Duoculture diminishes social interaction costs and improves growth rates of two fish species at different temperatures.

Duoculture has been reported to increase growth rates of some fishes when reared in combination, due to "shading" effects between the species. Two experiments, one involving outdoor cage-rearing in a reservoir, and the other, indoor tank-rearing, were conducted within each of three temperatures ranges (means of ~18.0°C, ~22.0°C and ~26.5°C), to determine whether duoculture of bluegill (BG) Lepomis macrochirus and yellow perch (YP) Perca flavescens would lead to improved growth relative to when the two species were reared separately. Juvenile bluegill and yellow perch were reared in triplicated groups each involving monoculture sets of 100% BG and 100% YP, and a duoculture set of 50% BG + 50% YP. Experiments in cages (Exp. 1) ran for 150 days while those in tanks ran for 126 days (Exp. 2). In Experiment 1, bluegill exhibited significantly greater (P<0.05) mean weight (P<0.05) in duoculture than in monoculture, under the high summer-like range of temperature (~26.5°C) over most of the experiment, whereas yellow perch showed no significant difference in mean weight in duoculture versus monoculture. By the end of a 150-d experiment, bluegill in duoculture outweighed those in monoculture by 62.5%. In Experiment 2, yellow perch in duoculture grew significantly larger than in monoculture (P<0.05) under the warm thermal regime (mean of ~22°C), while no significant differences were detected in mean weight of bluegill in monoculture versus duoculture. Yellow perch in duoculture outweighed those in monoculture by 33.1% at the end of the experiment. Yellow perch performed better in duoculture than in monoculture under the low thermal regime (mean of ~18°C) in both experiments. A significantly greater reduction of CVwt was observed for both bluegill and yellow perch in duoculture than in monoculture in Experiment 1, while no differences in CVwt reduction were detected for bluegill in Experiment 2. Feed conversion ratios (FCR) of bluegill and yellow perch reared in duoculture were significantly lower than for both fishes reared in monoculture in Experiment 1, while there were no significant differences in FCR among the three groups throughout most of Experiment 2. Findings indicate that duoculture of yellow perch and bluegill holds good potential to improve growth and FCR, and to reduce size variation by diminishing social interaction costs.

Meta-analysis of dynamic contrast enhancement and diffusion-weighted MRI for differentiation of benign from malignant non-mass enhancement breast lesions.

Purpose: The objective of this study was to conduct a meta-analysis comparing the diagnostic efficacy of models based on diffusion-weighted imaging (DWI)-MRI, dynamic contrast enhancement (DCE)-MRI, and combination models (DCE and DWI) in distinguishing benign from malignant non-mass enhancement (NME) breast lesions. Materials and methods: PubMed, Embase, and Cochrane Library were searched, from inception to January 30, 2023, for studies that used DCE or DWI-MRI for the prediction of NME breast cancer patients. A bivariate random-effects model was used to calculate the meta-analytic sensitivity, specificity, and area under the curve (AUC) of the DCE, DWI, and combination models. Subgroup analysis and meta-regression analysis were performed to find the source of heterogeneity. Results: Of the 838 articles screened, 18 were eligible for analysis (13 on DCE, five on DWI, and four studies reporting the diagnostic accuracy of both DCE and DWI). The funnel plot showed no publication bias (p > 0.5). The pooled sensitivity and specificity and the AUC of the DCE, DWI, and combination models were 0.58, 0.72, and 0.70, respectively; 0.84, 0.69, and 0.84, respectively; and 0.88, 0.79, 0.90, respectively. The meta-analysis found no evidence of a threshold effect and significant heterogeneity among trials in terms of DCE sensitivity and specificity, as well as DWI specificity alone (I2 > 75%). The meta-regression revealed that different diagnostic criteria contributed to the DCE study's heterogeneity (p < 0.05). Different reference criteria significantly influenced the heterogeneity of the DWI model (p < 0.05). Subgroup analysis revealed that clustered ring enhancement (CRE) had the highest pooled specificity (0.92) among other DCE features. The apparent diffusion coefficient (ADC) with a mean threshold <1.3 × 10-3 mm2/s had a slightly higher sensitivity of 0.86 compared to 0.82 with an ADC of ≥1.3 × 10-3 mm2/s. Conclusion: The combination model (DCE and DWI) outperformed DCE or DWI alone in identifying benign and malignant NME lesions. The DCE-CRE feature was the most specific test for ruling in NME cancers.

