Deep learning reconstruction for coronary CT angiography in patients with origin anomaly, stent or bypass graft.

PURPOSE: To develop and validate a deep learning (DL)-model for automatic reconstruction for coronary CT angiography (CCTA) in patients with origin anomaly, stent or bypass graft. MATERIAL AND METHODS: In this retrospective study, a DL model for automatic CCTA reconstruction was developed with training and validation sets from 6063 and 1962 patients. The algorithm was evaluated on an independent external test set of 812 patients (357 with origin anomaly or revascularization, 455 without). The image quality of DL reconstruction and manual reconstruction (using dedicated cardiac reconstruction software provided by CT vendors) was compared using a 5-point scale. The successful reconstruction rates and post-processing time for two methods were recorded. RESULTS: In the external test set, 812 patients (mean age, 64.0 ± 11.6, 100 with origin anomalies, 152 with stents, 105 with bypass grafts) were evaluated. The successful rates for automatic reconstruction were 100% (455/455), 97% (97/100), 100% (152/152), and 76.2% (80/105) in patients with native vessel, origin anomaly, stent, and bypass graft, respectively. The image quality scores were significantly higher for DL reconstruction than those for manual approach in all subgroups (4 vs. 3 for native vessel, 4 vs. 4 for origin anomaly, 4 vs. 3 for stent and 4 vs. 3 for bypass graft, all p < 0.001). The overall post-processing time was remarkably reduced for DL reconstruction compared to manual method (11 s vs. 465 s, p < 0.001). CONCLUSIONS: The developed DL model enabled accurate automatic CCTA reconstruction of bypass graft, stent and origin anomaly. It significantly reduced post-processing time and improved clinical workflow.

Effect of Prosocial Behaviors on e-Consultations in a Web-Based Health Care Community: Panel Data Analysis.

BACKGROUND: Patients using web-based health care communities for e-consultation services have the option to choose their service providers from an extensive digital market. To stand out in this crowded field, doctors in web-based health care communities often engage in prosocial behaviors, such as proactive and reactive actions, to attract more users. However, the effect of these behaviors on the volume of e-consultations remains unclear and warrants further exploration. OBJECTIVE: This study investigates the impact of various prosocial behaviors on doctors' e-consultation volume in web-based health care communities and the moderating effects of doctors' digital and offline reputations. METHODS: A panel data set containing information on 2880 doctors over a 22-month period was obtained from one of the largest web-based health care communities in China. Data analysis was conducted using a 2-way fixed effects model with robust clustered SEs. A series of robustness checks were also performed, including alternative measurements of independent variables and estimation methods. RESULTS: Results indicated that both types of doctors' prosocial behaviors, namely, proactive and reactive actions, positively impacted their e-consultation volume. In terms of the moderating effects of external reputation, doctors' offline professional titles were found to negatively moderate the relationship between their proactive behaviors and their e-consultation volume. However, these titles did not significantly affect the relationship between doctors' reactive behaviors and their e-consultation volume (P=.45). Additionally, doctors' digital recommendations from patients negatively moderated both the relationship between doctors' proactive behaviors and e-consultation volume and the relationship between doctors' reactive behaviors and e-consultation volume. CONCLUSIONS: Drawing upon functional motives theory and social exchange theory, this study categorizes doctors' prosocial behaviors into proactive and reactive actions. It provides empirical evidence that prosocial behaviors can lead to an increase in e-consultation volume. This study also illuminates the moderating roles doctors' digital and offline reputations play in the relationships between prosocial behaviors and e-consultation volume.

Validation of biomechanical assessment of coronary plaque vulnerability based on intravascular optical coherence tomography and digital subtraction angiography.

