IntroductionDiabetes affects both the peripheral and central nervous systems. The aim of this study was to explore the changes in brain activity in response to thermal stimuli in diabetic patients with and without diabetic peripheral neuropathy (DPN) using functional magnetic resonance imaging (fMRI).MethodsA total of 36 right-handed volunteers were enrolled: eight patients with Type-2 diabetes mellitus and DPN, 13 patients with Type-2 diabetes mellitus lacking DPN (NDPN patients), and 15 healthy volunteers (HV). Blood oxygenation level-dependent baseline scans were performed, first without any stimuli, and then with four sessions of thermal stimuli (0, 10, 34, and 44°C, in a random order) applied to the lateral side of the right lower extremity. There was a 240-s rest interval between each thermal stimulation. Each stimulation session consisted of three cycles of 30 s of stimulation followed by 30 s of rest. After each stimuli session, the participant rated pain and itch perception on a visual analog scale. The fMRI data series were analyzed by using Statistical Parametric Mapping 8 and Data Processing Assistant for Resting-State fMRI.ResultsIn response to temperature stimuli, DPN patients showed stronger activation than HV and NDPN patients, not only in brain areas that participate in somatosensory pathways (right insula, left caudate nucleus, frontal gyrus, and cingulate cortex), but also in the cognition-related cerebral areas (right temporal lobe, left hippocampus, and left fusiform gyrus). Activation of vermis 1–3 was greater in NDPN patients than in HV in response to 0°C stimulation.ConclusionsfMRI may be useful for the early detection of central nervous system impairment caused by DPN. Our results indicate that central nervous system impairment related to diabetic neuropathy may not be limited to motion- and sensation-related cortical regions. Cognition-associated cerebral regions such as the hippocampus and fusiform gyrus are also affected by functional changes caused by DPN. This suggests that fMRI can detect the early stages of cognitive impairment in DPN patients before the symptoms become clinically significant.
Colorectal cancer (CRC) is a common digestive tract tumor worldwide. In recent years, neoadjuvant chemoradiotherapy (CRT) has been the most comprehensive treatment for locally advanced rectal cancer (LARC). In this study, we explored immune infiltration in rectal cancer (RC) and identified immune-related differentially expressed genes (IRDEGs). Then, we identified response markers in datasets in GEO databases by principal component analysis (PCA). We also utilized three GEO datasets to identify the up- and downregulated response-related genes simultaneously and then identified genes shared between the PCA markers and three GEO datasets. Based on the hub IRDEGs, we identified target mRNAs and constructed a ceRNA network. Based on the ceRNA network, we explored prognostic biomarkers to develop a prognostic model for RC through Cox regression. We utilized the specimen to validate the expression of the two biomarkers. We also utilized LASSO regression to screen hub IRDEGs and built a nomogram to predict the response of LARC patients to CRT. All of the results show that the nomogram and prognostic model offer good prognostic value and that the ceRNA network can effectively highlight the regulatory relationship. hsa-mir-107 and WDFY3-AS2 may be prognostic biomarkers for RC.
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