Prediction of histopathologic grades of bladder cancer with radiomics based on MRI: Comparison with traditional MRI.

PURPOSE: To compare biparametric magnetic resonance imaging (bp-MRI) radiomics signatures and traditional MRI model for the preoperative prediction of bladder cancer (BCa) grade. MATERIALS AND METHODS: This retrospective study included 255 consecutive patients with pathologically confirmed 113 low-grade and 142 high-grade BCa. The traditional MRI nomogram model was developed using univariate and multivariate logistic regression by the mean apparent diffusion coefficient (ADC), vesical imaging reporting and data system, tumor size, and the number of tumors. Volumes of interest were manually drawn on T2-weighted imaging (T2WI) and ADC maps by 2 radiologists. Using one-way analysis of variance, correlation, and least absolute shrinkage and selection operator methods to select features. Then, a logistic regression classifier was used to develop the radiomics signatures. Receiver operating characteristic (ROC) analysis was used to compare the diagnostic abilities of the radiomics and traditional MRI models by the DeLong test. Finally, decision curve analysis was performed by estimating the clinical usefulness of the 2 models. RESULTS: The area under the ROC curves (AUCs) of the traditional MRI model were 0.841 in the training cohort and 0.806 in the validation cohort. The AUCs of the 3 groups of radiomics model [ADC, T2WI, bp-MRI (ADC and T2WI)] were 0.888, 0.875, and 0.899 in the training cohort and 0.863, 0.805, and 0.867 in the validation cohort, respectively. The combined radiomics model achieved higher AUCs than the traditional MRI model. decision curve analysis indicated that the radiomics model had higher net benefits than the traditional MRI model. CONCLUSION: The bp-MRI radiomics model may help distinguish high-grade and low-grade BCa and outperforming the traditional MRI model. Multicenter validation is needed to acquire high-level evidence for its clinical application.

Brain functional connectivity patterns associated with symptoms of vestibular migraine.

Background: Several functional magnetic resonance imaging (fMRI) investigations of patients with vestibular migraine (VM) have revealed abnormal functionality in different networks, indicating that VM is related to alterations in brain function. We sought to investigate the resting-state functional connectivity (FC) patterns during the interictal period in VM by combining data-driven voxel-wise degree centrality (DC) calculations and seed-based FC analyses, and thereby determine the associations between cerebral function and clinical symptoms. Methods: Thirty-eight patients with VM and 33 matched normal controls were recruited. DC was calculated and compared between the groups, and the FC of locations showing DC alterations was further tested using a seed-based technique. The participants' clinical indicators were correlated with the DC and FC values of the brain areas. Results: In contrast to the control group, the VM group showed considerably lower DC values in the bilateral medial prefrontal cortex (mPFC) and significantly higher DC values in the right occipital lobe. In the seed-based FC analyses, patients with VM demonstrated fewer connections of the bilateral mPFC with the bilateral posterior cingulate cortex, right parahippocampus, right cerebellar posterior lobe, bilateral cuneus, and left precuneus. In addition, clinical data from patients, such as pain intensity, episode frequency, and the Dizziness Handicap Inventory score, were negatively related to these FC and DC impairments. Conclusion: Our findings showed changes in the default mode network and visual cortex in patients with VM, providing further insights into the complexity of the mechanisms underlying VM.

Upper trapezius muscle elasticity in cervical myofascial pain syndrome measured using real-time ultrasound shear-wave elastography.

