A new neural network model that detects graft ruptures and contralateral anterior cruciate ligament injuries.

PURPOSE: The purpose of this study was to develop a neural network model for predicting second anterior cruciate ligament (ACL) injury risk following ACL reconstruction using patient features from medical records. METHODS: Of 486 consecutive patients who underwent primary unilateral ACL reconstruction, 386 patients (198 women, 188 men) with a mean age of 25.1 ± 11.6 years were included in this study. Fifty-eight features, including demographic data, surgical, preoperative and postoperative data, were retrospectively collected from medical records, and features with an incidence of less than 5% were excluded. Finally, 14 features were used for the analysis. The multilayer perceptron was composed of four hidden layers with a rectified linear unit as activation and was trained to maximise the area under the receiver-operating characteristic curve (auROC). Subsequently, validation was carried out through a rigorous threefold cross-validation process. To ascertain the most efficacious combination of features with the highest auROC, a single feature with the least impact on auROC maximisation was systematically eliminated from the comprehensive variable set, ultimately resulting in the retention of a mere two variables. RESULTS: The median follow-up period was 50.5 (24-142) months. Fifty-seven knees had a second ACL injury, with a graft rupture rate of 7.7% and a contralateral injury rate of 6.9%. The maximum auROC for predicting graft rupture was 0.81 with two features: young age and hamstring graft. Meanwhile, the maximum auROC for predicting contralateral ACL injury was 0.74 with seven features, including young age, presence of medial meniscus tear, small body mass index, hamstring graft, female sex and medial meniscus repair or treatment. CONCLUSION: A neural network model with patient features from medical records detected graft ruptures and contralateral ACL injuries with acceptable accuracy. This model can serve as a new, useful tool in clinical practice to inform decisions about ACL reconstruction and retuning to sports postoperatively. LEVEL OF EVIDENCE: Level IV.

Berotralstat for long-term prophylaxis of hereditary angioedema in Japan: Parts 2 and 3 of the randomized APeX-J Phase III trial.

Background: Berotralstat is a once-daily oral inhibitor of plasma kallikrein for the prophylaxis of hereditary angioedema (HAE) in patients ≥12 years. APeX-J aimed to evaluate the efficacy and safety of berotralstat in Japan. Methods: APeX-J was a Phase III trial comprising 3 parts (NCT03873116). Part 1 was a randomized, placebo-controlled evaluation of berotralstat 150 or 110 mg over 24 weeks. Part 2 was a 28-week dose-blinded phase in which berotralstat-treated patients continued the same dose and placebo patients were re-randomized to berotralstat 150 or 110 mg. In Part 3, all patients remaining on study received berotralstat 150 mg in an open-label manner for up to an additional 52 weeks. The primary endpoint of Parts 2 and 3 was long-term safety and tolerability, and secondary endpoints examined effectiveness. Results: Seventeen patients entered Part 2, and 11 continued into Part 3. Treatment-emergent adverse events (TEAEs) were reported by 14/17 patients (82.4%) in Parts 2 or 3; the most common were nasopharyngitis, abdominal pain, cystitis, influenza, and vertigo. One patient (5.9%) experienced a drug-related TEAE (Grade 4 increased hepatic enzyme). No drug-related serious TEAEs were reported. For patients who completed 26 months of treatment with berotralstat 150 mg (n = 5), mean (standard error of the mean) monthly HAE attack rates and on-demand medication use decreased from baseline by 1.15 (0.09) attacks/month and 2.8 (0.64) doses/month, respectively. Sustained improvements were also observed in patient quality of life and treatment satisfaction. Conclusions: Long-term prophylaxis with berotralstat raised no new safety signals and was effective at reducing attacks and improving patient-reported outcomes. Trial registration: ClinicalTrials.gov NCT03873116. Registered March 13, 2019. Retrospectively registered.

Pretreatment periodontitis is predictive of a poorer prognosis after esophagectomy for esophageal cancer.

