Homophily modulates double descent generalization in graph convolution networks.

Graph neural networks (GNNs) excel in modeling relational data such as biological, social, and transportation networks, but the underpinnings of their success are not well understood. Traditional complexity measures from statistical learning theory fail to account for observed phenomena like the double descent or the impact of relational semantics on generalization error. Motivated by experimental observations of "transductive" double descent in key networks and datasets, we use analytical tools from statistical physics and random matrix theory to precisely characterize generalization in simple graph convolution networks on the contextual stochastic block model. Our results illuminate the nuances of learning on homophilic versus heterophilic data and predict double descent whose existence in GNNs has been questioned by recent work. We show how risk is shaped by the interplay between the graph noise, feature noise, and the number of training labels. Our findings apply beyond stylized models, capturing qualitative trends in real-world GNNs and datasets. As a case in point, we use our analytic insights to improve performance of state-of-the-art graph convolution networks on heterophilic datasets.

Neural Activity in Quarks Language: Lattice Field Theory for a Network of Real Neurons.

Brain-computer interfaces have seen extraordinary surges in developments in recent years, and a significant discrepancy now exists between the abundance of available data and the limited headway made in achieving a unified theoretical framework. This discrepancy becomes particularly pronounced when examining the collective neural activity at the micro and meso scale, where a coherent formalization that adequately describes neural interactions is still lacking. Here, we introduce a mathematical framework to analyze systems of natural neurons and interpret the related empirical observations in terms of lattice field theory, an established paradigm from theoretical particle physics and statistical mechanics. Our methods are tailored to interpret data from chronic neural interfaces, especially spike rasters from measurements of single neuron activity, and generalize the maximum entropy model for neural networks so that the time evolution of the system is also taken into account. This is obtained by bridging particle physics and neuroscience, paving the way for particle physics-inspired models of the neocortex.

[Structural Design and Analysis of Portable Intelligent Wheelchair for Knee Rehabilitation].

Objective: In order to address the issues of inconvenience, high medical costs, and lack of universality associated with traditional knee rehabilitation equipment, a portable intelligent wheelchair for knee rehabilitation was designed in this study. Methods: Based on the analysis of the knee joint's structure and rehabilitation mechanisms, an electric pushrod-driven rehabilitation institution was developed. A multi-functional module was designed with a modular approach, and the control of the wheelchair body and each functional module was implemented using an STM32 single-chip microcomputer. A three-dimensional model was established using SolidWorks software. In conjunction with Adams and Ansys simulation software, kinematic and static analyses were conducted on the knee joint rehabilitation institution and its core components. A prototype was constructed to verify the equipment's actual performance. Results: According to the prototype testing, the actual range of motion for the knee joint swing rod is 15.1°~88.9°, the angular speed of the swing rod ranges from -7.9 to 8.1°/s, the angular acceleration of the swing rod varies from -4.2 to 1.6°/s², the thrust range of the electric pushrod is -82.6 to 153.1 N, and the maximum displacement of the load pedal is approximately 1.7 mm, with the leg support exhibiting a maximum deformation of about 1.5 mm. Conclusion: The intelligent knee joint rehabilitation wheelchair meets the designed functions and its actual performance aligns with the design criteria, thus validating the rationality and feasibility of the structural design.

In-hospital nursing care intervention increasing the effect of vacuum sealing drainage on wound healing: A meta-analysis.

Vacuum sealing drainage (VSD) could effectively drain superficial wounds and deep tissues, which is beneficial for wound healing. More incentives in nursing care to improve the therapeutic effect of VSD on wound healing were further investigated. Different databases were retrieved for full-text publications about the comparison between intervention nursing care and regular nursing care. Heterogeneity was detected by I2 method, and a random-effect model was applied for data pooling if there existed heterogeneity. Publication bias was analysed by a funnel plot. Eight studies with 762 patients were included for final meta-analysis. In the nursing care intervention group, shorter hospital stay duration (pooled SMD = -2.602, 95% confidence interval: -4.052--1.151), shorter wound healing time (pooled SMD = -1.105, 95% confidence interval: -1.857--0.353), lower pain score (pooled SMD = -2.490, 95% confidence interval: -3.521--1.458), lower drainage tube blocked rate (pooled RR = 0.361, 95% confidence interval: 0.268-0.486), and higher nursing satisfaction (pooled RR = 1.164, 95% confidence interval: 1.095-1.237) was confirmed. More active and incentive nursing care could significantly improve the therapeutic effect of VSD on wound healing, in terms of hospitalisation time, wound healing time, painful symptoms, drainage tube blockage, and nursing satisfaction.

