Intra-module Connectivity Research Articles

Lateral stiffness of modular steel joint with semi-rigid bolted intra-module connection

In contrast to the beam-column joints found in traditional assembled steel structures, modular steel structures feature inter-module and intra-module connections within their joints. While existing research has largely focused on the mechanical properties of inter-module connections, the impact of intra-module connection stiffness on the performance of modular steel joints remains unclear. This study introduces a novel corner-fitting-reinforced fully bolted joint specifically designed for modular steel structures. A series of experiments were conducted, including a flexural test on bolted intra-module connection to determine its initial rotational stiffness, and four groups of lateral static tests on full-scale modular steel joints with varying intra-module connection stiffnesses. These tests aimed to characterize mechanical properties such as load-carrying capacity, lateral stiffness, strain development, and ductility. The study elucidates the influence of intra-module connection stiffness on the lateral stiffness of modular steel joints. Furthermore, a refined finite-element (FE) model of the corner-fitting-reinforced fully bolted joint was developed. Simulation results showed good agreement with experimental findings., with an average error of less than 10 % for ultimate load-carrying capacity prediction. The FE model also, analyzed the stress-strain development of the corner fitting throughout the process. The study establishes a theoretical analysis model for the corner-fitting-reinforced fully bolted joint and derives a theoretical formula for the initial lateral stiffness of the modular steel joint, considering semi-rigid intra-module connections. This formula aligns well with both experimental and FE results, with a maximum error of 15 %. Finally, the study delves into the force-transfer mechanism of the corner-fitting-reinforced fully bolted joint, providing valuable insights for its design.

Multiomic meta-analysis suggests a correlation between steroid hormone-related genes and litter size in goats.

Litter size is a key indicator of production performance in livestock. However, its genetic basis in goats remains poorly understood. In this work, a genome-wide selection sweep analysis (GWSA) on 100 published goat genomes with different litter rates was performed for the first time to identify candidate genes related to kidding rate. This analysis was combined with the public RNA-sequencing data of ovary tissues (follicular phase) from high- and low-yielding goats. A total of 2278 genes were identified by GWSA. Most of these genes were enriched in signaling pathways related to ovarian follicle development and hormone secretion. Moreover, 208 differentially expressed genes between groups were obtained from the ovaries of goats with different litter sizes. These genes were substantially enriched in the cholesterol and steroid synthesis signaling pathways. Meanwhile, the weighted gene co-expression network was used to perform modular analysis of differentially expressed genes. The results showed that seven modules were reconstructed, of which one module showed a very strong correlation with litter size (r = -0.51 and p-value <0.001). There were 51 genes in this module, and 39 hub genes were screened by Pearson's correlation coefficient between core genes > 0.4, correlation coefficient between module members > 0.80 and intra-module connectivity ≥5. Finally, based on the results of GWSA and hub gene Venn analysis, seven key genes (ACSS2, HECW2, KDR, LHCGR, NAMPT, PTGFR and TFPI) were found to be associated with steroid synthesis and follicle growth development. This work contributes to understanding of the genetic basis of goat litter size and provides theoretical support for goat molecular breeding.

Topological Organization of the Brain Network in Patients with Primary Angle-closure Glaucoma Through Graph Theory Analysis.