Background: It has been suggested that biomechanical factors may influence plaque development. However, key determinants for assessing plaque vulnerability remain speculative. Methods: In this study, a two-dimensional (2D) structural mechanical analysis and a three-dimensional (3D) fluid-structure interaction (FSI) analysis were conducted based on intravascular optical coherence tomography (IV-OCT) and digital subtraction angiography (DSA) data sets. In the 2D study, 103 IV-OCT slices were analyzed. An in-depth morpho-mechanic analysis and a weighted least absolute shrinkage and selection operator (LASSO) regression analysis were conducted to identify the crucial features related to plaque vulnerability via the tuning parameter (λ). In the 3D study, the coronary model was reconstructed by fusing the IV-OCT and DSA data, and a FSI analysis was subsequently performed. The relationship between vulnerable plaque and wall shear stress (WSS) was investigated. Results: The influential factors were selected using the minimum criteria (λ-min) and one-standard error criteria (λ-1se). In addition to the common vulnerable factor of the minimum fibrous cap thickness (FCTmin), four biomechanical factors were selected by λ-min, including the average/maximal displacements and average/maximal stress, and two biomechanical factors were selected by λ-1se, including the average/maximal displacements. Additionally, the positions of the vulnerable plaques were consistent with the sites of high WSS. Conclusions: Functional indices are crucial for plaque status assessment. An evaluation based on biomechanical simulations might provide insights into risk identification and guide therapeutic decisions.

Leritrelvir for the treatment of mild or moderate COVID-19 without co-administered ritonavir: a multicentre randomised, double-blind, placebo-controlled phase 3 trial.

Background: Leritrelvir is a novel α-ketoamide based peptidomimetic inhibitor of SARS-CoV-2 main protease. A preclinical study has demonstrated leritrelvir poses similar antiviral activities towards different SARS-CoV-2 variants compared with nirmatrelvir. A phase 2 clinical trial has shown a comparable antiviral efficacy and safety between leritrelvir with and without ritonavir co-administration. This trial aims to test efficacy and safety of leritrelvir monotherapy in adults with mild-to-moderate COVID-19. Methods: This was a randomised, double-blind, placebo-controlled, multicentre phase 3 trial at 29 clinical sites in China. Enrolled patients were from 18 to 75 years old, diagnosed with mild or moderate COVID-19 and not requiring hospitalization. Patients had a positive SARS-CoV-2 nucleic acid test (NAT) and at least one of the COVID-19 symptoms within 48 h before randomization, and the interval between the first positive SARS-CoV-2 NAT and randomization was ≤120 h (5 days). Patients were randomly assigned in a 1:1 ratio to receive a 5-day course of either oral leritrelvir 400 mg TID or placebo. The primary efficacy endpoint was the time from the first dose to sustained clinical recovery of all 11 symptoms (stuffy or runny nose, sore throat, shortness of breath or dyspnea, cough, muscle or body aches, headache, chills, fever ≥37 °C, nausea, vomiting, and diarrhea). The safety endpoint was the incidence of adverse events (AE). Primary and safety analyses were performed in the intention-to-treat (ITT) population. This study is registered with ClinicalTrials.gov, NCT05620160. Findings: Between Nov 12 and Dec 30, 2022 when the zero COVID policy was abolished nationwide, a total of 1359 patients underwent randomization, 680 were assigned to leritrelvir group and 679 to placebo group. The median time to sustained clinical recovery in leritrelvir group was significantly shorter (251.02 h [IQR 188.95-428.68 h]) than that of Placebo (271.33 h [IQR 219.00-529.63 h], P = 0.0022, hazard ratio [HR] 1.20, 95% confidence interval [CI], 1.07-1.35). Further analysis of subgroups for the median time to sustained clinical recovery revealed that (1) subgroup with positive viral nucleic acid tested ≤72 h had a 33.9 h difference in leritrelvir group than that of placebo; (2) the subgroup with baseline viral load >8 log 10 Copies/mL in leritrelvir group had 51.3 h difference than that of placebo. Leritrelvir reduced viral load by 0.82 log10 on day 4 compared to placebo. No participants in either group progressed to severe COVID-19 by day 29. Adverse events were reported in two groups: leritrelvir 315 (46.46%) compared with placebo 292 (43.52%). Treatment-relevant AEs were similar 218 (32.15%) in the leritrelvir group and 186 (27.72%) in placebo. Two cases of COVID-19 pneumonia were reported in placebo group, and one case in leritrelvir group, none of them were considered by the investigators to be leritrelvir related. The most frequently reported AEs (occurring in ≥5% of participants in at least one group) were laboratory finding: hypertriglyceridemia (leritrelvir 79 [11.7%] vs. placebo 70 [10.4%]) and hyperlipidemia (60 [8.8%] vs. 52 [7.7%]); all of them were nonserious. Interpretation: Leritrelvir monotherapy has good efficacy for mild-to-moderate COVID-19 and without serious safety concerns. Funding: This study was funded by the National Multidisciplinary Innovation Team Project of Traditional Chinese Medicine, Guangdong Science and Technology Foundation, Guangzhou Science and Technology Planning Project and R&D Program of Guangzhou Laboratory.