[Genetic analysis of a child with XYY syndrome in conjunct with 3-methylglutaenedioic aciduria type I].

OBJECTIVE: To explore the genetic basis for a child with mental retardation. METHODS: The child was subjected to chromosomal microarray analysis (CMA) and targeted capture next-generation sequencing for the exons of genes related to genetic and metabolic diseases. Candidate variants were verified by Sanger sequencing of the child and his parents. RESULTS: CMA suggested that the child has a 47,XYY karyotype. Next-generation sequencing revealed that the child has harbored compound heterozygous variants of the AUH gene, including c.677G>A (p.R226H) and c.373C>T (p.R125W), which were respectively inherited from his parents. Based on the American college of Medical Genetics and Genomics (ACMG) standards and guidelines, the c.677G>A (P.r226h) variant was predicted as variant of uncertain significance (PM2+PP4+PP3), whilst the c.373C>T (P.R125W) variant was predicted as likely pathogenic (PM1+PM2+PP3+PP4). CONCLUSION: The child had XYY syndrome in conjunct with 3-methylglutaenedioic aciduria type I due to biallelic pathogenic variants of the AUH gene.

HLB induce changes in the tree physiology of citron (Citrus medica L. var. sarcodactylis Swingle).

Huanglongbing (HLB) is a highly destructive disease that decreases the yield and quality of Citrus medica L. var. sarcodactylis Swingle (C. medica var. sarcodactylis) and poses a great threat to the development of the global citrus industry. To explore the influence of HLB infection on C. medica var. sarcodactylis, levels of photosynthetic pigments, malondialdehyde (MDA), and carbohydrates, as well as antioxidant enzyme activities, were measured. The results show that HLB infection decreased photosynthetic pigment content, increased MDA content and antioxidant enzyme activities, and caused various changes in carbohydrate levels in stem, fruit, and leaf tissues. Transcriptomic analysis of C. medica var. sarcodactylis was also used to identify key genes related to the carbohydrate metabolic synthesis pathway in C. medica var. sarcodactylis. The C. medica var. sarcodactylis ADP-glucose pyrophosphorylase1 (CmAGP1), CmAGP2, C. medica var. sarcodactylis Granule-bound starch synthase (CmGBSS), C. medica var. sarcodactylis Sucrose synthases1 (CmSUS1), CmSUS2, C. medica var. sarcodactylis Sucrose phosphate synthase (CmSPS), C. medica var. sarcodactylis alkaline/neutral invertase1 (CmNi1), CmNi2, CmNi3 and CmNi4 were successfully cloned and identified, and differential expression analysis showed that HLB infection significantly upregulated these genes in stems and leaves. In conclusion, HLB infection causes cellular damage, a reduction in photosynthetic capacity, decreased pathogen resistance, and severe disorders in carbohydrate metabolism in C. medica var. sarcodactylis. Supplementary Information: The online version contains supplementary material available at 10.1007/s12298-022-01129-z.

Network temporality can promote and suppress information spreading.

Temporality is an essential characteristic of many real-world networks and dramatically affects the spreading dynamics on networks. In this paper, we propose an information spreading model on temporal networks with heterogeneous populations. Individuals are divided into activists and bigots to describe the willingness to accept the information. Through a developed discrete Markov chain approach and extensive numerical simulations, we discuss the phase diagram of the model and the effects of network temporality. From the phase diagram, we find that the outbreak phase transition is continuous when bigots are relatively rare, and a hysteresis loop emerges when there are a sufficient number of bigots. The network temporality does not qualitatively alter the phase diagram. However, we find that the network temporality affects the spreading outbreak size by either promoting or suppressing, which relies on the heterogeneities of population and of degree distribution. Specifically, in networks with homogeneous and weak heterogeneous degree distribution, the network temporality suppresses (promotes) the information spreading for small (large) values of information transmission probability. In networks with strong heterogeneous degree distribution, the network temporality always promotes the information spreading when activists dominate the population, or there are relatively fewer activists. Finally, we also find the optimal network evolution scale, under which the network information spreading is maximized.