BACKGROUND: Poor oral health is an independent risk factor for upper-aerodigestive tract cancers, including esophageal cancer. Several studies have investigated short-term outcomes after esophagectomy and the impact of periodontal disease, but few have examined the impact of periodontal disease on long-term outcomes. The purpose of this study was to investigate the rate of periodontitis among esophagectomy patients and the prognostic value of periodontitis and its effect on prognosis after esophagectomy. METHODS: A total of 508 patients who underwent esophagectomy received oral health care from a dentist before cancer treatment at Akita University Hospital between January 2009 and December 2021. We assessed the presence and severity of the patients' periodontitis and divided them into no-periodontitis, mild periodontitis, severe periodontitis and edentulous jaw groups. We then assessed 10-year overall survival (OS) and disease-specific survival (DSS) and determined whether periodontitis was an independent prognostic factor affecting OS and DSS. RESULTS: We found that 101 (19.9%) patients had no periodontitis, 207 (40.8%) had mild periodontitis, 176 (34.6%) had severe periodontitis requiring tooth extraction, and 24 (4.7%) had edentulous jaw. Both OS and DSS were significantly poorer in the periodontitis than no-periodontitis group (p < 0.001). In detail, the edentulous jaw group had the poorest prognosis (p < 0.001). Multivariate analysis showed that periodontitis was an independent risk factor affecting OS and DSS. CONCLUSION: Esophageal cancer patients had a high prevalence of periodontitis. Moreover, the presence of periodontitis and severity of periodontitis are independent risk factors contributing to a poorer prognosis after esophagectomy.

Risk Factors Contributing to Disparities in Medical Treatment and Lower Survival Rates among Patients with Non-Small Cell Lung Cancer Induced by Residential Areas.

OBJECTIVE: Because of a lack of medical resources for cancer treatment, particularly in rural areas, there are disparities in receiving medical treatment between urban and rural area. This study examined the association between residential area or areal deprivation index (ADI) and lack of surgical treatment or chemotherapy in patients with non-small cell lung cancer (NSCLC) in rural area, Japan. METHODS: We analyzed the Aomori population-based cancer registry data from 926 cancer patients with NSCLC diagnosed between January and December 2014. Multivariable logistic regression and Cox proportional hazards models were used to examine association of patients' residential area/ADI with either surgery/chemotherapy or survival time, respectively. The residential area was divided into six medical areas based on the location of specialist hospitals. The medical areas were defined by Aomori Prefecture. RESULTS: The residential area (medical area) was strongly associated with access to cancer treatment for patients with NSCLC and ultimately contributed to lower survival rates. There was no significant influence in the distance from home to hospital and areal deprivation. CONCLUSION: We identified the risk factors related to a lack of medical treatment and shorter survival in rural area, Japan.

Noninvasive Computed Tomography-Based Deep Learning Model Predicts In Vitro Chemosensitivity Assay Results in Pancreatic Cancer.

OBJECTIVES: We aimed to predict in vitro chemosensitivity assay results from computed tomography (CT) images by applying deep learning (DL) to optimize chemotherapy for pancreatic ductal adenocarcinoma (PDAC). MATERIALS AND METHODS: Preoperative enhanced abdominal CT images and the histoculture drug response assay (HDRA) results were collected from 33 PDAC patients undergoing surgery. Deep learning was performed using CT images of both the HDRA-positive and HDRA-negative groups. We trimmed small patches from the entire tumor area. We established various prediction labels for HDRA results with 5-fluorouracil (FU), gemcitabine (GEM), and paclitaxel (PTX). We built a predictive model using a residual convolutional neural network and used 3-fold cross-validation. RESULTS: Of the 33 patients, effective response to FU, GEM, and PTX by HDRA was observed in 19 (57.6%), 11 (33.3%), and 23 (88.5%) patients, respectively. The average accuracy and the area under the receiver operating characteristic curve (AUC) of the model for predicting the effective response to FU were 93.4% and 0.979, respectively. In the prediction of GEM, the models demonstrated high accuracy (92.8%) and AUC (0.969). Likewise, the model for predicting response to PTX had a high performance (accuracy, 95.9%; AUC, 0.979). CONCLUSIONS: Our CT patch-based DL model exhibited high predictive performance in projecting HDRA results. Our study suggests that the DL approach could possibly provide a noninvasive means for the optimization of chemotherapy.

A Logistic Regression Model for Predicting the Risk of Subsequent Surgery among Patients with Newly Diagnosed Crohn's Disease Using a Brute Force Method.