A Composite Bioinformatic Analysis to Explore Endoplasmic Reticulum Stress-Related Prognostic Marker and Potential Pathogenic Mechanisms in Glioma by Integrating Multiomics Data.

In recent years, abnormal endoplasmic reticulum stress (ERS) response, as an important regulator of immunity, may play a vital role in the occurrence, development, and treatment of glioma. Weighted correlation network analysis (WGCNA) based on six glioma datasets was used to screen eight prognostic-related differentially expressed ERS-related genes (PR-DE-ERSGs) and to construct a prognostic model. BMP2 and HEY2 were identified as protective factors (HR < 1), and NUP107, DRAM1, F2R, PXDN, RNF19A, and SCG5 were identified as risk factors for glioma (HR > 1). QRT-PCR further supported significantly higher DRAM1 and lower SCG5 relative mRNA expression in gliomas. Our model has demonstrated excellent performance in predicting the prognosis of glioma patients from numerous datasets. In addition, the model shows good stability in multiple tests. Our model also shows broad clinical promise in predicting drug treatment effects. More immune cells/processes in the high-risk population with poor prognosis illustrate the importance of the tumor immunosuppressive environment in glioma. The potential role of the HEY2-based competitive endogenous RNA (ceRNA) regulatory network in glioma was validated and revealed the possible important role of glycolysis in glioma ERS. IDH1 and TP53 mutations with better prognosis were strongly associated with the risk score and PR-DE-ERSGs expression in the model. mDNAsi was also closely related to the risk score and clinical characteristics.

Systematic pan-cancer analysis identifies APOC1 as an immunological biomarker which regulates macrophage polarization and promotes tumor metastasis.

Apolipoprotein C1 (APOC1) has been found to play an essential part in proliferation and metastasis of numerous cancers, but related mechanism has not been elucidated, especially its function and role in tumor immunity. Through systematic pan-cancer analysis, we identified that APOC1 was closely associated with the infiltration of various immune cells in multiple cancers. Besides, APOC1 was significantly co-expressed with the immune checkpoints, major histocompatibility complex (MHC) molecules, chemokines and other immune-related genes. Furthermore, single-cell sequencing analysis suggested that the vast majority of APOC1 was expressed in macrophages or tumor-associated macrophages (TAMs). Additionally, the expression of APOC1 was significantly related to the prognosis of different cancers. Since APOC1 was most significantly abnormally expressed in renal cell cancer (RCC), subsequent experiments were carried out in RCC to explore the role of APOC1 in tumor immunity. The expression of APOC1 was significantly elevated in the tumor and serum of RCC patients. Besides, APOC1 was mainly expressed in the macrophage and it was closely related to the immune cell infiltration of RCC. Co-culture with RCC cells could induce the generation of TAMs with M2 phenotype which be blocked by silencing APOC1. The expression of APOC1 was elevated in the M2 or TAMs and APOC1 promoted M2 polarization of macrophages through interacting with CD163 and CD206. Furthermore, macrophages overexpressing APOC1 promoted the metastasis of RCC cells via secreting CCL5. Together, these data indicate that APOC1 is an immunological biomarker which regulates macrophage polarization and promotes tumor metastasis.