[Identification of LINS1 gene variant in a patient with severe mental retardation].

OBJECTIVE: To explore the genetic basis of a child with idiopathic mental retardation. METHODS: Clinical data and peripheral blood sample of the child were collected. Genomic DNA was extracted and subjected to copy number analysis using single nucleotide polymrophism array comparative genome hybridization (SNP-aCGH) and targeted capture and next generation sequencing (NGS). RESULTS: No microdeletion/microduplication were detected by SNP-aCGH. NGS has detected homozygous c.722delA (p.Asp241fs) variant of the LISN1 gene, which is known to underlie autosomal recessive mental retardation-27 (MRT 27). Both parents are carriers of the variant, conforming to the autosomal recessive inheritance. CONCLUSION: A novel pathogenic variant of the LINS1 gene has been identified, which probably underlies the MRT 27 in the patient.

Clinical value of prenatal MRI for diagnosis of isolated ventriculomegaly and prediction of early postnatal developmental outcomes.

OBJECTIVE: To investigate the relationship of ventriculomegaly (VM) with postnatal neurological development. METHODS: Fetuses with isolated VM on MRI (n = 160; VM group) were separated into three subgroups according to lateral ventricle width: subgroup A (10.0-12.0 mm; n = 113), subgroup B (12.1-15.0 mm; n = 37), and subgroup C (>15.0 mm; n = 10). Fifty normal fetuses formed a control group. Post-delivery changes in ventricular width and neurological development were assessed with MRI/ultrasonography and the Gesell Development Schedules (GDS), respectively, at 3, 6, 12, and 18 months. RESULTS: GDS scores of subgroup A and subgroup B did not differ from that of the controls at 3 and 6 months. Subgroup B scores differed significantly from the control scores at 12 and 18 months. Subgroup C scores differed from the control scores at all-time points (all P < 0.05). In the VM group, GDS scores at 12 and 18 months were significantly different from the scores at 3 months, and the score at 18 months was significantly different from the score at 6 months (P < 0.05 for all). CONCLUSION: The milder the VM, the more likely it was to disappear or improve in the postnatal period. However, specific postnatal rehabilitation should be considered when fetal ventricular width is greater than 12.1 mm.

Misinformation spreading on correlated multiplex networks.

The numerous expanding online social networks offer fast channels for misinformation spreading, which could have a serious impact on socioeconomic systems. Researchers across multiple areas have paid attention to this issue with a view of addressing it. However, no systematical theoretical study has been performed to date on observing misinformation spreading on correlated multiplex networks. In this study, we propose a multiplex network-based misinformation spreading model, considering the fact that each individual can obtain misinformation from multiple platforms. Subsequently, we develop a heterogeneous edge-based compartmental theory to comprehend the spreading dynamics of our proposed model. In addition, we establish an analytical method based on stability analysis to obtain the misinformation outbreak threshold. On the basis of these theories, we finally analyze the influence of different dynamical and structural parameters on the misinformation spreading dynamics. Results show that the misinformation outbreak size R(∞) grows continuously with the effective transmission probability ß once ß exceeds a certain value, that is, the outbreak threshold ßc. Large average degrees, strong degree heterogeneity, or positive interlayer correlation will reduce ßc, accelerating the outbreak of misinformation. Besides, increasing the degree heterogeneity or a more positive interlayer correlation will enlarge (reduce) R(∞) for small (large) values of ß. Our systematic theoretical analysis results agree well with the numerical simulation results. Our proposed model and accurate theoretical analysis will serve as a useful framework to understand and predict the spreading dynamics of misinformation on multiplex networks and thereby pave the way to address this serious issue.

Optimizing spreading dynamics in interconnected networks.

