Comparative study of CT-guided radiofrequency and alcohol ablation in the treatment of primary hyperhidrosis

ObjectiveThis study compared the efficacy and complications of percutaneous radiofrequency ablation with anhydrous alcohol ablation of sympathetic nerves in treating hyperhidrosis of the head and palms.MethodsA retrospective analysis was conducted on 54 patients with primary hyperhidrosis in our department from June 2018 to June 2021, divided into a radiofrequency ablation group (30 cases) and an anhydrous alcohol ablation group (24 cases). Treatment outcomes were compared by analyzing the number of CT scans, effectiveness, and complications.ResultsIn the radiofrequency group, symptoms of bilateral hyperhidrosis significantly improved in 24 patients, with an 80% postoperative satisfaction rate. In the alcohol ablation group, symptoms significantly improved in 19 patients postoperatively, with a 79.2% satisfaction rate. There was no statistically significant difference in effectiveness or complications between the two groups (all P > 0.05). The number of CT scans in the radiofrequency group was 4.60 ± 0.56 and 6.08 ± 0.28 in the alcohol group, showing a statistically significant difference (P < 0.05).ConclusionThis study concluded that both percutaneous radiofrequency ablation and alcohol ablation are effective methods for hyperhidrosis treatment, with similar effectiveness and complication rates, but the radiofrequency ablation group required fewer CT scans

Large-scale dynamic causal modeling of major depressive disorder based on resting-state functional magnetic resonance imaging

Major depressive disorder (MDD) is a serious mental illness characterized by dysfunctional connectivity among distributed brain regions. Previous connectome studies based on functional magnetic resonance imaging (fMRI) have focused primarily on undirected functional connectivity and existing directed effective connectivity (EC) studies concerned mostly task-based fMRI and incorporated only a few brain regions. To overcome these limitations and understand whether MDD is mediated by within-network or between-network connectivities, we applied spectral dynamic causal modeling to estimate EC of a large-scale network with 27 regions of interests from four distributed functional brain networks (default mode, executive control, salience, and limbic networks), based on large sample-size resting-state fMRI consisting of 100 healthy subjects and 100 individuals with first-episode drug-naive MDD. We applied a newly developed parametric empirical Bayes (PEB) framework to test specific hypotheses. We showed that MDD altered EC both within and between high-order functional networks. Specifically, MDD is associated with reduced excitatory connectivity mainly within the default mode network (DMN), and between the default mode and salience networks. In addition, the network-averaged inhibitory EC within the DMN was found to be significantly elevated in the MDD. The coexistence of the reduced excitatory but increased inhibitory causal connections within the DMNs may underlie disrupted self-recognition and emotional control in MDD. Overall, this study emphasizes that MDD could be associated with altered causal interactions among high-order brain functional networks

Multiscale neural modeling of resting-state fMRI reveals executive-limbic malfunction as a core mechanism in major depressive disorder

Major depressive disorder (MDD) represents a grand challenge to human health and society, but the underlying pathophysiological mechanisms remain elusive. Previous neuroimaging studies have suggested that MDD is associated with abnormal interactions and dynamics in two major neural systems including the default mode - salience (DMN-SAL) network and the executive - limbic (EXE-LIM) network, but it is not clear which network plays a central role and which network plays a subordinate role in MDD pathophysiology. To address this question, we refined a newly developed Multiscale Neural Model Inversion (MNMI) framework and applied it to test whether MDD is more affected by impaired circuit interactions in the DMN-SAL network or the EXE-LIM network. The model estimates the directed connection strengths between different neural populations both within and between brain regions based on resting-state fMRI data collected from normal healthy subjects and patients with MDD. Results show that MDD is primarily characterized by abnormal circuit interactions in the EXE-LIM network rather than the DMN-SAL network. Specifically, we observe reduced frontoparietal effective connectivity that potentially contributes to hypoactivity in the dorsolateral prefrontal cortex (dlPFC), and decreased intrinsic inhibition combined with increased excitation from the superior parietal cortex (SPC) that potentially lead to amygdala hyperactivity, together resulting in activation imbalance in the PFC-amygdala circuit that pervades in MDD. Moreover, the model reveals reduced PFC-to-hippocampus excitation but decreased SPC-to-thalamus inhibition in MDD population that potentially lead to hypoactivity in the hippocampus and hyperactivity in the thalamus, consistent with previous experimental data. Overall, our findings provide strong support for the long-standing limbic-cortical dysregulation model in major depression but also offer novel insights into the multiscale pathophysiology of this debilitating disease

