Abstract Lotus ( Nelumbo nucifera Gaertn) possesses antioxidant, hepatoprotective, and anticancer potential. This study determined the protective role of aqueous extract from Nelumbo nucifera leaves (NLE) against N ‐diethylnitrosamine (DEN)‐induced oxidative stress and hepatocellular carcinogenesis in a sample of Sprague–Dawley rats. NLE was fed orally to rats in which hepatic carcinoma was induced with DEN for 12 weeks. Five groups of 12 rats each were used for the study: Group I (control group) rats received distilled water; Group II rats were induced with DEN; Group III rats were induced with DEN and cotreated with 0.5% NLE; Group IV rats were induced with DEN and cotreated with 1.0% NLE; and Group V rats were induced with DEN and cotreated with 2.0% NLE. Clinical chemistry, organ weight, inflammatory marker, protein expression, enzyme, and antioxidant analyses were conducted. NLE administration to rats resulted in significantly decreased levels of serum alanine aminotransferase, aspartate aminotransferase, and albumin, which is indicative of hepatocellular damage, compared with the control group. DEN‐induced oxidative stress was inhibited by NLE and this inhibition was paralleled by decreased lipid peroxides and increased glutathione transferase, superoxide dismutase, catalase, and glutathione peroxidase activity in liver tissues. The status of nonenzymatic antioxidants, such as reduced glutathione, was also found to be increased in NLE‐administered rats. Furthermore, NLE decreased tumor size, hepatic Rac1, PKCα, and GSTπ expressions compared with the DEN‐only group. Thus, supplementation of NLE reduced the adverse changes that occur because of liver cancer. These results prove that NLE protects against liver carcinogenesis induced because of treatment with DEN through blocking lipid peroxidation, hepatic cell damage, and enhancing the antioxidant defense system.
Abstract In this study, we present the growth of monolayer MoS 2 (molybdenum disulfide) film. Mo (molybdenum) film was formed on a sapphire substrate through e-beam evaporation, and triangular MoS 2 film was grown by direct sulfurization. First, the growth of MoS 2 was observed under an optical microscope. The number of MoS 2 layers was analyzed by Raman spectrum, atomic force microscope (AFM), and photoluminescence spectroscopy (PL) measurement. Different sapphire substrate regions have different growth conditions of MoS 2 . The growth of MoS 2 is optimized by controlling the amount and location of precursors, adjusting the appropriate growing temperature and time, and establishing proper ventilation. Experimental results show the successful growth of a large-area single-layer MoS 2 on a sapphire substrate through direct sulfurization under a suitable environment. The thickness of the MoS2 film determined by AFM measurement is about 0.73 nm. The peak difference between the Raman measurement shift of 386 and 405 cm-1 is 19.1 cm-1, and the peak of PL measurement is about 677 nm, which is converted into energy of 1.83 eV, which is the size of the direct energy gap of the MoS 2 thin film. The results verify the distribution of the number of grown layers. Based on the observation of the optical microscope (OM) images, MoS 2 continuously grows from a single layer of discretely distributed triangular single-crystal grains into a single-layer large-area MoS 2 film. This work provides a reference for growing MoS2 in a large area. We expect to apply this structure to various heterojunctions, sensors, solar cells, and thin-film transistors.
Federated learning (FL) has been recognized as a rapidly growing research area, where the model is trained over massively distributed clients under the orchestration of a parameter server (PS) without sharing clients' data. This paper delves into a class of federated problems characterized by non-convex and non-smooth loss functions, that are prevalent in FL applications but challenging to handle due to their intricate non-convexity and non-smoothness nature and the conflicting requirements on communication efficiency and privacy protection. In this paper, we propose a novel federated primal-dual algorithm with bidirectional model sparsification tailored for non-convex and non-smooth FL problems, and differential privacy is applied for privacy guarantee. Its unique insightful properties and some privacy and convergence analyses are also presented as the FL algorithm design guidelines. Extensive experiments on real-world data are conducted to demonstrate the effectiveness of the proposed algorithm and much superior performance than some state-of-the-art FL algorithms, together with the validation of all the analytical results and properties.
