BCLAF1 binds SPOP to stabilize PD-L1 and promotes the development and immune escape of hepatocellular carcinoma.

Interaction between programmed death-1 (PD-1) ligand 1 (PD-L1) on tumor cells and PD-1 on T cells allows tumor cells to evade T cell-mediated immune surveillance. Strategies targeting PD-1/PD-L1 have shown clinical benefits in a variety of cancers. However, limited response rates in hepatocellular carcinoma (HCC) have prompted us to investigate the molecular regulation of PD-L1. Here, we identify B cell lymphoma-2-associated transcription factor 1 (BCLAF1) as a key PD-L1 regulator in HCC. Specifically, BCLAF1 interacts with SPOP, an E3 ligase that mediates the ubiquitination and degradation of PD-L1, thereby competitively inhibiting SPOP-PD-L1 interaction and subsequent ubiquitination and degradation of PD-L1. Furthermore, we determined an SPOP-binding consensus (SBC) motif mediating the BCLAF1-SPOP interaction on BCLAF1 protein and mutation of BCLAF1-SBC motif disrupts the regulation of the SPOP-PD-L1 axis. In addition, BCLAF1 expression was positively correlated with PD-L1 expression and negatively correlated with biomarkers of T cell activation, including CD3 and CD8, as well as with the level of immune cell infiltration in HCC tissues. Besides, BCLAF1 depletion leads to a significant reduction of PD-L1 expression in vitro, and this reduction of PD-L1 promoted T cell-mediated cytotoxicity. Notably, overexpression of BCLAF1 sensitized tumor cells to checkpoint therapy in an in vitro HCC cells-Jurkat cells co-culture model, whereas BCLAF1-SBC mutant decreased tumor cell sensitivity to checkpoint therapy, suggesting that BCLAF1 and its SBC motif serve as a novel therapeutic target for enhancing anti-tumor immunity in HCC.

Glutathione-triggered prodrugs: Design strategies, potential applications, and perspectives.

The burgeoning prodrug strategy offers a promising avenue toward improving the efficacy and specificity of cytotoxic drugs. Elevated intracellular levels of glutathione (GSH) have been regarded as a hallmark of tumor cells and characteristic feature of the tumor microenvironment. Considering the pivotal involvement of elevated GSH in the tumorigenic process, a diverse repertoire of GSH-triggered prodrugs has been developed for cancer therapy, facilitating the attenuation of deleterious side effects associated with conventional chemotherapeutic agents and/or the attainment of more efficacious therapeutic outcomes. These prodrug formulations encompass a spectrum of architectures, spanning from small molecules to polymer-based and organic-inorganic nanomaterial constructs. Although the GSH-triggered prodrugs have been gaining increasing interests, a comprehensive review of the advancements made in the field is still lacking. To fill the existing lacuna, this review undertakes a retrospective analysis of noteworthy research endeavors, based on a categorization of these molecules by their diverse recognition units (i.e., disulfides, diselenides, Michael acceptors, and sulfonamides/sulfonates). This review also focuses on explaining the distinct benefits of employing various chemical architecture strategies in the design of these prodrug agents. Furthermore, we highlight the potential for synergistic functionality by incorporating multiple-targeting conjugates, theranostic entities, and combinational treatment modalities, all of which rely on the GSH-triggering. Overall, an extensive overview of the emerging field is presented in this review, highlighting the obstacles and opportunities that lie ahead. Our overarching goal is to furnish methodological guidance for the development of more efficacious GSH-triggered prodrugs in the future. By assessing the pros and cons of current GSH-triggered prodrugs, we expect that this review will be a handful reference for prodrug design, and would provide a guidance for improving the properties of prodrugs and discovering novel trigger scaffolds for constructing GSH-triggered prodrugs.

Ral GTPase promotes metastasis of pancreatic ductal adenocarcinoma via elevation of TGF-ß1 production.

