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ZAKβ Alleviates Oxidized Low-density Lipoprotein (ox-LDL)-Induced Apoptosis and B-type Natriuretic Peptide (BNP) Upregulation in Cardiomyoblast.
No full text[[abstract]]Oxidized low-density lipoprotein (ox-LDL) is a type of modified cholesterol that promotes apoptosis and inflammation and advances the progression of heart failure. Leucine-zipper and sterile-α motif kinase (ZAK) is a kinase of the MAP3K family which is highly expressed in the heart and encodes two variants, ZAKα and ZAKβ. Our previous study serendipitously found opposite effects of ZAKα and ZAKβ in which ZAKβ antagonizes ZAKα-induced apoptosis and hypertrophy of the heart. This study aims to test the hypothesis of whether ZAKα and ZAKβ are involved in the damaging effects of ox-LDL in the cardiomyoblast. Cardiomyoblast cells H9c2 were treated with different concentrations of ox-LDL. Cell viability and apoptosis were measured by MTT and TUNEL assay, respectively. Western blot was used to detect apoptosis, hypertrophy, and pro-survival signaling proteins. Plasmid transfection, pharmacological inhibition with D2825, and siRNA transfection were utilized to upregulate or downregulate ZAKβ, respectively. Ox-LDL concentration-dependently reduces the viability and expression of several pro-survival proteins, such as phospho-PI3K, phospho-Akt, and Bcl-xL. Furthermore, ox-LDL increases cleaved caspase-3, cleaved caspase-9 as indicators of apoptosis and increases B-type natriuretic peptide (BNP) as an indicator of hypertrophy. Overexpression of ZAKβ by plasmid transfection attenuates apoptosis and prevents upregulation of BNP. Importantly, these effects were abolished by inhibiting ZAKβ either by D2825 or siZAKβ application. Our results suggest that ZAKβ upregulation in response to ox-LDL treatment confers protective effects on cardiomyoblast
Apolipoprotein C3-Rich Low-Density Lipoprotein Induces Endothelial Cell Senescence via FBXO31 and Its Inhibition by Sesamol In Vitro and In Vivo
No full text[[abstract]]Premature endothelial senescence decreases the atheroprotective capacity of the arterial endothelium. Apolipoprotein C3 (ApoC3) delays the catabolism of triglyceride-rich particles and plays a critical role in atherosclerosis progression. FBXO31 is required for the intracellular response to DNA damage, which is a significant cause of cellular senescence. Sesamol is a natural antioxidant with cardiovascular-protective properties. In this study, we aimed to examine the effects of ApoC3-rich low-density lipoprotein (AC3RL) mediated via FBXO31 on endothelial cell (EC) senescence and its inhibition by sesamol. AC3RL and ApoC3-free low-density lipoproteins (LDL) (AC3(-)L) were isolated from the plasma LDL of patients with ischemic stroke. Human aortic endothelial cells (HAECs) treated with AC3RL induced EC senescence in a dose-dependent manner. AC3RL induced HAEC senescence via DNA damage. However, silencing FBXO31 attenuated AC3RL-induced DNA damage and reduced cellular senescence. Thus, FBXO31 may be a novel therapeutic target for endothelial senescence-related cardiovascular diseases. Moreover, the aortic arch of hamsters fed a high-fat diet with sesamol showed a substantial reduction in their atherosclerotic lesion size. In addition to confirming the role of AC3RL in aging and atherosclerosis, we also identified AC3RL as a potential therapeutic target that can be used to combat atherosclerosis and the onset of cardiovascular disease in humans
Women's trajectories of postpartum depression and social support: A repeated-measures study with implications for evidence-based practice
No full text[[abstract]]Background: Postpartum depression is one of the most common psychological disorders of women after childbirth. Despite the importance of social support as an influencing factor, there have been few studies on the trends and characteristics of social support as it relates to postpartum depression.
Aims: To explore the trends in postpartum depression and social support, to cross-analyze the correlation between the postpartum depression trajectory and the social support trajectory, and to investigate predictors of changes in postpartum depression trajectories.
Methods: A prospective repeated-measure study and convenience sampling were used to recruit 230 women at 1, 3, and 6 months after childbirth. Structured questionnaires were used for data collection. Trajectory analysis was used to explore the trajectories of postpartum depression and social support during the 6 months after childbirth, and polynomial logistic regression was used to explore predictors of the trajectory of postpartum depression.
Results: Postpartum depression was at its most serious in the third month after childbirth, showing patterns of low-risk, moderate-risk, and high-risk trajectories. Social support also showed low, moderate, and high patterns, and the trajectory of postpartum depression was significantly related to the trajectory of social support. The predictors of moderate-risk and high-risk postpartum depression were also found in this study.