Surgery avoidance is an important goal in Crohn's disease (CD) treatment and predicting the risk of subsequent surgery is important to determine adequate therapeutic strength for patients with newly diagnosed CD. Herein, we aimed to construct a prediction model for the risk of subsequent surgery based on disease characteristics at the patients' initial visit. We retrospectively collected disease characteristic data from 93 patients with newly diagnosed CD. A logistic regression model with a brute force method was used to maximize the area under the receiver operating characteristic curve (auROC) by employing a combination of potential predictors from 14 covariates (16,383). The auROC remained almost constant when one to 12 covariates were considered, reaching a peak of 0.89 at four covariates (small-bowel patency, extensive small-bowel lesions, main lesions, and the number of poor prognostic factors), and it decreased with increasing covariate size. The most significant predictors were small-bowel patency, extensive small-bowel lesions, and age or major lesions. Therefore, this prediction model using covariates may be helpful in determining the likelihood that a patient with newly diagnosed CD will require surgery, which can aid in appropriate treatment selection for high-risk patients.

Impact of postoperative complications on long-term survival in bladder cancer patients.

OBJECTIVE: To determine the impact of postoperative complications on long-term survival outcomes in patients with bladder cancer undergoing radical cystectomy. METHODS: This retrospective multi-institutional study included 766 bladder cancer patients who underwent radical cystectomy between 2011 and 2017. Patient characteristics, perioperative outcomes, all complications within 90 days after surgery and survival outcomes were collected. Each complication was graded based on the Clavien-Dindo system, and grouped using a standardized grouping method. The Comprehensive Complication Index, which incorporates all complications into a single formula weighted by their severity, was utilized. Overall survival and recurrence-free survival (local, distant or urothelial recurrences) were stratified by Comprehensive Complication Index (high: ≥26.2; low: <26.2). A multivariate model was utilized to identify independent prognostic factors. RESULTS: The incidence of any and major complications (≥Clavien-Dindo grade III) was 70 and 24%, respectively. In terms of Comprehensive Complication Index, 34% (261/766) of the patients had ≥26.2. Patients with Comprehensive Complication Index ≥ 26.2 had shorter overall survival (4-year, 59.5 vs. 69.8%, respectively, log-rank test, P = 0.0037) and recurrence free survival (51.9 vs. 60.1%, respectively, P = 0.0234), than those with Comprehensive Complication Index < 26.2. The Cox multivariate model identified the age, performance status, pT-stage, pN-stage and higher CCI (overall survival: HR = 1.35, P = 0.0174, recurrence-free survival: HR = 1.26, P = 0.0443) as independent predictors of both overall survivial and recurrence-free survival. CONCLUSIONS: Postoperative complications assessed by Comprehensive Complication Index had adverse effects on long-term survival outcomes. Physicians should be aware that major postoperative complications can adversely affect long-term disease control.

Comparison of Osteoconductive Ability of Two Types of Cholesterol-Bearing Pullulan (CHP) Nanogel-Hydrogels Impregnated with BMP-2 and RANKL-Binding Peptide: Bone Histomorphometric Study in a Murine Calvarial Defect Model.

The receptor activator of NF-κB ligand (RANKL)-binding peptide is known to accelerate bone morphogenetic protein (BMP)-2-induced bone formation. Cholesterol-bearing pullulan (CHP)-OA nanogel-crosslinked PEG gel (CHP-OA nanogel-hydrogel) was shown to release the RANKL-binding peptide sustainably; however, an appropriate scaffold for peptide-accelerated bone formation is not determined yet. This study compares the osteoconductivity of CHP-OA hydrogel and another CHP nanogel, CHP-A nanogel-crosslinked PEG gel (CHP-A nanogel-hydrogel), in the bone formation induced by BMP-2 and the peptide. A calvarial defect model was performed in 5-week-old male mice, and scaffolds were placed in the defect. In vivo µCT was performed every week. Radiological and histological analyses after 4 weeks of scaffold placement revealed that the calcified bone area and the bone formation activity at the defect site in the CHP-OA hydrogel were significantly lower than those in the CHP-A hydrogel when the scaffolds were impregnated with both BMP-2 and the RANKL-binding peptide. The amount of induced bone was similar in both CHP-A and CHP-OA hydrogels when impregnated with BMP-2 alone. In conclusion, CHP-A hydrogel could be an appropriate scaffold compared to the CHP-OA hydrogel when the local bone formation was induced by the combination of RANKL-binding peptide and BMP-2, but not by BMP-2 alone.

