The association between gray matter volume in the hippocampal subfield and antidepressant efficacy mediated by abnormal dynamic functional connectivity.

An abnormality of structures and functions in the hippocampus may have a key role in the pathophysiology of major depressive disorder (MDD). However, it is unclear whether structure factors of the hippocampus effectively impact antidepressant responses by hippocampal functional activity in MDD patients. We collected longitudinal data from 36 MDD patients before and after a 3-month course of antidepressant pharmacotherapy. Additionally, we obtained baseline data from 43 healthy controls matched for sex and age. Using resting-state functional magnetic resonance imaging (rs-fMRI), we estimated the dynamic functional connectivity (dFC) of the hippocampal subregions using a sliding-window method. The gray matter volume was calculated using voxel-based morphometry (VBM). The results indicated that patients with MDD exhibited significantly lower dFC of the left rostral hippocampus (rHipp.L) with the right precentral gyrus, left superior temporal gyrus and left postcentral gyrus compared to healthy controls at baseline. In MDD patients, the dFC of the rHipp.L with right precentral gyrus at baseline was correlated with both the rHipp.L volume and HAMD remission rate, and also mediated the effects of the rHipp.L volume on antidepressant performance. Our findings suggested that the interaction between hippocampal structure and functional activity might affect antidepressant performance, which provided a novel insight into the hippocampus-related neurobiological mechanism of MDD.

Linking inter-subject variability of cerebellar functional connectome to clinical symptoms in major depressive disorder.

Major depressive disorder (MDD) is a highly prevalent psychiatric disorder with remarkable inter-subject variability in clinical manifestations. Neuroimaging changes of the cerebellum have been recently proposed as a way to characterize MDD-related brain disruptions and might further explain various clinical symptoms. However, the cerebellar contributions to MDD clinical heterogeneity remain largely unknown. The analyzed data consisted of 251 MDD patients and 235 matching healthy controls (HC). The inter-subject variability of functional connectomes (IVFC) was estimated via Pearson's correlation analysis between each pair of the cerebellar and cerebral regions based on resting-state functional magnetic resonance imaging (rs-fMRI). A partial least squares (PLS) regression analysis was performed to determine the potential dimension linking the IVFC to clinical symptom measures. The results indicated that similar spatial distribution patterns of the cerebellar IVFC were observed between MDD and HC, but the MDD group exhibited abnormal IVFC alterations in the bilateral Cerebelum_4_5, bilateral Cerebelum_6, Vermis_1_2 and Vermis_8. The PLS model revealed that the IVFC pattern in the left Cerebelum_6 was significantly associated with three HAMD-17 items including the work and activities, psychomotor retardation, and depressed mood. These findings provided new evidence for the cerebellar changes in MDD. Specifically, we found that the altered inter-subject variability measurements correlated with clinical manifestations of this illness. Elucidating this variability could prove helpful for the evaluation of MDD heterogeneity as well as for understanding its pathophysiological mechanism.

Compressed primary-to-transmodal gradient is accompanied with subcortical alterations and linked to neurotransmitters and cellular signatures in major depressive disorder.

Major depressive disorder (MDD) has been shown to involve widespread changes in low-level sensorimotor and higher-level cognitive functions. Recent research found that a primary-to-transmodal gradient could capture a cortical hierarchical organization ranging from perception and action to cognition in healthy subjects, but a prominent gradient dysfunction in MDD patients. However, whether and how this cortical gradient is linked to subcortical impairments and whether it is reflected in the microscale neurotransmitter systems and cell type-specific transcriptional signatures remain largely unknown. Data were acquired from 323 MDD patients and 328 sex- and age-matched healthy controls derived from the REST-meta-MDD project, and the human brain neurotransmitter systems density maps and gene expression data were drawn from two publicly available datasets. We investigated alterations of the primary-to-transmodal gradient in MDD patients and their correlations with clinical symptoms of depression and anxiety, as well as  their paralleled subcortical impairments. The correlations between MDD-related gradient alterations and densities of the neurotransmitter systems and gene expression information were assessed, respectively. The results demonstrated that MDD patients had a compressed primary-to-transmodal gradient accompanied by paralleled alterations in subcortical regions including the caudate, amygdala, and thalamus. The case-control gradient differences were spatially correlated with the densities of the neurotransmitter systems including the serotonin and dopamine receptors, and meanwhile with gene expression enriched in astrocytes, excitatory and inhibitory neuronal cells. These findings mapped the paralleled subcortical impairments in cortical hierarchical organization and also helped us understand the possible molecular and cellular substrates of the co-occurrence of high-level cognitive impairments with low-level sensorimotor abnormalities in MDD.