Background: Myofascial pain syndrome (MPS) is a common cause of neck pain, which is a global public health problem. Because MPS does not present morphological changes within lesioned muscles, there are no imaging diagnostic criteria for this condition. In this study, we evaluate elasticity changes in upper trapezius muscles most frequently involved in cervical MPS using real-time ultrasound shear-wave elastography, and we examine their potential diagnostic value. Methods: We consecutively enrolled 109 right posterior neck pain patients for this prospective study. Of these, 51 were diagnosed with MPS and 58 with non-MPS in the right side of their neck. Among MPS patients, 19 fell into the 1-3 range (mild pain) for pain scores on the visual analog scale (VAS), 25 fell into the 4-6 range (moderate pain), and 7 into the 7-10 range (severe pain). MPS was diagnosed by two independent clinicians using the diagnostic criteria proposed by Simons et al. Using real-time ultrasound shear-wave elastography, we measured right trapezius mean shear-wave velocity (SWVmean). The midpoint of the line between the foramen magnum and the end of the right acromion served as measuring point. Regions of interest were scaled to span 0-8.0 m/s. Results: Trapezius SWVmean was significantly higher in MPS patients compared with non-MPS patients (P<0.001). Stratified analysis of MPS patients according to pain severity revealed similar trapezius SWVmean between mild pain and non-MPS patients (P=0.324), however SWVmean was higher in moderate and severe pain MPS patients compared with non-MPS patients (P<0.001). The area under the curve (AUC) value for upper trapezius SWVmean in MPS patients was 0.791 (95% CI: 0.703-0.863). Corresponding sensitivity and specificity values were 86.27% (95% CI: 73.7-94.3%) and 62.07% (95% CI: 48.4-74.5%). Stratified analysis of MPS patients by pain severity produced the following AUC values for trapezius SWVmean in MPS patients with mild, moderate, and severe pain: 0.578 (95% CI: 0.460-0.690), 0.899 (95% CI: 0.814-0.955), and 0.983 (95% CI: 0.914-0.999), respectively. Conclusions: Elasticity changes and increased stiffness in the trapezius occur in cervical MPS patients with moderate and severe pain. The SWVmean parameter reflecting trapezius muscle elasticity may be valuable for successful screening of cervical MPS, especially in patients with moderate and severe pain.

An MRI-based radiomics nomogram in predicting histologic grade of non-muscle-invasive bladder cancer.

Background: Non-muscle-invasive bladder cancer (NMIBC) is categorized into high and low grades with different clinical treatments and prognoses. Thus, accurate preoperative evaluation of the histologic NMIBC grade through imaging techniques is essential. Objectives: To develop and validate an MRI-based radiomics nomogram for individualized prediction of NMIBC grading. Methods: The study included 169 consecutive patients with NMIBC (training cohort: n = 118, validation cohort: n = 51). A total of 3148 radiomic features were extracted, and one-way analysis of variance and least absolute shrinkage and selection operator were used to select features for building the radiomics score(Rad-score). Three models to predict NMIBC grading were developed using logistic regression analysis: a clinical model, a radiomics model and a radiomics-clinical combined nomogram model. The discrimination and calibration power and clinical applicability of the models were evaluated. The diagnostic performance of each model was compared by determining the area under the curve (AUC) in receiver operating characteristic (ROC) curve analysis. Results: A total of 24 features were used to build the Rad-score. A clinical model, a radiomics model, and a radiomics-clinical nomogram model that incorporated the Rad-score, age, and number of tumors were constructed. The radiomics model and nomogram showed AUCs of 0.910 and 0.931 in the validation set, which outperformed the clinical model (0.745). The decision curve analysis also showed that the radiomics model and combined nomogram model yielded higher net benefits than the clinical model. Conclusion: A radiomics-clinical combined nomogram model has the potential to be used as a non-invasive tool for the differentiating low-from high-grade NMIBCs.

Decreased ALFF and Functional Connectivity of the Thalamus in Vestibular Migraine Patients.

BACKGROUND: The thalamus has been reported to be associated with pain modulation and processing. However, the functional changes that occur in the thalamus of vestibular migraine (VM) patients remain unknown. METHODS: In total, 28 VM patients and 28 healthy controls who were matched for age and sex underwent resting-state functional magnetic resonance imaging. They also responded to standardized questionnaires aimed at assessing the clinical features associated with migraine and vertigo. Differences in the amplitude of low-frequency fluctuation (ALFF) were analyzed and brain regions with altered ALFF in the two groups were used for further analysis of whole-brain functional connectivity (FC). The relationship between clusters and clinical features was investigated by correlation analyses. RESULTS: The ALFF in the thalamus was significantly decreased in the VM group versus the control group. In the VM group, the ALFF in the left thalamus negatively correlated with VM episode frequency. Furthermore, the left thalamus showed significantly weaker FC than both regions of the medial prefrontal cortex, both regions of the anterior cingulum cortex, the left superior/middle temporal gyrus, and the left temporal pole in the VM group. CONCLUSIONS: The thalamus plays an important role in VM patients and it is suggested that connectivity abnormalities of the thalamocortical region contribute to abnormal pain information processing and modulation, transmission, and multisensory integration in patients with VM.

