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Objective: Cervical traumatic spinal cord injury (CTSCI) is a seriously disabling disease that severely affects the physical and mental health of patients and imposes a huge economic burden on patients and their families. Accurate identification of the prognosis of CTSCI patients helps clinicians to design individualized treatment plans for patients. For this purpose, a dynamic nomogram was developed to predict the recovery of CTSCI patients after 6 months. Methods:We retrospectively included 475 patients with CTSCI in our institution between March 2013 and January 2022.The outcome variable of the current study was a satisfactory recovery of patients with CTSCI at 6 months. Univariate analyses and univariate logistic regression analyses were used to assess the factors affecting the prognosis of patients with CTSCI. Subsequently, variables (P < 0.05) were included in the multivariate logistic regression analysis to evaluate these factors further. Eventually, a nomogram model was constructed according to these independent risk factors. The concordance index (C-index) and the calibration curve were utilized to assess the model's predictive ability. The discriminating capacity of the prediction model was measured by the receiver operating characteristic (ROC) area under the curve (AUC). One hundred nine patients were randomly selected from 475 patients to serve as the center's internal validation test cohort. Results:The multivariate logistic regression model further screened out six independent factors that impact the recovery of patients with CTSCI. Including admission to the American Spinal Injury Association Impairment Scale (AIS) grade, the length of high signal in the spinal cord, maximum spinal cord compression (MSCC), spinal segment fractured, admission time, and hormonal therapy within 8 h after injury. A nomogram prediction model was developed based on the six independent factors above. In the training cohort, the AUC of the nomogram that included these predictors was 0.879, while in the test cohort, it was 0.824. The nomogram C-index incorporating these predictors was 0.872 in the training cohort and 0.813 in the test cohort, while the calibration curves for both cohorts also indicated good consistency. Furthermore, this nomogram was converted into a Web-based calculator, which provided individual probabilities of recovery to be generated for individuals with CTSCI after 6 months and displayed in a graphical format. Conclusion:The nomogram, including ASIA grade, the length of high signal in the spinal cord, MSCC, spinal segment fractured, admission time, and hormonal therapy within 8 h after injury, is a promising model to predict the probability of content recovery in patients with CTSCI. This nomogram assists clinicians in stratifying patients with CTSCI, enhancing evidence-based decision-making, and individualizing the most appropriate treatment.

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Aims: TANK-binding kinase 1 (TBK1) is involved in regulating the pathological process of a variety of inflammatory diseases in the central nervous system. However, its role and underlying molecular mechanisms in spinal cord injury (SCI) remain largely unknown. Methods:We employed the TBK1 inhibitor amlexanox (ALX) to address this question.An in vivo clip-compressive SCI model and in vitro lipopolysaccharide (LPS)-induced astrocyte inflammation model were established to examine the effects of TBK1 inhibition on the expression of proinflammatory cytokines. Results:In this study, we found that TBK1 and TBK1-medicated innate immune pathways, such as TBK1/IRF3 and noncanonical NF-κB signaling, were activated in astrocytes and neurons after SCI. Furthermore, inhibition of TBK1 by ALX alleviated neuroinflammation response, reduced the loss of motor neurons, and improved the functional recovery after SCI. Mechanistically, inhibition of TBK1 activity promoted the activation of the noncanonical NF-κB signaling pathway and inhibited p-IRF3 activity in LPS-induced astrocytes, and the TBK1 activity was required for astrocytic activation through yes-associated protein (YAP) signaling after SCI and in LPS-induced astrocytes inflammation model. Conclusion:TBK1-medicated innate immune pathway in astrocytes through YAP signaling plays an important role in the pathogenesis of SCI and inhibition of TBK1 may be a potential therapeutic drug for SCI.