Pancreatic ductal adenocarcinoma (PDAC), caused by activating mutations in K-Ras, is an aggressive malignancy due to its early invasion and metastasis. Ral GTPases are activated downstream of Ras and play a crucial role in the development and progression of PDAC. However, the underlying mechanisms remain unclear. In this study, we investigated the mechanism of Ral-induced invasion and metastasis of PDAC cells using RalGAPß-deficient PDAC cells with highly activated Ral GTPases. Array analysis and ELISA revealed increased expression and secretion of TGF-ß1 in RalGAPß-deficient PDAC cells compared to control cells. Blockade of TGF-ß1 signaling suppressed RalGAPß deficiency-enhanced migration and invasion in vitro and metastasis in vivo to levels similar to controls. Phosphorylation of c-Jun N-terminal kinase, a repressor of TGF-ß1 expression, was decreased by RalGAPß deficiency. These results indicate that Ral contributes to invasion and metastasis of PDAC cells by elevating autocrine TGF-ß1 signaling at least in part by decreasing c-Jun N-terminal kinase activity.

Fabrication of Nanocatalytic Medicine from Self-Assembling Peptides Containing an ATCUN-Like Copper-Binding Motif for Anticancer Therapy.

Development of nanomaterials with multiple enzymatic activities via a facile approach receives growing interests in recent years. Although peptide self-assembling provides an effective approach for the construction of biomimetic materials in recent years, fabrication of artificial enzymes from self-assembling peptides with multiple catalytic activities for anticancer therapy is still a challenge. Here, we report a simple method to prepare nanocatalysts with multienzyme-like activities from self-assembling peptides containing ATCUN copper-binding motifs. With the aid of the coordination interactions between the ATCUN motif and Cu(II) ions, these peptides could perform supramolecular self-assembly to form nanomaterials with biomimetic peroxidase, ascorbate oxidase and glutathione peroxidase activities. Moreover, these trienzyme-like effects can elevate oxidative stress levels and suppress the antioxidative capability of cancer cells, which synergistically induce the apoptosis of cancer cells. Because of the high biocompatibility, catalytic activities and drug encapsulation properties, this self-assembled peptide provides a biomimetic platform for the development of new nanocatalytic medicines for multimodal synergistic cancer therapies.

Perfusion of hepatocellular carcinomas measured by diffusion-derived vessel density biomarker: Higher hepatocellular carcinoma perfusion than earlier intravoxel incoherent motion reports.

Diffusion-derived vessel density (DVDD) is a physiological surrogate of the area of microvessels per unit tissue area. DDVD is calculated according to DDVD(b0b2) = Sb0/ROIarea0 - Sb2/ROIarea2, where Sb0 and Sb2 refer to the liver signal when b is 0 or 2 s/mm2. Pathohistological studies and contrast-enhanced CT/MRI data showed higher blood volume in hepatocellular carcinoma (HCC) relative to native liver tissue. With intravoxel incoherent motion (IVIM) imaging, most authors paradoxically reported a decreased perfusion fraction of HCC relative to the adjacent liver. This study applied DDVD to assess the perfusion of HCC. MRI was performed with a 3.0-T magnet. Diffusion-weighted images with b-values of 0 and 2 s/mm2 were acquired in 72 HCC patients. Thirty-two patients had microvascular invasion (MVI(+)) and 40 patients did not have microvascular invasion (MVI(-)). Fifty-eight patients had Edmondson-Steiner grade I or II HCC, and 14 patients had Edmondson-Steiner grade III or IV HCC. DDVD measurement was conducted on the axial slice that showed the largest HCC size. DDVD(b0b2) T/L = HCC DDVD(b0b2)/liver DDVD(b0b2). DDVD(b0b2) T/L median (95% confidence interval) of all HCCs was 2.942 (2.419-3.522), of MVI(-) HCCs was 2.699 (2.030-3.522), of MVI(+) HCCs was 2.988 (2.423-3.990), of Edmondson-Steiner grade I/II HCCs was 2.873 (2.277-3.465), and of Edmondson-Steiner grade III/IV HCCs was 3.403 (2.008-4.485). DDVD(b0b2) T/L approximately agrees with contrast agent dynamically enhanced CT/MRI literature data, whereas it differs from earlier IVIM study results, where HCC perfusion fraction was paradoxically lower relative to native liver tissue. A weak trend was noted with MIV(+) HCCs had a higher DDVD(b0b2) T/L than that of MVI(-) HCCs, and a weak trend was noted with the poorly differentiated group of HCCs (Edmondson-Steiner grade III and IV) had a higher DDVD(b0b2) T/L than that of the better differentiated group of HCCs (Edmondson-Steiner grade I and II).