A comparative study of ultrasound-guided percutaneous nephrolithotripsy and x-ray-guided percutaneous nephrolithotripsy in the treatment of complex renal calculi without hydronephrosis.

Objective: To compare and analyze the clinical effects of ultrasound-guided percutaneous nephrolithotripsy and X-ray-guided percutaneous nephrolithotripsy in the treatment of complex renal calculi without hydronephrosis. Methods: Eighty patients with multiple stones without hydronephrosis were admitted at Department of Ultrasound Diagnosis, The first medical center of Chinese PLA General Hospital from January 21, 2020 to December 21, 2020 randomly divided: into two groups: experimental group and control group, with 40 cases in each group. Patients in the experimental group were treated with ultrasound-guided percutaneous nephrolithotomy, while those in the control group were treated with X-ray-guided percutaneous nephrolithotomy. The differences in operation time, channel establishment time, channel number, blood loss and stone clearance rate between the two groups were compared and analyzed. Venous blood was drawn before surgery and on the first day after surgery, and serum creatinine, urea nitrogen, blood ß2-microglobulin, blood uric acid and other renal indexes were detected. Moreover, renal parenchymal injury was compared between the two groups by renal static imaging, and the incidence of postoperative complications such as pain, fever, urination through incision and injury of surrounding organs were compared and analyzed. Results: The operation time, channel establishment time, channel number and blood loss in the experimental group were significantly lower than those in the control group, with statistically significant differences (p<0.05). The postoperative renal injury score of the experimental group was 1.03±0.37, which was lower than 1.85±0.63 of the control group (p=0.00); Postoperative Cr, BUN, blood ß 2-microglobulin and other indicators in the control group were significantly higher than those in the experimental group, with statistically significant differences (p<0.05). The incidence of peripheral organ injury in experimental group was lower than that in control group, with a statistically significant difference (p=0.04). Conclusion: Ultrasound-guided percutaneous nephrolithotomy is a safe and effective treatment regimen, boasting various advantages such as real-time monitoring of the surgical process, more accurate and clear channel establishment, avoidance of large vessel injury, shortening of surgical time, alleviation of kidney injury and reduction of surgical complications, which is more advantageous for the treatment of complex renal calculi.

Decreased modular segregation of the frontal-parietal network in major depressive disorder.

Major depressive disorder (MDD) is a common psychiatric condition associated with aberrant large-scale distributed brain networks. However, it is unclear how the network dysfunction in MDD patients is characterized by imbalance or derangement of network modular segregation. Fifty-one MDD patients and forty-three matched healthy controls (HC) were recruited in the present study. We analyzed intrinsic brain activity derived from resting-state functional magnetic resonance imaging (R-fMRI) and then examined brain network segregation by computing the participation coefficient (PC). Further intra- and inter-modular connections analysis were preformed to explain atypical PC. Besides, we explored the potential relationship between the above graph theory measures and symptom severity in MDD. Lower modular segregation of the frontal-parietal network (FPN) was found in MDD compared with the HC group. The MDD group exhibited increased inter-module connections between the FPN and cingulo-opercular network (CON), between the FPN and cerebellum (Cere), between the CON and Cere. At the nodal level, the PC of the anterior prefrontal cortex, anterior cingulate cortex, inferior parietal lobule (IPL), and intraparietal sulcus showed larger in MDD. Additionally, the inter-module connections between the FPN and CON and the PC values of the IPL were negatively correlated with depression symptom in the MDD group. These findings might give evidence about abnormal FPN in MDD from the perspective of modular segregation in brain networks.

Charting the dorsal-medial functional gradient of the default mode network in major depressive disorder.

