Evidence Mapping Based on Systematic Reviews of Repetitive Transcranial Magnetic Stimulation on the Motor Cortex for Neuropathic Pain

Amygdala-Targeted Relief of Neuropathic Pain: Efficacy of Repetitive Transcranial Magnetic Stimulation in NLRP3 Pathway Suppression

This study investigates the effectiveness of repetitive transcranial magnetic stimulation (rTMS) as a nonpharmacological approach to treating neuropathic pain (NP), a major challenge in clinical research. Conducted on male Sprague-Dawley rats with NP induced through chronic constriction injury of the sciatic nerve, the research assessed pain behaviors and the impact of rTMS on molecular interactions within the amygdala. Through a comprehensive analysis involving Mechanical Withdrawal Threshold (MWT), Thermal Withdrawal Latency (TWL), RNA transcriptome sequencing, RT-qPCR, Western blotting, immunofluorescence staining, and Co-Immunoprecipitation (Co-IP), the study focused on the expression and interaction of integrin αvβ3 and its receptor P2X7R. Findings reveal that rTMS significantly influences the expression of integrin αvβ3 in NP models, suggesting an inhibition of the NP-associated NLRP3 inflammatory pathway through the disruption of integrin αvβ3-P2X7R interactions. These outcomes highlight the potential of rTMS in alleviating NP by targeting molecular interactions within the amygdala, offering a promising therapeutic avenue for managing NP.

Evidence mapping and quality assessment of systematic reviews on exercise intervention for Alzheimer's disease

BACKGROUND

A significant body of literature suggests that exercise can reverse cognitive impairment and ameliorate somatic function in patients with Alzheimer's disease (AD). Systematic reviews (SRs), a common approach of evidence-based medicine, concentrate on a specific issue of a research area. The objective of this work is to provide an overview of existing evidence on the effects of exercise intervention in AD patients and report related health outcomes by reviewing SRs.

METHODS

SRs on exercise intervention in AD patients were retrieved from the PubMed, the Cochrane Library, CBMdisc, Scopus, Web of Science, Embase (via Ovid), China National Knowledge Infrastructure, and WanFang databases from the time of inception to February 2023. The quality of the SRs was evaluated utilizing the A Measurement Tool to Assess Systematic Review 2 (AMSTAR 2) checklist. The results were reported according to the population-intervention-comparison-outcome (PICO) framework and the corresponding evidence mapping was illustrated in tables and bubble plots.

RESULTS

A total of 26 SRs met the eligibility criteria. In terms of methodological quality, 10 SRs were rated as "critically low", 13 SRs were rated as "low", and 3 SRs were rated as "moderate". Exercise was found to exert a beneficial effect on cognitive function, functional independence, physical function, and neuropsychiatric symptoms in patients with AD.

CONCLUSION

Exercise intervention benefits AD patients mainly by improving cognitive function, physical function, functional independence, and neuropsychiatric symptoms. However, due to the low-to-moderate methodology of most SRs included in this analysis, further investigations are required to support our current findings.

Effects of different transcranial magnetic stimulations on neuropathic pain after spinal cord injury

Introduction

Repetitive transcranial magnetic stimulation (rTMS) is an effective non-invasive cortical stimulation technique in the treatment of neuropathic pain. As a new rTMS technique, intermittent theta burst stimulation (iTBS) is also effective at relieving pain. We aimed to establish the pain-relieving effectiveness of different modalities on neuropathic pain. The study was conducted in individuals with spinal cord injury (SCI) and different modalities of rTMS.

Methods

Thirty-seven individuals with SCI were randomly allocated to three groups, in which the "iTBS" group received iTBS, the "rTMS" group received 10 Hz rTMS, and the "iTBS + rTMS" group received iTBS and 10 Hz rTMS successively of the primary motor cortex 5 days a week for 4 weeks, and they all underwent the full procedures. The primary outcome measure was change in the visual analog scale (VAS), and the secondary outcomes were measured using the Hamilton Rating Scale for Depression (HAM-D) and the Pittsburgh Sleep Quality Index (PSQI). All the outcomes were evaluated at 1 day before stimulation (baseline), 1 day after the first week of stimulation (S1), and 1 day after the last stimulation (S2).