Primary angle-closure glaucoma (PACG) is a sight-threatening eye condition that leads to irreversible blindness. While past neuroimaging research has identified abnormal brain function in PACG patients, the relationship between PACG and alterations in brain functional networks has yet to be explored. This study seeks to examine the influence of PACG on brain networks, aiming to advance knowledge of its neurobiological processes for better diagnostic and therapeutic approaches utilizing graph theory analysis. A cohort of 44 primary angle-closure glaucoma (PACG) patients and 44 healthy controls participated in this study. Functional brain networks were constructed using fMRI data and the Automated Anatomical Labeling 90 template. Subsequently, graph theory analysis was employed to evaluate global metrics, nodal metrics, modular organization, and network-based statistics (NBS), enabling a comparative analysis between PACG patients and the control group. The analysis of global metrics, including small-worldness and network efficiency, did not exhibit significant differences between the two groups. However, PACG patients displayed elevated nodal metrics, such as centrality and efficiency, in the left frontal superior medial, right frontal superior medial, and right posterior central brain regions, along with reduced values in the right temporal superior gyrus region compared to healthy controls. Furthermore, Module 5 showed notable disparities in intra-module connectivity, while Module 1 demonstrated substantial differences in inter-module connectivity with both Module 7 and Module 8. Noteworthy, the NBS analysis unveiled a significantly altered network when comparing the PACG and healthy control groups. The study proposes that PACG patients demonstrate variations in nodal metrics and modularity within functional brain networks, particularly affecting the prefrontal, occipital, and temporal lobes, along with cerebellar regions. However, an analysis of global metrics suggests that the overall connectivity patterns of the entire brain network remain unaltered in PACG patients. These results have the potential to serve as early diagnostic and differential markers for PACG, and interventions focusing on brain regions with high degree centrality and nodal efficiency could aid in optimizing therapeutic approaches.

Modular organization of functional brain networks in patients with degenerative cervical myelopathy

Previous studies have indicated that brain functional plasticity and reorganization in patients with degenerative cervical myelopathy (DCM). However, the effects of cervical cord compression on the functional integration and separation between and/or within modules remain unclear. This study aimed to address these questions using graph theory. Functional MRI was conducted on 46 DCM patients and 35 healthy controls (HCs). The intra- and inter-modular connectivity properties of the whole-brain functional network and nodal topological properties were then calculated using theoretical graph analysis. The difference in categorical variables between groups was compared using a chi-squared test, while that between continuous variables was evaluated using a two-sample t-test. Correlation analysis was conducted between modular connectivity properties and clinical parameters. Modules interaction analyses showed that the DCM group had significantly greater inter-module connections than the HCs group (DMN-FPN: t = 2.38, p = 0.02); inversely, the DCM group had significantly lower intra-module connections than the HCs group (SMN: t = − 2.13, p = 0.036). Compared to HCs, DCM patients exhibited higher nodal topological properties in the default-mode network and frontal–parietal network. In contrast, DCM patients exhibited lower nodal topological properties in the sensorimotor network. The Japanese Orthopedic Association (JOA) score was positively correlated with inter-module connections (r = 0.330, FDR p = 0.029) but not correlated with intra-module connections. This study reported alterations in modular connections and nodal centralities in DCM patients. Decreased nodal topological properties and intra-modular connection in the sensory-motor regions may indicate sensory-motor dysfunction. Additionally, increased nodal topological properties and inter-modular connection in the default mode network and frontal-parietal network may serve as a compensatory mechanism for sensory-motor dysfunction in DCM patients. This could provide an implicative neural basis to better understand alterations in brain networks and the patterns of changes in brain plasticity in DCM patients.

Computational Modelling of Intra-Module Connections and Their Influence on the Robustness of a Steel Corner-Supported Volumetric Module

This paper investigates the robustness of a single 3D volumetric corner-supported module made of square hollow-section (SHS) columns. Typically, the moment–rotation (M-θ) behaviour of connections within the module (intra-module) is assumed to be fully rigid rather than semi-rigid, resulting in inaccurate assessment (i.e., overestimated vertical stiffness) during extreme loading events, such as progressive collapse. The intra-module connections are not capable of rigidly transferring the moment from the beams to the SHS columns. In this paper, a computationally intensive shell element model (SEM) of the module frame is created. The M-θ relationship of the intra-module connections in the SEM is firstly validated against test results by others and then replicated in a new simplified phenomenological beam element model (BEM), using nonlinear spring elements to capture the M-θ relationship. Comparing the structural behaviour of the SEM and BEM, under notional support removal, shows that the proposed BEM with semi-rigid connections (SR-BEM) agrees well with the validated SEM and requires substantially lower modelling time (98.7% lower) and computational effort (97.4% less RAM). When compared to a BEM with the typically modelled fully rigid intra-module connections (FR-BEM), the vertical displacement in the SR-BEM is at least 16% higher. The results demonstrate the importance of an accurate assessment of framing rotational stiffness and the benefits of a computationally efficient model.

