Taz/Tead1 Promotes Alternative Macrophage Activation and Kidney Fibrosis via Transcriptional Upregulation of Smad3.

Macrophage alternative activation is involved in kidney fibrosis. Previous researches have documented that the transcriptional regulators Yes-associated protein (Yap)/transcriptional coactivator with PDZ-binding motif (Taz) are linked to organ fibrosis. However, limited knowledge exists regarding the function and mechanisms of their downstream molecules in regulating macrophage activation and kidney fibrosis. In this paper, we observed that the Hippo pathway was suppressed in macrophages derived from fibrotic kidneys in mice. Knockout of Taz or Tead1 in macrophages inhibited the alternative activation of macrophages and reduced kidney fibrosis. Additionally, by using bone marrow-derived macrophages (BMDMs), we investigated that knockout of Taz or Tead1 in macrophages impeded both cell proliferation and migration. Moreover, deletion of Tead1 reduces p-Smad3 and Smad3 abundance in macrophages. And chromatin immunoprecipitation (ChIP) assays showed that Tead1 could directly bind to the promoter region of Smad3. Collectively, these results indicate that Tead1 knockout in macrophages could reduce TGFß1-induced phosphorylation Smad3 via transcriptional downregulation of Smad3, thus suppressing macrophage alternative activation and IRI-induced kidney fibrosis.

TruthTrust: Truth Inference-Based Trust Management Mechanism on a Crowdsourcing Platform.

On a crowdsourcing platform, in order to cheat for rewards or sabotage the crowdsourcing processes, spam workers may submit numerous erroneous answers to the tasks published by requesters. This type of behavior extremely reduces the completion rate of tasks and the enthusiasm of honest users, which may lead a crowdsourcing platform to a failure. Defending against malicious attacks is an important issue in crowdsourcing, which has been extensively addressed by existing methods, e.g., verification-based defense mechanisms, data analysis solutions, trust-based defense models, and workers' properties matching mechanisms. However, verification-based defense mechanisms will consume a lot of resources, and data analysis solutions cannot motivate workers to provide high-quality services. Trust-based defense models and workers' properties matching mechanisms cannot guarantee the authenticity of information when collusion requesters publish shadow tasks to help malicious workers get more participation opportunities. To defend such collusion attacks in crowdsourcing platforms, we propose a new defense model named TruthTrust. Firstly, we define a complete life cycle system that from users' interaction to workers' recommendation, and separately define the trust value of each worker and the credence of each requester. Secondly, in order to ensure the authenticity of the information, we establish a trust model based on the CRH framework. The calculated truth value and weight are used to define the global properties of workers and requesters. Moreover, we propose a reverse mechanism to improve the resistance under attacks. Finally, extensive experiments demonstrate that TruthTrust significantly outperforms the state-of-the-art approaches in terms of effective task completion rate.

Resolvin D1 ameliorates cognitive impairment following traumatic brain injury via protecting astrocytic mitochondria.

Cognitive impairment is one of the most common and devastating neuropsychiatric sequelae after traumatic brain injury (TBI), and hippocampal neuronal survival plays a causal role in this pathological process. Resolvin D1 (RvD1), an important endogenous specialized pro-resolving mediator, has recently been reported to exert a potent protective effect on mitochondria. This suggests that RvD1 may suppress neuroinflammation and protect astrocytic mitochondria at the same time to play further neuroprotective roles. C57BL/6 mice subjected to TBI using a controlled cortical impact device were used for in vivo experiments. Cultured primary mouse astrocytes and an N2a mouse neuroblastoma cell line were used for in vitro experiments. In TBI mice, RvD1 significantly ameliorated cognitive impairment, suppressed gliosis and alleviated neuronal loss in the hippocampus. To explore the mechanism underlying this activity, we verified that RvD1 can induce a higher level of mitophagy to remove damaged mitochondria and eliminate extra mitochondria-derived reactive oxygen species (mitoROS) by activating ALX4/FPR2 receptors in astrocytes. In an in vitro model, we further confirmed that RvD1 can protect mitochondrial morphology and membrane potential in astrocytes and thereby enhance the survival of neurons. Meanwhile, RvD1 was also shown to increase the expression of brain-derived neurotrophic factor and glutamate aspartate transporter in the hippocampus following TBI, which indicates a possible way by which RvD1 increases the supportive function of astrocytes. These findings suggest that RvD1 may be a potent therapeutic option for ameliorating cognitive impairment following TBI by controlling neuroinflammation and protecting astrocytic mitochondria.