Optimization of the Ultrasonic-Assisted Extraction Technology of Steroidal Saponins from Polygonatum kingianum Collett & Hemsl and Evaluating Its Quality Planted in Different Areas.

Polygonatum kingianum Collett & Hemsl is one of the famous traditional Chinese herbs with satisfactory therapeutic effects on invigorating Qi, nourishing Yin and moistening lungs, in which steroidal saponins are one class of important active substances. The main purpose is to determine the optimal extraction technology of steroidal saponins and evaluate the quality of P. kingianum planted in five different areas. The optimal ultrasonic-assisted extraction (UAE) technology was established by using single-factor experiments and the response surface methodology (RSM), and the determination method of high-performance liquid chromatography (HPLC) for dioscin and diosgenin, two primary types of acid-hydrolyzed steroidal saponins, was constructed with good linear range and precision. The results showed that UAE was an efficient extraction method for steroidal saponins, and the extraction yield was significantly affected by the liquid-solid ratio. The optimal extraction technology was generated following a liquid-solid ratio of 10:1 (mL/g), an ethanol concentration of 85% (v/v), an extraction time of 75 min, an extraction temperature of 50 °C and three extractions, of which these parameters were in line with the predicted values calculated by RSM. Considering only dioscin and diosgenin, the quality of P. kingianum planted at five sample plots presented non-significant difference. However, the content of diosgenin in Pingbian Prefecture (PB) was higher than that of the other four areas with a value of 0.46 mg/g. Taken together, the optimal UAE technology for P. kingianum steroidal saponins was determined via RSM. The quality evaluation revealed that there was a non-significant difference among P. kingianum planted in different areas based on the contents of the sum of dioscin and diosgenin. This work has important reference value for the exploitation and utilization of P. kingianum.

A Panax notoginseng phosphate transporter, PnPht1;3, greatly contributes to phosphate and arsenate uptake.

The crisis of arsenic (As) accumulation in rhizomes threatens the quality and safety of Panax notoginseng (Burk.) F.H. Chen, which is a well-known traditional Chinese herb with a long clinical history. The uptake of arsenate (AsV) could be suppressed by supplying phosphate (Pi), in which Pi transporters play important roles in the uptake of Pi and AsV. Herein, the P . notoginseng Pi transporter-encoding gene PnPht1;3 was identified and characterised under Pi deficiency and AsV exposure. In this study, the open reading frame (ORF) of PnPht1;3 was cloned according to RNA-seq and encoded 545 amino acids. The relative expression levels revealed that PnPht1;3 was significantly upregulated under phosphate deficiency and AsV exposure. Heterologous expression in Saccharomyces cerevisiae MB192 demonstrated that PnPht1;3 performed optimally in complementing the yeast Pi-transport defect and accumulated more As in the cells. Combined with the subcellular localisation prediction, it was concluded that PnPht1;3 encodes a functional plasma membrane-localised transporter protein that mediates putative high-affinity Pi/H+ symport activity and enhances the uptake of Pi and AsV. Therefore, a better understanding of the roles of the P . notoginseng Pi transporter could provide new insight for solving As accumulation in medicinal plants.

A disease category feature database construction method of brain image based on deep convolutional neural network.