Revisiting the Modularity-Disease transmission Link: Uncovering the importance of intra-modular structure

Studies have shown that the internal structure of modules is hardly important for the spread of epidemics. However, most of these studies have assumed that intra-module connectivity and inter-module connectivity do not affect each other. In reality, changes in the internal structure of modules may affect inter-module links and thus change the modularity of the entire network. Therefore, we have developed a theoretical network model with adjustable modularity to investigate the impact of this situation on disease transmission. Our findings indicate that the intra-module structure plays a crucial role in disease outbreaks. Changes in intra-module structure lead to significant numerical changes in peak prevalence and duration of disease. This implies that the potential impact of changes in exposure patterns within modules should also be considered when investigating the exact impact of modular social networks on disease burden.

Finger motor representation supports the autonomy in arithmetic: neuroimaging evidence from abacus training.

Researches have reported the close association between fingers and arithmetic. However, it remains unclear whether and how finger training can benefit arithmetic. To address this issue, we used the abacus-based mental calculation (AMC), which combines finger training and mental arithmetic learning, to explore the neural correlates underlying finger-related arithmetic training. A total of 147 Chinese children (75 M/72 F, mean age, 6.89 ± 0.46) were recruited and randomly assigned into AMC and control groups at primary school entry. The AMC group received 5years of AMC training, and arithmetic abilities and resting-state functional magnetic resonance images data were collected from both groups at year 1/3/5. The connectome-based predictive modeling was used to find the arithmetic-related networks of each group. Compared to controls, the AMC's positively arithmetic-related network was less located in the control module, and the inter-module connections between somatomotor-default and somatomotor-control modules shifted to somatomotor-visual and somatomotor-dorsal attention modules. Furthermore, the positive network of the AMC group exhibited a segregated connectivity pattern, with more intra-module connections than the control group. Overall, our results suggested that finger motor representation with motor module involvement facilitated arithmetic-related network segregation, reflecting increased autonomy of AMC, thus reducing the dependency of arithmetic on higher-order cognitive functions.

Failure mechanisms of hexagonal-shaped intra-module connections in modular steel building

Modular construction has gained popularity for its cost-effectiveness, time savings, and environmental benefits. This research delves into innovating modular buildings to enhance their aesthetic value in contemporary architectural designs. Traditional rectangular modules have lost architectural significance in the modern era. The study focuses on the failure mechanisms of hexagonal intra-module connections under nonlinear static analysis, aiming for advanced structural design and performance in modular construction. The study tested a control model, a Welded Flange Bolted Web (WFBW) connection, and three variations with different parameters: boundary condition, bolt arrangement, and steel grade. For the boundary condition, the tie constraint between the beam's flanges and the diaphragm was removed. Bolt arrangement was assessed with staggered and non-staggered bolts. Steel grade variations included S275 and S355. Results showed that the WFBW connection outperformed the Bolted Web (BW) connection in load resistance. The most damaged component was the beam, with bearing failure at the upper bolt hole. Non-staggered bolts exhibited larger displacements than staggered bolts. The study emphasized the significance of steel material strength in terms of stress and strain on bolt capacity. It highlights the importance of intra-module connections in modular steel structures and the need to consider design parameters carefully. The findings offer insights into improving modular connections' performance and failure mechanisms, facilitating the creation of aesthetically pleasing and structurally sound modular structures. This nonlinear static analysis aids in developing advanced modular construction designs, enhancing architectural significance in the modern era. By merging structural performance and aesthetics, the study promotes innovative modular construction to meet contemporary architectural demands.