Heuristic Approaches for Enhancing the Privacy of the Leader in IoT Networks.

The privacy and security of the Internet of Things (IoT) are emerging as popular issues in the IoT. At present, there exist several pieces of research on network analysis on the IoT network, and malicious network analysis may threaten the privacy and security of the leader in the IoT networks. With this in mind, we focus on how to avoid malicious network analysis by modifying the topology of the IoT network and we choose closeness centrality as the network analysis tool. This paper makes three key contributions toward this problem: (1) An optimization problem of removing k edges to minimize (maximize) the closeness value (rank) of the leader; (2) A greedy (greedy and simulated annealing) algorithm to solve the closeness value (rank) case of the proposed optimization problem in polynomial time; and (3)UpdateCloseness (FastTopRank)-algorithm for computing closeness value (rank) efficiently. Experimental results prove the efficiency of our pruning algorithms and show that our heuristic algorithms can obtain accurate solutions compared with the optimal solution (the approximation ratio in the worst case is 0.85) and outperform the solutions obtained by other baseline algorithms (e.g., choose k edges with the highest degree sum).

SPS and DPS: Two New Grid-Based Source Location Privacy Protection Schemes in Wireless Sensor Networks.

Wireless Sensor Networks (WSNs) have been widely deployed to monitor valuable objects. In these applications, the sensor node senses the existence of objects and transmitting data packets to the sink node (SN) in a multi hop fashion. The SN is a powerful node with high performance and is used to collect all the information sensed by the sensor nodes. Due to the open nature of the wireless medium, it is easy for an adversary to trace back along the routing path of the packets and get the location of the source node. Once adversaries have got the source node location, they can capture the monitored targets. Thus, it is important to protect the source node location privacy in WSNs. Many methods have been proposed to deal with this source location privacy protection problem, and most of them provide routing path diversity by using phantom node (PN) which is a fake source node used to entice the adversaries away from the actual source node. But in the existing schemes, the PN is determined by the source node via flooding, which not only consumes a lot of communication overhead, but also shortens the safety period of the source node. In view of the above problems, we propose two new grid-based source location privacy protection schemes in WSNs called grid-based single phantom node source location privacy protection scheme (SPS) and grid-based dual phantom node source location privacy protection scheme (DPS) in this paper. Different from the idea of determining the phantom node by the source node in the existing schemes, we propose to use powerful sink node to help the source node to determine the phantom node candidate set (PNCS), from which the source node randomly selects a phantom node acting as a fake source node. We evaluate our schemes through theoretical analysis and experiments. Experimental results show that compared with other schemes, our proposed schemes are more efficient and achieves higher security, as well as keeping lower total energy consumption. Our proposed schemes can protect the location privacy of the source node even in resource-constrained wireless network environments.

miR-30a attenuates cardiac fibrosis in rats with myocardial infarction by inhibiting CTGF.

The mechanism of miR-30a in myocardial fibrosis in rats with myocardial infarction (MI) was investigated. rAAV9-miR-30a was constructed and transfected to heart via injecting into the left ventricular cavity of MI rats. The sham operation group, control group, miR-30a group and miR-30a-NC group were established. Besides, the 3'-UTR of CTGF was inserted into luciferase expression plasmid (pMir-report), then transfected into COS1 cells. miR-30a and control miRNA were, respectively, cotransfected into COS1 cells. The expression of luciferase was detected before and after knockdown of the binding site of miR-30a and the 3'-UTR of CTGF. Four weeks after MI surgery, cardiac function was measured by color Doppler echocardiography, including short axis shortening (FS) and left ventricular ejection fraction (LVEF); the myocardial collagen volume fraction (CVF) was observed by Masson's staining; deposition of collagen I and collagen III were evaluated by immunohistochemical stain; using real-time PCR to detect expression levels of miR-30a and CTGF; the expression of CTGF was observed by western blotting. In MI group, cardiac function was significantly improved, while the expression levels of CVF, collagen I and III, the ratio of type I/III collagen, CTGF were significantly reduced. After knockdown the binding site of miR-30a and the 3'-UTR of CTGF, luciferase expression in COS1 cells decreased significantly. miR-30a might inhibit the expression of CTGF by directly combining with the 3'-UTR site of CTGF after MI, thereby reduce the production of collagen in myocardia, inhibit myocardial fibrosis, then improve cardiac function.