Repeatability and reproducibility comparisons of liver IVIM imaging with free-breathing or respiratory-triggered sequences.

For liver intravoxel incoherent motion (IVIM) data acquisition, respiratory-triggering (RT) MRI is commonly used, and there are strong motivations to shorten the scan duration. For the same scan duration, more b values or higher numbers of excitations can be allowed for free-breathing (FB) imaging than for RT. We studied whether FB can be used to replace RT when careful IVIM image acquisition and image processing are conducted. MRI data of 22 healthy participants were acquired using a 3.0 T scanner. Diffusion imaging was based on a single-shot spin-echo-type echo-planar sequence and 16 b values of 0, 2, 4, 7, 10, 15, 20, 30, 46, 60, 72, 100, 150, 200, 400, and 600 s/mm2 . Each subject attended two scan sessions with an interval of 10-20 days. For each scan session, a subject was scanned twice, first with RT and then with FB. The mean image acquisition time was 5.4 min for FB and 10.8 min for RT. IVIM parameters were calculated with bi-exponential model segmented fitting with a threshold b value of 60 s/mm2 , and fitting started from b = 2 s/mm2 . There was no statistically significant difference between IVIM parameters measured with FB imaging or RT imaging. Perfusion fraction ICC (intraclass correlation coefficient) for FB imaging and RT imaging in the same scan session was 0.824. For perfusion fraction, wSD (within-subject standard deviation), BA (Bland-Altman) difference, BA 95% limit, and ICC were 0.022, 0.0001, -0.0635~0.0637, and 0.687 for FB and 0.031, 0.0122, -0.0723~0.0967, and 0.611 for RT. For Dslow (×10-3  s/mm2 ), wSD, BA difference, BA 95% limit, and ICC were 0.057, 0.0268, -0.1258~0.1793, and 0.471 for FB and 0.073, -0.0078, -0.2170-0.2014, and <0.4 for RT. The Dfast coefficient of variation was 0.20 for FB imaging and 0.28 for RT imaging. All reproducibility indicators slightly favored FB imaging.

Synthesis of a catalytic nanomaterial from polypyrrole and a pro-apoptotic peptide to target mitochondria for multimodal cancer therapy.

Development of biocompatible nanomaterials with mitochondria-targeting and multimodal therapeutic activities is important for cancer treatment. Herein, we designed and synthesized a multifunctional pyrrole-based nanomaterial with photothermal effects and mitochondria-targeting properties from polypyrrole and the pro-apoptotic peptide KLA. Different from traditional strategies for the preparation of PPy nanoparticles, we innovatively used the KLA peptide as the template and CuCl2 as the catalyst to trigger the oxidative polymerization of pyrrole for PPy-KLA-Cu nanoparticle formation. Besides, due to the presence of mixed-valence Cu(I)/Cu(II) states, PPy-KLA-Cu nanoparticles also exhibited multienzyme-like activities, such as peroxidase, ascorbate oxidase and glutathione peroxidase activities, which can be exploited to elevate the intracellular ROS level and simultaneously consume GSH in cancer cells. More importantly, the heat generated by PPy-KLA-Cu nanoparticles from NIR irradiation could enhance the nanozymatic activities for ROS elevation and increase the KLA-induced anticancer activity via mitochondrial dysfunction, realizing multimodal treatment of cancer cells with improved therapeutic efficacy.

Clinical study on the necessity and feasibility of routine MRCP in patients with cholecystolithiasis before LC.