A meta-analysis of MRI-based radiomic features for predicting lymph node metastasis in patients with cervical cancer.

PURPOSE: To evaluate the ability of preoperative MRI-based radiomic features in predicting lymph node metastasis (LNM) in patients with cervical cancer. METHODS: PubMed, Embase, Web of Science, Cochrane Library databases, and four Chinese databases were searched to identify relevant studies published up until October 22, 2021. Two reviewers screened all papers independently for eligibility. We included diagnostic accuracy studies that used radiomics-MRI for LNM in patients with cervical cancer, using histopathology as the reference standard.Quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 and Radiomics Quality Score. Overall diagnostic odds ratio (DOR), sensitivity, specificity and area under the curve (AUC) were calculated to assess the prediction efficacy of MRI-based radiomic features in patients with cervical cancer. Spearman's correlation coefficient was calculated and subgroup analysis performed to investigate causes of heterogeneity. RESULTS: Twelve studies comprising 793 female patients were included. The pooled DOR, sensitivity, specificity, and AUC of radiomics in detecting LNM were 12.08 [confidence interval (CI) 8.18, 17.85], 80% (72%, 87%), 76% (72%, 80%), and 0.83 (0.76, 0.89), respectively. The meta-analysis showed significant heterogeneity among the included studies. No threshold effect was detected. Subgroup analysis showed that multiple sequences, and radiomics combined with clinical factors, radiomics approach [DOR:15.49 (6.06, 39.62), 18.93 (8.46, 42.38), and 10.63 (6.23, 18.12), respectively] could slightly improve diagnostic performance compared with apparent diffusion coefficient-based radiomic features, T2 + dynamic contrast-enhanced MRI-based radiomic features, T2 images-based radiomic features, single radiomics, and human reading [DOR: 4.9 (1.91, 12.74), 7.63 (3.78, 15.38), 8.31 (3.05, 22.61), 16.10 (9.10, 28.47), and 6.46 (3.08, 13.56), respectively]. CONCLUSION: Our meta-analysis showed that preoperative MRI-based radiomic features performs well in predicting LNM in patients with cervical cancer. This noninvasive and convenient tool may be used to facilitate preoperative identification of LNM.

The Diagnostic Performance of Machine Learning-Based Radiomics of DCE-MRI in Predicting Axillary Lymph Node Metastasis in Breast Cancer: A Meta-Analysis.

OBJECTIVE: The aim of this study was to perform a meta-analysis to evaluate the diagnostic performance of machine learning(ML)-based radiomics of dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) DCE-MRI in predicting axillary lymph node metastasis (ALNM) and sentinel lymph node metastasis(SLNM) in breast cancer. METHODS: English and Chinese databases were searched for original studies. The Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) and Radiomics Quality Score (RQS) were used to assess the methodological quality of the included studies. The pooled sensitivity, specificity, diagnostic odds ratio (DOR), and area under the curve (AUC) were used to summarize the diagnostic accuracy. Spearman's correlation coefficient and subgroup analysis were performed to investigate the cause of the heterogeneity. RESULTS: Thirteen studies (1618 participants) were included in this meta-analysis. The pooled sensitivity, specificity, DOR, and AUC with 95% confidence intervals were 0.82 (0.75, 0.87), 0.83 (0.74, 0.89), 21.56 (10.60, 43.85), and 0.89 (0.86, 0.91), respectively. The meta-analysis showed significant heterogeneity among the included studies. There was no threshold effect in the test. The result of subgroup analysis showed that ML, 3.0 T, area of interest comprising the ALN, being manually drawn, and including ALNs and combined sentinel lymph node (SLN)s and ALNs groups could slightly improve diagnostic performance compared to deep learning, 1.5 T, area of interest comprising the breast tumor, semiautomatic scanning, and the SLN, respectively. CONCLUSIONS: ML-based radiomics of DCE-MRI has the potential to predict ALNM and SLNM accurately. The heterogeneity of the ALNM and SLNM diagnoses included between the studies is a major limitation.

Cortical Areas Associated With Multisensory Integration Showing Altered Morphology and Functional Connectivity in Relation to Reduced Life Quality in Vestibular Migraine.