Major depressive disorder (MDD) is a common and disabling psychiatric condition associated with aberrant functional activity of the default mode network (DMN). However, it is unclear how the DMN dysfunction in MDD patients is characterized by functional connectivity diversity or gradient and whether antidepressant therapy causes the abnormal functional gradient of the DMN to change toward normalization. In current work, we estimated the functional gradient of the DMN derived from resting state functional magnetic resonance imaging in MDD patients (n = 70) and matching healthy controls (n = 43) and identified MDD-related functional connectivity diversity of the DMN. The longitudinal changes of the DMN functional gradient in 36 MDD patients were assessed before and after 12-week antidepressant treatment. Compared to the healthy controls, the functional gradient of the DMN exhibited relatively relative compression along the dorsal-medial axis in MDD patients at baseline and antidepressant treatment could normalize these DMN gradient abnormalities. A regularized least-squares regression model based on DMN gradient features at baseline significantly predicted the change of Hamilton Depression Rating (HAMD) Scale scores after antidepressant treatment. The medial prefrontal cortex gradient had a more contribution to prediction of antidepressant efficacy. Our findings provided a novel insight into the neurobiological mechanism underlying MDD from the perspective of the DMN functional gradient.

Abnormal Dynamic Functional Connectivity of the Left Rostral Hippocampus in Predicting Antidepressant Efficacy in Major Depressive Disorder.

OBJECTIVE: Some pharmacological treatments are ineffective in parts of patients with major depressive disorder (MDD), hence this needs prediction of effective treatment responses. The study aims to examine the relationship between dynamic functional connectivity (dFC) of the hippocampal subregion and antidepressant improvement of MDD patients and to estimate the capability of dFC to predict antidepressant efficacy. METHODS: The data were from 70 MDD patients and 43 healthy controls (HC); the dFC of hippocampal subregions was estimated by sliding-window approach based on resting-state functional magnetic resonance imaging (R-fMRI). After 3 months treatment, 36 patients underwent second R-fMRI scan and were then divided into the response group and non-response group according to clinical responses. RESULTS: The result manifested that MDD patients exhibited lower mean dFC of the left rostral hippocampus (rHipp.l) compared with HC. After 3 months therapy, the response group showed lower dFC of rHipp.l compared with the non-response group. The dFC of rHipp.l was also negatively correlated with the reduction rate of Hamilton Depression Rating Scale. CONCLUSION: These findings highlighted the importance of rHipp in MDD from the dFC perspective. Detection and estimation of these changes might demonstrate helpful for comprehending the pathophysiological mechanism and for assessment of treatment reaction of MDD.

Identifying Boys With Autism Spectrum Disorder Based on Whole-Brain Resting-State Interregional Functional Connections Using a Boruta-Based Support Vector Machine Approach.

An increasing number of resting-state functional magnetic resonance neuroimaging (R-fMRI) studies have used functional connections as discriminative features for machine learning to identify patients with brain diseases. However, it remains unclear which functional connections could serve as highly discriminative features to realize the classification of autism spectrum disorder (ASD). The aim of this study was to find ASD-related functional connectivity patterns and examine whether these patterns had the potential to provide neuroimaging-based information to clinically assist with the diagnosis of ASD by means of machine learning. We investigated the whole-brain interregional functional connections derived from R-fMRI. Data were acquired from 48 boys with ASD and 50 typically developing age-matched controls at NYU Langone Medical Center from the publicly available Autism Brain Imaging Data Exchange I (ABIDE I) dataset; the ASD-related functional connections identified by the Boruta algorithm were used as the features of support vector machine (SVM) to distinguish patients with ASD from typically developing controls (TDC); a permutation test was performed to assess the classification performance. Approximately, 92.9% of participants were correctly classified by a combined SVM and leave-one-out cross-validation (LOOCV) approach, wherein 95.8% of patients with ASD were correctly identified. The default mode network (DMN) exhibited a relatively high network degree and discriminative power. Eight important brain regions showed a high discriminative power, including the posterior cingulate cortex (PCC) and the ventrolateral prefrontal cortex (vlPFC). Significant correlations were found between the classification scores of several functional connections and ASD symptoms (p < 0.05). This study highlights the important role of DMN in ASD identification. Interregional functional connections might provide useful information for the clinical diagnosis of ASD.

Altered dynamic functional connectivity of insular subregions could predict symptom severity of male patients with autism spectrum disorder.