Effects of constructional tolerances on lateral resistance of steel–concrete composite modular buildings with various connection rigidity

This study uses the non-linear static (pushover) analysis to investigate the lateral resistance of mid-rise and high-rise composite modular buildings with out-of-verticality resulting from constructional tolerances. A series of 40 full-scale simulation tests are conducted using a 3-D finite element model. Based on the results, three distinctive failure modes are identified for the multi-storey modular buildings subjected to lateral load. A comparison between the lateral responses of modular buildings with different deviations suggests that the standard constructional tolerances do not largely impair the overall performance of the modular buildings, while the exaggerated constructional tolerances result in average reductions of up to 9% in terms of global stiffness and load capacity. The relative significance of the connection rigidity is also assessed, including the connections within and between the modular units, namely the intra-module and the inter-module connections. It shows that the rotational stiffness of intra-module connections strongly influences global structural performance, while the rotational stiffness of inter-module connections has minor impacts. Moreover, the results indicate that the translational forces at inter-module connections may increase by up to 131% when constructional tolerances are introduced, which should be carefully addressed to facilitate the safety design of such connections.

Disrupted network integration and segregation involving the default mode network in autism spectrum disorder

Changes in the brain's default mode network (DMN) in the resting state are closely related to autism spectrum disorder (ASD). Module segmentation can effectively elucidate the neural mechanism of ASD and explore intra- and inter-network connections by means of the participation coefficient (PC). We used that resting-state fMRI data from 269 ASD patients and 340 healthy controls (HCs) in the current study. From the results, ASD subjects showed a significantly higher PC of the DMN than HC subjects. This difference was related to lower intra-module connections within the DMN and higher inter-network connections between the DMN and other networks. When the subjects were split into age groups, the results were verified in the 7–12- and 12–18-year-old age groups but not in the young adult group (18–25 years). When the subjects were divided according to different subtypes of ASD, the results were also observed in the classic autism and pervasive developmental disorder groups, but not in the Asperger disorder group. In conclusions, less developed network segregation in the DMN could be a valid biomarker for ASD. This provides network scientists with new insights into the intermodular connectivity configurations of complex networks from different dimensions in a systematic and comprehensive manner.

Microbial Networks Reveal the Structure of Water Microbial Communities in Kalamaili Mountain Ungulate Nature Reserve

Water microorganisms contribute to the key components of ecosystems in dryland waters, which are extremely important for wildlife. However, the distribution patterns of water microbes across different basal water sources are still largely unknown. This study was conducted to compare microorganisms in the water bodies of different types of water sources in the Kalamaili Mountain Ungulate Nature Reserve in China. Bioinformatic analysis revealed that the undirected microbial co-existence network consisted of 15 main modules referring to different water sources, which indicated specific molecular co-existence relationships. It was found that the most dominant phyla (namely Proteobacteria, Patescibacteria, Firmicutes, Bacteroidota, and Actinobacteriota) of the molecular ecological network shared the same structures as the microbial community, which justified the construction of the network via a random network formation. Principal coordinate analysis (PCoA) based on Bray–Curtis distances revealed that there were still considerable variations among different habitats, showing separate sample clusters. Additionally, the different topological roles of subnetworks trimmed to a uniform size indicated different co-existence patterns in the microbiome. The artificially recharged water from concrete pond substrate (ARC) subnetworks had a relatively discrete co-occurrence, while the natural water sources (NRE) and artificially recharged water from earthen pond substrate (ARE) groups were more compact with giant modules. The NRE and ARE groups were also richer in microbial composition and had a higher number of species with low abundance. Consequently, concrete substrates may contribute to dysfunction in water microbiomes. Moreover, the functional diversity of the NRE and ARE groups is due to more intra-module connections and more inter-module connections, indirectly leading to a stable function resilient to external environmental influences. In conclusion, the microecology of the NRE was more stable than that of the concrete substrate, and artificial transportation had less effect on the microbial community.

