Multimetric structural covariance in first-episode major depressive disorder: a graph theoretical analysis

Background: Abnormalities of cortical morphology have been consistently reported in major depressive disorder (MDD), with widespread focal alterations in cortical thickness, surface area and gyrification. However, it is unclear whether these distributed focal changes disrupt the system-level architecture (topology) of brain morphology in MDD. If present, such a topological disruption might explain the mechanisms that underlie altered cortical morphology in MDD. Methods: Seventy-six patients with first-episode MDD (33 male, 43 female) and 66 healthy controls (32 male, 34 female) underwent structural MRI scans. We calculated cortical indices, including cortical thickness, surface area and local gyrification index, using FreeSurfer. We constructed morphological covariance networks using the 3 cortical indices separately, and we analyzed the topological properties of these group-level morphological covariance networks using graph theoretical approaches. Results: Topological differences between patients with first-episode MDD and healthy controls were restricted to the thickness-based network. We found a significant decrease in global efficiency but an increase in local efficiency of the left superior frontal gyrus and the right paracentral lobule in patients with first-episode MDD. When we simulated targeted lesions affecting the most highly connected nodes, the thickness-based networks in patients with first-episode MDD disintegrated more rapidly than those in healthy controls. Limitations: Our sample of patients with first-episode MDD has limited generalizability to patients with chronic and recurrent MDD. Conclusion: A systems-level disruption in cortical thickness (but not surface area or gyrification) occurs in patients with first-episode MDD

Variational capacitance modeling using orthogonal polynomial method

ABSTRACT In this paper, we propose a novel statistical capacitance extraction method for interconnects considering process variations. The new method, called statCap, is based on the spectral stochastic method where orthogonal polynomials are used to represent the statistical processes in a deterministic way. We first show how the variational potential coefficient matrix is represented in a first-order form using Taylor expansion and orthogonal decomposition. Then an augmented potential coefficient matrix, which consists of the coefficients of the polynomials, is derived. After that, corresponding augmented system is solved to obtain the variational capacitance values in the orthogonal polynomial form. Experimental results show that our method is two orders of magnitude faster than the recently proposed statistical capacitance extraction method based on the spectral stochastic collocation approac

Cortical morphological heterogeneity of schizophrenia and its relationship with glutamatergic receptor variations

Abstract Background Recent genetic evidence implicates glutamatergic-receptor variations in schizophrenia. Glutamatergic excess during early life in people with schizophrenia may cause excitotoxicity and produce structural deficits in the brain. Cortical thickness and gyrification are reduced in schizophrenia, but only a subgroup of patients exhibits such structural deficits. We delineate the structural variations among unaffected siblings and patients with schizophrenia and study the role of key glutamate-receptor polymorphisms on these variations. Methods Gaussian Mixture Model clustering was applied to the cortical thickness and gyrification data of 114 patients, 112 healthy controls, and 42 unaffected siblings to identify subgroups. The distribution of glutamate-receptor (GRM3, GRIN2A, and GRIA1) and voltage-gated calcium channel (CACNA1C) variations across the MRI-based subgroups was studied. The comparisons in clinical symptoms and cognition between patient subgroups were conducted. Results We observed a “hypogyric,” “impoverished-thickness,” and “supra-normal” subgroups of patients, with higher negative symptom burden and poorer verbal fluency in the hypogyric subgroup and notable functional deterioration in the impoverished-thickness subgroup. Compared to healthy subjects, the hypogyric subgroup had significant GRIN2A and GRM3 variations, the impoverished-thickness subgroup had CACNA1C variations while the supra-normal group had no differences. Conclusions Disrupted gyrification and thickness can be traced to the glutamatergic receptor and voltage-gated calcium channel dysfunction respectively in schizophrenia. This raises the question of whether MRI-based multimetric subtyping may be relevant for clinical trials of agents affecting the glutamatergic system

The comparison of manual and mechanical anastomosis after total pharyngolaryngoesophagectomy

BackgroundTotal pharyngolaryngoesophagectomy (TPLE) is considered as a curative treatment for hypopharynx cancer and cervical esophageal carcinomas (HPCECs). Traditional pharyngo-gastric anastomosis is usually performed manually, and postoperative complications are common. The aim of this study was to introduce a new technique for mechanical anastomosis and to evaluate perioperative outcomes and prognosis.MethodsFrom May 1995 to Nov 2021, a series of 75 consecutive patients who received TPLE for a pathological diagnosis of HPCECs at Sun Yat-sen Memorial Hospital were evaluated. Mechanical anastomosis was performed in 28 cases and manual anastomosis was performed in 47 cases. The data from these patients were retrospectively analyzed.ResultsThe mean age was 57.6 years, and 20% of the patients were female. The rate of anastomotic fistula and wound infection in the mechanical group were significantly lower than that in the manual group. The operation time, intraoperative blood loss and postoperative hospital stays were significantly higher in the manual group than that in the mechanical group. The R0 resection rate and the tumor characteristics were not significantly different between groups. There was no significant difference in overall survival and disease-free survival between the two groups.ConclusionThe mechanical anastomosis technology adopted by this study was shown to be a safer and more effective procedure with similar survival comparable to that of manual anastomosis for the HPCECs patients

Deep Multilayer Brain Proteomics Identifies Molecular Networks in Alzheimer\u27s Disease Progression