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder characterized by difficulties with social communication and restricted or repetitive patterns of behavior. This disorder was characterized by widespread abnormalities involving distributed brain networks. As one such key network node, the insular cortex has been regarded as a research focus of ASD neuropathology. The insula is a functionally complex brain structure. However, it is not fully clear if dynamic characteristics of resting-state functional magnetic resonance imaging (R-fMRI) signals in insular heterogeneous could be used to depict abnormalities in ASD. To address this question, we investigated dynamic functional connectivity (dFC) of 12 insular subregions. Data were obtained from 44 individuals with ASD and 65 typically developing age-matched controls (TDC). We assessed dFC by sliding-window method and quantified its temporal variability. Multivariable linear regression models were constructed to determine whether dFC support complementary information about symptom severity of individuals with ASD rather than static functional connectivity (sFC). The results showed that individuals with ASD exhibited dFC and sFC alterations in distinct insular subregions. Some brain regions showed only abnormal dFC but not sFC with insular subregions. These abnormal dFC could significantly predict the symptom severity of individuals with ASD. Our findings might advance our knowledge about the potential of insular heterogeneity and dynamic characteristics in understanding the neuropathology mechanism of ASD and in developing neuroimaging biomarkers for clinical applications.

Effective Connectivity of Right Amygdala Subregions Predicts Symptom Improvement Following 12-Week Pharmacological Therapy in Major Depressive Disorder.

The low rates of treatment response still exist in the pharmacological therapy of major depressive disorder (MDD). Exploring an optimal neurological predictor of symptom improvement caused by pharmacotherapy is urgently needed for improving response to treatment. The amygdala is closely related to the pathological mechanism of MDD and is expected to be a predictor of the treatment. However, previous studies ignored the heterogeneousness and lateralization of amygdala. Therefore, this study mainly aimed to explore whether the right amygdala subregion function at baseline can predict symptom improvement after 12-week pharmacotherapy in MDD patients. We performed granger causality analysis (GCA) to identify abnormal effective connectivity (EC) of right amygdala subregions in MDD and compared the EC strength before and after 12-week pharmacological therapy. The results show that the abnormal EC mainly concentrated on the frontolimbic circuitry and default mode network (DMN). With relief of the clinical symptom, these abnormal ECs also change toward normalization. In addition, the EC strength of right amygdala subregions at baseline showed significant predictive ability for symptom improvement using a regularized least-squares regression predict model. These findings indicated that the EC of right amygdala subregions may be functionally related in symptom improvement of MDD. It may aid us to understand the neurological mechanism of pharmacotherapy and can be used as a promising predictor for symptom improvement in MDD.

Clinical value of SMI Combined with Low-Dose CT Scanning in differential diagnosis of Thyroid Lesions and Tumor Staging.

OBJECTIVES: To investigate the clinical value of Superb Microvascular Imaging (SMI) combined with low dose CT scanning in differential diagnosis of thyroid lesions and tumor staging. METHODS: A total of 120 patients with thyroid nodules admitted to the Chinese PLA General Hospital from January 2017 to July 2020 were selected. Paired design was adopted in this study. SMI and SMI combined with low-dose CT scanning were respectively carried out to these patients. The results were judged by two senior imaging physicians and two senior sonographers respectively. And t-test, χ2 test, Pearson correlation coefficient check and other methods were adopted to comparatively analyze the above two methods and the pathological results after operation or puncture. RESULTS: Compared with pathologic findings, the coincidence rate of SMI was 40%, and the coincidence rate of SMI combined with low dose CT scanning was 84%. The difference was significant (p=0.00); among the 120 thyroid nodule patients, 50 were diagnosed as malignant by pathological diagnosis, and 70 as benign; 27 malignant cases and 93 benign cases were detected by SMI; 48 malignant cases and 72 benign cases were detected by SMI combined with low dose CT scanning. The sensitivity and accuracy of the latter were significantly higher than those of the former, and the difference was statistically significant (p=0.00); the enhancement, edge sharpness and homogeneity of SMI increased with the increase of tumor malignancy, showing positive correlation property. CONCLUSION: SMI combined with low dose CT scanning has a higher diagnostic coincidence rate. Its sensitivity and accuracy are significantly superior. With the increase of tumor malignancy, the enhancement and unhomogeneity of SMI increase, and the edge is more blurred. That suggests: with the increase of tumor malignancy, neovascularization in the tumor is more obvious and more unevenly distributed; the increase of edge blur indicates more obvious tumor infiltration. The method has considerable clinical value for predicting the malignancy of tumors.

