A novel artificial intelligence-assisted "vascular healing" diagnosis for prediction of future clinical relapse in patients with ulcerative colitis: a prospective cohort study (with video).

BACKGROUND AND AIMS: Image-enhanced endoscopy has attracted attention as a method for detecting inflammation and predicting outcomes in patients with ulcerative colitis (UC); however, the procedure requires specialist endoscopists. Artificial intelligence (AI)-assisted image-enhanced endoscopy may help nonexperts provide objective accurate predictions with the use of optical imaging. We aimed to develop a novel AI-based system using 8853 images from 167 patients with UC to diagnose "vascular-healing" and establish the role of AI-based vascular-healing for predicting the outcomes of patients with UC. METHODS: This open-label prospective cohort study analyzed data for 104 patients with UC in clinical remission. Endoscopists performed colonoscopy using the AI system, which identified the target mucosa as AI-based vascular-active or vascular-healing. Mayo endoscopic subscore (MES), AI outputs, and histologic assessment were recorded for 6 colorectal segments from each patient. Patients were followed up for 12 months. Clinical relapse was defined as a partial Mayo score >2 RESULTS: The clinical relapse rate was significantly higher in the AI-based vascular-active group (23.9% [16/67]) compared with the AI-based vascular-healing group (3.0% [1/33)]; P = .01). In a subanalysis predicting clinical relapse in patients with MES ≤1, the area under the receiver operating characteristic curve for the combination of complete endoscopic remission and vascular healing (0.70) was increased compared with that for complete endoscopic remission alone (0.65). CONCLUSIONS: AI-based vascular-healing diagnosis system may potentially be used to provide more confidence to physicians to accurately identify patients in remission of UC who would likely relapse rather than remain stable.

Classically forbidden nonadiabatic transitions in multidimensional chemical dynamics.

An accurate method is proposed to deal with such nonadiabatic transitions as those energetically inaccessible, namely, classically forbidden transitions. This is formulated by using the corresponding Zhu-Nakamura formulas and finding the optimal paths in the classically forbidden tunneling regions that maximize the overall transition probabilities. This can be done for both the nonadiabatic tunneling type (so-called normal case in electron transfer) in which two diabatic potentials have opposite signs of slopes and the Landau-Zener type (inverted case) in which two diabatic potentials have the same sign of slopes. The method is numerically demonstrated to be useful for clarifying chemical and biological dynamics.

Cholestasis after Kasai operation predicts portal hypertension in native liver survivors of biliary atresia: a multicenter study.

PURPOSE: This study evaluated portal hypertension (PHT) and its predictors among native liver survivors (NLS) of biliary atresia (BA) after Kasai portoenterostomy (KPE). METHODS: This was a multicenter study using prospectively collected data. The subjects were patients who remained transplant-free for 5 years after KPE. Their status of PHT was evaluated and variables that predicted PHT were determined by regression analysis and receiver operating characteristic (ROC) curve. RESULTS: Six centers from East Asia participated in this study and 320 subjects with KPE between 1980 to 2018 were analyzed. The mean follow-up period was 10.6 ± 6.2 years. At the 5th year after KPE, PHT was found in 37.8% of the subjects (n = 121). Patients with KPE done before day 41 of life had the lowest percentage of PHT compared to operation at older age. At 12 months after KPE, PHT + ve subjects had a higher bilirubin level (27.1 ± 11.7 vs 12.3 ± 7.9 µmol/L, p = 0.000) and persistent jaundice conferred a higher risk for PHT (OR = 12.9 [9.2-15.4], p = 0.000). ROC analysis demonstrated that a bilirubin level above 38 µmol/L at 12 months after KPE predicted PHT development (sensitivity: 78%, specificity: 60%, AUROC: 0.75). CONCLUSIONS: In BA, early KPE protects against the development of PHT among NLSs. Patients with persistent cholestasis at one year after KPE are at a higher risk of this complication. They should receive a more vigilant follow-up. LEVEL OF EVIDENCE: Level III.

[Endovascular Repair of Aortic Injury Caused by Esophageal Foreign Body:Report of a Case].

A 51-year-old man visited to our hospital because of chest discomfort and hematemesis. He was diagnosed with Mallory-Weiss syndrome and followed in outpatient clinic. One week later, he visited our hospital again for fever and discomfort. Chest computed tomography (CT) showed a foreign body perforated in the mediastinum in the upper esophagus, and he was urgently hospitalized for surgical removal of esophageal foreign body. Before surgery he vomited the esophageal foreign body with a lot of blood. Hematemesis was stopped spontaneously and contrast-enhanced CT revealed a pseudoaneurysm in the distal aortic arch, so thoracic endovascular aortic repair (TEVAR) was performed to prevent rupture. Esophageal endoscopy found that the site of esophageal injury healed spontaneously, so the patient was followed conservatively with antibiotics. He was discharged on postoperative day 18 uneventfully. TEVAR was an effective treatment for aortic injury caused by esophageal foreign body in our case.

Suitable Promoter for DNA Vaccination Using a pDNA Ternary Complex.