A trial deep learning-based model for four-class histologic classification of colonic tumor from narrow band imaging.

Narrow band imaging (NBI) has been extensively utilized as a diagnostic tool for colorectal neoplastic lesions. This study aimed to develop a trial deep learning (DL) based four-class classification model for low-grade dysplasia (LGD); high-grade dysplasia or mucosal carcinoma (HGD); superficially invasive submucosal carcinoma (SMs) and deeply invasive submucosal carcinomas (SMd) and evaluate its potential as a diagnostic tool. We collected a total of 1,390 NBI images as the dataset, including 53 LGD, 120 HGD, 20 SMs and 17 SMd. A total of 598,801 patches were trimmed from the lesion and background. A patch-based classification model was built by employing a residual convolutional neural network (CNN) and validated by three-fold cross-validation. The patch-based validation accuracy was 0.876, 0.957, 0.907 and 0.929 in LGD, HGD, SMs and SMd, respectively. The image-level classification algorithm was derived from the patch-based mapping across the entire image domain, attaining accuracies of 0.983, 0.990, 0.964, and 0.992 in LGD, HGD, SMs, and SMd, respectively. Our CNN-based model demonstrated high performance for categorizing the histological grade of dysplasia as well as the depth of invasion in routine colonoscopy, suggesting a potential diagnostic tool with minimal human inputs.

Covered self-expandable metallic stents versus plastic stents for endoscopic ultrasound-guided hepaticogastrostomy in patients with malignant biliary obstruction.

BACKGROUND/AIMS: Covered self-expandable metallic stents (cSEMS) have become popular for endoscopic ultrasound-guided hepaticogastrostomy with transmural stenting (EUS-HGS). We compared the time to recurrent biliary obstruction (TRBO), complications, and reintervention rates between EUS-HGS using plastic stent (PS) and cSEMS in patients with unresectable malignancies at multicenter institutions in Japan. METHODS: Patients with unresectable malignant biliary obstruction who underwent EUS-HGS between April 2015 and July 2020 at any of the six participating facilities were enrolled. Primary endpoint: TRBO; secondary endpoints: rate of complications other than recurrent biliary obstruction and technical success rate of reintervention were evaluated. RESULTS: PS and cSEMS were used for EUS-HGS in 109 and 43 patients, respectively. The TRBO was significantly longer in the cSEMS group than in the PS group (646 vs. 202 days). Multivariate analysis identified two independent factors associated with a favorable TRBO: combined EUS-guided antegrade stenting with EUS-HGS and the use of cSEMS. No significant difference was observed in the rate of complications other than recurrent biliary obstruction between the two groups. The technical success rate of reintervention was 85.7% for PS and 100% for cSEMS (p=0.309). CONCLUSION: cSEMS might be a better option for EUS-HGS in patients with unresectable malignancies, given the longer TRBO.

Carborane bearing pullulan nanogel-boron oxide nanoparticle hybrid for boron neutron capture therapy.

Boron neutron capture therapy shows is a promising approach to cancer therapy, but the delivery of effective boron agents is challenging. To address the requirements for efficient boron delivery, we used a hybrid nanoparticle comprising a carborane = bearing pullulan nanogel and hydrophobized boron oxide nanoparticle (HBNGs) enabling the preparation of highly concentrated boron agents for efficient delivery. The HBNGs showed better anti-cancer effects on Colon26 cells than a clinically boron agent, L-BPA/fructose complex, by enhancing the accumulation and retention amount of the boron agent within cells in vitro. The accumulation of HBNGs in tumors, due to the enhanced permeation and retention effect, enabled the delivery of boron agents with high tumor selectivity, meeting clinical demands. Intravenous injection of boron neutron capture therapy (BNCT) using HBNGs decreased tumor volume without significant body weight loss, and no regrowth of tumor was observed three months after complete regression. The therapeutic efficacy of HBNGs was better than that of L-BPA/fructose complex. BNCT with HBNGs is a promising approach to cancer therapeutics.

Validation of the Japanese version of the Body Image Scale for bladder cancer patients.