Adding edges between layers of interconnected networks is an important way to optimize the spreading dynamics. While previous studies mostly focused on the case of adding a single edge, the theoretical optimal strategy for adding multiple edges still need to be studied. In this study, based on the susceptible-infected-susceptible model, we investigate the problem of maximizing the stationary spreading prevalence in interconnected networks. For two isolated networks, we maximize the spreading prevalence near the critical point by choosing multiple interconnecting edges. We present a theoretical analysis based on the discrete-time Markov chain approach to derive the approximate optimal strategy. The optimal interlayer structure predicted by the strategy maximizes the spreading prevalence, meanwhile minimizing the spreading outbreak threshold for the interconnected network simultaneously. Numerical simulations on synthetic and real-world networks show that near the critical point, the proposed strategy gives better performance than connecting large degree nodes and randomly connecting.

[Analysis of SYNE1 gene variant in an infant featuring epilepsy and developmental disorders].

OBJECTIVE: To explore the clinical features and molecular basis for a child featuring infantile epilepsy and developmental disorders. METHODS: Clinical data and peripheral blood samples of the child and his parents were collected. The coding regions of genes associated with nervous system development were subjected to target region capture sequencing. RESULTS: The child developed generalized spasm at 3 months and was diagnosed with epilepsy at 6 months of age. He was treated with Depakin but was diagnosed with mental retardation and developmental retardation at 3 years of age. A novel heterozygous c.3842T to G variant of the SYNE1 gene was detected. His father was found to carry the same variant and had a history of convulsions in infancy but with no mental or developmental anomalies. CONCLUSION: A novel variant of SYNE1 gene was identified in this child, and the prognosis may be poor.

The positive feedback between lncRNA TNK2-AS1 and STAT3 enhances angiogenesis in non-small cell lung cancer.

Evidence has shown the importance of long non-coding RNAs (lncRNAs) during angiogenesis and lung cancer progression. However, the potential functions of TNK2-AS1 in non-small cell lung cancer (NSCLC) remain elusive. By lncRNA profiling, we identified TNK2-AS1 as a novel oncogenic lncRNA in NSCLC. TNK2-AS1 was significantly upregulated in NSCLC and correlated with poor prognosis. We found that TNK2-AS1 could increase viability and migration of NSCLC cells in vitro. TNK2-AS1 also promoted NSCLC xenograft tumor growth and metastasis in vivo. TNK2-AS1 could interact with STAT3 to increase its protein stability by protecting it from proteasome-mediated degradation. STAT3 could also bind TNK2-AS1 promoter to trigger its transcription. The positive feedback loop between STAT3 and TNK2-AS1 therefore augmented STAT3 signaling by elevating VEGFA expression to facilitate angiogenesis. Collectively, our work has elucidated a novel mechanism of TNK2-AS1-mediated angiogenesis by enforcing STAT3/VEGFA signaling and may provide a potential target for therapeutic intervention.

Toward link predictability of complex networks.

The organization of real networks usually embodies both regularities and irregularities, and, in principle, the former can be modeled. The extent to which the formation of a network can be explained coincides with our ability to predict missing links. To understand network organization, we should be able to estimate link predictability. We assume that the regularity of a network is reflected in the consistency of structural features before and after a random removal of a small set of links. Based on the perturbation of the adjacency matrix, we propose a universal structural consistency index that is free of prior knowledge of network organization. Extensive experiments on disparate real-world networks demonstrate that (i) structural consistency is a good estimation of link predictability and (ii) a derivative algorithm outperforms state-of-the-art link prediction methods in both accuracy and robustness. This analysis has further applications in evaluating link prediction algorithms and monitoring sudden changes in evolving network mechanisms. It will provide unique fundamental insights into the above-mentioned academic research fields, and will foster the development of advanced information filtering technologies of interest to information technology practitioners.

Lower bound of assortativity coefficient in scale-free networks.

The degree-degree correlation is important in understanding the structural organization of a network and dynamics upon a network. Such correlation is usually measured by the assortativity coefficient r, with natural bounds r∈[-1,1]. For scale-free networks with power-law degree distribution p(k)∼k-γ, we analytically obtain the lower bound of assortativity coefficient in the limit of large network size, which is not -1 but dependent on the power-law exponent γ. This work challenges the validation of the assortativity coefficient in heterogeneous networks, suggesting that one cannot judge whether a network is positively or negatively correlated just by looking at its assortativity coefficient alone.

[Research on distribution and quality suitability division of Desmodium styracifolium].