Tumor metastasis is a major cause of death of patients with colorectal cancer (CRC). Our previous findings show that adenine has antiproliferation activity against tumor cells. However, whether adenine reduces the invasiveness of DLD-1 and SW480 CRC cells has not been thoroughly explored. In this study, we aimed to explore the effects of adenine on the invasion potential of DLD-1 cells. Our findings showed that adenine at concentrations of ≤200 μM did not influence the cell viability of DLD-1 and SW480 CRC cells. By contrast, adenine reduced the migratory potential of the CRC cells. Moreover, it decreased the invasion capacity of the CRC cells in a dose-dependent manner. We further observed that adenine downregulated the protein levels of tissue plasminogen activator, matrix metalloproteinase-9, Snail, TWIST, and vimentin, but upregulated the tissue inhibitor of metalloproteinase-1 expression in DLD-1 cells. Adenine decreased the integrin αV level and reduced the activation of integrin-associated signaling components, including focal adhesion kinase (FAK), paxillin, and Src in DLD-1 cells. Further observations showed that adenine induced AMP-activated protein kinase (AMPK) activation and inhibited mTOR phosphorylation in DLD-1 cells. The knockdown of AMPK restored the reduced integrin αV level and FAK/paxillin/Src signaling inhibited by adenine in DLD-1 cells. Collectively, these findings reveal that adenine reduces the invasion potential of DLD-1 cells through the AMPK/integrin/FAK axis, suggesting that adenine may have anti-metastatic potential in CRC cells.
The object of this study was to investigate the incidence rate of major adverse cardiovascular event (MACE) among patients with primary aldosteronism (PA) after adrenalectomy or mineralocorticoid receptor antagonist (MRA) treatment. A systematic review and meta-analysis was conducted by searching PubMed, Embase, Cochrane Library, Web of Science, CINAHL, and Scopus through April 15, 2024. Studies reporting the MACE incidence rate in patients with PA after treatment were included. We adapted the random-effects model and performed subgroup and meta-regression analyses. A total of 20 studies involving 16 927 patients with PA were included. There were 5939 patients with PA who underwent adrenalectomy. A total of 10 474 patients received MRA treatment. Additionally, 546 patients received either adrenalectomy or MRA treatment. The pooled incidence rate of MACE among patients with PA after treatment was 2.20/100 patient-years (95% CI, 1.70-2.80), higher than that of non-PA hypertension (1.20/100 patient-years [95% CI, 0.70-2.10]). Patients with PA after adrenalectomy had a lower MACE incidence rate (2.00/100 patient-years [95% CI, 1.40-2.60]) compared with those undergoing MRA treatment (3.30/100 patient-years [95% CI, 2.40-4.10], P=0.017). Advanced age (coefficient: 0.071, P<0.001) and diabetes (coefficient: 0.070, P=0.001) increased the risk of posttreatment MACE. A curvilinear dose-response relationship between the posttreatment plasma renin activity and the MACE incidence was observed, with the lowest risks at plasma renin activity of 1.0 to 2.0 ng/mL per hour (Pnonlinearity<0.001). The MACE incidence in treated patients with PA was 2.20 per 100 patient-years, higher than in patients with hypertension without PA. Maintaining posttreatment plasma renin activity between 1.0 and 2.0 ng/mL per hour appears crucial for minimizing cardiovascular risk. Adrenalectomy proved more effective than MRA treatment in reducing MACE risk. Advanced age and diabetes significantly increased the risk of posttreatment MACE.
