Antigravity Autonomous Superwettable Pumps for Spontaneous Separation of Oil-Water Emulsions.

Oil-water separation based on superwettable materials offers a promising way for the treatment of oil-water mixtures and emulsions. Nevertheless, such separation techniques often require complex devices and external energy input. Therefore, it remains a great challenge to separate oil-water mixtures and emulsions through an energy-efficient, economical, and sustainable way. Here, a novel approach demonstrating the successful separation of oil-water emulsions using antigravity-driven autonomous superwettable pumps is presented. By transitioning from traditional gravity-driven to antigravity-driven separation, the study showcases the unprecedented success in purifying oil/water from emulsions by capillary/siphon-driven superwettable autonomous pumps. These pumps, composed of self-organized interconnected channels formed by the packing of superhydrophobic and superhydrophilic sand particles, exhibit outstanding separation flux, efficiency, and recyclability. The findings of this study not only open up a new avenue for oil-water emulsion separation but also hold promise for profound impacts in the field.

Association of stress hyperglycemia ratio with left ventricular function and microvascular obstruction in patients with ST-segment elevation myocardial infarction: a 3.0 T cardiac magnetic resonance study.

BACKGROUND: Stress hyperglycemia, which is associated with poor prognosis in patients with acute myocardial infarction (AMI), can be determined using the stress hyperglycemia ratio (SHR). Impaired left ventricular function and microvascular obstruction (MVO) diagnosed using cardiac magnetic resonance (CMR) have also been proven to be linked to poor prognosis in patients with AMI and aid in risk stratification. However, there have been no studies on the correlation between fasting SHR and left ventricular function and MVO in patients with acute ST-segment elevation myocardial infarction (ASTEMI). Therefore, this study aimed to investigate the additive effect of fasting SHR on left ventricular function and global deformation in patients with ASTEMI and to explore the association between fasting SHR and MVO. METHODS: Consecutive patients who underwent CMR at index admission (3-7 days) after primary percutaneous coronary intervention (PPCI) were enrolled in this study. Basic clinical, biochemical, and CMR data were obtained and compared among all patients grouped by fasting SHR tertiles: SHR1: SHR < 0.85; SHR2: 0.85 ≤ SHR < 1.01; and SHR3: SHR ≥ 1.01. Spearman's rho (r) was used to assess the relationship between fasting SHR and left ventricular function, myocardial strain, and the extent of MVO. Multivariable linear regression analysis was performed to evaluate the determinants of left ventricular function and myocardial strain impairment in all patients with AMI. Univariable and multivariable regression analyses were performed to investigate the correlation between fasting SHR and the presence and extent of MVO in patients with AMI and those with AMI and diabetes mellitus (DM). RESULTS: A total of 357 patients with ASTEMI were enrolled in this study. Left ventricular ejection fraction (LVEF) and left ventricular global function index (LVGFI) were significantly lower in SHR2 and SHR3 than in SHR1. Compared with SHR1 and SHR2 groups, left ventricular strain was lower in SHR3, as evidenced by global radial (GRS), global circumferential (GCS), and global longitudinal (GLS) strains. Fasting SHR were negatively correlated with LVEF, LVGFI, and GRS (r = - 0.252; r = - 0.261; and r = - 0.245; all P<0.001) and positively correlated with GCS (r = 0.221) and GLS (r = 0.249; all P <0.001). Multivariable linear regression analysis showed that fasting SHR was an independent determinant of impaired LVEF, LVGFI, GRS, and GLS. Furthermore, multivariable regression analysis after adjusting for covariates signified that fasting SHR was associated with the presence and extent of MVO in patients with AMI and those with AMI and DM. CONCLUSION: Fasting SHR in patients with ASTEMI successfully treated using PPCI is independently associated with impaired cardiac function and MVO. In patients with AMI and DM, fasting SHR is an independent determinant of the presence and extent of MVO.

Ultra-Tough and Highly Stretchable Dual-Crosslinked Eutectogel Based on Coordinated and Non-Coordinated Two Types Deep Eutectic Solvent Mixture.