Results

The VAS scores showed significant pain improvement after 4 weeks of stimulation (p = 0.0396, p = 0.0396, and p = 0.0309, respectively) but not after 1 week of stimulation. HAM-D scores declined, but the decreases were not significant until 4 weeks later (p = 0.0444, p = 0.0315, and p = 0.0447, respectively). PSQI scores were also significantly decreased after 4 weeks of stimulation (p = 0.0446, p = 0.0244, and p = 0.0088, respectively). Comparing the three modalities, VAS, HAM-D, and PSQI scores at S1 showed no differences, and, at S2, VAS scores showed significant differences (p = 0.0120; multiple comparisons showed significant differences between iTBS and iTBS + rTMS, p = 0.0091), while the HAM-D and PSQI scores showed no differences.

Discussion

The primary and secondary outcomes all showed significant improvement, indicating that the three different modalities were all effective at relieving the pain. However, not all the three stimulations were of same effectiveness after treatment; there were statistical differences in the treatment of neuropathic pain between iTBS as a priming stimulus and as a single procedure.

The Role of Gut Microbiota in Various Neurological and Psychiatric Disorders-An Evidence Mapping Based on Quantified Evidence

Methods

We searched PubMed, Cochrane Library, and Epistemonikos to identify systematic reviews and meta-analysis (SRs). We searched for neurological diseases and psychiatric disorders, including Alzheimer's disease (AD), attention deficit hyperactivity disorder (ADHD), amyotrophic lateral sclerosis (ALS), autism spectrum disorder (ASD), anorexia nervosa (AN), bipolar disorder (BD), eating disorder (ED), generalized anxiety disorder (GAD), major depressive disorder (MDD), multiple sclerosis (MS), obsessive compulsive disorder (OCD), Parkinson's disease (PD), posttraumatic stress disorder (PTSD), spinal cord injury (SCI), schizophrenia, and stroke. We used A Measurement Tool to Assess Systematic Reviews (AMSTAR-2) to evaluate the quality of included SRs. We also created an evidence map showing the role of gut microbiota in neurological diseases and the certainty of the evidence.

Results

In total, 42 studies were included in this evidence mapping. Most findings were obtained from observational studies. According to the AMSTAR-2 assessment, 21 SRs scored "critically low" in terms of methodological quality, 16 SR scored "low," and 5 SR scored "moderate." A total of 15 diseases have been investigated for the potential association between gut microbiome alpha diversity and disease, with the Shannon index and Simpson index being the most widely studied. A total of 12 diseases were investigated for potential link between beta diversity and disease. At the phylum level, Firmicutes, Bacteroidetes, Actinobacteria, Proteobacteria, and Verrucomicrobia were more researched. At the genus level, Prevotella, Coprococcus, Parabacteroides, Phascolarctobacterium, Escherichia Shigella, Alistipes, Sutteralla, Veillonella, Odoribacter, Faecalibacterium, Bacteroides, Bifidobacterium, Dialister, and Blautia were more researched. Some diseases have been found to have specific flora changes, and some diseases have been found to have common intestinal microbiological changes.

Conclusion

We found varied levels of evidence for the associations between gut microbiota and neurological diseases; some gut microbiota increased the risk of neurological diseases, whereas others showed evidence of benefit that gut microbiota might be promising therapeutic targets for such diseases.

Artificial intelligence-directed acupuncture: a review

Acupuncture is widely used around the whole world nowadays and exhibits significant efficacy against many chronic diseases, especially in pain-related diseases. With the rapid development of artificial intelligence (AI), its implementation into acupuncture has achieved a series of significant breakthroughs in many areas of acupuncture practice, such as acupoints selection and prescription, acupuncture manipulation identification, acupuncture efficacy prediction, and so on. The paper will discuss the significant theoretical and technical achievements in AI-directed acupuncture. AI-based data mining methods uncovered crucial acupoint combinations for treating various diseases, which provide a scientific basis for acupoints prescription in clinical practice. Furthermore, the rapid development of modern TCM instruments facilitates the integration of modern medical instruments, AI techniques, and acupuncture. This integration significantly improves the quantification, objectification, and standardization of acupuncture as well as the delivery of clinical personalized acupuncture therapy. Machine learning-based clinical efficacy prediction of acupuncture can help doctors screen patients who may benefit from acupuncture treatment. However, the existing challenges require additional work for developing AI-directed acupuncture. Some include a better understanding of ancient Chinese philosophy for AI researchers, TCM acupuncture theory-based explanation of the knowledge discoveries, construction of acupuncture databases, and clinical trials for novel knowledge validation. This review aims to summarize the major contribution of AI techniques to the discovery of novel acupuncture knowledge, the improvement for acupuncture safety and efficacy, the development and inheritance of acupuncture, and the major challenges for the further development of AI-directed acupuncture. The development of acupuncture can progress with the help of AI.