BACKGROUND: Constructing a medical image feature database according to the category of disease can achieve a quick retrieval of images with similar pathological features. Therefore, this approach has important application values in the fields such as auxiliary diagnosis, teaching, research, and telemedicine. METHODS: Based on the deep convolutional neural network, an image classifier applicable to brain disease was designed to distinguish between the image features of the different brain diseases with similar anatomical structures. Through the extraction and analysis of visual features, the images were labelled with the corresponding semantic features of a specific disease category, which can establish an association between the visual features of brain images and the semantic features of the category of disease which will permit to construct a disease category feature database of brain images. RESULTS: Based on the similarity measurement and the matching strategy of high-dimensional visual feature, a high-precision retrieval of brain image with semantics category was achieved, and the constructed disease category feature database of brain image was tested and evaluated through large numbers of pathological image retrieval experiments, the accuracy and the effectiveness of the proposed approach was verified. CONCLUSION: The disease category feature database of brain image constructed by the proposed approach achieved a quick and effective retrieval of images with similar pathological features, which is beneficial to the categorization and analysis of intractable brain diseases. This provides an effective application tool such as case-based image data management, evidence-based medicine and clinical decision support.

Exploring Patients' Intentions for Continuous Usage of mHealth Services: Elaboration-Likelihood Perspective Study.

BACKGROUND: With the increasingly rapid development of Web 2.0 technologies, the application of mobile health (mHealth) care in the field of health management has become popular. Accordingly, patients are able to access consulting services and effective health information online without temporal and geographical constraints. The elaboration-likelihood model (ELM) is a dual-process persuasion theory that describes the change of attitudes and behavior. OBJECTIVE: In this study, we drew on the ELM to investigate patients' continuous usage intentions regarding mHealth services. In addition, we further examined which route-central or peripheral-has a stronger impact on a patient's usage of health care management. METHODS: To meet these objectives, five hypotheses were developed and empirically validated using a field survey to test the direct and indirect effects, via attitude, of the two routes on continuous usage intention. RESULTS: We found that patients' perceived mHealth information quality and perceived mHealth system quality had a positive effect on their personal attitudes. The results revealed that social media influence had a positive effect on a patient's attitude toward mHealth services. In particular, our findings suggest that a patient's health consciousness has a positive effect on the relationship between social media influence and attitude. CONCLUSIONS: This study contributes to the mHealth services literature by introducing the ELM as a referent theory for research, as well as by specifying the moderating role of health consciousness. For practitioners, this study introduces influence processes as policy tools that managers can employ to motivate the uptake of mHealth services within their organizations.

Phosphate transporters, PnPht1;1 and PnPht1;2 from Panax notoginseng enhance phosphate and arsenate acquisition.

BACKGROUND: Panax notoginseng is a medicinally important Chinese herb with a long history of cultivation and clinical application. The planting area is mainly distributed in Wenshan Prefecture, where the quality and safety of P. notoginseng have been threatened by high concentration of arsenic (As) from the soil. The roles of phosphate (Pi) transporters involved in Pi acquisition and arsenate (AsV) tolerance were still unclear in this species. RESULTS: In this study, two open reading frames (ORFs) of PnPht1;1 and PnPht1;2 separated from P. notoginseng were cloned based on RNA-seq, which encoded 527 and 541 amino acids, respectively. The results of relative expression levels showed that both genes responded to the Pi deficiency or As exposure, and were highly upregulated. Heterologous expression in Saccharomyces cerevisiae MB192 revealed that PnPht1;1 and PnPht1;2 performed optimally in complementing the yeast Pi-transport defect, particularly in PnPht1;2. Cells expressing PnPht1;2 had a stronger AsV tolerance than PnPht1;1-expressing cells, and accumulated less As in cells under a high-Pi concentration. Combining with the result of plasma membrane localization, these data confirmed that transporters PnPht1;1 and PnPht1;2 were putative high-affinity H+/H2PO4- symporters, mediating the uptake of Pi and AsV. CONCLUSION: PnPht1;1 and PnPht1;2 encoded functional plasma membrane-localized transporter proteins that mediated a putative high-affinity Pi/H+ symport activity. Expression of PnPht1;1 or PnPht1;2 in mutant strains could enhance the uptake of Pi and AsV, that is probably responsible for the As accumulation in the roots of P. notoginseng.