Eutectogels are gaining attention in flexible device applications for their superior ionic conductivity, stability, biocompatibility, and cost-effectiveness. However, most existing eutectogels suffer from low strength and toughness. Herein, ultra-tough and highly stretchable polyacrylamide (PAM) eutectogels featuring a dual-crosslinked network comprising chemical cross-linking and physical cross-linking facilitated by metal coordination bonds and hydrogen bonds are developed. This is achieved through a controlled strategy involving polymerization of acrylamide in a coordinated metal salt-type deep eutectic solvent (DES) combined with a non-coordinated choline chloride (ChCl)-type DES mixture. By varying the molar ratio of these two types of DES, exceptional and adjustable mechanical properties of the resulting eutectogel are achieved, including a high tensile strength ranging from 2.9 to 8.2 MPa and elongation at break ranging from 1725 to 747%, at a 70 wt% DES content. Furthermore, the reversible non-covalent crosslinking in these eutectogels enables self-recovery and self-healing capabilities of eutectogels. The prepared eutectogels also exhibit outstanding ionic conductivity (3.56 mS cm-1 ), making them well-suited for use as strain sensors in human motion detection. The toughening strategy is universally effective for creating tough eutectogels using coordinated metal salt-type DES with various metal ions, as well as a diverse range of coordinatable polymers.

Deep Learning-based Prediction of Percutaneous Recanalization in Chronic Total Occlusion Using Coronary CT Angiography.

Background CT is helpful in guiding the revascularization of chronic total occlusion (CTO), but manual prediction scores of percutaneous coronary intervention (PCI) success have challenges. Deep learning (DL) is expected to predict success of PCI for CTO lesions more efficiently. Purpose To develop a DL model to predict guidewire crossing and PCI outcomes for CTO using coronary CT angiography (CCTA) and evaluate its performance compared with manual prediction scores. MATERIALS AND METHODS: Participants with CTO lesions were prospectively identified from one tertiary hospital between January 2018 and December 2021 as the training set to develop the DL prediction model for PCI of CTO, with fivefold cross validation. The algorithm was tested using an external test set prospectively enrolled from three tertiary hospitals between January 2021 and June 2022 with the same eligibility criteria. All participants underwent preprocedural CCTA within 1 month before PCI. The end points were guidewire crossing within 30 minutes and PCI success of CTO.Results A total of 534 participants (mean age, 57.7 years ± 10.8 [SD]; 417 [78.1%] men) with 565 CTO lesions were included. In the external test set (186 participants with 189 CTOs), the DL model saved 85.0% of the reconstruction and analysis time of manual scores (mean, 73.7 seconds vs 418.2-466.9 seconds) and had higher accuracy than manual scores in predicting guidewire crossing within 30 minutes (DL, 91.0%; CT Registry of Chronic Total Occlusion Revascularization, 61.9%; Korean Multicenter CTO CT Registry [KCCT], 68.3%; CCTA-derived Multicenter CTO Registry of Japan (J-CTO), 68.8%; P < .05) and PCI success (DL, 93.7%; KCCT, 74.6%; J-CTO, 75.1%; P < .05). For DL, the area under the receiver operating characteristic curve was 0.97 (95% CI: 0.89, 0.99) for the training test set and 0.96 (95% CI: 0.90, 0.98) for the external test set. Conclusion The DL prediction model accurately predicted the percutaneous recanalization outcomes of CTO lesions and increased the efficiency of noninvasively grading the difficulty of PCI. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Pundziute-do Prado in this issue.

Quantification of Early Diffuse Myocardial Fibrosis Through 7.0 T Cardiac Magnetic Resonance T1 Mapping in a Type 1 Diabetic Mellitus Mouse Model.