Patients with end-stage renal disease have a higher risk of death from cardiovascular events, which can be mainly attributed to coronary artery calcification (CAC). Wnt signaling is involved in vascular development and may play a role in vascular calcification. This study aimed to evaluate CAC prevalence in patients on dialysis with severe secondary hyperparathyroidism (SHPT) and identify CAC risk factors. The study is a retrospective analysis of the severe hyperparathyroidism registration study that prospectively recruited patients on dialysis with severe SHPT who were candidates for parathyroidectomy, from October 2013 to May 2015. CAC and bone mineral density (BMD) were measured. Demographic and clinical data including calcium, phosphorus, alkaline phosphatase, intact parathyroid hormone, Dickkopf-related protein 1 (DKK1), and sclerostin levels were analyzed. CAC scores were reported in Agatston units (AU). A total of 61 patients were included in this study. No CAC, mild CAC (<100 AU), moderate CAC (>100 AU), and severe CAC (>400 AU) were observed in 4.9%, 11.4%, 14.8%, and 68.9% of patients, respectively. DKK1 and sclerostin were not associated with CAC. In univariate analysis, CAC was significantly correlated with age, sex (male), total cholesterol, and intravenous pulse calcitriol (p<0.05). CAC was not inversely correlated with the BMD, T scores, or Z scores of the femoral neck (p>0.05). In multivariate analysis, the stepwise forward multiple linear regression revealed that CAC was associated with age, male sex and intravenous pulse calcitriol (p<0.05). Furthermore, serum sclerostin was positively correlated with the BMD of the femoral neck but negatively associated with intact parathyroid hormone (p<0.05). Serum sclerostin was significantly associated with severely low bone mass with Z-scores<-2.5 of the femoral neck, even when adjusted for serum intact parathyroid hormone, vitamin D status, dialysis pattern, sex, and DKK-1 (p<0.05). The patients on dialysis with severe SHPT have a high prevalence of vascular calcification. Although the Wnt signaling pathway could play a role in hyperparathyroid bone disease, CAC may be mainly due to the treatment modality rather than the Wnt signaling pathway associated bone metabolism in patients on dialysis with severe SHPT.
One of the leading causes of cancer deaths is esophageal cancer (EC) because identifying it in early stage is challenging. Computer-aided diagnosis (CAD) could detect the early stages of EC have been developed in recent years. Therefore, in this study, complete meta-analysis of selected studies that only uses hyperspectral imaging to detect EC is evaluated in terms of their diagnostic test accuracy (DTA). Eight studies are chosen based on the Quadas-2 tool results for systematic DTA analysis, and each of the methods developed in these studies is classified based on the nationality of the data, artificial intelligence, the type of image, the type of cancer detected, and the year of publishing. Deeks’ funnel plot, forest plot, and accuracy charts were made. The methods studied in these articles show the automatic diagnosis of EC has a high accuracy, but external validation, which is a prerequisite for real-time clinical applications, is lacking.
Various attacks have emerged as the major threats to the success of a connected world like the Internet of Things (IoT), in which billions of devices interact with each other to facilitate human life. By exploiting the vulnerabilities of cheap and insecure devices such as IP cameras, an attacker can create hundreds of thousands of zombie devices and then launch massive volume attacks to take down any target. For example, in 2016, a record large-scale DDoS attack launched by millions of Mirai-injected IP cameras and smart printers blocked the accessibility of several high-profile websites. To date, the state-of-the-art defense systems against such attacks rely mostly on pre-defined features extracted from the entire flows or signatures. The feature definitions are manual, and it would be too late to block a malicious flow after extracting the flow features. In this work, we present an effective anomaly traffic detection mechanism, namely D-PACK, which consists of a Convolutional Neural Network (CNN) and an unsupervised deep learning model (e.g., Autoencoder) for auto-profiling the traffic patterns and filtering abnormal traffic. Notably, D-PACK inspects only the first few bytes of the first few packets in each flow for early detection. Our experimental results show that, by examining just the first two packets in each flow, D-PACK still performs with nearly 100% accuracy, while features an extremely low false-positive rate, e.g., 0.83%. The design can inspire the emerging efforts towards online anomaly detection systems that feature reducing the volume of processed packets and blocking malicious flows in time.
'/%3e%3cuse xlink:href='%23a' transform='rotate(60)'/%3e%3ccircle r='17' fill='%23000095'/%3e%3ccircle r='15' fill='%23fff'/%3e%3c/svg%3e)