Tropomodulin1 Expression Increases Upon Maturation in Dendritic Cells and Promotes Their Maturation and Immune Functions.

Dendritic cells (DCs) are the most potent antigen-presenting cells. Upon maturation, DCs express costimulatory molecules and migrate to the lymph nodes to present antigens to T cells. The actin cytoskeleton plays key roles in multiple aspects of DC functions. However, little is known about the mechanisms and identities of actin-binding proteins that control DC maturation and maturation-associated functional changes. Tropomodulin1 (Tmod1), an actin-capping protein, controls actin depolymerization and nucleation. We found that Tmod1 was expressed in bone marrow-derived immature DCs and was significantly upregulated upon lipopolysaccharide (LPS)-induced DC maturation. By characterizing LPS-induced mature DCs (mDCs) from Tmod1 knockout mice, we found that compared with Tmod1+/+ mDCs, Tmod1-deficient mDCs exhibited lower surface expression of costimulatory molecules and chemokine receptors and reduced secretion of inflammatory cytokines, suggesting that Tmod1 deficiency retarded DC maturation. Tmod1-deficient mDCs also showed impaired random and chemotactic migration, deteriorated T-cell stimulatory ability, and reduced F-actin content and cell stiffness. Furthermore, Tmod1-deficient mDCs secreted high levels of IFN-ß and IL-10 and induced immune tolerance in an experimental autoimmune encephalomyelitis (EAE) mouse model. Mechanistically, Tmod1 deficiency affected TLR4 signaling transduction, resulting in the decreased activity of MyD88-dependent NFκB and MAPK pathways but the increased activity of the TRIF/IRF3 pathway. Rescue with exogenous Tmod1 reversed the effect of Tmod1 deficiency on TLR4 signaling. Therefore, Tmod1 is critical in regulating DC maturation and immune functions by regulating TLR4 signaling and the actin cytoskeleton. Tmod1 may be a potential target for modulating DC functions, a strategy that would be beneficial for immunotherapy for several diseases.

Incentive Contract Design for the Water-Rail-Road Intermodal Transportation with Travel Time Uncertainty: A Stackelberg Game Approach.

In the management of intermodal transportation, incentive contract design problem has significant impacts on the benefit of a multimodal transport operator (MTO). In this paper, we analyze a typical water-rail-road (WRR) intermodal transportation that is composed of three serial transportation stages: water, rail and road. In particular, the entire transportation process is planned, organized, and funded by an MTO that outsources the transportation task at each stage to independent carriers (subcontracts). Due to the variability of transportation conditions, the travel time of each transportation stage depending on the respective carrier's effort level is unknown (asymmetric information) and characterized as an uncertain variable via the experts' estimations. Considering the decentralized decision-making process, we interpret the incentive contract design problem for the WRR intermodal transportation as a Stackelberg game in which the risk-neutral MTO serves as the leader and the risk-averse carriers serve as the followers. Within the framework of uncertainty theory, we formulate an uncertain bi-level programming model for the incentive contract design problem under expectation and entropy decision criteria. Subsequently, we provide the analytical results of the proposed model and analyze the optimal time-based incentive contracts by developing a hybrid solution method which combines a decomposition approach and an iterative algorithm. Finally, we give a simulation example to investigate the impact of asymmetric information on the optimal time-based incentive contracts and to identify the value of information for WRR intermodal transportation.

Research on supply chain performance based on retailers' fairness concerns: Wholesale prices versus cost sharing of efforts.