Aberrant Effective Connectivity of the Ventral Putamen in Boys With Attention-Deficit/Hyperactivity Disorder.

OBJECTIVE: The connectivity alterations in the putamen were found in revealing the neural correlates of attention-deficit/hyperactivity disorder (ADHD), but whether the effective connectivity of the putamen is atypical in ADHD remains unclear. Investigating this abnormality contributes to describing the neural circuit of ADHD at the level of macrostructural organization. METHODS: Data were acquired from thirty-two boys with ADHD and fifty-two matched typically developing controls (TDC) from Peking University (Peking) dataset deposited at the Neuroimaging Informatics Tools and Resources Clearinghouse (NITRC) platform. We examined the effective connectivity of the putamen using Granger causality analysis (GCA) and then determined whether these connections could differentiate ADHD from TDC. RESULTS: Compared with TDC, the ADHD group showed decreased effective connectivity from the left ventral rostral putamen (VRP) to left calcarine (CAL), right medial part of the superior frontal gyrus, left orbital part of superior frontal gyrus and left middle occipital gyrus (MOG). Increased effective connectivity from the left inferior occipital gyrus and right lingual gyrus to left VRP was also found in ADHD. The result of the classification accuracy showed that 72.3% of participants were correctly classified using support vector machine. Moreover, GCA values from the left VRP to left CAL and left MOG were significantly correlated with hyper/impulsive scores of patients with ADHD. CONCLUSION: The findings may help extend our understanding of the ADHD-related neural loops.

Brain state-dependent dynamic functional connectivity patterns in attention-deficit/hyperactivity disorder.

Attention-deficit/hyperactivity disorder (ADHD) patients have presented aberrant static brain networks, however identifying ADHD patients based on dynamic information in brain networks is not fully clear. Data were obtained from 32 boys with ADHD and 52 sex- and age-matched typically developing controls; a sliding-window method was used to assess dynamic functional connectivity (dFC), and two reoccurring dFC states (the hot and cool states) were then identified using a k-means clustering method. The results showed that ADHD patients had significant changes in occurrence, transitions times and dFC strength of the cingulo-opercular network (CON) and sensorimotor network (SMN) in the cool state. The severity of ADHD symptoms showed significant correlations with the regional amplitude of dFC fluctuations in the ventral medial prefrontal cortex (vmPFC), anterior medial prefrontal cortex (amPFC) and precuneus. These findings could provide insights on the state-dependent dynamic changes in large-scale brain connectivity and network configurations in ADHD.

Antidepressant Treatment-Induced State-Dependent Reconfiguration of Emotion Regulation Networks in Major Depressive Disorder.

Deficits in emotion regulation are the main clinical features, common risk factors, and treatment-related targets for major depressive disorder (MDD). The neural bases of emotion regulation are moving beyond specific functions and emphasizing instead the integrative functions of spatially distributed brain areas that work together as large-scale brain networks, but it is still unclear whether the dynamic interactions among these emotion networks would be the target of clinical intervention for MDD. Data were collected from 70 MDD patients and 43 sex- and age-matched healthy controls. The dynamic functional connectivity (dFC) between emotion regions was estimated via a sliding-window method based on resting-state functional magnetic resonance imaging (R-fMRI). A k-means clustering method was applied to classify all time windows across all participants into several dFC states reflecting recurring functional interaction patterns among emotion regions over time. The results showed that four dFC states were identified in the emotion networks. Their alterations of state-related occurrence proportion were found in MDD and subsequently normalized following 12-week antidepressant treatment. Baseline strong dFC could predict the reduction rate of Hamilton Depression Rating Scale (HAMD) scores. These findings highlighted the state-dependent reconfiguration of emotion regulation networks in MDD patients owing to antidepressant treatment.

Correlation of elastic characteristics of breast lesions with the expression of Smad2/3.

