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Sol–gel processed zinc oxide (ZnO) is one of the most widely used electron transport layers (ETLs) in inverted organic solar cells (OSCs). The high annealing temperature (≈200 °C) required for sintering to ensure a high electron mobility however results in severe damage to flexible substrates. Thus, flexible organic solar cells based on sol–gel processed ZnO exhibit significantly lower efficiency than rigid devices. In this paper, an indium‐doping approach is developed to improve the optoelectronic properties of ZnO layers and reduce the required annealing temperature. Inverted OSCs based on In‐doped ZnO (IZO) exhibit a higher efficiency than those based on ZnO for a range of different active layer systems. For the PM6:L8‐BO system, the efficiency increases from 17.0% for the pristine ZnO‐based device to 17.8% for the IZO‐based device. The IZO‐based device with an active layer of PM6:L8‐BO:BTP‐eC9 exhibits an even higher efficiency of up to 18.1%. In addition, a 1.2‐micrometer‐thick inverted ultrathin flexible organic solar cell is fabricated based on the IZO ETL that achieves an efficiency of 17.0% with a power‐per‐weight ratio of 40.4 W g−1, which is one of the highest efficiency for ultrathin (less than 10 micrometers) flexible organic solar cells. [ABSTRACT FROM AUTHOR]

Evidence for treating hypertension in patients with asymptomatic aortic valve stenosis(AS) is scarce. Given the paucity of data on the relationship between syncope and antihypertensive treatment in aortic stenosis. This study sought to investigate this association in patients admitted to our hospital. A total of 158 patients with asymptomatic moderate or severe aortic stenosis were analyzed. Follow-up was conducted by clinic visit, telephone contact, or review of electronic medical records. Outcomes were syncope. Hypertension were documented in 90 of the 158 patients with moderate or severe AS, and 77 of them received antihypertensive medications. During an average 28 months follow-up period, the occurrence of syncope was observed in 13 patients. Among them, 8 were in antihypertensive group (n = 77) and 5 in normotensive group (n = 68). There was no significant difference in incidence of syncope between the two groups. Patients with treated hypertension and syncope had a lower stroke volume index (SVi), a higher valve arterial impedance (ZVA), a smaller SAC than those without. Kaplan-Meier analysis showed that there was no significant difference in syncope cumulative incidence between antihypertensive group and normotensive group (log rank P =.478). Multivariate cox regression analysis showed that both ZVA (hazard ratio:19.006, 95% confidence interval: 4.664 to77.448;P =.002) and LVMI (hazard ratio:1.484, 95% confidence interval: 1.427 to 5.157;P =.016) were associated with development of syncope, whereas hypertension were not related independently to syncope (hazard ratio:0.935, 95% confidence interval: 0.786 to3.173; P =.869). In patients with moderate or severe AS, concomitant hypertension, and antihypertensive treatment didn't increase the occurrence of syncope, whereas higher ZVA was independently associated with greater risk of syncope. [ABSTRACT FROM AUTHOR]

Overexpression of the tumor necrosis factor receptor-associated factor 4 (TRAF4) has been detected in many cancer types and is considered to foster tumor progression. However, the role of TRAF4 in hepatocellular carcinoma (HCC) remains elusive. In this study, we found that TRAF4 was highly expressed in HCC cell lines and HCC tissues compared with normal liver cell lines and adjacent noncancerous tissues. TRAF4 overexpression in HCC tissues was correlated with tumor quantity and vascular invasion. In vitro studies showed that TRAF4 was associated with HCC cell migration and invasion. An in vivo study verified that TRAF4 overexpression facilitated metastasis in nude mice. In addition, overexpressed TRAF4 promoted the phosphorylation of Akt and induced Slug overexpression, leading to downregulated E-cadherin and upregulated vimentin, while silencing TRAF4 moderated the phosphorylation of Akt and repressed the expression of Slug, which resulted in upregulated E-cadherin and downregulated vimentin. These effects were inversed after pretreatment of the PI3K/Akt inhibitor LY294002 or overexpression of constitutively active Akt1. Our study demonstrated that TRAF4 was involved in promoting HCC cell migration and invasion. The process was induced by the EMT through activation of the PI3K/Akt signaling pathway. [ABSTRACT FROM AUTHOR]