The Body Image Scale (BIS) is a 10-item tool that measures the body images of cancer patients. This study aims to validate the Japanese version of the BIS for bladder cancer patients. A multicenter cross-sectional survey was used to identify the participants, which included Japanese bladder cancer patients. The percentage of missing responses, internal consistency, and known-group validity were evaluated. The correlations between the BIS and two HRQOL instruments (the Bladder Cancer Index and the SF-12) were assessed to determine convergent validity. Among 397 patients, 221 patients were treated by transurethral resection of bladder tumor (TURBT) endoscopically, 49 patients underwent cystectomy with neobladder, and 127 patients underwent cystectomy involving stoma. The percentage of missing responses in the BIS ranged from 8.1 to 15.6%. Cronbach's α coefficient was 0.924. Higher BIS scores indicate negative body image, and the median BIS score for patients with native bladders after TURBT (0.5) was significantly lower than those of the patients with neobladder (4.0) and stoma formation (7.0), which indicated the discriminatory ability of the BIS. Each domain of the Bladder Cancer Index and the role summary score of the SF-12 correlated to the BIS scores, which confirmed the convergent validity. A range of BIS scores were identified among patients who reported similar physical summary scores and mental summary scores of the SF-12. This study confirmed the reliability and validity of the Japanese version of the BIS for bladder cancer patients.

Differential diagnoses of gallbladder tumors using CT-based deep learning.

Background: The differential diagnosis between gallbladder cancer (GBC) and xanthogranulomatous cholecystitis (XGC) remains quite challenging, and can possibly lead to improper surgery. This study aimed to distinguish between XGC and GBC by combining computed tomography (CT) images and deep learning (DL) to maximize the therapeutic success of surgery. Methods: We collected a dataset, including preoperative CT images, from 28 cases of GBC and 21 XGC patients undergoing surgery at our facility. It was subdivided into training and validation (n = 40), and test (n = 9) datasets. We built a CT patch-based discriminating model using a residual convolutional neural network and employed 5-fold cross-validation. The discriminating performance of the model was analyzed in the test dataset. Results: Of the 40 patients in the training dataset, GBC and XGC were observed in 21 (52.5%), and 19 (47.5%) patients, respectively. A total of 61 126 patches were extracted from the 40 patients. In the validation dataset, the average sensitivity, specificity, and accuracy were 98.8%, 98.0%, and 98.5%, respectively. Furthermore, the area under the receiver operating characteristic curve (AUC) was 0.9985. In the test dataset, which included 11 738 patches, the discriminating accuracy for GBC patients after neoadjuvant chemotherapy (NAC) (n = 3) was insufficient (61.8%). However, the discriminating model demonstrated high accuracy (98.2%) and AUC (0.9893) for cases other than those receiving NAC. Conclusion: Our CT-based DL model exhibited high discriminating performance in patients with GBC and XGC. Our study proposes a novel concept for selecting the appropriate procedure and avoiding unnecessary invasive measures.

Difference in net survival using regional and national life tables in Japan.

BACKGROUND: National life table is commonly used for estimating cancer net survival. However, the national life table does not reflect condition of people in local area accurately, because there are disparities in cancer mortality rates among the local area in many cases. We investigated magnitude of difference in cancer net survival using the local area in Japan and Japanese life tables. METHODS: We analyzed data from 32,942 cancer patients diagnosed between 2010 and 2012 in Aomori prefecture, Japan. Expected survival rates in Aomori (ESA) and Japan (ESJ) were estimated based on the life table of each area. Five-year net survival rates using ESA and the ESJ were estimated using the Pohar-Perme method. RESULTS: The difference between net survival rates using the ESA (NSA) and the ESJ (NSJ) were larger than in men (0.3－3.0%) than in women (0.1－0.8%). The largest difference in the net survival rate was observed in prostate cancer patients, because the difference in the expected survival in oldest old men was remarkable. CONCLUSION: Two factors affected the difference in the net survival rates resulting from the sensitivity analysis. The difference was larger (1) among older patients or (2) with a longer observation period (person-years).

Perforated Hydrogels Consisting of Cholesterol-Bearing Pullulan (CHP) Nanogels: A Newly Designed Scaffold for Bone Regeneration Induced by RANKL-Binding Peptides and BMP-2.