BACKGROUND: To analyze the relationship between elastic characteristics and the expression of Smad2/3 in breast lesions. METHODS: Between April 2018 and October 2018, 135 lesions from 130 patients who underwent shear wave elastography before surgical excision or biopsy were included in the study. The shear wave elasticity features of the lesions, expression of Smad2/3 of the specimens, and their combined diagnostic efficacy was analyzed. RESULTS: Of the 135 lesions, 51 were malignant and 84 were benign. The elasticity ratio of lesions to peripheral parenchyma, maximum elasticity, mean elasticity, prevalent rate of "stiff rim sign", and the expression level of Smad2/3 in the malignant pathological changes were obviously superior to those with benign pathological change (P<0.001). The Smad2/3 expression level had a positive correlation with the maximum, average elasticity, and the elastic ratio of lesions to peripheral parenchyma (r=0.657, 0.640, and 0.470, respectively, P<0.001). The expression of Smad2/3 in lesions with "stiff rim sign" was statistically higher than that in lesions without "stiff rim sign" (P<0.001). Moreover, the combination of Smad2/3 expression and "stiff rim sign" was shown to greatly raise the sensitivity (100%) and accuracy (94.56%) in the differential diagnosis of mammary gland disease. CONCLUSIONS: In light of the findings, maximum, mean elasticity, elasticity ratio of lesions to peripheral parenchyma, and "stiff rim sign" are correlated with the expression of Smad2/3. The combination of the expression of Smad2/3 and "stiff rim sign" might contribute to the diagnosis of breast carcinoma.

Aberrant state-related dynamic amplitude of low-frequency fluctuations of the emotion network in major depressive disorder.

Major depressive disorder (MDD) is a highly prevalent mental disorder that is typically characterized by pervasive and persistent low mood. This durable emotional disturbance may represent a key aspect of the neuropathology of MDD, typified by the wide-ranging distribution of brain alterations involved in emotion processing. However, little is known about whether these alterations are represented as the state properties of dynamic amplitude of low-frequency fluctuation (dALFF) variability in the emotion network. To address this question, we investigated the time-varying intrinsic brain activity derived from resting-state functional magnetic resonance imaging (R-fMRI). Data were obtained from 50 MDD patients and 37 sex- and age-matched healthy controls; a sliding-window method was used to assess dALFF in the emotion network, and two reoccurring dALFF states throughout the entire R-fMRI scan were then identified using a k-means clustering method. The results showed that MDD patients had a significant decrease in dALFF variability in the emotion network and its three modules located in the lateral paralimbic, media posterior, and visual association regions. Altered state-wise dALFF was also observed in MDD patients. Specifically, we found that these altered dALFF measurements in the emotion network were related to scores on the Hamilton Rating Scale for Depression (HAMD) among patients with MDD. The detection and estimation of these temporal dynamic alterations could advance our knowledge about the brain mechanisms underlying emotional dysfunction in MDD.

Musculoskeletal ultrasound in the Differential Diagnosis of Gouty Arthritis and Rheumatoid Arthritis.

OBJECTIVE: To explore the role of musculoskeletal ultrasound (MSUS) in the differential diagnosis of gouty arthritis (GA) and rheumatoid arthritis (RA) and to analyze the ultrasound imaging features of the two diseases. METHODS: A retrospective study was carried out. A total of 66 patients who had been admitted to The First Medical Center of Chinese PLA General Hospital from May 2018 to March 2019 were enrolled. Among them, 34 patients were diagnosed with RA and were included in the RA group; 32 patients were diagnosed with gouty arthritis and were included in the GA group. The imaging features of musculoskeletal ultrasound were compared between the two groups of patients. RESULTS: A total of 34 patients were included in the RA group, including 17 males and 17 females. A total of 32 patients were included in the GA group, including 14 males and 18 females. There were no significant differences in gender composition, age, and duration of disease between the two groups (P>0.05). In the RA group, there were joint bone erosions with a clear boundary in seven cases and with a blurred boundary in 27 cases; synovial hyperplasia was observed in 27 cases, and point-like hyperechoic masses were observed in four cases. In the GA group, there were joint bone erosions with a clear boundary in 27 cases and with a blurred boundary in five cases; synovial hyperplasia was observed in four cases, tophus was observed in 23 cases, point-like hyperechoic masses were observed in 27 cases, and the tram-track sign was observed in 23 cases. The differences in bone erosion boundaries (c2=26.854, P<0.01), synovial hyperplasia (c2=29.631, P<0.01), tophus (P<0.01), point-like hyperechoic mass (c2=33.095, P<0.01), and tram-track sign (P<0.01) were statistically significant between the two groups of patients. In the RA group, blood flow signaling was Grade 0 in one case, Grade-I in five cases, Grade-II in 14 cases, and Grade-III in 14 cases. In the GA group, blood flow signaling was Grade 0 in 26 cases, Grade-I in three cases, Grade-II in three cases, and Grade-III in zero cases. The difference in the synovial blood flow signaling between the two groups of patients was statistically significant (c2=34.323, P<0.01). CONCLUSIONS: MSUS has certain diagnostic value in the differentiation of GA and RA. Moreover, the two conditions have their own ultrasound imaging features.