Background: Increasing evidence suggests that the temporal and parietal lobes are associated with multisensory integration and vestibular migraine. However, temporal and parietal lobe structural and functional connectivity (FC) changes related to vestibular migraine need to be further investigated. Methods: Twenty-five patients with vestibular migraine (VM) and 27 age- and sex- matched healthy controls participated in this study. Participants completed standardized questionnaires assessing migraine and vertigo-related clinical features. Cerebral cortex characteristics [i.e., thickness (CT), fractal dimension (FD), sulcus depth (SD), and the gyrification index (GI)] were evaluated using an automated Computational Anatomy Toolbox (CAT12). Regions with significant differences were used in a seed-based comparison of resting-state FC conducted with DPABI. The relationship between changes in cortical characteristics or FC and clinical features was also analyzed in the patients with VM. Results: Relative to controls, patients with VM showed significantly thinner CT in the bilateral inferior temporal gyrus, left middle temporal gyrus, and the right superior parietal lobule. A shallower SD was observed in the right superior and inferior parietal lobule. FD and GI did not differ significantly between the two groups. A negative correlation was found between CT in the right inferior temporal gyrus, as well as the left middle temporal gyrus, and the Dizziness Handicap Inventory (DHI) score in VM patients. Furthermore, patients with VM exhibited weaker FC between the left inferior/middle temporal gyrus and the left medial superior frontal gyrus, supplementary motor area. Conclusion: Our data revealed cortical structural and resting-state FC abnormalities associated with multisensory integration, contributing to a lower quality of life. These observations suggest a role for multisensory integration in patients with VM pathophysiology. Future research should focus on using a task-based fMRI to measure multisensory integration.

Altered Gray Matter Volume and Functional Connectivity in Patients With Vestibular Migraine.

SUBJECTS: Vestibular migraine (VM) is the most common neurological cause of vertigo in adults. Previous neuroimaging studies have reported structural alterations in areas associated with pain and vestibular processing. However, it is unclear whether altered resting-state functional connectivity (FC) exists in brain regions with structural abnormalities in patients with VM. METHODS: Resting-state functional magnetic resonance imaging (MRI) and three-dimensional T1-weighed MRI were performed in 30 patients with VM and 30 healthy controls (HCs). Patients underwent an evaluation of migraine and dizziness severity. FC and voxel-based morphometry (VBM) were performed using DPABI 4.3 and CAT12, respectively. The association between changes in gray matter (GM) volume or FC and clinical parameters was also analyzed. RESULTS: Compared with HCs, patients with VM demonstrated a reduced GM volume in the bilateral parietoinsular vestibular cortex (PIVC), right middle frontal gyrus, and precuneus. The GM volume of the left PIVC was negatively associated with Dizziness Handicap Inventory score in patients with VM. Taking this region as a seed region, we further observed increased FC between the left primary somatosensory cortex (S1)/inferior parietal lobule (IPL) and the left PIVC in patients with VM. CONCLUSION: FC between regions with a decline in GM volume (the PIVC and S1/IPL) is altered in patients with VM, suggesting that abnormalities in vestibular cortical network could be useful for understanding the underlying mechanisms of VM.

Right Frontoinsular Cortex: A Potential Imaging Biomarker to Evaluate T2DM-Induced Cognitive Impairment.

Cognitive impairment in type 2 diabetes mellitus (T2DM) is associated with functional and structural abnormalities in the intrinsic brain network. The salience network (SN) is a neurocognitive network that maintains normal cognitive function, but it has received little attention in T2DM. We explored SN changes in patients with T2DM with normal cognitive function (DMCN) and in patients with T2DM with mild cognitive impairment (DMCI). Sixty-five T2DM patients and 31 healthy controls (HCs) underwent a neuropsychological assessment, independent component analysis (ICA), and voxel-based morphometry (VBM) analysis. The ICA extracted the SN for VBM to compare SN functional connectivity (FC) and gray matter (GM) volume (GMV) between groups. A correlation analysis examined the relationship between abnormal FC and GMV and clinical/cognitive variables. Compared with HCs, DMCN patients demonstrated increased FC in the left frontoinsular cortex (FIC), right anterior insula, and putamen, while DMCI patients demonstrated decreased right middle/inferior frontal gyrus FC. Compared with DMCN patients, DMCI patients showed decreased right FIC FC. There was no significant difference in SN GMV in DMCN and DMCI patients compared with HCs. FIC GMV was decreased in the DMCI patients compared with DMCN patients. In addition, right FIC FC and SN GMV positively correlated with Montreal Cognitive Assessment and Mini-Mental State Examination (MMSE) scores. These findings indicate that changes in SN FC, and GMV are complex non-linear processes accompanied by increased cognitive dysfunction in patients with T2DM. The right FIC may be a useful imaging biomarker for supplementary assessment of early cognitive dysfunction in patients with T2DM.