Comparison of the effect of rosuvastatin versus rosuvastatin/ezetimibe on markers of inflammation in patients with acute myocardial infarction.

Statins lower low-density lipoprotein cholesterol (LDL-C) and high-sensitivity C-reactive protein (hsCRP), and the addition of ezetimibe to statins further reduces LDL-C and hsCRP. Lipoprotein-associated phospholipase A2 (Lp-PLA2) is a potentially important pathogenic factor participating in the progression of atherosclerosis. The aim of current study was to investigate how the addition of ezetimibe to rosuvastatin treatment affects reductions in LDL-C, hsCRP and Lp-PLA2 in patients with acute myocardial infarction (AMI). A total of 135 patients were enrolled in the study within 24 h of AMI, and were randomized to receive 10 mg rosuvastatin or 10 mg rosuvastatin plus 10 mg ezetimibe daily. HsCRP, Lp-PLA2, total cholesterol (TC), triglycerides (TG), LDL-C and high-density lipoprotein cholesterol (HDL-C) were determined at baseline and after 1, 3, 6 and 12 months of treatment. The addition of ezetimibe to rosuvastatin led to greater reduction of LDL-C compared with rosuvastatin monotherapy (from 3.00 to 1.19 mmol/l vs. 2.93 to 1.49 mmol/l, respectively; P<0.05), as well as reduced levels of hsCRP (from 5.15 to 0.68 mg/l vs. 4.33 to 1.49 mg/l, respectively; P<0.05) and Lp-PLA2 (from 333.13 to 79.07 mg/l vs. 327.95 to 123.62 mg/l, respectively; P<0.05). A positive association was identified between reductions of Lp-PLA2 and the changes of LDL-C (r=0.367; P=0.002). However, no significant correlation was observed between changes in Lp-PLA2 and hsCRP (r=0.264; P=0.512). The values of hsCRP and Lp-PLA2 appeared to increase during the first week after randomization, but dropped steeply to a lower level and remained stable thereafter. In conclusion, the addition of ezetimibe to rosuvastatin was demonstrated to further reduce LDL-C, hsCRP and Lp-PLA2 compared with rosuvastatin monotherapy in patients with AMI.

Voluntary Vaccination through Self-organizing Behaviors on Locally-mixed Social Networks.

Voluntary vaccination reflects how individuals weigh the risk of infection and the cost of vaccination against the spread of vaccine-preventable diseases, such as smallpox and measles. In a homogeneously mixing population, the infection risk of an individual depends largely on the proportion of vaccinated individuals due to the effects of herd immunity. While in a structured population, the infection risk can also be affected by the structure of individuals' social network. In this paper, we focus on studying individuals' self-organizing behaviors under the circumstance of voluntary vaccination in different types of social networks. Specifically, we assume that each individual together with his/her neighbors forms a local well-mixed environment, where individuals meet equally often as long as they have a common neighbor. We carry out simulations on four types of locally-mixed social networks to investigate the network effects on voluntary vaccination. Furthermore, we also evaluate individuals' vaccinating decisions through interacting with their "neighbors of neighbors". The results and findings of this paper provide a new perspective for vaccination policy-making by taking into consideration human responses in complex social networks.

Novel Threshold Changeable Secret Sharing Schemes Based on Polynomial Interpolation.

After any distribution of secret sharing shadows in a threshold changeable secret sharing scheme, the threshold may need to be adjusted to deal with changes in the security policy and adversary structure. For example, when employees leave the organization, it is not realistic to expect departing employees to ensure the security of their secret shadows. Therefore, in 2012, Zhang et al. proposed (t → t', n) and ({t1, t2,⋯, tN}, n) threshold changeable secret sharing schemes. However, their schemes suffer from a number of limitations such as strict limit on the threshold values, large storage space requirement for secret shadows, and significant computation for constructing and recovering polynomials. To address these limitations, we propose two improved dealer-free threshold changeable secret sharing schemes. In our schemes, we construct polynomials to update secret shadows, and use two-variable one-way function to resist collusion attacks and secure the information stored by the combiner. We then demonstrate our schemes can adjust the threshold safely.

Reputation-Based Investment Helps to Optimize Group Behaviors in Spatial Lattice Networks.