[Value of Thermal Tomography in Early Diagnosis of Breast Cancer in Animal Models].

Objective To obtain ultrasound and thermal tomography images of breast cancer during its growth and to assess the value of thermal tomography in detecting breast cancer. Methods Breast cancer models were established with NOD/SCID mice and SD rats. These animal models were examined by thermal tomography,plain ultrasound,and contrast-enhanced ultrasound. Tumor tissues were stained with CD34 to explore the relationship between tumor heat production and vascular pathology. Results Thermal tomography detected breast cancer 2-4 days earlier than ultrasound. The expression of CD34 in tumor tissues was increased,along with thickened,increased,and irregular blood vessels. Conclusion Thermal tomography can detect early breast cancer and is a promising tool for screening breast cancer.

Differentiating Boys with ADHD from Those with Typical Development Based on Whole-Brain Functional Connections Using a Machine Learning Approach.

PURPOSE: In recent years, machine learning techniques have received increasing attention as a promising approach to differentiating patients from healthy subjects. Therefore, some resting-state functional magnetic resonance neuroimaging (R-fMRI) studies have used interregional functional connections as discriminative features. The aim of this study was to investigate ADHD-related spatially distributed discriminative features derived from whole-brain resting-state functional connectivity patterns using machine learning. PATIENTS AND METHODS: We measured the interregional functional connections of the R-fMRI data from 40 ADHD patients and 28 matched typically developing controls. Machine learning was used to discriminate ADHD patients from controls. Classification performance was assessed by permutation tests. RESULTS: The results from the model with the highest classification accuracy showed that 85.3% of participants were correctly identified using leave-one-out cross-validation (LOOV) with support vector machine (SVM). The majority of the most discriminative functional connections were located within or between the cerebellum, default mode network (DMN) and frontoparietal regions. Approximately half of the most discriminative connections were associated with the cerebellum. The cerebellum, right superior orbitofrontal cortex, left olfactory cortex, left gyrus rectus, right superior temporal pole, right calcarine gyrus and bilateral inferior occipital cortex showed the highest discriminative power in classification. Regarding the brain-behaviour relationships, some functional connections between the cerebellum and DMN regions were significantly correlated with behavioural symptoms in ADHD (P < 0.05). CONCLUSION: This study indicated that whole-brain resting-state functional connections might provide potential neuroimaging-based information for clinically assisting the diagnosis of ADHD.

Intranasal Oxytocin Increases Perceptual Salience of Faces in the Absence of Awareness.

OBJECTIVE: The neuropeptide oxytocin has been found to improve human social cognition and promote prosocial behavior. However, it is still unclear about the mechanisms underlying these effects of oxytocin on neural processes, such as visual perception and awareness. Especially, it is still unclear whether oxytocin influences perceptual salience of social stimuli in the absence of awareness. METHODS: In a randomized double-blind, placebo-controlled trial we applied an interocular suppression paradigm and eye tracking methods to investigate the influence of intranasally administered oxytocin on perceptual salience of social stimuli. Suppression times and pupillometric data were measured during subjects being presented with gradually introduced pictures of social stimuli (neutral expression faces) or nonsocial stimuli (grayscale watch pictures) that were suppressed and invisible in 10 men who were administered 24 IU oxytocin and 10 men who were administered a placebo. RESULTS: The results demonstrated that the oxytocin group perceived social stimuli more quickly accompanied by subsequent larger increasing pupil diameter than nonsocial stimuli, indicating an increased unconscious salience of social stimuli. CONCLUSION: These findings provided new insights into oxytocin's modulatory role to social information processing, suggesting that oxytocin might enhance attentional bias to social stimuli even after removal of awareness.