BACKGROUND: Diffuse myocardial interstitial fibrosis (DMIF) is a key factor for heart failure (HF) in diabetic cardiomyopathy. MRI T1-mapping technique can quantitatively evaluate DMIF. PURPOSE: To evaluate of early DMIF in a type 1 diabetes mellitus (T1DM) mouse model through 7.0 T MRI T1 mapping. STUDY TYPE: Prospective. ANIMAL MODEL: A total of 50 8-week-old C57Bl/6J male mice were divided into control (n = 20) and T1DM (n = 30) groups. FIELD STRENGTH/SEQUENCE: A 7.0 T small animal MRI; gradient echo Look-Locker inversion recovery T1-mapping sequence; cine MRI. Scans were acquired in control and T1DM mice every 4 weeks until 24 weeks. ASSESSMENT: End-diastolic volume (EDV), end-systolic volume (ESV), ejection fraction (EF), left ventricle (LV) mass, fractional shortening (FS), and E/A ratio. They were evaluated through echocardiography and cine MRI. The extracellular volume fraction (ECV) was calculated. Sirius Red staining was performed and calculated collagen volume fraction (CVF). STATISTICAL TESTS: Differences in ECV and CVF between two groups were analyzed using one-way analysis of variance. The correlation between ECV and CVF was assessed using Pearson's correlations. RESULTS: Compared with the control group, a progressive decrease in FS, EF, and E/A ratio was observed in the T1DM group. Both ECV and CVF values gradually increased during diabetes progression. A significant increase in ECV and CVF values was observed at 12 weeks (ECV: 32.5% ± 1.6% vs. 28.1% ± 1.8%; CVF: 6.9% ± 1.8% vs. 3.3% ± 1.1%). ECV showed a strong correlation with CVF (r = 0.856). DATA CONCLUSION: ECV is an accurate and feasible imaging marker that can be used to quantitatively assess DMIF changes over time in T1DM mice. ECV has potential to accurately detect DMIF in the early stage and may be a useful imaging tool to assess the need for early intervention in T1DM mice. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 3.

Artificial intelligence-based full aortic CT angiography imaging with ultra-low-dose contrast medium: a preliminary study.

OBJECTIVES: To further reduce the contrast medium (CM) dose of full aortic CT angiography (ACTA) imaging using the augmented cycle-consistent adversarial framework (Au-CycleGAN) algorithm. METHODS: We prospectively enrolled 150 consecutive patients with suspected aortic disease. All received ACTA scans of ultra-low-dose CM (ULDCM) protocol and low-dose CM (LDCM) protocol. These data were randomly assigned to the training datasets (n = 100) and the validation datasets (n = 50). The ULDCM images were reconstructed by the Au-CycleGAN algorithm. Then, the AI-based ULDCM images were compared with LDCM images in terms of image quality and diagnostic accuracy. RESULTS: The mean image quality score of each location in the AI-based ULDCM group was higher than that in the ULDCM group but a little lower than that in the LDCM group (all p < 0.05). All AI-based ULDCM images met the diagnostic requirements (score ≥ 3). Except for the image noise, the AI-based ULDCM images had higher attenuation value than the ULDCM and LDCM images as well as higher SNR and CNR in all locations of the aorta analyzed (all p < 0.05). Similar results were also seen in obese patients (BMI > 25, all p < 0.05). Using the findings of LDCM images as the reference, the AI-based ULDCM images showed good diagnostic parameters and no significant differences in any of the analyzed aortic disease diagnoses (all K-values > 0.80, p < 0.05). CONCLUSIONS: The required dose of CM for full ACTA imaging can be reduced to one-third of the CM dose of the LDCM protocol while maintaining image quality and diagnostic accuracy using the Au-CycleGAN algorithm. KEY POINTS: • The required dose of contrast medium (CM) for full ACTA imaging can be reduced to one-third of the CM dose of the low-dose contrast medium (LDCM) protocol using the Au-CycleGAN algorithm. • Except for the image noise, the AI-based ultra-low-dose contrast medium (ULDCM) images had better quantitative image quality parameters than the ULDCM and LDCM images. • No significant diagnostic differences were noted between the AI-based ULDCM and LDCM images regarding all the analyzed aortic disease diagnoses.

Deep learning-based prognostic model using non-enhanced cardiac cine MRI for outcome prediction in patients with heart failure.