BACKGROUND: In the past quite a long time, intraoperative cholangiography(IOC)was necessary during laparoscopic cholecystectomy (LC). Now magnetic resonance cholangiopancreatography (MRCP) is the main method for diagnosing common bile duct stones (CBDS). Whether MRCP can replace IOC as routine examination before LC is still inconclusive. The aim of this study was to analyze the clinical data of patients undergoing LC for cholecystolithiasis, and to explore the necessity and feasibility of preoperative routine MRCP in patients with cholecystolithiasis. METHODS: According to whether MRCP was performed before operation, 184 patients undergoing LC for cholecystolithiasis in the Department of General Surgery, Beijing Shijitan Hospital, Capital Medical University from January 1, 2017 to December 31, 2018 were divided into non-MRCP group and MRCP group for this retrospective study. The results of preoperative laboratory test, abdominal ultrasound and MRCP, biliary related comorbidities, surgical complications, hospital stay and hospitalization expenses were compared between the two groups. RESULTS: Among the 184 patients, there were 83 patients in non-MRCP group and 101 patients in MRCP group. In MRCP group, the detection rates of cholecystolithiasis combined with CBDS and common bile duct dilatation by MRCP were higher than those by abdominal ultrasound (P < 0.05). The incidence of postoperative complications in non-MRCP group (8.43%) was significantly higher (P < 0.05) than that in MRCP group (0%). There was no significant difference in hospital stay (P > 0.05), but there was significant difference in hospitalization expenses (P < 0.05) between the two groups. According to the stratification of gallbladder stone patients with CBDS, hospital stay and hospitalization expenses were compared, and there was no significant difference between the two groups (P > 0.05). CONCLUSIONS: The preoperative MRCP can detect CBDS, cystic duct stones and anatomical variants of biliary tract that cannot be diagnosed by abdominal ultrasound, which is helpful to plan the surgical methods and reduce the surgical complications. From the perspective of health economics, routine MRCP in patients with cholecystolithiasis before LC does not increase hospitalization costs, and is necessary and feasible.

Cohen syndrome combined with psychiatric symptoms: a case report.

BACKGROUND: Cohen syndrome (CS) is a rare autosomal recessive inherited condition characterized by pathological changes affecting multiple systems. The extensive clinical variability associated with CS poses a significant diagnostic challenge. Additionally, there is limited documentation on the co-occurrence of CS with psychiatric symptoms. CASE REPORT: We report a case of a 30-year-old patient exhibiting characteristic physical features and psychiatric symptoms. Whole exome sequencing identified two heterozygous variants, a nonsense variation c.4336 C > T and a missense mutation c.4729G > A. Integrating clinical manifestations with genetic test results, we established the diagnosis of CS combined with psychiatric symptoms. CONCLUSIONS: This case introduces a novel missense variant as a candidate in the expanding array of VPS13B pathogenic variants. Its clinical significance remains unknown, and further investigation may broaden the spectrum of pathogenic variants associated with the VPS13B gene. Early diagnosis of CS is crucial for the prognosis of young children and holds significant importance for their families.

The Study of Endothelial-Mesenchymal Transition in an Atrial Fibrillation Rat Model.

Background: Activated fibroblasts are reported partly of endothelial origin, derived through endothelial-mesenchymal transition (EndMT). Few studies have investigated EndMT in atrial fibrillation (AF), which may have a potential effect on cardiac fibrosis. Objective: To investigate whether EndMT occurs in an animal model of AF. Methods: A total of 80 Sprague‒Dawley rats (8 weeks, male, 200-250 g) were randomly divided into two groups: the control group and the AF group (n = 40 in each group). Rats in the AF group received a daily intravenous injection of acetylcholine-calcium chloride for seven days to establish an AF model, and rats in the control rats were injected with saline in the same way. At different time points (Day 3, Day 5, Day 7, Day 9, Day 11, Day 13, Day 15, and Day 17), we observed changes in EndMT-related indexes (CD31, VE-cadherin, FSP-1, TGF-ß1 and collagen) and HIF-1α in the rat atria of two groups, as well as immunofluorescence co-expression of CD31/FSP-1 and VE-cadherin/FSP-1 in the endocardial endocardium of the atria. Results: In the AF group, atrial EndMT was observed and enhanced with time. Compared with the control group, the levels of CD31 and VE-cadherin in the AF group decreased, while mesenchymal marker (FSP-1) and EndMT inducer (TGF-ß1) were dynamically increased after Day 3. The co-expression of CD31/FSP-1 and VE-cadherin/FSP-1 was observed from Day 3 to the end of observation time Day 17 by immunofluorescence in AF rat hearts, indicating the existence of EndMT. In addition, the level of HIF-1α in the hearts of AF rats was increased. Conclusion: As far as we know, this is the first study to explore the dynamic process of EndMT in an AF rat model. The presence of EndMT was verified in the atria of the AF rat model, and Day 7-Day 17 was the best observation time point for the model. This may lead to a better understanding of the pathological changes and mechanisms in AF with a short modeling cycle.