The key sulfometuron-methyl degrading bacteria isolation based on soil bacterial phylogenetic molecular ecological networks and application for bioremediation of contaminated soil by immobilization

The analysis of soil bacterial community has guiding significance for fully utilization of soil microbial resources. The results of high-throughput sequencing (HTS) showed that the bacteria in the three sulfometuron-methyl contaminated soil samples were mainly composed of 677 genera, including Phenylobacterium, Bacillus, belonging to 28 phyla, including Proteobacteria, Firmicutes. The diversity and richness of bacterial community decreased with the increase in sulfometuron-methyl concentration. In addition, sulfometuron-methyl could also affect the soil bacterial function based on PICRUSt functional predictive analysis. Combined with the results of HTS and phylogenetic molecular ecological networks (pMENs), 12 genera, including Ralstonia (Pi=0.64), were identified as the key soil microflora (intra-module connectivity Zi ≥ 2.5 or inter-module connectivity Pi ≥ 0.62), and the abundance of Ralstonia significantly increased with the concentration of sulfometuron-methyl, indicating that the strains of this genus might be the potential degrading bacteria and could form a stable relationship with indigenous microorganisms. Among the isolated bacteria of genus Ralstonia, one strain, named Ralstonia sp. JM-1, was verified to possess higher sulfometuron-methyl degradation efficiency, which completely degraded 20 mg L−1 of sulfometuron-methyl within 96 h. Furthermore, the immobilized strains generated by the mixture of 2.0 g bamboo charcoal and 3.0 mL bacterial suspension for 24 h had the highest sulfometuron-methyl degradation rate than that under other conditions, and the dynamic process degrading 10–30 mg L−1 of sulfometuron-methyl conforms to the zero-order kinetic equation. The bioremediation of contaminated soil showed the immobilized strains could completely degrade sulfometuron-methyl (1.39 mg kg−1) in contaminated soil within 9 d, which is higher than that application of strains in the free state (74.8%). This study could provide ideas for the isolation of functional strains and a theoretical basis for the bioremediation of STM and other contaminated soils.

Effects of various reinforcing intra-module connection details on seismic behavior of corner-supported steel modular buildings

The rib stiffeners are usually used to reinforce the intra-module connections in corner-supported modular steel buildings; however, may be conflicted with the internal wall panels. There is a lack of relevant understanding of the effects of reinforcing intra-module connections on the seismic behavior of corner-supported steel modular structures. Therefore, this study investigated the effect of the intra-module connections reinforcing details on the seismic behavior of such modular structures. Such proposed reinforcing measures comply well with the architectural internal finishing demand, including vertical stiffeners or cover plates and an enlarging ceiling beam section. Four full-scale two-story plane frame structures were designed and experimentally examined under lateral cyclic loading to investigate and compare their seismic performance, such as the hysteretic performance, skeleton curves, and strain distribution. The experimental results showed that these reinforcing measures were helpful for the development of plastic deformation of such corner-supported modular structures through effectively moving local buckling away from the beam ends. Moreover, the reinforcing intra-module connection details were able to enhance the force resisting capacity and initial lateral stiffness of the overall structures. Additionally, the nonlinear finite-element (FE) modeling was developed and validated against the corresponding experiment. It showed satisfactory agreement with the failure responses and load–displacement curves. The plastic strains at reinforcing intra-module connection were further analyzed through the validated FE models, and the design suggestions were given accordingly.

Integrated weighted gene coexpression network analysis identifies Frizzled 2 (FZD2) as a key gene in invasive malignant pleomorphic adenoma