With the deepening of the research on supply chain management, scholars have increasingly begun to investigate the impact of fairness on a supply chain, and many conclusions suggest that a simple wholesale price can coordinate a supply chain under specific conditions. However, the corresponding analysis and other optimization mechanisms that affect the situation in which the channel cannot be coordinated are either omitted or given little attention. In this paper, we constructed a dyadic supply chain with a single manufacturer and a single retailer; the manufacturer acts as a selfish leader, and the retailer acts as a follower with fairness concerns and sales efforts. For this setting, we derived the equilibrium strategy solution for a wholesale price contract and cost sharing of effort (CS-E) contract offered by the manufacturer, and the results indicated that both contracts achieved channel coordination with different requirements. Further, the profit of the manufacturer and the sales effort of the retailer under CS-E contracts were never less than those for the wholesale price contract, and there was an interval during which the retailer's profit and utility and supply chain efficiency were better than those under the wholesale price contract. In addition, we described situations in which a CS-E contract is unnecessary. These results should be a useful reference for managerial decisions and organizations.

Diffusion MRI biomarkers predict the outcome of irreversible electroporation in a pancreatic tumor mouse model.

The purpose of this work is to explore the potential contribution of diffusion MRI to predict the effects of irreversible electroporation (IRE) in a pancreatic ductal adenocarcinoma (PDAC) mouse model. Thirteen mice were injected with Panc-02 PDAC cells in both flanks. One tumor was treated with IRE when it reached a diameter of about 5 mm. T2- and diffusion-weighted MRI sequences were acquired before IRE treatment and 1, 3 and 7 days later. The mice were euthanized 1 day (n = 6) or 2 weeks (n = 7) after treatment. The tumors were excised and stained with H&E, caspase-3, CD-3, F4/80. The volume and the mean and standard deviation of the apparent diffusion coefficient (ADC) were compared between treated and untreated lesions and correlated with histology-derived measures. At 1-day post-treatment, a dramatic ADC increase (+50.81%, P < 0.05) was found in ablated lesions, strongly correlated with apoptosis (τ = 0.90). At later time points the ADC returned to pre-treatment values, though histopathology showed a quite different scenario compared to the untreated controls. The ADC standard deviation measured within the treated tumors 1 day after IRE treatment had a strong negative correlation with the number of tumor cells found 14 days later (τ = 0.80). There was also a strong correlation between 1-day ADC and 14-day apoptosis in untreated tumors (τ = 0.95). In conclusion, diffusion MRI is sensitive to the short-term effects of IRE in PDAC tumors, and can help predict the long-term treatment outcome.

Genetically confirmed familial hypercholesterolemia in outpatients with hypercholesterolemia.

BACKGROUND: Familial hypercholesterolemia (FH) is an autosomal dominant disorder of lipoprotein metabolism which can lead to premature coronary heart disease (pCHD). There are about 3.8 million potential FH patients in China, whereas the clinical and genetic data of FH are limited. METHODS: Dutch Lipid Clinic Network (DLCN) criteria was used to diagnose FH in outpatients with hypercholesterolemia. Resequencing chip analysis combined with Sanger sequencing validation were used to identify mutations in the definite FH patients according to DLCN criteria. In silico analysis was conducted in mutations with previously unknown pathogenicity. Then, the novel mutant receptors were transfected into human embryo kidney 293 (HEK-293) cells. The binding and the internalization activities of the mutant receptors were analyzed by flow cytometry. RESULTS: The prevalence of definite FH in outpatients with hypercholesterolemia in this study is 3.2%. Using genetic testing, one homozygous FH (HoFH), one heterozygous FH (HeFH) and three compound heterozygous FH patients were confirmed. Eight mutations in low-density lipoprotein receptor (LDLR) gene were identified, in which c.357delG was a novel mutation and co-segregated with the FH phenotype. Bioinformatic analysis confirmed that c.357delG was a pathogenic mutation. Furthermore, when compared with the wild-type LDLRs by flow cytometry analysis, the binding and internalization activities of c.357delG mutant LDLRs were reduced by 35% and 49%, respectively. CONCLUSIONS: This study identified eight LDLR gene mutations in five patients with definite FH, in which c.357delG is a novel pathogenic mutation. These findings increase our understanding of the genetic spectrum of FH in China.

