Social media has become one of the main channels for people to access and consume news, due to the rapidness and low cost of news dissemination on it. However, such properties of social media also make it a hotbed of fake news dissemination, bringing negative impacts on both individuals and society. Therefore, detecting fake news has become a crucial problem attracting tremendous research effort. Most existing methods of fake news detection are supervised, which require an extensive amount of time and labor to build a reliably annotated dataset. In search of an alternative, in this paper, we investigate if we could detect fake news in an unsupervised manner. We treat truths of news and users’ credibility as latent random variables, and exploit users’ engagements on social media to identify their opinions towards the authenticity of news. We leverage a Bayesian network model to capture the conditional dependencies among the truths of news, the users’ opinions, and the users’ credibility. To solve the inference problem, we propose an efficient collapsed Gibbs sampling approach to infer the truths of news and the users’ credibility without any labelled data. Experiment results on two datasets show that the proposed method significantly outperforms the compared unsupervised methods.

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We explored whether acute atorvastatin treatment would improve clinical outcomes and reduce the incidence of cerebral vasospasm after aneurysmal subarachnoid hemorrhage in elderly Chinese adults. Patients (60 to 90 years old) were admitted to intensive care units after surgery to clip or embolize their aneurysms. We assessed 592 patients and assigned 159 to receive atorvastatin (20 mg/day) and 158 to receive placebo once daily for up to 14 days. The primary outcome was the Glasgow outcome scale at 6 months, and secondary outcomes were cerebral vasospasm, 30-days all-cause mortality, cerebral infarction, and delayed ischemic neurological deficit. The incidence of postoperative cerebral vasospasm (39.3% vs 56%, P =0.004) and cerebral infarction (18.7% vs 27.3%, P=0.027) were significantly lower in the atorvastatin group. The study did not detect benefits in the use of atorvastatin for 6 months clinical outcome or 30-day all-cause mortality, but it suggests that atorvastatin together with nimodipine can reduce cerebral vasospasm and cerebral infarction after subarachnoid hemorrhage.

Netrin‐1 ( NTN ‐1) is a novel drug to alleviate early brain injury following subarachnoid haemorrhage ( SAH ). However the molecular mechanism of NTN ‐1‐mediated protection against early brain injury following SAH remains largely elusive. This study aims to evaluate the effects and mechanisms of NTN ‐1 in protecting SAH ‐induced early brain injury. The endovascular perforation SAH model was constructed using male C57 BL /6J mice, and recombinant NTN ‐1 was administrated intravenously. Mortality rates, SAH grade, brain water content, neurological score and neuronal apoptosis were evaluated. The expression of PPAR γ, Bcl‐2, Bax and nuclear factor‐kappa B ( NF ‐κB) were detected by Western blot. Small interfering RNA specific to NTN ‐1 receptor, UNC 5B, and a selective PPAR γ antagonist, bisphenol A diglycidyl ether ( BADGE ), were applied in combination with NTN ‐1. The results suggested that NTN ‐1 improved the neurological deficits, reduced the brain water content and alleviated neuronal apoptosis. In addition, NTN ‐1 enhanced PPAR γ and Bcl‐2 expression and decreased the levels of Bax and NF ‐κB. However, the neuroprotection of NTN ‐1 was abolished by UNC 5B and BADGE . In conclusion, our results demonstrated that NTN ‐1 attenuates early brain injury following SAH via the UNC 5B PPAR γ/ NF ‐κB signalling pathway.

Monocyte chemoattractant protein-1 (MCP1) polymorphism has been reported to be associated with systemic lupus erythematosus (SLE). However, the correlation between the polymorphism and SLE is poorly understood. In this study we investigated the role of this polymorphism together with that of chemokine SDF1-3'A and chemokine receptor CCR2-V64I. The association between gene polymorphism and SLE was explored by way of a case-control study. In 143 patients with SLE and 157 healthy controls, the polymorphisms of SDF1-3'A, -2518MCP-1 and CCR2-V64I were determined using PCR-RFLP and an amplification-refractory mutation system, respectively. No significant difference was found in allelic and genotype frequency of SDF1-3'A, CCR2-V64I and -2518MCP-1 between SLE patients and controls. However, a significant increase in the frequency of the AG genotype of MCP-1 was found among patients with arthritis (P(c)=0.003, OR 3.08, 95%CI 1.27-7.57). The frequency of individuals having G at position -2518 of the MCP-1 gene was also increased among patients with arthritis (P(c)=0.028, OR 2.99, 95%CI 1.13-8.08). It is noteworthy that the frequency of -2518MCP-1G in the Chinese Han population was 64%. The results indicate an association between the presence of G at position -2518 in the MCP-1 promoter region and the presence of arthritis in patients with SLE.