BackgroundInvasive malignant pleomorphic adenoma (IMPA) is a highly malignant neoplasm of the oral salivary glands with a poor prognosis and a considerable risk of recurrence. Many disease-causing genes of IMPA have been identified in recent decades (e.g., P53, PCNA and HMGA2), but many of these genes remain to be explored. Weighted gene coexpression network analysis (WGCNA) is a newly emerged algorithm that can cluster genes and form modules based on similar gene expression patterns. This study constructed a gene coexpression network of IMPA via WGCNA and then carried out multifaceted analysis to identify novel disease-causing genes.MethodsRNA sequencing (RNA-seq) was performed for 10 pairs of IMPA and normal tissues to acquire the gene expression profiles. Differentially expressed genes (DEGs) were screened out with the cutoff criteria of |log2 Fold change (FC)|> 1 and adjusted p value < 0.05. Then, WGCNA was applied to systematically identify the hidden diagnostic hub genes of IMPA.ResultsIn this research, a total of 1970 DEGs were screened out in IMPA tissues, including 1056 upregulated DEGs and 914 downregulated DEGs. Functional enrichment analysis was performed for identified DEGs and revealed an enrichment of tumor-associated GO terms and KEGG pathways. We used WGCNA to identify gene module most relevant with the histological grade of IMPA. The gene FZD2 was then recognized as the hub gene of the selected module with the highest module membership (MM) value and intramodule connectivity in protein–protein interaction (PPI) network. According to immunohistochemistry (IHC) staining, the expression level of FZD2 was higher in low-grade IMPA than in high-grade IMPA.ConclusionFZD2 shows an expression dynamic that is negatively correlated with the clinical malignancy of IMPA and it plays a central role in the transcription network of IMPA. Thus, FZD2 serves as a promising histological indicator for the precise prediction of IMPA histological stages.

Differed biotic interactions influenced by anthropogenic disturbances among trophic levels in fragmented wetlands

Environmental changes derived from various human activities have largely disturbed the structure and functioning of various biological communities. However, little is known on how such disturbance impacts species interactions in biological communities. This study aims to elucidate the variation of species interactions across multiple trophic levels and further determine crucial factor(s) in regulating observed variation. We collected plankton samples from Sanjiang Wetlands in Northeastern China and used random matrix theory (MRT)-based approach to construct species interaction networks for bacterioplanktons, protozoans, and metazoans, respectively. We found that biotic interactions were more complex at lower trophic levels. Network key species (e.g., module hubs and connectors) were detected only in the bacterioplankton network. More inter- and intra-module connections, particularly negative connections, were detected in the bacterioplankton network. Across all three trophic levels, the element sodium (Na) was the most important factor influencing the network structure, while at each trophic level, physicochemical factors, nutrients, and organic pollutants were identified as crucial determinants but their relative importance differed. In particular, no correlation was detected between the metazoan network and any environmental factor. After separating protozoan and metazoan communities into subgroups in relatively poor and good water environments, we found community interaction networks were more complex in good conditions than in poor conditions. A simple network structure (e.g., no inter-module connectors or intra-module hubs, and less competitive links) and less association with environmental factors in the higher trophic levels clearly illustrate that metazoan and protozoan communities in the fragmented wetlands are unstable and vulnerable. Therefore, further environmental changes may greatly influence species interactions in these communities. Collectively, our findings provide new insights into dynamics of influence of environmental changes on biotic interactions in aquatic biological communities, highlighting the necessity to use a multi-trophic strategy when assessing negative effects of environmental changes in aquatic ecosystems.

Aberrant large-scale brain modules in deficit and non-deficit schizophrenia

ObjectiveSchizophrenia is a heterogenous psychiatric disease, and deficit schizophrenia (DS) is a clinical subgroup with primary and enduring negative symptoms. Although previous neuroimaging studies have identified functional connectome alterations in schizophrenia, the modular organizations in DS and nondeficit schizophrenia (NDS) remain poorly understood. Therefore, this study aimed to investigate the modular-level alterations in DS patients compared with the NDS and healthy control (HC) groups. MethodsA previously collected dataset was re-analyzed, in which 74 chronic male schizophrenia patients (33 DS and 41 NDS) and 40 HC underwent resting-state functional magnetic resonance imaging with eyes closed in a Siemens 3 T scanner (scanning duration = 8 min). Modular- (intramodule and intermodule connectivity) and nodal- [normalized within-module degree (Zi) and participation coefficient (PCi)] level graph theory properties were computed and compared among the three groups. Receiver operating characteristic curve (ROC) analyses were performed to examine the classification ability of these measures, and partial correlations were conducted between network measures and symptom severity. Validation analyses on head motion, network sparsity, and parcellation scheme were also performed. ResultsBoth schizophrenia subgroups showed decreased intramodule connectivity in salience network (SN), somatosensory-motor network (SMN), and visual network (VN), and increased intermodule connectivity in SMN-default mode network (DMN) and SMN-frontoparietal network (FPN). Compared with NDS patients, DS patients showed weaker intramodule connectivity in SN and stronger intermodule connectivity in SMN-FPN and SMN-VN. At the nodal level, the schizophrenia-related alterations were distributed in SN, SMN, VN, and DMN, and 7 DS-specific nodal alterations were identified. Intramodule connectivity of SN, intermodule connectivity of SMN-VN, and Zi of left precuneus successfully distinguished the three groups. Partial correlational analyses revealed that these measures were related to negative symptoms, general psychiatric symptoms, and neurocognitive function. ConclusionOur findings suggest that functional connectomes, especially SN, SMN, and VN, may capture the distinct and common disruptions of DS and NDS. These findings may help to understand the neuropathology of negative symptoms of schizophrenia and inform targets for treating different schizophrenia subtypes.

