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Abstract Objectives To explore the characteristics of myocardial involvement in Wilson Disease (WD) patients by cardiac magnetic resonance (CMR). Methods We prospectively included WD patients and age- and sex-matched healthy population. We applied CMR to analyze cardiac function, strain, T1 maps, T2 maps, extracellular volume fraction (ECV) maps, and LGE images. Subgroup analyzes were performed for patients with WD with predominantly neurologic manifestations (WD‐neuro +) or only hepatic manifestations (WD‐neuro −). Results Forty-one WD patients (age 27.9 ± 8.0 years) and 40 healthy controls (age 25.4 ± 2.9 years) were included in this study. Compared to controls, the T1, T2, and ECV values were significantly increased in the WD group (T1 1085.1 ± 39.1 vs. 1046.5 ± 33.1 ms, T2 54.2 ± 3.3 ms vs. 51.5 ± 2.6 ms, ECV 31.8 ± 3.6% vs. 24.3 ± 3.7%) (all p

Dysfunction of potassium voltage-gated channel subfamily Q member 1 (KCNQ1) is a primary cause of long QT syndrome type 1 (LQT1). Here, we report a missense mutation P441L in KCNQ1 C-terminus of a 37-year-old woman with severe LQT1 phenotype. Variant P441L transporting to the plasma membrane and interacting with KCNE1 were both markedly decreased, leading to potassium efflux disorder and eventually LQT1. Mutations between the C-terminal helix A and helix B of KCNQ1 have linked with low cardiac event risk, however, we firstly find variant P441L causing a severe LQT1 phenotype with a high risk of cardiac events.

Background: Bivalirudin is a direct thrombin inhibitor (DTI) that can be an alternative to unfractionated heparin (UFH). The efficacy and safety of bivalirudin in anticoagulation therapy in extracorporeal membrane oxygenation (ECMO) remain unknown.Methods: This study followed the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. A systematic literature search was performed in PubMed, EMBASE, and The Cochrane Library databases to identify all relevant original studies estimating bivalirudin’s efficacy and safety versus UFH as anticoagulation therapy in ECMO. The time limit for searching is from the search beginning to June 2021. Two researchers independently screened the literature, extracted data and evaluated the risk of bias of the included studies. The meta-analysis (CRD42020214713) was performed via the RevMan version 5.3.5 Software and STATA version 15.1 Software.Results: Ten articles with 847 patients were included for the quantitative analysis. Bivalirudin can significantly reduce the incidence of major bleeding in children (I2 = 48%, p = 0.01, odd ratio (OR) = 0.17, 95% confidence interval (CI): 0.04–0.66), patient thrombosis (I2 = 0%, p = 0.02, OR = 0.58, 95% CI: 0.37–0.93), in-circuit thrombosis/interventions (I2 = 0%, p = 0.0005, OR = 0.40, 95% CI: 0.24–0.68), and in-hospital mortality (I2 = 0%, p = 0.007, OR = 0.64, 95% CI: 0.46–0.88). Also, comparable clinical outcomes were observed in the incidence of major bleeding in adults (I2 = 48%, p = 0.65, OR = 0.87, 95% CI: 0.46–1.62), 30-day mortality (I2 = 0%, p = 0.61, OR = 0.83, 95% CI: 0.41–1.68), and ECMO duration in adults (I2 = 41%, p = 0.75, mean difference (MD) = −3.19, 95% CI: −23.01–16.63) and children (I2 = 76%, p = 0.65, MD = 40.33, 95% CI:−135.45–216.12).Conclusions: Compared with UFH, bivalirudin can be a safe and feasible alternative anticoagulant option to UFH as anticoagulation therapy in ECMO, especially for heparin resistance (HR) and heparin-induced thrombocytopenia (HIT) cases.

Abstract Background Nanosecond pulsed electric fields (nsPEF)‐based electroporation is a new therapy modality potentially synergized with radiation therapy to improve treatment outcomes. To verify its treatment accuracy intraoperatively, electroacoustic tomography (EAT) has been developed to monitor in‐vivo electric energy deposition by detecting ultrasound signals generated by nsPEFs in real‐time. However, utility of EAT is limited by image distortions due to the limited‐angle view of ultrasound transducers. Methods This study proposed a supervised learning‐based workflow to address the ill‐conditioning in EAT reconstruction. Electroacoustic signals were detected by a linear array and initially reconstructed into EAT images, which were then fed into a deep learning model for distortion correction. In this study, 56 distinct electroacoustic data sets from nsPEFs of different intensities and geometries were collected experimentally, avoiding simulation‐to‐real‐world variations. Forty‐six data were used for model training and 10 for testing. The model was trained using supervised learning, enabled by a custom rotating platform to acquire paired full‐view and single‐view signals for the same electric field. Results The proposed method considerably improved the image quality of linear array‐based EAT, generating pressure maps with accurate and clear structures. Quantitatively, the enhanced single‐view images achieved a low‐intensity error (RMSE: 0.018), high signal‐to‐noise ratio (PSNR: 35.15), and high structural similarity (SSIM: 0.942) compared to the reference full‐view images. Conclusions This study represented a pioneering stride in achieving high‐quality EAT using a single linear array in an experimental environment, which improves EAT's utility in real‐time monitoring for nsPEF‐based electroporation therapy.

