Functional connectivity of the anterior cingulate cortex in depression and in health

The first voxel-level resting-state functional connectivity (FC) neuroimaging analysis of depression of the anterior cingulate cortex (ACC) showed in 282 patients with major depressive disorder compared with 254 controls, some higher, and some lower FCs. However, in 125 unmedicated patients, primarily increases of FC were found: of the subcallosal anterior cingulate with the lateral orbitofrontal cortex, of the pregenual/supracallosal anterior cingulate with the medial orbitofrontal cortex, and of parts of the anterior cingulate with the inferior frontal gyrus, superior parietal lobule, and with early cortical visual areas. In the 157 medicated patients, these and other FCs were lower than in the unmedicated group. Parcellation was performed based on the FC of individual ACC voxels in healthy controls. A pregenual subdivision had high FC with medial orbitofrontal cortex areas, and a supracallosal subdivision had high FC with lateral orbitofrontal cortex and inferior frontal gyrus. The high FC in depression between the lateral orbitofrontal cortex and the subcallosal parts of the ACC provides a mechanism for more non-reward information transmission to the ACC, contributing to depression. The high FC between the medial orbitofrontal cortex and supracallosal ACC in depression may also contribute to depressive symptoms

Value of deep learning models based on ultrasonic dynamic videos for distinguishing thyroid nodules

ObjectiveThis study was designed to distinguish benign and malignant thyroid nodules by using deep learning(DL) models based on ultrasound dynamic videos.MethodsUltrasound dynamic videos of 1018 thyroid nodules were retrospectively collected from 657 patients in Zhejiang Cancer Hospital from January 2020 to December 2020 for the tests with 5 DL models.ResultsIn the internal test set, the area under the receiver operating characteristic curve (AUROC) was 0.929(95% CI: 0.888,0.970) for the best-performing model LSTM Two radiologists interpreted the dynamic video with AUROC values of 0.760 (95% CI: 0.653, 0.867) and 0.815 (95% CI: 0.778, 0.853). In the external test set, the best-performing DL model had AUROC values of 0.896(95% CI: 0.847,0.945), and two ultrasound radiologist had AUROC values of 0.754 (95% CI: 0.649,0.850) and 0.833 (95% CI: 0.797,0.869).ConclusionThis study demonstrates that the DL model based on ultrasound dynamic videos performs better than the ultrasound radiologists in distinguishing thyroid nodules

Metabolite identification in fecal microbiota transplantation mouse livers and combined proteomics with chronic unpredictive mild stress mouse livers

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.Major depressive disorder (MDD) is a common mood disorder. Gut microbiota may be involved in the pathogenesis of depression via the microbe–gut–brain axis. Liver is vulnerable to exposure of bacterial products translocated from the gut via the portal vein and may be involved in the axis. In this study, germ-free mice underwent fecal microbiota transplantation from MDD patients and healthy controls. Behavioral tests verified the depression model. Metabolomics using gas chromatography–mass spectrometry, nuclear magnetic resonance, and liquid chromatography–mass spectrometry determined the influence of microbes on liver metabolism. With multivariate statistical analysis, 191 metabolites were distinguishable in MDD mice from control (CON) mice. Compared with CON mice, MDD mice showed lower levels for 106 metabolites and higher levels for 85 metabolites. These metabolites are associated with lipid and energy metabolism and oxidative stress. Combined analyses of significantly changed proteins in livers from another depression model induced by chronic unpredictive mild stress returned a high score for the Lipid Metabolism, Free Radical Scavenging, and Molecule Transports network, and canonical pathways were involved in energy metabolism and tryptophan degradation. The two mouse models of depression suggest that changes in liver metabolism might be involved in the pathogenesis of MDD. Conjoint analyses of fecal, serum, liver, and hippocampal metabolites from fecal microbiota transplantation mice suggested that aminoacyl-tRNA biosynthesis significantly changed and fecal metabolites showed a close relationship with the liver. These findings may help determine the biological mechanisms of depression and provide evidence about “depression microbes” impacting on liver metabolism

Intrarenal Single-Cell Sequencing of Hepatitis B Virus Associated Membranous Nephropathy

To date, the pathogenesis of hepatitis B virus (HBV)-associated membranous nephropathy (MN) remains elusive. This study aimed to decipher the etiopathogenesis of HBV-associated MN by performing single-cell RNA sequencing (scRNA-seq) of kidney biopsy specimens from a patient with HBV-associated MN and two healthy individuals. We generated 4,114 intrarenal single-cell transcriptomes from the HBV-associated MN patient by scRNA-seq. Compared to healthy individuals, podocytes in the HBV-associated MN patient showed an increased expression of extracellular matrix formation-related genes, including HSPA5, CTGF, and EDIL3. Kidney endothelial cells (ECs) in the HBV-associated MN were enriched in inflammatory pathways, including NF-kappa B signaling, IL-17 signaling, TNF signaling and NOD-like receptor signaling. Gene ontology (GO) functional enrichment analysis and Gene Set Variation Analysis (GSVA) further revealed that differentially expressed genes (DEGs) of ECs from the HBV-associated MN patients were enriched in apoptotic signaling pathway, response to cytokine and leukocyte cell-cell adhesion. The up-regulated DEGs in glomerular ECs of HBV-associated MN patients were involved in biological processes such as viral gene expression, and protein targeting to endoplasmic reticulum. We further verified that the overexpressed genes in ECs from HBV-associated MN were mainly enriched in regulation of protein targeting to endoplasmic reticulum, exocytosis, viral gene expression, IL-6 and IL-1 secretion when compared with anti-phospholipase A2 receptor (PLA2R)-positive idiopathic membranous nephropathy (IMN). The receptor-ligand crosstalk analysis revealed potential interactions between endothelial cells and other cells in HBV-associated-MN. These results offer new insight into the pathogenesis of HBV-associated MN and may identify new therapeutic targets for HBV-associated MN