Encouraging cooperation among selfish individuals is crucial in many real-world systems, where individuals' collective behaviors can be analyzed using evolutionary public goods game. Along this line, extensive studies have shown that reputation is an effective mechanism to investigate the evolution of cooperation. In most existing studies, participating individuals in a public goods game are assumed to contribute unconditionally into the public pool, or they can choose partners based on a common reputation standard (e.g., preferences or characters). However, to assign one reputation standard for all individuals is impractical in many real-world deployment. In this paper, we introduce a reputation tolerance mechanism that allows an individual to select its potential partners and decide whether or not to contribute an investment to the public pool based on its tolerance to other individuals' reputation. Specifically, an individual takes part in a public goods game only if the number of participants with higher reputation exceeds the value of its tolerance. Moreover, in this paper, an individual's reputation can increase or decrease in a bounded interval based on its historical behaviors. We explore the principle that how the reputation tolerance and conditional investment mechanisms can affect the evolution of cooperation in spatial lattice networks. Our simulation results demonstrate that a larger tolerance value can achieve an environment that promote the cooperation of participants.

Fine-grained Database Field Search Using Attribute-Based Encryption for E-Healthcare Clouds.

An effectively designed e-healthcare system can significantly enhance the quality of access and experience of healthcare users, including facilitating medical and healthcare providers in ensuring a smooth delivery of services. Ensuring the security of patients' electronic health records (EHRs) in the e-healthcare system is an active research area. EHRs may be outsourced to a third-party, such as a community healthcare cloud service provider for storage due to cost-saving measures. Generally, encrypting the EHRs when they are stored in the system (i.e. data-at-rest) or prior to outsourcing the data is used to ensure data confidentiality. Searchable encryption (SE) scheme is a promising technique that can ensure the protection of private information without compromising on performance. In this paper, we propose a novel framework for controlling access to EHRs stored in semi-trusted cloud servers (e.g. a private cloud or a community cloud). To achieve fine-grained access control for EHRs, we leverage the ciphertext-policy attribute-based encryption (CP-ABE) technique to encrypt tables published by hospitals, including patients' EHRs, and the table is stored in the database with the primary key being the patient's unique identity. Our framework can enable different users with different privileges to search on different database fields. Differ from previous attempts to secure outsourcing of data, we emphasize the control of the searches of the fields within the database. We demonstrate the utility of the scheme by evaluating the scheme using datasets from the University of California, Irvine.

The outcomes of intra-aortic balloon pump usage in patients with acute myocardial infarction: a comprehensive meta-analysis of 33 clinical trials and 18,889 patients.

BACKGROUND: The effects of intra-aortic balloon pump (IABP) usage in patients with acute myocardial infarction remain controversial. This study sought to evaluate the outcomes of IABP usage in these patients. METHODS: Medline, EMBASE, and other internet sources were searched for relevant clinical trials. The primary efficacy endpoints (in-hospital, midterm, and long-term mortality) and secondary endpoints (reinfarction, recurrent ischemia, and new heart failure in the hospital) as well as safety endpoints (severe bleeding requiring blood transfusion and stroke in-hospital) were subsequently analyzed. RESULTS: Thirty-three clinical trials involving 18,889 patients were identified. The risk of long-term mortality in patients suffering from acute myocardial infarction was significantly decreased following IABP use (odds ratio [OR] 0.66, 95% confidence interval [CI]: 0.48-0.91, P=0.010). Both in-hospital and midterm mortality did not differ significantly between the IABP use group and no IABP use group (in-hospital: OR 0.87, 95% CI: 0.59-1.28, P=0.479; midterm: OR 1.12, 95% CI: 0.53-2.38, P=0.768). IABP insertion was not associated with the risk reduction of reinfarction, recurrent ischemia, or new heart failure. However, IABP use increased the risk of severe bleeding requiring blood transfusion (OR 2.05, 95% CI: 1.29-3.25, P=0.002) and stroke (OR 1.71, 95% CI: 1.04-2.82, P=0.035). In the thrombolytic therapy and cardiogenic shock subgroups, reduced mortality rates following IABP use were observed. CONCLUSION: IABP insertion is associated with feasible benefits with respect to long-term survival rates in patients suffering from acute myocardial infarction, particularly those suffering from cardiogenic shock and receiving thrombolytic therapy, but at the cost of higher incidence of severe bleeding and stroke.