The receptor activator of NF-κB ligand (RANKL)-binding peptide, OP3-4, is known to stimulate bone morphogenetic protein (BMP)-2-induced bone formation, but peptides tend to aggregate and lose their bioactivity. Cholesterol-bearing pullulan (CHP) nanogel scaffold has been shown to prevent aggregation of peptides and to allow their sustained release and activity; however, the appropriate design of CHP nanogels to conduct local bone formation needs to be developed. In the present study, we investigated the osteoconductive capacity of a newly synthesized CHP nanogel, CHPA using OP3-4 and BMP-2. We also clarified the difference between perforated and nonperforated CHPA impregnated with the two signaling molecules. Thirty-six, five-week-old male BALB/c mice were used for the calvarial defect model. The mice were euthanized at 6 weeks postoperatively. A higher cortical bone mineral content and bone formation rate were observed in the perforated scaffold in comparison to the nonperforated scaffold, especially in the OP3-4/BMP-2 combination group. The degradation rate of scaffold material in the perforated OP3-4/BMP-2 combination group was lower than that in the nonperforated group. These data suggest that perforated CHPA nanogel could lead to local bone formation induced by OP3-4 and BMP-2 and clarified the appropriate degradation rate for inducing local bone formation when CHPA nanogels are designed to be perforated.

Potential for replacing warfarin with a direct oral anticoagulant for endoscopic mucosal resection in the colorectum: A multicenter, open-label, randomized controlled trial.

Objectives: This study aimed to evaluate the efficacy and safety of apixaban replacement (AR) as an alternative to heparin bridging (HB) in patients taking warfarin and scheduled for endoscopic mucosal resection (EMR) in the colorectum. Methods: This trial was conducted at seven institutes in Japan between May 2016 and May 2018. Enrolled patients had been taking oral warfarin and were diagnosed within 3 months with colorectal polyps for which EMR was indicated. Patients were randomly assigned to receive HB or AR. The primary endpoint was the incidence of postoperative bleeding. Secondary endpoints were the length of hospital stay, therapeutic endoscopy outcomes, and adverse events. Results: The planned sample size was 160 patients, but due to a decrease in the number of patients taking warfarin, the target number of cases could not be achieved within the case enrollment period, 44 cases were enrolled. They were divided into HB and AR groups. The incidence of postoperative bleeding was 15% (3/20) in HB and 0% in AR (P = 0.199). The total number of postoperative bleeding events was five in HB and none in AR. The length of hospital stay was significantly shorter in AR than in HB (median: 3.0 vs. 13.5 days, p < 0.001). There were no serious adverse events and no cerebral infarction/systemic embolism events. Conclusion: AR for colorectal EMR may prove safe and has the potential to shorten hospital stay and reduce medical costs, though we were unable to evaluate the primary endpoint due to insufficient sample size.

Prediction of the need for emergency endoscopic treatment for upper gastrointestinal bleeding and new score model: a retrospective study.

BACKGROUND: Gastrointestinal bleeding is one of the major gastrointestinal diseases. In this study, our objective was to compare Glasgow-Blatchford score (GBS), AIMS65 score, MAP score, Modified GBS, and Iino score as outcome measures for upper gastrointestinal bleeding. In addition, we extracted factors associated with hemostatic procedures including endoscopy, and proposed a new robust score model. METHODS: From January 2015 to December 2019, 675 patients with symptoms such as hematemesis who visited the National Hospital Organization Disaster Medical Center and underwent urgent upper endoscopy with diagnosis of suspected non-variceal upper gastrointestinal bleeding were retrospectively reviewed. We evaluated the GBS, AIMS65 score, MAP score, Modified GBS, and Iino score, and assessed the outcomes of patients requiring hemostatic treatments at the subsequent emergency endoscopy. We performed logistic regression analysis of factors related to endoscopic hemostasis and upper gastrointestinal bleeding, created a new score model, and evaluated the prediction of hemostatic treatment and mortality in the new score and the existing scores. RESULTS: The factors associated with endoscopic treatment were hematemesis, heart rate, HB (hemoglobin), blood pressure, blood urea nitrogen (BUN). Based on these predictors and the partial regression coefficients, a new score named H3B2 (using the initial letters of hematemesis, heart rate, HB, blood pressure, and BUN) was generated. H3B2 score was slightly more discriminatory compared to GBS and Modified GBS (area under the receiver operating characteristic curves (AUROC): 0.73 versus 0.721 and 0.7128, respectively) in predicting hemostatic treatment in emergency endoscopy. The H3B2 score also showed satisfactory prediction accuracy for subsequent deaths (AUROC: 0.6857. P < 0.001). CONCLUSIONS: We proposed a new score, the H3B2 score, consisting of simple and objective indices in cases of suspected upper gastrointestinal bleeding. The H3B2 score is useful in identifying high-risk patients with suspected upper gastrointestinal bleeding who require urgent hemostatic treatment including emergency endoscopy.

