CREB1 Facilitates GABAergic Neural Differentiation of Human Mesenchymal Stem Cells through BRN2 for Pain Alleviation and Locomotion Recovery after Spinal Cord Injury.

The transplantation of GABAergic neuron cells has been reported to alleviate nerve pain and improve motor function after spinal cord injury (SCI). However, human mesenchymal stem cell (hMSC) differentiation into GABAergic neuron cells in a sufficient quantity remains to be accomplished. From a database screening, cAMP-responsive element-binding protein 1 (CREB1) was chosen as a potential modulator due to its critical role in the protein-protein interaction of genes related to GABAergic neural differentiation. Here, CREB1 was overexpressed in transfected hMSCs, where CREB1 could induce differentiation into GABAergic neuron cells with an upregulation of Map2 and GAD1 by 2- and 3.4-fold, respectively. Additionally, GABAergic neural differentiation was enhanced, while Notch signaling was inhibited, and BRN2 transcriptional activation played an important role in neuronal maturation. Moreover, transfected hMSCs injected into immunocompromised mice caused by CsA exhibited the neuronal markers Tuj1 and Map2 via the intraspinal route, suggesting an improvement in survival and neural differentiation. Significantly, improvement in both BMS scores (6.2 ± 1.30 vs. 4 ± 0) and thermal hyperalgesia latency (7.74 ± 2.36 s vs. 4.52 ± 0.39 s) was seen compared with the SCI naïve treatment at 4 weeks post-transplantation. Our study demonstrates that CREB1 is crucial in generating induced GABAergic neuron cells (iGNs) originating from hMSCs. Transplanting iGNs to injured spinal cord provides a promising strategy for alleviating neuropathic pain and locomotion recovery after SCI.

A Preoperative Predictive Model of Lower Lumbar Spine Instability Based on Three-Dimensional Computed Tomography: A Retrospective Case-Control Pilot Study.

OBJECTIVE: This study aimed to build a predictive model of lower lumbar instability. METHODS: This retrospective study included 199 patients. Patients were divided into the lower lumbar instability group (LLIG) (n = 98) and lower lumbar stability group (LLSG) (n = 101). All participants of LLIG were recruited over a 2-year period (2015-2017) from the patients who accept lumbar surgery at the First Hospital of Jilin University. The LLSG was selected from outpatients who had underwent lumbar spine computed tomography (CT) and Flexion and extension radiographs (FER) at the First Hospital of Jilin University from 2015 to 2017. Several lower lumbar parameters were measured, including Lordosis angle (LA), intervertebral height (IH), ratio of anterior height to posterior height (APR), angle between endplate and anterior edge of vertebral body (AEPVa), sagittal slip ratio (SSR), and angle between the upper endplate and z-axis on sagittal plane (AUEZS). These parameters were keyed into the SPSS software to create a predictive model for classification. Sensitivity, specificity, predictive accuracy, and Kappa value were used to evaluate the predictive model. RESULTS: Compared with LLSG, the LA of LLIG decreased by 3.49° (126.54° vs 130.3°). Similarly, the IH of LLIG decreased by 1.23°mm, 1.66°mm, and 0.71°mm at L3-4, L4-5, and L5-S1. Compared with LLSG, the SSR of LLIG is higher at L3-4, L4-5, and L5-S1 (0.54 vs 0.51, 0.57 vs 0.46, and 0.59 vs 0. 47). Moreover, the APR of LLIG is higher than those of LLSG at L3-4, L4-5, and L5-S1 (1.97 vs 1.81, 2.40 vs 1.97, and 2.69 vs 2.26). The LLIG has bigger AEPVa than LLIG at L3-4, L4-5, and L5-S1. Compared with LLSG, the AUEZS of LLIG is bigger at L3-4 (91.75° vs 90.81°) and smaller at L4-5 and L5-S1(84.63° vs 85.85° and 73.27° vs 75.01°). The SSR (L4) show highest predictive accuracy (83%) when every parameter was fed to LDA classifier to generate a univariate model. All parameters represent a statistically significant difference (P < 0.05) between LLSG and LLIG. The model including LA, APR (L5-S1), IH (L4-5), SSR (L5), AUEZS (L5) has highest predictive accuracy of 88.2%. The sensitivity, specificity, and Kappa value are 88.7%, 93.1%, and 0.77. CONCLUSION: The predictive model has good classification performance and can be an auxiliary tool for clinicians to evaluate lumbar instability in preoperative patients with severe pain aggravated by lumbar movement.

Thoracic gout tophus with abdominal wall protrusion: A case report.

RATIONALE: A patient presented the abdominal wall protrusion due to tophaceous gout of the spine. Similar cases were not reported in the literature. This study aimed to report a case of tophaceous gout of the spine with abdominal wall protrusion. PATIENT CONCERNS: A 38-year-old male patient had a 10-year history of gout and hyperuricemia. He complained of back pain and abdominal wall protrusion. DIAGNOSES: The patient was diagnosed with tophaceous gout of the spine with abdominal wall weakness caused by T11 nerve root compression. INTERVENTIONS: A semi-lamina decompression was performed at T11-T12. The pathological examination of the specimen demonstrated tophaceous gout of the spine. OUTCOMES: After the surgery, the patient's back pain was completely relieved and the abdominal wall weakness significant improved. LESSONS: This case highlighted that axial gout could mimic thoracic disk herniation clinically. The abdominal wall weakness might also be due to single T11 nerve compression by the tophaceous gout of the spine. In patients with a history of gout, axial gout should be considered as one of the differential diagnoses.