Salt-inducible kinase (SIK), which belongs to the sucrose non-fermenting 1/AMP-activated protein kinase family, was first discovered in the adrenal cortex of a rat on a high-salt diet. As an isoform of the SIK family, SIK2 modulates various biological functions and acts as a signal transmitter in various pathways. Compared with that in adjacent normal tissues, the expression of SIK2 is significantly higher in multiple types of tumors, which indicates its pivotal effect in oncogenesis. Studies on SIK2 have recently underlined its role in several signaling pathways, including the PI3K-Akt-mTOR pathway, the Hippo-YAP pathway, the LKB1-HDAC axis, and the cAMP-PKA axis. Moreover, a few small-molecule SIK2 inhibitors have been found to be able to rescue the oncogenicity of SIK2 during tumor development and reverse its abnormal activation of downstream pathways. In this mini-review, we discuss the results of in vivo and in vitro studies regarding the SIK2 mechanism in different signaling pathways, particularly their regulation of cancer cells. This work may provide new ideas for targeting SIK2 as a novel therapeutic strategy in tumor therapy.

An easy scoring system to predict the risk of poor outcome after mechanical thrombectomy among the elderly is currently not available. Therefore, we aimed to develop a nomogram for predicting the probability of negative prognosis in aged patients with acute ischemic stroke undergoing thrombectomy. In addition, we sought to investigate the association between histological thrombus composition and stroke characteristics. To this end, we prospectively studied a developed cohort using data collected from a stroke center from November 2015 to December 2019. The main outcome was functional independence, defined as a modified Rankin   Scale   score ≤ 2 at 90 days following a mechanical thrombectomy. A nomogram model based on multivariate logistic models was generated. The retrieved thrombi were stained with hematoxylin and eosin and assessed according to histological composition. Our results demonstrated that age ≥ 72   years was independently associated with poor outcome. A total of 304 participants completed the follow-up data to generate the nomogram model. After multivariate logistic regression, five variables remained independent predictors of outcome, including older age, hemorrhagic transformation, thrombolysis in cerebral infarction score, National Institute of Health Stroke score, and neutrophil-to-lymphocyte ratio, and were used to generate the nomogram. The area under the receiver-operating characteristic curve of the model was 0.803. The clots from elderly subjects with large-artery atherosclerosis, anterior circulation, and successful recanalization groups had a higher percentage of fibrin compared to those of younger patients. This is the first nomogram to be developed and validated in a stroke center cohort for individualized prediction of poor outcome in elderly patients after mechanical thrombectomy. Clot composition provides valuable information on the underlying pathogenesis of oxidation in older patients.

Background: Systemic immune-inflammation index (SII) is a novel biomarker that reflects the state of a patient's inflammatory and immune status. This study aimed to determine the clinical significance of SII as a predictor of delayed cerebral ischemia (DCI) in patients with aneurysmal subarachnoid hemorrhage (SAH).Methods: Retrospective data were collected from aneurysmal SAH patients who had been admitted to our hospital between January 2015 and October 2019. Both univariate and multivariate analyses were performed to investigate whether SII was an independent predictor of DCI. In addition, the receiver operating characteristic (ROC) curve and area under the curve (AUC) were also evaluated.Results: There were 333 patients with aneurysmal SAH included in this study. Multivariate logistic analysis revealed that a modified Fisher grade 3 and 4 score [odds ratio (OR) = 7.851, 95% confidence interval (CI): 2.312–26.661, P = 0.001] and elevated SII (OR = 1.001, 95% CI: 1.001–1.002, P < 0.001) were independent risk factors for DCI. ROC curves showed that SII could predict DCI with an AUC of 0.860 (95% CI: 0.818–0.896, P < 0.001). The optimal cut-off value for SII to predict DCI was 1,424, and an SII ≥ 1,424 could predict DCI with a sensitivity of 93.1% and a specificity of 68.1%. Patients with higher SII value on admission tended to have higher incidence of acute hydrocephalus and DCI, greater modified Fisher and Hunt-Hess scales, and poorer outcomes.Conclusions: SII is an independent predictor of DCI in patients with aneurysmal SAH. The SII system can be implemented in a routine clinical setting to help clinicians diagnose patients with high risk of DCI.