The research on distribution and quality suitability division of Desmodium styracifolium were formulated by Maxent and ArcGIS model based on the content of schaftoside and polysaccharide of D. styracifolium and its field research in the south and southwest areas of China (Guangdong, Guangxi, Hainan and Yunnan), and the most suitable habitats of distribution suitability and quality suitability were screened. The distribution suitability results indicated that average air temperature in April,mean temperature of coldest quarter, soil type, coldness index were found as the four dominant factors contributing to the plant distribution. The quality suitability results indicated that: ①Polysaccharide content and precipitation in April show significant positive correlation;Schaftoside content and mean temperature of April, mean temperature of coldest quarter show significant negative correlation. Schaftoside content shows significant negative correlation with the precipitation in October and November and the sunshine duration in April and May, while there is a significant positive correlation between schaftoside content and precipitation in April and temperature seasonality standard deviation, and a highly significant positive correlation was found between schaftoside content and precipitation in February and March. ②The quality zoning map was drawn depend on general content of polysaccharide and schaftoside as the index of quality. And this research provides scientific location basis for the production regionalization, cultivation bases selection and directive breeding of D. styracifolium.

[De novo sequencing and analysis of root transcriptome to reveal regulation of gene expression by moderate drought stress in Glycyrrhiza uralensis].

Moderate drought stress has been found to promote the accumulation of active ingredients in Glycyrrhiza uralensis root and hence improve the medicinal quality. In this study, the transcriptomes of 6-month-old moderate drought stressed and control G. uralensis root (the relative water content in soil was 40%-45% and 70%-75%, respectively) were sequenced using Illumina HiSeq 2000. A total of 80,490 490 and 82 588 278 clean reads, 94,828 and 305,100 unigenes with N50 sequence of 1,007 and 1,125 nt were obtained in drought treated and control transcriptome, respectively. Differentially expressed genes analysis revealed that the genes of some cell wall enzymes such as ß-xylosidase, legumain and GDP-L-fucose synthase were down-regulated indicating that moderate drought stress might inhibit the primary cell wall degradation and programmed cell death in root cells. The genes of some key enzymes involved in terpenoid and flavonoid biosynthesis were up-regulated by moderate drought stress might be the reason for the enhancement for the active ingredients accumulation in G. uralensis root. The promotion of the biosynthesis and signal transduction of auxin, ethylene and cytokinins by moderate drought stress might enhance the root formation and cell proliferation. The promotion of the biosynthesis and signal transduction of abscisic acid and jasmonic acid by moderate drought stress might enhance the drought stress tolerance in G. uralensis. The inhibition of the biosynthesis and signal transduction of gibberellin and brassinolide by moderate drought stress might retard the shoot growth in G. uralensis.

The role of (18F)-fluoro-D-glucose positron emission tomography/computed tomography in the surveillance of abnormal myocardial energy metabolism and cardiac dysfunction in a rat model of cardiopulmonary resuscitation.

PURPOSE: To investigate the feasibility and usefulness of 2-deoxy-2-(18F)-fluoro-D-glucose positron emission tomography/computed tomography [(18F)-FDG PET/CT] as a novel examination in the surveillance of abnormal myocardial energy metabolism and cardiac dysfunction after cardiopulmonary resuscitation (CPR). METHODS: Thirteen male Sprague-Dawley rats were randomly divided into a sham group (n = 4), CPR group (n = 4), and trimetazidine (TMZ) + CPR group (n = 5). The expression levels of the myocardial injury marker cardiac troponin I (CTNI) in serum were tested at 6 hours after CPR or TMZ + CPR. The ejection fraction and fraction shortening were evaluated by echocardiography. (18F)-FDG PET/CT was used to measure the FDG uptake and the standardized uptake value (SUV) after CPR or TMZ + CPR for 6 hours. The intermediary carbohydrate metabolites of glycolysis including phosphoenolpyruvate, 3-phospho-D-glycerate, and the lactate/pyruvate ratio were detected through the multiple reaction monitoring approach. Simultaneously, the authors also tested the expression levels of the total adenosine triphosphate (ATP) and the key intermediate products of glucose ovidation as alpha ketoglutarate, citrate, and succinate in the myocardium. RESULTS: The authors found that the aerobic oxidation of glucose was reduced, and the anaerobic glycolysis was significantly enhanced in the myocardium in the early stage of CPR. Meanwhile, the myocardial injury marker CTNI was upregulated considerably (P = 0.014, P = 0.021), and the left ventricular function of the animal heart also markedly deteriorated with the downregulation of ATP after CPR. In contrast, myocardial injury and cardiac function were greatly improved with the increase of ATP in the CPR + TMZ group. In addition, aerobic glucose oxidation metabolites were significantly increased (P < 0.05) and anaerobic glycolysis metabolites were significantly decreased (P < 0.05) after CPR in the myocardium. Surprisingly, (18F)-FDG PET/CT could track the above changes by detecting the FDG uptake value and the SUV. CONCLUSION: Glucose metabolism is an essential factor for myocardial self-repair after CPR. (18F) FDG PET/CT, as a non-invasive technology, can monitor myocardial energy metabolism and cardiac function by tracking changes in glucose metabolism after CPR.