Fusogenic Hybrid Extracellular Vesicles with PD-1 Membrane Proteins for the Cytosolic Delivery of Cargos.

Extracellular vesicles (EVs) are cell-derived lipid membrane capsules that can deliver functional molecules, such as nucleic acids, to target cells. Currently, the application of EVs is limited because of the difficulty of loading cargo into EVs. We constructed hybrid EVs by the fusion of liposomes and insect cell-derived EVs expressing recombinant programmed cell death 1 (PD-1) protein and baculoviral fusogenic glycoprotein gp64, and evaluated delivery of the model cargo molecule, Texas Red-labeled dextran (TR-Dex), into the cytosol. When PD-1 hybrid EVs were added to HeLa cells, the intracellular uptake of the hybrid EVs was increased compared with hybrid EVs without PD-1. After cellular uptake, the PD-1 hybrid EVs were shown to be localized to late endosomes or lysosomes. The results of fluorescence resonance energy transfer (FRET) indicated that membrane fusion between the hybrid EVs and organelles had occurred in the acidic environment of the organelles. When TR-Dex-loaded liposomes were fused with the PD-1 EVs, confocal laser scanning microscopy indicated that TR-Dex was distributed throughout the cells, which suggested that endosomal escape of TR-Dex, through membrane fusion between the hybrid EVs and acidic organelles, had occurred. These engineered PD-1 hybrid EVs have potential as delivery carriers for biopharmaceuticals.

Automated evaluation of colon capsule endoscopic severity of ulcerative colitis using ResNet50.

Capsule endoscopy has been widely used as a non-invasive diagnostic tool for small or large intestinal lesions. In recent years, automated lesion detection systems using machine learning have been devised. This study aimed to develop an automated system for capsule endoscopic severity in patients with ulcerative colitis along the entire length of the colon using ResNet50. Capsule endoscopy videos from patients with ulcerative colitis were collected prospectively. Each single examination video file was partitioned into four segments: the cecum and ascending colon, transverse colon, descending and sigmoid colon, and rectum. Fifty still pictures (576 × 576 pixels) were extracted from each partitioned video. A patch (128 × 128 pixels) was trimmed from the still picture at every 32-pixel-strides. A total of 739,021 patch images were manually classified into six categories: 0) Mayo endoscopic subscore (MES) 0, 1) MES1, 2) MES2, 3) MES3, 4) inadequate quality for evaluation, and 5) ileal mucosa. ResNet50, a deep learning framework, was trained using 483,644 datasets and validated using 255,377 independent datasets. In total, 31 capsule endoscopy videos from 22 patients were collected. The accuracy rates of the training and validation datasets were 0.992 and 0.973, respectively. An automated evaluation system for the capsule endoscopic severity of ulcerative colitis was developed. This could be a useful tool for assessing topographic disease activity, thus decreasing the burden of image interpretation on endoscopists.

Theranostic Agent Combining Fullerene Nanocrystals and Gold Nanoparticles for Photoacoustic Imaging and Photothermal Therapy.

Developing photoactivatable theranostic platforms with integrated functionalities of biocompatibility, targeting, imaging contrast, and therapy is a promising approach for cancer diagnosis and therapy. Here, we report a theranostic agent based on a hybrid nanoparticle comprising fullerene nanocrystals and gold nanoparticles (FGNPs) for photoacoustic imaging and photothermal therapy. Compared to gold nanoparticles and fullerene crystals, FGNPs exhibited stronger photoacoustic signals and photothermal heating characteristics by irradiating light with an optimal wavelength. Our studies demonstrated that FGNPs could kill cancer cells due to their photothermal heating characteristics in vitro. Moreover, FGNPs that are accumulated in tumor tissue via the enhanced permeation and retention effect can visualize tumor tissue due to their photoacoustic signal in tumor xenograft model mice. The theranostic agent with FGNPs shows promise for cancer therapy.