Increased team familiarity for surgical time savings: Effective primarily in complex surgical cases.

BACKGROUND: Cohesion between team members is critical for surgical performance. Our previous study has shown that the experience of working together (measured by Team Familiarity Score, TFS) helps reduce procedure time (PT). However, that conclusion was found in a relatively small sample size. With a large dataset including mixed general surgical procedures, we hypothesize that team familiarity makes a significant contribution to the improvement of team performance in complex cases, rather than in medium or basic surgical cases, measured by the procedure time, length of hospital stays (LOS), and surgical cost (COST). STUDY DESIGN: Patient demographics, operation, and patient outcome data of 922 general surgery cases were included. The cases were divided into three subgroups, including basic, medium, and complex surgical procedures. TFS and an Index of Difficulty of Surgery (IDS) were calculated for each procedure. Simple linear regression and random forest regressions were performed to analyze the association between surgical outcomes and all included independent variables (TFS, IDS, patient age, patient weight, and team size). RESULTS: When applied to complex cases, procedure time (r = -0.21) and cost (r = -0.23) dropped as TFS increases. In basic and medium surgical cases, increasing team familiarity failed to shorten the procedure time on average. CONCLUSION: Team familiarity is more important in complex cases because there is greater potential for improvement through team collaboration compared to basic and medium cases. Caution will be needed when applying team familiarity scores for examining surgical team performance in large databases with skewed to basic surgical cases.

Quantifying the Impact of Motions on Human Aiming Performance: Evidence from Eye Tracking and Bio-Signals.

Working on a moving platform can significantly impede human performance. Previous studies on moving vehicles have often focused on the overall impact on general task performance, whereas our study's emphasis is on precise hand movements, exploring the interaction between body motion and the escalation of task difficulty. We recruited 28 participants to engage in reciprocal aiming tasks, following Paul Fitts's setting, under both in-motion and stationary conditions. The task index of difficulty (ID) was manipulated by varying the width of the targets and the distance between the targets. We measured participants' movement time (MT), performance errors, and monitored their eye movements using an eye-tracking device, heart rate (HR), and respiration rate (RR) during the tasks. The measured parameters were compared across two experimental conditions and three ID levels. Compared to the stationary conditions, the in-motion conditions degraded human aiming performance, resulting in significantly prolonged MT, increased errors, and longer durations of eye fixations and saccades. Furthermore, HR and RR increased under the in-motion conditions. Linear relationships between MT and ID exhibited steeper slopes under the in-motion conditions compared to the stationary conditions. This study builds a foundation for us to explore the control mechanisms of individuals working in dynamic and demanding environments, such as pilots in airplanes and paramedics in ambulances.

Enhancing Semi-Supervised Semantic Segmentation of Remote Sensing Images via Feature Perturbation-Based Consistency Regularization Methods.

In the field of remote sensing technology, the semantic segmentation of remote sensing images carries substantial importance. The creation of high-quality models for this task calls for an extensive collection of image data. However, the manual annotation of these images can be both time-consuming and labor-intensive. This has catalyzed the advent of semi-supervised semantic segmentation methodologies. Yet, the complexities inherent within the foreground categories of these remote sensing images present challenges in preserving prediction consistency. Moreover, remote sensing images possess more complex features, and different categories are confused within the feature space, making optimization based on the feature space challenging. To enhance model consistency and to optimize feature-based class categorization, this paper introduces a novel semi-supervised semantic segmentation framework based on Mean Teacher (MT). Unlike the conventional Mean Teacher that only introduces perturbations at the image level, we incorporate perturbations at the feature level. Simultaneously, to maintain consistency after feature perturbation, we employ contrastive learning for feature-level learning. In response to the complex feature space of remote sensing images, we utilize entropy threshold to assist contrastive learning, selecting feature key-values more precisely, thereby enhancing the accuracy of segmentation. Extensive experimental results on the ISPRS Potsdam dataset and the challenging iSAID dataset substantiate the superior performance of our proposed methodology.

Magnetic Resonance Deep Learning Radiomic Model Based on Distinct Metastatic Vascular Patterns for Evaluating Recurrence-Free Survival in Hepatocellular Carcinoma.