Alzheimer\u27s disease (AD) displays a long asymptomatic stage before dementia. We characterize AD stage-associated molecular networks by profiling 14,513 proteins and 34,173 phosphosites in the human brain with mass spectrometry, highlighting 173 protein changes in 17 pathways. The altered proteins are validated in two independent cohorts, showing partial RNA dependency. Comparisons of brain tissue and cerebrospinal fluid proteomes reveal biomarker candidates. Combining with 5xFAD mouse analysis, we determine 15 Aβ-correlated proteins (e.g., MDK, NTN1, SMOC1, SLIT2, and HTRA1). 5xFAD shows a proteomic signature similar to symptomatic AD but exhibits activation of autophagy and interferon response and lacks human-specific deleterious events, such as downregulation of neurotrophic factors and synaptic proteins. Multi-omics integration prioritizes AD-related molecules and pathways, including amyloid cascade, inflammation, complement, WNT signaling, TGF-β and BMP signaling, lipid metabolism, iron homeostasis, and membrane transport. Some Aβ-correlated proteins are colocalized with amyloid plaques. Thus, the multilayer omics approach identifies protein networks during AD progression

A Facile Strategy for In Situ Core-Template-Functionalizing Siliceous Hollow Nanospheres for Guest Species Entrapment

The shell wall-functionalized siliceous hollow nanospheres (SHNs) with functional molecules represent an important class of nanocarriers for a rich range of potential applications. Herein, a self-templated approach has been developed for the synthesis of in situ functionalized SHNs, in which the biocompatible long-chain polycarboxylates (i.e., polyacrylate, polyaspartate, gelatin) provide the framework for silica precursor deposition by simply controlling chain conformation with divalent metal ions (i.e., Ca2+, Sr2+), without the intervention of any external templates. Metal ions play crucial roles in the formation of organic vesicle templates by modulating the long chains of polymers and preventing them from separation by washing process. We also show that, by in situ functionalizing the shell wall of SHNs, it is capable of entrapping nearly an eightfold quantity of vitamin Bc in comparison to the bare bulk silica nanospheres. These results confirm the feasibility of guest species entrapment in the functionalized shell wall, and SHNs are effective carriers of guest (bio-)molecules potentially for a variety of biomedical applications. By rationally choosing the functional (self-templating) molecules, this concept may represent a general strategy for the production of functionalized silica hollow structures

Coupling Analysis of the Road-Network Spatiotemporal Distribution and the Economy in B&R Countries Based on GIS

The Belt and Road (B&R) is a new strategy and measure for China to extend its opening up. To explore the influence of the spatiotemporal distribution of the national road network along the B&R on economic growth, this paper adopts the subjective and objective integrated weighting method to build a regional economic evaluation model, a transportation network evaluation model, and an economy–transportation coupling coordination degree model (E-T model). We also quantitatively analyze and evaluate the coordinated development of the economy and transportation in the countries along the B&R. Our results show that: (1) There are some differences in the comprehensive scores of economic level and transportation network in different countries, and the B&R has promoted the general economic and transportation level of various countries. (2) Approximately 84% of the countries have not reached a good coordination level, and the regional differences are significant, which indicates that the overall economic and transportation coupling coordination needs to be improved. (3) In recent years, driven by the B&R, the coupling coordination of approximately 30% of the countries has improved significantly. Therefore, the B&R not only has a positive impact on the economy and transportation of countries along the belt but also plays an important role in coordinating the economic and transportation development of countries, which is of great strategic significance

Coupling Analysis of the Road-Network Spatiotemporal Distribution and the Economy in B&R Countries Based on GIS

The Belt and Road (B&R) is a new strategy and measure for China to extend its opening up. To explore the influence of the spatiotemporal distribution of the national road network along the B&R on economic growth, this paper adopts the subjective and objective integrated weighting method to build a regional economic evaluation model, a transportation network evaluation model, and an economy–transportation coupling coordination degree model (E-T model). We also quantitatively analyze and evaluate the coordinated development of the economy and transportation in the countries along the B&R. Our results show that: (1) There are some differences in the comprehensive scores of economic level and transportation network in different countries, and the B&R has promoted the general economic and transportation level of various countries. (2) Approximately 84% of the countries have not reached a good coordination level, and the regional differences are significant, which indicates that the overall economic and transportation coupling coordination needs to be improved. (3) In recent years, driven by the B&R, the coupling coordination of approximately 30% of the countries has improved significantly. Therefore, the B&R not only has a positive impact on the economy and transportation of countries along the belt but also plays an important role in coordinating the economic and transportation development of countries, which is of great strategic significance

An Efficient Hybrid CNN-Transformer Approach for Remote Sensing Super-Resolution

Transformer models have great potential in the field of remote sensing super-resolution (SR) due to their excellent self-attention mechanisms. However, transformer models are prone to overfitting because of their large number of parameters, especially with the typically small remote sensing datasets. Additionally, the reliance of transformer-based SR models on convolution-based upsampling often leads to mismatched semantic information. To tackle these challenges, we propose an efficient super-resolution hybrid network (EHNet) based on the encoder composed of our designed lightweight convolution module and the decoder composed of an improved swin transformer. The encoder, featuring our novel Lightweight Feature Extraction Block (LFEB), employs a more efficient convolution method than depthwise separable convolution based on depthwise convolution. Our LFEB also integrates a Cross Stage Partial structure for enhanced feature extraction. In terms of the decoder, based on the swin transformer, we innovatively propose a sequence-based upsample block (SUB) for the first time, which directly uses the sequence of tokens in the transformer to focus on semantic information through the MLP layer, which enhances the feature expression ability of the model and improves the reconstruction accuracy. Experiments show that EHNet’s PSNR on UCMerced and AID datasets obtains a SOTA performance of 28.02 and 29.44, respectively, and is also visually better than other existing methods. Its 2.64 M parameters effectively balance model efficiency and computational demands