Predicting the Grade of Prostate Cancer Based on a Biparametric MRI Radiomics Signature.

Purpose: This study aimed to investigate the value of biparametric magnetic resonance imaging (bp-MRI)-based radiomics signatures for the preoperative prediction of prostate cancer (PCa) grade compared with visual assessments by radiologists based on the Prostate Imaging Reporting and Data System Version 2.1 (PI-RADS V2.1) scores of multiparametric MRI (mp-MRI). Methods: This retrospective study included 142 consecutive patients with histologically confirmed PCa who were undergoing mp-MRI before surgery. MRI images were scored and evaluated by two independent radiologists using PI-RADS V2.1. The radiomics workflow was divided into five steps: (a) image selection and segmentation, (b) feature extraction, (c) feature selection, (d) model establishment, and (e) model evaluation. Three machine learning algorithms (random forest tree (RF), logistic regression, and support vector machine (SVM)) were constructed to differentiate high-grade from low-grade PCa. Receiver operating characteristic (ROC) analysis was used to compare the machine learning-based analysis of bp-MRI radiomics models with PI-RADS V2.1. Results: In all, 8 stable radiomics features out of 804 extracted features based on T2-weighted imaging (T2WI) and ADC sequences were selected. Radiomics signatures successfully categorized high-grade and low-grade PCa cases (P < 0.05) in both the training and test datasets. The radiomics model-based RF method (area under the curve, AUC: 0.982; 0.918), logistic regression (AUC: 0.886; 0.886), and SVM (AUC: 0.943; 0.913) in both the training and test cohorts had better diagnostic performance than PI-RADS V2.1 (AUC: 0.767; 0.813) when predicting PCa grade. Conclusions: The results of this clinical study indicate that machine learning-based analysis of bp-MRI radiomic models may be helpful for distinguishing high-grade and low-grade PCa that outperformed the PI-RADS V2.1 scores based on mp-MRI. The machine learning algorithm RF model was slightly better.

Altered Cerebellar-Cerebral Circuits in Patients With Type 2 Diabetes Mellitus.

The role of the cerebellum in type 2 diabetes mellitus (T2DM) has been receiving increased attention. However, the functional connectivity (FC) between the cerebellar subregions and the cerebral cortex has not been investigated in T2DM. Therefore, the purpose of this study was to investigate cerebellar-cerebral FC and the relationship between FC and clinical/cognitive variables in patients with T2DM. A total of 34 patients with T2DM and 30 healthy controls were recruited for this study to receive a neuropsychological assessment and undergo resting-state FC. We selected four subregions of the cerebellum (bilateral lobules IX, right and left Crus I/II, and left lobule VI) as regions of interest (ROIs) to examine the differences in cerebellar-cerebral circuits in patients with T2DM compared to healthy controls. Correlation analysis was performed to examine the relationship between FC and clinical/cognitive variables in the patients. Compared to healthy controls, patients with T2DM showed significantly decreased cerebellar-cerebral FC in the default-mode network (DMN), executive control network (ECN), and visuospatial network (VSN). In the T2DM group, the FC between the left cerebellar lobule VI and the right precuneus was negatively correlated with the Trail Making Test A (TMT-A) score (r = -0.430, P = 0.013), after a Bonferroni correction. In conclusion, patients with T2DM have altered FC between the cerebellar subregions and the cerebral networks involved in cognitive and emotional processing. This suggests that a range of cerebellar-cerebral circuits may be involved in the neuropathology of T2DM cognitive dysfunction.

Altered functional connectivity of brain regions based on a meta-analysis in patients with T2DM: A resting-state fMRI study.