BACKGROUND: The metastatic vascular patterns of hepatocellular carcinoma (HCC) are mainly microvascular invasion (MVI) and vessels encapsulating tumor clusters (VETC). However, most existing VETC-related radiological studies still focus on the prediction of VETC status. PURPOSE: This study aimed to build and compare VETC-MVI related models (clinical, radiomics, and deep learning) associated with recurrence-free survival of HCC patients. STUDY TYPE: Retrospective. POPULATION: 398 HCC patients (349 male, 49 female; median age 51.7 years, and age range: 22-80 years) who underwent resection from five hospitals in China. The patients were randomly divided into training cohort (n = 358) and test cohort (n = 40). FIELD STRENGTH/SEQUENCE: 3-T, pre-contrast T1-weighted imaging spoiled gradient recalled echo (T1WI SPGR), T2-weighted imaging fast spin echo (T2WI FSE), and contrast enhanced arterial phase (AP), delay phase (DP). ASSESSMENT: Two radiologists performed the segmentation of HCC on T1WI, T2WI, AP, and DP images, from which radiomic features were extracted. The RFS related clinical characteristics (VETC, MVI, Barcelona stage, tumor maximum diameter, and alpha fetoprotein) and radiomic features were used to build the clinical model, clinical-radiomic (CR) nomogram, deep learning model. The follow-up process was done 1 month after resection, and every 3 months subsequently. The RFS was defined as the date of resection to the date of recurrence confirmed by radiology or the last follow-up. Patients were followed up until December 31, 2022. STATISTICAL TESTS: Univariate COX regression, least absolute shrinkage and selection operator (LASSO), Kaplan-Meier curves, log-rank test, C-index, and area under the curve (AUC). P < 0.05 was considered statistically significant. RESULTS: The C-index of deep learning model achieved 0.830 in test cohort compared with CR nomogram (0.731), radiomic signature (0.707), and clinical model (0.702). The average RFS of the overall patients was 26.77 months (range 1-80 months). DATA CONCLUSION: MR deep learning model based on VETC and MVI provides a potential tool for survival assessment. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 3.

Purpurogallin Reverses Neuronal Apoptosis and Enhances "M2" Polarization of Microglia Under Ischemia via Mediating the miR-124-3p/TRAF6/NF-κB Axis.

Purpurogallin (PPG) has been demonstrated to exert an anti-inflammatory function in neurological diseases. This study aimed at investigating the role of PPG on microglial polarization post ischemic stroke as well as the underlying mechanism. Mouse hippocampal neurons HT-22 and microglial BV2 cells were treated by oxygen and glucose deprivation to simulate an in-vitro ischemia model. qRT-PCR and ELISA examined expression of cytokines in microglia. CCK8 and flow cytometry measured HT-22 cell viability and apoptosis, respectively. The levels of miR-124-3p and TRAF6/NF-κB were determined. A mouse cerebral ischemia model was set up using middle cerebral artery occlusion (MCAO) method. After being dealt with PPG, the neurological functions, brain edema, neuronal apoptosis, and microglia activation of the mice were evaluated. As suggested by the results, PPG transformed "M1" to "M2" polarization of BV2 cells, and abated HT-22 cell apoptosis. PPG enhanced the neurological functions, alleviated brain edema, and decreased neuroinflammatory responses, and neuronal apoptosis in the brain lesions of MCAO mice. Furthermore, PPG enhanced miR-124-3p and repressed the TRAF6/NF-κB pathway. miR-124-3p suppressed the TRAF6/NF-κB pathway by targeting TRAF6. Collectively, PPG alleviates ischemia-induced neuronal damage and microglial inflammation by modulating the miR-124-3p/TRAF6/NF-κB pathway.

Deep learning nomogram based on Gd-EOB-DTPA MRI for predicting early recurrence in hepatocellular carcinoma after hepatectomy.

