PurposeStomach 36 (ST36, zusanli) is one of the important acupoints in acupuncture. Despite clinical functional magnetic resonance imaging (fMRI) studies of ST36 acupuncture, the brain activities and the neural mechanism following acupuncture at ST36 remain unclear.MethodsLiterature searches were conducted on online databases, including MEDLINE, Embase, Cochrane Library, Web of Science, China National Knowledge Infrastructure, Wanfang database, WeiPu database, and China Biology Medicine, for task-based fMRI studies of acupuncture at ST36 in healthy subjects. Brain regions activated by ST36 acupuncture were systematically evaluated and subjected to seed-based d mapping meta-analysis. Subgroup analysis was conducted on control procedures, manual acupuncture, electrical acupuncture (EA), and acupuncture-specific activations. Meta-regression analysis was performed to explore the effects of needle retention time on brain activities following ST36 acupuncture stimulation. The activated brain regions were further decoded and mapped on large-scale functional networks to further decipher the clinical relevance of acupuncturing at ST36.ResultsA total of sixteen studies, involving a total of 401 right-handed healthy participants, that satisfied the inclusion criteria were included in the present meta-analysis. Meta-analysis showed that acupuncturing on ST36 positively activates the opercular part of the right inferior frontal gyrus (IFG.R), left superior temporal gyrus (STG.L), and right median cingulate/paracingulate gyri (MCG.R) regions. Needle retention time in an acupuncture session positively correlates with the activation of the left olfactory cortex, as shown in meta-regression analysis. Subgroup analysis revealed that EA stimulation may be a source of heterogeneity in the pooled results. Functional network mappings showed that the activated areas were mapped to the auditory network and salience network. Further functional decoding analysis showed that acupuncture on ST36 was associated with pain, secondary somatosensory, sound and language processing, and mood regulation.ConclusionAcupuncture at ST36 in healthy individuals positively activates the opercular part of IFG.R, STG.L, and MCG.R. The left olfactory cortex may exhibit positive needle retention time-dependent activities. Our findings may have clinical implications for acupuncture in analgesia, language processing, and mood disorders.Systematic Review Registrationhttps://inplasy.com/inplasy-2021-12-0035.

Purpose The white matter (WM) of the brain of type 2 diabetes mellitus (T2DM) patients is susceptible to neurodegenerative processes, but the specific types and positions of microstructural lesions along the fiber tracts remain unclear. Methods In this study 61 T2DM patients and 61 healthy controls were recruited and underwent diffusion spectrum imaging (DSI). The results were reconstructed with diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI). WM microstructural abnormalities were identified using tract-based spatial statistics (TBSS). Pointwise WM tract differences were detected through automatic fiber quantification (AFQ). The relationships between WM tract abnormalities and clinical characteristics were explored with partial correlation analysis. Results TBSS revealed widespread WM lesions in T2DM patients with decreased fractional anisotropy and axial diffusivity and an increased orientation dispersion index (ODI). The AFQ results showed microstructural abnormalities in T2DM patients in specific portions of the right superior longitudinal fasciculus (SLF), right arcuate fasciculus (ARC), left anterior thalamic radiation (ATR), and forceps major (FMA). In the right ARC of T2DM patients, an aberrant ODI was positively correlated with fasting insulin and insulin resistance, and an abnormal intracellular volume fraction was negatively correlated with fasting blood glucose. Additionally, negative associations were found between blood pressure and microstructural abnormalities in the right ARC, left ATR, and FMA in T2DM patients. Conclusion Using AFQ, together with DTI and NODDI, various kinds of microstructural alterations in the right SLF, right ARC, left ATR, and FMA can be accurately identified and may be associated with insulin and glucose status and blood pressure in T2DM patients.

PurposeThis study aimed to investigate the changes in brain structure and function in middle-aged patients with type 2 diabetes mellitus (T2DM) using morphometry and blood oxygen level-dependent functional magnetic resonance imaging (BOLD-fMRI).MethodsA total of 44 middle-aged patients with T2DM and 45 matched healthy controls (HCs) were recruited. Surface-based morphometry (SBM) was used to evaluate the changes in brain morphology. Degree centrality (DC) and functional connectivity (FC) were used to evaluate the changes in brain function.ResultsCompared with HCs, middle-aged patients with T2DM exhibited cortical thickness reductions in the left pars opercularis, left transverse temporal, and right superior temporal gyri. Decreased DC values were observed in the cuneus and precuneus in T2DM. Hub-based FC analysis of these regions revealed lower connectivity in the bilateral hippocampus and parahippocampal gyrus, left precuneus, as well as left frontal sup.ConclusionCortical thickness, degree centrality, as well as functional connectivity were found to have significant changes in middle-aged patients with T2DM. Our observations provide potential evidence from neuroimaging for analysis to examine diabetes-related brain damage.

Background and purpose Neurodegenerative processes are widespread in the brains of type 2 diabetes mellitus (T2DM) patients; gaps remain to exist in the current knowledge of the associated gray matter (GM) microstructural alterations. Methods A cross‐sectional study was conducted to investigate alterations in GM microarchitecture in T2DM patients by diffusion tensor imaging and neurite orientation dispersion and density imaging (NODDI). Seventy‐eight T2DM patients and seventy‐four age‐, sex‐, and education level‐matched healthy controls (HCs) without cognitive impairment were recruited. Cortical macrostructure and GM microstructure were assessed by surface‐based analysis and GM‐based spatial statistics (GBSS), respectively. Machine learning models were trained to evaluate the diagnostic values of cortical intracellular volume fraction (ICVF) for the classification of T2DM versus HCs. Results There were no differences in cortical thickness or area between the groups. GBSS analysis revealed similar GM microstructural patterns of significantly decreased fractional anisotropy, increased mean diffusivity and radial diffusivity in T2DM patients involving the frontal and parietal lobes, and significantly lower ICVF values were observed in nearly all brain regions of T2DM patients. A support vector machine model with a linear kernel was trained to realize the T2DM versus HC classification and exhibited the highest performance among the trained models, achieving an accuracy of 74% and an area under the curve of 83%. Conclusions NODDI may help to probe the widespread GM neuritic density loss in T2DM patients occurs before measurable macrostructural alterations. The cortical ICVF values may provide valuable diagnostic information regarding the early GM microstructural alterations in T2DM.