OBJECTIVES: To evaluate the performance of a deep learning-based multi-source model for survival prediction and risk stratification in patients with heart failure. METHODS: Patients with heart failure with reduced ejection fraction (HFrEF) who underwent cardiac magnetic resonance between January 2015 and April 2020 were retrospectively included in this study. Baseline electronic health record data, including clinical demographic information, laboratory data, and electrocardiographic information, were collected. Short-axis non-contrast cine images of the whole heart were acquired to estimate the cardiac function parameters and the motion features of the left ventricle. Model accuracy was evaluated using the Harrell's concordance index. All patients were followed up for major adverse cardiac events (MACEs), and survival prediction was assessed using Kaplan-Meier curves. RESULTS: A total of 329 patients were evaluated (age 54 ± 14 years; men, 254) in this study. During a median follow-up period of 1041 days, 62 patients experienced MACEs and their median survival time was 495 days. When compared with conventional Cox hazard prediction models, deep learning models showed better survival prediction performance. Multi-data denoising autoencoder (DAE) model reached the concordance index of 0.8546 (95% CI: 0.7902-0.8883). Furthermore, when divided into phenogroups, the multi-data DAE model could significantly discriminate between the survival outcomes of the high-risk and low-risk groups compared with other models (p < 0.001). CONCLUSIONS: The proposed deep learning (DL) model based on non-contrast cardiac cine magnetic resonance imaging could independently predict the outcome of patients with HFrEF and showed better prediction efficiency than conventional methods. CLINICAL RELEVANCE STATEMENT: The proposed multi-source deep learning model based on cardiac magnetic resonance enables survival prediction in patients with heart failure. KEY POINTS: • A multi-source deep learning model based on non-contrast cardiovascular magnetic resonance (CMR) cine images was built to make robust survival prediction in patients with heart failure. • The ground truth definition contains electronic health record data as well as DL-based motion data, and cardiac motion information is extracted by optical flow method from non-contrast CMR cine images. • The DL-based model exhibits better prognostic value and stratification performance when compared with conventional prediction models and could aid in the risk stratification in patients with HF.

Longitudinal changes of health-related quality of life over 10 years in breast cancer patients treated with radiotherapy following breast-conserving surgery.

PURPOSES: The study intended to (1) assess changes of health-related quality of life (HRQoL) between early treatment-related time points and 10 years post-treatment in a cohort of breast cancer (BC) patients who received radiotherapy (RT), (2) to evaluate differences in HRQoL between long-term BC survivors and unaffected women from the same geographical region and (3) to identify determinants of long-term HRQoL in the survivor cohort. METHODS: 292 BC patients were recruited prior to RT after breast-conserving surgery between 1998 and 2001 in Germany and prospectively followed up for a median of 11.4 years (range 10.3-12.8 years). HRQoL was assessed using EORTC QLQ-C30 at pre-RT (baseline), during RT, 6 weeks after RT, and at the 10-year follow-up. Changes in mean HRQoL scores over time were assessed using linear-mixed models. HRQoL in long-term survivors and controls was compared using Wilcoxon rank-sum test, stratified by age groups. Multivariable linear regression models were used to identify determinants for HRQoL in long-term BC survivors. RESULTS: Compared to baseline level (mean summary score of 64.9), global health status/quality of life (GHS/QoL) declined during RT (62.4) and improved 6 weeks after RT (69.9) before decreasing to baseline level at the 10-year follow-up (66.7). Most functional domains deteriorated or remained stable at 10 years post-diagnosis compared to post-RT scores, except for role functioning which improved, while dyspnea and diarrhea significantly deteriorated between those two time points. There were no significant differences in long-term GHS/QoL between BC survivors 10 years post-RT and controls for all age groups (p > 0.05). However, deficits in specific HRQoL domains such as emotional burden, sleep problems or fatigue were found to more strongly affect survivors, in particular those younger than 65 years, compared to controls. In the determinant analysis, being overweight was associated with lower GHS/QoL and physical functioning, while living with others was found to be associated with better physical functioning, and decreased dyspnea and pain levels. Certain comorbidities such as depression had a strong association with multiple HRQoL domains, including lower GHS/QoL and functioning as well as a higher level of fatigue, pain, sleep/intestinal problems, and financial difficulties. Side effects such as lymphedema/pain and fibrosis were associated with worse physical and social functioning, respectively. CONCLUSION: The long-term GHS/QoL remained comparable when compared with the control population while restrictions in certain functional and symptoms domains in long-term BC survivors persisted over 10 years, in particular among younger survivors. Targeted screening to identify cancer survivors at risk for psychosocial/other impairment accounting also for comorbidities and treatment side effects may be warranted in long-term aftercare to address unmet health needs.

MMAP: a cloud computing platform for mining the maximum accuracy of predicting phenotypes from genotypes.