In this study, we evaluated the effect of several promoters on the transfection activity and immune-induction efficiency of a plasmid DNA (pDNA)/polyethylenimine/γ-polyglutamic acid complex (pDNA ternary complex). Model pDNAs encoding firefly luciferase (Luc) were constructed with several promoters, such as simian virus 40 (SV40), eukaryotic elongation factor 1 alpha (EF1), cytomegalovirus (CMV), and chicken beta actin hybrid (CBh) (pSV40-Luc, pEF1-Luc, pCMV-Luc, and pCBh-Luc, respectively). Four types of pDNA ternary complexes, each with approximately 145-nm particle size and -30-mV ζ-potential, were stably constructed. The pDNA ternary complex containing pSV40-Luc showed low gene expression, but the other complexes containing pEF1-Luc, pCMV-Luc, and pCBh-Luc showed high gene expression in DC2.4 cells and spleen after intravenous administration. After immunization using various pDNA encoding ovalbumin (OVA) such as pEF1-OVA, pCMV-OVA, and pCBh-OVA, only the pDNA ternary complex containing pCBh-OVA showed significant anti-OVA immunoglobulin G (IgG) induction. In conclusion, our results showed that the CBh promoter is potentially suitable for use in pDNA ternary complex-based DNA vaccination.

In vitro study of the embolic characteristics of imipenem/cilastatin particles.

BACKGROUND: Imipenem/cilastatin (IPM/CS) has long been administered intravenously as a carbapenem antibiotic. However, since this agent is poorly soluble in liquid, occasional reports have described its use as a short-acting, temporary embolic agent. The purpose of this study was to elucidate the characteristics of IPM/CS particles, which are thought to have pain-relieving effects against osteoarthritis-related pain, as an embolic agent. METHODS: Three aspects of IPM/CS as an embolic agent were evaluated in vitro: particle size; particle shape; and change in particle size over time. For particle size, the long diameter was measured. RESULTS: Mean particle size (n=244) was 29.2±12.0 µm (range, 1-60 µm). Shape (n=109) was round in 18.35%, elliptical in 11.93%, and polygonal in 69.72%, showing that most particles were polygonal. In observations of changes in particle size over time (n=9), particles had decreased to 75% of their original size at 82±10.7 min, 50% at 89.3±9.14 min, 25% at 91.3±8.74 min, complete dissolved at 91.8±9.02 min. A rapid shrinkage in diameter was seen in the final period. CONCLUSIONS: IPM/CS particles are ultrafine and the majority display a polygonal shape. This substance shows ultra-short embolic activity. This study revealed the characteristics of a substance that demonstrates an embolic effect not found in existing embolic materials.

Artificial intelligence-assisted video colonoscopy for disease monitoring of ulcerative colitis: A prospective study.

BACKGROUNDS AND AIMS: The Mayo endoscopic subscore (MES) is the most popular endoscopic disease activity measure of ulcerative colitis (UC). Artificial intelligence (AI)-assisted colonoscopy is expected to reduce diagnostic variability among endoscopists. However, no study has been conducted to ascertain whether AI-based MES assignments can help predict clinical relapse, nor has AI been verified to improve the diagnostic performance of non-specialists. METHODS: This open-label, prospective cohort study enrolled 110 patients with UC in clinical remission. The AI algorithm was developed using 74713 images from 898 patients who underwent colonoscopy at three centers. Patients were followed up after colonoscopy for 12 months, and clinical relapse was defined as a partial Mayo score >2. A multi-video, multi-reader analysis involving 124 videos was conducted to determine whether the AI system reduced the diagnostic variability among six non-specialists. RESULTS: The clinical relapse rate for patients with AI-based MES = 1 (24.5% [12/49]) was significantly higher (log-rank test, P = 0.01) than that for patients with AI-based MES = 0 (3.2% [1/31]). Relapse occurred during the 12-month follow-up period in 16.2% (13/80) of patients with AI-based MES = 0 or 1 and 50.0% (10/20) of those with AI-based MES = 2 or 3 (log-rank test, P = 0.03). Using AI resulted in better inter- and intra-observer reproducibility than endoscopists alone. CONCLUSIONS: Colonoscopy using the AI-based MES system can stratify the risk of clinical relapse in patients with UC and improve the diagnostic performance of non-specialists.

Differentiation grade as a risk factor for lymph node metastasis in T1 colorectal cancer.

Objectives: Japanese guidelines include high-grade (poorly differentiated) tumors as a risk factor for lymph node metastasis (LNM) in T1 colorectal cancer (CRC). However, whether the grading is based on the least or most predominant component when the lesion consists of two or more levels of differentiation varies among institutions. This study aimed to investigate which method is optimal for assessing the risk of LNM in T1 CRC. Methods: We retrospectively evaluated 971 consecutive patients with T1 CRC who underwent initial or additional surgical resection from 2001 to 2021 at our institution. Tumor grading was divided into low-grade (well- to moderately differentiated) and high-grade based on the least or predominant differentiation analyses. We investigated the correlations between LNM and these two grading analyses. Results: LNM was present in 9.8% of patients. High-grade tumors, as determined by least differentiation analysis, accounted for 17.0%, compared to 0.8% identified by predominant differentiation analysis. A significant association with LNM was noted for the least differentiation method (p < 0.05), while no such association was found for predominant differentiation (p = 0.18). In multivariate logistic regression, grading based on least differentiation was an independent predictor of LNM (p = 0.04, odds ratio 1.68, 95% confidence interval 1.00-2.83). Sensitivity and specificity for detecting LNM were 27.4% and 84.1% for least differentiation, and 2.1% and 99.3% for predominant differentiation, respectively. Conclusions: Tumor grading via least differentiation analysis proved to be a more reliable measure for assessing LNM risk in T1 CRC compared to grading by predominant differentiation.