2D organic–inorganic hybrid Ruddlesden–Popper perovskites have emerged recently as candidates for the light‐absorbing layer in solar cell technology due largely to their impressive operational stability compared with their 3D‐perovskite counterparts. The methods reported to date for the preparation of efficient 2D perovksite layers for solar cells involve a nonscalable spin‐coating step. In this work, a facile, spin‐coating‐free, directly scalable drop‐cast method is reported for depositing precursor solutions that self‐assemble into highly oriented, uniform 2D‐perovskite films in air, yielding perovskite solar cells with power conversion efficiencies (PCE) of up to 14.9% (certified PCE of 14.33% ± 0.34 at 0.078 cm2). This is the highest PCE to date for a solar cell with 2D‐perovskite layers fabricated by nonspin‐coating method. The PCEs of the cells display no evidence of degradation after storage in a nitrogen glovebox for more than 5 months. 2D‐perovskite layer deposition using a slot‐die process is also investigated for the first time. Perovskite solar cells fabricated using batch slot‐die coating on a glass substrate or R2R slot‐die coating on a flexible substrate produced PCEs of 12.5% and 8.0%, respectively. A simple, spin‐coating‐free, and directly scalable drop‐cast method is developed to prepare 2D‐perovskite films at arbitrary shapes. The precursor solutions can self‐assemble into highly oriented 2D‐perovskite films on a preheated substrate, producing perovskite solar cells with power conversion efficiencies (PCE) of up to 14.9%, the highest PCE to date for a solar cell with 2D‐perovskite layers fabricated by a nonspin‐coating method. [ABSTRACT FROM AUTHOR]

Background: Lenvatinib plus PD-1 inhibitors and interventional (LPI) therapy have demonstrated promising treatment effects in unresectable hepatocellular carcinoma (HCC). However, biomarkers for predicting the response to LPI therapy remain to be further explored. We aimed to develop a radiomics model to noninvasively predict the efficacy of LPI therapy., Methods: Clinical data of patients with HCC receiving LPI therapy were collected in our institution. The clinical model was built with clinical information. Nine machine learning classifiers were tested and the multilayer perceptron classifier with optimal performance was used as the radiomics model. The clinical-radiomics model was constructed by integrating clinical and radiomics scores through logistic regression analysis., Results: 151 patients were enrolled in this study (2:1 randomization, 101 and 50 in the training and validation cohorts), of which three achieved complete response, 69 showed partial response, 46 showed stable disease, and 33 showed progressive disease. The objective response rate, disease control rate, and conversion resection rates were 47.7, 78.1 and 23.2%. 14 features were selected from the initially extracted 1223 for radiomics model construction. The area under the curves of the radiomics model (0.900 for training and 0.893 for validation) were comparable to that of the clinical-radiomics model (0.912 for training and 0.892 for validation), and both were superior to the clinical model (0.669 for training and 0.585 for validation). Meanwhile, the radiomics model can categorize participants into high-risk and low-risk groups for progression-free survival (PFS) and overall survival (OS) in the training (HR 1.913, 95% CI 1.121 to 3.265, p=0.016 for PFS; HR 4.252, 95% CI 2.051 to 8.816, p=0.001 for OS) and validation sets (HR 2.347, 95% CI 1.095 to 5.031, p=0.012 for PFS; HR 2.592, 95% CI 1.050 to 6.394, p=0.019 for OS)., Conclusion: The promising machine learning radiomics model was developed and validated to predict the efficacy of LPI therapy for patients with HCC and perform risk stratification, with comparable performance to clinical-radiomics model., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)