Modular-level alterations of single-subject gray matter networks in schizophrenia.

Schizophrenia is often regarded as a psychiatric disorder caused by disrupted connections in the brain. Evidence suggests that the gray matter of schizophrenia patients is damaged in a modular pattern. Recently, abnormal topological organization was observed in the gray matter networks of patients with schizophrenia. However, the modular-level alteration of gray matter networks in schizophrenia remains unclear. In this study, single-subject gray matter networks were constructed for a total of 217 subjects (116 patients with schizophrenia and 101 controls). We analyzed the topological characteristics of the brain network and the strengths of connections between and within modules. Compared with the outcomes in the control group, the global efficiency and participation coefficient values of the single-subject gray matter networks in schizophrenic patients were significantly reduced. The nodal participation coefficient of the regions involving the frontoparietal attention network, default mode network and subcortical network were significantly decreased in subjects with schizophrenia. The intermodule connections between the frontoparietal attention network and visual network and between the default mode network and subcortical network, in the frontoparietal attention network were significantly reduced in the patient group. In the frontoparietal attention network, the intramodule nodal connection strength of the left orbital inferior frontal gyrus and right inferior parietal gyrus was significantly decreased in schizophrenia patients. Reduced intermodule nodal connection strength between the frontoparietal attention network and visual network was associated with the severity of schizophrenia symptoms. These findings suggest that abnormal intramodule and intermodule connections in the structural brain network may a biomarker of schizophrenia symptoms.

Experimental study of grouted sleeve connections under bending for steel modular buildings

In steel modular buildings, both inter- and intra-module connections can attract bending moment under the action of lateral loads. The moment is distributed in accordance with the relative stiffness ratios among the structural components and hence the connections should have sufficient flexural resistance and stiffness relative to the connecting members to be classified as a rigid connection. Typically, intra-module connections (beam-column joints within a module) are designed as full-strength rigid connections, while the inter-module connections are normally designed as pin-connected for fast-track construction. This paper proposes the use of grouted sleeve connection which does not require bolting or welding to achieve fast-track construction of modular buildings. An experimental programme is carried to investigate two types of inter-module connections, shear-keyed grouted sleeve versus slot-hole grouted sleeve, under flexural loading to evaluate their structural performance in terms of strength, stiffness, and ductility. The results showed that both connections have adequate moment resistance and ductility to resist bending and they can be classified as partial strength rigid connection for use in braced steel modular buildings. An analytical model, based on EN1992-1-1, is proposed to predict the moment resistance of the connection for the purpose of design.