Linking evidence to action: Postpartum mental health education and online learning systems should be used to increase social support for women after childbirth and reduce the incidence of postpartum depression
Involvement of FoxO1, Sp1, and Nrf2 in Upregulation of Negative Regulator of ROS by 15d PGJ2 Attenuates H2O2 Induced IL 6 Expression in Rat Brain Astrocytes
No full text[[abstract]]Excessive production of reactive oxygen species (ROS) by NADPH oxidase (Nox) resulted in inflammation. The negative regulator of ROS (NRROS) dampens ROS generation during inflammatory responses. 15-Deoxy-?12,14-prostaglandin J2 (15d-PGJ2) exhibits neuroprotective effects on central nervous system (CNS). However, whether 15d-PGJ2-induced NRROS expression was unknown in rat brain astrocytes (RBA-1). NRROS expression was determined by Western blot, RT/real-time PCR, and promoter activity assays. The signaling components were investigated using pharmacological inhibitors or specific siRNAs. The interaction between transcription factors and the NRROS promoter was investigated by chromatin immunoprecipitation assay. Upregulation of NRROS on the hydrogen peroxide (H2O2)-mediated ROS generation and interleukin 6 (IL-6) secretion was measured. 15d-PGJ2-induced NRROS expression was mediated through PI3K/Akt-dependent activation of Sp1 and FoxO1 and established the essential promoter regions. We demonstrated that 15d-PGJ2 activated PI3K/Akt and following by cooperation between phosphorylated nuclear FoxO1 and Sp1 to initiate the NRROS transcription. In addition, Nrf2 played a key role in NRROS expression induced by 15d-PGJ2 which was mediated through its phosphorylation. Finally, the NRROS stable clones attenuated the H2O2-induced ROS generation and expression of IL-6 through suppressing the Nox-2 activity. These results suggested that 15d-PGJ2-induced NRROS expression is mediated through a PI3K/Akt-dependent FoxO1 and Sp1 phosphorylation, and Nrf2 cascade, which suppresses ROS generation through attenuating the p47phox phosphorylation and gp91phox formation and IL-6 expression in RBA-1 cells. These results confirmed the mechanisms underlying 15d-PGJ2-induced NRROS expression which might be a potential strategy for prevention and management of brain inflammatory and neurodegenerative diseases
Thrombin Induces COX-2 and PGE2 Expression via PAR1/PKCalpha/MAPK-Dependent NF-κappaB Activation in Human Tracheal Smooth Muscle Cells
No full text[[abstract]]The inflammation of the airway and lung could be triggered by upregulation cyclooxygenase (COX)-2 and prostaglandin E2 (PGE2) induced by various proinflammatory factors. COX-2 induction by thrombin has been shown to play a vital role in various inflammatory diseases. However, in human tracheal smooth muscle cells (HTSMCs), how thrombin enhanced the levels of COX-2/PGE2 is not completely characterized. Thus, in this study, the levels of COX-2 expression and PGE2 synthesis induced by thrombin were determined by Western blot, promoter-reporter assay, real-time PCR, and ELISA kit. The various signaling components involved in the thrombin-mediated responses were differentiated by transfection with siRNAs and selective pharmacological inhibitors. The role of NF-κB was assessed by a chromatin immunoprecipitation (ChIP) assay, immunofluorescent staining, as well as Western blot. Our results verified that thrombin markedly triggered PGE2 secretion via COX-2 upregulation which were diminished by the inhibitor of thrombin (PPACK), PAR1 (SCH79797), Gi/o protein (GPA2), Gq protein (GPA2A), PKCα (G?6976), p38 MAPK (SB202190), JNK1/2 (SP600125), MEK1/2 (U0126), or NF-κB (helenalin) and transfection with siRNA of PAR1, Gq α, Gi α, PKCα, JNK2, p38, p42, or p65. Moreover, thrombin induced PAR1-dependent PKCα phosphorylation in HTSMCs. We also observed that thrombin induced p38 MAPK, JNK1/2, and p42/p44 MAPK activation through a PAR1/PKCα pathway. Thrombin promoted phosphorylation of NF-κB p65, leading to nuclear translocation and binding to the COX-2 promoter element to enhance promoter activity, which was reduced by G?6976, SP600125, SB202190, or U0126. These findings supported that COX-2/PGE2 expression triggered by thrombin was engaged in PAR1/Gq or Gi/o/PKCα/MAPK-dependent NF-κB activation in HTSMCs
A certificateless aggregate signature scheme for security and privacy protection in VANET
No full text[[abstract]]In the vehicular ad hoc network, moving vehicles can keep communicating with each other by entering or leaving the network at any time to establish a new connection. However, since many users transmit a substantial number of messages, it may cause reception delays and affect the entire system. A certificateless aggregate signature scheme can provide a signature compression that keeps the verification cost low. Therefore, it is beneficial for environments constrained by time, bandwidth, and storage, such as vehicular ad hoc network. In recent years, several certificateless aggregate signature schemes have been proposed. Unfortunately, some of them still have some security and privacy issues under specific existing attacks. This article offers an authentication scheme that can improve security, privacy, and efficiency. First, we apply the certificateless aggregate signature method to prevent the onboard unit devices from leaking sensitive information when sending messages. The scheme is proven to be secure against the Type-1 (A1) and Type-2 (A2) adversaries in the random oracle model under the computational Diffie–Hellman problem assumption. Then, the performance evaluation demonstrates that our proposed scheme is more suitable for deployment in vehicular ad hoc network environments
Adaptive Processor Frequency Adjustment for Mobile-Edge Computing With Intermittent Energy Supply