Accurately predicting phenotypes from genotypes holds great promise to improve health management in humans and animals, and breeding efficiency in animals and plants. Although many prediction methods have been developed, the optimal method differs across datasets due to multiple factors, including species, environments, populations and traits of interest. Studies have demonstrated that the number of genes underlying a trait and its heritability are the two key factors that determine which method fits the trait the best. In many cases, however, these two factors are unknown for the traits of interest. We developed a cloud computing platform for Mining the Maximum Accuracy of Predicting phenotypes from genotypes (MMAP) using unsupervised learning on publicly available real data and simulated data. MMAP provides a user interface to upload input data, manage projects and analyses and download the output results. The platform is free for the public to conduct computations for predicting phenotypes and genetic merit using the best prediction method optimized from many available ones, including Ridge Regression, gBLUP, compressed BLUP, Bayesian LASSO, Bayes A, B, Cpi and many more. Users can also use the platform to conduct data analyses with any methods of their choice. It is expected that extensive usage of MMAP would enrich the training data, which in turn results in continual improvement of the identification of the best method for use with particular traits. AVAILABILITY AND IMPLEMENTATION: The MMAP user manual, tutorials and example datasets are available at http://zzlab.net/MMAP. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Prognostic Value of Cardiac Magnetic Resonance in Assessing Right Ventricular Strain in Cardiovascular Disease: A Systematic Review and Meta-Analysis.

Objective: To evaluate the prognostic value of cardiac magnetic resonance (CMR) imaging in assessing right ventricular strain via meta-analysis of current literature. Background: Right ventricular strain recorded with CMR serves as a novel indicator to quantify myocardial deformation. Although several studies have reported the predictive value of right ventricular strain determined using CMR, their validity is limited by small sample size and low event number. Methods: Embase, Medline and Web of Science were searched for studies assessing the prognostic value of myocardial strain. The primary endpoint was a composite of all-cause mortality, cardiovascular death, aborted sudden cardiac death, heart transplantation and heart failure admissions. Results: A total of 14 studies met the selection criteria and were included in the analysis (n = 3239 adults). The random-effects model showed the association of parameters of right ventricular strain with major adverse cardiac events. Absolute value of right ventricular global longitudinal strain was negatively correlated with right ventricular ejection fraction (hazard ratio: 1.07, 95% confidence interval: 1.05-1.08; p = 0.013). Despite the small number of studies, right ventricular radial strain, right ventricular circumferential strain and right ventricular long-axis strain displayed potential prognostic value. Conclusions: Right ventricular strain measured with CMR is an effective prognostic indicator for cardiovascular disease.

Assessment of Image Quality of Coronary Computed Tomography Angiography in Obese Patients by Comparing Deep Learning Image Reconstruction With Adaptive Statistical Iterative Reconstruction Veo.

OBJECTIVE: The aim of the study was to evaluate the image quality of coronary computed tomography (CT) angiography (CCTA) in obese patients by using deep learning image reconstruction (DLIR) in comparison with adaptive statistical iterative reconstruction Veo (ASiR-V). METHODS: We prospectively evaluated 60 obese patients (body mass index [BMI] ≥ 30 kg/m2) who underwent coronary CT angiography in a single center. All CT scans were performed with GE Revolution 256-row CT at 120 kV (group A; 20 men, 10 women; mean age = 54.3 years; mean BMI = 33.4 kg/m2) or 100 kV (group B; 18 men; 12 women; mean age = 56.8 years; mean BMI = 32.9 kg/m2). Images in group A were reconstructed using ASiR-V, whereas images in group B were reconstructed using ASiR-V, DLIR-medium (DLIR-M), and DLIR-high (DLIR-H). Three blinded independent readers assessed the subjective image quality and measured the objective image quality. Radiation dose estimates were calculated and compared between patients by using 0.014 and 0.026 mSv·mGy-1 cm-1 corresponding to chest and heart conversion coefficients, respectively. RESULTS: The subjective score was significantly higher for images reconstructed using 120-kV ASiR-V (3.8), DLIR-M (3.9), and DLIR-H (4.0) compared with those reconstructed using 100-kV ASiR-V (3.5). Image noise was significantly lower in images reconstructed using DLIR-H compared with those reconstructed using other reconstruction algorithm (P < 0.001, respectively). The contrast-to-noise ratio was significantly higher in the DLIR-H group than in the groups using other reconstruction algorithm (P < 0.001). The effective radiation dose was significantly lower in group B than in group A (P < 0.001). CONCLUSIONS: Compared with ASiR-V, DLIR improved image quality in obese individuals without comprising image quality or increasing the radiation dose.

Impact of Sublingual Nitroglycerin on the Assessment of Computed Tomography-derived Fractional Flow Reserve: An Intraindividual Comparison Study.

