (42%) had recurrent events. The median overall survival was 137 days. Nine patients (75%) died due to disease progression. Conclusions: EUS-GJ with a FCSEMS seems safe and effective for MALS with high technical and clinical success rates and an acceptable recurrence rate.

Currently, endoscopic ultrasound-guided hepaticogastrostomy (EUS-HGS) is widely performed worldwide for various benign and malignant biliary diseases in cases of difficult or unsuccessful endoscopic transpapillary cholangiopancreatography (ERCP). Furthermore, its applicability as primary drainage has also been reported. Although recent advances in EUS systems and equipment have made EUS-HGS easier and safer, the risk of serious adverse events such as bile leak and stent migration still exists. Physicians and assistants need not only sufficient skills and experience in ERCP-related procedures and basic EUS-related procedures such as fine needle aspiration and pancreatic fluid collection drainage, but also knowledge and techniques specific to EUS-HGS. This technical review mainly focuses on EUS-HGS with self-expandable metal stents for unresectable malignant biliary obstruction and presents the latest and detailed tips for safe and successful performance of the technique.

Dysfunctional dopamine signaling is implicated in various neuropsychological disorders. Previously, we reported that dopamine increases D1 receptor (D1R)-expressing medium spiny neuron (MSN) excitability and firing rates in the nucleus accumbens (NAc) via the PKA/Rap1/ERK pathway to promote reward behavior. Here, the results show that the D1R agonist, SKF81297, inhibits KCNQ-mediated currents and increases D1R-MSN firing rates in murine NAc slices, which is abolished by ERK inhibition. In vitro ERK phosphorylates KCNQ2 at Ser414 and Ser476; in vivo, KCNQ2 is phosphorylated downstream of dopamine signaling in NAc slices. Conditional deletion of Kcnq2 in D1R-MSNs reduces the inhibitory effect of SKF81297 on KCNQ channel activity, while enhancing neuronal excitability and cocaine-induced reward behavior. These effects are restored by wild-type, but not phospho-deficient KCNQ2. Hence, D1R-ERK signaling controls MSN excitability via KCNQ2 phosphorylation to regulate reward behavior, making KCNQ2 a potential therapeutical target for psychiatric diseases with a dysfunctional reward circuit.

Endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) is a valid modality for nodal lung cancer staging. The sonographic features of EBUS helps determine suspicious lymph nodes (LNs). To facilitate this use of this method, machine-learning-based computer-aided diagnosis (CAD) of medical imaging has been introduced in clinical practice. This study investigated the feasibility of CAD for the prediction of nodal metastasis in lung cancer using endobronchial ultrasound images. Image data of patients who underwent EBUS-TBNA were collected from a video clip. Xception was used as a convolutional neural network to predict the nodal metastasis of lung cancer. The prediction accuracy of nodal metastasis through deep learning (DL) was evaluated using both the five-fold cross-validation and hold-out methods. Eighty percent of the collected images were used in five-fold cross-validation, and all the images were used for the hold-out method. Ninety-one patients (166 LNs) were enrolled in this study. A total of 5255 and 6444 extracted images from the video clip were analyzed using the five-fold cross-validation and hold-out methods, respectively. The prediction of LN metastasis by CAD using EBUS images showed high diagnostic accuracy with high specificity. CAD during EBUS-TBNA may help improve the diagnostic efficiency and reduce invasiveness of the procedure.