mohammadjavad nourmohammadi

Neuropathic pain is one of the most important chronic and pathological problems that can cause disruptions in human life. Some studies indicated that the release of inflammatory cytokines and increased oxidative activity can increase nerve damage. Adalimumab is a human anti-monoclonal drug that can cause therapeutic effects in different diseases. The present study aimed to investigate the analgesic effects of adalimumab in the chronic constriction injury (CCI) experimental pain model in rats.

A total of 20 male Wistar rats were utilized in this study and were randomly assigned to four groups: the first group served as the control, the second group underwent CCI, the third group received CCI in conjunction with adalimumab (5 mg/kg), and the fourth group received CCI with adalimumab (10 mg/kg). Behavioral assessments were conducted 4, 7, and 14 days post-CCI induction. The spinal cords were extracted after these assessments, and the supernatants were analyzed for inflammatory and oxidative enzymes. Data analysis was performed using Prism GraphPad statistical software.

The analysis of the obtained data indicated that the injection of adalimumab in the third and fourth groups decreased the activity of inflammatory cytokines, such as TNF-α, IL-6, and CRP. In addition, it decreased the activity of MDA and increased the SOD and CAT enzymes. Moreover, adalimumab significantly improved the outcomes of thermal allodynia, mechanical allodynia, and thermal hyperalgesia in the CCI rats treated with this medication.

The administration of adalimumab can be used to treat or reduce neuropathic pain with its anti-inflammatory and antioxidant activity, along with neuroprotective effects.

The present study was conducted to investigate the effects of granulocyte colony-stimulating factor (G-CSF) after acute spinal cord injury on increasing a grade of improvement entitled American spinal cord injury association impairment scale (AIS) as an individual participant data (IPD) meta-regression analysis of clinical trials. Methods and Materials/Patients: According to our search strategy, four studies were selected. Multilevel ordered logistic regression modeling was used to predict AIS grade with G-CSF administration and time variable (first day and a 3-month follow-up). The IDs of the studies as well as the time series variable were imported to the random part of the model. Odds ratio (OR) and 95% confidence interval (CI) were reported.

A total of 277 samples were studied. A fixed effect model was performed at first. Accordingly, using G-CSF was associated with increased AIS grade (lower impairment) (OR=1.503, 95% CI=1.110-2.035) adjusted with time series (OR=1.868, 95% CI=1.378-2.532). In the mixed effect model, G-CSF was again associated with increased AIS grade (OR=1.780, 95% CI=1.301- 2.436) adjusted with time series (OR=2.152, 95% CI=1.406-3.294).

The present meta-analysis showed the protective effect of GCS-F observed as an improvement in AIS grade. This protecting effect was further after adjusting the random effects of time series and individual studies. Although multilevel modeling could reduce our limitations, it should be regarded that the number of trials was not enough to establish strong conclusions.