OBJECTIVE: The aim of this study was to investigate the impact of nitroglycerin (NTG) on the assessment of computed tomography-derived fractional flow reserve (CT-FFR). MATERIALS AND METHODS: Seventy-seven patients with suspected coronary artery disease were recruited, and they underwent computed tomography angiography (CCTA) before and after NTG administration. The CT-FFRs were compared at 2 CCTAs. The difference was compared using the Wilcoxon signed rank test. Patients were divided into normal and stenosis groups according to CCTA results. Vessels in the stenosis group were further divided into different groups based on coronary artery calcium score (CACS) and stenosis degree. The poststenotic CT-FFR differences before and after NTG (DCT-FFR) were calculated to evaluate the impact of stenosis degree and CACS. Terminal CT-FFRs derived from CCTAs before and after NTG in total and vessel-specific levels were compared in the normal group. RESULTS: Of 47 patients in the stenosis group, poststenotic CT-FFR was significantly increased after NTG at per-vessel level. By taking CT-FFR of 0.75 or lower as the threshold, 5 and 4 patients showed abnormal CT-FFR before and after NTG, respectively. No significant differences were noted among the various stenosis degree and CACS groups regarding DCT-FFR. Of 30 patients in the normal group, terminal CT-FFR was significantly increased after NTG in total level and vessel-specific level of left anterior descending and right coronary artery, but not in the left circumflex. CONCLUSIONS: Both post lesion and distal vessel CT-FFR significantly improved after the administration of GTN with the degree of change not affected by stenosis severity or CACS.

NMR-Based Metabolomic Analysis for the Effects of α-Ketoglutarate Supplementation on C2C12 Myoblasts in Different Energy States.

α-Ketoglutarate (AKG) is attracting much attention from researchers owing to its beneficial effects on anti-aging and cancer suppression, and, more recently, in nutritional supplements. Given that glucose is the main source of energy to maintain normal physiological functions of skeletal muscle, the effects of AKG supplementation for improving muscle performance are closely related to the glucose level in skeletal muscle. The differences of AKG-induced effects in skeletal muscle between two states of normal energy and energy deficiency are unclear. Furthermore, AKG-induced metabolic changes in skeletal muscles in different energy states also remain elusive. Here, we assessed the effects of AKG supplementation on mouse C2C12 myoblast cells cultured both in normal medium (Nor cells) and in low-glucose medium (Low cells), which were used to mimic two states of normal energy and energy deficiency, respectively. We further performed NMR-based metabolomic analysis to address AKG-induced metabolic changes in Nor and Low cells. AKG supplementation significantly promoted the proliferation and differentiation of cells in the two energy states through glutamine metabolism, oxidative stress, and energy metabolism. Under normal culture conditions, AKG up-regulated the intracellular glutamine level, changed the cellular energy status, and maintained the antioxidant capacity of cells. Under low-glucose culture condition, AKG served as a metabolic substrate to reduce the glutamine-dependence of cells, remarkably enhanced the antioxidant capacity of cells and significantly elevated the intracellular ATP level, thereby ensuring the normal growth and metabolism of cells in the state of energy deficiency. Our results provide a mechanistic understanding of the effects of AKG supplements on myoblasts in both normal energy and energy deficiency states. This work may be beneficial to the exploitation of AKG applications in clinical treatments and nutritional supplementations.

Dually-Passivated Perovskite Solar Cells with Reduced Voltage Loss and Increased Super Oxide Resistance.

In recent years, the power conversion efficiency (PCE) of perovskite solar cells (PSCs) has witnessed rapid progress. Nevertheless, the pervasive defects prone to non-radiative recombination and decomposition exist at the surface and the grain boundaries (GBs) of the polycrystalline perovskite films. Herein, we report a comprehensive dual-passivation (DP) strategy to effectively passivate the defects at both surface and GBs to enhance device performance and stability further. Firstly, a fluorinated perylene-tetracarboxylic diimide derivative is permeated in the perovskite metaphase during antisolvent treatment, and then a fluorinated bulky aromatic ammonium salt is introduced over the annealed perovskite. The reduction of defect density can be unambiguously proved by the superoxide species generation/quenching reaction. As a result, optimized planar PSCs demonstrate a decreased open-circuit voltages deficit from 0.47 to 0.39 V and the best efficiency of 23.80 % from photocurrent scanning with a stabilized maximum power output efficiency of 22.99 %. Without encapsulation, one typical device can maintain over 85 % of the initial efficiency after heating on a hot plate at 100 °C for 30 h under relative humidity (RH) of 70 %. When the device is aged under 30±5 % RH, over 97 % of its initial PCE is retained after 1700 h.