A Novel Approach for Automatic Urban Surface Water Mapping with Land Surface Temperature (AUSWM)

The principal difficulty in extracting urban surface water using remote-sensing techniques is the influence of noise from complex urban environments. Although various methods exist, there are still many sources of noise interference when extracting urban surface water, and automatic cartographic methods with long time series are especially scarce. Here, we construct an automatic urban surface water extraction method from the combination of traditional water index, urban shadow index (USI), and land surface temperature (LST) by using the Google Earth Engine cloud computing platform and Landsat imagery. The three principal findings derived from the application of the method were as follows. (i) In comparison with autumn and winter, LST in spring and summer could better distinguish water from high-reflection ground objects, shadows, and roads and roofs covered by asphalt. (ii) The overall accuracy of Automated Water Extraction Index (AWEIsh) in Zhengzhou was 77.5% and the Kappa coefficient was 0.55; with consideration of the USI and LST, the overall accuracy increased to 96.0% and the Kappa coefficient increased to 0.92. (iii) During 1990–2020, the area of urban surface water in Zhengzhou increased, with an evident trend in expansion from 11.51 km2 in 2008 to 49.28 km2 in 2020. Additionally, possible omissions attributable to using 30m-resolution imagery to extract urban water areas were also discussed. The method proposed in this study was proven effective in eliminating the influence of noise in urban areas, and it could be used as a general method for high-accuracy long-term mapping of urban surface water

Accelerating Cities in an Unsustainable Landscape: Urban Expansion and Cropland Occupation in China, 1990–2030

It is crucial to assess the effects of urban expansion on croplands to allow sustainable urbanization and cropland supply. However, owing to the complexity of land conversion and various land policies in China, it is difficult to quantify the cropland dynamics and implications of urban expansion throughout the whole accelerated stage of urbanization. This study was based on land use data from 1990 to 2015 and urban expansion data from 2000 to 2030, analyzing urban expansion and predicting its impact on croplands. We found that urban area would continue to increase and croplands would contribute more than 70% of the urban expansion area. The urban area in China will likely reach 71.6–87.0 thousand km2 or more by 2030. Although the overall area of croplands may remain at a similar magnitude in future decades, our findings imply that croplands will tend to shift northward, resulting in some potential challenges owing to resource limitations in northern regions. Our study provides a new perspective in terms of assessing future cropland dynamics and the effects of urban expansion and highlights the significance of ensuring a realistic land policy in the future

On the Skew Spectra of Cartesian Products of Graphs

An oriented graph ${G^{\sigma}}$ is a simple undirected graph $G$ with an orientation, which assigns to each edge of $G$ a direction so that ${G^{\sigma}}$ becomes a directed graph. $G$ is called the underlying graph of ${G^{\sigma}}$ and we denote by $S({G^{\sigma}})$ the skew-adjacency matrix of ${G^{\sigma}}$ and its spectrum $Sp({G^{\sigma}})$ is called the skew-spectrum of ${G^{\sigma}}$. In this paper, the skew spectra of two orientations of the Cartesian products are discussed, as applications, new families of oriented bipartite graphs ${G^{\sigma}}$ with $Sp({G^{\sigma}})={\bf i} Sp(G)$ are given and the orientation of a product graph with maximum skew energy is obtained.</jats:p