Abstract Methods accurately predicting the responses of colorectal cancer (CRC) and colorectal cancer liver metastasis (CRLM) to personalized chemotherapy remain limited due to tumor heterogeneity. This study introduces an innovative patient‐derived CRC and CRLM tumor model for preclinical investigation, utilizing 3d‐bioprinting (3DP) technology. Efficient construction of homogeneous in vitro 3D models of CRC/CRLM is achieved through the application of patient‐derived primary tumor cells and 3D bioprinting with bioink. Genomic and histological analyses affirm that the CRC/CRLM 3DP tumor models effectively retain parental tumor biomarkers and mutation profiles. In vitro tests evaluating chemotherapeutic drug sensitivities reveal substantial tumor heterogeneity in chemotherapy responses within the 3DP CRC/CRLM models. Furthermore, a robust correlation is evident between the drug response in the CRLM 3DP model and the clinical outcomes of neoadjuvant chemotherapy. These findings imply a significant potential for the application of patient‐derived 3DP cancer models in precision chemotherapy prediction and preclinical research for CRC/CRLM.

Industrial heritage creative industrial parks are an organic component of historical neighborhood buildings. According to several field visits and surveys of creative industrial parks, it has been found that the external space of some creative industrial parks does not meet the needs of the people. This research primarily investigates the critical factors influencing the usability of external spaces in these revitalization projects. Spatial syntax, a field that has seen considerable advancement in recent years, offers a more scientific approach to understanding spatial relationships. Therefore, this paper employs spatial syntax as its principal methodology. It conducts a quantitative analysis of the external spatial morphology of four creative industrial parks of industrial heritage in Tianjin. The study critically evaluates the syntactic values and identifies issues in the external spatial morphology, including a dearth of cultural elements and limited environmental richness. Furthermore, it provides recommendations for the enhancement of these external spaces. The aim is to furnish data support and strategic insights to invigorate the revitalization efforts of Tianjin’s industrial heritage creative industrial parks.

Abstract Objective Despite its prevalence, cone beam computed tomography (CBCT) has poor soft‐tissue contrast, making it challenging to localize liver tumors. We propose a patient‐specific deep learning model to generate synthetic magnetic resonance imaging (MRI) from CBCT to improve tumor localization. Methods A key innovation is using patient‐specific CBCT‐MRI image pairs to train a deep learning model to generate synthetic MRI from CBCT. Specifically, patient planning CT was deformably registered to prior MRI, and then used to simulate CBCT with simulated projections and Feldkamp, Davis, and Kress reconstruction. These CBCT‐MRI images were augmented using translations and rotations to generate enough patient‐specific training data. A U‐Net‐based deep learning model was developed and trained to generate synthetic MRI from CBCT in the liver, and then tested on a different CBCT dataset. Synthetic MRIs were quantitatively evaluated against ground‐truth MRI. Results The synthetic MRI demonstrated superb soft‐tissue contrast with clear tumor visualization. On average, the synthetic MRI achieved 28.01, 0.025, and 0.929 for peak signal‐to‐noise ratio, mean square error, and structural similarity index, respectively, outperforming CBCT images. The model performance was consistent across all three patients tested. Conclusion Our study demonstrated the feasibility of a patient‐specific model to generate synthetic MRI from CBCT for liver tumor localization, opening up a potential to democratize MRI guidance in clinics with conventional LINACs.

As the largest developing country, China has permanently attached great importance to cultivated land protection. However, due to the different rules of cultivated land identification in the second and third national land surveys, the cultivated land area in the two surveys has changed greatly. Some agricultural lands in the south, such as plantations, forests, grasslands, aquaculture ponds, etc., belonged to cultivated land during the second survey, but they were identified as non-cultivated land in the third national land survey. This change has led to a sharp reduction in the area of cultivated land in some places. In order to calculate the actual change in the area of cultivated land since the second survey and provide a reasonable basis for the standard of cultivated land protection, this paper takes Gaochun District, a developed area in China, as an example; interprets the images of the second national land survey period with the deep learning network HRNet; and compares the results with the second and third national land survey rules. The results show that the actual reduction of cultivated land in Gaochun District in the past ten years accounts for 35.1% of the reduction of cultivated land in the two land surveys, while the reduction of cultivated land caused by the change of cultivated land identification rules accounts for 64.9% of the reduction of cultivated land in the two land surveys, indicating that the significant reduction in local cultivated land was mainly caused by the changes in the rules, and these cultivated land reduction behaviors existed before the second survey.

In recent years, deep learning has become the mainstream development direction in the change-detection field, and its accuracy and speed have also reached a high level. However, the change-detection method based on deep learning cannot predict all the change areas accurately, and its application is limited due to local prediction defects. For this reason, we propose an interactive change-detection network (ICD) for very high resolution (VHR) based on a deep convolution neural network. The network integrates positive- and negative-click information in the distance layer of the change-detection network, and users can correct the prediction defects by adding clicks. We carried out experiments on the open source dataset WHU and LEVIR-CD. By adding clicks, their F1-scores can reach 0.920 and 0.912, respectively, which are 4.3% and 4.2% higher than the original network. To better evaluate the correction ability of clicks, we propose a set of evaluation indices—click-correction ranges, which is suitable for evaluating clicks, and we carry out experiments on the above models. The results show that the method of adding clicks can effectively correct the prediction defects and improve the result accuracy.

Thiol-containing natural products possess a wide range of bioactivities. The burst of synthetic biology technology facilitates the discovery of new thiol-containing active ingredients. Herein, we report a sensitive, quick, and robust surface-enhanced Raman scattering technology for specific and multiplex detection of thiol-containing compounds without purification requirements and also indicating the thiols with different chemical environments. Using this platform, we successfully demonstrated the simultaneous detection of thiol-containing compounds from as low as 1 μM of analytes spiked in complex culture matrices.