MRI-guided interventional natural killer cell delivery for liver tumor treatment.

While natural killer (NK) cell-based adoptive transfer immunotherapy (ATI) provides only modest clinical success in cancer patients. This study was hypothesized that MRI-guided transcatheter intra-hepatic arterial (IHA) infusion permits local delivery to liver tumors to improve outcomes during NK-based ATI in a rat model of hepatocellular carcinoma (HCC). Mouse NK cells were labeled with clinically applicable iron nanocomplexes. Twenty rat HCC models were assigned to three groups: transcatheter IHA saline infusion as the control group, transcatheter IHA NK infusion group, and intravenous (IV) NK infusion group. MRI studies were performed at baseline and at 24 h, 48 h, and 8 days postinfusion. There was a significant difference in tumor R2* values between baseline and 24 h following the selective transcatheter IHA NK delivery to the tumors (P = 0.039) when compared to IV NK infusion (P = 0.803). At 8 days postinfusion, there were significant differences in tumor volumes between the control, IV, and IHA NK infusion groups (control vs. IV, P = 0.196; control vs. IHA, P < 0.001; and IV vs. IHA, P = 0.001). Moreover, there was a strong correlation between tumor R2* value change (∆R2*) at 24 h postinfusion and tumor volume change (∆volume) at 8 days in IHA group (R2  = 0.704, P < 0.001). Clinically applicable labeled NK cells with 12-h labeling time can be tracked by MRI. Transcatheter IHA infusion improves NK cell homing efficacy and immunotherapeutic efficiency. The change in tumor R2* value 24 h postinfusion is an important early biomarker for prediction of longitudinal response.

18F-FDG PET Biomarkers Help Detect Early Metabolic Response to Irreversible Electroporation and Predict Therapeutic Outcomes in a Rat Liver Tumor Model.

Purpose To test the hypothesis that biomarkers of fluorine 18 (18F) fluorodeoxyglucose (FDG) positron emission tomography (PET) can be used for the early detection of therapeutic response to irreversible electroporation (IRE) of liver tumor in a rodent liver tumor model. Materials and Methods The institutional animal care and use committee approved this study. Rats were inoculated with McA-RH7777 liver tumor cells in the left median and left lateral lobes. Tumors were allowed to grow for 7 days to reach a size typically at least 5 mm in longest diameter, as verified with magnetic resonance (MR) imaging. IRE electrodes were inserted, and eight 100-µsec, 2000-V pulses were applied to ablate the tumor tissue in the left median lobe. Tumor in the left lateral lobe served as a control in each animal. PET/computed tomography (CT) and MR imaging measurements were performed at baseline and 3 days after IRE for each animal. Additional MR imaging measurements were obtained 14 days after IRE. After 14-day follow-up MR imaging, rats were euthanized and tumors harvested for hematoxylin-eosin, CD34, and caspase-3 staining. Change in the maximum standardized uptake value (ΔSUVmax) was calculated 3 days after IRE. The maximum lesion diameter change (ΔDmax) was measured 14 days after IRE by using axial T2-weighted imaging. ΔSUVmax and ΔDmax were compared. The apoptosis index was calculated by using caspase-3-stained slices of apoptotic tumor cells. Pearson correlation coefficients were calculated to assess the relationship between ΔSUVmax at 3 days and ΔDmax (or apoptosis index) at 14 days after IRE treatment. Results ΔSUVmax, ΔDmax, and apoptosis index significantly differed between treated and untreated tumors (P < .001 for all). In treated tumors, there was a strong correlation between ΔSUVmax 3 days after IRE and ΔDmax 14 days after IRE (R = 0.66, P = .01) and between ΔSUVmax 3 days after IRE and apoptosis index 14 days after IRE (R = 0.57, P = .04). Conclusion 18F-FDG PET imaging biomarkers can be used for the early detection of therapeutic response to IRE treatment of liver tumors in a rodent model. © RSNA, 2017.