Combinational Proanthocyanidins and Resveratrol Synergistically Inhibit Human Breast Cancer Cells and Impact Epigenetic⁻Mediating Machinery.

Breast cancer is the second most common cancer and the second leading cause of death from cancer among women in the United States (US). Cancer prevention and therapy through the use of phytochemicals that have epigenetic properties has gained considerable interest during the past few decades. Such dietary components include, but are not limited to, grape seed proanthocyanidins (GSPs) and resveratrol (Res), both of which are present in red wine. In this study, we report for the first time the synergistic effects of GSPs and Res on inhibiting MDA-MB-231 and MCF-7 human breast cancer cells. Our results of 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assays and clonogenic assays indicate that treatments with the combinations of GSPs and Res synergistically decreased cell viability and posttreatment cell proliferation in both cell lines. Additional analyses show that treatments with GSPs and Res in combination synergistically induced apoptosis in MDA-MB-231 cells by upregulating Bax expression and down-regulating Bcl-2 expression. DNA methyltransferase (DNMT) activity and histone deacetylase (HDAC) activity were greatly reduced in MDA-MB-231 and MCF-7 cells after treatments with GSPs and Res in combination. Collectively, our findings suggest that GSPs and Res synergistically inhibit human breast cancer cells through inducing apoptosis, as well as modulating DNA methylation and histone modifications.

Structural performance of a hybrid FRP-aluminum modular triangular Truss system subjected to various loading conditions.

A novel hybrid FRP-aluminum truss system has been employed in a two-rut modular bridge superstructure composed of twin inverted triangular trusses. The actual flexural behavior of a one-rut truss has been previously investigated under the on-axis loading test; however, the structural performance of the one-rut truss subjected to an off-axis load is still not fully understood. In this paper, a geometrical linear finite element model is introduced and validated by the on-axis loading test; the structural performance of the one-rut truss subjected to off-axis load was numerically obtained; the dissimilarities of the structural performance between the two different loading cases are investigated in detail. The results indicated that (1) the structural behavior of the off-axis load differs from that of the on-axis load, and the off-axis load is the critical loading condition controlling the structural performance of the triangular truss; (2) under the off-axis load, the FRP trussed members and connectors bear certain out-of-plane bending moments and are subjected to a complicated stress state; and (3) the stress state of these members does not match that of the initial design, and optimization for the redesign of these members is needed, especially for the pretightened teeth connectors.

Prognostic Value of Left Atrial Volume and Late Gadolinium Enhancement on Cardiac Magnetic Resonance Imaging in Patients with Coronary Artery Disease and Severe Left Ventricular Dysfunction Underwent CABG.

RATIONALE AND OBJECTIVES: This study aims to investigate whether the combination of Left atrial volume (LAV) and late gadolinium enhancement (LGE) is helpful in stratifying the risk in CABG patients with CAD with EF≤ 35%. MATERIALS AND METHODS: We conducted a retrospective analysis involving 205 CAD patients with EF≤ 35% who underwent CABG. All patients underwent gadolinium-enhanced CMR before surgery. The CMR images were analyzed for LAV, biventricular function, LGE, and left ventricular myocardial strain. Primary endpoint events included all-cause mortality, revascularization, re-hospitalization due to myocardial infarction or heart failure, and stroke after CABG. Multivariable Cox analysis was performed to identify independent risk factors for adverse outcomes. Kaplan-Meier curve analysis with the log-rank test was employed to evaluate survival estimates. RESULTS: A total of 55 patients reached the primary endpoints. Univariate Cox proportional hazard regression analysis showed that LAV index (LAVi), left ventricular EF (LVEF), right ventricular EF, LGE percent, and global longitudinal strain were significantly associated with the primary outcome (all P < 0.05). Multivariable analysis showed that LAVi (hazard ratio [HR] 1.05, [95% confidence interval (CI) 1.02-1.07], P < 0.001) and LGE percent (HR 1.10, [95% CI 1.06-1.15], P < 0.001) were independently associated with the primary outcome. Kaplan-Meier analysis indicated a significant increase in the risk of endpoint occurrence when patients exhibited LAVi≥ 51.0 mL/m2 and LGE≥ 11.6% (both P < 0.05). CONCLUSION: For CAD patients with LVEF≤ 35%, the combination of LAVi and LGE percent demonstrated good predictive value for adverse events after CABG. CMR is a helpful tool to risk-stratify patients with severe left ventricular dysfunction undergoing CABG.