OBJECTIVES: The accurate prediction of post-hepatectomy early recurrence in patients with hepatocellular carcinoma (HCC) is crucial for decision-making regarding postoperative adjuvant treatment and monitoring. We aimed to explore the feasibility of deep learning (DL) features derived from gadoxetate disodium (Gd-EOB-DTPA) MRI, qualitative features, and clinical variables for predicting early recurrence. METHODS: In this bicentric study, 285 patients with HCC who underwent Gd-EOB-DTPA MRI before resection were divided into training (n = 195) and validation (n = 90) sets. DL features were extracted from contrast-enhanced MRI images using VGGNet-19. Three feature selection methods and five classification methods were combined for DL signature construction. Subsequently, an mp-MR DL signature fused with multiphase DL signatures of contrast-enhanced images was constructed. Univariate and multivariate logistic regression analyses were used to identify early recurrence risk factors including mp-MR DL signature, microvascular invasion (MVI), and tumor number. A DL nomogram was built by incorporating deep features and significant clinical variables to achieve early recurrence prediction. RESULTS: MVI (p = 0.039), tumor number (p = 0.001), and mp-MR DL signature (p < 0.001) were independent risk factors for early recurrence. The DL nomogram outperformed the clinical nomogram in the training set (AUC: 0.949 vs. 0.751; p < 0.001) and validation set (AUC: 0.909 vs. 0.715; p = 0.002). Excellent DL nomogram calibration was achieved in both training and validation sets. Decision curve analysis confirmed the clinical usefulness of DL nomogram. CONCLUSION: The proposed DL nomogram was superior to the clinical nomogram in predicting early recurrence for HCC patients after hepatectomy. KEY POINTS: • Deep learning signature based on Gd-EOB-DTPA MRI was the predominant independent predictor of early recurrence for hepatocellular carcinoma (HCC) after hepatectomy. • Deep learning nomogram based on clinical factors and Gd-EOB-DTPA MRI features is promising for predicting early recurrence of HCC. • Deep learning nomogram outperformed the conventional clinical nomogram in predicting early recurrence.

Affective Impressions Recognition under Different Colored Lights Based on Physiological Signals and Subjective Evaluation Method.

The design of the light environment plays a critical role in the interaction between people and visual objects in space. Adjusting the space's light environment to regulate emotional experience is more practical for the observers under lighting conditions. Although lighting plays a vital role in spatial design, the effects of colored lights on individuals' emotional experiences are still unclear. This study combined physiological signal (galvanic skin response (GSR) and electrocardiography (ECG)) measurements and subjective assessments to detect the changes in the mood states of observers under four sets of lighting conditions (green, blue, red, and yellow). At the same time, two sets of abstract and realistic images were designed to discuss the relationship between light and visual objects and their influence on individuals' impressions. The results showed that different light colors significantly affected mood, with red light having the most substantial emotional arousal, then blue and green. In addition, GSR and ECG measurements were significantly correlated with impressions evaluation results of interest, comprehension, imagination, and feelings in subjective evaluation. Therefore, this study explores the feasibility of combining the measurement of GSR and ECG signals with subjective evaluations as an experimental method of light, mood, and impressions, which provided empirical evidence for regulating individuals' emotional experiences.

Single-cell RNA sequencing of mouse left ventricle reveals cellular diversity and intercommunication.

Previous studies have revealed the diversity of the whole cardiac cellulome but not refined the left ventricle, which was essential for finding therapeutic targets. Here, we characterized single-cell transcriptional profiles of the mouse left ventricular cellular landscape using single-cell RNA sequencing (10× Genomics). Detailed t-distributed stochastic neighbor embedding (tSNE) analysis revealed the cell types of left ventricle with gene markers. Left ventricular cellulome contained cardiomyocytes highly expressed Trdn, endothelial cells highly expressed Pcdh17, fibroblast highly expressed Lama2, and macrophages highly expressed Hpgds, also proved by in situ hybridization. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analysis (ListHits > 2, P < 0.05) were employed with the DAVID database to investigate subtypes of each cell type with the underlying functions of differentially expressed genes (DEGs). Endothelial cells included 5 subtypes, fibroblasts comprising 7 subtypes, and macrophages contained 11 subtypes. The key representative DEGs (P < 0.001) were Gja4 and Gja5 in cluster 3 of endothelial cells, Aqp2 and Thbs4 in cluster 2 of fibroblasts, and Clec4e and Trem-1 in cluster 3 of macrophages perhaps involved in the occurrence of atherosclerosis, heart failure, and acute myocardial infarction proved by literature review. We also revealed extensive networks of intercellular communication in left ventricle. We suggested possible therapeutic targets for cardiovascular disease and autocrine and paracrine signaling underpins left ventricular homeostasis. This study provided new insights into the structure and function of the mammalian left ventricular cellulome and offers an important resource that will stimulate studies in cardiovascular research.