OBJECTIVE: To explore the neural mechanisms of brain impairment in type 2 diabetes mellitus (T2DM), abnormal changes to the functional connections between brain regions in the resting state were investigated based on a meta-analysis. METHODS: Resting-state functional magnetic resonance imaging (fMRI) and neuropsychological assessment were performed on 38 patients with T2DM and 33 healthy controls (HCs). Functional connectivity between regions based on a meta-analysis and other voxels in the brain was calculated and compared between the two groups using a two-sample t test. A correlation analysis was conducted between clinical/cognitive variables and functional connection values from the regions with significant differences in the above comparison. RESULTS: Patients in the T2DM group showed a significantly decreased functional connection between the right posterior cerebellum and the right middle/inferior occipital gyrus, left middle temporal gyrus, left superior frontal gyrus, left middle frontal gyrus, left insula, left precuneus, and right paracentral lobule/left precuneus when compared with HC group. The functional connection values between the right insula and left medial frontal gyrus, left supplementary motor area, and between the left lingual gyrus and right middle/inferior occipital gyrus in patients with T2DM were significantly decreased. Moreover, the functional connection values between the right posterior cerebellum and left middle frontal gyrus, and between the right posterior cerebellum and left precuneus were negatively correlated with HbA1c in the T2DM group (r = -.356, p = .03; r = -.334, p = .043). CONCLUSIONS: Our study showed a wide range of cerebellar-cerebral circuit abnormalities in patients with T2DM, which provides a new direction to investigate the neuropathological mechanisms of T2DM from the perspective of the cerebellum.

Altered structure of the vestibular cortex in patients with vestibular migraine.

INTRODUCTION: Previous voxel-based morphometry (VBM) studies have revealed changes in brain structure in patients with vestibular migraine (VM); these findings have improved the present understanding of pathophysiology. Few other studies have assessed the association between structural changes and the severity of dizziness in VM. This study aimed to examine the structural changes and cortical morphometric features associated with migraine and vertigo attacks in patients with VM. METHODS: Twenty patients with VM and 20 healthy normal volunteers were scanned on a 3-tesla MRI scanner. The gray matter volume (GMV) was estimated using the automated Computational Anatomy Toolbox (CAT12). The relationship between clinical parameters and morphometric abnormalities was also analyzed in VM. RESULTS: Compared with controls, VM patients have decreased GMV in the prefrontal cortex (PFC), posterior insula-operculum regions, inferior parietal gyrus, and supramarginal gyrus. Moreover, patient scores on the Dizziness Handicap Inventory (DHI) score showed a negative correlation with GMV in the posterior insula-operculum regions. CONCLUSION: These findings demonstrated abnormality in the central vestibular cortex and correlations between dizziness severity and GMV in core regions of the vestibular cortex of VM patients, suggesting a pathophysiological role of these core vestibular regions in VM patients.

Decreased Regional Cerebral Perfusion at Resting State in Acute Posttraumatic Stress Disorder Resulting From a Single, Prolonged Stress Event.

RATIONALE AND OBJECTIVES: This study evaluated the altered regional cerebral blood flow (rCBF) in resting state in patients with acute posttraumatic stress disorder (PTSD) 3 months after trauma. MATERIALS AND METHODS: The rCBF was measured in 30 patients with acute PTSD and 36 healthy controls. RESULTS: Survivors with acute PTSD showed decreased rCBF, the Clinician-Administered PTSD Scale score correlated negatively with the rCBF, and rCBF at resting state decreased in acute PTSD. CONCLUSIONS: PTSD symptom severity was associated with diminished cerebral blood flow in the right insular cortex and right orbital medial frontal gyrus. The rCBF may predict PTSD symptom severity.

Classification of Pelteobagrus fish in Poyang Lake based on mitochondrial COI gene sequence.

We use DNA molecular marker technology to correct the deficiency of traditional morphological taxonomy. Totality 770 Pelteobagrus fish from Poyang Lake were collected. After preliminary morphological classification, random selected eight samples in each species for DNA extraction. Mitochondrial COI gene sequence was cloned with universal primers and sequenced. The results showed that there are four species of Pelteobagrus living in Poyang Lake. The average of intraspecific genetic distance value was 0.003, while the average interspecific genetic distance was 0.128. The interspecific genetic distance is far more than intraspecific genetic distance. Besides, phylogenetic tree analysis revealed that molecular systematics was in accord with morphological classification. It indicated that COI gene is an effective DNA molecular marker in Pelteobagrus classification. Surprisingly, the intraspecific difference of some individuals (P. e6, P. n6, P. e5, and P. v4) from their original named exceeded species threshold (2%), which should be renewedly classified into Pelteobagrus fulvidraco. However, another individual P. v3 was very different, because its genetic distance was over 8.4% difference from original named Pelteobagrus vachelli. Its taxonomic status remained to be further studied.