Identifying the Exact Value of the Metric Dimension and Edge Dimension of Unicyclic Graphs

Given a simple connected graph G, the metric dimension dim(G) (and edge metric dimension edim(G)) is defined as the cardinality of a smallest vertex subset S⊆V(G) for which every two distinct vertices (and edges) in G have distinct distances to a vertex of S. It is an interesting topic to discuss the relation between these two dimensions for some class of graphs. This paper settles two open problems on this topic for unicyclic graphs. We recently learned that Sedlar and Škrekovski settled these problems, but our work presents the results in a completely different way. By introducing four classes of subgraphs, we characterize the structure of a unicyclic graph G such that dim(G) and edim(G) are equal to the cardinality of any minimum branch-resolving set for unicyclic graphs. This generates an approach to determine the exact value of the metric dimension (and edge metric dimension) for a unicyclic graph

University Ideological and Political Learning Model Based on Statistical Memory Curve Mathematical Equation

In order to consolidate the effect of classroom teaching and broaden students’ thinking, stimulate students’ interest in learning, avoid forgetting more and more, so that students actively explore knowledge. The author proposes an adaptive memory model based on Ebbinghaus’ forgetting curve theory. Firstly, the relationship between the mathematical equation of memory curve and Ebbinghaus forgetting curve theory is introduced. Select the forgetting curve fitting function, and then define the adaptive memory model, the software divides the user’s initial cognition of words into three types: cognition, vagueness, and ignorance, the average memory times of these three types of content are counted separately, finally, the average memory times of the three types of content are comprehensively averaged, finally, a comparative experiment is carried out based on the intelligent memory model of the Ebbinghaus forgetting curve. The results show that while not affecting the memory effect, using the intelligent memory model, the number of memories is reduced by 37.12% compared with the New Oriental memory method, using the adaptive memory model reduces the number of memories by 43.35% compared to the New Oriental memory method. The experimental results show, the adaptive memory model further saves 6.31% of memory times compared to the intelligent memory model, not only has good adaptability to each user’s memory situation, it also further improves memory efficiency. From this it can be seen that, university ideological and political learning model based on the mathematical equation of statistical memory curve: The adaptive memory model has certain reliability and feasibility

User Willingness toward Knowledge Sharing in Social Networks

Social networks introduce new potential for people to share knowledge with others. However, it is not clear what factors influence user willingness toward knowledge sharing in social networks. Aiming to answer these questions, in this paper we analyze the major factors influencing user willingness toward knowledge sharing in social networks and propose a new research model that is inspired by the technology acceptance model (TAM). In particular, we introduce a new independent variable called perceived value which is described by four aspects: social value, entertainment value, emotion value, and information value. In addition, we introduce a new mediating variable, trust, to reflect the intermediating relationship between perceived value and knowledge-sharing willingness. We conduct an empirical analysis on questionnaire data and present comprehensive results on reliability and validity, factor analysis, correlation analysis, and mediating effects analysis. The results show that perceived value has a significant impact on knowledge-sharing willingness, and trust plays a partial intermediate role between perceived value and knowledge-sharing willingness. Further, we present some research implications for knowledge sharing and learning innovation in social networks, as well as some suggestions for organizations to advance knowledge sharing and learning innovation in the social-network age

MeOTf-Induced Carboannulation of Isothiocyanates and Aryl Alkynes with CS Bond Cleavage: Access to Indenones

MeOTf-induced carboannulation of alkyl isothiocyanates and aryl alkynes for the synthesis of indenones in good yields under metal-free conditions with CS bond cleavage is described. The thioalkoxy group at the 3-position of the indenone can also be converted into other functional groups, such as phenyl, methylsulfonyl, amino, and ethoxy groups

Recent advances on the reduction of CO_2 to important C_(2+) oxygenated chemicals and fuels

The chemical utilization of CO 2 is a crucial step for the recycling of carbon resource. In recent years, the study on the conversion of CO 2 into a wide variety of C 2 + important chemicals and fuels has received considerable attention as an emerging technology. Since CO 2 is thermodynamically stable and kinetically inert, the effective activation of CO 2 molecule for the selective transformation to target products still remains a challenge. The well-designed CO 2 reduction route and efficient catalyst system has imposed the feasibility of CO 2 conversion into C 2 + chemicals and fuels. In this paper, we have reviewed the recent advances on chemical conversion of CO 2 into C 2 + chemicals and fuels with wide practical applications, including important alcohols, acetic acid, dimethyl ether, olefins and gasoline. In particular, the synthetic routes for C C coupling and carbon chain growth, multifunctional catalyst design and reaction mechanisms are exclusively emphasized

Recent advances on the reduction of CO2 to important C2+ oxygenated chemicals and fuels

The chemical utilization of CO2 is a crucial step for the recycling of carbon resource. In recent years, the study on the conversion of CO2 into a wide variety of C2+ important chemicals and fuels has received considerable attention as an emerging technology. Since CO2 is thermodynamically stable and kinetically inert, the effective activation of CO2 molecule for the selective transformation to target products still remains a challenge. The well-designed CO2 reduction route and efficient catalyst system has imposed the feasibility of CO2 conversion into C2+ chemicals and fuels. In this paper, we have reviewed the recent advances on chemical conversion of CO2 into C2+ chemicals and fuels with wide practical applications, including important alcohols, acetic acid, dimethyl ether, olefins and gasoline. In particular, the synthetic routes for C-C coupling and carbon chain growth, multifunctional catalyst design and reaction mechanisms are exclusively emphasized. (C) 2018 The Chemical Industry and Engineering Society of China, and Chemical Industry Press. All rights reserved