Community-informed connectomics of cortical intrinsic organization in subjective cognitive decline

Objective: To investigate the intrinsic organization of cortical circuitry in individuals with subjective cognitive decline (SCD) via resting-state functional magnetic resonance imaging (rs-fMRI) connectome analysis and its correlation with cognitive level. Methods: From June 2017 to November 2019, thirty-six middle-aged and elderly individuals with complaints of memory decline and 32 normal controls (NC) were enrolled from communities in Nanjing. We collected cognitive scale performance,T1-weighted imaging (T1WI) and rs-fMRI data of all subjects. There were 5 males and 31 females in the SCD group, with an average age of (64±5) years. In the NC group, there were 8 males and 24 females, with an average age of (65±5) years. Preprocessing of rs-fMRI data was conducted, then the cerebral cortex was divided into 333 cortical parcels (nodes) and 10 predefined communities according to the prior template. Further, we established full connection matrices between cortical parcels and calculated the within-module degree (WMD) and participation coefficient (PC) of each node based on the matrices. The WMD and PC values were compared between the SCD and NC groups,and their correlations with cognitive scale performance were analyzed. Results: Compared to the NC group,the SCD group showed increased WMD in the dorsolateral prefrontal cortex (DLPFC)(P<0.05,FDR corrected) and the middle frontal gyrus (P<0.005,uncorrected) of the right frontoparietal network (FPN). The SCD group also showed decreased WMD(P<0.05,FDR corrected) in the superior occipital gyrus of the left visual network (VN) and decreased PC (P<0.005,uncorrected) in the supramarginal gyrus of the left dorsal attention network (DAN). The WMD values in the DLPFC showed significant positive correlations with the auditory verbal learning test (AVLT)short-delayed memory (r=0.364,P=0.029),recognition memory (r=0.364, P=0.029) and the Boston naming test scores (BNT, r=0.356, P=0.033)in the SCD group. The PC values in the supramarginal gyrus were significantly positively correlated with the BNT scores (r=0.413, P=0.012) in the SCD group. Conclusion: Cortical network imbalance and reconstruction characterized by decreased intra-module connectivity of VN and inter-module connectivity of DAN exist in SCD subjects,while increased intra-module connectivity of FPN may serve in a compensatory way for the early cognitive decline.

Abstract P070: Differential Gene Expression In Neointima Hyperplasia In Ucp2 Knockout Mice

Uncoupling protein 2 (UCP2) is an inner mitochondrial membrane protein which may control mitochondria-derived reactive oxygen species. Our previous study demonstrated that knocking out the Ucp2 gene exacerbated vascular injury-induced neointima hyperplasia while overexpressing Ucp2 mitigated neointima formation in rodent and swine models. However, the underlying mechanism remains largely unknown. In this study, we performed transcriptome array analyses on arterial samples with and without neointima from wild-type and Ucp2 -/- mice to further explore UCP2-mediated regulation of neointima formation. Differential gene expression analyses (log 2-fold-change &gt; 2 and P value &lt; 0.05) identified 94 co-differentially expressed genes (co-DEGs) both between wild-type arterial samples with sham surgery and with injury-induced neointima and between arterial samples with injury-induced neointima from wild-type and Ucp2 -/- mice. Gene ontology analyses found that the 94 co-DEGs were mainly located in cellular components of cytoplasm and extracellular region and were enriched in biological processes including oxidation-reduction, lipid metabolic, and metabolic processes. The 94 co-DEGs were enriched in molecular functions including protein binding, protein homodimerization activity, and oxidoreductase activity. The KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway analysis indicated that the 94 co-DEGs were mainly enriched in pathways of metabolism by cytochrome P450 and glutathione metabolism. In the protein-protein interactions (PPI) network analyses, these 94 co-DEGs formed two protein modules, and the hub genes that have a high degree of intra-module connectivity were Ppara (peroxisome proliferator activated receptor alpha), SLC2A4 (solute carrier family 2 member 4, also known as Glut4), Gpd1 (glycerol-3-phosphate dehydrogenase 1), Cxcl1 (C-X-C motif chemokine ligand 1), and Cxcl13 (C-X-C motif chemokine ligand 13). These hub genes have been shown to be mainly involved in energy metabolism and leukocyte activation. Taken together, these findings provided new insights into the molecular mechanisms underlying the protective role of UCP2 in vascular injury-induced development of neointima hyperplasia.