Evaluating the efficacy and microenvironment changes of HER2 + gastric cancer during HLX02 and Endostar treatment using quantitative MRI.

BACKGROUND AND OBJECTIVES: Trastuzumab is an important targeted drug for HER2-positive gastric cancer. The treatment efficacy of a more cost-effective and accessible trastuzumab biosimilar, HLX02, was not well investigated, especially when combined with antiangiogenic treatment. In addition, the tumour microenvironment detected by functional MRI was still unclear during treatment. This study attempts to evaluate the therapeutic effect of antiangiogenic agents combined with HLX02 in a HER2-positive gastric cancer xenograft model and to detect microenvironmental changes using intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI). MATERIALS AND METHODS: We subcutaneously injected MKN-45 human gastric cancer cells into BALB/C nude mice to establish a tumour model. Twenty-eight mice were divided into four groups and treated with saline (Group 1), Endostar (Group 2), trastuzumab biosimilar HLX02 (Group 3), or the combination of Endostar and HLX02 (Group 4). We then performed IVIM-DWI before and at different time points after treatment. HE, HER2, TUNEL, E-cadherin staining, and α-SMA and CD31 double-staining were used to confirm the pathological changes. RESULTS: Group 4 demonstrated the smallest tumour volume at the end of treatment. The D value in Group 4 increased more dramatically, with the highest value on Day 20, compared with the other groups. Perfusion-related parameters (D* and f values) in Groups 2 and 4 increased initially and reversed after Day 10. Group 4 showed the lowest CD31 and HER2 and the highest TUNEL- and E-cadherin-positive staining rates. The D value was positively correlated with TUNEL but negatively correlated with HER2 staining. The D* and f values had positive correlations with CD31 and E-cadherin expression and the vessel maturity index. CONCLUSIONS: The trastuzumab biosimilar drug HLX02 exhibited good treatment efficacy in HER2-positive gastric cancer, especially when combined with Endostar. IVIM-DWI can noninvasively monitor the process of vascular normalization and reflect the treatment effect early at the molecular level.

Deep convolutional neural network for preoperative prediction of microvascular invasion and clinical outcomes in patients with HCCs.

OBJECTIVES: We aimed to develop and validate a deep convolutional neural network (DCNN) model for preoperative prediction of microvascular invasion (MVI) in hepatocellular carcinoma (HCC) and its clinical outcomes using contrast-enhanced computed tomography (CECT) in a large population of candidates for surgery. METHODS: This retrospective study included 1116 patients with HCC who had undergone preoperative CECT and curative hepatectomy. Radiological (R), DCNN, and combined nomograms were constructed in a training cohort (n = 892) respectively based on clinicoradiological factors, DCNN probabilities, and all factors; the performance of each model was confirmed in a validation cohort (n = 244). Accuracy and the AUC to predict MVI were calculated. Disease-free survival (DFS) and overall survival (OS) after surgery were recorded. RESULTS: The proportion of MVI-positive patients was respectively 38.8% (346/892) and 35.7 % (87/244) in the training and validation cohorts. The AUCs of the R, DCNN, and combined nomograms were respectively 0.809, 0.929, and 0.940 in the training cohorts and 0.837, 0.865, and 0.897 in the validation cohort. The combined nomogram outperformed the R nomogram in the training (p < 0.001) and validation (p = 0.009) cohorts. There was a significant difference in DFS and OS between the R, DCNN, and combined nomogram-predicted groups with and without MVI (p < 0.001). CONCLUSIONS: The combined nomogram based on preoperative CECT performs well for preoperative prediction of MVI and outcome. KEY POINTS: • A combined nomogram based on clinical information, preoperative CECT, and DCNN can predict MVI and clinical outcomes of patients with HCC. • DCNN provides added diagnostic ability to predict MVI. • The AUCs of the combined nomogram are 0.940 and 0.897 in the training and validation cohorts, respectively.