Study on the effect of Pogostemon cablin Benth on skin aging based on network pharmacology.

BACKGROUND: At present, there is still little research on the anti-aging effect of Pogostemon cablin Benth (PCB) on human skin. In this paper, the mechanism of anti-aging effect of PCB on human skin was studied by using network pharmacology and molecular docking methods. OBJECTIVE: To analyze the pharmacological mechanism of PCB in the treatment of skin aging, so as to provide reference for new drug development and clinical application. METHODS: Active ingredients and related targets of PCB and skin aging-related disease targets are obtained through public databases, and the "drug-disease-target" and protein-protein interaction (PPI) network diagrams were constructed with the help of software to screen the core targets; Then GO analysis and KEGG pathway analysis were performed on the target; Finally, the molecular docking between the components and the targets were verified. RESULTS: After screening, 112 intersection targets of active compounds of skin aging and PCB were obtained. Through GO and KEGG enrichment analysis, it is found that these biological processes mainly focus on epithelial cell proliferation, aging, growth factors, longevity regulation pathway, cancer pathway, AGE-RAGE signal pathway, PI3K Akt signal pathway and IL-17 signal pathway. The molecular docking results showed that quercetin, apigenin, irisnepalensis isoflavone, 3,23-dihydroxy-12-oleorene-28-oleic acid, 5-hydroxy-7,4'- dimethoxyflavone and other major compounds were connected with TP53, JUN, HSP90AAL, AKT1 and MAPK1 through hydrogen bonds, and there was high binding energy between them. CONCLUSION: Through multi-target prediction and molecular docking verification, it shows that PCB provides a strong effect in the treatment of skin aging, which provides a reference for its further research.

Comparative analysis and influencing factors of hospitalization expenses of three single diseases in a tertiary Class A general hospital.

OBJECTIVE: To compare the hospitalization expenses among three single diseases in The First Affiliated Hospital of Hebei North University (a tertiary Class A general hospital), and analyze the factors affecting hospitalization costs, so as to provide some basis for controlling the unreasonable increase of hospitalization expenses as well as to render references for medical management. METHODS: By retrospective investigation, we selected the basic information of inpatient medical records and detailed billing of patients hospitalized in our hospital from Jan. 1, 2016 to Dec. 31, 2018. The collected data were sorted based on the International Classification of Diseases (ICD-10). Finally, 1,199 cases of frequently-occurring diseases and common illnesses such as rectal cancer (RC), nodular goiter (NG) and chronic renal failure (hemodialysis, HD) (CRF) were selected to conduct descriptive statistics on influencing factors and cost structure. The influencing factors of hospitalization expenses were identified by one-way analysis of variance (ANOVA) and multiple linear regression analysis. RESULTS: The hospitalization cost of inpatients with RC or CRF (HD) mainly spent on drugs, diagnosis and materials. As to NG, the cost of surgery, diagnosis and materials were the main components of hospitalization costs. Occupation and length of stay (LOS) were identified as the main influencing factors of hospitalization expenses for RC patients. While age and LOS were the main influencing factors of hospitalization cost for NG patients, and LOS alone for patients with CRF (HD). A across-sectional study was conducted on the CRF (HD) patients over 60 years old. CONCLUSIONS: In order to reasonably control inpatient medical expenses, comprehensive intervention should be carried out in clinical work, from rational drug use and selection of consumables, to shorten the hospitalization days to an appropriate level and reduce the waste of medical resources.