No full text[[abstract]]With astonishing speed, bandwidth, and scale, Mobile Edge Computing (MEC) has played an increasingly important role in the next generation of connectivity and service delivery. Yet, along with the massive deployment of MEC servers, the ensuing energy issue is now on an increasingly urgent agenda. In the current context, the large scale deployment of renewable-energy-supplied MEC servers is perhaps the most promising solution for the incoming energy issue. Nonetheless, as a result of the intermittent nature of their power sources, these special design MEC server must be more cautious about their energy usage, in a bid to maintain their service sustainability as well as service standard. Targeting optimization on a single-server MEC scenario, we in this paper propose NAFA, an adaptive processor frequency adjustment solution, to enable an effective plan of the server's energy usage. By learning from the historical data revealing request arrival and energy harvest pattern, the deep reinforcement learning-based solution is capable of making intelligent schedules on the server's processor frequency, so as to strike a good balance between service sustainability and service quality. The superior performance of NAFA is substantiated by real-data-based experiments, wherein NAFA demonstrates up to 20% increase in average request acceptance ratio and up to 50% reduction in average request processing time
Does Weekends Effect Exist in Asia? Analysis of Endovascular Thrombectomy for Acute Ischemic Stroke in A Medical Center
No full text[[abstract]]Background: Discussing the quality measurements based on interrupted time series in ischemic stroke, delays are often attributed to weekends effect. This study compared the metrics and outcomes of emergent endovascular thrombectomy (EST) during working hours versus non-working hours in the emergency department of an Asian medical center.
Methods: A total of 297 patients who underwent EST between January 2015 and December 2018 were retrospectively included, with 52.5% of patients presenting during working hours and 47.5% presenting during nights, weekends, or holidays.
Results: Patients with diabetes were more in non-working hours than in working hours (53.9% vs. 41.0%; p=0.026). It took longer during nonworking hours than working hours in door-to -image times (13 min vs. 12 min; p=0.04) and door-to-groin puncture times (median: 112 min vs. 104 min; p=0.042). Significant statistical differences were not observed between the two groups in neurological outcomes, including successful reperfusion and complications such as intracranial hemorrhage and mortality. However, the change in National Institute of Health Stroke Scale (NIHSS) scores in 24 hours was better in the working-hour group than in the nonworking-hour group (4 vs. 2; p=0.058).
Conclusion: This study revealed that nonworking-hour effects truly exist in patients who received EST. Although delays in door-to-groin puncture times were noticed during nonworking hours, significant differences in neurological functions and mortality were not observed between working and non-working hours. Nevertheless, methods to improve the process during non-working hours should be explored in the future
LShape Partitioning: Parallel Skyline Query Processing using MapReduce
No full text[[abstract]]A skyline query searches the data points that are not dominated by others in the dataset. It is widely adopted for many applications which require multi-criteria decision making. However, skyline query processing is considerably time-consuming for a high-dimensional large scale dataset. Parallel computing techniques are therefore needed to address this challenge, among which MapReduce is one of the most popular frameworks to process big data. A great number of efficient MapReduce skyline algorithms have been proposed in the literature and most of their designs focus on partitioning and pruning the given dataset. However, there are still opportunities for further parallelism. In this study, we propose two parallel skyline processing algorithms using a novel LShape partitioning strategy and an effective Propagation Filtering method. These two algorithms are 2Phase LShape and 1Phase LShape , used for multiple reducers and single reducer, respectively. By extensive experiments, we verify that our algorithms outperformed the state-of-the-art approaches, especially for high-dimensional large scale datasets
Multimodal Time-Aware Attention Networks for Depression Detection
No full text[[abstract]]Depression is a common mental disorder, which may lead to suicide when the condition is severe. With the advancement of technology, there are billions of people who share their thoughts and feelings on social media at any time and from any location. Social media data has therefore become a valuable resource to study and detect the depression of the user. In our work, we use Instagram as the platform to study depression detection. We use hashtags to find users and label them as depressive or non-depressive according to their self-statement. Text, image, and posting time are used jointly to detect depression. Furthermore, the time interval between posts is important information when studying medical-related data. In this paper, we use time-aware LSTM to handle the irregularity of time intervals in social media data and use an attention mechanism to pay more attention to the posts that are important for detecting depression. Experiment results show that our model outperforms previous work with an F1-score of 95.6%. In addition to the good performance on Instagram, our model also outperforms state-of-the-art methods in detecting depression on Twitter with an F1-score of 90.8%. This indicates the potential of our model to be a reference for psychiatrists to assess the patient; or for users to know more about their mental health condition