Cardiac magnetic resonance analysis of left atrium function in patients with pre-apical hypertrophic cardiomyopathy.

Background: Patients presenting with unexplained T wave inversion on electrocardiogram combined with thickened left ventricular apex but less than 15 mm had been proposed as a preclinical scope of apical hypertrophy cardiomyopathy (pre-ApHCM). However, analysis of left atrial (LA) function in these patients has not been studied. This study aims to evaluate the LA function in pre-ApHCM patients and compare it with patients with ApHCM using cardiac magnetic resonance (CMR) imaging. Methods: In this retrospective case-control study, a total of 3,593 CMR reports from Beijing Anzhen Hospital, Capital Medical University, China were reviewed. Finally, 31 pre-ApHCM patients were identified and 40 ApHCM and 31 normal controls were included for comparison. LA volumetric and strain were analyzed by CMR. Two-tailed one-way ANOVA was used to analyze the difference of three groups. Pearson correlation test was used for correlation analysis. Results: All of the volumetric parameters in pre-ApHCM group were higher than those in control group. LA reservoir (LA total EF, εs) and conduit function (LA passive EF, εe) parameters, were significantly different among the three groups, which were the lowest in the ApHCM group, intermediate in the pre-ApHCM group, and the highest in the control group ((all P<0.001). Compared with the control group, the LA booster pump function, both the booster EF and booster pump strain (εa) in ApHCM were impaired (P=0.003 and P=0.002 respectively). Meanwhile, only the εa was impaired (P=0.016) while LA booster EF was not (P=0.064) in the pre-ApHCM group, neither εa nor the booster EF show difference between the ApHCM and pre-ApHCM (P=0.272 and P=0.518 respectively). Conclusions: LA function features in pre-ApHCM patients were similar to ApHCM but different from the normal controls. In pre-ApHCM and ApHCM patients, LA reservoir and conduit function impaired earlier before left atrium enlarged and decreased progressively as apex thickens. These findings may help to understand the LA functional change from pre-ApHCM to ApHCM, and to detect subclinical changes in patients with pre-ApHCM before overt hypertrophy or clinical symptoms develop.

Performance of artificial intelligence in detecting the chronic total occlusive lesions of coronary artery based on coronary computed tomographic angiography.

Background: Coronary chronic total occlusion (CTO) increases the risk of developing major adverse cardiovascular events (MACE) and cardiogenic shock. Coronary computed tomography angiography (CCTA) is a safe, noninvasive method to diagnose CTO lesions. With the development of artificial intelligence (AI), AI has been broadly applied in cardiovascular images, but AI-based detection of CTO lesions from CCTA images is difficult. We aim to evaluate the performance of AI in detecting the CTO lesions of coronary arteries based on CCTA images. Methods: We retrospectively and consecutively enrolled patients with 50% stenosis, 50-99% stenosis, and CTO lesions who received CCTA scans between June 2021 and June 2022 in Beijing Anzhen Hospital. Four-fifths of them were randomly assigned to the training dataset, while the rest (1/5) were randomly assigned to the testing dataset. Performance of the AI-assisted CCTA (CCTA-AI) in detecting the CTO lesions was evaluated through sensitivity, specificity, positive predictive value, negative predictive value, accuracy, and receiver operating characteristic analysis. With invasive coronary angiography as the reference, the diagnostic performance of AI method and manual method was compared. Results: A total of 537 patients with 1,569 stenotic lesions (including 672 lesions with <50% stenosis, 493 lesions with 50-99% stenosis, and 404 CTO lesions) were enrolled in our study. CCTA-AI saved 75% of the time in post-processing and interpreting the CCTA images when compared to the manual method (116±15 vs. 472±45 seconds). In the testing dataset, the accuracy of CCTA-AI in detecting CTO lesions was 86.2% (79.0%, 90.3%), with the area under the curve of 0.874. No significant difference was found in detecting CTO lesions between AI and manual methods (P=0.53). Conclusions: AI can automatically detect CTO lesions based on CCTA images, with high diagnostic accuracy and efficiency.